Reactive oxygen species (ROS, partial reduction or derivatives of free radicals) are highly reactive, dangerous and can cause oxidative cell death. In addition to their role as toxic by-products of aerobic metabolism, ROS play a role in the control and regulation of biological processes such as growth, the cell cycle, programmed cell death, hormone signaling, biotic and abiotic stress reactions and development. ROS always arise in plants as a by-product of several metabolic processes that are located in different cell compartments, or as a result of the inevitable escape of electrons to oxygen from the electron transport activities of chloroplasts, mitochondria and plasma membranes. These reactive species are formed in chloroplasts, mitochondria, plasma membranes, peroxisomes, apoplasts, the endoplasmic reticulum and cell walls. The action of many non-enzymatic and enzymatic antioxidants present in tissues is required for efficient scavenging of ROS generated during various environmental stressors. The current review provides an in-depth look at the fate of ROS in plants, a beneficial role in managing stress and other irregularities. The production sites are also explained with their negative effects. In addition, the biochemical properties and sources of ROS generation, capture systems, the influence of ROS on cell biochemistry and the crosstalk of ROS with other signaling molecules/pathways are discussed.

Artificial intelligence (AI) techniques in general and convolutional neural networks (CNNs) in particular have attained successful results in medical image analysis and classification. A deep CNN architecture has been proposed in this paper for the diagnosis of COVID‐19 based on the chest X‐ray image classification. Due to the nonavailability of sufficient‐size and good‐quality chest X‐ray image dataset, an effective and accurate CNN classification was a challenge. To deal with these complexities such as the availability of a very‐small‐sized and imbalanced dataset with image‐quality issues, the dataset has been preprocessed in different phases using different techniques to achieve an effective training dataset for the proposed CNN model to attain its best performance. The preprocessing stages of the datasets performed in this study include dataset balancing, medical experts’ image analysis, and data augmentation. The experimental results have shown the overall accuracy as high as 99.5% which demonstrates the good capability of the proposed CNN model in the current application domain. The CNN model has been tested in two scenarios. In the first scenario, the model has been tested using the 100 X‐ray images of the original processed dataset which achieved an accuracy of 100%. In the second scenario, the model has been tested using an independent dataset of COVID‐19 X‐ray images. The performance in this test scenario was as high as 99.5%. To further prove that the proposed model outperforms other models, a comparative analysis has been done with some of the machine learning algorithms. The proposed model has outperformed all the models generally and specifically when the model testing was done using an independent testing set.

Extensive research has been carried out during the last few decades, providing a detailed account of thousands of discovered phytochemicals and their biological activities that have the potential to be exploited for a wide variety of medicinal purposes. These phytochemicals, which are pharmacologically important for clinical use, primarily consist of polyphenols, followed by terpenoids and alkaloids. There are numerous published reports indicating the primary role of phytochemicals proven to possess therapeutic potential against several diseases. However, not all phytochemicals possess significant medicinal properties, and only some of them exhibit viable biological effects. Naringenin, a flavanone found in citrus fruits, is known to improve immunity, repair DNA damage, and scavenge free radicals. Despite the very low bioavailability of naringenin, it is known to exhibit various promising biological properties of medicinal importance, including anti-inflammatory and antioxidant activities. This review focuses on the various aspects related to naringenin, particularly its physicochemical, pharmacokinetic, and pharmacodynamic properties. Furthermore, various pharmacological activities of naringenin, such as anticancer, antidiabetic, hepatoprotective, neuroprotective, cardioprotective, nephroprotective, and gastroprotective effects, have been discussed along with their mechanisms of action.

Doxorubicin (Dox) is an operational and largely used anticancer drug, used to treat an array of malignancies. Nonetheless, its beneficial use is constrained due to its renal and hepatotoxicity dose dependently. Numerous research findings favor the use of antioxidants may impact Dox-induced liver injury/damage. In the current study, Wistar rats were given naringenin (50 and 100 mg/kg b.wt.) orally for 20 days as prophylactic dose, against the hepatotoxicity induced by single intraperitoneal injection of Dox (20 mg/kg b.wt.). Potency of naringenin against the liver damage caused by Dox was assessed by measuring malonyl aldehyde (MDA) as a by-product of lipid peroxidation, biochemical estimation of antioxidant enzyme system, reactive oxygen species (ROS) level, and inflammatory mediators. Naringenin-attenuated ROS production, ROS-induced lipid peroxidation, and replenished reduced antioxidant armory, namely, catalase (CAT), glutathione reductase (GR), superoxide dismutase (SOD), glutathione peroxidase (GPx), and glutathione (GSH). Naringenin similarly diminished expression of Cox-2 and levels of NF-κB and other inflammatory molecules induced by the Dox treatment. Histology added further evidence to the defensive effects of naringenin on Dox-induced liver damage. The outcomes of the current study reveal that oxidative stress and inflammation are meticulously linked with Dox-triggered damage, and naringenin illustrates the potential effect on Dox-induced hepatotoxicity probably through diminishing the oxidative stress and inflammation.

Background: Ulcerative colitis (UC) is a long-term condition which results in inflammation and ulcers of the colon and rectum. The key indications of active disease are abdominal pain and diarrhea mixed with blood. Aims: We explore the underlying colon protective mechanism of sinapic acid (SA) against acetic acid (AA) induced ulcerative colitis in rats. The implications of inflammation, oxidative stress, and apoptosis are studied. Methodology: Twenty-four rats were distributed into four categories, normal control (NC), ulcerative colitis (UC), ulcerative Colitis with SA 40 mg/kg (SA 40 mg/kg + AA), and ulcerative colitis with prednisolone (PRDL 10 mg/kg + AA), and were pretreated orally with saline, saline and SA (40 mg/kg/day) or PRDL (10 mg/kg/day) respectively, for 7 days. UC was prompted by trans-rectal administration of 4% AA on the 5th day, colon tissues were surgically removed for gross morphology and histological inspection, oxidative stress, and inflammatory markers and immunoblot analysis of Bax, caspase-3, and Bcl-2. Results: Macroscopic and histological inspection demonstrated that both SA 40 mg/kg and PRDL (10 mg/kg/day) significantly ameliorates colonic injuries. In addition, both pretreatments significantly ameliorates AA-induced UC, oxidative stress, as indicated by suppressed malondialdehyde (MDA), nitric oxide (NO) levels and restoring antioxidant/oxidant balance as indicated by catalase and glutathione levels, suppressed inflammation via inhibiting cytokines TNF-α, IL-6, inflammatory markers MPO, PGE₂, COX-2 and NF-κB and inhibiting the protein expression of Bax and caspase-3 apoptotic protein and increasing the anti-apoptotic protein, Bcl-2 thereby inhibiting apoptosis. Conclusion: Sinapic acid significantly ameliorates AA induced UC in rats by suppressing inflammation, oxidative stress, and apoptosis in colonic tissues which exhibits its potential for the management of UC.