Researchers commonly use cyclization recombination enzyme/locus of X-over P1 (Cre/loxP) technology-based conditional gene knockouts of model mice to investigate the functional roles of genes of interest in Sertoli and Leydig cells within the testis. However, the shortcomings of these genetic tools include high costs, lengthy experimental periods, and limited accessibility for researchers. Therefore, exploring alternative gene silencing techniques is of great practical value. In this study, we employed adeno-associated virus (AAV) as a vector for gene silencing in Sertoli and Leydig cells. Our findings demonstrated that AAV serotypes 1, 8, and 9 exhibited high infection efficiency in both types of testis cells. Importantly, we discovered that all three AAV serotypes exhibited exquisite specificity in targeting Sertoli cells via tubular injection while demonstrating remarkable selectivity in targeting Leydig cells via interstitial injection. We achieved cell-specific knockouts of the steroidogenic acute regulatory ( Star ) and luteinizing hormone/human chorionic gonadotropin receptor (Lhcgr) genes in Leydig cells, but not in Sertoli cells, using AAV9-single guide RNA (sgRNA)-mediated gene editing in Rosa26-LSL-Cas9 mice. Knockdown of androgen receptor ( Ar ) gene expression in Sertoli cells of wild-type mice was achieved via tubular injection of AAV9-short hairpin RNA (shRNA)-mediated targeting. Our findings offer technical approaches for investigating gene function in Sertoli and Leydig cells through AAV9-mediated gene silencing.
Animals ; Male ; Leydig Cells/metabolism* ; Mice ; Dependovirus/genetics* ; Sertoli Cells/metabolism* ; Gene Silencing ; Genetic Vectors ; Testis/cytology*

Objective:To assess the relationship between basophil levels and mortality in patients with intra-abdominal infection.Methods:Information on patients with intraperitoneal infection admitted to the intensive care unit were extracted from the MIMIC database.A time-dependent Cox regression model was used to adjust for confounders associated with 28-day mortality.Propensity score matching(PSM)was used to balance the baseline differences be-tween groups with different basophil levels,and a restricted cube chart(RCS)was used to show the relationship between basophil count and 28-day mortality in patients with intra-abdominal infection.Results:A total of 4403 patients with intra-abdominal infection were enrolled in the MIMIC database.Patients with high basophil levels have lower mortality than those with low basophil levels.There was an L-shaped curve between basophil level and 28-day mortality,with a cut-off value of 0.47×109/L.Cox regression analysis showed that basophil levels were an independent protective factor for mortal-ity in patients with intra-abdominal infection after adjusting for potential confounders(HR=0.586,95%CI:0.443-0.769).Protective factors for death at basophil levels remained after PSM adjusted for potential confounders(HR=0.628,95%CI:0.470-0.832).Conclusion:Basophil level is an independent protective factor for mortality in patients with intra-abdominal infection,and basophil levels should be dynamically monitored to better evaluate the prognosis of patients.

Objective To explore the influencing factors of health-related quality of life in patients after ileal ureteral replacement,and to provide a reference for formulating effective management plans.Methods Based on the conceptual model of health-related quality of life,16 patients who underwent ileal ureteral replacement in the Department of Urology of a tertiary A hospital in Beijing were selected for semi-structured interviews using descriptive research methods and purposive sampling method.The data were analyzed using directed content analysis.Results There are 6 themes and 10 sub-themes:symptom factors(distress of tube-related symptoms,distress of gastrointestinal symptoms);individual characteristics factors(obvious negative emotions,health behavior development);environmental factors(support from relatives and colleagues,lack of primary medical services);functional status factors(physical function rehabilitation,social function recovery);physiological function factors(test abnormal test index,risk of primary disease recurrence);general health perception factors.Conclusion The health-related quality of life of patients undergoing ileal ureteral replacement surgery was affected by symptoms,negative emotions,health behaviors,social support,functional status et al.In view of the above factors,medical staff should carry out effective evaluation and intervention in time,so as to improve the quality of life of patients.

[Purpose]To analyze the prevalence characteristics and disease burden of lung cancer in Hebei cancer registration areas from 2012 to 2020.[Methods]Lung cancer data were collected from the Hebei Provincial Cancer Registry from 2012 to 2020.The crude incidence/mortality rates,age-standardized incidence/mortality rates by Chinese standard population(ASIRC/ASMRC)and by world standard population(ASIRW/ASMRW)were calculated.The Joinpoint model was used to calculate the annual percentage change(APC)and average annual percentage change(AAPC).Years of life lost(YLL)and years lived with disability(YLD)and the disability-adjusted life years(DALY)were calculated.[Results]From 2012 to 2020,the ASIRW of lung cancer in Hebei can-cer registration areas was 33.13/105,44.56/105 for men and 22.54/105 for women,respectively;the incidence rates of urban and rural areas were 29.05/105 and 33.52/105,respectively.The incidence rates increased with ages,reaching a peak in the age group of 80～84 years old.There was a de-creasing trend in the ASIRW of lung cancer(AAPC=-3.99％,P＜0.05).From 2012 to 2020,the ASMRW of lung cancer was 25.80/105,36.56/105 for men and 15.96/105 for women,respectively;the mortality rates of urban and rural areas were 25.14/105 and 26.12/105,respectively.The mor-tality rates increase with ages,reaching a peak in the age group of 85 and above years old.There was a decreasing trend in the mortality of lung cancer(AAPC=-4.65％,P＜0.001)from 2012 to 2020.The DALY of lung cancer in Hebei Province from 2012 to 2020 was 484 194 person-years,with male accounting for 66.77％,female accounted for 33.23％,the DALY rate of lung cancer was 3.31‰,of which 35.57％in urban areas and 64.43％in rural areas.[Conclusion]Lung can-cer incidence and mortality rate in Hebei cancer registration areas from 2012 to 2020 showed a decreasing trend.The disease burden is gradually increasing with age in middle-aged and el-derly population.

Objective To evaluate the service efficiency of nursing homes in China from a medical care integration per-spective and analyze influencing factors.Methods The three-stage Data Envelopment Analysis(DEA)model was applied to e-liminate the influence of environmental factors to analyze the efficiency of nursing homes in various provinces in China.Addition-ally,a Tobit model was used to examine the determinants of efficiency.Results During the research period,the traditional DEA model overestimated the comprehensive efficiency and scale efficiency of nursing homes in 31 provinces,municipalities,and au-tonomous regions in China,and underestimated the pure technical efficiency.Environmental factors such as per capita GDP,the elderly dependency ratio,and the proportion of urban population impacted the input variables to significantly different extents,with a comprehensive efficiency score of 0.785,a pure technical efficiency score of 0.870,and a scale efficiency score of 0.901.Key influencing factors of the service efficiency of elderly care institutions included basic elderly care facilities,regional popula-tion size,residents'consumption capacity,degree of disability of the care recipients,quality of human resources,and capacity of medical services.Conclusion After eliminating the influence of environmental factors through the three-stage DEA,the efficien-cy evaluation is more accurate.The service efficiency of nursing homes varies across different regions in China:the eastern region exhibits the highest efficiency,followed by the central region and the western region.

ObjectiveTomatoes are one of the highest-yielding and most widely cultivated economic crops globally, playing a crucial role in agricultural production and providing significant economic benefits to farmers and related industries. However, early blight in tomatoes is known for its rapid infection, widespread transmission, and severe destructiveness, which significantly impacts both the yield and quality of tomatoes, leading to substantial economic losses for farmers. Therefore, accurately identifying early symptoms of tomato early blight is essential for the scientific prevention and control of this disease. Additionally, visualizing affected areas can provide precise guidance for farmers, effectively reducing economic losses. This study combines hyperspectral imaging technology with machine learning algorithms to develop a model for the early identification of symptoms of tomato early blight, facilitating early detection of the disease and visual localization of affected areas. MethodsTo address noise interference present in hyperspectral images, robust principal component analysis (RPCA) is employed for effective denoising, enhancing the accuracy of subsequent analyses. To avoid insufficient information representation caused by the subjective selection of regions of interest, the Otsu’s thresholding method is utilized to extract tomato leaves effectively from the background, with the average spectrum of the entire leaf taken as the primary object of study. Furthermore, a comprehensive spectral preprocessing workflow is established by integrating multivariate scatter correction (MSC) and standardization methods, ensuring the reliability and effectiveness of the data. Based on the processed spectral data, a discriminant model utilizing a linear kernel function support vector machine (SVM) is constructed, focusing on characteristic wavelengths to improve the model's discriminative capability. ResultsCompared to full-spectrum modeling, this approach results in an 8.33% increase in accuracy on the test set. After optimizing the parameters of the SVM model, when C=1.64, the accuracies of the training set and test set reach 91.67% and 94.44%, respectively, demonstrating a 1.19% increase in training set accuracy compared to the unoptimized model, while maintaining the same accuracy on the test set, effectively alleviating issues of underfitting. ConclusionThis study successfully establishes an early discriminant model for tomato early blight using hyperspectral imaging and achieves visualization of early symptoms. Experimental results indicate that the SVM discriminant model based on characteristic wavelengths and a linear kernel function can effectively identify early symptoms of tomato early blight. Visualization of these symptoms in terms of disease probability allows for a more intuitive detection of early diseases and timely implementation of corresponding control measures. This visual analysis not only enhances the efficiency of disease identification but also provides farmers with more straightforward and practical information, aiding them in formulating more reasonable prevention strategies. These research findings provide valuable references for the early identification and visualization of plant diseases, holding significant practical implications for monitoring, identifying, and scientifically preventing crop diseases. Future research could further explore how to apply this model to disease detection in other crops and how to integrate IoT technology to create intelligent disease monitoring systems, enhancing the scientific and efficient management of crops.

OBJECTIVE: Cigarette smoking exacerbates the progression of pulmonary tuberculosis (TB). The role of tertiary lymphoid structures (TLS) in chronic lung diseases has gained attention; however, it remains unclear whether smoking-exacerbated lung damage in TB is associated with TLS. This study aimed to analyze the characteristics of pulmonary TLS in smokers with TB and to explore the possible role of TLS in smoking-related lung injury in TB. METHODS: Lung tissues from 36 male patients (18 smokers and 18 non-smokers) who underwent surgical resection for pulmonary TB were included in this study. Pathological and immunohistological analyses were conducted to evaluate the quantity of TLS, and chest computed tomography (CT) was used to assess the severity of lung lesions. The correlation between the TLS quantity and TB lesion severity scores was analyzed. The immune cells and chemokines involved in TLS formation were also evaluated and compared between smokers and non-smokers. RESULTS: Smoker patients with TB had significantly higher TLS than non-smokers ( P < 0.001). The TLS quantity in both the lung parenchyma and peribronchial regions correlated with TB lesion severity on chest CT (parenchyma: r = 0.5767; peribronchial: r = 0.7373; both P < 0.001). Immunohistochemical analysis showed increased B cells, T cells, and C-X-C motif chemokine ligand 13 (CXCL13) expression in smoker patients with TB ( P < 0.001). CONCLUSION Smoker TB patients exhibited increased pulmonary TLS, which was associated with exacerbated lung lesions on chest CT, suggesting that cigarette smoking may exacerbate lung damage by promoting TLS formation.
Humans ; Male ; Tuberculosis, Pulmonary/immunology* ; Middle Aged ; Tertiary Lymphoid Structures/pathology* ; Adult ; Lung/pathology* ; Smoking/adverse effects* ; Smokers ; Aged ; Tomography, X-Ray Computed

Objective: To delineate the epidemiologic profile of rifampicin resistant pulmonary tuberculosis (RR-PTB) among students in Chongqing, so as to provide evidence for effectively controlling RR-PTB outbreaks in schools. Methods: Individual level surveillance records of 395 student RR-PTB cases reported from 2015 to 2024 were extracted from the China Information System for Disease Control and Prevention. The Joinpoint regression analysis was employed to quantify temporal trends in the registration rate of student RR-PTB cases, and the comparison of RR-PTB registration rates with different demographic characteristics and different regions was performed using Chi-square test. Results: From 2015 to 2024, a total of 395 student RR-PTB cases were identified, with the registration rate ranged from 0.07 per 100 000 to 1.47 per 100 000, showed a fluctuating upward trend ( AAPC= 35.22%, t =4.13, P <0.01). A turning point was detected in 2017, rates rose during 2015-2017 (APC=295.23%， t =4.62， P < 0.01 ) and plateaued thereafter (APC=-0.47%， t =-0.12， P =0.91). The proportion of RR-PTB cases occurring among students increased both among all RR-PTB cases (1.54% in 2015, 7.48% in 2024) and all student pulmonary tuberculosis cases (0.20% in 2015, 7.17% in 2024), with significant linear trends ( χ 2 trend =33.55,159.98, both P <0.01). The majority of cases were enrolled in senior high school (50.38%), classified as retreatment (53.92%), of Han ethnicity (75.95%), and diagnosed with multidrug resistant tuberculosis(53.16%). There were significant differences in the composition of different ethnicity, registration category and resistance pattern between different years( χ 2=23.47, 17.23, 59.64，all P <0.05). The South-Eastern Wuling Mountainous Region exhibited the highest notification rate (3.96 per 100 000), whereas the western region had the lowest rate ( 0.47 per 100 000). County level jurisdictions reported higher rates than district level ones (2.16 per 100 000 vs 0.63 per 100 000 ). Statistically significant differences were observed in the RR-PTB reported rates among students across different districts and counties( χ 2=418.05,167.05,both P <0.01). Conclusions From 2015 to 2024, the registration rate of detected student RR-PTB cases in Chongqing showed an increasing trend. Students have become one of the key populations for drug resistant TB prevention and control. Intensified health education and active case finding should be implemented to enhance proactive surveillance capabilities.

Objective:To analyze the interference of an exogenous glucose test on urinary creatinine-related renal injury biomarkers in patients with chronic kidney disease (CKD).Methods:This cross-sectional study enrolled CKD patients who visited Peking University First Hospital between October 2023 and March 2024. The patients (age: 50±18 years) included 90 males and 70 females. Fresh morning urine samples were collected, totaling 160 samples. Each urine sample was divided into 5 aliquots,each containing 225 μl. One aliquot received 75 μl of deionized water as the control. The other aliquots received 75 μl of glucose solutions at concentrations of 120, 480, 960, and 1200 mmol/L, resulting in final glucose concentrations of 30, 120, 240, and 300 mmol/L in the urine samples, respectively. Urinary creatinine in each sample was measured using both the enzymatic method and the picric acid (Jaffe) method. The following ratios were calculated: urinary albumin-to-creatinine ratio (uACR), urinary protein-to-creatinine ratio (uPCR), urinary transferrin-to-creatinine ratio (uTRF/uCr), urinary α1-microglobulin-to-creatinine ratio (uA1M/uCr), urinary immunoglobulin G-to-creatinine ratio (uIgG/uCr), and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/uCr).Results:Under high glucose concentrations, significant differences ( P<0.05) were observed between the enzymatic method and the picric acid method in measuring urinary creatinine-related renal injury biomarkers. At glucose concentrations of 30, 120, 240, and 300 mmol/L, the mean percentage biases for creatinine measured by the enzymatic method were -0.19%, -0.27%, -0.20%, and -0.21%, respectively. The mean percentage biases for creatinine measured by the picric acid method were 0.78%, 1.26%, 1.35%, and 1.38%, respectively, showing an increasing deviation between the results before and after glucose addition as the glucose concentration rose. For uACR measurement, the mean absolute biases using the enzymatic method were -0.01, 1.27, 0.95, and 1.10 mg/g at the respective glucose concentrations. Using the picric acid method, the mean absolute biases for uACR were -11.69, -14.98, -16.91, and-18.51 mg/g. The biases of the picric acid method were significantly higher than the those of the enzymatic method, and the absolute value of the mean biases increased with rising glucose concentration. For uPCR, uTRF/uCr, uA1M/uCr, uNAG/uCr, and uIgG/uCr, the deviations measured by the enzymatic method were consistently smaller than those measured by the picric acid method. Conclusions:The measurement of creatinine and related renal injury biomarkers by the enzymatic method is less affected by glucose concentration. In contrast, the measurement results obtained using the picric acid method are significantly affected by glucose concentration.

As a third major discipline on par with internal medicine and surgery,interventional radiology is one of the key branches of modern medicine.The unique practicality and innovation of interventional radiology make it play an irreplaceable role in the diagnosis and treatment of diseases.In recent years,with the rapid development of technology and the updating of educational concepts,the teaching mode of interventional radiology is facing new challenges and opportunities.This article combines the clinical training methods adopted by interventional physicians in Europe and Germany,integrates imaging,anatomy and pathology teaching,strengthens the foundation,uses virtual reality(VR),augmented reality(AR)technology,and simulation training to enhance the practical ability of medical students.At the same time,with the help of online education platforms,the innovative methods and optimization strategies such as personalized learning program are implemented,which can greatly improve the teaching effectiveness of interventional radiology and provide useful references for teaching reform in this field.