Highlights COVID -19 cases now confirmed in multiple countries. assessed the prevalence of comorbidities in infected patients.  comorbidities are risk factors for severe patients compare with Non-severe.J o u r n a l P r e -p r o o f 2  help the health sector guide vulnerable populations and assess the risk of deterioration.Background: An outbreak of Novel Coronavirus in Wuhan, China, the epidemic is more widespread than initially estimated, with cases now confirmed in multiple countries. Aims:The aim of the meta-analysis was to assess the prevalence of comorbidities in the COVID-19 infection patients and the risk of underlying diseases in severe patients compared to non-severe patients. Methods:A literature search was conducted using the databases PubMed, EMBASE, and Web of sciences until February 25, 2020. Risk ratio (OR) and 95% confidence intervals (CIs) were pooled using random-effects models.Results: Eight studies were included in the meta-analysis, including 46248 infected patients. The result showed the most prevalent clinical symptom was fever ( 91±3, 95% CI 86-97% ), followed by cough (67±7, 95% CI 59-76%), fatigue ( 51±0, 95% CI 34-68% ) and dyspnea ( 30±4, 95% CI 21-40%). The most prevalent comorbidity were hypertension (17±7, 95% CI 14-22%) and diabetes ( 8±6, 95% CI 6-11% ), followed by cardiovascular diseases ( 5±4, 95% CI 4-7% ) and respiratory system disease( 2±0, 95% CI 1-3% ). Compared with the Non-severe patient, the pooled odds ratio of hypertension, respiratory system disease, cardiovascular disease in severe patients were (OR 2.36, 95% CI: 1.46-3.83) ,(OR 2.46, 95% CI: 1.76-3.44) and (OR 3.42, 95% CI: 1.88-6.22)respectively. Conclusion:We assessed the prevalence of comorbidities in the COVID-19 infection patients and found underlying disease, including hypertension, respiratory system disease and cardiovascular, may be a risk factor for severe patients compared with Non-severe patients.

Alzheimer's disease (AD), one of the leading neurodegenerative disorders of older adults, which causes major socioeconomic burdens globally, lacks effective therapeutics without significant side effects. Besides the hallmark pathology of amyloid plaques and neurofibrillary tangles (NFTs), it has been reported that cyclin-dependent kinase 5 (Cdk5), a critical neuronal kinase, is hyperactivated in AD brains and is, in part, responsible for the above pathology. Here we show that a modified truncated 24-aa peptide (TFP5), derived from the Cdk5 activator p35, penetrates the blood-brain barrier after intraperitoneal injections, inhibits abnormal Cdk5 hyperactivity, and significantly rescues AD pathology (up to 70-80%) in 5XFAD AD model mice. The mutant mice, injected with TFP5 exhibit behavioral rescue, whereas no rescue was observed in mutant mice injected with either saline or scrambled peptide. However, TFP5 does not inhibit cell cycle Cdks or normal Cdk5/p35 activity, and thereby has no toxic side effects (even at 200 mg/kg), a common problem in most current therapeutics for AD. In addition, treated mice displayed decreased inflammation, amyloid plaques, NFTs, cell death, and an extended life by 2 mo. These results suggest TFP5 as a potential therapeutic, toxicity-free candidate for AD.

BackgroundThis study aimed to determine whether community-acquired pneumonia (CAP) had a metabolic profile and whether this profile can be used for disease severity assessment.MethodsA total of 175 individuals including 119 CAP patients and 56 controls were enrolled and divided into two cohorts. Serum samples from a discovery cohort (n = 102, including 38 non-severe CAP, 30 severe CAP, and 34 age and sex-matched controls) were determined by untargeted ultra-high-performance liquid chromatography with tandem mass spectrometry (LC-MS/MS)-based metabolomics. Selected differential metabolites between CAP patients versus controls, and between the severe CAP group versus non-severe CAP group, were confirmed by targeted mass spectrometry assays in a validation cohort (n = 73, including 32 non-severe CAP, 19 severe CAP and 22 controls). Pearson’s correlation analysis was performed to assess relationships between the identified metabolites and clinical severity of CAP. The area under the curve (AUC), sensitivity and specificity of the metabolites for predicting the severity of CAP were also investigated.ResultsThe metabolic signature was markedly different between CAP patients and controls. Fifteen metabolites were found to be significantly dysregulated in CAP patients, which were mainly mapped to the metabolic pathways of sphingolipid, arginine, pyruvate and inositol phosphate. The alternation trends of five metabolites among the three groups including sphinganine, p-Cresol sulfate, dehydroepiandrosterone sulfate (DHEA-S), lactate and l-arginine in the validation cohort were consistent with those in the discovery cohort. Significantly lower concentrations of sphinganine, p-Cresol sulfate and DHEA-S were observed in CAP patients than in controls (p < 0.05). Serum lactate and sphinganine levels were positively correlated with confusion, urea level, respiratory rate, blood pressure, and age > 65 years (CURB-65), pneumonia severity index (PSI) and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, while DHEA-S inversely correlated with the three scoring systems. Combining lactate, sphinganine and DHEA-S as a metabolite panel for discriminating severe CAP from non-severe CAP exhibited a better AUC of 0.911 (95% confidence interval 0.825–0.998) than CURB-65, PSI and APACHE II scores.ConclusionsThis study demonstrates that serum metabolomics approaches based on the LC-MS/MS platform can be applied as a tool to reveal metabolic changes during CAP and establish a metabolite signature related to disease severity.Trial registrationClinicalTrials.gov, NCT03093220. Registered retrospectively on 28 March 2017.Electronic supplementary materialThe online version of this article (10.1186/s13054-018-2049-2) contains supplementary material, which is available to authorized users.

Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy‐to‐monitor and highly stable materials for diagnosing Community‐acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP‐related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA‐miRNA‐mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus‐infection‐related signaling pathways (such as HTLV‐1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP‐related regulatory interactions that should inform future hypothesis‐driven research into the causes and potential treatment of this widespread and frequently fatal disease.

HRV is a common etiology in CAP among China adults, especially in severe CAP. Clinicians should be vigilant considering of the poor outcome. Highly qualified multiplex PCR techniques with invasive sampling are needed to increase the detection rate.