Biomimetic Nanotechnology for SARS-CoV-2 Treatment.

More than 600 million people worldwide have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in the pandemic of coronavirus disease 2019 (COVID-19). In particular, new waves of COVID-19 caused by emerging SARS-CoV-2 variants pose new health risks to the global population. Nanotechnology has developed excellent solutions to combat the virus pandemic, such as ACE2-based nanodecoys, nanobodies, nanovaccines, and drug nanocarriers. Lessons learned and strategies developed during this battle against SARS-CoV-2 variants may also serve as inspiration for developing nanotechnology-based strategies to combat other global infectious diseases and their variants in the future.

Towards Accurate and Robust Domain Adaptation Under Multiple Noisy Environments.

In many non-stationary environments, machine learning algorithms usually confront the distribution shift scenarios. Previous domain adaptation methods have achieved great success. However, they would lose algorithm robustness in multiple noisy environments where the examples of source domain become corrupted by label noise, feature noise, or open-set noise. In this paper, we report our attempt toward achieving noise-robust domain adaptation. We first give a theoretical analysis and find that different noises have disparate impacts on the expected target risk. To eliminate the effect of source noises, we propose offline curriculum learning minimizing a newly-defined empirical source risk. We suggest a proxy distribution-based margin discrepancy to gradually decrease the noisy distribution distance to reduce the impact of source noises. We propose an energy estimator for assessing the outlier degree of open-set-noise examples to defeat the harmful influence. We also suggest robust parameter learning to mitigate the negative effect further and learn domain-invariant feature representations. Finally, we seamlessly transform these components into an adversarial network that performs efficient joint optimization for them. A series of empirical studies on the benchmark datasets and the COVID-19 screening task show that our algorithm remarkably outperforms the state-of-the-art, with over 10% accuracy improvements in some transfer tasks.

Evaluation and Follow-up of Myopia Prevalence Among School-Aged Children Subsequent to the COVID-19 Home Confinement in Feicheng, China.

Importance: Progression of myopia in a school-aged population due to home confinement (January to May 2021) during the COVID-19 pandemic has been previously reported. A key remaining question was whether the myopia spike in children aged 6 to 8 years persisted. Objective: To investigate the changes in refractive status and prevalence of myopia in school-aged children 1 year after home confinement ended in China. Design, Setting, and Participants: This cross-sectional study with a cohort substudy prospectively evaluated data from school-based photoscreening in Feicheng, China. Children aged 6 to 13 years participated in 8 screenings from 2015 to 2021. Exposures: Noncycloplegic photorefraction was conducted using the Spot Vision photoscreener. Main Outcomes and Measures: The main outcomes were the differences in spherical equivalent refraction (SER) and prevalence of myopia between 2020 (during home confinement) and 2021 (after home confinement). The SER was recorded for each child, and the prevalence of myopia was calculated annually for each age group. Results: A total of 325 443 children participated in the study (51.4% boys, 48.6% girls; age range, 6 to 13 years). Compared with 2020, the mean SER of children in 2021 increased significantly for those aged 6 (0.42 diopters [D]), 7 (0.41 D), and 8 (0.33 D) years. The prevalence of myopia in 2021 was similar to in 2019 for each age group (aged 6 years: 7.9% vs 5.7%; aged 7 years: 13.9% vs 13.6%; aged 8 years: 29.5% vs 26.2%). Both the prevalence of myopia and mean SER for these children returned to their prepandemic levels. Conclusions and Relevance: Compared with 2020, the prevalence of myopia among children aged 6 to 8 years in the 2021 screenings decreased, and the mean SER returned to prepandemic level. The refractive development in children aged 6 to 8 years may be most susceptible to environmental changes. These findings support the premise that age 6 to 8 years is a critical period for myopia development and suggest a need to focus preventive interventions for myopia control on children in this age range.

Peptide-based inhibitors hold great promise as the broad-spectrum agents against coronavirus.

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome (MERS), and the recent SARS-CoV-2 are lethal coronaviruses (CoVs) that have caused dreadful epidemic or pandemic in a large region or globally. Infections of human respiratory systems and other important organs by these pathogenic viruses often results in high rates of morbidity and mortality. Efficient anti-viral drugs are needed. Herein, we firstly take SARS-CoV-2 as an example to present the molecular mechanism of CoV infection cycle, including the receptor binding, viral entry, intracellular replication, virion assembly, and release. Then according to their mode of action, we provide a summary of anti-viral peptides that have been reported in peer-reviewed publications. Even though CoVs can rapidly evolve to gain resistance to the conventional small molecule drugs, peptide-based inhibitors targeting various steps of CoV lifecycle remain a promising approach. Peptides can be continuously modified to improve their antiviral efficacy and spectrum along with the emergence of new viral variants.

Peptide-based inhibitors hold great promise as the broad-spectrum agents against coronavirus

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome (MERS), and the recent SARS-CoV-2 are lethal coronaviruses (CoVs) that have caused dreadful epidemic or pandemic in a large region or globally. Infections of human respiratory systems and other important organs by these pathogenic viruses often results in high rates of morbidity and mortality. Efficient anti-viral drugs are needed. Herein, we firstly take SARS-CoV-2 as an example to present the molecular mechanism of CoV infection cycle, including the receptor binding, viral entry, intracellular replication, virion assembly, and release. Then according to their mode of action, we provide a summary of anti-viral peptides that have been reported in peer-reviewed publications. Even though CoVs can rapidly evolve to gain resistance to the conventional small molecule drugs, peptide-based inhibitors targeting various steps of CoV lifecycle remain a promising approach. Peptides can be continuously modified to improve their antiviral efficacy and spectrum along with the emergence of new viral variants.

Dual Multiscale Mean Teacher Network for Semi-Supervised Infection Segmentation in Chest CT Volume for COVID-19.

Automated detecting lung infections from computed tomography (CT) data plays an important role for combating coronavirus 2019 (COVID-19). However, there are still some challenges for developing AI system: 1) most current COVID-19 infection segmentation methods mainly relied on 2-D CT images, which lack 3-D sequential constraint; 2) existing 3-D CT segmentation methods focus on single-scale representations, which do not achieve the multiple level receptive field sizes on 3-D volume; and 3) the emergent breaking out of COVID-19 makes it hard to annotate sufficient CT volumes for training deep model. To address these issues, we first build a multiple dimensional-attention convolutional neural network (MDA-CNN) to aggregate multiscale information along different dimension of input feature maps and impose supervision on multiple predictions from different convolutional neural networks (CNNs) layers. Second, we assign this MDA-CNN as a basic network into a novel dual multiscale mean teacher network (DM 2 T-Net) for semi-supervised COVID-19 lung infection segmentation on CT volumes by leveraging unlabeled data and exploring the multiscale information. Our DM 2 T-Net encourages multiple predictions at different CNN layers from the student and teacher networks to be consistent for computing a multiscale consistency loss on unlabeled data, which is then added to the supervised loss on the labeled data from multiple predictions of MDA-CNN. Third, we collect two COVID-19 segmentation datasets to evaluate our method. The experimental results show that our network consistently outperforms the compared state-of-the-art methods.

A high-dimensional cytometry atlas of peripheral blood over the human life span.

Age can profoundly affect susceptibility to a broad range of human diseases. Children are more susceptible to some infectious diseases such as diphtheria and pertussis, while in others, such as coronavirus disease 2019 and hepatitis A, they are more protected compared with adults. One explanation is that the composition of the immune system is a major contributing factor to disease susceptibility and severity. While most studies of the human immune system have focused on adults, how the immune system changes after birth remains poorly understood. Here, using high-dimensional spectral flow cytometry and computational methods for data integration, we analyzed more than 50 populations of immune cells in the peripheral blood, generating an immune cell atlas that defines the healthy human immune system from birth up to 75 years of age. We focused our efforts on children under 18 years old, revealing major changes in immune cell populations after birth and in children of schooling age. Specifically, CD4⁺ T effector memory cells, Vδ2⁺ gamma delta (γδ)T cells, memory B cells, plasmablasts, CD11c⁺ B cells and CD16⁺ CD56^bright natural killer (NK) cells peaked in children aged 5-9 years old, whereas frequencies of T helper 1, T helper 17, dendritic cells and CD16⁺ CD57⁺ CD56^dim NK cells were highest in older children (10-18 years old). The frequency of mucosal-associated invariant T cells was low in the first several years of life and highest in adults between 19 and 30 years old. Late adulthood was associated with fewer mucosal-associated invariant T cells and Vδ2⁺ γδ T cells but with increased frequencies of memory subsets of B cells, CD4⁺ and CD8⁺ T cells and CD57⁺ NK cells. This human immune cell atlas provides a critical resource to understand changes to the immune system during life and provides a reference for investigating the immune system in the context of human disease. This work may also help guide future therapies that target specific populations of immune cells to protect at-risk populations.

SC2Net: A Novel Segmentation-Based Classification Network for Detection of COVID-19 in Chest X-Ray Images.

The pandemic of COVID-19 has become a global crisis in public health, which has led to a massive number of deaths and severe economic degradation. To suppress the spread of COVID-19, accurate diagnosis at an early stage is crucial. As the popularly used real-time reverse transcriptase polymerase chain reaction (RT-PCR) swab test can be lengthy and inaccurate, chest screening with radiography imaging is still preferred. However, due to limited image data and the difficulty of the early-stage diagnosis, existing models suffer from ineffective feature extraction and poor network convergence and optimisation. To tackle these issues, a segmentation-based COVID-19 classification network, namely SC2Net, is proposed for effective detection of the COVID-19 from chest x-ray (CXR) images. The SC2Net consists of two subnets: a COVID-19 lung segmentation network (CLSeg), and a spatial attention network (SANet). In order to supress the interference from the background, the CLSeg is first applied to segment the lung region from the CXR. The segmented lung region is then fed to the SANet for classification and diagnosis of the COVID-19. As a shallow yet effective classifier, SANet takes the ResNet-18 as the feature extractor and enhances high-level feature via the proposed spatial attention module. For performance evaluation, the COVIDGR 1.0 dataset is used, which is a high-quality dataset with various severity levels of the COVID-19. Experimental results have shown that, our SC2Net has an average accuracy of 84.23% and an average F1 score of 81.31% in detection of COVID-19, outperforming several state-of-the-art approaches.

Relationship between meteorological factors, air pollutants and hand, foot and mouth disease from 2014 to 2020.

BACKGROUND: Meteorological factors and air pollutants have been reported to be associated with hand, foot, and mouth disease (HFMD) epidemics before the introduction of vaccine. However, there is limited evidence for studies with long-term dimensions. METHODS: We collected the daily HFMD counts, weather and air pollution data from 2014 to 2020 in Chengdu. Distributed lag non-linear models (DLNM) were used to assess the associations of meteorological factors and air pollutants on HFMD cases. RESULTS: From 2014-2020, high relative humidity and precipitation and extremely high and low levels of PM10, O3, SO2 and CO increased the risk of HFMD. In pre-vaccination period, extreme high and low temperatures, PM10 and NO2, low precipitation and high concentrations of PM2.5 and O3 significantly increase the risk of HFMD; In post-vaccination period, high relative humidity and low level of CO can significantly increase the incidence of HFMD; During the period of COVID-19, only low temperature will significantly increase the risk of HFMD; Low concentration of air pollutants has the greatest impact on the 6-14 age group, while the high concentration of air pollutants has the greatest impact on the 0-1 age group. CONCLUSIONS: Our study suggest that high relative humidity and precipitation and extremely high and low levels of PM10, O3, SO2 and CO increased the risk of HFMD from 2014 to 2020. The results of this study provide a reference for local authorities to formulate intervention measures and establish an environment-based disease early warning system.

Generation and Effect Testing of a SARS-CoV-2 RBD-Targeted Polyclonal Therapeutic Antibody Based on a 2-D Airway Organoid Screening System.

Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The US FDA has approved several therapeutics and vaccines worldwide through the emergency use authorization in response to the rapid spread of COVID-19. Nevertheless, the efficacies of these treatments are being challenged by viral escape mutations. There is an urgent need to develop effective treatments protecting against SARS-CoV-2 infection and to establish a stable effect-screening model to test potential drugs. Polyclonal antibodies (pAbs) have an intrinsic advantage in such developments because they can target rapidly mutating viral strains as a result of the complexity of their binding epitopes. In this study, we generated anti-receptor-binding domain (anti-RBD) pAbs from rabbit serum and tested their safety and efficacy in response to SARS-CoV-2 infection both in vivo and ex vivo. Primary human bronchial epithelial two-dimensional (2-D) organoids were cultured and differentiated to a mature morphology and subsequently employed for SARS-CoV-2 infection and drug screening. The pAbs protected the airway organoids from viral infection and tissue damage. Potential side effects were tested in mouse models for both inhalation and vein injection. The pAbs displayed effective viral neutralization effects without significant side effects. Thus, the use of animal immune serum-derived pAbs might be a potential therapy for protection against SARS-CoV-2 infection, with the strategy developed to produce these pAbs providing new insight into the treatment of respiratory tract infections, especially for infections with viruses undergoing rapid mutation.

Progression of Myopia in School-Aged Children After COVID-19 Home Confinement.

Importance: Time spent in outdoor activities has decreased owing to home confinement for the coronavirus disease 2019 (COVID-19) pandemic. Concerns have been raised about whether home confinement may have worsened the burden of myopia owing to substantially decreased time spent outdoors and increased screen time at home. Objective: To investigate the refractive changes and prevalence of myopia in school-aged children during the COVID-19 home confinement. Design, Setting, and Participants: A prospective cross-sectional study using school-based photoscreenings in 123 535 children aged 6 to 13 years from 10 elementary schools in Feicheng, China, was conducted. The study was performed during 6 consecutive years (2015-2020). Data were analyzed in July 2020. Exposures: Noncycloplegic photorefraction was examined using a photoscreener device. Main Outcomes and Measures: The spherical equivalent refraction was recorded for each child and the prevalence of myopia for each age group during each year was calculated. The mean spherical equivalent refraction and prevalence of myopia were compared between 2020 (after home confinement) and the previous 5 years for each age group. Results: Of the 123 535 children included in the study, 64 335 (52.1%) were boys. A total of 194 904 test results (389 808 eyes) were included in the analysis. A substantial myopic shift (approximately -0.3 diopters [D]) was found in the 2020 school-based photoscreenings compared with previous years (2015-2019) for younger children aged 6 (-0.32 D), 7 (-0.28 D), and 8 (-0.29 D) years. The prevalence of myopia in the 2020 photoscreenings was higher than the highest prevalence of myopia within 2015-2019 for children aged 6 (21.5% vs 5.7%), 7 (26.2% vs 16.2%), and 8 (37.2% vs 27.7%) years. The differences in spherical equivalent refraction and the prevalence of myopia between 2020 and previous years were minimal in children aged 9 to 13 years. Conclusions and Relevance: Home confinement during the COVID-19 pandemic appeared to be associated with a significant myopic shift for children aged 6 to 8 years according to 2020 school-based photoscreenings. However, numerous limitations warrant caution in the interpretation of these associations, including use of noncycloplegic refractions and lack of orthokeratology history or ocular biometry data. Younger children's refractive status may be more sensitive to environmental changes than older ages, given the younger children are in a critical period for the development of myopia.

Optimization of imaging parameters in chest CT for COVID-19 patients: an experimental phantom study.

BACKGROUND: With the global outbreak of coronavirus disease 2019 (COVID-19), chest computed tomography (CT) is vital for diagnosis and follow-up. The increasing contribution of CT to the population-collected dose has become a topic of interest. Radiation dose optimization for chest CT of COVID-19 patients is of importance in clinical practice. The present study aimed to investigate the factors affecting the detection of ground-glass nodules and exudative lesions in chest CT among COVID-19 patients and to find an appropriate combination of imaging parameters that optimize detection while effectively reducing the radiation dose. METHODS: The anthropomorphic thorax phantom, with 9 spherical nodules of different diameters and CT values of -800, -630, and 100 HU, was used to simulate the lesions of COVID-19 patients. Four custom-simulated lesions of porcine fat and ethanol were also scanned at 3 tube potentials (120, 100, and 80 kV) and corresponding milliampere-seconds (mAs) (ranging from 10 to 100). Separate scans were performed at pitches of 0.6, 0.8, 1.0, 1.15, and 1.49, and at collimations of 10, 20, 40, and 80 mm at 80 kV and 100 mAs. CT values and standard deviations of simulated nodules and lesions were measured, and radiation dose quantity (volume CT dose index; CTDIvol) was collected. Contrast-to-noise ratio (CNR) and figure of merit (FOM) were calculated. All images were subjectively evaluated by 2 radiologists to determine whether the nodules were detectable and if the overall image quality met diagnostic requirements. RESULTS: All simulated lesions, except -800 HU nodules, were detected at all scanning conditions. At a fixed voltage of 120 or 100 kV, with increasing mAs, image noise tended to decrease, and the CNR tended to increase (F=9.694 and P=0.033 for 120 kV; F=9.028 and P=0.034 for 100 kV). The FOM trend was the same as that of CNR (F=2.768 and P=0.174 for 120 kV; F=1.915 and P=0.255 for 100 kV). At 80 kV, the CNRs and FOMs had no significant change with increasing mAs (F=4.522 and P=0.114 for CNRs; F=1.212 and P=0.351 for FOMs). For the 4 nodules of -800 and -630 HU, CNRs had no statistical differences at each of the 5 pitches (F=0.673, P=0.476). The CNRs and FOMs at each of the 4 collimations had no statistical differences (F=2.509 and P=0.125 for CNRs; F=1.485 and P=0.309 for FOMs) for each nodule. CNRs and subjective evaluation scores increased with increasing parameter values for each imaging iteration. The CNRs of 4 -800 HU nodules in the qualified images at the thresholds of scanning parameters of 120 kV/20 mAs, 100 kV/40 mAs, and 80 kV/80 mAs, had statistical differences (P=0.038), but the FOMs had no statistical differences (P=0.085). Under the 3 threshold conditions, the CNRs and FOMs of the 4 nodules were highest at 100 kV and 40 mAs (1.6 mGy CTDIvol). CONCLUSIONS: For chest CT among COVID-19 patients, it is recommended that 100 kV/40 mAs is used for average patients; the radiation dose can be reduced to 1.6 mGy with qualified images to detect ground-glass nodules and exudation lesions.

Current role of imaging in COVID-19 infection with recent recommendations of point of care ultrasound in the contagion: a narrative review.

Radiological studies have an important role in the diagnosis and follow up of many infectious diseases. With current pandemic of Coronavirus disease 2019 (COVID-19) though the molecular analysis with reverse transcriptase polymerase chain reaction (RT-PCR) remains the cornerstone of diagnosis, the critical role of chest imaging including CT scan and baseline X-ray became apparent early in the course due to concern for less than optimal sensitivity of PCR testing. Delay in molecular diagnosis due to a shortage of testing kits and laboratory personnel also makes imaging an important modality in early diagnosis for appropriate triage and isolation decisions. CT scan technology is widely available in developed parts of the world but in developing countries, CT scanner is not widely available especially in rural settings. CT imaging usually requires patient movement to the radiology department and the scanner is not easy to disinfect. Point of care ultrasound (POCUS) has been used for many years in the assessment of critically ill patients in emergency departments and intensive care units. It is rapidly gaining popularity across many specialties and part of many general medicine training programs across the United States. It can be learned rapidly and with experienced hands, POCUS can help identify disease patterns in the lung parenchyma, and during the current pandemic has been gaining special attention. In this article, we review the most prominent imaging findings on chest X-ray and CT scan in patients with COVID-19. We also focus on the background and evolution of POCUS with studies showing the promising role of this diagnostic modality in COVID-19 infection. In addition, we describe step by step guidance on the use and disinfection of the portable ultrasound machine.

MARCH8 Inhibits Ebola Virus Glycoprotein, Human Immunodeficiency Virus Type 1 Envelope Glycoprotein, and Avian Influenza Virus H5N1 Hemagglutinin Maturation.

Membrane-associated RING-CH-type 8 (MARCH8) strongly blocks human immunodeficiency virus type 1 (HIV-1) envelope glycoprotein (Env) incorporation into virions by downregulating its cell surface expression, but the mechanism is still unclear. We now report that MARCH8 also blocks the Ebola virus (EBOV) glycoprotein (GP) incorporation via surface downregulation. To understand how these viral fusion proteins are downregulated, we investigated the effects of MARCH8 on EBOV GP maturation and externalization via the conventional secretion pathway. MARCH8 interacted with EBOV GP and furin when detected by immunoprecipitation and retained the GP/furin complex in the Golgi when their location was tracked by a bimolecular fluorescence complementation (BiFC) assay. MARCH8 did not reduce the GP expression or affect the GP modification by high-mannose N-glycans in the endoplasmic reticulum (ER), but it inhibited the formation of complex N-glycans on the GP in the Golgi. Additionally, the GP O-glycosylation and furin-mediated proteolytic cleavage were also inhibited. Moreover, we identified a novel furin cleavage site on EBOV GP and found that only those fully glycosylated GPs were processed by furin and incorporated into virions. Furthermore, the GP shedding and secretion were all blocked by MARCH8. MARCH8 also blocked the furin-mediated cleavage of HIV-1 Env (gp160) and the highly pathogenic avian influenza virus H5N1 hemagglutinin (HA). We conclude that MARCH8 has a very broad antiviral activity by prohibiting different viral fusion proteins from glycosylation and proteolytic cleavage in the Golgi, which inhibits their transport from the Golgi to the plasma membrane and incorporation into virions.IMPORTANCE Enveloped viruses express three classes of fusion proteins that are required for their entry into host cells via mediating virus and cell membrane fusion. Class I fusion proteins are produced from influenza viruses, retroviruses, Ebola viruses, and coronaviruses. They are first synthesized as a type I transmembrane polypeptide precursor that is subsequently glycosylated and oligomerized. Most of these precursors are cleaved en route to the plasma membrane by a cellular protease furin in the late secretory pathway, generating the trimeric N-terminal receptor-binding and C-terminal fusion subunits. Here, we show that a cellular protein, MARCH8, specifically inhibits the furin-mediated cleavage of EBOV GP, HIV-1 Env, and H5N1 HA. Further analyses uncovered that MARCH8 blocked the EBOV GP glycosylation in the Golgi and inhibited its transport from the Golgi to the plasma membrane. Thus, MARCH8 has a very broad antiviral activity by specifically inactivating different viral fusion proteins.

Application of lung ultrasonography in critically ill patients with COVID-19.

PURPOSE: Lung ultrasonography (LU) is useful to assess lung lesions and variations at bedside. To investigate the results of LU in severe and critical patients with coronavirus disease 2019 (COVID-19), we performed a single-institution study to evaluate the related lung lesions and variations, and prophylactic strategies, in a large referral and treatment center. METHODS: We included 91 adult patients with severe and critical COVID-19, namely 62 males and 29 females, with an average age of 59 ± 11 years, who underwent LU. We collected the following patient information: sex, age, days in hospital, and days in ICU. In the ultrasound examinations, we recorded the presence of discrete B lines, confluent B lines, consolidation, pleural thickening, pleural effusion, and pneumothorax (PTX). RESULTS: Among the 91 severe and critical patients, 59 cases had scattered B lines, 56 cases had confluent B lines, 58 cases had alveolar-interstitial syndrome (AIS), 48 cases had lung consolidation, six cases had pleural thickening, 39 cases had pleural effusion (average depth of the pleural effusion: 1.0 ± 1.5 cm), and 20 patients developed PTX. In the Cox multivariate analysis, there were significant differences in age, hospitalization days, ICU days, and lung consolidation. CONCLUSION: Lung ultrasonography performed at the bedside can detect lung diseases, such as B lines, PTX, pulmonary edema, lung consolidation, pleural effusion, and variations of these findings. Our findings support the use of LU and measurements for estimating factors, and monitoring response to therapy in severe and critical COVID-19 patients.

Applicability of bedside ultrasonography for the diagnosis of deep venous thrombosis in patients with COVID-19 and treatment with low molecular weight heparin.

PURPOSE: The aim of this study was to evaluate the applicability of bedside ultrasonography for the diagnosis of deep venous thrombosis (DVT) in patients infected with corona virus disease 2019 (COVID-19) with and without treatment with low molecular weight heparin (LMWH). METHODS: We retrospectively analyzed the records of deceased and surviving patients in whom ultrasonography detected or not a DVT, and in whom LMWH was or not prescribed. RESULTS: The incidence of DVT is higher in the deceased (33/35) than in the surviving (22/46) patients. LMWH was administered in a larger proportion of surviving (18/22) than of deceased (18/33) patients. D-dimer concentrations decreased in patients who received LMWH in both groups. CONCLUSIONS: There was a high incidence of DVT in patients who succumbed to COVID-19. Bedside ultrasonography can detect the presence of DVT as early as possible and help assessing the risk of venous thromboembolism, allowing early and reasonable use of LMWH.

Distribution of ACE2, CD147, CD26, and other SARS-CoV-2 associated molecules in tissues and immune cells in health and in asthma, COPD, obesity, hypertension, and COVID-19 risk factors.

BACKGROUND: Morbidity and mortality from COVID-19 caused by novel coronavirus SARS-CoV-2 is accelerating worldwide, and novel clinical presentations of COVID-19 are often reported. The range of human cells and tissues targeted by SARS-CoV-2, its potential receptors and associated regulating factors are still largely unknown. The aim of our study was to analyze the expression of known and potential SARS-CoV-2 receptors and related molecules in the extensive collection of primary human cells and tissues from healthy subjects of different age and from patients with risk factors and known comorbidities of COVID-19. METHODS: We performed RNA sequencing and explored available RNA-Seq databases to study gene expression and co-expression of ACE2, CD147 (BSG), and CD26 (DPP4) and their direct and indirect molecular partners in primary human bronchial epithelial cells, bronchial and skin biopsies, bronchoalveolar lavage fluid, whole blood, peripheral blood mononuclear cells (PBMCs), monocytes, neutrophils, DCs, NK cells, ILC1, ILC2, ILC3, CD4+ and CD8+ T cells, B cells, and plasmablasts. We analyzed the material from healthy children and adults, and from adults in relation to their disease or COVID-19 risk factor status. RESULTS: ACE2 and TMPRSS2 were coexpressed at the epithelial sites of the lung and skin, whereas CD147 (BSG), cyclophilins (PPIA andPPIB), CD26 (DPP4), and related molecules were expressed in both epithelium and in immune cells. We also observed a distinct age-related expression profile of these genes in the PBMCs and T cells from healthy children and adults. Asthma, COPD, hypertension, smoking, obesity, and male gender status generally led to the higher expression of ACE2- and CD147-related genes in the bronchial biopsy, BAL, or blood. Additionally, CD147-related genes correlated positively with age and BMI. Interestingly, we also observed higher expression of CD147-related genes in the lesional skin of patients with atopic dermatitis. CONCLUSIONS: Our data suggest different receptor repertoire potentially involved in the SARS-CoV-2 infection at the epithelial barriers and in the immune cells. Altered expression of these receptors related to age, gender, obesity and smoking, as well as with the disease status, might contribute to COVID-19 morbidity and severity patterns.