Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.

In the field of dental aesthetics,digital aesthetic design plays a crucial role in helping dentists to predict treatment outcomes vis-ually,as well as in enhancing the consistency of knowledge and understanding of aesthetic goals between dentists and patients.It serves as the foundation for achieving ideal aesthetic effects.However,there is no clear standard for this digital process currently in China and abroad.Many dentists lack of systematic understanding of how to carry out digital aesthetic design for treatment.To establish standardized processes for dental aesthetic design and to improve the homogeneity of treatment outcomes,Chinese Society of Digital Dental Industry(CSD-DI)convened domestic experts in related field to compile this consensus.This article elaborates on the key aspects of digital aesthetic data collection,integration steps,and the digital aesthetic design process.It also formulates a decision tree for dental aesthetics at macro level and outlines corresponding workflows for various clinical scenarios,serving as a reference for clinicians.

Analyze the changes in phenolic components and gene expression profiles of Tetrastigma hemsleyanum leaves with supplemental blue light, and screen differentially expressed genes related to phenolic metabolism, providing a basis for improving the quality of T. hemsleyanum leaves. Using the leaves of T. hemsleyanum under supplemental blue light and visible light as research materials, the content of phenolic components such as neochlorogenic acid, chlorogenic acid, and 3-O-coumaroyl quinic acid was significantly increased by supplemental blue light. A total of 102 949 unigenes were obtained from the transcriptome, including 14 564 differentially expressed unigenes. They can be divided into 52 subclasses by gene ontology (GO) function, kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis showed that these differentially expressed unigenes were significantly enriched in phenolic metabolic pathways such as phenylpropane biosynthesis, flavonoid biosynthesis and isoflavone biosynthesis. A total of 63 differentially expressed unigenes were identified in the pathways related to the biosynthesis of phenolic cpmponents, including 19 key enzymes such as phenylalanine ammonia-lyase (PAL), cinnamyl-alcohol dehydrogenase (CAD), flavonol synthase (FLS), and so on. This study greatly enriched the genetic data information of T. hemsleyanum and laid a foundation for analyzing the mechanism of blue light promoting the biosynthesis of phenols and molecular breeding of T. hemsleyanum.

Objective: To identify the main metals involved in cognitive impairment in the Chinese oldest old, and explore the association between these metal exposures and cognitive impairment. Methods: A cross-sectional study was conducted on 1 568 participants aged 80 years and older from Healthy Aging and Biomarkers Cohort Study (2017 to 2018). Fasting venous blood was collected to measure the levels of nine metals (selenium, lead, cadmium, arsenic, antimony, chromium, manganese, mercury, and nickel). The cognitive function of these participants was evaluated by using the Chinese version of the Mini-Mental State Examination (CMMSE). The random forest (RF) was applied to independently identify the main metals that affected cognitive impairment. The multivariate logistic regression model and restricted cubic splines (RCS) model were used to further verify the association of the main metals with cognitive impairment. Results: The age of 1 568 study subjects was (91.8±7.6) years old, including 912 females (58.2%) and 465 individuals (29.7%) with cognitive function impairment. Based on the RF model (the out-of-bag error rate was 22.9%), the importance ranking of variables was conducted and the feature screening of five times ten-fold cross-validation was carried out. It was found that selenium was the metal that affected cognitive function impairment, and the other eight metals were not included in the model. After adjusting for covariates, the multivariate logistic regression model showed that with every increase of 10 μg/L of blood selenium levels, the risk of cognitive impairment decreased (OR=0.921, 95%CI: 0.889-0.954). Compared with the lowest quartile(Q₁) of blood selenium, the ORs (95%CI) of Q₃ and Q₄ blood selenium were 0.452 (0.304-0.669) and 0.419 (0.281-0.622) respectively. The RCS showed a linear dose-response relationship between blood selenium and cognitive impairment (P_nonlinear>0.05). Conclusion: Blood selenium is negatively associated with cognitive impairment in the Chinese oldest old.
Aged, 80 and over ; Female ; Humans ; Selenium ; Cohort Studies ; Cross-Sectional Studies ; Metals/analysis* ; Cognitive Dysfunction/epidemiology* ; China/epidemiology*

Objective: A Mendelian randomization (MR) analysis was performed to assess the relationship between tea consumption and cancer. Methods: There were 100 639 participants with the information of gene sequencing of whole genome in the China Kadoorie Biobank. After excluding those with cancer at baseline survey, a total of 100 218 participants were included in this study. The baseline information about tea consumption were analyzed, including daily tea consumption or not, cups of daily tea consumption, and grams of daily tea consumption. We used the two-stage least square method to evaluate the associations between three tea consumption variables and incidence of cancer and some subtypes, including stomach cancer, liver and intrahepatic bile ducts cancer, colorectal cancer, tracheobronchial and lung cancer, and female breast cancer. Multivariable MR and analysis only among nondrinkers were used to control the impact of alcohol consumption. Sensitivity analyses were also performed, including inverse variance weighting, weighted median, and MR-Egger. Results: We used 54, 42, and 28 SNPs to construct non-weighted genetic risk scores as instrumental variables for daily tea consumption or not, cups of daily tea consumption, and grams of daily tea consumption, respectively. During an average of (11.4±3.0) years of follow-up, 6 886 cases of cancer were recorded. After adjusting for age, age², sex, region, array type, and the first 12 genetic principal components, there were no significant associations of three tea consumption variables with the incidence of cancer and cancer subtypes. Compared with non-daily tea drinkers, the HR (95%CI) of daily tea drinkers for cancer and some subtypes, including stomach cancer, liver and intrahepatic bile ducts cancer, colorectal cancer, tracheobronchial and lung cancer, and female breast cancer, are respectively 0.99 (0.78-1.26), 1.17 (0.58-2.36), 0.86 (0.40-1.84), 0.85 (0.42-1.73), 1.39 (0.85-2.26) and 0.63 (0.28-1.38). After controlling the impact of alcohol consumption and performing multiple sensitivity analyses, the results were similar. Conclusion: There is no causal relationship between tea consumption and risk of cancer in population in China.
Humans ; Female ; Stomach Neoplasms/epidemiology* ; Mendelian Randomization Analysis/methods* ; Tea ; Breast Neoplasms ; Lung Neoplasms ; Colorectal Neoplasms ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study

Objective: To analyze the prevalence and the risk factors of fungal sepsis in 25 neonatal intensive care units (NICU) among preterm infants in China, and to provide a basis for preventive strategies of fungal sepsis. Methods: This was a second-analysis of the data from the "reduction of infection in neonatal intensive care units using the evidence-based practice for improving quality" study. The current status of fungal sepsis of the 24 731 preterm infants with the gestational age of <34⁺⁰ weeks, who were admitted to 25 participating NICU within 7 days of birth between May 2015 and April 2018 were retrospectively analyzed. These preterm infants were divided into the fungal sepsis group and the without fungal sepsis group according to whether they developed fungal sepsis to analyze the incidences and the microbiology of fungal sepsis. Chi-square test was used to compare the incidences of fungal sepsis in preterm infants with different gestational ages and birth weights and in different NICU. Multivariate Logistic regression analysis was used to study the outcomes of preterm infants with fungal sepsis, which were further compared with those of preterm infants without fungal sepsis. The 144 preterm infants in the fungal sepsis group were matched with 288 preterm infants in the non-fungal sepsis group by propensity score-matched method. Univariate and multivariate Logistic regression analysis were used to analyze the risk factors of fungal sepsis. Results: In all, 166 (0.7%) of the 24 731 preterm infants developed fungal sepsis, with the gestational age of (29.7±2.0) weeks and the birth weight of (1 300±293) g. The incidence of fungal sepsis increased with decreasing gestational age and birth weight (both P<0.001). The preterm infants with gestational age of <32 weeks accounted for 87.3% (145/166). The incidence of fungal sepsis was 1.0% (117/11 438) in very preterm infants and 2.0% (28/1 401) in extremely preterm infants, and was 1.3% (103/8 060) in very low birth weight infants and 1.7% (21/1 211) in extremely low birth weight infants, respectively. There was no fungal sepsis in 3 NICU, and the incidences in the other 22 NICU ranged from 0.7% (10/1 397) to 2.9% (21/724), with significant statistical difference (P<0.001). The pathogens were mainly Candida (150/166, 90.4%), including 59 cases of Candida albicans and 91 cases of non-Candida albicans, of which Candida parapsilosis was the most common (41 cases). Fungal sepsis was independently associated with increased risk of moderate to severe bronchopulmonary dysplasia (BPD) (adjusted OR 1.52, 95%CI 1.04-2.22, P=0.030) and severe retinopathy of prematurity (ROP) (adjusted OR 2.55, 95%CI 1.12-5.80, P=0.025). Previous broad spectrum antibiotics exposure (adjusted OR=2.50, 95%CI 1.50-4.17, P<0.001), prolonged use of central line (adjusted OR=1.05, 95%CI 1.03-1.08, P<0.001) and previous total parenteral nutrition (TPN) duration (adjusted OR=1.04, 95%CI 1.02-1.06, P<0.001) were all independently associated with increasing risk of fungal sepsis. Conclusions: Candida albicans and Candida parapsilosis are the main pathogens of fungal sepsis among preterm infants in Chinese NICU. Preterm infants with fungal sepsis are at increased risk of moderate to severe BPD and severe ROP. Previous broad spectrum antibiotics exposure, prolonged use of central line and prolonged duration of TPN will increase the risk of fungal sepsis. Ongoing initiatives are needed to reduce fungal sepsis based on these risk factors.
Infant ; Infant, Newborn ; Humans ; Birth Weight ; Intensive Care Units, Neonatal ; Retrospective Studies ; Tertiary Care Centers ; Infant, Extremely Low Birth Weight ; Gestational Age ; Infant, Extremely Premature ; Sepsis/epidemiology* ; Retinopathy of Prematurity/epidemiology* ; Bronchopulmonary Dysplasia/epidemiology*

The present study investigated the chemical constituents in the aerial part of Cannabis sativa. The chemical constituents were isolated and purified by silica gel column chromatography and HPLC and identified according to their spectral data and physicochemical properties. Thirteen compounds were isolated from the acetic ether extract of C. sativa and identified as 3',5',4″,2-tetrahydroxy-4'-methoxy-3-methyl-3″-butenyl p-disubstituted benzene ethane(1), 16R-hydroxyoctadeca-9Z,12Z,14E-trienoic acid methyl ester(2),(1'R,2'R)-2'-(2-hydroxypropan-2-yl)-5'-methyl-4-pentyl-1',2',3',4'-tetrahydro-(1,1'-biphenyl)-2,6-diol(3), β-sitosteryl-3-O-β-D-glucopyranosyl-6'-O-palmitate(4), 9S,12S,13S-trihydroxy-10-octadecenoate methyl ester(5), benzyloxy-1-O-β-D-glucopyranoside(6), phenylethyl-O-β-D-glucopyranoside(7), 3Z-enol glucoside(8), α-cannabispiranol-4'-O-β-D-glucopyranose(9), 9S,12S,13S-trihydroxyoctadeca-10E,15Z-dienoic acid(10), uracil(11), o-hydroxybenzoic acid(12), and 2'-O-methyladenosine(13). Compound 1 is a new compound, compound 3 is a new natural product, and compounds 2, 4-8, 10, and 13 were isolated from Cannabis plant for the first time.
Cannabis ; Biological Products ; Esters ; Dihydrostilbenoids ; Plant Components, Aerial

OBJECTIVE: To investigate the effect of Baicalin on the proliferation and pyroptosis of diffuse large B-cell lymphoma cell line DB and its mechanism. METHODS: DB cells were treated with baicalin at different concentrations (0, 5, 10, 20, 40 μmol/L). Cell proliferation was detected by CCK-8 assay and half maximal inhibitory concentration (IC₅₀) was calculated. The morphology of pyroptosis was observed under an inverted microscope, the integrity of the cell membrane was verified by LDH content release assay, and the expressions of pyroptosis-related mRNA and protein (NLRP3, GSDMD, GSDME, N-GSDMD, N-GSDME) were detected by real-time fluorescence quantitative PCR and Western blot. In order to further clarify the relationship between baicalin-induced pyroptosis and ROS production in DB cells, DB cells were divided into control group, baicalin group, NAC group and NAC combined with baicalin group. DB cells in the NAC group were pretreated with ROS inhibitor N-acetylcysteine (NAC) 2 mmol/L for 2 h. Baicalin was added to the combined treatment group after pretreatment, and the content of reactive oxygen species (ROS) in the cells was detected by DCFH-DA method after 48 hours of culture. RESULTS: Baicalin inhibited the proliferation of DB cells in a dose-dependent manner (r=-0.99), and the IC₅₀ was 20.56 μmol/L at 48 h. The morphological changes of pyroptosis in DB cells were observed under inverted microscope. Compared with the control group, the release of LDH in the baicalin group was significantly increased (P<0.01), indicating the loss of cell membrane integrity. Baicalin dose-dependently increased the expression levels of NLRP3, N-GSDMD, and N-GSDME mRNA and protein in the pyroptosis pathway (P<0.05). Compared with the control group, the level of ROS in the baicalin group was significantly increased (P<0.05), and the content of ROS in the NAC group was significantly decreased (P<0.05). Compared with the NAC group, the content of ROS in the NAC + baicalin group was increased. Baicalin significantly attenuated the inhibitory effect of NAC on ROS production (P<0.05). Similarly, Western blot results showed that compared with the control group, the expression levels of pyroptosis-related proteins was increased in the baicalin group (P<0.05). NAC inhibited the expression of NLRP3 and reduced the cleavage of N-GSDMD and N-GSDME (P<0.05). Compared with the NAC group, the NAC + baicalin group had significantly increased expression of pyroptosis-related proteins. These results indicate that baicalin can effectively induce pyroptosis in DB cells and reverse the inhibitory effect of NAC on ROS production. CONCLUSION Baicalin can inhibit the proliferation of DLBCL cell line DB, and its mechanism may be through regulating ROS production to affect the pyroptosis pathway.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Reactive Oxygen Species/pharmacology* ; Pyroptosis ; Cell Line ; RNA, Messenger ; Lymphoma, Large B-Cell, Diffuse

Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.
Humans ; Female ; Blood Platelets/pathology* ; Biomarkers, Tumor/genetics* ; Ovarian Neoplasms/pathology* ; China

Objective To understand the distribution and changes in antimicrobial resistance of clinically isolated Pseudomonas aeruginosa(P.aeruginosa)in the member hospitals of Hunan Provincial Antimicrobial Resistance Surveillance System from 2012 to 2021.Methods Antimicrobial susceptibility testing by disk diffusion or automa-ted instrument was performed on clinical isolates.Testing results were determined according to the standards of 2022 edition from American Clinical Laboratory Standards Institute(CLSI).Statistical analysis was performed by WHONET 5.6 software.Data were analyzed by trend test(Cochran-armitage)and Chi-square test with SPSS.Results A total of 176 441 strains of P.aeruginosa were surveilled by Hunan Provincial Antimicrobial Resistance Surveillance System from 2012 to 2021.99.4％of the strains were isolated from hospitalized patients,and about 70％of the strains were isolated from respiratory specimens.8.4％of P.aeruginosa were from children(0-17 years old),91.6％were from adults.Antimicrobial susceptibility testing results showed that P.aeruginosa was most sensitive to polymyxin B over 10 years,with a resis-tance rate of less than 6％.Resistance rates to piperacil-lin,piperacillin/tazobactam,ceftazidime,cefepime,aztreonam,imipenem,amikacin,gentamicin,tobramycin,cip-rofloxacin,levofloxacin,and polymyxin B all showed downward trends.A total of 29 920 carbapenem-resistant P.aeruginosa(CRPA)strains were detected.The average isolation rate of CRPA in this province was 18.0％over 10 years.CRPA detection rate from adult was 18.5％,higher than that from children(12.3％),and both showing downward trends.Conclusion The resistance rate of clinically isolated P.aeruginosa in Hunan Province to most commonly used antimicrobial agents is decreasing.