With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To analyze the levels of soluble growth stimulation expressed gene 2(sST2)and natural killer(NK)cell in traumatic brain injury(TBI)patients and their correlation.Methods A total of 147 patients with TBI admitted to Affiliated Jiangning Hospital,Nanjing Medical University from January 2023 to May 2024 were selected as the TBI group,including 55 cases of mild,57 ca-ses of moderate,and 35 cases of severe.Additionally,30healthy individuals were selected as the control group.Flow cytometry fluores-cence assay was utilized to measure the levels of cytokines interleukin(IL)-2,IL-6,tumor necrosis factor-α(TNF-α),and IL-17 A in the serum of both groups.Flow cytometry was also employed to determine the proportion of NK cell(CD45+CD3-CD19-CD56+)in the peripheral blood of the subjects.Furthermore,an immunofluorescence dry quantitative method was used to assess the levels of sST2 in the serum of the subjects,with the goal of investigating the association between serum sST2 levels and the proportion of NK cell in TBI patients.Results Compared with the control group,the expression levels of serum sST2 in TBI group were significantly increased,and the levels of cytokines IL-2,IL-6,TNF-α and IL-17 A were also significantly increased.The proportion of NK cell was significantly decreased in severe TBI patients,the differences were statistically significant(P＜0.05).Additionally,there was a negative correlation between the expression levels of serum sST2 and the proportion of NK cells in moderate and severe TBI patients(r=-0.328,P＜0.01).In contrast,no significant correlation is observed between these two parameters in patients with mild TBI(P＞0.05).Conclusion There is a correlation between the expression levels of sST2 and NK cell in moderate and severe TBI patients,whereas no significant correlation exists between sST2 expression levels and NK cells in patients with mild TBI.

BACKGROUND: Double-stranded RNA-specific adenosine deaminase 1 (ADAR1) binds to double-stranded RNA and catalyzes the deamination of adenosine (A) to inosine (I). The functional mechanism of ADAR1 in non-small cell lung cancer (NSCLC) remains incompletely understood. This study aimed to investigate the prognostic significance of ADAR1 in NSCLC and to elucidate its potential role in regulating tumor cell proliferation and migration. METHODS: Data from The Cancer Genome Atlas (TCGA) and cBioPortal were analyzed to assess the correlation between high ADAR1 expression and clinicopathological features as well as prognosis in lung cancer. We performed Western blot (WB), cell proliferation assays, Transwell invasion/migration assays, and nude mouse xenograft modeling to examine the phenotypic changes and molecular mechanisms induced by ADAR1 knockdown. Furthermore, the ADAR1 p150 overexpression model was utilized to validate the proposed mechanism. RESULTS: ADAR1 expression was significantly elevated in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues compared with adjacent non-tumor tissues (LUAD: P=3.70×10-15, LUSC: P=0.016). High ADAR1 expression was associated with poor prognosis (LUAD: P=2.03×10-2, LUSC: P=2.81×10-2) and distant metastasis (P=0.003). Gene Set Enrichment Analysis (GSEA) indicated that elevated ADAR1 was associated with mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway activation, matrix metalloproteinase-9 (MMP-9) expression, and cell adhesion. ADAR1 and MMP-9 levels showed a strongly positive correlation (P=6.45×10-34) in 10 lung cancer cell lines, highest in H1581. Knockdown of ADAR1 in H1581 cells induced a rounded cellular morphology with reduced pseudopodia. Concomitantly, it suppressed cell proliferation, invasion, migration, and in vivo tumorigenesis. It also suppressed ERK phosphorylation and downregulated cellular Finkel-Biskis-Jinkins murine osteosarcoma viral oncogene homolog (c-FOS), MMP-9, N-cadherin, and Vimentin. Conversely, ADAR1 p150 overexpression in PC9 cells enhanced ERK phosphorylation and increased c-FOS and MMP-9 expression. CONCLUSIONS High ADAR1 expression is closely associated with poor prognosis and distant metastasis in NSCLC patients. Mechanistically, ADAR1 may promote proliferation, invasion, migration, and tumorigenesis in lung cancer cells via the ERK/c-FOS/MMP-9 axis.
Humans ; Lung Neoplasms/physiopathology* ; Adenosine Deaminase/genetics* ; Matrix Metalloproteinase 9/genetics* ; Cell Proliferation ; Carcinoma, Non-Small-Cell Lung/physiopathology* ; Cell Movement ; Animals ; Mice ; RNA-Binding Proteins/genetics* ; Female ; Male ; Cell Line, Tumor ; Proto-Oncogene Proteins c-fos/genetics* ; Middle Aged ; MAP Kinase Signaling System ; Gene Expression Regulation, Neoplastic ; Mice, Nude ; Extracellular Signal-Regulated MAP Kinases/genetics*

[This corrects the article DOI: 10.1016/j.apsb.2019.01.013.].

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To analyze the levels of soluble growth stimulation expressed gene 2(sST2)and natural killer(NK)cell in traumatic brain injury(TBI)patients and their correlation.Methods A total of 147 patients with TBI admitted to Affiliated Jiangning Hospital,Nanjing Medical University from January 2023 to May 2024 were selected as the TBI group,including 55 cases of mild,57 ca-ses of moderate,and 35 cases of severe.Additionally,30healthy individuals were selected as the control group.Flow cytometry fluores-cence assay was utilized to measure the levels of cytokines interleukin(IL)-2,IL-6,tumor necrosis factor-α(TNF-α),and IL-17 A in the serum of both groups.Flow cytometry was also employed to determine the proportion of NK cell(CD45+CD3-CD19-CD56+)in the peripheral blood of the subjects.Furthermore,an immunofluorescence dry quantitative method was used to assess the levels of sST2 in the serum of the subjects,with the goal of investigating the association between serum sST2 levels and the proportion of NK cell in TBI patients.Results Compared with the control group,the expression levels of serum sST2 in TBI group were significantly increased,and the levels of cytokines IL-2,IL-6,TNF-α and IL-17 A were also significantly increased.The proportion of NK cell was significantly decreased in severe TBI patients,the differences were statistically significant(P＜0.05).Additionally,there was a negative correlation between the expression levels of serum sST2 and the proportion of NK cells in moderate and severe TBI patients(r=-0.328,P＜0.01).In contrast,no significant correlation is observed between these two parameters in patients with mild TBI(P＞0.05).Conclusion There is a correlation between the expression levels of sST2 and NK cell in moderate and severe TBI patients,whereas no significant correlation exists between sST2 expression levels and NK cells in patients with mild TBI.

Objective To assess the effectiveness of the evaluation of military physical function(EMPF)system in predicting the occurrence of military training injuries among new recruits to provide scientific guidance and methodological choice for military training.Methods A total of 527 new recruits from 5 grassroots units from July 2016 to February 2018 were selected for the study.The recruits underwent EMPF testing,and their military training injuries were monitored over a 2-year follow-up period.Those who sustained injuries during training were divided into injury group(n=163),while the remaining recruits were placed in healthy group(n=364).The predictive ability of the total EMPF score for training injuries was assessed using the receiver operating characteristic curve(ROC),and the correlation between the total EMPF score,individual test scores,and military training injuries were analyzed using binary logistic regression.Results The total EMPF score of new recruits in injury group(19.52±1.97)was significantly lower than that of healthy group(24.31±1.54)(P<0.001),which also demonstrated a high diagnostic value in predicting the risk of military training injuries,with an area under the curve(AUC)of ROC of 0.971(P<0.001).A cut-off value of 22 scores was found to have the highest accuracy in predicting future training injuries,with an odds ratio(OR)of 25.63,sensitivity of 0.939,specificity of 0.879,positive likelihood ratio of 7.76,and a post-test probability of 0.67.Binary logistic regression analysis revealed that 6 EMPF tests,including holding the ball over and leaning back,bending forward and touching the ground with the ball,lunge squat and twist,swallow balance with holding the ball afterward,vertical jump,and respiratory pattern assessment,were negatively associated with the risk of military training injuries(P<0.0001).Conclusion The EMPF system can effectively predict the risk of military training injuries,with military personnel whose total EMPF score is less than 22 being at higher risk of sustaining such injuries.

Objective:To assess the value of a model based on helicobacter pylori(Hp)status and peripheral blood levels of pepsinogen Ⅰ(PGⅠ),PGⅡ,and gastrin-17(G-17)for predicting disease progression in high-risk populations for gastric cancer.Methods:Retrospective se-lection of clinical data from 126 high-risk individuals for gastric cancer who underwent PGⅠ,PGⅡ,G-17,and C14 urea breath tests and gastro-scopy tissue biopsy at Tianjin University Jinnan Hospital from January 2023 to January 2024,Based on pathological biopsy results using gast-ric cancer tissues obtained by gastroscopy,the high-risk population for gastric cancer was assigned into normal control,precancerous lesion,and early gastric cancer groups.The diagnostic efficacies of PGⅠ,PGⅡ,G-17,C14 urea breath,and other indicators in each patient group were determined,and a predictive model was constructed.Results:The HP-positivity rate(82.35％)and PGⅡ level(22.73 ng/mL)in the early gastric cancer group were higher than those in the precancerous lesion and control groups.The PGI level(51.36 ng/mL)was lower in early gastric cancer than in precancerous lesions and control tissues.The G-17 level(5.17 pmol/L)was lower in the precancerous lesion group than in the control and early gastric cancer groups(P<0.05).Combined use of PGⅠ、PGⅡ、G-17and Hp,the area under curve(AUC)can reach 0.899,a sensitivity of 94.12％,and a specificity of 95.65％,making these factors ideal diagnostic tools for gastric cancer.According to the prediction model,the threshold for precancerous lesions was 10 points,and the critical value for early cancer was 19 points.Conclu-sions:Implementation of the C14 urea breath test combined with PGⅠ,PGⅡ,and G-17 detection in high-risk populations for gastric cancer can help monitor disease progression in high-risk populations for gastric cancer.