Impact of maternal fecal microbiota on the early development of microbial community in the neonatal meconium

Impact of maternal fecal microbiota on the early development of microbial community in the neonatal meconium | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of maternal fecal microbiota on the early development of microbial community in the neonatal meconium Jae Yoon Jo, In Ae Cho, Jin-su Jun, Ji Sook Park This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8517689/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The maternal gut microbiota is regarded as a major contributor to the establishment of the infant gut microbial community; however, the extent to which neonatal meconium microbiota reflects the maternal fecal microbiota remains unclear. Methods We prospectively collected paired fecal samples from mothers and their offspring after informed consent was obtained. Maternal fecal samples were collected within a week before delivery, and neonatal fecal samples were collected within a week after birth. Fecal microbial compositions were analyzed using 16S-based microbiome taxonomic profiling. Mother–newborn pairs were stratified according to concordance or discordance of the dominant bacterial phylum, and associated perinatal characteristics were analyzed. Results A total of 21 maternal-newborn pairs, comprising 21 mothers and 25 neonates, were included in the analysis. Firmicutes was the predominant phylum in both maternal and neonatal samples, with 12 of 21 pairs (57.1%) exhibiting concordant dominant phyla. Neonatal meconial microbiota showed significantly lower species richness and diversity compared with maternal stool microbiota (Wilcoxon rank-sum, P < 0.05). At the species level, maternal and neonatal fecal microbiota communities formed clearly distinct clusters in ordination analyses, with significant differences in overall community composition (PERMANOVA, P = 0.001). No statistically significant associations were observed between maternal or neonatal characteristics and concordance of dominant phyla within the pairs. Conclusion These findings suggest that the maternal gut serves as a partial source for early intestinal microbiota formation of the offspring, independent of delivery mode or feeding type. However, additional factors are likely to contribute to the early development of the neonatal gut microbiota. Mother-Neonate Pair Fecal microbiota Meconium Figures Figure 1 Figure 2 Figure 3 Background The human gut microbiota is a dynamic ecosystem that undergoes rapid expansion and maturation beginning at birth. Maternal microbial strains originating from the vagina, skin, and gut constitute the dominant inoculum in early life, outweighing other sources. Subsequently, the composition and functional capacity of the gut microbial community change rapidly in response to breastfeeding, weaning, and later dietary transitions [ 1 , 2 ]. During the neonatal period, the gut microbiota is characterized by low diversity; however, with the initiation of weaning, microbial richness and complexity progressively increase [ 1 ]. Concurrently, bidirectional interactions between intestinal epithelial cells and resident microbes promote maturation of metabolic functions related to substrate utilization and contribute to the biosynthesis of essential nutrients for the host [ 3 , 4 ]. Large-scale cohort studies have consistently described this process as a stepwise pattern of microbial maturation [ 5 – 7 ]. Although the exact trajectory is modulated by interindividual variability, environmental exposures, and methodological factors, a shared developmental axis has been repeatedly observed across populations [ 5 , 7 , 8 ]. When this developmental program is disrupted or unhealthy dietary patterns persist, accumulating evidence indicates an increased risk of non-communicable diseases, such as allergies, obesity, and inflammatory bowel disease, attributable to impaired immune maturation and dysregulation of metabolic-inflammatory pathways [ 1 , 9 , 10 ]. In preterm infants, microbial dysbiosis often precedes clinical disease. In cases of necrotizing enterocolitis, reproducible increases or depletions of specific microbial taxa have been observed before onset [ 11 ]. These associations intersect with patterns of antibiotic exposure, feeding modalities, and modes of delivery. Furthermore, recent literature suggests that early microbiota-host interactions extend to neurodevelopmental pathways, indicating that the gut-brain axis may influence long-term health outcomes [ 12 , 13 ]. Accordingly, strategies aimed at steering infant gut microbiota colonization toward a health-promoting trajectory are of critical importance, and identification of the key determinants underlying this process represents a necessary first step. Previous studies have demonstrated that mode of delivery, exposure to intrapartum or perinatal antibiotics, breastfeeding, timing of weaning and introduction of solid foods, and maternal diet exert substantial influences on initial microbial community assembly [ 1 , 14 , 15 ]. Notably, studies that rigorously account for the low-biomass nature of first-pass meconium indicate that “immediate perinatal” factors, particularly delivery mode and intrapartum antibiotic administration, explain a greater proportion of variance in meconium microbiota composition than putative in utero influences [ 16 ]. However, Dos Santos et al. reported weaker associations between perinatal factors and gut microbial community structure later in infancy, suggesting that additional determinants become increasingly influential over time [ 17 ]. The precise mechanisms underlying neonatal gut microbiota community assembly remain incompletely understood. Therefore, the present study aimed to investigate the impact of maternal fecal microbiota on early neonatal gut microbiota community formation by enrolling maternal-neonatal pairs and collecting paired fecal samples under uniform environmental conditions. Methods Between January and June 2024, stool specimens were prospectively collected from mother-newborn pairs. Maternal samples were collected aseptically before delivery, and neonatal samples were obtained within the first week after birth, following informed consent from the Korea Biobank Network. Immediately after collection, all specimens were frozen at − 80°C and stored in the Biobank of Gyeongsang National University Hospital (GNUH), a member of the Korea Biobank Network, until analysis. For microbiota analysis, frozen fecal samples were thawed, resuspended, homogenized, subjected to bead-beating, and centrifuged at 14,000 × g for 10 minutes. The resulting supernatants were diluted with nuclease-free water and used as templates for polymerase chain reaction amplification. The V3–V4 hypervariable region of the bacterial 16S rRNA gene was amplified using primers 341F and 805R. Amplicons from individual samples were combined in equimolar amounts and purified using the AMPure XP purification kit (Beckman Coulter, Indianapolis, IN, USA), following the manufacturer’s protocol. Purified libraries were sequenced on an Illumina MiSeq platform with the MiSeq Reagent Kit v3 (Illumina, San Diego, CA, USA) using 2 × 250 bp paired-end reads. Extraction of bacterial DNA from fecal samples for 16S rRNA gene sequencing and initial taxonomic assignment was performed by a commercial provider (CJ Bioscience, Seoul, Korea). Taxonomic profiling of bacterial communities was conducted with EzBioCloud’s Microbiome Taxonomic Profiling (MTP) cloud pipeline using the PKSSU4.0 reference database. Organisms sharing ≥ 95% average nucleotide identity were grouped into a single “species group,” as individual members cannot be reliably distinguished at the sequence identity thresholds typically applied in 16S rRNA gene–based profiling. A comprehensive list of conventional species names corresponding to each species group is available on the EzBioCloud taxonomy page ( https://www.ezbiocloud.net/mtp/taxonomy ). To enable comparison of α-diversity indices among samples, read counts were rarefied to 1,000 reads per sample, representing the lowest sequencing depth in the dataset. For β-diversity analyses, read abundances were adjusted for 16S rRNA gene copy number variation to reduce compositional bias. Species richness was estimated using an abundance-based coverage estimator and by enumerating observed operational taxonomic units (OTUs). Overall diversity was summarized using the NPShannon index, while phylogenetic diversity was calculated from the OTU occurrence matrix. Differences in OTU composition between samples were quantified using generalized UniFrac distance and visualized with principal coordinate analysis (PCoA) combined with K-means clustering. We also obtained demographic and perinatal factors, including delivery mode, gestational age, maternal weight, offspring birth weight, use of antibiotics, and feeding methods of the mother and baby pair from the Biobank of GNUH. Differences in fecal microbial composition were analyzed according to these factors to investigate potential associations with neonatal gut microbiota patterns. Continuous variables are presented as means and standard deviations (SD), and categorical variables are expressed as numbers and percentages. Maternal or neonatal factors were analyzed using Fisher’s exact test or the Mann-Whitney U test, as appropriate. Associations between taxonomic profile variations, diversity indices, and sample categories of mothers and neonates were assessed using the Wilcoxon rank-sum test and permutational multivariate analysis of variance (PERMANOVA). Taxonomic profiling of fecal microbiota across groups and related statistical analyses were conducted using the EzBioCloud taxonomy webpage ( https:/www.ezbiocloud.net/mtp/view myMTPSetAnalyzer) [ 18 ]. Correlation analyses between demographic or perinatal factors of mother–neonate pairs and concordance of the dominant phylum were performed using logistic regression analysis in SPSS 27.0 (IBM, NY, US), and graphical representations were generated with GraphPad Prism 10.0.2 (GraphPad Software, Boston, US). This study was approved by the Institutional Review Board of GNUH (GNUH 2025-06-007). Results During the study period, a total of 21 mothers and 25 neonates were included (Table 1). The mean maternal age was 34.0 ± 4.7 years, and the mean maternal height was 161.3 ± 5.3 cm. The mean pre-pregnancy body mass index (BMI) was 23.2 ± 5.4 kg/m², and increased to 27.3 ± 5.8 kg/m² at the time of delivery. The mean maternal weight during late pregnancy was 71.3 ± 17.3 kg. Maternal stool samples were collected before delivery, with a mean sampling interval of -0.1 ± 0.7 days relative to birth. Six women (28.6%) received antenatal betamethasone for threatened preterm birth. Pregnancy-related complications included prolonged preterm rupture of membranes in two mothers (M2 and M7, 9.5%), both of whom received antibiotic therapy within one week before delivery. Gestational diabetes mellitus (GDM) was diagnosed in six mothers (28.6%), and glycemic control was adequately achieved through dietary modification or insulin therapy. Twin pregnancies occurred in four cases (19%). Parity was nearly evenly distributed, with 11 primiparous women (52.4%) and 10 multiparous women (47.6%): most multiparous women were in their second pregnancy. Neonatal baseline characteristics are as follows. The mean gestational age at birth was 36.9 ± 1.8 weeks, and the mean birth weight was 2.7 ± 0.7 kg. The mean 5-minute Apgar score was 9.8 ± 0.5, with scores ranging from 8 to 10. Meconium samples were collected from neonates at a mean of 4.1 ± 2.3 days after birth, and the mean duration of hospital stay was 7.4 ± 5.2 days. Fourteen neonates (56.0%) were female. Four neonates (B17, B18, B23, and B24; 16.0%) developed tachypnea shortly after birth and were diagnosed with transient tachypnea of the newborn (TTN). Five neonates (B2, B11, B12, B13, and B17; 29.4%) received antibiotic treatment during hospitalization, and all were exposed to antibiotics before stool sample collection. Fecal microbiota analyses were conducted for 21 mothers and 25 corresponding offspring using 16S-based MTP. Firmicutes was identified as the most prevalent bacterial phylum in both mothers and neonates (Fig. 1 ). Concordance of the dominant phylum between mothers and neonates was observed in 12 mother-neonate pairs (57.1%), including M1-B1, M3-B3, M4-B4, M5-B5, M7-B7, M8-B8, M10-B11, M11-B12, M12-B13, M14-B15, M16-B18, and M20-B23-B24. In contrast, the remaining 42.9% of pairs showed discordant dominant phyla (Table 1). Among the four mothers who delivered twins (M1, M10, M18, and M20), only one twin pair shared the same dominant phylum as their mother (M20-B23-B24), whereas the remaining twin pairs did not. Table 1. Clinical Characteristics of mothers and neonates participating in the study (M = 21, B = 25) Pairs of mother and Baby Maternal factors Neonatal factors Age (year) Wt (kg) BMI (kg/m 2 ) Obstetric problem primipara Antibiotics Del Stool GA (week) BW (kg) Sex antibiotics formula Stool Day Dominant phylum Day Dominant phylum M1-B1 40.1 79.8 28.4 Twin Y N CS 0 Fir 36.9 3.07 M N WM 0 Fir M2-B2 31.0 88.8 34.5 GDM, PPROM N Y VD 0 Pro 36.1 2.90 F Y BM 7 Fir M3-B3 40.2 79.4 27.8 - N N CS 0 Fir 38.0 3.25 F N BM 8 Fir M4-B4 38.6 62.7 24.6 - N N CS -3 Fir 38.3 3.32 M N BM 4 Fir M5-B5 35.9 60.0 24.3 PTL N N CS -1 Fir 34.1 2.07 F N WM 5 Fir M6-B6 37.8 49.8 19.0 FGR N N CS 0 Bac 37.3 1.97 F N WM 1 Pro M7-B7 43.6 75.4 31.3 GDM, PPROM N Y CS -1 Fir 34.0 2.01 F N WM 5 Fir M8-B8 39.8 59.9 23.7 GDM, PE Y N CS 0 Fir 35.3 1.79 M N WM 4 Fir M9-B9 34.8 77.0 28.5 - Y N VD 0 Fir 39.6 3.81 M N BM 5 Pro M10-B10 30.9 73.4 25.8 Twin Y N CS 0 Fir 37.1 2.85 M N BM 1 Pro -B11 37.1 2.46 F Y WM 1 Fir M11-B12 27.4 64.0 25.0 - Y N CS 0 Fir 38.7 3.43 F Y BM 6 Fir M12-B13 35.0 54.0 20.1 PTL N N VD 0 Pro 36.0 2.47 M Y WM 4 Pro M13-B14 32.7 64.5 27.0 GDM Y N CS 0 Bac 33.4 1.69 M N WM 5 Fir M14-B15 25.9 55.5 24.4 - Y N CS 0 Fir 38.6 3.11 F N BM 4 Fir M15-B16 32.9 64.7 25.5 - Y N CS 0 Fir 38.0 3.24 M N BM 7 Pro M16-B17 35.2 63.8 26.9 IUGR N N CS 0 Fir 36.4 2.48 M Y WM 4 Pro -B18 36.4 2.19 M N WM 4 Fir M17-B19 36.1 131.8 47.8 GDM N N CS 0 Fir 37.7 3.54 F N WM 7 Pro M18-B20 33.6 66.0 27.8 Twin N N CS 0 Fir 36.0 2.21 F N WM 0 Pro -B21 36.0 2.18 F N WM 0 Pro M19-B22 41.6 41.6 30.1 - Y N CS 0 Fir 38.4 3.88 F N WM 7 Pro M20-B23 30.6 70.6 27.6 GDM, Twin Y N CS 1 Fir 35.3 2.06 F N BM 6 Fir -B24 35.3 2.23 M N BM 6 Fir M21-B25 33.6 68.1 24.9 - Y N CS 0 Fir 39.1 3.63 F N BM 6 Chl Abbreviations: Wt, weight; GDM, gestational DM; PPROM, prolonged rupture of membranes defined as the rupture of the amniotic membrane more than 18 hours before delivery; PTL, preterm labor pain; PE, preeclampsia; IUGR, intrauterine growth restriction; CS, Cesarean section; VD, vaginal delivery; WM, whole milk feeding; BM, breast milk feeding; Fir, Firmicutes; Pro, Proteobacteria; Bac, Bacteroidetes; Chl, Chlorobi; Y, yes; N, no. The clinical characteristics of mother-neonate pairs with concordant dominant phyla (n = 12) and those with discordant dominant phyla (n = 11) are summarized in Table 2. No statistically significant differences in maternal or neonatal factors were identified between the two groups. Maternal pre- and late-pregnancy BMI values were higher in the discordant dominant phylum group than those in the concordant group; however, the difference was not statistically significant. We performed logistic regression analyses to identify factors associated with concordance; however, no statistically significant associations were observed (Table 2). Since maternal and neonatal factors were analyzed separately according to dominant phylum concordance within mother-neonate pairs, M10 was considered as one in the discordant group. During analyses, the factors of the M10-B10-B11 pair were not duplicated, although the pair was classified into one concordant pair (M10-B11) and one discordant pair (M10-B10), respectively. Using this approach, cesarean section (CS) delivery, multiple gestation, gestational age, birth weight, tachypnea, and postnatal antibiotic exposure were associated with a lower likelihood of dominant phylum concordance (Exp [B] < 0.8); however, no statistical significance was observed (Table 3). Table 2. Comparison of clinical characteristics in mother-neonate pairs between concordant and discordant dominant phylum groups Factors, Mean ± SD, n (%) Concordant pair (n = 12) Discordant pair (n =11) P Maternal factors Age (year) 35.7 ± 6.0 34.6 ± 3.1 0.468 Weight (kg) 66.9 ±10.2 75.7 ± 21.5 0.251 BMI, pre-pregnancy 22.3 ± 3.8 24.0 ± 6.6 0.809 BMI at delivery 25.7 ± 3.1 28.9 ±7.3 0.197 Primiparous 5 (50.0) 6 (54.5) 1.000 GDM 3 (30.0) 3 (27.3) 1.000 Stool collection -0.4 ± 1.1 0.0 ± 0.0 0.159 CS delivery 9 (90.0) 9 (81.8) 1.000 Neonatal factors GA (week) 36.5 ± 1.6 37.1 ± 1.7 0.326 Birth Weight (kg) 2.57 ± 0.58 2.86 ± 0.76 0.347 Male 6 (46.2) 5 (41.7) 1.000 Stool day 4.4 ± 2.1 4.2 ± 2.9 0.794 Breast milk 6 (46.2) 5 (41.7) 1.000 Tachypnea 3 (23.1) 1 (8.3_ 0.593 Antibiotics 3 (23.1) 2 (16.7) 1.000 Hospital duration 8.0 ± 4.2 6.8 ± 6.3 0.194 P -values were obtained using Fisher’s exact test or the Mann-Whitney test. Abbreviations: SD, standard deviation; BMI, body mass index; GDM, gestational diabetes mellitus; CS, Cesarean section; GA, gestational age. Table 3. Logistic regression analysis of maternal or neonatal clinical factors associated with concordant dominant phylum Factors Exp (B) 95% CI (lower-upper) P Maternal factor Age, year 1.038 0.853–1.264 0.708 BMI 0.869 0.691–1.093 0.231 Weight changes, kg 0.957 0.834–1.098 0.530 CS delivery 0.389 0.029–5.214 0.476 GDM 0.857 0.124–5.944 0.876 Primi-parous 0.800 0.131–4.874 0.809 Multi-gestation 0.500 0.037–6.683 0.600 Neonatal factor GA, week 0.773 0.463–1.290 0.324 Birth weight, kg 0.504 0.146–1.737 0.277 Male 0.833 0.171–4.058 0.821 BM 0.833 0.171–4.058 0.821 Tachypnea 0.303 0.027–3.407 0.334 Postnatal antibiotics 0.667 0.091–4.889 0.690 Abbreviations: BMI, body mass index; CS, Cesarean section; GDM, gestational diabetes mellitus; GA, gestational age; BM, breast milk. We compared α‑diversity between maternal fecal samples (n = 21) and neonatal meconium samples (n = 25) using two complementary metrics, such as species richness (observed features) and a community diversity index, and evaluated group differences using a two‑sided Wilcoxon rank‑sum test. Across both metrics, neonatal meconium exhibited significantly lower α‑diversity than that of maternal fecal microbiota ( P < 0.05, Fig. 2). PCoA with K-means clustering at the species level demonstrated clear separation between maternal fecal and neonatal meconium microbiota communities in the score plot, and overall differences in community composition were statistically significant by PERMANOVA ( P = 0.001, Fig. 3). Discussion In this study, we examined 21 mother-neonate pairs recruited from a single tertiary medical center to compare maternal fecal microbiota collected shortly before delivery with the offspring’s meconium microbiota. The primary aim was to determine whether, and to what extent, the maternal gut microbiota influences the initial formation of the neonatal fecal microbiota community. We observed that mothers and neonates shared a broadly similar phylum-level composition dominated by Firmicutes (Fig. 1). However, neonatal meconium constituted a low-diversity, low-biomass community, exhibiting significantly reduced species richness and lower Shannon indices than maternal stool (Fig. 2). Furthermore, maternal fecal and neonatal meconial microbiota communities were clearly segregated (Fig. 3), indicating the establishment of distinct ecological niches. When mother-neonate pairs were stratified into groups with “concordant” versus “discordant” dominant phyla and compared across clinical variables, no statistically significant associations were observed with perinatal factors such as pre-pregnancy and gestational weight, gestational diabetes, mode of delivery, or peripartum antibiotic exposure (Table 2). Our findings reinforce the prevailing concept that the maternal gut microbiota serves as a key reservoir for the neonatal intestinal microbiome, while simultaneously demonstrating that the community structure observed in the first meconium is not merely a reduced-scale replica of the maternal fecal microbiota. Recent studies using phylogenetic and genomic analyses have shown that maternal gut, vaginal, and skin microbes are transmitted to the infant gut and oral cavity at the strain level, with the maternal gut microbiota contributing most durably over the long term [2, 19]. Cohort studies further indicate that maternal gut microbes exhibit statistically significant transmission patterns at the amplicon sequence variant level, with higher transmission rates observed in vaginal deliveries [20, 21]. The concordance observed in dominant phyla among certain mother-neonate pairs in this study may be consistent with this “maternal dependency” hypothesis. At the same time, the markedly reduced alpha diversity (Fig. 2) and the clear separation of maternal and neonatal communities in unweighted distance-based clustering (Fig. 3) suggest that, at birth, the meconium microbiota remains in an early pioneering, or seeding, stage of community assembly [22, 23]. Time-series analyses of the intestinal microbiota indicate that, immediately after birth, facultative anaerobes such as Escherichia and Enterococcus initially dominate the gut. Over the ensuing months, the microbial community shifts toward a Bifidobacterium -centered configuration. Following weaning, Bacteroides and members of the phylum Firmicutes increase in abundance, and the ecosystem gradually converges toward an adult-like community structure [24, 25]. In both the Environmental Determinants of Diabetes in the Young cohort and the Swedish longitudinal study, the gut microbiota develops through three stages—developmental, transitional, and stable—over the first several years of life, achieving adult-like richness and community composition only around five years of age [5, 7]. The present study is noteworthy because it examines the earliest point along the neonatal gut microbiota successional pathway—namely, the immediate postnatal meconium—and evaluates its relationship with the maternal gut microbiota. The observed low diversity and clear separation of neonatal meconium microbiota from their mothers indicate that meconium, although already shaped by environmental, intrauterine milieu, and intrapartum influences, represents a pre-colonization transmission state. This stage precedes the establishment of a fully developed microbial community. At this early time point, the microbial composition likely reflects a composite signal of DNA from maternally derived bacteria, intrapartum contaminants, and a very small number of pioneer colonizers, and thus has a limited capacity to reliably predict the longer-term developmental trajectory of the gut microbiota over subsequent weeks and months. The influence of maternal and perinatal factors on initial gut communities has been reported with conflicting results. A recent comprehensive review of maternal microbial inheritance concluded that maternal obesity, dysregulated glucose metabolism, and unhealthy dietary patterns—factors that remodel the maternal gut microbiota—may exert lasting effects on infant gut microbiome composition and function. These effects, in turn, have the potential to program immune, metabolic, and neurodevelopmental axes, ultimately influencing health outcomes in the next generation [26]. In a large longitudinal cohort of very preterm infants, maternal pre-pregnancy BMI was identified as the only perinatal factor consistently associated not only with hospital length of stay but also with early childhood gut microbial community structure and functional pathways [27]. In contrast, studies focusing on meconium or other low-biomass samples collected immediately after birth have frequently reported weak or inconsistent associations between maternal BMI, mode of delivery, and antibiotic exposure [28-30]. In the present study, although the risk ratios of Exp [B] suggested directional trends for maternal BMI, gestational diabetes, and gestational weight gain in relation to concordant dominant phyla between mothers and neonates, none of these associations reached statistical significance (Tables 2 and 3). Several factors may account for these findings, including the limited sample size, the relatively coarse categorical outcome defined by concordance of the dominant phylum, and the inherent difficulty of detecting subtle effects in meconium, an extremely low-biomass and contamination-prone specimen. Notably, concordance with the maternal dominant phylum was inconsistent in twin deliveries, suggesting that immediate postnatal exposures and stochastic processes may contribute to the observed variability. Mode of delivery and intrapartum antibiotic exposure remain among the best-established determinants of gut microbiota trajectories from birth through infancy. Large birth cohorts have shown that infants delivered via CS experience delayed colonization by Bacteroides strains compared with vaginally delivered infants. During the neonatal period, CS-delivered infants’ intestinal communities are dominated by opportunistic, hospital-associated taxa such as Enterococcus , Enterobacter , and Klebsiella , whose relative abundance remains significantly higher than that in vaginally delivered infants throughout infancy [31]. Previous studies have linked the composition of maternal vaginal and gut microbiomes to fetal and neonatal gut communities. However, most of these studies examined stool samples collected after the first postnatal week, and datasets directly comparing maternal stool with neonatal meconium, as in the present study, remain relatively scarce. Despite the high rates of CS delivery in our study, the absence of clear differences according to dominant phylum concordance suggests that mode of delivery and intrapartum antibiotic exposure may exert a stronger influence on the pace of microbial colonization and community stabilization over the subsequent weeks and months than on the microbial composition captured at the meconium stage. This study has several strengths. First, we analyzed paired maternal-neonatal samples collected within a short interval, enabling direct comparison of maternal stool and neonatal meconium obtained immediately after delivery. Second, both maternal stool and neonatal meconium were prospectively collected and processed using an identical analytical pipeline, ensuring methodological consistency and minimizing technical variability. Nonetheless, several limitations must be acknowledged. The study was limited by a small sample size, with participants recruited from a single center and representing a relatively homogeneous ethnic background, which constrains the generalizability of the findings. High-risk exposures such as maternal obesity and major obstetric complications were relatively uncommon, reducing the statistical power to detect their potential effects. CS was the predominant mode of delivery in this study (85.7%, n = 18), exceeding the national average of approximately 58% reported for Korea in 2023 [32]. The high proportion of CS delivery may have limited our ability to fully assess the contribution of vaginal birth to mother-infant microbial transmission, a limitation similarly reported in other studies requiring practical access to maternal feces at delivery [33]. In addition, we performed only 16S rRNA gene-based relative abundance profiling, which precluded assessment of strain-level transmission and functional pathway dynamics. Finally, because meconium is an extremely low-biomass sample that is inherently susceptible to environmental contamination, residual contamination cannot be entirely excluded for certain low-abundance taxa, despite rigorous preprocessing and inclusion of negative controls. Despite these limitations, our study directly examines the relationship between maternal gut microbiota and neonatal meconium at the dyadic mother-infant level, suggesting that the intuitive assumption—that maternal gut microbiota overwhelmingly dictates early meconium community structure—may be only partially valid. Meconium collected immediately after birth exhibited a broadly similar phylum-level profile to maternal stool; however, in terms of alpha diversity and taxonomic composition, it represents a distinct, low-complexity community whose configuration cannot be fully explained by maternal clinical variables alone. By characterizing the microbiota of mother-neonate pairs, including maternal stool at delivery and neonatal meconium, this study contributes to understanding ongoing controversies surrounding the initial assembly of the neonatal gut microbial community. Future studies in larger cohorts should integrate multi-site maternal microbiome (gut, vagina, oral cavity, and skin) with meconium and subsequent infant stools to resolve strain-level transmission and functional potential. Such investigations should also evaluate how modifiable maternal factors—including dietary patterns, weight management, antibiotic exposure, and infant feeding practices—shape gut microbiota development and downstream health outcomes throughout infancy and early childhood. Ultimately, a stronger evidence base may enable microbiota-informed strategies along the maternal-fetal-neonatal axis to guide immune, metabolic, and neurodevelopmental trajectories of the next generation toward a healthier course. Conclusions In this single-center prospective cohort of 21 mother–newborn pairs, neonatal meconium microbiota showed markedly reduced richness and diversity compared with maternal fecal microbiota and formed distinct community clusters. Although Firmicutes predominated in both mothers and neonates, only 57% of pairs shared the same dominant phylum, and concordance was not explained by delivery mode, feeding type, maternal BMI, gestational diabetes, or perinatal antibiotic exposure. These findings indicate that the maternal gut represents a partial reservoir for early neonatal intestinal seeding, but meconium captures an early, low-biomass community shaped by additional stochastic and perinatal influences. Larger, multi-site, multi-omics studies with strain-level resolution and rigorous contamination control are needed to define transmission routes and identify modifiable maternal factors that support healthy microbiota maturation. Abbreviations BMI – Body Mass Index CS – Cesarean Section GNUH – Gyeongsang National University Hospital IRB – Institutional Review Board MTP – Microbiome Taxonomic Profiling OTU – Operational Taxonomic Unit PCoA – Principal Coordinates Analysis TTN – Transient Tachypnea of the Newborn Declarations Ethics approval and consent to participate: This study was reviewed and approved by the Institutional Review Board (IRB) at Gyeongsang National University Hospital (GNUH 2025-06-007). We conducted the present study in accordance with the principles of the Declaration of Helsinki, and the feces used in this study were provided by the GNUH, a member of the Korea Biobank Network. The biospecimen were legally permitted by the Bioethics and Safety Act of the Republic of Korea. Therefore, the consent to participate was waived from the IRB of GNUH. Consent for publication Not applicable. Availability of data and materials All data generated or analyzed during this study are included in this published article. Competing interest The authors declare no competing interests. Funding This work was supported by biomedical research institute fund (GNUHBRIF-2024-0003) from the Gyeongsang National University Hospital. Authors’ contributions JS Park designed the study. JS Park, IA Cho, JY Jo and JS Jun performed sample collection, JS Park analyzed and interpreted the data, JS Park and JY Jo wrote the initial draft of the manuscript. JS Park and JY Jo provided editorial changed to the manuscript. JS Park supervised all aspects of the manuscript process. All authors read and approved the final manuscript. Acknowledgements The biospecimens and data used in this study were provided by the Biobank of GNUH, a member of the Korea Biobank Network. Authors’ information 1 Department of Obstetrics and Gynecology, Gyeongsang National University College of Medicine, Jinju, Korea 2 Department of Obstetrics and Gynecology, Gyeongsang National University Hospital, Jinju, Korea 3 Department of Pediatrics, Gyeongsang National University College of Medicine, Jinju, Korea 4 Department of Pediatrics, Gyeongsang National University Hospital, Jinju, Korea 5 Institute of Medical Science, Gyeongsang National University, Jinju, Korea *Correspondance: Ji Sook Park, M.D., and Ph.D. Address: Department of Pediatrics, Gyeongsang National University College of Medicine 15, Jinju-daero 816beon-gil, Jinju-si, Gyeongsangnam-do, 52727, Republic of Korea Tel: +82-55-750-8156 Fax: +82-55-752-9339 E-mail: [email protected] References Delaroque C, Chassaing B. Microbiome in heritage: how maternal microbiome transmission impacts next generation health. Microbiome. 2025;13:196. Ferretti P, Pasolli E, Tett A, Asnicar F, Gorfer V, Fedi S, et al. 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Nature. 2018;562:583–8. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486:222–7. Fan Y, Pedersen O. Gut microbiota in human metabolic health and disease. Nat Rev Microbiol. 2021;19:55–71. Tan J, McKenzie C, Potamitis M, Thorburn AN, Mackay CR, Macia L. The role of short-chain fatty acids in health and disease. Adv Immunol. 2014;121:91–119. Pammi M, Cope J, Tarr PI, Warner BB, Morrow AL, Mai V, et al. Intestinal dysbiosis in preterm infants preceding necrotizing enterocolitis: a systematic review and meta-analysis. Microbiome. 2017;5:31. Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The microbiota-gut-brain axis. Physiol Rev. 2019;99:1877–2013. Cryan JF. Microbiome and brain development: a tale of two systems. Ann Nutr Metab. 2025;81(Suppl 1):34–46. Delaroque C et al. Maternal diters offspring’s early life host-microbiota communication through goblet cells, resulting in long-lasting diseases susceptibility. bioRxiv. 2024: p. 2024.07:05.602179. Pabst O, Slack E. IgA and the intestinal microbiota: the importance of being specific. Mucosal Immunol. 2020;13:12–21. Reyman M, van Houten MA, van Baarle D, Bosch AATM, Man WH, Chu MLJN, et al. Impact of delivery mode-associated gut microbiota dynamics on health in the first year of life. Nat Commun. 2019;10:4997. Dos Santos SJ, Pakzad Z, Albert AYK, Elwood CN, Grabowska K, Links MG, et al. Maternal vaginal microbiome composition does not affect development of the infant gut microbiome in early life. Front Cell Infect Microbiol. 2023;13:1144254. Yoon S-H, Ha S-M, Kwon S, Lim J, Kim Y, Seo H, et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol. 2017;67:1613–7. Xie H, Meng L, Duan X, Liang X, Huang T, Ma G, et al. Establishment of the early gut microbiota in vaginally delivered infants: the influence of maternal gut microbiota outweighs vaginal microbiota. Microbiol Spectr. 2025;13:e0177525. Caprara GL, von Ameln Lovison O, Martins AF, Bernardi JR, Goldani MZ. Gut microbiota transfer evidence from mother to newborn. Eur J Pediatr. 2024;183:749–57. Iqbal F, Shenoy PA, Lewis LES, Siva N, Purkayastha J, Eshwara VK. Influence of perinatal antibiotic on neonatal gut microbiota: a prospective cohort study. BMC Pediatr. 2025;25:560. Hu J, Nomura Y, Bashir A, Fernandez-Hernandez H, Itzkowitz S, Pei Z, et al. Diversified microbiota of meconium is affected by maternal diabetes status. PLoS ONE. 2013;8:e78257. He Q, Kwok LY, Xi X, Zhong Z, Ma T, Xu H, et al. The meconium microbiota shares more features with the amniotic fluid microbiota than the maternal fecal and vaginal microbiota. Gut Microbes. 2020;12:1794266. Beller L, Deboutte W, Falony G, Vieira-Silva S, Tito RY, Valles-Colomer M, et al. Successional stages in infant gut microbiota maturation. mBio. 2021;12:e0185721. Wampach L, Heintz-Buschart A, Hogan A, Muller EEL, Narayanasamy S, Laczny CC, et al. Colonization and succession within the human gut microbiome by archaea, bacteria, and microeukaryotes during the first year of life. Front Microbiol. 2017;8:738. Grech A, Collins CE, Holmes A, Lal R, Duncanson K, Taylor R, et al. Maternal exposures and the infant gut microbiome: a systematic review with meta-analysis. Gut Microbes. 2021;13:1–30. Toubon G, Patin C, Delannoy J, Rozé JC, Barbut F, Ancel PY, et al. Very preterm gut microbiota development from the first week of life to 3.5 years of age: a prospective longitudinal multicenter study. Microbiol Spectr. 2025;13:e0163624. Turunen J, Tejesvi MV, Paalanne N, Pokka T, Amatya SB, Mishra S, et al. Investigating prenatal and perinatal factors on meconium microbiota: a systematic review and cohort study. Pediatr Res. 2024;95:135–45. Chu DM, Antony KM, Ma J, Prince AL, Showalter L, Moller M, et al. The early infant gut microbiome varies in association with a maternal high-fat diet. Genome Med. 2016;8:77. Chang Y-S, Li C-W, Chen L, Wang X-A, Lee M-S, Chao Y-H. Early gut microbiota profile in healthy neonates: microbiome analysis of the First-Pass meconium using next-generation sequencing technology. Child (Basel). 2023;10:1260. Shao Y, Forster SC, Tsaliki E, Vervier K, Strang A, Simpson N, et al. Stunted microbiota and opportunistic pathogen colonization in caesarean-section birth. Nature. 2019;574:117–21. Kim S, Oh J-W, Yun J-W. Narrative review on the trend of childbirth in South Korea and feasible intervention to reduce cesarean section rate. J Korean Soc Matern Child Health. 2023;27:1–13. Cho KH, et al. Influence of maternal weight dynamics prior to and throughout gestation on early infant gut microbiome colonization. Microb Ecol. 2025;88:1–11. Additional Declarations No competing interests reported. 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11:58:06","extension":"xml","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":132149,"visible":true,"origin":"","legend":"","description":"","filename":"e9cec94bf245401e95ad5107c98b2fb61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/5f7fccdd1be0492e138f2c66.xml"},{"id":100400360,"identity":"d5bb14c6-b5af-4996-bef5-1e7d47ceb363","added_by":"auto","created_at":"2026-01-16 11:58:06","extension":"html","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":141809,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/f4c350361578243bca3bfe8c.html"},{"id":100421520,"identity":"543562f0-5b58-4db0-9350-2db0854857fc","added_by":"auto","created_at":"2026-01-16 13:33:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":367716,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the fecal microbiome in maternal stool and neonatal meconium samples. The inner circle represents phylum-level composition, and the outer circle represents species-level composition.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/b813726b088b69ee4fa74c4c.png"},{"id":100400058,"identity":"087d387a-31f6-4fdf-b98b-c6361626751b","added_by":"auto","created_at":"2026-01-16 11:57:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35739,"visible":true,"origin":"","legend":"\u003cp\u003eAlpha diversity of the gut microbiota in mothers and infants.\u003cbr\u003e\nSpecies richness and diversity indices are shown for maternal (Mother, \u003cem\u003en\u003c/em\u003e = 21) and infant (Baby, \u003cem\u003en\u003c/em\u003e = 25) samples. Higher values indicate greater within‑sample diversity. Group differences between mothers and infants were assessed using the Wilcoxon rank‑sum test. Abbreviations; ACE, abundance-based coverage estimator; OTUs, observed operational taxonomic units.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/05a187bcdfeeab225aae34a1.png"},{"id":100400367,"identity":"2d392b80-1cb3-4d7d-9e36-71b1f6036010","added_by":"auto","created_at":"2026-01-16 11:58:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46522,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of gut microbial β‑diversity at the species level.\u003c/p\u003e\n\u003cp\u003ePrincipal Coordinates Analysis (PCoA) plot based on Generalized UniFrac distances illustrates compositional differences between maternal fecal (blue circle) and neonatal meconium (pink circle) samples. The first two principal coordinates explain 34.3% (PC1) and 22.2% (PC2) of the total variance, respective\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/ac64c051772f81a9004d1aa5.png"},{"id":101669680,"identity":"803c86ec-0804-44a4-a261-b345600073da","added_by":"auto","created_at":"2026-02-02 12:26:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1135157,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8517689/v1/577d9c35-46d6-49e6-a982-8edc4a04bdc3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of maternal fecal microbiota on the early development of microbial community in the neonatal meconium","fulltext":[{"header":"Background","content":"\u003cp\u003eThe human gut microbiota is a dynamic ecosystem that undergoes rapid expansion and maturation beginning at birth. Maternal microbial strains originating from the vagina, skin, and gut constitute the dominant inoculum in early life, outweighing other sources. Subsequently, the composition and functional capacity of the gut microbial community change rapidly in response to breastfeeding, weaning, and later dietary transitions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. During the neonatal period, the gut microbiota is characterized by low diversity; however, with the initiation of weaning, microbial richness and complexity progressively increase [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Concurrently, bidirectional interactions between intestinal epithelial cells and resident microbes promote maturation of metabolic functions related to substrate utilization and contribute to the biosynthesis of essential nutrients for the host [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Large-scale cohort studies have consistently described this process as a stepwise pattern of microbial maturation [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Although the exact trajectory is modulated by interindividual variability, environmental exposures, and methodological factors, a shared developmental axis has been repeatedly observed across populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhen this developmental program is disrupted or unhealthy dietary patterns persist, accumulating evidence indicates an increased risk of non-communicable diseases, such as allergies, obesity, and inflammatory bowel disease, attributable to impaired immune maturation and dysregulation of metabolic-inflammatory pathways [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In preterm infants, microbial dysbiosis often precedes clinical disease. In cases of necrotizing enterocolitis, reproducible increases or depletions of specific microbial taxa have been observed before onset [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These associations intersect with patterns of antibiotic exposure, feeding modalities, and modes of delivery. Furthermore, recent literature suggests that early microbiota-host interactions extend to neurodevelopmental pathways, indicating that the gut-brain axis may influence long-term health outcomes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Accordingly, strategies aimed at steering infant gut microbiota colonization toward a health-promoting trajectory are of critical importance, and identification of the key determinants underlying this process represents a necessary first step. Previous studies have demonstrated that mode of delivery, exposure to intrapartum or perinatal antibiotics, breastfeeding, timing of weaning and introduction of solid foods, and maternal diet exert substantial influences on initial microbial community assembly [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Notably, studies that rigorously account for the low-biomass nature of first-pass meconium indicate that \u0026ldquo;immediate perinatal\u0026rdquo; factors, particularly delivery mode and intrapartum antibiotic administration, explain a greater proportion of variance in meconium microbiota composition than putative in utero influences [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, Dos Santos et al. reported weaker associations between perinatal factors and gut microbial community structure later in infancy, suggesting that additional determinants become increasingly influential over time [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The precise mechanisms underlying neonatal gut microbiota community assembly remain incompletely understood.\u003c/p\u003e \u003cp\u003eTherefore, the present study aimed to investigate the impact of maternal fecal microbiota on early neonatal gut microbiota community formation by enrolling maternal-neonatal pairs and collecting paired fecal samples under uniform environmental conditions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eBetween January and June 2024, stool specimens were prospectively collected from mother-newborn pairs. Maternal samples were collected aseptically before delivery, and neonatal samples were obtained within the first week after birth, following informed consent from the Korea Biobank Network. Immediately after collection, all specimens were frozen at \u0026minus;\u0026thinsp;80\u0026deg;C and stored in the Biobank of Gyeongsang National University Hospital (GNUH), a member of the Korea Biobank Network, until analysis.\u003c/p\u003e \u003cp\u003eFor microbiota analysis, frozen fecal samples were thawed, resuspended, homogenized, subjected to bead-beating, and centrifuged at 14,000 \u0026times; g for 10 minutes. The resulting supernatants were diluted with nuclease-free water and used as templates for polymerase chain reaction amplification. The V3\u0026ndash;V4 hypervariable region of the bacterial 16S rRNA gene was amplified using primers 341F and 805R. Amplicons from individual samples were combined in equimolar amounts and purified using the AMPure XP purification kit (Beckman Coulter, Indianapolis, IN, USA), following the manufacturer\u0026rsquo;s protocol. Purified libraries were sequenced on an Illumina MiSeq platform with the MiSeq Reagent Kit v3 (Illumina, San Diego, CA, USA) using 2 \u0026times; 250 bp paired-end reads. Extraction of bacterial DNA from fecal samples for 16S rRNA gene sequencing and initial taxonomic assignment was performed by a commercial provider (CJ Bioscience, Seoul, Korea). Taxonomic profiling of bacterial communities was conducted with EzBioCloud\u0026rsquo;s Microbiome Taxonomic Profiling (MTP) cloud pipeline using the PKSSU4.0 reference database. Organisms sharing\u0026thinsp;\u0026ge;\u0026thinsp;95% average nucleotide identity were grouped into a single \u0026ldquo;species group,\u0026rdquo; as individual members cannot be reliably distinguished at the sequence identity thresholds typically applied in 16S rRNA gene\u0026ndash;based profiling. A comprehensive list of conventional species names corresponding to each species group is available on the EzBioCloud taxonomy page (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ezbiocloud.net/mtp/taxonomy\u003c/span\u003e\u003cspan address=\"https://www.ezbiocloud.net/mtp/taxonomy\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo enable comparison of α-diversity indices among samples, read counts were rarefied to 1,000 reads per sample, representing the lowest sequencing depth in the dataset. For β-diversity analyses, read abundances were adjusted for 16S rRNA gene copy number variation to reduce compositional bias. Species richness was estimated using an abundance-based coverage estimator and by enumerating observed operational taxonomic units (OTUs). Overall diversity was summarized using the NPShannon index, while phylogenetic diversity was calculated from the OTU occurrence matrix. Differences in OTU composition between samples were quantified using generalized UniFrac distance and visualized with principal coordinate analysis (PCoA) combined with K-means clustering.\u003c/p\u003e \u003cp\u003eWe also obtained demographic and perinatal factors, including delivery mode, gestational age, maternal weight, offspring birth weight, use of antibiotics, and feeding methods of the mother and baby pair from the Biobank of GNUH. Differences in fecal microbial composition were analyzed according to these factors to investigate potential associations with neonatal gut microbiota patterns.\u003c/p\u003e \u003cp\u003eContinuous variables are presented as means and standard deviations (SD), and categorical variables are expressed as numbers and percentages. Maternal or neonatal factors were analyzed using Fisher\u0026rsquo;s exact test or the Mann-Whitney U test, as appropriate. Associations between taxonomic profile variations, diversity indices, and sample categories of mothers and neonates were assessed using the Wilcoxon rank-sum test and permutational multivariate analysis of variance (PERMANOVA). Taxonomic profiling of fecal microbiota across groups and related statistical analyses were conducted using the EzBioCloud taxonomy webpage (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps:/www.ezbiocloud.net/mtp/view\u003c/span\u003e\u003cspan address=\"https://www.ezbiocloud.net/mtp/view\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e myMTPSetAnalyzer) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Correlation analyses between demographic or perinatal factors of mother\u0026ndash;neonate pairs and concordance of the dominant phylum were performed using logistic regression analysis in SPSS 27.0 (IBM, NY, US), and graphical representations were generated with GraphPad Prism 10.0.2 (GraphPad Software, Boston, US).\u003c/p\u003e \u003cp\u003eThis study was approved by the Institutional Review Board of GNUH (GNUH 2025-06-007).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the study period, a total of 21 mothers and 25 neonates were included (Table\u0026nbsp;1). The mean maternal age was 34.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7 years, and the mean maternal height was 161.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3 cm. The mean pre-pregnancy body mass index (BMI) was 23.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4 kg/m\u0026sup2;, and increased to 27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 kg/m\u0026sup2; at the time of delivery. The mean maternal weight during late pregnancy was 71.3\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3 kg. Maternal stool samples were collected before delivery, with a mean sampling interval of -0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 days relative to birth. Six women (28.6%) received antenatal betamethasone for threatened preterm birth. Pregnancy-related complications included prolonged preterm rupture of membranes in two mothers (M2 and M7, 9.5%), both of whom received antibiotic therapy within one week before delivery. Gestational diabetes mellitus (GDM) was diagnosed in six mothers (28.6%), and glycemic control was adequately achieved through dietary modification or insulin therapy. Twin pregnancies occurred in four cases (19%). Parity was nearly evenly distributed, with 11 primiparous women (52.4%) and 10 multiparous women (47.6%): most multiparous women were in their second pregnancy. Neonatal baseline characteristics are as follows. The mean gestational age at birth was 36.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 weeks, and the mean birth weight was 2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 kg. The mean 5-minute Apgar score was 9.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5, with scores ranging from 8 to 10. Meconium samples were collected from neonates at a mean of 4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 days after birth, and the mean duration of hospital stay was 7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 days. Fourteen neonates (56.0%) were female. Four neonates (B17, B18, B23, and B24; 16.0%) developed tachypnea shortly after birth and were diagnosed with transient tachypnea of the newborn (TTN). Five neonates (B2, B11, B12, B13, and B17; 29.4%) received antibiotic treatment during hospitalization, and all were exposed to antibiotics before stool sample collection.\u003c/p\u003e \u003cp\u003eFecal microbiota analyses were conducted for 21 mothers and 25 corresponding offspring using 16S-based MTP. \u003cem\u003eFirmicutes\u003c/em\u003e was identified as the most prevalent bacterial phylum in both mothers and neonates (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Concordance of the dominant phylum between mothers and neonates was observed in 12 mother-neonate pairs (57.1%), including M1-B1, M3-B3, M4-B4, M5-B5, M7-B7, M8-B8, M10-B11, M11-B12, M12-B13, M14-B15, M16-B18, and M20-B23-B24. In contrast, the remaining 42.9% of pairs showed discordant dominant phyla (Table\u0026nbsp;1). Among the four mothers who delivered twins (M1, M10, M18, and M20), only one twin pair shared the same dominant phylum as their mother (M20-B23-B24), whereas the remaining twin pairs did not.\u0026nbsp;\u003c/p\u003e \u003cp\u003eTable 1. Clinical Characteristics of mothers and neonates participating in the study (M = 21, B = 25)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"116%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003ePairs of mother and Baby\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"9\" valign=\"top\" style=\"width: 529px;\"\u003e\n \u003cp\u003eMaternal factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 472px;\"\u003e\n \u003cp\u003eNeonatal factors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003eAge (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eWt (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003cp\u003e(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eObstetric problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eprimipara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eAntibiotics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eDel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003eStool\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eGA (week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eBW (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eantibiotics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eformula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 149px;\"\u003e\n \u003cp\u003eStool\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eDay\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eDominant phylum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eDay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eDominant phylum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM1-B1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e40.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e79.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eTwin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM2-B2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e31.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e88.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e34.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM, PPROM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eVD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM3-B3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e40.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e79.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e27.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM4-B4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e62.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e24.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e-3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM5-B5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e35.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ePTL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e34.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM6-B6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e37.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e49.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eFGR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eBac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e37.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM7-B7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e75.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e31.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM, PPROM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM8-B8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e39.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e59.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e23.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM, PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM9-B9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e77.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eVD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e39.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM10-B10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e30.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 48px;\"\u003e\n \u003cp\u003e73.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e25.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eTwin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-B11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e37.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM11-B12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e27.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e64.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM12-B13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e54.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003ePTL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eVD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM13-B14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e32.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e64.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e27.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eBac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e1.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM14-B15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e25.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e55.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM15-B16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e32.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e64.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM16-B17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e35.2\u003c/p\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 48px;\"\u003e\n \u003cp\u003e63.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e26.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eIUGR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-B18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM17-B19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e131.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM18-B20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e33.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 48px;\"\u003e\n \u003cp\u003e66.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e27.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eTwin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-B21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e36.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM19-B22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e30.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eWM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003ePro\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM20-B23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e30.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 48px;\"\u003e\n \u003cp\u003e70.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e27.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eGDM, Twin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e-B24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e35.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e2.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eM21-B25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e 33.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e68.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003eFir\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e39.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eChl\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: Wt, weight; GDM, gestational DM; PPROM, prolonged rupture of membranes defined as the rupture of the amniotic membrane more than 18 hours before delivery; PTL, preterm labor pain; PE, preeclampsia; IUGR, intrauterine growth restriction; CS, Cesarean section; VD, vaginal delivery; WM, whole milk feeding; BM, breast milk feeding; Fir, Firmicutes; Pro, Proteobacteria; Bac, Bacteroidetes; Chl, Chlorobi; Y, yes; N, no.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe clinical characteristics of mother-neonate pairs with concordant\u0026nbsp;dominant phyla (n = 12) and those with discordant dominant phyla (n = 11) are summarized in Table 2. No statistically significant differences in maternal or neonatal factors were identified between the two groups. Maternal pre- and late-pregnancy BMI values were higher in the discordant dominant phylum group than those in the concordant group; however, the difference was not statistically significant. We performed logistic regression analyses to identify factors associated with concordance; however, no statistically significant associations were observed (Table 2). Since maternal and neonatal factors were analyzed separately according to dominant phylum concordance within mother-neonate pairs, M10 was considered as one in the discordant group. During analyses, the factors of the M10-B10-B11 pair were not duplicated, although the pair was classified into one concordant pair (M10-B11) and one discordant pair (M10-B10), respectively. Using this approach, cesarean section (CS) delivery, multiple gestation, gestational age, birth weight, tachypnea, and postnatal antibiotic exposure were associated with a lower likelihood of dominant phylum concordance (Exp [B] \u0026lt; 0.8); however, no statistical significance was observed (Table 3).\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of clinical characteristics in mother-neonate pairs between concordant and discordant dominant phylum groups\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003eFactors, Mean \u0026plusmn; SD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eConcordant pair\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(n = 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eDiscordant pair\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(n =11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eMaternal factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAge (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e35.7 \u0026plusmn; 6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e34.6 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.468\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eWeight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e66.9 \u0026plusmn;10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e75.7 \u0026plusmn; 21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eBMI, pre-pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e22.3 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e24.0 \u0026plusmn; 6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eBMI at delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e25.7 \u0026plusmn; 3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e28.9 \u0026plusmn;7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003ePrimiparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e5 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e6 (54.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eStool collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e-0.4 \u0026plusmn; 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.0 \u0026plusmn; 0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eCS delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e9 (90.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e9 (81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eNeonatal factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eGA (week)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e36.5 \u0026plusmn; 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e37.1 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eBirth Weight (kg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e2.57 \u0026plusmn; 0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e2.86 \u0026plusmn; 0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e6 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eStool day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e4.4 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e4.2 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eBreast milk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e6 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eTachypnea\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1 (8.3_\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.593\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eAntibiotics\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e3 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e2 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eHospital duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e8.0 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e6.8 \u0026plusmn; 6.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e0.194\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003eP\u003c/em\u003e-values were obtained using Fisher\u0026rsquo;s exact test or the Mann-Whitney test.\u003c/p\u003e\n\u003cp\u003eAbbreviations: SD, standard deviation; BMI, body mass index; GDM, gestational diabetes mellitus; CS, Cesarean section; GA, gestational age.\u003c/p\u003e\n\u003cp\u003eTable 3. Logistic regression analysis of maternal or neonatal clinical factors associated with concordant dominant phylum\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 241px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExp (B)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI (lower-upper)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003eMaternal factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eAge, year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e1.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.853\u0026ndash;1.264\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.691\u0026ndash;1.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eWeight changes, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.834\u0026ndash;1.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eCS delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.029\u0026ndash;5.214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eGDM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.124\u0026ndash;5.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003ePrimi-parous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.131\u0026ndash;4.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMulti-gestation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.037\u0026ndash;6.683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" valign=\"top\" style=\"width: 105px;\"\u003e\n \u003cp\u003eNeonatal factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eGA, week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.463\u0026ndash;1.290\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.324\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eBirth weight, kg\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.146\u0026ndash;1.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eMale\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.171\u0026ndash;4.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eBM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.171\u0026ndash;4.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003eTachypnea\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.027\u0026ndash;3.407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 136px;\"\u003e\n \u003cp\u003ePostnatal antibiotics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 169px;\"\u003e\n \u003cp\u003e0.091\u0026ndash;4.889\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; CS, Cesarean section; GDM, gestational diabetes mellitus; GA, gestational age; BM, breast milk.\u003c/p\u003e\n\u003cp\u003eWe compared \u0026alpha;‑diversity between maternal fecal samples (n = 21) and neonatal meconium samples (n = 25) using two complementary metrics, such as species richness (observed features) and a community diversity index, and evaluated group differences using a two‑sided Wilcoxon rank‑sum test. Across both metrics, neonatal meconium exhibited significantly lower \u0026alpha;‑diversity than that of maternal fecal microbiota (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05, Fig. 2). PCoA with K-means clustering at the species level demonstrated clear separation between maternal fecal and neonatal meconium microbiota communities in the score plot, and overall differences in community composition were statistically significant by PERMANOVA (\u003cem\u003eP\u003c/em\u003e = 0.001, Fig. 3).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we examined 21 mother-neonate pairs recruited from a single tertiary medical center to compare maternal fecal microbiota collected shortly before delivery with the offspring\u0026rsquo;s meconium microbiota. The primary aim was to determine whether, and to what extent, the maternal gut microbiota influences the initial formation of the neonatal fecal microbiota community. We observed that mothers and neonates shared a broadly similar phylum-level composition dominated by \u003cem\u003eFirmicutes\u0026nbsp;\u003c/em\u003e(Fig. 1). However, neonatal meconium constituted a low-diversity, low-biomass community, exhibiting significantly reduced species richness and lower Shannon indices than maternal stool (Fig. 2). Furthermore, maternal fecal and neonatal meconial microbiota communities were clearly segregated (Fig. 3), indicating the establishment of distinct ecological niches. When mother-neonate pairs were stratified into groups with \u0026ldquo;concordant\u0026rdquo; versus \u0026ldquo;discordant\u0026rdquo; dominant phyla and compared across clinical variables, no statistically significant associations were observed with perinatal factors such as pre-pregnancy and gestational weight, gestational diabetes, mode of delivery, or peripartum antibiotic exposure (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings reinforce the prevailing concept that the maternal gut microbiota serves as a key reservoir for the neonatal intestinal microbiome, while simultaneously demonstrating that the community structure observed in the first meconium is not merely a reduced-scale replica of the maternal fecal microbiota. Recent studies using phylogenetic and genomic analyses have shown that maternal gut, vaginal, and skin microbes are transmitted to the infant gut and oral cavity at the strain level, with the maternal gut microbiota contributing most durably over the long term [2, 19]. Cohort studies further indicate that maternal gut microbes exhibit statistically significant transmission patterns at the amplicon sequence variant level, with higher transmission rates observed in vaginal deliveries [20, 21]. The concordance observed in dominant phyla among certain mother-neonate pairs in this study may be consistent with this \u0026ldquo;maternal dependency\u0026rdquo; hypothesis. At the same time, the markedly reduced alpha diversity (Fig. 2) and the clear separation of maternal and neonatal communities in unweighted distance-based clustering (Fig. 3) suggest that, at birth, the meconium microbiota remains in an early pioneering, or seeding, stage of community assembly [22, 23].\u003c/p\u003e\n\u003cp\u003eTime-series analyses of the intestinal microbiota indicate that, immediately after birth, facultative anaerobes such as \u003cem\u003eEscherichia\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e initially dominate the gut. Over the ensuing months, the microbial community shifts toward a \u003cem\u003eBifidobacterium\u003c/em\u003e-centered configuration. Following weaning, \u003cem\u003eBacteroides\u003c/em\u003e and members of the phylum \u003cem\u003eFirmicutes\u003c/em\u003e increase in abundance, and the ecosystem gradually converges toward an adult-like community structure [24, 25]. In both the Environmental Determinants of Diabetes in the Young cohort and the Swedish longitudinal study, the gut microbiota develops through three stages\u0026mdash;developmental, transitional, and stable\u0026mdash;over the first several years of life, achieving adult-like richness and community composition only around five years of age [5, 7]. The present study is noteworthy because it examines the earliest point along the neonatal gut microbiota successional pathway\u0026mdash;namely, the immediate postnatal meconium\u0026mdash;and evaluates its relationship with the maternal gut microbiota. The observed low diversity and clear separation of neonatal meconium microbiota from their mothers indicate that meconium, although already shaped by environmental, intrauterine milieu, and intrapartum influences, represents a pre-colonization transmission state. This stage precedes the establishment of a fully developed microbial community. At this early time point, the microbial composition likely reflects a composite signal of DNA from maternally derived bacteria, intrapartum contaminants, and a very small number of pioneer colonizers, and thus has a limited capacity to reliably predict the longer-term developmental trajectory of the gut microbiota over subsequent weeks and months.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe influence of maternal and perinatal factors on initial gut communities has been reported with conflicting results. A recent comprehensive review of maternal microbial inheritance concluded that maternal obesity, dysregulated glucose metabolism, and unhealthy dietary patterns\u0026mdash;factors that remodel the maternal gut microbiota\u0026mdash;may exert lasting effects on infant gut microbiome composition and function. These effects, in turn, have the potential to program immune, metabolic, and neurodevelopmental axes, ultimately influencing health outcomes in the next generation [26]. In a large longitudinal cohort of very preterm infants, maternal pre-pregnancy BMI was identified as the only perinatal factor consistently associated not only with hospital length of stay but also with early childhood gut microbial community structure and functional pathways [27]. In contrast, studies focusing on meconium or other low-biomass samples collected immediately after birth have frequently reported weak or inconsistent associations between maternal BMI, mode of delivery, and antibiotic exposure\u0026nbsp;[28-30]. In the present study, although the risk ratios of Exp [B] suggested directional trends for maternal BMI, gestational diabetes, and gestational weight gain in relation to concordant dominant phyla between mothers and neonates, none of these associations reached statistical significance (Tables 2 and 3). Several factors may account for these findings, including the limited sample size, the relatively coarse categorical outcome defined by concordance of the dominant phylum, and the inherent difficulty of detecting subtle effects in meconium, an extremely low-biomass and contamination-prone specimen. Notably, concordance with the maternal dominant phylum was inconsistent in twin deliveries, suggesting that immediate postnatal exposures and stochastic processes may contribute to the observed variability.\u003c/p\u003e\n\u003cp\u003eMode of delivery and intrapartum antibiotic exposure remain among the best-established determinants of gut microbiota trajectories from birth through infancy. Large birth cohorts have shown that infants delivered via CS experience delayed colonization by \u003cem\u003eBacteroides\u003c/em\u003e strains compared with vaginally delivered infants. During the neonatal period, CS-delivered infants\u0026rsquo; intestinal communities are dominated by opportunistic, hospital-associated taxa such as \u003cem\u003eEnterococcus\u003c/em\u003e, \u003cem\u003eEnterobacter\u003c/em\u003e, and \u003cem\u003eKlebsiella\u003c/em\u003e, whose relative abundance remains significantly higher than that in vaginally delivered infants throughout infancy [31]. Previous studies have linked the composition of maternal vaginal and gut microbiomes to fetal and neonatal gut communities. However, most of these studies examined stool samples collected after the first postnatal week, and datasets directly comparing maternal stool with neonatal meconium, as in the present study, remain relatively scarce. Despite the high rates of CS delivery in our study, the absence of clear differences according to dominant phylum concordance\u0026nbsp;suggests that mode of delivery and intrapartum antibiotic exposure may exert a stronger influence on the pace of microbial colonization and community stabilization over the subsequent weeks and months than on the microbial composition captured at the meconium stage.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study has several strengths. First, we analyzed paired maternal-neonatal samples collected within a short interval, enabling direct comparison of maternal stool and neonatal meconium obtained immediately after delivery. Second, both maternal stool and neonatal meconium were prospectively collected and processed using an identical analytical pipeline, ensuring methodological consistency and minimizing technical variability. Nonetheless, several limitations must be acknowledged. The study was limited by a small sample size, with participants recruited from a single center and representing a relatively homogeneous ethnic background, which constrains the generalizability of the findings. High-risk exposures such as maternal obesity and major obstetric complications were relatively uncommon, reducing the statistical power to detect their potential effects. CS was the predominant mode of delivery in this study (85.7%, n = 18), exceeding the national average of approximately 58% reported for Korea in 2023\u0026nbsp;[32]. The high proportion of CS delivery may have limited our ability to fully assess the contribution of vaginal birth to mother-infant microbial transmission, a limitation similarly reported in other studies requiring practical access to maternal feces at delivery [33]. In addition, we performed only 16S rRNA gene-based relative abundance profiling, which precluded assessment of strain-level transmission and functional pathway dynamics. Finally, because meconium is an extremely low-biomass sample that is inherently susceptible to environmental contamination, residual contamination cannot be entirely excluded for certain low-abundance taxa, despite rigorous preprocessing and inclusion of negative controls.\u003c/p\u003e\n\u003cp\u003eDespite these limitations, our study directly examines the relationship between maternal gut microbiota and neonatal meconium at the dyadic mother-infant level, suggesting that the intuitive assumption\u0026mdash;that maternal gut microbiota overwhelmingly dictates early meconium community structure\u0026mdash;may be only partially valid. Meconium collected immediately after birth exhibited a broadly similar phylum-level profile to maternal stool; however, in terms of alpha diversity and taxonomic composition, it represents a distinct, low-complexity community whose configuration cannot be fully explained by maternal clinical variables alone. By characterizing the microbiota of mother-neonate pairs, including maternal stool at delivery and neonatal meconium, this study contributes to understanding ongoing controversies surrounding the initial assembly of the neonatal gut microbial community. Future studies in larger cohorts should integrate multi-site maternal microbiome (gut, vagina, oral cavity, and skin) with meconium and subsequent infant stools to resolve strain-level transmission and functional potential. Such investigations should also evaluate how modifiable maternal factors\u0026mdash;including dietary patterns, weight management, antibiotic exposure, and infant feeding practices\u0026mdash;shape gut microbiota development and downstream health outcomes throughout infancy and early childhood. Ultimately, a stronger evidence base may enable microbiota-informed strategies along the maternal-fetal-neonatal axis to guide immune, metabolic, and neurodevelopmental trajectories of the next generation toward a healthier course.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this single-center prospective cohort of 21 mother\u0026ndash;newborn pairs, neonatal meconium microbiota showed markedly reduced richness and diversity compared with maternal fecal microbiota and formed distinct community clusters. Although Firmicutes predominated in both mothers and neonates, only 57% of pairs shared the same dominant phylum, and concordance was not explained by delivery mode, feeding type, maternal BMI, gestational diabetes, or perinatal antibiotic exposure. These findings indicate that the maternal gut represents a partial reservoir for early neonatal intestinal seeding, but meconium captures an early, low-biomass community shaped by additional stochastic and perinatal influences. Larger, multi-site, multi-omics studies with strain-level resolution and rigorous contamination control are needed to define transmission routes and identify modifiable maternal factors that support healthy microbiota maturation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e \u0026ndash; Body Mass Index\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCS\u003c/strong\u003e \u0026ndash; Cesarean Section\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGNUH\u003c/strong\u003e \u0026ndash; Gyeongsang National University Hospital\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRB\u003c/strong\u003e \u0026ndash; Institutional Review Board\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMTP\u003c/strong\u003e \u0026ndash; Microbiome Taxonomic Profiling\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOTU\u003c/strong\u003e \u0026ndash; Operational Taxonomic Unit\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCoA\u003c/strong\u003e \u0026ndash; Principal Coordinates Analysis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTTN\u003c/strong\u003e \u0026ndash; Transient Tachypnea of the Newborn\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Institutional Review Board (IRB) at Gyeongsang National University Hospital (GNUH 2025-06-007). We conducted the present study in accordance with the principles of the Declaration of Helsinki, and the feces used in this study were provided by the GNUH, a member of the Korea Biobank Network. The biospecimen were legally permitted by the Bioethics and Safety Act of the Republic of Korea. Therefore, the consent to participate was waived from the IRB of GNUH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by biomedical research institute fund (GNUHBRIF-2024-0003) from the Gyeongsang National University Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJS Park designed the study. JS Park, IA Cho, JY Jo and JS Jun performed sample collection, JS Park analyzed and interpreted the data, JS Park and JY Jo wrote the initial draft of the manuscript. JS Park and JY Jo provided editorial changed to the manuscript. JS Park supervised all aspects of the manuscript process. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe biospecimens and data used in this study were provided by the Biobank of GNUH, a member of the Korea Biobank Network.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u0026nbsp;\u003c/sup\u003eDepartment of Obstetrics and Gynecology, Gyeongsang National University College of Medicine, Jinju, Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eDepartment of Obstetrics and Gynecology, Gyeongsang National University Hospital, Jinju, Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u0026nbsp;\u003c/sup\u003eDepartment of Pediatrics, Gyeongsang National University College of Medicine, Jinju, Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u0026nbsp;\u003c/sup\u003eDepartment of Pediatrics, Gyeongsang National University Hospital, Jinju, Korea\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e5\u0026nbsp;\u003c/sup\u003eInstitute of Medical Science, Gyeongsang National University, Jinju, Korea\u003c/p\u003e\n\u003cp\u003e*Correspondance: Ji Sook Park, M.D., and Ph.D.\u003c/p\u003e\n\u003cp\u003eAddress: Department of Pediatrics, Gyeongsang National University College of Medicine\u003c/p\u003e\n\u003cp\u003e15, Jinju-daero 816beon-gil, Jinju-si, Gyeongsangnam-do, 52727, Republic of Korea\u003c/p\u003e\n\u003cp\u003eTel: +82-55-750-8156\u003c/p\u003e\n\u003cp\u003eFax: +82-55-752-9339\u003c/p\u003e\n\u003cp\u003eE-mail: [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDelaroque C, Chassaing B. 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Microb Ecol. 2025;88:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mother-Neonate Pair, Fecal microbiota, Meconium","lastPublishedDoi":"10.21203/rs.3.rs-8517689/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8517689/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe maternal gut microbiota is regarded as a major contributor to the establishment of the infant gut microbial community; however, the extent to which neonatal meconium microbiota reflects the maternal fecal microbiota remains unclear.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe prospectively collected paired fecal samples from mothers and their offspring after informed consent was obtained. Maternal fecal samples were collected within a week before delivery, and neonatal fecal samples were collected within a week after birth. Fecal microbial compositions were analyzed using 16S-based microbiome taxonomic profiling. Mother\u0026ndash;newborn pairs were stratified according to concordance or discordance of the dominant bacterial phylum, and associated perinatal characteristics were analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 21 maternal-newborn pairs, comprising 21 mothers and 25 neonates, were included in the analysis. \u003cem\u003eFirmicutes\u003c/em\u003e was the predominant phylum in both maternal and neonatal samples, with 12 of 21 pairs (57.1%) exhibiting concordant dominant phyla. Neonatal meconial microbiota showed significantly lower species richness and diversity compared with maternal stool microbiota (Wilcoxon rank-sum, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At the species level, maternal and neonatal fecal microbiota communities formed clearly distinct clusters in ordination analyses, with significant differences in overall community composition (PERMANOVA, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). No statistically significant associations were observed between maternal or neonatal characteristics and concordance of dominant phyla within the pairs.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThese findings suggest that the maternal gut serves as a partial source for early intestinal microbiota formation of the offspring, independent of delivery mode or feeding type. However, additional factors are likely to contribute to the early development of the neonatal gut microbiota.\u003c/p\u003e","manuscriptTitle":"Impact of maternal fecal microbiota on the early development of microbial community in the neonatal meconium","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 08:48:43","doi":"10.21203/rs.3.rs-8517689/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63c75559-0ebd-4f5d-98ee-b19a460c1d09","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T12:23:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 08:48:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8517689","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8517689","identity":"rs-8517689","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}