This paper aimed to explore the effects of Duzhong Decoction(DZD)-containing serum on the proliferation and osteoblast differentiation of MC3T3-E1 cells through L-type voltage-gated calcium channels(L-VGCCs). L-VGCCs inhibitors, nifedipine and verapamil, were used to block L-VGCCs in osteoblasts. MC3T3-E1 cells were divided into a control group, a low-dose DZD-containing serum(L-DZD) group, a medium-dose DZD-containing serum(M-DZD) group, a high-dose DZD-containing serum(H-DZD) group, a nifedipine group, a H-DZD + nifedipine group, verapamil group, and a H-DZD + verapamil group. The CCK-8 method was used for cell proliferation analysis, alkaline phosphatase(ALP) assay kits for intracellular ALP activity measurement, Western blot for protein expression level in cells, real-time fluorescence quantitative PCR technology for intracellular mRNA expression level determination, fluorescence spectrophotometer for free Ca~(2+) concentration determination in osteoblasts, and alizarin red staining(ARS) for mineralized nodule formation in osteoblasts. The experimental results show that compared to the control group, DZD groups can promote MC3T3-E1 cell proliferation, ALP activity, and mineralized nodule formation, increase intracellular Ca~(2+) concentrations, and upregulate the protein expression of bone morphogenetic protein 2(BMP2), collagen Ⅰ(COL1), α2 subunit protein of L-VGCCs(L-VGCCα2), and the mRNA expression of Runt-related transcription factor 2(RUNX2), and BMP2. After blocking L-VGCCs with nifedipine and verapamil, the intervention effects of DZD-containing serum were inhibited to varying degrees. Both nifedipine and verapamil could inhibit ALP activity, reduce mineralized nodule areas, and downregulate the expression of bone formation-related proteins. Moreover, the effects of DZD-containing serum on increasing MC3T3-E1 cell proliferation, osteoblast differentiation, and Ca~(2+) concentrations, upregulating the mRNA expression of osteoprotegerin(OPG) and protein expression of phosphorylated protein kinase B(p-Akt) and phosphorylated forkhead box protein O1(p-FOXO1), and upregulating phosphatase and tensin homolog(PTEN) expression were reversed by nifedipine. The results indicate that DZD-containing serum can increase the Ca~(2+) concentration in MC3T3-E1 cells to promote bone formation, which may be mediated by L-VGCCs and the PTEN/Akt/FoxO1 signaling pathway, providing a new perspective on the mechanism of DZD in treating osteoporosis.
Animals ; Osteoblasts/metabolism* ; Cell Proliferation/drug effects* ; Cell Differentiation/drug effects* ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Calcium Channels, L-Type/genetics* ; Alkaline Phosphatase/genetics* ; Serum/chemistry* ; Cell Line ; Osteogenesis/drug effects* ; Bone Morphogenetic Protein 2/genetics*

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

Objective To explore the relevant factors of new-onset conduction disturbance(NOCD)after transcatheter aortic valve replacement(TAVR),such as anatomical structure,device type,surgical strategies,etc.,discover relevant predictive factors,and establish a predictive model to assess the risk of conduction blockages.Methods From January 2016 to March 2022,clinical data of symptomatic patients with severe aortic valve stenosis or severe regurgitation who underwent TAVR at Xiangya Second Hospital of Central South University were collected through the hospital information system and imaging database.ECG,echocardiography,CTA,surgical materials,etc.,were extracted and analyzed by specialists.SPSS software was used for statistical analysis,and a multi-factor regression prediction model for NOCDwas built.Results A total of 184 patients were included,the occurrence rate of NOCD after TAVR was 31.0%,pure regurgitation patients'NOCD occurrence rate was 63.6%(7/11).The NOCD group had a larger aortic angles[(57.7±10.3)°vs.(52.0±9.0)°,P＜0.001],larger Oversizing[(129±28)%vs.(120±21)%,P=0.018],deeper implantation depth[(7.2±5.1)mm vs.(4.8±4.2)mm,P=0.001],and higher pure regurgitation patients'proportion[12.3%vs.3.1%,P=0.037]than the non-NOCD group.Multifactorial Logistic regression analysis indicated that an aorta angle＞54.5°(OR 3.78,95%CI 1.86-7.63,P＜0.001)or implantation depth＞5.7 mm(OR 3.39,95%CI 1.68-6.85,P＜0.001)are independent risk factors for new onset conduction disturbances after TAVR,and a predictive model was established with aortic angle,implantation depth,and Oversizing ratio as variables.The receiver operating characteristics curve showed area under ROC curve 0.709,95%CI 0.623-0.795,predicting NOCD after TAVR.Conclusions A retrospective analysis carried out at a single center discovered that the aortic angle in the NOCD group was larger than that in the non-NOCD group,the Oversizing ratio was higher,the implantation location was deeper,and there was a higher proportion of patients with pure regurgitation lesions.An aortic angle greater than 54.5°or an implantation depth more than 5.7 mm were identified as independent risk factors for NOCD after TAVR.

AIM To establish the HPLC fingerprints for Tanacetum tatsienense(Bureau & Franchet)K.Bremer & Humphries and to determine the contents of chlorogenic acid,quercetin-3-O-glucoside,luteolin-7-O-glucoside,luteolin-7-O-glucuronide,apigenin-7-O-glucuronide,luteolin and apigenin.METHODS The analysis was performed on a 35 ℃ thermostatic Agilent ZORBAX Extend C18 column(4.6 mm×250 mm,0.5 μm),with the mobile phase comprising of 0.5％phosphoric acid-acetonitrile flowing at 1.0 mL/min,and the detection wavelength was set at 350 nm.Subsequently,principal component analysis,partial least squares discriminant analysis and cluster analysis were carried out.RESULTS There were twelve common peaks in the fingerprints for fourteen batches of samples with the similarities of 0.761-0.975.Seven constituents showed good linear relationships within their own ranges(R2≥0.999 1),whose average recoveries were 84.00％-105.11％with the RSDs of 1.28％-2.86％.Various batches of samples were clustered into three types,and seven differential constituents were observable,containing peaks 4(luteolin-7-O-glucoside),12(apigenin),9(apigenin-7-O-glucuronide),8,11(luteolin),5(luteolin-7-O-glucuronide)and 2.CONCLUSION This precise,stable,specific and reproducible method can be used for the quality control of T.tatsienense.

The aim of this study was to investigate the prevalence of spotted fever group rickettsia(SFGR)in wild rodents collected from Fengshan County in the Guangxi Zhuang Autonomous Region,and to determine their species.Wild rodents were captured in cages in Fengshan County,Hechi City,Guangxi Zhuang Autonomous Region.The rodents were identified according to morphological characteristics,and the findings were confirmed through molecular biology methods.Subsequently,spleen samples were collected,and DNA was extracted.The outer membrane protein A(ompA)gene was amplified with semi-nested PCR to determine the species of SFGR in captured wild rodents.After sequencing of the PCR products,homology and phylogenetic analyses of ompA gene sequences were performed.A total of 105 wild rodents belonging to seven species were captured.FGR was detected in six rodent species(Bandicota indica,Leopoldamys edwardsi,Mus caroli,Mus Pahari,Rat-tus andamanensis,and Rattus losea,but not Berylmys bower si),and the total positivity rate was 23.8％.Three Rickettsia species,Candidatus Rickettsia jingxinensis,Rickettsia raoultii,and Rickettsia sibirica,were identified from analysis of the ompA gene sequence.This study revealed the presence of three species of SFGR infecting wild rodents from Fengshan County,Guangxi Zhuang Autonomous Region,thus suggesting that Fengshan County is a natural focus of tick-borne spotted fever.This study highlights the need to strengthen monitoring and prevention measures for rickettsiosis.

This paper aimed to study the chemical constituents from the root bark of Schisandra sphenanthera. Silica, Sephadex LH-20 and RP-HPLC were used to separate and purify the 80% ethanol extract of S. sphenanthera. Eleven compounds were identified by ~1H-NMR, ~(13)C-NMR, ESI-MS, etc., which were 2-[2-hydroxy-5-(3-hydroxypropyl)-3-methoxyphenyl]-propane-1,3-diol(1), threo-7-methoxyguaiacylglycerol(2),4-O-(2-hydroxy-1-hydroxymethylethyl)-dihydroconiferylalcohol(3), morusin(4), sanggenol A(5), sanggenon I(6), sanggenon N(7), leachianone G(8),(+)-catechin(9), epicatechin(10), and 7,4'-dimethoxyisoflavone(11). Among them, compound 1 was a new compound, and compounds 2-9 were isolated from S. sphenanthera for the first time. Compounds 2-11 were subjected to cell viability assay, and the results revealed that compounds 4 and 5 had potential cytotoxicity, and compound 4 also had potential antiviral activity.
Schisandra ; Plant Bark ; Antiviral Agents ; Biological Assay ; Catechin ; Phenols

Objective: To investigate the relationship between serum lysophosphatidylcholine (LPC) level and the health index of the elderly. Methods: A total of 251 subjects were selected from the 2016 baseline survey of the Yongfu Longevity Cohort in Guangxi Province among whom 66, 63 and 122 were in the young and middle-aged group (≤59 years old), the young group (60-89 years old) and the longevity group (≥90 years old), respectively. Demographic data were collected and related indicators of height, weight, blood pressure and lipid metabolism were measured. The cognitive and physical functions of the elderly were assessed by the results of the simple mental state scale and the daily living activity scale to construct the health index of the elderly. The serum levels of LPC16∶0, LPC18∶0, LPC18∶1 and LPC18∶2 were determined by liquid chromatography-tandem mass spectrometry, and the differences among different ages and health status groups were compared. The logistic regression model was used to analyze the relationship between the serum LPC level and the health index of the elderly. Results: With the increase in age, the proportion of female subjects increased, and the rate of smoking and drinking decreased. BMI, TC, TG, LDL-C, diastolic blood pressure, and the four LPCs levels decreased with the increase of age, and systolic blood pressure levels increased with the increase of age (all P values<0.05). There was no significant difference in HDL-C levels among age groups (P>0.05). With the decline of health status in the elderly, serum levels of LPC16∶0, LPC18∶0, LPC18∶1 and LPC18∶2 showed a downward trend (all P values<0.001). After adjusting for age and gender, only LPC18∶0 was associated with the health status in old age [OR (95%CI): 0.48 (0.25-0.92)]. For every 1 standard deviation (16.87 nmol/L) increase in serum LPC18∶0 concentration, the risk of poor health status in old age decreased by 52%. Conclusion: Serum LPC18∶0 was associated with the health status in old age independent of age and sex.
Aged ; Middle Aged ; Humans ; Female ; Aged, 80 and over ; Lysophosphatidylcholines ; Risk Factors ; China ; Longevity ; Surveys and Questionnaires ; Triglycerides

International research on healthy life expectancy (HALE) focuses on inequality of socioeconomic status and individual natural attributes. With the acceleration of population ageing and the increase in average life expectancy, the extension of unhealthy life expectancy and the increase of social and economic burden caused by diseases have gradually attracted the attention of countries around the world. Therefore, the evaluation of disease factors affecting HALE is a meaningful direction in the future. This study introduces the development process and commonly used measurement methods of HALE. According to the definition of health from the Global Burden of Disease Study and World Health Organization, physical and mental diseases such as cardiovascular and cerebrovascular diseases, chronic respiratory diseases, diabetes, malignant tumors and depression were selected to summarize the impact of these diseases and pre-disease states on HALE. It is expected to provide a theoretical basis for the formulation of relevant public health policies and the improvement of quality of life in China.
Humans ; Healthy Life Expectancy ; Quality of Life ; Life Expectancy ; Causality ; Social Class

[Abstract] Objective To study whether the regulation of mammalian target of rapamycin complex 2(mTORC2) / Akt signaling pathway has a protective effect on SH-SY5Y cell line damaged by 6-hydroxydopamine (6-OHDA), and to clarify its molecular mechanism. Methods SH-SY5Y cells treated with retinoic acid (RA) were given 6-OHDA, mTORC2 signaling pathway inhibitor PP242 and agonist A-443654 respectively. The changes of cell number in each group were investigated by immunofluorescent staining; The total protein was extracted and the expression level and interaction of key proteins in mTORC2 signaling pathway were determined by Western blotting and co-immunoprecipitation (CoIP); The apoptosis rate of cells in each group was detected by flow cytometry. At the same time, the co-culture Parkinson’ s disease (PD) model was made using SH-SY5Y cell line and Bv-2 cell line; MTT colorimetric method was used to detect the cell viability of each group; ELISA was used to detect the content of tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) in cell culture supernatant. Results The number of tyrosine hydroxylase(TH) / proliferating cell nuclear antigen (PCNA) / hochest-, TH / 5-bronmo-2’ -deoxyuridine(BrdU) -labeled positive cells in 6-OHDA-lesioned PD cell model group was significantly lower than that in the normal group; The apoptosis rate was higher; The expression of Rictor, p-Akt and regulated in DNA damage and development 1(REDD1) was increased; There was an interaction between Rictor and p-Akt or REDD1; The cell viability was significantly reduced in the co-culture model; the content of TNF-α and IL-β increased in the cell culture supernatant. With further up-regulation of the abovementioned protein expressions, the cell survival, apoptosis and pro-inflammatory cytokine levels in A-443654 group were significantly ameliorated, while PP242 group showed the opposite changes. Conclusion A-443654 activates mTORC2 signaling pathway by p-Akt, which increases the expression of Rictor and REDD1 protein. These changes contribute to the amelioration in cell survival rate, apoptosis rate, and the proliferation and differentiation and decreasion of apoptosis rate of SH-SY5Y cells. These result improved 6-OHDA-induced cell damage and inhibited the release of pro-inflammatory cytokines.

This study used machine learning techniques combined with routine blood cell analysis parameters to build preliminary prediction models, helping differentiate patients with depression from healthy controls, or patients with anxiety. A multicenter study was performed by collecting blood cell analysis data of Beijing Chaoyang Hospital and the First Hospital of Hebei Medical University from 2020 to 2021. Machine learning techniques, including support vector machine, decision tree, naïve Bayes, random forest and multi-layer perceptron were explored to establish a prediction model of depression. The results showed that based on the blood cell analysis results of healthy controls and depression group, the accuracy of prediction model reached as high as 0.99, F1 was 0.975. Receiver operating characteristic curve area and average accuracy were 0.985 and 0.967, respectively. Platelet parameters contributed mostly to depression prediction model. While, to random forest differential diagnosis model based on the data from depression and anxiety groups, prediction accuracy reached 0.68 and AUC 0.622. Age, platelet parameters, and average volume of red blood cells contributed the most to the model. In conclusion, the study researched on the prediction model of depression by exploring blood cell analysis parameters, revealing that machine learning models were more objective in the evaluation of mental illness.
Humans ; Depression ; Bayes Theorem ; Machine Learning ; Support Vector Machine ; Blood Cell Count