An Integrated Radiologic-Pathologic Understanding of COVID-19 Pneumonia.

This article reviews the radiologic and pathologic findings of the epithelial and endothelial injuries in COVID-19 pneumonia to help radiologists understand the fundamental nature of the disease. The radiologic and pathologic manifestations of COVID-19 pneumonia result from epithelial and endothelial injuries based on viral toxicity and immunopathologic effects. The pathologic features of mild and reversible COVID-19 pneumonia involve nonspecific pneumonia or an organizing pneumonia pattern, while the pathologic features of potentially fatal and irreversible COVID-19 pneumonia are characterized by diffuse alveolar damage followed by fibrosis or acute fibrinous organizing pneumonia. These pathologic responses of epithelial injuries observed in COVID-19 pneumonia are not specific to SARS-CoV-2 but rather constitute universal responses to viral pneumonia. Endothelial injury in COVID-19 pneumonia is a prominent feature compared with other types of viral pneumonia and encompasses various vascular abnormalities at different levels, including pulmonary thromboembolism, vascular engorgement, peripheral vascular reduction, a vascular tree-in-bud pattern, and lung perfusion abnormality. Chest CT with different imaging techniques (eg, CT quantification, dual-energy CT perfusion) can fully capture the various manifestations of epithelial and endothelial injuries. CT can thus aid in establishing prognosis and identifying patients at risk for deterioration.

Autopsy Case Report of Severe COVID-19 Pneumonia at a General Municipal Hospital.

We present the autopsy procedure and findings of severe coronavirus disease 2019 (COVID-19) pneumonia in an 85-year-old man. The patient required intubation immediately after admission for severe COVID-19 pneumonia. He had severe hypoxia that did not improve despite treatment with remdesivir, corticosteroids, and appropriate mechanical ventilation. On day 13, the patient developed sudden hypercapnia. His renal dysfunction subsequently worsened and became associated with hyperkalemia, and he passed away on day 15. An autopsy was performed to clarify the cause of the hypercapnic hypoxia. None of the medical personnel involved in the autopsy developed symptoms of COVID-19. Histologic examination showed various stages of diffuse alveolar damage throughout the lungs, with intra-alveolar hemorrhage in the upper zones. Microscopic examination of the kidneys revealed acute tubular necrosis. There was no significant systemic thrombosis. The autopsy findings were consistent with those typical of COVID-19.

Pathophysiological conditions induced by SARS-CoV-2 infection reduce ACE2 expression in the lung.

SARS-CoV-2 infection causes a variety of physiological responses in the lung, and understanding how the expression of SARS-CoV-2 receptor, angiotensin-converting enzyme 2 (ACE2), and its proteolytic activator, transmembrane serine protease 2 (TMPRSS2), are affected in patients with underlying disease such as interstitial pneumonia will be important in considering COVID-19 progression. We examined the expression of ACE2 and TMPRSS2 in an induced usual interstitial pneumonia (iUIP) mouse model and patients with IPF as well as the changes in whole-lung ACE2 and TMPRSS2 expression under physiological conditions caused by viral infection. Histopathological and biochemical characteristics were analyzed using human specimens from patients with IPF and precision-cut lung slices (PCLS) from iUIP mouse model showing UIP with honeycombing and severe fibrosis after non-specific interstitial pneumonia. ACE2 expression decreased with acute lung inflammation and increased in the abnormal lung epithelium of the iUIP mouse model. ACE2 is also expressed in metaplastic epithelial cells. Poly(I:C), interferons, and cytokines associated with fibrosis decreased ACE2 expression in PCLS in the iUIP model. Hypoxia also decreases ACE2 via HIF1α in PCLS. Antifibrotic agent, nintedanib attenuates ACE2 expression in invasive epithelial cells. Patients with IPF are at a higher risk of SARS-CoV-2 infection due to the high expression of ACE2. However, ACE2 and TMPRSS2 expression is decreased by immune intermediaries, including interferons and cytokines that are associated with viral infection and upon administration of antifibrotic agents, suggesting that most of the viral infection-induced pathophysiological responses aid the development of resistance against SARS-CoV-2 infection.

Bibliometric analysis of global research trends on pyroptosis in lung disease.

Background: Pyroptosis is a lytic pro-inflammatory programmed cell death mode that depends on caspase, inflammasome, and Gasdermin D (GSDMD). A growing number of studies have shown that pyroptosis is closely related to the pathophysiological mechanism of lung. The purpose of this study is to analyze the literature from Science Citation Index Expanded (SCI-expanded) of Web of Science Core Collection (WoSCC) and visualize the current trends and hotspots in the research of pyroptosis in lung disease. Methods: On February 20, 2022, we retrieved all articles on pyroptosis in lung disease from SCI-expanded of WoSCC. Original articles and reviews published in English from 2007 to 2021 were included in the analysis. VOSviewer 1.6.17 and CiteSpace 5.8.R2 were used to analyze the retrieved data and visualize the results. Result: 1798 qualified original articles and reviews on pyroptosis in lung disease were included in the bibliometric analysis. So far, the research in this field is still in a period of growth, and the number of global publications has increased yearly. Among the 66 countries that have published relevant articles, China ranked first in the number of publications, and the USA ranked first in the number of cited articles. Holian,A. was the author with the largest number of articles, including 21 published. The University of California System in the USA was the organization with the largest number of articles, totaling 55. Frontiers in Immunology was the journal with the most publications in pyroptosis. After bibliometric analysis, the frequently used keywords are: "NOD-like receptor3 (NLRP3) inflammasome", "inflammation", "oxidative stress", and "acute lung injury (ALI)". Conclusion: The research on pyroptosis in lung disease is in its growth stage. The information released in this article may help researchers better understand the hotspots and developmental trends in this field, the cooperation network information of authors, countries, and institutions, and the citation correlation between articles. With the in-depth study of the mechanism of pyroptosis, the focus has shifted to increasing research on the connections and influences of different diseases. So far, increasing attention has been paid to the research field of the relationship between ALI and pyroptosis related to COVID-19.

Effect of heated tobacco products and traditional cigarettes on pulmonary toxicity and SARS-CoV-2-induced lung injury.

Cigarette smoke (CS) significantly contributes to the development of chronic obstructive pulmonary disease (COPD). Heated tobacco products (HTPs), newly developed cigarette products, have been proposed as an alternative for safe cigarette smoking. Although it is plausible to think that replacing traditional cigarettes with HTPs would lower the risks of COPD, this notion requires confirmation by further investigations from sources independent of the tobacco industry. COPD is characterized by an ongoing inflammatory process in the lungs, and the renin-angiotensin system (RAS) has been implicated in the pathogenesis of COPD. Angiotensin-converting enzyme-2 (ACE2) functions as a negative regulator of RAS and has been suggested as a cellular receptor for the causative agent of SARS-CoV-2. It has been shown that smoking is most likely associated with the negative progression and adverse outcomes of SARS-CoV-2. In this study, we found that cigarette smoke extracts from traditional cigarettes (CSE) caused higher cytotoxicity and higher oxidative stress levels than extracts from HTPs (HTPE) in two lung cell lines (Calu-3 and Beas-2B). CSE and HTPE induced RAS activation, MAPK activation, and NF-kB inflammatory pathway activation, resulting in the production of inflammatory cytokines. Furthermore, CSE and a high dose of HTPE reduced tight junction proteins, including claudin 1, E-cadherin, and ZO-1, and disrupted lung epidermal tight junctions at the air-liquid interface (ALI). Finally, CSE and HTPE enhanced the spike protein S1-induced lung injury response. Together, these results suggest that HTPE induced similar lung pathogenesis relevant to COPD and SARS-CoV-2-induced lung injury caused by CSE.

Three-stage segmentation of lung region from CT images using deep neural networks.

BACKGROUND: Lung region segmentation is an important stage of automated image-based approaches for the diagnosis of respiratory diseases. Manual methods executed by experts are considered the gold standard, but it is time consuming and the accuracy is dependent on radiologists' experience. Automated methods are relatively fast and reproducible with potential to facilitate physician interpretation of images. However, these benefits are possible only after overcoming several challenges. The traditional methods that are formulated as a three-stage segmentation demonstrate promising results on normal CT data but perform poorly in the presence of pathological features and variations in image quality attributes. The implementation of deep learning methods that can demonstrate superior performance over traditional methods is dependent on the quantity, quality, cost and the time it takes to generate training data. Thus, efficient and clinically relevant automated segmentation method is desired for the diagnosis of respiratory diseases. METHODS: We implement each of the three stages of traditional methods using deep learning methods trained on five different configurations of training data with ground truths obtained from the 3D Image Reconstruction for Comparison of Algorithm Database (3DIRCAD) and the Interstitial Lung Diseases (ILD) database. The data was augmented with the Lung Image Database Consortium (LIDC-IDRI) image collection and a realistic phantom. A convolutional neural network (CNN) at the preprocessing stage classifies the input into lung and none lung regions. The processing stage was implemented using a CNN-based U-net while the postprocessing stage utilize another U-net and CNN for contour refinement and filtering out false positives, respectively. RESULTS: The performance of the proposed method was evaluated on 1230 and 1100 CT slices from the 3DIRCAD and ILD databases. We investigate the performance of the proposed method on five configurations of training data and three configurations of the segmentation system; three-stage segmentation and three-stage segmentation without a CNN classifier and contrast enhancement, respectively. The Dice-score recorded by the proposed method range from 0.76 to 0.95. CONCLUSION: The clinical relevance and segmentation accuracy of deep learning models can improve though deep learning-based three-stage segmentation, image quality evaluation and enhancement as well as augmenting the training data with large volume of cheap and quality training data. We propose a new and novel deep learning-based method of contour refinement.

Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection.

In this retrospective study, chest CTs of 121 symptomatic patients infected with coronavirus disease-19 (COVID-19) from four centers in China from January 18, 2020 to February 2, 2020 were reviewed for common CT findings in relationship to the time between symptom onset and the initial CT scan (i.e. early, 0-2 days (36 patients), intermediate 3-5 days (33 patients), late 6-12 days (25 patients)). The hallmarks of COVID-19 infection on imaging were bilateral and peripheral ground-glass and consolidative pulmonary opacities. Notably, 20/36 (56%) of early patients had a normal CT. With a longer time after the onset of symptoms, CT findings were more frequent, including consolidation, bilateral and peripheral disease, greater total lung involvement, linear opacities, "crazy-paving" pattern and the "reverse halo" sign. Bilateral lung involvement was observed in 10/36 early patients (28%), 25/33 intermediate patients (76%), and 22/25 late patients (88%).

Lipopolysaccharide induces acute lung injury and alveolar haemorrhage in association with the cytokine storm, coagulopathy and AT1R/JAK/STAT augmentation in a rat model that mimics moderate and severe Covid-19 pathology.

Progress in the study of Covid-19 disease in rodents has been hampered by the lack of angiotensin-converting enzyme 2 (ACE2; virus entry route to the target cell) affinities for the virus spike proteins across species. Therefore, we sought to determine whether a modified protocol of lipopolysaccharide (LPS)-induced acute respiratory distress syndrome in rats can mimic both cell signalling pathways as well as severe disease phenotypes of Covid-19 disease. Rats were injected via intratracheal (IT) instillation with either 15 mg/kg of LPS (model group) or saline (control group) before being killed after 3 days. A severe acute respiratory syndrome (SARS)-like effect was observed in the model group as demonstrated by the development of a "cytokine storm" (>2.7 fold increase in blood levels of IL-6, IL-17A, GM-CSF, and TNF-α), high blood ferritin, demonstrable coagulopathy, including elevated D-dimer (approximately 10-fold increase), PAI-1, PT, and APTT (p < 0.0001). In addition, LPS increased the expression of lung angiotensin II type I receptor (AT1R)-JAK-STAT axis (>4 fold increase). Chest imaging revealed bilateral small patchy opacities of the lungs. Severe lung injury was noted by the presence of both, alveolar collapse and haemorrhage, desquamation of epithelial cells in the airway lumen, infiltration of inflammatory cells (CD45+ leukocytes), widespread thickening of the interalveolar septa, and ultrastructural alterations similar to Covid-19. Thus, these findings demonstrate that IT injection of 15 mg/kg LPS into rats, induced an AT1R/JAK/STAT-mediated cytokine storm with resultant pneumonia and coagulopathy that was commensurate with moderate and severe Covid-19 disease noted in humans.

Persistent pulmonary pathology after COVID-19 is associated with high viral load, weak antibody response, and high levels of matrix metalloproteinase-9.

The association between pulmonary sequelae and markers of disease severity, as well as pro-fibrotic mediators, were studied in 108 patients 3 months after hospital admission for COVID-19. The COPD assessment test (CAT-score), spirometry, diffusion capacity of the lungs (DLCO), and chest-CT were performed at 23 Norwegian hospitals included in the NOR-SOLIDARITY trial, an open-labelled, randomised clinical trial, investigating the efficacy of remdesivir and hydroxychloroquine (HCQ). Thirty-eight percent had a CAT-score ≥ 10. DLCO was below the lower limit of normal in 29.6%. Ground-glass opacities were present in 39.8% on chest-CT, parenchymal bands were found in 41.7%. At admission, low pO2/FiO2 ratio, ICU treatment, high viral load, and low antibody levels, were predictors of a poorer pulmonary outcome after 3 months. High levels of matrix metalloproteinase (MMP)-9 during hospitalisation and at 3 months were associated with persistent CT-findings. Except for a negative effect of remdesivir on CAT-score, we found no effect of remdesivir or HCQ on long-term pulmonary outcomes. Three months after hospital admission for COVID-19, a high prevalence of respiratory symptoms, reduced DLCO, and persistent CT-findings was observed. Low pO2/FiO2 ratio, ICU-admission, high viral load, low antibody levels, and high levels of MMP-9 were associated with a worse pulmonary outcome.

Interactions between the Gut Microbiome, Lung Conditions, and Coronary Heart Disease and How Probiotics Affect These.

The importance of a healthy microbiome cannot be overemphasized. Disturbances in its composition can lead to a variety of symptoms that can extend to other organs. Likewise, acute or chronic conditions in other organs can affect the composition and physiology of the gut microbiome. Here, we discuss interorgan communication along the gut-lung axis, as well as interactions between lung and coronary heart diseases and between cardiovascular disease and the gut microbiome. This triangle of organs, which also affects the clinical outcome of COVID-19 infections, is connected by means of numerous receptors and effectors, including immune cells and immune-modulating factors such as short chain fatty acids (SCFA) and trimethlamine-N-oxide (TMAO). The gut microbiome plays an important role in each of these, thus affecting the health of the lungs and the heart, and this interplay occurs in both directions. The gut microbiome can be influenced by the oral uptake of probiotics. With an improved understanding of the mechanisms responsible for interorgan communication, we can start to define what requirements an 'ideal' probiotic should have and its role in this triangle.

The History and Mystery of Alveolar Epithelial Type II Cells: Focus on Their Physiologic and Pathologic Role in Lung.

Alveolar type II (ATII) cells are a key structure of the distal lung epithelium, where they exert their innate immune response and serve as progenitors of alveolar type I (ATI) cells, contributing to alveolar epithelial repair and regeneration. In the healthy lung, ATII cells coordinate the host defense mechanisms, not only generating a restrictive alveolar epithelial barrier, but also orchestrating host defense mechanisms and secreting surfactant proteins, which are important in lung protection against pathogen exposure. Moreover, surfactant proteins help to maintain homeostasis in the distal lung and reduce surface tension at the pulmonary air-liquid interface, thereby preventing atelectasis and reducing the work of breathing. ATII cells may also contribute to the fibroproliferative reaction by secreting growth factors and proinflammatory molecules after damage. Indeed, various acute and chronic diseases are associated with intensive inflammation. These include oedema, acute respiratory distress syndrome, fibrosis and numerous interstitial lung diseases, and are characterized by hyperplastic ATII cells which are considered an essential part of the epithelialization process and, consequently, wound healing. The aim of this review is that of revising the physiologic and pathologic role ATII cells play in pulmonary diseases, as, despite what has been learnt in the last few decades of research, the origin, phenotypic regulation and crosstalk of these cells still remain, in part, a mystery.

Airway-On-A-Chip: Designs and Applications for Lung Repair and Disease.

The lungs are affected by illnesses including asthma, chronic obstructive pulmonary disease, and infections such as influenza and SARS-CoV-2. Physiologically relevant models for respiratory conditions will be essential for new drug development. The composition and structure of the lung extracellular matrix (ECM) plays a major role in the function of the lung tissue and cells. Lung-on-chip models have been developed to address some of the limitations of current two-dimensional in vitro models. In this review, we describe various ECM substitutes utilized for modeling the respiratory system. We explore the application of lung-on-chip models to the study of cigarette smoke and electronic cigarette vapor. We discuss the challenges and opportunities related to model characterization with an emphasis on in situ characterization methods, both established and emerging. We discuss how further advancements in the field, through the incorporation of interstitial cells and ECM, have the potential to provide an effective tool for interrogating lung biology and disease, especially the mechanisms that involve the interstitial elements.

Pathological Features in 100 Deceased Patients With COVID-19 in Correlation With Clinical and Laboratory Data.

Background: Autopsies on COVID-19 deceased patients have many limitations due to necessary epidemiologic and preventative measures. The ongoing pandemic has caused a significant strain on healthcare systems and is being extensively studied around the world. Clinical data does not always corelate with post-mortem findings. The goal of our study was to find pathognomonic factors associated with COVID-19 mortality in 100 post-mortem full body autopsies. Materials and Methods: Following necessary safety protocol, we performed 100 autopsies on patients who were diagnosed with COVID-19 related death. The macroscopic and microscopic pathologies were evaluated along with clinical and laboratory findings. Results: Extensive coagulopathic changes are seen throughout the bodies of diseased patients. Diffuse alveolar damage is pathognomonic of COVID-19 viral pneumonia, and is the leading cause of lethal outcome in younger patients. Extrapulmonary pathology is predominantly seen in the liver and spleen. Intravascular thrombosis is often widespread and signs of septic shock are often present. Conclusion: The described pathological manifestations of COVID-19 in deceased patients are an insight into the main mechanisms of SARS-CoV-2 associated lethal outcome. The disease bears no obvious bias in severity, but seems to be more severe in some patients, hinting at genetic or epigenetic factors at play.

Interleukin-13: A pivotal target against influenza-induced exacerbation of chronic lung diseases.

Non-communicable, chronic respiratory diseases (CRDs) affect millions of individuals worldwide. The course of these CRDs (asthma, chronic obstructive pulmonary disease, and cystic fibrosis) are often punctuated by microbial infections that may result in hospitalization and are associated with increased risk of morbidity and mortality, as well as reduced quality of life. Interleukin-13 (IL-13) is a key protein that regulates airway inflammation and mucus hypersecretion. There has been much interest in IL-13 from the last two decades. This cytokine is believed to play a decisive role in the exacerbation of inflammation during the course of viral infections, especially, in those with pre-existing CRDs. Here, we discuss the common viral infections in CRDs, as well as the potential role that IL-13 plays in the virus-induced disease pathogenesis of CRDs. We also discuss, in detail, the immune-modulation potential of IL-13 that could be translated to in-depth studies to develop IL-13-based therapeutic entities.

Tobacco use disorder and the lungs.

This narrative review provides a summary of the impact of tobacco smoking on the respiratory system and the benefits of smoking cessation. Tobacco smoking is one of the leading preventable causes of death world-wide and a major risk factor for lung cancer and chronic obstructive pulmonary disease. Smoking is also associated with an increased risk of respiratory infections and appears to be related to poorer outcomes among those with COVID-19. Non-smokers with second-hand smoke exposure also experience significant adverse respiratory effects. Smoking imposes enormous health- and non-health-related costs to societies. The benefits of smoking cessation, in both prevention and management of respiratory disease, have been known for decades and, to this day, cessation support remains one of the most important cost-effective interventions that health professionals can provide to people who smoke. Cessation at any age confers substantial health benefits, even in smokers with established morbidities. As other treatments for chronic respiratory disease advance and survival rates increase, smoking cessation treatment will become even more relevant. While smoking cessation interventions are available, the offer of these by clinicians and uptake by patients remain limited.

Chronic lung diseases are associated with gene expression programs favoring SARS-CoV-2 entry and severity.

Patients with chronic lung disease (CLD) have an increased risk for severe coronavirus disease-19 (COVID-19) and poor outcomes. Here, we analyze the transcriptomes of 611,398 single cells isolated from healthy and CLD lungs to identify molecular characteristics of lung cells that may account for worse COVID-19 outcomes in patients with chronic lung diseases. We observe a similar cellular distribution and relative expression of SARS-CoV-2 entry factors in control and CLD lungs. CLD AT2 cells express higher levels of genes linked directly to the efficiency of viral replication and the innate immune response. Additionally, we identify basal differences in inflammatory gene expression programs that highlight how CLD alters the inflammatory microenvironment encountered upon viral exposure to the peripheral lung. Our study indicates that CLD is accompanied by changes in cell-type-specific gene expression programs that prime the lung epithelium for and influence the innate and adaptive immune responses to SARS-CoV-2 infection.

Integrated evaluation of lung disease in single animals.

During infectious disease, pathogen load drives inflammation and immune response that together contribute to tissue injury often resulting in organ dysfunction. Pulmonary failure in SARS-CoV2-infected hospitalized COVID-19 patients is one such prominent example. Intervention strategies require characterization of the host-pathogen interaction by accurately assessing all of the above-mentioned disease parameters. To study infection in intact mammals, mice are often used as essential genetic models. Due to humane concerns, there is a constant unmet demand to develop studies that reduce the number of mice utilized while generating objective data. Here, we describe an integrated method of evaluating lung inflammation in mice infected with Pseudomonas aeruginosa or murine gammaherpesvirus (MHV)-68. This method conserves animal resources while permitting evaluation of disease mechanisms in both infection settings. Lungs from a single euthanized mouse were used for two purposes-biological assays to determine inflammation and infection load, as well as histology to evaluate tissue architecture. For this concurrent assessment of multiple parameters from a single euthanized mouse, we limit in-situ formalin fixation to the right lung of the cadaver. The unfixed left lung is collected immediately and divided into several segments for biological assays including determination of pathogen titer, assessment of infection-driven cytokine levels and appearance of cell death markers. In situ fixed right lung was then processed for histological determination of tissue injury and confirmation of infection-driven cell death patterns. This method reduces overall animal use and minimizes inter-animal variability that results from sacrificing different animals for different types of assays. The technique can be applied to any lung disease study in mice or other mammals.

Identification of VEGFA-centric temporal hypoxia-responsive dynamic cardiopulmonary network biomarkers.

AIMS: Hypoxia, a pathophysiological condition, is profound in several cardiopulmonary diseases (CPD). Every individual's lethality to a hypoxia state differs in terms of hypoxia exposure time, dosage units and dependent on the individual's genetic makeup. Most of the proposed markers for CPD were generally aim to distinguish disease samples from normal samples. Although, as per the 2018 GOLD guidelines, clinically useful biomarkers for several cardio pulmonary disease patients in stable condition have yet to be identified. We attempt to address these key issues through the identification of Dynamic Network Biomarkers (DNB) to detect hypoxia induced early warning signals of CPD before the catastrophic deterioration. MATERIALS AND METHODS: The human microvascular endothelial tissues microarray datasets (GSE11341) of lung and cardiac expose to hypoxia (1% O2) for 3, 24 and 48 h were retrieved from the public repository. The time dependent differentially expressed genes were subjected to tissue specificity and promoter analysis to filtrate the noise levels in the networks and to dissect the tissue specific hypoxia induced genes. These filtered out genes were used to construct the dynamic segmentation networks. The hypoxia induced dynamic differentially expressed genes were validated in the lung and heart tissues of male rats. These rats were exposed to hypobaric hypoxia (simulated altitude of 25,000 or PO2 - 282 mm of Hg) progressively for 3, 24 and 48 h. KEY FINDINGS: To identify the temporal key genes regulated in hypoxia, we ranked the dominant genes based on their consolidated topological features from tissue specific networks, time dependent networks and dynamic networks. Overall topological ranking described VEGFA as a single node dynamic hub and strongly communicated with tissue specific genes to carry forward their tissue specific information. We named this type of VEGFAcentric dynamic networks as "V-DNBs". As a proof of principle, our methodology helped us to identify the V-DNBs specific for lung and cardiac tissues namely V-DNBL and V-DNBC respectively. SIGNIFICANCE: Our experimental studies identified VEGFA, SLC2A3, ADM and ENO2 as the minimum and sufficient candidates of V-DNBL. The dynamic expression patterns could be readily exploited to capture the pre disease state of hypoxia induced pulmonary vascular remodelling. Whereas in V-DNBC the minimum and sufficient candidates are VEGFA, SCL2A3, ADM, NDRG1, ENO2 and BHLHE40. The time dependent single node expansion indicates V-DNBC could also be the pre disease state pathological hallmark for hypoxia-associated cardiovascular remodelling. The network cross-talk and expression pattern between V-DNBL and V-DNBC are completely distinct. On the other hand, the great clinical advantage of V-DNBs for pre disease predictions, a set of samples during the healthy condition should suffice. Future clinical studies might further shed light on the predictive power of V-DNBs as prognostic and diagnostic biomarkers for CPD.

Segmenting lung lesions of COVID-19 from CT images via pyramid pooling improved Unet.

Segmenting lesion regions of Coronavirus Disease 2019 (COVID-19) from computed tomography (CT) images is a challenge owing to COVID-19 lesions characterized by high variation, low contrast between infection lesions and around normal tissues, and blurred boundaries of infections. Moreover, a shortage of available CT dataset hinders deep learning techniques applying to tackling COVID-19. To address these issues, we propose a deep learning-based approach known as PPM-Unet to segmenting COVID-19 lesions from CT images. Our method improves an Unet by adopting pyramid pooling modules instead of the conventional skip connection and then enhances the representation of the neural network by aiding the global attention mechanism. We first pre-train PPM-Unet on COVID-19 dataset of pseudo labels containing1600 samples producing a coarse model. Then we fine-tune the coarse PPM-Unet on the standard COVID-19 dataset consisting of 100 pairs of samples to achieve a fine PPM-Unet. Qualitative and quantitative results demonstrate that our method can accurately segment COVID-19 infection regions from CT images, and achieve higher performance than other state-of-the-art segmentation models in this study. It offers a promising tool to lay a foundation for quantitatively detecting COVID-19 lesions.

Four-Month Clinical Status of a Cohort of Patients After Hospitalization for COVID-19.

Importance: Little is known about long-term sequelae of COVID-19. Objective: To describe the consequences at 4 months in patients hospitalized for COVID-19. Design, Setting, and Participants: In a prospective uncontrolled cohort study, survivors of COVID-19 who had been hospitalized in a university hospital in France between March 1 and May 29, 2020, underwent a telephone assessment 4 months after discharge, between July 15 and September 18, 2020. Patients with relevant symptoms and all patients hospitalized in an intensive care unit (ICU) were invited for further assessment at an ambulatory care visit. Exposures: Survival of hospitalization for COVID-19. Main Outcomes and Measures: Respiratory, cognitive, and functional symptoms were assessed by telephone with the Q3PC cognitive screening questionnaire and a checklist of symptoms. At the ambulatory care visit, patients underwent pulmonary function tests, lung computed tomographic scan, psychometric and cognitive tests (including the 36-Item Short-Form Health Survey and 20-item Multidimensional Fatigue Inventory), and, for patients who had been hospitalized in the ICU or reported ongoing symptoms, echocardiography. Results: Among 834 eligible patients, 478 were evaluated by telephone (mean age, 61 years [SD, 16 years]; 201 men, 277 women). During the telephone interview, 244 patients (51%) declared at least 1 symptom that did not exist before COVID-19: fatigue in 31%, cognitive symptoms in 21%, and new-onset dyspnea in 16%. There was further evaluation in 177 patients (37%), including 97 of 142 former ICU patients. The median 20-item Multidimensional Fatigue Inventory score (n = 130) was 4.5 (interquartile range, 3.0-5.0) for reduced motivation and 3.7 (interquartile range, 3.0-4.5) for mental fatigue (possible range, 1 [best] to 5 [worst]). The median 36-Item Short-Form Health Survey score (n = 145) was 25 (interquartile range, 25.0-75.0) for the subscale "role limited owing to physical problems" (possible range, 0 [best] to 100 [worst]). Computed tomographic lung-scan abnormalities were found in 108 of 171 patients (63%), mainly subtle ground-glass opacities. Fibrotic lesions were observed in 33 of 171 patients (19%), involving less than 25% of parenchyma in all but 1 patient. Fibrotic lesions were observed in 19 of 49 survivors (39%) with acute respiratory distress syndrome. Among 94 former ICU patients, anxiety, depression, and posttraumatic symptoms were observed in 23%, 18%, and 7%, respectively. The left ventricular ejection fraction was less than 50% in 8 of 83 ICU patients (10%). New-onset chronic kidney disease was observed in 2 ICU patients. Serology was positive in 172 of 177 outpatients (97%). Conclusions and Relevance: Four months after hospitalization for COVID-19, a cohort of patients frequently reported symptoms not previously present, and lung-scan abnormalities were common among those who were tested. These findings are limited by the absence of a control group and of pre-COVID assessments in this cohort. Further research is needed to understand longer-term outcomes and whether these findings reflect associations with the disease.