Background The impact of COVID-19 on physical and mental health and employment after hospitalisation with acute disease is not well understood. The aim of this study was to determine the effects of COVID-19-related hospitalisation on health and employment, to identify factors associated with recovery, and to describe recovery phenotypes. MethodsThe Post-hospitalisation COVID-19 study (PHOSP-COVID) is a multicentre, long-term follow-up study of adults (aged ≥18 years) discharged from hospital in the UK with a clinical diagnosis of COVID-19, involving an assessment between 2 and 7 months after discharge, including detailed recording of symptoms, and physiological and biochemical testing. Multivariable logistic regression was done for the primary outcome of patient-perceived recovery, with age, sex, ethnicity, body-mass index, comorbidities, and severity of acute illness as covariates. A posthoc cluster analysis of outcomes for breathlessness, fatigue, mental health, cognitive impairment, and physical performance was done using the clustering large applications k-medoids approach. The study is registered on the ISRCTN Registry (ISRCTN10980107). Findings We report findings for 1077 patients discharged from hospital between March 5 and Nov 30, 2020, who underwent assessment at a median of 5•9 months (IQR 4•9-6•5) after discharge. Participants had a mean age of 58 years (SD 13); 384 (36%) were female, 710 (69%) were of white ethnicity, 288 (27%) had received mechanical ventilation, and 540 (50%) had at least two comorbidities. At follow-up, only 239 (29%) of 830 participants felt fully recovered, 158 (20%) of 806 had a new disability (assessed by the Washington Group Short Set on Functioning), and 124 (19%) of 641 experienced a health-related change in occupation. Factors associated with not recovering were female sex, middle age (40-59 years), two or more comorbidities, and more severe acute illness. The magnitude of the persistent health burden was substantial but only weakly associated with the severity of acute illness. Four clusters were identified with different severities of mental and physical health impairment (n=767): very severe (131 patients, 17%), severe (159, 21%), moderate along with cognitive impairment (127, 17%), and mild (350, 46%). Of the outcomes used in the cluster analysis, all were closely related except for cognitive impairment. Three (3%) of 113 patients in the very severe cluster, nine (7%) of 129 in the severe cluster, 36 (36%) of 99 in the moderate cluster, and 114 (43%) of 267 in the mild cluster reported feeling fully recovered. Persistently elevated serum C-reactive protein was positively associated with cluster severity.Interpretation We identified factors related to not recovering after hospital admission with COVID-19 at 6 months after discharge (eg, female sex, middle age, two or more comorbidities, and more acute severe illness), and four different recovery phenotypes. The severity of physical and mental health impairments were closely related, whereas cognitive health impairments w...

The unprecedented outbreak of coronavirus disease 2019 (COVID-19) was declared a pandemic by the WHO, with >34 million people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, and with>1 million COVID-19-related deaths worldwide 1. COVID-19 can lead to a disease spectrum ranging from mild respiratory symptoms to acute respiratory distress syndrome (ARDS) and death 2-4. SARS-CoV-2 is now the third highly pathogenic and transmissible coronavirus identified in humans. Human coronaviruses were first dis covered in the 1960s 5 , but it was not until the 21st century that coronaviruses were recognized as major threats to public health. SARS-CoV 6-9 , Middle East respiratory syndrome coronavirus (MERS-CoV) 10 and SARS-CoV-2 all cause severe respiratory tract infections and have been associated with global pandemics. SARS-CoV was first reported in China in 2003 and infected >8,000 indivi duals, causing 774 deaths worldwide 11. A decade later, MERS was first reported in Saudi Arabia and infected >2,494 individuals and caused 858 deaths, with an extremely high death rate of 34% in part owing to the lack of effective therapies 12,13. SARS-CoV, MERS-CoV and SARS-CoV-2 belong to the Betacoronavirus genus, which is one of four genera of coronavirus 14. Phylogenetic analysis revealed that SARS-CoV-2 is closely related to two bat-derived SARS-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21 (with around 88% sequence identity), SARS-CoV (approximately 79% sequence identity) and MERS-CoV (approximately 50% sequence identity) 15. Homology modelling revealed that the receptor-binding domain structures in SARS-CoV and SARS-CoV-2 are similar, despite some amino acid variations 15. MERS-CoV infects human cells by binding to the dipeptidyl peptidase 4 receptor 16 , whereas both SARS-CoV 17 and SARS-CoV-2 (refs 18,19) use angiotensin-converting enzyme 2 (ACE2) as a receptor to infect cells. For SARS-CoV-2 infection, in addition to ACE2, one or more proteases including transmembrane protease serine 2 (TMPRSS2), basigin (also known as CD147) and potentially cathepsin B or cathepsin L are required 18,19. Acute respiratory distress syndrome (ArDs). A syndrome characterized by severe acute respiratory failure arising from inflammation and fluid build-up in the lungs.

Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of more than 3300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, hepatocyte growth factor, interleukin-8, and granulocyte colony-stimulating factor, which were the strongest predictors of critical illness. Evidence of neutrophil activation was present on the first day of hospitalization in patients who would only later require transfer to the intensive care unit, thus preceding the onset of critical illness and predicting increased mortality. In the health system database, early elevations in developing and mature neutrophil counts also predicted higher mortality rates. Altogether, these data suggest a central role for neutrophil activation in the pathogenesis of severe COVID-19 and identify molecular markers that distinguish patients at risk of future clinical decompensation.

Infection results in the rapid activation of immunity genes in the Drosophila fat body. Two classes of transcription factors have been implicated in this process: the REL-containing proteins, Dorsal, Dif, and Relish, and the GATA factor Serpent. Here we present evidence that REL-GATA synergy plays a pervasive role in the immune response. SELEX assays identified consensus binding sites that permitted the characterization of several immunity regulatory DNAs. The distribution of REL and GATA sites within these DNAs suggests that most or all fat-specific immunity genes contain a common organization of regulatory elements: closely linked REL and GATA binding sites positioned in the same orientation and located near the transcription start site. Aspects of this "regulatory code" are essential for the immune response. These results suggest that immunity regulatory DNAs contain constrained organizational features, which may be a general property of eukaryotic enhancers.

DNA cytosine methylation plays a considerable role in normal development, gene regulation, and carcinogenesis. Hypermethylation of the promoters of some tumor suppressor genes and the associated silencing of these genes often occur in certain cancer types. The reversal of this process by DNA methylation inhibitors is a promising new strategy for cancer therapy. In addition to the four wellcharacterized nucleoside analogue methylation inhibitors, 5-azacytidine, 5-aza-2V -deoxycytidine (5-Aza-CdR), 5-fluoro-2V -deoxycytidine, and zebularine, there is a growing list of non-nucleoside inhibitors. However, a systemic study comparing these potential demethylating agents has not been done. In this study, we examined three non-nucleoside demethylating agents, (À)-epigallocatechin-3-gallate, hydralazine, and procainamide, and compared their effects and potencies with 5-Aza-CdR, the most potent DNA methylation inhibitor. We found that 5-Aza-CdR is far more effective in DNA methylation inhibition as well as in reactivating genes, compared with non-nucleoside inhibitors. [Mol Cancer Ther 2005;4(10):1515 -20]