The Chinese health index assessment system integrates the dialectical thinking of traditional philosophy， taking the Taoist cosmology， Confucian ethical view， and the holistic perspective of traditional Chinese medicine （TCM） as its theoretical foundation. It deeply analyzes the sages' conceptions of the ideal personality and social order， as well as their ideas on mind-body cultivation， while incorporating modern health concepts from psychology， medicine. The study systematically explicates the connotation and characteristics of eight components of the Chinese health index， including harmony， dedication， compassion， happiness， peace of mind， innovation， fulfillment， and adaptability. This system establishes a multidimensional assessment framework covering physical health， psychological well-being， human-social relations， and the relationship with nature， which demonstrates high cultural adaptability and practical applicability， offering theoretical reference for assessing the mind-body health of the Chinese population and for informing health promotion policies.

Perioperative drug-related rare adverse reactions are often characterized by acute onset,high risk,and unpredictable,involving complex physiological and genetic factors.Currently,most perioperative pharmacovigilance relies on clinical monitoring and real-time data reporting by medical teams.However,due to scattered data and the masking of symptoms by anesthetics and pain medications,it is difficult to predict rare adverse reactions accurately and promptly.This paper systematically reviews the latest advancements in the integration of digital and intelligent technologies across various fields.Based on real-world data,our research team had leveraged digital-intelligence fusion technologies to deeply integrate big data with artificial intelligence,thereby constructing a standardized anesthesia-specific database.This enabled dynamic monitoring of vital signs,individualized risk prediction,and comprehensive analysis of multimodal data in real-world studies,providing an innovative solution for perioperative pharmacovigilance.The aim of this paper is to enhance the personalization and intelligence of perioperative drug safety management,thereby offering more effective protection for patient medication safety during the perioperative period.

Perioperative drug-related rare adverse reactions are often characterized by acute onset,high risk,and unpredictable,involving complex physiological and genetic factors.Currently,most perioperative pharmacovigilance relies on clinical monitoring and real-time data reporting by medical teams.However,due to scattered data and the masking of symptoms by anesthetics and pain medications,it is difficult to predict rare adverse reactions accurately and promptly.This paper systematically reviews the latest advancements in the integration of digital and intelligent technologies across various fields.Based on real-world data,our research team had leveraged digital-intelligence fusion technologies to deeply integrate big data with artificial intelligence,thereby constructing a standardized anesthesia-specific database.This enabled dynamic monitoring of vital signs,individualized risk prediction,and comprehensive analysis of multimodal data in real-world studies,providing an innovative solution for perioperative pharmacovigilance.The aim of this paper is to enhance the personalization and intelligence of perioperative drug safety management,thereby offering more effective protection for patient medication safety during the perioperative period.

Objective To improve the accuracy of intelligent detection and evaluation of traditional Chinese medicine(TCM)pieces and solve the problems of leakage,misdetection,inaccurate localization and low confidence in the study of TCM pieces identification,YOLOv3 algorithm which has good detection effect for high overlap and small targets was improved.Methods An RGB image database containing 148 commonly used TCM pieces was established.Based on the YOLOv3 algorithm model,the anchor box size was improved by K-means clustering algorithm.The CIoU loss function was introduced for bounding box regression to improve the localization accuracy and confidence of bounding boxes.The traditional non-maximum suppression was improved to DIoUNMS to reduce the problems of missed detection and false detection of dense targets with high overlap by YOLOv3 algorithm.Results 148 kinds of TCM pieces were tested with the improved algorithm,and the average detection accuracy of 98.47%was achieved,which is 1.83%better than the original YOLOv3 algorithm.It realizes better detection effect for TCM pieces in complex situations such as dense,high overlapping,etc.Problems such as leakage,misdetection,imprecise positioning and low confidence level have been alleviated to a certain extent.Conclusion The improved algorithm effectively improves the recognition accuracy and generalization ability of TCM pieces,providing a new reference for the realization of automated intelligent detection of TCM pieces.

Objective To explore the value of combining apparent diffusion coefficient(ADC)heterogeneity with morphological indicators in assessing the pathological grading of non-muscle invasive bladder cancer(NMIBC).Methods The MRI images of 86 patients confirmed with NMIBC by surgical pathology were analyzed retrospectively.All patients underwent T2WI,diffusion weighted ima-ging(DWI),and dynamic contrast enhancement(DCE)examinations.Two radiologists independently measured tumor largest diam-eter(LD),actual tumor-wall contact length(ACTCL),ADCmean,ADCmin,and ADCmax values.ADC heterogeneity was calculated using the formula(ADCmax-ADCmin)/ADCmean.Differences in quantitative parameters between low-and high-grade NMIBC were compared using the Mann-Whitney U test,while differences in qualitative parameters were compared using the chi-square test.Univariate and multivariate logistic regression analyses were used to identify independent predictors of high-grade NMIBC,and receiver operating characteristic(ROC)curves were drawn to evaluate the performance of ADC heterogeneity combined with morphological indicators in assessing high-grade NMIBC.Results ADC heterogeneity and ACTCL were independent predictors for preoperative assessment of NMIBC pathological grading.The area under the curve(AUC)of ADC heterogeneity and ACTCL in assessing high-grade NMIBC were 0.843 and 0.744,respectively.The combined AUC was 0.902.The difference was statistically significant(P<0.05).Conclusion The combination of ADC heterogeneity with ACTCL can effectively improve the efficiency of preoperative assessment of NMIBC pathological grading,and providing more precise clinical decision-making and prognosis monitoring.

Objective To improve the accuracy of intelligent detection and evaluation of traditional Chinese medicine(TCM)pieces and solve the problems of leakage,misdetection,inaccurate localization and low confidence in the study of TCM pieces identification,YOLOv3 algorithm which has good detection effect for high overlap and small targets was improved.Methods An RGB image database containing 148 commonly used TCM pieces was established.Based on the YOLOv3 algorithm model,the anchor box size was improved by K-means clustering algorithm.The CIoU loss function was introduced for bounding box regression to improve the localization accuracy and confidence of bounding boxes.The traditional non-maximum suppression was improved to DIoUNMS to reduce the problems of missed detection and false detection of dense targets with high overlap by YOLOv3 algorithm.Results 148 kinds of TCM pieces were tested with the improved algorithm,and the average detection accuracy of 98.47%was achieved,which is 1.83%better than the original YOLOv3 algorithm.It realizes better detection effect for TCM pieces in complex situations such as dense,high overlapping,etc.Problems such as leakage,misdetection,imprecise positioning and low confidence level have been alleviated to a certain extent.Conclusion The improved algorithm effectively improves the recognition accuracy and generalization ability of TCM pieces,providing a new reference for the realization of automated intelligent detection of TCM pieces.

Sufficient bone tissue is required to ensure the long-term stability of implants. Based on the principles of guided bone regeneration, Dr. Istvan Urban proposed the “sausage technique”. Research indicates that the horizontal bone augmentation observed with the sausage technique averages (5.3 ± 2.3) mm and the vertical bone augmentation averages (4.2 ± 1.9) mm, which is significantly greater than the outcomes achieved with traditional guided bone regeneration techniques. The sausage technique is reliable because the biological membrane has sufficient elasticity and toughness with the application of membrane screws, which stabilizes the mixture of autologous bone and bone graft materials in the bone grafting area and prevents the grafting materials from being displaced. Using substitute materials for autologous bone graft balances the osteogenic activity and the low graft absorption rate. A ball drill is used to prepare nourishing holes in the cortical bone of the recipient area, providing a pathway for mesenchymal stem cells and bone progenitor cells to migrate to the bone regeneration area. Furthermore, this method accelerates the early angiogenesis of wound healing, fully reduces tension during suturing, and ensures that excessive pressure is not applied to the healing area during suturing. Thus, the sausage technique is consistent and reliable. Despite the good outcomes demonstrated by the sausage technique in clinical applications, its potential complications related to soft and hard tissue have attracted widespread attention. These complications negatively affect the patient’s recovery process and influence the final results of the surgery. Therefore, a complete understanding of the complications associated with the sausage technique and their underlying causes is necessary to enhance the clinical safety and effectiveness of the sausage technique. This article summarizes the application principles, clinical effects, barrier membrane applications, selection of bone transplant materials, and related complications of the sausage technique, aiming to provide a reference for clinical application.

Objective: To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder (PDD) through data mining and network analysis. Methods: A comprehensive literature search was conducted across PubMed, Embase, Ovid Technologies (OVID), Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), China National Knowledge Infrastructure Database (VIP), Wanfang Data, and SinoMed Database from database foundation to January 31, 2025, for clinical studies on acupuncture treatment of PDD. Descriptive statistics, high-frequency acupoint analysis, degree and betweenness centrality evaluation, and core acupoint prescription mining identified predominant therapeutic combinations for PDD. Network acupuncture was used to predict therapeutic target for the core acupoint prescription. Subsequent protein-protein interaction (PPI) network and molecular complex detection (MCODE) analyses were conducted to identify the key targets and functional modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD. Results: A total of 57 acupoint prescriptions underwent systematic analysis. The core therapeutic combinations comprised Baihui (GV20), Yintang (GV29), Neiguan (PC6), Hegu (LI4), and Shenmen (HT7). Network acupuncture analysis identified 88 potential therapeutic targets (79 overlapping with PDD), while PPI network analysis revealed central regulatory nodes, including interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, toll-like receptor 4 (TLR4), IL-10, brain-derived neurotrophic factor (BDNF), transforming growth factor (TGF)-β1, C-X-C motif chemokine ligand 10 (CXCL10), mitogen-activated protein kinase 3 (MAPK3), and nitric oxide synthase 1 (NOS1). MCODE-based modular analysis further elucidated three functionally coherent clusters: inflammation-homeostasis (score = 6.571), plasticity-neurotransmission (score = 3.143), and oxidative stress (score = 3.000). GO and KEGG analyses demonstrated significant enrichment of the MAPK, phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), and hypoxia-inducible factor (HIF)-1 signaling pathways. These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation, neuroplasticity restoration, and immune-oxidative stress homeostasis. Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism, primarily involving the neuroinflammation suppression, neuroplasticity enhancement, and oxidative stress regulation. These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research.

BACKGROUND: The sirtuin family is well recognized for its crucial involvement in various cellular processes. Nevertheless, studies on its role in the human endometrium are limited. This study aimed to explore the expression and localization of the sirtuin family in the human endometrium, focusing on sirtuin 3 (SIRT3) and its potential role in the oxidative imbalance of the endometrium in polycystic ovary syndrome (PCOS). METHODS: Endometrial specimens were collected from both patients with PCOS and controls undergoing hysteroscopy at the Center for Reproductive Medicine, Peking University Third Hospital, from July to August 2015 and used for cell culture. The protective effects of SIRT3 were investigated, and the mechanism of SIRT3 in improving endometrial receptivity of patients with PCOS was determined using various techniques, including cellular bioenergetic analysis, small interfering ribonucleic acid (siRNA) silencing, real-time quantitative polymerase chain reaction, Western blot, immunofluorescence, immunohistochemistry, and flow cytometry analysis. RESULTS: The sirtuin family was widely expressed in the human endometrium, with SIRT3 showing a significant increase in expression in patients with PCOS compared with controls ( P <0.05), as confirmed by protein and gene assays. Concurrently, endometrial antioxidant levels were elevated, while mitochondrial respiratory capacity was reduced, in patients with PCOS ( P <0.05). An endometrial oxidative stress (OS) model revealed that the downregulation of SIRT3 impaired the growth and proliferation status of endometrial cells and reduced their receptivity to day 4 mouse embryos. The results suggested that SIRT3 might be crucial in maintaining normal cellular state by regulating antioxidants, cell proliferation, and apoptosis, thereby contributing to enhanced endometrial receptivity. CONCLUSIONS Our findings proposed a significant role of SIRT3 in improving endometrial receptivity in patients with PCOS by alleviating OS and regulating the balance between cell proliferation and apoptosis. Therefore, SIRT3 could be a promising target for predicting and improving endometrial receptivity in this patient population.
Humans ; Female ; Polycystic Ovary Syndrome/metabolism* ; Endometrium/metabolism* ; Sirtuin 3/genetics* ; Oxidative Stress/genetics* ; Adult ; Animals ; Mice ; Apoptosis/physiology* ; Immunohistochemistry ; Cell Proliferation/physiology*

Osteoarthritis(OA)is a common concern over the world.Garlic is a kind of natural herbal medicine,and its active ingredients have shown some anti-inflammatory,antioxidant,anti-catabolic,analgesic and other phar-macological effects.Garlic and its active components alleviate the inflammatory response of OA by inhibiting the ex?pression of inflammatory factors and signal pathways such as NF?κB and PI3K/Akt.They slow down the progression of OA by inhibiting the expression of extracellular matrix(ECM)degrading enzymes.Additionally,they reduce the oxidative damage of joints by upregulating the expression of antioxidant enzymes.Moreover,the active components of garlic can relieve OA pain by activating the potassium ion pathway(Kv7),ATP?sensitive potassium channel(K?ATP),and the nuclear factor erythroid 2?related factor 2(Nrf2)/heme oxygenase 1(HO?1)?NAD(P)H:qui?none oxidoreductase 1(NQO1)signaling pathway.