BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA). METHODS: This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods. RESULTS: The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment. CONCLUSIONS A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans ; Tomography, X-Ray Computed/methods* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Artificial Intelligence ; Aged ; Pneumonia/diagnosis* ; Latent Class Analysis ; Adult

Forensic injury analysis is of great significance in the field of forensic medicine,but the complexity of injury formation process and individual differences make it highly professional.The finite element method(FEM),with its wide applicability,controllable accuracy and efficient computing power,combined with visualization,has shown great application potential in the field of forensic science.Through literature analysis,this paper introduces the basic principles of FEM and discusses its application in analysis of injuries caused by traffic accidents,shooting,tool injury and fall from height.By analyzing the simulation parameters,simulation results and research focus of each application scenario and collision site,this study evaluates the feasibility and limitations of FEM in forensic injury analysis,thereby providing reference and technical approaches for forensic injury analysis.

Multimodal biometric identification technology,which combines multiple biometric methods,is being increasingly used in forensic science due to its advantages such as difficulty of forgery and great accuracy.However,the current identification mainly relies on unimodal biometrics including facial recognition,hand recognition,iris recognition,gait recognition,and voice recognition.Thus,to a large extent,the accuracy of identification depends on the quality of the unimodal data,which faces multiple challenges.In contrast,multimodal biometrics has more obvious advantages in the field of identification,which can not only effectively resist attacks,but also enrich the feature representation with complementary information from multimodal sources,mitigate the impact of environment on the identification performance,and enhance the robustness of the system.To this end,this paper combs through the relevant work in this field,and comprehensively reviews the current research status and development trend of biometric identification technology.First,based on bibliometrics,the paper combs through the relevant research results in the past ten years,analyzes,summarizes,and discusses the commonly used deep learning models in this field,respectively,from unimodal recognition to multi-modal fusion recognition.Then the paper discusses the future development direction of the multimodal biometric identification field in the light of the practical needs of court science and provides reference for identification research.

Multimodal biometric identification technology,which combines multiple biometric methods,is being increasingly used in forensic science due to its advantages such as difficulty of forgery and great accuracy.However,the current identification mainly relies on unimodal biometrics including facial recognition,hand recognition,iris recognition,gait recognition,and voice recognition.Thus,to a large extent,the accuracy of identification depends on the quality of the unimodal data,which faces multiple challenges.In contrast,multimodal biometrics has more obvious advantages in the field of identification,which can not only effectively resist attacks,but also enrich the feature representation with complementary information from multimodal sources,mitigate the impact of environment on the identification performance,and enhance the robustness of the system.To this end,this paper combs through the relevant work in this field,and comprehensively reviews the current research status and development trend of biometric identification technology.First,based on bibliometrics,the paper combs through the relevant research results in the past ten years,analyzes,summarizes,and discusses the commonly used deep learning models in this field,respectively,from unimodal recognition to multi-modal fusion recognition.Then the paper discusses the future development direction of the multimodal biometric identification field in the light of the practical needs of court science and provides reference for identification research.

Forensic injury analysis is of great significance in the field of forensic medicine,but the complexity of injury formation process and individual differences make it highly professional.The finite element method(FEM),with its wide applicability,controllable accuracy and efficient computing power,combined with visualization,has shown great application potential in the field of forensic science.Through literature analysis,this paper introduces the basic principles of FEM and discusses its application in analysis of injuries caused by traffic accidents,shooting,tool injury and fall from height.By analyzing the simulation parameters,simulation results and research focus of each application scenario and collision site,this study evaluates the feasibility and limitations of FEM in forensic injury analysis,thereby providing reference and technical approaches for forensic injury analysis.

Clinical researches including the Mayo Anesthesia Safety in Kids (MASK) study have found that children undergoing multiple anesthesia may have a higher risk of fine motor control difficulties. However, the underlying mechanisms remain elusive. Here, we report that erythropoietin receptor (EPOR), a microglial receptor associated with phagocytic activity, was significantly downregulated in the medial prefrontal cortex of young mice after multiple sevoflurane anesthesia exposure. Importantly, we found that the inhibited erythropoietin (EPO)/EPOR signaling axis led to microglial polarization, excessive excitatory synaptic pruning, and abnormal fine motor control skills in mice with multiple anesthesia exposure, and those above-mentioned situations were fully reversed by supplementing EPO-derived peptide ARA290 by intraperitoneal injection. Together, the microglial EPOR was identified as a key mediator regulating early synaptic development in this study, which impacted sevoflurane-induced fine motor dysfunction. Moreover, ARA290 might serve as a new treatment against neurotoxicity induced by general anesthesia in clinical practice by targeting the EPO/EPOR signaling pathway.
Animals ; Sevoflurane/toxicity* ; Microglia/drug effects* ; Anesthetics, Inhalation/adverse effects* ; Mice ; Mice, Inbred C57BL ; Receptors, Erythropoietin/metabolism* ; Neuronal Plasticity/drug effects* ; Male ; Prefrontal Cortex/drug effects* ; Erythropoietin/pharmacology* ; Signal Transduction/drug effects*

Objective:To investigate the value of implantable cardiac monitor (ICM) in the diagnosis and treatment of patients over 60 years old with unexplained syncope.Methods:This was a multi-center, prospective cohort study. Between June 2018 and April 2021, patients over the age of 60 with unexplained syncope at Beijing Hospital, Fuwai Hospital, Beijing Anzhen Hospital and Puren Hospital were enrolled. Patients were divided into 2 groups based on their decision to receive ICM implantation (implantation group and conventional follow-up group). The endpoint was the recurrence of syncope and cardiogenic syncope as determined by positive cardiac arrhythmia events recorded at the ICM or diagnosed during routine follow-up. Kaplan‐Meier survival analysis was used to compare the differences of cumulative diagnostic rate between the 2 groups. A multivariate Cox regression analysis was performed to determine independent predictors of diagnosis of cardiogenic syncope in patients with unexplained syncope.Results:A total of 198 patients with unexplained syncope, aged (72.9±8.25) years, were followed for 558.0 (296.0,877.0) d, including 98 males (49.5%). There were 100 (50.5%) patients in the implantation group and 98 (49.5%) in the conventional follow-up group. Compared with conventional follow-up group, patients in the implantation group were older, more likely to have comorbidities, had a higher proportion of first degree atrioventricular block indicated by baseline electrocardiogram, and had a lower body mass index (all P<0.05). During the follow-up period, positive cardiac arrhythmia events were recorded in 58 (58.0%) patients in the ICM group. The diagnosis rate (42.0% (42/100) vs. 4.1% (4/98), P<0.001) and the intervention rate (37.0% (37/100) vs. 2.0% (2/98), P<0.001) of cardiogenic syncope in the implantation group were higher than those in the conventional follow-up group (all P<0.001). Kaplan-Meier survival analysis showed that the cumulative diagnostic rate of cardiogenic syncope was significantly higher in the implantation group than in the traditional follow-up group ( HR=11.66, 95% CI 6.49-20.98, log-rank P<0.001). Multivariate analysis indicated that ICM implantation, previous atrial fibrillation, diabetes mellitus or first degree atrioventricular block in baseline electrocardiogram were independent predictors for cardiogenic syncope (all P<0.05). Conclusions:ICM implantation improves the diagnosis and intervention rates in patients with unexplained syncope, and increases diagnostic efficiency in patients with unexplained syncope.

Objective:To describe the characteristics, etiology and patterns of outpatients and inpatients patients with moderate or severe valvular heart disease (VHD).Methods:This is a cross-sectional study. Outpatients and inpatients with moderate or severe VHD who underwent transthoracic echocardiography for first examination from 1 st January 2001 to 1 st January 2020 in Southwest Hospital, Army Medical University were enrolled. Data were collected from medical records and big data platform of Southwest Hospital. Characteristics of age and gender, etiology and types of VHD were descriptively analysed. Results:A total of 68 354 patients with moderate or severe VHD were enrolled. The age was 63 (50, 72) years. And 35 706 (52.24%) patients were female. (1) Age characteristics: There was similar age trend between male and female patients with moderate or severe VHD. The number of patients increased firstly and then decreased and reached its peak in the age group of 65-69 years old. The peak age of mitral stenosis patients was 45-49 years, which was earlier than that of whole patients with moderate or severe VHD. The median age of patients with bicuspid aortic valve was 42 years. (2) Gender characteristics: The proportion of tricuspid regurgitation, pulmonary regurgitation, mitral regurgitation, mitral stenosis and valve surgery in female patients with moderate or severe VHD were higher than those in male patients. The proportion of aortic regurgitation, aortic stenosis and bicuspid aortic valve in male patients with moderate or severe VHD were significantly higher than those in female patients (all P<0.05). (3) Etiology: The proportion of rheumatic VHD was 13.07% (8 934/68 354), which was higher than that of degenerative VHD (0.67% (458/68 354)). (4) Types of VHD: Tricuspid regurgitation made contribution to the largest proportion with 60.72% (41 503/68 354), followed by mitral regurgitation, aortic regurgitation, mitral stenosis, pulmonary regurgitation and aortic stenosis. Conclusions:There are certain regional characteristics in the prevalence of moderate or severe VHD in southwest China, suggesting different attention should be paid on the whole process of refined management of moderate or severe VHD.

The testis is pivotal for male reproduction, and its progressive functional decline in aging is associated with infertility. However, the regulatory mechanism underlying primate testicular aging remains largely elusive. Here, we resolve the aging-related cellular and molecular alterations of primate testicular aging by establishing a single-nucleus transcriptomic atlas. Gene-expression patterns along the spermatogenesis trajectory revealed molecular programs associated with attrition of spermatogonial stem cell reservoir, disturbed meiosis and impaired spermiogenesis along the sequential continuum. Remarkably, Sertoli cell was identified as the cell type most susceptible to aging, given its deeply perturbed age-associated transcriptional profiles. Concomitantly, downregulation of the transcription factor Wilms' Tumor 1 (WT1), essential for Sertoli cell homeostasis, was associated with accelerated cellular senescence, disrupted tight junctions, and a compromised cell identity signature, which altogether may help create a hostile microenvironment for spermatogenesis. Collectively, our study depicts in-depth transcriptomic traits of non-human primate (NHP) testicular aging at single-cell resolution, providing potential diagnostic biomarkers and targets for therapeutic interventions against testicular aging and age-related male reproductive diseases.
Animals ; Male ; Testis ; Sertoli Cells/metabolism* ; Transcriptome ; Spermatogenesis/genetics* ; Primates ; Aging/genetics* ; Stem Cells