Comparison between discarded facemask and common plastic waste on microbial colonization and physiochemical properties during aging in seawater.

Facemasks are indispensable for preventing the spread of COVID-19. However, improper disposal of discarded facemasks has led to their contamination in the marine environment. To understand the environmental risk of this emerging plastic pollution, it's important to clarify the features that distinguish discarded facemasks from common plastic waste during aging. This study compared the microbial colonization, degradation-related enzymes, and physicochemical properties among surgical masks, polystyrene cups, polycarbonate bottles, and polyethylene terephthalate bottles in their aging processes in natural seawater. Compared to the other plastic wastes, surgical masks were colonized by the most diverse microorganisms, reaching 1521 unique prokaryotic OTUs after 21-day exposure in seawater. Moreover, the activity of eukaryotic enzymes associated with plastic degradation was 80-fold higher than that in seawater, indicating that the colonized eukaryotes would be the major microorganisms degrading the surgical masks. Meanwhile, the nano-sized defects (depth between 8 and 61 nm) would evolve into cracks of bigger sizes and result in the breakage of the microfibers and releasing microplastics into the ocean. Overall, our study demonstrated a distinctive plastisphere occurred in surgical masks from both microbial and physiochemical aspects. This work provides new insights for assessing the potential risk of plastic pollution caused by the COVID-19 pandemic.

COVID-19-associated monocytic encephalitis (CAME): histological and proteomic evidence from autopsy.

Severe neurological symptoms are associated with Coronavirus disease 2019 (COVID-19). However, the morphologic features, pathological nature and their potential mechanisms in patient brains have not been revealed despite evidence of neurotropic infection. In this study, neuropathological damages and infiltrating inflammatory cells were quantitatively evaluated by immunohistochemical staining, ultrastructural examination under electron microscopy, and an image threshold method, in postmortem brains from nine critically ill COVID-19 patients and nine age-matched cadavers of healthy individuals. Differentially expressed proteins were identified by quantitative proteomic assays. Histopathological findings included neurophagocytosis, microglia nodules, satellite phenomena, extensive edema, focal hemorrhage, and infarction, as well as infiltrating mononuclear cells. Immunostaining of COVID-19 brains revealed extensive activation of both microglia and astrocytes, severe damage of the blood-brain barrier (BBB) and various degrees of perivascular infiltration by predominantly CD14+/CD16+/CD141+/CCR7+/CD11c+ monocytes and occasionally CD4+/CD8+ T lymphocytes. Quantitative proteomic assays combined with bioinformatics analysis identified upregulated proteins predominantly involved in immune responses, autophagy and cellular metabolism in COVID-19 patient brains compared with control brains. Proteins involved in brain development, neuroprotection, and extracellular matrix proteins of the basement membrane were downregulated, potentially caused by the activation of transforming growth factor ß receptor and vascular endothelial growth factor signaling pathways. Thus, our results define histopathological and molecular profiles of COVID-19-associated monocytic encephalitis (CAME) and suggest potential therapeutic targets.

Eukaryotic community succession on discarded face masks in the marine environment.

Wearing facemasks remains an essential strategy for combating the COVID-19 pandemic. However, used masks are becoming plastic wastes that are widespread in the oceans, which is raising concerns about the potential impacts of these novel plastic niches on marine organisms. To delve into this issue, we exposed surgical masks to coastal waters for 30 days. Valuable information was recorded weekly in regard to the succession of the eukaryotic community inhabiting the masks via high-throughput 18S rRNA gene sequencing. Generally, the community on masks was significantly distinct from that in the surrounding seawater. With 1150 different eukaryotic taxa identified, the diversity of the vigorous colonizers of masks peaked at the beginning and decreased over time. A hallmark of initial colonization was the aggregation of diatoms, which formed biofilms on masks, followed by dinoflagellates that acted as a turning point for subsequent development of calcified species and other predators. This study provides insight into the eukaryotic community dynamics on discarded masks in the marine environment and highlights that the potential mask-mediated harmful species clustering may threaten the marine ecosystem.

Weathering and degradation of polylactic acid masks in a simulated environment in the context of the COVID-19 pandemic and their effects on the growth of winter grazing ryegrass.

The COVID-19 pandemic has led to explosive growth in the production and consumption of disposable medical masks, which has caused new global environmental problems due to the improper disposal of these masks and lack of effective mask recycling methods. To reduce the environmental load caused by the inability of synthetic plastics to degrade, polylactic acid (PLA) masks, as a biodegradable environmentally friendly plastic, may become a solution. This study simulated the actual degradation process of new PLA masks in different environments by soaking them in various solutions for 4 weeks and explored the influence of the treated PLA fabric fibers on the growth of winter ryegrass. The results show that the weathering degradation of PLA fibers in water mainly occurs through the hydrolysis of ester bonds, and weathering leads to cheese-like and gully-like erosion on the surface of the PLA fiber fabric layer and finally to fiber fracture and the release of microplastics (MPs). The average number of MPs released within 4 weeks is 149.5 items/piece, the particle size is 20-500 µm (44%), and 63.57% of the MPs are transparent fibers. The outer, middle, and inner layers of weathered PLA masks tend to be hydrophilic and have lower mechanical strength. PLA fibers after different treatment methods affect the growth of winter ryegrass. PLA masks are undoubtedly a greener choice than ordinary commercial masks, but in order to confirm this, the entire degradation process, the final products, and the impact on the environment need to be further studied. In the future, masks may be developed to be made from more environmentally friendly biodegradable materials that can have good protecting effects and also solve the problem of end-of-life recycling. A SYNOPSIS: Simulation of the actual degradation process of PLA masks and exploration of the influence of mask degradation on the growth of winter ryegrass.

Clinical evaluation and application of detection of IgM and IgG antibodies against SARS-CoV-2 using a colloidal gold immunochromatography assay

The pandemic of the novel coronavirus (SARS-CoV-2) infection has seriously threated global public health, a rapid and easy operated method for coronavirus disease (COVID-19) diagnosis is needed. To evaluate the clinical application efficacy of the colloidal gold rapid test kit for detection of the IgM/IgG antibodies to SARS-CoV-2, a total of 304 clinical diagnosed case, 138 health donor (of which 114 showed SARS-CoV-2) viral RNA negative and 64 other fever patients with respiratory symptoms were selected for the study and the plasma or serum samples were tested for both IgM and IgG with the kit. The comparison of the detection coincidence of the samples from whole blood and plasma or serum were also performed;Furthermore, the time distribution of SARS-CoV-2 viral RNA and IgM/IgG antibodies detections were analyzed. The results showed that, of the 304 clinical diagnosed cases, 105 cases were positive for viral RNA detection, among which the detection sensitivity of IgM and IgG antibodies to SARS-CoV-2 by colloidal gold rapid assay was 76.2% (80/105) and 86.6% (91/105), respectively, and the overall coincidence rate of IgM/IgG antibody was 96.1% (101/105);and 73 cases were negative for both nucleic acid and antibody detection. Of the remaining 126 clinical diagnosed cases, the positive rate of IgM and IgG was 69.2% (87/126) and 98.3% (125/126), respectively, and the overall coincidence rate of IgM/IgG antibody was 100% (126/126). In detections for healthy and other fever patients, the specificity of IgM and IgG was 99% (200/202) and 98% (198/202), respectively, and the total coincidence rate of antibody detection results of homologous whole blood and plasma samples was 99%, indicating a high degree of consistency. In this study, the detection assay of SARS-CoV-2 antibodies using colloidal gold method showed satisfactory detection effect, and it could be used for clinical auxiliary diagnosis and epidemiological investigation, which could be applied in a wide range of scenarios and play a valuable role in the prevention and control of SARS-CoV-2 pandemic.

Early prediction of noninvasive ventilation failure after extubation: development and validation of a machine-learning model.

BACKGROUND: Noninvasive ventilation (NIV) has been widely used in critically ill patients after extubation. However, NIV failure is associated with poor outcomes. This study aimed to determine early predictors of NIV failure and to construct an accurate machine-learning model to identify patients at risks of NIV failure after extubation in intensive care units (ICUs). METHODS: Patients who underwent NIV after extubation in the eICU Collaborative Research Database (eICU-CRD) were included. NIV failure was defined as need for invasive ventilatory support (reintubation or tracheotomy) or death after NIV initiation. A total of 93 clinical and laboratory variables were assessed, and the recursive feature elimination algorithm was used to select key features. Hyperparameter optimization was conducted with an automated machine-learning toolkit called Neural Network Intelligence. A machine-learning model called Categorical Boosting (CatBoost) was developed and compared with nine other models. The model was then prospectively validated among patients enrolled in the Cardiac Surgical ICU of Zhongshan Hospital, Fudan University. RESULTS: Of 929 patients included in the eICU-CRD cohort, 248 (26.7%) had NIV failure. The time from extubation to NIV, age, Glasgow Coma Scale (GCS) score, heart rate, respiratory rate, mean blood pressure (MBP), saturation of pulse oxygen (SpO2), temperature, glucose, pH, pressure of oxygen in blood (PaO2), urine output, input volume, ventilation duration, and mean airway pressure were selected. After hyperparameter optimization, our model showed the greatest accuracy in predicting NIV failure (AUROC: 0.872 [95% CI 0.82-0.92]) among all predictive methods in an internal validation. In the prospective validation cohort, our model was also superior (AUROC: 0.846 [95% CI 0.80-0.89]). The sensitivity and specificity in the prediction group is 89% and 75%, while in the validation group they are 90% and 70%. MV duration and respiratory rate were the most important features. Additionally, we developed a web-based tool to help clinicians use our model. CONCLUSIONS: This study developed and prospectively validated the CatBoost model, which can be used to identify patients who are at risk of NIV failure. Thus, those patients might benefit from early triage and more intensive monitoring. TRIAL REGISTRATION: NCT03704324. Registered 1 September 2018, https://register. CLINICALTRIALS: gov .

Proactive Coping and Mental Health Among Airline Pilots During China's Regular Prevention and Control of COVID-19: The Role of Perceived Stress and Social Support.

Mental health has always been a prominent public health concern, and it has become more important in the wake of the COVID-19 pandemic. The mental health of airline pilots plays a significant role in their occupational health and overall performance. It is also vital for ensuring the safe operation of aircrafts. Therefore, it is crucial to identify the factors that may improve the mental health of pilots. This study investigates the relationship between proactive coping, perceived stress, social support, and mental health among airline pilots during China's regular prevention and control of COVID-19. Using a sample consisting of 285 Chinese commercial airline pilots, we tested a moderated mediation model to explore whether, how, and when proactive coping affects the mental health of pilots. The results show that proactive coping has a direct and positive effect on pilots' mental health, as well as an indirect effect on mental health through its influence on perceived stress. Social support was found to weaken the relationship between perceived stress and mental health. It also weakened the indirect relationship between proactive coping and mental health through perceived stress. These findings advance our understanding of the underlying mechanisms that affect the mental health of pilots. It also provides empirical evidence for effective mental health interventions for airline pilots during regular prevention and control of COVID-19.

Spatial region-resolved proteome map reveals mechanism of COVID-19-associated heart injury.

Direct myocardial and vascular injuries due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-driven inflammation is the leading cause of acute cardiac injury associated with coronavirus disease 2019 (COVID-19). However, in-depth knowledge of the injury characteristics of the heart affected by inflammation is lacking. In this study, using a quantitative spatial proteomics strategy that combines comparative anatomy, laser-capture microdissection, and histological examination, we establish a region-resolved proteome map of the myocardia and microvessels with obvious inflammatory cells from hearts of patients with COVID-19. A series of molecular dysfunctions of myocardia and microvessels is observed in different cardiac regions. The myocardia and microvessels of the left atrial are the most susceptible to virus infection and inflammatory storm, suggesting more attention should be paid to the lesion and treatment of these two parts. These results can guide in improving clinical treatments for cardiovascular diseases associated with COVID-19.

Fate of face masks after being discarded into seawater: Aging and microbial colonization.

Billions of discarded masks have entered the oceans since the outbreak of the COVID-19 pandemic. Current reports mostly discuss the potential of masks as plastic pollution, but there has been no study on the fate of this emerging plastic waste in the marine environment. Therefore, we exposed masks in natural seawater and evaluated their aging and effects on the microbial community using a combination of physicochemical and biological techniques. After 30-day exposure in natural seawater, the masks suffered from significant aging. Microbial colonizers such as Rhodobacteraceae Flavobacteriaceae, Vibrionaceae and fouling organisms like calcareous tubeworms Hydroides elegans were massively present on the masks. The roughness and modulus of the mask fiber increased 3 and 5 times, respectively, and the molecular weight decreased 7%. The growth of biofouling organisms caused the masks negatively buoyant after 14-30 days. Our study sheds some light on the fate of discarded masks in a coastal area and provides fundamental data to manage this important plastic waste during COVID-19 pandemic.

Clinical Applicable AI System Based on Deep Learning Algorithm for Differentiation of Pulmonary Infectious Disease.

Objective: To assess the performance of a novel deep learning (DL)-based artificial intelligence (AI) system in classifying computed tomography (CT) scans of pneumonia patients into different groups, as well as to present an effective clinically relevant machine learning (ML) system based on medical image identification and clinical feature interpretation to assist radiologists in triage and diagnosis. Methods: The 3,463 CT images of pneumonia used in this multi-center retrospective study were divided into four categories: bacterial pneumonia (n = 507), fungal pneumonia (n = 126), common viral pneumonia (n = 777), and COVID-19 (n = 2,053). We used DL methods based on images to distinguish pulmonary infections. A machine learning (ML) model for risk interpretation was developed using key imaging (learned from the DL methods) and clinical features. The algorithms were evaluated using the areas under the receiver operating characteristic curves (AUCs). Results: The median AUC of DL models for differentiating pulmonary infection was 99.5% (COVID-19), 98.6% (viral pneumonia), 98.4% (bacterial pneumonia), 99.1% (fungal pneumonia), respectively. By combining chest CT results and clinical symptoms, the ML model performed well, with an AUC of 99.7% for SARS-CoV-2, 99.4% for common virus, 98.9% for bacteria, and 99.6% for fungus. Regarding clinical features interpreting, the model revealed distinctive CT characteristics associated with specific pneumonia: in COVID-19, ground-glass opacity (GGO) [92.5%; odds ratio (OR), 1.76; 95% confidence interval (CI): 1.71-1.86]; larger lesions in the right upper lung (75.0%; OR, 1.12; 95% CI: 1.03-1.25) with viral pneumonia; older age (57.0 years ± 14.2, OR, 1.84; 95% CI: 1.73-1.99) with bacterial pneumonia; and consolidation (95.8%, OR, 1.29; 95% CI: 1.05-1.40) with fungal pneumonia. Conclusion: For classifying common types of pneumonia and assessing the influential factors for triage, our AI system has shown promising results. Our ultimate goal is to assist clinicians in making quick and accurate diagnoses, resulting in the potential for early therapeutic intervention.

Establishment of Human Pluripotent Stem Cell-Derived Skin Organoids Enabled Pathophysiological Model of SARS-CoV-2 Infection.

Coronavirus disease 2019 (COVID-19) patients with impact on skin and hair loss are reported. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is detected in the skin of some patients; however, the detailed pathological features of skin tissues from patients infected with SARS-CoV-2 at a molecular level are limited. Especially, the ability of SARS-CoV-2 to infect skin cells and impact their function is not well understood. A proteome map of COVID-19 skin is established here and the susceptibility of human-induced pluripotent stem cell (hiPSC)-derived skin organoids with hair follicles and nervous system is investigated, to SARS-CoV-2 infection. It is shown that KRT17+ hair follicles can be infected by SARS-CoV-2 and are associated with the impaired development of hair follicles and epidermis. Different types of nervous system cells are also found to be infected, which can lead to neuron death. Findings from the present work provide evidence for the association between COVID-19 and hair loss. hiPSC-derived skin organoids are also presented as an experimental model which can be used to investigate the susceptibility of skin cells to SARS-CoV-2 infection and can help identify various pathological mechanisms and drug screening strategies.

Syndecan-1, an indicator of endothelial glycocalyx degradation, predicts outcome of patients admitted to an ICU with COVID-19.

BACKGROUND: We investigated the feasibility of two biomarkers of endothelial damage (Syndecan-1 and thrombomodulin) in coronavirus disease 2019 (COVID-19), and their association with inflammation, coagulopathy, and mortality. METHODS: The records of 49 COVID-19 patients who were admitted to an intensive care unit (ICU) in Wuhan, China between February and April 2020 were examined. Demographic, clinical, and laboratory data, and outcomes were compared between survivors and non-survivors COVID-19 patients, and between patients with high and low serum Syndecan-1 levels. The dynamics of serum Syndecan-1 levels were also analyzed. RESULTS: The levels of Syndecan-1 were significantly higher in non-survivor group compared with survivor group (median 1031.4 versus 504.0 ng/mL, P = 0.002), and the levels of thrombomodulin were not significantly different between these two groups (median 4534.0 versus 3780.0 ng/mL, P = 0.070). Kaplan-Meier survival analysis showed that the group with high Syndecan-1 levels had worse overall survival (log-rank test: P = 0.023). Patients with high Syndecan-1 levels also had significantly higher levels of thrombomodulin, interleukin-6, and tumor necrosis factor-α. Data on the dynamics of Syndecan-1 levels indicated much greater variations in non-survivors than survivors. CONCLUSIONS: COVID-19 patients with high levels of Syndecan-1 develop more serious endothelial damage and inflammatory reactions, and have increased mortality. Syndecan-1 has potential for use as a marker for progression or severity of COVID-19. Protecting the glycocalyx from destruction is a potential treatment for COVID-19.

Antibody-dependent cellular cytotoxicity response to SARS-CoV-2 in COVID-19 patients.

Antibody-dependent cellular cytotoxicity (ADCC) responses to viral infection are a form of antibody regulated immune responses mediated through the Fc fragment. Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered ADCC responses contributes to COVID-19 disease development is currently not well understood. To understand the potential correlation between ADCC responses and COVID-19 disease development, we analyzed the ADCC activity and neutralizing antibody response in 255 individuals ranging from asymptomatic to fatal infections over 1 year post disease. ADCC was elicited by 10 days post-infection, peaked by 11-20 days, and remained detectable until 400 days post-infection. In general, patients with severe disease had higher ADCC activities. Notably, patients who had severe disease and recovered had higher ADCC activities than patients who had severe disease and deceased. Importantly, ADCC activities were mediated by a diversity of epitopes in SARS-COV-2-infected mice and induced to comparable levels against SARS-CoV-2 variants of concern (VOCs) (B.1.1.7, B.1.351, and P.1) as that against the D614G mutant in human patients and vaccinated mice. Our study indicates anti-SARS-CoV-2 ADCC as a major trait of COVID-19 patients with various conditions, which can be applied to estimate the extra-neutralization level against COVID-19, especially lethal COVID-19.

ECCO2R in 12 COVID-19 ARDS Patients With Extremely Low Compliance and Refractory Hypercapnia.

Purpose: A phenotype of COVID-19 ARDS patients with extremely low compliance and refractory hypercapnia was found in our ICU. In the context of limited number of ECMO machines, feasibility of a low-flow extracorporeal carbon dioxide removal (ECCO2R) based on the renal replacement therapy (RRT) platform in these patients was assessed. Methods: Single-center, prospective study. Refractory hypercapnia patients with COVID-19-associated ARDS were included and divided into the adjusted group and unadjusted group according to the level of PaCO2 after the application of the ECCO2R system. Ventilation parameters [tidal volume (VT), respiratory rate, and PEEP], platform pressure (Pplat) and driving pressure (DP), respiratory system compliance, arterial blood gases, and ECCO2R system characteristics were collected. Results: Twelve patients with refractory hypercapnia were enrolled, and the PaCO2 was 64.5 [56-88.75] mmHg. In the adjusted group, VT was significantly reduced from 5.90 ± 0.16 to 5.08 ± 0.43 ml/kg PBW; DP and Pplat were also significantly reduced from 23.5 ± 2.72 mmHg and 29.88 ± 3.04 mmHg to 18.5 ± 2.62 mmHg and 24.75 ± 3.41 mmHg, respectively. In the unadjusted group, PaCO2 decreased from 94 [86.25, 100.3] mmHg to 80 [67.50, 85.25] mmHg but with no significant difference, and the DP and Pplat were not decreased after weighing the pros and cons. Conclusions: A low-flow ECCO2R system based on the RRT platform enabled CO2 removal and could also decrease the DP and Pplat significantly, which provided a new way to treat these COVID-19 ARDS patients with refractory hypercapnia and extremely low compliance. Clinical Trial Registration: https://www.clinicaltrials.gov/, identifier NCT04340414.

Divergence between serum creatine and cystatin C in estimating glomerular filtration rate of critically ill COVID-19 patients.

BACKGROUND: The clinical use of serum creatine (sCr) and cystatin C (CysC) in kidney function evaluation of critically ill patients has been in continuous discussion. The difference between estimated glomerular filtration rate calculated by sCr (eGFRcr) and CysC (eGFRcysc) of critically ill COVID-19 patients were investigated in this study. METHODS: This is a retrospective, single-center study of critically ill patients with COVID-19 admitted in intensive care unit (ICU) at Wuhan, China. Control cases were moderate COVID-19 patients matched in age and sex at a ratio of 1:1. The eGFRcr and eGFRcysc were compared. The association between eGFR and death were analyzed in critically ill cases. The potential factors influencing the divergence between eGFRcr and eGFRcysc were explored. RESULTS: A total of 76 critically ill COVID-19 patients were concluded. The mean age was 64.5 ± 9.3 years. The eGFRcr (85.45 (IQR 60.58-99.23) ml/min/1.73m2) were much higher than eGFRcysc (60.6 (IQR 34.75-79.06) ml/min/1.73m2) at ICU admission. About 50 % of them showed eGFRcysc < 60 ml/min/1.73 m2 while 25% showed eGFRcr < 60 ml/min/1.73 m2 (χ2 = 10.133, p = 0.001). This divergence was not observed in moderate group. The potential factors influencing the divergence included serum interleukin-6 (IL-6), tumor necrosis factor (TNF-α) level as well as APACHEII, SOFA scores. Reduced eGFRcr (<60 mL/min/1.73 m2) was associated with death (HR = 1.939, 95%CI 1.078-3.489, p = 0.027). CONCLUSIONS: The eGFRcr was generally higher than eGFRcysc in critically ill COVID-19 cases with severe inflammatory state. The divergence might be affected by inflammatory condition and illness severity. Reduced eGFRcr predicted in-hospital death. In these patients, we advocate for caution when using eGFRcysc.

Face masks as a source of nanoplastics and microplastics in the environment: Quantification, characterization, and potential for bioaccumulation.

Billions of disposable face masks are consumed daily due to the COVID-19 pandemic. The role of these masks as a source of nanoplastics (NPs) and microplastics (MPs) in the environment has not been studied in previous studies. We quantified and characterized face mask released particles and evaluated their potential for accumulation in humans and marine organisms. More than one billion of NPs and MPs were released from each surgical or N95 face mask. These irregularly-shaped particles sized from c. 5 nm to c. 600 µm. But most of them were nano scale sized <1 µm. The middle layers of the masks had released more particles than the outer and inner layers. That MPs were detected in the nasal mucus of mask wearers suggests they can be inhaled while wearing a mask. Mask released particles also adsorbed onto diatom surfaces and were ingested by marine organisms of different trophic levels. This data is useful for assessing the health and environmental risks of face masks.