PURPOSE: To investigate the protective effect of sub-hypothermic mechanical perfusion combined with membrane lung oxygenation on ischemic hypoxic injury of yorkshire brain tissue caused by traumatic blood loss. METHODS: This article performed a random controlled trial. Brain tissue of 7 yorkshire was selected and divided into the sub-low temperature anterograde machine perfusion group (n = 4) and the blank control group (n = 3) using the random number table method. A yorkshire model of brain tissue injury induced by traumatic blood loss was established. Firstly, the perfusion temperature and blood oxygen saturation were monitored in real-time during the perfusion process. The number of red blood cells, hemoglobin content, NA⁺, K⁺, and Ca²⁺ ions concentrations and pH of the perfusate were detected. Following perfusion, we specifically examined the parietal lobe to assess its water content. The prefrontal cortex and hippocampus were then dissected for histological evaluation, allowing us to investigate potential regional differences in tissue injury. The blank control group was sampled directly before perfusion. All statistical analyses and graphs were performed using GraphPad Prism 8.0 Student t-test. All tests were two-sided, and p value of less than 0.05 was considered to indicate statistical significance. RESULTS: The contents of red blood cells and hemoglobin during perfusion were maintained at normal levels but more red blood cells were destroyed 3 h after the perfusion. The blood oxygen saturation of the perfusion group was maintained at 95% - 98%. NA⁺ and K⁺ concentrations were normal most of the time during perfusion but increased significantly at about 4 h. The Ca²⁺ concentration remained within the normal range at each period. Glucose levels were slightly higher than the baseline level. The pH of the perfusion solution was slightly lower at the beginning of perfusion, and then gradually increased to the normal level. The water content of brain tissue in the sub-low and docile perfusion group was 78.95% ± 0.39%, which was significantly higher than that in the control group (75.27% ± 0.55%, t = 10.49, p < 0.001), and the difference was statistically significant. Compared with the blank control group, the structure and morphology of pyramidal neurons in the prefrontal cortex and CA1 region of the hippocampal gyrus were similar, and their integrity was better. The structural integrity of granulosa neurons was destroyed and cell edema increased in the perfusion group compared with the blank control group. Immunofluorescence staining for glail fibrillary acidic protein and Iba1, markers of glial cells, revealed well-preserved cell structures in the perfusion group. While there were indications of abnormal cellular activity, the analysis showed no significant difference in axon thickness or integrity compared to the 1-h blank control group. CONCLUSIONS Mild hypothermic machine perfusion can improve ischemia and hypoxia injury of yorkshire brain tissue caused by traumatic blood loss and delay the necrosis and apoptosis of yorkshire brain tissue by continuous oxygen supply, maintaining ion homeostasis and reducing tissue metabolism level.
Animals ; Perfusion/methods* ; Disease Models, Animal ; Brain Injuries/etiology* ; Swine ; Male ; Hypothermia, Induced/methods*

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

Medical equipment, as an important indicator of smart hospital evaluation, plays a vital role in hospital operations. To ensure the safe and efficient operation of medical equipment, a reasonable performance evaluation system is indispensable. This study introduces a platform based on Internet of Things (IoT) technology that connects medical devices and collects data, achieving standardized and structured data processing, and supporting online operational supervision. Through the Delphi method, a performance evaluation system for large medical equipment is constructed, including 4 primary indicators and 22 secondary indicators. DICOM data acquisition devices are used to achieve functions such as efficiency analysis, benefit analysis, usage evaluation, and decision-making support for medical equipment. The study is still in its early stages, and in the future, it is expected to integrate more types of equipment, achieve rational resource allocation, and significantly impact decision-making for the development of public hospitals.
Internet of Things ; Delphi Technique

OBJECTIVE: To analyze the clinical characteristics of elderly patients with sepsis, identify the key factors affecting their clinical outcomes, construct a death risk assessment scale for elderly patients with sepsis, and evaluate its predictive value. METHODS: A retrospective case-control study was conducted. The clinical data of sepsis patients admitted to intensive care unit (ICU) of the First Affiliated Hospital of Wenzhou Medical University from September 2021 to September 2023 were collected, including basic information, clinical characteristics, and clinical outcomes. The patients were divided into non-elderly group (age ≥ 65 years old) and elderly group (age < 65 years old) based on age. Additionally, the elderly patients were divided into survival group and death group based on their 30-day survival status. The clinical characteristics of elderly patients with sepsis were analyzed. Univariate and multivariate Logistic regression analyses were used to screen the independent risk factors for 30-day death in elderly patients with sepsis, and the regression equation was constructed. The regression equation was simplified, and the death risk assessment scale was established. The predictive value of different scores for the prognosis of elderly patients with sepsis was compared. RESULTS: (1) A total of 833 patients with sepsis were finally enrolled, including 485 in the elderly group and 348 in the non-elderly group. Compared with the non-elderly group, the elderly group showed significantly lower counts of lymphocyte, T cell, CD8⁺ T cell, and the ratio of T cells and CD8⁺ T cells [lymphocyte count (×10⁹/L): 0.71 (0.43, 1.06) vs. 0.83 (0.53, 1.26), T cell count (cells/μL): 394.0 (216.0, 648.0) vs. 490.5 (270.5, 793.0), CD8⁺ T cell count (cells/μL): 126.0 (62.0, 223.5) vs. 180.0 (101.0, 312.0), T cell ratio: 0.60 (0.48, 0.70) vs. 0.64 (0.51, 0.75), CD8⁺ T cell ratio: 0.19 (0.13, 0.28) vs. 0.24 (0.16, 0.34), all P < 0.01], higher natural killer cell (NK cell) count, acute physiology and chronic health evaluation II (APACHE II) score, ratio of invasive mechanical ventilation (IMV) during hospitalization, and 30-day mortality [NK cell count (cells/μL): 112.0 (61.0, 187.5) vs. 95.0 (53.0, 151.0), APACHE II score: 16.00 (12.00, 21.00) vs. 13.00 (8.00, 17.00), IMV ratio: 40.6% (197/485) vs. 31.9% (111/348), 30-day mortality: 28.9% (140/485) vs. 19.5% (68/348), all P < 0.05], and longer length of ICU stay [days: 5.5 (3.0, 10.0) vs. 5.0 (3.0, 8.0), P < 0.05]. There were no statistically significant differences in the levels of inflammatory markers such as C-reactive protein (CRP), procalcitonin (PCT), tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), and interleukins (IL-2, IL-4, IL-6, IL-10) between the two groups. (2) In 485 elderly patients with sepsis, 345 survived in 30 days, and 140 died with the 30-day mortality of 28.9%. Compared with the survival group, the patients in the death group were older, and had lower body mass index (BMI), white blood cell count (WBC), PCT, platelet count (PLT) and higher IL-6, IL-10, N-terminal pro-brain natriuretic peptide (NT-proBNP), total bilirubin (TBil), blood lactic acid (Lac), and ratio of in-hospital IMV and continuous renal replacement therapy (CRRT). Multivariate Logistic regression analysis indicated that BMI [odds ratio (OR) = 0.783, 95% confidence interval (95%CI) was 0.678-0.905, P = 0.001], IL-6 (OR = 1.073, 95%CI was 1.004-1.146, P = 0.036), TBil (OR = 1.009, 95%CI was 1.000-1.018, P = 0.045), Lac (OR = 1.211, 95%CI was 1.072-1.367, P = 0.002), and IMV during hospitalization (OR = 6.181, 95%CI was 2.214-17.256, P = 0.001) were independent risk factors for 30-day death in elderly patients with sepsis, and the regression equation was constructed (Logit P = 1.012-0.244×BMI+0.070×IL-6+0.009×TBil+0.190×Lac+1.822×IMV). The regression equation was simplified to construct a death risk assessment scale, namely BITLI score. Receiver operator characteristic curve (ROC curve) analysis showed that the area under the ROC curve (AUC) of BITLI score for predicting death risk was 0.852 (95%CI was 0.769-0.935), and it was higher than APACHE II score (AUC = 0.714, 95%CI was 0.623-0.805) and sequential organ failure assessment (SOFA) score (AUC = 0.685, 95%CI was 0.578-0.793). The determined cut-off value of BITLI score was 1.50, while achieving a sensitivity of 83.3% and specificity of 74.0%. CONCLUSIONS Elderly patients with sepsis often have reduced lymphocyte counts, severe conditions, and poor prognosis. BMI, IL-6, TBil, Lac, and IMV during hospitalization were independent risk factors for 30-day death in elderly patients with sepsis. The BITLI score constructed based above risk factors is more precise and reliable than traditional APACHE II and SOFA scores in predicting the outcomes of elderly patients with sepsis.
Humans ; Sepsis/mortality* ; Aged ; Retrospective Studies ; Risk Assessment ; Case-Control Studies ; Prognosis ; Male ; Female ; Intensive Care Units ; Risk Factors ; Aged, 80 and over ; Logistic Models ; Middle Aged

Objective:To explore the key components and mechanism of Qufeng Ningfei Powder in treating asthma through qualitative analysis of its blood components, combined with network pharmacology and molecular docking techniques.Methods:The blood components of Qufeng Ningfei Powder were qualitatively analyzed using UPLC-QE-Orbitrap-MS technology. R language was employed to analyze chip data from the GEO database, obtaining a list of differentially expressed genes. SwissTargetPrediction was utilized to predict the targets of drug components. Asthma-related targets were searched through databases such as OMIM, GeneCards, and TTD. The intersection of drug and disease targets was identified using Venn online analysis tool, constructing a "drug-component-target-disease" network to screen potential core components. A protein-protein interaction network (PPI) of core targets was constructed using STRING platform and Cytoscape software. GO function enrichment and KEGG pathway analysis were conducted using DAVID database to validate potential mechanism. Molecular docking was performed to verify the interaction between key components and core targets.Results:A total of 64 components were identified, from which 53 active components were screened, corresponding to 609 targets. Further searching disease databases revealed 96 target genes related to asthma, with an intersection of 6 genes between drug and asthma differential genes. Core target gene IL6 and its corresponding core compound were determined through network topology analysis. Molecular docking confirmed the binding of the main active components of Qufeng Ningfei Powder with the core target protein IL6.Conclusion:The blood components of Qufeng Ningfei Powder may regulate IL-17 through IL6, counteract airway remodeling, oxidative stress, and airway hyperresponsiveness, and thus treat asthma.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective To investigate the differences and the immunocompatibility of wild-type (WT), four-gene modified (TKO/hCD55) and six-gene modified (TKO/hCD55/hCD46/hTBM) pig erythrocytes with human serum. Methods The blood samples were collected from 20 volunteers with different blood groups. WT, TKO/hCD55, TKO/hCD55/hCD46/hTBM pig erythrocytes, ABO-compatible (ABO-C) and ABO-incompatible (ABO-I) human erythrocytes were exposed to human serum of different blood groups, respectively. The blood agglutination and antigen-antibody binding levels (IgG, IgM) and complement-dependent cytotoxicity were detected. The immunocompatibility of two types of genetically modified pig erythrocytes with human serum was evaluated. Results No significant blood agglutination was observed in the ABO-C group. The blood agglutination levels in the WT and ABO-I groups were higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (all P<0.001). The level of erythrocyte lysis in the WT group was higher than those in the ABO-C, TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups. The level of erythrocyte lysis in the ABO-I group was higher than those in the TKO/hCD55 and TKO/hCD55/hCD46/hTBM groups (both P<0.01). The pig erythrocyte binding level with IgM and IgG in the TKO/hCD55 group was lower than those in the WT and ABO-I groups. The pig erythrocyte binding level with IgG and IgM in the TKO/hCD55/hCD46/hTBM group was lower than that in the WT group and pig erythrocyte binding level with IgG was lower than that in the ABO-I group (all P<0.05). Conclusions The immunocompatibility of genetically modified pig erythrocytes is better than that of wild-type pigs and close to that of ABO-C pigs. Humanized pig erythrocytes may be considered as a blood source when blood sources are extremely scarce.

This paper explains the mechanism of the mutual switching between physiological sleep and wakefulness from the aspects of the sleep circadian system and the sleep homeostasis system. In the circadian rhythm system, with the suprachiasmatic nucleus as the core, the anatomical connections between the suprachiasmatic nucleusand various systems that affect sleep are summarized, starting from the suprachiasmatic nucleus, passing through the four pathways of the melatonin system, namely, subventricular area of the hypothalamus, the ventrolateral nucleus of the preoptic area, orexin neurons, and melatonin, then the related mechanisms of their regulation of sleep and wakefulness are expounded. In the sleep homeostasis system, with adenosine and prostaglandin D2 as targets, the role of hypnogen in sleep arousal mechanisms in regulation is also expounded.

Objective To analyze the literature on artificial intelligence in forensic research from 2012 to 2022 in the Web of Science Core Collection Database,to explore research hotspots and developmen-tal trends.Methods A total of 736 articles on artificial intelligence in forensic medicine in the Web of Science Core Collection Database from 2012 to 2022 were visualized and analyzed through the litera-ture measuring tool CiteSpace.The authors,institution,country(region),title,journal,keywords,cited references and other information of relevant literatures were analyzed.Results A total of 736 articles published in 220 journals by 355 authors from 289 institutions in 69 countries(regions)were identi-fied,with the number of articles published showing an increasing trend year by year.Among them,the United States had the highest number of publications and China ranked the second.Academy of Forensic Science had the highest number of publications among the institutions.Forensic Science Inter-national,Journal of Forensic Sciences,International Journal of Legal Medicine ranked high in publica-tion and citation frequency.Through the analysis of keywords,it was found that the research hotspots of artificial intelligence in the forensic field mainly focused on the use of artificial intelligence technol-ogy for sex and age estimation,cause of death analysis,postmortem interval estimation,individual identification and so on.Conclusion It is necessary to pay attention to international and institutional cooperation and to strengthen the cross-disciplinary research.Exploring the combination of advanced ar-tificial intelligence technologies with forensic research will be a hotspot and direction for future re-search.

Objective To investigate the clinical value of coronary computed tomography angiography(CCTA)based CT derived fractional flow reserve(CT-FFR)and ΔCT-FFR in improving the diagnostic efficiency for coronary abnormal hemodynamics in patients with severe calcification.Methods We retrospectively analyzed the clinical data of coronary artery disease(CAD)patients who underwent CCTA,CT-FFR,invasive coronary angiography(ICA)and FFR during hospitalization from January 2018 to June 2019 in Chinese PLA General Hospital.Severe calcification was defined as coronary artery calcium score(CACS)≥100 on single vessel level.A total of 107 CAD patients with 149 coronary arteries were included in the present study.The enrolled coronary arteries were assigned to CACS≥100 group(n=56)and CACS<100 group(n=93).CT-FFR was performed on the deep FFR platform based on machine learning(ML)algorithms and ΔCT-FFR was defined as CT-FFR difference between proximal and distal to the coronary lesion.The correlation and consistency between CT-FFR and FFR values were analyzed by Pearson and Bland-Altman methods.We attempted to analyze the incremental value of ΔCT-FFR for coronary functional evaluation,especial for coronary arteries with severe calcification,regarding FFR≤0.8 as the diagnostic gold standard.Comparison of receiver operating characteristic curves(ROC)between different diagnostic methods was presented by Delong test.Results Pearson and Bland-Altman analyses showed appreciable correlation(CACS≥100 group,r=0.71,P<0.01;CACS<100 group,r=0.73,P<0.01)and consistency(CACS≥100 group,Mean=-0.01,P=0.25;CACS<100 group,Mean=0,P=0.96)between CT-FFR and FFR values in both groups.FFR(0.80±0.08 vs.0.84±0.09,P=0.004)and CT-FFR(0.81±0.06 vs.0.85±0.06,P<0.001)levels were significant lower in CACS≥100 group than those in CACS<100 group,while ΔCT-FFR(0.14±0.06 vs.0.09±0.06,P<0.001)levels were significant higher in CACS≥100 group.Moreover,the diagnostic efficiency of CT-FFR in CACS≥100 group was inferior to that in CACS<100 group[AUC=0.792(95%CI 0.663-0.889)vs.AUC=0.929(95%CI 0.856-0.972),P=0.04],while it achieved significant improvement after ΔCT-FFR adjustment[AUC=0.876(95%CI 0.760-0.949)vs.AUC=0.792(95%CI 0.663-0.889),P=0.02]and was similar to that in CACS<100 group(P=0.37).Conclusion For coronary arteries with severe calcification,CT-FFR demonstrated significant incremental value in improving the diagnostic efficiency of coronary abnormal hemodynamics after ΔCT-FFR adjustment.