https://cronfa.swan.ac.uk/Record/cronfa54196/Download/54196__17493__47815979be224dde9a7b3f9b037ce7ec.pdf

Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science.

Incidence of thrombotic complications in critically ill ICU patients with COVID-19.

https://escholarship.org/content/qt1r33f4p8/qt1r33f4p8.pdf?t=qho8bi

Dementia prevention, intervention, and care: 2020 report of the Lancet Commission.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Alongside investigations into the virology of SARS-CoV-2, understanding the fundamental physiological and immunological processes underlying the clinical manifestations of COVID-19 is vital for the identification and rational design of effective therapies. Here, we provide an overview of the pathophysiology of SARS-CoV-2 infection. We describe the interaction of SARS-CoV-2 with the immune system and the subsequent contribution of dysfunctional immune responses to disease progression. From nascent reports describing SARS-CoV-2, we make inferences on the basis of the parallel pathophysiological and immunological features of the other human coronaviruses targeting the lower respiratory tract - severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV). Finally, we highlight the implications of these approaches for potential therapeutic interventions that target viral infection and/or immunoregulation.

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The trinity of COVID-19: immunity, inflammation and intervention.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that emerged in late 2019 and has caused a pandemic of acute respiratory disease, named ‘coronavirus disease 2019’ (COVID-19), which threatens human health and public safety. In this Review, we describe the basic virology of SARS-CoV-2, including genomic characteristics and receptor use, highlighting its key difference from previously known coronaviruses. We summarize current knowledge of clinical, epidemiological and pathological features of COVID-19, as well as recent progress in animal models and antiviral treatment approaches for SARS-CoV-2 infection. We also discuss the potential wildlife hosts and zoonotic origin of this emerging virus in detail. In this Review, Shi and colleagues summarize the exceptional amount of research that has characterized acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19) since this virus has swept around the globe. They discuss what we know so far about the emergence and virology of SARS-CoV-2 and the pathogenesis and treatment of COVID-19.

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Characteristics of SARS-CoV-2 and COVID-19

BACKGROUNDSince December 2019, an outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, and is now becoming a global threat. We aimed to delineate and compare the immunological features of severe and moderate COVID-19.METHODSIn this retrospective study, the clinical and immunological characteristics of 21 patients (17 male and 4 female) with COVID-19 were analyzed. These patients were classified as severe (11 cases) and moderate (10 cases) according to the guidelines released by the National Health Commission of China.RESULTSThe median age of severe and moderate cases was 61.0 and 52.0 years, respectively. Common clinical manifestations included fever, cough, and fatigue. Compared with moderate cases, severe cases more frequently had dyspnea, lymphopenia, and hypoalbuminemia, with higher levels of alanine aminotransferase, lactate dehydrogenase, C-reactive protein, ferritin, and D-dimer as well as markedly higher levels of IL-2R, IL-6, IL-10, and TNF-α. Absolute numbers of T lymphocytes, CD4+ T cells, and CD8+ T cells decreased in nearly all the patients, and were markedly lower in severe cases (294.0, 177.5, and 89.0 × 106/L, respectively) than moderate cases (640.5, 381.5, and 254.0 × 106/L, respectively). The expression of IFN-γ by CD4+ T cells tended to be lower in severe cases (14.1%) than in moderate cases (22.8%).CONCLUSIONThe SARS-CoV-2 infection may affect primarily T lymphocytes, particularly CD4+ and CD8+ T cells, resulting in a decrease in numbers as well as IFN-γ production by CD4+ T cells. These potential immunological markers may be of importance because of their correlation with disease severity in COVID-19.TRIAL REGISTRATIONThis is a retrospective observational study without a trial registration number.FUNDINGThis work is funded by grants from Tongji Hospital for the Pilot Scheme Project, and partly supported by the Chinese National Thirteenth Five Years Project in Science and Technology for Infectious Disease (2017ZX10202201).

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Clinical and immunological features of severe and moderate coronavirus disease 2019.

Objective To delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) who died. Design Retrospective case series. Setting Tongji Hospital in Wuhan, China. Participants Among a cohort of 799 patients, 113 who died and 161 who recovered with a diagnosis of covid-19 were analysed. Data were collected until 28 February 2020. Main outcome measures Clinical characteristics and laboratory findings were obtained from electronic medical records with data collection forms. Results The median age of deceased patients (68 years) was significantly older than recovered patients (51 years). Male sex was more predominant in deceased patients (83; 73%) than in recovered patients (88; 55%). Chronic hypertension and other cardiovascular comorbidities were more frequent among deceased patients (54 (48%) and 16 (14%)) than recovered patients (39 (24%) and 7 (4%)). Dyspnoea, chest tightness, and disorder of consciousness were more common in deceased patients (70 (62%), 55 (49%), and 25 (22%)) than in recovered patients (50 (31%), 48 (30%), and 1 (1%)). The median time from disease onset to death in deceased patients was 16 (interquartile range 12.0-20.0) days. Leukocytosis was present in 56 (50%) patients who died and 6 (4%) who recovered, and lymphopenia was present in 103 (91%) and 76 (47%) respectively. Concentrations of alanine aminotransferase, aspartate aminotransferase, creatinine, creatine kinase, lactate dehydrogenase, cardiac troponin I, N-terminal pro-brain natriuretic peptide, and D-dimer were markedly higher in deceased patients than in recovered patients. Common complications observed more frequently in deceased patients included acute respiratory distress syndrome (113; 100%), type I respiratory failure (18/35; 51%), sepsis (113; 100%), acute cardiac injury (72/94; 77%), heart failure (41/83; 49%), alkalosis (14/35; 40%), hyperkalaemia (42; 37%), acute kidney injury (28; 25%), and hypoxic encephalopathy (23; 20%). Patients with cardiovascular comorbidity were more likely to develop cardiac complications. Regardless of history of cardiovascular disease, acute cardiac injury and heart failure were more common in deceased patients. Conclusion Severe acute respiratory syndrome coronavirus 2 infection can cause both pulmonary and systemic inflammation, leading to multi-organ dysfunction in patients at high risk. Acute respiratory distress syndrome and respiratory failure, sepsis, acute cardiac injury, and heart failure were the most common critical complications during exacerbation of covid-19.

https://www.bmj.com/content/bmj/368/bmj.m1091.full.pdf

Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study.

Background Since late December, 2019, an outbreak of pneumonia cases caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, and continued to spread throughout China and across the globe. To date, few data on immunologic features of Coronavirus Disease 2019 (COVID-19) have been reported. Methods In this single-centre retrospective study, a total of 21 patients with pneumonia who were laboratory-confirmed to be infected with SARS-CoV-2 in Wuhan Tongji hospital were included from Dec 19, 2019 to Jan 27, 2020. The immunologic characteristics as well as their clinical, laboratory, radiological features were compared between 11 severe cases and 10 moderate cases. Results Of the 21 patients with COVID-19, only 4 (19%) had a history of exposure to the Huanan seafood market. 7 (33.3%) patients had underlying conditions. The average age of severe and moderate cases was 63.9 and 51.4 years, 10 (90.9%) severe cases and 7 (70.0%) moderate cases were male. Common clinical manifestations including fever (100%, 100%), cough (70%, 90%), fatigue (100%, 70%) and myalgia (50%, 30%) in severe cases and moderate cases. PaO2/FiO2 ratio was significantly lower in severe cases (122.9) than moderate cases (366.2). Lymphocyte counts were significantly lower in severe cases (0.7 × 10□/L) than moderate cases (1.1 × 10□/L). Alanine aminotransferase, lactate dehydrogenase levels, high-sensitivity C-reactive protein and ferritin were significantly higher in severe cases (41.4 U/L, 567.2 U/L, 135.2 mg/L and 1734.4 ug/L) than moderate cases (17.6 U/L, 234.4 U/L, 51.4 mg/L and 880.2 ug /L). IL-2R, TNF-α and IL-10 concentrations on admission were significantly higher in severe cases (1202.4 pg/mL, 10.9 pg/mL and 10.9 pg/mL) than moderate cases (441.7 pg/mL, 7.5 pg/mL and 6.6 pg/mL). Absolute number of total T lymphocytes, CD4+T cells and CD8+T cells decreased in nearly all the patients, and were significantly lower in severe cases (332.5, 185.6 and 124.3 × 106/L) than moderate cases (676.5, 359.2 and 272.0 × 106/L). The expressions of IFN-γ by CD4+T cells tended to be lower in severe cases (14.6%) than moderate cases (23.6%). Conclusion The SARS-CoV-2 infection may affect primarily T lymphocytes, particularly CD4+T cells, resulting in significant decrease in number as well as IFN-γ production, which may be associated with disease severity. Together with clinical characteristics, early immunologic indicators including diminished T lymphocytes and elevated cytokines may serve as potential markers for prognosis in COVID-19.

https://www.medrxiv.org/content/medrxiv/early/2020/02/19/2020.02.16.20023903.full.pdf

Clinical and immunologic features in severe and moderate forms of Coronavirus Disease 2019

Synthetic aperture radar (SAR) satellites can provide microwave remote sensing images without weather and light constraints, so they are widely applied in the maritime monitoring field. Current SAR ship detection methods based on deep learning (DL) are difficult to deploy on satellites, because these methods usually have complex models and huge calculations. To solve this problem, based on the You Only Look Once version 5 (YOLOv5) algorithm, we propose a lightweight on-board SAR ship detector called Lite-YOLOv5, which (1) reduces the model volume; (2) decreases the floating-point operations (FLOPs); and (3) realizes the on-board ship detection without sacrificing accuracy. First, in order to obtain a lightweight network, we design a lightweight cross stage partial (L-CSP) module to reduce the amount of calculation and we apply network pruning for a more compact detector. Then, in order to ensure the excellent detection performance, we integrate a histogram-based pure backgrounds classification (HPBC) module, a shape distance clustering (SDC) module, a channel and spatial attention (CSA) module, and a hybrid spatial pyramid pooling (H-SPP) module to improve detection performance. To evaluate the on-board SAR ship detection ability of Lite-YOLOv5, we also transplant it to the embedded platform NVIDIA Jetson TX2. Experimental results on the Large-Scale SAR Ship Detection Dataset-v1.0 (LS-SSDD-v1.0) show that Lite-YOLOv5 can realize lightweight architecture with a 2.38 M model volume (14.18% of model size of YOLOv5), on-board ship detection with a low computation cost (26.59% of FLOPs of YOLOv5), and superior detection accuracy (1.51% F1 improvement compared with YOLOv5).

/pdf/lite-yolov5-a-lightweight-deep-learning-detector-for-on-243d6zej.pdf

Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images

Existing instance segmentation models mostly pay less attention to the targeted characteristics of ships in synthetic aperture radar (SAR) images, which hinders further accuracy improvements, leading to poor segmentation performance in more complex SAR image scenes. To solve this problem, we propose a hybrid task cascade plus (HTC+) for better SAR ship instance segmentation. Aiming at the specific SAR ship task, seven techniques are proposed to ensure the excellent performance of HTC+ in more complex SAR image scenes, i.e., a multi-resolution feature extraction network (MRFEN), an enhanced feature pyramid net-work (EFPN), a semantic-guided anchor adaptive learning network (SGAALN), a context ROI extractor (CROIE), an enhanced mask interaction network (EMIN), a post-processing technique (PPT), and a hard sample mining training strategy (HSMTS). Results show that each of them offers an observable accuracy gain, and the instance segmentation performance in more complex SAR image scenes becomes better. On two public datasets SSDD and HRSID, HTC+ surpasses the other nine competitive models. It achieves 6.7% higher box AP and 5.0% higher mask AP than HTC on SSDD. These are 4.9% and 3.9% on HRSID.

/pdf/htc-for-sar-ship-instance-segmentation-2h5vgipv.pdf

Xiaoping Zhang

Papers

Clinical and immunological features of severe and moderate coronavirus disease 2019.

Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study.

Clinical and immunologic features in severe and moderate forms of Coronavirus Disease 2019

Lite-YOLOv5: A Lightweight Deep Learning Detector for On-Board Ship Detection in Large-Scene Sentinel-1 SAR Images

HTC+ for SAR Ship Instance Segmentation