BackgroundPatients with chronic schizophrenia often suffer from cognitive impairment. Traditional cognitive rehabilitation training has problems such as a single form and poor compliance， making it urgent to develop new cognitive intervention methods. ObjectiveTo explore the intervention effect of smartphone games on the cognitive function of patients with chronic schizophrenia， and to analyze the differences in cognitive function improvement between patients of different genders， in order to provide references for the cognitive function intervention of these patients. MethodsThis study was a prospective cohort study. A total of 30 patients who were hospitalized in the Psychiatry Department of Chaohu Hospital Affiliated to Anhui Medical University from March to October 2021， met the diagnostic criteria for schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）， and had a disease duration of above 5 years， were selected as the research subjects. All patients received smartphone game intervention for 12 weeks， 5 times a week， each session lasting 1 hour， in addition to conventional antipsychotic drug treatment. At the baseline and at 3， 6， 9， and 12 weeks of the intervention， the cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status （RBANS）， the Positive and Negative Syndrome Scale （PANSS） was used to assess mental symptoms， and the Problematic Mobile Gaming Questionnaire （PMGQ） was used to assess addiction symptoms. ResultsA total of 26 patients （86.67%） completed the study， including 13 females and 13 males. The time effects， group effects， and interaction effect between time and group for the immediate memory factor score of RBANS in the female group and the male group were all statistically significant （F=36.682， 5.712， 3.090， P<0.05 or 0.01）， and the time effects and group effects for the verbal and delayed memory factors as well as the total score in both groups were also statistically significant （F=3.841， 6.149， 15.372， P<0.05 or 0.01）. The time effects and group effects of the total score of PANSS in both groups had no statistical significance （F=2.041， 0.623， P>0.05 for both）， and the interaction effect between time and group was statistically significant （F=5.728， P<0.01）. The time effects， group effects， and interaction effect of the total score of PMGQ in both groups were all without statistical significance （F=2.672， 0.166， 0.642， P>0.05 for both）. ConclusionSmartphone game intervention may help improve the cognitive function of patients with chronic schizophrenia （especially immediate memory， verbal function， and delayed memory）， and the benefits are greater for female patients. The smartphone game intervention did not induce game addiction， but no significant improvement in psychotic symptoms was observed. ［Funded by Excellent Young Talents Support Program of Anhui Provincial Department of Education （number， gxyqZD2022022）； www.chictr.org.cn number， ChiCTR2100044113］

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

End-stage liver disease (ESLD) covers the end-stage of acute and chronic liver diseases, mainly involving decompensated cirrhosis, various types of liver failure, and advanced liver cancer. Hepatocyte transplantation has shown promise in treating ESLD, but its clinical application is hampered by the shortage of donor hepatocytes. Cell therapy, an emerging effective treatment for ESLD, faces the same limitation due to scarce hepatocyte availability. Hepatocyte-like cells (HLCs), which are terminally differentiated cells, can be induced from both stem cells and somatic cells. As HLCs exhibit the morphology and function of primary hepatocytes, they offer a promising supplementary source of hepatocytes for cell therapy. First, we provide a background for the differentiation and maturation of primary hepatocytes. Subsequently, based on the current insights into the molecular pathways that regulate hepatocyte differentiation in vivo, we describe a strategy for establishing HLC derived from either stem cells or somatic cells. The key characteristics of these HLCs are also detailed. Furthermore, HLC offers therapeutic potential for liver failure, and HLC-based liver organoids and bioartificial liver systems have demonstrated the ability to provide liver functions, offering an innovative approach to treating various types of ESLD. Despite their promise, challenges such as efficiency in differentiation and functional maturation need to be addressed to improve the clinical application of HLCs. This review discusses these advancements and outlines the therapeutic potential and current challenges of HLC therapy for ESLD.

Objective To investigate the potential protective mechanism of tanshinone ⅡA against acetaminophen （APAP）-induced acute liver injury. Methods Thirty mice were randomly divided into the normal group, model group, low-dose tanshinone ⅡA group （5 mg/kg）, medium-dose tanshinone ⅡA group （10 mg/kg） and high-dose tanshinone ⅡA group （20 mg/kg）. All groups were intragastrically administered once daily for 7 consecutive days. On the 7th day, except for the normal group, mice in the remaining groups were intraperitoneally injected with 400 mg/kg APAP to establish the acute lung injury （ALI） model. The protective effect of tanshinone ⅡA was evaluated based on the liver weight ratio, the levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT）, and HE staining. Targets of tanshinone ⅡA were predicted by the Traditional Chinese Medicine Systems Pharmacology （TCMSP）, and a shared target protein-protein interaction （PPI） network was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins （STRING） 11.5 in combination with disease targets from GeneCards. The Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis was performed by Database for Annotation, Visualization and Integrated Discovery （DAVID）, and the component-target-pathway network was constructed. The molecular docking between tanshinone ⅡA and the core targets was performed by AutoDock and visualised. Results Compared with the normal group, the liver weight ratio and serum aminotransferase level of mice with acute liver injury were significantly elevated （P<0.05）, and the pathological injury of liver tissue was obvious. After tanshinone ⅡA treatment, the above index were significantly reduced （P<0.05）, and the pathological injury was significantly improved. Further network pharmacological analysis was carried out and found that KEGG pathway enrichment analysis focused on IL-17 signaling pathway and tumor necrosis factor （TNF） signaling pathway, etc. In addition, the PPI core network showed that the key targets of tanshinone ⅡA to ameliorate acute liver injury mainly included TP53, AKT1, SRC, TNF and JUN. The molecular docking results showed that tanshinone ⅡA had high binding scores with the targets of MMP9, NFKB1, TNF, EP300 and SMAD3; and was able to bind to the targets of TP53, AKT1, SRC and JUN. Conclusion Tanshinone ⅡA may play a protective role against acute liver injury by regulating genes such as AKT1, JUN and TNF, and participating in signaling pathways such as TNF and IL-17.

ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

ObjectiveAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties with communication and social interaction, restricted and repetitive behaviors. Previous studies have indicated that individuals with ASD exhibit early and lifelong attention deficits, which are closely related to the core symptoms of ASD. Basic visual attention processes may provide a critical foundation for their social communication and interaction abilities. Therefore, this study explores the behavior of children with ASD in capturing attention to changes in topological properties. MethodsOur study recruited twenty-seven ASD children diagnosed by professional clinicians according to DSM-5 and twenty-eight typically developing (TD) age-matched controls. In an attention capture task, we recorded the saccadic behaviors of children with ASD and TD in response to topological change (TC) and non-topological change (nTC) stimuli. Saccadic reaction time (SRT), visual search time (VS), and first fixation dwell time (FFDT) were used as indicators of attentional bias. Pearson correlation tests between the clinical assessment scales and attentional bias were conducted. ResultsThis study found that TD children had significantly faster SRT (P<0.05) and VS (P<0.05) for the TC stimuli compared to the nTC stimuli, while the children with ASD did not exhibit significant differences in either measure (P>0.05). Additionally, ASD children demonstrated significantly less attention towards the TC targets (measured by FFDT), in comparison to TD children (P<0.05). Furthermore, ASD children exhibited a significant negative linear correlation between their attentional bias (measured by VS) and their scores on the compulsive subscale (P<0.05). ConclusionThe results suggest that children with ASD have difficulty shifting their attention to objects with topological changes during change detection. This atypical attention may affect the child’s cognitive and behavioral development, thereby impacting their social communication and interaction. In sum, our findings indicate that difficulties in attentional capture by TC may be a key feature of ASD.

OBJECTIVES: Renal cell carcinoma (RCC) is a malignant renal tumor that poses a significant threat to patient health. Accurate preoperative pathological grading plays a crucial role in determining the appropriate treatment for this disease. Currently, deep learning technology has become an important method for pathological grading of RCC. However, existing methods primarily rely on single-phase computed tomography (CT) imaging for analysis and prediction, which has limitations such as missing small lesions, one-sided evaluation, and local focusing issues. Therefore, this study proposes a multi-modal deep learning algorithm that integrates multi-phase enhanced CT images with clinical variable data, aiming to provide a basis for predicting the pathological grading of RCC. METHODS: First, the algorithm took four-phase enhanced CT images from the plain scan, arterial phase, venous phase, and delayed phase, along with clinical variables, as inputs. Then, an embedding encoding module was used to extract heterogeneous information from the clinical variables, and a 3-dimensional (3D) ResNet50 model was employed to capture spatial information from the multi-phase enhanced CT image data. Finally, a Fusion module deeply integrated the feature information from clinical variables and each phase's CT image features, further utilizing a cross-self-attention mechanism to achieve multi-phase feature fusion. This approach comprehensively captures the deep semantic information from the patient data, fully leveraging the complementary advantages of multi-modal and multi-phase data. To validate the effectiveness of the proposed method, a total of 1 229 RCC patients were approved by ethics review were included to train the model. RESULTS: Experimental results demonstrated superior performance compared to traditional radiomics and state-of-the-art deep learning methods, achieving an accuracy of 83.87%, a recall rate of 95.04%, and an F1-score of 82.23%. CONCLUSIONS The proposed algorithm exhibits strong stability and sensitivity, significantly enhancing the predictive performance of RCC pathological grading. It offers a novel approach for accurate RCC diagnosis and personalized treatment planning.
Humans ; Carcinoma, Renal Cell/pathology* ; Deep Learning ; Kidney Neoplasms/diagnostic imaging* ; Tomography, X-Ray Computed/methods* ; Algorithms ; Neoplasm Grading ; Male ; Female ; Middle Aged

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Graves'ophthalmopathy(GO)is a specific autoimmune disease occurring in orbital tissues and is closely related to hyperthyroidism caused by Graves'disease(GD).Its disabling and disfiguring features significantly impact the quality of life of patients.The exact mechanism of GO still remains to be fully elucidated.In recent years,gene sequencing and medical microbiology studies have shown that changes in the gut microbiota may play a role in the development and progression of GO,with gut dysbiosis altering immune system regulatory signals and causing immune damage to organs.Clarifying the correlation between gut microbiota and GO helps to understand the disease's pathogenic mechanism and provides a theoretical basis for the diagnosis and treatment of GO.This review summarizes the impact of gut microbiota dysbiosis in the pathogenesis of GO and promising therapeutic approaches,including research progress in aspects such as gut microbiota experiments,case studies,pathogenesis,and treatment strategies.

Objective To analyze the relationship between the visceral adiposity index(VAI)and nocturia in the US adult population.Methods A cross-sectional study was performed.Data from subjects aged≥20 years in the National Health and Nutrition Examination Survey(NHANES)database from 2007 to 2020 were collected,including waist circumference,triglyceride,body mass index(BMI),high-density lipoprotein,age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,cancer,and nocturnal urination frequency.Weighted analysis,multivariate logistic regression,generalized additive model(GAM),and curve fitting were employed to evaluate the association between VAI and nocturia,adjusting for age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,and cancer.Subgroup analyses were conducted based on age,gender,race,hypertension and diabetes to further evaluate the relationship between VAI and the risk of nocturia.Results A total of 29,196 American adults were included.All subjects were divided into 4 groups based on VAI quartiles:Q1 group(0.32≤VAI<1.01),Q2 group(1.01≤VAI<1.70),Q3 group(1.70≤VAI<2.95),and Q4 group(2.95≤VAI<13.59),with nocturia prevalence rates of 28.5%,31.4%,33.3%,and 34.9%,respectively.In subgroup analyses,the risk of nocturia significantly increased with higher VAI in the 20-40 age group,females and other Hispanics(OR=1.04,95%CI 1.01-1.08,P=0.006;OR=1.02,95%CI 1.00-1.04,P=0.035;OR=1.05,95%CI 1.01-1.09,P=0.026).GAM analysis results showed a nonlinear relationship between VAI and nocturia.Conclusion VAI is positively associated with the risk of nocturia,and may be an effective indicator for predicting the risk of nocturia occurrence.