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.

Objective:To analyze the molecular epidemiological characteristics of norovirus (NoV) outbreaks in Qingdao.Methods:Anus swab specimens were collected during NoV outbreaks from 2016 to 2020 and detected by real-time RT-PCR. Full length of RNA-dependent RNA polymerase (RdRp) and VP1 gene were amplified by RT-PCR for sequencing, evolutionary analysis, and homology modeling.Results:A total of 65 NoV outbreaks were reported, with 59 outbreaks occurring in kindergartens and primary/secondary schools, showing a double peak epidemic pattern, with peaks occurring from March to May and from October to December. A GⅡ.P16 outbreak in Qingdao first appeared in March 2017 and became the predominant strains from 2017 to 2020(67.9%, 38/56), including two genotypes: GⅡ.2[P16] (97.4%, 37/38) and GⅡ.4 Sydney[P16] (2.6%, 1/38). The GⅡ.2[P16] strains isolated were closely related to the 2010-2012 GⅡ.2[P16] strains, from whichi they probably evolved. The GⅡ.2[P16] Qingdao strains shared five common substitutions, namely D173E (motif F), V175I (motif F), S293T, K357Q (motif D), and T360A (motif D). The RdRp nucleotide consistency between GⅡ.2[P16] and GⅡ.4 Sydney[P16] was greater than 95%, and there were mainly four amino acid differences, namely K54R, V125A, A312T, and K457R.The evolutionary variation of GⅡ.2[P16] VP1 was minimal, with only a few amino acid substitutions taking place. The main functional variations of GⅡ.4 Sydney[P16] VP1 included R297H (epitope A), D310N (NERK motif), D372N (epitope A), and R373H (positive selection site).Conclusions:GⅡ.P16 NoV is the predominant epidemic strain of ad norovirus outbreaks in Qingdao from 2016 to 2020, and continuous monitoring of its epidemic trend and in-depth study of its evolutionary mechanism are necessary.

BACKGROUND: Several studies have demonstrated the occurrence of secondary tumors as a rare but significant complication of chimeric antigen receptor T (CAR-T) cell therapy, underscoring the need for a detailed investigation. Given the limited variety of secondary tumor types reported to date, a comprehensive characterization of the various secondary tumors arising after CAR-T therapy is essential to understand the associated risks and to define the role of the immune microenvironment in malignant transformation. This study aims to characterize the immune microenvironment of a newly identified secondary tumor post-CAR-T therapy, to clarify its pathogenesis and potential therapeutic targets. METHODS: In this study, the bone marrow (BM) samples were collected by aspiration from the primary and secondary tumors before and after CD19 CAR-T treatment. The CD45 + BM cells were enriched with human CD45 microbeads. The CD45 + cells were then sent for 10× genomics single-cell RNA sequencing (scRNA-seq) to identify cell populations. The Cell Ranger pipeline and CellChat were used for detailed analysis. RESULTS: In this study, a rare type of secondary chronic myelomonocytic leukemia (CMML) were reported in a patient with diffuse large B-cell lymphoma (DLBCL) who had previously received CD19 CAR-T therapy. The scRNA-seq analysis revealed increased inflammatory cytokines, chemokines, and an immunosuppressive state of monocytes/macrophages, which may impair cytotoxic activity in both T and natural killer (NK) cells in secondary CMML before treatment. In contrast, their cytotoxicity was restored in secondary CMML after treatment. CONCLUSIONS This finding delineates a previously unrecognized type of secondary tumor, CMML, after CAR-T therapy and provide a framework for defining the immune microenvironment of secondary tumor occurrence after CAR-T therapy. In addition, the results provide a rationale for targeting macrophages to improve treatment strategies for CMML treatment.
Humans ; Lymphoma, Large B-Cell, Diffuse/therapy* ; Tumor Microenvironment/genetics* ; Antigens, CD19/metabolism* ; Leukemia, Myelomonocytic, Chronic/genetics* ; Immunotherapy, Adoptive/adverse effects* ; Male ; Single-Cell Analysis/methods* ; Female ; Sequence Analysis, RNA/methods* ; Receptors, Chimeric Antigen ; Middle Aged

Objective To construct a predictive model for patients with verte-brobasilar dolichoectasia(VBD)complicated by posterior circulation acute cerebral infarction(ACI)based on the characteristics of verte-brobasilar artery magnetic resonance vascular wall imaging(MR-VWI),thereby providing a reference for clinical prevention.Methods A total of 102 patients with VBD complicated by posterior circulation ACI who were admitted to our hospital between March 2016 and January 2023 were selected as the concurrent group.An addi-tional 102 patients with VBD without concurrent posterior circulation ACI were selected as the non-concurrent group at a 1∶1 ratio.The MR-VWI characteristics(basilar artery[BA]diameter,BA length,vertebral artery[VA]intracranial segment length,BA deviation grade,and BA bifurcation height grade)and clinical data of the two groups were compared,and the factors influencing posterior circulation ACI in patients with VBD were analyzed.Based on the MR-VWI features and related influencing factors,a nomogram prediction model of pos-terior circulation ACI in patients with VBD was constructed,and the clinical significance of the nomogram prediction model was evaluated using receiver operating characteristic(ROC)and calibration curves.Results A significant difference were observed in the D-dimer levels between the two groups(P＜0.05).BA diameter,BA length,and VA intracranial length were greater in the concurrent group than in the non-concurrent group.The proportion of BA bifurcation height grade ≥ 2 and BA deviation grade≥2 in the concurrent group was higher than that in the non-concurrent group(P＜0.05).BA diameter,BA length,BA bifurcation height classification,BA deviation classi-fication,and D-dimer level were all independent risk factors for posterior circulation ACI in patients with VBD(P＜0.05).The area under the curve of the posterior circulation ACI predicted using the nomogram model was 0.900(95％CI:0.858-0.943),and good calibration was noted.Conclusion BA diameter,BA length,BA bifurcation height classification,BA offset classification,and D-dimer level were inde-pendent influencing factors of posterior circulation ACI in patients with VBD.Based on these factors,a nomogram prediction model was constructed with high prediction efficiency and good calibration.

Objective To explore the predictive value of MRI parameters of carotid artery plaque combined with low density lipoprotein cholesterol/high density lipoprotein cholesterol(LDL-C/HDL-C)ratio for predicting ischemic stroke in young patients with carotid atherosclerosis.Methods Totally 125 young patients with carotid atherosclerosis were prospectively included and divided into stroke group and non-stroke group based on whether ischemic stroke occurred within 3 months.Clinical data,laboratory indicators and carotid plaque-related MRI parameters were compared between groups.Based on carotid plaque-related MRI parameters being statistically different between groups,combined model 1 was constructed using multivariable logistic regression analysis,while combined model 2 was constructed combined with LDL-C/HDL-C ratio.The efficacy of each parameter and model for predicting ischemic stroke in young adults was analyzed.Results There were 48 cases in stroke group and 77 cases in non-stroke group.The levels of glycosylated hemoglobin,LDL-C,LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index and plaque enhancement rate in stroke group were all higher than those in non-stroke group(all P＜0.05).The area under the curve(AUC)of LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index,plaque enhancement rate,combined model 1 and 2 for predicting ischemic stroke in young adults was 0.816,0.757,0.768,0.805,0.883 and 0.936,respectively,of combined model 1 was higher than those of single parameter(all P＜0.05),while of combined model 2 was higher than that of combined model 1(Z=2.336,P=0.020).Conclusion MRI parameters of carotid artery plaque combined with LDL-C/HDL-C ratio could effectively predict ischemic stroke in young patients with carotid atherosclerosis.

Objective To establish a risk factor model for intracranial artery stenosis in young patients with acute ischemic stroke(AIS)based on high-resolution magnetic resonance vascular wall imaging(HR-VWI).Methods Young patients with AIS(n=290)treated at Hengshui People's Hospital between January 2021 and January 2023 were retrospectively analyzed and randomly divided into a modeling set(203 cases)and a validation set(n=87)at a ratio of 7∶3.Patients in the modeling set were divided into the stenosis and non-ste-nosis groups according to whether they had intracranial artery stenosis.Multivariate logistic regression was used to analyze the clinical data and HR-VWI characteristics of the patients in the modeling set to screen for factors influencing intracranial artery stenosis in young patients with AIS.R software was used to construct and verify the risk factor model.Results Among the 290 patients,88 had intracranial artery stenosis(30.34％).The proportions of low-density lipoprotein cholesterol(LDL-C),plaque load,smoking history,hypertension,and eccentric plaques were higher in the stenosis group than in the non-stenosis group(P＜0.05),and the minimum lumen area and remode-ling index were lower in the stenosis group than in the non-stenosis group(P＜0.05).Multivariate logistic regression analysis showed that smoking history,hypertension,LDL-C level,plaque load,plaque morphology,and remodeling index were all factors influencing intracra-nial artery stenosis in young patients with AIS(P＜0.05).Based on the above risk factors,R was used to build a nomogram early warning model.The ROC results showed that the AUC of the nomogram model for predicting intracranial artery stenosis in the modelling and vali-dation sets were 0.872(95％CI:0.815-0.902)and 0.850(95％CI:0.789-0.891),respectively.The Hosmer-Lemeshow test results of the modeling and validation sets were x2=0.589,P=0.571 and x2=0.602,P=0.558,respectively.The calibration curves of the two groups were consistent with the standard curves.Conclusion The risk factor model for intracranial artery stenosis in young patients built in this study based on HR-VWI features exhibits good predictive efficacy,providing a new method for clinical prevention and treatment.

Objective To construct a predictive model for patients with verte-brobasilar dolichoectasia(VBD)complicated by posterior circulation acute cerebral infarction(ACI)based on the characteristics of verte-brobasilar artery magnetic resonance vascular wall imaging(MR-VWI),thereby providing a reference for clinical prevention.Methods A total of 102 patients with VBD complicated by posterior circulation ACI who were admitted to our hospital between March 2016 and January 2023 were selected as the concurrent group.An addi-tional 102 patients with VBD without concurrent posterior circulation ACI were selected as the non-concurrent group at a 1∶1 ratio.The MR-VWI characteristics(basilar artery[BA]diameter,BA length,vertebral artery[VA]intracranial segment length,BA deviation grade,and BA bifurcation height grade)and clinical data of the two groups were compared,and the factors influencing posterior circulation ACI in patients with VBD were analyzed.Based on the MR-VWI features and related influencing factors,a nomogram prediction model of pos-terior circulation ACI in patients with VBD was constructed,and the clinical significance of the nomogram prediction model was evaluated using receiver operating characteristic(ROC)and calibration curves.Results A significant difference were observed in the D-dimer levels between the two groups(P＜0.05).BA diameter,BA length,and VA intracranial length were greater in the concurrent group than in the non-concurrent group.The proportion of BA bifurcation height grade ≥ 2 and BA deviation grade≥2 in the concurrent group was higher than that in the non-concurrent group(P＜0.05).BA diameter,BA length,BA bifurcation height classification,BA deviation classi-fication,and D-dimer level were all independent risk factors for posterior circulation ACI in patients with VBD(P＜0.05).The area under the curve of the posterior circulation ACI predicted using the nomogram model was 0.900(95％CI:0.858-0.943),and good calibration was noted.Conclusion BA diameter,BA length,BA bifurcation height classification,BA offset classification,and D-dimer level were inde-pendent influencing factors of posterior circulation ACI in patients with VBD.Based on these factors,a nomogram prediction model was constructed with high prediction efficiency and good calibration.

Objective To explore the predictive value of MRI parameters of carotid artery plaque combined with low density lipoprotein cholesterol/high density lipoprotein cholesterol(LDL-C/HDL-C)ratio for predicting ischemic stroke in young patients with carotid atherosclerosis.Methods Totally 125 young patients with carotid atherosclerosis were prospectively included and divided into stroke group and non-stroke group based on whether ischemic stroke occurred within 3 months.Clinical data,laboratory indicators and carotid plaque-related MRI parameters were compared between groups.Based on carotid plaque-related MRI parameters being statistically different between groups,combined model 1 was constructed using multivariable logistic regression analysis,while combined model 2 was constructed combined with LDL-C/HDL-C ratio.The efficacy of each parameter and model for predicting ischemic stroke in young adults was analyzed.Results There were 48 cases in stroke group and 77 cases in non-stroke group.The levels of glycosylated hemoglobin,LDL-C,LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index and plaque enhancement rate in stroke group were all higher than those in non-stroke group(all P＜0.05).The area under the curve(AUC)of LDL-C/HDL-C ratio,carotid artery stenosis rate,plaque eccentricity index,plaque enhancement rate,combined model 1 and 2 for predicting ischemic stroke in young adults was 0.816,0.757,0.768,0.805,0.883 and 0.936,respectively,of combined model 1 was higher than those of single parameter(all P＜0.05),while of combined model 2 was higher than that of combined model 1(Z=2.336,P=0.020).Conclusion MRI parameters of carotid artery plaque combined with LDL-C/HDL-C ratio could effectively predict ischemic stroke in young patients with carotid atherosclerosis.

Objective To establish a risk factor model for intracranial artery stenosis in young patients with acute ischemic stroke(AIS)based on high-resolution magnetic resonance vascular wall imaging(HR-VWI).Methods Young patients with AIS(n=290)treated at Hengshui People's Hospital between January 2021 and January 2023 were retrospectively analyzed and randomly divided into a modeling set(203 cases)and a validation set(n=87)at a ratio of 7∶3.Patients in the modeling set were divided into the stenosis and non-ste-nosis groups according to whether they had intracranial artery stenosis.Multivariate logistic regression was used to analyze the clinical data and HR-VWI characteristics of the patients in the modeling set to screen for factors influencing intracranial artery stenosis in young patients with AIS.R software was used to construct and verify the risk factor model.Results Among the 290 patients,88 had intracranial artery stenosis(30.34％).The proportions of low-density lipoprotein cholesterol(LDL-C),plaque load,smoking history,hypertension,and eccentric plaques were higher in the stenosis group than in the non-stenosis group(P＜0.05),and the minimum lumen area and remode-ling index were lower in the stenosis group than in the non-stenosis group(P＜0.05).Multivariate logistic regression analysis showed that smoking history,hypertension,LDL-C level,plaque load,plaque morphology,and remodeling index were all factors influencing intracra-nial artery stenosis in young patients with AIS(P＜0.05).Based on the above risk factors,R was used to build a nomogram early warning model.The ROC results showed that the AUC of the nomogram model for predicting intracranial artery stenosis in the modelling and vali-dation sets were 0.872(95％CI:0.815-0.902)and 0.850(95％CI:0.789-0.891),respectively.The Hosmer-Lemeshow test results of the modeling and validation sets were x2=0.589,P=0.571 and x2=0.602,P=0.558,respectively.The calibration curves of the two groups were consistent with the standard curves.Conclusion The risk factor model for intracranial artery stenosis in young patients built in this study based on HR-VWI features exhibits good predictive efficacy,providing a new method for clinical prevention and treatment.