Objective:To investigate the association between small vulnerable newborn (SVN) phenotypes and the risk of neurodevelopmental delay at the age of 1 year.Methods:A prospective cohort study was conducted. A total of 25 860 singleton infants from "The Born in Guangzhou Cohort Study" who completed the Gesell developmental scale assessment at 1 year of age between January 2013 and June 2025 were included. Maternal sociodemographic characteristics, and other information were collected using a self-administered questionnaire, and maternal pregnancy-related information and neonatal birth data were extracted from medical records. Global developmental delay (GDD) was defined as a developmental quotient below 86 in ≥3 domains of the Gesell developmental scale, which assesses the adaptive, gross motor, fine motor, language, and personal-social domains. The random forest algorithm was employed for missing data imputation. Based on prematurity, small for gestational age (SGA), and low birth weight (LBW), newborns were categorized into 6 phenotypes: preterm-SGA-LBW, preterm-appropriate for gestational age (AGA)-LBW, preterm-AGA-nonLBW, term-SGA-LBW, term-LBW-only or term-SGA-only, and term-AGA-nonLBW phenotype. Among these, the first 5 were classified as SVN phenotypes, and the last one served as the reference group. Inter-group comparisons were performed using analysis of variance (ANOVA), χ2 tests, or Kruskal-Wallis test, as appropriate.?? Multivariable robust Poisson regression models were applied to analyze the association of different SVN phenotypes with the risks of GDD and developmental delays in specific domains, with stratified analyses by sex. Results:Among the 25 860 infants, 13 719 (53.1%) were male and 12 141 (46.9%) were female. The gestational age at birth was 39.4 (38.6, 40.0) weeks. The overall detection rate of GDD at 1 year of age was 3.7% (962/25 860). The rates of delay across developmental domains, in descending order, language in 8 134 cases (31.5%), gross motor in 4 488 cases (17.4%), personal-social in 1 271 cases (4.9%), adaptive in 1 262 cases (4.9%), and fine motor in 621 cases (2.4%). Compared with the reference group, preterm-AGA-LBW, preterm-SGA-LBW, preterm-AGA-noneLBW, and term-SGA-LBW phenotypes were all associated with an increased risk of GDD, with the adjusted RR (95% CI) of 6.07(5.01-7.35), 4.81(3.11-7.46), 2.10(1.54-2.88) and 1.89(1.29-2.76) respectively.The preterm-AGA-noneLBW phenotype was all associated with an increased risk of delay in gross motor, language and personal-social functional domains (all P<0.05). The term-SGA-LBW phenotype was associated with an increased risk of delay in gross motor, fine motor and personal-social functional domains (all P<0.01). Whereas the term-LBW-only or term-SGA-only phenotype showed no statistically association with developmental delay in any functional domain (all P≥0.05). Conclusion:The combined classification based on gestational age and birth weight helps identify infants at high risk for neurodevelopmental delay at 1 year of age, suggesting that it may offer a reference for the rational allocation of clinical resources.

Objective:To investigate the association between small vulnerable newborn (SVN) phenotypes and the risk of neurodevelopmental delay at the age of 1 year.Methods:A prospective cohort study was conducted. A total of 25 860 singleton infants from "The Born in Guangzhou Cohort Study" who completed the Gesell developmental scale assessment at 1 year of age between January 2013 and June 2025 were included. Maternal sociodemographic characteristics, and other information were collected using a self-administered questionnaire, and maternal pregnancy-related information and neonatal birth data were extracted from medical records. Global developmental delay (GDD) was defined as a developmental quotient below 86 in ≥3 domains of the Gesell developmental scale, which assesses the adaptive, gross motor, fine motor, language, and personal-social domains. The random forest algorithm was employed for missing data imputation. Based on prematurity, small for gestational age (SGA), and low birth weight (LBW), newborns were categorized into 6 phenotypes: preterm-SGA-LBW, preterm-appropriate for gestational age (AGA)-LBW, preterm-AGA-nonLBW, term-SGA-LBW, term-LBW-only or term-SGA-only, and term-AGA-nonLBW phenotype. Among these, the first 5 were classified as SVN phenotypes, and the last one served as the reference group. Inter-group comparisons were performed using analysis of variance (ANOVA), χ2 tests, or Kruskal-Wallis test, as appropriate.?? Multivariable robust Poisson regression models were applied to analyze the association of different SVN phenotypes with the risks of GDD and developmental delays in specific domains, with stratified analyses by sex. Results:Among the 25 860 infants, 13 719 (53.1%) were male and 12 141 (46.9%) were female. The gestational age at birth was 39.4 (38.6, 40.0) weeks. The overall detection rate of GDD at 1 year of age was 3.7% (962/25 860). The rates of delay across developmental domains, in descending order, language in 8 134 cases (31.5%), gross motor in 4 488 cases (17.4%), personal-social in 1 271 cases (4.9%), adaptive in 1 262 cases (4.9%), and fine motor in 621 cases (2.4%). Compared with the reference group, preterm-AGA-LBW, preterm-SGA-LBW, preterm-AGA-noneLBW, and term-SGA-LBW phenotypes were all associated with an increased risk of GDD, with the adjusted RR (95% CI) of 6.07(5.01-7.35), 4.81(3.11-7.46), 2.10(1.54-2.88) and 1.89(1.29-2.76) respectively.The preterm-AGA-noneLBW phenotype was all associated with an increased risk of delay in gross motor, language and personal-social functional domains (all P<0.05). The term-SGA-LBW phenotype was associated with an increased risk of delay in gross motor, fine motor and personal-social functional domains (all P<0.01). Whereas the term-LBW-only or term-SGA-only phenotype showed no statistically association with developmental delay in any functional domain (all P≥0.05). Conclusion:The combined classification based on gestational age and birth weight helps identify infants at high risk for neurodevelopmental delay at 1 year of age, suggesting that it may offer a reference for the rational allocation of clinical resources.

ObjectiveTo investigate the contamination status of ochratoxin A (OTA) in commercially available food products in Shanghai, and to assess OTA exposure levels and the associated non-carcinogenic and carcinogenic risks among pregnant women by integrating dietary consumption data of this population. MethodsThe levels of OTA contamination in 1 520 food samples collected in Shanghai from 2022 to 2023 were determined using liquid chromatography-tandem mass spectrometry. An exposure assessment model was developed based on the dietary consumption levels of pregnant women from the 2016‒2017 Shanghai Pregnant Women Dietary Monitoring Survey to calculate the estimated daily intake (EDI) of OTA, the margin of exposure for non-carcinogenic toxicity (MOE₁), and the margin of exposure for carcinogenic toxicity (MOE₂). An MOE₁ greater than 200 and an MOE₂ greater than 10 000 indicate that the non-carcinogenic toxicity and carcinogenic toxicity resulting from exposure are negligible, respectively. For samples with OTA contamination levels below the limit of detection (LOD), which accounted for more than 80% of the samples, the OTA levels were assigned values of 0 and LOD, respectively, for subsequent calculations. ResultsThe detection rates of OTA in cereals, nuts, dried fruits, and alcohol samples collected in 2022 were 2.03%, 0, 0, and 0, respectively. The OTA detection rates in cereals, nuts, dried fruits, beans, and alcohol samples collected in 2023 were 2.50%, 0.39%, 2.47%, 1.67%, and 13.33%, respectively. For pregnant women in Shanghai in 2022, simulation results indicated that when assigning a value of 0 and the LOD, theP₅₀ values of EDI for dietary OTA exposure were 0.05 and 0.72 ng·(kg·d)^-1, respectively, and the P₉₅ values of EDI for dietary OTA exposure were 0.25 and 2.40 ng·(kg·d)^-1, respectively. For pregnant women in Shanghai in 2023, the P₅₀ values of EDI for dietary OTA exposure were 0.04 and 1.00 ng·(kg·d)^-1, respectively, and the P₉₅ values of EDI for dietary OTA exposure were 0.23 and 2.67 ng·(kg·d)^-1, respectively, both substantially below the tolerable daily intake (TDI) for OTA [17 ng·(kg·d)^-1]. The EDI for dietary OTA exposure in 100.0% of Shanghai pregnant women was lower than the TDI, indicating an overall low level of dietary OTA exposure among this population. For 100.0% of pregnant women, the MOE₁ for dietary OTA exposure exceeded 200. When assigned a value of 0, the MOE₂ for 100.0% of pregnant women in both 2022 and 2023 exceeded10 000. When assigned the LOD value, 72.3% and 81.8% of pregnant women in 2022 and 2023, respectively, had an MOE₂ exceeding 10 000. ConclusionFrom 2022 to 2023, samples of cereals, nuts, dried fruits, beans, and alcohol sold in Shanghai exhibited varying degrees of OTA contamination. The overall EDI of OTA exposure among pregnant women in Shanghai remained at a low level. The non-carcinogenic and carcinogenic risks associated with OTA exposure were generally low and at controllable levels.

Background Deoxynivalenol (DON), a priority contaminant for food safety risk monitoring, is produced by Fusarium spp. infesting crops, and its common derivatives are 3-acetyl-DON (3A-DON) and 15-acetyl-DON (15A-DON), which have been shown to possess gastrointestinal toxicity, immunotoxicity, reproductive toxicity, and cytotoxicity. Due to the stable physicochemical properties of the DON family of toxins (DONs), they cannot be effectively removed during food processing, thus following the food chain, entering the human body, and posing health risks. Objective To understand the contamination status of DONs in commercial foods (cereals and bakery products) in Shanghai in 2022–2023, and to assess the exposure risk of DONs in pregnant women by combining their dietary consumption data. Methods Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to determine the contamination level of DONs in 1 100 food samples (cereals and baked goods) collected in 2022 and 944 samples collected in 2023 from Shanghai. The dietary monitoring data of pregnant women in Shanghai from 2016 to 2017 were adopted. The monitoring employed the food frequency questionnaire distributed among pregnant women through a combination of online telephone enquiry and offline on-site face-to-face survey to estimate their food consumption levels. An exposure assessment model was established to calculate the exposure level to DONs, and the probability distribution of the DONs exposure level in the pregnant women group in Shanghai was obtained by applying @Risk 7.5 software and simulating the calculation according to the Monte Carlo principle. With reference to the tolerable daily intake (TDI) of DONs [1.00 µg·(kg·d)⁻¹] proposed by the Joint FAO/WHO Expert Committee on Food Additives, the risk of exposure to DONs from commercial cereals and bakery products in pregnant women in Shanghai was assessed. Results DONs were detected in cereal and bakery samples collected in 2022 and 2023 with different levels of contamination. The level of DONs in cereal foods in 2023 (mean: 36.33 µg·kg⁻¹) decreased compared to 2022 (mean: 23.64 µg·kg⁻¹). However, the positive rate (71.67%) and level (mean: 51.22 µg·kg⁻¹) of DONs in bakery products increased significantly compared with 2022 (positive rate: 10.00%, mean: 24.39 µg·kg⁻¹). The mean consumption of cereals in 783 pregnant women was 222.48 g·d⁻¹ and the mean consumption of bakery products was 36.07 g·d⁻¹, and there was no statistically significant difference in the intake of all types of cereals and bakery products across the early, middle, and late stages of pregnancy. The modelled intakes of DONs via commercial cereals and bakery products for pregnant women in Shanghai were calculated to be 0.20 and 0.57 µg·(kg·d)⁻¹ in 2022 for the mean level and the 95th percentile level, respectively, and 0.16 µg·(kg·d)⁻¹ and 0.35 µg·(kg·d)⁻¹ in 2023, respectively. The results of the health risk assessment showed that pregnant women in Shanghai had 2.6% and 1.4% probability of exposure to DONs from cereal consumption in 2022 and 2023, respectively. Conclusion The risk of exposure of pregnant women in Shanghai to DONs via commercial cereals and bakery products is relatively low (1.4%-2.6%). However, considering the physical sensitivity of pregnant women, they should avoid consuming moldy grains and appropriately reduce intake of bakery products.

OBJECTIVE: To investigate the biological behavior, differentiation ability, and differential gene expression of lymph node mesenchymal stem cells (MSCs) in patients with diffuse large B-cell lymphoma (DLBCL) and reactive lymphoid hyperplasia (RLH), providing a theoretical basis for clinical chemotherapy resistance. METHODS: Lymph node MSCs from patients with DLBCL and RLH were separated, passaged and cultured. The cell morphology and growth status were observed. Flow cytometry was performed to detect the immune phenotype of MSCs. The in vitro directed differentiation ability of the two types of MSCs was observed. High-throughput sequencing was used to analyze the differential gene expression and enrichment of two groups of MSCs. RESULTS: The lymph node MSCs of patients with DLBCL and RLH had similar cell morphology and growth characteristics, and both groups of MSCs expressed CD90, CD105, and CD73 on the cell surface. Compared with lymph node MSCs derived from patients with RLH, lymph node MSCs derived from DLBCL patients showed stronger osteogenic and adipogenic differentiation abilities. High-throughput sequencing results displayed that lymph node MSCs derived from DLBCL patients significantly upregulated some genes such as TOP2A, LFNG, GRIA3, SEC14L2, SPON2, AURKA, LRRC15, FOXD1, HOXC9, CDC20 and remarkably downregulated some genes such as TBC1D8, LDLR, PCDHAC2, POLH, PKP2, ANKRD37, DMKN, HSD11B1, ARHGAP20, PTGS1,etc. CONCLUSION Lymph node MSCs in DLBCL patients exhibit unique biological behavior and gene expression profiles, which may be closely related to clinical chemotherapy resistance.
Humans ; Mesenchymal Stem Cells/cytology* ; Lymphoma, Large B-Cell, Diffuse/pathology* ; Cell Differentiation ; Lymph Nodes/pathology* ; Pseudolymphoma/pathology*

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Objective:To validate the usefulness of copy number variation sequencing (CNV-seq) in detecting the deletion/duplication of the DMD gene in Duchenne muscular dystrophy (DMD)/Becker muscular dystrophy (BMD) patients. Methods:One hundred and seventy-seven cases who visited the Department of Medical Genetics, Affiliated Hospital of Kunming University of Science and Technology/the First People′s Hospital of Yunnan Province from April 2018 to November 2023 were collected. All patients had previously accepted multiplex ligation-dependent probe amplification (MLPA) to detect the deletion/duplication of the DMD gene, including 90 cases of normal control with a negative result of MLPA and 87 cases with the deletion or duplication of the DMD gene (61 cases of DMD and 26 cases of BMD). CNV-seq was performed in a single-blind manner to detect DMD gene deletion or duplication for all of 177 cases to obtain the detection efficiency of CNV-seq in comparison with MLPA. Results:Comparing to MLPA, CNV-seq had a coincidence rate of 88.7% (157/177) for detecting DMD gene deletion/duplication, with a sensitivity of 77.0% (67/87), a specificity and a positive predictive value of both 100.0% (90/90 and 67/67, respectively), a negative predictive value of 81.8% (90/110), and a Kappa value of 0.773. Of the 87 patients with the deletion or duplication of the DMD gene, CNV-seq detected 67 cases with DMD gene deletion/duplication, including 62 cases with deletion and 5 cases with duplication, with fragment ranging from 150 to 750 kb. While CNV-seq missed 23.0% (20/87) of positive cases, mainly due to the involved fragments spanning only 1 to 4 exons, and with a variation size less than 50 kb, below the resolution (100 kb) of CNV-seq. The detection rate of CNV-seq in BMD cases (84.6%, 22/26) was a little higher than that in DMD cases (73.8%, 45/61), but there was no significant difference between 2 subgroups ( χ2=1.211, P=0.271). The results of CNV-seq in normal controls were all negative, and consistent with the results of MLPA. Conclusion:CNV-seq can detect 77.0% (67/87) of deletion/duplication of the DMD gene in patients with DMD/BMD, while the deletion/duplication less than 100 kb may be inevitably unidentified, therefore it is recommended as an assistant screening technique in prenatal diagnosis for DMD gene deletion or duplication.

Objective:To explore the gaze characteristics towards emotional portraits in children with attention deficit hyperactivity disorder(ADHD),in order to reveal their potential unique patterns of emotional cognition.Methods:A case-control design was employed,including 81 children diagnosed with the DSM-5 ADHD and 57 normal control(NC)children.Emotional images from the Chinese Children's Emotional Image Library were used as stimuli.The Tobii Pro X3-120 eye-tracking device was utilized to record fixation count(FC)and fixation duration percentage(FDP)under a free-viewing paradigm.Mixed-effects ANOVA was applied to explore the effects of group,gaze region(eyes and mouth),and emotional attributes on gaze characteristics,controlling for gen-der and age.Results:The FC and FDP of ADHD children were lower than those of NC children,particularly in the eye region of non-negative emotional images(P＜0.05).However,no significant differences were observed be-tween the two groups when viewing negative emotional images(sadness and anger)(P＞0.05).NC children ex-hibited a significant emotional bias effect in their gaze behavior towards emotional portraits(P＜0.05),whereas ADHD group showed only slight differences between non-negative emotional images(adjusted P＜0.05),indica-ting a weaker overall emotional attention bias.Conclusion:Children with ADHD display reduced attention to non-negative emotional expressions and a diminished emotional attention bias,suggesting potential deficits in emotional processing during face perception.

Objective:To investigate and validate the performance of a dosiomics model that utilized 3D dose distribution to forecast radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) patients following intensity-modulated radiotherapy (IMRT).Methods:Clinical data of 3578 patients diagnosed with NPC admitted to Jiangsu Cancer Hospital from January 2011 to December 2021 were retrospectively analyzed. According to the inclusion and exclusion criteria, 97 NPC patients who developed RTLI were assigned into the case group. A 1:1 propensity score matching (PSM) method was used to match 97 NPC patients without RTLI as the control group. Patients were assigned into the training cohort ( n=135) and the validation cohort ( n=59) at a 7:3 ratio by simple random method. Dosiomics features were extracted from the patients' three-dimensional dose distribution maps. Spearman rho and the least absolute shrinkage and selection operator regression were used to select dosiomics features. Clinical features were collected and screened by univariate and multivariate analyses. Eight machine learning classifiers were then trained to build dosiomics models and clinical models, respectively. The area under the ROC curve (AUC), sensitivity, and specificity were calculated to compare the predictive performance of the dosiomics and clinical models. Multivariate analysis was conducted using logistic regression to assess the influencing factors, while comparisons of the ROC curves between two different models were performed using the DeLong test. Results:A total of 1130 dosiomics features were extracted from the three-dimensional dose distribution maps, and 14 features were retained for model building after feature selection. The model based on the support vector machine (SVM) classifier achieved the highest AUC value of 0.977 (95% CI: 0.949-1.000) in the validation cohort, with an AUC of 1.000 (95% CI: 1.000-1.000) in the training cohort. By conducting univariate and multivariate analyses of the patients' clinical features, 2 clinical features were retained to build the clinical model. The model based on the SVM classifier achieved the optimal AUC value of 0.667 (95% CI: 0.523-0.810) in the validation cohort, with an AUC of 0.804 (95% CI: 0.730-0.878) in the training cohort. DeLong test showed that the difference between the dosiomics and clinical models was statistically significant ( P<0.05). Conclusion:The dosiomics model based on 3D dose distribution yields high predictive performance for RTLI in NPC patients after IMRT, which surpasses the clinical feature model, providing a new approach for early clinical prediction of RTLI.