Objective:To discuss the influencing factors of angina pectoris in the patients with diabetes mellitus(DM),to construct a Bayesian network model to explore the network relationships among the influencing factors,and to predict the risk of angina pectoris in the patients with DM.Methods:Based on the UK Biobank(UKB)database,the Logistic regression aralysis model was used to screen the influencing factors of angina pectoris in the patients with DM.The taboo search algorithm was used for structure learning,and the Bayesian parameter estimation method was used for parameter learning to construct the Bayesian network model.Results:A total of 22 712 DM patients were included.The influencing factors of angina pectoris in the patients with DM included 14 variables:gender,age,body mass index(BMI),triglycerides(TG),total cholesterol(TC),glycated hemoglobin(HbA1c),hypertension,maternal smoking around delivery,smoking status,alcohol consumption,regular exercise,insomnia,sleep duration,and childhood relative body size(P<0.05).A Bayesian network model was constructed with 15 nodes and 22 directed edges.Among them,age,HbA1c,hypertension,regular exercise,BMI,and sleep duration were directly associated with the occurrence of angina pectoris in the patients with DM,while gender,smoking status,alcohol consumption,TC,TG,insomnia,childhood relative body size,and maternal smoking around delivery were indirectly associated with the occurrence of angina pectoris in the patients with DM.Conclusion:Age,HbA1c,hypertension,regular exercise,BMI,and sleep duration are direct influencing factors of angina pectoris in the patients with DM.Controlling HbA1c,blood pressure,and BMI levels,engaging in regular exercise,and maintaining appropriate sleep duration are beneficial for reducing the risk of angina pectoris in the patients with DM.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

Objective:To screen the main characteristic variables affecting the incidence of cardiovascular and cerebrovascular diseases,and to construct the Bayesian network model of cardiovascular and cerebrovascular disease incidence risk based on the top 10 characteristic variables,and to provide the reference for predicting the risk of cardiovascular and cerebrovascular disease incidence.Methods:From the UK Biobank Database,315 896 participants and related variables were included.The feature selection was performed by categorical boosting(CatBoost)algorithm,and the participants were randomly divided into training set and test set in the ratio of 7∶3.A Bayesian network model was constructed based on the max-min hill-climbing(MMHC)algorithm.Results:The prevalence of cardiovascular and cerebrovascular diseases in this study was 28.8％.The top 10 variables selected by the CatBoost algorithm were age,body mass index(BMI),low-density lipoprotein cholesterol(LDL-C),total cholesterol(TC),the triglyceride-glucose(TyG)index,family history,apolipoprotein A/B ratio,high-density lipoprotein cholesterol(HDL-C),smoking status,and gender.The area under the receiver operating characteristic(ROC)curve(AUC)for the CatBoost training set model was 0.770,and the model accuracy was 0.764;the AUC of validation set model was 0.759 and the model accuracy was 0.763.The clinical efficacy analysis results showed that the threshold range for the training set was 0.06-0.85 and the threshold range for the validation set was 0.09-0.81.The Bayesian network model analysis results indicated that age,gender,smoking status,family history,BMI,and apolipoprotein A/B ratio were directly related to the incidence of cardiovascular and cerebrovascular diseases and they were the significant risk factors.TyG index,HDL-C,LDL-C,and TC indirectly affect the risk of cardiovascular and cerebrovascular diseases through their impact on BMI and apolipoprotein A/B ratio.Conclusion:Controlling BMI,apolipoprotein A/B ratio,and smoking behavior can reduce the incidence risk of cardiovascular and cerebrovascular diseases.The Bayesian network model can be used to predict the risk of cardiovascular and cerebrovascular disease incidence.

Objective:To explore the effect path of death attitude and purpose in life on attitude toward hospice care of undergraduate intern nursing students.Methods:This study was a cross-sectional study. Using the convenient sampling method, a total of 229 undergraduate intern nursing students from two schools in Hefei, Anhui Province were selected as the research objects from October to December 2022. General data questionnaire, Chinese Version of Frommelt Attitudes Toward Care of the Dying Scale Form B (FATCOD-B-C), Chinese Version of Death Attitude Profile-Revised (DAP-R) Scale and Chinese Version of Purpose in Life Test (PIL-C) were used to investigate. Pearson correlation analysis was used to explore the correlation between death attitudes, purpose in life and attitude toward hospice care among undergraduate intern nursing students. Structural equation model was used to examine the path relationship between attitude towards death and purpose in life on attitude toward hospice care.Results:A total of 229 questionnaires were sent out in this study, and 214 were effectively recovered, with an effective recovery rate of 93.45% (214/229). Among 214 undergraduate intern nursing students, the scores of FATCOD-B-C, Chinese Version DAP-R Scale, and PIL-C were (101.06±8.16), (91.21±12.13) and (94.45±11.90), respectively. The results of Pearson correlation analysis showed that the purpose in life was positively correlated with attitude toward hospice care ( r=0.290, P<0.01), while the attitude to death was negatively correlated with attitude toward hospice care ( r=-0244, P<0.01). The results of structural equation model path analysis showed that the purpose in life (life goal, life attitude) can affect attitude toward hospice care through death attitude (escape acceptance, natural acceptance, fear of death) . Conclusions:Effective interventions on purpose in life and attitude towards death of undergraduate intern nursing students can improve their attitudes toward hospice care .

Monoclonal antibody-based therapy has achieved great success and is now one of the most crucial therapeutic modalities for cancer therapy. The first monoclonal antibody authorized for treating human epidermal growth receptor 2 (HER2)-positive breast cancer is trastuzumab. However, resistance to trastuzumab therapy is frequently encountered and thus significantly restricts the therapeutic outcomes. To address this issue, tumor microenvironment (TME) pH-responsive nanoparticles (NPs) were herein developed for systemic mRNA delivery to reverse the trastuzumab resistance of breast cancer (BCa). This nanoplatform is comprised of a methoxyl-poly (ethylene glycol)-b-poly (lactic-co-glycolic acid) copolymer with a TME pH-liable linker (Meo-PEG-Dlink _m -PLGA) and an amphiphilic cationic lipid that can complex PTEN mRNA via electrostatic interaction. When the long-circulating mRNA-loaded NPs build up in the tumor after being delivered intravenously, they could be efficiently internalized by tumor cells due to the TME pH-triggered PEG detachment from the NP surface. With the intracellular mRNA release to up-regulate PTEN expression, the constantly activated PI3K/Akt signaling pathway could be blocked in the trastuzumab-resistant BCa cells, thereby resulting in the reversal of trastuzumab resistance and effectively suppress the development of BCa.

The patients with trauma have a high mortality and disability rate, and the incidence of trauma is increasing year by year.Rapid and accurate diagnosis is the key to improve the prognosis of patients with trauma.The traditional diagnostic imaging techniques are X-ray and CT examination.Although X-ray examination can be completed at the bedside, its sensitivity is not high.The diagnostic sensitivity of CT examination is high, but it can not be completed by bedside.Moreover, the process of repeated transportation of patients will delay the best treatment time, even cause secondary injury.Bedside ultrasound has the advantages of fast, real-time, noninvasive and repeatable operation.With the continuous development of bedside ultrasound technology, it has been widely used in the diagnosis of trauma.This review summarized the clinical applications of bedside ultrasound in trauma patients.

Cystatin, a cysteine protease inhibitor found in many parasites, plays important roles in immune evasion. This study analyzed the molecular characteristics of a cystatin from Fasciola hepatica (FhCystatin) and expressed recombinant FhCystatin (rFhcystatin) to investigate the immune modulatory effects on lipopolysaccharide-induced proliferation, migration, cytokine secretion, nitric oxide (NO) production, and apoptosis in mouse macrophages. The FhCystatin gene encoded 116 amino acids and contained a conserved cystatin-like domain. rFhCystatin significantly inhibited the activity of cathepsin B. rFhCystatin bound to the surface of mouse RAW264.7 cells, significantly inhibited cell proliferation and promoted apoptosis. Moreover, rFhCystatin inhibited the expression of cellular nitric oxide, interleukin-6, and tumor necrosis factor-α, and promoted the expression of transforming growth factor-β and interleukin-10. These results showed that FhCystatin played an important role in regulating the activity of mouse macrophages. Our findings provide new insights into mechanisms underlying the immune evasion and contribute to the exploration of potential targets for the development of new drug to control F. hepatica infection.

Rift Valley fever (RVF) is an acute, febrile zoonotic disease that is caused by the RVF virus (RVFV). RVF is mainly prevalent on the Arabian Peninsula, the African continent, and several islands in the Indian Ocean near southeast Africa. RVFV has been classified by the World Organisation for Animal Health (OIE) as a category A pathogen. To avoid biological safety concerns associated with use of the pathogen in RVFV neutralization assays, the present study investigated and established an RVFV pseudovirus-based neutralization assay. This study used the human immunodeficiency virus (HIV) lentiviral packaging system and RVFV structural proteins to successfully construct RVFV pseudoviruses. Electron microscopy observation and western blotting indicated that the size, structure, and shape of the packaged pseudoviruses were notably similar to those of HIV lentiviral vectors. Infection inhibition assay results showed that an antibody against RVFV inhibited the infective ability of the RVFV pseudoviruses, and an antibody neutralization assay for RVFV detection was then established. This study has successfully established a neutralization assay based on RVFV pseudoviruses and demonstrated that this method can be used to effectively evaluate antibody neutralization.
Africa ; Animals ; Blotting, Western ; HIV ; Indian Ocean ; Islands ; Methods ; Microscopy, Electron ; Product Packaging ; Rift Valley fever virus ; Rift Valley Fever ; Zoonoses

Objective To study the significance of leptin and its receptor(OB-R) in the occurrence and development of pulmonary arterial hypertension(PAH) induced by monocrotaline(MCT).Methods Fifteen SD rats were divided into the control group(n=5) and two experimental groups(n=10).The experimental groups were intraperitoneally injected by MCT for constructing the PAH model and the control group was injected by the same dose of solvent groups.The venous blood was extracted at 2,4 weeks after MCT injection in the two experimental groups.The mean pulmonary artery pressure(mPAP) and right ventricular hypertrophy index(RVHI) were measured and then the lung tissue was removed.The pathological change of lung blood vessels was observed.The expression of serum leptin was detected by ELISA.The expression of OB-R in lung tissue was tested by Western blot.Results Compared with the control group,mPAP and RVHI in the experimental groups were significantly increased(P＜0.05);the expression levels of serum leptin and lung tissue OB-R were increased significantly(P＜0.05),moreover,which were positively correlated with mPAP(r=0.912,P＜0.05;r=0.861,P＜0.05).Conclusion Leptin and OB-R may play an important role in the occurrence and development of PAH induced by MCT.

Objective To investigate the clinical and imaging features of pseudo subarachnoid hemorrhage(pseudo-SAH) in order to provide a theoretical basis for correct diagnosis and reducing misdiagnosis.Methods The clinical and imaging data of 5 patients with pseudo-SAH were retrospectively analyzed and summarized.Results Five pseudo-SAH patients had a history of unconsciousness,respiratory disorder,mechanical ventilation,hypoxemia and acidosis.Cranial CT showed diffuse cerebral edema and high density of cerebral fissure and cerebral ventricle,and there was no bloody cerebrospinal fluid via lumbar puncture.In the five patients,one improved,three died,and one gave up treating because of invalid treatment.Conclusions All patients have a history of hypoxic-ischemic encephalopathy before onset of pseudo-SAH.The clinical manifestation of pseudoSAH includes encephalopathy symptom such as unconsciousness,headache,seizure,etc.Cranial CT shows diffuse cerebral edema,high density of cerebral fissure and cerebral ventricle,and there is no bloody cerebrospinal fluid via lumbar puncture.Prognosis of pseudo-SAH is often bad.And most patients show critically illness and high mortality.