A recombinant adenovirus(rAd)for expression of Mycobacterium tuberculosis(M.tb)c-di-AMP phosphodiesterase CnpB was constructed,and its induced humoral immune response was detected.The codon-optimized gene of M.tb CnpB was cloned into the adenoviral plasmid pcADV.The recombinant plasmid pcADV-CnpB was transfected into HEK293T cells,and expression was detected with Western blot.The recombinant plasmid pcADV-CnpB and the backbone plasmid were co-transfected into HEK293T cells to obtain the recombinant adenovirus rAd-CnpB.rAd-CnpB was amplified in HEK293T cells,and the target protein expression of rAd-CnpB was detected with Western blot and immunofluorescence.Mice were immunized with rAd-CnpB intranasally,and their sera and bronchoalveolar lavage fluid(BALF)were collected.ELISA was used to detect levels of antigen-specific antibodies.Restriction enzyme digestion and sequencing indicated that the recombinant plasmid pcADV-CnpB was successfully constructed and led to protein expression in eukaryotic cells.rAd-CnpB was packaged and produced in HEK293T cells.After amplification and purification,rAd-CnpB with a titer of 5.53×1010 PFU/mL was obtained.rAd-CnpB led to CnpB expression in HEK293T cells.Intranasal immunization with rAd-CnpB increased levels of IgG and secretory IgA in BALF and led to high levels of IgG in sera.rAd-CnpB,the recombinant adenovirus for expression of c-di-AMP phosphodiesterase CnpB was successfully constructed,and was found to induce antigen-specific humoral and mucosal immune responses through mucosal immunization.Thus,rAd-CnpB may be used in further research on new TB vaccine strategies.

Objective:To investigate the pharmacological mechanism of Compound Xuanju Capsule in the treatment of erectile dysfunction(ED)by using network pharmacology and molecular docking technology.Methods:The active ingredients and targets of Compound Xuanju Capsule were screened using Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform(TCMSP).TTD,OMIM,DrugBank and GeneCards databases were used to obtain genes related to ED,and the union of the results was taken as the disease genes of ED.The common target of drug and disease was taken as the potential target of Compound Xuanju Capsule in ED,and the drug-disease interaction network was constructed by using Cytoscape software.The protein-protein interaction(PPI)network was constructed by using String database,which was then imported into Cytoscape to identify the key target.Based on the drug-disease intersection genes,GO and KEGG enrichment analyses were performed to predict the relevant signaling pathways and molecular mechanisms of Compound Xuanju Capsule for the treatment of ED.Autodock software was used to perform molecular docking between the active ingredients and the core targets.Results:Forty chemical components of Compound Xuanju Capsule were screened,and 239 predicted targets were obtained.A total of 1 907 ED-related genes were screened,and 97 common targets were identified between Compound Xuanju Capsule and ED,among which the core targets included EGFR,ESR1,HIF1A,PTGS2,and STAT3.The signaling pathways obtained by KEGG enrichment analysis included calcium signaling pathway,HIF-1 signaling pathway,PI3K-Akt signaling pathway,cGMP-PKG signaling pathway,relaxin signaling pathway,Serotonergic synapse signaling pathway.The molecular docking results showed that there were molecular binding sites between the key active ingredients and the core targets with strong binding activity.Conclusion:Compound Xuanju Capsule may treat ED through multi-target pathways such as anti-inflamnmato-ry and improving cellular oxidative stress.

Gene editing technology has become an important tool for biomedical research because of its high efficiency and precision in target gene localization and cleavage.The technology not only facilitates basic research on gene function,but also provides new strategies for gene therapy of hereditary diseases and genetic improvement of crops.With the integration of artificial intelligence(AI)technology,espe-cially the application of machine learning algorithms,the design and execution of gene editing have be-come more intelligent.AI technology optimizes the design of sgRNAs through predictive analysis and pat-tern recognition,improving the specificity and efficiency of editing while reducing the risk of off-target effects.In addition,AI plays a key role in the parsing of large-scale genomic data,providing new per-spectives for understanding complex biological processes and disease mechanisms.This paper reviews the research progress of data-driven gene editing technology in target precision,safety enhancement and per-sonalized therapy,aiming to provide reference and inspiration for researchers in the field of gene editing technology and to promote the application and development of AI in gene editing technology.

Objective To evaluate the efficacy and safety of transcatheter aortic valve implantation(TAVI)for the treatment of primary aortic valve regurgitation(NAVR)and to compare the difference in the choice of prosthetic valve size and the difference in complications with aortic stenosis(AS).Methods According to the definition of Valve Academic Research Consortium(VARC-3),143 patients with NAVR/AS treated with TAVI and patients with NAVR treated with surgical aortic valve replacement(SAVR)at Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,China,from March 2019 to September 2024 were selected,and clinical data on baseline,perioperative,and primary endpoint events were were retrospectively collected and compared.Results Forty-three patients with NAVR were treated with TAVI,with a device success rate of 86.0％and a surgical success rate of 95.3％.Subgroup comparisons:(1)NAVR-TAVI group than NAVR-SAVR group:patients in the TAVI group had a significantly shorter operative time than those in the SAVR group(P＜0.001);complete left bundle branch block was more likely to occur after TAVI(P=0.042),and complete right bundle branch block was more likely to occur after SAVR(P=0.044).SAVR postoperatively The incidence of congestive heart failure was higher(P=0.013),and the mortality rate was significantly higher in the SAVR group than in the TAVI group(P=0.019).(2)NAVR-TAVI group than AS-TAVI group:the differences in access selection,THV size[28(22,34)mm vs.24(22,32)mm,P=0.044]and proportion of THV overdiameter[14％(7％,20％)vs.7％(3％,11％),P＜0.001]were statistically significant.patients in AS and NAVR groups had 1 case of permanent pacing after TAVI treatment.In the AS and NAVR groups,there was 1 case of permanent pacemaker implantation after TAVI.2 patients in the AS group were converted to surgical treatment,and 6 patients died.Conclusions The use of"off-label"(transfemoral)and"on-label"(transapical)TAVI devices(both from domestic sources)is safer than SAVR for the treatment of NAVR,especially in elderly and high-risk patients.Compared with patients with AS treated with TAVI,larger diameter annulas are usually selected for NAVR,with higher rates of valve migration,but overall safety and efficacy are comparable to AS.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVES: To report the development, validation, and findings of the Multi-dimensional Attention Rating Scale (MARS), a self-report tool crafted to evaluate six-dimension attention levels. METHODS: The MARS was developed based on Classical Test Theory (CTT). Totally 202 highly educated healthy adult participants were recruited for reliability and validity tests. Reliability was measured using Cronbach's alpha and test-retest reliability. Structural validity was explored using principal component analysis. Criterion validity was analyzed by correlating MARS scores with the Toronto Hospital Alertness Test (THAT), the Attentional Control Scale (ACS), and the Attention Network Test (ANT). RESULTS: The MARS comprises 12 items spanning six distinct dimensions of attention: focused attention, sustained attention, shifting attention, selective attention, divided attention, and response inhibition.As assessed by six experts, the content validation index (CVI) was 0.95, the Cronbach's alpha for the MARS was 0.78, and the test-retest reliability was 0.81. Four factors were identified (cumulative variance contribution rate 68.79%). The total score of MARS was correlated positively with THAT (r = 0.60, P < 0.01) and ACS (r = 0.78, P < 0.01) and negatively with ANT's reaction time for alerting (r = -0.31, P = 0.049). CONCLUSIONS The MARS can reliably and validly assess six-dimension attention levels in real-world settings and is expected to be a new tool for assessing multi-dimensional attention impairments in different mental disorders.
Humans ; Adult ; Male ; Attention/physiology* ; Female ; Middle Aged ; Reproducibility of Results ; Young Adult ; Psychometrics

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.