By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

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.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Objective By analyzing the gene expression data in TCGA-THCA dataset,the differentially expressed genes related to thyroid carcinoma(THCA)were identified,a risk model was construct,and the role of CCL chemokine family in the development of THCA and its effect on the tumor immune microenvironment were investigated.Methods TCGA-THCA dataset was downloaded and analyzed,including 512 cancer samples and 59 adjacent tissue samples.The differentially expressed genes were obtained by taking the intersection of R packages of differential analysis,and the principal component analysis(PCA),Gene Ontology(GO),and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were performed.CellMarker,monocle,and CellChat were used to explore the Cell atlas,pseudotemporal trajectory,and cellular communication.Results A total of 698 up-regulated genes and 285 down-regulated genes were identified.PCA showed that there were significant differences in gene expression patterns between the THCA group and the normal group.GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly involved in biological processes such as extracellular matrix tissue,cell junction assembly,and complement system.The results of risk model showed that the CCL genes was significantly correlated with poor prognosis(P=0.005).Single cell analysis revealed that fibroblasts played a key role in the development of THCA,and the expression of CCL gene was significantly up-regulated in fibroblasts(P<0.05).The results of pseudotemporal trajectory analysis showed that CCL gene was differentially expressed during cellular differentiation;the results of cellular communication analysis showed that the interaction between fibroblasts and endothelial cells is crucial in the tumor microenvironment.Conclusion The expression of CCL chemokine family in THCA is closely related to poor prognosis,especially CCL4,which activates the downstream signaling pathways by interacts with CCR receptors of cancer-associated fibroblasts,thereby promoting the development of cancer.These findings provide novel insights for understanding the role of CCL chemokine family in THCA and its regulation of the tumor immune microenvironment.

Objective To systematically evaluate the effectiveness and acceptability of antidepressant drugs in the treatment of postpartum depression(PPD).Methods The PubMed,Cochrane Library,Embase,Web of Science,China National Knowledge Infrastructure(CNKI),Wanfang Database,VIP Journals of Chinese Scienc were searched,and Chinese Biomedical Literature Service System(SinoMed)database until November 2023.Screen randomized controlled trials(RCTs)of antidepressant drugs for the treatment of PPD.The treatment group was given antidepressant drugs,and the control group was given placebo or another antidepressant drug.Meta-analysis of effectiveness and acceptability is performed using Stata 17.0 software.Results A total of 27 RCTs with a total of 2 202 patients were included.The results of meta-analysis showed:The top three efficacy relative to placebo were mirtazapine[odds ratio(OR)=2.25,95％confidence interval(CI)=(1.20-3.30),P＜0.05],nortriptyline[OR=1.50,95％CI=(0.55-2.44),P＞0.05],venlafaxine[OR=1.35,95％CI=(0.13-2.56),P＞0.05].Acceptability is compared with placebo in the top three Chinese herbal medicine[OR=0.47,95％CI=(-0.72-1.66),P＞0.05],nortriptyline[OR=-0.08,95％CI=(-1.16-1.33),P＞0.05],venlafaxine[OR=-0.12,95％CI=(-1.47-1.24),P＞0.05].Conclusion Nortriptyline,venlafaxine,trazodone,and duloxetine are effective in treating PPD without obvious adverse drug reactions.

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.

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

There is a complex biological mechanism in the phosphatidylinositol-3-kinase(PI3K)/protein kinase B(PKB/Akt)/mammalian target of rapamycin(mTOR)signaling pathway,which plays a key role in the development and development of lymphoma.In this review,the relevant literature of PI3K inhibitor research in the past five years summarized and analyzed,and found that the research and development,application,efficacy,and adverse reactions of PI3K inhibitors are the current research hotspots,and the positive results of PI3K inhibitors in clinical trials and basic research have strongly demonstrated the potential of PI3K inhibitors in personalized treatment of lymphoma.In order to maximize the clinical benefits,a variety of strategies need to be explored,including novel drugs with better selectivity and safety,and related combination therapies.

Aim To explore the mechanism by which the compound Chaijin Jieyu formula(CCJJY)regulates the TLR4/NLRP3 signaling pathway to inhibit central oxidative stress and improve hippocampal synaptic plasticity damage in depression.Methods SD rats were randomly divided into the control group,chronic unpredictable mild stress group,sleep deprivation group,chronic unpredictable mild stress combined with sleep deprivation group,positive drug group(venlafax-ine+melatonin),low-dose group of CCJJY,medium dose group of CCJJY,and high-dose group of CCJJY,with nine rats in each group.Except for the control group,a rat model of depression complicated with in-somnia was established using chronic unpredictable mild stress combined with sleep deprivation.Depres-sion-like and sleep behaviors in rats were evaluated through weight,food intake,water maze,and pento-barbital sodium tests.ELisa was used to detect ROS,AANAT,and HPLC-EC was used to detect 5-HT con-tent,while Western blot/RT-PCR was used to detect the expression of IL-1β,TLR4,NLRP3,PSD-95,and SYN related proteins and mRNA.HE and Golgic stai-ning were used to observe the pathological changes in the third ventricle,hippocampus,and neuronal synap-ses.Results Compared with the control group,the depression-like behaviors of the model group rats were significant.The expression of IL-1β,TLR4,and NL-RP3 in the hippocampus increased,while the expres-sion of PSD-95 and SYN decreased.Activation of NL-RP3 inflammasomes led to "sleeve like" pathological changes in the third ventricle,with hippocampal neu-rons undergoing apoptosis and significant damage to neuronal synaptic plasticity.Compared with the model group,after intervention with CCJJY,the expression of ROS,IL-1β,TLR4,and NLRP3 decreased,while the expression of AANAT,5-HT,PSD-95,and SYN in-creased.Pathological damage to the third ventricle and hippocampal neurons was repaired.Conclusion The CCJJY improves hippocampal synaptic plasticity dam-age in depression by regulating the TLR4/NLRP3 sig-naling pathway to inhibit central oxidative stress.