A Study on the Correlation Between intestinal flora Characteristics and Serum Zinc and Iron Levels in Paediatric Patients with Mycoplasma pneumoniae pneumonia

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Methods Faecal and serum samples were collected from 30 children with M. pneumoniae pneumonia (MPP group), 30 children with non-M. pneumoniae pneumonia (NMP group), and 30 healthy children (N group) who met the study criteria and were treated at our hospital between November 2024 and March 2025. These samples underwent 16S rRNA sequencing and trace element detection analyses. Results Alpha diversity showed no significant differences ( P > 0.05). Beta diversity analysis revealed significant intergroup differences ( P < 0.05). At the phylum level, all three groups were dominated by Firmicutes , Bacteroidetes , Actinobacteria , and Proteobacteria . The MPP group exhibited the lowest abundance of Firmicutes and the highest abundance of Bacteroidetes . At the genus level, the MPP group showed higher abundances of Bacteroides , Enterococcus , and Escherichia-Shigella compared to the control group. Analysis of intestinal flora differences revealed that the abundances of Prevotella and Lachnoclostridium in the MPP group were higher than those in both the NMP and N groups, whereas the abundance of Enterococcus was higher than that in the N group ( P < 0.05). The NMP group exhibited higher abundances of Eubacterium , Anaerostipes , and Collinsella than the MPP and N groups ( P < 0.05). The N group demonstrated higher abundances of Roseburia , Lachnospiraceae , and Subdoligranulum than the MPP and NMP groups ( P < 0.05). Blood zinc and iron levels were lower in the MPP group than in the NMP and N groups. The heatmap of intestinal flora correlations with clinical parameters showed positive associations between Faecalibacterium , Parabacteroides , and Blautia with blood zinc and iron levels. Among these, the correlation between Parabacteroides and blood zinc levels was statistically significant (r = 0.370, P < 0.05). Escherichia-Shigella and Intestinibacter showed negative correlations with serum zinc and iron levels. Conclusion Paediatric patients with MPP exhibit disrupted intestinal flora composition alongside reduced serum zinc and iron levels, with specific bacterial genera correlating with alterations in serum zinc and iron concentrations. 16S rRNA children iron intestinal flora M. pneumoniae pneumonia zinc Figures Figure 1 Figure 2 Introduction Mycoplasma pneumoniae (MP) is a common pathogen that causes respiratory infections in children and adolescents. M. pneumoniae pneumonia (MPP) is an acute respiratory disease caused by MP infection, typically observed in children aged five years and older. It represents a major proportion of community-acquired pneumonia, accounting for up to 40% of cases17[ 1 ]. Globally, epidemics of mycoplasma infection occur approximately every 35 years, with each epidemic lasting about 1–2 years[ 2 ]. The adhesive properties and toxins produced by MP directly damage ciliated epithelial cells and disrupt immune function. This leads to reduced immunity and slower recovery in children with MPP. In China, poor response to macrolide therapy in some patients and recurrent mycoplasma epidemics impose a significant burden on society and families[ 3 , 4 ]. The gut is the largest immune organ in the body and functions as a complex microecological system. The gut-lung axis serves as a pivotal interface for interactions between the pulmonary and intestinal microbiota. Consequently, the intestinal flora plays a crucial role in immune responses to respiratory infections. Pathogenic respiratory infections can induce gut dysbiosis, and conversely, alterations in the intestinal flora may also influence the prognosis of respiratory diseases. Trace elements are substances present in concentrations below 0.01% of body weight; they participate in physiological metabolism and influence immune system function. Zinc and iron are two essential trace elements with relatively high concentrations and critically important functions in the human body, playing pivotal roles in childhood growth and development, as well as in maintaining immune function. MP infection is associated with trace element imbalances in the body [ 5 ]. Therefore, this study aimed to examine the correlation between intestinal flora characteristics and serum zinc and iron levels in children with MPP from a gut microbiome perspective. Research objects and methods The experimental group (MPP group, 30 cases) comprised paediatric patients diagnosed with M. pneumoniae pneumonia who met the study criteria and were admitted to the 940th Hospital of Joint Logistics Support Force of People's Liberation Army Department of Pediatrics between November 2024 and March 2025. A control group consisting of children with non-M. pneumoniae pneumonia (NMP group, 30 cases) and healthy children from the paediatric health clinic (N group, 30 cases) were selected concurrently. The inclusion criteria were as follows: (1) age 3–14 years; (2) good patient compliance and complete clinical records; and (3) parental informed consent obtained. (4) Experimental group: met the consensus criteria from the 2023 Pediatric Mycoplasma Pneumonia Diagnosis and Treatment Guidelines[ 6 ]: a) Physical examination revealed acute respiratory infection symptoms (fever, cough, or wheezing) with infiltrates on chest imaging; b) Single-serum MP antibody titer ≥ 1:160 (PA method); seroconversion with a fourfold or greater increase in MP antibody titer between two serum samples during the disease course; c) Positive MP-DNA or RNA detection; (5) Control groups: NMP group: a. Physical examination revealing acute respiratory infection symptoms (fever, cough, or wheezing) with infiltrates visible on chest imaging. Negative MP DNA or RNA detection. N group: No history of respiratory diseases, such as pneumonia or asthma, within the preceding month. The exclusion criteria were as follows: (1) patients with measles, pertussis, varicella, tuberculosis, or other infectious diseases; (2) patients with underlying conditions such as congenital heart disease, renal disease, or immunodeficiency; (3) paediatric patients treated with antibiotics, corticosteroids, intestinal flora agents, or other immunosuppressive agents within the past month; and (4) inadequate stool sample collection or insufficient sample data for analysis. All children and their families provided informed consent, and the study was approved by the hospital ethics committee (2024KY22213). Methods Sample and Data Collection (1) Clinical data collection: ① Basic information: gender, age, mode of delivery, height, weight, feeding method; ② Laboratory parameters: complete blood count, procalcitonin (PCT), interleukin-6 (IL-6), C-reactive protein (CRP), biochemical indicators, etc. (2) Faecal Specimen Collection: ① Fresh faecal samples (3–5 g) were collected within 24 hours of admission or prior to antibiotic treatment and placed into sterile centrifuge tubes containing preservation solution, thoroughly mixing the faeces with the solution; ② Unique codes were assigned to collected samples, which were stored at − 80°C within two hours; ③ The original stool samples were shipped on dry ice to the testing company for intestinal flora analysis. (3) Peripheral blood collection: 0.5 mL of peripheral blood was collected in an anticoagulant tube within 24 h of the child's admission or on the day of their visit to our paediatric health clinic. A qualified professional conducted blood zinc and iron level testing in accordance with the relevant testing protocols. intestinal flora 16S Diversity Sequencing Genomic DNA was extracted from the samples using the MagPure Soil DNA LQ Kit (Magan) according to the manufacturer's protocol. DNA concentration and purity were assessed using NanoDrop 2000 (Thermo Fisher Scientific, USA) and agarose gel electrophoresis. The extracted DNA was stored at -20°C. Using the extracted genomic DNA as a template, PCR amplification of the bacterial 16S rRNA gene was performed with barcoded specific primers and Takara Ex Taq High Fidelity Enzyme. The V3–V4 variable region of the 16S rRNA gene was amplified using the universal primers 343F (5’-TACGGRAGGCAGCAG-3’) and 798R (5’-AGGGTATCTAATCCT-3’) for bacterial diversity analysis. PCR products were detected via agarose gel electrophoresis, and qualified products were sequenced using the Illumina NovaSeq 6000 platform. Sequencing was performed by Shanghai Ouyi Biotechnology Co. Ltd. Bioinformatics Analysis and Statistical Data Analysis The raw data were in FASTQ format. Following sequencing, Cutawv-xsrnvirxdapt software was first employed to trim the primer sequences from the raw data sequences. Subsequently, DADA2 was used to perform quality filtering, denoising, assembly, and de-chimera analysis on the qualified paired-end raw data using the default QIIME 2 (2020.11) parameters, yielding representative sequences and ASV abundance tables. Following the selection of representative sequences for each ASV using the QIIME 2 software package, all representative sequences were annotated by alignment against the Silva database (version 138). Species annotation was performed using the q2-feature-classifier software with the default parameters. Alpha and beta diversity analyses were conducted using the QIIME 2 software. Alpha diversity was assessed using indices including Chao1 and Shannon diversity. Beta diversity was evaluated using unweighted UniFrac principal coordinate analysis (PCoA) based on unweighted UniFrac distance matrices. Kruskal–Wallis tests were used for differential analysis. LEfSe was used for the differential analysis of species abundance profiles. Blood Zinc and Iron Content Detection Peripheral blood samples were collected from the children, diluted, and directly analyzed using atomic absorption spectroscopy. Statistical Analysis Data were organized and analyzed using SPSS 26.0 software. For normally distributed quantitative data, the results are presented as mean ± standard deviation (x̄±s). Comparisons among the three groups were performed using one-way analysis of variance (ANOVA). For non-normally distributed data, results are presented as median (P 25 , P 75 ), with comparisons conducted using the Kruskal–Wallis test. Count data are presented as case numbers and percentages (%). Intergroup comparisons were performed using theχ²test or Fisher's exact probability test. The significance level was set at α = 0.05, with P < 0.05 indicating statistically significant differences. Results General Clinical Data This study included three groups of subjects, each comprising 30 patients. There was a statistically significant difference in serum zinc levels among the three groups ( F = 5.712, P 0.05) ( Table 1 ). Table 1 Comparison of General Characteristics Among the Three Groups of Children Variables MPP group(n = 30) NMPgroup(n = 30) Ngroup(n = 30) F value P value Gender 0.307 0.737 Male(case) 12 15 13 Female(case) 18 15 17 Age(y) 6.10 ± 2.55 5.50 ± 1.66 5.63 ± 1.54 0.768 0.467 Hight(cm) 120.46 ± 18.72 115.87 ± 13.93 112.57 ± 9.59 2.225 0.114 Weight(Kg) 22.91 ± 9.08 21.05 ± 8.63 19.53 ± 3.93 1.498 0.229 Zinc content(mmol/L) 81.31 ± 13.18 85.10 ± 8.12 90.27 ± 8.91 5.712 0.005 Iron content(mmol/L) 8.94 ± 0.81 9.04 ± 0.82 9.28 ± 0.66 1.597 0.208 Characteristics of intestinal flora Changes Alpha Diversity Analysis To compare the richness and evenness of the intestinal flora across the three sample groups, we assessed microbial diversity and distribution uniformity by calculating various alpha indices. The Chao1 and ACE indices focus on species richness: higher Chao1 values indicate greater total species abundance, whereas higher ACE values reflect greater overall diversity. The Shannon and Simpson indices reflect microbial diversity. Higher species diversity and more even distribution correspond to larger Shannon index values; conversely, a higher Simpson's index indicates greater microbial diversity. Goods Coverage reflects sequencing depth: values closer to 1 indicate sufficient sequencing depth to cover all species within the sample, signifying higher microbial diversity. The PD index represents the evolutionary relationships of species. A higher index value signifies that the microbial community encompasses a broader and more dispersed evolutionary lineage, that is, more distantly related species, serving as a crucial dimension for assessing gut microbiome health. The results of the Kruskal–Wallis test ( Table 2 ) indicate that the differences in intestinal flora among the three sample groups for the Chao1, Shannon, Simpson, ACE, observed species, Goods_coverage, and PD indices did not reach statistical significance ( P = 0.443, P = 0.238, P = 0.255, P = 0.423, P = 0.325, P = 0.766, and P = 0.385), suggesting limited microbial differences between groups, potentially constrained by sample size limitations. Future studies with larger sample sizes are required to validate these findings. Although no significant differences in alpha diversity were observed among the three groups, an in-depth analysis of each index revealed that children with MPP exhibited lower richness and evenness of intestinal flora than the control group. Table 2 Alpha diversity analysis of intestinal flora in children in three groups MPP group NMP group N group H value P value Chao 1 210.52(115.30,229.90) 238.43(121.10,226.88) 225.70(141.40,240.88) 1.62 0.443 Shannon 4.84(3.26,5.41) 4.44(3.74,5.40) 5.03(4.42,5.90) 2.873 0.238 Simpson 0.84(0.77,0.95) 0.83(0.83,0.95) 0.90(0.89,0.97) 2.981 0.255 ACE 208.54(110.85,227.49) 238.29(117.45,225.98) 225.84(145.39,242.87) 1.720 0.423 Observed species 202.72(107.70,220.23) 227.51(113.15,217.30) 217.14(137.25,186.65) 2.087 0.352 goods_coverage 1.00(1.00,1.00) 1.00(1.00,1.00) 1.00(1.00,1.00) 0.534 0.766 PD_whole_tree 22.35(15.48,27.23) 24.06(14.84,23.37) 24.23(15.88,26.97) 1.907 0.385 Beta Diversity Analysis The Unweighted UniFrac distance algorithm is a core method for β-diversity analysis, used to compare the phylogenetic structures of microbial communities across different samples. This study employed Unweighted UniFrac-based NMDS analysis to assess species diversity, that is, β-diversity, among the three sample groups. NMDS analysis is a dimension-reduction visualization technique based on distance matrices, enabling a clear depiction of similarities or differences in the overall microbial community structures across samples. The stress value in the NMDS analysis serves as an indicator of the accuracy of the true distances between samples. Generally, stress < 0.2 yields results with good interpretability; stress values ranging from 0.05 to 0.2 indicate good sample reliability; when stress < 0.05, it signifies excellent representativeness of the samples. NMDS analysis revealed (Fig. 1a) a stress value of 0.098, indicating good sample quality and reliable results across the three groups in this experiment. Both analytical methods demonstrated phylogenetic-level differences in the intestinal flora composition among the three groups ( P < 0.05). intestinal flora Structural Analysis Analysis of phylum-level composition and relative abundance in the MPP, NMP, and N groups (Fig. 1b) revealed that Firmicutes , Bacteroidetes, Actinobacteria , and Proteobacteria dominated all three groups. The sum of the relative abundances of these phyla accounted for over 98% of the community richness. The Firmicutes phylum exhibited higher relative abundance across all three study groups, accounting for 39.4%, 46.9%, and 50.0% in the MPP, NMP, and N groups, respectively, with the lowest relative abundance observed in the MPP group. The abundance of the Bacteroidetes phylum was significantly higher in the MPP group (32.6%) than in the NMP (20.3%) and N groups (27.4%). The intestinal flora composition at the genus level exhibited significant differences among the three groups of children (Fig. 1c) , with the relative abundance of the same genus varying across groups. The top 10 genera with abundance levels exceeding 1% in the MPP group were, in descending order: Bacteroides , Bifidobacterium , Faecalibacterium , Parabacteroides , Escherichia-Shigella , Enterococcus , Blautia , Intestinibacter , Streptococcus , and Subdoligranulum . Analysis of intestinal flora Composition Differences Differential species boxplot analysis (Fig. 1d) screened the top 10 genus-level species abundance data across the three paediatric groups based on P-values. The results indicated that the abundance of Prevotella and Lachnospiraceae was higher in the MPP group than in the NMP and N groups, whereas the abundance of Enterococcus exceeded that of the N group. Conversely, the abundance of Eubacterium , Anaerostipes , and Collinsella was higher in the NMP group than in the MPP and N groups. The N group exhibited higher abundances of Roseburia , Lachnospiraceae , and Subdoligranulum than the MPP and NMP groups. Further analysis of intergroup microbial differences using P-values indicated that P < 0.05 signified significant differences between groups, while P < 0.01 indicated highly significant differences ( Table 3 ). Table 3 The relative abundance of intestinal flora levels was compared Bacterial Genera MPP group NMP group N group H value P value Enterococcus 0.037(0.000,0.008) 0.079(0.002,0.014) 0.002(0.000,0.001) 10.847 0.004 Subdoligranulum 0.015(0.000,0.019) 0.009(0.000,0.018) 0.021(0.003,0.034) 6.821 0.033 Roseburia 0.002(0.000,0.001) 0.006(0.000,0006) 0.028(0.001,0.052) 21.164 <0.0001 Fusicatenibacter 0.011(0.000,0.005) 0.009(0.000,0.016) 0.015(0.002,0.019) 10.256 0.006 Lachnoclostridium 0.018(0.002,0.018) 0.014(0.002,0.016) 0.004(0.001,0.005) 8.256 0.016 Eubacterium 0.005(0.000,0.004) 0.018(0.000,0.033) 0.011(0.001,0.016) 13.493 0.001 Anaerostipes 0.007(0.000,0.006) 0.011(0.000,0.003) 0.010(0.001,0.12) 7.904 0.019 Prevotella 0.016(0.001,0.003) 0.003(0.001,0.003) 0.007(0.000,0.001) 13.652 0.001 Lachnospiraceae 0.006(0.000,0.004) 0.003(0.000,0.003) 0.016(0.001,0.011) 8.960 0.011 Collinsella 0.002(0.000,0.001) 0.015(0.000,0.019) 0.003(0.000,0.005) 6.716 0.035 intestinal flora LEfSe Analysis To identify the most significant intestinal flora biomarkers between groups, linear discriminant analysis Effect Size (LEfSe) analysis was conducted. This analytical tool is designed to discover and interpret biomarkers in high-dimensional data, enabling comparisons between two or more groups of samples. It emphasizes both statistical significance and biological relevance, identifying biomarkers that exhibit statistical differences between groups. LEfSe analyzes all hierarchical levels (phylum, class, order, family, genus, and species) collectively, without distinguishing between levels. The bar chart primarily displays species with linear discriminant analysis (LDA) values exceeding the preset threshold, that is, statistically significant biomarkers. The length of each bar represents the LDA value, indicating the degree of influence exerted by the significantly different species across groups. Analysis of the distinct microbial communities between the three groups revealed 21 differentially abundant species (Fig. 1e). Using an LDA SCORE threshold of>4, the following were identified: Actinobacteriota (LDA = 4.55), o_Bacteroidales (LDA = 4.85), Enterococcaceae (LDA=5.56), Enterococcus (LDA = 4.56), and g_Roseburia (LDA = 4.09) were significantly enriched ( P < 0.05). The branch evolution diagram (Fig. 1f) displays significantly different species with relatively higher abundance in different groups. Analysis revealed the enrichment of two genera at the genus level within the MPP group: Prevotella and Lachnoclostridium , while Bacteroidales was enriched at the order level. The NMP group exhibited enrichment of three genera at the genus level: Enterococcaceae , Collinsella , and Eubacterium . At the order level, enrichment was observed in Coriobacteriia . At the family level, enrichment was observed in the Coriobacteriaceae and Enterococcaceae families. Random Forest Analysis The random forest algorithm enables the accurate and efficient classification of microbial community samples while identifying ASVs that distinguish intergroup differences. This study employed random forest analysis on the top 30 genera based on relative abundance (Fig. 1g) . The results revealed the following ranking of important genera across the three sample groups: Prevotella , Eubacterium hallii group (an unclassified Eubacterium genus ), Roseburia , Fusicatenibacter , and Lactobacillus . Figure 1 Analysis of changes in the intestinal flora in the three groups of children. a NMDS analysis plots for all three groups; b Phylum-level analysis plots for all three groups; c Genus-level analysis plots for all three groups; d Box plots comparing relative abundance at the genus level across intestinal flora for all three groups, with different colors representing different sample groups and the y-axis showing log-transformed relative abundance values; e LEfSe analysis depicting LDA SCORE > 4 differential microbiota; f Phylogenetic tree of the three groups, where orange denotes enrichment in the MPP group, green in the NMP group, purple in the N group, and yellow nodes indicate no significant differences. Node diameter correlates positively with relative abundance; each layer of nodes represents phylum, class, order, family, and genus from innermost to outermost; g Importance-point plot: the horizontal axis represents importance metrics, the vertical axis displays genus names ranked by importance, and the right-hand bar chart shows relative genus abundance. Heatmap of Correlation Between intestinal flora and Clinical Laboratory Indicators Based on the relative abundance of microorganisms in the samples and the corresponding clinical indicator data, Pearson's correlation analysis was used to assess the relationship between the two. Analysis at the top 15 genus level (Fig. 2) revealed that Faecalibacterium , Parabacteroides , and Blautia exhibited positive correlations with serum zinc levels. Among these, Parabacteroides demonstrated a statistically significant correlation with serum zinc (r = 0.370, P < 0.05). Escherichia-Shigella and Intestinibacter exhibited negative correlations with blood zinc levels, with Escherichia-Shigella demonstrating a statistically significant association (r = -0.399, P < 0.05). Faecalibacterium , Parabacteroides , and Blautia were positively correlated with serum iron levels, whereas Escherichia-Shigella , Intestinibacter , Lachnoclostridium , and Subdoligranulum (a rare genus of small cocci) were negatively correlated with serum iron levels. Furthermore, this study also found that lymphocyte counts were positively correlated with Bacteroides (r = 0.424, P < 0.05) and negatively correlated with Subdoligranulum (r = -0.389, P < 0.05) and Alistipes (r = -0.371, P < 0.05). Neutrophil counts were positively correlated with Muribaculaceae (r = 0.579, P < 0.01). The Neutrophil-to-Lymphocyte Ratio (NLR) showed positive correlations with Lachnoclostridium (r = 0.449, P < 0.05), Muribaculaceae (r = 0.440, P < 0.05), and Subdoligranulum (r = 0.452, P < 0.05). PCT was positively correlated with Muribaculaceae (r = 0.651, P < 0.01). CRP (r =-0.369, P < 0.05) and CRP-ALB (r=-0.374, P < 0.05) levels were negatively correlated. LDH demonstrated a positive correlation with Alistipes (r = 0.452, P < 0.05). Figure 2 Correlation between intestinal flora and clinical laboratory indicators. The horizontal axis represents the top 15 bacterial genera, and the vertical axis represents the clinical laboratory indicators. Red indicates a positive correlation, and blue denotes a negative correlation. * P < 0.05, ** P < 0.01. Discussion The diversity and abundance of intestinal flora undergo dynamic changes, forming an adult-like intestinal flora structure by age 3, which then enters a state of relative stability [ 7 ]. This microbial homeostasis facilitates the development of the immune system, metabolic processes, and the establishment of internal environmental stability. Probiotic-dominant intestinal flora supports immune system maturation. Numerous studies have indicated [ 8 , 9 ] that the intestinal flora plays a pivotal role in immune responses to respiratory infectious diseases, with respiratory pathogen infections capable of altering the composition and function of the intestinal flora. Currently, research on MP infection and pulmonary disease remains relatively scarce, with a primary focus on bacterial and viral studies. Although trace elements exist in minute quantities within the body, they play a crucial role in maintaining physiological functions. Deficiencies or imbalances in zinc and iron are also associated with alterations in the intestinal flora. Changes in intestinal flora Characteristics in Children with MPP This study employed alpha diversity analysis, which revealed no statistically significant differences in intestinal flora richness or diversity among the three groups of children. However, children in the MPP group exhibited lower intestinal flora richness and evenness than those in the control group, as measured by both the Chao1 and Shannon indices, suggesting dysbiosis in MPP patients. Multiple studies have demonstrated that children with MP infection exhibit lower microbiota richness and diversity than healthy controls [ 10 , 11 ]. A study by Wang et al. showed that Mycoplasma infection reduced gut microbial diversity compared to non-Mycoplasma-infected children, a finding consistent with the present study[ 12 ]. These studies collectively indicate an altered intestinal flora composition in children with MPP, manifested as reduced diversity and richness of intestinal flora. Beta diversity analysis revealed significant differences in the overall intestinal flora structure among the three groups. In all three groups, the dominant phyla were Firmicutes , Bacteroidetes , Actinobacteria , and Proteobacteria , consistent with previous reports[ 13 ]. Relative phylum-level abundances differed among the groups, with the MPP group exhibiting the lowest relative abundance of Firmicutes and the highest relative abundance of Bacteroidetes . One study demonstrated an increased relative abundance of Escherichia-Shigella , Bifidobacterium , and Streptococcus , alongside a reduced abundance of Bacteroides , Faecalibacterium , and Ruminococcus in the intestinal flora of children with community-acquired pneumonia [ 14 ]. A study by Pang Minghui et al. showed that conducted a comparative analysis of intestinal flora characteristics between children with M. pneumoniae pneumonia (MPP) and Streptococcus pneumoniae pneumonia , revealing a significantly increased abundance of Bacteroidetes and a reduced abundance of Firmicutes in MPP patients, consistent with the present findings [ 15 ]. Genus-level analysis indicated a higher abundance of Bacteroides in the intestinal flora of children with MPP. Research has demonstrated that the Bacteroides genus can alter intestinal permeability and damage the intestinal epithelium [ 16 ], thereby increasing the risk of allergies and other diseases. Bacteroides play a crucial role in the synthesis of short-chain fatty acids (SCFAs), a key class of metabolites produced by gut microbes fermenting carbohydrates, including butyrate, propionate, and acetate, which influence gut health through energy supply, signalling, and immune regulation. When MP infection induces lung injury, SCFAs may prevent severe mycoplasma pneumonia through immune modulation [ 17 ]. Bacteroides are opportunistic pathogens. In this study, children with MPP exhibited elevated Bacteroides abundance in their intestinal flora. The compromised immune status during MPP facilitates the proliferation of opportunistic pathogens, which exacerbate inflammation by compromising the intestinal epithelium. This suggests that pathogenic bacteria participate in the disease process of MP infection via the lung-gut axis. This study identified significant differences in intestinal flora composition among the three groups of children. The MPP group predominantly harboured Prevotella , Enterococcus , and Clostridium , with markedly reduced levels of Roseburia . Prevotella is one of the dominant commensal bacteria in the lower respiratory tract, inducing regulatory T-cell differentiation and suppressing inflammatory responses. Upon M. pneumoniae infection, Prevotella may inhibit inflammation through metabolites such as short-chain fatty acids, thereby mitigating tissue damage [ 18 ]. Enterococcus is an opportunistic pathogen. Our findings indicate its higher abundance in the intestinal flora of children with MPP compared to healthy children, consistent with the conclusions of Shou et al. [ 19 ]. We further observed that the relative abundance of Enterococcus correlated positively with inflammatory markers, including the neutrophil-to-lymphocyte ratio, lymphocyte ratio, and C-reactive protein (CRP). This suggests that opportunistic pathogens such as Enterococcus participate in the inflammatory response in children with MPP, potentially influencing their prognosis. The abundance of Enterococcus faecalis , Bifidobacterium , Lactobacillus , and Clostridium butyricum in the intestines of children with MPP was lower than that in healthy children. This study also compared the intestinal flora of children with MPP with and without wheezing, finding significantly reduced levels of Enterococcus faecalis and Clostridium butyricum in children with wheezing[ 20 ]. Domestic researchers categorised children with MPP into acute-phase and recovery-phase groups. Results indicated that the relative abundances of Bacteroides, Lactobacillus, Bifidobacterium , and Peptostreptococcus were lower in both acute-phase and recovery-phase children with MPP compared to healthy controls [ 21 ]. This demonstrates intestinal flora dysbiosis in children with MPP, with the degree of microbiota reduction holding some value for distinguishing between acute-phase and recovery-phase MPP. Clostridium and Enterococcus exhibited higher relative abundance in children with MPP compared to healthy controls, consistent with findings by Wei et al.[ 22 ]. While that study reported decreased abundance of pathogenic bacteria such as Escherichia - Shigella alongside increased Roseburia abundance following probiotic treatment in children with MPP, the present study demonstrates lower Roseburia abundance in MPP patients relative to controls. Roseburia constitutes beneficial intestinal flora that further protects the intestinal mucosal barrier by reducing pro-inflammatory cytokine IL-17 production [ 23 ]. Research shows that increased Roseburia abundance following probiotic treatment in children with MPP, thus differing from the present findings[ 22 ]. Studies indicate that children with severe pneumonia exhibit markedly elevated gut dysbiosis indices and significantly reduced Roseburia abundance compared to those with mild pneumonia, suggesting an association between decreased Roseburia abundance and systemic inflammatory responses[ 24 ]. These findings suggest that children with MPP exhibit reduced abundance of beneficial bacteria and increased abundance of opportunistic pathogens. These differential bacterial genera may represent key therapeutic targets for future MPP treatments. The precise mechanisms linking M. pneumoniae infection to intestinal flora alterations remain incompletely elucidated, warranting further investigation at the metabolic and metagenomic levels. Blood Zinc and Iron Levels in MPP Paediatric Patients Iron is the most abundant trace element in the body, serving as a vital component of haemoglobin and myoglobin. It is also essential for maintaining cellular function and supporting growth and development. Iron deficiency can impair immune function, whereas excessive iron may induce oxidative stress and increase susceptibility to pathogen infection. This study observed reduced blood zinc and iron levels in children with MPP, suggesting immune dysfunction. Research indicates that serum iron levels in paediatric pneumonia patients are lower than in healthy controls, with more pronounced reductions in severe pneumonia cases [ 25 ]. MP infection may disrupt paediatric iron homeostasis via pro-inflammatory mediators IL-6 and TNF-α. As a result, iron depletion in children with RMPP was markedly less pronounced than in typical MPP cases, suggesting that reduced serum iron levels correlate with MP infection [ 26 ]. Supplementation therapy was found to improve clinical outcomes. Zinc is an essential trace element in the body, second only to iron in abundance. Zinc deficiency reduces the numbers of T lymphocytes and B lymphocytes, thereby diminishing the body's ability to resist pathogens and increasing susceptibility to disease [ 27 ]. The immune system is highly sensitive to fluctuations in zinc levels. Severe zinc deficiency affects multiple organ systems, including the immune, central nervous, and skeletal systems, while marginal zinc deficiency is also associated with immune dysfunction. Zinc deficiency may increase mortality risks from diarrhoea and pneumonia [ 28 , 29 ], with children under five being most affected by zinc-deficient diarrhoea and pneumonia [ 30 ]. A randomised controlled trial demonstrated that prophylactic zinc supplementation reduced the incidence of diarrhoea by 13% and pneumonia by 19% [ 31 ]. Findings from Rerksuppaphol et al. [ 32 ] indicate that zinc supplementation shortens hospital stays for paediatric pneumonia patients, accelerates the resolution of pneumonia, and restores blood oxygen saturation and body temperature to normal ranges, thereby improving treatment efficacy. An international study involving 94 children with severe pneumonia, aged between 2 months and 2 years, found that the zinc supplementation group experienced slightly shorter cough duration and recovery time compared to the control group [ 33 ]. However, a trial targeting children aged 3–60 months with pneumonia indicated that zinc supplementation had no effect on the duration of the resolution phase or hospital stay [ 34 ]. Excessive dietary zinc supplementation alters intestinal flora composition and reduces resistance to Clostridium difficile, potentially increasing infection risk through heightened pathogen virulence and altered immune responses [ 35 ]. Discrepancies in these findings may stem from variations in the ages of study subjects and zinc formulations, necessitating further validation in subsequent research. Correlation between intestinal flora Characteristics and Serum Zinc or Iron Levels in MPP Paediatric Patients The gut-lung axis theory suggests that both the mucosal immune system and the intestinal flora are key modulators of systemic immune function. Alterations in the immune system induced by MP also influence the composition of the intestinal flora [ 36 ]. Notably, our findings indicate that certain beneficial bacteria, such as Faecalibacterium , Parabacteroides , and Blautia , are positively correlated with serum zinc and iron levels, whereas potentially pathogenic bacteria like Escherichia-Shigella and Intestinibacter display negative correlations. Zinc influences the intestinal flora by maintaining intestinal epithelial barrier integrity and reducing mucosal inflammation. Additionally, it plays a role in immune regulation by enhancing T-cell function, promoting mucosal immunity, mitigating oxidative stress responses, and facilitating recovery from infection. Zinc also contributes to the structural remodeling of the intestinal flora by fostering the proliferation of short-chain fatty acid–producing bacteria, such as Faecalibacterium , which modulate host immune responses via fatty acid metabolic pathways. Furthermore, short-chain fatty acids inhibit the carbohydrate metabolic pathways of pathogenic bacteria by suppressing the function of membrane transport phosphotransferase systems (PTS) [ 37 ]. Research further confirms that zinc regulates the relative abundance of beneficial bacteria like Parabacteroides and promotes the repair of the intestinal mucosal barrier [ 38 ]. The intestinal flora, in turn, modulates iron levels by regulating intestinal iron absorption, while iron content reciprocally affects microbial composition and metabolism. Disrupted iron metabolism can impair specific microbial functions, thereby influencing clinical treatment outcomes and prognosis, although appropriate interventions may mitigate these effects [ 39 ]. Moreover, Blautia increases intestinal permeability to iron, further influencing iron absorption [ 40 ]. In summary, the interactions between the intestinal flora and blood zinc/iron levels play an integral role in maintaining intestinal health. Conclusion Pediatric patients with M. pneumoniae pneumonia exhibit decreased blood levels of zinc and iron, concomitant with dysbiosis of the intestinal flora. Zinc and iron are known to regulate the relative abundance of beneficial and pathogenic bacteria in the gut, thereby modulating pulmonary inflammatory responses through the lung-gut axis. Currently, macrolide antibiotics remain the cornerstone of MPP treatment, although the emergence of drug resistance poses a significant challenge. Enhancing innate immunity through the modulation of intestinal flora and nutritional status may represent a novel strategy to reduce disease burden. Therefore, in managing MPP, it is imperative to prioritize not only conventional anti-mycoplasma therapy but also a comprehensive assessment and intervention targeting trace element levels and gut microbial composition. It is important to note that this study is a single-center investigation; the representativeness of the intestinal flora data obtained via 16S rDNA high-throughput sequencing may be limited. Future research should therefore include multicenter, large-sample studies to improve the generalizability of the findings. Declarations Ethics approval and consent to participate This study was approved by the Ethics Review the 940th Hospital of Joint Logistics Support Force of People's Liberation Army Department of Pediatrics (2024KY22213). Informed consents to participate in the study have been obtained from participants (or their parent or legal guardian).All procedures performed were in accordance with the ethical standards of the institutional research board in accordance with Helsinki declaration 2013. Consent for publication Not Applicable. Clinical trial number not applicable. No additional interventions were implemented for the patients; all testing items were based on an expanded analysis of routine clinical diagnosis and treatment needs. Although this experiment was not subjected to clinical registration, we place a high value on the ethical compliance of the study; the study protocol has undergone comprehensive review by the ethics committee and has received formal approval. Conflict of interest No financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article. Funding This work was supported by the Gansu Provincial Joint Research Fund (No. 25JRRA1185) and Natural Science Foundation of Gansu Province(23JRRA725). Author Contribution XY and DYL contributed equally to this study. XY conceptual research, design experimental schemes, and write the first draft of the paper; DYL visualizes data, manages and designs protocols; LH and YYL data management and provision software; HTL and WX collect clinical data, collect samples, collate and statistical data; GLM validates the analysis results, reviews papers and supervises experimental research progress. LYM provides key experimental material, guides the entire research project, oversees research progress, and reviews and edits papers. Acknowledgements We would like to acknowledge all patients and guardians who decided to participate to the study. We thank all the team of Shanghai Ouyi Biotechnology Co. Data Availability The raw sequencing data generated in this study can be accessed in the SRA database by searching PRJNA1335416 on NCBI References Sun Y, Li P, Jin R, et al. 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Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 Jan, 2026 Read the published version in BMC Pediatrics → Version 1 posted Editorial decision: Revision requested 11 Nov, 2025 Reviews received at journal 01 Nov, 2025 Reviews received at journal 31 Oct, 2025 Reviewers agreed at journal 30 Oct, 2025 Reviewers agreed at journal 30 Oct, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers invited by journal 27 Oct, 2025 Editor assigned by journal 27 Oct, 2025 Editor invited by journal 06 Oct, 2025 Submission checks completed at journal 03 Oct, 2025 First submitted to journal 03 Oct, 2025 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. 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10:01:46","extension":"xml","order_by":27,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":131151,"visible":true,"origin":"","legend":"","description":"","filename":"d13d4296341141978de1f743b9d6d1981structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7592399/v1/0f382dcfbb65366061d903a9.xml"},{"id":95321211,"identity":"5688aa41-a5ba-4c22-bbd4-c1fd05be17c8","added_by":"auto","created_at":"2025-11-06 16:47:36","extension":"html","order_by":28,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":148311,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7592399/v1/1247f72c308278c6405c98e5.html"},{"id":95524300,"identity":"36448de6-0f54-400e-892f-6750b02e24bb","added_by":"auto","created_at":"2025-11-10 10:02:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":772118,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of changes in the intestinal flora in the three groups of children.\u003cstrong\u003e a\u003c/strong\u003e NMDS analysis plots for all three groups; \u003cstrong\u003eb\u003c/strong\u003ePhylum-level analysis plots for all three groups; \u003cstrong\u003ec\u003c/strong\u003e Genus-level analysis plots for all three groups; \u003cstrong\u003ed\u003c/strong\u003e Box plots comparing relative abundance at the genus level across intestinal flora for all three groups, with different colors representing different sample groups and the y-axis showing log-transformed relative abundance values; \u003cstrong\u003ee\u003c/strong\u003e LEfSe analysis depicting LDA SCORE \u0026gt; 4 differential microbiota; \u003cstrong\u003ef\u003c/strong\u003e Phylogenetic tree of the three groups, where orange denotes enrichment in the MPP group, green in the NMP group, purple in the N group, and yellow nodes indicate no significant differences. Node diameter correlates positively with relative abundance; each layer of nodes represents phylum, class, order, family, and genus from innermost to outermost；\u003cstrong\u003eg\u003c/strong\u003eImportance-point plot: the horizontal axis represents importance metrics, the vertical axis displays genus names ranked by importance, and the right-hand bar chart shows relative genus abundance.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7592399/v1/fee0c17ff064b2cf268ef1ee.jpg"},{"id":95321183,"identity":"489831a2-2386-433b-a14a-adf3b6de0689","added_by":"auto","created_at":"2025-11-06 16:47:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":92179,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between intestinal flora and clinical laboratory indicators. The horizontal axis represents the top 15 bacterial genera, and the vertical axis represents the clinical laboratory indicators. Red indicates a positive correlation, and blue denotes a negative correlation. * \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05, **\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Fig2tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7592399/v1/492291277c15800f97568120.jpg"},{"id":100069302,"identity":"af8d03b8-e595-48f2-9dc7-ccdfbd75ba46","added_by":"auto","created_at":"2026-01-12 16:12:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2017468,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7592399/v1/17578914-228e-4126-97f4-4d4d073d0cd8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Study on the Correlation Between intestinal flora Characteristics and Serum Zinc and Iron Levels in Paediatric Patients with Mycoplasma pneumoniae pneumonia","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eMycoplasma pneumoniae\u003c/em\u003e (MP) is a common pathogen that causes respiratory infections in children and adolescents. \u003cem\u003eM. pneumoniae pneumonia\u003c/em\u003e (MPP) is an acute respiratory disease caused by MP infection, typically observed in children aged five years and older. It represents a major proportion of community-acquired pneumonia, accounting for up to 40% of cases17[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Globally, epidemics of mycoplasma infection occur approximately every 35 years, with each epidemic lasting about 1\u0026ndash;2 years[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The adhesive properties and toxins produced by MP directly damage ciliated epithelial cells and disrupt immune function. This leads to reduced immunity and slower recovery in children with MPP. In China, poor response to macrolide therapy in some patients and recurrent mycoplasma epidemics impose a significant burden on society and families[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe gut is the largest immune organ in the body and functions as a complex microecological system. The gut-lung axis serves as a pivotal interface for interactions between the pulmonary and intestinal microbiota. Consequently, the intestinal flora plays a crucial role in immune responses to respiratory infections. Pathogenic respiratory infections can induce gut dysbiosis, and conversely, alterations in the intestinal flora may also influence the prognosis of respiratory diseases. Trace elements are substances present in concentrations below 0.01% of body weight; they participate in physiological metabolism and influence immune system function. Zinc and iron are two essential trace elements with relatively high concentrations and critically important functions in the human body, playing pivotal roles in childhood growth and development, as well as in maintaining immune function. MP infection is associated with trace element imbalances in the body [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, this study aimed to examine the correlation between intestinal flora characteristics and serum zinc and iron levels in children with MPP from a gut microbiome perspective.\u003c/p\u003e"},{"header":"Research objects and methods","content":"\u003cp\u003eThe experimental group (MPP group, 30 cases) comprised paediatric patients diagnosed with M. pneumoniae pneumonia who met the study criteria and were admitted to the 940th Hospital of Joint Logistics Support Force of People's Liberation Army Department of Pediatrics between November 2024 and March 2025. A control group consisting of children with non-M. pneumoniae pneumonia (NMP group, 30 cases) and healthy children from the paediatric health clinic (N group, 30 cases) were selected concurrently. The inclusion criteria were as follows: (1) age 3\u0026ndash;14 years; (2) good patient compliance and complete clinical records; and (3) parental informed consent obtained. (4) Experimental group: met the consensus criteria from the 2023 Pediatric Mycoplasma Pneumonia Diagnosis and Treatment Guidelines[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]: a) Physical examination revealed acute respiratory infection symptoms (fever, cough, or wheezing) with infiltrates on chest imaging; b) Single-serum MP antibody titer\u0026thinsp;\u0026ge;\u0026thinsp;1:160 (PA method); seroconversion with a fourfold or greater increase in MP antibody titer between two serum samples during the disease course; c) Positive MP-DNA or RNA detection; (5) Control groups: NMP group: a. Physical examination revealing acute respiratory infection symptoms (fever, cough, or wheezing) with infiltrates visible on chest imaging. Negative MP DNA or RNA detection. N group: No history of respiratory diseases, such as pneumonia or asthma, within the preceding month. The exclusion criteria were as follows: (1) patients with measles, pertussis, varicella, tuberculosis, or other infectious diseases; (2) patients with underlying conditions such as congenital heart disease, renal disease, or immunodeficiency; (3) paediatric patients treated with antibiotics, corticosteroids, intestinal flora agents, or other immunosuppressive agents within the past month; and (4) inadequate stool sample collection or insufficient sample data for analysis.\u003c/p\u003e\u003cp\u003e All children and their families provided informed consent, and the study was approved by the hospital ethics committee (2024KY22213).\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003eSample and Data Collection\u003c/h2\u003e\u003cp\u003e(1) Clinical data collection: ① Basic information: gender, age, mode of delivery, height, weight, feeding method; ② Laboratory parameters: complete blood count, procalcitonin (PCT), interleukin-6 (IL-6), C-reactive protein (CRP), biochemical indicators, etc.\u003c/p\u003e\u003cp\u003e(2) Faecal Specimen Collection: ① Fresh faecal samples (3\u0026ndash;5 g) were collected within 24 hours of admission or prior to antibiotic treatment and placed into sterile centrifuge tubes containing preservation solution, thoroughly mixing the faeces with the solution; ② Unique codes were assigned to collected samples, which were stored at \u0026minus;\u0026thinsp;80\u0026deg;C within two hours; ③ The original stool samples were shipped on dry ice to the testing company for intestinal flora analysis.\u003c/p\u003e\u003cp\u003e(3) Peripheral blood collection: 0.5 mL of peripheral blood was collected in an anticoagulant tube within 24 h of the child's admission or on the day of their visit to our paediatric health clinic. A qualified professional conducted blood zinc and iron level testing in accordance with the relevant testing protocols.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eintestinal flora 16S Diversity Sequencing\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted from the samples using the MagPure Soil DNA LQ Kit (Magan) according to the manufacturer's protocol. DNA concentration and purity were assessed using NanoDrop 2000 (Thermo Fisher Scientific, USA) and agarose gel electrophoresis. The extracted DNA was stored at -20\u0026deg;C. Using the extracted genomic DNA as a template, PCR amplification of the bacterial 16S rRNA gene was performed with barcoded specific primers and Takara Ex Taq High Fidelity Enzyme. The V3\u0026ndash;V4 variable region of the 16S rRNA gene was amplified using the universal primers 343F (5\u0026rsquo;-TACGGRAGGCAGCAG-3\u0026rsquo;) and 798R (5\u0026rsquo;-AGGGTATCTAATCCT-3\u0026rsquo;) for bacterial diversity analysis. PCR products were detected via agarose gel electrophoresis, and qualified products were sequenced using the Illumina NovaSeq 6000 platform. Sequencing was performed by Shanghai Ouyi Biotechnology Co. Ltd.\u003c/p\u003e\n\u003ch3\u003eBioinformatics Analysis and Statistical Data Analysis\u003c/h3\u003e\n\u003cp\u003eThe raw data were in FASTQ format. Following sequencing, Cutawv-xsrnvirxdapt software was first employed to trim the primer sequences from the raw data sequences. Subsequently, DADA2 was used to perform quality filtering, denoising, assembly, and de-chimera analysis on the qualified paired-end raw data using the default QIIME 2 (2020.11) parameters, yielding representative sequences and ASV abundance tables. Following the selection of representative sequences for each ASV using the QIIME 2 software package, all representative sequences were annotated by alignment against the Silva database (version 138). Species annotation was performed using the q2-feature-classifier software with the default parameters. Alpha and beta diversity analyses were conducted using the QIIME 2 software. Alpha diversity was assessed using indices including Chao1 and Shannon diversity. Beta diversity was evaluated using unweighted UniFrac principal coordinate analysis (PCoA) based on unweighted UniFrac distance matrices. Kruskal\u0026ndash;Wallis tests were used for differential analysis. LEfSe was used for the differential analysis of species abundance profiles.\u003c/p\u003e\n\u003ch3\u003eBlood Zinc and Iron Content Detection\u003c/h3\u003e\n\u003cp\u003ePeripheral blood samples were collected from the children, diluted, and directly analyzed using atomic absorption spectroscopy.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eData were organized and analyzed using SPSS 26.0 software. For normally distributed quantitative data, the results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (x̄\u0026plusmn;s). Comparisons among the three groups were performed using one-way analysis of variance (ANOVA). For non-normally distributed data, results are presented as median (P\u003csub\u003e25\u003c/sub\u003e, P\u003csub\u003e75\u003c/sub\u003e), with comparisons conducted using the Kruskal\u0026ndash;Wallis test. Count data are presented as case numbers and percentages (%). Intergroup comparisons were performed using theχ\u0026sup2;test or Fisher's exact probability test. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicating statistically significant differences.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eGeneral Clinical Data\u003c/h2\u003e\u003cp\u003eThis study included three groups of subjects, each comprising 30 patients. There was a statistically significant difference in serum zinc levels among the three groups (\u003cem\u003eF\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.712, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no significant differences were observed in sex, age, height, weight, or serum iron levels (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\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 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of General Characteristics Among the Three Groups of Children\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eVariables\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eMPP group(n\u0026thinsp;=\u0026thinsp;30)\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNMPgroup(n\u0026thinsp;=\u0026thinsp;30)\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNgroup(n\u0026thinsp;=\u0026thinsp;30)\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eF\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.737\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale(case)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale(case)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(y)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.10\u0026thinsp;\u0026plusmn;\u0026thinsp;2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.63\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.768\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.467\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHight(cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e120.46\u0026thinsp;\u0026plusmn;\u0026thinsp;18.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e115.87\u0026thinsp;\u0026plusmn;\u0026thinsp;13.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112.57\u0026thinsp;\u0026plusmn;\u0026thinsp;9.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight(Kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.91\u0026thinsp;\u0026plusmn;\u0026thinsp;9.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.05\u0026thinsp;\u0026plusmn;\u0026thinsp;8.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZinc content(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e81.31\u0026thinsp;\u0026plusmn;\u0026thinsp;13.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.10\u0026thinsp;\u0026plusmn;\u0026thinsp;8.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e90.27\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e5.712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIron content(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.208\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\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eCharacteristics of intestinal flora Changes\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eAlpha Diversity Analysis\u003c/h2\u003e\u003cp\u003eTo compare the richness and evenness of the intestinal flora across the three sample groups, we assessed microbial diversity and distribution uniformity by calculating various alpha indices. The Chao1 and ACE indices focus on species richness: higher Chao1 values indicate greater total species abundance, whereas higher ACE values reflect greater overall diversity. The Shannon and Simpson indices reflect microbial diversity. Higher species diversity and more even distribution correspond to larger Shannon index values; conversely, a higher Simpson's index indicates greater microbial diversity. Goods Coverage reflects sequencing depth: values closer to 1 indicate sufficient sequencing depth to cover all species within the sample, signifying higher microbial diversity. The PD index represents the evolutionary relationships of species. A higher index value signifies that the microbial community encompasses a broader and more dispersed evolutionary lineage, that is, more distantly related species, serving as a crucial dimension for assessing gut microbiome health.\u003c/p\u003e\u003cp\u003eThe results of the Kruskal\u0026ndash;Wallis test \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e indicate that the differences in intestinal flora among the three sample groups for the Chao1, Shannon, Simpson, ACE, observed species, Goods_coverage, and PD indices did not reach statistical significance (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.443, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.238, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.255, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.423, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.325, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.766, and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.385), suggesting limited microbial differences between groups, potentially constrained by sample size limitations. Future studies with larger sample sizes are required to validate these findings. Although no significant differences in alpha diversity were observed among the three groups, an in-depth analysis of each index revealed that children with MPP exhibited lower richness and evenness of intestinal flora than the control group.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAlpha diversity analysis of intestinal flora in children in three groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eMPP group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNMP group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eN group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eH\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChao 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e210.52(115.30,229.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e238.43(121.10,226.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e225.70(141.40,240.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.443\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShannon\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.84(3.26,5.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.44(3.74,5.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e5.03(4.42,5.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.873\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.238\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSimpson\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.84(0.77,0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.83(0.83,0.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.90(0.89,0.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.981\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e208.54(110.85,227.49)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e238.29(117.45,225.98)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e225.84(145.39,242.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.423\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObserved species\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e202.72(107.70,220.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e227.51(113.15,217.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e217.14(137.25,186.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003egoods_coverage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00(1.00,1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00(1.00,1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.00(1.00,1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.534\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePD_whole_tree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.35(15.48,27.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.06(14.84,23.37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e24.23(15.88,26.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.907\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\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\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eBeta Diversity Analysis\u003c/h2\u003e\u003cp\u003eThe Unweighted UniFrac distance algorithm is a core method for β-diversity analysis, used to compare the phylogenetic structures of microbial communities across different samples. This study employed Unweighted UniFrac-based NMDS analysis to assess species diversity, that is, β-diversity, among the three sample groups. NMDS analysis is a dimension-reduction visualization technique based on distance matrices, enabling a clear depiction of similarities or differences in the overall microbial community structures across samples. The stress value in the NMDS analysis serves as an indicator of the accuracy of the true distances between samples. Generally, stress\u0026thinsp;\u0026lt;\u0026thinsp;0.2 yields results with good interpretability; stress values ranging from 0.05 to 0.2 indicate good sample reliability; when stress\u0026thinsp;\u0026lt;\u0026thinsp;0.05, it signifies excellent representativeness of the samples. NMDS analysis revealed \u003cb\u003e(Fig.\u0026nbsp;1a)\u003c/b\u003e a stress value of 0.098, indicating good sample quality and reliable results across the three groups in this experiment. Both analytical methods demonstrated phylogenetic-level differences in the intestinal flora composition among the three groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eintestinal flora Structural Analysis\u003c/h2\u003e\u003cp\u003eAnalysis of phylum-level composition and relative abundance in the MPP, NMP, and N groups \u003cb\u003e(Fig.\u0026nbsp;1b)\u003c/b\u003e revealed that \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eBacteroidetes, Actinobacteria\u003c/em\u003e, and \u003cem\u003eProteobacteria\u003c/em\u003e dominated all three groups. The sum of the relative abundances of these phyla accounted for over 98% of the community richness. The \u003cem\u003eFirmicutes\u003c/em\u003e phylum exhibited higher relative abundance across all three study groups, accounting for 39.4%, 46.9%, and 50.0% in the MPP, NMP, and N groups, respectively, with the lowest relative abundance observed in the MPP group. The abundance of the \u003cem\u003eBacteroidetes\u003c/em\u003e phylum was significantly higher in the MPP group (32.6%) than in the NMP (20.3%) and N groups (27.4%).\u003c/p\u003e\u003cp\u003eThe intestinal flora composition at the genus level exhibited significant differences among the three groups of children \u003cb\u003e(Fig.\u0026nbsp;1c)\u003c/b\u003e, with the relative abundance of the same genus varying across groups. The top 10 genera with abundance levels exceeding 1% in the MPP group were, in descending order: \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, \u003cem\u003eIntestinibacter\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003eSubdoligranulum\u003c/em\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of intestinal flora Composition Differences\u003c/h2\u003e\u003cp\u003eDifferential species boxplot analysis \u003cb\u003e(Fig.\u0026nbsp;1d)\u003c/b\u003e screened the top 10 genus-level species abundance data across the three paediatric groups based on P-values. The results indicated that the abundance of \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eLachnospiraceae\u003c/em\u003e was higher in the MPP group than in the NMP and N groups, whereas the abundance of \u003cem\u003eEnterococcus\u003c/em\u003e exceeded that of the N group. Conversely, the abundance of \u003cem\u003eEubacterium\u003c/em\u003e, \u003cem\u003eAnaerostipes\u003c/em\u003e, and \u003cem\u003eCollinsella\u003c/em\u003e was higher in the NMP group than in the MPP and N groups. The N group exhibited higher abundances of \u003cem\u003eRoseburia\u003c/em\u003e, \u003cem\u003eLachnospiraceae\u003c/em\u003e, and \u003cem\u003eSubdoligranulum\u003c/em\u003e than the MPP and NMP groups. Further analysis of intergroup microbial differences using P-values indicated that \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 signified significant differences between groups, while P\u0026thinsp;\u0026lt;\u0026thinsp;0.01 indicated highly significant differences \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eThe relative abundance of intestinal flora levels was compared\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eBacterial Genera\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eMPP group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eNMP group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003eN group\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eH\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cspan type=\"ItalicSmallCaps\" class=\"ItalicSmallCaps\" name=\"Emphasis\"\u003eP\u003c/span\u003e \u003cspan type=\"SmallCaps\" class=\"SmallCaps\" name=\"Emphasis\"\u003evalue\u003c/span\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEnterococcus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.037(0.000,0.008)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.079(0.002,0.014)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.002(0.000,0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.847\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubdoligranulum\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.015(0.000,0.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.009(0.000,0.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.021(0.003,0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.821\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRoseburia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.002(0.000,0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.006(0.000,0006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.028(0.001,0.052)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21.164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFusicatenibacter\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.011(0.000,0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.009(0.000,0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.015(0.002,0.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLachnoclostridium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.018(0.002,0.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.014(0.002,0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.004(0.001,0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEubacterium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.005(0.000,0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018(0.000,0.033)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.011(0.001,0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.493\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAnaerostipes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.007(0.000,0.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.011(0.000,0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.010(0.001,0.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.904\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrevotella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.016(0.001,0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003(0.001,0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007(0.000,0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.652\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLachnospiraceae\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.006(0.000,0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.003(0.000,0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.016(0.001,0.011)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.960\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollinsella\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.002(0.000,0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.015(0.000,0.019)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.003(0.000,0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.716\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.035\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\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eintestinal flora LEfSe Analysis\u003c/h2\u003e\u003cp\u003eTo identify the most significant intestinal flora biomarkers between groups, linear discriminant analysis Effect Size (LEfSe) analysis was conducted. This analytical tool is designed to discover and interpret biomarkers in high-dimensional data, enabling comparisons between two or more groups of samples. It emphasizes both statistical significance and biological relevance, identifying biomarkers that exhibit statistical differences between groups. LEfSe analyzes all hierarchical levels (phylum, class, order, family, genus, and species) collectively, without distinguishing between levels. The bar chart primarily displays species with linear discriminant analysis (LDA) values exceeding the preset threshold, that is, statistically significant biomarkers. The length of each bar represents the LDA value, indicating the degree of influence exerted by the significantly different species across groups. Analysis of the distinct microbial communities between the three groups revealed 21 differentially abundant species \u003cb\u003e(Fig.\u0026nbsp;1e).\u003c/b\u003e Using an LDA SCORE threshold of\u0026gt;4, the following were identified: \u003cem\u003eActinobacteriota\u003c/em\u003e (LDA\u0026thinsp;=\u0026thinsp;4.55), \u003cem\u003eo_Bacteroidales\u003c/em\u003e (LDA\u0026thinsp;=\u0026thinsp;4.85), \u003cem\u003eEnterococcaceae\u003c/em\u003e (LDA=5.56), \u003cem\u003eEnterococcus\u003c/em\u003e (LDA\u0026thinsp;=\u0026thinsp;4.56), and \u003cem\u003eg_Roseburia\u003c/em\u003e (LDA\u0026thinsp;=\u0026thinsp;4.09) were significantly enriched (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003eThe branch evolution diagram \u003cb\u003e(Fig.\u0026nbsp;1f)\u003c/b\u003e displays significantly different species with relatively higher abundance in different groups. Analysis revealed the enrichment of two genera at the genus level within the MPP group: \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eLachnoclostridium\u003c/em\u003e, while \u003cem\u003eBacteroidales\u003c/em\u003e was enriched at the order level. The NMP group exhibited enrichment of three genera at the genus level: \u003cem\u003eEnterococcaceae\u003c/em\u003e, \u003cem\u003eCollinsella\u003c/em\u003e, and \u003cem\u003eEubacterium\u003c/em\u003e. At the order level, enrichment was observed in \u003cem\u003eCoriobacteriia\u003c/em\u003e. At the family level, enrichment was observed in \u003cem\u003ethe Coriobacteriaceae\u003c/em\u003e and \u003cem\u003eEnterococcaceae\u003c/em\u003e families.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eRandom Forest Analysis\u003c/h2\u003e\u003cp\u003eThe random forest algorithm enables the accurate and efficient classification of microbial community samples while identifying ASVs that distinguish intergroup differences. This study employed random forest analysis on the top 30 genera based on relative abundance \u003cb\u003e(Fig.\u0026nbsp;1g)\u003c/b\u003e. The results revealed the following ranking of important genera across the three sample groups: \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eEubacterium hallii group (an unclassified Eubacterium genus\u003c/em\u003e), \u003cem\u003eRoseburia\u003c/em\u003e, \u003cem\u003eFusicatenibacter\u003c/em\u003e, and \u003cem\u003eLactobacillus\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 1\u003c/b\u003e Analysis of changes in the intestinal flora in the three groups of children. \u003cb\u003ea\u003c/b\u003e NMDS analysis plots for all three groups; \u003cb\u003eb\u003c/b\u003e Phylum-level analysis plots for all three groups; \u003cb\u003ec\u003c/b\u003e Genus-level analysis plots for all three groups; \u003cb\u003ed\u003c/b\u003e Box plots comparing relative abundance at the genus level across intestinal flora for all three groups, with different colors representing different sample groups and the y-axis showing log-transformed relative abundance values; \u003cb\u003ee\u003c/b\u003e LEfSe analysis depicting LDA SCORE\u0026thinsp;\u0026gt;\u0026thinsp;4 differential microbiota; \u003cb\u003ef\u003c/b\u003e Phylogenetic tree of the three groups, where orange denotes enrichment in the MPP group, green in the NMP group, purple in the N group, and yellow nodes indicate no significant differences. Node diameter correlates positively with relative abundance; each layer of nodes represents phylum, class, order, family, and genus from innermost to outermost;\u003cb\u003eg\u003c/b\u003e Importance-point plot: the horizontal axis represents importance metrics, the vertical axis displays genus names ranked by importance, and the right-hand bar chart shows relative genus abundance.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eHeatmap of Correlation Between intestinal flora and Clinical Laboratory Indicators\u003c/h2\u003e\u003cp\u003eBased on the relative abundance of microorganisms in the samples and the corresponding clinical indicator data, Pearson's correlation analysis was used to assess the relationship between the two. Analysis at the top 15 genus level \u003cb\u003e(Fig.\u0026nbsp;2)\u003c/b\u003e revealed that \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eBlautia\u003c/em\u003e exhibited positive correlations with serum zinc levels. Among these, \u003cem\u003eParabacteroides\u003c/em\u003e demonstrated a statistically significant correlation with serum zinc (r\u0026thinsp;=\u0026thinsp;0.370, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eEscherichia-Shigella\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e exhibited negative correlations with blood zinc levels, with \u003cem\u003eEscherichia-Shigella\u003c/em\u003e demonstrating a statistically significant association (r = -0.399, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eBlautia\u003c/em\u003e were positively correlated with serum iron levels, whereas \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003eIntestinibacter\u003c/em\u003e, \u003cem\u003eLachnoclostridium\u003c/em\u003e, and \u003cem\u003eSubdoligranulum\u003c/em\u003e (a rare genus of small cocci) were negatively correlated with serum iron levels.\u003c/p\u003e\u003cp\u003eFurthermore, this study also found that lymphocyte counts were positively correlated with \u003cem\u003eBacteroides\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.424, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and negatively correlated with \u003cem\u003eSubdoligranulum\u003c/em\u003e (r = -0.389, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and \u003cem\u003eAlistipes\u003c/em\u003e (r = -0.371, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Neutrophil counts were positively correlated with \u003cem\u003eMuribaculaceae\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.579, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The Neutrophil-to-Lymphocyte Ratio (NLR) showed positive correlations with \u003cem\u003eLachnoclostridium\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.449, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), \u003cem\u003eMuribaculaceae\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.440, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and \u003cem\u003eSubdoligranulum\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.452, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). PCT was positively correlated with \u003cem\u003eMuribaculaceae\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.651, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). CRP (r =-0.369, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and CRP-ALB (r=-0.374, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) levels were negatively correlated. LDH demonstrated a positive correlation with \u003cem\u003eAlistipes\u003c/em\u003e (r\u0026thinsp;=\u0026thinsp;0.452, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eFigure 2\u003c/b\u003e Correlation between intestinal flora and clinical laboratory indicators. The horizontal axis represents the top 15 bacterial genera, and the vertical axis represents the clinical laboratory indicators. Red indicates a positive correlation, and blue denotes a negative correlation. * \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe diversity and abundance of intestinal flora undergo dynamic changes, forming an adult-like intestinal flora structure by age 3, which then enters a state of relative stability [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This microbial homeostasis facilitates the development of the immune system, metabolic processes, and the establishment of internal environmental stability. Probiotic-dominant intestinal flora supports immune system maturation. Numerous studies have indicated [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] that the intestinal flora plays a pivotal role in immune responses to respiratory infectious diseases, with respiratory pathogen infections capable of altering the composition and function of the intestinal flora. Currently, research on MP infection and pulmonary disease remains relatively scarce, with a primary focus on bacterial and viral studies. Although trace elements exist in minute quantities within the body, they play a crucial role in maintaining physiological functions. Deficiencies or imbalances in zinc and iron are also associated with alterations in the intestinal flora.\u003c/p\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eChanges in intestinal flora Characteristics in Children with MPP\u003c/h2\u003e\u003cp\u003eThis study employed alpha diversity analysis, which revealed no statistically significant differences in intestinal flora richness or diversity among the three groups of children. However, children in the MPP group exhibited lower intestinal flora richness and evenness than those in the control group, as measured by both the Chao1 and Shannon indices, suggesting dysbiosis in MPP patients. Multiple studies have demonstrated that children with MP infection exhibit lower microbiota richness and diversity than healthy controls [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A study by Wang et al. showed that Mycoplasma infection reduced gut microbial diversity compared to non-Mycoplasma-infected children, a finding consistent with the present study[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These studies collectively indicate an altered intestinal flora composition in children with MPP, manifested as reduced diversity and richness of intestinal flora. Beta diversity analysis revealed significant differences in the overall intestinal flora structure among the three groups.\u003c/p\u003e\u003cp\u003eIn all three groups, the dominant phyla were \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eBacteroidetes\u003c/em\u003e, \u003cem\u003eActinobacteria\u003c/em\u003e, and \u003cem\u003eProteobacteria\u003c/em\u003e, consistent with previous reports[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Relative phylum-level abundances differed among the groups, with the MPP group exhibiting the lowest relative abundance of \u003cem\u003eFirmicutes\u003c/em\u003e and the highest relative abundance of \u003cem\u003eBacteroidetes\u003c/em\u003e. One study demonstrated an increased relative abundance of \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, and \u003cem\u003eStreptococcus\u003c/em\u003e, alongside a reduced abundance of \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eFaecalibacterium\u003c/em\u003e, and \u003cem\u003eRuminococcus\u003c/em\u003e in the intestinal flora of children with community-acquired pneumonia [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. A study by Pang Minghui et al. showed that conducted a comparative analysis of intestinal flora characteristics between children with \u003cem\u003eM. pneumoniae pneumonia\u003c/em\u003e (MPP) and \u003cem\u003eStreptococcus pneumoniae pneumonia\u003c/em\u003e, revealing a significantly increased abundance of \u003cem\u003eBacteroidetes\u003c/em\u003e and a reduced abundance of \u003cem\u003eFirmicutes\u003c/em\u003e in MPP patients, consistent with the present findings [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Genus-level analysis indicated a higher abundance of \u003cem\u003eBacteroides\u003c/em\u003e in the intestinal flora of children with MPP. Research has demonstrated that the \u003cem\u003eBacteroides\u003c/em\u003e genus can alter intestinal permeability and damage the intestinal epithelium [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], thereby increasing the risk of allergies and other diseases. \u003cem\u003eBacteroides\u003c/em\u003e play a crucial role in the synthesis of short-chain fatty acids (SCFAs), a key class of metabolites produced by gut microbes fermenting carbohydrates, including butyrate, propionate, and acetate, which influence gut health through energy supply, signalling, and immune regulation. When MP infection induces lung injury, SCFAs may prevent severe mycoplasma pneumonia through immune modulation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. \u003cem\u003eBacteroides\u003c/em\u003e are opportunistic pathogens. In this study, children with MPP exhibited elevated \u003cem\u003eBacteroides\u003c/em\u003e abundance in their intestinal flora. The compromised immune status during MPP facilitates the proliferation of opportunistic pathogens, which exacerbate inflammation by compromising the intestinal epithelium. This suggests that pathogenic bacteria participate in the disease process of MP infection via the lung-gut axis.\u003c/p\u003e\u003cp\u003eThis study identified significant differences in intestinal flora composition among the three groups of children. The MPP group predominantly harboured \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e, with markedly reduced levels of \u003cem\u003eRoseburia\u003c/em\u003e. \u003cem\u003ePrevotella\u003c/em\u003e is one of the dominant commensal bacteria in the lower respiratory tract, inducing regulatory T-cell differentiation and suppressing inflammatory responses. Upon \u003cem\u003eM. pneumoniae\u003c/em\u003e infection, \u003cem\u003ePrevotella\u003c/em\u003e may inhibit inflammation through metabolites such as short-chain fatty acids, thereby mitigating tissue damage [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. \u003cem\u003eEnterococcus\u003c/em\u003e is an opportunistic pathogen. Our findings indicate its higher abundance in the intestinal flora of children with MPP compared to healthy children, consistent with the conclusions of Shou et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. We further observed that the relative abundance of \u003cem\u003eEnterococcus\u003c/em\u003e correlated positively with inflammatory markers, including the neutrophil-to-lymphocyte ratio, lymphocyte ratio, and C-reactive protein (CRP). This suggests that opportunistic pathogens such as \u003cem\u003eEnterococcus\u003c/em\u003e participate in the inflammatory response in children with MPP, potentially influencing their prognosis. The abundance of \u003cem\u003eEnterococcus faecalis\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e butyricum in the intestines of children with MPP was lower than that in healthy children. This study also compared the intestinal flora of children with MPP with and without wheezing, finding significantly reduced levels of \u003cem\u003eEnterococcus faecalis\u003c/em\u003e and \u003cem\u003eClostridium\u003c/em\u003e butyricum in children with wheezing[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Domestic researchers categorised children with MPP into acute-phase and recovery-phase groups. Results indicated that the relative abundances of \u003cem\u003eBacteroides, Lactobacillus, Bifidobacterium\u003c/em\u003e, and \u003cem\u003ePeptostreptococcus\u003c/em\u003e were lower in both acute-phase and recovery-phase children with MPP compared to healthy controls [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This demonstrates intestinal flora dysbiosis in children with MPP, with the degree of microbiota reduction holding some value for distinguishing between acute-phase and recovery-phase MPP. \u003cem\u003eClostridium\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e exhibited higher relative abundance in children with MPP compared to healthy controls, consistent with findings by Wei et al.[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. While that study reported decreased abundance of pathogenic bacteria such as \u003cem\u003eEscherichia\u003c/em\u003e -\u003cem\u003eShigella\u003c/em\u003e alongside increased \u003cem\u003eRoseburia\u003c/em\u003e abundance following probiotic treatment in children with MPP, the present study demonstrates lower \u003cem\u003eRoseburia\u003c/em\u003e abundance in MPP patients relative to controls. \u003cem\u003eRoseburia\u003c/em\u003e constitutes beneficial intestinal flora that further protects the intestinal mucosal barrier by reducing pro-inflammatory cytokine IL-17 production [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Research shows that increased \u003cem\u003eRoseburia\u003c/em\u003e abundance following probiotic treatment in children with MPP, thus differing from the present findings[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Studies indicate that children with severe pneumonia exhibit markedly elevated gut dysbiosis indices and significantly reduced \u003cem\u003eRoseburia\u003c/em\u003e abundance compared to those with mild pneumonia, suggesting an association between decreased \u003cem\u003eRoseburia\u003c/em\u003e abundance and systemic inflammatory responses[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. These findings suggest that children with MPP exhibit reduced abundance of beneficial bacteria and increased abundance of opportunistic pathogens. These differential bacterial genera may represent key therapeutic targets for future MPP treatments. The precise mechanisms linking \u003cem\u003eM. pneumoniae\u003c/em\u003e infection to intestinal flora alterations remain incompletely elucidated, warranting further investigation at the metabolic and metagenomic levels.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eBlood Zinc and Iron Levels in MPP Paediatric Patients\u003c/h2\u003e\u003cp\u003eIron is the most abundant trace element in the body, serving as a vital component of haemoglobin and myoglobin. It is also essential for maintaining cellular function and supporting growth and development. Iron deficiency can impair immune function, whereas excessive iron may induce oxidative stress and increase susceptibility to pathogen infection. This study observed reduced blood zinc and iron levels in children with MPP, suggesting immune dysfunction. Research indicates that serum iron levels in paediatric pneumonia patients are lower than in healthy controls, with more pronounced reductions in severe pneumonia cases [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. MP infection may disrupt paediatric iron homeostasis via pro-inflammatory mediators IL-6 and TNF-α. As a result, iron depletion in children with RMPP was markedly less pronounced than in typical MPP cases, suggesting that reduced serum iron levels correlate with MP infection [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Supplementation therapy was found to improve clinical outcomes.\u003c/p\u003e\u003cp\u003eZinc is an essential trace element in the body, second only to iron in abundance. Zinc deficiency reduces the numbers of T lymphocytes and B lymphocytes, thereby diminishing the body's ability to resist pathogens and increasing susceptibility to disease [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The immune system is highly sensitive to fluctuations in zinc levels. Severe zinc deficiency affects multiple organ systems, including the immune, central nervous, and skeletal systems, while marginal zinc deficiency is also associated with immune dysfunction. Zinc deficiency may increase mortality risks from diarrhoea and pneumonia [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], with children under five being most affected by zinc-deficient diarrhoea and pneumonia [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A randomised controlled trial demonstrated that prophylactic zinc supplementation reduced the incidence of diarrhoea by 13% and pneumonia by 19% [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Findings from Rerksuppaphol et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] indicate that zinc supplementation shortens hospital stays for paediatric pneumonia patients, accelerates the resolution of pneumonia, and restores blood oxygen saturation and body temperature to normal ranges, thereby improving treatment efficacy. An international study involving 94 children with severe pneumonia, aged between 2 months and 2 years, found that the zinc supplementation group experienced slightly shorter cough duration and recovery time compared to the control group [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, a trial targeting children aged 3\u0026ndash;60 months with pneumonia indicated that zinc supplementation had no effect on the duration of the resolution phase or hospital stay [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Excessive dietary zinc supplementation alters intestinal flora composition and reduces resistance to Clostridium difficile, potentially increasing infection risk through heightened pathogen virulence and altered immune responses [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Discrepancies in these findings may stem from variations in the ages of study subjects and zinc formulations, necessitating further validation in subsequent research.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eCorrelation between intestinal flora Characteristics and Serum Zinc or Iron Levels in MPP Paediatric Patients\u003c/h2\u003e\u003cp\u003eThe gut-lung axis theory suggests that both the mucosal immune system and the intestinal flora are key modulators of systemic immune function. Alterations in the immune system induced by MP also influence the composition of the intestinal flora [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Notably, our findings indicate that certain beneficial bacteria, such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eBlautia\u003c/em\u003e, are positively correlated with serum zinc and iron levels, whereas potentially pathogenic bacteria like \u003cem\u003eEscherichia-Shigella\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e display negative correlations. Zinc influences the intestinal flora by maintaining intestinal epithelial barrier integrity and reducing mucosal inflammation. Additionally, it plays a role in immune regulation by enhancing T-cell function, promoting mucosal immunity, mitigating oxidative stress responses, and facilitating recovery from infection. Zinc also contributes to the structural remodeling of the intestinal flora by fostering the proliferation of short-chain fatty acid\u0026ndash;producing bacteria, such as \u003cem\u003eFaecalibacterium\u003c/em\u003e, which modulate host immune responses via fatty acid metabolic pathways. Furthermore, short-chain fatty acids inhibit the carbohydrate metabolic pathways of pathogenic bacteria by suppressing the function of membrane transport phosphotransferase systems (PTS) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Research further confirms that zinc regulates the relative abundance of beneficial bacteria like Parabacteroides and promotes the repair of the intestinal mucosal barrier [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The intestinal flora, in turn, modulates iron levels by regulating intestinal iron absorption, while iron content reciprocally affects microbial composition and metabolism. Disrupted iron metabolism can impair specific microbial functions, thereby influencing clinical treatment outcomes and prognosis, although appropriate interventions may mitigate these effects [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Moreover, \u003cem\u003eBlautia\u003c/em\u003e increases intestinal permeability to iron, further influencing iron absorption [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In summary, the interactions between the intestinal flora and blood zinc/iron levels play an integral role in maintaining intestinal health.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003ePediatric patients with M. pneumoniae pneumonia exhibit decreased blood levels of zinc and iron, concomitant with dysbiosis of the intestinal flora. Zinc and iron are known to regulate the relative abundance of beneficial and pathogenic bacteria in the gut, thereby modulating pulmonary inflammatory responses through the lung-gut axis. Currently, macrolide antibiotics remain the cornerstone of MPP treatment, although the emergence of drug resistance poses a significant challenge. Enhancing innate immunity through the modulation of intestinal flora and nutritional status may represent a novel strategy to reduce disease burden. Therefore, in managing MPP, it is imperative to prioritize not only conventional anti-mycoplasma therapy but also a comprehensive assessment and intervention targeting trace element levels and gut microbial composition. It is important to note that this study is a single-center investigation; the representativeness of the intestinal flora data obtained via 16S rDNA high-throughput sequencing may be limited. Future research should therefore include multicenter, large-sample studies to improve the generalizability of the findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\u003cp\u003e This study was approved by the Ethics Review the 940th Hospital of Joint Logistics Support Force of People's Liberation Army Department of Pediatrics (2024KY22213). Informed consents to participate in the study have been obtained from participants (or their parent or legal guardian).All procedures performed were in accordance with the ethical standards of the institutional research board in accordance with Helsinki declaration 2013.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot Applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003e not applicable. No additional interventions were implemented for the patients; all testing items were based on an expanded analysis of routine clinical diagnosis and treatment needs. Although this experiment was not subjected to clinical registration, we place a high value on the ethical compliance of the study; the study protocol has undergone comprehensive review by the ethics committee and has received formal approval.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eNo financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the Gansu Provincial Joint Research Fund (No. 25JRRA1185) and Natural Science Foundation of Gansu Province(23JRRA725).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXY and DYL contributed equally to this study. XY conceptual research, design experimental schemes, and write the first draft of the paper; DYL visualizes data, manages and designs protocols; LH and YYL data management and provision software; HTL and WX collect clinical data, collect samples, collate and statistical data; GLM validates the analysis results, reviews papers and supervises experimental research progress. LYM provides key experimental material, guides the entire research project, oversees research progress, and reviews and edits papers.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe would like to acknowledge all patients and guardians who decided to participate to the study. We thank all the team of Shanghai Ouyi Biotechnology Co.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw sequencing data generated in this study can be accessed in the SRA database by searching PRJNA1335416 on NCBI\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSun Y, Li P, Jin R, et al. Characterizing the epidemiology of \u003cem\u003eMycoplasma pneum-oniae\u003c/em\u003e infections in China in 2022\u0026ndash;2024: a nationwide cross-sectional study of over 1.6 million cases. Emerg Microbes Infect. 2025;14(1):2482703. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/22221751.2025.2482703\u003c/span\u003e\u003cspan address=\"10.1080/22221751.2025.2482703\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYan C, Xue GH, Zhao HQ, et al. 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J Nutr. 2016;146(9):1694\u0026ndash;700. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3945/jn.116.235358\u003c/span\u003e\u003cspan address=\"10.3945/jn.116.235358\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"16S rRNA, children, iron, intestinal flora, M. pneumoniae pneumonia, zinc","lastPublishedDoi":"10.21203/rs.3.rs-7592399/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7592399/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study aimed to investigate the correlation between intestinal flora characteristics and serum zinc and iron levels in paediatric patients with \u003cem\u003eM. pneumoniae pneumonia\u003c/em\u003e (MPP).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFaecal and serum samples were collected from 30 children with \u003cem\u003eM. pneumoniae pneumonia\u003c/em\u003e (MPP group), 30 children with \u003cem\u003enon-M. pneumoniae pneumonia\u003c/em\u003e (NMP group), and 30 healthy children (N group) who met the study criteria and were treated at our hospital between November 2024 and March 2025. These samples underwent 16S rRNA sequencing and trace element detection analyses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlpha diversity showed no significant differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Beta diversity analysis revealed significant intergroup differences (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At the phylum level, all three groups were dominated by \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eBacteroidetes\u003c/em\u003e, \u003cem\u003eActinobacteria\u003c/em\u003e, and \u003cem\u003eProteobacteria\u003c/em\u003e. The MPP group exhibited the lowest abundance of \u003cem\u003eFirmicutes\u003c/em\u003e and the highest abundance of \u003cem\u003eBacteroidetes\u003c/em\u003e. At the genus level, the MPP group showed higher abundances of \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003eEscherichia-Shigella\u003c/em\u003e compared to the control group. Analysis of intestinal flora differences revealed that the abundances of \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eLachnoclostridium\u003c/em\u003e in the MPP group were higher than those in both the NMP and N groups, whereas the abundance of \u003cem\u003eEnterococcus\u003c/em\u003e was higher than that in the N group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The NMP group exhibited higher abundances of \u003cem\u003eEubacterium\u003c/em\u003e, \u003cem\u003eAnaerostipes\u003c/em\u003e, and \u003cem\u003eCollinsella\u003c/em\u003e than the MPP and N groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The N group demonstrated higher abundances of \u003cem\u003eRoseburia\u003c/em\u003e, \u003cem\u003eLachnospiraceae\u003c/em\u003e, and \u003cem\u003eSubdoligranulum\u003c/em\u003e than the MPP and NMP groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Blood zinc and iron levels were lower in the MPP group than in the NMP and N groups. The heatmap of intestinal flora correlations with clinical parameters showed positive associations between \u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eBlautia\u003c/em\u003e with blood zinc and iron levels. Among these, the correlation between \u003cem\u003eParabacteroides\u003c/em\u003e and blood zinc levels was statistically significant (r\u0026thinsp;=\u0026thinsp;0.370, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). \u003cem\u003eEscherichia-Shigella\u003c/em\u003e and \u003cem\u003eIntestinibacter\u003c/em\u003e showed negative correlations with serum zinc and iron levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePaediatric patients with MPP exhibit disrupted intestinal flora composition alongside reduced serum zinc and iron levels, with specific bacterial genera correlating with alterations in serum zinc and iron concentrations.\u003c/p\u003e","manuscriptTitle":"A Study on the Correlation Between intestinal flora Characteristics and Serum Zinc and Iron Levels in Paediatric Patients with Mycoplasma pneumoniae pneumonia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-06 16:47:31","doi":"10.21203/rs.3.rs-7592399/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-11T12:46:16+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-01T19:55:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-31T10:32:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"64206103484210957551808372941021138319","date":"2025-10-30T16:02:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"197425801591386159271389189088697500539","date":"2025-10-30T08:45:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185623681765925541239220354670075336539","date":"2025-10-27T15:46:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-27T13:14:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-27T07:01:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-06T06:21:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-03T10:36:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-10-03T10:32:34+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a59f992b-2cc9-496a-a6af-cb1fdd06ed30","owner":[],"postedDate":"November 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:03:36+00:00","versionOfRecord":{"articleIdentity":"rs-7592399","link":"https://doi.org/10.1186/s12887-025-06470-2","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2026-01-05 15:58:12","publishedOnDateReadable":"January 5th, 2026"},"versionCreatedAt":"2025-11-06 16:47:31","video":"","vorDoi":"10.1186/s12887-025-06470-2","vorDoiUrl":"https://doi.org/10.1186/s12887-025-06470-2","workflowStages":[]},"version":"v1","identity":"rs-7592399","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7592399","identity":"rs-7592399","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}