BACKGROUND:Parkinson's disease has the main pathological changes in the midbrain,especially in the dense substantia nigra,leading to impaired motor and non-motor function in patients.At present,research is limited by cellular heterogeneity,and its pathogenesis still needs to be further elucidated.In recent years,single-cell RNA sequencing(scRNA-seq)has gradually been applied in neurodegenerative diseases,which is of great significance for understanding intercellular heterogeneity,disease development mechanisms,and treatment strategies. OBJECTIVE:To review the research progress of scRNA-seq technology applied to Parkinson's disease in recent years,providing a theoretical basis for the application of scRNA-seq in the treatment and diagnosis of Parkinson's disease. METHODS:The first author used a computer system to search for relevant literature in the CNKI,WanFang,PubMed,and Web of Science databases,with the Chinese search terms"single-cell RNA sequencing,Parkinson's disease,cell heterogeneity,cell subtypes,dopaminergic neurons,glial cells"and English search terms"single-cell RNA seq,Parkinson disease,heterogenicity,subtypes,dopaminergic neurons,glial cells."71 articles were ultimately included for review and analysis. RESULTS AND CONCLUSION:(1)scRNA-seq is a high-throughput experimental technique that utilizes RNA sequencing at the single-cell level to quantify gene expression profiles in specific cell populations,revealing cellular mysteries at the molecular level.Compared with traditional sequencing techniques,scRNA-seq technology is used to reveal the diversity of cell types and changes in specific gene expression in complex tissues under various physiological and pathological conditions through automatic clustering analysis of cell transcriptome.(2)By using scRNA-seq,the development process of dopaminergic neurons and the unique functional characteristics of various cell subtypes are elucidated,in order to better understand potential therapeutic molecular targets.(3)The use of scRNA-seq analysis has improved our understanding of the response of Parkinson's disease glial cells,enabling us to comprehensively map and characterize different cell type populations,identify specific glial cell subpopulations related to neurodegeneration,and draw valuable single cell maps as reference data for future research.(4)The application of scRNA-seq to detect embryonic mice and stem cells will help improve the in vitro differentiation protocol and quality control of cell therapy,as well as evaluate the overall cell quality and developmental stage of dopaminergic neurons derived from stem cells.

Objective:To investigate the impact of blood pressure outcomes on the risk of arteriosclerosis in non-hypertensive populations.Methods:This study was a retrospective cohort study. All data were derived from Kailuan Cohort. Non-hypertensive individuals who completed two brachial-ankle pulse wave velocity (baPWV) measurements between January 2014 and December 2019 (using the first measurement as the baseline and the second as the follow-up) were enrolled, and clinical data such as blood pressure and baPWV were collected. According to the blood pressure level at baseline and follow-up, participants were divided into new-onset hypertension group (no hypertension at baseline but diagnosed at follow-up) and non-hypertension group (no hypertension at both baseline and follow-up). Multiple linear regression and multivariate logistic regression were used to analyze the impact of new-onset hypertension on arteriosclerosis progression. Subgroup analysis further classified participants into six blood pressure transition categories: normal-maintained, normal-to-high-normal, normal-to-hypertensive, high-normal-to-normal, high-normal-maintained, and high-normal-to-hypertensive groups. Multivariate logistic regression analysis was used to assess the impact of different blood pressure outcomes on arteriosclerosis progression.Results:A total of 7 049 participants were enrolled, with the age of (40.45±9.04) years, including 3 645 males (51.71%). There were 800 cases in the new-onset hypertension group and 6 249 individuals in the non-hypertension group. During follow-up, arteriosclerosis occurred in 2 154 cases (30.56%). Multivariable linear regression analysis revealed a positive correlation between new-onset hypertension and baPWV levels. The baPWV in the new-onset hypertension group was significantly higher by 63.94 cm/s compared to the non-hypertension group ( β=63.94, P<0.01). Additionally, the risk of arteriosclerosis in the new-onset hypertension group was 2.09 times that of the non-hypertension group ( OR=2.09, 95% CI: 1.77-2.46, P<0.01). Subgroup analysis revealed significantly higher arteriosclerosis risks in normal-to-high-normal ( OR=1.65, 95% CI 1.38-1.98, P<0.01), normal-to-hypertensive ( OR=2.47, 95% CI 1.70-3.59, P<0.01), high-normal-maintained ( OR=1.50, 95% CI 1.21-1.86, P<0.01), and high-normal-to-hypertensive groups ( OR=2.86, 95% CI 2.20-3.73, P<0.01) than normal-maintained group, except for a non-significant difference in high-normal-to-normal group ( OR=0.95, 95% CI 0.74-1.20, P>0.05). Conclusion:Blood pressure outcome in non-hypertensive populations is closely related to arteriosclerosis risk. Progression to or maintenance of high-normal blood pressure or higher levels substantially increases arteriosclerosis risk, while regression from high-normal to normal blood pressure shows no significant increase in arteriosclerosis risk.

Objective:To establish a combined model of tumor heterogeneity metabolic parameters using 18F-FDG PET/CT and explore its value in differentiating benign from malignant pulmonary lesions. Methods:A total of 251 patients (157 males, 94 females; age 15-88 years) who were diagnosed with malignant lung lesions by 18F-FDG PET/CT and with definitive pathological results at Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from February 2017 to February 2024 were retrospectively enrolled. Analysis was conducted on clinical data, traditional parameters (SUV max, metabolic tumor volume (MTV), total lesion glycolysis (TLG)) of primary lesions on 18F-FDG PET/CT, and intra-tumoral metabolic heterogeneity index (HI; such as cumulative SUV volume histogram AUC (AUC-CSH), linear regression slope, CV). AUC-CSH and CV were calculated using SUV thresholds of 2.5 and 40%SUV max. Logistic univariate and multivariate regression analyses were used to extract independent predictors in clinical features and PET/CT parameters for the differential diagnosis of pulmonary lesions. A multi-parameter combined model was established through logistic regression and validated for diagnostic efficacy using ROC curve analysis. Results:Among 251 patients, 101 were benign and 150 were malignant. In univariate analysis, gender, age, tumor markers, spiculation sign, lobulation sign, vessel convergence sign, air bronchogram, long diameter, short diameter, SUV max, AUC-CSH 2.5, AUC-CSH 40%, CV2.5, and CV40% were predictive factors for the diagnosis of benign and malignant tumors (odds ratio ( OR): 0.57-17.39, all P<0.05). In multivariate analysis, gender, age, tumor markers, lobulation sign, vessel convergence sign, SUV max, AUC-CSH 40%, and CV40% were independent predictors for the diagnosis of benign and malignant tumors ( OR: 2.30-13.18, all P<0.05). The AUC, sensitivity, specificity, and accuracy of the multi-parameter combined model established with the above independent predictors were 0.89, 77.33%(116/150), 84.16%(85/101), 80.08%(201/251), respectively. Conclusion:18F-FDG PET/CT multi-parameter combined model has high value in the differentiation of benign and malignant pulmonary lesions.

Objective:To establish a combined model of tumor heterogeneity metabolic parameters using 18F-FDG PET/CT and explore its value in differentiating benign from malignant pulmonary lesions. Methods:A total of 251 patients (157 males, 94 females; age 15-88 years) who were diagnosed with malignant lung lesions by 18F-FDG PET/CT and with definitive pathological results at Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School from February 2017 to February 2024 were retrospectively enrolled. Analysis was conducted on clinical data, traditional parameters (SUV max, metabolic tumor volume (MTV), total lesion glycolysis (TLG)) of primary lesions on 18F-FDG PET/CT, and intra-tumoral metabolic heterogeneity index (HI; such as cumulative SUV volume histogram AUC (AUC-CSH), linear regression slope, CV). AUC-CSH and CV were calculated using SUV thresholds of 2.5 and 40%SUV max. Logistic univariate and multivariate regression analyses were used to extract independent predictors in clinical features and PET/CT parameters for the differential diagnosis of pulmonary lesions. A multi-parameter combined model was established through logistic regression and validated for diagnostic efficacy using ROC curve analysis. Results:Among 251 patients, 101 were benign and 150 were malignant. In univariate analysis, gender, age, tumor markers, spiculation sign, lobulation sign, vessel convergence sign, air bronchogram, long diameter, short diameter, SUV max, AUC-CSH 2.5, AUC-CSH 40%, CV2.5, and CV40% were predictive factors for the diagnosis of benign and malignant tumors (odds ratio ( OR): 0.57-17.39, all P<0.05). In multivariate analysis, gender, age, tumor markers, lobulation sign, vessel convergence sign, SUV max, AUC-CSH 40%, and CV40% were independent predictors for the diagnosis of benign and malignant tumors ( OR: 2.30-13.18, all P<0.05). The AUC, sensitivity, specificity, and accuracy of the multi-parameter combined model established with the above independent predictors were 0.89, 77.33%(116/150), 84.16%(85/101), 80.08%(201/251), respectively. Conclusion:18F-FDG PET/CT multi-parameter combined model has high value in the differentiation of benign and malignant pulmonary lesions.

Human epidermal growth factor receptor 2 (HER2) is a key therapeutic target for breast cancer. With the wide application of anti-HER2 and HER2 antibody-drug conjugates such as trastuzumab, pertuzumab, trastuzumab emtansine, and trastuzumab deruxtecan, the survival of patients with advanced HER2-positive breast cancers have been significantly improved. However, the subsequent drug-induced interstitial lung disease (DILD) has gradually become an important complication affecting the therapeutic effect and safety. However, the clinical understanding of interstitial lung disease (ILD) caused by this type of drugs is still insufficient, the management lacks unified standards, and the molecular mechanism has not been fully clarified. This study, through two clinical cases of severe DILD, explores the pathogenesis, treatment strategies, risk factors and follow-up monitoring requirements of ILD caused by HER2-targeted drugs, providing a scientific basis for optimizing the clinical diagnosis and treatment plan.

Objective To explore the perioperative therapeutic effects and follow-up manage-ment in 16 patients with left ventricular assist device(LVAD)implantation.Methods A retrospec-tive analysis was conducted in data of 16 patients who underwent LVAD implantation in the depart-ment of cardiovascular surgery.Data of 6-minute walk test(6MWT),European Quality of Life-5 Di-mension-5 Levels(EQ-5D-5L),New York Heart Association(NYHA)classification,echocardio-graphy,chest radiography,cardiothoracic ratio,and occurrence of complications(infection,bleed-ing,thrombosis,right heart failure,neurological issues)were collected via the electronic medical re-cord system before surgery and at 30,60,and 90 days postoperatively.Results All patients sur-vived with the pump at 90 days postoperatively.One patient with preoperative renal insufficiency un-derwent dialysis and received a heart transplant after 8 months.One patient developed a sterile granu-loma at the percutaneous lead site on the abdominal wall,which improved after treatment,no complica-tions occurred in other patients.At 90 days postoperatively,there was no statistically significant differ-ence in the right ventricular area change fraction and tricuspid annular plane systolic excursion com-pared with preoperative values(P＞0.05).The left ventricular ejection fraction,left ventricular end-diastolic diameter,and cardiothoracic ratio showed significant improvement compared with preoperative levels(P＜0.05).At 30 days postoperatively,30％of patients recovered to NYHA class Ⅰ and 70％to class Ⅱ;at 60 days,80％of patients to class Ⅰ and 20％to class Ⅱ;at 90 days,90％to classⅠ and 10％to class Ⅱ.The 6MWT and EQ-5D-5L scores of patients significantly increased within 90 days postoperatively(P＜0.01).Conclusion Through rigorous preoperative assessment by a multidisciplinary LVAD team,refinement of surgical techniques,and comprehensive management during hospitalization,self-management before discharge,daily follow-up after discharge,and fol-low-up management upon returning to the hospital for patients with LVAD implantation,the cardiac function and quality of life of patients are significantly improved at 90 days postoperatively.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective:To evaluate the prognostic value of 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT metabolic parameters in small cell lung cancer (SCLC) . Methods:A retrospective analysis was conducted on the clinical and imaging data of 156 SCLC patients, who underwent 18F-FDG PET/CT imaging and were diagnosed by histopathological examination at Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School from September 2013 to February 2024. The metabolic tumor volume (MTV), total lesion glycolysis (TLG), linear regression slope, area under the curve of cumulative standard uptake value (SUV) volume histogram (AUC-CSH), and coefficient of variation (CV) were calculated using LIFEx software with different SUV thresholds. Univariate and multivariate analyses were performed using Cox proportional hazards model. Patient stratification was based on the critical values determined by receiver operator characteristic (ROC) curve analysis. The survival curve was plotted using the Kaplan-Meier method and log-rank test was performed. Results:Univariate analysis showed that MTV 40% ( HR=2.91, 95% CI: 1.55-5.47, P=0.001), MTV 60% ( HR=2.31, 95% CI: 1.29-4.17, P=0.005), TLG 40% ( HR=2.07, 95% CI: 1.19-3.60, P=0.010), linear regression slope ( HR=0.45, 95% CI: 0.26-0.79, P=0.005), and CV 40% ( HR=0.27, 95% CI: 0.08-0.84, P=0.024) were factors affecting progression-free survival (PFS) in SCLC patients. MTV 40% ( HR=1.98, 95% CI: 1.22-3.22, P=0.005), MTV 60% ( HR=1.80, 95% CI: 1.12-2.88, P=0.015), MTV 80% ( HR=1.71, 95% CI: 1.08-2.74, P=0.024), TLG 40% ( HR=3.68, 95% CI: 1.59-8.49, P=0.002), linear regression slope ( HR=0.49, 95% CI: 0.30-0.80, P=0.004), and AUC-CSH 80% ( HR=0.44, 95% CI: 0.23-0.84, P=0.013) were found to be factors affecting overall survival (OS) in SCLC patients. Multivariate analysis revealed that MTV 40% ( HR=4.76, 95% CI: 1.11-20.50, P=0.036) was an independent factor influencing PFS, and TLG 40% ( HR=3.19, 95% CI: 1.02-9.92, P=0.046) was an independent factor influencing OS in SCLC patients. ROC curve analysis identified the optimal cutoff value for MTV 40% in predicting PFS as 5.5cm 3 and the optimal cutoff value for TLG 40% in predicting OS as 41.5 g in SCLC patients. Survival analysis showed that patients with MTV 40%≤5.5 cm 3 ( n=33) had a median PFS that was not reached, while patients with MTV 40%>5.5 cm 3 ( n=123) had a median PFS of 10.3 months, with a statistically significant difference ( χ2=12.09, P=0.001). For patients with TLG 40%≤41.5 g ( n=35), the median OS was not reached, whereas for TLG 40%>41.5 g ( n=121), the median OS was 31.6 months, with a statistically significant difference ( χ2=10.55, P=0.001) . Conclusions:The 18F-FDG PET/CT metabolic parameter MTV 40% is an independent factor influencing PFS, while TLG 40% is an independent factor influencing OS in SCLC patients. The above two parameters may serve as indicators for assessing the prognosis of SCLC patients.

Objective:To investigate the impact of blood pressure outcomes on the risk of arteriosclerosis in non-hypertensive populations.Methods:This study was a retrospective cohort study. All data were derived from Kailuan Cohort. Non-hypertensive individuals who completed two brachial-ankle pulse wave velocity (baPWV) measurements between January 2014 and December 2019 (using the first measurement as the baseline and the second as the follow-up) were enrolled, and clinical data such as blood pressure and baPWV were collected. According to the blood pressure level at baseline and follow-up, participants were divided into new-onset hypertension group (no hypertension at baseline but diagnosed at follow-up) and non-hypertension group (no hypertension at both baseline and follow-up). Multiple linear regression and multivariate logistic regression were used to analyze the impact of new-onset hypertension on arteriosclerosis progression. Subgroup analysis further classified participants into six blood pressure transition categories: normal-maintained, normal-to-high-normal, normal-to-hypertensive, high-normal-to-normal, high-normal-maintained, and high-normal-to-hypertensive groups. Multivariate logistic regression analysis was used to assess the impact of different blood pressure outcomes on arteriosclerosis progression.Results:A total of 7 049 participants were enrolled, with the age of (40.45±9.04) years, including 3 645 males (51.71%). There were 800 cases in the new-onset hypertension group and 6 249 individuals in the non-hypertension group. During follow-up, arteriosclerosis occurred in 2 154 cases (30.56%). Multivariable linear regression analysis revealed a positive correlation between new-onset hypertension and baPWV levels. The baPWV in the new-onset hypertension group was significantly higher by 63.94 cm/s compared to the non-hypertension group ( β=63.94, P<0.01). Additionally, the risk of arteriosclerosis in the new-onset hypertension group was 2.09 times that of the non-hypertension group ( OR=2.09, 95% CI: 1.77-2.46, P<0.01). Subgroup analysis revealed significantly higher arteriosclerosis risks in normal-to-high-normal ( OR=1.65, 95% CI 1.38-1.98, P<0.01), normal-to-hypertensive ( OR=2.47, 95% CI 1.70-3.59, P<0.01), high-normal-maintained ( OR=1.50, 95% CI 1.21-1.86, P<0.01), and high-normal-to-hypertensive groups ( OR=2.86, 95% CI 2.20-3.73, P<0.01) than normal-maintained group, except for a non-significant difference in high-normal-to-normal group ( OR=0.95, 95% CI 0.74-1.20, P>0.05). Conclusion:Blood pressure outcome in non-hypertensive populations is closely related to arteriosclerosis risk. Progression to or maintenance of high-normal blood pressure or higher levels substantially increases arteriosclerosis risk, while regression from high-normal to normal blood pressure shows no significant increase in arteriosclerosis risk.

Objective:To conduct a scoping review of domestic and international risk prediction models for the recurrence of diabetic foot ulcers (DFU) and provide a basis for clinical nursing practices and related research.Methods:A computer search of nine databases in both Chinese and English was conducted, with the search period extending up to September 1, 2023. Two researchers independently performed data selection and extraction. The methodological quality of the included studies was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST) .Results:A total of seven studies were included, comprising thirteen risk prediction models. History of previous foot ulcers, smoking, duration of diabetes, and foot lesions were identified as the primary predictive factors, with predictive discrimination ranging from 0.660 to 0.943.Conclusions:Nursing staff should pay close attention to the risk factors for recurrence of DFU, develop low-bias and highly applicable risk prediction models, and validate and refine existing models.