ObjectiveTo establish an animal model of atrial fibrillation（AF） that accurately reflects the phlegm-heat and blood stasis（TRYZ） pathogenesis in traditional Chinese medicine. MethodsForty SPF-grade SD rats were randomly assigned using a random number table to the following groups：the control group， the TRYZ+AF group，the AF group and the TRYZ group， with ten rats in each group. The TRYZ+AF and TRYZ groups underwent a high-fat diet combined with intraperitoneal lipopolysaccharide（LPS） injection to simulate the pathological alterations of TRYZ syndrome. Groups TRYZ+AF and AF were induced with acetylcholine-calcium chloride（Ach-CaCl₂） via caudal vein injection to induce AF. The control group received no intervention and was maintained under normal conditions. The modeling period lasted 3 weeks. Electrocardiography was used to assess AF episodes and duration， echocardiography evaluated left atrial dimensions and cardiac function， fully automated biochemical analyzer measured the levels of total cholesterol（TC）， triglycerides（TG）， high-density lipoprotein cholesterol（HDL-C） and low-density lipoprotein cholesterol（LDL-C）， hemoreometer analyzed the whole blood viscosity， plasma viscosity， and whole blood reduced viscosity， a coagulation analyzer assessed prothrombin time（PT）， activated partial thromboplastin time（APTT）， thrombin time（TT）， and fibrinogen（FIB）， enzyme-linked immunosorbent assay（ELISA） was used to determine the levels of C-reactive protein（CRP）， interleukin（IL）-1β， IL-6， IL-17， tumour necrosis factor（TNF）-α， matrix metalloproteinase-9（MMP-9）， galectin-3（Gal-3）， Collagen Ⅰ， and α-smooth muscle actin（α-SMA）. Hematoxylin-eosin（HE） staining and Masson's trichrome staining were used to analyze pathological changes in atrial myocardium， Western blot was employed to detect MMP-9， Collagen Ⅰ and α-SMA protein expression in myocardial tissue， real-time quantitative polymerase chain reaction（Real-time PCR） evaluated fibrous factor gene expression levels. Changes in the TRYZ syndrome were assessed via body weight， tongue color［red（R）， green（G）， and blue（B）］， and rectal temperature. Ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was employed to detect differential metabolites between the control group and the TRYZ+AF group. ResultsFollowing three weeks of sustained modeling， compared with the control group， rats in the TRYZ+AF and the TRYZ groups exhibited reduced body weight， dry faeces， elevated rectal temperature， dark red tongue， decreased RGB values on the tongue surface， and markedly elevated TC and LDL-C levels（P<0.05， P<0.01）. The TRYZ+AF， TRYZ， and AF groups exhibited significantly decreased TT， APTT and PT， along with markedly elevated whole blood viscosity and FIB（P<0.05， P<0.01）. Rats in the TRYZ+AF and AF groups exhibited AF rhythm， markedly decreased heart rate， prolonged RR intervals， enlarged left atrium， and significantly reduced ejection fraction and shortening fraction（P<0.05， P<0.01）. Serum levels of CRP， IL-1β， IL-6， IL-17， TNF-α， MMP-9， Gal-3， Collagen Ⅰ， and α-SMA were elevated in rats from the TRYZ+AF， TRYZ， and AF groups compared to the control group， with the most pronounced increase observed in the TRYZ+AF group（P<0.05， P<0.01）. Histopathology revealed that the collagen fiber deposition in the atrial of rats in the TRYZ+AF， TRYZ and AF groups was higher than that in the control group（P<0.05， P<0.01）. Western blot and Real-time PCR results further demonstrated that the protein and mRNA expression levels of MMP-9， Collagen Ⅰ and α-SMA in the myocardial tissue of the TRYZ+AF group were higher than those in the other three groups（P<0.05， P<0.01）. Metabolomic analysis revealed 173 differentially expressed metabolites in the TRYZ+AF group and the control group， primarily enriched in pathways such as glycerophospholipid metabolism and glycolysis/gluconeogenesis. ConclusionThis study successfully establishes a rat model of AF integrated with the TRYZ syndrome， demonstrating the pathological process where the interactions of phlegm， heat and stasis jointly trigger tremor， this provides a reliable experimental tool for in-depth research into the biological basis of this disease syndrome.

ObjectiveTo investigate the effect of nicotinamide adenine dinucleotide on vascular endothelial injury in hypertension and its molecular mechanism. MethodsC57BL/6J mice were randomly divided into saline group （Saline） and hypertension group （Ang Ⅱ， which were infused with Ang Ⅱ via subcutaneously implanted osmotic pumps）， and supplemented daily with nicotinamide mononucleotide （300 mg/kg）， a precursor of NAD⁺. Blood pressure， endothelial relaxation function and pulse wave velocity were measured after 4 weeks. Wound healing assay and adhesion assay were used to evaluate the function of endothelial cells in vitro. mtROS levels were detected by immunofluorescence staining. RT-PCR was used to detect the mRNA expression of mtDNA， SIRT3 and isocitrate dehydrogenase 2 （IDH2）. 8-hydroxy-2'-deoxyguanosine levels were detected by enzyme-linked immunosorbent assay. The protein expression levels of p-eNOS， eNOS， SIRT3 and IDH2 were detected by Western blot. ResultsNMN supplementation reduced blood pressure （P<0.001） and improved endothelial function and arterial stiffness （P<0.001） in hypertensive mice. In vitro， NMN improved endothelial function in AngII-stimulated endothelial cells （P<0.05） and attenuated mitochondrial oxidative stress levels （P<0.001）. Mechanistically， NMN elevated SIRT3 activity （P<0.001）， which subsequently enhanced IDH activity （P<0.001） and reduced oxidative stress levels in endothelial cells. Conversely， knockdown of IDH2 would reverse the effect of SIRT3 in improving endothelial function （P<0.001）. ConclusionNAD⁺ lowers blood pressure and enhances vascular function in hypertension by reducing the level of oxidative stress in endothelial cells through activation of the SIRT3/IDH2 signal pathway.

Clinical practice guidelines represent the best recommendations for patient care. They are developed through systematically reviewing currently available clinical evidence and weighing the relative benefits and risks of various interventions. However, clinical practice guidelines have to go through a long translation cycle from development and revision to clinical promotion and application, facing problems such as scattered distribution, high duplication rate, and low actual utilization. At present, the clinical practice guideline information platform can directly or indirectly solve the problems related to the lengthy revision cycles, decentralized dissemination and limited application of clinical practice guidelines. Therefore, this paper systematically examines different types of clinical practice guideline information platforms and investigates their corresponding challenges and emerging trends in platform design, data integration, and practical implementation, with the aim of clarifying the current status of this field and providing valuable reference for future research on clinical practice guideline information platforms.

Objective To provide theoretical basis for the clinical application of the rational compatibility of C. odorata by studying the related domestic and international literature and explore the properties of C. odorata according to the theory of Traditional Chinese Medicine. Methods The medical literature related to C. odorata was retrieved and screened from CNKI, VIP, Wanfang Data, China Biomedical Literature Database and foreign literature databases such as PubMed, Web of Science, Scopus, Embase, and SciFinder. A total of 397 English articles and 50 Chinese articles were included in the study, which were systematically classified according to clinical application, chemical composition, pharmacological effect, toxic and side effects, and were analyzed according to the theory of Traditional Chinese Medicine. Results C. odorata features spicy, astringent tastes, a cool nature, entering heart and liver meridians, and a slightly toxic.Its functions included astringing to stop bleeding, detoxifying and promoting tissue regeneration, as well as intercepting malaria and killing parasites. It was used for conditions such as hematemesis, haemoptysis, traumatic bleeding, sores and abscesses, malaria, and leech bites. Conclusion The exploration of the properties and efficacy of C. odorata could provide reference for its clinical research and application in Traditional Chinese Medicine.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Background: Both sodium-glucose cotransporters (SGLTs) and Na+/H+ exchangers (NHEs) rely on a favorable Na-electrochemical gradient. Gastrin, through the cholecystokinin B receptor (CCKBR), can induce natriuresis and diuresis by inhibiting renal NHEs activity. The present study aims to unveil the role of renal CCKBR in diabetes through SGLT2-mediated glucose reabsorption. Methods: Renal tubule-specific Cckbr-knockout (CckbrCKO) mice and wild-type (WT) mice were utilized to investigate the effect of renal CCKBR on SGLT2 and systemic glucose homeostasis under normal diet, high-fat diet (HFD), and HFD with a subsequent injection of a low dose of streptozotocin. The regulation of SGLT2 expression by gastrin/CCKBR and the underlying mechanism was explored using human kidney (HK)-2 cells. Results: CCKBR was downregulated in kidneys of diabetic mice. Compared with WT mice, CckbrCKO mice exhibited a greater susceptibility to obesity and diabetes when subjected to HFD. In vitro experiments using HK-2 cells revealed an upregulation of glucose transporters after incubation with high glucose, a response that was significantly attenuated following gastrin intervention. The glucose uptake from the culture medium of cells was altered accordingly. Moreover, gastrin administration effectively mitigated hyperglycemia in WT diabetic mice by inhibition of SGLT2 mediated glucose reabsorption, but this effect was compromised in the absence of CCKBR, as seen in CckbrCKO mice. Mechanistically, gastrin/CCKBR substantially reduced SGLT2 expression in HK-2 cells exposed to high glucose, via modulating Erkuclear factor-kappa B (NF-κB) pathway. Conclusion Our study underscores the crucial role of renal gastrin/CCKBR in SGLT2 regulation and glucose reabsorption, and renal gastrin/CCKBR can be a promising therapeutic target for diabetes.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

BACKGROUND:Currently,there have been studies on three-dimensional digitalization and visualization systems for adult acupoints,but there are not many reports on the visualization of pediatric acupoints based on real pediatric digital sectional anatomical datasets. OBJECTIVE:To design and develop a digital three-dimensional visualization system for children's neck acupoints,to provide a basis for acupuncture and moxibustion,meridian and acupoint science teaching,clinical practice,acupuncture manipulation practice,and acupuncture safety research,and to provide a basis for the development of children's acupoint simulation system. METHODS:Based on a real cross-sectional anatomical dataset of pre-school boys,a three-dimensional digital virtual anatomical model of the neck region of children and internal multi-organ three-dimensional reconstruction were completed using PhotoShop 2021 and Digihuman Reconstruction System software.A database of 11 acupoints was compiled,including Fengfu and Fengchi,using the Unity database language.A three-dimensional model of children's neck anatomy,acupoint database,and writing acupuncture operation codes were integrated in Unity3D software.A three-dimensional digital visualization system for children's neck acupoints was successfully created,which integrated simulation acupoint positioning,three-dimensional acupoint anatomy,acupuncture training,clinical teaching,and acupuncture safety research. RESULTS AND CONCLUSION:(1)This study was based on real child specimens.Manual layer by layer segmentation of cross-sectional images was used to ensure the accuracy of the three-dimensional model to the greatest extent possible.The 3D software Digihuman Reconstruction System was utilized to extract and save independent segmentation data.PhotoShop 2021 software was collaborated with to complete dozens of three-dimensional reconstruction anatomical models of the outer skin of the neck and its internal bone structure,cervical spinal cord,blood vessels and nerves,muscles,and ligaments in children.The basic morphology and overall contour integrity verification of each independent structure were completed in MeshLab software.The 3-material research 13.0 software was applied for final fine tuning and anatomical position confirmation,successfully simulating and restoring the true anatomical morphology of the neck of preschool children.(2)Based on and referring to the national standards of the People's Republic of China,a database of commonly used acupoints in children's neck region was collected and organized,including their names,meridians,positioning,local anatomy,needle insertion levels,acupuncture methods,acupuncture accidents and prevention,acupoint indications,and two-dimensional anatomical sectional images.(3)Unity3D software was employed to integrate the three-dimensional model of children's neck,acupuncture simulation operation,and acupoint database,and a three-dimensional digital children's neck acupoint acupuncture visualization system was successfully constructed.The system displayed information on children's neck acupoints,two-dimensional and three-dimensional anatomical structures,and achieved two-dimensional and three-dimensional acupuncture simulation functions and acupuncture safety research functions for children's neck acupoints.Based on the ultra-thin sectional anatomical dataset of real child specimens,the first three-dimensional digital and visualization system for acupoints in the neck region of children had been constructed.Compared with previous acupoint acupuncture systems,it is more in line with the anatomical and morphological development characteristics of Asian children and has high application value in the fields of acupuncture safety research,clinical teaching,and acupuncture simulation training.