Detection of COVID-19 from chest X-ray images: Boosting the performance with convolutional neural network and transfer learning.

Coronavirus disease (COVID-19) is a pandemic that has caused thousands of casualties and impacts all over the world. Most countries are facing a shortage of COVID-19 test kits in hospitals due to the daily increase in the number of cases. Early detection of COVID-19 can protect people from severe infection. Unfortunately, COVID-19 can be misdiagnosed as pneumonia or other illness and can lead to patient death. Therefore, in order to avoid the spread of COVID-19 among the population, it is necessary to implement an automated early diagnostic system as a rapid alternative diagnostic system. Several researchers have done very well in detecting COVID-19; however, most of them have lower accuracy and overfitting issues that make early screening of COVID-19 difficult. Transfer learning is the most successful technique to solve this problem with higher accuracy. In this paper, we studied the feasibility of applying transfer learning and added our own classifier to automatically classify COVID-19 because transfer learning is very suitable for medical imaging due to the limited availability of data. In this work, we proposed a CNN model based on deep transfer learning technique using six different pre-trained architectures, including VGG16, DenseNet201, MobileNetV2, ResNet50, Xception, and EfficientNetB0. A total of 3886 chest X-rays (1200 cases of COVID-19, 1341 healthy and 1345 cases of viral pneumonia) were used to study the effectiveness of the proposed CNN model. A comparative analysis of the proposed CNN models using three classes of chest X-ray datasets was carried out in order to find the most suitable model. Experimental results show that the proposed CNN model based on VGG16 was able to accurately diagnose COVID-19 patients with 97.84% accuracy, 97.90% precision, 97.89% sensitivity, and 97.89% of F1-score. Evaluation of the test data shows that the proposed model produces the highest accuracy among CNNs and seems to be the most suitable choice for COVID-19 classification. We believe that in this pandemic situation, this model will support healthcare professionals in improving patient screening.

Inhibitory effects of ultralow-dose sodium hypochlorite on Microcystis aeruginosa and Chlorella vulgaris: Differences in sensitivity and physiology

Throughout the COVID-19 pandemic, the application of residual free chlorine has been emphasized as an effective disinfectant;however, the discharged residual chlorine is associated with potential ecological risk at concentrations even below 0.1 mg/L. However, the influence of free chlorine at ultralow-doses (far below 0.01 mg/L) on phytoplankton remains unclear. Due to limitations of detection limit and non-linear dissolution, different dilution rates (1/500, 1/1000, 1/5000, 1/10000, and 1/50000 DR) of a NaClO stock solution (1 mg/L) were adopted to represent ultralow-dose NaClO gradients. Two typical microalgae species, cyanobacterium Microcystis aeruginosa and chlorophyta Chlorella vulgaris, were explored under solo- and co-culture conditions to analyze the inhibitory effects of NaClO on microalgae growth and membrane damage. Additionally, the effects of ultralow-dose NaClO on photosynthesis activity, intracellular reactive oxygen species (ROS) production, and esterase activity were investigated, in order to explore physiological changes and sensitivity. With an initial microalgae cell density of approximately 1 × 106 cell/mL, an inhibitory effect on M. aeruginosa was achieved at a NaClO dosage above 1/10000 DR, which was lower than that of C. vulgaris (above 1/5000 DR). The variation in membrane integrity and photosynthetic activity further demonstrated that the sensitivity of M. aeruginosa to NaClO was higher than that of C. vulgaris, both in solo- and co-culture conditions. Moreover, NaClO is able to interfere with photosynthetic activity, ROS levels, and esterase activity. Photosynthetic activity declined gradually in both microalgae species under sensitive NaClO dosage, but esterase activity increased more rapidly in M. aeruginosa, similar to the behavior of ROS in C. vulgaris. These findings of differing NaClO sensitivity and variations in physiological activity between the two microalgae species contribute to a clearer understanding of the potential ecological risk associated with ultralow-dose chlorine, and provide a basis for practical considerations. Graphical Unlabelled Image

Toxicity of 17 Disinfection By-products to Different Trophic Levels of Aquatic Organisms: Ecological Risks and Mechanisms.

Intensified disinfection of wastewater during the COVID-19 pandemic increased the release of toxic disinfection by-products (DBPs). However, studies relating to the ecological impacts of DBPs on the aquatic environment remain insufficient. In this study, we comparatively investigated the toxicities and ecological risks of 17 typical, halogenated DBPs to three trophic levels of organisms in the freshwater ecosystem, including phytoplankton (Scenedesmus sp.), zooplankton (Daphnia magna), and fish (Danio rerio). Toxicity of DBPs was found to be species-specific: Scenedesmus sp. was the most sensitive to haloacetic acids, while D. magna was the most sensitive to haloacetonitriles and trihalomethanes. Specific to each DBP, toxicities were also related to their classes and substituted halogen atoms. Damage to photosystems and oxidative stress served as the potential mechanisms for DBPs toxicity to microalgae. The different sensitivities to DBPs indicate that a battery of bioassays with organisms at different trophic levels is necessary to determine the ecotoxicity of DBPs. Furthermore, the ecological risks of DBPs were assessed by calculating the risk quotients (RQs) based on toxicity data from multiple bioassays. The cumulative RQs of DBPs to all the organisms were greater than 1.0, indicating high ecological risks of DBPs in wastewater effluents.

Human endeavor for anti-SARS-CoV-2 pharmacotherapy: A major strategy to fight the pandemic.

The global spread of COVID-19 constitutes the most dangerous pandemic to emerge during the last one hundred years. About seventy-nine million infections and more than 1.7 million death have been reported to date, along with destruction of the global economy. With the uncertainty evolved by alarming level of genome mutations, coupled with likelihood of generating only a short lived immune response by the vaccine injections, the identification of antiviral drugs for direct therapy is the need of the hour. Strategies to inhibit virus infection and replication focus on targets such as the spike protein and non-structural proteins including the highly conserved RNA-dependent-RNA-polymerase, nucleotidyl-transferases, main protease and papain-like proteases. There is also an indirect option to target the host cell recognition systems such as angiotensin-converting enzyme 2 (ACE2), transmembrane protease, serine 2, host cell expressed CD147, and the host furin. A drug search strategy consensus in tandem with analysis of currently available information is extremely important for the rapid identification of anti-viral. An unprecedented display of cooperation among the scientific community regarding SARS-CoV-2 research has resulted in the accumulation of an enormous amount of literature that requires curation. Drug repurposing and drug combinations have drawn tremendous attention for rapid therapeutic application, while high throughput screening and virtual searches support de novo drug identification. Here, we examine how certain approved drugs targeting different viruses can play a role in combating this new virus and analyze how they demonstrate efficacy under clinical assessment. Suggestions on repurposing and de novo strategies are proposed to facilitate the fight against the COVID-19 pandemic.

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences.

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

Hyperbaric oxygen therapy in an elderly critical coronavirus disease 2019 patient with endotracheal intubation: clinical effect analysis

Objective To sum up our experience of hyperbaric oxygen therapy (HBOT) in an elderly critical coronavirus disease 2019 (COVID-19) patient with endotracheal intubation, providing references for the application of HBOT in COVID-19 treatment. Methods and results The patient was 87 years old male and presented coma symptoms on Feb. 3, 2020. Chest computed tomography (CT) showed multiple small flake fuzzy shadows in both lungs. The nucleic acid test of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in bronchoalveolar lavage fluid was positive on Feb.5 and the diagnosis of COVID-19 was confirmed. After symptomatic and supportive treatment, the patient's condition became stable gradually, and the tracheal intubation was removed on Feb. 22. However, the patient was intubated again on Feb. 24 because of loss of coughing and sputum expelling abilities, and the patient's condition was judged to be critical. On Feb. 29, the patient received HBOT for the first time, and medical staff entered the hyperbaric oxygen cabin through the special channel. After HBOT for four times, arterial partial pressure of oxygen (PaO 2) and arterial partial pressure of carbon dioxide (PaCO 2) of the patient tended to be stable, carbon dioxide retention was alleviated, liver and kidney function improved, and coagulation function recovered. On Mar. 6, SARS-CoV-2 immunoglobulin (Ig) test showed that SARS-CoV-2 IgM was negative and SARS-CoV-2 IgG was positive. The patient was then transferred to general wards. Conclusion HBOT can alleviate CO2 retention in critical COVID-19 patients, and has a positive effect on reducing hypoxia and protecting important organs. The HBOT infection control procedure is feasible, and the safety of medical staff can be guaranteed by reasonable design.