Renal lymphatic vessel density is clinically relevant in kidney disease but is still assessed by slow, subjective visual estimation. We evaluated a weakly supervised, attention-based multiple-instance learning framework for automated detection and quantification of renal lymphatic vessel density on D2-40-stained whole-slide images (WSIs). Methods: Two independent internal datasets from Tongji Hospital were collected, including 198 cases of chronic kidney disease (CKD) and 50 cases of hypertensive nephropathy (HTN). All biopsies were immunohistochemically stained for D2-40 and digitized as WSIs. Pathologists provided only slide-level labels (D2-40 high vs. D2-40 low). Tissue regions were automatically segmented, tiled into patches, and encoded using a pretrained convolutional neural network. Patch embeddings were then analyzed with a clustering-constrained attention multiple-instance learning (CLAM) model. Unlike conventional multiple-instance learning (MIL) methods that only weight instances, CLAM jointly performs attention-based instance selection and instance-level clustering to distinguish positive from negative evidence within each slide, yielding more discriminative slide-level features and interpretable attention maps. Performance was compared with a classic MIL model trained on the same features. Results: CLAM achieved area under the receiver operating characteristic curves of 0.942 and 0.858 on the CKD and HTN datasets, respectively, outperforming classic MIL (0.866 and 0.801). Attention maps highlighted lymphatic-rich regions consistent with renal pathologists’ assessments. Conclusions: This clustering-constrained, attention-based weakly supervised framework enables fully automated, reproducible quantification of renal lymphatic vessel density from WSIs, providing renal pathologists with rapid visual and numerical support for diagnosis and risk stratification in CKD and HTN.

BackgroundThe prevalence， disability rate and mortality rate of cerebral small vessel disease （CSVD） are relatively high among the elderly population， imposing a heavy burden on families and society. Among the various clinical manifestations of CSVD， cognitive impairment is the most common， and it is also the most closely related neuro-psychiatric syndrome to clinical practice in psychiatry. Previous studies on CSVD-related cognitive impairment （CSVD-CI） have mostly focused on the field of imaging， while studies on non-invasive electrophysiological and cerebral hemodynamic assessments are relatively scarce. ObjectiveTo analyze the characteristics of event-related potential （ERP） and functional near-infrared spectroscopy （fNIRS） in patients with CSVD-CI， and to explore their correlations with the severity of white matter lesions， in order to provide references for the objective assessment and early identification of CSVD-CI. MethodsA total of 40 patients with CSVD who met the diagnostic criteria of the Chinese Guideline for Diagnosis and Treatment of Cerebral Small Vessel Disease （2020） and had cognitive impairment， as well as were admitted to the Affiliated Hospital of North Sichuan Medical College from December 2024 to December 2025， were enrolled as the case group. Meanwhile， 40 healthy volunteers matched for gender， age and education level were recruited as the control group. Both groups underwent assessment using the Mini-Mental State Examination （MMSE）， ERP-P300 detection， and fNIRS examination. The ERP-P300 indicators， functional connectivity strength of the whole brain and cognitive-related regions of interest （ROI） in fNIRS of the two groups were compared. The severity of the patients' white matter lesions was classified as follows： the Fazekas grade I group （mild white matter lesions） and the Fazekas grades II to III group （moderate to severe white matter lesions）. Spearman correlation analysis was employed to investigate the correlation between the Fazekas grading of brain white matter lesions and the latency of ERP-P300， as well as the strength of functional connectivity measured by fNIRS. ResultsThe MMSE score of the CSVD-CI group was lower than that of the control group （Z=-6.250， P<0.01）， and ERP-P300 lantency was significantly longer than that of the control group （t=12.291， P<0.01）. The MMSE score of the sub-group with Fazekas grade I was higher than that of the sub-groups with grades II to III （Z=-2.420， P<0.05）， and showed a shorter P300 latency than that of the sub-groups with grades II to III （Z=-4.210， P<0.01）. All the differences were statistically significant. The resting-state whole-brain functional connectivity strength in the CSVD-CI group was lower than that in the control group， and the difference was statistically significant （t=10.243， P<0.05）. Compared with the control group， the differences in the functional connectivity strength within the left premotor cortex （PMC）， right PMC， left frontopolar cortex （FPC）， right FPC， left dorsolateral prefrontal cortex （DLPFC）， right DLPFC， left orbitofrontal cortex （OFC）， and right OFC regions in the CSVD-CI group were all statistically significant （P_{FDR correction}<0.01）. The differences in the functional connectivity strength between multiple prefrontal-related brain regions between the CSVD-CI group and the control group were all statistically significant （P_{FDR correction}<0.01）. The severity of white matter lesions in CSVD-CI patients was positively correlated with the P300 latency （r_s=0.891， P<0.05）， and negatively correlated with the fNIRS functional connectivity strength （r_s=-0.359， P<0.05）. ConclusionPatients with CSVD-CI exhibit prolonged P300 latency， as well as decreased functional connectivity strength in multiple brain regions including the whole brain and the prefrontal lobe during the resting state. Moreover， these indicators are correlated with the severity of white matter lesions.

Congenital cataract(CC)is one of the important causes of visual impairment in infants and young children. Approximately 30% of cases are associated with monogenic mutations. It is one of the core diseases in pediatric blindness prevention and treatment. The maintenance of lens transparency is closely related to membrane protein-mediated intercellular communication, water transport, and the orderly arrangement of fiber cells. This review focuses on the gap junction protein genes(GJA8 and GJA3), related to lens membrane function, the major intrinsic protein gene(MIP/AQP0), and the lens intrinsic membrane protein 2 gene(LIM2), and summarizes the inheritance patterns, clinical phenotypes, and pathogenic mechanisms of related monogenic mutations. Current evidence indicates that GJA8 and GJA3 mutations mainly disrupt lens cell homeostasis by affecting gap junction channel function, protein localization, and hemichannel opening; MIP/AQP0 mutations may impair water transport and intercellular adhesion, leading to abnormal fiber cell arrangement; in addition to the classic autosomal recessive inheritance pattern, dominant LIM2 mutations may affect membrane protein complex assembly through aberrant disulfide bond formation, thereby causing lens opacification. A systematic review of the mutational characteristics and mechanisms of these genes may help clarify the role of membrane protein abnormalities in the development and progression of CC and provide a reference for molecular diagnosis, genetic counseling, and subsequent intervention research.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To measure the narrative medicine ability of medical students and evaluate the effectiveness of reflective writing in enhancing this ability.Methods:The narrative medicine ability of medical students was measured and classified by the Narrative Medicine Ability Scale.A controlled comparative experiment was conducted in teaching practice,the control group adopted reflective writing on general topics,while the experimental group adopted reflective writing on medical topics.Writing outputs were measured from four dimensions including narrative medicine concept,knowledge,ability and perception.Results:The post-test scores of the two groups were significantly higher than the pre-test scores(P＜0.05).The improvement of medical students'reflection ability was positively correlated with the concept and perception of humanistic care,with correlation coefficients of 0.43 and 0.744,respectively(P＜0.05),showed no correlation with the ability and knowledge of humanistic care(P＞0.05).Conclusions:Reflective writing can promote the reflection ability of medical students.Reflective writing based on medical topics can enhance medical students'medical narrative concept and perception.

Objective:To investigate the expression levels and clinical significance of miR-627 and miR-448 in colorectal cancer tissues.Methods:Ninety-eight patients with colorectal cancer admitted to Xi’an Jiaotong University Affiliated Red Cross Hospital from Apr. 2019 to Apr. 2021 were gathered. Colorectal cancer tissue and adjacent tissues were collected during surgery, and the expression levels of miR-627 and miR-448 were detected by qRT-PCR. According to postoperative follow-up, patients were separated into a good prognosis group and a poor prognosis group. Kaplan-Meier survival curve was applied to analyze the relationship between miR-627, miR-448 and the prognosis of colorectal cancer patients. ROC curve was plotted to analyze the predictive value of miR-627 and miR-448 for poor prognosis in colorectal cancer. The prognostic factors of colorectal cancer patients were analyzed using COX regression.Results:There was a difference in the expression levels of miR-627 and miR-448 between colorectal cancer tissue and adjacent tissues ( P<0.05). The expression of miR-627 and miR-448 in colorectal cancer tissue was related to clinical features (TNM stage, differentiation degree, lymph node metastasis, and depth of infiltration) ( P<0.05). The survival rate of patients with high expression of miR-627 was higher than that of patients with low expression ( χ2=10.050, P<0.05); the survival rate of patients with high expression of miR-448 was higher than that of patients with low expression ( χ2=9.033, P<0.05). The expression levels of miR-627 and miR-448 in the poor prognosis group were greatly lower than those in the good prognosis group ( P<0.05). According to the ROC curve, the AUC of miR-627 in predicting poor prognosis of colorectal cancer was 0.811, the AUC of miR-448 in predicting poor prognosis of colorectal cancer was 0.772, and the AUC of combination of the two in predicting poor prognosis of colorectal cancer was 0.859. The combination of the two was better than their individual predictions (Z combination vs. miR-627=2.538, Z combination vs. miR-448=2.572, P<0.05). Multivariate COX regression found that miR-627, miR-448, and clinical features (TNM stage, degree of differentiation, lymph node metastasis, and depth of infiltration) were risk factors affecting the prognosis of colorectal cancer patients ( P<0.05) . Conclusion:The expression levels of miR-627 and miR-448 in colorectal cancer tissues were greatly reduced. The combination of the two is related to the clinical characteristics and prognosis of patients, and can greatly improve the predictive value for prognosis of colorectal cancer patients.

Objective:To investigate the expression levels and clinical significance of miR-627 and miR-448 in colorectal cancer tissues.Methods:Ninety-eight patients with colorectal cancer admitted to Xi’an Jiaotong University Affiliated Red Cross Hospital from Apr. 2019 to Apr. 2021 were gathered. Colorectal cancer tissue and adjacent tissues were collected during surgery, and the expression levels of miR-627 and miR-448 were detected by qRT-PCR. According to postoperative follow-up, patients were separated into a good prognosis group and a poor prognosis group. Kaplan-Meier survival curve was applied to analyze the relationship between miR-627, miR-448 and the prognosis of colorectal cancer patients. ROC curve was plotted to analyze the predictive value of miR-627 and miR-448 for poor prognosis in colorectal cancer. The prognostic factors of colorectal cancer patients were analyzed using COX regression.Results:There was a difference in the expression levels of miR-627 and miR-448 between colorectal cancer tissue and adjacent tissues ( P<0.05). The expression of miR-627 and miR-448 in colorectal cancer tissue was related to clinical features (TNM stage, differentiation degree, lymph node metastasis, and depth of infiltration) ( P<0.05). The survival rate of patients with high expression of miR-627 was higher than that of patients with low expression ( χ2=10.050, P<0.05); the survival rate of patients with high expression of miR-448 was higher than that of patients with low expression ( χ2=9.033, P<0.05). The expression levels of miR-627 and miR-448 in the poor prognosis group were greatly lower than those in the good prognosis group ( P<0.05). According to the ROC curve, the AUC of miR-627 in predicting poor prognosis of colorectal cancer was 0.811, the AUC of miR-448 in predicting poor prognosis of colorectal cancer was 0.772, and the AUC of combination of the two in predicting poor prognosis of colorectal cancer was 0.859. The combination of the two was better than their individual predictions (Z combination vs. miR-627=2.538, Z combination vs. miR-448=2.572, P<0.05). Multivariate COX regression found that miR-627, miR-448, and clinical features (TNM stage, degree of differentiation, lymph node metastasis, and depth of infiltration) were risk factors affecting the prognosis of colorectal cancer patients ( P<0.05) . Conclusion:The expression levels of miR-627 and miR-448 in colorectal cancer tissues were greatly reduced. The combination of the two is related to the clinical characteristics and prognosis of patients, and can greatly improve the predictive value for prognosis of colorectal cancer patients.

Perceptual decision making refers to the process by which individuals make choices and judgments based on sensory information, serving as a fundamental ability for human adaptation to complex environments. While traditional research has focused on perceptual decision making in isolated contexts, growing evidence highlights the profound influence of social contexts prevalent in real-world scenarios. As a crucial factor supporting individual survival and development, social context not only provides rich information sources but also shapes perceptual decision making through top-down processing mechanisms, prompting researchers to recognize the inherently social nature of human decisions. Empirical studies have demonstrated that social information, such as others’ choices or group norms, can systematically bias individuals’ perceptual decisions, often manifesting as conformity behaviors. Social influence can also facilitate performance under certain conditions, particularly when individuals can accurately identify and adopt high-quality social information. The impact of social context on perceptual decisions is modulated by a variety of external and internal factors, including group characteristics(e.g., group size, response consistency), attributes of peers (e.g., familiarity, social status, distinctions between human and artificial agents), as well as individual differences such as confidence, personality traits, and developmental stage. The motivations driving social influence encompass three primary mechanisms: improving decision accuracy through informational influence, gaining social acceptance through normative influence, and maintaining positive self-concept. Recent computational approaches have employed diverse theoretical frameworks to provide valuable insights into the cognitive mechanisms underlying social influence in perceptual decision making. Reinforcement learning models demonstrate how social feedback shapes future choices through reward-based updating. Bayesian inference frameworks describe how individuals integrate personal beliefs with social information based on their respective reliabilities, dynamically updating beliefs to optimize decisions under uncertainty. Drift diffusion models offer powerful tools to decompose social influence into distinct cognitive components, allowing researchers to differentiate between changes in perceptual processing and shifts in decision criteria. Collectively, these models establish a comprehensive methodological foundation for disentangling the multiple pathways by which social context shapes perceptual decisions. Neuroimaging and electrophysiological studies provide converging evidence that social context influences perceptual decision making through multi-level neural mechanisms. At early perceptual processing stages, social influence modulates sensory evidence accumulation in parietal cortex and directly alters primary visual cortex activity, while guiding selective attention to stimulus features consistent with social norms through attentional alignment mechanisms. At higher cognitive levels, the reward system (ventral striatum, ventromedial prefrontal cortex) is activated during group-consistent decisions; emotion-processing networks (anterior cingulate cortex, insula, amygdala) regulate experiences of social acceptance and rejection; and mentalizing-related brain regions (dorsomedial prefrontal cortex, temporoparietal junction) support inference of others’ mental states and social information integration. These neural circuits work synergistically to achieve top-down multi-level modulation of perceptual decision making. Understanding the mechanisms by which social context shapes perceptual decision making has broad theoretical and practical implications. These insights inform the optimization of collective decision-making, the design of socially adaptive human-computer interaction systems, and interventions for cognitive disorders such as autism spectrum disorder and anorexia nervosa. Future studies should combine computational modeling and neuroimaging approaches to systematically investigate the multi-level and dynamic nature of social influences on perceptual decision making.

INTRODUCTION: Obstructive sleep apnoea (OSA) is common in Singapore, with moderate to severe OSA affecting around 30% of residents. These consensus statements aim to provide scientifically grounded recommendations for the management of OSA, standar-dise the management of OSA in Singapore and promote multidisciplinary collaboration. METHOD: An expert panel, which was convened in 2024, identified several areas of OSA management that require guidance. The expert panel reviewed the current literature and developed consensus statements, which were later independently voted on using a 3-point Likert scale (agree, neutral or disagree). Consensus (total ratings of agree and neutral) was set a priori at ≥80% agreement. Any statement not reaching consensus was excluded. RESULTS: The final consensus included 49 statements that provide guidance on the screening, diagnosis and management of adults with OSA. Additionally, 23 statements on the screening, diagnosis and management of paediatric OSA achieved consensus. These 72 consensus statements considered not only the latest clinical evidence but also the benefits and harms, resource implications, feasibility, acceptability and equity impact of the recommendations. CONCLUSION The statements presented in this paper aim to guide clinicians based on the most updated evidence and collective expert opinion from sleep specialists in Singapore. These recommendations should augment clinical judgement rather than replace it. Management decisions should be individualised, taking into account the patient's clinical characteristics, as well as patient and caregiver concerns and preferences.
Humans ; Sleep Apnea, Obstructive/diagnosis* ; Singapore ; Consensus ; Adult