Drought is one of the most common abiotic stresses, affecting the growth and productivity of crop plants globally, particularly in arid and semi-arid regions. Different strategies are used to mitigate the impact of drought among crop plants. Exogenous application of different substances are known to decrease the effects of various abiotic stresses, including drought stress. The aim of this study was to evaluate the effect of Ca2+ and H2O2 in developing drought stress tolerance in Brassica napus “Bulbul-98” seedlings. Brassica napus “Bulbul-98” seedlings were exposed to 5, 10 and 15 mM Ca2+ and 2, 5 and 10 μM H2O2 concentrations twice at an interval of two days for up to 20 days after germination. Drought stress decreased relative water content (RWC), chlorophyll content and increased proline, H2O2, soluble protein and electrolyte leakage in Brassica seedlings. Exogenous Ca2+ (5, 10,15 mM) and H2O2 (2, 5, 10 μM) supplementations, during drought stress induction, showed a significant increase in RWC by 5.4%, 18.06%, 26.2% and 6.87%, 13.9%, 18.3% respectively. Similarly, with the exogenous application of Ca2+ (5, 10, 15 mM) and H2O2 (2, 5, 10 μM), chlorophyll content was increased by 15.03%, 22.2%, and 28.4%, and 9.6%, 23.3%, and 27.5% respectively. It was confirmed that the seedlings under drought stress that were supplemented with Ca2+ and H2O2 recovered from water content reduction and chlorosis, and were able to grow normally.

In folk medicine Mallotus repandus (Willd.) Muell. Arg. is used to treat muscle pain, itching, fever, rheumatic arthritis, snake bite, hepatitis, and liver cirrhosis. This study aimed to evaluate the antinociceptive as well as the anti-inflammatory activities of the methanol extract of leaf. The leaves were extracted with methanol following hot extraction and tested for the presence of phytochemical constituents. Analgesic and anti-inflammatory activities were evaluated using acetic acid induced writhing test, xylene induced ear edema, cotton pellet induced granuloma, and tail immersion methods at doses of 500, 1000, and 2000 mg/kg body weight. The presence of flavonoids, saponins, and tannins was identified in the extract. The extract exhibited considerable antinociceptive and anti-inflammatory activities against four classical models of pain. In acetic acid induced writhing, xylene induced ear edema, and cotton pellet granuloma models, the extract revealed dose dependent activity. Additionally, it increased latency time in tail immersion model. It can be concluded that M. repandus possesses significant antinociceptive potential. These findings suggest that this plant can be used as a potential source of new antinociceptive and anti-inflammatory candidates. The activity of methanol extract is most likely mediated through central and peripheral inhibitory mechanisms. This study justified the traditional use of leaf part of this plant.

Citrus macroptera Montr. (C. macroptera) is locally known as Satkara. The fruit of this plant is used as appetite stimulant and in the treatment of fever. This study therefore aimed to evaluate the toxic effects of the fruit extract using some biochemical and hematological parameters in rat model. The effects of methanol extract of Citrus macroptera Montr. fruit administered at 250, 500 and 1000 mg/kg body weight were investigated on hematological and biochemical parameters in Sprague-Dawley female rats. Moreover, histopathological study was performed to observe the presence of pathological lesions in primary body organs. The extract presented no significant effect on body weight, percent water content, relative organ weight and hematological parameters in rat. Significant decrease from control group was observed in the levels of triglyceride, total cholesterol, low density lipoprotein and very low density lipoprotein; thus leading to significant decrease of cardiac risk ratio, castelli's risk index-2, atherogenic coefficient and atherogenic index of plasma at all doses. 500 mg/kg dose significantly decreased alkaline phosphatase (P<0.05), 1000 mg/kg dose significantly increased high density lipoprotein cholesterol (P<0.05) and 250 mg/kg dose significantly decreased the level of glycated hemoglobin (P<0.05) from the control group. There were no significant alterations observed with other serum biochemical parameters. Histopathological study confirmed the absence of inflammatory and necrotic features in the primary body organs. Study results indicate that methanolic fruit extract is unlikely to have significant toxicity. Moreover, these findings justified the cardio-protective, moderate hepato-protective and glucose controlling activities of the fruit extract.

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Artificial intelligence has significantly enhanced the research paradigm and spectrum with a substantiated promise of continuous applicability in the real world domain. Artificial intelligence, the driving force of the current technological revolution, has been used in many frontiers, including education, security, gaming, finance, robotics, autonomous systems, entertainment, and most importantly the healthcare sector. With the rise of the COVID-19 pandemic, several prediction and detection methods using artificial intelligence have been employed to understand, forecast, handle, and curtail the ensuing threats. In this study, the most recent related publications, methodologies and medical reports were investigated with the purpose of studying artificial intelligence’s role in the pandemic. This study presents a comprehensive review of artificial intelligence with specific attention to machine learning, deep learning, image processing, object detection, image segmentation, and few-shot learning studies that were utilized in several tasks related to COVID-19. In particular, genetic analysis, medical image analysis, clinical data analysis, sound analysis, biomedical data classification, socio-demographic data analysis, anomaly detection, health monitoring, personal protective equipment (PPE) observation, social control, and COVID-19 patients’ mortality risk approaches were used in this study to forecast the threatening factors of COVID-19. This study demonstrates that artificial-intelligence-based algorithms integrated into Internet of Things wearable devices were quite effective and efficient in COVID-19 detection and forecasting insights which were actionable through wide usage. The results produced by the study prove that artificial intelligence is a promising arena of research that can be applied for disease prognosis, disease forecasting, drug discovery, and to the development of the healthcare sector on a global scale. We prove that artificial intelligence indeed played a significantly important role in helping to fight against COVID-19, and the insightful knowledge provided here could be extremely beneficial for practitioners and research experts in the healthcare domain to implement the artificial-intelligence-based systems in curbing the next pandemic or healthcare disaster.