ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

ObjectiveObesity, a global chronic metabolic disease, is closely associated with disruptions in lipid metabolism and gut microbiota. Current intervention strategies still have limitations in terms of safety and microecological regulation, necessitating the exploration of novel natural regulatory approaches. Based on the early pathological characteristics of obesity, this study innovatively employs a rectal delivery method alongside a high-fat diet (HFD)-induced obesity model to systematically evaluate the inhibitory effects, safety, and gut microbiota regulation mechanisms of leek-derived and konjac-derived extracellular vesicles on obesity development. By simulating early clinical intervention scenarios, this study aims to explore the preventive potential of plant-derived extracellular vesicles during the initial stages of obesity onset. MethodsExtracellular vesicles from leek and konjac were isolated using ultracentrifugation combined with density gradient centrifugation. Their nanoscale properties were characterized by dynamic light scattering (DLS), transmission electron microscopy (TEM), and nanoparticle tracking analysis (NTA). Male C57BL/6J mice were randomly divided into four groups: normal control (NC), high-fat diet (HFD), leek-derived extracellular vesicles (LEVs), and konjac-derived extracellular vesicles (KEVs). Beginning simultaneously with HFD feeding, mice in the intervention groups received 20 g/L vesicles rectally every 3 d for 4 weeks. Body mass and body composition were monitored throughout. At endpoint, mouse serum, adipose tissue, and colonic contents were collected. Serum biochemical indices (lipid profile, liver and kidney function, cardiac markers) were assessed to evaluate safety and metabolic efficacy, while 16S rRNA sequencing was employed to analyze gut microbial structure and diversity. ResultsDLS, NTA, and TEM confirmed that both LEVs and KEVs exhibited typical cup-shaped nanostructures with average particle sizes of approximately 284 nm and 223 nm, respectively. LEVs and KEVs treatment significantly suppressed HFD-induced weight gain and elevation of body-fat percentage (P<0.05), and reduced accumulation of abdominal white and epididymal adipose tissue. Serological analyses showed that both vesicles lowered total cholesterol, triglycerides and LDL-cholesterol, and ameliorated liver enzyme profiles (ALT, AST), demonstrating lipid-metabolic regulation and hepatoprotective effects. No hepatic, renal or cardiac dysfunction was observed, indicating favorable safety. Gut microbiota analyses revealed that vesicle intervention partially restored HFD-depleted microbial diversity and reshaped community structure. Notably, LEVs markedly increased the relative abundance of the beneficial taxon Lachnospiraceae at the family level, which is known for producing short-chain fatty acids and enhancing intestinal barrier function. Furthermore, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) functional prediction suggested that LEVs and KEVs modulated gut microbial functions through distinct mechanisms: LEVs downregulated pathways related to ribosomes and DNA replication while enhancing xenobiotic degradation, whereas KEVs tended to upregulate energy metabolism and protein synthesis toward healthy levels. ConclusionRectally administered LEVs and KEVs exhibit excellent safety and pronounced metabolic benefits during the early phase of obesity, suppressing weight gain, correcting lipid dysregulation, and exerting effects via modulation of gut microbial composition and function. This study provides systematic experimental evidence supporting plant-derived exosome-like vesicles as an early intervention strategy against obesity.

AIM: To conduct whole exome sequencing(WES)analysis on three pedigrees with blepharophimosis-ptosis-epicanthus inversus syndrome(BPES)to identify the pathogenic gene loci, uncover novel mutations, and expand the mutation spectrum of the disease-associated genes.METHODS:Retrospective study. A total of 3 pedigrees and 30 patients with BPES(with criteria of bilateral blepharophimosis, ptosis, epicanthus inversus and wider inner canthal distance at birth)treated in the Ophthalmology Department of the Second People's Hospital of Yunnan Province were collected from January 2021 to August 2021, including 8 patients and 22 unaffected family members. Peripheral blood samples were collected from patients and related family members, and genomic DNA was extracted for whole exome sequencing. The sequencing results were screened to identify potential pathogenic gene loci, and candidate mutations were validated using Sanger sequencing.RESULTS:WES analysis identified pathogenic gene mutations in 3 BPES pedigrees: pedigree 1(6 members, 3 affected individuals, with a history of disease across three generations)harbored a novel heterozygous mutation in the PIEZO2 gene(located 36 bp upstream of exon 11, G>C). Sanger sequencing confirmed that this mutation was present in all affected individuals and absent in normal family members, and it represents the first report of this mutation. Pedigree 2(14 members, 2 affected individuals)and pedigree 3(10 members, 3 affected individuals)carried known heterozygous mutations in the FOXL2 gene, namely the missense mutation c.313A>C(p.N105H)and the in-frame mutation c.672_701dupAGCGGCTGCAGCAGCTGCGGCTGCAGCCGC(p.A225_A234dupAAAAAAAAAA), respectively.CONCLUSION:WES successfully identified the pathogenesis of familial congenital BPES in two families, including a known FOXL2 gene mutation and a newly discovered PIEZO2 gene mutation. These findings provide a theoretical basis for genetic counseling and reproductive guidance. Notably, the PIEZO2 gene mutation(located 36 bp upstream of exon 11, G>C)discovered in the pedigree 1 is reported for the first time and plays a critical role in the onset of the disease in this family. Further investigation of this new mutation could not only expand the mutation spectrum of BPES, but also enhance our understanding of its pathogenic mechanisms.

Traditional Chinese medicine （TCM） diagnostics is a discipline that studies the basic theories and fundamental skills of diagnostic methods， disease diagnosis， and differentiation in accordance with the theories of TCM. The artificial intelligence （AI） technology has gained remarkable achievements in the intelligentization of the four diagnostic methods in TCM and the standardization of differentiation and diagnosis. However， it still faces many challenges. The standardization of clinical data collection is difficult， and the data quality is uneven， which affects the usability of the data. The integration of the four diagnostic information is insufficient. Most instruments can only collect data from a single diagnostic method， lacking overall integrity. The scientific nature of the diagnostic model needs to be improved. The existing models lack dynamics and the reasoning logic of TCM differentiation. The accuracy of intelligent methods needs to be improved， and the existing evaluation indicators cannot fully reflect the practical application effect of the model. Furthermore， the relevant laws and regulations are still not perfect， and data security and patient privacy lack guarantees. The cultivation of compound talents is insufficient， and there is a lack of interdisciplinary talents who are proficient in both TCM and AI. On this basis， this paper expounded on the current development status， difficulties， and bottlenecks of AI in TCM diagnosis and then explored the development trend of AI in the field of TCM diagnosis. It proposed solutions such as optimizing the data collection process， constructing multimodal diagnostic models， facilitating multi-disciplinary exchanges and cooperation， improving laws and regulations， and cultivating compound talents. It is hoped that modern， standardized， normalized， and intelligent TCM diagnosis can be further promoted， thereby providing new impetus and methods for the inheritance and innovation of TCM.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Work serves as a critical means of obtaining resources, facilitating personal growth, realizing self-worth, and engaging in social interactions. However, work-related diseases pose significant threats to workers’ health and productivity, and impose considerable economic burdens. This article categorized work-related diseases into six major types, including musculoskeletal disorders, mental and behavioral disorders, cardiovascular and metabolic diseases, digestive system diseases, reproductive system diseases, and non-specific respiratory diseases, and summarized their risk factors, assessment methods, policy regulation, and prevention and control measures. Current research in this field predominantly relies on cross-sectional studies, which present limitations in causal inference and potential risks of bias. Future studies should expand sample sizes, optimize research designs, and establish multidimensional evaluation systems to comprehensively assess the health and economic impacts of work-related diseases. It is recommended to enhance the translation of research findings into practice, thereby providing a scientific basis for the occupational health protection system and promoting the well-being and sustainable development of the working population.

Background: s/Aims: Postoperative pancreatic fistulas (POPF) remain a major cause of morbidity and mortality following pancreatoduodenectomy (PD). Pancreatogastrostomy (PG) and pancreatojejunostomy (PJ) are the two most commonly used reconstruction techniques, yet evidence favoring one over the other is inconclusive. This study evaluates postoperative outcomes following open PD at a single institution that transitioned from PG to PJ as the preferred reconstruction method. Methods: This retrospective comparative study included patients who underwent PD between April 2005 and August 2022. Of 757 patients identified, 522 met the inclusion criteria. Propensity score matching (PSM) was performed to adjust for clinically relevant covariates. Primary endpoints were clinically relevant (CR) POPF (grade B/C) and Clavien–Dindo (CD) grade ≥ 3 POPFs. Secondary outcomes included post-pancreatectomy hemorrhage (PPH), delayed gastric emptying (DGE), systemic complications, length of hospital stay, and mortality. Results: Overall, CR-POPF and CD grade ≥ 3 POPFs occurred in 21.3% and 8.0% of patients, respectively. Thirty-day and in-hospital mortality rates were 3.1% and 4.2%. After PSM, 368 patients (184 PG and 184 PJ) were analyzed. Grade B POPFs were more frequent following PJ than PG (24.5% vs. 15.8%, p < 0.001). Although CR-POPF and CD grade ≥ 3 POPFs were numerically higher in the PJ group, differences were not statistically significant. In contrast, DGE, PPH, and in-hospital mortality were significantly higher following PG (37.0% vs. 25.0%, p = 0.025; 16.3% vs. 8.7%, p = 0.025; and 7.6% vs. 2.7%, p = 0.049, respectively). Conclusions PG was associated with a lower incidence of grade B POPFs but higher rates of DGE, PPH, and in-hospital mortality.

Introduction: The 2021 IDF-DAR risk calculator had been previously evaluated in multiple studies and subsequently widely accepted and applied in clinical practice as a practical standardized tool for patient risk stratification. Recently updated, the 2026 IDF-DAR Risk calculator enables a more individualized, evidence-related evaluation of patientrelated and disease-related risk factors, incorporating modern diabetes technologies, including continuous glucose monitoring (CGM), automated insulin delivery (AID) systems, and advanced insulin formulations to enhance risk stratification. This tool allows medical professionals to tailor Ramadan practices based on overall factors toward promoting safe fasting. Methodology: This prospective multicentre observational study recruited adults with Type 1 and Type 2 diabetes attending public hospitals nationwide. People with diabetes (PwD) intending to perform Ramadan fasting were invited to participate and assessed using the 2026 IDF-DAR Risk Calculator in the 6-week pre-Ramadan period between 30th January and 19th March 2026. Results: A total of 458 PwD were evaluated and stratified into low (15.7%), moderate (41%), and high risk (43.3%) categories. Most participants had Type 2 diabetes (83.6%), with 60.3% having a disease duration exceeding 10 years and 43% exhibiting poor glycemic control (hemoglobin A1c >9%). Insulin therapy was used by 76.4% of participants, including two individuals with Type 1 diabetes using AID systems. Most participants reported no recent hypoglycemia (76.4%), 81.0% performed glucose monitoring, and 3.3% used CGM. Severe comorbidities were uncommon, with 1.1% having unstable macrovascular disease and 4.4% advanced chronic kidney disease (estimated glomerular filtration rate <30). Notably, 72.2% received structured Ramadan education. Conclusion Majority of PwD attending tertiary diabetes clinics were in the moderate- to high-risk category and intended to fast despite medical advice against fasting in some cases. Although most participants were on insulin therapy, hypoglycemia was low in the pre-Ramadan period. Integration of modern technologies, advanced insulin therapies, and structured education may support safer fasting practices.
Risk Assessment ; Diabetes Mellitus ; Hospitals ; Fasting

Objective To analyze the current status of medical services in secondary and tertiary hospitals in Shandong Province based on DRG,and to provide effective support for the implementation strategies of bidirectional referral.Methods The DRG group was used to analyze 42.348 3 million cases from 75 secondary hospitals and 69 tertiary hospitals in Shandong Province from 2019 to 2023.Experts were organized to establish standards for bidirectional referral of diseases.Results(1)35 high-frequency DRG disease groups with diagnosis,treatment ability and medical resources in secondary hospitals were selected,(2)The medical expenses and medical quality in the high-frequency DRG disease groups within secondary hospitals were lower than those in tertiary hospitals,(3)To develop standardized referral standards and programs with esophageal cancer as an example.Conclusion It is urgent to triage patients gradually and accurately through disease classification management,and formulate disease diagnosis and treatment plans and bidirectional referral standards to improve the medical quality of secondary hospitals.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.