Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

In recent years,artificial intelligence(AI)has been introduced into the field of mental health interventions,which not only brings innovation and progress,but also causes a series of ethical problems.This paper systematically analyzes the triple ethical challenges of AI applying to mental health interventions.Firstly,the current ethical frameworks for AI-based mental health interventions primarily expand upon medical ethics principles,emphasizing benefit maximization,risk minimization,and patient autonomy.However,these frameworks face challenges such as insufficient standardization and difficulties in dynamically capturing and regulating ethical risks arising from rapid technological iteration.Secondly,ethical challenges related to data governance in AI-based mental health applications include data privacy issues and decision fairness concerns stemming from algorithmic bias.Finally,AI as a proxy resource risks eroding user autonomy and fostering interpersonal alienation,primarily through exerting influence beyond comprehension to undermine autonomous decision-making capabilities.Overreliance and blind trust in AI systems during usage may weaken social motivation,thereby threatening autonomy and psychological integrity.

Purpose Discover new prostate cancer-related single nucleotide variants.Methods Tissue wax blocks from 21 prostate cancer patients who underwent radical surgery and had relatively complete clinical data were collected for somatic mutation detection to analyze new mutated genes associated with prostate cancer.The levels of cor-responding proteins in the urine of prostate cancer patients were tested according to the results of the selected genes.Results All 21 prostate cancer patients showed obvious somatic mutations,and the mutation types were dominated by C＞T and G＞A.The number of somatic mutations was 521,of which 27 genes had high mutation proportions(≥2 ca-ses),including ZSWIM6(5/21),FOXA1(4/21),SPTA1(2/21),FAM47C(2/21),FLG2(2/21),PRSS3(2/21),TP53(2/21),FLG(2/21),UBR4(2/21),and the mutations occurring in ZSWIM6 were all deletion muta-tions,and the mutations occurring in FOXA1 were missense mutations,deletion mutations,and deletion insertion mu-tations.The urinary levels of UPF1,SPTA1,and IDH1 proteins of the 10 prostate cancer patients were significantly different than those of the healthy controls.Correlation analysis showed that FOXA1 was positively correlated with UBR4(r=0.669,P=0.001),SPTA1 was positively correlated with FLG2(r=1.000,P＜0.001),FAM47C was positively correlated with PRSS3(r=1.000,P＜0.001),and there was a significant positive correlation between TP53 and FLG(r=1.000,P＜0.001).ZSWIM6 and FOXA1 were not correlated with biochemical recurrence.SP-TA1 mutation affected progression-free survival(PFS)[(66.0±0)months vs(30.0±7.8)months,P=0.008].FAM47C was positively correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].ZNF676 was correlated with PFS[(66.0±0)months vs(26.0±5.0)months,P=0.008].FLG2 was correlated with PFS[(66.0±0)months vs(30.0±7.8)months,P=0.008].PRSS3 was correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].Conclusion All 21 prostate cancer patients harbored somatic mutations,including ZSWIM6(5/21)and FOXA1(4/21)mutations.SPTA1,FAM47C,ZNF676,FLG2,and PRSS3 may be associated with prognosis.

Purpose Discover new prostate cancer-related single nucleotide variants.Methods Tissue wax blocks from 21 prostate cancer patients who underwent radical surgery and had relatively complete clinical data were collected for somatic mutation detection to analyze new mutated genes associated with prostate cancer.The levels of cor-responding proteins in the urine of prostate cancer patients were tested according to the results of the selected genes.Results All 21 prostate cancer patients showed obvious somatic mutations,and the mutation types were dominated by C＞T and G＞A.The number of somatic mutations was 521,of which 27 genes had high mutation proportions(≥2 ca-ses),including ZSWIM6(5/21),FOXA1(4/21),SPTA1(2/21),FAM47C(2/21),FLG2(2/21),PRSS3(2/21),TP53(2/21),FLG(2/21),UBR4(2/21),and the mutations occurring in ZSWIM6 were all deletion muta-tions,and the mutations occurring in FOXA1 were missense mutations,deletion mutations,and deletion insertion mu-tations.The urinary levels of UPF1,SPTA1,and IDH1 proteins of the 10 prostate cancer patients were significantly different than those of the healthy controls.Correlation analysis showed that FOXA1 was positively correlated with UBR4(r=0.669,P=0.001),SPTA1 was positively correlated with FLG2(r=1.000,P＜0.001),FAM47C was positively correlated with PRSS3(r=1.000,P＜0.001),and there was a significant positive correlation between TP53 and FLG(r=1.000,P＜0.001).ZSWIM6 and FOXA1 were not correlated with biochemical recurrence.SP-TA1 mutation affected progression-free survival(PFS)[(66.0±0)months vs(30.0±7.8)months,P=0.008].FAM47C was positively correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].ZNF676 was correlated with PFS[(66.0±0)months vs(26.0±5.0)months,P=0.008].FLG2 was correlated with PFS[(66.0±0)months vs(30.0±7.8)months,P=0.008].PRSS3 was correlated with PFS[(66.0±0)months vs(19.0±0)months,P＜0.001].Conclusion All 21 prostate cancer patients harbored somatic mutations,including ZSWIM6(5/21)and FOXA1(4/21)mutations.SPTA1,FAM47C,ZNF676,FLG2,and PRSS3 may be associated with prognosis.

Objective:To investigate the recognition of the post competency index system among rural general practice assistant physicians and its influencing factors.Methods:This study was a cross-sectional survey. A questionnaire survey on the recognition of post competency index system was conducted from October 2020 to September 2021 among rural general practice assistant physicians from 10 provinces/municipalities selected by stratified cluster sampling method. The recognition of rural general practice assistant physicians at all levels of indexs and the factors influencing recognition were analyzed.Results:A total of 1 123 questionnaires were distributed and 1 024 valid ones were collected with a recovery rate of 91.18%. Of the 1 024 respondents, 529 were male(51.7%) and 435 were aged 40-49 years(42.5%), which was the highest proportion by age group. The average overall recognition score of the index system was 4.41, and the scores of the primary indexes were 4.32-4.45. Three primary indexes had the highest recognition scores: professional competence, basic health care services, and interpersonal communication and teamwork. The recognition scores on the second level index were 4.18-4.61, and the proportion of recognition scores greater than 4 was over 80%. There were significant differences in the recognition scores of the index system among assistant physicians with different working years, educational background, professional title and work unit ( F/H=6.41, 14.83, 12.45, 7.53, P<0.01). Educational background(associate degree: B=0.091, P=0.015; bachelor degree and above: B=0.196, P<0.001) and professional title(intermediate professional title and above: B=-0.234, P<0.001) were the independent factors influencing the recognition degree of the index system for rural general practice assistant physicians. Conclusions:The post competency index system is generally recognized by rural general practice assistant physician, and academic qualifications and professional title status may influence its recognition.

Objective:To evaluate the application feasibility of the post competency index system of rural general practice assistant physicians, and to analyze and compare the post competency of rural general practice assistant physicians with different characteristics through a survey among rural general practice assistant physicians in China.Methods:This study was a cross-sectional study. A questionnaire survey was conducted among rural general practice assistant physicians in 10 provinces/municipalities selected by stratified cluster sampling method from October 2020 to September 2021. The post competency scores were self-evaluated based on the post competency index system of rural general practice assistant physicians. The results of the survey were analyzed and the application feasibility of the index system was evaluated.Results:A total of 1 123 questionnaires were distributed and 1 024 valid questionnaires were returned with a recovery rate of 91.2%. Of the 1 024 respondents, 529 were males (51.7%), 435 were aged 40-49 years (42.5%), 434 had a secondary school education or less (42.4%), and 531 were junior practitioners (51.9%). The Cronbach′s α coefficient of the overall questionnaire was 0.987, and the Cronbach′s α coefficient of the first level index ranged from 0.897 to 0.974. The cumulative variance contribution rate of exploratory factor analysis was 72.012%. The confirmatory factor analysis showed χ2/ df=3.926, RMSEA=0.076, CFI=0.858, IFI=0.859, indicating that the model fit was basically good. The average self-evaluation scores of the first level index ranged from 3.95 to 4.25, and the average self-evaluation scores of the second level index ranged from 3.74 to 4.36. There were significant differences in self-evaluation scores of post competency among rural general practice assistant physicians with different working years, professional titles, working units and economic regions( F=4.67, 10.54, 22.16 and 20.90,all P<0.05). People with low self-evaluation scores of post competency had the following characteristics: working 10-19 years, intermediate or above titles, working in community health service centers, located in the eastern region.People with high self-evaluation scores of post competency had the following characteristics: primary professional title, working in the village clinic. Conclusion:The competency index system of rural general practice assistant physicians has good application feasibility,and it can be used to evaluate post competency for the education and training of rural general practice assistant physicians.

Objective:To survey the competency characteristics of rural general practitioners using behavioral event interview.Methods:The competency characteristics of rural general practitioners were extracted by literature research method, and the behavior event interviews were conducted with 18 rural general practitioners nationwide from January to April 2019. According to the interview results, the items were modified and refined. On this basis, the benchmark competencies and excellent competencies of rural general practitioners were extracted.Results:A total of 45 885-second audio recordings and 174 523-word transcripts were obtained from the interviews. Eight identification competencies and 10 benchmark competencies were extracted. Identification competencies included "professionalism, altruism and dedication, love and compassion, visiting a patient at home, establishing good relationships, achievement-oriented, having expertise, and mastering community population dynamics and health status actively". Benchmark competencies included "diagnosis and treatment of common diseases, basic medical skills, learning consciousness and ability, solving medical problems with traditional Chinese medicine, health care for focal groups, rational administration of drug, referral services, managing chronic non communicable diseases, understanding health care system and related policies, and emergency treatment ability".Conclusions:This study preliminarily obtains the identification competencies and benchmark competencies of rural general practitioners. Managers can improve the service quality of rural general practitioners according to these elements.

Objective:To construct a post competency index system for rural general practice assistant physicians.Methods:On the basis of previous literature research and behavioral event interviews, the questionnaire of Delphi consultation was designed. Two rounds of Delphi expert consultation were conducted from October 2019 to January 2020 to develop an index system of post competency for rural general practice assistant physicians, and the analytic hierarchy process methods was used to calculate the weight of each index.Results:A total of 26 experts were included, with an average age of (48.7±8.6) years and an average working seniority of (22.8±8.8) years. After 2 rounds of consultation, the competency index system was developed, including 6 first level items and 60 seconds level items. The positive coefficient of experts in the 2 rounds was 87% and 100%, respectively; the expert authority coefficient was 0.7-1.0; the coordination coefficient was 0.312 and 0.241, respectively ( P<0.001). According to the order of weight, the first level items were basic medical and health services (0.311 1), basic public health services (0.196 0), medical knowledge and lifelong learning (0.196 0), interpersonal communication and team cooperation (0.138 6), professional quality (0.102 8), information utilization and management ability (0.055 5). The top 2 secondary indexes were clinical expertise (0.079 2), learning awareness and ability (0.055 3). The last 2 secondary indexes were achievement orientation (0.001 6) and inductive thinking (0.002 0). Conclusion:A post competency index system for rural general practice assistant physicians has been preliminary constructed in this study, which may provide reference for the selection, training and assessment of relevant medical workers.

Objective:To explore the competency for the assistant general practitioners in China to provide theoretical support for the construction of the post competence model of assistant general practitioners and training and evaluation of assistant general practitioners.Methods:During January 22 to June 18, 2019, Using snowball sampling method and behavioral event interviews, 23 general practitioners and assistant general practitioners were interviewed in China, including 14 general practitioners in the superior performance group and 9 assistant general practitioners in the average performance group. The interview contents were coded and analyzed, and the statistical methods of t test and rank sum test of two independent samples were used to screen competency characteristics and construct the competence model of assistant general practitioners.Results:The total classification consistency and the total coding reliability coefficient was respectively 0.79, 0.87. 59 competency characteristics of assistant general practitioners were obtained including 3 differentiated competency characteristics "Understanding the medical and health system and related policies", "Critical thinking skills" and "General practitioner clinical thinking" and 10 baseline competency characteristics. There was no statistically significant difference between the average performance group and the superior performance group in the total frequency of competency [(29.4±12.7) times to (23.4±7.0) times, t=1.27, P=0.22]. Conclusion:The preliminary competency characteristics of assistant general practitioners have good reliability and can provide references for further exploration of the competency model.

OBJECTIVE: To evaluate the association of GRIK2 and NLGN1 with autism spectrum disorder in a Chinese population. METHODS: We performed spatio-temporal expression analysis of GRIK2 and NLGN1 in the developing prefrontal cortex, and examined the expression of the genes in ASD cases and healthy controls using the GSE38322 data set. Following, we performed a case-control study in a Chinese population. RESULTS: The analysis using the publicly available expression data showed that GRIK2 and NLGN1 may have a role in the development of human brain and contribute to the risk of ASD. Later genetic analysis in the Chinese population showed that the GRIK2 rs6922753 for the T allele, TC genotype and dominant model played a significant protective role in ASD susceptibility (respectively: OR=0.840, p=0.023; OR=0.802, p=0.038; OR=0.791, p=0.020). The NLGN1 rs9855544 for the G allele and GG genotype played a significant protective role in ASD susceptibility (respectively: OR=0.844, p=0.019; OR=0.717, p=0.022). After adjusting p values, the statistical significance was lost (p>0.05). CONCLUSION: Our results suggested that GRIK2 rs6922753 and NLGN1 rs9855544 might not confer susceptibility to ASD in the Chinese population.
Alleles ; Asian Continental Ancestry Group ; Autism Spectrum Disorder ; Autistic Disorder ; Brain ; Case-Control Studies ; Dataset ; Genotype ; Glutamic Acid ; Humans ; Prefrontal Cortex ; Receptors, Ionotropic Glutamate