BackgroundIn humans, many diseases are associated with the accumulation of free radicals. Antioxidants can scavenge free radicals and minimize their impact. Therefore, the search for naturally occurring antioxidants of plant origin is imperative. Here, we aimed to investigate the antioxidant and free radical scavenging properties of methanolic extracts from Tabebuia pallida (T. pallida) stem bark (TPSB), root bark (TPRB), leaves (TPL), and flowers (TPF).MethodsThe antioxidant and free radical scavenging activity were determined by several standard methods using spectrophotomer. Total phenolic and flavonoid contents were estimated using Folin-Ciocalteu reagent and aluminum chloride colorimetric assay methods, respectively.ResultsAmong the extracts, TPL showed the highest total antioxidant capacity followed by TPRB, TPF, and TPSB. Based on DPPH and hydroxyl radical scavenging activity, TPL showed strong scavenging activity (91.05 ± 1.10 and 62.00 ± 0.57) with IC50 of 9.20 ± 0.28 and 46.00 ± 2.84 μg/mL, respectively when compared with standard BHT (IC50 of 7.00 ± 0.25 μg/mL) and CA (75.00 ± 0.14 μg/mL). These results suggest that TPL had the highest radical scavenging activity among the extractives that closely resembled the standard’s. In lipid peroxidation inhibition assay, TPL exhibited the most potent inhibitory activity (83.18 ± 2.12 %) with IC50 of 12.00 ± 2.12 μg/mL, which closely resembled standard CA (IC50 of 10.50 ± 0.28 μg/mL). Also, the reducing capacity on ferrous ion was in the following order: TPL > TPRB > TF > TPSB. The phenolic and flavonoid contents of TPL were higher than other extractives. A positive correlation (pvalue <0.001) was observed between phenolic content and free radical (DPPH· and ·OH) scavenging efficiencies and lipid peroxidation inhibition activity.ConclusionMethanolic extract of T. pallida leaf is a potential source of natural antioxidants and serves as an effective free radical scavenger and/or inhibitor. Hence, T. pallida might be a good plant-based pharmaceutical product for several diseases caused by free radicals.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1618-6) contains supplementary material, which is available to authorized users.

Mounting evidence support the potential benefits of functional foods or nutraceuticals for human health and diseases. Black cumin (Nigella sativa L.), a highly valued nutraceutical herb with a wide array of health benefits, has attracted growing interest from health-conscious individuals, the scientific community, and pharmaceutical industries. The pleiotropic pharmacological effects of black cumin, and its main bioactive component thymoquinone (TQ), have been manifested by their ability to attenuate oxidative stress and inflammation, and to promote immunity, cell survival, and energy metabolism, which underlie diverse health benefits, including protection against metabolic, cardiovascular, digestive, hepatic, renal, respiratory, reproductive, and neurological disorders, cancer, and so on. Furthermore, black cumin acts as an antidote, mitigating various toxicities and drug-induced side effects. Despite significant advances in pharmacological benefits, this miracle herb and its active components are still far from their clinical application. This review begins with highlighting the research trends in black cumin and revisiting phytochemical profiles. Subsequently, pharmacological attributes and health benefits of black cumin and TQ are critically reviewed. We overview molecular pharmacology to gain insight into the underlying mechanism of health benefits. Issues related to pharmacokinetic herb–drug interactions, drug delivery, and safety are also addressed. Identifying knowledge gaps, our current effort will direct future research to advance potential applications of black cumin and TQ in health and diseases.

There is an obvious concern globally regarding the fact about the emerging coronavirus 2019 novel coronavirus (2019-nCoV) as a worldwide public health threat. As the outbreak of COVID-19 causes by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) progresses within China and beyond, rapidly available epidemiological data are needed to guide strategies for situational awareness and intervention. The recent outbreak of pneumonia in Wuhan, China, caused by the SARS-CoV-2 emphasizes the importance of analyzing the epidemiological data of this novel virus and predicting their risks of infecting people all around the globe. In this study, we present an effort to compile and analyze epidemiological outbreak information on COVID-19 based on the several open datasets on 2019-nCoV provided by the Johns Hopkins University, World Health Organization, Chinese Center for Disease Control and Prevention, National Health Commission, and DXY. An exploratory data analysis with visualizations has been made to understand the number of different cases reported (confirmed, death, and recovered) in different provinces of China and outside of China. Overall, at the outset of an outbreak like this, it is highly important to readily provide information to begin the evaluation necessary to understand the risks and begin containment activities.

COVID-19 or novel coronavirus disease, which has already been declared as a worldwide pandemic, at first had an outbreak in a small town of China, named Wuhan. More than two hundred countries around the world have already been affected by this severe virus as it spreads by human interaction. Moreover, the symptoms of novel coronavirus are quite similar to the general flu. Screening of infected patients is considered as a critical step in the fight against COVID-19. Therefore, it is highly relevant to recognize positive cases as early as possible to avoid further spreading of this epidemic. However, there are several methods to detect COVID-19 positive patients, which are typically performed based on respiratory samples and among them one of the critical approach which is treated as radiology imaging or X-Ray imaging. Recent findings from X-Ray imaging techniques suggest that such images contain relevant information about the SARS-CoV-2 virus. In this article, we have introduced a Deep Neural Network (DNN) based Faster Regions with Convolutional Neural Networks (Faster R-CNN) framework to detect COVID-19 patients from chest X-Ray images using available open-source dataset. Our proposed approach provides a classification accuracy of 97.36%, 97.65% of sensitivity, and a precision of 99.28%. Therefore, we believe this proposed method might be of assistance for health professionals to validate their initial assessment towards COVID-19 patients.

Honey and its compounds are drawing attention as an effective natural therapy because of its ability to attenuate acute inflammation through enhancing immune response. Several studies have proved its potential healing capability against numerous chronic diseases/conditions, including pulmonary disorders, cardiac disorders, diabetes, hypertension, autophagy dysfunction, bacterial, and fungal infections. More importantly, honey has proved its virucidal effect on several enveloped viruses such as HIV, influenza virus, herpes simplex, and varicella-zoster virus. Honey may be beneficial for patients with COVID-19 which is caused by an enveloped virus SARS-CoV-2 by boosting the host immune system, improving comorbid conditions, and antiviral activities. Moreover, a clinical trial of honey on COVID-19 patients is currently undergoing. In this review, we have tried to summarize the potential benefits of honey and its ingredients in the context of antimicrobial activities, some chronic diseases, and the host immune system. Thus, we have attempted to establish a relationship with honey for the treatment of COVID-19. This review will be helpful to reconsider the insights into the possible potential therapeutic effects of honey in the context of the COVID-19 pandemic. However, the effects of honey on SARS-CoV-2 replication and/or host immune system need to be further investigated by in vitro and in vivo studies.