OBJECTIVE: Chromosome conformation-based karyotype analysis (C-MoKa) technology was used to test a couple who had experienced multiple adverse pregnancies in order to provide them with genetic counseling and reproductive guidance. METHODS: A couple presented at the Reproductive Medicine Center of the First Hospital of Lanzhou University in 2023 was selected as the study subject. Through C-MoKa testing, copy number variation sequencing (CNV-seq), and preimplantation genetic testing for aneuploidy (PGT-A), it was found that the couple's repeatedly miscarried fetuses and abnormal embryos exhibited highly similar chromosomal structural abnormalities. Using C-MoKa, the potential genetic abnormalities in both partners were traced, and reproductive guidance was provided based on the result. This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: LDYYSZLLKH2025-09). RESULTS: CNV-seq analysis of the couple's miscarriage fetal chorionic villi showed del(18)(q21.2q23)(28.90 Mb) and dup(13)(q31.2q34)(26.26 Mb). Chromosomal karyotyping analysis of both partners showed no abnormality. From 2024 to 2025, the couple underwent three rounds of PGT-A assisted reproduction. The first embryo test showed del(13)(q31.2q34)(26.77 Mb) and dup(18)(q21.2q23)(29.08 Mb). The second embryo test showed dup(13)(q31.2q34)(26.26 Mb) and del(18)(q21.2q23)(28.90 Mb). And the third embryo test results showed complex chromosomal abnormalities. In 2025, after genetic counseling, the couple had opted C-MoKa test, which has detected no abnormality in the wife, but a balanced 46,XY,t(13;18)(q31.2;q21.2) translocation in the husband. CONCLUSION As a high-throughput sequencing method based on the three-dimensional conformation of chromatin, C-MoKa has the advantages of high resolution and high accuracy, and can accurately detect balanced translocations with similar banding patterns. It has therefore offered a powerful new tool for chromosomal analysis.
Female ; Humans ; Male ; Pregnancy ; Abortion, Habitual/genetics* ; DNA Copy Number Variations ; Karyotyping/methods* ; Preimplantation Diagnosis ; Translocation, Genetic

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective To compare clinical efficacy of different regimens in treatment of pruritus in maintenance hemodialysis(MHD)patients.Methods A total of 50 patients with MHD admitted to the Sixth People's Hospital of Jiujiang City from August 1,2022 to April 30,2024 as subjects and were divided into two groups according to random number table method.Control group(n=25)was treated with sodium thiosulfate.On this basis,gabapentin combination therapy was added in observation group(n=25).Effects of two groups were compared after 8 weeks of treatment.Results Total clinical effective rate of observation group was significantly higher than that of control group(P＜0.05).After 8 weeks of treatment,scores and total scores of all dimensions of quality of life in two groups were higher than before treatment,and observation group was higher than control group(P＜0.05).Conclusion Sodium thiosulfate combined with gabapentin in treatment of MHD patients with pruritus can not only relieve pruritus symptoms,improve sleep quality,but also have good safety.

Objective To explore the mechanism of IgA nephropathy(IgAN)caused by multi-glycosides of Tripterygium wilfordii(GTW)through the regulation of Silent information regulatory factor 1(SIRT 1)/nuclear transcription factor E2-related factor 2(Nrf 2)/antioxidant enzyme heme oxygenase 1(HO-1)signaling pathway.Methods Forty-five male SD rats were selected and randomly divided into two groups:the blank group(n=9)and the model group(n=36).In addition to the blank group,the BSA+CCl4+LPS group was used.At the end of 12 weeks,two rats were randomly selected for verification,and the model was successfully established.The 34 model rats were randomly divided into 3 groups:the model group(n=10),prednisone group(n=12),and GTW group(n=12).Urine,blood and kidney tissues were harvested 4 weeks after drug administration.Urinary erythrocyte number,24-h urinary protein quantification(24 h-UTP),alanine transaminase(ALT),serum albumin(ALB),urea nitrogen(BUN),and blood creatinine(SCr)were performed for each group;the protein expression of SIRT1,Nrf2,HO-1 and PINK1 was detected by Western blotting analysis;real-time polymerase chain reaction(RT-PCR)detection of SIRT1,Nrf2,HO-1 and PINK1 mRNA expression in rat kidney tissue;and detection of IgA deposition in the renal mesangial area by immunofluorescence.Kidney histopathological changes were observed in all the rats by hematoxylin-eosin(HE)staining.Results The results compared with those in the blank group,the urinary red blood cell count and 24 h-UTP,ALT,BUN,and SCr levels were significantly greater(P<0.01);The ALB level was significantly lower(P<0.01);renal tissue SIRT1,Nrf2,HO-1,PINK1 protein and mRNA expression were significantly lower(P<0.01);IgA deposition in the mesentery was obvious;renal pathological damage was severe;and the difference was statistically significant. Compared with those in the model group,urinary red blood cell counts and 24 h-UTP,ALT,BUN,and SCr levels in the prednisone and GTW groups were significantly lower (P<0.01);ALB levels were significantly greater (P<0.01);SIRT1,Nrf2,HO-1,PINK1 protein and mRNA expression were significantly greater (P<0.01);IgA deposition in the mesangial area was reduced,and renal pathology was improved,with statistically significant difference. Conclusions GTW may alleviate oxidative stress injury,protect renal function,and improve renal injury by activating the SIRT 1/Nrf 2/HO-1 signaling pathway.

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 compare the clinical and functional differences between transoral and submandibular approach in mandibu-lar segmental resection and reconstruction with free fibula flaps(FFFs).Methods Patients who underwent mandibular segmental re-section and FFFs reconstruction in the Department of Oral and Maxillofacial Surgery of the Affiliated Stomatological Hospital of Nanjing Medical University from January 2015 to March 2023 were retrospectively analyzed.All cases were divided into transoral approach and submandibular approach groups.Clinical characteristics of the patients were recorded including age,gender,follow-up time,pathologi-cal diagnosis,body mass index(BMI),American Society of Anesthesiologists(ASA)classification,James Brown classification of mandibular defect and number of fibular segments.The perioperative indexes,such as average operation time,average bleeding vol-ume,average blood transfusion volume,average drainage volume,average hospitalization time and postoperative complications such as malocclusion,fistula,infection,flap failure,and restriction of mouth opening were compared between the two groups.The University of Washington Quality of Life Questionnaire was used to investigate the appearance,function of swallow and speech more than 6-month postoperatively.Results The average intraoperative bleeding and postoperative drainage were significantly lower in the transoral ap-proach group than in the submandibular approach group(P=0.013 9,P=0.001 9).The appearance score was significantly higher in the transoral approach group than in the submandibular approach group(83.52±12.37)vs.(67.19±13.64)(P＜0.000 1).The differ-ences between the two groups in other variables were not statistically significant.Conclusion Cases of transoral approach had signifi-cantly better aesthetic outcomes compared with those of submandibular approach.

Background Workers in the cable manufacturing industry are exposed to high-speed machinery and equipment for a long time, coupled with heavy workload, which poses significant risks to their physical health. However, the issue of occupational injuries in this industry has not received enough attention yet. Objective To understand the incidence of occupational injury of workers in cable manufacturing industry and to analyze the influencing factors. Method A basic information questionnaire and an occupational injury questionnaire were developed to investigate the occupational injuries of 1 343 workers in a cable manufacturing enterprise in the past year, and a total of 1 225 valid questionnaires were recovered, with an effective rate of 91.2%. Descriptive statistics were used to characterize the causes, injury locations, injury types, and other characteristics of employees’ occupational injuries. Chi-square test was used to analyze the occupational injury status of groups with different demographic characteristics, occupational characteristics, lifestyles, and interpersonal relationships. Logistic regression was used to analyze the influencing factors of occupational injuries. Result The incidence of occupational injuries among workers in a cable manufacturing enterprise in the past year was 8.6%, which mainly happened in male workers (80.0%) and occurred from May to July in summer (45.7%). The main causes were mechanical injuries (32.4%) and object blows (27.6%). The main sources of damage were machinery and equipment (36.2%) as well as raw materials and products (15.2%). The main injuries were located in upper limbs (53.3%) and lower limbs (22.9%). The main types of injuries were fractures (33.3%) and abrasions/contusions/puncture wounds (19.0%). The results of univariate analysis showed that there were statistically significant variations in the incidence of occupational injuries by gender, overtime, pre-job training, years of service in current position, alcohol consumption, physical exercise per week, and co-worker relationship (P<0.05). The logistic regression model showed that workers who exercised less than twice a week, did not participate in pre-job training, worked overtime, and had fair/poor/very poor colleague relationship had a higher risk of occupational injury, while women had a lower risk of occupational injury. Conclusion The distribution of occupational injury population is mainly male, and the time distribution is mainly from May to July. Gender, physical exercise, pre-job training, overtime, and colleague relationship are the influencing factors of occupational injuries. We should strengthen pre-job training, arrange work hours reasonably, and create a good working atmosphere to reduce the occurrence of occupational injuries.

Background Social psychological factors have emerged as a key area of research in occupational injury prevention. Occupational stress, a significant component of social psychology, has garnered widespread attention due to its potential impact on occupational injury. Objective To analyze the factors influencing occupational stress among cable manufacturing workers and explore the relationship between occupational stress and occupational injury, and to provide scientific evidence for reducing occupational stress and injury. Methods A questionnaire on basic demographics, occupational injury, and occupational stress (Effort-Reward Imbalance, ERI) was used to investigate 1343 workers in a cable enterprise. Chi-square test was employed to analyze the distribution of occupational stress across different worker characteristics. Logistic regression was used to identify factors influencing occupational stress, and a decision tree model was applied to assess the impact of occupational stress on injury risk. Results A total of 1225 valid questionnaires were collected, yielding a response rate of 91.2%. The positive rate of occupational stress was 28.7%, while the incidence of occupational injury in the past year was 8.6%. The results of univariate analysis revealed that workers who had experienced occupational injuries had a higher positive rate of occupational stress compared to those without injuries (P<0.05), and there were significant differences in the distribution of occupational stress by genders, overtime work, shift work, daily working hours, fatigue levels, sleep duration, family relationships, and colleague relationships (P<0.05). The logistic regression results showed that individuals who worked shifts, had fair/poor/very colleague relationships, and frequently worked overtime had a higher risk of occupational stress (P<0.05). The final decision tree model confirmed that occupational stress was a risk factor for occupational injury. Additional factors influencing occupational injury included physical exercise, colleague relationships, pre-job training participation, and gender. Workers who exercised less than twice per week and experienced occupational stress had a significantly higher risk of injury (23.6%) compared to those without occupational stress (10.9%). Conclusion Shift work, colleague relationships, and overtime work are correlated with the positive rate of occupational stress among cable manufacturing workers. Implementing a reasonable work schedule and fostering a positive work environment are recommended. Reducing occupational stress may help lower the risk of occupational injuries in this industry.

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*