ObjectiveTo investigate the effects of Trpc6 knockout on chronic lipopolysaccharide （LPS）-induced myocardial inflammation and fibrosis in mice and its potential mechanisms. MethodsMale C57BL/6 wild-type （WT） mice and Trpc6 knockout （Trpc6^-/-） mice of the same background were randomly divided into four groups： WT control， WT+LPS （200 μg/kg）， Trpc6^-/- control， and Trpc6^-/-+LPS （200 μg/kg）. Group with LPS received intraperitoneal LPS injections for 21 consecutive days to induce chronic myocardial inflammatory injury. Cardiac ultrasound assessed changes in left ventricular ejection fraction （EF）， left ventricular shortening fraction （FS）， and cardiac output （CO）. Hematoxylin and eosin （HE） staining and periodic acid-Schiff （PAS） staining were used to examine morphological alterations in myocardial tissue. Masson’s trichrome staining was used to assess myocardial fiber alterations； Western blot analysis was used to measure myocardial tissue expression of transient receptor potential calcium channel 6 （TRPC6）， NOD-like receptor family pyrin domain-containing 3 inflammasome （NLRP3），absent in melanoma 2 inflammasome （AIM2）， Caspase-1， interleukin （IL）-6， and IL-1β in mouse myocardial tissue. ResultsCompared with the WT control group， the WT+LPS group exhibited decreased cardiac EF （P<0.01）， FS （P<0.01）， and CO （P<0.05）， along with significantly increased myocardial tissue damage， glycoprotein deposition， and fibrosis （P<0.01）. Further analysis revealed that compared with the WT control group， the WT+LPS group exhibited markedly increased myocardial tissue expression of TRPC6， NLRP3， AIM2， Caspase-1， IL-6， and IL-1β （P<0.01）. Compared with the WT+LPS group， mice in the Trpc6^-/- +LPS group exhibited elevated EF （P<0.01） and FS （P<0.05）， along with reduced myocardial tissue injury， glycoprotein deposition， and fibrosis （P<0.05）. ConclusionChronic LPS treatment can activate NLRP3/AIM2 inflammasomes through the up-regulation of TRPC6 expression， and then lead to chronic myocardial inflammatory injury and fibrosis， while Trpc6 knockdown can reduce myocardial inflammatory injury and fibrosis， and the mechanism is related to inhibiting the activation of NLRP3/AIM2 inflammasomes.

Objective To explore the effective induction scheme for differentiation of adipose-derived mesenchymal stem cell (ADMSC) to insulin producing cell (IPC). Methods Different schemes of small molecule compound were used to induce the differentiation of ADMSC. The purity of cells was analyzed by flow cytometry and the morphological changes of cells were observed under the microscope. The quality, performance and insulin related indicators of cells were detected by hematoxylin-eosin and immunohistochemical staining. The maturity and activity of cells were detected by dithizone (DTZ) and diacetylfluorescein/propidium iodide staining. The induction effect of ADMSC differentiated into IPC was analyzed. Results The purity of ADMSC reached more than 99%, and the sphere forming properties of schemes Ⅰ, Ⅱ and Ⅲ were good. Cell induction mass, the expression effects of pancreatic and duodenal homeobox 1 (PDX1), musculoaponeurotic fibrosarcoma oncogene homolog A (MAFA) and insulin and C peptide of schemes Ⅰ were both better than those of other schemes. The DTZ staining depth may be related to IPC maturity, among which the number of apoptotic cells in scheme Ⅰ was significantly less than that of scheme Ⅱ and Ⅲ. Conclusions Induction scheme Ⅰ may improve the differentiation efficiency of ADMSC to IPC and lay a certain foundation for future clinical IPC transplantation applications.

Objective To explore the impact of an intelligent puncture navigation used by different physicians with varying years of experience to perform the lung puncture biopsy surgery.Methods A retrospective selection was conducted of 182 patients who completed lung puncture biopsy surgery.The primary parameters were recorded included puncture time,the number of needle adjust-ments,dose length product(DLP),and complications.The physicians were categorized into high-experience and low-experience groups based on their years of clinical practice.The differences of navigation guidance and manual puncture were compared between the two groups.Results The use of navigation guidance significantly reduced the procedure time for both groups of physicians(P<0.05).Additionally,for the low-experience group,navigation guidance notably decreased the number of needle adjustments(P<0.05)and reduced the radiation dose received by patients(P<0.05).Conclusion The application of intelligent puncture navigation can shorten the procedure time,reduce the number of needle adjustments,and lower the radiation dose received by patients in lung puncture biopsy procedures.It also bridges the operational performance gap between low-experience and high-experience physicians,making it a val-uable imaging-guided tool for widespread adoption.

Objective To explore the impact of an intelligent puncture navigation used by different physicians with varying years of experience to perform the lung puncture biopsy surgery.Methods A retrospective selection was conducted of 182 patients who completed lung puncture biopsy surgery.The primary parameters were recorded included puncture time,the number of needle adjust-ments,dose length product(DLP),and complications.The physicians were categorized into high-experience and low-experience groups based on their years of clinical practice.The differences of navigation guidance and manual puncture were compared between the two groups.Results The use of navigation guidance significantly reduced the procedure time for both groups of physicians(P<0.05).Additionally,for the low-experience group,navigation guidance notably decreased the number of needle adjustments(P<0.05)and reduced the radiation dose received by patients(P<0.05).Conclusion The application of intelligent puncture navigation can shorten the procedure time,reduce the number of needle adjustments,and lower the radiation dose received by patients in lung puncture biopsy procedures.It also bridges the operational performance gap between low-experience and high-experience physicians,making it a val-uable imaging-guided tool for widespread adoption.

Aim Based on coronary CT-fractional flow reserve(CT-FFR)combined with machine learning methods,a nomogram prediction model for coronary in-stent restenosis(ISR)was developed to assess the risk of ISR.Methods Retrospective analysis was performed on patients who underwent re-examination after PCI at our hospital from January 2022 to January 2025.According to the exclusion criteria,a total of 210 patients were enrolled,including 100 cases of ISR and 110 cases of non-ISR.The dataset was randomly divided into training and test sets at a 7∶3 ratio.Af-ter univariate analysis to screen potential predictors,LASSO regression was applied to identify feature variables with non-ze-ro coefficients.Subsequently,three machine learning(ML)algorithms including random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGB)were used to rank the importance of the significant factors.The intersection of the top 10 variables from each algorithm was used as input for bidirectional stepwise multivariate Logistic re-gression.An ISR risk score was then constructed and visualized using a nomogram.Results A total of 14 predictive factors were identified through LASSO regression,including diastolic blood pressure,C-reactive protein,triglycerides(TG),N-terminal pro-brain natriuretic peptide(NT-proBNP),low density lipoprotein cholesterol(LDLC),minimum stent diameter＜3 mm,systolic blood pressure,△CT-FFR,CT-FFR,interleukin-6(IL-6),body mass index,glycosylated hemoglobin(HbA1c),history of hypertension,and high density lipoprotein cholesterol(HDLC).Following stepwise screening using three ML algorithms and Logistic regression,six independent risk factors for ISR were identified:elevated△CT-FFR,IL-6,NT-proBNP,TG and CT-FFR values,and minimum stent diameter＜3 mm.The area under the curve for the training set and test set were 0.995(95％CI:0.989～1.000)and 0.965(95％CI:0.927～1.000),respectively.Decision curve analysis demonstrated high net benefit across threshold probabilities of 0～1.00 in the training set and 0～0.92 in the test set.The nomogram integrating these six predictors exhibited high accuracy and clinical utility.Con-clusion The ISR nomogram prediction model based on LASSO-ML combined with CT-FFR technology has high accuracy and clinical utility for ISR.

Pediatric urological non-Hodgkin lymphoma is relatively rare.When a single renal or ureteral tumor with multiple lymph node or bone metastases is present, it is very easy to be misdiagnosed as urinary tumor with metastasis, resulting in unnecessary radical nephrectomy. This paper reports two cases of non-Hodgkin lymphoma presenting with single urinary nodules. Case 1 was diagnosed with a 4.5cm tumor in the right kidney due to fever and fatigue. CT and PET-CT showed multiple bone destruction and lymph node metastasis. Renal biopsy was performed and ALK-positive anaplastic large cell lymphoma was diagnosed. Chemotherapy was effective for 6 months. Case 2 was diagnosed with left hydronephrosis due to intermittent low back pain for 2 weeks. Ultrasound examination revealed ureteral dilation with left hydronephrosis and low echo occupying of the lower ureter. The patient had sudden blurred vision before surgery. MRI examination revealed space occupying in the right optic nerve frame, and PET-CT found multiple bone, lymph nodes and nerve invasion. A lymph node biopsy was performed and Burkitt lymphoma was diagnosed. After 6 months of chemotherapy and radiotherapy, the tumor shrank significantly.

Aim Based on coronary CT-fractional flow reserve(CT-FFR)combined with machine learning methods,a nomogram prediction model for coronary in-stent restenosis(ISR)was developed to assess the risk of ISR.Methods Retrospective analysis was performed on patients who underwent re-examination after PCI at our hospital from January 2022 to January 2025.According to the exclusion criteria,a total of 210 patients were enrolled,including 100 cases of ISR and 110 cases of non-ISR.The dataset was randomly divided into training and test sets at a 7∶3 ratio.Af-ter univariate analysis to screen potential predictors,LASSO regression was applied to identify feature variables with non-ze-ro coefficients.Subsequently,three machine learning(ML)algorithms including random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGB)were used to rank the importance of the significant factors.The intersection of the top 10 variables from each algorithm was used as input for bidirectional stepwise multivariate Logistic re-gression.An ISR risk score was then constructed and visualized using a nomogram.Results A total of 14 predictive factors were identified through LASSO regression,including diastolic blood pressure,C-reactive protein,triglycerides(TG),N-terminal pro-brain natriuretic peptide(NT-proBNP),low density lipoprotein cholesterol(LDLC),minimum stent diameter＜3 mm,systolic blood pressure,△CT-FFR,CT-FFR,interleukin-6(IL-6),body mass index,glycosylated hemoglobin(HbA1c),history of hypertension,and high density lipoprotein cholesterol(HDLC).Following stepwise screening using three ML algorithms and Logistic regression,six independent risk factors for ISR were identified:elevated△CT-FFR,IL-6,NT-proBNP,TG and CT-FFR values,and minimum stent diameter＜3 mm.The area under the curve for the training set and test set were 0.995(95％CI:0.989～1.000)and 0.965(95％CI:0.927～1.000),respectively.Decision curve analysis demonstrated high net benefit across threshold probabilities of 0～1.00 in the training set and 0～0.92 in the test set.The nomogram integrating these six predictors exhibited high accuracy and clinical utility.Con-clusion The ISR nomogram prediction model based on LASSO-ML combined with CT-FFR technology has high accuracy and clinical utility for ISR.

Pediatric urological non-Hodgkin lymphoma is relatively rare.When a single renal or ureteral tumor with multiple lymph node or bone metastases is present, it is very easy to be misdiagnosed as urinary tumor with metastasis, resulting in unnecessary radical nephrectomy. This paper reports two cases of non-Hodgkin lymphoma presenting with single urinary nodules. Case 1 was diagnosed with a 4.5cm tumor in the right kidney due to fever and fatigue. CT and PET-CT showed multiple bone destruction and lymph node metastasis. Renal biopsy was performed and ALK-positive anaplastic large cell lymphoma was diagnosed. Chemotherapy was effective for 6 months. Case 2 was diagnosed with left hydronephrosis due to intermittent low back pain for 2 weeks. Ultrasound examination revealed ureteral dilation with left hydronephrosis and low echo occupying of the lower ureter. The patient had sudden blurred vision before surgery. MRI examination revealed space occupying in the right optic nerve frame, and PET-CT found multiple bone, lymph nodes and nerve invasion. A lymph node biopsy was performed and Burkitt lymphoma was diagnosed. After 6 months of chemotherapy and radiotherapy, the tumor shrank significantly.

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-positive bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-positive bacteria from blood cultures in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:A total of 3 163 strains of Gram-positive pathogens were collected from 51 member units，and the top five bacteria were Staphylococcus aureus（ n=1 147，36.3%），coagulase-negative Staphylococci（ n=928，29.3%）， Enterococcus faecalis（ n=369，11.7%）， Enterococcus faecium（ n=296，9.4%）and alpha-hemolyticus Streptococci（ n=192，6.1%）. The detection rates of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）were 26.4%（303/1 147）and 66.7%（619/928），respectively. No glycopeptide and daptomycin-resistant Staphylococci were detected. The sensitivity rates of Staphylococcus aureus to cefpirome，rifampin，compound sulfamethoxazole，linezolid，minocycline and tigecycline were all >95.0%. Enterococcus faecium was more prevalent than Enterococcus faecalis. The resistance rates of Enterococcus faecium to vancomycin and teicoplanin were both 0.5%（2/369），and no vancomycin-resistant Enterococcus faecium was detected. The detection rate of MRSA in southern China was significantly lower than that in other regions（ χ2=14.578， P=0.002），while the detection rate of MRCNS in northern China was significantly higher than that in other regions（ χ2=15.195， P=0.002）. The detection rates of MRSA and MRCNS in provincial hospitals were higher than those in municipal hospitals（ χ2=13.519 and 12.136， P<0.001）. The detection rates of MRSA and MRCNS in economically more advanced regions（per capita GDP≥92 059 Yuan in 2022）were higher than those in economically less advanced regions（per capita GDP<92 059 Yuan）（ χ2=9.969 and 7.606， P=0.002和0.006）. Conclusions:Among the Gram-positive pathogens causing bloodstream infections in China， Staphylococci is the most common while the MRSA incidence decreases continuously with time；the detection rate of Enterococcus faecium exceeds that of Enterococcus faecalis. The overall prevalence of vancomycin-resistant Enterococci is still at a low level. The composition ratio of Gram-positive pathogens and resistant profiles varies slightly across regions of China，with the prevalence of MRSA and MRCNS being more pronounced in provincial hospitals and areas with a per capita GDP≥92 059 yuan.