Diabetic kidney disease(DKD)is one of the serious complications of diabetes.Ferroptosis causes pathological damage and is involved in the progression of DKD.How to inhibit ferroptosis and delay DKD is a new academic hotspot.The author's team further enriched and proposed the core pathogenesis theory of"internal heat induced disease"on the basis of the traditional DKD"yin deficiency and dryness-heat"theory,and explained the general development law of DKD.In this article,"internal heat"and"Zhengjia"in the theory of DKD"internal heat induced diseases"are used as the starting point to explore the relationship of the main pathological damage of ferroptosis such as activating inflammatory response,enhancing oxidative stress,promoting fibrosis and so on with the internal mechanism of the theory of"internal heat induced diseases",further explained the scientific connotation of DKD"internal heat induced diseases",in order to provide ideas and theoretical basis for the TCM prevention and treatment of DKD.

Objective:To design a remote monitoring and early warning system of ventilators,so as to adapt to data collection for different types of ventilators,and achieve early warning for abnormal status in operation data of ventilators.Methods:A three-layer structure,which used information gateway of Internet of Things(IoTs)with multi communication standard as the core,and integrated with multiple interfaces,was adopted to construct a remote monitoring and early warning system of ventilators.Boolean function was used to determine strings of incorrect data,and extract respiratory information.Using incremental isolated forest algorithm processed ventilators'operation data for realizing anomaly detection.And then,the detection results were presented through a display module,so as to conduct early warning for existing abnormal situations.Results:The remote monitoring and early warning system of ventilator had an accuracy rate of monitoring over 98.0%for abnormity of different types of ventilators,which timely warning rate was over 98.5%.Conclusion:The designed remote monitoring and early warning system of ventilator can provide clear results of remote monitoring and early warning of ventilator,which can timely find abnormal status,and effectively improve management efficiency for ventilator,and promote the intelligent development of medical treatment.

Objective:To evaluate the value of acid-base indicators and strong ion gap (SIG) in the prognostic diagnosis of patients with acute paraquat poisoning (APP).Methods:The medical records of 78 APP patients admitted to the First People′s Hospital of Lianyungang from March 2021 to March 2024 were analyzed retrospectively. The patients were divided into the death group ( n=56) and the survival group ( n=22) according to their prognosis. Clinical data, acid-base indicators, and SIG levels were compared between the two groups. Logistic regression analysis was used to identify the influencing factors of prognosis in APP patients and construct a nomogram. Receiver operating characteristic (ROC) curve was established to analyze the diagnostic value of combined acid-base indicators and SIG for the prognosis of APP patients. Results:There were no statistically significant differences in gender, age, body mass index, time from poisoning to treatment, history of diabetes, or history of hypertension between the two groups (all P>0.05). The levels of anion gap (AG), bicarbonate ion (HCO 3-), lactic acid (Lac), and SIG in the death group were higher than those in the survival group (all P<0.05). Logistic regression analysis showed that AG, HCO 3-, Lac, and SIG levels were influencing factors for the prognosis of APP patients (all P<0.05). ROC curve results indicated that the area under the curve (AUC) of AG, HCO 3-, Lac, and SIG combined in predicting the prognosis of APP patients was significantly higher than that of single prediction. Conclusions:Acid-base indicators and SIG have good diagnostic value for the prognosis of APP patients.

Diabetic kidney disease(DKD)is one of the serious complications of diabetes.Ferroptosis causes pathological damage and is involved in the progression of DKD.How to inhibit ferroptosis and delay DKD is a new academic hotspot.The author's team further enriched and proposed the core pathogenesis theory of"internal heat induced disease"on the basis of the traditional DKD"yin deficiency and dryness-heat"theory,and explained the general development law of DKD.In this article,"internal heat"and"Zhengjia"in the theory of DKD"internal heat induced diseases"are used as the starting point to explore the relationship of the main pathological damage of ferroptosis such as activating inflammatory response,enhancing oxidative stress,promoting fibrosis and so on with the internal mechanism of the theory of"internal heat induced diseases",further explained the scientific connotation of DKD"internal heat induced diseases",in order to provide ideas and theoretical basis for the TCM prevention and treatment of DKD.

Objective:To design a remote monitoring and early warning system of ventilators,so as to adapt to data collection for different types of ventilators,and achieve early warning for abnormal status in operation data of ventilators.Methods:A three-layer structure,which used information gateway of Internet of Things(IoTs)with multi communication standard as the core,and integrated with multiple interfaces,was adopted to construct a remote monitoring and early warning system of ventilators.Boolean function was used to determine strings of incorrect data,and extract respiratory information.Using incremental isolated forest algorithm processed ventilators'operation data for realizing anomaly detection.And then,the detection results were presented through a display module,so as to conduct early warning for existing abnormal situations.Results:The remote monitoring and early warning system of ventilator had an accuracy rate of monitoring over 98.0%for abnormity of different types of ventilators,which timely warning rate was over 98.5%.Conclusion:The designed remote monitoring and early warning system of ventilator can provide clear results of remote monitoring and early warning of ventilator,which can timely find abnormal status,and effectively improve management efficiency for ventilator,and promote the intelligent development of medical treatment.

Objective:To evaluate the value of acid-base indicators and strong ion gap (SIG) in the prognostic diagnosis of patients with acute paraquat poisoning (APP).Methods:The medical records of 78 APP patients admitted to the First People′s Hospital of Lianyungang from March 2021 to March 2024 were analyzed retrospectively. The patients were divided into the death group ( n=56) and the survival group ( n=22) according to their prognosis. Clinical data, acid-base indicators, and SIG levels were compared between the two groups. Logistic regression analysis was used to identify the influencing factors of prognosis in APP patients and construct a nomogram. Receiver operating characteristic (ROC) curve was established to analyze the diagnostic value of combined acid-base indicators and SIG for the prognosis of APP patients. Results:There were no statistically significant differences in gender, age, body mass index, time from poisoning to treatment, history of diabetes, or history of hypertension between the two groups (all P>0.05). The levels of anion gap (AG), bicarbonate ion (HCO 3-), lactic acid (Lac), and SIG in the death group were higher than those in the survival group (all P<0.05). Logistic regression analysis showed that AG, HCO 3-, Lac, and SIG levels were influencing factors for the prognosis of APP patients (all P<0.05). ROC curve results indicated that the area under the curve (AUC) of AG, HCO 3-, Lac, and SIG combined in predicting the prognosis of APP patients was significantly higher than that of single prediction. Conclusions:Acid-base indicators and SIG have good diagnostic value for the prognosis of APP patients.

Venous thromboembolism(VTE)is a prevalent complication in orthopedics.In recent years,machine learning has been widely applied in orthopedics.The essence of machine learning lies in utilizing algorithms to analyze vast amounts of data and construct risk prediction models that can accurately forecast unknown clinical outcomes.By integrating high-risk factors,machine learning aids medical professionals in precisely identifying and screening individuals with a high risk of VTE and offering them timely individualized interventions.This article reviews the concept and classification of machine learning,the advantages of machine learning in enhancing model prediction ability,and the current application status of machine learning in constructing risk prediction models for patients with VTE.

ObjectiveTo analyze the monitoring results and trends of Oncomelania in Songjiang District of Shanghai from 2007 to 2023， and to provide reference for future monitoring work. MethodsThe data of snail monitoring in Songjiang District from 2007 to 2023 were collected， including the location of snail spots， the number of survey frames， the area with snails， the number of frames with snails， the total number of snails， etc. The density of living snails and the occurrence rate of living snail frames were calculated. ResultsFrom 2007 to 2023， a total of 158 snail spots were found in 22 administrative villages in 4 towns in Songjiang District， including 131 emerging snail habitats （82.91%） and 27 reemerging snail habitats （17.09%）. The total snail area was 175 980 m²， the number of snail frames was 10 061， and 33 302 snails were captured. The highest density was 260/0.11 m²， and 15 662 snails were dissected. No positive snails were found. The average density of living snails was 0.60/0.11 m² and the average occurrence rate of living snail frames was 17.99%. The snail areas in different areas were Yexie Town 126 000 m² （71.60%）， Maogang Town 26 470 m² （15.04%）， Xinbang Town 17 040 m² （9.68%）， and Shihudang Town 6 470 m² （3.68%）. The average density of living snails in different areas was 0.89/0.11 m² in Yexie Town， 0.65/0.11 m² in Maogang Town， 0.26/0.11 m² in Shihudang Town and 0.24/0.11 m² in Xinbang Town. The snail areas of different snail habitats were as follows： woodland 151 250 m²（85.95%）， river 13 810 m²（7.85%）， ditch 6 910 m²（3.93%）， farmland 4 010 m²（2.28%）. The average density of living snails in different snail habitats： ditch 1.01/0.11 m²， beach 0.86/0.11 m²， woodland 0.57/0.11 m²， river 0.40/0.11 m². The occurrence rate of living snail frames in different regions and different snail environment types showed a downward trend and the difference was statistically significant. ConclusionAlthough the snail monitoring indicators such as snail area， average living snail density and average living snail frame occurrence rate in Songjiang District are still at its historically low level， the average living snail density and average living snail frame occurrence rate are still high compared with other regions or the national average. We should focus on the upper reaches and tributaries of the Huangpu River， especially the key areas of seedling transplantation， and strengthen monitoring and supervision to reduce the risk of snail input.

Objective: The association between school bullying and attention deficit hyperactivity disorder (ADHD) symptoms among students in primary schools and the moderating role of gender was explored to provide scientific evidence for the prevention and control of school bullying. Methods: A total of 4 764 students from 2 primary schools in Wuhan were selected using the convenience sampling method in March 2023. The Olweus Bully/Victim Questionnaire and Strengths and Difficulties Questionnaire were used. A Pearson χ 2 test was used to compare differences in school bullying rates among children with and without ADHD symptoms. Pearson correlation analysis and Process 3.3 were used to analyse the association between ADHD symptoms, and school bullying behaviour and the moderating role of gender. Results: The reported rate of bullying victims in primary schools was 24.2% and the rate of bullying perpetration was 3.8%. The rate of ADHD symptom detection among primary school students was 5.9%. ADHD symptoms were positively associated with bullying and bullying victim behaviour ( r =0.16, 0.27, P <0.01). Specifically, the association between ADHD symptoms and bullying behavior tended to be stronger among boys than girls ( β boy =0.17, t =11.13; β girl =0.07, t =4.11, P <0.01). Conclusions ADHD symptoms are an important factor influencing school bullying behaviors in students, and gender moderates the association. In the process of preventing and controlling school bullying, ADHD symptoms and gender differences should be emphasized and comprehensive interventions should be implemented.

Objective:To evaluate the diagnostic efficacy of the multiparametric MRI (mpMRI) deep learning artificial intelligence (AI) analysis system combined with 68Ga-prostate specific membrane antigen (PSMA) PET for prostate cancer. Methods:Data of 103 patients (age: 45-85 years) who underwent 68Ga-PSMA PET/MR at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology from May 2018 to October 2023 for suspected or confirmed prostate cancer were retrospectively collected. ROI was delineated to measure SUV max of primary tumor or prostate, and a deep learning AI system was applied to analyze MR images of the prostate. The diagnostic efficacies of T 2 weighted imaging (WI), diffusion WI (DWI), mpMRI, PET SUV max, and PET/MR for prostate cancer were assessed, with using the pathological results as the gold standard. Results:Among 103 patients, 82 cases (79.61%) were with prostate cancer. PET unimodality demonstrated the best specificity (100%, 21/21), positive predictive value (100%, 58/58), and AUC (0.860, 95% CI: 0.777-0.920). The mpMRI AI analysis provided rapid diagnostic results and the sensitivity and accuracy were improved by combining with PET (sensitivities of PET, mpMRI and the combination of the two were 70.73%(58/82), 86.59%(71/82), and 92.68%(76/82), respectively; the accuracies were 76.70%(79/103), 81.55%(84/103) and 86.41%(89/103), respectively). Among 44 patients with negative PET, 30 patients received an accurate diagnosis when the results of mpMRI AI analysis were added. Conclusions:68Ga-PSMA PET demonstrates good specificity for prostate cancer and mpMRI AI analysis is time-saving. The combined application improves the diagnostic sensitivity and accuracy, which provides a valuable tool for 68Ga-PSMA PET/MR image analysis.