Childhood obesity has become a global public health issue. Current research indicates that early life obesogen exposure has emerged as a significant risk factor for childhood obesity. While obesogens have been confirmed to influence the development and progression of childhood obesity through mechanisms such as endocrine disruption and epigenetic programming, controversies remain regarding the establishment of causal relationships, assessment of combined exposures, and validation of transgenerational effects in humans. In recent years, novel approaches including multi-omics technologies, exposome-based analysis, and multigenerational cohort studies have integrated dynamic biomarker monitoring with analyses of social-environmental interactions, offering new perspectives and methodologies for constructing a systematic "exposure-mechanism-outcome" research framework. This article reviews literature from PubMed and Web of Science up to August 2025 on the association between early life obesogen exposure and childhood obesity, summarizing evidence on the health effects of early life obesogen exposure, major exposure pathways and internal exposure assessment, interactions and amplifying effects of social and environmental factors, as well as the biological mechanisms underlying obesogen action. It further examines current research frontiers and challenges, aiming to provide a theoretical foundation for early prevention and precision intervention of childhood obesity.

BACKGROUND:Total knee arthroplasty serves as an effective intervention for the treatment of late-stage knee joint disorders.However,prosthetic liners are prone to wear and failure due to internal stress variations,resulting in limited lifespan and decreased postoperative patient activity.Addressing how to enhance prosthetic design to meet a broader range of patient needs constitutes a significant focus in prosthesis research. OBJECTIVE:Based on the morphological design of the meniscus,we propose an asymmetric design prosthesis and compare it with a symmetric posterior stabilized prosthesis.The stress distribution patterns and variations in the contact area of the liners for both prostheses were analyzed to explore whether the asymmetric prosthesis design offers advantages over the symmetric design. METHODS:Using the finite element method,we simulated the osteotomy and prosthesis assembly in a knee osteoarthritis patient.Two different prostheses(asymmetric design and posterior stabilized)were employed to establish post-total knee arthroplasty knee joint models.Under flexion conditions at 0°,10°,20°,and 30°,we investigated the Mises stress on the femoral and tibial components as well as the liner.Additionally,by comparing the contact area on the inner and outer sides of the liner,we aimed to explore the changes in biomechanics and alterations in motion behavior in the post-total knee arthroplasty knee joint. RESULTS AND CONCLUSION:(1)Throughout the flexion range from 0 to 30 degrees,the Mises stress peak on the liner exhibited a trend of initial decrease followed by an increase,with the stress on the medial side consistently surpassing that on the lateral side.(2)In comparison to the posterior stabilized prosthesis,the asymmetrically designed prosthesis demonstrated smaller stress peaks.At a flexion angle of 30 degrees,the Mises stress peak values of the medial and lateral parts of the asymmetric prosthesis were 15.81 MPa and 11.95 MPa,and those of the posterior stabilization prosthesis were 16.70 MPa and 13.76 MPa.The difference of Mises stress on the medial part was 5.33%,and the difference of Mises stress on the lateral part was 13.15%.Comparing the peak Mises stress on the femoral and tibial components,the asymmetric component was always lower than the posterior stable component during knee flexion.(3)In the upright position at 0 degrees,the medial contact area of the posterior stabilization prosthesis was 17.96 mm2,and the lateral contact area was 34.10 mm2.The contact area on the inner and outer sides of the asymmetric design prosthesis liner was 105.47 mm2 and 107.80 mm2,respectively,indicating a larger contact area with a smaller difference between the inner and outer sides.(4)These results suggest that the biomechanical performance of the asymmetric prosthesis is superior,contributing to the maintenance of knee joint stability and improved joint mobility.This design,to a certain extent,mimics the rotational motion mechanism of the knee joint about the medial condyle as an axis,making it a more effective choice for knee joint prosthesis selection.

BACKGROUND:The regeneration and remodeling of Achilles tendon rupture after surgery are difficulties in clinical treatment.Tissue engineering hydrogels afford the possibility on the healing of postoperative Achilles tendon. OBJECTIVE:To investigate the effect of tannic acid modified interpenetrating network hydrogel on tissue regeneration and remodeling of ruptured Achilles tendon in rats. METHODS:(1)The interpenetrating network hydrogel was prepared under the blue light and the immersion of CaSO4 solution.The micromorphology,mechanical properties,adhesion properties,in vitro drug release properties,and biocompatibility of hydrogels were characterized.(2)Thirty Sprague-Dawley rats were randomly divided into sham operation group,operation group,and hydrogel group,with 10 rats in each group.The animal model of Achilles tendon rupture was established in the latter two groups.In the operation group,the ruptured Achilles tendon was sutured using the modified Kessler method.In the hydrogel group,the ruptured Achilles tendon was repaired by the same method,and the tannic acid modified interpenetrating network hydrogel patch was completely wrapped around the joint of the broken end.Four weeks after the operation,imaging examination,histological evaluation,biomechanical test,and the level test of inflammatory factors were performed. RESULTS AND CONCLUSION:(1)Scanning electron microscope showed that tannic acid modified interpenetrating network hydrogels had porous microstructure with pore size of 3-10 μm,and the hydrogels had good in vitro drug release properties,adhesion strength and tensile strength.CCK-8 assay and live/dead staining showed that the hydrogel had no significant effect on the proliferation activity of rat bone marrow mesenchymal stem cells,and had good biocompatibility.(2)MRI imaging showed that compared with the operation group,the Achilles tendon in the hydrogel group showed uniform low signal,the thickness of the anteroposterior diameter of the Achilles tendon was reduced,and the boundary between the Achilles tendon and the surrounding tissue was more clear,and the performance was more similar to that of the sham operation group.Hematoxylin-eosin staining and Masson staining showed that the tendon fibers in the operation group were arranged in a loose and chaotic manner,with increased cell density and disordered arrangement,accompanied by obvious inflammatory cell infiltration,and intratendinous ossification appeared in some areas.In the hydrogel group,the tendon fibers were arranged in an orderly manner;the cell density was reduced and arranged orderly;the inflammatory cell infiltration was significantly reduced.The tensile strength of Achilles tendon in the operation group was lower than that in the sham operation group(P<0.05).The tensile strength of Achilles tendon in the hydrogel group was higher than that in the operation group(P<0.05).Compared with sham operation group,the mass concentration and mRNA expression of interleukin-1β,interleukin-6,and tumor necrosis factor α in Achilles tendon of rats were increased in the operation group(P<0.05).Compared with the operation group,the level and mRNA expression of three inflammatory factors were decreased in the hydrogel group.(3)It is concluded that tannic acid modified interpenetrating network hydrogel can inhibit the local inflammatory response and promote the tendon remodeling.

BACKGROUND: While emotional distress, encompassing anxiety and depression, has been associated with negative clinical outcomes, its impact across various clinical departments and general hospitals has been less explored. Previous studies with limited sample sizes have examined the effectiveness of specific treatments (e.g., antidepressants) rather than a systemic management strategy for outcome improvement in non-psychiatric inpatients. To enhance the understanding of the importance of addressing mental health care needs among non-psychiatric patients in general hospitals, this study retrospectively investigated the impacts of emotional distress and the effects of early detection and management of depression and anxiety on hospital length of stay (LOS) and rate of long LOS (LLOS, i.e., LOS >30 days) in a large sample of non-psychiatric inpatients. METHODS: This retrospective cohort study included 487,871 inpatients from 20 non-psychiatric departments of a general hospital. They were divided, according to whether they underwent a novel strategy to manage emotional distress which deployed the Huaxi Emotional Distress Index (HEI) for brief screening with grading psychological services (BS-GPS), into BS-GPS ( n = 178,883) and non-BS-GPS ( n = 308,988) cohorts. The LOS and rate of LLOS between the BS-GPS and non-BS-GPS cohorts and between subcohorts with and without clinically significant anxiety and/or depression (CSAD, i.e., HEI score ≥11 on admission to the hospital) in the BS-GPS cohort were compared using univariable analyses, multilevel analyses, and/or propensity score-matched analyses, respectively. RESULTS: The detection rate of CSAD in the BS-GPS cohort varied from 2.64% (95% confidence interval [CI]: 2.49%-2.81%) to 20.50% (95% CI: 19.43%-21.62%) across the 20 departments, with a average rate of 5.36%. Significant differences were observed in both the LOS and LLOS rates between the subcohorts with CSAD (12.7 days, 535/9590) and without CSAD (9.5 days, 3800/169,293) and between the BS-GPS (9.6 days, 4335/178,883) and non-BS-GPS (10.8 days, 11,483/308,988) cohorts. These differences remained significant after controlling for confounders using propensity score-matched comparisons. A multilevel analysis indicated that BS-GPS was negatively associated with both LOS and LLOS after controlling for sociodemographics and the departments of patient discharge and remained negatively associated with LLOS after controlling additionally for the year of patient discharge. CONCLUSION Emotional distress significantly prolonged the LOS and increased the LLOS of non-psychiatric inpatients across most departments and general hospitals. These impacts were moderated by the implementation of BS-GPS. Thus, BS-GPS has the potential as an effective, resource-saving strategy for enhancing mental health care and optimizing medical resources in general hospitals.
Humans ; Retrospective Studies ; Male ; Length of Stay/statistics & numerical data* ; Female ; Middle Aged ; Adult ; Psychological Distress ; Inpatients/psychology* ; Aged ; Anxiety/diagnosis* ; Depression/diagnosis*

Intelligence encompasses various abilities, including logical reasoning, comprehension, self-awareness, learning, planning, creativity, and problem-solving. Extensive research and practical experience suggest that there are sex differences in intellectual development, with females typically maturing earlier than males. However, the key genes and molecular network mechanisms underlying these sex differences in intellectual development remain unclear. To date, Genome-Wide Association Studies (GWAS) have identified 507 genes that are significantly associated with intelligence. This study first analyzed RNA sequencing data from different stages of brain development (from BrainSpan), revealing that during the late embryonic stage, the average expression levels of intelligence-related genes are higher in males than in females, while the opposite is observed during puberty. This study further constructed interaction networks of intelligence-related genes with sex-differential expression in the brain, including the prenatal male network (HELP-M: intelligence genes with higher expression levels in prenatal males) and the pubertal female network (HELP-F: intelligence genes with higher expression levels in pubertal females). The findings indicate that the key genes in both networks are Ep300 and Ctnnb1. Specifically, Ep300 regulates the transcription of 53 genes in both HELP-M and HELP-F, while Ctnnb1 regulates the transcription of 45 genes. Ctnnb1 plays a more prominent role in HELP-M, while Ep300 is more crucial in HELP-F. Finally, this study conducted sequencing validation on rats at different developmental stages, and the results indicated that in the prefrontal cortex of female rats during adolescence, the expression levels of the intelligence genes in HELP-F, as well as key genes Ep300 and Ctnnb1, were higher than those in male rats. These genes were also involved in neurodevelopment-related biological processes. The findings reveal a sex-differentiated intelligence gene network and its key genes, which exhibit varying expression levels during the neurodevelopmental process.
Female ; Intelligence/physiology* ; Male ; Sex Characteristics ; Animals ; Brain/growth & development* ; E1A-Associated p300 Protein/physiology* ; beta Catenin/physiology* ; Transcriptome ; Rats ; Gene Expression Profiling ; Genome-Wide Association Study

Objective: To assess the effectiveness of vertebral cement augmentation (VCA) at upper instrumented vertebra (UIV) and UIV+1 in preventing proximal junction complications in correction surgery for adult spinal deformity patients. Methods: A literature search was conducted on Web of Science, PubMed, and Cochrane Library databases for comparative studies published before December 30th, 2024. Two reviewers independently screened eligible articles based on the inclusion and exclusion criteria, assessed study quality with Newcastle-Ottawa scale, and extracted data like study characteristics, surgical details, primary and secondary outcomes. Data analysis was performed using Review Manager 5.4 and Stata software. Results: Of all 513 papers screened, a meta-analysis was conducted on 7 articles, which included 333 cases in the VCA group and 827 cases in the control group. Patients in the VCA group had significantly older age and lower T score than patients in the control group. Although there was no statistically significant difference in the incidence of proximal junctional failure between the 2 groups, the results of the meta-analysis showed that the incidence of proximal junctional failure and the need for revision surgery were reduced by 36% and 71%, respectively, in the VCA group. One study reported 2 clinically silent pulmonary cement embolism and 1 patient requiring surgical decompression for cement leak into the spinal canal. Conclusion This meta-analysis supported the use of VCA in corrective surgery for spinal deformities patients, especially in patients with advanced age and osteoporosis.

Optical imaging is highly valued for its superior temporal and spatial resolution. This is particularly important in near-infrared II (NIR-II, 1 000-3 000 nm) imaging, which offers advantages such as reduced tissue absorption, minimal scattering, and low autofluorescence. These characteristics make NIR-II imaging especially suitable for deep tissue visualization, where high contrast and minimal background interference are critical for accurate diagnosis and monitoring. Currently, inorganic fluorescent probes—such as carbon nanotubes, rare earth nanoparticles, and quantum dots—offer high brightness and stability. However, they are hindered by ambiguous structures, larger sizes, and potential accumulation toxicity in vivo. In contrast, organic fluorescent probes, including small molecules and polymers, demonstrate higher biocompatibility but are limited by shorter emission wavelengths, lower quantum yields, and reduced stability. Recently, gold clusters have emerged as a promising class of nanomaterials with potential applications in biocatalysis, fluorescence sensing, biological imaging, and more. Water-soluble gold clusters are particularly attractive as fluorescent probes due to their remarkable optical properties, including strong photoluminescence, large Stokes shifts, and excellent photostability. Furthermore, their outstanding biocompatibility—attributed to good aqueous stability, ultra-small hydrodynamic size, and high renal clearance efficiency—makes them especially suitable for biomedical applications. Gold clusters hold significant potential for NIR-II fluorescence imaging. Atomic-precision gold clusters, typically composed of tens to hundreds of gold atoms and measuring only a few nanometers in diameter, possess well-defined three-dimensional structures and clear spatial coordination. This atomic-level precision enables fine-tuned structural regulation, further enhancing their fluorescence properties. Variations in cluster size, surface ligands, and alloying elements can result in distinct physicochemical characteristics. The incorporation of different atoms can modulate the atomic and electronic structures of gold clusters, while diverse ligands can influence surface polarity and steric hindrance. As such, strategies like alloying and ligand engineering are effective in enhancing both fluorescence and catalytic performance, thereby meeting a broader range of clinical needs. In recent years, gold clusters have attracted growing attention in the biomedical field. Their application in NIR-II imaging has led to significant progress in vascular, organ, and tumor imaging. The resulting high-resolution, high signal-to-noise imaging provides powerful tools for clinical diagnostics. Moreover, biologically active gold clusters can aid in drug delivery and disease diagnosis and treatment, offering new opportunities for clinical therapeutics. Despite the notable achievements in fundamental research and clinical translation, further studies are required to address challenges related to the standardized synthesis and complex metabolic behavior of gold clusters. Resolving these issues will help accelerate their clinical adoption and broaden their biomedical applications.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective:To explore the clinical application value of convolutional neural network（CNN）based on deep learning in the automatic measurement of dynamic pelvic floor ultrasound video parameters and the diagnosis and classification of cystocele.Methods:A retrospective analysis was conducted on dynamic pelvic floor ultrasound videos from 398 postpartum women who underwent examinations at the First People's Hospital of Foshan between June 2020 and June 2022. The lowest point of the posterior bladder wall（PWB），urethral rotation angle（URA），and retrovesical angle（RVA）were manually measured by a senior radiologist（R1）and a junior radiologist（R2），and cystocele was classified according to the Green standard. The CNN model was employed to automatically extract the above parameters and to diagnose and classify cystocele. Using R1 measurements as a reference，intraclass correlation coefficient（ICC）was used to evaluate the consistency between the CNN model and R1，as well as between R2 and R1. The Kappa value was used to assess the agreement between the CNN model，R2，and R1 in the diagnosis and classification of cystocele. Additionally，the time consumption of the three measurement methods was compared.Results:The CNN model showed good consistency with R1 in measuring PWB and URA（ICC = 0.983，0.894），while its consistency in measuring RVA was moderate（ICC = 0.614）. The ICC between R2 and R1 in measuring PWB，URA，and RVA was 0.979，0.815，and 0.627，respectively. In the measurement of PWB and URA，the consistency between the CNN model and R1 was superior to that between R2 and R1. For cystocele diagnosis，the Kappa value between the CNN model and R1 was 0.924，which was higher than that between R2 and R1（0.904）. In cystocele classification，the Kappa value between the CNN model and R1 was 0.503，also higher than that between R2 and R1（0.426）. The CNN model processed a single video in 2.5（0.6）s，significantly faster than R1［59.9（16.9）s］and R2［56.8（11.2）s］（all P < 0.001）. Conclusions:The CNN model demonstrates high accuracy and efficiency in the measurement，diagnosis，and classification of cystocele，outperforming a junior radiologist and showing potential for clinical application.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.