AIM To screen the material basis for Rhei Radix et Rhizoma on improving human umbilical vein endothelial cell(HUVECs)injury before and after carbonization.METHODS The HPLC fingerprints were established,after which difference analysis was performed by orthogonal partial least squares discriminant analysis.The LPS-induced HUVECs injury model was established,then NO,MDA levels and SOD activity were detected.Gray correlation analysis and partial least squares regression were adopted in the investigation of spectrum-effect relationship,and active constituents were screened.RESULTS There were 22 and 20 common peaks in the fingerprints for 17 batches of raw products and carbonized products,respectively,along with the similarities of more than 0.8.Twelve main difference components were observable,among which gallic acid,5-hydroxymethylfurfural,catechin,aloe rhodopsin-8-O-β-D-glucoside,rhubarbic acid-8-O-β-D-glucoside and sennosides A were identified.The carbonized products demonstrated stronger effect on improving HUVECs injury than the raw product.The correlations of common peaks were more than 0.5 in the fingerprints for raw products and carbonized products,and peaks 3,5,11,12,15,19,23 exhibited significant effects on their efficacy(VIP values＞1).CONCLUSION This accurate,reliable and reproducible method can provide a basis for clarifying the material basis for hemostatic efficacy of Rhei Radix et Rhizoma and its carbonized product.

Objective:To investigate the role of SiHa cell-derived exosomal hsa-miR-29c-3p in the angiogenesis of cervical cancer(CC).Methods:Cancer tissue specimens from 45 patients with cervical squamous cell carcinoma(CSCC)and normal cervical tissue specimens from 15 controls were collected from Department of Gynecology,Hengyang Central Hospital from January 2019 to December 2021.CSCC SiHa cells and human umbilical vein endothelial cells(HUVECs)were routinely cultured.miRNA-NC,hsa-miR-29c-3p,si-miRNA-NC,and si-hsa-miR-29c-3p were transfected into SiHa cells with Lipofectamine 2000,grouped as miRNA-NC group,hsa-miR-29c-3p group,si-miRNA-NC group and si-hsa-miR-29c-3p group,respectively.HUVECs were transfected with mimic-NC,miR-29c-3p-mimic,pCMV-NC,and pCMV-ATAD2B(ATPase family protein 2B with AAA domain)using Lipofectamine 2000,grouped as the mimic-NC group,miR-29c-3p-mimic group,pCMV-NC group,pCMV-ATAD2B group,and pCMV-ATAD2B+miR-29c-3p-mimic group.The expression of hsa-miR-29c-3p in CSCC tissues was detected by in situ hybridization(ISH),and CD31-positive blood vessels in CSCC tissues and xenograft tissues were detected by immunohistochemistry(IHC).Exosomes from SiHa and C33a cells were isolated and characterized using transmission electron microscopy(TEM)and western blotting(WB).The uptake of exosomes by HUVECs was examined.The expression of hsa-miR-29c-3p and ATAD2B mRNA in SiHa and C33a cells,as well as in their derived exosomes,was detected using qPCR.Tube-forming assay,Transwell assay,and scratch healing assay were performed to detect the effect of exosomes on the ability of HUVEC migration and tube formation.Dual luciferase reporter gene assay verified the interaction between hsa-miR-29c-3p and ATAD2B.Xenograft experiments examined the effects of SiHa cell-derived exosomes on transplanted tumor growth and angiogenesis in each group.Results:hsa-miR-29c-3p was highly expressed in CSCC tissues and was positively correlated with microvessel density(MVD)(all P<0.05).Exosomes derived from SiHa and C33a cells exhibited typical exosomal morphology and protein expression patterns.Exosomal hsa-miR-29c-3p from SiHa and C33a cells were efficiently taken up by HUVECs in vitro.The SiHa cell-derived exosomal hsa-miR-29c-3p promoted not only the tube-forming and migration of HUVECs in vitro but also the xenograft growth and angiogenesis in vivo(all P<0.05).hsa-miR-29c-3p directly targeted ATAD2B and regulated its expression(P<0.05).Overexpression of ATAD2B reversed the promotive effect of hsa-miR-29c-3p on tube-formation,migration,and scratch-healing in HUVECs(all P<0.05).Conclusion:SiHa cell-derived exosomal hsa-miR-29c-3p regulates angiogenesis in CSCC tissues by targeting ATAD2B.Exosomal hsa-miR-29c-3p may be a potential diagnostic marker and therapeutic target for CC diagnosis and treatment.

Objective To organize and summarize the medication rules of GU Nai-fang in treating skin diseases through real-world data.Methods We collected traditional Chinese medicine prescriptions for GU Nai-fang's treatment of skin diseases from the outpatient medical record system of Shanghai Traditional Chinese Medicine Hospital to establish a database.Statistical analysis of disease types,performance,and efficacy was conducted,and association rules and systematic clustering analysis were performed using SPSS Modeler 18.0 and SPSS 26.0 software,respectively.Results A total of 5 020 patients were included,and 5 020 prescriptions were collected,involving 241 traditional Chinese medicines with a total frequency of 85 758 uses.The frequency of using heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface clearing drugs,and wind and dampness dispelling drugs was relatively high;most drugs tended to be cold and warm,mainly targeting the heart,lungs,and colon meridians.The top 15 Chinese medicines with the highest frequency of use were Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,Scutellariae Radix,Cynanchi Paniculati Radix et Rhizoma,Schisandrae Chinensis Fructus,Violsse Herba,Mume Fructus,Herba Pyrolae,Hedyotis Diffusae Herba,Lonicerae Japonicae Flos,Cicadae Periostracum,Bombyx Batryticatus,Radix Salviae.Association rule analysis obtained 15 high-frequency combinations of 2 traditional Chinese medicines and 3 traditional Chinese medicines.Cluster analysis resulted in 7 clustered prescriptions.Conclusion GU Nai-fang commonly used heat clearing drugs,deficiency tonifying drugs,blood activating and stasis removing drugs,surface resolving drugs,and wind and dampness dispelling drugs in the treatment of skin diseases,and Smilacis Glabrae Rhixoma,Cortex Moutan,Radix Paeoniae Rubra,Rehmanniae Radix,and Scutellariae Radix were the most frequently used drugs.

AIM To evaluate the quality of Rubi Fructus.METHODS UPLC-Q-TOF-MS/MS was adopted in the component identification,after which the HPLC fingerprints were established,cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition.and the contents of chlorogenic acid,ferulic acid,ellagic acid,isoquercitrin,kaempferol-3-O-rutinoside,astragalin,tiliroside quercetin,kaempferol were determined.RESULTS Total 34 constituents were identified.There were 19 common peaks in the fingerprints for 31 batches of medicinal materials with the similarities of more than 0.8.Wild varieties and cultivated varieties,and medicinal materials from different producing areas could be distinguished;4 principal components demonstrated the accumulative variance contribution rate of 84.142％;8 differential components were screened,2 of which were ellagic acid and astragalin.Ellagic acid and astragalin displayed higher contents in the wild varieties than those in the cultivated varieties(P＜0.05,P＜0.01).CONCLUSION UPLC-Q-TOF-MS/MS,HPLC fingerprints combined with content determination can be used for the quality control of Rubi Fructus.

Bismuth iodide(BiOI)with different crystal plane ratios of(110)to(001)was synthesized,and typeⅡheterojunction formed between(001)and(110)crystal planes of BiOI was used to improve the separation efficiency of photogenerated electrons and holes.Then the BiOI(001)/(110)was composited with nitrogen-doped graphene quantum dots(N-GQDs)to prepare a ternary composites,which could enhance the range and intensity of light absorption,and prolonged the lifetime of photogenerated electrons due to the formation of Z-scheme heterojunctions between BiOI and N-GQDs,thereby leading to the excellent photoelectric performance of the BiOI/N-GQDs for generating sensitive photoelectric response signals.A photoelectrochemical sensor for sensitive detection of chlorpyrifos(CPF)was designed with BiOI/N-GQDs-modified FTO electrode as a photocathode.The S and N atoms contained in CPF were coordinated with Bi(Ⅲ)on the surface of BiOI,which reduced the photocurrent of BiOI/N-GQDs.The photocurrent change was linear with logarithm of concentration of CPF in the range of 1.5×10-12-5.0×10-9 mol/L,and the detection limit was 1.5×10-12 mol/L.The sensor was highly sensitive,selective and stable,and could be used for determination of trace CPF in environmental and food samples.

A pyrene-phenol-based fluorescent probe PyP which showed typical intramolecular charge transfer(ICT)and monomer-excimer activities was synthesized by using pyrene carboxaldehyde hydrazone and 4-tert-butyl-2,6-diformylphenol as the raw materials.The effects of solvents on PyP were studied,and the results showed that the color of protic polar solvents(Ethanol,N,N-dimethylformamide,methanol and H2O)were successfully identified.Based on the solvent polarity-regulated PyP monomer-excimer switching,the rapid and highly sensitive ratiometric probe,"Turn-off"and"Turn-on"multimodal probes were established for detection of trace water content in organic solvents(Dimethyl sulfoxide,N,N-dimethylformamide,ethanol and methanol),with detection limits(3σ/k)of 0.0021％,0.046％,0.062％and 0.024％.The method was successfully used to detect water content in dimethyl sulfoxide,N,N-dimethy lformamide,ethanol and methanol commercial organic solvents,with recoveries ranging from 97.2％to 108.0％.The developed method showed good accuracy and stability,and had good application prospect.

Lung cancer has the highest incidence and mortality among malignant tumors in China.Persistent subsolid nodules(SSNs)are closely associated with early-stage lung adenocarcinoma.Artificial intelligence(AI),as an emerging technology,is capable of performing in-depth analysis of large-scale imaging data through autonomous learning and possesses the ability to predict outcomes from new data,demonstrating great potential and application prospects in the assessment of SSNs.AI can not only effectively assist radiologists in diagnosis and treatment,but also improve work efficiency while reducing misdiagnosis and missed diagnosis rates.This review summarizes the recent applications and research progress of AI in the assessment of SSNs,to provide new insights for the diagnosis and treatment of SSNs.

Objective To investigate the epidemiological characteristics of knee osteoarthritis(KOA)among military personnel in plateau regions and to explore its risk factors.Methods From July 2023 to July 2024,a multi-stage stratified cluster random sampling method was employed to survey the prevalence of KOA and related risk factors among military personnel in the northwest plateau regions of China,covering different altitudes(1500-4500 m)and geographical areas(Gansu,Qinghai,Tibet,and Xinjiang).All study subjects were divided into KOA and non-KOA groups based on the presence or absence of KOA.Variables including age,gender,body mass index(BMI),education level,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury were selected for univariate analyses between groups.Variables with P<0.05 in the univariate analyses were included in the binary multifactor logistic regression to identify risk factors for KOA.Results A total of 3000 questionnaires were distributed,and 2854 valid questionnaires were collected,with a response rate of 95.13%.The sample included 2584 males and 270 females,with 510 cases of KOA,resulting in a prevalence rate of 17.9%.Univariate analysis showed that there were statistically significant differences between KOA and non-KOA groups in terms of age,BMI,smoking status,military rank,military branch,service duration,regional altitude,annual average temperature,training duration,perceived training intensity,and history of knee injury(P<0.05).However,no significant differences were found in gender and education level(P>0.05).Binary multivariate logistic regression analysis revealed that older age(OR=1.382,P=0.017),higher BMI(P<0.01),smoking(OR=1.929,P<0.01),higher military rank(OR=1.485,P=0.007),being a member of the Armed Police(P<0.01),longer service duration(P<0.01),higher regional altitude(OR=1.459,P<0.01),lower annual average temperature(OR=1.188,P=0.001),longer training duration(P<0.01),higher perceived training intensity(OR=2.450,P<0.01),and history of knee injury(OR=2.768,P=0.002)were independent risk factors for KOA.Conclusions Older age,overweight/obesity,smoking,higher military rank,being a member of the Armed Police,longer service duration,higher altitude,cold climate,longer training duration,higher training intensity,and history of knee injury are independent risk factors for KOA among military personnel in the northwest plateau regions of China.

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

OBJECTIVE: We aimed to investigate the patterns of fasting blood glucose (FBG) trajectories and analyze the relationship between various occupational hazard factors and FBG trajectories in male steelworkers. METHODS: The study cohort included 3,728 workers who met the selection criteria for the Tanggang Occupational Cohort (TGOC) between 2017 and 2022. A group-based trajectory model was used to identify the FBG trajectories. Environmental risk scores (ERS) were constructed using regression coefficients from the occupational hazard model as weights. Univariate and multivariate logistic regression analyses were performed to explore the effects of occupational hazard factors using the ERS on FBG trajectories. RESULTS: FBG trajectories were categorized into three groups. An association was observed between high temperature, noise exposure, and FBG trajectory ( P < 0.05). Using the first quartile group of ERS1 as a reference, the fourth quartile group of ERS1 had an increased risk of medium and high FBG by 1.90 and 2.21 times, respectively (odds ratio [ OR] = 1.90, 95% confidence interval [ CI]: 1.17-3.10; OR = 2.21, 95% CI: 1.09-4.45). CONCLUSION An association was observed between occupational hazards based on ERS and FBG trajectories. The risk of FBG trajectory levels increase with an increase in ERS.
Humans ; Male ; Adult ; Blood Glucose/analysis* ; China ; Prospective Studies ; Occupational Exposure/adverse effects* ; Risk Factors ; Middle Aged ; Steel ; Fasting/blood* ; Metal Workers ; East Asian People