Gas therapy is emerging as a highly promising therapeutic strategy for cancer treatment. However, there are limitations, including the lack of targeted subcellular organelle accuracy and spatiotemporal release precision, associated with gas therapy. In this study, we developed a series of photoactivatable nitric oxide (NO) donors NRh-R-NO (R = Me, Et, Bn, iPr, and Ph) based on an N-nitrosated upconversion luminescent rhodamine scaffold. Under the irradiation of 808 nm light, only NRh-Ph-NO could effectively release NO and NRh-Ph with a significant turn-on frequency upconversion luminescence (FUCL) signal at 740 nm, ascribed to lower N-N bond dissociation energy. We also investigated the involved multistage near-infrared-controlled cascade release of gas therapy, including the NO released from NRh-Ph-NO along with one NRh-Ph molecule generation, the superoxide anion O₂^⋅- produced by the photodynamic therapy (PDT) effect of NRh-Ph, and highly toxic peroxynitrite anion (ONOO^‒) generated from the co-existence of NO and O₂^⋅-. After mild nano-modification, the nanogenerator (NRh-Ph-NO NPs) empowered with superior biocompatibility could target mitochondria. Under an 808 nm laser irradiation, NRh-Ph-NO NPs could induce NO/ROS to generate RNS, causing a decrease in the mitochondrial membrane potential and initiating apoptosis by caspase-3 activation, which further induced tumor immunogenic cell death (ICD). In vivo therapeutic results of NRh-Ph-NO NPs showed augmented RNS-potentiated gas therapy, demonstrating excellent biocompatibility and effective tumor inhibition guided by real-time FUCL imaging. Collectively, this versatile strategy defines the targeted RNS-mediated cancer therapy.

Skin wounds are global public problems,especially in terms of the difficult healing of chronic wounds,which may seriously affect patients'lives.Most skin-wound animal models are currently established by physical method,and different animal models have different biological characteristics.This review therefore classifies mouse,rat,and other animal models of skin wounds according to the literature,summarizes and analyzes the construction of skin-wound animal models based on physical method and evaluation indicators,and considers the advantages and disadvantages of different animal models,to provide a basis for the rational construction of skin-wound animal models and drug research and development.

Objective:To explore the impact of early postoperative hypocaloric parenteral nutrition on perioperative infectious complications in patients undergoing hepatectomy for primary hepatic carcinoma.Methods:The data of 205 patients who underwent hepatectomy for primary hepatic carcinoma in the Division of Hepatobiliary and Transplantation Surgery at Nanjing Drum Tower Hospital between February 2020 and December 2022 were collected by a single center prospective cohort study. The patients were divided into a hypocaloric group ( n=108) and a normal calorie group ( n=97) based on whether they received hypocaloric parenteral nutrition within 72 hours postoperatively. The influence of early parenteral nutrition caloric on perioperative infectious complications was analyzed. Measurement data with normal distribution were expressed as mean±standard deviation ( ± s) and compared using t-test. Measurement data with skewed distribution were expressed as M( Q1, Q3) and compared using the Wilcoxon rank-sum test. Comparison of categorical data was performed using the chi-square test or Fisher′s exact test. To adjust for confounding factors, patients were grouped for comparison based on whether they experienced infectious complications within the 30-day postoperative follow-up period. Factors that may influence postoperative infectious complications were first analyzed using univariate analysis, and variables with statistical significance were then included in multivariate analysis. Results:A total of 82 patients experiencing infectious complications, resulting in an incidence rate of 40.0%. Patients in the hypocaloric parenteral nutrition group had significantly lower rates of hyperglycemic events (17.6% vs 29.9%, P=0.038) and gastrointestinal reactions (12.0% vs 22.7%, P=0.043) compared to the normal calorie parenteral nutrition group, with no intergroup differences in other nutrition-related complications. Univariate analysis results revealed that hypocaloric parenteral nutrition, hepatocellular carcinoma, malnutrition assessed by the GLIM criteria, open surgery, major hepatectomy, perioperative hyperglycemic events, and the presence of pleural or ascitic fluid were potential influencing factors for the occurrence of infectious complications ( P<0.05). Multivariate analysis results suggested that malnutrition ( OR=2.707, 95% CI: 1.153-6.354, P=0.022), open surgery ( OR=2.103, 95% CI: 1.073-4.122, P=0.030), perioperative hyperglycemic events ( OR=2.630, 95% CI: 1.228-5.631, P=0.013), and the presence of pleural or ascitic fluid ( OR=2.714, 95% CI: 1.388-5.306, P=0.004) were risk factors for perioperative infectious complications in patients undergoing hepatectomy for primary hepatic carcinoma, while early postoperative hypocaloric parenteral nutrition ( OR=0.388, 95% CI: 0.199-0.757, P=0.006) was a protective factor. Conclusion:For patients undergoing hepatectomy for primary hepatic carcinoma, early postoperative hypocaloric parenteral nutrition may reduce the incidence of perioperative infectious complications compared to normal caloric parenteral nutrition, thereby improving patient clinical outcomes.

OBJECTIVE To create a highly effective algorithm for automatically generating easily confused drug catalogs （ECDC）， as well as to develop a management system for ECDC based on this algorithm， in order to improve the management efficiency of ECDC. METHODS This study， based on Levenshtein distance algorithm， delved deeply into the automatic identification mechanism of easily confused drugs and the screening method for determining similarity thresholds， ultimately leading to the development of an algorithm for automatically generating ECDC. Besides a management system was designed and developed， using SQL Server 2008 R2 Express as the data storage platform and Visual Basic.NET as the programming language. RESULTS The similarity threshold δ played a crucial role in the algorithm for automatically generating ECDC. As the value of δ gradually increased， the total count of easily confused drugs decreased gradually， while the count of drug groups exhibited a pattern of initially increasing and then decreasing. Practically， ECDC could be created using either the generic or varietal names of drugs， with corresponding similarity thresholds of 0.75 and 0.83. Furthermore， ECDC management system had significantly reduced the time required to establish a catalog from about one week to less than one hour， resulting in a substantial enhancement in work efficiency. CONCLUSIONS The algorithm used to automatically generate ECDC is highly efficient and rapid， offering robust technical assistance for the management of easily confused drugs. Implementing the ECDC system can greatly reduce the time cost related to building and maintaining the catalogs， thus significantly improving the efficiency of managing ECDC.

Background Bacteria are the most diverse and widely sourced microorganisms in the indoor air of subway stations, where pathogenic bacteria can spread through the air, leading to increased health risks. Objective To understand the status and distribution characteristics of indoor air bacterial pollution in subway stations and compartments in a city of Central South China, and to provide a scientific basis for formulating intervention measures to address indoor air bacteria pollution in subways. Methods Three subway stations and the compartments of trains parking there in a city in Central South China were selected according to passenger flow for synchronous air sampling and monitoring. Temperature, humidity, wind speed, carbon dioxide (CO₂), fine particulate matter (PM_2.5), and inhalable particulate matter (PM₁₀) were measured by direct reading method. In accordance with the requirements of Examination methods for public places-Part 3: Airborne microorganisms (GB/T 18204.3-2013), air samples were collected at a flow rate of 28.3 L·min⁻¹, and total bacterial count was estimated. Bacterial microbial species were identified with a mass spectrometer and pathogenic bacteria were distinguished from non-pathogenic bacteria according to the Catalogue of pathogenic microorganisms transmitted to human beings issued by National Health Commission. Kruskal-Wallis H test was used to compare the subway hygiene indicators in different regions and time periods, and Bonferroni test was used for pairwise comparison. Spearman correlation test was used to evaluate the correlation between CO₂ concentration and total bacterial count. Results The pass rates were 100.0% for airborne total bacteria count, PM_2.5, and PM₁₀ in the subway stations and train compartments, 94.4% for temperature and wind speed, 98.6% for CO₂, but 0% for humidity. The overall median (P₂₅, P₇₅) total bacteria count was 177 (138,262) CFU·m⁻³. Specifically, the total bacteria count was higher in station halls than in platforms, and higher during morning peak hours than during evening peak hours (P<0.05). A total of 874 strains and 82 species were identified by automatic microbial mass spectrometry. The results of identification were all over 9 points, and the predominant bacteria in the air were Micrococcus luteus (52.2%) and Staphylococcus hominis (9.8%). Three pathogens, Acinetobacter baumannii (0.3%), Corynebacterium striatum (0.1%), and Staphylococcus epidermidis bacilli (2.2%) were detected in 23 samples (2.6%), and the associated locations were mainly distributed in train compartments during evening rush hours. Conclusion The total bacteria count in indoor air varies by monitoring sites of subway stations and time periods, and there is a risk of opportunistic bacterial infection. Attention should be paid to cleaning and disinfection during peak passenger flow hours in all areas.

Objective A knowledge graph construction pipeline of traditional Chinese medicine(TCM)diagnosis and treatment was designed and applied,aiming at the automatic construction of the"disease-symptom-pathogenesis-and medicine"knowledge graph based on the medical records of famous TCM physicians,to analyze,organize and present medical records efficiently.Methods Firstly,The entity extraction method of medical records combining Deep Learning and Regular Expression was designed to extract disease,symptom,pathogenesis,and TCM entities from unstructured medical records automatically;secondly,entity relationships were defined and the correlations between entities were calculated using HAN method,and then the"entity-relation-entity"triplets were built;the graph database Neo4j and Gephi were used for knowledge storage and visual display separately;Finally,the application was verified in the Medical records of lung cancer treated by the old famous TCM physicians.Results The precision,Recall and F1 of the knowledge extraction model for medical records entities extraction are 88.49%,90.02%and 89.25%,respectively,and each index is better than the comparison methods.A total of 1077 triples are extracted through entity correlation calculation,and the knowledge graph is successfully constructed.It can reflect the relationship between 'disease-symptom-pathogenesis-medicine' in the treatment of lung cancer by the famous specialists of TCM.Conclusion The method in this paper can effectively solve the extraction,organization and expression of clinical medical records of famous TCM physicians,and realize the automatic construction process from the text of medical records to the knowledge graph.Relevant research ideas and methods proposed in this paper could provide a reference for the construction of the diagnosis and treatment knowledge graph of famous TCM physicians based on medical records.

Objective:To study the influence of intensive magnet fields on radiation dose measurement, and to demonstrate the feasibility of measuring magnet field correction factor by a combination of medical linac with variable magnet fields in view of needing for accurate measurement of the doses from reference beam arising in MR image-guided radiotherapy.Methods:A photon radiation field and a variable field with 6 MV nominal high voltage were produced by using conventional medical electron linear accelerator equipped with a pair of electromagnets with magnetic field strength up to 1.5 T. Both PTW30013 and PTW31010 ionization chambers were used to test the responses of ionization chambers under different magnetic field strengths at four orientations in which the angles between ionization chamber axis and magnetic field direction were 0°, 180°, 90° and 270°, respectively. The magnetic factors, kB, M was calculated and compared with the reported values in literature. Results:The response of ionization chamber was proportional to the magnetic field strength before it reached to a peak around 1 T, and then fell down as the magnetic field continued to rise. When the magnetic field was 0.35 T, the magnetic factors of PTW31010 were 0.988 2±0.000 3 and 0.997 4±0.000 4 corresponding to 90° and 0° directions, the discrepancy between 0° scenario and literature was 0.05% ± 0.04%. When the magnetic field reached 1.5 T, the magnetic factor of PTW30013 was 0.958 9±0.000 5 at the situation of 90°, which was 0.60% ± 0.05% different from the literature value.Conclusions:Conventional 6 MV medical accelerator equipped with electromagnet can be used to measure the magnetic field factor of reference dosimetry for MRIgRT.

Objective To investigate the modification effect of atmospheric temperature on outpatient visits caused by O₃ in Linzhi City. Methods The daily outpatient data, the daily O₃ concentration and daily meteorological data (including daily average temperature, average relative humidity, etc.) in Linzhi City from 2018 to 2019 were collected. The distributed lag non-liner-model (DLNM) was used to quantitatively evaluate the impact of O₃ in different temperature layers on the risk of outpatient visits. Results At low temperature layers, the cumulative relative risk (CRR) of total outpatient visits and non-injury outpatient visits increased by 53.8%（4.2% -126.9%) and 59.1%（5.8% -139.2%）for every 10 μg/m³ increase of O₃ concentration, respectively. The subgroup analysis showed that for every 10 μg/m³ increase of O₃ concentration at low temperature, the CRR of patients with circulatory diseases, men, women, and people being <14 years old and 14-65 years old increased by 152.1% (15.1% - 451.9%), 58.3% (2.1%-145.5%), 49.2% (3.0% -116.1%), 39.6% (2.5% - 90.3%), and 61% (0.8%-157.1%), respectively. Conclusion The average temperature may have a modifying effect on the outpatient visits caused by O₃ in Linzhi City. In general, the cumulative risk increases as the temperature decreases.

Imipenem-cilastatin is a broad-spectrum carbapenem antibiotic drug that has been widely used in clinical practice ， but there is a lack of guidelines and expert consensus on the development of individualized regimens for special status populations [e.g. continuous renal replacement therapy （CRRT）patients，extracorporeal membrane oxygenation （ECMO）patients， critically ill burn patients ，neonates and children]. In this paper ，by searching population pharmacokinetics research of imipenem- cilastatin in special status populations ，it is recommended that imipenem-cilastatin is given 1 to 3 g/d for CRRT patients ；500 mg to 1 g，q6 h for burn patients ；750 mg to 1 g，q6 h for ECMO patients ；20 mg/kg or 25 mg/kg，q8 h for neonates ；and 25 mg/kg，q6 h for children.

Objective To compare the effects of Autoregressive Integrated Moving Average model-X (ARIMAX) and multivariate Long Short Term Memory Network (multivariate LSTM) in the prediction of daily total death toll in Yancheng City. Methods Based on total death toll data, meteorological data and air quality data from January 1^st, 2014 to June 30^th,2017 in Yancheng City, Jiangsu province, ARIMAX model and multivariate LSTM model were established to predict the daily total death toll from July 1^st,2017 to July 14^th,2017. RMSE, MAE and MAPE were used as evaluation indexes to compare the prediction effects of these two models. Results RMSE, MAE and MAPE of ARIMAX model and multivariate LSTM model were 20.742、15.094、9.921 and 47.182、35.863、19.633, respectively. Conclusion ARIMAX model is better than multivariate LSTM model to predict the daily death toll in Yancheng city.