Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RS_GSFM and drug efficacy, suggesting that RS_GSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

The application of artificial intelligence (AI) in perioperative anesthesia decision-making is becoming a research hotspot, particularly in anesthesia risk assessment, depth of anesthesia monitoring, and postoperative recovery management, where it demonstrates significant potential. AI technologies, especially machine learning and deep learning, have demonstrated exceptional capabilities in processing and analyzing high-dimensional complex data. By leveraging these technologies, it is possible to efficiently interpret vast amounts of intricate clinical data, thereby providing anesthesiologists with personalized and precise decision support. However, implementing AI technologies in clinical practice faces numerous challenges, mainly including data quality, algorithm interpretability, and technological compatibility. Furthermore, concerns surrounding data privacy and ethical considerations urgently need to be addressed to ensure that the application of AI technologies aligns with clinical ethics and legal standards. This article aims to provide a comprehensive overview of AI technologies, their applications in perioperative anesthesia decision-making, existing limitations, and future directions. The goal is to offer insights into clinical anesthesia practice and to promote the realization of personalized precision anesthesia.

Objective:It aims to systematically evaluate the current status of knowledge,attitude,and practice(KAP)regarding universal commercial medical insurance among residents of the sample province from the demand-side perspective.Methods:Utilizing a quota sampling method,face-to-face surveys were conducted via the Questionnaire Star platform to collect demographic characteristics and KAP data of the participants.Comparisons of differences among different groups were made using t-tests,analysis of variance,and chi-square tests.Furthermore,multiple linear regression and structural equation modeling were utilized to analyze the influencing factors of KAP,as well as the pathways among these three factors.Results:Out of the 415 valid questionnaires collected,there were notable differences in KAP among respondents with diverse demographic backgrounds.Regression analysis revealed that education level,frequency of health check-ups,and engagement in other commercial health insurances significantly influenced knowledge;education level,involvement in other commercial health insurances,and self-assessed health status were pivotal in shaping attitudes;whereas age,education level,frequency of health check-ups,and participation in other commercial health insurances were critical in affecting practice.The path analysis results indicate that knowledge of universal commercial medical insurance has a significant direct association with attitude(β=0.379,P＜0.001)and practice(β=0.323,P＜0.001).It also influences practice through attitude as a mediator(β=0.016,P＜0.001),but the direct effect of attitude on practice is not significant(β=0.04,P=0.403).Conclusion:While residents in the sample province exhibit a positive attitude towards universal commercial medical insurance,there is a need to enhance their level of knowledge and engagement in practice.It is recommended to strengthen targeted educational and promotional measures to promote the healthy and sustainable development of universal insurance.

OBJECTIVES: To investigate the risk factors of overall postoperative complications in elderly patients undergoing gastrointestinal surgeries. METHODS: This study was conducted among a total of 1388 elderly patients, who underwent elective gastrointestinal surgeries at 17 centers across China between April, 2020 and April, 2022. The primary outcome was the incidence of postoperative complications within 30 days, including procedure-related, neuropsychiatric, respiratory, cardiovascular, and gastrointestinal complications as well as acute kidney injury. Baseline characteristics, preoperative psychological and functional status, intraoperative anesthesia and surgical factors, intraoperative medication, use of nerve block, and postoperative analgesia methods were compared between the patients experiencing one or more postoperative complications and those without complications. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors for postoperative complications. The relationship between postoperative acute pain and each type of complication were explored. RESULTS: The incidence of overall postoperative complications was 50.8% (705/1388) in these patients. Multivariate analysis showed that age (OR: 1.026; 95% CI: 1.006-1.046), prognostic nutritional index (OR: 0.998; 95% CI: 0.997-1.000), preoperative EuroQol-5 dimensions score (OR: 0.094; 95% CI: 0.018-0.500), blood loss (OR: 1.002; 95% CI: 1.001-1.003), and acute postoperative pain (OR: 1.308; 95% CI: 1.033-1.657) were significantly associated with the occurrence of postoperative complications. Specifically, patients experiencing severe postoperative pain had a significantly higher incidence of neuropsychiatric (27.2% vs 19.8%), procedure-related (17.3% vs 10.2%), and cardiovascular complications (3.6% vs 1.7%). CONCLUSIONS An advanced age, a low preoperative nutritional index, a poor quality of life score, a greater volume of intraoperative blood loss, and acute postoperative pain are independent risk factors for postoperative complications in elderly patients undergoing gastrointestinal surgeries. There is a significant association between acute postoperative pain and multi-system complications.
Humans ; Postoperative Complications/etiology* ; Aged ; Risk Factors ; Digestive System Surgical Procedures/adverse effects* ; Male ; Female ; China/epidemiology* ; Pain, Postoperative/epidemiology* ; Incidence ; Aged, 80 and over

This research study focuses on addressing the limitations of current neuropathic pain (NP) treatments by developing a novel dual-target modulator, E0199, targeting both Na_V1.7, Na_V1.8, and Na_V1.9 and K_V7 channels, a crucial regulator in controlling NP symptoms. The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP. Through an experimental design involving both in vitro and in vivo methods, E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury (CCI) mouse model. The results demonstrated that E0199 significantly inhibited Na_V1.7, Na_V1.8, and Na_V1.9 channels with a particularly low half maximal inhibitory concentration (IC₅₀) for Na_V1.9 by promoting sodium channel inactivation, and also effectively increased K_V7.2/7.3, K_V7.2, and K_V7.5 channels, excluding K_V7.1 by promoting potassium channel activation. This dual action significantly reduced the excitability of dorsal root ganglion neurons and alleviated pain hypersensitivity in mice at low doses, indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically. The safety of E0199 was supported by neurobehavioral evaluations. Conclusively, E0199 represents a ground-breaking approach in NP treatment, showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe therapeutic option for NP. This study introduces a promising direction for the future development of NP therapeutics.

This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Nav1.7,Nay1.8,and Nay1.9 and Kv7 channels,a crucial regulator in controlling NP symptoms.The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP.Through an experimental design involving both in vitro and in vivo methods,E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury(CCI)mouse model.The results demonstrated that E0199 significantly inhibited Nav1.7,Nav1.8,and Nav1.9 channels with a particularly low half maximal inhibitory concentration(ICs0)for Nay1.9 by promoting sodium channel inactivation,and also effectively increased Kv7.2/73,Kv7.2,and Kv7.5 channels,excluding Kv7.1 by promoting potassium channel acti-vation.This dual action significantly reduced the excitability of dorsal root ganglion neurons and alle-viated pain hypersensitivity in mice at low doses,indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically.The safety of E0199 was supported by neurobehavioral evaluations.Conclusively,E0199 represents a ground-breaking approach in NP treatment,showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe thera-peutic option for NP.This study introduces a promising direction for the future development of NP therapeutics.

BACKGROUND:There are still great controversies in the etiology,clinical manifestations,diagnosis and treatment of pigmented villonodular synovitis.Bibliometric and visualization studies on pigmented villonodular synovitis can clarify the research development context and point out the direction for future research.OBJECTIVE:To analyze the global research status,hotspot,and trend of pigmented villonodular synovitis.METHODS:All publications related to pigmented villonodular synovitis from 1995 to 2023 were retrieved from Web of Science and CNKI.Citespace and bibliometrics were used to analyze the clustering,co-occurrence,and emergent words of all articles.The Web of Science database adopts subject headings plus free words for retrieval,while the CNKI database retrieves through subject headings.Finally,986 English articles and 599 Chinese articles were included.RESULTS AND CONCLUSION:(1)The United States has an absolute leading position in research in this field,ranking first in the number of published papers,H index,and cited times.China ranks the 4th in the total volume of published articles and 12th in the H index.The quality of published articles and international cooperation still need to be improved.(2)Cluster analysis of pigmented villonodular synovitis studies showed that the top five clusters were radiotherapy,soft tissue sarcoma,rheumatoid arthritis,magnetic resonance imaging,and diagnosis.(3)The key words that continued to emerge until 2023 were colony-stimulating factor 1,giant cell tumor of tendon sheath,case report,chromosome translocation,radiotherapy,expression,and kinase.(4)Based on keyword analysis and co-citation analysis,it is found that the research on the clinical characteristics of pigmented villonodular synovitis,the development of new colony-stimulating factor 1 inhibitors,and the application of colony-stimulating factor 1 inhibitors in the treatment process are current research hotspots.(5)Combining thematic evolution with the analysis of current research hotspots,based on clarifying the etiology,pathogenesis,and clinical characteristics of pigmented villonodular synovitis,improving the diagnostic accuracy of pigmented villonodular synovitis,enhancing the precision of treatment,and reducing the recurrence rate after treatment will be key issues that require focus in the future.

This study aims to investigate the medication rules of patented traditional Chinese medi-cine(TCM)compound formulas and molecular mechanisms of core drugs for treating sepsis using data mining and network pharmacology approaches.In the present study,we first searched the PubMed database,Web of Science database,and the China National Knowledge Infrastructure(CNKI)since the establishment of the library to April 30,2024 for the relevant literature on the treatment of sepsis by traditional Chinese medicine.The prescriptions were then statistically ana-lyzed for drug frequency and association analysis to obtain the core drugs.Then we screened the ef-fective active ingredients of the core drugs by TCMSP and other database platforms,obtained sep-sis-related genes in GeneCards and other databases,and statistically intersected targets,and predic-ted the mechanism of action of the core TCMs by subjecting the intersected targets to PPI analy-sis,GO function and KEGG pathway enrichment analysis.Finally,the relationship between key tar-gets and herbal components was examined in reverse by molecular docking method.The results showed that 64 compound formulas were obtained,with a total of 150 Chinese medicines,which were mostly sweet in taste,cold in nature,and belonged to the spleen,stomach and intestinal me-ridians.According to the association rules,the core drugs were identified as"mirabilite-peach ker-nel-rheum officinale".There were 79 intersecting targets between the core drugs and sepsis,with core targets such as IL-1β,EGFR and SRC.MAPK,TNF,IL-17 and other signaling pathways are involved to mediate inflammatory responses,apoptosis and other biological processes to exert ther-apeutic effects on sepsis.The molecular docking results indicated that the docking activity of the key targets with the main components of the drug,and sennoside E_qt has the lowest binding ener-gy and the best docking activity with SRC.In conclusion,this study showed that the prescription of Chinese medicine for sepsis is mostly based on tonifying the spleen and clearing heat.The mecha-nism of action of the core drug"mirabilite-peach kernel-rheum officinale"in the treatment of sep-sis is multilevel and multifaceted,which provides a certain theoretical basis for the treatment of sepsis by traditional Chinese medicine.

The application of artificial intelligence (AI) in perioperative anesthesia decision-making is becoming a research hotspot, particularly in anesthesia risk assessment, depth of anesthesia monitoring, and postoperative recovery management, where it demonstrates significant potential. AI technologies, especially machine learning and deep learning, have demonstrated exceptional capabilities in processing and analyzing high-dimensional complex data. By leveraging these technologies, it is possible to efficiently interpret vast amounts of intricate clinical data, thereby providing anesthesiologists with personalized and precise decision support. However, implementing AI technologies in clinical practice faces numerous challenges, mainly including data quality, algorithm interpretability, and technological compatibility. Furthermore, concerns surrounding data privacy and ethical considerations urgently need to be addressed to ensure that the application of AI technologies aligns with clinical ethics and legal standards. This article aims to provide a comprehensive overview of AI technologies, their applications in perioperative anesthesia decision-making, existing limitations, and future directions. The goal is to offer insights into clinical anesthesia practice and to promote the realization of personalized precision anesthesia.

Objective:It aims to systematically evaluate the current status of knowledge,attitude,and practice(KAP)regarding universal commercial medical insurance among residents of the sample province from the demand-side perspective.Methods:Utilizing a quota sampling method,face-to-face surveys were conducted via the Questionnaire Star platform to collect demographic characteristics and KAP data of the participants.Comparisons of differences among different groups were made using t-tests,analysis of variance,and chi-square tests.Furthermore,multiple linear regression and structural equation modeling were utilized to analyze the influencing factors of KAP,as well as the pathways among these three factors.Results:Out of the 415 valid questionnaires collected,there were notable differences in KAP among respondents with diverse demographic backgrounds.Regression analysis revealed that education level,frequency of health check-ups,and engagement in other commercial health insurances significantly influenced knowledge;education level,involvement in other commercial health insurances,and self-assessed health status were pivotal in shaping attitudes;whereas age,education level,frequency of health check-ups,and participation in other commercial health insurances were critical in affecting practice.The path analysis results indicate that knowledge of universal commercial medical insurance has a significant direct association with attitude(β=0.379,P＜0.001)and practice(β=0.323,P＜0.001).It also influences practice through attitude as a mediator(β=0.016,P＜0.001),but the direct effect of attitude on practice is not significant(β=0.04,P=0.403).Conclusion:While residents in the sample province exhibit a positive attitude towards universal commercial medical insurance,there is a need to enhance their level of knowledge and engagement in practice.It is recommended to strengthen targeted educational and promotional measures to promote the healthy and sustainable development of universal insurance.