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1.
PeerJ ; 2022.
Article in English | ProQuest Central | ID: covidwho-1837194

ABSTRACT

Objective To investigate the impact of COVID-19 social distancing on medical research from the perspective of postgraduate students. Methods A cross-sectional study using an online survey was conducted from October 31 to November 1, 2021. A questionnaire was used to assess the impact of COVID-19 social distancing on medical research among postgraduate students. The questionnaire included basic information, medical research information, and information about social distancing measures. Participants also completed the self-made Research Work Affected Scale of Postgraduates (RWAS-P;qualitative evaluation: very mildly 0–10;mildly 11–20;moderately 21–30;severely 31–40;very severely 41–50). Logistic regression was used to identify factors related to the impact of COVID-19 social distancing. Results A total of 468 participants were analyzed;95.2% of the participants adhered to social distancing measures. The median total RWAS-P score was 22. The median RWAS-P scores for earlier research data, current research projects, future research plans, paper publication, and graduation schedule were 2, 6, 6, 6, and 4, respectively (score range 0–10). The higher grade of students, experimental research, and existence of inappetence or sleeplessness were related to negative attitude towards COVID-19 social distancing (odd ratio = 6.35, 9.80, 2.31, 2.15, 1.95, respectively). Conclusions Participants reported that social distancing had a moderate overall impact on their medical research. Social distancing had the greatest impact on current research projects, future research plans, and paper publications among postgraduate students. Higher grade level, experimental research type, inappetence, and sleeplessness were related to the impact of social distancing on their medical research.

2.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335433

ABSTRACT

The emergence of SARS-CoV-2 variants poses enormous challenges to the prevention and control of COVID-19 with alterations in antigenicity, transmissibility and pathogenicity. The rapid evolution of RNA viruses could be caused by high mutation frequencies during replication, arising by replication errors, intergenomic recombination or even host deaminases. We sought to understand whether host deaminases are involved in SARS-CoV-2 mutation, and how they orchestrate host deaminases to trigger this process. Herein, we provided the experimental evidence that APOBEC and ADAR deaminases act as the driving forces for SARS-CoV-2 mutagenesis. Mechanistically, SARS-CoV-2 nucleocapsid (N) protein, which is responsible for packaging viral genomic RNA, complexes with host deaminases to facilitate viral RNA mutation. Moreover, N protein employs deaminases-involved condensates to further promote viral RNA mutation. Mutant N protein with F17A substitution, defective in entry of deaminases-involved RNA granules, leads to the decreased mutation of viral RNA, confirming the function of N protein-deaminase condensates on RNA editing. Our study sheds light on the novel mechanism of SARS-CoV-2 mutation during host-virus arms race.

3.
J Virol ; : e0007022, 2022 May 02.
Article in English | MEDLINE | ID: covidwho-1832352

ABSTRACT

In global infection and serious morbidity and mortality, porcine epidemic diarrhea virus (PEDV) has been regarded as a dreadful porcine pathogen, but the existing commercial vaccines are not enough to fully protect against the epidemic strains. Therefore, it is of great necessity to feature the PEDV-host interaction and develop efficient countermeasures against viral infection. As an RNA/DNA protein, the trans-active response DNA binding protein (TARDBP) plays a variety of functions in generating and processing RNA, including transcription, splicing, transport, and mRNA stability, which have been reported to regulate viral replication. The current work aimed to detect whether and how TARDBP influences PEDV replication. Our data demonstrated that PEDV replication was significantly suppressed by TARDBP, regulated by KLF16, which targeted its promoter. We observed that through the proteasomal and autophagic degradation pathway, TARDBP inhibited PEDV replication via the binding as well as degradation of PEDV-encoded nucleocapsid (N) protein. Moreover, we found that TARDBP promoted autophagic degradation of N protein via interacting with MARCHF8, an E3 ubiquitin ligase, as well as NDP52, a cargo receptor. We also showed that TARDBP promoted host antiviral innate immune response by inducing interferon (IFN) expression through the MyD88-TRAF3-IRF3 pathway during PEDV infection. In conclusion, these data revealed a new antiviral role of TARDBP, effectively suppressing PEDV replication through degrading virus N protein via the proteasomal and autophagic degradation pathway and activating type I IFN signaling via upregulating the expression of MyD88. IMPORTANCE PEDV refers to the highly contagious enteric coronavirus that has quickly spread globally and generated substantial financial damage to the global swine industry. During virus infection, the host regulates the innate immunity and autophagy process to inhibit virus infection. However, the virus has evolved plenty of strategies with the purpose of limiting IFN-I production and autophagy processes. Here, we identified that TARDBP expression was downregulated via the transcription factor KLF16 during PEDV infection. TARDBP could inhibit PEDV replication through the combination as well as degradation of PEDV-encoded nucleocapsid (N) protein via proteasomal and autophagic degradation pathways and promoted host antiviral innate immune response by inducing IFN expression through the MyD88-TRAF3-IRF3 pathway. In sum, our data identify a novel antiviral function of TARDBP and provide a better grasp of the innate immune response and protein degradation pathway against PEDV infection.

4.
Gastroenterology ; 2021 Dec 23.
Article in English | MEDLINE | ID: covidwho-1830208
5.
Respir Res ; 23(1): 105, 2022 Apr 29.
Article in English | MEDLINE | ID: covidwho-1817223

ABSTRACT

BACKGROUND: Quantitative computed tomography (QCT) analysis may serve as a tool for assessing the severity of coronavirus disease 2019 (COVID-19) and for monitoring its progress. The present study aimed to assess the association between steroid therapy and quantitative CT parameters in a longitudinal cohort with COVID-19. METHODS: Between February 7 and February 17, 2020, 72 patients with severe COVID-19 were retrospectively enrolled. All 300 chest CT scans from these patients were collected and classified into five stages according to the interval between hospital admission and follow-up CT scans: Stage 1 (at admission); Stage 2 (3-7 days); Stage 3 (8-14 days); Stage 4 (15-21 days); and Stage 5 (22-31 days). QCT was performed using a threshold-based quantitative analysis to segment the lung according to different Hounsfield unit (HU) intervals. The primary outcomes were changes in percentage of compromised lung volume (%CL, - 500 to 100 HU) at different stages. Multivariate Generalized Estimating Equations were performed after adjusting for potential confounders. RESULTS: Of 72 patients, 31 patients (43.1%) received steroid therapy. Steroid therapy was associated with a decrease in %CL (- 3.27% [95% CI, - 5.86 to - 0.68, P = 0.01]) after adjusting for duration and baseline %CL. Associations between steroid therapy and changes in %CL varied between different stages or baseline %CL (all interactions, P < 0.01). Steroid therapy was associated with decrease in %CL after stage 3 (all P < 0.05), but not at stage 2. Similarly, steroid therapy was associated with a more significant decrease in %CL in the high CL group (P < 0.05), but not in the low CL group. CONCLUSIONS: Steroid administration was independently associated with a decrease in %CL, with interaction by duration or disease severity in a longitudinal cohort. The quantitative CT parameters, particularly compromised lung volume, may provide a useful tool to monitor COVID-19 progression during the treatment process. Trial registration Clinicaltrials.gov, NCT04953247. Registered July 7, 2021, https://clinicaltrials.gov/ct2/show/NCT04953247.


Subject(s)
COVID-19 , COVID-19/drug therapy , Humans , Lung/diagnostic imaging , Lung Volume Measurements/methods , Retrospective Studies , Steroids/therapeutic use
6.
Anal Chem ; 94(18): 6703-6710, 2022 May 10.
Article in English | MEDLINE | ID: covidwho-1815468

ABSTRACT

Ratiometric assays of label-free dual-signaling reporters with enzyme-free amplification are intriguing yet challenging. Herein, yellow- and red-silver nanocluster (yH-AgNC and rH-AgNC) acting as bicolor ratiometric emitters are guided to site-specifically cluster in two template signaling hairpins (yH and rH), respectively, and originally, both of them are almost non-fluorescent. The predesigned complement tethered in yH is recognizable to a DNA trigger (TOC) related to SARS-CoV-2. With the help of an enhancer strand (G15E) tethering G-rich bases (G15) and a linker strand (LS), a switchable DNA construct is assembled via their complementary hybridizing with yH and rH, in which the harbored yH-AgNC close to G15 is lighted-up. Upon introducing TOC, its affinity ligating with yH is further implemented to unfold rH and induce the DNA construct switching into closed conformation, causing TOC-repeatable recycling amplification through competitive strand displacement. Consequently, the harbored rH-AgNC is also placed adjacent to G15 for turning on its red fluorescence, while the yH-AgNC is retainable. As demonstrated, the intensity ratio dependent on varying TOC is reliable with high sensitivity down to 0.27 pM. By lighting-up dual-cluster emitters using one G15 enhancer, it would be promising to exploit a simpler ratiometric biosensing format for bioassays or clinical theranostics.


Subject(s)
Biosensing Techniques , COVID-19 , Metal Nanoparticles , COVID-19/diagnosis , DNA , Fluorescence , Humans , SARS-CoV-2 , Silver , Spectrometry, Fluorescence
7.
J Infect Public Health ; 15(6): 609-614, 2022 Apr 29.
Article in English | MEDLINE | ID: covidwho-1814760

ABSTRACT

BACKGROUND: Despite substantial resources deployed to curb SARS-CoV-2 transmission, controlling the COVID-19 pandemic has been a major challenge. New variants of the virus are frequently emerging leading to new waves of infection and re-introduction of control measures. In this study, we assessed the effectiveness of containment strategies implemented in the early phase of the pandemic. METHODS: Real-world data for COVID-19 cases was retrieved for the period Jan 1 to May 1, 2020 from a number of different sources, including PubMed, MEDLINE, Facebook, Epidemic Forecasting and Google Mobility Reports. We analyzed data for 18 countries/regions that deployed containment strategies such as travel restrictions, lockdowns, stay-at-home requests, school/public events closure, social distancing, and exposure history information management (digital contact tracing, DCT). Primary outcome measure was the change in the number of new cases over 30 days before and after deployment of a control measure. We also compared the effectiveness of centralized versus decentralized DCT. Time series data for COVID-19 were analyzed using Mann-Kendall (M-K) trend tests to investigate the impact of these measures on changes in the number of new cases. The rate of change in the number of new cases was compared using M-K z-values and Sen's slope. RESULTS: In spite of the widespread implementation of conventional strategies such as lockdowns, travel restrictions, social distancing, school closures, and stay-at-home requests, analysis revealed that these measures could not prevent the spread of the virus. However, countries which adopted DCT with centralized data storage were more likely to contain the spread. CONCLUSIONS: Centralized DCT was more effective in containing the spread of COVID-19. Early implementation of centralized DCT should be considered in future outbreaks. However, challenges such as public acceptance, data security and privacy concerns will need to be addressed.

8.
Sustainability ; 14(8):4562, 2022.
Article in English | ProQuest Central | ID: covidwho-1810141

ABSTRACT

Oil prices and rapidly increasing urbanization could have a long-lasting impact on the environment in oil-abundant Gulf Cooperation Council (GCC) countries. Therefore, the environmental role of oil price, economic growth, and urbanization on CO2 emissions should be tested. The present study investigates the impact of oil price, economic growth, and urbanization on CO2 emissions in those countries, considering asymmetrical relationships. For this purpose, a nonlinear autoregressive distributive lag cointegration approach is applied in GCC countries during the 1980–2019 period, and cointegration is corroborated in all investigated models. Long-run results show that rising economic growth positively affects CO2 emissions in Kuwait, Oman, Qatar, and Saudi Arabia. Decreasing economic growth positively affects CO2 emissions in Bahrain, Kuwait, Qatar, and the United Arab Emirates (UAE). Moreover, the rising oil price has a positive impact on CO2 emissions and shows a scale effect in Oman, Qatar, and Saudi Arabia. Moreover, it has a negative effect and corroborates technique and composition effects in Kuwait and the UAE. Further, decreasing oil prices has a positive impact on CO2 emissions in Bahrain and has a negative effect in Kuwait and the UAE. Lastly, urbanization positively affects CO2 emissions in Bahrain, Oman, Qatar, and the UAE. Economic growth is found asymmetrical in all GCC countries, and the asymmetrical effect of oil price is also observed in all GCC countries except the UAE.

9.
Front Vet Sci ; 9: 820625, 2022.
Article in English | MEDLINE | ID: covidwho-1809643

ABSTRACT

Infectious bronchitis virus (IBV) is the first coronavirus discovered in the world, which is also the prototype of gamma-coronaviruses. Nowadays, IBV is widespread all over the world and has become one of the causative agent causing severe economic losses in poultry industry. Generally, it is believed that the viral replication and immune evasion functions of IBV were modulated by non-structural and accessory proteins, which were also considered as the causes for its pathogenicity. In this study, we summarized the current knowledge about the immune evasion functions of IBV non-structural and accessory proteins. Some non-structural proteins such as nsp2, nsp3, and nsp15 have been shown to antagonize the host innate immune response. Also, nsp7 and nsp16 can block the antigen presentation to inhibit the adapted immune response. In addition, nsp13, nsp14, and nsp16 are participating in the formation of viral mRNA cap to limit the recognition by innate immune system. In conclusion, it is of vital importance to understand the immune evasion functions of IBV non-structural and accessory proteins, which could help us to further explore the pathogenesis of IBV and provide new horizons for the prevention and treatment of IBV in the future.

10.
Front Microbiol ; 13: 693196, 2022.
Article in English | MEDLINE | ID: covidwho-1809431

ABSTRACT

Infectious bronchitis (IB) virus (IBV) causes considerable economic losses to poultry production. The data on transmission dynamics of IBV in China are limited. The complete genome sequences of 212 IBV isolates in China during 1985-2020 were analyzed as well as the characteristics of the phylogenetic tree, recombination events, dN/dS ratios, temporal dynamics, and phylogeographic relationships. The LX4 type (GI-19) was found to have the highest dN/dS ratios and has been the most dominant genotype since 1999, and the Taiwan-I type (GI-7) and New type (GVI-1) showed an increasing trend. A total of 59 recombinants were identified, multiple recombination events between the field and vaccine strains were found in 24 isolates, and the 4/91-type (GI-13) isolates were found to be more prone to being involved in the recombination. Bayesian phylogeographic analyses indicated that the Chinese IBVs originated from Liaoning province in the early 1900s. The LX4-type viruses were traced back to Liaoning province in the late 1950s and had multiple transmission routes in China and two major transmission routes in the world. Viral phylogeography identified three spread regions for IBVs (including LX4 type) in China: Northeastern China (Heilongjiang, Liaoning, and Jilin), north and central China (Beijing, Hebei, Shanxi, Shandong, and Jiangsu), and Southern China (Guangxi and Guangdong). Shandong has been the epidemiological center of IBVs (including LX4 type) in China. Overall, our study highlighted the reasons why the LX4-type viruses had become the dominant genotype and its origin and transmission routes, providing more targeted strategies for the prevention and control of IB in China.

11.
J Comput Sci Technol ; 37(2): 330-343, 2022.
Article in English | MEDLINE | ID: covidwho-1803050

ABSTRACT

COVID-19 is a contagious infection that has severe effects on the global economy and our daily life. Accurate diagnosis of COVID-19 is of importance for consultants, patients, and radiologists. In this study, we use the deep learning network AlexNet as the backbone, and enhance it with the following two aspects: 1) adding batch normalization to help accelerate the training, reducing the internal covariance shift; 2) replacing the fully connected layer in AlexNet with three classifiers: SNN, ELM, and RVFL. Therefore, we have three novel models from the deep COVID network (DC-Net) framework, which are named DC-Net-S, DC-Net-E, and DC-Net-R, respectively. After comparison, we find the proposed DC-Net-R achieves an average accuracy of 90.91% on a private dataset (available upon email request) comprising of 296 images while the specificity reaches 96.13%, and has the best performance among all three proposed classifiers. In addition, we show that our DC-Net-R also performs much better than other existing algorithms in the literature. Supplementary Information: The online version contains supplementary material available at 10.1007/s11390-020-0679-8.

12.
Comput Biol Med ; 146: 105531, 2022 Apr 16.
Article in English | MEDLINE | ID: covidwho-1797031

ABSTRACT

BACKGROUND: As of Feb 27, 2022, coronavirus (COVID-19) has caused 434,888,591 infections and 5,958,849 deaths worldwide, dealing a severe blow to the economies and cultures of most countries around the world. As the virus has mutated, its infectious capacity has further increased. Effective diagnosis of suspected cases is an important tool to stop the spread of the pandemic. Therefore, we intended to develop a computer-aided diagnosis system for the diagnosis of suspected cases. METHODS: To address the shortcomings of commonly used pre-training methods and exploit the information in unlabeled images, we proposed a new pre-training method based on transfer learning with self-supervised learning (TS). After that, a new convolutional neural network based on attention mechanism and deep residual network (RANet) was proposed to extract features. Based on this, a hybrid ensemble model (TSRNet) was proposed for classifying lung CT images of suspected patients as COVID-19 and normal. RESULTS: Compared with the existing five models in terms of accuracy (DarkCOVIDNet: 98.08%; Deep-COVID: 97.58%; NAGNN: 97.86%; COVID-ResNet: 97.78%; Patch-based CNN: 88.90%), TSRNet has the highest accuracy of 99.80%. In addition, the recall, f1-score, and AUC of the model reached 99.59%, 99.78%, and 1, respectively. CONCLUSION: TSRNet can effectively diagnose suspected COVID-19 cases with the help of the information in unlabeled and labeled images, thus helping physicians to adopt early treatment plans for confirmed cases.

13.
BMC Vet Res ; 18(1): 90, 2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1789121

ABSTRACT

BACKGROUND: Infectious bronchitis virus (IBV) leads to huge economic losses in the poultry industry worldwide. The high levels of mutations of IBV render vaccines partially protective. Therefore, it is urgent to explore an effective antiviral drug or agent. The present study aimed to investigate the in vivo anti-IBV activity of a mixture of plant essential oils (PEO) of cinnamaldehyde (CA) and glycerol monolaurate (GML), designated as Jin-Jing-Zi. RESULTS: The antiviral effects were evaluated by clinical signs, viral loads, immune organ indices, antibody levels, and cytokine levels. The infection rates in the PEO-M (middle dose) and PEO-H (high dose) groups were significantly lower than those in the prevention, positive drug, and PEO-L (low dose) groups. The cure rates in the PEO-M and PEO-H groups were significantly higher than those in the prevention, positive drug, and PEO-L groups, and the PEO-M group had the highest cure rate of 92.31%. The symptom scores and IBV mRNA expression levels were significantly reduced in the PEO-M group. PEO significantly improved the immune organ indices and IBV-specific antibody titers of infected chickens. The anti-inflammatory factor levels of IL-4 and IFN-γ in the PEO-M group maintained high concentrations for a long time. The IL-6 levels in the PEO-M group were lower than those in prevention, positive drug, and PEO-L groups. CONCLUSION: The PEO had remarkable inhibition against IBV and the PEO acts by inhibiting virus multiplication and promoting immune function, suggesting that the PEO has great potential as a novel anti-IBV agent for inhibiting IBV infection.


Subject(s)
Coronavirus Infections , Infectious bronchitis virus , Oils, Volatile , Poultry Diseases , Viral Vaccines , Animals , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Chickens , Coronavirus Infections/drug therapy , Coronavirus Infections/prevention & control , Coronavirus Infections/veterinary , Oils, Volatile/pharmacology , Oils, Volatile/therapeutic use , Plant Oils/pharmacology , Plant Oils/therapeutic use , Poultry Diseases/drug therapy , Poultry Diseases/prevention & control , Viral Vaccines/therapeutic use
14.
Front Biosci (Landmark Ed) ; 27(2): 48, 2022 02 11.
Article in English | MEDLINE | ID: covidwho-1772157

ABSTRACT

BACKGROUND: Thymosin-α1 has been implicated into the treatment of novel respiratory virus Coronavirus Disease 2019 (COVID-19), but the underlying mechanisms are still disputable. AIM: Herein we aimed to reveal a previously unrecognized mechanism that thymosin-α1 prevents COVID-19 by binding with angiotensin-converting enzyme (ACE), which was inspired from the tool of network pharmacology. METHODS: KEGG pathway enrichment of thymosin-α1 treating COVID-19 was analyzed by Database of Functional Annotation Bioinformatics Microarray Analysis, then core targets were validated by ligand binding kinetics assay and fluorometric detection of ACE and ACE2 enzymatic activity. The production of angiotensin I, angiotensin II, angiotensin (1-7) and angiotensin (1-9) were detected by enzyme linked immunosorbent assay. RESULTS: We found that thymosin-α1 impaired the expressions of angiotensin-converting enzyme 2 and angiotensin (1-7) of human lung epithelial cells in a dose-dependent way (p < 0.001). In contrast, thymosin-α1 had no impact on their ACE and angiotensin (1-9) expressions but significantly inhibited the enzymatic activity of ACE (p > 0.05). CONCLUSION: The bioinformatic findings of network pharmacology and the corresponding pharmacological validations have revealed that thymosin-α1 treatment could decrease ACE2 expression in human lung epithelial cells, which strengthens the potential clinical applications of thymosin-α1 to prevent severe acute respiratory syndrome coronavirus 2 infection.


Subject(s)
Angiotensin-Converting Enzyme 2 , COVID-19 , Angiotensin-Converting Enzyme Inhibitors/pharmacology , Angiotensin-Converting Enzyme Inhibitors/therapeutic use , COVID-19/drug therapy , Humans , SARS-CoV-2 , Thymalfasin/pharmacology
15.
Chemistry ; 28(18): e202104054, 2022 Mar 28.
Article in English | MEDLINE | ID: covidwho-1767322

ABSTRACT

The ongoing outbreak of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has spread globally and poses a threat to public health and National economic development. Rapid and high-throughput SARS-CoV-2 RNA detection without the need of RNA extraction and amplification remain a key challenge. In this study, a new SARS-CoV-2 RNA detection strategy using a microfluidic biochip for the rapid and ultrasensitive detection of SARS-CoV-2 without RNA extraction and amplification was developed. This new strategy takes advantage of the specific SARS-CoV-2 RNA and probe DNA reaction in the microfluidic channel, fluorescence signal regulation by nanomaterials, and accurate sample control by the microfluidic chip. It presents an ultralow limit of detection of 600 copies mL-1 in a large linear detection regime from 1 aM to 100 fM. Fifteen samples were simultaneously detected in 40 min without the need for RNA purification and amplification. The detection accuracy of the strategy was validated through quantitative reverse transcription polymerase chain reaction (qRT-PCR), with a recovery of 99-113 %. Therefore, the SARS-CoV-2 RNA detection strategy proposed in this study can potentially be used for the quantitative diagnosis of viral infectious diseases.


Subject(s)
COVID-19 Testing , COVID-19 , Microfluidics , SARS-CoV-2 , COVID-19/diagnosis , COVID-19 Testing/methods , Humans , Nucleic Acid Amplification Techniques , RNA, Viral/genetics , SARS-CoV-2/genetics , Sensitivity and Specificity
16.
Stem Cell Res Ther ; 13(1): 124, 2022 03 24.
Article in English | MEDLINE | ID: covidwho-1759777

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread into more than 200 countries and infected approximately 203 million people globally. COVID-19 is associated with high mortality and morbidity in some patients, and this disease still does not have effective treatments with reproducibly appreciable outcomes. One of the leading complications associated with COVID-19 is acute respiratory distress syndrome (ARDS); this is an anti-viral host inflammatory response, and it is usually caused by a cytokine storm syndrome which may lead to multi-organ failure and death. Currently, COVID-19 patients are treated with approaches that mostly fall into two major categories: immunomodulators, which promote the body's fight against viruses efficiently, and antivirals, which slow or stop viruses from multiplying. These treatments include a variety of novel therapies that are currently being tested in clinical trials, including serum, IL-6 antibody, and remdesivir; however, the outcomes of these therapies are not consistently appreciable and remain a subject of debate. Mesenchymal stem/stromal cells (MSCs), the multipotent stem cells that have previously been used to treat viral infections and various respiratory diseases such as ARDS exhibit immunomodulatory properties and can ameliorate tissue damage. Given that SARS-CoV-2 targets the immune system and causes tissue damage, it is presumable that MSCs are being explored to treat COVID-19 patients. This review summarizes the potential mechanisms of action of MSC therapy, progress of MSC, and its related products in clinical trials for COVID-19 therapy based on the outcomes of these clinical studies.


Subject(s)
COVID-19 , Mesenchymal Stem Cells , Pneumonia , Respiratory Distress Syndrome , COVID-19/therapy , Humans , Mesenchymal Stem Cells/metabolism , SARS-CoV-2
17.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-331100

ABSTRACT

Under the growing crisis of coronavirus disease 2019 pandemic, the global medical system is facing the predicament of an acute shortage of medical-grade oxygen (O 2 , ≥ 99.5% purity). Herein, we manufactured an oxygen generation device relying on electrochemical technology. The performance of electrochemical oxygen generator (EOG) was remarkably improved to a practically applicable level, achieving long-term (>200 h), stable, and quick production (>1.5L/min) of high purity O 2 (99.9%) under high energy efficiency (496 L/kW·h), viasimultaneous optimizations for intrinsic electrochemical reaction mechanism, electrocatalysts, and external cell structure. The EOG also presents powerful competitiveness in user experience, which finds expression in high portability (4.7 kg), nearly instant O 2 production (<1 s), and a quiet working condition (<39 dB). The EOG shows great potential to substitute commercial pressure swing adsorption O 2 generation devices, which may significantly impact the traditional oxygen production industry.

18.
Tomography ; 8(2): 869-890, 2022 03 21.
Article in English | MEDLINE | ID: covidwho-1753687

ABSTRACT

The automatic recognition of COVID-19 diseases is critical in the present pandemic since it relieves healthcare staff of the burden of screening for infection with COVID-19. Previous studies have proven that deep learning algorithms can be utilized to aid in the diagnosis of patients with potential COVID-19 infection. However, the accuracy of current COVID-19 recognition models is relatively low. Motivated by this fact, we propose three deep learning architectures, F-EDNC, FC-EDNC, and O-EDNC, to quickly and accurately detect COVID-19 infections from chest computed tomography (CT) images. Sixteen deep learning neural networks have been modified and trained to recognize COVID-19 patients using transfer learning and 2458 CT chest images. The proposed EDNC has then been developed using three of sixteen modified pre-trained models to improve the performance of COVID-19 recognition. The results suggested that the F-EDNC method significantly enhanced the recognition of COVID-19 infections with 97.75% accuracy, followed by FC-EDNC and O-EDNC (97.55% and 96.12%, respectively), which is superior to most of the current COVID-19 recognition models. Furthermore, a localhost web application has been built that enables users to easily upload their chest CT scans and obtain their COVID-19 results automatically. This accurate, fast, and automatic COVID-19 recognition system will relieve the stress of medical professionals for screening COVID-19 infections.


Subject(s)
COVID-19 , Deep Learning , Algorithms , COVID-19/diagnostic imaging , Humans , Neural Networks, Computer , Tomography, X-Ray Computed/methods
19.
Signal Transduct Target Ther ; 7(1): 83, 2022 03 11.
Article in English | MEDLINE | ID: covidwho-1740428

ABSTRACT

SARS-CoV-2 induced marked lymphopenia in severe patients with COVID-19. However, whether lymphocytes are targets of viral infection is yet to be determined, although SARS-CoV-2 RNA or antigen has been identified in T cells from patients. Here, we confirmed that SARS-CoV-2 viral antigen could be detected in patient peripheral blood cells (PBCs) or postmortem lung T cells, and the infectious virus could also be detected from viral antigen-positive PBCs. We next prove that SARS-CoV-2 infects T lymphocytes, preferably activated CD4 + T cells in vitro. Upon infection, viral RNA, subgenomic RNA, viral protein or viral particle can be detected in the T cells. Furthermore, we show that the infection is spike-ACE2/TMPRSS2-independent through using ACE2 knockdown or receptor blocking experiments. Next, we demonstrate that viral antigen-positive T cells from patient undergone pronounced apoptosis. In vitro infection of T cells induced cell death that is likely in mitochondria ROS-HIF-1a-dependent pathways. Finally, we demonstrated that LFA-1, the protein exclusively expresses in multiple leukocytes, is more likely the entry molecule that mediated SARS-CoV-2 infection in T cells, compared to a list of other known receptors. Collectively, this work confirmed a SARS-CoV-2 infection of T cells, in a spike-ACE2-independent manner, which shed novel insights into the underlying mechanisms of SARS-CoV-2-induced lymphopenia in COVID-19 patients.


Subject(s)
Angiotensin-Converting Enzyme 2/metabolism , COVID-19/metabolism , SARS-CoV-2/metabolism , T-Lymphocytes/metabolism , Animals , Caco-2 Cells , Chlorocebus aethiops , Humans , Vero Cells
20.
Aging (Albany NY) ; 14(5): 2062-2080, 2022 03 10.
Article in English | MEDLINE | ID: covidwho-1737486

ABSTRACT

BACKGROUND: During the COVID-19 pandemic, there are growing concerns about the safety of administering immunotherapy in cancer patients with COVID-19. However, current clinical guidelines provided no clear recommendation. METHODS: Studies were searched and retrieved from electronic databases. The meta-analysis was performed by employing the generic inverse-variance method. A random-effects model was used to calculate the unadjusted odds ratios (ORs) and adjusted ORs with the corresponding 95% CIs. RESULTS: This meta-analysis included 20 articles with 6,042 cancer patients diagnosed with COVID-19. According to the univariate analysis, the acceptance of immunotherapy within 30 days before COVID-19 diagnosis did not increase the mortality of cancer patients (OR: 0.92; 95% CI: 0.68-1.25; P=0.61). Moreover, after adjusting for confounders, the adjusted OR for mortality was 0.51, with borderline significance (95% CI: 0.25-1.01; P=0.053). Similarly, the univariate analysis showed that the acceptance of immunotherapy within 30 days before COVID-19 diagnosis did not increase the risk of severe/critical disease in cancer patients (OR: 1.07; 95% CI: 0.78-1.47; P=0.66). No significant between-study heterogeneity was found in these analyses. CONCLUSIONS: Accepting immunotherapy within 30 days before the diagnosis of COVID-19 was not significantly associated with a higher risk of mortality or severe/critical disease of infected cancer patients. Further prospectively designed studies with large sample sizes are required to evaluate the present results.


Subject(s)
COVID-19/diagnosis , Immunotherapy, Active , Neoplasms/therapy , Adult , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/epidemiology , COVID-19 Testing , Female , Humans , Immunotherapy, Active/adverse effects , Immunotherapy, Active/statistics & numerical data , Male , Middle Aged , Neoplasms/complications , Neoplasms/diagnosis , Neoplasms/epidemiology , Pandemics , Prognosis , SARS-CoV-2/physiology , Treatment Outcome , Young Adult
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