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COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the common clinical manifestations of severe COVID-19 and it is also responsible for the current shortage of ventilators worldwide. This study aims to analyze the clinical characteristics of COVID-19 ARDS patients and establish a diagnostic system based on artificial intelligence (AI) method to predict the probability of ARDS in COVID-19 patients. We collected clinical data of 659 COVID-19 patients from 11 regions in China. The clinical characteristics of the ARDS group and no-ARDS group of COVID-19 patients were elaborately compared and both traditional machine learning algorithms and deep learning-based method were used to build the prediction models. Results indicated that the median age of ARDS patients was 56.5 years old, which was significantly older than those with non-ARDS by 7.5 years. Male and patients with BMI > 25 were more likely to develop ARDS. The clinical features of ARDS patients included cough (80.3%), polypnea (59.2%), lung consolidation (53.9%), secondary bacterial infection (30.3%), and comorbidities such as hypertension (48.7%). Abnormal biochemical indicators such as lymphocyte count, CK, NLR, AST, LDH, and CRP were all strongly related to the aggravation of ARDS. Furthermore, through various AI methods for modeling and prediction effect evaluation based on the above risk factors, decision tree achieved the best AUC, accuracy, sensitivity and specificity in identifying the mild patients who were easy to develop ARDS, which undoubtedly helped to deliver proper care and optimize use of limited resources.

AbstractObjectiveTo use the relation between cigarette consumption and cardiovascular disease to quantify the risk of coronary heart disease and stroke for light smoking (one to five cigarettes/day).DesignSystematic review and meta-analysis.Data sourcesMedline 1946 to May 2015, with manual searches of references.Eligibility criteria for selecting studiesProspective cohort studies with at least 50 events, reporting hazard ratios or relative risks (both hereafter referred to as relative risk) compared with never smokers or age specific incidence in relation to risk of coronary heart disease or stroke.Data extraction/synthesisMOOSE guidelines were followed. For each study, the relative risk was estimated for smoking one, five, or 20 cigarettes per day by using regression modelling between risk and cigarette consumption. Relative risks were adjusted for at least age and often additional confounders. The main measure was the excess relative risk for smoking one cigarette per day (RR1_per_day−1) expressed as a proportion of that for smoking 20 cigarettes per day (RR20_per_day−1), expected to be about 5% assuming a linear relation between risk and consumption (as seen with lung cancer). The relative risks for one, five, and 20 cigarettes per day were also pooled across all studies in a random effects meta-analysis. Separate analyses were done for each combination of sex and disorder.ResultsThe meta-analysis included 55 publications containing 141 cohort studies. Among men, the pooled relative risk for coronary heart disease was 1.48 for smoking one cigarette per day and 2.04 for 20 cigarettes per day, using all studies, but 1.74 and 2.27 among studies in which the relative risk had been adjusted for multiple confounders. Among women, the pooled relative risks were 1.57 and 2.84 for one and 20 cigarettes per day (or 2.19 and 3.95 using relative risks adjusted for multiple factors). Men who smoked one cigarette per day had 46% of the excess relative risk for smoking 20 cigarettes per day (53% using relative risks adjusted for multiple factors), and women had 31% of the excess risk (38% using relative risks adjusted for multiple factors). For stroke, the pooled relative risks for men were 1.25 and 1.64 for smoking one or 20 cigarettes per day (1.30 and 1.56 using relative risks adjusted for multiple factors). In women, the pooled relative risks were 1.31 and 2.16 for smoking one or 20 cigarettes per day (1.46 and 2.42 using relative risks adjusted for multiple factors). The excess risk for stroke associated with one cigarette per day (in relation to 20 cigarettes per day) was 41% for men and 34% for women (or 64% and 36% using relative risks adjusted for multiple factors). Relative risks were generally higher among women than men.ConclusionsSmoking only about one cigarette per day carries a risk of developing coronary heart disease and stroke much greater than expected: around half that for people who smoke 20 per day. No safe level of smoking exists for cardiovascular disease. Smokers should aim to quit instead of cutting down to significantly reduce their risk of these two common major disorders.

Background Pneumonia is a common complication of influenza and closely related to mortality in influenza patients. The present study examines cytokines as predictors of the prognosis of influenza-associated pneumonia. Methods This study included 101 inpatients with influenza (64 pneumonia and 37 non-pneumonia patients). 48 cytokines were detected in the serum samples of the patients and the clinical characteristics were analyzed. The correlation between them was analyzed to identify predictive biomarkers for the prognosis of influenza-associated pneumonia. Results Seventeen patients had poor prognosis and developed pneumonia. Among patients with influenza-associated pneumonia, the levels of 8 cytokines were significantly higher in those who had a poor prognosis: interleukin-6 (IL-6), interferon-γ (IFN-γ), granulocyte colony-stimulating factor (G-CSF), monocyte colony-stimulating factor (M-CSF), monocyte chemoattractant protein-1 (MCP-1), monocyte chemoattractant protein-3, Interleukin-2 receptor subunit alpha and Hepatocyte growth factor. Correlation analysis showed that the IL-6, G-CSF, M-CSF, IFN-γ, and MCP-1 levels had positive correlations with the severity of pneumonia. IL-6 and G-CSF showed a strong and positive correlation with poor prognosis in influenza-associated pneumonia patients. The combined effect of the two cytokines resulted in the largest area (0.926) under the receiver-operating characteristic curve. Conclusion The results indicate that the probability of poor prognosis in influenza patients with pneumonia is significantly increased. IL-6, G-CSF, M-CSF, IFN-γ, and MCP-1 levels had a positive correlation with the severity of pneumonia. Importantly, IL-6 and G-CSF were identified as significant predictors of the severity of influenza-associated pneumonia.

To provide a complete toxicity profile, toxicity spectrum, and a safety ranking of immune checkpoint inhibitor (ICI) drugs for treatment of cancer. Systematic review and network meta-analysis. Electronic databases (PubMed, Embase, Cochrane Library, and Web of Science) were systematically searched to include relevant studies published in English between January 2007 and February 2018. Only head-to-head phase II and III randomised controlled trials comparing any two or three of the following treatments or different doses of the same ICI drug were included: nivolumab, pembrolizumab, ipilimumab, tremelimumab, atezolizumab, conventional therapy (chemotherapy, targeted therapy, and their combinations), two ICI drugs, or one ICI drug with conventional therapy. Eligible studies must have reported site, organ, or system level data on treatment related adverse events. High quality, single arm trials and placebo controlled trials on ICI drugs were selected to establish a validation group. 36 head-to-head phase II and III randomised trials (n=15 370) were included. The general safety of ICI drugs ranked from high to low for all adverse events was as follows: atezolizumab (probability 76%, pooled incidence 66.4%), nivolumab (56%, 71.8%), pembrolizumab (55%, 75.1%), ipilimumab (55%, 86.8%), and tremelimumab (54%, not applicable). The general safety of ICI drugs ranked from high to low for severe or life threatening adverse events was as follows: atezolizumab (49%, 15.1%), nivolumab (46%, 14.1%), pembrolizumab (72%, 19.8%), ipilimumab (51%, 28.6%), and tremelimumab (28%, not applicable). Compared with conventional therapy, treatment-related adverse events for ICI drugs occurred mainly in the skin, endocrine, hepatic, and pulmonary systems. Taking one ICI drug was generally safer than taking two ICI drugs or one ICI drug with conventional therapy. Among the five ICI drugs, atezolizumab had the highest risk of hypothyroidism, nausea, and vomiting. The predominant treatment-related adverse events for pembrolizumab were arthralgia, pneumonitis, and hepatic toxicities. The main treatment-related adverse events for ipilimumab were skin, gastrointestinal, and renal toxicities. Nivolumab had a narrow and mild toxicity spectrum, mainly causing endocrine toxicities. Integrated evidence from the pooled incidences, subgroup, and sensitivity analyses implied that nivolumab is the best option in terms of safety, especially for the treatment of lung cancer. Compared with other ICI drugs used to treat cancer, atezolizumab had the best safety profile in general, and nivolumab had the best safety profile in lung cancer when taking an integrated approach. The safety ranking of treatments based on ICI drugs is modulated by specific treatment-related adverse events. PROSPERO CRD42017082553.

Objectives To investigate prognostic-related gene signature based on DNA damage repair and tumor microenvironment statue in human papillomavirus 16 negative (HPV16-) head and neck squamous cell carcinoma (HNSCC). Methods For the RNA-sequence matrix in HPV16- HNSCC in the Cancer Genome Atlas (TCGA) cohort, the DNA damage response (DDR) and tumor microenvironment (TM) status of each patient sample was estimated by using the ssGSEA algorithm. Through bioinformatics analysis in DDR_high/TM_high ( n  = 311) and DDR_high/TM_low ( n  = 53) groups, a survival-related gene signature was selected in the TCGA cohort. Two independent external validation cohorts (GSE65858 ( n  = 210) and GSE41613 ( n  = 97)) with HPV16- HNSCC patients validated the gene signature. Correlations among the clinical-related hub differentially expressed genes (DEGs) and infiltrated immunocytes were explored with the TIMER2.0 server. Drug screening based on hub DEGs was performed using the CellMiner and GSCALite databases. The loss-of-function studies were used to evaluate the effect of screened survival-related gene on the motility of HPV- HNSCC cells in vitro. Results A high DDR level ( P  = 0.025) and low TM score ( P  = 0.012) were independent risk factors for HPV16- HNSCC. Downregulated expression of ALOX12B or SPRR1A was associated with poor survival rate and advanced cancer stages. The pathway enrichment analysis showed the DDR_high/TM_low samples were enriched in glycosphingolipid biosynthesis-lacto and neolacto series, glutathione metabolism, platinum drug resistance, and ferroptosis pathways, while the DDR_high/TM_low samples were enriched in Th17 cell differentiation, Neutrophil extracellular trap formation, PD − L1 expression and PD − 1 checkpoint pathway in cancer. Notably, the expression of ALOX12B and SPRR1A were negatively correlated with cancer-associated fibroblasts (CAFs) infiltration and CAFs downstream effectors. Sensitivity to specific chemotherapy regimens can be derived from gene expressions. In addition, ALOX12B and SPRR1A expression was associated with the mRNA expression of insulin like growth factor 1 receptor (IGF1R), AKT serine/threonine kinase 1 (AKT1), mammalian target of rapamycin (MTOR), and eukaryotic translation initiation factor 4E binding protein 1 (EIF4EBP1) in HPV negative HNSCC. Down-regulation of ALOX12B promoted HPV- HNSCC cells migration and invasion in vitro. Conclusions ALOX12B and SPRR1A served as a gene signature for overall survival in HPV16- HNSCC patients, and correlated with the amount of infiltrated CAFs. The specific drug pattern was determined by the gene signature.

Old school public health and technology can allow aggressive containment to succeed

Currently, pyroptosis has received more and more attention because of its association with innate immunity and disease. The research scope of pyroptosis has expanded with the discovery of the gasdermin family. A great deal of evidence shows that pyroptosis can affect the development of tumors. The relationship between pyroptosis and tumors is diverse in different tissues and genetic backgrounds. In this review, we provide basic knowledge of pyroptosis, explain the relationship between pyroptosis and tumors, and focus on the significance of pyroptosis in tumor treatment. In addition, we further summarize the possibility of pyroptosis as a potential tumor treatment strategy and describe the side effects of radiotherapy and chemotherapy caused by pyroptosis. In brief, pyroptosis is a double-edged sword for tumors. The rational use of this dual effect will help us further explore the formation and development of tumors, and provide ideas for patients to develop new drugs based on pyroptosis.

Background Depression has been reported to be associated with some types of cancer in observational studies. However, the direction and magnitude of the causal relationships between depression and different types of cancer remain unclear. Methods We performed the two-sample bi-directional mendelian randomization with the publicly available GWAS summary statistics to investigate the causal relationship between the genetically predicted depression and the risk of multiple types of cancers, including ovarian cancer, breast cancer, lung cancer, glioma, pancreatic cancer, lymphoma, colorectal cancer, thyroid cancer, bladder cancer, and kidney cancer. The total sample size varies from 504,034 to 729,150. Causal estimate was calculated by inverse variance weighted method. We also performed additional sensitivity tests to evaluate the validity of the causal relationship. Results After correction for heterogeneity and horizontal pleiotropy, we only detected suggestive evidence for the causality of genetically predicted depression on breast cancer (OR = 1.09, 95% CI: 1.03–1.15, P  = 0.0022). The causal effect of depression on breast cancer was consistent in direction and magnitude in the sensitivity analysis. No evidence of causal effects of depression on other types of cancer and reverse causality was detected. Conclusions The result of this study suggests a causative effect of genetically predicted depression on specific type of cancer. Our findings emphasize the importance of depression in the prevention and treatment of breast cancer.