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Abstract Dinanath grass (Pennisetum pedicellatum Trin.) is an extensively grown forage grass known for its significant drought resilience. In order to comprehensively grasp the adaptive mechanism of Dinanath grass in response to water deficient conditions, transcriptomic and metabolomics were applied in the leaves of Dinanath grass exposed to two distinct drought intensities (48-hour and 96-hour). Transcriptomic analysis of Dinanath grass leaves revealed that a total of 218 and 704 genes were differentially expressed under 48- and 96-hour drought conditions, respectively. The genes that were expressed differently (DEGs) and the metabolites that accumulated in response to 48-hour drought stress mainly showed enrichment in the biosynthesis of secondary metabolites, particularly phenolics and flavonoids. Conversely, under 96-hour drought conditions, the enriched pathways predominantly involved lipid metabolism, specifically sterol lipids. In particular, phenylpropanoid pathway and brassinosteroid signaling played a crucial role in drought response to 48- and 96-hour water deficit conditions, respectively. This variation in drought response indicates that the adaptation mechanism in Dinanath grass is highly dependent on the intensity of drought stress. In addition, different genes associated with phenylpropanoid and fatty acid biosynthesis, as well as signal transduction pathways namely phenylalanine ammonia-lyase, putrescine hydroxycinnamoyl transferase, abscisic acid 8’-hydroxylase 2, syntaxin-61, lipoxygenase 5, calcium-dependent protein kinase and phospholipase D alpha one, positively regulated with drought tolerance. Combined transcriptomic and metabolomic analyses highlights the outstanding involvement of regulatory pathways related to secondary cell wall thickening and lignin biosynthesis in imparting drought tolerance to Dinanath grass leaves. These findings collectively contribute to an enhanced understanding of candidate genes and key metabolites relevant to drought response in Dinanath grass. Furthermore, they establish a groundwork for the creation of a transcriptome database aimed at developing abiotic stress-tolerant grasses and major crop varieties through both transgenic and genome editing approaches.

Globally, diabetes mellitus (DM) and stroke are two common chronic illnesses that have a substantial impact on rates of morbidity and mortality. There is significant evidence linking diabetes to an increased risk of stroke in terms of incidence, severity, and mortality. This extensive review looks at shared risk factors, underlying pathophysiological mechanisms, epidemiological trends, and evidence-based therapy approaches to give a thorough analysis of the causal relationship between diabetes mellitus and stroke. Studies using epidemiological data regularly show that people with diabetes have a higher incidence of stroke than people without the disease. Furthermore, diabetes is linked to a less favorable outcome following a stroke, as well as an elevated chance of stroke recurrence. Determining the pathophysiological pathways that connect diabetes and stroke is essential to understanding their relationship. Key pathophysiological processes associated with these disorders include endothelial dysfunction, inflammation, oxidative stress, hyperglycemia, and dyslipidemia. Due to microvascular complications, these mechanisms raise the risk of hemorrhagic stroke and predispose diabetics to an increased risk of ischemic stroke by creating a prothrombotic and atherosclerotic milieu. Diabetes and stroke are linked due to shared risk factors like smoking, obesity, dyslipidemia, hypertension, and poor glycemic control. Lifestyle changes, blood pressure control, lipid-lowering therapy, antiplatelet medicines, and a nutritious diet are essential for stroke risk reduction. Reducing the risk of stroke in people with diabetes requires the implementation of management techniques that focus on both diabetes control and stroke prevention. Optimizing results and lowering the frequency of stroke-related complications in diabetics requires multidisciplinary care. The intricate interactions between diabetes mellitus and stroke are highlighted in this review’s conclusion, which also highlights the value of patient education, risk factor treatment, the effect of antidiabetic therapy on stroke, and integrated care in lowering the incidence of stroke in people with diabetes.

The most frequent infantile tumor is a hemangioma, and its most common complication is ulceration. A quickly progressing ulcer called a hemangioma can also result in secondary infection. The mechanism of ulcer formation is unknown but is thought to develop during the rapid growth phase. Infantile hemangiomas are diagnosed clinically, based on the progression of the lesion's history and a clinical examination. Physical interventions (laser surgery, cryosurgery, excision) and systemic corticosteroids or beta-blockers are the usual course of treatment; all carry the potential for substantial side effects. A two-month young female baby approached us, with a diagnosis of hemangiomatous ulcer. Skin grafting was advised by a plastic surgeon, but the baby's parents approached for Ayurveda treatment. The case was treated with oral medicine bilwadi agada and external treatments vranaprakshalana with triphala kwatha and jatyadi taila local application for 2 months. There was complete healing of the ulcer.

Elliptic-curve cryptography (ECC) is a popular technique of public-key cryptography used for secure communications in Internet of Things (IoT) applications. In this study, the implementation and analyze the Elliptic Curve Digital Signature Algorithm (ECDSA) with NIST-256 on MicroBlaze processors based on RISC-V architecture. This implementation aims to enhance secure communication and data exchange between IoT devices and also provides a detailed account of our ECDSA implementation on a RISC-V processor and evaluates its performance, achieving a reduction of 11.8% in execution time compared to existing techniques. The implementation takes 483 clock cycles and utilizes approximately 4096 bytes of memory. These results demonstrate that ECDSA can be efficiently implemented on RISC-V processors, making it a promising option for secure communication in IoT applications. Furthermore, the study highlights specific security considerations critical to implementing ECC on RISC-V processors, ensuring robust and reliable security in IoT environments.