Objective To investigate the current distribution and predict the future suitable habitats of Haemaphysalis longicornis in Nanjing City, so as to provide insights into control and early warning of ticks and management of tick-borne diseases in Nanjing City. Methods The electronic map of Nanjing City was obtained from the National Platform for Common GeoSpatial Information Services. The distribution of H. longicornis and the longitude and latitude of distribution points from 2022 to 2024 were obtained from centers for disease control and prevention across each district in Nanjing City. Climatic and environmental variable data in Nanjing City were captured from the Worldclim database. Initially, 19 bioclimatic variables in this database were selected, including annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the warmest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest quarter, mean temperature of the coldest quarter, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, precipitation of the warmest quarter, and precipitation of the coldest quarter. The elevation and normalized difference vegetation index were obtained from Data Sharing Platform of the Center for Resources and Environmental Sciences, Chinese Academy of Sciences. Then, the distribution points of H. longicornis, elevation, vegetation index and 19 bioclimatic variables were loaded into the software MaxEnt 3.4.4 to evaluate and screen out the variables with a contribution rate of 1% and higher. ArcGIS 10.8.1 software was used to extract the elevation, vegetation index and 19 bioclimatic variables of the distribution points of H. longicornis for a correlation analysis. If the absolute value of the correlation coefficient was 0.8 and higher, the variable with the higher contribution was retained. The 2050 dataset of the BCCCSM2-MR atmospheric circulation model in the coupled model intercomparison project phase 6 (CMIP6) were obtained from the Worldclim database as climate data for 2050. Screened H. longicornis species data and environmental and climate data were loaded into the maximum entropy (MaxEnt) model with the software MaxEnt 3.4.4 for training and validation, and then, all data generated from the model were imported into the software ArcGIS 10.8.1 to generate raster data and yield the map pertaining to the distribution of H. longicornis risk in Nanjing City. The accuracy of the model was evaluated with a receiver operating characteristic (ROC) curve, and the predictive effect of the model was assessed with area under the ROC curve (AUC). The suitable habitats of H. longicornis were classified in Nanjing City with the software ArcGIS 10.8.1, and the areas of distribution of suitable habitats in various categories were recorded to create the map of current H. longicornis suitable habitats classification in Nanjing City. The climatic and geographic information data in 2050 were employed as future environmental and climatic factors, and current environmental and climatic factors and current H. longicornis distribution data were additionally used to predict the future suitable habitats of H. longicornis in Nanjing City. In addition, the contributions of environmental and climatic factors to distribution of suitable habitats of H. longicornis was evaluated with the Jackknife method in Nanjing City. Results A total of 10 environmental and climatic variables were screened for analysis of the suitability of H. longicornis in Nanjing City based on correlation analyses and contributions of the MaxEnt model, including annual mean temperature, precipitation of the warmest quarter, vegetation index, precipitation of the wettest month, temperature annual range, annual precipitation, mean temperature of the warmest quarter, elevation, mean temperature of the wettest quarter, and maximum temperature of the warmest month, and annual mean temperature (34.8%), precipitation of the warmest quarter (17.3%), vegetation index (13.1%), and precipitation of the wettest month (10.8%) contributed relatively highly to the distribution of suitable habitats of H. longicornis in Nanjing City. The mean AUC of the ROC curve was 0.810 ± 0.055 for 10 repeated modeling results of the MaxEnt model, indicating high predictive performance of the model. The potential distribution areas of H. longicornis were predicted to be mainly located in Luhe District, Pukou District, Jiangning District, Lishui District, and Gaochun District in Nanjing City with the MaxEnt model. Under current climatic conditions, the area of potential suitable habitats of H. longicornis was 4 182.42 km² in Nanjing City, including 1 252.94 km² highly suitable habitats, which accounted for 19.00% of the total area of Nanjing City. Under the climate scenario in 2050, the area of potential suitable habitats of H. longicornis was projected to increase to 5 467.58 km² in Nanjing City, accounting for 82.95% of the total area of the city, and these habitats were mainly concentrated in Luhe District, Pukou District, Jiangning District, Lishui District, and Gaochun District. The areas of suitable habitats of H. longicornis at various categories were predicted to vary greatly in 2050, and the area of highly suitable habitats of H. longicornis was projected to increase to 2 378.82 km², accounting for 36.08% of the total area of Nanjing City. Based on jackknife tests and contributions of environmental and climatic variables, 6 dominant environmental and climatic factors were screened, including annual mean temperature (34.8% contribution), precipitation of the warmest quarter (17.3% contribution), vegetation index (13.1% contribution), precipitation of the wettest month (10.8% contribution), temperature annual range (5.4% contribution), and mean temperature of the warmest quarter (5.0% contribution), with cumulative contributions of 86.4%. Conclusion The distribution of H. longicornis is strongly associated with vegetation, temperature and precipitation in Nanjing City. Future climate change may lead to an expansion of the distribution area of H. longicornis in Nanjing City.

Objective To evaluate the efficacy and safety of super-mini percutaneous nephrolithotomy(SMP)and standard percutaneous nephrolithotomy(sPCNL)in the treatment of 2-4 cm renal calculi, so as to provide reference for the management of medium-sized renal calculi. Methods A retrospective analysis was conducted on 168 patients with 2-4 cm renal calculi who underwent either SMP or sPCNL at our hospital during Sep. 2020 and Mar. 2025. The patients were divided into the SMP group(n=85)and sPCNL group(n=83). The baseline characteristics, stone features, operation time, perioperative complications, transfusion rate, postoperative hemoglobin drop, pain score, hospital stay, and stone-free rate(SFR)were compared between the two groups. Results There were no significant differences in baseline characteristics, stone features, and SFR between the two groups(P＞0.05). Compared to the sPCNL group, the SMP group had a longer operation time [(71.76±22.49)vs.(64.22±15.01)min, P=0.034]. However, it had lower postoperative pain score [(2.51 ±0.85)vs.(4.11±0.47), P＜0.001], shorter hospital stay [(3.16±1.45)vs.(4.30±1.06)days, P＜0.001], lower hospitalization costs [(19982.67±4267.80)vs.(21688.53±4575.74)RMB, P=0.004], a slighter decrease in hemoglobin [(6.64±10.56)vs.(12.22±11.50)g/L, P=0.032], and a significantly higher tubeless rate(83.53% vs. 0%, P＜0.001). There was no statistically significant difference in the overall complication rate between the two groups(P＞0.05). Conclusion For 2—4 cm renal calculi, SMP achieves a comparable SFR as sPCNL. Although the operation time with SMP is slightly longer, it offers significant advantages, including reduced postoperative pain, shorter hospitalization, lower costs, less bleeding, and a higher tubeless rate. SMP is a valuable technique worthy of broader clinical application.

Vacuum compression molding (VCM) is a novel technology supporting the research and development of pharmaceutical solid dispersions. It is widely applied due to its precision and convenience in sample preparation. This technology integrates the principles of heating, melting, cooling, and vacuum compression to transform solid powders into shaped solids directly. By selecting different molds, temperatures, and pressures, researchers can prepare samples with diverse characteristics. This paper presents an overview of the equipment composition and working principles of VCM technology, demonstrating its distinct advantages in the formulation screening process of amorphous solid dispersions through comparative analysis with hot melt extrusion using case studies, and introduces its applications in the development of drug delivery systems and rheological characterization analysis, with a perspective on the future development of its functions.

Objective:To investigate the current application of blood purification in the treatment of acute poisoning within Jiangsu Province and to evaluate the impact of extracorporeal blood purification on the clinical outcomes of critically poisoned patients.Methods:This multicenter, cross-sectional real-world observational study followed patients presenting with poisoning to the emergency departments of nine hospitals in Jiangsu Province between June 2015 and May 2019. Data were collected on demographic characteristics, vital signs within the first hour of emergency presentation, treatment modalities, length of hospital stay, and survival outcomes. Clinical data from patients who underwent extracorporeal blood purification were compared with those who did not, using the Wilcoxon rank-sum test and Chi-square test.Results:A total of 4 178 poisoning cases were included between June 2015 and May 2019. Among them, 21.7% (908/4 178) received blood purification therapy, while 78.3% (3 270/4 178) did not. Hemoperfusion (90.4%) was the most frequently employed method, followed by continuous renal replacement therapy (CRRT) (4.4%). In combined blood purification modalities, 4.8% underwent hemoperfusion combined with CRRT, 0.1% received hemoperfusion with plasma exchange, and another 0.1% underwent hemoperfusion combined with both CRRT and plasma exchange. Among patients who underwent blood purification, pesticide poisoning was the most prevalent (76.3%), with the most common toxic agents being paraquat (23.7%), dichlorvos (8.7%), methamidophos (5.2%), omethoate (4.0%), and glyphosate (3.7%). Compared to the non-blood purification group, patients in the blood purification group were more likely to present within the first hour with a low Glasgow Coma Scale (GCS) score (3-8) (22.6% vs. 9.7%, P <0.05), low mean arterial pressure (8.0% vs. 3.2%, P <0.05), longer hospital stays [5(3,9) days vs. 2(1,4) days, P <0.05] and a higher in-hospital mortality rate (21.1% vs. 5.3%, P <0.05). Follow-up via telephone 28 days after discharge revealed a survival rate of 78.9%, with a mortality rate of 21.1% in the blood purification group. Conclusions:Hemoperfusion is the most commonly utilized blood purification technique for treating poisoning in Jiangsu Province, with pesticides being the primary toxic agents treated. Although the mortality rate is higher in the blood purification group, the intervention may still contribute to improved patient outcomes.

Objective:To evaluate the utility of ultrasonographic monitoring of the rectus femoris muscle—specifically, the rates of change in thickness and cross-sectional area (CSA)—in assessing nutritional status and long-term functional outcomes in patients with sepsis.Methods:In this prospective observational study, sepsis patients admitted to the ICU of the Second Affiliated Hospital of Soochow University between October 2023 and October 2024 were classified by nutritional status at discharge using the Global Leadership Initiative on Malnutrition (GLIM) criteria. Differences in serial ultrasound-measured rectus femoris thickness and CSA on days 1, 3, 5, and 7 were compared between malnourished and non-malnourished groups. The predictive value of these ultrasound parameters for malnutrition was analyzed. Functional prognosis was assessed using the Sarcopenia Assessment Scale, Short Physical Performance Battery, and Manual Muscle Testing, with correlations to muscle changes examined.Results:Of the 71 enrolled patients (median age 73.00 [ IQR: 61.00–80.00]; 47.89% female, 52.11% male), those with malnutrition showed significantly greater variation rates in rectus femoris thickness and CSA on days 3, 5, and 7 compared to the non-malnourished group ( P < 0.05). ROC analysis revealed that the day-7 CSA variation rate had the highest predictive value for malnutrition (AUC = 0.817, 95% CI: 0.713-0.930). These muscle variation rates also correlated strongly with conventional nutritional markers such as BMI, albumin, and urea. Similarly, patients with impaired functional outcomes exhibited higher variation rates in muscle parameters on days 3, 5, and 7 ( P < 0.05), with the day-7 CSA variation rate being most predictive of functional prognosis (AUC = 0.749, 95% CI: 0.632-0.867). Conclusions:Ultrasonographic assessment of rectus femoris thickness and CSA variation rates provides a valuable tool for evaluating nutritional status and predicting functional prognosis in sepsis patients, outperforming traditional biomarkers. This method shows promise for guiding individualized nutrition support and rehabilitation strategies to improve long-term outcomes.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Liver cancer imposes a substantial global disease burden.Hepatocellular carcinoma(HCC),as the primary pathological type of primary liver cancer,accounts for approximately 90％of all cases.As a minimally invasive treatment,thermal ablation causes minimal impact on liver function and trauma,serving as the first-line treatment option for early-stage HCC patients unsuit-able for surgical resection.However,clinical data indicate that 5-year recurrence rate of HCC pa-tients after thermal ablation treatment is as high as 50％～70％,and incomplete ablation remains a core factor leading to recurrence.Therefore,exploring and optimizing complete ablation strategies has become a critical direction for improving the efficacy of thermal ablation in HCC and enhanc-ing long-term survival rates of patients.This paper systematically reviews the current applications of thermal ablation in HCC treatment and focuses on discussing key technologies and strategies for achieving complete ablation,with the aim of providing theoretical foundations and technical refer-ences for improving the complete ablation rate of thermal ablation in clinical practice and formu-lating personalized diagnosis and treatment plans.