Corpus overview


Overview

MeSH Disease

Pneumonia (938)

Infections (439)

Disease (435)

Coronavirus Infections (273)

Death (203)


Human Phenotype

Pneumonia (1024)

Fever (166)

Cough (133)

Respiratory distress (78)

Hypertension (59)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 1064
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    Rationale for the Use of Radiation-Activated Mesenchymal Stem Cells in Acute Respiratory Distress HP Syndrome MESHD

    Authors: Isabel Tovar Martín; Rosa Guerrero; Jesús Joaquín Lopez-Peñalver; José Expósito; José Mariano Ruiz de Almodóvar

    id:10.20944/preprints202008.0035.v1 Date: 2020-08-02 Source: Preprints.org

    Previously we have shown that the combination of radiotherapy with human-umbilical-cord-derived mesenchymal stem-cell therapy significantly reduces the size of the xenotumours in mice, both in the directly irradiated tumour and in the distant non-irradiated tumour or in its metastasis. We have also shown that exosomes secreted from mesenchymal stem-cells pre-irradiated with 2 Gy are quantitatively, functionally and qualitatively different from the exosomes secreted from non-irradiated mesenchymal cells and also that proteins, exosomes and microvesicles secreted by mesenchymal cells suffer a dramatic change when cells are activated or non-activated, with the amount of protein present in the exosomes of the pre-irradiated cells being 1.5-fold times greater compared to those from non-irradiated cells. This finding correlates with a dramatic increase in the anti-tumour activity of the exosomes secreted by pre-irradiated mesenchymal-cells. After the proteomic analysis of the load of the exosomes released from both irradiated and non-irradiated cells, we conclude that annexin A1 is the most important and significant difference between the exosomes released by the cells in either status. Knowing the role of annexin A1 in the control of hypoxia MESHD and inflammation MESHD which is characteristic of acute- distress-respiratory HP syndrome MESHD, we have designed a hypothetical therapeutic strategy, based on the transplantation of mesenchymal stem cells stimulated with radiation, to alleviate the symptoms of patients who, due to pneumonia MESHD pneumonia HP caused by COVID-19, require the care of an intensive care unit for patients with life-threatening conditions. With this hypothesis, we would seek to improve the patients’ respiratory capacity and increase the expectations of their cure.

    COVID-19: Role of the Interferons

    Authors: Claudio G. Gallo; Sirio Fiorino; Giovanni Posabella; Donato Antonacci; Antonio Tropeano; Emanuele Pausini; Carlotta Pausini; Tommaso Guarniero; Marco Zancanaro

    id:202008.0018/v1 Date: 2020-08-02 Source: Preprints.org

    COVID-19 disease MESHD, caused by the SARS-CoV2 virus, is a potentially fatal disease MESHD that represents a serious public health and economic problem worldwide. The SARS-CoV2 virus infects the lower respiratory tract and can cause pneumonia MESHD pneumonia HP in humans. ARDS is the leading cause of death MESHD in COVID-19 disease MESHD. One of the main characteristics of ARDS is the cytokine storm, an uncontrolled systemic inflammatory response resulting from the release of pro-inflammatory cytokines and chemokines and growth factors, by immune cells. The other important aspect of the disease MESHD is represented by the involvement of the vascular organ that undergoes endothelitis. Hyperinflammation and endothelitis contribute in various ways to trigger coagulation disorders with diffuse micro thrombotic and thromboembolic phenomena. Lastly, multiple organ failure MESHD may occur (MOF). Since so far there is no approved treatment, there is an urgent need to reposition known treatments, considered safe, to be included in trials. Naturally produced interferons represent the body's first line of defense against viruses. Pharmacological forms, obtained by means of genetic recombination techniques, have long been approved and used to treat numerous pathologies. Interferons are divided into three families, within which some subfamilies are distinguishable. Only IFN-II comprises a single isoform which has completely different aspects and functions. The IFN I and III, however, each comprise different subfamilies (17 subfamilies the IFN-I and 4 subfamilies the IFN-III), share many aspects, representing the body's first antiviral response, but play different roles. The use of IFNs has been studied in two severe hCoV (Human Coronavirus) diseases MESHD, closely related to COVID-19 disease MESHD, such as SARS and MERS. Numerous in vitro and in vivo studies have been conducted, often in combination with other antivirals. The results have been controversial. The positive results in vitro and in experimental animals were often not replicable in humans. The possible positioning of these molecules in the right window of therapeutic opportunity requires that the complex dialogue between IFN, inflammasome, cytokines, pro-inflammatory chemokines, growth factors and barrier function be shed light.

    Mitigating Arrhythmia HP Risk in Hydroxychloroquine and Azithromycin Treated COVID-19 Patients using Arrhythmia HP Risk Management Plan

    Authors: Kazimieras Maneikis M.D.; Ugne Ringeleviciute M.D.; Justinas Bacevicius M.D.; Egle Dieninyte-Misiune M.D.; Emilija Burokaite M.D.; Gintare Kazbaraite M.D.; Marta Monika Janusaite M.D.; Austeja Dapkeviciute M.D.; Andrius Zucenka M.D.; Valdas Peceliunas M.D. Ph.D.; Lina Kryzauskaite M.D.; Vytautas Kasiulevicius M.D. Ph.D.; Donata Ringaitiene M.D. Ph.D.; Birute Zablockiene M.D. Ph.D.; Tadas Zvirblis; Germanas Marinskis M.D. Ph.D.; Ligita Jancoriene M.D. Ph.D.; Laimonas Griskevicius M.D. Ph.D.

    doi:10.21203/rs.3.rs-50501/v1 Date: 2020-07-29 Source: ResearchSquare

    Background: Hydroxychloroquine and Azithromycin use is associated with QT interval prolongation and arrhythmias HP. Despite ongoing multiple clinical trials for treatment of COVID19 infection MESHD, no definite cardiac safety protocols were proposed. The aim of our study was to assess cardiac safety in COVID-19 patients treated with the combination of Hydroxychloroquine and Azithromycin using close monitoring and arrhythmia HP risk management plan.Methods and results: We retrospectively examined arrhythmia HP safety of treatment with Hydroxychloroquine and Azithromycin in the setting of pre-defined cardiac arrhythmia MESHD arrhythmia HP risk management plan. 81 patients were included from March 23rd to May 10th 2020. The median age TRANS was 59 years, 58.0% were female TRANS. The majority of the study population (82.7%) had comorbidities, 98.8% had radiological signs of pneumonia MESHD pneumonia HP. 7 patients (8.6%) had QTc prolongation of ≥500 ms. The treatment was discontinued in 4 patients (4.9%). 14 patients (17.3%) experienced QTc≥480 ms and 16 patients (19.8%) had an increase of QTc≥60 ms. None of the patients developed ventricular tachycardia MESHD ventricular tachycardia HP. The risk factors significantly associated with QTc≥500 ms were hypokalemia MESHD hypokalemia HP (p = 0.032) and use of diuretics during the treatment (p = 0.020). Three patients had a lethal outcome; none of them associated with ventricular arrhythmias HP.Conclusion: We recorded a low incidence of QTc prolongation ≥500 ms and no ventricular tachycardia MESHD ventricular tachycardia HP events in COVID-19 patients treated with Hydroxychloroquine and Azithromycin using cardiac arrhythmia MESHD arrhythmia HP risk management plan.

    Clinical characteristics of neonates with coronavirus disease MESHD 2019 (COVID-19): a systematic review

    Authors: Yuan Hu; Jing Xiong; Yuan Shi

    doi:10.21203/rs.3.rs-50795/v1 Date: 2020-07-29 Source: ResearchSquare

    This study aimed to summarize the existing literature on severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) infection in newborns to clarify the clinical features and outcomes of neonates with COVID-19. A systematic search was performed in PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP databases from January 1, 2019 to April 30, 2020. The references of relevant studies were also searched. A descriptive summary was organized by aspects of clinical presentations (symptoms, laboratory examinations, and imaging) and outcomes. We identified 14 studies reporting 18 newborns with COVID-19. The most common clinical manifestations were fever MESHD fever HP (62.5%), shortness of breath (50.0%), diarrhea MESHD diarrhea HP/ vomiting MESHD vomiting HP/feeding intolerance(43.8%), cough MESHD cough HP (37.5%), dyspnea MESHD dyspnea HP (25.0%), and nasal congestion/runny nose/ sneeze MESHD sneeze HP(25.0%). Atypical symptoms included jaundice MESHD jaundice HP and convulsion. Lymphocyte numbers decreased in 5 cases, and radiographic findings were likely to show pneumonia MESHD pneumonia HP. All newborns recovered and discharged from the hospital, and there was no death MESHD.Conclusion: Clinical symptoms of neonatal SARS-CoV-2 infection MESHD are atypical, most of them are mild. Up to now, the prognosis of newborns is good, and there is no death MESHD. Intrauterine vertical transmission TRANS is possible, but confirmed evidence is still lacking. The Long-term follow-up of potential influences of SARS-CoV-2 infection MESHD on neonates need further exploration.

    PDCOVIDNet: A Parallel-Dilated Convolutional Neural Network Architecture for Detecting COVID-19 from Chest X-Ray Images

    Authors: Nihad Karim Chowdhury; Md. Muhtadir Rahman; Muhammad Ashad Kabir

    id:2007.14777v1 Date: 2020-07-29 Source: arXiv

    The COVID-19 pandemic continues to severely undermine the prosperity of the global health system. To combat this pandemic, effective screening techniques for infected patients are indispensable. There is no doubt that the use of chest X-ray images for radiological assessment is one of the essential screening techniques. Some of the early studies revealed that the patient's chest X-ray images showed abnormalities, which is natural for patients infected with COVID-19. In this paper, we proposed a parallel-dilated convolutional neural network (CNN) based COVID-19 detection system from chest x-ray images, named as Parallel-Dilated COVIDNet (PDCOVIDNet). First, the publicly available chest X-ray collection fully preloaded and enhanced, and then classified by the proposed method. Differing convolution dilation rate in a parallel form demonstrates the proof-of-principle for using PDCOVIDNet to extract radiological features for COVID-19 detection. Accordingly, we have assisted our method with two visualization methods, which are specifically designed to increase understanding of the key components associated with COVID-19 infection MESHD. Both visualization methods compute gradients for a given image category related to feature maps of the last convolutional layer to create a class-discriminative region. In our experiment, we used a total of 2,905 chest X-ray images, comprising three cases (such as COVID-19, normal, and viral pneumonia MESHD pneumonia HP), and empirical evaluations revealed that the proposed method extracted more significant features expeditiously related to the suspected disease MESHD. The experimental results demonstrate that our proposed method significantly improves performance SERO metrics: accuracy, precision, recall SERO, and F1 scores reach 96.58%, 96.58%, 96.59%, and 96.58%, respectively, which is comparable or enhanced compared with the state-of-the-art methods.

    Severity detection for the coronavirus disease MESHD 2019 (COVID-19) patients using a machine learning model based on the blood SERO and urine tests

    Authors: Haochen Yao; Nan Zhang; Ruochi Zhang; Meiyu Duan; Tianqi Xie; Jiahui Pan; Ejun Peng; Juanjuan Huang; Yingli Zhang; Xiaoming Xu; Hong Xu; Fengfeng Zhou; Guoqing Wang

    doi:10.1101/2020.07.27.20044990 Date: 2020-07-29 Source: medRxiv

    The recent outbreak of the coronavirus disease MESHD-2019 (COVID-19) caused serious challenges to the human society in China and across the world. COVID-19 induced pneumonia MESHD pneumonia HP in human hosts and carried a highly inter-person contagiousness. The COVID-19 patients may carry severe symptoms, and some of them may even die of major organ failures. This study utilized the machine learning algorithms to build the COVID-19 severeness detection model. Support vector machine (SVM) demonstrated a promising detection accuracy after 32 features were detected to be significantly associated with the COVID-19 severeness. These 32 features were further screened for inter-feature redundancies. The final SVM model was trained using 28 features and achieved the overall accuracy 0.8148. This work may facilitate the risk estimation of whether the COVID-19 patients would develop the severe symptoms. The 28 COVID-19 severeness associated biomarkers may also be investigated for their underlining mechanisms how they were involved in the COVID-19 infections MESHD.

    Efficacy and tolerability of bevacizumab in patients with severe Covid -19

    Authors: Jiaojiao Pang; Feng Xu; Gianmarco Aondio; Yu Li; Alberto Fumagalli; Ming Lu; Giuseppe Valmadre; Jie Wei; Yuan Bian; Margherita Canesi; Giovanni Damiani; Yuan Zhang; Dexin Yu; Jun Chen; Xiang Ji; Wenhai Sui; Bailu Wang; Shuo Wu; Attila Kovacs; Miriam Revera; Hao Wang; Ying Zhang; Yuguo Chen; Yihai Cao

    doi:10.1101/2020.07.26.20159756 Date: 2020-07-29 Source: medRxiv

    On the basis of Covid-19-induced pulmonary pathological and vascular changes, we hypothesized that the anti-VEGF drug bevacizumab might be beneficial for treating Covid-19 patients. We recruited 26 patients from 2-centers (China and Italy) with confirmed severe Covid-19, with respiratory rate [≥]30 times/min, oxygen saturation [≤]93% with ambient air, or partial arterial oxygen pressure to fraction of inspiration O2 ratio (PaO2/FiO2) >100mmHg and [≤]300 mmHg, and diffuse pneumonia MESHD pneumonia HP confirmed by chest radiological imaging. This trial was conducted from Feb 15 to April 5, 2020, and followed up for 28 days. Relative to comparable control patients with severe Covid-19 admitted in the same centers, bevacizumab showed clinical efficacy by improving oxygenation and shortening oxygen-support duration. Among 26 hospitalized patients with severe Covid-19 (median age TRANS, 62 years, 20 [77%] males TRANS), bevacizumab plus standard care markedly improved the PaO2/FiO2 ratios at days 1 and 7 (elevated values, day 1, 50.5 [4.0,119.0], p<0.001; day 7, 111.0 [85.0,165.0], p<0.001). By day 28, 24 (92%) patients showed improvement in oxygen-support status, 17 (65%) patients were discharged, and none showed worsen oxygen-support status nor died. Significant reduction of lesion areas and ratios were shown in chest CT or X-ray analysis within 7 days. Of 14 patients with fever MESHD fever HP, body temperature normalized within 72 hours in 13 (93%) patients. Lymphocyte counts in peripheral blood SERO were significantly increased and CRP levels were markedly decreased as shown in available data. Our findings suggested bevacizumab plus standard care was highly beneficial for treating patients with severe Covid-19. Clinical efficacy of bevacizumab warrants double blind, randomized, placebo-controlled trials.

    From SARS-CoV-2 hematogenous spreading to endothelial dysfunction: clinical-histopathological study of cutaneous signs of COVID-19

    Authors: Angela Patrì; Maria Vargas; Pasquale Buonanno; Maria Carmela Annunziata; Daniela Russo; Stefania Staibano; Giuseppe Servillo; Gabriella Fabbrocini

    doi:10.21203/rs.3.rs-50000/v1 Date: 2020-07-28 Source: ResearchSquare

    Background: To date, very few studies on clinical-histopathological correlations of cutaneous disorders associated with COVID-19 have been conducted. Case presentation: The Case 1 was a 90-year-old man, who tested positive for SARS-CoV-2 from a nasopharyngeal swab. Two days later,  he was hospitalized and after eleven days transferred to Intensive Care Unit. A chest CT showed bilateral ground-glass opacities. Just that day, an erythematous maculo-papular rash appeared on trunk, shoulders and neck, becoming purpuric after few days. Histological evaluations revealed a chronic superficial dermatitis MESHD with purpuric aspects. The superficial and papillary dermis appeared edematous, with a perivascular lympho-granulocytic infiltrate and erythrocytic extravasation. At intraepithelial level, spongiosis and a granulocyte infiltrate were detected. Arterioles, capillaries and post-capillary venules showed endothelial swelling and appeared ectasic. The patient was treated with hydroxychloroquine, azithromycin, lopinavir-ritonavir and tocilizumab. Regrettably, due to severe lung impairment, he died.The Case 2 was a 85-year-old man, admitted to Intensive Care Unit, where he was intubated. He had tested positive for SARS-CoV-2 from a nasopharyngeal swab two days before. A chest RX showed bilateral atypical pneumonia MESHD pneumonia HP. After seven days, a cutaneous reddening involving trunk, upper limbs, neck and face developed, configuring a sub- erythroderma HP. Histological evaluations displayed edema MESHD edema HP in the papillary and superficial reticular dermis, and a perivascular lymphocytic infiltrate in the superficial dermis. The patient was treated with hydroxychloroquine, azithromycin, lopinavir-ritonavir and tocilizumab. Sub- erythroderma HP as well as respiratory symptoms gradually improved until healing. Conclusions: The endothelial swelling detected in the Case 1 could be a morphological expression of SARS-CoV-2-induced endothelial dysfunction. We hypothesize that cutaneous damage could be initiated by endothelial dysfunction, caused by SARS-CoV-2 infection MESHD of endothelial cells or induced by immune system activation. The disruption of endothelial integrity could enhance microvascular permeability, extravasation of inflammatory cells and cytokines, with cutaneous injury. The Case 2 developed a sub- erythroderma HP associated with COVID-19, and a non-specific chronic dermatitis MESHD was detected at histological level. We speculate that a purpuric rash could represent the cutaneous sign of a more severe coagulopathy, as highlighted histologically by vascular abnormalities, while a sub- erythroderma HP could be expression of viral hematogenous spreading, inducing a non-specific chronic dermatitis MESHD.

    Real-Time Neural Network Scheduling of Emergency MESHD Medical Mask Production during COVID-19

    Authors: Chen-Xin Wu; Min-Hui Liao; Mumtaz Karatas; Sheng-Yong Chen; Yu-Jun Zheng

    id:2007.14055v1 Date: 2020-07-28 Source: arXiv

    During the outbreak of the novel coronavirus pneumonia MESHD pneumonia HP (COVID-19), there is a huge demand for medical masks. A mask manufacturer often receives a large amount of orders that are beyond its capability. Therefore, it is of critical importance for the manufacturer to schedule mask production tasks as efficiently as possible. However, existing scheduling methods typically require a considerable amount of computational resources and, therefore, cannot effectively cope with the surge of orders. In this paper, we propose an end-to-end neural network for scheduling real-time production tasks. The neural network takes a sequence of production tasks as inputs to predict a distribution over different schedules, employs reinforcement learning to optimize network parameters using the negative total tardiness as the reward signal, and finally produces a high-quality solution to the scheduling problem. We applied the proposed approach to schedule emergency MESHD production tasks for a medical mask manufacturer during the peak of COVID-19 in China. Computational results show that the neural network scheduler can solve problem instances with hundreds of tasks within seconds. The objective function value (i.e., the total weighted tardiness) produced by the neural network scheduler is significantly better than those of existing constructive heuristics, and is very close to those of the state-of-the-art metaheuristics whose computational time is unaffordable in practice.

    CovMUNET: A Multiple Loss Approach towards Detection of COVID-19 from Chest X-ray

    Authors: A. Q. M. Sazzad Sayyed; Dipayan Saha; Abdul Rakib Hossain

    id:2007.14318v1 Date: 2020-07-28 Source: arXiv

    The recent outbreak of COVID-19 has halted the whole world, bringing a devastating effect on public health, global economy, and educational systems. As the vaccine of the virus is still not available, the most effective way to combat the virus is testing and social distancing. Among all other detection techniques, the Chest X-ray (CXR) based method can be a good solution for its simplicity, rapidity, cost, efficiency, and accessibility. In this paper, we propose CovMUNET, which is a multiple loss deep neural network approach to detect COVID-19 cases from CXR images. Extensive experiments are performed to ensure the robustness of the proposed algorithm and the performance SERO is evaluated in terms of precision, recall SERO, accuracy, and F1-score. The proposed method outperforms the state-of-the-art approaches with an accuracy of 96.97% for 3-class classification (COVID-19 vs normal vs pneumonia MESHD pneumonia HP) and 99.41% for 2-class classification (COVID vs non-COVID). The proposed neural architecture also successfully detects the abnormality in CXR images.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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