Objective:To explore the typology and influencing factors of nursing undergraduates'career willingness to care for terminally ill elderly patients.Methods:Using a convenience sampling method,a survey was conducted among 488 nursing undergraduates from three universities in Hunan Province between May and June 2024.Latent profile analysis(LPA)was employed to classify career willingness to care for terminally ill elderly patients,and logistic regression analysis was used to analyze factors influencing the career willingness.Results:Heterogeneity was observed in nursing undergraduates'career willingness,which was categorized into three groups:low positive attitude-low care awareness group(24.8%),high positive attitude-low care awareness group(56.7%),and high positive attitude-high care awareness group(18.5%).Logistic regression analysis revealed that gender,cohabitation with terminally ill elderly patients,only-child status,experience in caring for terminally ill patients,geriatric nursing training,and hospice care education were statistically significant factors influencing career willingness(P＜0.05).Conclusions:Nursing undergraduates'career willingness to care for terminally ill elderly patients exhibits distinct categorical characteristics.Individualized educational strategies should be developed to enhance their professional identity and career intention in this field.

BACKGROUND:Rheumatoid arthritis is a chronic autoimmune disease.Early diagnosis is crucial for preventing disease progression and for effective treatment.Therefore,it is of significance to investigate the diagnostic characteristics and immune cell infiltration of rheumatoid arthritis. OBJECTIVE:Based on the Gene Expression Omnibus(GEO)database,to screen potential diagnostic markers of rheumatoid arthritis using machine learning algorithms and to investigate the relationship between the diagnostic characteristics of rheumatoid arthritis and immune cell infiltration in this pathology. METHODS:The gene expression datasets of synovial tissues related to rheumatoid arthritis were obtained from the GEO database.The data sets were merged using a batch effect removal method.Differential expression analysis and functional correlation analysis of genes were performed using R software.Bioinformatics analysis and three machine learning algorithms were used for the extraction of disease signature genes,and key genes related to rheumatoid arthritis were screened.Furthermore,we analyzed immune cell infiltration on all differentially expressed genes to examine the inflammatory state of rheumatoid arthritis and investigate the correlation between their diagnostic characteristics and infiltrating immune cells. RESULTS AND CONCLUSION:In both rheumatoid arthritis and normal synovial tissues,we identified 179 differentially expressed genes,with 124 genes up-regulated and 55 genes down-regulated.Enrichment analysis revealed a significant correlation between rheumatoid arthritis and immune response.Three machine learning algorithms identified LRRC15 and MICB as potential biomarkers of rheumatoid arthritis.LRRC15(area under the curve=0.964,95%confidence interval:0.924-0.992)and MICB(area under the curve=0.961,95%confidence interval:0.923-0.990)demonstrated strong diagnostic performance on the validation dataset.The infiltration of 13 types of immune cells was altered,with macrophages being the most affected.In rheumatoid arthritis,the majority of proinflammatory pathways in immune cell function were activated.Immunocorrelation analysis revealed that LRRC15 and MICB had the strongest correlation with M1 macrophages.To conclude,this study identified LRRC15 and MICB as potential diagnostic markers for rheumatoid arthritis,with strong diagnostic performance and significant correlation with immune cell infiltration.Machine learning and bioinformatics analysis deepened the understanding of immune infiltration in rheumatoid arthritis and provided new ideas for the diagnosis and treatment of rheumatoid arthritis.

Objective To explore the diagnostic and prognostic relevance of genes associated with trastuzumab resistance and sensitivity in gastric cancer using machine learning algorithms.Methods The data on resistant and sensitive genes were downloaded from the GEO database and subjected to functional enrichment analysis.Intersection analysis was performed using TCGA and GEO data to identify feature genes related to gastric cancer drug-resistance.LASSO and SVM-RFE methods were used for feature gene selection.The expressions of these feature genes were detected in both test and validation groups,and their diagnostic value was analyzed using receiver operating characteristic curves.The prognostic value of SH3GL2 was assessed using online databases,and its role in patient survival was further explored.CIBERSORT algorithm was used to evaluate the relationship between SH3GL2 and immune cell infiltration in gastric cancer,and analyze its effect on immune microenvironment.Results Fifteen resistance-related genes were identified,and 12 diagnostic biomarkers related to gastric cancer were selected through machine learning,including MMP7,COCH,VCAN,SH3GL2,SYNM,KLK6,STC2,PPP1R1B,CDH3,WNT11,PMEPA1,and BCAT1.SH3GL2 showed low expression in both test and validation groups,and its high expression was associated with poorer prognosis in gastric cancer(P<0.01).SH3GL2 expression level was related to various immune cells(activated CD8+T cells,activated DC cells)and showed positive correlations with immune suppressive factors(such as TGFB1,VTCN1)and negative correlations with immune stimulatory factors(such as CD70,CD80).Conclusion The 12 selected feature genes can serve as potential diagnostic biomarkers for gastric cancer.SH3GL2 has a low expression in gastric cancer,and its high expression might shorten patient survival by inhibiting anti-tumor immunity.

Objective:To explore the typology and influencing factors of nursing undergraduates'career willingness to care for terminally ill elderly patients.Methods:Using a convenience sampling method,a survey was conducted among 488 nursing undergraduates from three universities in Hunan Province between May and June 2024.Latent profile analysis(LPA)was employed to classify career willingness to care for terminally ill elderly patients,and logistic regression analysis was used to analyze factors influencing the career willingness.Results:Heterogeneity was observed in nursing undergraduates'career willingness,which was categorized into three groups:low positive attitude-low care awareness group(24.8%),high positive attitude-low care awareness group(56.7%),and high positive attitude-high care awareness group(18.5%).Logistic regression analysis revealed that gender,cohabitation with terminally ill elderly patients,only-child status,experience in caring for terminally ill patients,geriatric nursing training,and hospice care education were statistically significant factors influencing career willingness(P＜0.05).Conclusions:Nursing undergraduates'career willingness to care for terminally ill elderly patients exhibits distinct categorical characteristics.Individualized educational strategies should be developed to enhance their professional identity and career intention in this field.

Objective To explore the diagnostic and prognostic relevance of genes associated with trastuzumab resistance and sensitivity in gastric cancer using machine learning algorithms.Methods The data on resistant and sensitive genes were downloaded from the GEO database and subjected to functional enrichment analysis.Intersection analysis was performed using TCGA and GEO data to identify feature genes related to gastric cancer drug-resistance.LASSO and SVM-RFE methods were used for feature gene selection.The expressions of these feature genes were detected in both test and validation groups,and their diagnostic value was analyzed using receiver operating characteristic curves.The prognostic value of SH3GL2 was assessed using online databases,and its role in patient survival was further explored.CIBERSORT algorithm was used to evaluate the relationship between SH3GL2 and immune cell infiltration in gastric cancer,and analyze its effect on immune microenvironment.Results Fifteen resistance-related genes were identified,and 12 diagnostic biomarkers related to gastric cancer were selected through machine learning,including MMP7,COCH,VCAN,SH3GL2,SYNM,KLK6,STC2,PPP1R1B,CDH3,WNT11,PMEPA1,and BCAT1.SH3GL2 showed low expression in both test and validation groups,and its high expression was associated with poorer prognosis in gastric cancer(P<0.01).SH3GL2 expression level was related to various immune cells(activated CD8+T cells,activated DC cells)and showed positive correlations with immune suppressive factors(such as TGFB1,VTCN1)and negative correlations with immune stimulatory factors(such as CD70,CD80).Conclusion The 12 selected feature genes can serve as potential diagnostic biomarkers for gastric cancer.SH3GL2 has a low expression in gastric cancer,and its high expression might shorten patient survival by inhibiting anti-tumor immunity.

Objective To investigate the serological and molecular characteristics of twenty blood samples carrying ABO?AW.37 allele and to analyze ABO allelic enhancement.Methods The ABO phenotype of the twenty samples was de-termined by serological methods and the genotype of 1-7 ABO exons was analyzed by Sanger sequencing.Results Sequen-cing analysis showed that all twenty samples contained a c.940A>G(p.Lys314Glu)mutation of A allele,which was defined as ABO?AW.37.When ABO?AW.37 and B alleles were inherited simultaneously in 9 cases,in forward typing anti-A anti-bodies all agglutinated and the serological phenotype was Aw B.Among the 11 cases with ABO?AW.37 and O alleles inherited simultaneously,there was no agglutination of anti-A in forward typing.For absorption and elution tests,5 cases were weakly positive and the serological phenotype was Ael,while 6 cases were negative for absorption and elution tests and the serologi-cal phenotype was O type.Conclusion Allelic enhancement occured when both ABO?AW.37 allele and B allele were in-herited simultaneously.When ABO? AW.37 was inherited simultaneously with O allele,the serological phenotype was Aelor O type and attention should be paid to blood type identification.

【Objective】 To investigate the reasonable serological detection method by analyzing the characteristics of anti-K and anti-Wr^a from a patient who received treatment with daratumumab. 【Methods】 Unexpected antibody screening and identification were performed by saline method, polybrene, cardioagglutinin, dithiothreitol (DTT) treatment, trypsin treatment and papain treatment in the patient's plasma and acid elution solution. Heat elution test was detected after absorbing patient serum with K antigen negative red blood cells. The characteristics of antibodies were analyzed and their titer was continuously detected. Cross matching was performed after excluding interference of daratumumab. 【Results】 Anti-K and anti-Wr^a were detected in saline and polybrene in the patient's plasma. The patient's elution solution contained daratumumab. DTT or trypsin treatment excluded interference of daratumumab but papain treatment did not. DTT treatment destroyed K antigen and missed the detection of IgG antibodies in the Kell system. Trypsin treatment did not affect K antigen and can detect IgG antibodies of Kell system(anti-k)in the serum of the patient treated with daratumumab. Anti K was IgM and the titer was 4 by saline method and it decreased to no agglutination in room temperature after 39 days. Anti-Wr^a was IgG and the titer by polybrene method was 4, and it decreased to 1 after 39 days. After 76 days, neither anti-K nor anti-Wr^a could be detected. Transfusions of K and Wr^a antigen negative red blood cells were safe and effective. 【Conclusion】 DTT treatment can exclude interference of daratumumab, but attention should be paid to missed detection of anti-K. To avoid interference of daratumumab and identify unexpected antibody, multiple methods such as DTT treatment, polybrene and trypsin treatment in combination are recommended.

OBJECTIVE: To explore the clinical characteristics and genetic basis of a child with autism spectrum disorder (ASD) in conjunct with congenital heart disease (CHD). METHODS: A child who was hospitalized at the Third People's Hospital of Chengdu on April 13, 2021 was selected as the study subject. Clinical data of the child were collected. Peripheral blood samples of the child and his parents were collected and subjected to whole exome sequencing (WES). A GTX genetic analysis system was used to analyze the WES data and screen candidate variants for ASD. Candidate variant was verified by Sanger sequencing and bioinformatics analysis. Real-time fluorescent quantitative PCR (qPCR) was carried out to compare the expression of mRNA of the NSD1 gene between this child and 3 healthy controls and 5 other children with ASD. RESULTS: The patient, an 8-year-old male, has manifested with ASD, mental retardation and CHD. WES analysis revealed that he has harbored a heterozygous c.3385+2T>C variant in the NSD1 gene, which may affect the function of its protein product. Sanger sequencing showed that neither of his parent has carried the same variant. By bioinformatic analysis, the variant has not been recorded in the ESP, 1000 Genomes and ExAC databases. Analysis with Mutation Taster online software indicated it to be disease causing. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was predicted to be pathogenic. By qPCR analysis, the expression level of mRNA of the NSD1 gene in this child and 5 other children with ASD was significantly lower than that of the healthy controls (P < 0.001). CONCLUSION The c.3385+2T>C variant of the NSD1 gene can significantly reduce its expression, which may predispose to ASD. Above finding has enriched the mutational spectrum the NSD1 gene.
Male ; Child ; Humans ; Autism Spectrum Disorder/genetics* ; Heart Defects, Congenital/genetics* ; Computational Biology ; Genomics ; Mutation ; RNA, Messenger/genetics* ; Histone-Lysine N-Methyltransferase/genetics*

Objective:To comprehensively evaluate the tricuspid valve, right heart anatomical characteristics and related dynamic parameters in patients with different degrees of functional tricuspid regurgitation (FTR) using four-dimensional auto tricuspid valve quantitative(4D Auto TVQ), four-dimensional auto right ventricle quantitative(4D Auto RVQ), and four-dimensional auto left atrium quantitative(4D Auto LAQ), and to investigate the structural and functional changes of the tricuspid valve and right heart in them.Methods:Sixty-three patients with FTR diagnosed by echocardiography at the First Affiliated Hospital of Guangxi Medical University from February to July 2022 were prospectively selected as the case group, including 30 patients with mild FTR and 33 patients with moderate or above FTR, and 30 healthy subjects were selected as the control group. Transthoracic echocardiography was used for two-dimensional and three-dimensional image acquisition of the heart. The tricuspid regurgitation volume, left ventricular ejection fraction (LVEF), right ventricular global strain (RVGS) were measured by 2D images, and pulmonary artery systolic pressure (PASP) were measured from the tricuspid regurgitation pressure difference. The 3D images were imported into EchoPAC 204 to obtain the tricuspid valve, right heart structure and related dynamic parameters. The annulus area (AA), annulus perimeter(AP), spherical index (SI), annulus area change fraction (AC), coaptation point height (CPH), and tenting volume (TV) were measured by 4D Auto TVQ. The right atrial maximum volume (RAVmax) and right atrial minimum volume (RAVmin) were measured by 4D Auto LAQ. Right ventricular end-diastolic volume (RVEDV), right ventricular end-systolic volume (RVESV), right ventricular fractional area change (RVFAC) and tricuspid annular plane systolic excursion (TAPSE) were measured by 4D Auto RVQ. After standardizing the dimension parameters with body surface area (BSA), the differences in the above parameters were compared between the three groups, the correlation between regurgitant volume and each parameter was compared by correlation analysis, and the independent factors of increased tricuspid regurgitant volume were investigated by univariate and multivariate linear regression analysis.Results:There were statistically significant differences in PASP, AA/BSA, AP/BSA, AC, TV, RAVmax/BSA, RAVmin/BSA, RVFAC, RVGS, and TAPSE between the three groups (all P<0.05). There were statistically significant differences in LVEF, CPH, RVEDV/BSA, and RVESV/BSA in the moderate and above FTR group compared with the control and mild FTR groups (all P<0.05). Correlation analysis showed that RAVmin was the most highly correlated with tricuspid regurgitant volume ( r=0.875, P<0.001) and TV and end-systolic annulus area(ESAA) were highly correlated with tricuspid regurgitant volume ( r=0.747, 0.683; both P<0.001) in patients with FTR. Multifactorial linear regression showed that RAVmin, TV and regurgitant volume were independently positively correlated (β=0.721, 0.205; both P<0.05). Conclusions:The four quantification technique can provide valid structural and functional information by quantifying the tricuspid valve as well as the right heart in patients with FTR, and RAVmin and TV are independent correlates of increased tricuspid regurgitant volume.

OBJECTIVE: To explore the molecular reasons of weak expression of B antigen on the red cell. METHODS: Serological test for blood group was carried out, including red cell and plasma grouping, and anti-A1 and anti-H testing, and confirming weak A or B antigens by adsorption and elution. Exons 1-7 were sequenced directly, and one of them was cloned and sequenced. RESULTS: All of the 23 samples showed the weak B antigen by serological method. The alleles of the subgroups were identified by DNA sequencing, including 2 Bel subgroup, 4 B3 subgroup, 14 Bw subgroup, 2 CisAB subgroup and a novel allele. The novel allele showed a nucleotide substitution 662G>A in the exon 7, and the sequence was submitted to Blood Group Antigen Gene Mutation Database, and the novel allele was named Bel10. CONCLUSION Nucleotide substitution in exon results in blood subgroup, which showed that the antigens were weakened, and Bw phenotype was the most frequently subgroup.
ABO Blood-Group System/genetics* ; Alleles ; Exons ; Genotype ; Humans ; Nucleotides ; Phenotype