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 enhance the efficiency and accuracy of post-marketing safety monitoring and evaluation of drugs in China by studying large language models-based patient medical record pharmacovigilance profiling techniques,providing scientific methods and technical support to ensure the safe use of drugs for patients.Methods This study constructs a pharmacovigilance profile that includes individual patient differences,medication details,and adverse reaction manifestations.It enhances a large language model with a knowledge graph in the field of pharmacovigilance and designs targeted prompts to guide the model to output pharmacovigilance profiles.Results Large language models demonstrate significant advantages in active monitoring,effectively processing and analyzing medical text data,and improving the monitoring and prediction capabilities of drug adverse reactions.Through the design of prompts,the model can more accurately depict patient pharmacovigilance profiles,providing decision support for medical professionals.Conclusions The study of large language model-based patient medical record pharmacovigilance profiling technology provides scientific evidence and technical support for the early detection and prevention of drug adverse reactions,helping to reduce medical costs,improve medical outcome prognoses,and opens new paths to ensure patient drug safety.

Caenorhabditis elegans,as an emerging model organism,has been widely used in multiple disciplines such as medicine,life science,and environmental science in recent years,due to its charac-teristics of short life cycle,clear genetic background,highly conserved evolution,complete genome analysis and excellent fitting between experimental data and human results.It also shows unique advan-tages in the field of toxicology.This paper summarizes its advantages in toxicological research starting from the biological characteristics of C.elegans,introduces the toxicological research methods and progress based on the C.elegans model,focuses on demonstrating its applications in environmental fo-rensic medicine and forensic toxicology,and looks forward to the application of the relevant results in the field of forensic science.

AIM To study the chemical constituents from the petroleum ether fraction of the roots of Gypsophila licentiana Hand.-Mazz.METHODS Silica gel,Sephadex LH-20 and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Eighteen compounds were isolated and identified as dibutyl phthalate(1),glyceryl arachidate(2),bis(2-ethylhexyl)terephthalate(3),9,12-octadecadienoic acid(Z,Z)-methyl ester(4),(3'S,4'S)-3'-acetoxy-4'-angeloyloxy-3',4'-dihydroseselin(5),3-(4-hydroxy-3-methoxyphenyl)-propanoic acid(6),bis(2-ethylhexyl)phthalate(7),2,2'-oxybis(1,4)-di-tert-butylbenzene(8),gypsogenin(9),3-keto,16α-hydroxy,24-noroleanolic acid(10),3-oxo-olean-12-en-28-oic acid(11),10-eicosenoic acid(12),hexacosanic acid(13),enniatin B(14),(R,Z)-21-methyl-8-pentatriacontene(15),ethyl gallate(16),stellarine A(17),pentacosane(18).CONCLUSION All compounds are isolated from this plant for the first time.

The inheritance, innovation, and development of traditional Chinese medicine(TCM) need to be based on Chinese medicinal materials. The TCM seed industry is the source of TCM production, which is related to the stable supply and quality safety of TCM. This paper summarizes the basic situation of the TCM seed industry and introduces relevant policies and regulations to TCM seeds in the seed industry and the TCM field. At present, the Management Measures of TCM Seeds and Seedlings has not yet promulgated, and TCM seeds are classified as non-major crops in the category of crops for management. This paper also describes the current situation of TCM seed and seedling system construction, which is in the development stage, from six aspects, including the construction of TCM seed industry technical support system; the establishment of TCM seed standard; the construction of germplasm resource preservation system; TCM seed testing, variety registration, and variety protection; production and management of TCM seeds; TCM seed supervision. According to the development status of the TCM seed industry, four problems are put forward, including imperfect systems and standards relevant to TCM seeds, insufficient supervision and law enforcement regarding TCM seeds, insufficient policy measures and capital investment to promote the development of the industry, and the industry's falling into a low-level cycle.Accordingly, four suggestions are provided, including improving laws, regulations, and policies, perfecting standards and norms,strengthening supervision and law enforcement, and promoting support system construction, in order to boost the high-quality development of the TCM seed industry.
Seeds/chemistry* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry*

OBJECTIVES: To evaluate the clinical utility and translational potential of a remote jaundice monitoring system for home-based screening of neonatal hyperbilirubinemia. METHODS: A prospective self-controlled study was conducted, enrolling 538 newborns with gestational age ≥35 weeks, birth weight ≥2 000 g, and postnatal age ≤14 days at the Women's Hospital of Nanjing Medical University from March to October 2023. Four screening protocols with different predictive indicators were developed based on the Chinese Neonatal Transcutaneous Hourly Bilirubin Nomogram. The effectiveness of the system was evaluated, and the feasibility of using the remote jaundice monitoring system in actual home settings was analyzed. RESULTS: A total of 538 paired transcutaneous bilirubin (TcB) and total serum bilirubin (TSB) measurements showed a strong correlation (r=0.85, P<0.001), with 95.0% (511/538) of samples within the 95% limits of agreement. Using TcB ≥ the 95th percentile as the predictive indicator, the system achieved 100% sensitivity, 46.2% specificity, and an area under the receiver operating characteristic curve of 0.731 (95%CI: 0.682-0.780). This approach could reduce unnecessary hospital visits by 41.4% (221/538). CONCLUSIONS The system integrates the QBH-801 transcutaneous bilirubinometer, intelligent early warning, and remote guidance services, establishing a closed-loop "hospital-to-home" management model. It demonstrates high safety and feasibility, with significant clinical translational value.
Humans ; Infant, Newborn ; Female ; Male ; Bilirubin/blood* ; Feasibility Studies ; Prospective Studies ; Hyperbilirubinemia, Neonatal/diagnosis* ; Neonatal Screening/methods* ; Jaundice, Neonatal/diagnosis*

AIM To study the chemical constituents from the petroleum ether fraction of the roots of Gypsophila licentiana Hand.-Mazz.METHODS Silica gel,Sephadex LH-20 and semi-preparative HPLC were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.RESULTS Eighteen compounds were isolated and identified as dibutyl phthalate(1),glyceryl arachidate(2),bis(2-ethylhexyl)terephthalate(3),9,12-octadecadienoic acid(Z,Z)-methyl ester(4),(3'S,4'S)-3'-acetoxy-4'-angeloyloxy-3',4'-dihydroseselin(5),3-(4-hydroxy-3-methoxyphenyl)-propanoic acid(6),bis(2-ethylhexyl)phthalate(7),2,2'-oxybis(1,4)-di-tert-butylbenzene(8),gypsogenin(9),3-keto,16α-hydroxy,24-noroleanolic acid(10),3-oxo-olean-12-en-28-oic acid(11),10-eicosenoic acid(12),hexacosanic acid(13),enniatin B(14),(R,Z)-21-methyl-8-pentatriacontene(15),ethyl gallate(16),stellarine A(17),pentacosane(18).CONCLUSION All compounds are isolated from this plant for the first time.

Objective To enhance the efficiency and accuracy of post-marketing safety monitoring and evaluation of drugs in China by studying large language models-based patient medical record pharmacovigilance profiling techniques,providing scientific methods and technical support to ensure the safe use of drugs for patients.Methods This study constructs a pharmacovigilance profile that includes individual patient differences,medication details,and adverse reaction manifestations.It enhances a large language model with a knowledge graph in the field of pharmacovigilance and designs targeted prompts to guide the model to output pharmacovigilance profiles.Results Large language models demonstrate significant advantages in active monitoring,effectively processing and analyzing medical text data,and improving the monitoring and prediction capabilities of drug adverse reactions.Through the design of prompts,the model can more accurately depict patient pharmacovigilance profiles,providing decision support for medical professionals.Conclusions The study of large language model-based patient medical record pharmacovigilance profiling technology provides scientific evidence and technical support for the early detection and prevention of drug adverse reactions,helping to reduce medical costs,improve medical outcome prognoses,and opens new paths to ensure patient drug safety.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.