Objective To establish a scientific, comprehensive, and operable community resilience evaluation index system for emergent major infectious diseases. Methods Based on the social ecosystem theory, a preliminary evaluation index system was formed by using content analysis and boundary analysis. The index system was then supplemented and revised through panel discussions. The final index system and index weights were clarified by two rounds of Delphi method. Results The expert positive coefficient, expert authority coefficient, and expert coordination coefficient of the two rounds of expert consultations were examined. According to the screening principle of the ^“threshold method^”, the indicators were screened, and the weights of each indicator were determined in the second round of Delphi expert consultation. The analysis of the reliability of the indicator system showed Cronbach's α= 0.399 , indicating that the indicator system had a relatively high reliability. Factor analysis was carried out on 7 primary indicators, and the measure of sampling adequacy (MSA) values were all greater than 0.5, which passed the validity test. Conclusion A set of evaluation index system that can accurately reflect the resilience level of communities with emergent major infectious diseases has been constructed, including 7 primary indicators, 21 secondary indicators, 54 tertiary indicators, and 108 tertiary indicators, which has realized the quantitative evaluation of the hidden resilience level of communities.

Objective:To evaluate the clinical value of combined detection of placenta associated 8 (PLAC8) and platelet activating factor acetylhydrolase (PLA2G7) for early identification of sepsis and non-infectious systemic inflammatory response syndrome (SIRS).Methods:A cross-sectional study was conducted. A total of 189 febrile patients suspected infection who were admitted to Huashan Hospital, Fudan University from October 2022 to April 2023 were included. Based on etiological, laboratory test results and clinical data, patients were classified as infection or non-infection, and further classified as sepsis or non-infectious SIRS according to diagnostic criteria. Real-time fluorescence polymerase chain reaction was used to detect the mRNA levels of PLAC8 and PLA2G7 in peripheral venous blood of patients. Hematology, inflammatory markers including C-reactive protein (CRP), interleukin-6 (IL-6) and procalcitonin, sepsis-related organ failure assessment (SOFA) score, and the difference of cycle threshold (Ct) values between PLA2G7 and PLAC8 ((PLA2G7-PLAC8)ΔCt value))were compared between the sepsis and non-infectious SIRS groups. Statistical comparison was analyzed using Mann-Whitney U test, and the diagnostic performance of (PLA2G7-PLAC8)ΔCt value in discriminating sepsis from non-infectious SIRS was evaluated using receiver operating characteristic curve. Results:Among the 189 febrile patients suspected infection, there were 80 non-infectious patients, including 51 non-infectious SIRS patients, and 109 infection patients, including 53 sepsis patients. The neutrophil ratio, CRP, IL-6, procalcitonin, and SOFA score of non-infectious SIRS patients were lower than those of the sepsis group, and the differences were all statistically significant ( Z=-2.70, -3.11, -2.16, -3.76 and -2.33, respectively, all P<0.05). The (PLA2G7-PLAC8)ΔCt value in the non-infectious SIRS group was 4.38(1.41), which was lower than 8.18 (6.19) in the sepsis group, with a statistically significant difference ( U=193.50, P<0.001). The area under the receiver operating characteristic curve (AUROC) for (PLA2G7-PLAC8)ΔCt value in the differential diagnosis of sepsis and non-infectious SIRS was 0.859, with the optimal cut-off value of 5.86. The sensitivity and specificity were 82.2% and 71.9%, respectively. When combined with procalcitonin, the AUROC was 0.917, with a sensitivity of 95.6% and specificity of 70.6%. Conclusions:The (PLA2G7-PLAC8)ΔCt value in peripheral blood has good clinical value for early identification of sepsis and non-infectious SIRS, especially when combined with procalcitonin, which could further improve the accuracy of differential diagnosis.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Objective To analyze the risk factors of poor prognosis in patients with extended-spectrum β-lactamase producing enterobacterales(ESBL-E)bloodstream infection,and establish a nomogram prediction model to provide help for clinical diagnosis and treatment.Methods A total of 235 patients with ESBL-E bloodstream infection were collected from the First People's Hospital of Jiande City.According to their prognosis,the patients were divided into survival group(n=211)and death group(n=224).The clinical data of the patients were collected,and the independent risk factors of poor prognosis were screened by multivariate Logistic regression analysis.The nomogram was established and verified.Results The mortality of ESBL-E bloodstream infection patients with shock,respiratory failure,diabetes and leukemia,ICU admission,hypoproteinemia,increased or decreased white blood cells,and thrombocytopenia was higher(P＜0.05).Multivariate Logistic regression analysis showed that combined shock,respiratory failure and leukemia were independent risk factors for death from ESBL-E bloodstream infection.Conclusion The nomogram prediction model of adverse prognostic risk factors in patients with ESBL-E bloodstream infection can provide help for clinicians to judge the poor prognosis in the early stage,and it is of reference significance to take early intervention measures to reduce the mortality of patients.

ObjectiveTo investigate the mechanism of neferine（Nef） in promoting vascular regeneration against cerebral ischemia through modulation of mitochondrial calcium uniporter（MCU） ion channel. MethodTaking the area of subintestinal vessels in microvascular deficiency zebrafish as an index， the vascular regenerative efficacy of Nef was evaluated， and the median effective concentration（EC₅₀） was calculated. Rats were randomly divided into a sham operation group， a model group， a positive drug group（butylphthalide， 6 mg·kg^-1）， and Nef low， medium， and high dose groups（0.125， 0.625， 3.125 μg·kg^-1）. Except for the sham operation group， the middle cerebral artery occlusion（MCAO） model was established in other groups. After modeling， the groups were administered the corresponding dose of drugs by gavage， while the sham operation and model groups received equal volumes of saline， once a day for 7 consecutive days. Neurobehavioral scores were assessed for each group of rats， and the infarct rate of ischemic brain tissue was calculated by 2，3，5-triphenyltetrazolium chloride（TTC） staining. The regional cerebral blood flow（rCBF） of each group was measured using a speckle contrast imaging. Immunofluorescence and Western blot were conducted to detect the expression of vascular endothelial growth factor（VEGF）， platelet endothelial cell adhesion molecule-1（CD31）， and hypoxia-inducible factor-1α（HIF-1α） proteins in each group. Human umbilical vein endothelial cells（HUVECs） were divided into the normal group， model group， positive drug group（astragaloside Ⅳ， 10 μmol·L^-1）， and Nef group （32 nmol·L^-1）. In the verification of mitochondrial protection of Nef and its mechanism in promoting vascular regeneration， the spermine（MCU agonist） and Nef+spermine group were added. HUVECs model of oxygen-glucose deprivation（OGD） was established in all groups except the normal group， the cell viability was assessed using 3-（4，5-dimethylthiazol-2-yl）-2，5-diphenyltetrazolium bromide（MTT） assay， and cell migration ability was evaluated through scratch and tube formation assays. Fluorescent probes（Rhod-2 AM， Fluo-3 AM， JC-1， Calcein AM） and a cellular energy metabolism analyzer were used to analyze the mitochondrial protective effects of Nef. Molecular docking was performed to predict the binding ability of Nef with MCU and HIF-1α， and Western blot was used to detect the effects of Nef on the protein expressions of MCU， B-cell lymphoma-2 associated X protein（Bax）， Caspase-3 and HIF-1α in the OGD model HUVECs. ResultThe results of vascular regeneration in microvascular deficiency zebrafish showed that compared to the normal group， the area of subintestinal vessels in the model group significantly decreased（P<0.01）. Compared to the model group， different concentrations of Nef could significantly increase the area of subintestinal vessels（P<0.01）， with the maximum tolerated concentration of 10.24 μmol·L^-1 and the EC₅₀ of 0.23 μmol·L^-1. Anti-cerebral ischemia results on MCAO rats showed that compared to the sham operation group， the model group had a significant decrease in rCBF and a significant increase in infarct rate， while CD31 expression significantly decreased（P<0.01）， and VEGF and HIF-1α protein expressions significantly increased（P<0.05）. Compared to the model group， the treated groups showed significant increases in rCBF， significant reductions in infarct volume， and significant increases in CD31， VEGF， and HIF-1α protein expression（P<0.01）. Cell experiment results showed that compared to the normal group， the model group had decreased cell viability and migration ability， increased intracellular Ca²⁺ and mitochondrial Ca²⁺ levels， reduced mitochondrial permeability transition pore（MPTP） opening， and decreased mitochondrial energy metabolism capability， with increased expressions of MCU， Bax， Caspase-3 and HIF-1α proteins（P<0.05， P<0.01）. Compared to the model group， the Nef group showed increased cell viability and migration ability， decreased intracellular Ca²⁺ and mitochondrial Ca²⁺ levels， increased MPTP opening， enhanced mitochondrial energy metabolism capability， decreased expressions of MCU， Bax and Caspase-3 proteins， and increased HIF-1α protein expression（P<0.05， P<0.01）. ConclusionNef can stabilize mitochondrial membrane potential and inhibit mitochondrial apoptosis. By down-regulating the expression of MCU， it suppresses the activation of intracellular Bax and Caspase-3 while activating the HIF-1α signaling pathway， enhancing the expression of VEGF and CD31， thereby promoting vascular regeneration to treat ischemic brain injury.

Objective To construct a model with a spatial and channel reconstruction convolutional module for accurate identification and classification of lung sound data.Method We propose a convolutional network architecture combining the spatial-channel reconstruction convolution(SCConv)module.A lung sound feature extraction method combining the dual tunable Q-factor wavelet transform(DTQWT)with the triple Wigner-Ville transform(WVT)was used to improve the model's ability to capture the key features of the lung sounds by adaptively focusing on the important channel and spatial features.The performance of the model for classification of normal,crackles,wheezes,and crackles with wheezes was tested using the ICBHI2017 dataset.Results and Conclusion The accuracy,sensitivity,specificity and F1 score of the proposed method reached 85.68%,93.55%,86.79%and 90.51%,respectively,demonstrating its good performance in classification tasks in the ICBHI2017 lung sound database,especially for distinguishing normal from abnormal lung sounds.

Objective To construct a model with a spatial and channel reconstruction convolutional module for accurate identification and classification of lung sound data.Method We propose a convolutional network architecture combining the spatial-channel reconstruction convolution(SCConv)module.A lung sound feature extraction method combining the dual tunable Q-factor wavelet transform(DTQWT)with the triple Wigner-Ville transform(WVT)was used to improve the model's ability to capture the key features of the lung sounds by adaptively focusing on the important channel and spatial features.The performance of the model for classification of normal,crackles,wheezes,and crackles with wheezes was tested using the ICBHI2017 dataset.Results and Conclusion The accuracy,sensitivity,specificity and F1 score of the proposed method reached 85.68%,93.55%,86.79%and 90.51%,respectively,demonstrating its good performance in classification tasks in the ICBHI2017 lung sound database,especially for distinguishing normal from abnormal lung sounds.

Sarcopenia, which is characterized by progressive and generalized loss of skeletal muscle mass and strength, has been well described to be associated with numerous poor postoperative outcomes, such as increased perioperative mortality, postoperative sepsis, prolonged length of stay, increased cost of care, decreased functional outcome, and poorer oncological outcomes in cancer surgery. Multimodal prehabilitation, as a concept that involves boosting and optimizing the preoperative condition of a patient prior to the upcoming stressors of a surgical procedure, has the purported benefits of reversing the effects of sarcopenia, shortening hospitalization, improving the rate of return to bowel activity, reducing the costs of hospitalization, and improving quality of life. This review aims to present the current literature surrounding the concept of sarcopenia, its implications pertaining to colorectal cancer and surgery, a summary of studied multimodal prehabilitation interventions, and potential future advances in the management of sarcopenia.

Objective To investigate the distribution and drug resistance characteristics of pathogens in donors and recipients undergoing simultaneous pancreas-kidney transplantation (SPK). Methods Clinical data of 231 pairs of donors and recipients undergoing SPK were analyzed retrospectively. The pathogens of samples from donors and recipients were identified by VITEK-2 analyzer, and drug sensitivity test was performed by K-B method. The source distribution and composition ratio of pathogens in donor and recipient samples, distribution characteristics of multi-drug resistant organism, infection of recipients and drug resistance characteristics of pathogens were analyzed. Results A total of 395 strains of pathogens were cultured from 1 294 donor samples, and the detection rate was 30.53%. Gram-negative bacteria mainly consisted of klebsiella pneumoniae, Gram-positive bacteria mainly comprised staphylococcus aureus, and fungi primarily included candida albicans, respectively. In total, 2 690 strains of pathogens were cultured from 10 507 recipient samples, and the detection rate was 25.60%. Gram-negative bacteria mainly consisted of pseudomonas maltophilia, Gram-positive bacteria primarily comprised enterococcus faecalis, and fungi mainly included candida albicans, respectively. Among 395 pathogens of donors, 15 strains of methicillin-resistant staphylococcus aureus (MRSA), 16 strains of extended-spectrum β-lactamase (ESBL) positive drug-resistant bacteria, 8 strains of carbapenem-resistant pseudomonas aeruginosa (CR-PA), 21 strains of carbapenem-resistant acinetobacter baumannii (CR-AB), 2 strains of carbapenem-resistant enterobacteriaceae (CRE) and 1 strain of multiple-drug/pan-drug resistant pseudomonas aeruginosa (MDR/PDR-PA) were identified. Among 2 690 strains of recipient pathogens, 73 strains of ESBL positive drug-resistant bacteria, 44 strains of CR-PA, 31 strains of CR-AB and 3 strains of MDR/PDR-PA were detected. One recipient developed donor-derived infection, 69 cases of pneumonia, 52 cases of urinary tract infection, 35 cases of abdominal infection and 2 cases of hematogenous infection were reported within postoperative 1 year. Gram-negative bacteria were resistant to certain antibiotics. Gram-positive bacteria were sensitive to vancomycin. Fungi were sensitive to amphotericin B. Conclusions Gram-negative bacteria are the main pathogens of SPK recipients, which are resistant to certain antibiotics. Empirical use of antibiotics can be delivered before culture results are obtained. Subsequently, sensitive antibiotics should be chosen according to the culture results to improve the survival rate of SPK recipients.

Heart failure is a disease that seriously threatens human health and has become a global public health problem. Diagnostic and prognostic analysis of heart failure based on medical imaging and clinical data can reveal the progression of heart failure and reduce the risk of death of patients, which has important research value. The traditional analysis methods based on statistics and machine learning have some problems, such as insufficient model capability, poor accuracy due to prior dependence, and poor model adaptability. In recent years, with the development of artificial intelligence technology, deep learning has been gradually applied to clinical data analysis in the field of heart failure, showing a new perspective. This paper reviews the main progress, application methods and major achievements of deep learning in heart failure diagnosis, heart failure mortality and heart failure readmission, summarizes the existing problems and presents the prospects of related research to promote the clinical application of deep learning in heart failure clinical research.
Humans ; Artificial Intelligence ; Deep Learning ; Heart Failure/diagnosis* ; Machine Learning ; Diagnostic Imaging