Clinicobiochemical and GC-MS Based Serum Metabolomics for determination of Therapeutic Efficacy of Silymarin in Pneumonic Sheep

Clinicobiochemical and GC-MS Based Serum Metabolomics for determination of Therapeutic Efficacy of Silymarin in Pneumonic Sheep | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinicobiochemical and GC-MS Based Serum Metabolomics for determination of Therapeutic Efficacy of Silymarin in Pneumonic Sheep Hany Hassan, Ahmed Kamr, Abdel Nasser El-Gendy, Ramiro Toribio, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4344803/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The goal of this study was to evaluate the therapeutic efficacy of silymarin against sheep pneumonia utilizing clinical, biochemical and metabolomics approaches. Methods: Fifty adult male Barki sheep were divided into two groups based on their health status. Group 1 included healthy sheep (n = 10); Group 2 included sick sheep with clinical evidence of pneumonia (n = 40), which were further classified into four subgroups based on treatment protocols: subgroup 1 (SG1) was given traditional treatment; subgroup 2 (SG2) received traditional treatment plus daily 280 mg of silymarin orally; subgroup 3 (SG3) was administrated daily 280 mg of silymarin orally; and subgroup 4 (SG4) received daily 560 mg of silymarin orally. Evaluation of hepatic and renal function as well as serum lipid profile, glucose concentrations, malondialdehyde (MDA) concentrations, and total antioxidant activity (TAC) was carried out using commercial kits. Efficacy-directed distinction between therapeutic groups was accomplished based on GC-MS generated serum metabolite profiles supported by partial least squares regression analysis (PLS). Results: PLS score plot showed a clear discrimination between the healthy and pneumonic sheep groups that exhibited lower concentrations of TAC, total cholesterol, HDL-cholesterol, and glucose, but elevated liver enzyme, urea, creatinine, MDA and LDL-cholesterol (P < 0.05). Through clinical evaluations, the rapid clinical responses were achieved by the oral administration of silymarin 560 mg and through selective analysis of metabolomics profile, pneumonic therapy with 280 mg of silymarin was the best therapeutic outcome relying on a SG3 was strongly correlated with the upregulation of TAC, glucose, and total and HDL-cholesterol values. Conclusions: Pneumonic sheep treated with silymarin exhibited healing as well as greater clinical, metabolomic and biochemical improvement than treatment with traditional treatment alone. Silybum marianum Metabolites profile Discrimination analyses Pneumonia Figures Figure 1 Figure 2 Background Pneumonia is a complex disease that in small ruminants results from a combination of environmental, management, immune, and infectious (bacterial, viral, and mycotic agents) factors that results in major economic losses due to cost of treatment, reduced productivity, and high mortality rates [ 1 , 2 ]. Fluoroquinolones and macrolides are broad-spectrum antibiotics commonly used to treat pneumonia in sheep [ 3 ]. In addition, anti-inflammatory drugs are often indicated to control disease severity. Currently, antimicrobial resistance is a global concern that requires multidisciplinary strategies to ensure efficient therapies for human and animal populations [ 4 ]. In recent years, herbal therapy has received attention as a novel and alternative therapeutic approach due to its safety and cultural acceptability [ 5 , 6 ]. Silybum marianum (SM; milk thistle) has been used for centuries as a natural remedy to cure a variety of illnesses, particularly hepatic ones. It contains a flavonolignan complex termed silymarin mainly found in the seeds and fruits [ 7 ]. Silymarin, of which silibinin is the main active component, has antimicrobial, antimycotic, anti-inflammatory, antifibrotic, immunomodulating, and anthelmintic properties [ 8 ]. It also reduces the expression of sterol regulatory element binding protein 1 and fatty acid transport protein 5 in hepatic cells to prevent the fat accumulation caused by free fatty acids [ 9 , 10 ]. Silymarin's ability to scavenge free radicals and boost endogenous antioxidant defenses, such as the glutathione system, is linked to its ability to reduce oxidative stress-induced hepatocellular damage [ 11 ]. It protects kidney cells in vitro from medication-induced nephrotoxicity as well as from cyclosporine nephrotoxicity [ 12 ]. Given the pleiotropic actions of silymarin and the clinical importance of respiratory disease in small ruminants, investigating silymarin in sheep with pneumonia could provide valuable information. Metabolomics analysis is a contemporary approach in drug development, disease diagnosis, pathophysiology, and prognosis. It provides more biochemical insight and understanding than other systems biology omics techniques [ 13 ]. Furthermore, it enables the measurement of changes in endogenous small molecules within cells, tissues, and biofluids of the body in response to environmental changes or contaminants. Gas chromatography-mass spectrometry (GC-MS) is the most used metabolomics technology for quantitatively analyzing various metabolites in biological materials. It can effectively and rapidly separate and identify large pools of metabolites [ 14 ]. Recently, scientists have directed their attention towards the biological and pharmaceutical applications of metabolites obtained from edible plants and foods [ 15 , 16 ]. The purpose of this study was to assess the therapeutic effectiveness of silymarin in pneumonic sheep using clinical examination, metabolomics profiling, and biochemical parameter measurements. We expected that treating pneumonic sheep with silymarin would cure and enhance their health. Methods Milk thistle extract ( Silybum marianum ) Silymarin powder was provided by Medical Union Pharmaceuticals (MUP) Company , Egypt. The powder consists of 50% silymarin with a potency of 104.49%, with code number 0111304600. Animals’ criteria and experimental design A total of fifty male adult Barki sheep at private farm in Sadat City, Egypt, aged between 1 to 2 years with a mean body weight of 60 ± 2 kilograms were assigned to two groups based on their health condition. Group 1 (G1; n =10), included healthy sheep with no clinical or laboratory evidence of disease, were free of external and internal parasites, and served as a control group. Group 2 (G2; n = 40), consisted of sheep with evidence of respiratory disease, including copious nasal discharge, fever, cough, dyspnea, and abnormal respiratory sounds upon auscultation. This group was further divided into four subgroups according to the therapeutic protocol. SG1 (n =10) included pneumonic sheep that received the traditional antimicrobial treatment for pneumonia using florfenicol (20 mg/kg body weight/ IM injection), a non-steroidal anti-inflammatory drug as diclofenac sodium (2.5 mg/kg body weight/ IM injection) and anti-histaminic drug as diphenhydramine hydrochloride 20 mg (1 ml/45 kg bodyweight/ IM injection). SG2 (n =10) consisted of pneumonic sheep treated as SG1 plus daily oral administration of silymarin at a dose of 280 mg every 24 hours for seven consecutive days. SG3 (n =10) consisted of pneumonic sheep treated with oral administration of silymarin 280 mg every 24 hours for seven consecutive days [17]. SG4 (n =10) included pneumonic sheep treated by daily oral administration of silymarin 560 mg every 24 hours for seven consecutive days. General clinical examination Clinical history and physical examination follow-ups were done for all sheep involved in this study [18]. Sampling Blood samples were collected at early morning by jugular venipuncture from healthy and pneumonic sheep before starting different treatment protocols (zero day) and seventh days post treatment (7 th DPT) in serum clot tubes and kept at room temperature until coagulation for at least 60 minutes. The clotted blood samples were centrifuged at 2000 x g for 10 minutes at 4°C and aliquoted into small tubes then stored in at -80°C until analysis. Biochemical assays of hepatic, renal function tests, glucose, lipid profile, malondialdehyde and total antioxidant capacity Colorimetric methods were used to determine serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), creatinine, urea, glucose, triglycerides, cholesterol, HDL-cholesterol, LDL-cholesterol, malondialdehyde (MDA), and total antioxidant capacity (TAC). Preparation of Metabolomic Samples Frozen serum samples were thawed on ice and silymarin metabolites extracted and silylated using xylitol as an internal standard, as previously described [15]. Briefly, 100 µL of serum was combined with cold acetonitrile (100%, 200 µL) and centrifuged at 7000 x g for 15 min. Nitrogen gas was used to evaporate the supernatant until it was completely dry. A 50 µL pyridine solution of methoxyamine (20 mg/mL) was first added to the dried residue, then incubated at 60°C for 1 h to derivatize the metabolites. A second derivatization phase was performed by adding 100 µL N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) containing trimethylsilyl (TMS; 1%) to the mixture and incubating this for 1 h at 60°C. The quality control (QC) sample was formed by mixing aliquots from all samples into a pooled sample to analyze changes in MS response. Additionally, a hydrocarbon mixture standard (C8–C40) was analyzed. GC–MS based serum metabolite profiling The serum metabolite profiling was determined using gas chromatography (Thermo Scientific Corp., USA) and a thermo-mass spectrometer detector (ISQ Single Quadrupole Mass Spectrometer). The chromatographic separation was performed as described by [19], with few modifications over TG-5MS columns (30mm x 0.25mm i.d, 0.25 μm film thickness) and helium (He) at a 1 mL/min flow rate as carrier gas, and a 1:10 split ratio and according to the temperature program: 2 min at 80°C, rising with 5°C/min up to 300°C and held for 5 min. Both the injector and detector were held at 280°C. The mass spectral data were acquired via the electron ionization (EI) at 70 eV, with the spectral ranging at m/z 35–500. Processing of GC–MS Data, Molecular Networking and Multivariate Data Analyses Serum metabolite identification was accomplished via comparisons of their retention indices (RI) relative to n-alkanes standards (C8–C40) alongside mass matching to NIST library database. Before mass spectral matching, AMDIS software (www.amdis.net) was used to deconvolute the peaks. Data regarding metabolite abundance were retrieved using MS Dial software with default settings and Pareto scaling in preparation for multivariate data analysis. The detection (LOD) and quantification (LOQ) limits of 32 metabolites were also determined and signal-to-noise ratios of 3:1 and 10:1, respectively, were considered. Statistical analyses A Shapiro-Wilk test was used to determine data normality. Data in this study was normally distributed and expressed as mean with standard deviation. One way ANOVA was carried out to determine the difference between groups Using IBM SPSS statistics 16 (IBM Corporation, Armonk, NY). Comparative analysis of serum metabolic profiles derived from GC-MS of the different therapeutic approaches was performed using both supervised pattern recognition methods, i.e. partial least-squares regression analysis (PLS) using the program SIMCA-P Version 14.0 (Umetrics, Umeå, Sweden). Further, GC-MS derived serum profiles of endogenous metabolites and biochemical parameters viz. MDA and TAC, lipid profile (i.e. triglycerides (TG), cholesterol, HDL- cholesterol, LDL- cholesterol) and blood glucose concentrations, liver enzyme activities (AST, ALT, GGT) and kidney function tests (creatinine and urea) were subjected to partial least-squares regression analysis (PLS) for the sake of efficacy discrimination between the therapeutic approaches and to determine the serum metabolites that are positively or negatively correlated to restoration of pneumonic conditions in sheep to the normal status as implied by the concentrations of the different biochemical markers. Serum metabolites responsible for the differentiation between the four therapeutic approaches were identified based on variable influence on projection (VIP) values of the constructed PLS model (VIP > 1.0). Statistical significance for all analyses in this study was set to P < 0.05. All variables were mean-centered and scaled to Pareto variance [20]. Results The effect of traditional treatment and/ or silymarin on clinical profile. Group 2 showed copious nasal discharge, fever, cough, dyspnea, and abnormal respiratory sounds upon auscultation. G2 showed significantly higher body temperature, respiratory and pulse rates than healthy ones (P < 0.05; Table 1 ). At 7th DPT, SG1 had still significant higher body temperature, respiratory and pulse rates compared to healthy ones (P value 0.05). The rapid clinical response to treatment was achieved early 3 days post treatment in SG 4 by the high dose of oral silymarin administration (560 mg), while the therapeutic responses of SG2 and 3 were achieved at 7th DPT. Table 1 Effect of traditional and /or silymarin on clinical examination of sheep Variables Body temperature (c) Respiratory rate (cycle/ min) Pulse rate (beat/min) G1 (n = 10) 39.01 ± 0.27 a 42.00 ± 2.58 a 70.9 ± 3.2 a G 2 (n = 40) 41.46 ± 0.28 b 68.2 ± 2.5 b 103.5 ± 5. 4 b SG 1 (n = 10); 7th DPT 39.9 ± 0.38 c 52.8 ± 1.98 c 84.9 ± 3.2 c SG 2 (n = 10); 7th DPT 39.4 ± 0.35 a 44.6 ± 2.27 a 73.7 ± 3.77 a SG 3 (n = 10); 7th DPT 39.2 ± 0.13 a 44.00 ± 1.6 a 72.8 ± 2.89 a SG 4 (n = 10); 7th DPT 39.29 ± 0.38 a 42.8 ± 2.4 a 71.5 ± 2.3 a n: number; DPT, days post treatment; Means with different letter superscripts in the same column are significantly different at (P < 0.05). The effect of traditional treatment and/ or silymarin on liver and kidney function tests Pneumonic sheep had significantly higher AST, ALT, GGT, creatinine, and urea concentrations than healthy sheep (P 0.05; Table 2 ), with exception in SG2 which revealed significantly higher creatinine and urea concentrations than healthy sheep (P < 0.05; Table 2 ), while SG 1 showed increased AST, ALT, creatinine, and urea concentrations than healthy sheep (P < 0.05; Table 2 ). Table 2 Effect of traditional and /or silymarin on hepatic and renal function tests Variables AST (U/L) ALT (U/L) GGT (U/L) Creatinine (µmol/L) Urea (mmol/l) G1 (n = 10) 47. 3 ± 1.9 a 27.75 ± 1.12 a 32.24 ± 1.13 a 41.04 ± 1.68 a 1.12 ± 0.15 a G 2 (n = 40) 68.12 ± 2.6 b 42.16 ± 2.08 b 46.53 ± 3. 8 b 53.55 ± 1.48 b 2.8 ± 0.25 b SG 1 (n = 10); 7th DPT 52. 7 ± 1.8 c 31.65 ± 1.017 c 34.68 ± 1.4 c 43.22 ± 1.36 c 1.45 ± 0.11 c SG 2 (n = 10); 7th DPT 48.8 ± 1.06 a 29.16 ± 0.84 a 32.36 ± 0.76 a 42.3 ± 0.8 c 1.34 ± 0.05 c SG 3 (n = 10); 7th DPT 48.46 ± 1.5 a 28.8 ± 1.2 a 32.6 ± 0.63 a 40.93 ± 0.87 a 1.23 ± 0.08 a SG 4 (n = 10); 7th DPT 47.06 ± 0.9 a 28.69 ± 0.9 a 32.17 ± 1.1 a 39.82 ± 1.4 a 1.26 ± 0.07 a n: number; DPT, days post treatment; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase, GGT: Gamma-glutamyl transferase; Means with different letter superscripts in the same column are significantly different at (P < 0.05). The effect of traditional treatment and/ or silymarin on glucose and lipid profile. Pneumonic sheep had significantly higher triglyceride and LDL-cholesterol, and lower cholesterol, HDL-cholesterol, and glucose concentrations than healthy sheep (P 0.05; Table 3 ). Table 3 Effect of traditional and /or silymarin treatment on glucose and lipid profile Variables Triglycerides (mg/dl) Cholesterol (mg/dl) HDL-cholesterol (mg/dl) LDL-Cholesterol (mg/dl) Glucose (mg/dl) G 1 (n = 10) 38.15 ± 1.2 a 68.77 ± 1.9 a 56.02 ± 1.79 a 25.54 ± 1.18 a 62.63 ± 1.12 a G 2 (n = 40) 47.9 ± 1.33 b 43.17 ± 1.68 b 44.1 ± 2.01 b 34.14 ± 1.8 b 43.68 ± 1.79 b SG 1 (n = 10); 7th DPT 39.68 ± 1.03 a 64.75 ± 1.3 a 52.5 ± 0.77 a 25.5 ± 1.12 a 60.84 ± 1.23 a SG 2 (n = 10); 7th DPT 38.96 ± 0.87 a 67.26 ± 1.04 a 54.95 ± 1.1 a 25.7 ± 1.08 a 61.26 ± 1.12 a SG 3 (n = 10); 7th DPT 38.92 ± 0.78 a 67.63 ± 1.8 a 55.72 ± 0.9 a 25.69 ± 10.6 a 60.85 ± 1.6 a SG 4 (n = 10); 7th DPT 38.95 ± 0.86 a 68.11 ± 1.5 a 55.11 ± 0.94 a 25.19 ± 1.02 a 61.66 ± 1.47 a n: number; DPT, days post treatment; HDL: High density lipoprotein; LDL: Low density lipoprotein; Means with different letter superscripts in the same column are significantly different at (P < 0.05). The effect of traditional treatment and/ or silymarin on oxidant and antioxidant status Pneumonic sheep had significantly higher MDA and lower TAC concentrations than healthy sheep (P 0.05), while SG1 showed higher concentrations than healthy sheep (P 0.05), while SG1 and SG2 had lower concentrations of TAC compared to healthy sheep (P < 0.05; Table 4 ) . Table 4 Effect of traditional treatment and silymarin on oxidant and antioxidant status Variables MDA (nmol/ml) TAC (mmol/l) G 1 (n = 10) 2.82 ± 0.2 a 0.83 ± 0.06 a G 2 (n = 40) 4.7 ± 0.45 b 0.33 ± 0.08 b SG 1 (n = 10); 7th DPT 3.12 ± 0.15 c 0.67 ± 0.03 c SG 2 (n = 10); 7th DPT 2.94 ± 0.23 a 0.77 ± 0.04 d SG 3 (n = 10); 7th DPT 2.8 ± 0.18 a 0.8 ± 0.06 a SG 4 (n = 10); 7th DPT 2.7 ± 0.18 a 0.82 ± 0.04 a n: number; DPT, days post treatment; MDA: Malonaldehyde; TAC: Total antioxidant capacity; Means with different letter superscripts in the same column are significantly different at (P < 0.05). Serum metabolites profiling via GC-MS analysis aided by chemometrics. Serum GC/MS-derived metabolite profiles of 49 endogenous metabolites, including organic acids, amino acids, fatty acids, and sugars were identified in group 1, 2 and treated subgroups (1–4) ( Table 5 ). Supervised pattern recognition method i.e, PLS was employed to model serum-based GC-MS derived metabolite profiles of G1 as X-variables versus G2 and other seven PLS models were modeled to correlate the GC-MS derived serum metabolite profiles of four therapeutic approaches (SG 1- SG 4) along with G2 to the 12 tested biochemical parameters. Table 5 Serum metabolites percentile level based on GC/MS analysis No. RT (min) RI Identification G 1 G 2 SG 1, 7th DPT SG 2, 7th DPT SG 3, 7th DPT SG 4, 7th DPT Amino acids 1 4.15 1099 L-Alanine, 2TMS 0.08 ± 0.02 0.21 ± 0.09 0.15 ± 0.01 --- 0.17 ± 0.02 --- 2 4.71 1106 Cystathionine, di-TMS --- 0.05 ± 0.01 --- --- --- --- 3 5.95 1165 Pyruvic acid, MEOX-TMS 0.06 ± 0.01 0.17 ± 0.05 0.13 ± 0.01 --- --- 0.22 ± 0.08 4 6.84 1208 L-Valine, 2TMS 0.02 ± 0.01 0.29 ± 0.02 0.15 ± 0.03 --- 0.23 ± 0.05 0.20 ± 0.05 5 7.4 1210 L-Alanine, 2TMS isomer 0.34 ± 0.08 0.50 ± 0.04 1.01 ± 0.23 0.64 ± 0.12 1.05 ± 0.02 0.84 ± 0.10 6 8.27 1305 L-Leucine, 2TMS 0.22 ± 0.10 0.32 ± 0.10 0.27 ± 0.06 --- --- --- 7 8.79 1316 L-Isoleucine, 2TMS --- 0.15 ± 0.01 0.14 ± 0.01 --- --- --- 8 10.7 1362 Serine, 3TMS --- 0.10 ± 0.04 --- --- --- --- 9 11.62 1377 L-Threonine, 3TMS --- 0.15 ± 0.09 0.19 ± 0.07 --- --- --- 10 11.70 1385 L-Proline, 2TMS 0.04 ± 0.00 0.07 ± 0.01 0.24 ± 0.06 0.07 ± 0.02 0.42 ± 0.08 0.26 ± 0.05 11 12.08 1402 Glycine, 2TMS 1.09 ± 0.16 1.08 ± 0.03 0.16 ± 0.03 1.19 ± 0.05 2.45 ± 0.03 1.53 ± 0.09 12 13.99 1470 L-Threonine, 3TMS isomer 0.05 ± 0.01 0.08 ± 0.01 0.13 ± 0.02 0.01 ± 0.02 0.02 ± 0.04 0.01 ± 0.03 13 16.16 1473 Pyroglutamic acid, 2TMS 0.17 ± 0.05 0.28 ± 0.17 0.15 ± 0.02 0.03 ± 0.08 0.30 ± 0.08 0.19 ± 0.05 14 18.49 1612 Phenylalanine, 2TMS 0.02 ± 0.01 0.01 ± 0.02 0.11 ± 0.01 --- --- --- 15 18.57 1616 L-Glutamic acid, 3TMS 0.15 ± 0.03 0.19 ± 0.06 0.36 ± 0.04 0.03 ± 0.07 0.53 ± 0.18 0.29 ± 0.06 16 22.55 1788 L-Ornithine, 4TMS 0.10 ± 0.02 0.13 ± 0.03 0.21 ± 0.03 --- 0.25 ± 0.06 --- Total Amino acids 2.32 3.76 3.39 1.97 5.42 3.55 Fatty acids 17 25.82 2031 Palmitic acid, TMS 0.95 ± 0.17 0.34 ± 0.21 0.62 ± 0.2 1.17 ± 0.03 0.77 ± 0.12 0.46 ± 0.15 18 28.27 2154 Linoleic acid, TMS 0.71 ± 0.21 0.33 ± 0.04 0.57 ± 0.03 0.81 ± 0.02 0.70 ± 0.08 0.50 ± 0.03 19 28.39 2166 Oleic acid, TMS 2.26 ± 0.09 0.69 ± 0.05 0.91 ± 0.04 2.28 ± 0.07 1.49 ± 0.07 1.01 ± 0.04 20 28.82 2183 Stearic acid, TMS 0.23 ± 0.15 0.17 ± 0.07 0.26 ± 0.08 0.85 ± 0.03 0.42 ± 0.06 0.27 ± 0.06 Total Fatty acids 4.15 1.53 2.36 5.10 3.38 2.23 Esters 21 33.69 2210 1-Monopalmitin, 4TMS 0.38 ± 0.03 0.17 ± 0.02 0.31 ± 0.04 0.52 ± 0.13 0.39 ± 0.05 0.39 ± 0.06 22 36.06 2235 1-Monostearin, 2TMS 0.24 ± 0.08 0.18 ± 0.03 0.35 ± 0.06 0.60 ± 0.012 0.49 ± 0.08 0.45 ± 0.05 Total Esters 0.62 0.35 0.66 1.12 0.88 0.85 Organic acids 23 5.41 1140 Propane-1,2-diol, di-TMS 0.73 ± 0.04 0.82 ± 0.05 --- 1.99 ± 0.03 0.23 ± 0.11 0.67 ± 0.04 24 6.49 1060 Lactic Acid, 2TMS 58.15 ± 1.41 39.56 ± 0.17 27.49 ± 2.87 9.14 ± 0.08 11.51 ± 1.05 24.43 ± 1.48 25 8.07 1081 Glycolic acid, 2TMS 0.98 ± 0.20 1.35 ± 0.09 4.87 ± 0.07 2.22 ± 0.06 3.88 ± 0.06 3.00 ± 0.06 26 8.64 1156 4-Hydroxybutanoic acid, 2TMS 0.38 ± 0.07 1.61 ± 0.07 1.80 ± 0.22 1.75 ± 0.02 2.85 ± 0.05 1.30 ± 0.12 27 10.22 1325 Caproic acid, TMS --- 0.15 ± 0.01 --- --- --- --- 28 10.58 1136 Oxalic acid, 2TMS --- 0.11 ± 0.01 0.18 ± 0.02 --- --- --- 29 11.80 1178 α-Aminocaproic acid (tms) 0.06 ± 0.01 0.13 ± 0.02 1.10 ± 0.15 0.35 ± 0.10 0.26 ± 0.06 0.25 ± 0.05 30 16.44 1503 3-Methylglutaric acid, 2TMS ---- 0.22 ± 0.09 0.14 ± 0.04 --- --- --- 31 22.47 1778 Citric acid, (4TMS) 0.16 ± 0.04 --- --- --- 0.45 ± 0.16 --- Total Organic acids 60.46 43.94 35.580 15.45 19.19 29.657 Inorganic acids 32 11.29 1306 Phosphoric acid, 3TMS 0.22 ± 0.07 0.89 ± 0.11 0.91 ± 0.04 1.59 ± 0.03 0.99 ± 0.02 0.73 ± 0.05 Inorganic acids 0.22 0.89 0.910 1.59 0.99 0.732 Nitrogenous compounds 33 4.61 1101 Bis(trimethylsilyl)carbodiimide 0.17 ± 0.05 0.16 ± 0.02 0.37 ± 0.08 0.88 ± 0.06 0.43 ± 0.08 0.50 ± 0.08 34 7.86 1105 Hydroxylamine, 3TMS 0.16 ± 0.05 0.17 ± 0.04 0.23 ± 0.08 0.28 ± 0.01 0.28 ± 0.08 0.41 ± 0.12 35 7.95 1113 3-Hydroxybutyric acid, 2TMS --- 0.11 ± 0.03 0.26 ± 0.07 0.32 ± 0.01 0.22 ± 0.05 --- 36 10.09 1281 Urea, 2TMS 7.62 ± 0.16 13.56 ± 0.60 14.81 ± 1.17 20.01 ± 0.02 27.73 ± 1.95 23.67 ± 1.95 37 17.2 1486 Creatinine, 3TMS 0.10 ± 0.01 0.10 ± 0.03 0.18 ± 0.07 0.03 ± 0.03 0.32 ± 0.04 0.18 ± 0.04 Total Nitrogenous compounds 8.04 14.00 15.85 21.53 28.98 24.77 Sugars 38 11.53 1300 Glycerol, 3TMS 0.37 ± 0.1 0.64 ± 0.09 0.57 ± 0.13 0.75 ± 0.03 0.71 ± 0.12 0.66 ± 0.26 39 20.25 1666 D-Arabinose, 4TMS 0.02 ± 0.01 0.15 ± 0.02 0.17 ± 0.02 --- 0.20 ± 0.04 40 24.10 1858 Glucose, 5TMS 0.09 ± 0.02 --- --- --- --- 41 24.16 1860 β-Galactopyranose, 5TMS 0.25 ± 0.04 0.46 ± 0.06 0.97 ± 0.05 1.36 ± 0.04 0.92 ± 0.21 0.77 ± 0.12 42 24.33 1858 Glucose, methyloxime, 5TMS 20.39 ± 0.80 30.00 ± 0.40 33.28 ± 2.40 39.45 ± 2.06 32.72 ± 1.20 31.50 ± 2.11 43 24.42 1866 D-Mannose, 5TMS --- --- 0.13 ± 0.01 --- --- --- 44 24.63 1885 D-(+)-Talose, 5TMS 2.49 ± 0.08 2.99 ± 0.06 4.47 ± 0.04 5.25 ± 0.20 5.40 ± 0.07 3.76 ± 0.09 45 24.95 1493 Lactulose, 6TMS --- 0.09 ± 0.02 0.16 ± 0.01 --- --- --- 46 25.63 1515 Glucopyranose, 5TMS 0.10 ± 0.02 --- --- --- --- 0.14 ± 0.04 47 26.38 1568 β-D-Glucopyranose, TMS 0.04 ± 0.01 0.16 ± 0.05 0.18 ± 0.02 --- --- 0.21 ± 0.03 48 27.53 1586 Myoinositol TMS 0.15 ± 0.04 0.40 ± 0.11 0.64 ± 0.21 0.71± 0.59 ± 0.12 0.40 ± 0.06 Total Sugars 23.89 34.88 40.57 47.52 40.34 37.64 Unknown 49 28.48 2172 unknown1 --- --- --- 0.53 ± 0.14 --- --- 50 35.33 2212 unknown2 --- 0.20 ± 0.02 --- --- --- --- 51 37.10 2274 unknown3 --- --- --- 1.04 ± 0.08 --- --- 52 37.13 2278 unknow4 --- --- --- 3.02 ± 0.04 --- --- 53 37.42 2284 unknow5 --- --- --- 0.37 ± 0.08 --- --- 54 40.31 2389 unknow6 0.21 ± 0.05 0.25 ± 0.05 0.50 ± 0.10 0.73 ± 0.14 0.57 ± 0.10 0.43 ± 0.05 Total unknown 0.21 0.45 0.50 5.69 0.57 0.43 99.90 99.89 99.81 99.96 99.75 99.84 To explore the differential therapeutic efficacy of the four therapeutic approaches and their influence on restoring the biochemical parameters in pneumonic sheep to their normal status, seven PLS models were attempted to correlate the GC-MS derived serum metabolite profiles of four therapeutic approaches (SG 1 - SG 4) along with the pneumonic sheep group (G 2) to the twelve tested biochemical parameters (Fig. 1 ). Validation of the PLS model represented by the relationship between observed and predicted values and permutation plots are depicted in Fig. S2. The percent of variation that can be predicted by the models according to a leave-one-out cross-validation procedure are ranging from 90.7–71.9% (Q2X(cum)). As observed in Fig. 1 (A-H), PLS models exhibited strong correlations between GC-MS serum metabolite profiles of the pneumonic sheep treated with the four therapeutic approaches as well as the pneumonic sheep group (G 2) (R2 = 0.878 to 0.907) as observed for the regression lines and the significant spread of the samples along the reference lines. Hence, strong relationships between the defined and predicted values of the tested biochemical parameters exist. The derived PLS score plots (Fig. 1 A) provided a clear distinction between the modeled groups (SG 1- SG 4) with pneumonic sheep group (G 2) the most distant from them. Further, all the scores plots exhibited trends of either decreasing or increasing order of the samples potency in modulating the tested biochemical parameters to restore their values to the normal status. For example, in PLS scores plot depicted in Figs. 2 A & G, the samples were spanned from the positive to the negative PC1 side in order of their increasing potency in lowering MDA concentrations and liver activity markers, i.e. AST, ALT & GGT as follows: SG 1˂ SG 4˂ SG 2˂ SG 3, than that observed in the pneumonic sheep group (G 2) located at the positive side of PC1 with the highest positive score. The strongest effect on increasing the TAC concentrations was demonstrated with SG 2, and a trend of increasing potency of the therapeutic approaches was also found along PC1 as spanning from negative to positive side (SG 1˂ SG 4˂ SG 2 ≤ SG 3) in PLS score plot depicted in Fig. 1 B. The same order was noticed in Fig. 1 C for lowering the TG and LDL-cholesterol but increasing the total and HDL-cholesterol concentrations (Fig. 1 D) and decreasing creatinine and urea (Fig. 1 E) in serum of the pneumonic sheep groups in response to the four therapeutic approaches. The endogenous metabolites that were deemed to be crucial in distinguishing between the different therapeutic approaches respective to their therapeutic efficacy on restoring the values of the biochemical parameters level to the normal status were those possessing VIP values > 1 in the Variable Importance for Projection (VIP) plots (Fig. S3) namely lactic acid, glycolic acid, urea, glucose, α-aminocaproic acid, propane-1,2-diol, glycine, L-alanine, 4-hydroxybutanoic acid, D-(+)-talose and oleic acid. These metabolites were considered the most important for the model prediction, which were then used to create two other PLS models to compare the two therapeutic approaches, SG 2 & SG 3, that were proposed to be the most effective pneumonic treatments in the PLS model depicted in Fig. 1 . The correlations between the two therapeutic approaches (SG 2 & SG 3) to their respective biochemical parameters were explored via two PLS regression models (Figs. 2 A & B). The elevated biochemical parameters due to pneumonic condition that were suppressed by the therapeutic approaches i.e., TAC, glucose, and total and HDL-cholesterol were regressed in one model (Fig. 2 A), and the other parameters were found to be decreasing in pneumonic condition and shown to be elevated by the treatment are regressed in the second model (Fig. 2 B) which are MDA, LDL-cholesterol, creatinine, urea, AST, ALT and GGT. The two models were validated using 200 random permutations and showed a performance with goodness of model fit (R2 = 0.956 and 0.873) and predictive power of the model (Q2 = 0.781 and 0.241), respectively, with the second model showing a lower predictive power. Validation of the two PLS models was demonstrated from the regression analysis and permutation plots depicted in Fig. S4 & S5, respectively. The derived biplot (an amalgamation of the information revealed by both the score and loading plots) (Fig. 2 A) showed that therapeutic approach relying on a silymarin dose of 280 mg only (SG 3) was strongly correlated with the upregulation of TAC, glucose, and total and HDL-cholesterol values as being projected close to SG 3 samples on the right side of the biplot however, all of the SG 2 samples were remotely distributed on the left side of the biplot. This indicated that the subgroup 3 treatment was more effective in increasing the TAC, glucose, and total and HDL-cholesterol values than the SG 2 treatment. Hence, SG 2 was more efficacious in suppressing oxidative stress and restoring lipid profile and blood sugar to their normal status. PLS model (Fig. S1 ) was initially established by modeling the GC-MS derived serum metabolite profiles of healthy control (G1) (as X-variables) versus pneumonic sheep (G2) to the twelve tested biochemical parameters (as Y-variables) to identify endogenous metabolite markers and the biochemical status of each group. The covered variance and prediction power of the model was assessed by R2 and Q2 values which were computed to be 0.942 and 0.82 indicating model validity. PLS score plot (Fig. S1 A) showed a clear discrimination between the healthy and pneumonic sheep groups, and that discrimination was explained by the loading plot (Fig. S1 B), which revealed that lactic acid was more elevated in the healthy sheep, whereas urea and creatinine were detected at higher concentrations in pneumonic sheep. Furthermore, it was shown that some biochemical parameters were found to be more elevated in the pneumonic sheep group (G 2) i.e., liver and kidney functions (AST, ALT, ALT, GGT, creatinine, urea) as well as oxidative stress occur as represented by high MDA values in addition to high LDL-cholesterol than the healthy sheep. However, TAC, total cholesterol, HDL-cholesterol, and glucose were found at higher concentrations in the healthy sheep compared to the pneumonic sheep. Discussion Group 2 showed copious nasal discharge, fever, cough, dyspnea, abnormal respiratory sounds upon auscultation, higher body temperature, respiratory and pulse rates than healthy ones, the same results were recorded by [ 21 ]. SG1 had significant higher body temperature, respiratory and pulse rates compared to healthy ones, this could be attributed to the microbial resistance to antibiotics administration [ 22 ], while SG2, 3 and 4 did not significantly differ than G1. The rapid clinical response to treatment was achieved early 3 days post treatment in SG 4 by the high dose of oral silymarin administration (560 mg) that could be attributed to the broad spectrum activity of silymarin as anti-inflammatory, anti-oxidative and antimicrobial agents [11; 22]. In the present study, pneumonic sheep had significantly higher AST, ALT, GGT, creatinine, and urea concentrations than healthy sheep. The same results were recorded [23; 24]. The increase of these liver function tests may be due to hepatic cellular damage and degenerative modifications brought on by bacterial infection and its toxins [ 25 ], or due to severe exposure to oxidative stress resulting in damage of phospholipid structure of hepatic cell membrane [ 21 ], while higher creatinine and urea concentrations could be related to renal damage caused by excessive release of free radicals that exhibited during the inflammatory progression and enhanced the protein catabolism [ 26 ]. Interestingly, liver and kidney functions were improved in pneumonic sheep treated with silymarin than traditional treatment. Our findings were similar to previous studies [ 27 ]. It is plausible that silymarin has an anti-inflammatory and antioxidants property that protect against cellular injury [ 28 – 30 ]. Pneumonic sheep had significantly higher triglyceride and LDL-cholesterol, and lower cholesterol, HDL-cholesterol and glucose concentrations compared to healthy sheep. Similar findings has been reported in previous studies [ 31 ]. Inflammation can cause hypertriglyceridemia in both humans and animals [ 32 ]. Lower serum cholesterol concentrations in the sheep of this study could have be due to liver injury with subsequent changes to lipoprotein metabolism [ 33 ]. Pneumonic sheep that received silymarin had significantly lower triglyceride and LDL-cholesterol and higher cholesterol, HDL-cholesterol, and glucose concentrations. Potential explanation include that silymarin could decrease blood cholesterol concentration by slowing down liver cell cholesterol synthesis and speeding up the conversion of cholesterol to other molecules [ 34 ], also the silymarin normalize the binding of low- density LDL [ 35 ], while the significant increase of HDL- cholesterol may be due to reducing cholesterol absorption in pneumonic sheep received silymarin in the protocol of treatment [ 36 ]. In the current study pneumonic sheep had significantly higher MDA and lower TAC concentrations compared to healthy sheep, similar to the results recorded by [ 21 ]. The increase in serum MDA concentrations could be due to excessive lipid peroxidation, while reduction of TAC in pneumonic sheep may be due to its sequestration during the inflammatory process in lung tissue [ 37 ]. Pneumonic sheep received silymarin in the protocol of treatment showed a significantly decrease in MDA and an increase in TAC concentrations compared to sheep treated by traditional treatment. It’s possible that silymarin has antioxidant and neutralization effects either on free radicals or toxins [ 35 ]. Conclusions Discriminatory analysis of metabolomics profile revealed that pneumonic sheep treated with 280 mg oral silymarin had an improved health status and metabolomics profile. Furthermore, pneumonic sheep treated with 560 mg oral silymarin had faster curative achievement. Silymarin administration either alone or in combination with traditional treatment exhibited greater therapeutic improvement than treatment with traditional treatment alone. Declarations Authors’ contributions Hany Hassan: Conceptualization, Project administration, Supervision, reviewed the manuscript editing. Ahmed Kamr: Writing - original draft- review& editing. Abdel Nasser El-Gendy: Metabolomic analysis, Validation resources, Writing - original draft- review & editing. Ramiro Toribio: Writing - original draft- review & editing. Amira R. Khattab: Metabolomic analysis, Writing - original draft- review & editing. Walid Mousa : Investigation, Methodology. Hadeer Khaled: Investigation, Methodology. Abdelsalam Elkholey: Investigation, Methodology, Mohamed Kasem: Investigation, Methodology. Ali Arbaga: Investigation, Methodology, Writing- Original draft- review& editing. Funding Postgraduate studies and research sector funded this study- University of Sadat City, Egypt; under grant number: 22 in (29-12-2021). Data Availability All data generated and/or analyzed during this study are included in this manuscript. The raw data are available from the corresponding author upon reasonable request. Ethics approval and consent to participate This study was approved by the Animal Ethics Committee at the Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval code VUSC-028-1-22). All methods were performed in accordance with the guidelines and regulations of this committee. Consent to Participate declaration Not applicable. Competing Interests The authors declared that they have no competing interests. References Thompson M. Respiratory diseases in sheep. Vet Pr. Today. 2019; 7(4): 48–51. Yahya KH, Al-Mahmood SS, Al-Hubeity TY. Necropsy findings and histopathological analysis of a terminal stage ewe from a herd with sudden deaths in Mosul. 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GC-MS-based metabolomic profiling of thymoquinone in streptozotocin-induced diabetic nephropathy in rats. Nat. Prod. Commun. 2017; 12(4): 553–558. Rummun N, Khattab AR, Bahorun T, Farag MA, Neergheen VS. Biochemometric approach to reveal Terminalia bentzoë cytotoxic effect against HepG2 cells in relation to its different organs and extraction solvents as analysed via UPLC-MS. South African J. Bot. 2023; 159: 507–518. Hassan HY, Kamr A, Abdelazeim A, Khaled H. Hemato-Biochemical Response with Highlights on the Role of Oxidants and Antioxidants in Pneumonic Sheep. J Vet Mar. Sci. 2019; 1(1): 7–14. Hassan H, Kamr A, Mousa W, Toribio R, El-Gendy A, Khaled H, Elkholey A, Arbaga A.. Silymarin Antibacterial Efficacy against Some Isolated Bacterial Strains from Pneumonic Sheep - Vitro Study. PVJ. 2024; DOI: 10.29261/pakvetj/2024.157. Arbaga A, Hassan H, Anis A, Osthman N, Kamr A. Hematological changes and serum minerals concentrations in pneumonic sheep. Benha Vet. Med. 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Effect of silymarin on serum levels of ALT and GGT in ethanol induced hepatotoxicity in albino rats. J. Ayub Med. Coll. Abbottabad. 2009; 21(4): 73–75. Andrade RJ, Tulkens PM. Hepatic safety of antibiotics used in primary care. J. Antimicrob. Chemother. 2011; 66(7): 1431–1446. El-Deeb WM, Tharwat M. Lipoproteins profile, acute phase proteins, proinflammatory cytokines and oxidative stress biomarkers in sheep with pneumonic pasteurellosis. Comp. Clin. Path. 2015; 24: 581–588. Phetteplace HW, Sedkova N, Hirano K, Davidson NO, Lanza‐Jacoby SP. Escherichia coli sepsis increases hepatic apolipoprotein B secretion by inhibiting degradation. Lipids. 2000; 35(10): 1079–1086. El-Deeb WM, Elmoslemany AM. The diagnostic accuracy of acute phase proteins and proinflammatory cytokines in sheep with pneumonic pasteurellosis. 2016; PeerJ 4: 1-12. Fallah Huseini H, Zaree AB, Babaei Zarch A, Heshmat R. The effect of herbal medicine Silybum marianum (L.) Gaertn. seed extract on galactose induced cataract formation in rat. J. Med. Plants. 2004; 3: 58–62. Khazaei R, Seidavi A, Bouyeh M. A review on the mechanisms of the effect of silymarin in milk thistle (Silybum marianum) on some laboratory animals. Vet. Med. Sci. 2022; 8(1): 289–301. Sobolová L, Škottová N, Večeřa R, Urbánek K. Effect of silymarin and its polyphenolic fraction on cholesterol absorption in rats. Pharmacol. Res. 2006; 53(2): 104–112. Del Rio D, Stewart AJ, Pellegrini N. A review of recent studies on malondialdehyde as toxic molecule and biological marker of oxidative stress. Nutr. Metab. Cardiovasc. Dis. 2005; 15(4): 316–328. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4344803","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":300983573,"identity":"f982687d-83bb-4e7e-9dfe-6206a1f656a8","order_by":0,"name":"Hany Hassan","email":"","orcid":"","institution":"University of Sadat City","correspondingAuthor":false,"prefix":"","firstName":"Hany","middleName":"","lastName":"Hassan","suffix":""},{"id":300983575,"identity":"aa30f400-af9e-4eac-8ce5-533daad43413","order_by":1,"name":"Ahmed Kamr","email":"","orcid":"","institution":"University of Sadat City","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Kamr","suffix":""},{"id":300983576,"identity":"c8eabd8b-bedd-4339-8e7b-f44b252bf0c2","order_by":2,"name":"Abdel Nasser El-Gendy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYNACNgYG+/YGBmbStBjwHCBZi0QCkVr4+5dfky4oO8xgLvnG8HNBhQ0Df3t3Al4tEjfelEnPOHeYwXJ2jrH0jDNpDBJnzm7Ab82NM2nSvG2HGRhu5xiAGQYSufi1yMO13Dxj/JsoLQbn249BDL/BY0acLYY3eJitec6lM0j2pJVZ85xJ4yHoF7nzxx/e5imzZuBnP7z5Nk+FjRx/ey8B70vkGADJ5voGBg4Qg4EHv3IQ4D/+AEjWATH7A8KqR8EoGAWjYEQCAP1GRdtCkU3NAAAAAElFTkSuQmCC","orcid":"","institution":"National Research Centre","correspondingAuthor":true,"prefix":"","firstName":"Abdel","middleName":"Nasser","lastName":"El-Gendy","suffix":""},{"id":300983577,"identity":"4ffa6feb-bda1-43d4-873c-f4a400d981c4","order_by":3,"name":"Ramiro Toribio","email":"","orcid":"","institution":"the Ohio State University","correspondingAuthor":false,"prefix":"","firstName":"Ramiro","middleName":"","lastName":"Toribio","suffix":""},{"id":300983580,"identity":"1191ab6f-de3a-4348-8f28-698f1325c6f7","order_by":4,"name":"Amira R. 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B) correlating therapeutic approaches (SG 2, red dots) \u0026amp; SG 3, violet dots) based on their GC-MS derived metabolite profiles (X-variables) correlated to the elevated biochemical parameters due to pneumonic condition \u003cem\u003ei.e.\u003c/em\u003e TAC, glucose, and total and HDL-cholesterol (Y-variables) and the decreased biochemical parameters due to pneumonic condition \u003cem\u003ei.e.\u003c/em\u003e MDA, LDL-cholesterol, creatinine, urea, AST, ALT and GGT\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4344803/v1/bfda80013be210e8d4b25150.jpg"},{"id":56846055,"identity":"e38b23ff-bafe-40c2-9eb0-cc2b87fd6cd5","added_by":"auto","created_at":"2024-05-21 08:05:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2098474,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4344803/v1/9726f510-cfb7-4409-8db4-f5617a60e271.pdf"},{"id":56440985,"identity":"393b512c-a406-45bb-bc99-be1b02d41c6f","added_by":"auto","created_at":"2024-05-14 08:35:01","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":7952245,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4344803/v1/4154b6de6e4e3280fcfbbdb2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinicobiochemical and GC-MS Based Serum Metabolomics for determination of Therapeutic Efficacy of Silymarin in Pneumonic Sheep","fulltext":[{"header":"Background","content":"\u003cp\u003ePneumonia is a complex disease that in small ruminants results from a combination of environmental, management, immune, and infectious (bacterial, viral, and mycotic agents) factors that results in major economic losses due to cost of treatment, reduced productivity, and high mortality rates [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFluoroquinolones and macrolides are broad-spectrum antibiotics commonly used to treat pneumonia in sheep [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In addition, anti-inflammatory drugs are often indicated to control disease severity. Currently, antimicrobial resistance is a global concern that requires multidisciplinary strategies to ensure efficient therapies for human and animal populations [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In recent years, herbal therapy has received attention as a novel and alternative therapeutic approach due to its safety and cultural acceptability [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eSilybum marianum\u003c/em\u003e (SM; milk thistle) has been used for centuries as a natural remedy to cure a variety of illnesses, particularly hepatic ones. It contains a flavonolignan complex termed silymarin mainly found in the seeds and fruits [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Silymarin, of which silibinin is the main active component, has antimicrobial, antimycotic, anti-inflammatory, antifibrotic, immunomodulating, and anthelmintic properties [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It also reduces the expression of sterol regulatory element binding protein 1 and fatty acid transport protein 5 in hepatic cells to prevent the fat accumulation caused by free fatty acids [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Silymarin's ability to scavenge free radicals and boost endogenous antioxidant defenses, such as the glutathione system, is linked to its ability to reduce oxidative stress-induced hepatocellular damage [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. It protects kidney cells \u003cem\u003ein vitro\u003c/em\u003e from medication-induced nephrotoxicity as well as from cyclosporine nephrotoxicity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Given the pleiotropic actions of silymarin and the clinical importance of respiratory disease in small ruminants, investigating silymarin in sheep with pneumonia could provide valuable information.\u003c/p\u003e \u003cp\u003eMetabolomics analysis is a contemporary approach in drug development, disease diagnosis, pathophysiology, and prognosis. It provides more biochemical insight and understanding than other systems biology omics techniques [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Furthermore, it enables the measurement of changes in endogenous small molecules within cells, tissues, and biofluids of the body in response to environmental changes or contaminants. Gas chromatography-mass spectrometry (GC-MS) is the most used metabolomics technology for quantitatively analyzing various metabolites in biological materials. It can effectively and rapidly separate and identify large pools of metabolites [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Recently, scientists have directed their attention towards the biological and pharmaceutical applications of metabolites obtained from edible plants and foods [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe purpose of this study was to assess the therapeutic effectiveness of silymarin in pneumonic sheep using clinical examination, metabolomics profiling, and biochemical parameter measurements. We expected that treating pneumonic sheep with silymarin would cure and enhance their health.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eMilk thistle extract (\u003cem\u003eSilybum marianum\u003c/em\u003e)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSilymarin powder was provided by Medical Union Pharmaceuticals (MUP) \u003cem\u003eCompany\u003c/em\u003e, Egypt. The powder consists of 50% silymarin with a potency of 104.49%, with code number 0111304600.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimals\u0026rsquo; criteria\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eand experimental design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of fifty male adult Barki sheep at private farm in Sadat City, Egypt, aged between 1 to 2 years with a mean body weight of 60 \u0026plusmn; 2 kilograms\u0026nbsp;were\u0026nbsp;assigned to\u0026nbsp;two\u0026nbsp;groups based on their health condition.\u0026nbsp;Group 1 (G1; n =10),\u0026nbsp;included healthy sheep with no clinical or laboratory evidence of disease, were free of external and internal parasites, and served as a control\u0026nbsp;group.\u0026nbsp;Group 2 (G2; n = 40),\u0026nbsp;consisted of sheep with evidence of respiratory disease, including\u0026nbsp;copious nasal discharge, fever, cough, dyspnea, and abnormal respiratory sounds upon auscultation. This\u0026nbsp;group was further divided into four\u0026nbsp;subgroups according to the therapeutic protocol.\u0026nbsp;SG1 (n =10)\u0026nbsp;included pneumonic sheep that received the\u0026nbsp;traditional antimicrobial treatment for pneumonia using florfenicol (20 mg/kg body weight/ IM injection), a non-steroidal anti-inflammatory drug as diclofenac sodium (2.5 mg/kg body weight/ IM injection) and anti-histaminic drug as diphenhydramine hydrochloride 20 mg (1 ml/45 kg bodyweight/ IM injection). SG2 (n =10)\u0026nbsp;consisted of pneumonic sheep treated as\u0026nbsp;SG1 plus daily oral administration of silymarin at a dose of 280 mg every 24 hours for seven consecutive days. SG3 (n =10)\u0026nbsp;consisted of pneumonic sheep treated with\u0026nbsp;oral administration of silymarin 280 mg every 24 hours for seven consecutive days\u0026nbsp;[17].\u0026nbsp;SG4 (n =10)\u0026nbsp;included pneumonic sheep treated by\u0026nbsp;daily oral administration of silymarin 560 mg every 24 hours for seven consecutive days.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral clinical examination\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClinical history and physical examination follow-ups were done for all sheep involved in this study\u0026nbsp;[18].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBlood samples were collected at early morning by jugular venipuncture from healthy and pneumonic sheep before starting different treatment protocols (zero day) and seventh days post treatment (7\u003csup\u003eth\u003c/sup\u003e DPT) in serum clot tubes and kept at room temperature until coagulation for at least 60 minutes. The clotted blood samples were centrifuged at 2000 x \u003cem\u003eg\u003c/em\u003e for 10 minutes\u0026nbsp;at 4\u0026deg;C\u0026nbsp;and aliquoted into small tubes then stored in at -80\u0026deg;C until analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiochemical assays of hepatic, renal function tests, glucose, lipid profile, malondialdehyde and total antioxidant capacity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eColorimetric methods were used to determine serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), creatinine, urea, glucose, triglycerides, cholesterol, HDL-cholesterol, LDL-cholesterol, malondialdehyde (MDA), and\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003etotal antioxidant capacity (TAC).\u003cstrong\u003e\u003cs\u003e\u0026nbsp;\u003c/s\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of Metabolomic Samples\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrozen serum samples were thawed on ice and silymarin metabolites extracted and silylated using xylitol as an internal standard, as previously described\u0026nbsp;[15]. Briefly, 100 \u0026micro;L of serum was combined with cold acetonitrile (100%, 200 \u0026micro;L) and centrifuged at 7000 x g for 15 min. Nitrogen gas was used to evaporate the supernatant until it was completely dry. A 50 \u0026micro;L pyridine solution of methoxyamine (20 mg/mL) was first added to the dried residue, then incubated at 60\u0026deg;C for 1 h to derivatize the metabolites. A second derivatization phase was performed by adding 100 \u0026micro;L N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA) containing\u0026nbsp;trimethylsilyl (TMS;\u0026nbsp;1%) to the mixture and incubating this for 1 h at 60\u0026deg;C. The quality control (QC) sample was formed by mixing aliquots from all samples into a pooled sample to analyze changes in MS response. Additionally, a hydrocarbon mixture standard (C8\u0026ndash;C40) was analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGC\u0026ndash;MS based serum metabolite profiling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe serum metabolite profiling was determined using gas chromatography (Thermo Scientific Corp., USA) and a thermo-mass spectrometer detector (ISQ Single Quadrupole Mass Spectrometer). The chromatographic separation was performed as described by [19], with few modifications over TG-5MS columns (30mm x 0.25mm i.d, 0.25 \u0026mu;m film thickness) and helium (He) at a 1 mL/min flow rate as carrier gas, and a 1:10 split ratio and according to the temperature program: 2 min at 80\u0026deg;C, rising with 5\u0026deg;C/min up to 300\u0026deg;C and held for 5 min. Both the injector and detector were held at 280\u0026deg;C. The mass spectral data were acquired via the electron ionization (EI) at 70 eV, with the spectral ranging at m/z 35\u0026ndash;500.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcessing of GC\u0026ndash;MS Data, Molecular Networking and Multivariate Data Analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum metabolite identification was accomplished via comparisons of their retention indices (RI) relative to n-alkanes standards (C8\u0026ndash;C40) alongside mass matching to NIST library database. Before mass spectral matching, AMDIS software (www.amdis.net) was used to deconvolute the peaks. Data regarding metabolite abundance were retrieved using MS Dial software with default settings and Pareto scaling in preparation for multivariate data analysis. The detection (LOD) and quantification (LOQ) limits of 32 metabolites were also determined and signal-to-noise ratios of 3:1 and 10:1, respectively, were considered.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA Shapiro-Wilk test was used to determine data normality. Data in this study was normally distributed and expressed as mean with standard deviation. One way ANOVA was carried out to determine the difference between groups Using IBM SPSS statistics 16 (IBM Corporation, Armonk, NY). \u0026nbsp;Comparative analysis of serum metabolic profiles derived from GC-MS of the different therapeutic approaches was\u0026nbsp;performed\u0026nbsp;using both supervised pattern recognition methods, \u003cem\u003ei.e.\u0026nbsp;\u003c/em\u003epartial least-squares regression analysis (PLS) using the program SIMCA-P Version 14.0 (Umetrics, Ume\u0026aring;, Sweden). Further, GC-MS derived serum profiles of endogenous metabolites and biochemical parameters \u003cem\u003eviz.\u003c/em\u003e MDA and\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTAC, lipid profile (i.e. triglycerides (TG), cholesterol, HDL- cholesterol, LDL- cholesterol) and blood glucose concentrations, liver enzyme activities (AST, \u0026nbsp;ALT, GGT) and kidney function tests (creatinine and urea) were subjected to partial least-squares regression analysis (PLS) for the sake of efficacy discrimination between the therapeutic approaches and to determine the serum metabolites that are positively or negatively correlated to restoration of pneumonic conditions in sheep to the normal status as implied by the concentrations of the different biochemical markers. Serum metabolites responsible for the differentiation between the four therapeutic approaches were identified based on variable influence on projection (VIP) values of the constructed PLS model (VIP \u0026gt; 1.0). Statistical significance for all analyses in this study was set to P \u0026lt; 0.05. All variables were mean-centered and scaled to Pareto variance [20].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eThe effect of traditional treatment and/ or silymarin on clinical profile.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGroup 2 showed copious nasal discharge, fever, cough, dyspnea, and abnormal respiratory sounds upon auscultation. G2 showed significantly higher body temperature, respiratory and pulse rates than healthy ones (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At 7th DPT, SG1 had still significant higher body temperature, respiratory and pulse rates compared to healthy ones (P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) and showed respiratory manifestations, while SG 2, 3 and 4 were not significantly different than G1 (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The rapid clinical response to treatment was achieved early 3 days post treatment in SG 4 by the high dose of oral silymarin administration (560 mg), while the therapeutic responses of SG2 and 3 were achieved at 7th DPT.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of traditional and /or silymarin on clinical examination of sheep\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBody temperature (c)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRespiratory rate (cycle/ min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePulse rate (beat/min)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.58 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 2 (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5. 4 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 1 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 2 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.27 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.77 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 3 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 4 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003en: number; DPT, days post treatment; Means with different letter superscripts in the same column are significantly different at (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eThe effect of traditional treatment and/ or silymarin on liver and kidney function tests\u003c/h2\u003e \u003cp\u003ePneumonic sheep had significantly higher AST, ALT, GGT, creatinine, and urea concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At 7th DPT, SG 2, 3 and 4 were not significantly different than healthy sheep (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with exception in SG2 which revealed significantly higher creatinine and urea concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), while SG 1 showed increased AST, ALT, creatinine, and urea concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of traditional and /or silymarin on hepatic and renal function tests\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGGT (U/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUrea (mmol/l)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47. 3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.24\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 2 (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.16\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3. 8 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 1 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52. 7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.017 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 2 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 3 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 4 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003en: number; DPT, days post treatment; AST: Aspartate aminotransferase; ALT: Alanine aminotransferase, GGT: Gamma-glutamyl transferase; Means with different letter superscripts in the same column are significantly different at (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of traditional treatment and/ or silymarin on glucose and lipid profile.\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePneumonic sheep had significantly higher triglyceride and LDL-cholesterol, and lower cholesterol, HDL-cholesterol, and glucose concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), while, at 7th DPT, SG 1, 2,3 and 4 were not different than healthy ones (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of traditional and /or silymarin treatment on glucose and lipid profile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTriglycerides (mg/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCholesterol (mg/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHDL-cholesterol (mg/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLDL-Cholesterol (mg/dl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlucose (mg/dl)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 1 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 2 (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.17\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.14\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.79 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 1 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.23 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 2 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.87 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 3 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.69\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 4 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.86 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003en: number; DPT, days post treatment; HDL: High density lipoprotein; LDL: Low density lipoprotein; Means with different letter superscripts in the same column are significantly different at (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eThe effect of traditional treatment and/ or silymarin on oxidant and antioxidant status\u003c/h2\u003e \u003cp\u003ePneumonic sheep had significantly higher MDA and lower TAC concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For MDA concentrations at 7th DPT, SG 2, 3 and 4 were not significantly different than healthy sheep (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while SG1 showed higher concentrations than healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and for TAC concentrations at 7th DPT, SG3 and SG 4 were not significantly different than healthy ones (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while SG1 and SG2 had lower concentrations of TAC compared to healthy sheep (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEffect of traditional treatment and silymarin on oxidant and antioxidant status\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMDA (nmol/ml)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTAC (mmol/l)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 1 (n\u0026thinsp;=\u0026thinsp;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG 2 (n\u0026thinsp;=\u0026thinsp;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 1 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 2 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 3 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSG 4 (n\u0026thinsp;=\u0026thinsp;10); 7th DPT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003en: number; DPT, days post treatment; MDA: Malonaldehyde; TAC: Total antioxidant capacity; Means with different letter superscripts in the same column are significantly different at (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSerum metabolites profiling via GC-MS analysis aided by chemometrics.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSerum GC/MS-derived metabolite profiles of 49 endogenous metabolites, including organic acids, amino acids, fatty acids, and sugars were identified in group 1, 2 and treated subgroups (1\u0026ndash;4) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Supervised pattern recognition method i.e, PLS was employed to model serum-based GC-MS derived metabolite profiles of G1 as X-variables versus G2 and other seven PLS models were modeled to correlate the GC-MS derived serum metabolite profiles of four therapeutic approaches (SG 1- SG 4) along with G2 to the 12 tested biochemical parameters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSerum metabolites percentile level based on GC/MS analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRT (min)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eG 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eG 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSG 1, 7th DPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSG 2, 7th DPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSG 3, 7th DPT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSG 4, 7th DPT\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAmino acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1099\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Alanine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1106\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCystathionine, di-TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1165\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePyruvic acid,\u0026nbsp;MEOX-TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.84\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1208\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Valine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1210\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Alanine, 2TMS isomer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8.27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1305\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Leucine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8.79\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1316\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Isoleucine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1362\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSerine, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1377\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Threonine, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.70\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1385\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Proline, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1402\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlycine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e13.99\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1470\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Threonine, 3TMS isomer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e16.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1473\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePyroglutamic acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e18.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1612\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePhenylalanine, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e18.57\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1616\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Glutamic acid, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e22.55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1788\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eL-Ornithine, 4TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Amino acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eFatty acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2031\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePalmitic acid, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e28.27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2154\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLinoleic acid, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e28.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2166\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOleic acid, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e28.82\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2183\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eStearic acid, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Fatty acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eEsters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e33.69\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2210\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1-Monopalmitin, 4TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e36.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2235\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1-Monostearin, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Esters\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eOrganic acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e5.41\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1140\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePropane-1,2-diol, di-TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1060\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLactic Acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.15\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1081\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlycolic acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e8.64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1156\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e4-Hydroxybutanoic acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.80\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.30\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1325\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCaproic acid, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1136\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eOxalic acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1178\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eα-Aminocaproic acid (tms)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e16.44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1503\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3-Methylglutaric acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e----\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e22.47\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1778\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCitric acid, (4TMS)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Organic acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.580\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e29.657\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eInorganic acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1306\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ePhosphoric acid, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eInorganic acids\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c10\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNitrogenous compounds\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4.61\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1101\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eBis(trimethylsilyl)carbodiimide\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.86\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1105\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eHydroxylamine, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1113\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3-Hydroxybutyric acid, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1281\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eUrea, 2TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e23.67\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e17.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1486\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCreatinine, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Nitrogenous compounds\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e15.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e28.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e24.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSugars\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1300\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlycerol, 3TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e20.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1666\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eD-Arabinose, 4TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1858\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlucose, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1860\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eβ-Galactopyranose, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1858\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlucose, methyloxime, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.28\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e39.45\u0026thinsp;\u0026plusmn;\u0026thinsp;2.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.72\u0026thinsp;\u0026plusmn;\u0026thinsp;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e31.50\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1866\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eD-Mannose, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1885\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eD-(+)-Talose, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.76\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e24.95\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1493\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eLactulose, 6TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25.63\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1515\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eGlucopyranose, 5TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e26.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1568\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eβ-D-Glucopyranose, TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e27.53\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1586\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMyoinositol TMS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.71\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.40\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal Sugars\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e47.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e40.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e37.64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003e\u003cb\u003eUnknown\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e28.48\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2172\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknown1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e35.33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2212\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknown2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e37.10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2274\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknown3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e37.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2278\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknow4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e37.42\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2284\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknow5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e40.31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2389\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eunknow6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eTotal unknown\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e99.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e99.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e99.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e99.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo explore the differential therapeutic efficacy of the four therapeutic approaches and their influence on restoring the biochemical parameters in pneumonic sheep to their normal status, seven PLS models were attempted to correlate the GC-MS derived serum metabolite profiles of four therapeutic approaches (SG 1 - SG 4) along with the pneumonic sheep group (G 2) to the twelve tested biochemical parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Validation of the PLS model represented by the relationship between observed and predicted values and permutation plots are depicted in Fig. S2. The percent of variation that can be predicted by the models according to a leave-one-out cross-validation procedure are ranging from 90.7\u0026ndash;71.9% (Q2X(cum)).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs observed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(A-H), PLS models exhibited strong correlations between GC-MS serum metabolite profiles of the pneumonic sheep treated with the four therapeutic approaches as well as the pneumonic sheep group (G 2) (R2\u0026thinsp;=\u0026thinsp;0.878 to 0.907) as observed for the regression lines and the significant spread of the samples along the reference lines. Hence, strong relationships between the defined and predicted values of the tested biochemical parameters exist.\u003c/p\u003e \u003cp\u003eThe derived PLS score plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA) provided a clear distinction between the modeled groups (SG 1- SG 4) with pneumonic sheep group (G 2) the most distant from them. Further, all the scores plots exhibited trends of either decreasing or increasing order of the samples potency in modulating the tested biochemical parameters to restore their values to the normal status. For example, in PLS scores plot depicted in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u0026amp; G, the samples were spanned from the positive to the negative PC1 side in order of their increasing potency in lowering MDA concentrations and liver activity markers, i.e. AST, ALT \u0026amp; GGT as follows: SG 1˂ SG 4˂ SG 2˂ SG 3, than that observed in the pneumonic sheep group (G 2) located at the positive side of PC1 with the highest positive score. The strongest effect on increasing the TAC concentrations was demonstrated with SG 2, and a trend of increasing potency of the therapeutic approaches was also found along PC1 as spanning from negative to positive side (SG 1˂ SG 4˂ SG 2\u0026thinsp;\u0026le;\u0026thinsp;SG 3) in PLS score plot depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB. The same order was noticed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC for lowering the TG and LDL-cholesterol but increasing the total and HDL-cholesterol concentrations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) and decreasing creatinine and urea (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE) in serum of the pneumonic sheep groups in response to the four therapeutic approaches.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe endogenous metabolites that were deemed to be crucial in distinguishing between the different therapeutic approaches respective to their therapeutic efficacy on restoring the values of the biochemical parameters level to the normal status were those possessing VIP values\u0026thinsp;\u0026gt;\u0026thinsp;1 in the Variable Importance for Projection (VIP) plots (Fig. S3) namely lactic acid, glycolic acid, urea, glucose, α-aminocaproic acid, propane-1,2-diol, glycine, L-alanine, 4-hydroxybutanoic acid, D-(+)-talose and oleic acid. These metabolites were considered the most important for the model prediction, which were then used to create two other PLS models to compare the two therapeutic approaches, SG 2 \u0026amp; SG 3, that were proposed to be the most effective pneumonic treatments in the PLS model depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe correlations between the two therapeutic approaches (SG 2 \u0026amp; SG 3) to their respective biochemical parameters were explored via two PLS regression models (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u0026amp; B). The elevated biochemical parameters due to pneumonic condition that were suppressed by the therapeutic approaches i.e., TAC, glucose, and total and HDL-cholesterol were regressed in one model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), and the other parameters were found to be decreasing in pneumonic condition and shown to be elevated by the treatment are regressed in the second model (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB) which are MDA, LDL-cholesterol, creatinine, urea, AST, ALT and GGT.\u003c/p\u003e \u003cp\u003eThe two models were validated using 200 random permutations and showed a performance with goodness of model fit (R2\u0026thinsp;=\u0026thinsp;0.956 and 0.873) and predictive power of the model (Q2\u0026thinsp;=\u0026thinsp;0.781 and 0.241), respectively, with the second model showing a lower predictive power. Validation of the two PLS models was demonstrated from the regression analysis and permutation plots depicted in Fig. S4 \u0026amp; S5, respectively.\u003c/p\u003e \u003cp\u003eThe derived biplot (an amalgamation of the information revealed by both the score and loading plots) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA) showed that therapeutic approach relying on a silymarin dose of 280 mg only (SG 3) was strongly correlated with the upregulation of TAC, glucose, and total and HDL-cholesterol values as being projected close to SG 3 samples on the right side of the biplot however, all of the SG 2 samples were remotely distributed on the left side of the biplot. This indicated that the subgroup 3 treatment was more effective in increasing the TAC, glucose, and total and HDL-cholesterol values than the SG 2 treatment. Hence, SG 2 was more efficacious in suppressing oxidative stress and restoring lipid profile and blood sugar to their normal status.\u003c/p\u003e \u003cp\u003ePLS model (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) was initially established by modeling the GC-MS derived serum metabolite profiles of healthy control (G1) (as X-variables) versus pneumonic sheep (G2) to the twelve tested biochemical parameters (as Y-variables) to identify endogenous metabolite markers and the biochemical status of each group. The covered variance and prediction power of the model was assessed by R2 and Q2 values which were computed to be 0.942 and 0.82 indicating model validity. PLS score plot (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA) showed a clear discrimination between the healthy and pneumonic sheep groups, and that discrimination was explained by the loading plot (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB), which revealed that lactic acid was more elevated in the healthy sheep, whereas urea and creatinine were detected at higher concentrations in pneumonic sheep. Furthermore, it was shown that some biochemical parameters were found to be more elevated in the pneumonic sheep group (G 2) i.e., liver and kidney functions (AST, ALT, ALT, GGT, creatinine, urea) as well as oxidative stress occur as represented by high MDA values in addition to high LDL-cholesterol than the healthy sheep. However, TAC, total cholesterol, HDL-cholesterol, and glucose were found at higher concentrations in the healthy sheep compared to the pneumonic sheep.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eGroup 2 showed copious nasal discharge, fever, cough, dyspnea, abnormal respiratory sounds upon auscultation, higher body temperature, respiratory and pulse rates than healthy ones, the same results were recorded by [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. SG1 had significant higher body temperature, respiratory and pulse rates compared to healthy ones, this could be attributed to the microbial resistance to antibiotics administration [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], while SG2, 3 and 4 did not significantly differ than G1. The rapid clinical response to treatment was achieved early 3 days post treatment in SG 4 by the high dose of oral silymarin administration (560 mg) that could be attributed to the broad spectrum activity of silymarin as anti-inflammatory, anti-oxidative and antimicrobial agents [11; 22].\u003c/p\u003e \u003cp\u003eIn the present study, pneumonic sheep had significantly higher AST, ALT, GGT, creatinine, and urea concentrations than healthy sheep. The same results were recorded [23; 24]. The increase of these liver function tests may be due to hepatic cellular damage and degenerative modifications brought on by bacterial infection and its toxins [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], or due to severe exposure to oxidative stress resulting in damage of phospholipid structure of hepatic cell membrane [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while higher creatinine and urea concentrations could be related to renal damage caused by excessive release of free radicals that exhibited during the inflammatory progression and enhanced the protein catabolism [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Interestingly, liver and kidney functions were improved in pneumonic sheep treated with silymarin than traditional treatment. Our findings were similar to previous studies [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. It is plausible that silymarin has an anti-inflammatory and antioxidants property that protect against cellular injury [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePneumonic sheep had significantly higher triglyceride and LDL-cholesterol, and lower cholesterol, HDL-cholesterol and glucose concentrations compared to healthy sheep. Similar findings has been reported in previous studies [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Inflammation can cause hypertriglyceridemia in both humans and animals [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Lower serum cholesterol concentrations in the sheep of this study could have be due to liver injury with subsequent changes to lipoprotein metabolism [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Pneumonic sheep that received silymarin had significantly lower triglyceride and LDL-cholesterol and higher cholesterol, HDL-cholesterol, and glucose concentrations. Potential explanation include that silymarin could decrease blood cholesterol concentration by slowing down liver cell cholesterol synthesis and speeding up the conversion of cholesterol to other molecules [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], also the silymarin normalize the binding of low- density LDL [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], while the significant increase of HDL- cholesterol may be due to reducing cholesterol absorption in pneumonic sheep received silymarin in the protocol of treatment [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the current study pneumonic sheep had significantly higher MDA and lower TAC concentrations compared to healthy sheep, similar to the results recorded by [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The increase in serum MDA concentrations could be due to excessive lipid peroxidation, while reduction of TAC in pneumonic sheep may be due to its sequestration during the inflammatory process in lung tissue [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Pneumonic sheep received silymarin in the protocol of treatment showed a significantly decrease in MDA and an increase in TAC concentrations compared to sheep treated by traditional treatment. It\u0026rsquo;s possible that silymarin has antioxidant and neutralization effects either on free radicals or toxins [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eDiscriminatory analysis of metabolomics profile revealed that pneumonic sheep treated with 280 mg oral silymarin had an improved health status and metabolomics profile. Furthermore, pneumonic sheep treated with 560 mg oral silymarin had faster curative achievement. Silymarin administration either alone or in combination with traditional treatment exhibited greater therapeutic improvement than treatment with traditional treatment alone.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHany Hassan:\u003c/strong\u003e Conceptualization, Project administration, Supervision, reviewed the manuscript editing. \u003cstrong\u003eAhmed Kamr:\u003c/strong\u003e Writing - original draft- review\u0026amp; editing. \u003cstrong\u003eAbdel Nasser El-Gendy:\u003c/strong\u003e Metabolomic analysis, Validation resources, Writing - original draft- review \u0026amp; editing. \u0026nbsp;\u003cstrong\u003eRamiro Toribio:\u003c/strong\u003e Writing - original draft- review \u0026amp; editing. \u003cstrong\u003eAmira R.\u0026nbsp;Khattab:\u003c/strong\u003e Metabolomic analysis, Writing - original draft- review \u0026amp; editing. \u003cstrong\u003eWalid Mousa\u003c/strong\u003e: Investigation, Methodology. \u003cstrong\u003eHadeer Khaled:\u003c/strong\u003e Investigation, Methodology. \u003cstrong\u003eAbdelsalam Elkholey:\u0026nbsp;\u003c/strong\u003eInvestigation, Methodology, \u003cstrong\u003eMohamed Kasem:\u003c/strong\u003e Investigation, Methodology. \u0026nbsp;\u003cstrong\u003eAli Arbaga:\u003c/strong\u003e Investigation, Methodology, Writing- Original draft- review\u0026amp; editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePostgraduate studies and research sector funded this study- University of Sadat City, Egypt; under grant number: 22 in (29-12-2021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated and/or analyzed during this study are included in this manuscript. The raw data are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Animal Ethics Committee at the Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval code VUSC-028-1-22). All methods were performed in accordance with the guidelines and regulations of this committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to Participate declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eThompson M. Respiratory diseases in sheep. Vet Pr. Today. 2019; 7(4): 48\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eYahya KH, Al-Mahmood SS, Al-Hubeity TY. Necropsy findings and histopathological analysis of a terminal stage ewe from a herd with sudden deaths in Mosul. Iraqi J. Vet. Sci. 2021; 35(3): 599\u0026ndash;604. \u003c/li\u003e\n\u003cli\u003eBerge ACB, Sischo WM, Craigmill AL. Antimicrobial susceptibility patterns of respiratory tract pathogens from sheep and goats. J. Am. Vet. Med. Assoc. 2006; 229(8): 1279\u0026ndash;1281.\u003c/li\u003e\n\u003cli\u003eMagstadt DR, Schuler AM, Coetzee JF, Krull AC, O\u0026rsquo;Connor AM, Cooper VL, Engelken TJ. Treatment history and antimicrobial susceptibility results for Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni isolates from bovine respiratory disease cases submitted to the Iowa State University Veterinary Diagnostic Laboratory from. J. Vet. Diagnostic Investig. 2018; 30(1): 99\u0026ndash;104.\u003c/li\u003e\n\u003cli\u003eLaudato M, Capasso R. 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Picroside II attenuates fatty acid accumulation in HepG2 cells via modulation of fatty acid uptake and synthesis. Clin. Mol. Hepatol. 2018; 24(1): 77\u0026ndash;87.\u003c/li\u003e\n\u003cli\u003ePferschy-Wenzig EM, Atanasov AG, Malainer C, Noha SM, Kunert O, Schuster D, Heiss EH, Oberlies NH, Wagner H, Bauer R. Identification of isosilybin a from milk thistle seeds as an agonist of peroxisome proliferator-activated receptor gamma. J. Nat. Prod. 2014; 77(4): 842\u0026ndash;847.\u003c/li\u003e\n\u003cli\u003eOu Q, Weng Y, Wang S, Zhao Y, Zhang F, Zhou J, Wu X. Silybin alleviates hepatic steatosis and fibrosis in NASH mice by inhibiting oxidative stress and involvement with the Nf-\u0026kappa;B pathway. Dig. Dis. Sci. 2018; 63: 3398\u0026ndash;3408.\u003c/li\u003e\n\u003cli\u003eGoli F, Karimi J, Khodadadi I, Tayebinia H, Kheiripour N, Hashemnia M, Rahimi R. Silymarin attenuates ELMO-1 and KIM-1 expression and oxidative stress in the kidney of rats with type 2 diabetes. Indian J. Clin. Biochem. 2019; 34: 172\u0026ndash;179.\u003c/li\u003e\n\u003cli\u003eSchrimpe-Rutledge AC, Codreanu SG, Sherrod SD, McLean JA. Untargeted metabolomics strategies\u0026mdash;challenges and emerging directions. J. Am. Soc. Mass Spectrom. 2016; 27(12): 1897\u0026ndash;1905.\u003c/li\u003e\n\u003cli\u003eIbrahim N, Taleb M, Heiss AG, Kropf M, Farag MA. GC-MS based metabolites profiling of nutrients and anti-nutrients in 10 Lathyrus seed genotypes: A prospect for phyto-equivalency and chemotaxonomy. Food Biosci. 2021; 42: 101183.\u003c/li\u003e\n\u003cli\u003eAmmar NM, Hassan HA, Abdallah HMI, Afifi SM, Elgamal AM, Farrag ARH, El-Gendy AG, Farag MA, Elshamy AI. Protective effects of naringenin from Citrus sinensis (var. Valencia) peels against CCl4-induced hepatic and renal injuries in rats assessed by metabolomics, histological and biochemical analyses. Nutrients. 2022; 14(4): 841.\u003c/li\u003e\n\u003cli\u003eElshamy AI, Abdallah HMI, El Gendy AG, El-Kashak W, Muscatello B, De Leo M, Pistelli L. Evaluation of anti-inflammatory, antinociceptive, and antipyretic activities of Prunus persica var. nucipersica (nectarine) kernel. Planta Med. 2019; 85(11): 1016\u0026ndash;1023.\u003c/li\u003e\n\u003cli\u003eAflatouni M, Panahi N, Mortazavi P, Shemshadi B, Kakoolaki S. Hepatoprotective activity of silymarin in combination with clorsulon against Fasciola hepatica in naturally infected sheep. Kafkas \u0026Uuml;niversitesi Vet. Fak\u0026uuml;ltesi Derg. 2020; 26(2): 279\u0026ndash;285.\u003c/li\u003e\n\u003cli\u003eConstable PD, Hinchcliff KW, Done SH, Gr\u0026uuml;nberg W. Veterinary medicine: a textbook of the diseases of cattle, horses, sheep, pigs and goats. Elsevier Health Sciences St. Louis, Missouri, USA. 2017; 2308.\u003c/li\u003e\n\u003cli\u003eRaish M, Ahmad A, Jan BL, Alkharfy KM, Mohsin K, Ahamad SR, Ansari MA. GC-MS-based metabolomic profiling of thymoquinone in streptozotocin-induced diabetic nephropathy in rats. Nat. Prod. Commun. 2017; 12(4): 553\u0026ndash;558.\u003c/li\u003e\n\u003cli\u003eRummun N, Khattab AR, Bahorun T, Farag MA, Neergheen VS. Biochemometric approach to reveal Terminalia bentzo\u0026euml; cytotoxic effect against HepG2 cells in relation to its different organs and extraction solvents as analysed via UPLC-MS. South African J. Bot. 2023; 159: 507\u0026ndash;518.\u003c/li\u003e\n\u003cli\u003eHassan HY, Kamr A, Abdelazeim A, Khaled H. Hemato-Biochemical Response with Highlights on the Role of Oxidants and Antioxidants in Pneumonic Sheep. J Vet Mar. Sci. 2019; 1(1): 7\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eHassan H, Kamr A, Mousa W, Toribio R, El-Gendy A, Khaled H, Elkholey A, Arbaga A.. Silymarin Antibacterial Efficacy against Some Isolated Bacterial Strains from Pneumonic Sheep - Vitro Study. PVJ. 2024; DOI: 10.29261/pakvetj/2024.157.\u003c/li\u003e\n\u003cli\u003eArbaga A, Hassan H, Anis A, Osthman N, Kamr A. Hematological changes and serum minerals concentrations in pneumonic sheep. Benha Vet. Med. J. 2022; 42(2): 143\u0026ndash;146.\u003c/li\u003e\n\u003cli\u003eSaeed MG, SadeqNoomi B, Sarhat ER. Relation between Level of Some Immunological Markers and Liver Functions with Respiratory Bacterial Infection in Sheep. Indian J. Forensic Med. Toxicol. 2021; 15(4): 1924\u0026ndash;1929.\u003c/li\u003e\n\u003cli\u003eAytekin I, Mamak N, Ulucan A, Kalinbacak A. Clinical, haematological, biochemical and pathological findings in lambs with peste des petits ruminants. Kafkas Univ. Vet. Fak. Derg. 2011; 17(3): 349\u0026ndash;355.\u003c/li\u003e\n\u003cli\u003eSaleh NS, Allam TS. Pneumonia in Sheep: Bacteriological and Clinicopathological Studies. Am. J. Res. Commun. 2014; 2(11): 70\u0026ndash;88.\u003c/li\u003e\n\u003cli\u003eSaller R, Melzer J, Reichling J, Brignoli R, Meier R. 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Path. 2015; 24: 581\u0026ndash;588.\u003c/li\u003e\n\u003cli\u003ePhetteplace HW, Sedkova N, Hirano K, Davidson NO, Lanza‐Jacoby SP. Escherichia coli sepsis increases hepatic apolipoprotein B secretion by inhibiting degradation. Lipids. 2000; 35(10): 1079\u0026ndash;1086.\u003c/li\u003e\n\u003cli\u003eEl-Deeb WM, Elmoslemany AM. The diagnostic accuracy of acute phase proteins and proinflammatory cytokines in sheep with pneumonic pasteurellosis. 2016; PeerJ 4: 1-12.\u003c/li\u003e\n\u003cli\u003eFallah Huseini H, Zaree AB, Babaei Zarch A, Heshmat R. The effect of herbal medicine Silybum marianum (L.) Gaertn. seed extract on galactose induced cataract formation in rat. J. Med. Plants. 2004; 3: 58\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eKhazaei R, Seidavi A, Bouyeh M. A review on the mechanisms of the effect of silymarin in milk thistle (Silybum marianum) on some laboratory animals. Vet. Med. Sci. 2022; 8(1): 289\u0026ndash;301.\u003c/li\u003e\n\u003cli\u003eSobolov\u0026aacute; L, \u0026Scaron;kottov\u0026aacute; N, Večeřa R, Urb\u0026aacute;nek K. Effect of silymarin and its polyphenolic fraction on cholesterol absorption in rats. Pharmacol. Res. 2006; 53(2): 104\u0026ndash;112.\u003c/li\u003e\n\u003cli\u003eDel Rio D, Stewart AJ, Pellegrini N. A review of recent studies on malondialdehyde as toxic molecule and biological marker of oxidative stress. Nutr. Metab. Cardiovasc. Dis. 2005; 15(4): 316\u0026ndash;328.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Silybum marianum, Metabolites profile, Discrimination analyses, Pneumonia","lastPublishedDoi":"10.21203/rs.3.rs-4344803/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4344803/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The goal of this study was to evaluate the therapeutic efficacy of silymarin against sheep pneumonia utilizing clinical, biochemical and metabolomics approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Fifty adult male Barki sheep were divided into two groups based on their health status. Group 1 included healthy sheep (n = 10); Group 2 included sick sheep with clinical evidence of pneumonia (n = 40), which were further classified into four subgroups based on treatment protocols: subgroup 1 (SG1) was given traditional treatment; subgroup 2 (SG2) received traditional treatment plus daily 280 mg of silymarin orally; subgroup 3 (SG3) was administrated daily 280 mg of silymarin orally; and subgroup 4 (SG4) received daily 560 mg of silymarin orally. Evaluation of hepatic and renal function as well as serum lipid profile, glucose concentrations, malondialdehyde (MDA) concentrations, and total antioxidant activity (TAC) was carried out using commercial kits. Efficacy-directed distinction between therapeutic groups was accomplished based on GC-MS generated serum metabolite profiles supported by partial least squares regression analysis (PLS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e PLS score plot showed a clear discrimination between the healthy and pneumonic sheep groups that exhibited lower concentrations of TAC, total cholesterol, HDL-cholesterol, and glucose, but elevated liver enzyme, urea, creatinine, MDA and LDL-cholesterol (P \u0026lt; 0.05). Through clinical evaluations, the rapid clinical responses were achieved by the oral administration of silymarin 560 mg and through selective analysis of metabolomics profile, pneumonic therapy with 280 mg of silymarin was the best therapeutic outcome relying on a SG3 was strongly correlated with the upregulation of TAC, glucose, and total and HDL-cholesterol values.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003ePneumonic sheep treated with silymarin exhibited healing as well as greater clinical, metabolomic and biochemical improvement than treatment with traditional treatment alone.\u003c/p\u003e","manuscriptTitle":"Clinicobiochemical and GC-MS Based Serum Metabolomics for determination of Therapeutic Efficacy of Silymarin in Pneumonic Sheep","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-14 08:34:52","doi":"10.21203/rs.3.rs-4344803/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"672384df-bd5d-4adb-a0fe-bdad140c7dd6","owner":[],"postedDate":"May 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-21T07:57:43+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-14 08:34:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4344803","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4344803","identity":"rs-4344803","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}