Background/Objectives: High-fat diets (HFDs) are widely used to induce obesity, but cost-effective and reproducible formulations remain challenging. Moreover, the reversibility of metabolic and gut microbiota alterations following HFD withdrawal is not fully understood. This study evaluated a low-cost HFD model in mice and investigated metabolic, oxidative, and gut microbiota changes during a subsequent 12-week dietary normalization phase. Methods: Male C57BL/6 mice were fed a standard diet (CTN) or a lard-supplemented HFD for 12 weeks (Phase 1), followed by 12 weeks dietary normalization to a standard diet (Phase 2). Body weight, adiposity, blood glucose, biochemical parameters, and oxidative markers were assessed. Fecal samples were analyzed for short-chain fatty acids (SCFAs), microbiota composition (16S rRNA sequencing), and predicted functions using FAPROTAX and PICRUSt2. Results: The HFD significantly increased body weight, abdominal circumference, the Lee index, and adipose tissue mass compared to CTN. Following diet normalization, both groups exhibited weight loss, but the previously obese mice maintained a higher Lee index and distinct lipid and uric acid profiles. No hepatic oxidative stress was detected after normalization. SCFA profiles underwent a temporal shift: CTN showed higher fecal acetate, while HFD mice exhibited elevated butyrate. Functional prediction revealed one pathway associated with an unclassified Rickettsiales bacterium that was exclusively found in HFD mice. The CTN group exhibited a higher abundance of the thiamine diphosphate formation pathway (PWY-7357), suggesting enhanced oxidative metabolism. Conclusions: This low-cost HFD successfully induced obesity and dysbiosis. Dietary normalization resulted in a partial modulation of metabolic and microbial balance, thereby highlighting host–microbe metabolic plasticity.

Development and temporal validation of a deep learning model for automatic fetal biometry from ultrasound videos.

Fetal growth patterns in women with preeclampsia: Insights from the REVAMP study.

Notice of Retraction: "Does an Early Isolated Increase in Fetal Abdominal Circumference Heighten the Risk of Macrosomia? [ID 1242]" and Notice of Retraction: "Does an Early Isolated Decrease in Fetal Abdominal Circumference Heighten the Risk of Growth Restriction? [ID 1300]".

Fetal growth restriction (FGR) is a progressive condition that amplifies risks with advancing gestation. This study develops a time-dependent random survival forest (RSF) model integrating prenatal screening markers to predict FGR and explore temporal factors, aiding clinical decision making for targeted intervention. This was a retrospective cohort study in tertiary hospitals in Taizhou City, China (2016-2022) including 27 543 singleton pregnancies with serial prenatal records, excluding major fetal anomalies or incomplete follow-up. An RSF model was developed using gestational week as the time variable and Delphi-defined FGR as the event. The model incorporates maternal biological data, serologic markers, and ultrasound measurements as feature variables. Performance was assessed using time-dependent receiver operating characteristic (ROC) curves and decision curve analysis (DCA). Feature-based cumulative risk curves were employed for interpreting the model. Main outcomes were measured using model validation (C-index, area under the curve [AUC]) and utility (individual prediction curves, feature risk curve). The RSF model demonstrated high performance (C-index: 0.864), with peak predictive power between 28 and 36 weeks' gestation (AUC: 0.87-0.91). It identified both early- and late-onset FGR. Key predictors included ultrasound markers such as abdominal circumference and femur length. Late-onset FGR was mainly caused by a cumulative mild effect of multiple factors, while early-onset FGR was driven by maternal factors and fetal markers like AFP and E3. The RSF model outperforms traditional models in accuracy and flexibility, providing dynamic FGR risk predictions and supporting timely clinical intervention.

The aim of the study was to identify key fetometric markers in predicting fetal and newborn weight. Methods. The study used data from 5,161 full-term newborns and 8,022 ultrasound examinations conducted using a retrospective design. The sample included objects that meet the criteria for complete clinical information on the main fetometric parameters. The duration of follow-up covered the period from the first ultrasound scan to delivery. The main endpoint of the study was the newborn's birth weight. Descriptive and correlation analysis, multiple linear regression, quantile regression with coefficients accurate to the third digit, as well as machine learning methods (Random Forest and XGBoost) were used to assess the contribution of indicators. Additionally, a principal component analysis (PCA) was performed to determine the overall fetal growth factor. Results. The analysis showed that the circumference of the abdomen correlated with the weight of the newborn with a coefficient of r = 0.820, while the length of the femur and the circumference of the head demonstrated coefficients of r = 0.620 and r = 0.540, respectively. Multiple regression with the inclusion of all three parameters gave the value R2 = 0.730. Quantile regression revealed that the value of the coefficient for abdominal circumference increases for the upper quantile of mass (β = 23,500 at τ = 0.900) compared with the median (β = 18,900 at τ = 0.500). Machine learning methods confirmed the dominant role of abdominal circumference in predicting weight (feature importance – 50-55%), and PCA showed that the first main component, interpreted as a general indicator of size, explains 78% of the variation and has a high correlation with weight (r = 0.850). Conclusion. The results obtained confirm that abdominal circumference is the most informative fetometric indicator for predicting fetal weight, while the length of the femur complements the assessment by reflecting skeletal growth, and the circumference of the head makes a minimal contribution. The complex application of classical statistical methods and machine learning algorithms makes it possible to recommend an emphasis on coolant and DB when assessing fetal weight.

This research presents a comparative analysis of two advanced statistical methodologies for predicting neonatal birth weight using maternal anthropometric measures. We developed and evaluated both Generalized Least Squares (GLS) and Generalized Inverse Regression (GIR) models to account for complex error structures and measurement uncertainties inherent in obstetric data. Data were collected from 150 mothers delivering full-term, singleton infants at a regional hospital, recording maternal weight, abdominal circumference, and neonatal birth weight. The GLS approach addressed correlated errors through covariance matrix transformation, while the GIR model incorporated measurement error adjustments using Stein estimation techniques. Both models demonstrated strong predictive capabilities, with the GLS model achieving slightly better accuracy (R² = 0.78, MAE = 0.15 kg) compared to the GIR model (R² = 0.75, MAE = 0.18 kg). However, the GIR model showed superior robustness in handling measurement errors. The study concludes that both methodologies offer valuable approaches for birth weight prediction, with GLS preferred for optimal accuracy and GIR preferred for enhanced robustness in settings with significant measurement uncertainties.

Objectives Postpartum abdominal skin laxity represents a common yet challenging condition, with increasing demand for effective and safe noninvasive or minimally invasive treatments, such as phototherapy, radiofrequency (RF), and ultrasound, due to their controlled penetration depth and lower risks. Conventional treatments are limited by reason of thermal injury risk and long recovery periods, necessitating safer and more effective interventions. Methods This open-label, single-arm study evaluated bipolar microneedle radiofrequency (MNRF) for treating abdominal skin laxity in 17 postpartum women. Participants received three treatments at 8-week intervals. Assessments included global aesthetic improvement, abdominal circumference (AC), biomechanical properties, and patient satisfaction. Results Significant improvements were observed in skin elasticity, viscoelasticity, and echo density; AC showed a non-significant reduction trend with notable aesthetic enhancement. Histological analysis in one subject showed increased collagen density and restoration of the dermal-epidermal junction. Eighty percent of the subjects expressed satisfaction during the treatment period, with a subjective comfort score of 2.93 ± 1.29 (0–10) and an overall satisfaction of 2.40 ± 0.88 (0–4), and no serious adverse events occurred. Conclusions These results indicate that bipolar MNRF is an effective and safe minimally invasive option for improving postpartum abdominal laxity.

We aim to evaluate the potential contribution of chest computed tomography (CT)-derived body composition parameters in predicting adverse events in sepsis patients with pneumonia. A retrospective study was conducted on sepsis with pneumonia cases who visited Shengjing Hospital of China Medical University from January 2023 to September 2024. We used chest CT scans to quantify skeletal muscle area (SMA) at the fourth thoracic vertebra (T4) and the first lumbar vertebra (L1) levels, as well as abdominal circumference (AC), subcutaneous adipose tissue (SAT), and intramuscular adipose tissue (IMAT) at the L1 level. A total of 303 patients (203 men; median age 70 years, interquartile range 63-79) were included in the study. Fully adjusted models identified low SMAT4, low SATL1, and high ACL1 as independent risk factors for medical intensive care unit (MICU) admission, with odds ratios (ORs) of 0.795, 0.897, and 2.095, respectively. Low SMAT4 (OR 0.880, 95% confidence interval [CI] 0.800-0.967, p = 0.008) and high ACL1 (OR 1.527, 95% CI 1.122-2.079, p = 0.007) were both independently associated with in-hospital mortality. High IMATL1 (β: -2.360, p = 0.003) was associated with a greater decrease in the PaO2/FiO2 ratio during hospitalization. Models using chest CT-derived body composition parameters to predict MICU admission, septic shock, and in-hospital mortality in patients with sepsis were as effective as sequential organ failure assessment scores. The assessment of frailty status and visceral obesity, determined by chest CT measurements of low thoracic muscle mass and elevated AC, is independently correlated with an increased risk of admission to the MICU and mortality among sepsis patients with pneumonia. This underscores the significance of CT-derived body composition as a critical imaging biomarker that reflects the physiological reserve of sepsis patients and their associated risk of adverse events.

Monitoring maternal and fetal health during pregnancy is crucial for preventing adverse outcomes. While tests such as ultrasound scans offer high accuracy, they can be costly and inconvenient. Telehealth solutions and more accessible body shape information provide pregnant women with a convenient way to monitor their health. This study explores the potential of 3D body scan data, captured during the 18-24 gestational weeks, to predict adverse pregnancy outcomes and estimate clinical parameters. We developed a novel algorithm with two parallel streams which are used for extract body shape features: one for supervised learning to extract sequential abdominal level circumference information, and the other for unsupervised learning to extract global shape descriptors, alongside a branch incorporating shape-related demographic data. Our results demonstrated that 3D body shapes can support the prediction of preterm labor and gestational diabetes mellitus (GDM), as well as the estimation of fetal weight. Compared to other machine learning models, our algorithm achieved the best performance, with prediction accuracies exceeding 89% and fetal weight estimation accuracy of 72.22% within a 10% error margin, outperforming the conventional anthropometric measurements-based method by 18.18%.

Introduction: Dental caries and nutritional alterations are common in childhood, particularly in rural communities with limited access to health services. Objective: To determine the association between anthropometric indicators and the presence of dental caries in children aged 5 to 11 years from selected rural communities in the Peruvian Amazon. Methods: Cross-sectional study including 116 children from Llaylla, Pampa Hermosa, and Belén (Satipo, Junín). Body mass index for age (BMI/A), abdominal circumference for age (AC/A), and height for age (H/A) were assessed according to WHO and MINSA standards. Dental caries was evaluated using the DMFT/dmft index and the clinical consequences of untreated dental caries (pufa/PUFA). Associations between anthropometric variables and dental caries were analyzed using logistic regression adjusted for age and sex, with p<0.05 considered statistically significant. Results: Children with overweight/obesity had a higher risk of caries in permanent dentition (OR=3.875) and a lower risk in primary dentition (OR=0.539). Those with high or very high risk according to AC/A showed OR=0.968 in permanent dentition and OR=0.864 in primary dentition. Children with low height for age (H/A) presented OR=1.319 in permanent dentition and OR=1.757 in primary dentition. All associations were not statistically significant (p>0.05). Conclusion: Dental caries is highly prevalent among Amazonian children. Anthropometric indicators were not significantly associated with caries, suggesting the influence of other factors such as diet and access to dental care.

BackgroundPrenatal diagnosis of nervous system malformations associated with the abnormal development of cerebrospinal fluid is most commonly made in the mid-trimester. During early gestation, the choroid plexus is the dominant structure occupying the lateral ventricles. Detection of abnormally positioned choroid plexuses within the fetal head may serve as a novel sonographic marker for the early identification of these malformations.MethodsThis was a retrospective study of singleton pregnancies with nervous system abnormalities. In the first trimester, the choroid plexus area (CPA), choroid plexus length (CPL), occipitofrontal diameter (OFD), head area (HA), head circumference (HC), abdominal circumference (AC), and the distance between the anterior margin of the choroid plexus (CP) and the medial side of the frontal bone (CFD) were measured in the transventricular axial plane. The ratios of CPA/HA, CPL/OFD, CFD/OFD, and HC/AC were also assessed.ResultsA total of 256 fetuses were included in the control group, and a reference range was established. In total, 52 cases with nervous system abnormalities associated with abnormal cerebrospinal fluid development were confirmed. In the control group, the ratios of CPA/HA and CPL/OFD decreased (r = −0.499, −0.216, respectively, both p < 0.001), while the CFD/OFD ratio increased (r = 0.445, p < 0.001). Compared with the control group, scatter diagrams and box-and-whiskers plots showed ventriculomegaly (VM) fetuses had significantly decreased CPA/HA and CPL/OFD ratios (p < 0.001), but increased CFD/OFD and HC/AC ratios (p < 0.001). The CPA/HA, CPL/OFD, and CFD/OFD ratios were all significantly higher in fetuses with open spina bifida (OSB) (p < 0.05). Fetuses with microcephaly showed a significantly higher CPA/HA ratio (p < 0.001), higher CPL/OFD ratio (p < 0.001), and lower HC/AC ratio (p < 0.05).ConclusionChoroid-plexus-to-head ratios offer an objective means of assessing nervous system malformations associated with abnormal cerebrospinal fluid development during the first trimester.

Prenatal exposure to legacy and emerging PFAS and sex-specific associations with fetal growth: Evidence from a Chinese birth cohort.

Amniotic fluid volume, measured in terms of the amniotic fluid index (AFI), is used widely in prenatal care to assess fetal health and development. We investigated whether distinct longitudinal AFI trajectories exist during pregnancy and their association with fetal growth. This secondary analysis of a randomized controlled trial included singleton pregnancies without pre-existing or gestational diabetes mellitus that received prenatal care at National Taiwan University Hospital in Taipei and its Hsin-Chu Branch in Hsinchu, Taiwan. Ultrasonography was performed at 22 + 0 to 24 + 6 weeks, 30 + 0 to 32 + 6 weeks, 35 + 0 to 37 + 6 weeks and at admission for delivery to measure fetal biometry and AFI. Neonatal anthropometrics and adiposity were measured at delivery. Group-based trajectory modeling was used to identify distinct AFI trajectory patterns during pregnancy. Regression analysis was used to determine differences in fetal and neonatal parameters between AFI trajectory groups, with adjustment for confounders. Overall, 802 pregnancies were included. Two AFI trajectory patterns were identified: one characterized by gradually decreasing AFI during gestation and the other by gradually increasing AFI. On linear regression analysis, compared with the decreasing AFI trajectory, increasing AFI was associated with higher gestational-age-specific Z-scores for abdominal circumference (P = 0.003) and estimated fetal weight (P = 0.036) at 30 + 0 to 32 + 6 weeks, as well as higher sex- and gestational-age-specific Z-scores for birth weight (P = 0.019), neonatal head circumference (P = 0.011), neonatal chest circumference (P = 0.009) and neonatal skinfold thickness (subscapular, P = 0.004; triceps, P = 0.002), after adjusting for maternal prepregnancy body mass index, history of gestational diabetes mellitus and fasting plasma glucose and triglyceride levels. The adjusted odds ratio of high neonatal adiposity for the increasing vs decreasing AFI trajectory was 2.47 ((95% CI, 1.21-5.11); P = 0.014). An increasing AFI trajectory during pregnancy was associated with enhanced intrauterine fetal growth, higher birth weight and greater neonatal adiposity. This highlights the potential of AFI trajectory to serve as an indicator of fetal growth alongside fetal biometry. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

An important part of prenatal care is gender determination, which shows expectant parents and medical professionals significant personal and medical insights. It becomes extremely important to determine early fetal gender for enhancing treatment approaches for sex-chromosome-related illnesses, like X-linked disorders. Objectives: To investigate the relationship between fetal gender determination during the second and third trimesters of pregnancy and ultrasound-based fetal biometric parameters, including estimated fetal weight (EFW), femur length (FL), abdominal circumference (AC), head circumference (HC), and biparietal diameter (BPD). Methods: This cross-sectional comparative study was conducted at the Radiology Department of Meer Khan Children and Family Hospital. Women between 14–40 weeks of gestation undergoing ultrasound for fetal assessment were included. Data were analyzed using SPSS version 26.0, applying an independent samples t-test and one-way ANOVA with a significance level set at p&lt;0.05. The Shapiro-Wilk test was used in order to evaluate the data distribution normality. Results: The study found biometric ultrasound measurements of 125 fetuses (63 male and 62 female). Three important metrics showed higher values were found in male fetuses: Male had significantly higher FL (p=0.002, 95% CI: 3.16–14.28 mm). The test also indicated male with significantly higher AC, p=0.005, 95% CI: 10.77–58.44 mm, also significantly higher HC (p=0.016), 95% CI: 5.06–48.10 mm, in male was observed. Conclusions: Male fetuses had increased BPD and EFW compared to the female fetuses, whereas EFW and BPD showed non-significant trends toward higher values in male. Moreover, male fetuses have significantly greater AC, FL, and head circumference HC than female fetuses.

This study investigated populations of children at increased health risks using an integrated analysis of anthropometric/body composition data. A cross-sectional study of elementary school students (first-sixth grade) was conducted from 2020 onward. Body composition measurements using bioelectrical impedance method, anthropometric measurement, and sub-measures (abdominal circumference, serum lipid levels, activity level, and sleep duration) were performed. Measurements were repeated at 1 and 2 years. Body composition data were standardized using polynomial regression models, and hierarchical clustering analysis was performed to identify subpopulations. Reference value models were constructed using 917 standardized body composition data. Cluster analysis of standardized body composition data with body mass index (BMI) identified five clusters. Two high BMI clusters were identified: one characterized by high fat and muscle mass, and the other by high fat but average muscle mass. Cluster classification revealed significant effects for body fat percentage, abdominal circumference, lipid-related indicators, and sleep duration. The subpopulation with high fat/average muscle mass had high body fat percentage, large abdominal circumference, high lipid-related indices, and short sleep duration. Anthropometric and body composition data integration identified a subgroup of children at increased health risk, highlighting the importance of incorporating body composition assessment into routine childhood physical examinations. We established reference data for fat mass, lean body mass, muscle mass, bone mass, and total water mass indices in children aged 7 to 14 years. Integrating anthropometric and body composition data allowed effective identification of pediatric subpopulations at increased health risks, even in generally healthy populations. Children with a high fat mass but average muscle mass had a high body fat percentage, large abdominal circumference, poor lipid profiles, and shorter sleep duration. Incorporating body composition analysis into standard health checkups for children could facilitate the identification of groups at high risk of health problems.

Pre-eclampsia (PE) and fetal growth restriction (FGR) have been shown to impact fetal cardiac remodeling in the third trimester and postnatally, with evidence to suggest that this leads to increased long-term cardiovascular risk. This study aimed to examine fetal cardiac remodeling in pregnancies with PE and/or FGR during the second trimester. This was a retrospective nationwide cohort study of ultrasound images from routine screening at 18-22 weeks of gestation in Denmark. We included 139 430 singleton pregnancies that were conceived spontaneously for which at least one relevant standardized cardiac plane (four-chamber view and/or three-vessel view) was available from the second-trimester scan. An artificial intelligence model performed automated segmentation and extraction of fetal cardiac biometric measurements. Data were collected for four groups: the reference group, defined as appropriate-for-gestational-age (AGA) fetuses from a normotensive pregnancy (n = 131 150); AGA fetuses from a PE pregnancy (AGA + PE group; n = 3095); FGR fetuses from a normotensive pregnancy (normotensive + FGR group; n = 4572); and FGR fetuses from a PE pregnancy (PE + FGR group; n = 613). Differences between groups in cardiac biometric measurements were presented as Z-scores adjusted for abdominal circumference at the second-trimester scan. Compared with the reference group, fetuses in the PE + AGA group had significantly larger right-sided heart structures, and the main pulmonary artery (MPA) and ventricular septum were wider. Fetuses in the normotensive + FGR group displayed significantly smaller cardiac structures, including smaller MPA and ascending aorta diameters, and increased left ventricular sphericity compared with the reference group. Fetuses in the PE + FGR group differed significantly from the reference group only in terms of smaller left atrial area, narrower ascending aorta and increased left ventricular sphericity. However, PE + FGR fetuses had significantly wider MPA andventricular septumand larger right-sided structures compared with normotensive + FGR fetuses, mimicking the features of the PE + AGA group, suggesting a distinct effect of PE on fetal cardiac remodeling. Cardiac remodeling is evident as early as the second trimester, with distinct patterns of modulation in fetuses from pregnancies affected by PE vs FGR. In particular, PE is associated with an enlarged right heart and greater MPA diameter. Understanding these early differences in fetal cardiac morphology may improve risk prediction models and guide early intervention to improve long-term cardiovascular outcome. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Abstract Disclosure: M. Romero Ibarguengoitia: None. A. Abrego-Sánchez: None. A. Ramirez Cazares: None. D. Gutierrez González: None. A. Sánchez García: None. I. Fernández Chau: None. A. González Cantu: None. Few studies evaluate the impact of both paternal and maternal health status during pregnancy, as well as birth weight and early feeding, as indicators of obesity in adolescents. This study aims to provide insights into the role these factors through the long-term follow-up of a cohort of adolescents (10-12 years old) who received yearly medical check-ups since the pregestational stages. Information related to paternal and maternal history during pregnancy, birth weight, and early feeding was obtained from medical records. Additionally, indicators of the adolescents’ health such as body mass index (BMI), abdominal circumference, metabolic syndrome severity score (MSSS) percentile, blood pressure (BP), lipids, creatinine, uric acid, and glucose were collected. We evaluated a total of 134 adolescents, 74 (55.2%) males, with a median (IQR) age of 11 (1) years. A total of 52 subjects were overweight or obese. When comparing between normal weight vs. overweight/obesity groups, the latter had higher systolic (SBP) and diastolic (DBP) blood pressure [SBP 100(10) mmHg vs. 100(13) mmHg, p=0.002)], (DBP 60(5) vs 60(10), p=0.016)]. Other parameters that were higher in overweight or obese were creatinine (0.49(0.07) vs 0.53(0.1) mg/dl, p=0.002), uric acid (3.8(0.9) vs 4.7(1.1) mg/dl, p&amp;lt;0.001), and MSSS percentile (35.9(23) vs 58.5(24) %, p&amp;lt;0.001). Multiple regression models were performed in which the independent variable was the adolescents’ BMI percentile and abdominal circumference. In the first model, predictors for BMI percentile were paternal type 2 diabetes mellitus (ß= 0.161, p=0.003) and adolescent birth weight (ß 0.153, p=0.005), R2 of 0.649. Predictors for abdominal circumference were exclusive breastfeeding time (ß= -0.116, p=0.040) and maternal obesity (ß= 0.150, p=0.007), with an R2 of 0.614. In conclusion, this long-term follow-up study demonstrates the impact of paternal diabetes, maternal obesity, and duration of exclusive breastfeeding as predictors of BMI and abdominal circumference percentiles in their offspring during the adolescent years, with their ensuing implications for metabolic function. Presentation: Monday, July 14, 2025

Disclosure: M. Mirabelli: None. M. Greco: None. F.S. Brunetti: None. E. Chiefari: None. D.P. Foti: None. A. Brunetti: None.Background: Prothymosin-alpha (ProT-α), an immunomodulatory protein, has recently gained attention as a biomarker of obesity-driven insulin resistance (IR), particularly among women. Although its significance in metabolic disorders is increasingly recognized, its specific role in gestational diabetes mellitus (GDM) and fetal growth (FG) remains less understood. Known contributors to GDM—such as maternal hyperglycemia, obesity, and placental dysfunction—can affect FG, yet pinpointing which pregnancies are most at risk is often challenging. In this observational study, we explored the associations among maternal metabolic parameters, inflammatory cytokines (including ProT-α), and early FG, acknowledging that adverse intrauterine conditions may begin to influence fetal development as early as 20 weeks of gestation (wg). Methods: Forty-six singleton pregnant women were included, fulfilling IADPSG criteria for either GDM (n=8) or normal glucose tolerance (NGT; n=38) at 24-28 wg. During the 75-g OGTT, we measured serum maternal glucose, insulin, inflammatory cytokines, and ProT-α levels. FG was evaluated via ultrasound at 20 wg, focusing on abdominal circumference (AC) and estimated fetal weight (EFW) percentiles. Factors affecting FG were determined through correlation and regression analyses. Results: Compared with NGT, women with GDM were significantly older and had higher BMI. They also displayed higher glucose readings at each OGTT time point, coupled with hyperinsulinemic responses, and tended to carry fetuses with larger AC and EFW. Notably, levels of IL-8 (p=0.034), TNFα (p=0.046), and IL-1α (p=0.007) were lower in the GDM group. Although ProT-α values were also lower in GDM, this difference was not statistically significant. Nonetheless, ProT-α exhibited a significant inverse correlation with EFW percentiles (β = -0.431, p=0.022). Regression analyses further revealed that 2-h post-load glucose (β = 0.545, p=0.010), VEGF (β = 0.380, p=0.021), and EGF (β = 0.374, p=0.047) positively predicted accelerated FG, whereas IL-10 (β = -0.416, p=0.030) and ProT-α were negative predictors. Conclusions: These findings underscore the interplay between maternal glucose metabolism, inflammatory pathways, and angiogenic factors in shaping early FG. ProT-α emerges as a novel biomarker that is inversely associated with FG, warranting deeper investigation into its mechanistic underpinnings and its potential as a therapeutic target in GDM, maternal obesity, and IR.Presentation: Sunday, July 13, 2025

This study examines gender-based differences in neonatal physical characteristics using multivariate statistical techniques. A total of 1,000 newborns (male and female) were sampled from the Federal University Wukari Teaching Hospital, Taraba State, Nigeria. Key anthropometric variables measured included occipito-frontal circumference (OFC), cranial circumference (CC), length of birth (LOB), abdominal circumference (AC), and weight (WT). Due to perfect correlation with other variables, AC was excluded from the multivariate analysis. The objective was to determine whether statistically significant physical differences exist between male and female neonates at birth. The study employed Hotelling’s T² test and profile analysis; however, the assumptions of homogeneity of covariance matrices (tested via Box’s M) and independence (assessed via scatter plots) were violated. To address these issues, a robust non-parametric permutation-based Hotelling’s T² test was conducted, yielding a statistically significant result (p &lt; 0.001), indicating notable gender-based differences in multivariate mean vectors. While the main effect of Feature was highly significant (p &lt; 0.001), revealing differences among OFC, CC, LOB, and WT, the Gender × Feature interaction was non-significant (p &gt; 0.05), suggesting parallel measurement patterns across genders. The study concludes that gender significantly influences neonatal physical traits and that advanced multivariate methods, including Hotelling’s T² and profile analysis, are effective for analyzing high-dimensional neonatal data—even under violations of classical assumptions such as normality and homoscedasticity.