Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Turning to critical illness is a common stage of various diseases and injuries before death. Patients usually have complex health conditions, while the treatment process involves a wide range of content, along with high requirements for doctor′s professionalism and multi-specialty teamwork, as well as a great demand for time-sensitive treatments. However, this is not matched with critical care professionals and the current state of medical care in China. Telemedicine, which shortens the distance of medical professionals and the gap of disease diagnosis and treatments in various regions through electronic information, can effectively solve the current problem. Therefore, there is an urgent need to develop a standardized, high-quality visualization telemedicine round system .Therefore, experts have been organized to search domestic and foreign literature on telemedicine round for critically ill patients and to form this consensus based on clinical experiences so as to further improve the level of critical care treatments in regions.

Background::Acute pulmonary embolism (APE) is a fatal cardiovascular disease, yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs. A simple, objective technique will help clinicians make a quick and precise diagnosis. In population studies, machine learning (ML) plays a critical role in characterizing cardiovascular risks, predicting outcomes, and identifying biomarkers. This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models.Methods::This is a single-center retrospective study. Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets. A total of 8 ML models, including random forest (RF), Na?ve Bayes, decision tree, K-nearest neighbors, logistic regression, multi-layer perceptron, support vector machine, and gradient boosting decision tree were developed based on the training set to diagnose APE. Thereafter, the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies, including the Wells score, revised Geneva score, and Years algorithm. Eventually, the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic (ROC) analysis.Results::The ML models were constructed using eight clinical features, including D-dimer, cardiac troponin T (cTNT), arterial oxygen saturation, heart rate, chest pain, lower limb pain, hemoptysis, and chronic heart failure. Among eight ML models, the RF model achieved the best performance with the highest area under the curve (AUC) (AUC = 0.774). Compared to the current clinical assessment strategies, the RF model outperformed the Wells score ( P = 0.030) and was not inferior to any other clinical probability assessment strategy. The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726. Conclusions::Based on RF algorithm, a novel prediction model was finally constructed for APE diagnosis. When compared to the current clinical assessment strategies, the RF model achieved better diagnostic efficacy and accuracy. Therefore, the ML algorithm can be a useful tool in assisting with the diagnosis of APE.

Objective To investigate the expression of pseudokinase Tribbles homology 3(TRIB3)and its clinical prognostic value in Siewert type Ⅱ adenocarcinoma of esophagogastric junction(AEG).Methods Western blot and immunohistochemical method were used to detect the expression of TRIB3 in R0 resected Siewert type Ⅱ AEG and its corresponding adjacent tissues,and analyze its rela-tionship with clinical parameters,survival and prognosis.Results Western blot analysis showed that the expression level of TRIB3 in Siewert type Ⅱ AEG tissues was significantly lower than that in the adjacent tissues(P<0.05).The immunohistochemical Results showed that the positive expression rate of TRIB3 in cancer tissues was significantly lower than that in adjacent tissues(P<0.01).The expression of TRIB3 was significantly correlated with the degree of differentiation,clinical TNM stage and lymph node metastasis(P<0.05),but not with age,gender and pathological morphology(P>0.05).Kaplan-Meier survival analysis showed that the long-term survival of patients with positive TRIB3 expression was significantly better than that of patients with negative TRIB3 expression(P<0.01).Univariate(HR =0.290,95%CI:0.110-0.761,P =0.012)and multivariate(HR =0.179,95%CI:0.051-0.630,P = 0.007)COX regression analysis showed that TRIB3 could be used as an independent prognostic factor for patients with Siewert type ⅡAEG(P<0.05).Conclusion TRIB3 may be involved in the occurrence and development of Siewert typeⅡ AEG.It is expected to be-come a new target for early diagnosis and treatment of AEG,and can be used as an important indicator for judging the prognosis of patients.

New threats posed by the emerging circulating variants of SARS-CoV-2 highlight the need to find conserved neutralizing epitopes for therapeutic antibodies and efficient vaccine design. Here, we identified a receptor-binding domain (RBD)-binding antibody, XG014, which potently neutralizes β-coronavirus lineage B (β-CoV-B), including SARS-CoV-2, its circulating variants, SARS-CoV and bat SARSr-CoV WIV1. Interestingly, antibody family members competing with XG014 binding show reduced levels of cross-reactivity and induce antibody-dependent SARS-CoV-2 spike (S) protein-mediated cell-cell fusion, suggesting a unique mode of recognition by XG014. Structural analyses reveal that XG014 recognizes a conserved epitope outside the ACE2 binding site and completely locks RBD in the non-functional "down" conformation, while its family member XG005 directly competes with ACE2 binding and position the RBD "up". Single administration of XG014 is effective in protection against and therapy of SARS-CoV-2 infection in vivo. Our findings suggest the potential to develop XG014 as pan-β-CoV-B therapeutics and the importance of the XG014 conserved antigenic epitope for designing broadly protective vaccines against β-CoV-B and newly emerging SARS-CoV-2 variants of concern.
Angiotensin-Converting Enzyme 2 ; Antibodies, Neutralizing ; Antibodies, Viral ; COVID-19 ; Epitopes ; Humans ; SARS-CoV-2/genetics* ; Spike Glycoprotein, Coronavirus/genetics*

Animals ; Autoantigens ; genetics ; metabolism ; Cell Line, Tumor ; Golgi Apparatus ; genetics ; metabolism ; Golgi Matrix Proteins ; Insulin-Secreting Cells ; metabolism ; Membrane Proteins ; genetics ; metabolism ; Proinsulin ; genetics ; metabolism ; Rats ; rab1 GTP-Binding Proteins ; genetics ; metabolism

Objective To explore the clinical efficiency and safety of radiofrequency ablation combined with Tegafur,Gimeracil and Oteracil Porassium Capsules( S-1 capsules) for hepatocellular carcinoma.Methods Sixty HCC patients included in this study were underwent initial radiofrequency ablation and then they were di-vided into RFA+S-1 group and RFA control group according to the metronomic chemotherapy either with S-1 or not.The local tumor control and disease free survival outcome between the two groups were compared.Results Follow-up observation showed that the total control rate after 9 months′treatment was 93.3%in RFA+S-1 group vs.73.4%in RFA control group(P=0.038).During the 18 months of follow up,the median time for dis-ease free survival was 16.25 months in RFA+S-1 group vs.12.25 months in RFA control group( P<0.001) . One-year progression free survival rate in RFA group was 53.3%,which was significantly lower than the RFA+S-1 group(83.3%)(P=0.012).The major complication rate was 13.3%.No procedu rerelated death or severe complications occurred.Conclusion Metronomic chemotherapy with S-1 following initial radiofrequency ablation delays tumor progression and prolongs overall survival of patients with HCC tumors.