Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Objective:To investigate the nutritional risk status of children in PICU and analyze its influencing factors.Methods:From July 2021 to February 2023,all children aged 1 to 18 years admitted to PICU of Beijing Children's Hospital were investigated by using the pediatric Yorkhill Malnutrition Scoring tool(PYMS)and the clinical data questionnaire.Results:A total of 492 children in PICU were enrolled.The first nutritional risk screening results showed that there were 32 cases of no/low nutritional risk(6.5%),76 cases of medium risk(15.4%),and 384 cases of high risk(78.1%).The incidence of medium/high nutritional risk was as high as 93.5%.The PYMS score of nutritional risk in PICU was(2.61±1.42).The results of multiple linear regression analysis showed that weight,fever time before admission,white blood cells,body mass index,primary diagnosis,father's education,and diet before illness were the main influencing factors of nutritional risk of children in PICU(P<0.05).Conclusion:Children in PICU are in a state of high nutritional risk.It is suggested that children in PICU should carry out nutritional screening in a standardized manner,identify children with high nutritional risk and its influencing factors early.To actively conduct nutritional assessment and nutritional intervention could improve the clinical outcome of children in PICU.

A rapid and accurate method for textile fiber identification was developed for quality control and consumer protection.This method utilized electric soldering iron burning-mesh collision enhanced microtube plasma ionization mass spectrometry(ESIB-MC-μTP-MS)to acquire textile fiber MS data and used a random forest(RF)prediction model to identify fiber composition based on these MS data.The MC-μTP device involved in the method was a homemade low-temperature plasma ionization device constructed using cost-effective and readily available components.The system was applicable for direct analysis of small amount of textile samples without any complex sample pretreatment processes.Characteristic thermal decomposition products of different fibers were generated via soldering iron burning(350℃)in ambient atmosphere,and were subsequently analyzed by a mass spectrometer,with each analysis completed within 5 s.Raw MS data underwent noise reduction,normalization,and global binning steps to form a dataset,and its intrinsic class separability was evaluated using principal component analysis(PCA)combined with k-means clustering.Then,the RF model was trained based on the dimensionality-reduced textile fiber dataset.After grid search optimization,this model demonstrated robust performance with a 0.9762 out-of-bag score,a 0.9683 cross-validation accuracy(5-fold),and a 0.9636 test accuracy,supported by precision,recall,and F1-scores exceeding 0.889 for all fiber classes.The method was applied to analysis of 30 luxury apparel samples from eight brands,among which 20 samples achieved 100%prediction confidence,aligning with labeled compositions.The identification result of two low-confidence samples was further confirmed using attenuated total reflection Fourier transform infrared spectroscopy(ATR-FT-IR).The method has been proven to be simple,portable and with minimal sample requirements for on-site customs inspections,providing a viable tool in the fight against counterfeit products,therefore supporting regulatory enforcement and consumer trust in the textile goods market.

Due to the poor ionization efficiency and the weak mass spectrometry(MS)intensity of weakly polar substances,direct analysis using the traditional electrospray ionization mass spectrometry(ESI-MS)is a big challenge.In this study,a novel rapid on-site detection method of four prohibited sex hormones in cosmetics was proposed using online derivatization strategy coupled with a miniature mass spectrometer.The target substances in the samples were extracted by a custom-made polyaniline/multi-walled carbon nanotube solid-phase microextraction(SPME)probe.The stirring speed was 200 r/min,the extraction temperature was 40℃,and the extraction time was 2 min.A pulled dual-channel θ borosilicate glass capillary emitter was used as the nano-ESI ion source.The SPME probe was inserted into the channel containing methanol in theθborosilicate glass capillary.When the spray voltage was applied,the four sex hormones were desorbed and formed spray microdroplets,which then collided with the hydroxylamine microdroplets generated from the other channel.The microdroplets of reaction product entered into the miniature mass spectrometer for direct analysis.The limits of detection(LOD)and limits of quantification(LOQ)for the four sex hormones were 10-20 ng/mL and 20-50 ng/mL,respectively.The recoveries were from 84.6%to 107.8%with the relative standard deviations(RSD)from 4.1%to 11.6%.Compared to detection without derivatization,the MS signals of the four target substances were increased by 3 to 15 times.This method was simple,rapid,highly efficient and sensitive,and suitable for on-site rapid analysis of weakly polar sex hormones in cosmetics.

Insulin is an important protein hormone that participates in multiple metabolic pathways.Biosynthetic insulin has been widely used in the treatment of type 1 and type 2 diabetes.Currently,the number of reported cases of insulin overdose both at home and abroad is gradually increasing,and insulin homicide is no longer a means of"committing murder without leaving a trace".At present,there are no systematic protocols for the identification of insulin overdose in the field of forensic medi-cine in China.This article introduces the causes,toxicological characteristics,forensic examination,labo-ratory testing methods and indicator reference of insulin overdose.Based on the identification practice and research results and referring to relevant studies on insulin overdose at home and abroad,this pa-per aims to provide recommendations and references for the formulation of forensic identification guide-lines for insulin overdose cases.

PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning

BACKGROUND: Atrial fibrillation (AF) is a common cardiac arrhythmia in the elderly. This study aimed to evaluate urban-rural disparities in its prevalence and management in elderly Chinese. METHODS: Consecutive participants aged ≥ 65 years attending outpatient clinics were enrolled for AF screening using handheld single-lead electrocardiogram (ECG) from April 2017 to December 2022. Each ECG rhythm strip was reviewed from the research team. AF or uninterpretable single-lead ECGs were referred for 12-lead ECG. Primary study outcome comparison was between rural and urban areas for the prevalence of AF. The Student's t-test was used to compare mean values of clinical characteristics between rural and urban participants, while the Pearson's chi-square test was used to compare between-group proportions. Multivariate stepwise logistic regression analysis was performed to estimate the association between AF and various patient characteristics. RESULTS: The 29,166 study participants included 13,253 men (45.4%) and had a mean age of 72.2 years. The 7073 rural participants differed significantly (P ≤ 0.02) from the 22,093 urban participants in several major characteristics, such as older age, greater body mass index, and so on. The overall prevalence of AF was 4.6% (n = 1347). AF was more prevalent in 7073 rural participants than 22,093 urban participants (5.6% vs. 4.3%, P < 0.01), before and after adjustment for age, body mass index, blood pressure, pulse rate, cigarette smoking, alcohol consumption and prior medical history. Multivariate logistic regression analysis identified overweight/obesity (OR = 1.35, 95% CI: 1.17-1.54) in urban areas and cigarette smoking (OR = 1.62, 95% CI: 1.20-2.17) and alcohol consumption (OR = 1.42, 95% CI: 1.04-1.93) in rural areas as specific risk factors for prevalent AF. In patients with known AF in urban areas (n = 781) and rural areas (n = 338), 60.6% and 45.9%, respectively, received AF treatment (P < 0.01), and only 22.4% and 17.2%, respectively, received anticoagulation therapy (P = 0.05). CONCLUSIONS In China, there are urban-rural disparities in AF in the elderly, with a higher prevalence and worse management in rural areas than urban areas. Our study findings provide insight for health policymakers to consider urban-rural disparity in the prevention and treatment of AF.

BACKGROUND: The beneficial effects of sodium-glucose co-transporter-2 inhibitors (SGLT2i) on adverse cardiac outcomes in diabetic patients are well-established. However, the effects of SGLT2i against cancer therapy-related cardiotoxicity remain understudied. We investigated the association between SGLT2i and cardiac outcomes in cancer patients. METHODS: PubMed, Embase, and the Cochrane Library were searched from their inception until September 30, 2024 for studies evaluating the effects of SGLT2i in patients with cancer. The primary outcomes included incident heart failure (HF), HF exacerbation, HF hospitalization, atrial fibrillation/atrial flutter (AF/AFL), myocardial infarction, and all-cause mortality. The secondary outcomes included acute kidney injury and sepsis. Odds ratio (OR) with 95% CI was pooled. RESULTS: Thirteen studies with 85,596 patients were included. Compared to non-SGLT2i use, SGLT2i treatment was associated with lower risks of incident HF (OR = 0.51, 95% CI: 0.32-0.79, P = 0.003), HF exacerbation (OR = 0.74, 95% CI: 0.63-0.87, P < 0.001), AF/AFL (OR = 0.67, 95% CI: 0.55-0.82, P < 0.001), myocardial infarction (OR = 0.61, 95% CI: 0.41-0.90, P = 0.01), and all-cause mortality (OR = 0.44, 95% CI: 0.28-0.69, P < 0.001), but not for HF hospitalization (OR = 0.58, 95% CI: 0.22-1.55, P = 0.28). As for safety outcomes, SGLT2i use was associated with lower risks of acute kidney injury (OR = 0.68, 95% CI: 0.57-0.81, P < 0.001) and sepsis (OR = 0.32, 95% CI: 0.23-0.44, P < 0.001). CONCLUSIONS SGLT2i were associated with lower risks of incident HF, HF exacerbation, AF/AFL, myocardial infarction, all-cause mortality, acute kidney injury, and sepsis in cancer patients.