Objective:To investigate the predictive value of multimodal magnetic resonance imaging (MRI) techniques in assessing symptom remission of post-traumatic stress disorder (PTSD) of bereaved parents who lost their only child.Methods:In this prospective study, 34 parents with PTSD resulting from the loss of the only child were followed-up for 2 years. Based on the PTSD diagnostic status at the end of the follow-up, participants were divided into the remission group and the persistent group.R 3.6.1 and SPSS 20.0 software were used for statistical analysis.Baseline clinical data and neuroimaging findings were compared between the two groups. Logistic regression and LASSO regression analyses were used to identify independent predictors of PTSD symptom remission. The predictive performance of these factors was evaluated by receiver operating characteristic (ROC) curve analysis.Results:Initial screening with univariate Logistic regression and LASSO regression revealed that regional homogeneity (ReHo) in the left middle temporal gyrus, the combined predictive value based on ReHo, and the integrated predictive value combining gray matter volume (GMV) and ReHo (GMV-ReHo predictor) were significant factors influencing symptom remission (all P<0.05). Multivariate Logistic regression further demonstrated that the GMV-ReHo predictor retained independent predictive significance ( P<0.05), with ROC curve analysis showing an area under the curve (AUC) of 0.979 (95% CI=0.935-0.996, P<0.001) for its ability to predict PTSD remission. Notably, a combined model incorporating both the scores of the clinician administered PTSD scale (CAPS) and the GMV-ReHo predictor achieved an enhanced predictive performance, yielding an AUC of 0.984 (95% CI=0.952-0.998, P<0.001). Conclusion:The GMV-ReHo predictor effectively identifies symptom remission in PTSD resulting from the loss of the only child.

Objective To explore the application value of the deep learning image reconstruction algorithm(ClearInfinity,CI)combined with high tube voltage and low tube current low-dose computed tomography(LDCT)in lung screening.Methods A total of 216 patients underwent lung screening CT plain scan were selected.Patients were randomly divided into conventional-dose group(A group)and low-dose group(B group).Image reconstructed by using the iterative algorithm(ClearView+,CV)in group A,CV-60％,CI-30％,CI-60％,and CI-90％algorithms in group B.CT value,noise,image quality,and edge detail were conducted with both objective and subjective evaluations.Lung nodules were automatically detected by using computer-aided diagnosis software,and radiation doses were recorded.Results Images reconstructed with the CI showed significantly superior signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)than with the CV(P＜0.05).Additionally,there was a significant correlation in lung nodule detection performance between the CI and the CV(P＜0.05).The effective dose(ED)in group B was reduced by approximately 85.80％compared to group A(P＜0.01).Although the SNR and CNR were highest with CI-90％,the subjective image quality was lower than that of CI-60％.CI-60％and CI-90％showed same performance in lung nodule detection using artificial intelligence(AI)software.Conclusion The application of LDCT scanning protocol using the CI algorithm based on deep learning,combined with high tube voltage and low tube current is feasible for lung screening.It is recommended to use CI-60％in clinical diagnosis to improve the safety and diagnostic confidence of lung CT screening.

Objective:To investigate the predictive value of multimodal magnetic resonance imaging (MRI) techniques in assessing symptom remission of post-traumatic stress disorder (PTSD) of bereaved parents who lost their only child.Methods:In this prospective study, 34 parents with PTSD resulting from the loss of the only child were followed-up for 2 years. Based on the PTSD diagnostic status at the end of the follow-up, participants were divided into the remission group and the persistent group.R 3.6.1 and SPSS 20.0 software were used for statistical analysis.Baseline clinical data and neuroimaging findings were compared between the two groups. Logistic regression and LASSO regression analyses were used to identify independent predictors of PTSD symptom remission. The predictive performance of these factors was evaluated by receiver operating characteristic (ROC) curve analysis.Results:Initial screening with univariate Logistic regression and LASSO regression revealed that regional homogeneity (ReHo) in the left middle temporal gyrus, the combined predictive value based on ReHo, and the integrated predictive value combining gray matter volume (GMV) and ReHo (GMV-ReHo predictor) were significant factors influencing symptom remission (all P<0.05). Multivariate Logistic regression further demonstrated that the GMV-ReHo predictor retained independent predictive significance ( P<0.05), with ROC curve analysis showing an area under the curve (AUC) of 0.979 (95% CI=0.935-0.996, P<0.001) for its ability to predict PTSD remission. Notably, a combined model incorporating both the scores of the clinician administered PTSD scale (CAPS) and the GMV-ReHo predictor achieved an enhanced predictive performance, yielding an AUC of 0.984 (95% CI=0.952-0.998, P<0.001). Conclusion:The GMV-ReHo predictor effectively identifies symptom remission in PTSD resulting from the loss of the only child.

Objective To explore the application value of the deep learning image reconstruction algorithm(ClearInfinity,CI)combined with high tube voltage and low tube current low-dose computed tomography(LDCT)in lung screening.Methods A total of 216 patients underwent lung screening CT plain scan were selected.Patients were randomly divided into conventional-dose group(A group)and low-dose group(B group).Image reconstructed by using the iterative algorithm(ClearView+,CV)in group A,CV-60％,CI-30％,CI-60％,and CI-90％algorithms in group B.CT value,noise,image quality,and edge detail were conducted with both objective and subjective evaluations.Lung nodules were automatically detected by using computer-aided diagnosis software,and radiation doses were recorded.Results Images reconstructed with the CI showed significantly superior signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)than with the CV(P＜0.05).Additionally,there was a significant correlation in lung nodule detection performance between the CI and the CV(P＜0.05).The effective dose(ED)in group B was reduced by approximately 85.80％compared to group A(P＜0.01).Although the SNR and CNR were highest with CI-90％,the subjective image quality was lower than that of CI-60％.CI-60％and CI-90％showed same performance in lung nodule detection using artificial intelligence(AI)software.Conclusion The application of LDCT scanning protocol using the CI algorithm based on deep learning,combined with high tube voltage and low tube current is feasible for lung screening.It is recommended to use CI-60％in clinical diagnosis to improve the safety and diagnostic confidence of lung CT screening.

Objective To prepare human SET8 monoclonal antibody and explore its effects on the proliferation,apoptosis,and cell cycle of hepatoma cells,and to evaluate its anti-tumor effect in mouse models of hepatocellular carcinoma.Methods We immunized mice with human SET8 polypeptide fragment and screened and fused B cells and myeloma cells to establish a hybridoma cell line that stably secreted SET8 monoclonal antibody.Production was expanded by intraperitoneal injection into mice and the collection and purification of ascites.We investigated the effects of SET8 monoclonal antibody on the proliferation,apoptosis,cell cycle,and apoptosis-related protein expression of hepatocellular carcinoma cells by CCK-8,flow cytometry,and Western blot,respectively.Finally,we constructed a mouse model of human hepatocellular carcinoma by cell transplantation to evaluate the inhibitory effect of SET8 monoclonal antibody on tumor growth in vivo.Results Human SET8 monoclonal antibody significantly inhibited the viability of Huh-7 and Mahlavu hepatoma cells at concentrations of 50 and 100 μg/mL,in a concentration-dependent manner(P＜0.05).Flow cytometry analysis showed that SET8 monoclonal antibody,paclitaxel,and their combination significantly increased the apoptosis rate of Mahlavu cells compared with the blank control group,with the combination group having the greatest effect(P＜0.05).SET8 monoclonal antibody also induced Mahlavu cell cycle arrest in S and G2 phases and reduced G1 phase cells.Western blot analysis showed that the monoclonal antibody increased the expression of the apoptosis-related proteins Bax and Caspase-3(P＜0.05).SET8 monoclonal antibody,alone or in combination with paclitaxel,also effectively inhibited the proliferation of hepatocellular carcinoma cells in nude mice,with the combination therapy having the most significant effect(P＜0.05).Conclusions The prepared human SET8 monoclonal antibody effectively inhibited the proliferation and promoted the apoptosis of hepatocellular carcinoma cells,and showed good anti-tumor effects in mice.

Objective To prepare human SET8 monoclonal antibody and explore its effects on the proliferation,apoptosis,and cell cycle of hepatoma cells,and to evaluate its anti-tumor effect in mouse models of hepatocellular carcinoma.Methods We immunized mice with human SET8 polypeptide fragment and screened and fused B cells and myeloma cells to establish a hybridoma cell line that stably secreted SET8 monoclonal antibody.Production was expanded by intraperitoneal injection into mice and the collection and purification of ascites.We investigated the effects of SET8 monoclonal antibody on the proliferation,apoptosis,cell cycle,and apoptosis-related protein expression of hepatocellular carcinoma cells by CCK-8,flow cytometry,and Western blot,respectively.Finally,we constructed a mouse model of human hepatocellular carcinoma by cell transplantation to evaluate the inhibitory effect of SET8 monoclonal antibody on tumor growth in vivo.Results Human SET8 monoclonal antibody significantly inhibited the viability of Huh-7 and Mahlavu hepatoma cells at concentrations of 50 and 100 μg/mL,in a concentration-dependent manner(P＜0.05).Flow cytometry analysis showed that SET8 monoclonal antibody,paclitaxel,and their combination significantly increased the apoptosis rate of Mahlavu cells compared with the blank control group,with the combination group having the greatest effect(P＜0.05).SET8 monoclonal antibody also induced Mahlavu cell cycle arrest in S and G2 phases and reduced G1 phase cells.Western blot analysis showed that the monoclonal antibody increased the expression of the apoptosis-related proteins Bax and Caspase-3(P＜0.05).SET8 monoclonal antibody,alone or in combination with paclitaxel,also effectively inhibited the proliferation of hepatocellular carcinoma cells in nude mice,with the combination therapy having the most significant effect(P＜0.05).Conclusions The prepared human SET8 monoclonal antibody effectively inhibited the proliferation and promoted the apoptosis of hepatocellular carcinoma cells,and showed good anti-tumor effects in mice.

Cardiovascular System/pathology* ; Constriction, Pathologic/genetics* ; Point Mutation ; Neurofibromin 1/genetics* ; Animals ; Mice

PURPOSE: T helper (Th) 17 cells play a critical role in the development of asthma, but the underlying mechanism of how interleukin (IL)-17 is regulated in allergic airway inflammation is poorly understood. In this study, we investigated the impact of Bcl11b on Th17 response in asthma. METHODS: Blood samples from patients with mild asthma (MA) and severe asthma (SA) were collected. Expression of Bcl11b, IL-4, IL-5, IL-13, IL-17A and transforming growth factor (TGF)-β1 were determined in CD4+ T cells and plasma by polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA). Relative mRNA and protein levels of Bcl11b, IL-17A and genes involved in the TGF/Smad signaling pathway were examined by PCR, ELISA and western blot analysis in house dust mite (HDM)-challenged mice. Ectopic expression of Bcl11b in HDM-stimulated primary mouse splenocytes was achieved by nucleofection of Bcl11b expression plasmid. RESULTS: We found significantly decreased Bcl11b but increased IL-17A and TGF-β1 expression in patients with asthma and a strongly negative correlation between Bcl11b and these 2 cytokines in SA patients. Similar expression patterns of Bcl11b, IL-17A and TGF-β1 were also found in mice with HDM-induced allergic airway inflammation. We demonstrated further that Smad2/3 phosphorylation was increased in HDM-challenged mice and that ectopic expression of Bcl11b in HDM-stimulated primary mouse splenocytes reduced Smad2 phosphorylation and IL-17 expression. CONCLUSIONS: Our findings demonstrate a potential effect of Bc111b in controlling IL-17-mediated inflammation in asthma and suggest that Bc111b may be a useful therapeutic target for asthma.
Animals ; Asthma* ; Blotting, Western ; Cytokines ; Ectopic Gene Expression ; Enzyme-Linked Immunosorbent Assay ; Humans ; Inflammation ; Interleukin-13 ; Interleukin-17* ; Interleukin-4 ; Interleukin-5 ; Interleukins ; Mice ; Phosphorylation ; Plasma ; Plasmids ; Polymerase Chain Reaction ; Pyroglyphidae ; RNA, Messenger ; T-Lymphocytes ; Transforming Growth Factors

Objective: To investigate the relationship between the mutations in precore/core (preC/C) region of hepatitis B virus (HBV) gene and the postoperative survival in patients with hepatocellular carcinoma. Methods: A total of 81 cases in HBV associated hepatocellular carcinoma (HBV-HCC) patients with cancer tissue genomic DNA were extracted. The preC/C region of HBV was amplified and sequenced, and survival-associated HBV mutations were identified according to the NCBI database. The relationships between the mutations in the preC/C region and HCC survival was analyzed with the Kaplan-Meier method and the Cox proportional hazards model. Eleven mutational sites were identified as statistically significant independent predictors of HBV-HCC postoperative survival. Results: The portal vein thrombosis, tumor TNM classification and size were identified as statistically significant independent predictors of survival in HBV-HCC patients. In the research, we found that seven mutational sites in preC/C region of HBV were associated with independent risk factors for postoperative survival in patients of HBV-HCC. The following five mutational sites were identified as statistically significant independent predictors of HBV-HCC survival: 1915, 2134, 2176, 2221, 2260. The mutational site of 1979 and 2245 were identified for the association with survival at a borderline significance level. Conclusions The portal vein thrombosis, tumor TNM classification, size and seven mutational sites in the PreC/C region were identified as independent predictors of postoperative survival in HCC patients.

Objective To investigate the accumulation of mutations and single nucleotide polymorphisms ( SNPs) in the displacement loop ( D-loop ) of mitochondrial DNA ( mtDNA ) might be associated with cancer risk and disease outcome.Methods We obtained cancerous and noncancerous liver tissues from 49 HBV-related HCC patients at the Fourth Hospital of Hebei Medical University.mtDNA of the liver tissues was extracted with Mitochondrial DNA Extraction Kit.Mutation and polymorphism were confirmed by repeated analysis.We assessed the prediction power of D-loop SNPs in hepatocellular carcinoma ( HCC) patients.Results No mutation in these HCC patients had prediction power for post-operational survival, whereas one SNP site ( nucleotide 150 C/T ) was identified by the log-rank test for statistically significant prediction of HCC survival.In an overall multivariate analysis, allele 150 was identified as an independent predictor of HCC outcome.The length of survival of patients with allele 150C was significantly shorter than that of patients with allele 150T (relative risk, 0.246;95% CI, 0.070–0.861; P=0.028).Conclusions The analysis of genetic polymorphisms in the mitochondrial D-loop helps to identify patient subgroups at high risk of a poor disease outcome.