OBJECTIVE: To explore the genetic etiology of 46 Chinese pedigrees affected with Hereditary multiple exostoses (HME) and provide genetic counseling and reproductive intervention. METHODS: Whole-exome sequencing and Sanger sequencing were carried out on 87 patients from the 46 pedigrees to analyze the variants of EXT1 and EXT2 genes. Pathogenicity of the variants was assessed based on the guidelines from the American College of Medical Genetics and Genomics and Association for Molecular Pathology (ACMG/AMP). Prenatal diagnosis and preimplantation genetic testing (PGT) were provided for couples with identified pathogenic mutations. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: LL-SC-SG-2014-010). RESULTS: In total 17 and 22 pathogenic variants were respectively identified in the EXT1 and EXT2 genes, among which 5 EXT1 and 12 EXT2 variants were unreported previously. Three patients with no family history were found to harbor de novo variants of the EXT1 gene. Twenty nine couples had opted for PGT or underwent prenatal diagnosis following natural conception, and 17 healthy babies were born. CONCLUSION This study has clarified the genetic etiology of 45 HME pedigrees and identified 17 novel variants, which has enriched the mutational spectrum of the EXT1 and EXT2 genes. Reproductive intervention through PGT and prenatal diagnosis have prevented the recurrence of HME in these families.
Humans ; Female ; Male ; Pedigree ; Exostoses, Multiple Hereditary/diagnosis* ; N-Acetylglucosaminyltransferases/genetics* ; Adult ; Exostosin 1 ; Asian People/genetics* ; Genetic Testing ; Exostosin 2 ; Mutation ; China ; Prenatal Diagnosis ; Pregnancy ; Genetic Counseling ; Preimplantation Diagnosis ; Exome Sequencing ; East Asian People

The pathogenesis of metabolic dysfunction-associated steatotic liver disease （MASLD） is fundamentally rooted in spleen deficiency and is closely associated with phlegm turbidity， damp-heat and blood stasis. Clinically， liver constraint with spleen deficiency and internal retention of damp turbidity represent the predominant traditional Chinese medicine （TCM） syndrome patterns. Researches have indicated intrinsic connections between the syndrome patterns and biological indicators such as gut microbiota and metabolic profiles. Regarding treatment， classical famous formulas， modern empirical formulas， and newly developed TCM drugs show positive effects in regulating glucose and lipid metabolism， improving insulin resistance， and alleviating metabolic inflammation， exhibiting multi-target mechanisms of action； acupuncture and other external therapies also provide adjunctive value. Nevertheless， current researches still have limitations such as the lack of high-quality clinical evidence and insufficient systematic elucidation of the uncerlying mechanisms. Future efforts should focus on conducting high-quality TCM clinical trials with hard endpoint outcomes such as hepatic histology outcomes， and utilizing modern technologies like multi-omics to elucidate TCM's mechanisms of action， thereby advancing the position of TCM as a first-line therapeutic strategy for MASLD.

Objective: To develop a clinical decision and prescription generation system (CDPGS) specifically for diarrhea in traditional Chinese medicine (TCM), utilizing a specialized large language model (LLM), Qwen-TCM-Dia, to standardize diagnostic processes and prescription generation. Methods: Two primary datasets were constructed: an evaluation benchmark and a fine-tuning dataset consisting of fundamental diarrhea knowledge, medical records, and chain-of-thought (CoT) reasoning datasets. After an initial evaluation of 16 open-source LLMs across inference time, accuracy, and output quality, Qwen2.5 was selected as the base model due to its superior overall performance. We then employed a two-stage low-rank adaptation (LoRA) fine-tuning strategy, integrating continued pre-training on domain-specific knowledge with instruction fine-tuning using CoT-enriched medical records. This approach was designed to embed the clinical logic (symptoms → pathogenesis → therapeutic principles → prescriptions) into the model’s reasoning capabilities. The resulting fine-tuned model, specialized for TCM diarrhea, was designated as Qwen-TCM-Dia. Model performance was evaluated for disease diagnosis and syndrome type differentiation using accuracy, precision, recall, and F1-score. Furthermore, the quality of the generated prescriptions was compared with that of established open-source TCM LLMs. Results: Qwen-TCM-Dia achieved peak performance compared to both the base Qwen2.5 model and five other open-source TCM LLMs. It achieved 97.05% accuracy and 91.48% F1-score in disease diagnosis, and 74.54% accuracy and 74.21% F1-score in syndrome type differentiation. Compared with existing open-source TCM LLMs (BianCang, HuangDi, LingDan, TCMLLM-PR, and ZhongJing), Qwen-TCM-Dia exhibited higher fidelity in reconstructing the “symptoms → pathogenesis → therapeutic principles → prescriptions” logic chain. It provided complete prescriptions, whereas other models often omitted dosages or generated mismatched prescriptions. Conclusion By integrating continued pre-training, CoT reasoning, and a two-stage fine-tuning strategy, this study establishes a CDPGS for diarrhea in TCM. The results demonstrate the synergistic effect of strengthening domain representation through pre-training and activating logical reasoning via CoT. This research not only provides critical technical support for the standardized diagnosis and treatment of diarrhea but also offers a scalable paradigm for the digital inheritance of expert TCM experience and the intelligent transformation of TCM.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Gastric cancer remains a highly prevalent malignancy worldwide, with surgical resection currently constituting the cornerstone of treatment aimed at improving long-term patient survival. Owing to their notable advantages, including reduced surgical trauma and accelerated postoperative recovery, minimally invasive procedures are progressively supplanting conventional open surgery and have become the mainstream approach in gastric cancer management. Concurrently, the rapid advancement of artificial intelligence (AI) technologies has enabled real-time intraoperative monitoring of surgical scenes, thereby furnishing novel technical support for adjunctive decision-making, surgical navigation, and skill assessment during gastrectomy. This article provides a systematic review of the current status of AI applications in minimally invasive gastric cancer surgery, with a particular focus on research progress pertaining to instrument recognition, surgical phase identification, delineation of normal anatomical structures, detection of metastatic foci, and early warning of intraoperative adverse events. Furthermore, we discuss the potential value of AI in enhancing surgical efficiency, ensuring patient safety, and optimizing surgical education. On this basis, we further analyze the principal challenges and inherent risks confronting current AI systems, with the aim of informing future technological innovation and facilitating clinical translation.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

ObjectiveTo investigate the incidence， glucolipid metabolism characteristics， and associated factors of postoperative overweight/obesity in children and adolescent with craniopharyngioma. MethodsA retrospective study was conducted using follow-up data from 44 patients （aged 0-18 years） diagnosed with craniopharyngioma who underwent surgical treatment and received follow-up care at Sun Yat-sen Memorial Hospital， Sun Yat-sen University， between January 2006 and February 2024. The incidence and glucolipid metabolism characteristics of overweight/obesity were summarized， and potential influencing factors were analyzed. ResultsA total of 44 patients were enrolled. The mean age at surgery was （8.57 ± 4.25） years， and the mean age at last follow-up was （16.02 ± 5.36 ）years. The mean follow-up duration was （7.45 ± 4.64） years （range， 8 months to 17.5 years）. The preoperative incidence of overweight/obesity was 40.91% （predominantly overweight， 27.27%）， which increased to 68.18% postoperatively （predominantly obesity， 50.00%）. Postoperatively， all patients （44/44， 100%） underwent fasting plasma glucose （FPG） testing， among whom 2 （4.55%） had impaired fasting glucose （IFG）. Fasting insulin （FINS） was measured in 20 patients， and insulin resistance was identified in 11 （55.00%）. Oral glucose tolerance testing （OGTT） with insulin release assessment was performed in 12 patients， and all （100%） exhibited abnormal insulin secretion， including 5 （41.67%） with hyperinsulinemia and 3 （25.00%） diagnosed with diabetes mellitus （DM）. All patients （44/44， 100%） underwent lipid profile assessment. The incidence of dyslipidemia was 81.82% （36/44）， including elevated non-high-density lipoprotein cholesterol （29/44， 65.91%）， hypertriglyceridemia （29/44， 65.91%）， low high-density lipoprotein cholesterol （22/44， 50.00%）， and mixed hyperlipidemia （13/44， 29.55%）. Logistic regression analysis indicated that preoperative overweight/obesity and postoperative abnormal glucose metabolism were significant factors associated with postoperative overweight/obesity. Compared with normal-weight patients， those with postoperative overweight/obesity had higher FINS levels （14.22 mU/L vs. 3.57 mU/L）， higher insulin resistance index（HOMA-IR） （2.88 vs. 0.52）， and a higher incidence of abnormal glucose metabolism （77.78% vs. 23.08%）. However， no significant difference was observed in the incidence of dyslipidemia （94.44% vs. 73.08%）. ConclusionsChildren and adolescent with craniopharyngioma exhibit a higher incidence of overweight/obesity than healthy peers preoperatively， which becomes more pronounced after surgery. This is accompanied by a high incidence of glucolipid metabolic disorders， placing these patients at increased risk of metabolic syndrome， which warrants clinical attention and regular metabolic assessment. In patients who develop postoperative obesity， particular attention should be given to the risk of glucose metabolism abnormalities， and further monitoring of glucose homeostasis is recommended.

Heteromeric amino acid transporters (HATs), formed by the assembly of solute carrier 3(SLC3) and solute carrier 7(SLC7) family members, play essential roles in amino acid transmembrane transport, cellular nutrient sensing, and redox homeostasis. Dysregulation of multiple HATs members has been closely associated with tumor metabolic reprogramming, ferroptosis resistance, and inherited amino acid metabolic disorders, making them important targets for drug development. However, the high conservation of substrate-binding pockets, the limited druggability of zwitterionic compounds, and safety concerns arising from their broad expression in normal tissues have collectively hindered the clinical translation of HATs-targeted therapeutics. Recent advances in cryo-electron microscopy (Cryo-EM) have enabled the determination of high-resolution structures of multiple HATs, providing a critical foundation for understanding their molecular mechanisms and for guiding targeted interventions. These structural studies have systematically revealed the molecular basis of selective substrate recognition and ion coupling among different family members and have identified non-conserved structural features that may serve as potential opportunities for subtype-selective targeting. In this review, we systematically summarize recent advances in the structural biology of HATs, with a particular emphasis on their assembly mechanisms, substrate recognition modes, and conformational transitions. Furthermore, we highlight recent progress in structure-based drug design (SBDD), including strategies to enhance ligand affinity by exploiting non-conserved hydrophobic side pockets, as well as approaches to block the transport cycle by disrupting the secondary structures of transmembrane helices TM3 and TM10. Collectively, these insights provide an important structural framework and new perspectives for the development of highly selective inhibitors for HATs and related therapeutic strategies.

Objective: To investigate the current status and influencing factors of dry eye syndrome among medical staff in Dongcheng District of Beijing Municipality, so as to provide reference for formulating targeted intervention measures and promoting eye health among medical staff. Methods: In June 2025, on-the-job medical staff from 20 medical institutions in Dongcheng District were selected as participants by stratified random cluster sampling method. Data including demographic information, eye health status, and lifestyle behaviors were collected through questionnaire surveys. Depressive symptoms and dry eye syndrome were assessed using the Patient Health Questionnaire-9 and the Ocular Surface Disease Index, respectively. A multivariable logistic regression model was used to analyze the influencing factors of dry eye syndrome among medical staff. Results: A total of 2 745 participants were surveyed, including 427 males (15.56%) and 2 318 females (84.44%). The mean age of the participants was (38.96±9.07) years. Dry eye syndrome was detected in 1 816 participants, with a detection rate of 66.16%. Multivariable logistic regression analysis showed that female (OR=1.626, 95%CI: 1.255-2.108), physicians (OR=1.820, 95%CI: 1.174-2.820), myopia (OR=2.322, 95%CI: 1.874-2.876), astigmatism (OR=1.375, 95%CI: 1.125-1.679), presbyopia (OR=2.933, 95%CI: 2.250-3.822), other ocular diseases (OR=2.260, 95%CI: 1.237-4.152), daily electronic screen time ≥5 h (5-<7 h, OR=1.336, 95%CI: 1.053-1.695; 7-<9 h, OR=1.792, 95%CI: 1.395-2.300; ≥9 h, OR=1.978, 95%CI: 1.510-2.591), depressive symptoms (mild, OR=3.653, 95%CI: 2.977-4.482; moderate, OR=6.300, 95%CI: 4.785-8.294; moderately severe, OR=11.461, 95%CI: 6.288-20.892; severe, OR=7.093, 95%CI: 4.014-12.533) had a higher risks of dry eye syndrome; daily sleep duration ≥6 h (6-<8 h, OR=0.723, 95%CI: 0.583-0.898; ≥8 h, OR=0.458, 95%CI: 0.301-0.696) had a lower risk of dry eye syndrome. Conclusion The detection rate of dry eye syndrome was relatively high among medical staff in Dongcheng District, and was associated to gender, job position, myopia, astigmatism, presbyopia, other ocular diseases, daily electronic screen time, daily sleep duration and depressive symptoms.

OBJECTIVE: Acupuncture therapies are known for their effectiveness in treating a variety of gastric diseases, although the mechanisms underlying these effects are not fully understood. This study tested the effectiveness of electroacupuncture (EA) at acupoints Zhongwan (RN12) and Weishu (BL21) for managing gastric motility disorder (GMD) and investigated the underlying mechanisms involved. METHODS: A GMD model was used to evaluate the impact of EA on various aspects of gastric function including the amplitude of gastric motility, electrogastrogram, food intake, and the rate of gastric emptying. Immunofluorescence techniques were used to explore the activation of spinal neurons by EA, specifically examining the presence of cholera toxin B subunit (CTB)-positive neurons and fibers emanating from acupoints RN12 and BL21. The stimulation of γ-aminobutyric acid (GABA)-ergic neurons in the spinal dorsal horn, the inhibition of sympathetic preganglionic neurons in the spinal lateral horn, and their collective effects on the activity of sympathetic nerves were examined. RESULTS: EA at RN12 and BL21 significantly improved gastric motility compromised by GMD. Notably, EA activated spinal neurons, with CTB-positive neurons and fibers from RN12 and BL21 being detectable in both the dorsal root ganglia and the spinal dorsal horn. Further analysis revealed that EA at these acupoints not only stimulated GABAergic neurons in the spinal dorsal horn but also suppressed sympathetic preganglionic neurons in the spinal lateral horn, effectively reducing excessive activity of sympathetic nerves triggered by GMD. CONCLUSION EA treatment at RN12 and BL21 effectively enhances gastric motility in a GMD model. The therapeutic efficacy of this approach is attributed to the activation of spinal neurons and the modulation of the spinal GABAergic-sympathetic pathway, providing a neurobiological foundation for the role of acupuncture in treating gastric disorders. Please cite this article as: Zhang MT, Liang YF, Dai Q, Gao HR, Wang H, Chen L, Huang S, Wang XY, Shen GM. A spinal neural circuit for electroacupuncture that regulates gastric functional disorders. J Integr Med. 2025; 23(1): 56-65.
Electroacupuncture ; Animals ; Male ; Acupuncture Points ; Stomach Diseases/physiopathology* ; Rats, Sprague-Dawley ; Gastrointestinal Motility ; Rats ; Gastric Emptying ; Neurons ; Spinal Cord ; Stomach/physiopathology*