Objective: To investigate the status of condom use and its influencing factors among men who have sex with men (MSM), so as to provide a basis for improving condom utilization rates and AIDS prevention and control in this population. Methods: From May to October 2024, a snowball sampling method was employed to recruit MSM in Songjiang District, Shanghai Municipality. Self-administered questionnaires were used to collect data on demographic characteristics, AIDS-related knowledge, sexual behaviors, pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), and condom use in the past six months. Multivariable logistic regression model was used to analyze the influencing factors for consistent condom use. Results: A total of 921 MSM were surveyed, with a median age of 29.00 (interquartile range, 9.00) years. Among them, 697 (75.68%) were aware of AIDS-related knowledge, 826 (89.69%) expressed willingness to use PrEP, and 835 (90.66%) were willing to use PEP. Additionally, 787 (85.45%) MSM reported their age at first homosexual intercourse as ≥18 years, while 519 (56.35%) reported consistent condom use in the past six months. Multivariable logistic regression analysis revealed that MSM who were aware of AIDS-related knowledge (OR=0.582, 95% CI: 0.423-0.801), willing to use PrEP (OR =0.611, 95% CI: 0.385-0.969), and whose age at first homosexual intercourse was <18 years (OR=0.480, 95% CI: 0.330-0.700) were less likely to consistent use condoms. Conclusion The proportion of consistent condom use among the MSM remains relatively low, which is primarily associated with AIDS-related knowledge, willingness to use PrEP, and the age at first homosexual intercourse.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective To establish a risk prediction model for cerebral edema after mechanical thrombectomy in acute cerebral infarction (ACI) based on multimodal computed tomography (CT) parameters. Methods A total of 220 ACI patients who underwent mechanical thrombectomy at The People’s Hospital of Bozhou between January 2022 and June 2025 were enrolled. All patients underwent preoperative conventional non-contrast CT, CT perfusion imaging, and multiphase CT angiography. Based on the presence or absence of cerebral edema at 72 hours postoperatively, patients were divided into cerebral edema and non-cerebral edema groups. General data and multimodal CT parameters were compared between the two groups. Multivariable logistic regression model was used to analyze the influencing factors of postoperative cerebral edema. A nomogram prediction model was constructed based on the multivariable analysis results, and the efficacy of the model was validated. Results The incidence of postoperative cerebral edema was 23.64% (52/220). Multivariable logistic regression analysis showed that time from onset to recanalization (OR=1.081, 95%CI=1.017-1.149), cerebral blood flow (OR=0.903, 95%CI=0.828-0.984), time to peak (OR=1.171, 95%CI=1.041-1.317), mean transit time (OR=2.815, 95%CI=1.823-6.178), and collateral circulation score (OR=0.960, 95%CI=0.930-0.990) were influencing factors for cerebral edema after mechanical thrombectomy in ACI patients (P<0.05). A nomogram model was constructed based on these factors. The calibration curve indicated good model fit, and the decision curve demonstrated net benefit. The area under the receiver operating characteristic curve for predicting cerebral edema after mechanical thrombectomy in patients with ACI was 0.961, with a sensitivity of 88.46% and a specificity of 91.07%. The Hosmer–Lemeshow goodness-of-fit test showed good model fit (χ²=1.766, P=0.962). Conclusion A risk prediction model for cerebral edema after mechanical thrombectomy in ACI patients was constructed using multimodal CT parameters. The model demonstrated high sensitivity and specificity.

Objective:To compare the efficacy of new nasopharyngeal airway and laryngeal mask airway for airway management in the patients undergoing non-intubated video-assisted thoracoscopic surgery (NIVATS).Methods:In this randomised, controlled, non-inferiority trial, 60 American Society of Anesthesiologists Physical Status classification I or Ⅱ patients of both sexes, aged 18-79 yr, scheduled for elective NIVATS from December 2021 to December 2023 at Jining No.1 People′s Hospital, were divided into 2 groups ( n=30 each) using a computer-generated random code in a 1∶1 ratio: new type nasopharyngeal airway group (group N) and laryngeal mask airway group (group L). After anesthesia induction, a new nasopharyngeal airway was inserted in group N, and a laryngeal mask airway was inserted in group L. Spontaneous ventilation was maintained during the NIVATS. Ultrasound-guided serratus anterior plane block was performed on the affected side before anesthesia induction. Anesthesia was maintained with propofol and remifentanil. The primary outcome measure was the rate of intraoperative airway intervention, the airway interventions included repositioning of the airway tools, manual assisted ventilation, jaw-thrust maneuver, and conversion to endotracheal intubation. The secondary outcome measures included the first-attempt success rate of airway device placement, time for establishing a patent airway, the minimum value of SpO 2, the maximum value of P ETCO 2, and incidence of complications such as postoperative sore throat. Results:The rate of intraoperative airway intervention was 27% in group L and 47% in group N ( χ2=2.58, P=0.108). The difference in the rate of intraoperative airway intervention between the two groups was 0.20 (95% confidence interval 0.15-0.25), with a 95% confidence interval upper limit higher than the non-inferiority boundary (10%), indicating that this non-inferiority hypothesis was not established. In comparison to group L, the rate of intraoperative jaw-thrust maneuver intervention was significantly increased, the time to establish a patent airway was shortened, and the incidence of postoperative sore throat was decreased in group N ( P<0.05). Conclusions:Compared with the laryngeal mask airway, the new nasopharyngeal airway can reduce the development of postoperative throat pain, however, it is less effective in maintaining a patent airway. It requires careful consideration of risks and benefits when used for NIVATS.

Intestinal radiosensitivity makes radiation-induced intestinal injury (RIII) as a common complication among individuals exposed to accidental radiation and patients with abdominal or pelvic malignancies receiving radiotherapy. At present, there are no effective measures for the prevention and treatment of RIII. Developing novel prevention and treatment strategies is of great significance for improving the prognosis and quality of life for both individuals exposed to accidental radiation and cancer patients. Lactobacillus, a Gram-positive bacterium, is widely observed in humans and animals. It exhibits notable probiotic functions, including maintaining gut microbiota homeostasis, preserving intestinal barrier, and modulating immune responses. Substantial studies have demonstrated that Lactobacillus has remarkable protective and therapeutic effects against radiation-induced injury, specifically significantly alleviating RIII. These probiotic functions of Lactobacillus make it have high priority to become the chassis of genetically engineered strains. However, multiple factors influence the construction of a genetically engineered strain, limiting the application of Lactobacillus as a chassis. This review focuses on the probiotic functions of Lactobacillus, highlighting advances in research on Lactobacillus and its engineered probiotics in radiation protection and treatment. Furthermore, it summarizes key factors influencing the construction of genetically engineered strains based on the Lactobacillus chassis. It aims to provide insights for developing genetically engineered strains with radioprotective and therapeutic effects using Lactobacillus as the chassis.

Objective:To evaluate the left atrial structure and function in patients with non-obstructive hypertrophic cardiomyopathy（NOHCM）and atrial fibrillation（AF）using four-dimensional automatic left atrial quantification（4D Auto LAQ）technology，and to explore the correlation between left atrial remodeling and AF.Methods:Ninety patients with NOHCM treated in the First Affiliated Hospital of Zhengzhou University from May 2023 to September 2024 were prospectively selected and divided into AF group（ n=27）and non-AF group（ n=63）according to whether they had AF. Clinical data of all enrolled patients were collected，and two-dimensional，color Doppler，and tissue Doppler ultrasound parameters were measured. 4D Auto LAQ technology was used to obtain left atrial volume and strain parameters. Inter-group comparison，univariate and multivariate Logistic regression analysis，and repeatability test were used to analyze the data. Results:Compared with non-AF group，left atrial maximum volume index（LAVImax），left atrial minimum volume index（LAVImin）and left atrial pre-systolic volume index（LAVIpreA）were increased in the AF group，but left atrial total ejection fraction（LAEF），left atrial passive ejection fraction（LApEF），left atrial active ejection fraction（LAaEF）and the absolute values of left atrial reservoir longitudinal and circumferential strains（LASr，LASr-c），left atrial conduit longitudinal and circumferential strains（LAScd，LAScd-c）and left atrial contraction longitudinal and circumferential strains（LASct，LASct-c）were decreased（all P<0.05）. Multivariate Logistic regression analysis showed that LAVImin was independently associated with AF（ OR=0.837， P<0.001）. Conclusions:4D Auto LAQ can quantitatively evaluate the left atrial structure and function in patients with NOHCM and AF，and LAVImin is independently associated with the presence of AF.

Objective:To explore the value of three-dimensional automatic right ventricular quantitive analysis（3D Auto RVQ）technology in predicting the improvement of left ventricular ejection fraction（LVEF）in patients with heart failure with reduced ejection fraction（HFrEF）.Methods:A retrospective analysis was conducted on 89 HFrEF patients admitted to the Cardiology Department of Central China Fuwai Hospital of Zhengzhou University from April 2022 to June 2024. All patients received medication treatment and were further divided into heart failure with improved ejection fraction（HFimpEF）group and non HFimpEF group based on changes detected by echocardiography in LVEF after treatment. The clinical data，biological indicators，and medication treatment status of patients were collected，routine echocardiographic parameters and right ventricular strain parameters were measured，3D right ventricular ejection fraction（3D-RVEF），3D right ventricular stroke volume index（3D-RVSVI），3D right ventricular end-diastolic volume index（3D-RVEDVI），3D right ventricular end-systolic volume index（3D-RVESVI），3D tricuspid annular plane systolic excursion（3D-TAPSE），and 3D right ventricular fractional area change（3D-RVFAC）were measured using 3D Auto RVQ technology. The differences of the above parameters between the two groups were compared. The ROC curve was used to analyze the predictive efficiency of right ventricular parameters for HFimpEF，and the area under ROC curve（AUC）was calculated and compared. Logistic regression models were used to analyze the predictive value of right ventricular parameters for HFimpEF.Results:Compared with the non HFimpEF group，the HFimpEF group had a younger age，shorter heart failure course，a smaller proportion of males，New York Heart Association（NYHA）functional class ≥Ⅲ，and patients with concomitant coronary heart disease. The baseline LVEF，absolute value of two dimensional right ventricular global longitudinal strain（2D-RVGLS），3D-RVEF，3D-TAPSE，and 3D-RVSVI were higher in the HFimpEF group（all P<0.05）. ROC curve analysis showed that the AUC of 3D-RVEF for predicting HFimpEF was 0.858，and the predictive efficiency was higher than other right ventricular parameters. According to the Yoden index，the optimal cutoff value for predicting HFimpEF based on 3D-RVEF was 36.2%，with a corresponding sensitivity of 84.0% and specificity of 75.0%. After adjusting for clinical and other echocardiographic parameters，the logistic regression model showed that 3D-RVEF was an independent predictor of HFimpEF（ OR=1.435，95% CI=1.145-1.800， P<0.05）. Conclusions:The 3D-RVEF evaluated by 3D Auto RVQ technology has high predictive value for HFimpEF，which can provide a reference for clinical treatment，thereby improving the prognosis of HFrEF patients.

Objective To investigate the influencing factors for the short-term prognosis of patients with alcohol-related liver diseases-acute-on-chronic liver failure(ALD-ACLF)comorbid with infection.Methods A total of 89 ALD-ACLF patients with infection who were admitted to the Fifth Medical Center of PLA General Hospital from January 2019 to December 2021 were enrolled as subjects,and related clinical data were collected at baseline(time of patient enrollment).According to the 28-day survival status of patients,they were divided into survival group with 53 patients and death group with 36 patients,and baseline clinical data were compared between the two groups.The t-test was used for comparison of normally distributed continuous data between groups,and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between groups;the chi-square test was used for comparison of categorical data between groups.A non-conditional Logistic regression analysis was used to perform the multivariate analysis.The Z-test was used for comparison of the area under the ROC curve(AUC),and the diagnostic value of the model was assessed.Results Compared with the survival group,the death group had significantly higher hemoglobin(t=-2.397,P=0.019),alanine aminotransferase(Z=-3.437,P=0.001),gamma-glutamyl transpeptidase(Z=-2.617,P=0.009),creatinine(Z=-3.938,P<0.001),blood urea nitrogen(Z=-3.423,P=0.001),NH3(Z=-4.406,P<0.001),international normalized ratio(Z=-3.428,P=0.001),C-reactive protein(Z=-2.128,P=0.033),procalcitonin(Z=-2.441,P=0.015),Model for End-Stage Liver Disease(MELD)score(t=-4.817,P<0.001),incidence rate of acute kidney injury(χ2=21.602,P<0.001),incidence rate of pulmonary infection(χ2=4.866,P=0.027),and incidence rate of shock(χ2=16.285,P<0.001),as well as significantly lower albumin(Z=-2.473,P=0.013)and incidence rate of abdominal infection(χ2=5.897,P=0.015).The multivariate analysis showed that NH3(odds ratio[OR]=1.027,95%confidence interval[CI]:1.006-1.049,P=0.012),MELD score(OR=1.103,95%CI:1.011-1.203,P=0.027],and the incidence rate of shock(OR=6.326,95%CI:1.533-26.101,P=0.011)were independent risk factors for 28-day mortality in ALD-ACLF patients comorbid with infection.Based on these factors,a predictive model was established as Y=0.027×NH3+0.098×MELD score+1.845×shock-4.111.The ROC curve analysis showed that the new model had an AUC of 0.861,a sensitivity of 77.78%,and a specificity of 88.68%,while MELD score had an AUC of 0.776,a sensitivity of 77.78%,and a specificity of 67.92%,suggesting that the new model had a significantly higher diagnostic value than MELD score(Z=2.136,P=0.032 6).Conclusion ALD-ACLF patients with infection tend to have a poor short-term prognosis,and MELD score,NH3,and shock are influencing factors for the short-term prognosis of such patients.The combination of these three factors has a high value in predicting short-term prognosis.

Carotid artery perivascular adipose tissue (PVAT) can influence plaque formation and progression. Recently, carotid artery PVAT density has emerged as a novel imaging biomarker being capable of reflecting local metabolic and inflammatory states of adipose tissue. It is closely associated with vulnerable plaque characteristics, such as intraplaque hemorrhage, thinning or rupture of the fibrous cap, lipid-rich necrotic core, and calcification. Therefore, carotid artery PVAT density holds promise as a key parameter for early identification of vulnerable carotid plaques and stroke risk prediction. This article reviews the definition and pathophysiological mechanism of PVAT and application of imaging techniques in PVAT, as well as the association between carotid artery PVAT density and vulnerable characteristics of plaques, with the aim of providing references for early identification of asymptomatic high-risk plaques and individualized prevention strategies of ischemic stroke.