{"paper_id":"4897c2b7-52bf-47c4-8950-d59effb73e5e","body_text":"Proteomics based evaluation of the antidiabetic activity of a polyherbal formulation in Streptozotocin-induced hyperglycemia in rats | 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 Proteomics based evaluation of the antidiabetic activity of a polyherbal formulation in Streptozotocin-induced hyperglycemia in rats Shridhar Chougule, Amey Shirolkar, Rajesh Gacche, Sudesh Gaidhani, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4694505/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Proteomics have proven advantage in drug and disease physiology characterization. Here the polyherbal formulation was administered daily via oral gavage in two groups of Six Sprague Dawley diabetic rats at the doses of 250 mg/kg and 500 mg/kg body weight for 21 days to understand its antidiabetic potential with proteomics approach. Blood sugar levels were monitored weekly during experimentation. The concurrent control group receiving 10 mL/kg water was also maintained. Rats were examined regularly for signs of toxicity and mortality and underwent detailed clinical examinations prior to initiation and weekly thereafter. Body weight and food consumption were recorded weekly. The anti-hyperglycaemic effect of the formulation was estimated from blood glucose levels weekly. There was no observed mortality or adverse clinical signs among the rats exposed to the standard drug and formulation. Streptozotocin caused a significant weight loss in rats, while treatment with formulation at 250 and 500 mg/kg b.w. concentrations and Glibenclamide as a standard drug; restrained the decrease in body weight. The streptozotocin-induced diabetic rats exhibited a sharp elevation in blood glucose levels. The blood glucose levels were significantly lowered in a dose dependent manner post formulation treatment, in comparison to the control group. Treatment with formulation, standard, and streptozotocin did not induce any remarkable gross pathological alterations in any of the organs/tissues of rats. In proteomics analysis, in formulation treatment groups ECM and Circadian entrainment pathways were activated which are in line with the objective of normalization of altered metabolism in diabetes. Antidiabetic activity Streptozotocin Polyherbal formulation Serum proteomics Glibenclamide Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. INTRODUCTION Diabetes is a global epidemic with an estimated worldwide prevalence of 537 million people in the year 2021 and is forecasted to cross 700 million by the year 2045; in India, about 77 million people are living with diabetes and this number is predicted to cross 134.2 million by 2045 (IDF, 2019, DIABETES ATLAS). Consequently, diabetes poses a serious challenge to healthcare systems around the world. Diabetes is a metabolic disorder of diverse etiologies characterized by chronic hyperglycemia with disturbance of carbohydrate, fat, and protein metabolism resulting from defects in insulin secretion, insulin action, or both, also it is a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation (WHO, 2021, fact sheet). There are two types of diabetes Type 1 and 2; Type 1 diabetes (aka insulin-dependent, juvenile, or childhood-onset) is characterized by deficient insulin production and requires daily administration of insulin hormone. Neither the cause of Type 1 diabetes nor the means to prevent it are known. Type 2 diabetes (also known as insulin-independent or adulthood) results from the body's ineffective use of insulin. People affected by type 2 diabetes are in majority among the people with diabetes. This type of diabetes is primarily a result of obesity and lack of exercise. Until recently, type 2 diabetes was only found in adults, but it is now becoming more common in children (WHO, 2021, fact sheet). Reports from various countries have shown that patients with diabetes have a 50% higher liability of mortality when affected by COVID-19 than those without (Bornstein et al., 2020). In India, 73% of COVID-19 deaths are associated with co-morbidities including diabetes, hypertension, and cardiovascular and respiratory diseases. Heightening the risk, more than half (57%) of the 77 million diabetic people in India are unaware that they have diabetes and hence may not monitor their condition or take steps to control it. Of the patients who have been diagnosed, 20% do not seek treatment, thus making the situation even more alarming. COVID-19 is also linked to the development of diabetes because it affects the pancreas (Abramczyk, U et al., 2022). Many oral antidiabetic agents, such as sulfonylureas and biguanides, are available for the treatment of diabetes along with insulin (Aschner, P., 2020), but these agents embody significant adverse effects, and some are inefficacious in chronic conditions. Thus, there is an increasing need for potent antidiabetic products with lesser side effects. An ideal therapy should have a higher degree of efficacy without any troublesome side effects. Alternative treatments for diabetes are becoming highly popular, comprising medicinal herbs, nutritional supplementation, acupuncture, and naturopathy (Gayathri, A., & Saranya, P. (2021), Kesavadev, J et al, 2023). In India, traditional medicine has played a vital role in recuperation from diabetes for several decades. In the Ayurvedic literature, it has been mentioned, usage of the following plants; Pterocarpus Marsupium Roxb., Gymnema sylvestre (Retz.) Schult., Holarrhena antidysenterica ( Roxb. ex Fleming) Wallich ex A. DC., Tinospora cordifolia (Willd.) Miers, Rubia cordifolia L. and Terminalia Arjuna (Roxb.) Wight & Arn. for the treatment of diabetes (Astanga Hriday Sutrasthan, 15/20 and Chakradutta, 35/8–10,13). Various research findings and evaluations have confirmed that Pterocarpus Marsupium (Raina, K et al., 2020), Gymnema sylvestre (Shanmugam, S. K et al., 2023), Holarrhena antidysenterica (Divya, C. A et al., 2021), Tinospora cordifolia (Katara, A et al., 2021), Rubia cordifolia (Bana, S., et al., 2023), and Terminalia Arjuna (Gaikwad, D. T et al., 2022), plants possess anti-diabetic potential. The polyherbal formulation was composed of the above-mentioned plants for the treatment of diabetes. Proteomics yields a great deal of information regarding treatment responsive changes in protein expression levels, resulting in better understanding of the involved pathway/mechanism of action. Therefore this study aimed to evaluate the efficacy and antidiabetic mechanism of the polyherbal formulation involved in the treatment of streptozotocin-induced hyperglycemia in rats. 2. MATERIALS AND METHODS 2.1 Preparation of plant extract: The freshly collected plant materials were identified by the botanist and were kept for preservation in the herbarium of National Research Institute of Basic Ayurvedic Sciences, Pune, the voucher specimen numbers assigned were as follows; Rubia cordifolia No. 4398, Gymnema sylvestre No. 4399, Terminalia Arjuna No. 4400, Pterocarpus Marsupium No. 4404, Holarrhena antidysenterica No. 4405, and Tinospora cordifolia No. 4406. The plant materials were shade dried with occasional shifting and then powdered with a mechanical grinder and stored in an airtight container. The dry powdered plant materials were mixed (1:1:1:1:1:1 ratio) together, and the formulation powder was mixed with water and alcohol (1:1) for preparation of hydro alcoholic extract by cold maceration. The extract thus obtained was then lyophilized using lyophilizer (Labconco Freezone 4.5) at -50 o C and 0.020 mbar pressure for three days. Later, the lyophilized material was suspended in distilled water for everyday fresh preparation of the drug just before dosing. 2.2 Chemicals: Trypsin (Cat. T6567), Idoacetamide (Cat. I1149), Ammonium bicarbonate (NH 4 HCO 3 ) (Cat. 09830), Dithiothreitol (DTT) (Cat. 43815), LCMS grade Acetonitrile (ACN), and Water (H2O), and Formic acid were procured from Sigma-Aldrich. RapiGest SF Surfactant was procured for Waters Corporation. 2.3 Animal Husbandry: All the experimental protocols were approved by the Institutional Animal Ethics Committee and the study was conducted according to the Committee for Control and Supervision of Experiments on Animals Guidelines for the use and care of experimental animals. The Sprague Dawley rats, 10–12 weeks old, weighing 180 to 220 g were procured from the National Institute of Biosciences, Pune. The weight variation of animals used didn’t exceed ± 20% of the mean weight. The individual animals were identified by cage tags and corresponding picric acid color body markings. All the animals were housed in an air-conditioned room with 10–15 air changes per hour, temperature between 19–25ºC, relative humidity 30–70%, and an illumination cycle set to 12 hours of artificial fluorescent light and 12 hours dark. Animals were housed in polypropylene cages with stainless steel griddles, feeding fixtures and water bottles, and clean rice husk bedding. The animals were provided ad libitum feed (Nutrimix brand pelleted standard rat feed manufactured by Nutrivet Life Sciences, Pune). The drinking water (passed through an R.O. filtration system and followed by treatment of U.V. light) was provided ad libitum in glass bottles with stainless steel sipper tubes. 2.4 Acute oral Toxicity in rats: The study was conducted in compliance with the Organization for Economic Co-operation and Development (OECD) Guidelines for Testing of Chemicals (No. 423, Section 4: Health Effects) on the conduct of the \"Acute Oral Toxicity - Acute Toxic Class Method\" (Adopted: 17th December 2001) (Test No. 423, OECD Guidelines, 2002). Based on the available historical toxicity data for individual plants, a starting dose level of 2000 mg/kg body weight was selected from one of the four fixed levels (5, 50, 300, and 2000 mg/kg). Rats were subjected to overnight fasting before the dosage of the polyherbal formulation. During fasting rats were provided with ample water ad libitum . The toxicity of the formulation following oral gavage dosing was assessed by stepwise treatment of animals. Three rats were used per step. Rats were observed for mortality and signs of intoxication for 14 days of administration of the formulation. In addition, this study was repeated in his three other rats at the same dose level and observed for 14 days. On the day of dosing, all animals were observed for mortality and signs of intoxication at 0.5, 1, 2, 3, 4, and 6 hours following dosing, and thereafter they were observed once a day for 14 days. The appearance, progress, and disappearance of these signs were recorded. The body weights of rats were individually recorded before dosing and at weekly intervals thereafter. All animals were terminally sacrificed and subjected to a detailed necropsy. As no gross pathological findings were encountered in any of the organs, a histopathological examination was not conducted. 2.5 Streptozotocin induced Hyperglycemia in rats: Hyperglycemia was experimentally induced in Sprague Dawley rats fasted for 12 h by a single intraperitoneal dose (60 mg/kg body weight) of Streptozotocin dissolved in citrate buffer (pH 4.5) (Szkudelski., 2001, Akbarzadeh et al., 2007). To overcome the hypoglycemic coma that occurs within the first 24 h following streptozotocin injection, a 5% glucose solution was given instead of plain drinking water for 2 days until sustained hyperglycemia was established. Three days after the Streptozotocin injection, rats were screened for blood glucose levels. Rats having glucose ranging from 200 to 300 mg/dL were considered moderate diabetic and included in the experiment. After the selection of animals, they were randomly divided into five groups, six rats per group. Group I received only vehicle, serving as the Healthy control group. Group II animals served as hyperglycemia/disease control. Group III received Glibenclamide as the positive control (10 mg/kg) daily by oral gavage for 21 days period. Group IV and V animals received polyherbal formulation daily at the doses of 250 mg/kg and 500 mg/kg body weight orally for 21 days respectively. Blood sugar was estimated weekly during the 21 days period. Necropsy was performed on all animals after an observation period of 21 days. The body weights of rats were individually recorded before dosing and at weekly intervals thereafter. Group mean body weights were calculated. The portion of food consumed by rats in each cage was recorded on the day of commencement of treatment and weekly thereafter. Food intake was calculated using the amount of food offered and leftovers in each cage. Analysis of serum blood sugar levels was performed using the Erba EC5 Plus Analyser (Transasia Bio-Medicals Ltd., India) using standard methodology. Urine analysis was performed using Multi stix SG. On completion of 21 days of treatment, blood samples from all rats were withdrawn and then they were sacrificed by exsanguinations under carbon dioxide anesthesia and were subjected to a thorough necropsy. The data were evaluated by One-Way ANOVA (Dennett’s test) and Student’s t-test using Graphpad prism at the level of significance from the control means at p < 0.05. 2.6 Protein extraction: Protein extraction was carried out using solvent precipitation (Fic et al., 2010), from blood samples collected after 21 days of treatment. In brief, blood samples were subjected to protein precipitation by adding methanol, chloroform, and water in 4:1:3 ratios respectively (Haar T von der., 2022; Wessel and Flügge., 1984). The mixture was vortexed briefly and centrifuged at 14,000 rpm for 1 minute to obtain three layers of separation. The uppermost water/methanol layer was removed without disturbing the interface (protein precipitate). Then methanol was added to wash the precipitate, and after vigorous vortexing, the samples were centrifuged at 15,000 rpm for 20 minutes to pellet the protein precipitate. The obtained protein pellet was redissolved using an 8M Urea solution. 2.7 Protein digestion: The proteins were quantified using standard Bradford's assay procedure (Bradford., 1976). The protein digestion protocol was as per Promega: Technical Bulletin TB373 ( https://www.promega.in/ ) with modification. Precipitate the protein (100 µg), air-dry the pellet for 3–5 min., and solubilize with RapiGest SF Surfactant 0.1% in 50 mM NH 4 HCO 3 . A final volume of 93.5 µL was adjusted using 50 mM NH 4 HCO 3 .1µL of 0.5 M DTT was added and incubated at 56°C for 20 minutes to disrupt disulfide bonds. 2.7 µL of 0.55 M iodoacetamide was added and incubated at RT in the dark for 15 min. to alkylate reduced cysteine residues of proteins. Add 1 µL of 1 µg/µL trypsin (MS grade) was added and the mixture was kept for digestion overnight at 37ºC. After the completion of incubation, trypsin was inactivated by adding formic acid (0.5% final concentration), and the samples were stored at − 20ºC till further analysis. UPLC–MS for proteins : LC/MS experiments were performed on Agilent 1290 Infinity Series RRLC interfaced with an Agilent 6538 Accurate Mass Q-TOF MS, as mentioned by Gayakwad et. al., 2020. A injection volume of 20 µL of per sample was applied to an assembly of C18 ZORBAX 300 extend (4.6 ×150 mm) column of particle size 5 µm. The column temperature was set at 40°C. The solvent system had aqueous, 0.1% formic acid-water and organic, 0.1% formic acid–acetonitrile in a proportion of 95:5. The gradient mode {concentration/time (%/min)} used for solvent B were 3%/0; 60%/10; 97%/14; 97%/15.5; 30%/21; 5%/25; and 5%/30 with 0.3 mL/ min flow rate. The mass spectrometer was operated in positive ion polarity mode with parameters: ionization type dual electrospray ionization (ESI), gas temperature 325°C, nebulizer 45 psi, gas flow 9.0 L/min, capillary voltage 3500 V, nozzle 750 V and the fragmentor voltage 150 V. The data acquisition was carried out in the range of 100–3000 m/z (28). 2.8 Liquid Chromatography and Mass Spectrometry (LCMS): Standard runs for calibration were performed using BSA. LC separation was carried out using Agilent’s ZORBAX 300SB-C18 column, acetonitrile: water as mobile phase. The method used for the sample run was in positive mode for 44 min. The mass range of 300 to 3500 Da was set for MS mode, 50 to 3000 Da for MS-MS mode, and data was collected in positive mode. The samples were duplicated for maintaining data integrity. 2.9 Peptide and Protein Identification: Identification of the differentially expressed proteins was performed on Agilent Technologies’ Spectrum Mill MS Proteomics Workbench Rev B.06.00.201 ( http://spectrummill.mit.edu/ ), which compares the experimentally determined tryptic peptide masses with theoretical peptide masses calculated for proteins contained in the protein databases. Freely available online tools such as Batch Entrez ( https://www.ncbi.nlm.nih.gov/sites/batchentrez ), Uniprot ( https://www.uniprot.org/ ), Panther pathway ( http://www.pantherdb.org/ ), STRING ( https://string-db.org/ ), etc. were used for further curation of data generated after Spectrum mill analysis. M + H + 600 − 60,000 m/z, extraction time range 0–30 min., allowed charge states 2–4, maximum ambiguous precursor charge 3, precursor mass tolerance ± 1.0 Da, product mass tolerance ± 0.5 Da, maximum # missed cleavages 2, minimum detected peaks 4, sequence tag length > 3, protein pI 3.0–10.0, and maximum reported hits 5. In the auto-validation step in Spectrum Mill, by default, FDR was set as 1.2% (28). 3. RESULTS 3.1 Acute oral Toxicity in rats: Polyherbal formulation, when tested on rats at the dose level of 2000 mg/kg body weight, did not cause any mortality and no evident toxic signs were observed on the day of dosing and during the observation period of 14 days thereafter. Treatment of rats with the formulation and standard drug neither induce any abnormal clinical signs nor gross pathological alterations in the organs/tissues, as evident during the detailed necropsy carried out at the termination of the study. The values of average daily food consumption by rats were found to be comparable to those of the concurrent control groups. The body weight gain in healthy control rats was not found to be adversely affected during the 14 days observation period, following the dosing step. 3.2 Streptozotocin induced Hyperglycemia in rats: Streptozotocin-treated rats showed a marked decrease in net body weight. However, Glibenclamide as a standard drug and polyherbal formulation attenuated the decline in the body weights during the 21 days treatment period (Fig. 1 , Sup. Table 1). The values of average daily food consumption by rats exposed to the formulation and standard drug were found to be comparable to those of the healthy control group. Table 1 Functional annotation analysis of healthy control group using DAVID Bioinformatics Resource 6.8 Category Term Count % p Value Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR KEGG PATHWAY rno05132: Salmonella infection 4 8.695652 0.001798 P38650, Q62698, Q9JJ79, D3ZHA0 24 83 7749 15.56024 0.152575 0.165404 0.165404 KEGG PATHWAY rno04962: Vasopressin-regulated water reabsorption 3 6.521739 0.007068 P38650, Q62698, Q9JJ79 24 43 7749 22.52616 0.479279 0.325116 0.325116 KEGG PATHWAY rno04510:Focal adhesion 4 8.695652 0.023303 O35346, P05539, P63319, D3ZHA0 24 210 7749 6.15 0.885741 0.611479 0.611479 KEGG PATHWAY rno04530: Tight junction 3 6.521739 0.030008 Q62812, Q9JLT0, O35889 24 92 7749 10.52853 0.939373 0.611479 0.611479 KEGG PATHWAY rno04066:HIF-1 signaling pathway 3 6.521739 0.036273 P27881, O35462, P63319 24 102 7749 9.496324 0.966597 0.611479 0.611479 KEGG PATHWAY rno05146: Amoebiasis 3 6.521739 0.042999 O35346, P05539, P63319 24 112 7749 8.648438 0.982463 0.611479 0.611479 KEGG PATHWAY rno04670: Leukocyte transendothelial migration 3 6.521739 0.046526 O35346, P63319, O35889 24 117 7749 8.278846 0.987514 0.611479 0.611479 Treatment of rats with the formulation at 500 mg/kg and the standard drug showed a remarkable decrease in blood sugar levels on the 7th, 14 th, and 21st days of observation. In respective experimental groups after the treatment of formulation and Glibenclamide, the blood glucose levels were found to be close to normal (Fig. 2 , Sup. Table 2). We have also tested the effect of this formulation in three different models Viz., normoglycemic animals, oral glucose tolerance test (OGTT); Streptozotocin, and Nicotinamide induced Type 2 diabetes data, which has not been included in this proteomics study. Table 2 Functional annotation analysis of disease control group using DAVID tool. Category Term Count % p Value Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR KEGG PATHWAY rno04925: Aldosterone synthesis and secretion 2 8.333333 0.083537 Q9EQ60, Q63269 9 84 7749 20.5 0.963662 1 1 KEGG PATHWAY rno04911: Insulin secretion 2 8.333333 0.085449 Q9JKS6, Q63269 9 86 7749 20.02326 0.966435 1 1 KEGG PATHWAY rno04713: Circadian entrainment 2 8.333333 0.095904 Q9EQ60, Q63269 9 97 7749 17.75258 0.978315 1 1 3.3 Mass spectrometric analysis: 3.3.1 Proteome analysis: The Extracted Ion Chromatogram (EIC) profile view displayed the variations in protein levels among 5 study groups. The EIC chromatograms of the two sampling groups are shown in overlaid mode (Figs. 3 and 4 ). The proteins that were identified from the samples of all 5 study groups have been noted in supp. Table 3 ; only the proteins that were identified with a minimum of 2 or more distinct peptides have been listed. We were able to identify numbers of proteins in various treatment groups i.e. 98 proteins in healthy control, 24 proteins in disease control, 51 proteins in Glibenclamide standard treatment, 51 proteins in 250 mg/kg formulation treatment, and 53 proteins in 500 mg/kg formulation treatment group. In Supp. Table 3 , a total of 277 proteins were observed in this study, out of which four proteins were found to be directly involved in diabetes-associated metabolic pathways; are Hexokinase 2 (Healthy control group): It catalyzes the phosphorylation of D-glucose and D-fructose, to hexose 6-phosphate (D-glucose 6-phosphate and D-fructose 6-phosphate). It plays a key role in maintaining the integrity of the outer mitochondrial membrane by preventing the release of apoptogenic molecules from the intermembrane space and subsequent apoptosis; Acetoacetyl CoA Synthetase (250 mg/kg treatment group): catalyzes the formation of Acetyl-CoA that can be used in the TCA cycle in aerobic respiration to produce energy and electron carriers; Angiotensin-converting enzyme ACE (500 mg/kg treatment group), it converts the hormone angiotensin I to the active vasoconstrictor angiotensin II. ACE is a core element of the renin-angiotensin system (RAS), it modulates blood pressure by changing the volume of fluids in the body; the Insulin receptor (500 mg/kg treatment group) is the linchpin in glucose homeostasis. Also occurrence of Murinoglobulin-1 protein post treatment (500 mg/kg treatment group), it has a significant role in inflammation regulation, protease inhibition, and in management of oxidative stress. Table 3 Functional annotation analysis of 250 mg/kg formulation study group using DAVID tool. Category Term Count % p Value Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR KEGG PATHWAY rno04510: Focal adhesion 4 7.843137 0.018206 P28818, P02466, P02454, P20909 22 210 7749 6.709091 0.629225 0.427956 0.427956 KEGG PATHWAY rno04974: Protein digestion and absorption 3 5.882353 0.023775 P02466, P02454, P20909 22 89 7749 11.87283 0.727298 0.427956 0.427956 KEGG PATHWAY rno04512: ECM-receptor interaction 3 5.882353 0.023775 P02466, P02454, P20909 22 89 7749 11.87283 0.727298 0.427956 0.427956 KEGG PATHWAY rno05146: Amoebiasis 3 5.882353 0.036361 P02466, P02454, P20909 22 112 7749 9.434659 0.864674 0.490871 0.490871 KEGG PATHWAY rno04611: Platelet activation 3 5.882353 0.050982 P02466, P02454, P20909 22 135 7749 7.827273 0.940732 0.550605 0.550605 To explore the underlying association of the differential protein expression among the groups were represented as a heat map (Fig. 5 ). The heat map has been created using the respective spectral intensities of 30 proteins. Around 25 proteins were found to be altered in diseased state when compared to healthy control. In the 250 mg/kg and 500 mg/kg treatment group a total of 19 and 18 proteins respectively with altered levels were normalized comparable to the healthy group. 3.3.2 Protein-protein interaction analysis : Protein-protein interactions (PPIs) are fundamental to almost every aspect of cellular function and regulation. PPIs play a key role in predicting the function of target protein and druggability of molecules. The lists of identified proteins were analyzed using the STRING 11.0b tool to obtain the protein-protein interactions network information. The STRING database contains functional protein association network data, which contains both experimentally validated and computationally predicted protein-protein interaction data, also it includes physical as well as functional associations (Szklarczyk et al., 2019). The information of only those proteins has been listed (Supp. Table 4 ) that was linked by experimentally validated interactions. The interactions obtained from STRING analysis for all study groups have been depicted in Fig. 6 – 10 . Table 4 Functional annotation analysis of 500 mg/kg formulation study group using DAVID tool. Category Term Count % p Value Genes List Total Pop Hits Pop Total Fold Enrichment Bonferroni Benjamini FDR KEGG PATHWAY rno04974: Protein digestion and absorption 3 5.660377 0.028223 Q9JI03, P26433, P02466 24 89 7749 10.88343 0.917153 1 1 KEGG PATHWAY rno04713: Circadian entrainment 3 5.660377 0.033081 B0LPN4, Q00960, O54898 24 97 7749 9.985825 0.946426 1 1 In the Healthy control group 7 proteins, namely Plcb1, Ptk2, Trip12, Dync1li2, Dyync1h1, Gfm1 and Mrps7, were with experimentally validated interactions. The PPIs depict general growth, maintenance, GTP-dependent ribosomal translocation, vesicular transport, and development associated interactions. Briefly, the ongoing cellular processes related with overall homeostasis and development were observed in the healthy control group. In the Disease control group, Foxm1, Alb, Pzp, Ank3, Itpr3, Kif5a were the proteins having maximum interactions. The PPIs shed light on the repair mechanism being activated, resulting from streptozotocin treatment that damages beta cells of Islets of Langerhans. Also the disturbed calcium homeostasis was observed which is correlated with complications of diabetic cardiomyopathy (Pereira, L., et al, 2014). Which is expected in the disease control group. For the Glibenclamide standard group 9 proteins namely Map4, Prkar2a, Apoe, Alb, Akap6, Syng, Synj1, Dync1h1, Nup98 were the most interacting proteins. The PPIs reveal microtubule assembly promotion, metabolism of lipoproteins, and membrane trafficking in the trans-Golgi network (TGN). Indicating the activation of various signaling cascades in response to Glibenclamide treatment. In the 250 mg/kg drug treatment group about 12 proteins namely Col1a2, Col1a1, Col11a1, Apoe, Alb, Ptprz1, Mapk7, Kalrn, Dlg4, Neo1, Ush2a proteins that established functional correlations. The PPIs related to cell growth, cell cycle regulation, developmental processes and cell survival that unveil the active cell proliferation, differentiation, and growth in response to treatment of formulation. In the 500 mg/kg drug treatment group, Ryr2, Cacna1g, Lrrn3, Cntn3, Pdzd2, Grin2b, Dlgap3, Grik1, Alb, A1i3, Mug1, Ank3, Cntnap1, Col1a2, and Col5a1 are the 15 proteins with maximum interactions. The PPIs highlight a surge in metabolic activity, as most of the interactions were found to be related to transmembrane signal receptors, protein modifying enzymes and metabolite interconversion enzymes. A key protein, murinoglobulin-1’s functional interactions are responsible for maintenance of pancreatic well being as according to Umans, L et al., (1999), α2-macroglobulin and murinoglobulin-1-deficiency leads to acute pancreatitis. The presence of this key protein in the 500 mg/kg treatment group stipulates the alleviation of streptozotocin induced pancreatic damage. 3.3.3 Pathway analysis : The Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis of identified proteins yielded probable pathways that were active or stimulated, using the KEGG pathway map (Huang et al., 2009; Sherman et al., 2022). The DAVID tool was unable to assign any pathway for Glibenclamide standard group, whereas for rest 4 groups i.e., healthy control (Table 1 , Supp. Figure 1 ), disease control (Table 2 , Supp. Figure 2 ), 250 mg/kg treatment (Table 3 , Supp. Figure 3 ), and 500 mg/kg treatment group (Table 4 , Supp. Figure 4 ) pathways with significant p -values were assigned. 4. Discussion Diabetes is one of the most common and thus important diseases in the world, hence it requires special attention with more emphasis on translational research. In the past few decades, several treatment regimes have been practiced; unfortunately, their associated adverse effects are not yet satisfactorily resolved (WHO, 2021, fact sheet; Nugraha, R. V et al., 2020). Studies have revealed that the phytochemicals present in polyherbal formulations can be a constitutive source (Dinda, B., & Dinda, M. (2022; Mukherjee P. K. et al., 2021) and their amalgamation into the main treatment regime can be the solution we have been seeking. Researchers have found that owing to their complex composition ayurvedic/polyherbal formulations tend to interact with multiple targets, and resonate in a dynamic way providing an enhanced effect. Proteomics is a crucial tool for understanding the disease/physiological condition and associated pathways, and in mapping the mechanism of action of respective drugs/compounds. Here, we have prepared a polyherbal formulation by mixing 6 plant powdered materials namely Rubia cordifolia, Gymnema sylvestre, Terminalia Arjuna, Pterocarpus Marsupium, Holarrhena antidysenterica , and Tinospora cordifolia in equal proportions. There are no reports of toxicity for the individual components of formulation in the current study (Balkrishna, A et al., 2022; Eskandarzadeh et al., 2023; Verma, P et a., 2022; Rekha, B. C et al., 2016; Raji, R. O et al., 2021; Patil, S. G et al., 2016; Anantharaman et. al., 2016). Due to synergism, poly-herbalism offers benefits not deliverable by a single herbal drug. It enables better therapeutic effects with lower doses, reducing the risk of adverse side effects of individual plants, if any (Kotmire, S et al., 2024). Also, presence of multiple active compounds together can provide a potentiating effect that may not be achievable by any single compound. Thus, a polyherbal formulation can provide a complete therapy against a disease condition (Karole, S et al., 2019). In the present study, the formulation at the dose level of 2000 mg/kg body weight, did not cause any mortality or toxicity thus confirming that after combination the formulation is nontoxic. This indicates that the maximum tolerated dose of the polyherbal formulation was more than 2000 mg/kg and thus, no observed adverse effect level (NOAEL) of the formulation should be above 2000 mg/kg with approximate LD 50 more than 2500 mg/kg. Thus, according to the \"Globally Harmonized System (GHS) for classification of chemicals which cause acute toxicity, OECD series on testing and assessment, Number 33; Harmonized Integrated Classification System for Human and Environmental Hazards of Chemical Substances and Mixtures (ENV/JM/MONO (2001) 6)\", the Polyherbal formulation can be classified as GHS Category 5 or Unclassified for the obligatory labeling requirement for oral toxicity. Although there can be side effects when taken alongside other medicine prescribed in diabetic condition. As some of the individual components have been known to enhance the immune response, lower the blood glucose levels, expedite liver metabolism, and have anticoagulant activity (Parasuraman, S et al., 2014). When co-consumed, patients with autoimmune response can experience severe reaction, it can lead to hypoglycemic conditions, and it may also all together alter the pharmacokinetics of drugs. In the current study the combination effects of modern medicine and the formulation has not been studied. For the formation of polyherbal formulations, drug antagonism is a critical factor to be considered. In the preparation of polyherbal, it is crucial to note that some herbs are incompatible ( viruddha ) and should not be taken in combination. Such discordance can be due to quantitative incompatibility, energetic incompatibility or functional incompatibility (Parasuraman, S et al., 2014). In our formulation we have not observed any adverse effect during and after treatment in animal model. The formulation was found to be most effective at 500 mg/kg concentration in regulating body weight and maintaining blood glucose levels in the STZ induced diabetic rat model. It was able to revert the declined bodyweight and elevated blood glucose levels to normal (Figs. 1 and 2 ). Suggesting that the formulation has an positive effect on glucose uptake and metabolism (Kang et. al, 2009; Xu et al., 2019; Liu et al., 2021, Sharma et. al., 2021; Li Y et. al., 2019; Kim et. al., 2017; Biswas et. al, 2011; Mohanty et. al., 2019; Pari et. al., 2018; Mishra et. al., 2013; Ali et. al., 2011; Sharma et. al., 2021; Jamadagni et al., 2017; Chandrasekaran et al., 2009; Joshi et al., 2004; Kumari et al., 2021; Ogawa et al., 2004). Here we aimed to provide a better understanding of the molecular mechanisms involved in the treatment of diabetes using a polyherbal formulation, and the importance of natural resources for improving the quality of life. Hallmark of diabetes mellitus is hindered glucose uptake and metabolism due incapacitated or damaged pancreatic β-cells. There are reports suggesting the pancreatic β-cells repair/regenerative potential displayed by the individual component plants on the STZ-induced rat model (Shanmugasundaram et al., 1990; Bolkent et al., 2000; Daisy et al., 2009; Mishra et. al., 2013; Rajalakshmi and Anita., 2016). Here, we have tested the synergistic effect of the polyherbal formulation on the STZ-induced rat model for the same. By studying the protein-protein interactions, we can link cellular pathways and their intricate cross-connectivity. In the Healthy control group, the PPIs show overall growth, progression, maintenance, and homeostasis. As per the condition in the disease control group, the PPIs displays an ongoing active repair mechanism resultant of streptozotocin treatment. Also the interaction depicting disturbed calcium homeostasis which can be correlated with diabetic cardiomyopathy were observed (Pereira, L., et al, 2014). For the Glibenclamide standard group, PPIs reveal microtubule assembly promotion, metabolism of lipoproteins, and membrane trafficking in the trans-Golgi network (TGN). In the 250 mg/kg drug treatment group, the PPIs related to cell growth, cell cycle regulation, developmental processes and cell survival that unveil the active cell proliferation, differentiation, and growth in response to treatment of formulation. In the 500 mg/kg treatment group, PPIs have shed light on significant ongoing cellular processes that hint towards a repair mechanism being activated in response to damage incurred to pancreatic β-cells. As we were able to identify insulin receptor protein which is an integral component of glucose metabolism, and a key protein, murinoglobulin-1’s functional interactions are responsible for maintenance of pancreatic well being (Umans, L., et al., 1999). The DAVID-KEGG pathway analysis of identified proteins uncovered the possible pathways that were triggered in respective study groups. Namely the HIF-1 signaling pathway in the healthy control group, Insulin secretion and circadian entrainment pathways in the disease control group, ECM-receptor interaction pathway in the 250 mg/kg group, and circadian entrainment pathway in the 500 mg/kg group. In the healthy control group, three proteins from our study namely Hexokinase-2, Angiopoietin-2, and Protein kinase C gamma type were found to be associated with the HIF-1 signaling pathway. Hypoxia-inducible factor 1 (HIF-1) is a transcription factor that functions as a master regulator of oxygen homeostasis in all metazoan species. HIF-1 controls oxygen delivery, by regulating angiogenesis and vascular remodeling, and oxygen utilization, by regulating glucose metabolism and redox homeostasis (Cerychova and Pavlinkova., 2018; Krock et al., 2011; Semenza., 2014). Bosch-Marce et. al., (2007) have demonstrated that the therapeutic enhancement of HIF activity can overcome age and diabetes, as ectopic expression of HIF-1α can partially rescue limb perfusion in old mice. In the disease control category, three proteins from our study were found to be involved with Insulin secretion and circadian entrainment pathways; these were Inositol 1,4,5-trisphosphate receptor type 3, Voltage-dependent T-type calcium channel subunit alpha-1H and Protein piccolo. The Inositol triphosphate pathway mobilizes the calcium ions from organelles and consequently increases the secretion of insulin (Onaolapo et al., 2018). Mechanisms for Ca 2+ entry include voltage-operated channels (VOC), receptor-operated channels (ROC), and store-operated channels (SOC) as well as two families of intracellular Ca 2+ release channels, the ryanodine receptor (RyR) and InsP3R (Hagar and Ehrlich, 2000; Yang et al., 2013). In 2002, Fujimoto et. al. demonstrated the importance of the cAMP-GEFIIּ Rim2ּ Piccolo complex in cAMP-induced insulin secretion. Thus indicating the effort of the body to regulate the imbalanced insulin levels due to damaged pancreas (islet of Langerhans). In the 250 mg/kg formulation treatment category, three proteins were found to be engaged with ECM-receptor interaction; the Collagen alpha-1(XI) chain, Collagen alpha-1(I) chain, and Collagen alpha-2(I) chain. During the onset and progression of Diabetes, the ECM protein expression and functioning are impaired, leading to structural alteration of the ECM network as well as normal tissues and cell behavior including cell-cell interactions (Bansode and Gacche., 2019; Shirolkar et al., 2022). Subsequently, these changes lead to diabetes-induced organ-dependent diseases such as nephropathy, retinopathy, and diabetic cardiomyopathy. Spiro and Crowley (1993) have also demonstrated that Alloxan-induced diabetes in rats displayed a significant increase in collagen type VI when compared to collagen types I and IV and other ECM proteins. A high glucose environment and other changes in diabetes lead to alterations in ECM, such as decreased collagen deposition and abnormal collagen metabolism mitigate wound healing (Huang and Kyriakides., 2020). Thus, indicating the therapeutic effect of formulation in mitigating the diabetic condition via up regulation of ECM network. In the 500 mg/kg treatment category, three proteins were found to be involved in the circadian entrainment pathway; those were Ryanodine receptor 2, Glutamate receptor ionotropic NMDA 2B, and Voltage-dependent T-type calcium channel subunit alpha-1G. The CLOCK and BMAL1 proteins are known to activate the transcription of genes in the pancreas, which are responsible for insulin synthesis/transport and glucose-stimulated secretion (Stenvers et al., 2019). Marcheva et. al., (2010) have demonstrated using both CLOCK and BMAL1 mutants that disruption of the biological clock components leads to hypoinsulinemia and diabetes. Uehara et. al., (2004) have suggested that the mGluR4-mediated signaling and GABAA receptor-mediated cascade; both individually act through the L-glutamatergic system that may act as autocrine transmitter and inhibit glucagon, in the islet of Langerhans. This displays the fringe benefit of the polyherbal formulation at 500 mg/kg in diabetes condition, as it maneuvers towards normalization of the metabolism. As discussed herewith we have demonstrated that diabetes-specific proteins and pathways are associated with progressions and recovery using a polyherbal formulation holistically. 5. Conclusion As witnessed from the current animal experimentation results, the proposed polyherbal formulation is not toxic and possesses promising anti-hyperglycemic activity based on the insights provided by proteomics study. Among the treatment groups, the most potent effect was observed at 500 mg/kg b.w. dose level. At the said dosage, the blood glucose levels were comparable to that of standard drug treatment and concurrent healthy control. In an effort to investigate the mechanism of action, the serum-based proteomic profiling revealed; A multi-faceted mechanism of action being regulation of blood glucose levels, upregulation of glucose uptake, and metabolism. Circadian entrainment, ECM-receptor, HIF-1 signaling, and Insulin secretion pathways were the prominent pathways that were found to be distinguished. Three proteins observed in the 500 mg/kg treatment study category are most significant; namely Angiotensin-converting enzyme (ACE), Insulin receptor protein, and murinoglobuline-1 are very crucial in repair/rejuvenation of pancreatic β-cells. The proposed polyherbal formulation has promising potential as a candidate for diabetes treatment. Thus we propose to evaluate and explore the proposed polyherbal formulation through randomized clinical trials and multi-omics approaches, as a remedy for efficient diabetes management. Declarations Conflict of Interests: Authors declare no conflict of interest. Funding information: This research did not receive any specific grant from any funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution SP conceived and designed the research; SC and AS performed the research and acquired the data;SC, AS, SP analysed and interpreted the data;RG, SG provided useful technical inputs in experimentation and in data analysis ; all authors (SC, AS, RG, SG, SP) were involved in drafting and revising the manuscript. Acknowledgement NA Data Availability The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD031550 and 10.6019/PXD031550. References Abramczyk U, Nowaczyński M, Słomczyński A, Wojnicz P, Zatyka P, Kuzan A (2022) Consequences of COVID-19 for the Pancreas. Int J Mol Sci 23(2):864 Akbarzadeh A, Norouzian D, Mehrabi MR, Jamsh:di SH, Farhangi A, Verdi AA, Mofidian SMA, Rad BL (2007) Induction of diabetes by streptozotocin in rats. Indian J Clin Biochem 22:60–64 Ali KM, Chatterjee K, De D, Jana K, Bera TK, Ghosh D (2011) Inhibitory effect of hydro-methanolic extract of seed of Holarrhena antidysenterica on alpha-glucosidase activity and postprandial blood glucose level) in normoglycemic rat. J Ethnopharmacol 135(1):194–196 Anantharaman A, Priya RR, Hemachandran H, Akella S, Rajasekaran C, Ganesh J, Fulzele DP, Siva R (2016) Toxicity study of dibutyl phthalate of R ubia cordifolia fruits: in vivo and in silico analysis. Environ Toxicol 31(9):1059–1067 Aschner P (2020) Insulin therapy in type 2 diabetes. Am J Ther 27(1):e79–e90 Bana S, Kumar N, Sartaj A, Alhalmi A, Qurtam AA, Nasr FA, Goel R (2023) Rubia cordifolia L. Attenuates Diabetic Neuropathy by Inhibiting Apoptosis and Oxidative Stress in Rats. Pharmaceuticals 16(11):1586 Bansode SB, Gacche RN (2019) Glycation-induced modification of tissue-specific ECM proteins: A pathophysiological mechanism in degenerative diseases. Biochim et Biophys Acta (BBA)-General Subj 1863(11):129411 Bolkent Ş, Yanardağ R, Tabakoğlu-Oğuz A, Özsoy-Saçan Ö (2000) Effects of chard (Beta vulgaris L. var. cicla) extract on pancreatic B cells in streptozotocin-diabetic rats: a morphological and biochemical study. J Ethnopharmacol 73(1–2):251–259 Bornstein SR, Rubino F, Khunti K, Mingrone G, Hopkins D, Birkenfeld AL, Boehm B, Amiel S, Holt RI, Skyler JS, DeVries JH (2020) Practical recommendations for the management of diabetes in patients with COVID-19. lancet Diabetes Endocrinol 8(6):546–550 Bosch-Marce M, Okuyama H, Wesley JB, Sarkar K, Kimura H, Liu YV, Zhang H, Strazza M, Rey S, Savino L, Zhou YF (2007) Effects of aging and hypoxia-inducible factor-1 activity on angiogenic cell mobilization and recovery of perfusion after limb ischemia. Circul Res 101(12):1310–1318 Bradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72(1–2):248–254 Cerychova R, Pavlinkova G (2018) HIF-1, metabolism, and diabetes in the embryonic and adult heart. Front Endocrinol 9:460 Chandrasekaran CV, Mathuram LN, Daivasigamani P, Bhatnagar U (2009) Tinospora cordifolia, a safety evaluation. Toxicol In Vitro 23(7):1220–1226 Daisy P, Eliza J, Farook KAMM (2009) A novel dihydroxy gymnemic triacetate isolated from Gymnema sylvestre possessing normoglycemic and hypolipidemic activity on STZ-induced diabetic rats. J Ethnopharmacol 126(2):339–344 Dinda B, Dinda M (2022) Natural products, a potential source of new drugs discovery to combat obesity and diabetes: their efficacy and multi-targets actions in treatment of these diseases. Natural Products in Obesity and Diabetes: Therapeutic Potential and Role in Prevention and Treatment. Springer International Publishing, Cham, pp 101–275 Divya CA, Dhar SK, Shantaram M, Das M (2021) Anti-diabetic effects of Holarrhena antidysentrica extracts: Results from a Longitudinal Meta-analysis. bioRxiv, 2021–2002 Fic E, Kedracka-Krok S, Jankowska U, Pirog A, Dziedzicka‐Wasylewska M (2010) Comparison of protein precipitation methods for various rat brain structures prior to proteomic analysis. Electrophoresis 31(21):3573–3579 Fujimoto K, Shibasaki T, Yokoi N, Kashima Y, Matsumoto M, Sasaki T, Tajima N, Iwanaga T, Seino S (2002) Piccolo, a Ca2 + sensor in pancreatic β-cells: involvement of cAMP-GEFII· Rim2· Piccolo complex in cAMP-dependent exocytosis. J Biol Chem 277(52):50497–50502 Gaikwad DT, Bansode SP, Mali DP, Wadkar GH, Pawar VT, Tamboli FA (2022) Promising Discovery of Alpha Amylase Enzyme Inhibitors from Terminalia arjuna for Antidiabetic Potential. Technology 12(3):1020–1024 Gayakwad S, Shirolkar A, Warkad S, Bharsakale S, Gaidhani S, Pawar S (2020) Proteomic and metabolomic analysis of Nothapodytes nimmoniana (J. Graham) extracts’ treatment on HeLa cells. J Proteins Proteom 11:27–62 Gayathri A, Saranya P (2021) A cross sectional study on utilization of complementary and alternative medicine in patients with diabetes mellitus. Annals of the Romanian Society for Cell Biology, pp 1360–1379 von Haar T (2022) der. Methanol Precipitation of Proteins. wwwprotocolsio. Published online September 4, 2019. Accessed December 23, https://www.protocols.io/view/methanol-precipitation-of-proteins-icecate.html Hagar RE, Ehrlich BE (2000) Regulation of the type III InsP3 receptor and its role in β cell function. Cell Mol Life Sci CMLS 57:1938–1949 Huang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44–57 Huang Y, Kyriakides TR (2020) The role of extracellular matrix in the pathophysiology of diabetic wounds. Matrix biology plus 6:100037 International Diabetes Federation (2021) DIABETES ATLAS 10th Edition 2021 https://diabetesatlas.org/en/sections/worldwide-toll-of-diabetes.html Joshi MC, Dorababu M, Prabha T, Kumar MM, Goel RK (2004) Effects of Pterocarpus marsupium on NIDDM-induced rat gastric ulceration and mucosal offensive and defensive factors. Indian J Pharmacol 36(5):296 Kang W, Zhang L, Song Y (2009) Alpha-glucosidase inhibitors from Rubia cordifolia. Zhongguo Zhong yao za zhi = Zhongguo Zhongyao Zazhi = China. J Chin Materia Med 34(9):1104–1107 Katara A, Garg NK, Mathur M (2021) Separation and Identification of Anti-diabetic compounds in Tinospora cordifolia extract and Ayurvedic formulation Guduchi Satva by GCMS and FTIR study with Subsequent Evaluation of in-vitro Hypoglycemic Potential. Int J Pharm Sci Drug Res 13:183–189 Kesavadev J, Basanth A, Kalra S (2023) Unproven Therapies for Diabetes. The Diabetes Textbook: Clinical Principles, Patient Management and Public Health Issues. Springer International Publishing, Cham, pp 1125–1139 Kim HJ, Kim S, Lee AY, Jang Y, Davaadamdin O, Hong SH, Kim JS, Cho MH (2017) The effects of Gymnema sylvestre in high-fat diet-induced metabolic disorders. Am J Chin Med 45(04):813–832 Krock BL, Skuli N, Simon MC (2011) Hypoxia-induced angiogenesis: good and evil. Genes cancer 2(12):1117–1133 Kumari I, Kaurav H, Choudhary G (2021) Rubia cordifolia (Manjishtha): A review based upon its Ayurvedic and Medicinal uses. Himal J Health Sci 6(2):17–28 Li Y, Liu Y, Liang J, Wang T, Sun M, Zhang Z (2019) Gymnemic acid ameliorates hyperglycemia through PI3K/AKT-and AMPK-mediated signaling pathways in type 2 diabetes mellitus rats. J Agric Food Chem 67(47):13051–13060 Liu M, Zhou T, Zhang J, Liao G, Lu R, Yang X (2021) Identification of C21 steroidal glycosides from Gymnema sylvestre (Retz.) and evaluation of their glucose uptake activities. Molecules 26(21):6549 Marcheva B, Ramsey KM, Buhr ED, Kobayashi Y, Su H, Ko CH, Ivanova G, Omura C, Mo S, Vitaterna MH, Lopez JP (2010) Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature 466(7306):627–631 Mohanty IR, Borde M, Maheshwari U (2019) Dipeptidyl peptidase IV Inhibitory activity of Terminalia arjuna attributes to its cardioprotective effects in experimental diabetes: In silico, in vitro and in vivo analyses. Phytomedicine 57:158–165 Mukherjee PK, Banerjee S, Biswas S, Das B, Kar A, Katiyar CK (2021) Withania somnifera (L.) Dunal-Modern perspectives of an ancient Rasayana from Ayurveda. J Ethnopharmacol 264:113157 Nugraha RV, Ridwansyah H, Ghozali M, Khairani AF, Atik N (2020) Traditional herbal medicine candidates as complementary treatments for COVID-19: a review of their mechanisms, pros and cons. Evidence-Based Complementary and Alternative Medicine, 2020 Ogawa Y, Sekita K, Umemura T, Saito M, Ono A, Kawasaki Y, Uchida O, Matsushima Y, Inoue T, Kanno J (2004) Gymnema sylvestre leaf extract: a 52-week dietary toxicity study in Wistar rats. Shokuhin eiseigaku zasshi. J Food Hyg Soc Japan 45(1):8–18 Onaolapo AY, Onaolapo OJ (2018) Circadian dysrhythmia-linked diabetes mellitus: Examining melatonin’s roles in prophylaxis and management. World J diabetes 9(7):99–114 Pari L, Majeed M, Rathinam A, Chandramohan R (2018) Molecular action of inflammation and oxidative stress in hyperglycemic rats: effect of different concentrations of Pterocarpus marsupiums extract. J Diet supplements 15(4):452–470 Raina K, Manek RA, Sheth DB, Naik DJ (2020) Pterocarpus Marsupium Extract Exaggerates Anti Diabetic Activity Of Metformin. J Adv Sci Res 11(04):275–283 Rajalakshmi M, Anita R (2016) β-cell regenerative efficacy of a polysaccharide isolated from methanolic extract of Tinospora cordifolia stem on streptozotocin-induced diabetic Wistar rats. Chemico-Biol Interact 243:45–53 Semenza GL (2014) Hypoxia-inducible factor 1 and cardiovascular disease. Annu Rev Physiol 76:39–56 Shanmugam SK, Singh M, Kumar D, Mishra R, Barman M (2023) Exploring Antidiabetic Potential of Gymnema sylvestre. J Appl Pharm Sci Res 6(2):30–35 Shanmugasundaram ERB, Gopinath KL, Shanmugasundaram KR, Rajendran VM (1990) Possible regeneration of the islets of Langerhans in streptozotocin-diabetic rats given Gymnema sylvestre leaf extracts. J Ethnopharmacol 30(3):265–279 Sharma R, Bolleddu R, Maji JK, Ruknuddin G, Prajapati PK (2021) In-Vitro α-amylase, α-glucosidase inhibitory activities and in-vivo anti-hyperglycemic potential of different dosage forms of guduchi (tinospora cordifolia [willd.] miers) prepared with ayurvedic bhavana process. Front Pharmacol 12:642300 Sherman BT, Hao M, Qiu J, Jiao X, Baseler MW, Lane HC, Imamichi T, Chang W (2022) DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res 50(W1):W216–W221 Shirolkar A, Yadav A, Nale A, Phogat J, Dabur R (2022) Integrated omics analysis revealed the Tinospora cordifolia intervention modulated multiple signaling pathways in hypertriglyceridemia patients-a pilot clinical trial. J Diabetes Metabolic Disorders 21(1):379–397 Spiro MJ, Crowley TJ (1993) Increased rat myocardial type VI collagen in diabetes mellitus and hypertension. Diabetologia 36:93–98 Stenvers DJ, Scheer FA, Schrauwen P, la Fleur SE, Kalsbeek A (2019) Circadian clocks and insulin resistance. Nat Reviews Endocrinol 15(2):75–89 Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ (2019) STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 47(D1):D607–D613 Szkudelski T (2001) The mechanism of alloxan and streptozotocin action in B cells of the rat pancreas. Physiol Res 50(6):537–546 Test No. 423: Acute Oral toxicity - Acute Toxic Class Method (2002) In OECD Guidelines for the Testing of Chemicals, Section 4. OECD. https://doi.org/10.1787/9789264071001-en Uehara S, Muroyama A, Echigo N, Morimoto R, Otsuka M, Yatsushiro S, Moriyama Y (2004) Metabotropic glutamate receptor type 4 is involved in autoinhibitory cascade for glucagon secretion by α-cells of islet of Langerhans. Diabetes 53(4):998–1006 Wessel DM, Flügge UI (1984) A method for the quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal Biochem 138(1):141–143 World Health Organization (2021) Fact sheet: Diabetes. https://www.who.int/news-room/fact-sheets/detail/diabetes Xu L, Xing M, Xu X, Saadeldeen FS, Liu Z, Wei J, Kang W (2019) Alizarin increase glucose uptake through PI3K/Akt signaling and improve alloxan-induced diabetic mice. Future Med Chem 11(5):395–406 Yang J, Li S, Liu YX (2013) Systematic analysis of diabetes-and glucose metabolism-related proteins and its application to Alzheimer’s disease. 6:615–644. 10.4236/jbise.2013.66078 Kotmire S, Desai A, Chougule N (2024) The advances in polyherbal formulation. J Pharmacognosy Phytochemistry 13(1):210–221 Balkrishna A, Bhattacharya K, Sinha S, Dev R, Srivastava J, Singh P, Varshney A (2022) Apparent hepatotoxicity of Giloy (Tinospora cordifolia): far from what meets the eyes. J Clin Experimental Hepatol 12(1):239–240 Eskandarzadeh M, Esmaeili A, Nikbakht MR, Hitotsuyanagi Y, Shkryl YN, Yadegari G, Khalilifard J, J (2023) Genus Rubia: Therapeutic Effects and Toxicity: A Review. Herb Med J 8(1):34–48 Verma P, Paswan SK, Chandra G, Gupta A, Rao CV (2022) Hydro alcoholic extract of Holarrhena antidysenterica L. induced toxicity research in experimental animals. Emerging Trends in IoT and Computing Technologies. Routledge, pp 212–218 Rekha BC, Tangeti S, Madhavi L, Pathapati RM (2016) Toxicity, Acute and Longterm Anti-Diabetic Profile of Methanolic Extract of Leaves of Pterocarpus Marsupium on Alloxan Induced Diabetic Albino Rats. Pharma Innov 5(7):90 Part B) Raji RO, Muhammad HL, Abubakar A, Maikai SS, Raji HF (2021) Acute and sub-acute toxicity profile of crude extract and fractions of Gymnema sylvestre. Clin Phytoscience 7(1):56 Patil SG, Bhadane BS, Patil MP, Belemkar S, Patil RH (2016) In-vitro antioxidant activity, acute oral toxicity studies and preliminary phytochemical characterization of the bark extract of Terminalia arjuna (L). J Pharm Nutr Sci 6:15–21 Karole S, Shrivastava S, Thomas S, Soni B, Khan S, Dubey J, Jain DK (2019) Polyherbal formulation concept for synergic action: a review. J Drug Delivery Ther 9(1–s):453–466 Parasuraman S, Thing GS, Dhanaraj SA (2014) Polyherbal formulation: Concept of ayurveda. Pharmacogn Rev 8(16):73 Pereira L, Ruiz-Hurtado G, Rueda A, Mercadier JJ, Benitah JP, Gómez AM (2014) Calcium signaling in diabetic cardiomyocytes. Cell Calcium 56(5):372–380 Umans L, Serneels L, Overbergh L, Stas L, Van Leuven F (1999) α2-macroglobulin-and murinoglobulin-1-deficient mice: A mouse model for acute pancreatitis. Am J Pathol 155(3):983–993 Additional Declarations No competing interests reported. Supplementary Files Graphicalabstracttiff.tiff RatproteinpapersupplimentaryJPP.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 19 Sep, 2024 Reviews received at journal 16 Sep, 2024 Reviewers agreed at journal 09 Sep, 2024 Reviewers invited by journal 05 Sep, 2024 Editor assigned by journal 11 Jul, 2024 Submission checks completed at journal 08 Jul, 2024 First submitted to journal 05 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4694505\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":328566936,\"identity\":\"18f3d2a0-8c5e-47d7-96df-feb2209731ea\",\"order_by\":0,\"name\":\"Shridhar Chougule\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Regional Ayurveda Research Institute for Fundamental Research, Kothrud, Pune-411038, Maharashtra, India.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shridhar\",\"middleName\":\"\",\"lastName\":\"Chougule\",\"suffix\":\"\"},{\"id\":328566938,\"identity\":\"5e50a164-aa87-4cb8-a290-ea36fc8ef704\",\"order_by\":1,\"name\":\"Amey Shirolkar\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Regional Ayurveda Research Institute for Fundamental Research, Kothrud, Pune-411038, Maharashtra, India.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Amey\",\"middleName\":\"\",\"lastName\":\"Shirolkar\",\"suffix\":\"\"},{\"id\":328566940,\"identity\":\"4431630d-ab1f-4b20-b73e-d226d3c62ffe\",\"order_by\":2,\"name\":\"Rajesh Gacche\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Department of Biotechnology, Savitribai Phule Pune University, Pune-411007, Maharashtra, India.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rajesh\",\"middleName\":\"\",\"lastName\":\"Gacche\",\"suffix\":\"\"},{\"id\":328566943,\"identity\":\"2fabae37-3720-4311-a65b-40e02d33479f\",\"order_by\":3,\"name\":\"Sudesh Gaidhani\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Central Council for Research in Ayurvedic Sciences, Janakpuri, New Delhi-110058, India.\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sudesh\",\"middleName\":\"\",\"lastName\":\"Gaidhani\",\"suffix\":\"\"},{\"id\":328566945,\"identity\":\"ed681c29-48b9-40c6-ae27-31fb502ed554\",\"order_by\":4,\"name\":\"Sharad Pawar\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYFCCBAjFz8DARqIWyQaStRgcIFaLfHsC24OfbXb5xjeSnz34UMEgzy92AL8WgzMP2A1725Itt91IMzeccYbBcObsBAJaJBLYJHi3MRuY3Ugwk+ZtY0gwuE1Ai/yMBDbJv9vqDYxnpH8jTgvDjQQ2ad5thw0MJHKItAXkF2PZf8cNJM68KZOccUaCsF9AIfbwzZlqA/729G0SHyps5PmlCTmMgf8bhBYAq5QgpBwMoDHIf4Ao1aNgFIyCUTACAQCMAj7hz81Z9gAAAABJRU5ErkJggg==\",\"orcid\":\"\",\"institution\":\"Regional Ayurveda Research Institute for Fundamental Research, Kothrud, Pune-411038, Maharashtra, India.\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Sharad\",\"middleName\":\"\",\"lastName\":\"Pawar\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2024-07-06 01:23:20\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-4694505/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-4694505/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":61486626,\"identity\":\"1217dd5a-b1a5-49c7-96c7-8854afeb3e38\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:51:07\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":283152,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eBody weights (g) of rats during the study period.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/ece5d7086be6c431be2f81a5.png\"},{\"id\":61486615,\"identity\":\"e597574f-a62d-4569-8129-a6655c2cc20d\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:51:07\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":244049,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eBlood sugar levels (mg/dl) of Rats during the study period.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/77e21519646dab034ef780a0.png\"},{\"id\":61488188,\"identity\":\"d12bcf79-d6ed-4962-bcef-a131a6dddab0\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 10:07:07\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":120056,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe EIC chromatograms of five study categories in overlaid mode, Disease control group (Purple), Healthy control (Red), Std. Glibenclamide (Green), Formulation 250 mg/kg (Brown), and Formulation 500 mg/kg (Orange).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/1701d599f368fcda65869389.png\"},{\"id\":61487258,\"identity\":\"aacd5acf-c7d1-4edf-984d-624b77ef0aa4\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:59:07\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":160101,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe EIC chromatograms of five study categories in overlaid mode.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/91d9041d28a58d8f1ed5c093.png\"},{\"id\":61487255,\"identity\":\"cd310adb-3499-4644-9442-38c67271ae31\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:59:07\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":77174,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe differential proteins expression heat map of 30 proteins belonging to 5 study categories created using respective intensities.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/fbfd19ad1a08bb9e7b62a3c3.png\"},{\"id\":61486619,\"identity\":\"d2bad65a-12d2-4129-893d-5ee707017f89\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:51:07\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":196969,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein–protein interactions map of Healthy control group obtained through STRING 11.0 tool showed the interaction between 63 proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/676ba92404cbfbdd3eec21b8.png\"},{\"id\":61488933,\"identity\":\"3f27229c-b790-45aa-a3a0-3ad15a262572\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 10:15:07\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":144502,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein–protein interactions map of Disease control group obtained through STRING 11.0 tool showed the interaction between 11 proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/6ecab924c520692900da5427.png\"},{\"id\":61487257,\"identity\":\"57e88767-5e39-4bd4-923b-797f69c9b178\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:59:07\",\"extension\":\"png\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":100825,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein–protein interactions map of Glibenclamide standard drug treatment group obtained through STRING 11.0 tool showed the interaction between 17 proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"8.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/8cb977347077aaa891d56a55.png\"},{\"id\":61488189,\"identity\":\"5807600b-c739-4752-aae8-1df71d97a117\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 10:07:07\",\"extension\":\"png\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":133300,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein–protein interactions map of 250mg/kg drug treatment group obtained through STRING 11.0 tool showed the interaction between 24 proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"9.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/77bb292473b9519c02488ca4.png\"},{\"id\":61487262,\"identity\":\"b127f6f1-0c4f-41b7-9d67-05f693516d0f\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:59:07\",\"extension\":\"png\",\"order_by\":10,\"title\":\"Figure 10\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":175996,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eProtein–protein interactions map of 500mg/kg drug treatment group obtained through STRING 11.0 tool showed the interaction between 26 proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"10.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/5b606ad2cbc43e2f74b231a5.png\"},{\"id\":61489462,\"identity\":\"b0102df2-c960-47dd-8590-61991e0214b0\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 10:23:08\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2221531,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/6ac6c261-6fcf-43c0-a6c8-2cb86b82b2b1.pdf\"},{\"id\":61487259,\"identity\":\"98ae440c-7a4e-4c11-8d12-7c96626c9a9f\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:59:07\",\"extension\":\"tiff\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":1256336,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Graphicalabstracttiff.tiff\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/dd5ecfebae839f2ee25b43ca.tiff\"},{\"id\":61486623,\"identity\":\"227f0aec-fad6-45d2-a2c4-d818d63523f4\",\"added_by\":\"auto\",\"created_at\":\"2024-07-31 09:51:07\",\"extension\":\"docx\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":607781,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"RatproteinpapersupplimentaryJPP.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-4694505/v1/39f8467f4206c1b92b37061b.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Proteomics based evaluation of the antidiabetic activity of a polyherbal formulation in Streptozotocin-induced hyperglycemia in rats\",\"fulltext\":[{\"header\":\"1. INTRODUCTION\",\"content\":\"\\u003cp\\u003eDiabetes is a global epidemic with an estimated worldwide prevalence of 537\\u0026nbsp;million people in the year 2021 and is forecasted to cross 700\\u0026nbsp;million by the year 2045; in India, about 77\\u0026nbsp;million people are living with diabetes and this number is predicted to cross 134.2\\u0026nbsp;million by 2045 (IDF, 2019, DIABETES ATLAS). Consequently, diabetes poses a serious challenge to healthcare systems around the world. Diabetes is a metabolic disorder of diverse etiologies characterized by chronic hyperglycemia with disturbance of carbohydrate, fat, and protein metabolism resulting from defects in insulin secretion, insulin action, or both, also it is a major cause of blindness, kidney failure, heart attacks, stroke, and lower limb amputation (WHO, 2021, fact sheet). There are two types of diabetes Type 1 and 2; Type 1 diabetes (aka insulin-dependent, juvenile, or childhood-onset) is characterized by deficient insulin production and requires daily administration of insulin hormone. Neither the cause of Type 1 diabetes nor the means to prevent it are known. Type 2 diabetes (also known as insulin-independent or adulthood) results from the body's ineffective use of insulin. People affected by type 2 diabetes are in majority among the people with diabetes. This type of diabetes is primarily a result of obesity and lack of exercise. Until recently, type 2 diabetes was only found in adults, but it is now becoming more common in children (WHO, 2021, fact sheet). Reports from various countries have shown that patients with diabetes have a 50% higher liability of mortality when affected by COVID-19 than those without (Bornstein et al., 2020). In India, 73% of COVID-19 deaths are associated with co-morbidities including diabetes, hypertension, and cardiovascular and respiratory diseases. Heightening the risk, more than half (57%) of the 77\\u0026nbsp;million diabetic people in India are unaware that they have diabetes and hence may not monitor their condition or take steps to control it. Of the patients who have been diagnosed, 20% do not seek treatment, thus making the situation even more alarming. COVID-19 is also linked to the development of diabetes because it affects the pancreas (Abramczyk, U et al., 2022). Many oral antidiabetic agents, such as sulfonylureas and biguanides, are available for the treatment of diabetes along with insulin (Aschner, P., 2020), but these agents embody significant adverse effects, and some are inefficacious in chronic conditions. Thus, there is an increasing need for potent antidiabetic products with lesser side effects. An ideal therapy should have a higher degree of efficacy without any troublesome side effects. Alternative treatments for diabetes are becoming highly popular, comprising medicinal herbs, nutritional supplementation, acupuncture, and naturopathy (Gayathri, A., \\u0026amp; Saranya, P. (2021), Kesavadev, J et al, 2023). In India, traditional medicine has played a vital role in recuperation from diabetes for several decades. In the Ayurvedic literature, it has been mentioned, usage of the following plants; \\u003cem\\u003ePterocarpus Marsupium\\u003c/em\\u003e Roxb., \\u003cem\\u003eGymnema sylvestre\\u003c/em\\u003e (Retz.) Schult., \\u003cem\\u003eHolarrhena antidysenterica (\\u003c/em\\u003eRoxb. ex Fleming) Wallich ex A. DC., \\u003cem\\u003eTinospora cordifolia\\u003c/em\\u003e (Willd.) Miers, \\u003cem\\u003eRubia cordifolia\\u003c/em\\u003e L. and \\u003cem\\u003eTerminalia Arjuna\\u003c/em\\u003e (Roxb.) Wight \\u0026amp; Arn. for the treatment of diabetes (Astanga Hriday Sutrasthan, 15/20 and Chakradutta, 35/8\\u0026ndash;10,13). Various research findings and evaluations have confirmed that \\u003cem\\u003ePterocarpus Marsupium\\u003c/em\\u003e (Raina, K et al., 2020), \\u003cem\\u003eGymnema sylvestre\\u003c/em\\u003e (Shanmugam, S. K et al., 2023), \\u003cem\\u003eHolarrhena antidysenterica\\u003c/em\\u003e (Divya, C. A et al., 2021), \\u003cem\\u003eTinospora cordifolia\\u003c/em\\u003e (Katara, A et al., 2021), \\u003cem\\u003eRubia cordifolia\\u003c/em\\u003e (Bana, S., et al., 2023), and \\u003cem\\u003eTerminalia Arjuna\\u003c/em\\u003e (Gaikwad, D. T et al., 2022), plants possess anti-diabetic potential. The polyherbal formulation was composed of the above-mentioned plants for the treatment of diabetes. Proteomics yields a great deal of information regarding treatment responsive changes in protein expression levels, resulting in better understanding of the involved pathway/mechanism of action. Therefore this study aimed to evaluate the efficacy and antidiabetic mechanism of the polyherbal formulation involved in the treatment of streptozotocin-induced hyperglycemia in rats.\\u003c/p\\u003e\"},{\"header\":\"2. MATERIALS AND METHODS\",\"content\":\"\\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.1 Preparation of plant extract:\\u003c/h2\\u003e \\u003cp\\u003eThe freshly collected plant materials were identified by the botanist and were kept for preservation in the herbarium of National Research Institute of Basic Ayurvedic Sciences, Pune, the voucher specimen numbers assigned were as follows; \\u003cem\\u003eRubia cordifolia\\u003c/em\\u003e No. 4398, \\u003cem\\u003eGymnema sylvestre\\u003c/em\\u003e No. 4399, \\u003cem\\u003eTerminalia Arjuna\\u003c/em\\u003e No. 4400, \\u003cem\\u003ePterocarpus Marsupium\\u003c/em\\u003e No. 4404, \\u003cem\\u003eHolarrhena antidysenterica\\u003c/em\\u003e No. 4405, and \\u003cem\\u003eTinospora cordifolia\\u003c/em\\u003e No. 4406. The plant materials were shade dried with occasional shifting and then powdered with a mechanical grinder and stored in an airtight container. The dry powdered plant materials were mixed (1:1:1:1:1:1 ratio) together, and the formulation powder was mixed with water and alcohol (1:1) for preparation of hydro alcoholic extract by cold maceration. The extract thus obtained was then lyophilized using lyophilizer (Labconco Freezone 4.5) at -50\\u003csup\\u003eo\\u003c/sup\\u003eC and 0.020 mbar pressure for three days. Later, the lyophilized material was suspended in distilled water for everyday fresh preparation of the drug just before dosing.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.2 Chemicals:\\u003c/h2\\u003e \\u003cp\\u003eTrypsin (Cat. T6567), Idoacetamide (Cat. I1149), Ammonium bicarbonate (NH\\u003csub\\u003e4\\u003c/sub\\u003eHCO\\u003csub\\u003e3\\u003c/sub\\u003e) (Cat. 09830), Dithiothreitol (DTT) (Cat. 43815), LCMS grade Acetonitrile (ACN), and Water (H2O), and Formic acid were procured from Sigma-Aldrich. RapiGest SF Surfactant was procured for Waters Corporation.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.3 Animal Husbandry:\\u003c/h2\\u003e \\u003cp\\u003e All the experimental protocols were approved by the Institutional Animal Ethics Committee and the study was conducted according to the Committee for Control and Supervision of Experiments on Animals Guidelines for the use and care of experimental animals.\\u003c/p\\u003e \\u003cp\\u003eThe Sprague Dawley rats, 10\\u0026ndash;12 weeks old, weighing 180 to 220 g were procured from the National Institute of Biosciences, Pune. The weight variation of animals used didn\\u0026rsquo;t exceed\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;20% of the mean weight. The individual animals were identified by cage tags and corresponding picric acid color body markings. All the animals were housed in an air-conditioned room with 10\\u0026ndash;15 air changes per hour, temperature between 19\\u0026ndash;25\\u0026ordm;C, relative humidity 30\\u0026ndash;70%, and an illumination cycle set to 12 hours of artificial fluorescent light and 12 hours dark. Animals were housed in polypropylene cages with stainless steel griddles, feeding fixtures and water bottles, and clean rice husk bedding. The animals were provided \\u003cem\\u003ead libitum\\u003c/em\\u003e feed (Nutrimix brand pelleted standard rat feed manufactured by Nutrivet Life Sciences, Pune). The drinking water (passed through an R.O. filtration system and followed by treatment of U.V. light) was provided \\u003cem\\u003ead libitum\\u003c/em\\u003e in glass bottles with stainless steel sipper tubes.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.4 Acute oral Toxicity in rats:\\u003c/h2\\u003e \\u003cp\\u003eThe study was conducted in compliance with the Organization for Economic Co-operation and Development (OECD) Guidelines for Testing of Chemicals (No. 423, Section 4: Health Effects) on the conduct of the \\\"Acute Oral Toxicity - Acute Toxic Class Method\\\" (Adopted: 17th December 2001) (Test No. 423, OECD Guidelines, 2002). Based on the available historical toxicity data for individual plants, a starting dose level of 2000 mg/kg body weight was selected from one of the four fixed levels (5, 50, 300, and 2000 mg/kg). Rats were subjected to overnight fasting before the dosage of the polyherbal formulation. During fasting rats were provided with ample water \\u003cem\\u003ead libitum\\u003c/em\\u003e. The toxicity of the formulation following oral gavage dosing was assessed by stepwise treatment of animals. Three rats were used per step. Rats were observed for mortality and signs of intoxication for 14 days of administration of the formulation. In addition, this study was repeated in his three other rats at the same dose level and observed for 14 days. On the day of dosing, all animals were observed for mortality and signs of intoxication at 0.5, 1, 2, 3, 4, and 6 hours following dosing, and thereafter they were observed once a day for 14 days. The appearance, progress, and disappearance of these signs were recorded. The body weights of rats were individually recorded before dosing and at weekly intervals thereafter. All animals were terminally sacrificed and subjected to a detailed necropsy. As no gross pathological findings were encountered in any of the organs, a histopathological examination was not conducted.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec7\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.5 Streptozotocin induced Hyperglycemia in rats:\\u003c/h2\\u003e \\u003cp\\u003eHyperglycemia was experimentally induced in Sprague Dawley rats fasted for 12 h by a single intraperitoneal dose (60 mg/kg body weight) of Streptozotocin dissolved in citrate buffer (pH 4.5) (Szkudelski., 2001, Akbarzadeh et al., 2007). To overcome the hypoglycemic coma that occurs within the first 24 h following streptozotocin injection, a 5% glucose solution was given instead of plain drinking water for 2 days until sustained hyperglycemia was established. Three days after the Streptozotocin injection, rats were screened for blood glucose levels. Rats having glucose ranging from 200 to 300 mg/dL were considered moderate diabetic and included in the experiment. After the selection of animals, they were randomly divided into five groups, six rats per group. Group I received only vehicle, serving as the Healthy control group. Group II animals served as hyperglycemia/disease control. Group III received Glibenclamide as the positive control (10 mg/kg) daily by oral gavage for 21 days period. Group IV and V animals received polyherbal formulation daily at the doses of 250 mg/kg and 500 mg/kg body weight orally for 21 days respectively. Blood sugar was estimated weekly during the 21 days period. Necropsy was performed on all animals after an observation period of 21 days. The body weights of rats were individually recorded before dosing and at weekly intervals thereafter. Group mean body weights were calculated. The portion of food consumed by rats in each cage was recorded on the day of commencement of treatment and weekly thereafter. Food intake was calculated using the amount of food offered and leftovers in each cage. Analysis of serum blood sugar levels was performed using the Erba EC5 Plus Analyser (Transasia Bio-Medicals Ltd., India) using standard methodology. Urine analysis was performed using Multi stix SG. On completion of 21 days of treatment, blood samples from all rats were withdrawn and then they were sacrificed by exsanguinations under carbon dioxide anesthesia and were subjected to a thorough necropsy.\\u003c/p\\u003e \\u003cp\\u003eThe data were evaluated by One-Way ANOVA (Dennett\\u0026rsquo;s test) and Student\\u0026rsquo;s t-test using Graphpad prism at the level of significance from the control means at \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;\\u0026lt;\\u0026thinsp;0.05.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.6 Protein extraction:\\u003c/h2\\u003e \\u003cp\\u003eProtein extraction was carried out using solvent precipitation (Fic et al., 2010), from blood samples collected after 21 days of treatment. In brief, blood samples were subjected to protein precipitation by adding methanol, chloroform, and water in 4:1:3 ratios respectively (Haar T von der., 2022; Wessel and Fl\\u0026uuml;gge., 1984). The mixture was vortexed briefly and centrifuged at 14,000 rpm for 1 minute to obtain three layers of separation. The uppermost water/methanol layer was removed without disturbing the interface (protein precipitate). Then methanol was added to wash the precipitate, and after vigorous vortexing, the samples were centrifuged at 15,000 rpm for 20 minutes to pellet the protein precipitate. The obtained protein pellet was redissolved using an 8M Urea solution.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.7 Protein digestion:\\u003c/h2\\u003e \\u003cp\\u003eThe proteins were quantified using standard Bradford's assay procedure (Bradford., 1976). The protein digestion protocol was as per Promega: Technical Bulletin TB373 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.promega.in/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.promega.in/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) with modification. Precipitate the protein (100 \\u0026micro;g), air-dry the pellet for 3\\u0026ndash;5 min., and solubilize with RapiGest SF Surfactant 0.1% in 50 mM NH\\u003csub\\u003e4\\u003c/sub\\u003eHCO\\u003csub\\u003e3\\u003c/sub\\u003e. A final volume of 93.5 \\u0026micro;L was adjusted using 50 mM NH\\u003csub\\u003e4\\u003c/sub\\u003eHCO\\u003csub\\u003e3\\u003c/sub\\u003e.1\\u0026micro;L of 0.5 M DTT was added and incubated at 56\\u0026deg;C for 20 minutes to disrupt disulfide bonds. 2.7 \\u0026micro;L of 0.55 M iodoacetamide was added and incubated at RT in the dark for 15 min. to alkylate reduced cysteine residues of proteins. Add 1 \\u0026micro;L of 1 \\u0026micro;g/\\u0026micro;L trypsin (MS grade) was added and the mixture was kept for digestion overnight at 37\\u0026ordm;C. After the completion of incubation, trypsin was inactivated by adding formic acid (0.5% final concentration), and the samples were stored at \\u0026minus;\\u0026thinsp;20\\u0026ordm;C till further analysis.\\u003c/p\\u003e \\u003cp\\u003e \\u003cb\\u003eUPLC\\u0026ndash;MS for proteins\\u003c/b\\u003e:\\u003c/p\\u003e \\u003cp\\u003eLC/MS experiments were performed on Agilent 1290 Infinity Series RRLC interfaced with an Agilent 6538 Accurate Mass Q-TOF MS, as mentioned by Gayakwad et. al., 2020. A injection volume of 20 \\u0026micro;L of per sample was applied to an assembly of C18 ZORBAX 300 extend (4.6 \\u0026times;150 mm) column of particle size 5 \\u0026micro;m. The column temperature was set at 40\\u0026deg;C. The solvent system had aqueous, 0.1% formic acid-water and organic, 0.1% formic acid\\u0026ndash;acetonitrile in a proportion of 95:5. The gradient mode {concentration/time (%/min)} used for solvent B were 3%/0; 60%/10; 97%/14; 97%/15.5; 30%/21; 5%/25; and 5%/30 with 0.3 mL/ min flow rate. The mass spectrometer was operated in positive ion polarity mode with parameters: ionization type dual electrospray ionization (ESI), gas temperature 325\\u0026deg;C, nebulizer 45 psi, gas flow 9.0 L/min, capillary voltage 3500 V, nozzle 750 V and the fragmentor voltage 150 V. The data acquisition was carried out in the range of 100\\u0026ndash;3000 m/z (28).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.8 Liquid Chromatography and Mass Spectrometry (LCMS):\\u003c/h2\\u003e \\u003cp\\u003eStandard runs for calibration were performed using BSA. LC separation was carried out using Agilent\\u0026rsquo;s ZORBAX 300SB-C18 column, acetonitrile: water as mobile phase. The method used for the sample run was in positive mode for 44 min. The mass range of 300 to 3500 Da was set for MS mode, 50 to 3000 Da for MS-MS mode, and data was collected in positive mode. The samples were duplicated for maintaining data integrity.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e2.9 Peptide and Protein Identification:\\u003c/h2\\u003e \\u003cp\\u003eIdentification of the differentially expressed proteins was performed on Agilent Technologies\\u0026rsquo; Spectrum Mill MS Proteomics Workbench Rev B.06.00.201 (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://spectrummill.mit.edu/\\u003c/span\\u003e\\u003cspan address=\\\"http://spectrummill.mit.edu/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), which compares the experimentally determined tryptic peptide masses with theoretical peptide masses calculated for proteins contained in the protein databases. Freely available online tools such as Batch Entrez (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.ncbi.nlm.nih.gov/sites/batchentrez\\u003c/span\\u003e\\u003cspan address=\\\"https://www.ncbi.nlm.nih.gov/sites/batchentrez\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), Uniprot (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.uniprot.org/\\u003c/span\\u003e\\u003cspan address=\\\"https://www.uniprot.org/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), Panther pathway (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://www.pantherdb.org/\\u003c/span\\u003e\\u003cspan address=\\\"http://www.pantherdb.org/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), STRING (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://string-db.org/\\u003c/span\\u003e\\u003cspan address=\\\"https://string-db.org/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e), etc. were used for further curation of data generated after Spectrum mill analysis. M\\u0026thinsp;+\\u0026thinsp;H\\u003csup\\u003e+\\u003c/sup\\u003e 600\\u0026thinsp;\\u0026minus;\\u0026thinsp;60,000 m/z, extraction time range 0\\u0026ndash;30 min., allowed charge states 2\\u0026ndash;4, maximum ambiguous precursor charge 3, precursor mass tolerance\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;1.0 Da, product mass tolerance\\u0026thinsp;\\u0026plusmn;\\u0026thinsp;0.5 Da, maximum # missed cleavages 2, minimum detected peaks 4, sequence tag length\\u0026thinsp;\\u0026gt;\\u0026thinsp;3, protein pI 3.0\\u0026ndash;10.0, and maximum reported hits 5. In the auto-validation step in Spectrum Mill, by default, FDR was set as 1.2% (28).\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"3. RESULTS\",\"content\":\"\\u003cdiv id=\\\"Sec13\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.1 Acute oral Toxicity in rats:\\u003c/h2\\u003e \\u003cp\\u003ePolyherbal formulation, when tested on rats at the dose level of 2000 mg/kg body weight, did not cause any mortality and no evident toxic signs were observed on the day of dosing and during the observation period of 14 days thereafter. Treatment of rats with the formulation and standard drug neither induce any abnormal clinical signs nor gross pathological alterations in the organs/tissues, as evident during the detailed necropsy carried out at the termination of the study. The values of average daily food consumption by rats were found to be comparable to those of the concurrent control groups. The body weight gain in healthy control rats was not found to be adversely affected during the 14 days observation period, following the dosing step.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec14\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.2 Streptozotocin induced Hyperglycemia in rats:\\u003c/h2\\u003e \\u003cp\\u003eStreptozotocin-treated rats showed a marked decrease in net body weight. However, Glibenclamide as a standard drug and polyherbal formulation attenuated the decline in the body weights during the 21 days treatment period (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, Sup. Table\\u0026nbsp;1). The values of average daily food consumption by rats exposed to the formulation and standard drug were found to be comparable to those of the healthy control group.\\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 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFunctional annotation analysis of healthy control group using DAVID Bioinformatics Resource 6.8\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" 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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCategory\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTerm\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCount\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep Value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eGenes\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eList Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003ePop Hits\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ePop Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFold Enrichment\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003eBonferroni\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eBenjamini\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003eFDR\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno05132: Salmonella infection\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.695652\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.001798\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP38650, Q62698, Q9JJ79, D3ZHA0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e83\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e15.56024\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.152575\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.165404\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.165404\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04962: Vasopressin-regulated water reabsorption\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.521739\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.007068\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP38650, Q62698, Q9JJ79\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e43\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e22.52616\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.479279\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.325116\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.325116\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04510:Focal adhesion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.695652\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.023303\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eO35346, P05539, P63319, D3ZHA0\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e210\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e6.15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.885741\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04530: Tight junction\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.521739\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.030008\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eQ62812, Q9JLT0, O35889\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e92\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e10.52853\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.939373\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04066:HIF-1 signaling pathway\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.521739\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.036273\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP27881, O35462, P63319\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e102\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e9.496324\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.966597\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno05146: Amoebiasis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.521739\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.042999\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eO35346, P05539, P63319\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e112\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e8.648438\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.982463\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG\\u003c/p\\u003e \\u003cp\\u003ePATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04670: Leukocyte transendothelial migration\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e6.521739\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.046526\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eO35346, P63319, O35889\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e117\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e8.278846\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.987514\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.611479\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.611479\\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\\u003eTreatment of rats with the formulation at 500 mg/kg and the standard drug showed a remarkable decrease in blood sugar levels on the 7th, 14\\u003csup\\u003eth,\\u003c/sup\\u003e and 21st days of observation. In respective experimental groups after the treatment of formulation and Glibenclamide, the blood glucose levels were found to be close to normal (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, Sup. Table\\u0026nbsp;2). We have also tested the effect of this formulation in three different models Viz., normoglycemic animals, oral glucose tolerance test (OGTT); Streptozotocin, and Nicotinamide induced Type 2 diabetes data, which has not been included in this proteomics study.\\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 2\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFunctional annotation analysis of disease control group using DAVID tool.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" 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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCategory\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTerm\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCount\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep Value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eGenes\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eList Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003ePop Hits\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ePop Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFold Enrichment\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003eBonferroni\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eBenjamini\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003eFDR\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04925: Aldosterone synthesis and secretion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.333333\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.083537\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eQ9EQ60, Q63269\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e84\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e20.5\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.963662\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04911: Insulin secretion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.333333\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.085449\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eQ9JKS6, Q63269\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e86\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e20.02326\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.966435\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04713: Circadian entrainment\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e2\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e8.333333\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.095904\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eQ9EQ60, Q63269\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e9\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e17.75258\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.978315\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003c/div\\u003e\\u003c/div\\u003e \\u003cdiv id=\\\"Sec15\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003e3.3 Mass spectrometric analysis:\\u003c/h2\\u003e \\u003cdiv id=\\\"Sec16\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.1 Proteome analysis:\\u003c/h2\\u003e \\u003cp\\u003eThe Extracted Ion Chromatogram (EIC) profile view displayed the variations in protein levels among 5 study groups. The EIC chromatograms of the two sampling groups are shown in overlaid mode (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e). The proteins that were identified from the samples of all 5 study groups have been noted in supp. Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e; only the proteins that were identified with a minimum of 2 or more distinct peptides have been listed. We were able to identify numbers of proteins in various treatment groups i.e. 98 proteins in healthy control, 24 proteins in disease control, 51 proteins in Glibenclamide standard treatment, 51 proteins in 250 mg/kg formulation treatment, and 53 proteins in 500 mg/kg formulation treatment group. In Supp. Table \\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, a total of 277 proteins were observed in this study, out of which four proteins were found to be directly involved in diabetes-associated metabolic pathways; are Hexokinase 2 (Healthy control group): It catalyzes the phosphorylation of D-glucose and D-fructose, to hexose 6-phosphate (D-glucose 6-phosphate and D-fructose 6-phosphate). It plays a key role in maintaining the integrity of the outer mitochondrial membrane by preventing the release of apoptogenic molecules from the intermembrane space and subsequent apoptosis; Acetoacetyl CoA Synthetase (250 mg/kg treatment group): catalyzes the formation of Acetyl-CoA that can be used in the TCA cycle in aerobic respiration to produce energy and electron carriers; Angiotensin-converting enzyme ACE (500 mg/kg treatment group), it converts the hormone angiotensin I to the active vasoconstrictor angiotensin II. ACE is a core element of the renin-angiotensin system (RAS), it modulates blood pressure by changing the volume of fluids in the body; the Insulin receptor (500 mg/kg treatment group) is the linchpin in glucose homeostasis. Also occurrence of Murinoglobulin-1 protein post treatment (500 mg/kg treatment group), it has a significant role in inflammation regulation, protease inhibition, and in management of oxidative stress.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\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 3\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFunctional annotation analysis of 250 mg/kg formulation study group using DAVID tool.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" 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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCategory\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTerm\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCount\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep Value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eGenes\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eList Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003ePop Hits\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ePop Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFold Enrichment\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003eBonferroni\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eBenjamini\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003eFDR\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04510: Focal adhesion\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e4\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e7.843137\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.018206\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP28818, P02466, P02454, P20909\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e210\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e6.709091\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.629225\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04974: Protein digestion and absorption\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.882353\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.023775\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP02466, P02454, P20909\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e11.87283\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.727298\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04512: ECM-receptor interaction\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.882353\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.023775\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP02466, P02454, P20909\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e11.87283\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.727298\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.427956\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno05146: Amoebiasis\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.882353\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.036361\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP02466, P02454, P20909\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e112\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e9.434659\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.864674\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.490871\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.490871\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04611: Platelet activation\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.882353\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.050982\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eP02466, P02454, P20909\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e22\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e135\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e7.827273\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.940732\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e0.550605\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e0.550605\\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 underlying association of the differential protein expression among the groups were represented as a heat map (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The heat map has been created using the respective spectral intensities of 30 proteins. Around 25 proteins were found to be altered in diseased state when compared to healthy control. In the 250 mg/kg and 500 mg/kg treatment group a total of 19 and 18 proteins respectively with altered levels were normalized comparable to the healthy group.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec17\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.2 \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003eProtein-protein interaction analysis\\u003c/span\\u003e:\\u003c/h2\\u003e \\u003cp\\u003eProtein-protein interactions (PPIs) are fundamental to almost every aspect of cellular function and regulation. PPIs play a key role in predicting the function of target protein and druggability of molecules. The lists of identified proteins were analyzed using the STRING 11.0b tool to obtain the protein-protein interactions network information. The STRING database contains functional protein association network data, which contains both experimentally validated and computationally predicted protein-protein interaction data, also it includes physical as well as functional associations (Szklarczyk et al., 2019). The information of only those proteins has been listed (Supp. Table \\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e) that was linked by experimentally validated interactions. The interactions obtained from STRING analysis for all study groups have been depicted in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e\\u0026ndash;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\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 4\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eFunctional annotation analysis of 500 mg/kg formulation study group using DAVID tool.\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"13\\\"\\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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" 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=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c9\\\" colnum=\\\"9\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c10\\\" colnum=\\\"10\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c11\\\" colnum=\\\"11\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c12\\\" colnum=\\\"12\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"char\\\" char=\\\".\\\" class=\\\"colspec\\\" colname=\\\"c13\\\" colnum=\\\"13\\\"\\u003e\\u003c/div\\u003e \\u003cthead\\u003e \\u003ctr\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eCategory\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003eTerm\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003eCount\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e%\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ep Value\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eGenes\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003eList Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003ePop Hits\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003ePop Total\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003eFold Enrichment\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003eBonferroni\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003eBenjamini\\u003c/p\\u003e \\u003c/th\\u003e \\u003cth align=\\\"left\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003eFDR\\u003c/p\\u003e \\u003c/th\\u003e \\u003c/tr\\u003e \\u003c/thead\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04974: Protein digestion and absorption\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.660377\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.028223\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eQ9JI03, P26433, P02466\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e89\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e10.88343\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.917153\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eKEGG PATHWAY\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\"\\u003e \\u003cp\\u003erno04713: Circadian entrainment\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003e3\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003e5.660377\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003e0.033081\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eB0LPN4, Q00960, O54898\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e24\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e97\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c9\\\"\\u003e \\u003cp\\u003e7749\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c10\\\"\\u003e \\u003cp\\u003e9.985825\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c11\\\"\\u003e \\u003cp\\u003e0.946426\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c12\\\"\\u003e \\u003cp\\u003e1\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"char\\\" char=\\\".\\\" colname=\\\"c13\\\"\\u003e \\u003cp\\u003e1\\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\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003eIn the Healthy control group 7 proteins, namely Plcb1, Ptk2, Trip12, Dync1li2, Dyync1h1, Gfm1 and Mrps7, were with experimentally validated interactions. The PPIs depict general growth, maintenance, GTP-dependent ribosomal translocation, vesicular transport, and development associated interactions. Briefly, the ongoing cellular processes related with overall homeostasis and development were observed in the healthy control group.\\u003c/p\\u003e \\u003cp\\u003eIn the Disease control group, Foxm1, Alb, Pzp, Ank3, Itpr3, Kif5a were the proteins having maximum interactions. The PPIs shed light on the repair mechanism being activated, resulting from streptozotocin treatment that damages beta cells of Islets of Langerhans. Also the disturbed calcium homeostasis was observed which is correlated with complications of diabetic cardiomyopathy (Pereira, L., et al, 2014). Which is expected in the disease control group.\\u003c/p\\u003e \\u003cp\\u003eFor the Glibenclamide standard group 9 proteins namely Map4, Prkar2a, Apoe, Alb, Akap6, Syng, Synj1, Dync1h1, Nup98 were the most interacting proteins. The PPIs reveal microtubule assembly promotion, metabolism of lipoproteins, and membrane trafficking in the trans-Golgi network (TGN). Indicating the activation of various signaling cascades in response to Glibenclamide treatment.\\u003c/p\\u003e \\u003cp\\u003eIn the 250 mg/kg drug treatment group about 12 proteins namely Col1a2, Col1a1, Col11a1, Apoe, Alb, Ptprz1, Mapk7, Kalrn, Dlg4, Neo1, Ush2a proteins that established functional correlations. The PPIs related to cell growth, cell cycle regulation, developmental processes and cell survival that unveil the active cell proliferation, differentiation, and growth in response to treatment of formulation.\\u003c/p\\u003e \\u003cp\\u003eIn the 500 mg/kg drug treatment group, Ryr2, Cacna1g, Lrrn3, Cntn3, Pdzd2, Grin2b, Dlgap3, Grik1, Alb, A1i3, Mug1, Ank3, Cntnap1, Col1a2, and Col5a1 are the 15 proteins with maximum interactions. The PPIs highlight a surge in metabolic activity, as most of the interactions were found to be related to transmembrane signal receptors, protein modifying enzymes and metabolite interconversion enzymes. A key protein, murinoglobulin-1\\u0026rsquo;s functional interactions are responsible for maintenance of pancreatic well being as according to Umans, L et al., (1999), α2-macroglobulin and murinoglobulin-1-deficiency leads to acute pancreatitis. The presence of this key protein in the 500 mg/kg treatment group stipulates the alleviation of streptozotocin induced pancreatic damage.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec18\\\" class=\\\"Section3\\\"\\u003e \\u003ch2\\u003e3.3.3 \\u003cspan type=\\\"Underline\\\" class=\\\"Underline\\\" name=\\\"Emphasis\\\"\\u003ePathway analysis\\u003c/span\\u003e:\\u003c/h2\\u003e \\u003cp\\u003eThe Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis of identified proteins yielded probable pathways that were active or stimulated, using the KEGG pathway map (Huang et al., 2009; Sherman et al., 2022). The DAVID tool was unable to assign any pathway for Glibenclamide standard group, whereas for rest 4 groups i.e., healthy control (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab3\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e, Supp. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), disease control (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab4\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, Supp. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e), 250 mg/kg treatment (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e, Supp. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e), and 500 mg/kg treatment group (Table\\u0026nbsp;\\u003cspan refid=\\\"Tab2\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e, Supp. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e) pathways with significant \\u003cem\\u003ep\\u003c/em\\u003e-values were assigned.\\u003c/p\\u003e \"},{\"header\":\"4. Discussion\",\"content\":\"\\u003cp\\u003eDiabetes is one of the most common and thus important diseases in the world, hence it requires special attention with more emphasis on translational research. In the past few decades, several treatment regimes have been practiced; unfortunately, their associated adverse effects are not yet satisfactorily resolved (WHO, 2021, fact sheet; Nugraha, R. V et al., 2020). Studies have revealed that the phytochemicals present in polyherbal formulations can be a constitutive source (Dinda, B., \\u0026amp; Dinda, M. (2022; Mukherjee P. K. et al., 2021) and their amalgamation into the main treatment regime can be the solution we have been seeking. Researchers have found that owing to their complex composition ayurvedic/polyherbal formulations tend to interact with multiple targets, and resonate in a dynamic way providing an enhanced effect.\\u003c/p\\u003e \\u003cp\\u003eProteomics is a crucial tool for understanding the disease/physiological condition and associated pathways, and in mapping the mechanism of action of respective drugs/compounds. Here, we have prepared a polyherbal formulation by mixing 6 plant powdered materials namely \\u003cem\\u003eRubia cordifolia, Gymnema sylvestre, Terminalia Arjuna, Pterocarpus Marsupium, Holarrhena antidysenterica\\u003c/em\\u003e, and \\u003cem\\u003eTinospora cordifolia\\u003c/em\\u003e in equal proportions. There are no reports of toxicity for the individual components of formulation in the current study (Balkrishna, A et al., 2022; Eskandarzadeh et al., 2023; Verma, P et a., 2022; Rekha, B. C et al., 2016; Raji, R. O et al., 2021; Patil, S. G et al., 2016; Anantharaman et. al., 2016). Due to synergism, poly-herbalism offers benefits not deliverable by a single herbal drug. It enables better therapeutic effects with lower doses, reducing the risk of adverse side effects of individual plants, if any (Kotmire, S et al., 2024). Also, presence of multiple active compounds together can provide a potentiating effect that may not be achievable by any single compound. Thus, a polyherbal formulation can provide a complete therapy against a disease condition (Karole, S et al., 2019).\\u003c/p\\u003e \\u003cp\\u003eIn the present study, the formulation at the dose level of 2000 mg/kg body weight, did not cause any mortality or toxicity thus confirming that after combination the formulation is nontoxic. This indicates that the maximum tolerated dose of the polyherbal formulation was more than 2000 mg/kg and thus, no observed adverse effect level (NOAEL) of the formulation should be above 2000 mg/kg with approximate LD\\u003csub\\u003e50\\u003c/sub\\u003e more than 2500 mg/kg. Thus, according to the \\\"Globally Harmonized System (GHS) for classification of chemicals which cause acute toxicity, OECD series on testing and assessment, Number 33; Harmonized Integrated Classification System for Human and Environmental Hazards of Chemical Substances and Mixtures (ENV/JM/MONO (2001) 6)\\\", the \\u003cb\\u003ePolyherbal formulation\\u003c/b\\u003e can be classified as \\u003cb\\u003eGHS Category 5 or Unclassified\\u003c/b\\u003e for the obligatory labeling requirement for oral toxicity.\\u003c/p\\u003e \\u003cp\\u003eAlthough there can be side effects when taken alongside other medicine prescribed in diabetic condition. As some of the individual components have been known to enhance the immune response, lower the blood glucose levels, expedite liver metabolism, and have anticoagulant activity (Parasuraman, S et al., 2014). When co-consumed, patients with autoimmune response can experience severe reaction, it can lead to hypoglycemic conditions, and it may also all together alter the pharmacokinetics of drugs. In the current study the combination effects of modern medicine and the formulation has not been studied.\\u003c/p\\u003e \\u003cp\\u003eFor the formation of polyherbal formulations, drug antagonism is a critical factor\\u003c/p\\u003e \\u003cp\\u003eto be considered. In the preparation of polyherbal, it is crucial to note that some herbs are incompatible (\\u003cem\\u003eviruddha\\u003c/em\\u003e) and should not be taken in combination. Such discordance can be due to quantitative incompatibility, energetic incompatibility or functional incompatibility (Parasuraman, S et al., 2014). In our formulation we have not observed any adverse effect during and after treatment in animal model.\\u003c/p\\u003e \\u003cp\\u003eThe formulation was found to be most effective at 500 mg/kg concentration in regulating body weight and maintaining blood glucose levels in the STZ induced diabetic rat model. It was able to revert the declined bodyweight and elevated blood glucose levels to normal (Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e). Suggesting that the formulation has an positive effect on glucose uptake and metabolism (Kang et. al, 2009; Xu et al., 2019; Liu et al., 2021, Sharma et. al., 2021; Li Y et. al., 2019; Kim et. al., 2017; Biswas et. al, 2011; Mohanty et. al., 2019; Pari et. al., 2018; Mishra et. al., 2013; Ali et. al., 2011; Sharma et. al., 2021; Jamadagni et al., 2017; Chandrasekaran et al., 2009; Joshi et al., 2004; Kumari et al., 2021; Ogawa et al., 2004). Here we aimed to provide a better understanding of the molecular mechanisms involved in the treatment of diabetes using a polyherbal formulation, and the importance of natural resources for improving the quality of life.\\u003c/p\\u003e \\u003cp\\u003eHallmark of diabetes mellitus is hindered glucose uptake and metabolism due incapacitated or damaged pancreatic β-cells. There are reports suggesting the pancreatic β-cells repair/regenerative potential displayed by the individual component plants on the STZ-induced rat model (Shanmugasundaram et al., 1990; Bolkent et al., 2000; Daisy et al., 2009; Mishra et. al., 2013; Rajalakshmi and Anita., 2016). Here, we have tested the synergistic effect of the polyherbal formulation on the STZ-induced rat model for the same. By studying the protein-protein interactions, we can link cellular pathways and their intricate cross-connectivity. In the Healthy control group, the PPIs show overall growth, progression, maintenance, and homeostasis. As per the condition in the disease control group, the PPIs displays an ongoing active repair mechanism resultant of streptozotocin treatment. Also the interaction depicting disturbed calcium homeostasis which can be correlated with diabetic cardiomyopathy were observed (Pereira, L., et al, 2014). For the Glibenclamide standard group, PPIs reveal microtubule assembly promotion, metabolism of lipoproteins, and membrane trafficking in the trans-Golgi network (TGN). In the 250 mg/kg drug treatment group, the PPIs related to cell growth, cell cycle regulation, developmental processes and cell survival that unveil the active cell proliferation, differentiation, and growth in response to treatment of formulation. In the 500 mg/kg treatment group, PPIs have shed light on significant ongoing cellular processes that hint towards a repair mechanism being activated in response to damage incurred to pancreatic β-cells. As we were able to identify insulin receptor protein which is an integral component of glucose metabolism, and a key protein, murinoglobulin-1\\u0026rsquo;s functional interactions are responsible for maintenance of pancreatic well being (Umans, L., et al., 1999).\\u003c/p\\u003e \\u003cp\\u003eThe DAVID-KEGG pathway analysis of identified proteins uncovered the possible pathways that were triggered in respective study groups. Namely the HIF-1 signaling pathway in the healthy control group, Insulin secretion and circadian entrainment pathways in the disease control group, ECM-receptor interaction pathway in the 250 mg/kg group, and circadian entrainment pathway in the 500 mg/kg group.\\u003c/p\\u003e \\u003cp\\u003eIn the healthy control group, three proteins from our study namely Hexokinase-2, Angiopoietin-2, and Protein kinase C gamma type were found to be associated with the HIF-1 signaling pathway. Hypoxia-inducible factor 1 (HIF-1) is a transcription factor that functions as a master regulator of oxygen homeostasis in all metazoan species. HIF-1 controls oxygen delivery, by regulating angiogenesis and vascular remodeling, and oxygen utilization, by regulating glucose metabolism and redox homeostasis (Cerychova and Pavlinkova., 2018; Krock et al., 2011; Semenza., 2014). Bosch-Marce et. al., (2007) have demonstrated that the therapeutic enhancement of HIF activity can overcome age and diabetes, as ectopic expression of HIF-1α can partially rescue limb perfusion in old mice.\\u003c/p\\u003e \\u003cp\\u003eIn the disease control category, three proteins from our study were found to be involved with Insulin secretion and circadian entrainment pathways; these were Inositol 1,4,5-trisphosphate receptor type 3, Voltage-dependent T-type calcium channel subunit alpha-1H and Protein piccolo. The Inositol triphosphate pathway mobilizes the calcium ions from organelles and consequently increases the secretion of insulin (Onaolapo et al., 2018). Mechanisms for Ca\\u003csup\\u003e2+\\u003c/sup\\u003e entry include voltage-operated channels (VOC), receptor-operated channels (ROC), and store-operated channels (SOC) as well as two families of intracellular Ca\\u003csup\\u003e2+\\u003c/sup\\u003e release channels, the ryanodine receptor (RyR) and InsP3R (Hagar and Ehrlich, 2000; Yang et al., 2013). In 2002, Fujimoto et. al. demonstrated the importance of the cAMP-GEFIIּ Rim2ּ Piccolo complex in cAMP-induced insulin secretion. Thus indicating the effort of the body to regulate the imbalanced insulin levels due to damaged pancreas (islet of Langerhans).\\u003c/p\\u003e \\u003cp\\u003eIn the 250 mg/kg formulation treatment category, three proteins were found to be engaged with ECM-receptor interaction; the Collagen alpha-1(XI) chain, Collagen alpha-1(I) chain, and Collagen alpha-2(I) chain. During the onset and progression of Diabetes, the ECM protein expression and functioning are impaired, leading to structural alteration of the ECM network as well as normal tissues and cell behavior including cell-cell interactions (Bansode and Gacche., 2019; Shirolkar et al., 2022). Subsequently, these changes lead to diabetes-induced organ-dependent diseases such as nephropathy, retinopathy, and diabetic cardiomyopathy. Spiro and Crowley (1993) have also demonstrated that Alloxan-induced diabetes in rats displayed a significant increase in collagen type VI when compared to collagen types I and IV and other ECM proteins. A high glucose environment and other changes in diabetes lead to alterations in ECM, such as decreased collagen deposition and abnormal collagen metabolism mitigate wound healing (Huang and Kyriakides., 2020). Thus, indicating the therapeutic effect of formulation in mitigating the diabetic condition via up regulation of ECM network.\\u003c/p\\u003e \\u003cp\\u003eIn the 500 mg/kg treatment category, three proteins were found to be involved in the circadian entrainment pathway; those were Ryanodine receptor 2, Glutamate receptor ionotropic NMDA 2B, and Voltage-dependent T-type calcium channel subunit alpha-1G. The CLOCK and BMAL1 proteins are known to activate the transcription of genes in the pancreas, which are responsible for insulin synthesis/transport and glucose-stimulated secretion (Stenvers et al., 2019). Marcheva et. al., (2010) have demonstrated using both CLOCK and BMAL1 mutants that disruption of the biological clock components leads to hypoinsulinemia and diabetes. Uehara et. al., (2004) have suggested that the mGluR4-mediated signaling and GABAA receptor-mediated cascade; both individually act through the L-glutamatergic system that may act as autocrine transmitter and inhibit glucagon, in the islet of Langerhans. This displays the fringe benefit of the polyherbal formulation at 500 mg/kg in diabetes condition, as it maneuvers towards normalization of the metabolism. As discussed herewith we have demonstrated that diabetes-specific proteins and pathways are associated with progressions and recovery using a polyherbal formulation holistically.\\u003c/p\\u003e\"},{\"header\":\"5. Conclusion\",\"content\":\"\\u003cp\\u003eAs witnessed from the current animal experimentation results, the proposed polyherbal formulation is not toxic and possesses promising anti-hyperglycemic activity based on the insights provided by proteomics study. Among the treatment groups, the most potent effect was observed at 500 mg/kg b.w. dose level. At the said dosage, the blood glucose levels were comparable to that of standard drug treatment and concurrent healthy control. In an effort to investigate the mechanism of action, the serum-based proteomic profiling revealed; A multi-faceted mechanism of action being regulation of blood glucose levels, upregulation of glucose uptake, and metabolism. Circadian entrainment, ECM-receptor, HIF-1 signaling, and Insulin secretion pathways were the prominent pathways that were found to be distinguished. Three proteins observed in the 500 mg/kg treatment study category are most significant; namely Angiotensin-converting enzyme (ACE), Insulin receptor protein, and murinoglobuline-1 are very crucial in repair/rejuvenation of pancreatic β-cells. The proposed polyherbal formulation has promising potential as a candidate for diabetes treatment. Thus we propose to evaluate and explore the proposed polyherbal formulation through randomized clinical trials and multi-omics approaches, as a remedy for efficient diabetes management.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e \\u003ch2\\u003eConflict of Interests:\\u003c/h2\\u003e \\u003cp\\u003eAuthors declare no conflict of interest.\\u003c/p\\u003e \\u003c/p\\u003e\\u003ch2\\u003eFunding information:\\u003c/h2\\u003e \\u003cp\\u003eThis research did not receive any specific grant from any funding agencies in the public, commercial, or not-for-profit sectors.\\u003c/p\\u003e\\u003ch2\\u003eAuthor Contribution\\u003c/h2\\u003e\\u003cp\\u003eSP conceived and designed the research; SC and AS performed the research and acquired the data;SC, AS, SP analysed and interpreted the data;RG, SG provided useful technical inputs in experimentation and in data analysis ; all authors (SC, AS, RG, SG, SP) were involved in drafting and revising the manuscript.\\u003c/p\\u003e\\u003ch2\\u003eAcknowledgement\\u003c/h2\\u003e\\u003cp\\u003eNA\\u003c/p\\u003e\\u003ch2\\u003eData Availability\\u003c/h2\\u003e\\u003cp\\u003eThe mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD031550 and 10.6019/PXD031550.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\u003cli\\u003e\\u003cspan\\u003eAbramczyk U, Nowaczyński M, Słomczyński A, Wojnicz P, Zatyka P, Kuzan A (2022) Consequences of COVID-19 for the Pancreas. Int J Mol Sci 23(2):864\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAkbarzadeh A, Norouzian D, Mehrabi MR, Jamsh:di SH, Farhangi A, Verdi AA, Mofidian SMA, Rad BL (2007) Induction of diabetes by streptozotocin in rats. Indian J Clin Biochem 22:60\\u0026ndash;64\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAli KM, Chatterjee K, De D, Jana K, Bera TK, Ghosh D (2011) Inhibitory effect of hydro-methanolic extract of seed of Holarrhena antidysenterica on alpha-glucosidase activity and postprandial blood glucose level) in normoglycemic rat. J Ethnopharmacol 135(1):194\\u0026ndash;196\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAnantharaman A, Priya RR, Hemachandran H, Akella S, Rajasekaran C, Ganesh J, Fulzele DP, Siva R (2016) Toxicity study of dibutyl phthalate of R ubia cordifolia fruits: in vivo and in silico analysis. Environ Toxicol 31(9):1059\\u0026ndash;1067\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eAschner P (2020) Insulin therapy in type 2 diabetes. Am J Ther 27(1):e79\\u0026ndash;e90\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBana S, Kumar N, Sartaj A, Alhalmi A, Qurtam AA, Nasr FA, Goel R (2023) Rubia cordifolia L. Attenuates Diabetic Neuropathy by Inhibiting Apoptosis and Oxidative Stress in Rats. Pharmaceuticals 16(11):1586\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBansode SB, Gacche RN (2019) Glycation-induced modification of tissue-specific ECM proteins: A pathophysiological mechanism in degenerative diseases. Biochim et Biophys Acta (BBA)-General Subj 1863(11):129411\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBolkent Ş, Yanardağ R, Tabakoğlu-Oğuz A, \\u0026Ouml;zsoy-Sa\\u0026ccedil;an \\u0026Ouml; (2000) Effects of chard (Beta vulgaris L. var. cicla) extract on pancreatic B cells in streptozotocin-diabetic rats: a morphological and biochemical study. J Ethnopharmacol 73(1\\u0026ndash;2):251\\u0026ndash;259\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBornstein SR, Rubino F, Khunti K, Mingrone G, Hopkins D, Birkenfeld AL, Boehm B, Amiel S, Holt RI, Skyler JS, DeVries JH (2020) Practical recommendations for the management of diabetes in patients with COVID-19. lancet Diabetes Endocrinol 8(6):546\\u0026ndash;550\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBosch-Marce M, Okuyama H, Wesley JB, Sarkar K, Kimura H, Liu YV, Zhang H, Strazza M, Rey S, Savino L, Zhou YF (2007) Effects of aging and hypoxia-inducible factor-1 activity on angiogenic cell mobilization and recovery of perfusion after limb ischemia. Circul Res 101(12):1310\\u0026ndash;1318\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBradford MM (1976) A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 72(1\\u0026ndash;2):248\\u0026ndash;254\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eCerychova R, Pavlinkova G (2018) HIF-1, metabolism, and diabetes in the embryonic and adult heart. Front Endocrinol 9:460\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eChandrasekaran CV, Mathuram LN, Daivasigamani P, Bhatnagar U (2009) Tinospora cordifolia, a safety evaluation. Toxicol In Vitro 23(7):1220\\u0026ndash;1226\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDaisy P, Eliza J, Farook KAMM (2009) A novel dihydroxy gymnemic triacetate isolated from Gymnema sylvestre possessing normoglycemic and hypolipidemic activity on STZ-induced diabetic rats. J Ethnopharmacol 126(2):339\\u0026ndash;344\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDinda B, Dinda M (2022) Natural products, a potential source of new drugs discovery to combat obesity and diabetes: their efficacy and multi-targets actions in treatment of these diseases. Natural Products in Obesity and Diabetes: Therapeutic Potential and Role in Prevention and Treatment. Springer International Publishing, Cham, pp 101\\u0026ndash;275\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eDivya CA, Dhar SK, Shantaram M, Das M (2021) Anti-diabetic effects of Holarrhena antidysentrica extracts: Results from a Longitudinal Meta-analysis. bioRxiv, 2021\\u0026ndash;2002\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFic E, Kedracka-Krok S, Jankowska U, Pirog A, Dziedzicka‐Wasylewska M (2010) Comparison of protein precipitation methods for various rat brain structures prior to proteomic analysis. Electrophoresis 31(21):3573\\u0026ndash;3579\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eFujimoto K, Shibasaki T, Yokoi N, Kashima Y, Matsumoto M, Sasaki T, Tajima N, Iwanaga T, Seino S (2002) Piccolo, a Ca2\\u0026thinsp;+\\u0026thinsp;sensor in pancreatic β-cells: involvement of cAMP-GEFII\\u0026middot; Rim2\\u0026middot; Piccolo complex in cAMP-dependent exocytosis. J Biol Chem 277(52):50497\\u0026ndash;50502\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGaikwad DT, Bansode SP, Mali DP, Wadkar GH, Pawar VT, Tamboli FA (2022) Promising Discovery of Alpha Amylase Enzyme Inhibitors from Terminalia arjuna for Antidiabetic Potential. Technology 12(3):1020\\u0026ndash;1024\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGayakwad S, Shirolkar A, Warkad S, Bharsakale S, Gaidhani S, Pawar S (2020) Proteomic and metabolomic analysis of Nothapodytes nimmoniana (J. Graham) extracts\\u0026rsquo; treatment on HeLa cells. J Proteins Proteom 11:27\\u0026ndash;62\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eGayathri A, Saranya P (2021) A cross sectional study on utilization of complementary and alternative medicine in patients with diabetes mellitus. Annals of the Romanian Society for Cell Biology, pp 1360\\u0026ndash;1379\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003evon Haar T (2022) der. Methanol Precipitation of Proteins. wwwprotocolsio. Published online September 4, 2019. Accessed December 23, \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.protocols.io/view/methanol-precipitation-of-proteins-icecate.html\\u003c/span\\u003e\\u003cspan address=\\\"https://www.protocols.io/view/methanol-precipitation-of-proteins-icecate.html\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHagar RE, Ehrlich BE (2000) Regulation of the type III InsP3 receptor and its role in β cell function. Cell Mol Life Sci CMLS 57:1938\\u0026ndash;1949\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHuang DW, Sherman BT, Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 4(1):44\\u0026ndash;57\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eHuang Y, Kyriakides TR (2020) The role of extracellular matrix in the pathophysiology of diabetic wounds. Matrix biology plus 6:100037\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eInternational Diabetes Federation (2021) DIABETES ATLAS 10th Edition 2021 \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://diabetesatlas.org/en/sections/worldwide-toll-of-diabetes.html\\u003c/span\\u003e\\u003cspan address=\\\"https://diabetesatlas.org/en/sections/worldwide-toll-of-diabetes.html\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eJoshi MC, Dorababu M, Prabha T, Kumar MM, Goel RK (2004) Effects of Pterocarpus marsupium on NIDDM-induced rat gastric ulceration and mucosal offensive and defensive factors. Indian J Pharmacol 36(5):296\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKang W, Zhang L, Song Y (2009) Alpha-glucosidase inhibitors from Rubia cordifolia. Zhongguo Zhong yao za zhi\\u0026thinsp;=\\u0026thinsp;Zhongguo Zhongyao Zazhi\\u0026thinsp;=\\u0026thinsp;China. J Chin Materia Med 34(9):1104\\u0026ndash;1107\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKatara A, Garg NK, Mathur M (2021) Separation and Identification of Anti-diabetic compounds in Tinospora cordifolia extract and Ayurvedic formulation Guduchi Satva by GCMS and FTIR study with Subsequent Evaluation of in-vitro Hypoglycemic Potential. Int J Pharm Sci Drug Res 13:183\\u0026ndash;189\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKesavadev J, Basanth A, Kalra S (2023) Unproven Therapies for Diabetes. The Diabetes Textbook: Clinical Principles, Patient Management and Public Health Issues. Springer International Publishing, Cham, pp 1125\\u0026ndash;1139\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKim HJ, Kim S, Lee AY, Jang Y, Davaadamdin O, Hong SH, Kim JS, Cho MH (2017) The effects of Gymnema sylvestre in high-fat diet-induced metabolic disorders. Am J Chin Med 45(04):813\\u0026ndash;832\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKrock BL, Skuli N, Simon MC (2011) Hypoxia-induced angiogenesis: good and evil. Genes cancer 2(12):1117\\u0026ndash;1133\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKumari I, Kaurav H, Choudhary G (2021) Rubia cordifolia (Manjishtha): A review based upon its Ayurvedic and Medicinal uses. Himal J Health Sci 6(2):17\\u0026ndash;28\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLi Y, Liu Y, Liang J, Wang T, Sun M, Zhang Z (2019) Gymnemic acid ameliorates hyperglycemia through PI3K/AKT-and AMPK-mediated signaling pathways in type 2 diabetes mellitus rats. J Agric Food Chem 67(47):13051\\u0026ndash;13060\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eLiu M, Zhou T, Zhang J, Liao G, Lu R, Yang X (2021) Identification of C21 steroidal glycosides from Gymnema sylvestre (Retz.) and evaluation of their glucose uptake activities. Molecules 26(21):6549\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMarcheva B, Ramsey KM, Buhr ED, Kobayashi Y, Su H, Ko CH, Ivanova G, Omura C, Mo S, Vitaterna MH, Lopez JP (2010) Disruption of the clock components CLOCK and BMAL1 leads to hypoinsulinaemia and diabetes. Nature 466(7306):627\\u0026ndash;631\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMohanty IR, Borde M, Maheshwari U (2019) Dipeptidyl peptidase IV Inhibitory activity of Terminalia arjuna attributes to its cardioprotective effects in experimental diabetes: In silico, in vitro and in vivo analyses. Phytomedicine 57:158\\u0026ndash;165\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eMukherjee PK, Banerjee S, Biswas S, Das B, Kar A, Katiyar CK (2021) Withania somnifera (L.) Dunal-Modern perspectives of an ancient Rasayana from Ayurveda. J Ethnopharmacol 264:113157\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eNugraha RV, Ridwansyah H, Ghozali M, Khairani AF, Atik N (2020) Traditional herbal medicine candidates as complementary treatments for COVID-19: a review of their mechanisms, pros and cons. Evidence-Based Complementary and Alternative Medicine, 2020\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOgawa Y, Sekita K, Umemura T, Saito M, Ono A, Kawasaki Y, Uchida O, Matsushima Y, Inoue T, Kanno J (2004) Gymnema sylvestre leaf extract: a 52-week dietary toxicity study in Wistar rats. Shokuhin eiseigaku zasshi. J Food Hyg Soc Japan 45(1):8\\u0026ndash;18\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eOnaolapo AY, Onaolapo OJ (2018) Circadian dysrhythmia-linked diabetes mellitus: Examining melatonin\\u0026rsquo;s roles in prophylaxis and management. World J diabetes 9(7):99\\u0026ndash;114\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePari L, Majeed M, Rathinam A, Chandramohan R (2018) Molecular action of inflammation and oxidative stress in hyperglycemic rats: effect of different concentrations of Pterocarpus marsupiums extract. J Diet supplements 15(4):452\\u0026ndash;470\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRaina K, Manek RA, Sheth DB, Naik DJ (2020) Pterocarpus Marsupium Extract Exaggerates Anti Diabetic Activity Of Metformin. J Adv Sci Res 11(04):275\\u0026ndash;283\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRajalakshmi M, Anita R (2016) β-cell regenerative efficacy of a polysaccharide isolated from methanolic extract of Tinospora cordifolia stem on streptozotocin-induced diabetic Wistar rats. Chemico-Biol Interact 243:45\\u0026ndash;53\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSemenza GL (2014) Hypoxia-inducible factor 1 and cardiovascular disease. Annu Rev Physiol 76:39\\u0026ndash;56\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShanmugam SK, Singh M, Kumar D, Mishra R, Barman M (2023) Exploring Antidiabetic Potential of Gymnema sylvestre. J Appl Pharm Sci Res 6(2):30\\u0026ndash;35\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShanmugasundaram ERB, Gopinath KL, Shanmugasundaram KR, Rajendran VM (1990) Possible regeneration of the islets of Langerhans in streptozotocin-diabetic rats given Gymnema sylvestre leaf extracts. J Ethnopharmacol 30(3):265\\u0026ndash;279\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSharma R, Bolleddu R, Maji JK, Ruknuddin G, Prajapati PK (2021) In-Vitro α-amylase, α-glucosidase inhibitory activities and in-vivo anti-hyperglycemic potential of different dosage forms of guduchi (tinospora cordifolia [willd.] miers) prepared with ayurvedic bhavana process. Front Pharmacol 12:642300\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSherman BT, Hao M, Qiu J, Jiao X, Baseler MW, Lane HC, Imamichi T, Chang W (2022) DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res 50(W1):W216\\u0026ndash;W221\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eShirolkar A, Yadav A, Nale A, Phogat J, Dabur R (2022) Integrated omics analysis revealed the Tinospora cordifolia intervention modulated multiple signaling pathways in hypertriglyceridemia patients-a pilot clinical trial. J Diabetes Metabolic Disorders 21(1):379\\u0026ndash;397\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSpiro MJ, Crowley TJ (1993) Increased rat myocardial type VI collagen in diabetes mellitus and hypertension. Diabetologia 36:93\\u0026ndash;98\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eStenvers DJ, Scheer FA, Schrauwen P, la Fleur SE, Kalsbeek A (2019) Circadian clocks and insulin resistance. Nat Reviews Endocrinol 15(2):75\\u0026ndash;89\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSzklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ (2019) STRING v11: protein\\u0026ndash;protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 47(D1):D607\\u0026ndash;D613\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eSzkudelski T (2001) The mechanism of alloxan and streptozotocin action in B cells of the rat pancreas. Physiol Res 50(6):537\\u0026ndash;546\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eTest No. 423: Acute Oral toxicity - Acute Toxic Class Method (2002) In OECD Guidelines for the Testing of Chemicals, Section 4. OECD. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://doi.org/10.1787/9789264071001-en\\u003c/span\\u003e\\u003cspan address=\\\"10.1787/9789264071001-en\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eUehara S, Muroyama A, Echigo N, Morimoto R, Otsuka M, Yatsushiro S, Moriyama Y (2004) Metabotropic glutamate receptor type 4 is involved in autoinhibitory cascade for glucagon secretion by α-cells of islet of Langerhans. Diabetes 53(4):998\\u0026ndash;1006\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWessel DM, Fl\\u0026uuml;gge UI (1984) A method for the quantitative recovery of protein in dilute solution in the presence of detergents and lipids. Anal Biochem 138(1):141\\u0026ndash;143\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eWorld Health Organization (2021) Fact sheet: Diabetes. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://www.who.int/news-room/fact-sheets/detail/diabetes\\u003c/span\\u003e\\u003cspan address=\\\"https://www.who.int/news-room/fact-sheets/detail/diabetes\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eXu L, Xing M, Xu X, Saadeldeen FS, Liu Z, Wei J, Kang W (2019) Alizarin increase glucose uptake through PI3K/Akt signaling and improve alloxan-induced diabetic mice. Future Med Chem 11(5):395\\u0026ndash;406\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eYang J, Li S, Liu YX (2013) Systematic analysis of diabetes-and glucose metabolism-related proteins and its application to Alzheimer\\u0026rsquo;s disease. 6:615\\u0026ndash;644. \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003e10.4236/jbise.2013.66078\\u003c/span\\u003e\\u003cspan address=\\\"10.4236/jbise.2013.66078\\\" targettype=\\\"DOI\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKotmire S, Desai A, Chougule N (2024) The advances in polyherbal formulation. J Pharmacognosy Phytochemistry 13(1):210\\u0026ndash;221\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eBalkrishna A, Bhattacharya K, Sinha S, Dev R, Srivastava J, Singh P, Varshney A (2022) Apparent hepatotoxicity of Giloy (Tinospora cordifolia): far from what meets the eyes. J Clin Experimental Hepatol 12(1):239\\u0026ndash;240\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eEskandarzadeh M, Esmaeili A, Nikbakht MR, Hitotsuyanagi Y, Shkryl YN, Yadegari G, Khalilifard J, J (2023) Genus Rubia: Therapeutic Effects and Toxicity: A Review. Herb Med J 8(1):34\\u0026ndash;48\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eVerma P, Paswan SK, Chandra G, Gupta A, Rao CV (2022) Hydro alcoholic extract of Holarrhena antidysenterica L. induced toxicity research in experimental animals. Emerging Trends in IoT and Computing Technologies. Routledge, pp 212\\u0026ndash;218\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRekha BC, Tangeti S, Madhavi L, Pathapati RM (2016) Toxicity, Acute and Longterm Anti-Diabetic Profile of Methanolic Extract of Leaves of Pterocarpus Marsupium on Alloxan Induced Diabetic Albino Rats. Pharma Innov 5(7):90 Part B)\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eRaji RO, Muhammad HL, Abubakar A, Maikai SS, Raji HF (2021) Acute and sub-acute toxicity profile of crude extract and fractions of Gymnema sylvestre. Clin Phytoscience 7(1):56\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePatil SG, Bhadane BS, Patil MP, Belemkar S, Patil RH (2016) In-vitro antioxidant activity, acute oral toxicity studies and preliminary phytochemical characterization of the bark extract of Terminalia arjuna (L). J Pharm Nutr Sci 6:15\\u0026ndash;21\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eKarole S, Shrivastava S, Thomas S, Soni B, Khan S, Dubey J, Jain DK (2019) Polyherbal formulation concept for synergic action: a review. J Drug Delivery Ther 9(1\\u0026ndash;s):453\\u0026ndash;466\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eParasuraman S, Thing GS, Dhanaraj SA (2014) Polyherbal formulation: Concept of ayurveda. Pharmacogn Rev 8(16):73\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003ePereira L, Ruiz-Hurtado G, Rueda A, Mercadier JJ, Benitah JP, G\\u0026oacute;mez AM (2014) Calcium signaling in diabetic cardiomyocytes. Cell Calcium 56(5):372\\u0026ndash;380\\u003c/span\\u003e\\u003c/li\\u003e \\u003cli\\u003e\\u003cspan\\u003eUmans L, Serneels L, Overbergh L, Stas L, Van Leuven F (1999) α2-macroglobulin-and murinoglobulin-1-deficient mice: A mouse model for acute pancreatitis. Am J Pathol 155(3):983\\u0026ndash;993\\u003c/span\\u003e\\u003c/li\\u003e\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-proteins-and-proteomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [Journal of Proteins and Proteomics](https://www.springer.com/journal/42485)\",\"snPcode\":\"42485\",\"submissionUrl\":\"https://submission.nature.com/new-submission/42485/3\",\"title\":\"Journal of Proteins and Proteomics\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false},\"keywords\":\"Antidiabetic activity, Streptozotocin, Polyherbal formulation, Serum proteomics, Glibenclamide\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4694505/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4694505/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"Proteomics have proven advantage in drug and disease physiology characterization. Here the polyherbal formulation was administered daily via oral gavage in two groups of Six Sprague Dawley diabetic rats at the doses of 250 mg/kg and 500 mg/kg body weight for 21 days to understand its antidiabetic potential with proteomics approach. Blood sugar levels were monitored weekly during experimentation. The concurrent control group receiving 10 mL/kg water was also maintained. Rats were examined regularly for signs of toxicity and mortality and underwent detailed clinical examinations prior to initiation and weekly thereafter. Body weight and food consumption were recorded weekly. The anti-hyperglycaemic effect of the formulation was estimated from blood glucose levels weekly. There was no observed mortality or adverse clinical signs among the rats exposed to the standard drug and formulation. Streptozotocin caused a significant weight loss in rats, while treatment with formulation at 250 and 500 mg/kg b.w. concentrations and Glibenclamide as a standard drug; restrained the decrease in body weight. The streptozotocin-induced diabetic rats exhibited a sharp elevation in blood glucose levels. The blood glucose levels were significantly lowered in a dose dependent manner post formulation treatment, in comparison to the control group. Treatment with formulation, standard, and streptozotocin did not induce any remarkable gross pathological alterations in any of the organs/tissues of rats. In proteomics analysis, in formulation treatment groups ECM and Circadian entrainment pathways were activated which are in line with the objective of normalization of altered metabolism in diabetes.\",\"manuscriptTitle\":\"Proteomics based evaluation of the antidiabetic activity of a polyherbal formulation in Streptozotocin-induced hyperglycemia in rats\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-07-31 09:51:02\",\"doi\":\"10.21203/rs.3.rs-4694505/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2024-09-19T18:54:57+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2024-09-16T11:38:37+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"222484785971700708123211220933174241872\",\"date\":\"2024-09-09T04:25:10+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2024-09-05T10:18:07+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2024-07-11T18:43:47+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2024-07-08T10:28:29+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"Journal of Proteins and Proteomics\",\"date\":\"2024-07-06T01:16:15+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"journal-of-proteins-and-proteomics\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"\",\"sideBox\":\"Learn more about [Journal of Proteins and Proteomics](https://www.springer.com/journal/42485)\",\"snPcode\":\"42485\",\"submissionUrl\":\"https://submission.nature.com/new-submission/42485/3\",\"title\":\"Journal of Proteins and Proteomics\",\"twitterHandle\":\"\",\"acdcEnabled\":true,\"dfaEnabled\":true,\"editorialSystem\":\"stoa\",\"reportingPortfolio\":\"Springer Hybrid\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":false}}],\"origin\":\"\",\"ownerIdentity\":\"2263472b-fe79-4a06-a401-01dfff033a45\",\"owner\":[],\"postedDate\":\"July 31st, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-06-13T11:38:31+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-07-31 09:51:02\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-4694505\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-4694505\",\"identity\":\"rs-4694505\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}