ObjectiveTo perform a genome-wide association study of rubella virus vaccine strain BRD-Ⅱ, so as to fully grasp the sequence characteristics of this genome. MethodsSecond-generation sequencing method was used to conduct the whole-genome sequencing on the vaccine strain BRD-Ⅱ, and the affinity tree of this genome with some vaccine strains and wild-type rubella virus strains was analyzed using the maximum likelihood method. The average genetic distance of nucleic acid sequence of each vaccine strain protein was determined. And homology comparison of structural proteins of each rubella vaccine strain, plus the comparison between this genome with the AY258323.1 genome sequence, were conducted to analyze the homology of E1 protein between the wild-type rubella virus reference strain and vaccine strain BRD-Ⅱ. ResultsThe sequencing results showed that the BRD-Ⅱ strain was a single-molecule single-stranded positive-strand ribonucleic acid (RNA), composed of 9 778 nucleotides, with a GC content of 69.35 %. The C protein was composed of 300 amino acids, the E2 glycoprotein was composed of 282 amino acids, and the E1 glycoprotein was composed of 481 amino acids. The results of preliminary analysis showed that the average genetic distances of nucleic acid sequences were 0.066 700 for the P150 protein, 0.061 933 for the P90 protein, 0.057 850 for the C protein, 0.068 167 for the E2 protein, and 0.068 833 for the E1 protein, respectively. The amino acid sequences in the E2 protein and E1 protein regions of the two BRD-Ⅱ strains did not change, confirming the conserved regions of the E1 protein by comparison. ConclusionThe sequence characteristics of the genome are clarified, which have laid a broad foundation for the subsequent detection of the genetic stability of the main antigen genes.

OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms and vocal emotional characteristics of individuals with subthreshold depression to facilitate early identification of subthreshold depression. METHODS: We collected voice data from both normal individuals and participants with subthreshold depression by asking them to read specifically chosen words and texts. From each voice sample, 384-dimensional vocal emotional feature variables were extracted, including energy feature, Meir frequency cepstrum coefficient, zero cross rate feature, sound probability feature, fundamental frequency feature, difference feature. The Recursive Feature Elimination (RFE) method was employed to select voice feature variables. Classification models were then built using the machine learning algorithms Adaptive Boosting (AdaBoost), Random Forest (RF), Linear Discriminant Analysis (LDA), Logistic Regression (LR), Lasso Regression (LRLasso), and Support Vector Machine (SVM), and the performance of these models was evaluated. To assess generalization capability of the models, we used real-world speech data to evaluate the best speech recognition classification model. RESULTS: The AdaBoost, RF, and LDA models achieved high prediction accuracies of 100%, 100%, and 93.3% on word-reading speech test set, respectively. In the text-reading speech test set, the accuracies of the AdaBoost, RF, and LDA models were 90%, 80%, and 90%, respectively, while the accuracies of the other 3 models were all below 80%. On real-world word-reading and text-reading speech data, the classification models using AdaBoost and Random Forest still achieved high predictive accuracies (91.7% and 80.6% for AdaBoost and 86.1% and 77.8% for Random, respectively). CONCLUSIONS Analyzing vocal emotional characteristics allows effective identification of individuals with subthreshold depression. The AdaBoost and RF models show excellent performance for classifying subthreshold depression individuals, and may thus potentially offer valuable assistance in the clinical and research settings.
Humans ; Machine Learning ; Emotions ; Depression/diagnosis* ; Algorithms ; Voice ; Support Vector Machine ; Male ; Female

Dog and cat bites are the most common types of animal injuries, which cause various types of tissue damage and have a high incidence of wound infections. These infections are often mixed with multiple microorganisms and have their characteristics and complexity. Selecting appropriate antimicrobial drugs for prevention and treatment can help prevent the occurrence of infections and improve the effectiveness of infection treatment. To better prevent and treat wound infections caused by dog and cat bites, this article reviews the research progress in the epidemiology of dog and cat bites, characteristics of wounds, incidence of wound infections, types of infections, common pathogens, infection assessment, and antimicrobial treatment, to provide a reference for the selection of antimicrobial drugs for wound infections caused by dog and cat bites.

Informed consent in psychological counseling is the first step for clients to initiate the counseling process， and the degree and effectiveness of informed consent are important factors that determine the subsequent effectiveness and development of psychological counseling. By elaborating on the connotation and importance of informed consent in psychological counseling， the ethical dilemmas of the issue of informed consent in psychological counseling were classified and summarized. There were ethical dilemmas， such as the lack of consensus， procedural guarantee mechanisms， special clients procedures and informed consent principles， as well as non-standard informed consent procedures in online psychological counseling. The paper also proposed to clarify the explanatory obligations of counselors， strengthen procedural ethical constraints， formulate special norms for informed consent for special subjects， and enhance the ethical education and capacity building of psychological counselors.

Objective To observe the effects of growth differentiation factor-15(GDF-15)on collateral circulation and cardiac function in rats with acute myocardial infarction(AMI)in relation to the nitric oxide(NO)/cyclic guanosine monophosphate(cGMP)/protein kinase G(PKG)signaling pathway.Methods An AMI rat model was constructed by ligating the left anterior descending coronary artery.After modeling,the rats were divided randomly into Sham,Model,and GDF-15 groups(n=12 rats per group).Rats in the GDF-15 group were injected intraperitoneally with recombinant GDF-15 protein,and the other two groups were injected with the same amount of normal saline twice a week for 8 consecutive weeks.Cardiac function was detected by echocardiography.Pathological damage to rat myocardial tissue was detected by hematoxylin and eosin staining and the collateral circulation was observed by CD31 immunohistochemical staining.Vascular endothelial growth factor(VEGF)mRNA expression was detected by quantitative polymerase chain reaction.Transcriptomic sequencing of heart tissues in the model and GDF-15 groups was performed and differentially expressed genes(DEGs)were screened.Pathway enrichment analysis of the DEGS was carried out according to the Kyoto Encyclopedia of Genes and Genomes(KEGG).Nitric oxide(NO),reactive oxygen species(ROS),and cGMP were detected using kits,and VEGF,endothelial nitric oxide synthase(eNOS)monomer,p-eNOSser1177monomer,eNOS dimer,and PKG protein were detected by Western blot.Results Left ventricular end-systolic diameter(LVEDs)and left ventricular end-diastolic diameter(LVEDd)were increased(P＜0.001),and left ventricular ejection fraction(LVEF)and the short-axis shortening rate(FS)were decreased in the Model group compared with the Sham group(P＜0.001).Myocardial cell necrosis was more severe,vascular density in the infarcted area was decreased(P＜0.05),but VEGF mRNA and protein levels were no change(P＞0.05),and levels of NO,eNOS dimer,cGMP,and PKG protein were decreased(P＜0.05),and expression levels of ROS,eNOS monomer,and p-eNOSser1177 monomer were increased(P＜0.05).LVEDs and LVEDd decreased(P＜0.05),LVEF and FS increased(P＜0.01),myocardial cell necrosis was relieved,vascular density in the infarcted area increased significantly(P＜0.0001),and VEGF mRNA levels increased(P＜0.0001),compared with the Model group.Transcriptomic sequencing identified 324 DEGs,including 230 up-regulated and 94 down-regulated genes.According to KEGG enrichment analysis,the cGMP-PKG signaling pathway showed the most significant difference in the T20 pathway.VEGF,NO,eNOS dimer,cGMP,and PKG protein levels were all increased(P＜0.05),while ROS,eNOS monomer,and p-eNOSser1177 monomer were decreased in the GDF-15 group(P＜0.05).Conclusions GDF-15 can promote collateral circulation in ischemic myocardium and improve cardiac function by inhibiting eNOS decoupling and activating the NO/cGMP/PKG pathway.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

AIM:To investigate the impact of recombinant human CC16 protein(rhCC16)on cigarette smoke extract(CSE)-induced senescence-associated secretory phenotype(SASP)in human bronchial epithelial cells(HBECs)and in the lung tissues of chronic obstructive pulmonary disease(COPD)mice,and to explore the underlying mechanism.METHODS:HBECs were induced into cellular senescence using 5%CSE.The senescent HBECs were treated with 250 ng/mL rhCC16,and the levels of reactive oxygen species(ROS)were assessed using the 2',7'-dichlorodihydrofluorescein diacetate(DCFH-DA)method.The levels of trimethylated histone H3 at lysine 9(H3K9me3),a marker of senescence-associated heterochromatic foci(SAHF),were detected using a Western blot assay.RT-qPCR and ELISA were utilized to measure the mRNA expression and protein levels of SASP components including interleukin-1 beta(IL-1β),IL-6,IL-8,chemokine(C-X-C motif)ligand-1(CXCL-1),matrix metalloproteinase 1(MMP1)and MMP3.Passive smoking was con-ducted for six months to induce COPD in mice.RhCC16(2.5 μg/g body weight)or an equal volume of PBS(20 μL)was intranasally administered from the 16th week of smoking in the COPD+rhCC16 group or COPD+PBS group,respectively,with administration 2 hours before smoking.ROS levels in lung tissue cells were investigated using DCFH-DA staining.H3K9me3 levels in lung tissues were tested using Western blot assay.RT-qPCR and ELISA were performed to examine the mRNA expression and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3.RESULTS:DCFH-DA staining results showed that CSE stimulation increased ROS levels in HBECs,while rhCC16 treatment reduced them(P＜0.01).Western blot results indicated that CSE stimulation elevated H3K9me3 levels in HBECs,which were decreased with rhCC16 treatment(P＜0.01).RT-qPCR and ELISA assays demonstrated that CSE stimulation upregulated the mRNA and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3 in HBECs,which were reduced with rhCC16 admin-istration(P＜0.05).DCFH-DA staining results showed an increase in ROS levels in the lung tissues of COPD mice,which were decreased with rhCC16 administration(P＜0.01).Western blot data revealed an increase in H3K9me3 levels in the lung tissues of COPD mice,which were reduced with rhCC16 treatment(P＜0.01).RT-qPCR and ELISA assays demon-strated an upregulation of the mRNA and protein levels of IL-1β,IL-6,IL-8,CXCL-1,MMP1 and MMP3 in the lung tis-sues of COPD mice,which were reduced with rhCC16 treatment(P＜0.05).No statistically significant differences were ob-served in the above-mentioned indicators between the lung tissues of COPD and COPD+PBS mice(P＞0.05).CONCLU-SION:rhCC16 can effectively inhibit CSE-induced SASP in HBECs and in the lung tissues of COPD mice,with its under-lying mechanism potentially related to the inhibition of the ROS-H3K9me3 signaling pathway.

Dog and cat bites are the most common types of animal injuries, which cause various types of tissue damage and have a high incidence of wound infections. These infections are often mixed with multiple microorganisms and have their characteristics and complexity. Selecting appropriate antimicrobial drugs for prevention and treatment can help prevent the occurrence of infections and improve the effectiveness of infection treatment. To better prevent and treat wound infections caused by dog and cat bites, this article reviews the research progress in the epidemiology of dog and cat bites, characteristics of wounds, incidence of wound infections, types of infections, common pathogens, infection assessment, and antimicrobial treatment, to provide a reference for the selection of antimicrobial drugs for wound infections caused by dog and cat bites.

Objective This study aimed to develop an automated method for syndrome element differenti-ation in Traditional Chinese Medicine(TCM).Methods We first constructed and trained an Instruction-tuned Multi-Task TCM text embedding model(Instr-MT-TCM)using four distinct TCM task datasets,including domain knowledge,synonymous terminology,syndrome differentiation and treatment,and TCM case labels.Subsequently,five TCM diagnostics experts holding master's degrees or higher were organized to screen a real-world TCM case dataset and annotate symptoms and signs.The purpose was to evaluate the F1-score of the proposed method—the combination of Instr-MT-TCM and a Large Language Model(LLM)—by comparing its performance against the manual annotation result on the syndrome element differentiation task.Finally,to validate its feasibility in real-world clinical settings,the method was applied to 48 prostate cancer cases to calculate the syndrome element scores.Results The Instr-MT-TCM model showed rapid performance improvement in its early training phase,achieving a Recall@1(R@1)of 0.848.Experts curated a dataset of 1,793 real-world clinical cases,covering 34 common diseases and 66 syndrome patterns.In the syndrome element differentiation task,the collaborative framework of LLM and Instr-MT-TCM achieved a mean F1-score of 0.927,outperforming the 0.512 from manual annota-tion.The syndrome element analysis revealed that the predominant elements of disease nature were fire(heat)and yin deficiency,while the main elements of disease location were bladder and kidney.Conclusion This study proposes and validates a novel method for automated TCM syndrome element dif-ferentiation based on the synergy between LLM and our custom Instr-MT-TCM model.Achieving a high F1-score(0.927)on real-world data,the method demonstrates excellent accuracy and generalization ability.Its application in prostate cancer analysis highlights its significant clinical potential,offering effective technical support,and a new research direction for intelligent TCM syndrome element differentiation.

Objective To observe the effects of growth differentiation factor-15(GDF-15)on collateral circulation and cardiac function in rats with acute myocardial infarction(AMI)in relation to the nitric oxide(NO)/cyclic guanosine monophosphate(cGMP)/protein kinase G(PKG)signaling pathway.Methods An AMI rat model was constructed by ligating the left anterior descending coronary artery.After modeling,the rats were divided randomly into Sham,Model,and GDF-15 groups(n=12 rats per group).Rats in the GDF-15 group were injected intraperitoneally with recombinant GDF-15 protein,and the other two groups were injected with the same amount of normal saline twice a week for 8 consecutive weeks.Cardiac function was detected by echocardiography.Pathological damage to rat myocardial tissue was detected by hematoxylin and eosin staining and the collateral circulation was observed by CD31 immunohistochemical staining.Vascular endothelial growth factor(VEGF)mRNA expression was detected by quantitative polymerase chain reaction.Transcriptomic sequencing of heart tissues in the model and GDF-15 groups was performed and differentially expressed genes(DEGs)were screened.Pathway enrichment analysis of the DEGS was carried out according to the Kyoto Encyclopedia of Genes and Genomes(KEGG).Nitric oxide(NO),reactive oxygen species(ROS),and cGMP were detected using kits,and VEGF,endothelial nitric oxide synthase(eNOS)monomer,p-eNOSser1177monomer,eNOS dimer,and PKG protein were detected by Western blot.Results Left ventricular end-systolic diameter(LVEDs)and left ventricular end-diastolic diameter(LVEDd)were increased(P＜0.001),and left ventricular ejection fraction(LVEF)and the short-axis shortening rate(FS)were decreased in the Model group compared with the Sham group(P＜0.001).Myocardial cell necrosis was more severe,vascular density in the infarcted area was decreased(P＜0.05),but VEGF mRNA and protein levels were no change(P＞0.05),and levels of NO,eNOS dimer,cGMP,and PKG protein were decreased(P＜0.05),and expression levels of ROS,eNOS monomer,and p-eNOSser1177 monomer were increased(P＜0.05).LVEDs and LVEDd decreased(P＜0.05),LVEF and FS increased(P＜0.01),myocardial cell necrosis was relieved,vascular density in the infarcted area increased significantly(P＜0.0001),and VEGF mRNA levels increased(P＜0.0001),compared with the Model group.Transcriptomic sequencing identified 324 DEGs,including 230 up-regulated and 94 down-regulated genes.According to KEGG enrichment analysis,the cGMP-PKG signaling pathway showed the most significant difference in the T20 pathway.VEGF,NO,eNOS dimer,cGMP,and PKG protein levels were all increased(P＜0.05),while ROS,eNOS monomer,and p-eNOSser1177 monomer were decreased in the GDF-15 group(P＜0.05).Conclusions GDF-15 can promote collateral circulation in ischemic myocardium and improve cardiac function by inhibiting eNOS decoupling and activating the NO/cGMP/PKG pathway.