Shenzhen Maternity and Child Healthcare Hospital

Joint learning on diverse ultrasonic source scenarios presents a challenge in preserving stable generalization due to the combination of heterogeneity of different sources and the inconsistency of joint learning features. Previous joint learning studies, which are not source-resilient frameworks, may not preserve stable generalization when trained on diverse source scenarios. Furthermore, the limited variations in single-source data and the interference from ultrasound imaging, which are common in ultrasonic source scenarios, further decrease generalization. To address these problems, we proposed a source-resilient joint learning framework consisting of three stages: 1) Source transforming, where our 1-to-N transformation unifies diverse source scenarios for source-resiliency. 2) Our feature enhancement modules model the source-resilient joint learning network, including a manifold-constraint normalization module (MCNM) for addressing heterogeneity by minimizing manifold-based loss, a task-consistent attention module (TCAM) shares the multi-scale features with self-attention to address inconsistency, and an adaptive feature-shifting module (AFSM) for feature-level augmentation to overcome single-source data. 3) Our ultrasound-hybrid linear mapping (USmapping) cascades speckle randomization and mask-guiding Monge-Kantorovitch linear mapping to achieve ultrasonic style randomization for addressing the interference of ultrasonic data. Our framework was evaluated on eight ultrasound datasets from various scanners at multiple centers and surpassed previous comparable studies in both segmentation (DSC$WAvg$ of 75.7%) and classification (AUROC$WAvg$ of 68.8%) tasks. Our framework has the potential to serve as a general framework for enhancing the performance of joint learning under diverse ultrasonic source scenarios.

To examine the association of gestational weight gain (GWG) z-scores and their trajectories with neurodevelopmental delays in children aged 0-24 months. Prospective study. Shenzhen, China. 19 702 mother-singleton child pairs. GWG z-score trajectories were established using group-based trajectory modelling. Associations of GWG z-scores and their trajectories with neurodevelopmental delays were assessed by multivariable logistic regression. Neurodevelopmental delays assessed using the parent-completed Ages and Stages Questionnaire, third edition. Most assessments (63.51%) were conducted at child age 0-6 months. Compared with children whose mothers had average GWG (z-score ≥ -0.5 and < 0.5), those with very low GWG (z-score < -1.5) had higher risks of delay in communication (OR: 1.30, 95% CI: 1.09, 1.56), gross motor (OR: 1.34, 95% CI: 1.07, 1.68), problem-solving (OR: 1.32, 95% CI: 1.06, 1.65) and personal-social skills (OR: 1.25, 95% CI: 1.03, 1.51). Among children of overweight/obese mothers, very high GWG (z-score > 1.5) was associated with higher risks of delay in problem-solving (OR: 2.66, 95% CI: 1.20, 5.90) and personal-social skills (OR: 2.68, 95% CI: 1.39, 5.15). Compared with children whose mothers followed GWG trajectories that started at high levels and ended at average levels, those with GWG trajectories ending at low levels had higher risks of neurodevelopmental delays. Very low GWG and GWG trajectories ending at low levels were associated with modestly higher risks of neurodevelopmental delays in early childhood. Very high GWG in mothers with overweight/obesity was also associated with higher risks of neurodevelopmental delays in children.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality globally; however, the molecular drivers remain unclear. Dysregulated cholesterol metabolism is a hallmark of HCC and contributes to tumor progression. The Niemann-Pick type C1 protein (NPC1), a lysosomal cholesterol transporter, is overexpressed in cancers; however, its oncogenic mechanisms in HCC remain unclear. In this study, we identified NPC1 as a critical regulator of HCC progression through dual mechanisms involving p53 destabilization and modulation of cholesterol metabolism. Analysis of the clinical data revealed that NPC1 was significantly upregulated in HCC tissues and correlated with poor prognosis. Functional studies have demonstrated that NPC1 silencing suppresses HCC cell proliferation, both in vitro and in vivo. Mechanistically, NPC1 interacts with deubiquitinase ubiquitin-specific protease 7 (USP7), disrupting its binding to p53 and enhancing p53 ubiquitination and proteasomal degradation. Concurrently, NPC1 modulates cholesterol synthesis and distribution via the p53-SREBP2 axis, and p53 knockdown reverses the cholesterol reduction caused by NPC1 silencing. The pharmacological activation of p53 reversed the decrease in cholesterol levels mediated by the overexpression of NPC1. These findings reveal that NPC1 is a multifaceted oncoprotein in HCC, linking cholesterol metabolism to p53 regulation and highlighting its potential as a therapeutic target for HCC intervention.

We conducted a network meta-analysis of randomized trials to assess the effect of different exercises on the renal and cardiovascular function of patients with chronic kidney disease not receiving dialysis. The PubMed, Embase, Web of science, COCHRANE LIBRARY, Trials, CNKI, WANFANG DATA and VIP were searched. The standardized mean difference (SMD), with a 95% confidence interval (CI), for outcomes were summarized. A random effects model was used across all comparisons. Surface under the cumulative ranking curve (SUCRA) and mean ranks were reported to evaluate the treatment hierarchy. A total of 49studies were included. Regarding renal function, resistance exercise (RE), RE + blood flow restriction (BFR), and aerobic exercise (AE) significantly improved eGFR compared to the control group, except for AE + RE; and just AE could significantly improve SCR (serum creatinine). Regarding cardiovascular function, compared with the control group, RE + BFR, RE, and AE significantly reduced systolic blood pressure (SBP) and diastolic blood pressure (DBP); AE and AE + RE were suitable for improving the VO2peak. However, no significant differences were found in pulse wave velocity (PWV), TC, TG, LDL, or HDL levels between any of the groups when compared pairwise. Furthermore, RE significantly reduced CRP, and AE + RE significantly reduced BMI compared with the control group. According to SUCRA, RE + BFR, followed by RE appeared to yield relatively greater improvements in eGFR and blood pressure. The results of this study indicate that different physical exercises can improve renal and cardiovascular functions to various extents, and patients are advised to perform personalized physical exercises in order to achieve to specific outcomes.

Fetal ultrasound screening is a uniquely complex diagnostic task involving the simultaneous assessment of multiple fetal organs—each with its own anatomical and clinical context—within a single examination. Automating report generation for such cases poses a significant challenge: unlike existing methods that focus on single-organ radiology tasks (e.g., chest X-rays), fetal ultrasound requires reasoning over a structured, multiple-to-multiple setting, i.e., multi-organ images corresponding to a multi-section report. In this paper, we introduce FetusR, the first large-scale dataset for multi-organ fetal ultrasound reporting, containing 15,594 real-world cases with rich organ-wise annotations. To address the intrinsic image-report alignment, we propose Organ-Aware Routing Mixture-of-Retrieval Augmented Generation (ORM-RAG) inspired by the Mixture-of-Experts paradigm. Our method decomposes the complex alignment problem into multiple one-to-one sub-retrieval tasks. Specifically, ORM-RAG integrates (1) an organ-aware mixture-of-retrieval module that partitions the retrieval space into organ-specific corpora for independent retrieval, and (2) a dynamic routing mechanism that selectively aggregates high-confidence organ-specific reports while filtering uncertain ones. Extensive experiments demonstrate that our method significantly outperforms state-of-the-art baselines across both textual similarity and clinical accuracy metrics. Our work opens a new direction for long-form, structured report generation in real-world, multi-organ medical imaging scenarios.

ObjectivesPost-COVID-19 respiratory infection patterns require updated epidemiological data. To investigate the prevalence and infection patterns of upper respiratory tract infections (URTIs), a survey was conducted to assess the presence of influenza A (IFV A), influenza B (IFV B), respiratory syncytial virus (RSV), human rhinovirus (HRV), adenovirus (Adv), and SARS-CoV-2 among outpatients diagnosed with URTIs.DesignA community-based cross-sectional study.SettingThree cities in Sichuan, China.Participants1174 outpatients diagnosed with URTIs from December 2023 to February 2024.MethodsOropharyngeal swabs were collected using sterile flocked swabs, preserved at 4°C and analysed within 24 hours. Viral nucleic acid was extracted automatically and detected via multiplex PCR-melting curve analysis.ResultsResults showed in positive detection rates varied significantly by age (p<0.001), peaking in children (77.42%), followed by adolescents (73.23%), adults (63.59%) and older adults (57.58%). IFV B and A predominated, followed by HRV, Adv, RSV and SARS-CoV-2. 12 co-infection types were identified, with HRV/Adv and IFV B/HRV most prevalent. In children and adolescents, co-infections were significantly more common, with predominant types including HRV/Adv, HRV/RSV and RSV/IFV B.ConclusionsThis study reveals persistent influenza dominance and age-stratified co-infection risks and provides critical baseline data for optimising respiratory infectious disease control in the post-pandemic era.