ObjectiveA mouse model of vaccinia virus Tiantan strain (VTT)-induced encephalopathy was developed using AG6 mice. MethodsVTT was amplified by infecting Vero cells at a multiplicity of infection (MOI) of 0.01, followed by concentration and titration. After 72 h of incubation, virus-containing cells were collected and subjected to concentration. The concentrated viral suspension was serially diluted (10-fold dilutions) and added to 6-well plates containing confluent Vero cell monolayers for plaque assay. The number of plaques formed in each well was counted, and the virus titer was calculated based on the dilution factor. Fourteen 5-6-week-old AG6 mice (half male and half female, housed separately by sex) were randomly divided into a control group (n=3, PBS), a low-dose group (n=6, 1×10⁵ PFU), and a high-dose group (n=5, 5×10⁵ PFU). The mice were anesthetized by isoflurane inhalation and then infected via intranasal instillation. The mental state of the mice in each group was observed daily, and the body weight and mortality were recorded. On day 13 post-infection, 2% Evans Blue (4 mL/kg body weight) was administered via tail vein injection to assess blood-brain barrier (BBB) disruption. Subsequently, brain tissue samples were collected for immunofluorescence analysis to evaluate the activation of astrocytes and microglia. ResultsThe titer of purified VTT was 1×10⁷ PFU/mL. Compared with the control group, mice in the low-dose group showed no significant change in body weight, and no lethality was observed. In contrast, mice in the high-dose group exhibited significant weight loss starting on day 5 post-infection (P<0.05), accompanied by lethality. On day 13 post-infection, no Evans Blue extravasation was detected in the brain tissues of the low-dose group, while the olfactory bulb region of the high-dose group displayed distinct blue staining, indicating disruption of the BBB. Immunofluorescence analysis revealed no significant proliferation of astrocytes and microglia in the olfactory bulb region of the low-dose group on day 13 post-infection. In contrast, marked activation of glial cells was observable in the high-dose group. ConclusionAn animal model of VTT-induced encephalopathy in AG6 mice is successfully established, characterized by BBB disruption and reactive gliosis specifically localized to the olfactory bulb region, manifested as astrocytic and microglial proliferation.

Objective: To explore the impact of adverse childhood experiences (ACEs) on health risk behaviors (HRBs) among college students and the mediating role of psychological symptoms, so as to provide a basis for developing intervention strategies. Methods: From March to April 2023, a convenience cluster sample of 1 801 students from 12 universities in Nanning, Liuzhou, Guilin, Wuzhou of Guangxi completed an online survey. A self designed questionnaire, Adverse Childhood Experiences-International Questionnaire (ACE-IQ) and Symptom Checklist-90 (SCL-90) were used for evaluation tools. Binary Logistic regression, structural equation modeling (SEM) and Bootstrap methods were used to analyze the associations and mediating effects. Results: Overall, 71.2% of college students experienced at least one type of ACE, with emotional neglect (40.3%) and emotional abuse ( 25.2 %) having the highest detection rates. The top three HRBs were unhealthy diet (77.8%), physical inactivity (54.1%), and smoking/alcohol use (18.5%). Logistic regression showed that poor family functioning, abuse, and extra familial violence were each associated with an increased risk of smoking/alcohol use ( OR =1.14, 1.11, 1.18) and deliberate self harm ( OR =1.26, 1.19,1.30) (all P <0.05). Experience of abuse increased the risk of high risk sexual behavior and family dysfunction increaded the risk of physical inactivity, respectively ( OR = 1.07 , 1.04, both P <0.05). Mediation analysis revealed that anxiety ( β =0.20) and depression ( β = 0.09 ) partially mediated the pathway from poor family functioning to deliberate self harm; paranoia ( β =0.02) partially mediated the pathway from abuse to high risk sexual behavior; and obsessive-compulsive symptoms ( β =0.26) and depression ( β =0.10) partially mediated the pathway from extra familial violence to deliberate self harm (all P <0.05). Conclusion Psychological symptoms play a mediating role in the association between ACEs and HRBs, and mental health interventions may reduce the risk of HRBs among college students.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective To address the need for rapid review of automated organ-at-risk (OAR) contouring for head-and-neck cancer in online adaptive radiotherapy, this study used dosimetric indices as the reference standard to evaluate the suitability of geometric similarity metrics and to develop a rapid screening model that balances the risk of missed errors with review efficiency. Methods This retrospective study included 29 patients with head-and-neck radiotherapy, yielding 243 pairs of OAR contours (auto-generated vs. manual). Geometric similarity metrics, including the Dice similarity coefficient (Dice), the 95th percentile Hausdorff distance (HD95), and the maximum Hausdorff distance (HD100), were computed between the two contour sets. Using the dose distributions from clinical treatment plans, dosimetric differences between the two contour sets were calculated for key indices, including mean dose (D_mean) and maximum dose (D_max). Correlations between geometric metrics and dosimetric differences were analyzed. Dosimetric discrepancy events were defined as Y_3Gy using a threshold of 3 Gy. Within a univariable logistic regression triage framework, each geometric metric was used as an independent variable to estimate the probability of Y_3Gy. Discriminative performance was assessed using receiver operating characteristic (ROC) curves and precision-recall (PR) curves, with the area under the curve (AUC) including ROC-AUC and PR-AUC. Practical operating thresholds were determined via threshold sweeping. Results Geometric similarity metrics showed weak-to-moderate correlations with dosimetric differences; compared with maximum dose, correlations with mean dose differences were more consistent. Among the evaluated metrics, HD95 achieved the best classification performance for Y_3Gy. Threshold sweeping suggested that an HD95 threshold in the range of 4-9 mm can balance the risk of missed discrepancies with the efficiency of automated contour quality assurance (QA). Conclusion Several geometric similarity metrics demonstrated only weak-to-moderate associations with dosimetric differences. For head-and-neck OAR contour QA in this study, HD95 provided the best discriminative performance and can support rapid triage of automated contours, with a practical operating threshold range of 4-9 mm, potentially improving the efficiency of adaptive radiotherapy workflows.

Objective:The purpose of this study was to analyze the influencing factors of readmission after percutaneous coronary intervention(PCI)in patients with coronary heart disease and type 2 diabetes(T2DM),and to build a nomogram model.Methods:A retrospective study was conducted on 260 patients with coronary heart disease and T2DM who received PCI treatment in Yancheng Third People's Hospital from May 2019 to May 2023,clinical data were collected and followed up for 1 year.They were divided into on readmission group and unreadmission group based on their readmission after 1 year.Multivariate logistic regression analysis was conducted to determine risk factors,and a nomogram model was constructed using R software to evaluate its predictive efficiency.Results:Among the 260 patients,65 were readmitted after surgery,with a readmission rate of 25.00％(65/260).Univariate analysis showed that,left ventricular ejection fraction(LVEF),age,left main artery disease,hypertension history,number of coronary artery lesions,dyslipidemia,glycosylated hemoglobin(HbA1c),course of diabetes,fasting blood glucose(FBG),number of stents,and regular postoperative medication were related to readmission 1 year after PCI(P＜0.05).Age ≥ 70 years,hypertension history,coronary artery multi vessel disease,course of diabetes ≥ 10 years,HbA1c ≥7％,left main artery disease,dyslipidemia,LVEF＜50％,number of stents ≥3 were risk factor for readmission 1 year after PCI(P＜0.05).The nomogram model constructed based on the above risk factors has a C-index of 0.835 and an area under the receiver operating characteristic(ROC)the area under the curve(AUC)of 0.826.Conclusion:This study identified multiple risk factors for readmission in patients with coronary heart disease and T2DM 1 year after PCI.The constructed nomogram model can provide an effective tool for predicting the risk of readmission in clinical practice,and help medical staff develop personalized intervention measures to improve patient prognosis.

AKT,also known as Protein Kinase B(PKB),plays a critical role in cell proliferation and metabolism.There are three isoforms of AKT:AKT1,AKT2,and AKT3.The effects of these isoforms on the pluripotency and differentiation of mouse embryonic stem cells(mESCs)remain unclear.This study aims to explore the impact of three AKT isoform-specific knockouts on the self-renewal and differen-tiation of mouse embryonic stem cells.Using CRISPR/Cas9 gene-editing technology,AKT isoform-spe-cific knockout cell lines were established.The phenotypic and molecular changes were analyzed through Western blotting,flow cytometry,qRT-PCR,CCK-8 assays,Alkaline Phosphatase(AP)staining,and RNA-seq.The construction of AKT isoform-specific knockout cell lines was successful.The loss of AKT1 and AKT2 inhibited the proliferation of mESCs.The knockout of any single AKT isoform did not affect the expression of pluripotency genes at both mRNA or protein levels.However,during embryoid body forma-tion,the deletion of any of the three AKT isoforms affected the mRNA expression levels of genes in all three germ layers.Transcriptome analysis showed that compared to wild-type mESCs,995,547,and 429 differentially expressed genes(|log2FC|≧1,P＜0.05)were identified inAKT1,AKT2,and AKT3 isoform-specific knockout cells,respectively.There was some overlap in the differentially expressed genes regulated by these three isoforms.In conclusion,the independent knockout of AKT isoforms does not af-fect the maintenance of pluripotency in mouse embryonic stem cells,but they are crucial for differentia-tion.The three AKT isoforms can collectively regulate gene expression while retaining their own regulato-ry specificity.This study provides a foundation for understanding the unique and overlapping roles of AKT isoforms in stem cell biology,highlighting their importance in maintaining stem cell function and differen-tiation.

Objective To perform an analytical comparison of CT findings between sarcomatoid clear cell renal cell carcinoma(sccRCC)and grade 4 clear cell renal cell carcinoma(ccRCC),to improve preoperative diagnosis for sccRCC.Methods The pathology and imaging data of 18 patients with sccRCC and 23 patients with grade 4 ccRCC were retrospectively analyzed,the differences of non-contrast and contrast-enhanced CT features between the two groups were compared.Results(1)sccRCC and ccRCC demonstrated similar features regarding hemorrhage,calcification,retroperitoneal lymph node enlargement,distant metastasis,invasion of perinephric organs,vascular invasion,and neovascularization around and within the tumor,as well as CT values at different phases.No statistically significant differences were observed between the two groups(P＞0.05).(2)In the sccRCC,solid components were predominant in 6 cases,compared to 16 cases in the ccRCC,showed a significant difference(P=0.017).The ratio of cystic and necrotic areas in sccRCC was 0.66±0.20,and that in ccRCC was 0.51±0.17,with a statistically significant difference(P=0.015).(3)Using a cystic and necrotic area ratio of 0.63 as the diagnostic threshold yields the optimal discriminative performance,with an area under the curve(AUC)of 0.732,a sensitivity of 0.611,and a specificity of 0.826.Conclusion sccRCC is distinguished by a significantly higher proportion of cystic and necrotic elements as opposed to the grade 4 ccRCC.

Pituitary neuroendocrine tumors(PitNETs)are benign tumors originating from the pituitary gland.Although surgical and pharmacological treatments can achieve gross total resection of the tumor and restore endocrine function,patients often experience cognitive dysfunction and emotional regulation disorders,which can reduce their quality of life.Different types of PitNETs present with varying psychological and mental symptoms.For example,patients with prolactinomas,growth hormone-secreting pituitary tumors,and adrenocorticotropic hormone-secreting pituitary tumors commonly experience cognitive impairment(e.g.,memory and executive function)and emotional dysregulation(e.g.,anxiety and depression).Patients with non-functioning PitNETs commonly experience headaches and visual disturbances due to the mass effect of the tumor.Additionally,some of these patients may also develop cognitive impairments.Future research should focus on elucidating the specific mechanisms by which PitNETs influence neuropsychological function,developing more precise bedside assessment tools,and exploring personalized intervention strategies to improve overall treatment outcomes and quality of life for these patients.

Objective:The purpose of this study was to analyze the influencing factors of readmission after percutaneous coronary intervention(PCI)in patients with coronary heart disease and type 2 diabetes(T2DM),and to build a nomogram model.Methods:A retrospective study was conducted on 260 patients with coronary heart disease and T2DM who received PCI treatment in Yancheng Third People's Hospital from May 2019 to May 2023,clinical data were collected and followed up for 1 year.They were divided into on readmission group and unreadmission group based on their readmission after 1 year.Multivariate logistic regression analysis was conducted to determine risk factors,and a nomogram model was constructed using R software to evaluate its predictive efficiency.Results:Among the 260 patients,65 were readmitted after surgery,with a readmission rate of 25.00％(65/260).Univariate analysis showed that,left ventricular ejection fraction(LVEF),age,left main artery disease,hypertension history,number of coronary artery lesions,dyslipidemia,glycosylated hemoglobin(HbA1c),course of diabetes,fasting blood glucose(FBG),number of stents,and regular postoperative medication were related to readmission 1 year after PCI(P＜0.05).Age ≥ 70 years,hypertension history,coronary artery multi vessel disease,course of diabetes ≥ 10 years,HbA1c ≥7％,left main artery disease,dyslipidemia,LVEF＜50％,number of stents ≥3 were risk factor for readmission 1 year after PCI(P＜0.05).The nomogram model constructed based on the above risk factors has a C-index of 0.835 and an area under the receiver operating characteristic(ROC)the area under the curve(AUC)of 0.826.Conclusion:This study identified multiple risk factors for readmission in patients with coronary heart disease and T2DM 1 year after PCI.The constructed nomogram model can provide an effective tool for predicting the risk of readmission in clinical practice,and help medical staff develop personalized intervention measures to improve patient prognosis.