Allelopathic effect of the methanol extract of the weed species-red sorrel (Rumex acetosella L.) on the growth, phytohormone content and antioxidant activity of the cover crop - white clover (Trifolium repens L.).

Allelopathy is a biological process in which one organism releases biochemicals that affect the growth and development of other organisms. The current investigation sought to determine the allelopathic effect of Rumex acetosella on white clover (Trifolium repens) growth and development by using its shoot extract (lower IC50 value) as a foliar treatment. Here, different concentrations (25, 50, 100, and 200 g/L) of shoot extract from Rumex acetosella were used as treatments. With increasing concentrations of shoot extract, the plant growth parameters, chlorophyll and total protein content of Trifolium repens decreased. On the other hand, ROS, such as O2.- and H2O2, and antioxidant enzymes, including SOD, CAT, and POD, increased with increasing shoot extract concentration. A phytohormonal study indicated that increased treatment concentrations increased ABA and SA levels while JA levels were reduced. For the identification of allelochemicals, liquid‒liquid extraction, thin-layer chromatography, and open-column chromatography were conducted using R. acetosella shoot extracts, followed by a seed bioassay on the separated layer. A lower IC50 value was obtained through GC/MS analysis. gammaSitosterol was identified as the most abundant component. The shoot extract of Rumex acetosella has strong allelochemical properties that may significantly impede the growth and development of Trifolium repens. This approach could help to understand the competitive abilities of this weed species and in further research provide an alternate weed management strategy.

Ethylene-mediated stomatal responses to dehydration and rehydration in seed plants.

Ethylene, a plant hormone that significantly influences both plant growth and response to stress, plays a well-established role in stress signaling. However, its impact on stomatal opening and closure during dehydration and rehydration remains relatively unexplored and is still debated. Exogenous ethylene has been proven to induce stomatal closure through a series of signaling pathways, including the accumulation of reactive oxygen species (ROS), subsequent synthesis of nitric oxide (NO) and hydrogen sulfide (H2S), and SLOW ANION CHANNEL-ASSOCIATED 1 (SLAC1) activation. Thus, it has been suggested that ethylene might function to induce stomatal closure synergistically with abscisic acid (ABA). Furthermore, it has also been shown that increased ethylene can inhibit ABA- and jasmonic acid (JA)-induced stomatal closure, thus hindering drought-induced closure during dehydration. Simultaneously, other stresses, such as chilling, ozone pollution and K+ deficiency, inhibit drought and ABA-induced stomatal closure through an ethylene synthesis dependent way. However, ethylene has been shown to take on an opposing role during rehydration, preventing stomatal opening in the absence of ABA through its own signaling pathway. These findings offer novel insights into the function of ethylene in stomatal regulation during dehydration and rehydration, gaining a better understanding of the mechanisms underlying ethylene-induced stomatal movement in seed plants.

Appraising water resources for irrigation and spatial analysis based on fuzzy logic model in the tribal-prone areas of Bangladesh.

The lack of quality water resources for irrigation is one of the main threats for sustainable farming. This pioneering study focused on finding the best area for farming by looking at irrigation water quality and analyzing its location using a fuzzy logic model on a Geographic Information System platform. In the tribal-prone areas of Khagrachhari Sadar Upazila, Bangladesh, 28 surface water and 39 groundwater samples were taken from shallow tube wells, rivers, canals, ponds, lakes, and waterfalls. The samples were then analyzed for irrigation water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium adsorption ratio (SAR), soluble sodium percentage (SSP), residual sodium bicarbonate (RSBC), magnesium hazard ratio (MHR), Kelley's ratio (KR), and permeability index (PI). Fuzzy Irrigation Water Quality Index (FIWQI) was employed to determine the irrigation suitability of water resources. Spatial maps for parameters like EC, KR, MH, Na%, PI, SAR, and RSBC were developed using fuzzy membership values for groundwater and surface water. The FIWQI results indicate that 100% of the groundwater and 75% of the surface water samples range in the categories of excellent to good for irrigation uses. A new irrigation suitability map constructed by overlaying all parameters showed that surface water (75%) and some groundwater (100%) in the northern and southwestern portions are fit for agriculture. The western and central parts are unfit for irrigation due to higher bicarbonate and magnesium contents. The Piper and Gibbs diagram also indicated that the water in the study area is magnesium-bicarbonate type and the primary mechanism of water chemistry is controlled by the weathering of rocks, respectively. This research pinpoints the irrigation spatial pattern for regional water resource practices, identifies novel suitable areas, and improves sustainable agricultural uses in tribal-prone areas.

Polyamines inhibit abscisic acid-induced stomatal closure by scavenging hydrogen peroxide.

Stomatal closure is regulated by plant hormones and some small molecules to reduce water loss under stress conditions. Both abscisic acid (ABA) and polyamines alone induce stomatal closure; however, whether the physiological functions of ABA and polyamines are synergistic or antagonistic with respect to inducing stomatal closure is still unknown. Here, stomatal movement in response to ABA and/or polyamines was tested in Vicia faba and Arabidopsis thaliana, and the change in the signaling components under stomatal closure was analyzed. We found that both polyamines and ABA could induce stomatal closure through similar signaling components, including the synthesis of hydrogen peroxide (H2 O2 ) and nitric oxide (NO) and the accumulation of Ca2+ . However, polyamines partially inhibited ABA-induced stomatal closure both in epidermal peels and in planta by activating antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), to eliminate the ABA-induced increase in H2 O2 . These results strongly indicate that polyamines inhibit abscisic acid-induced stomatal closure, suggesting that polyamines could be used as potential plant growth regulators to increase photosynthesis under mild drought stress.

Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.

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.

A clear trade-off between leaf hydraulic efficiency and safety in an aridland shrub during regrowth.

It has been suggested that a trade-off between hydraulic efficiency and safety is related to drought adaptation across species. However, whether leaf hydraulic efficiency is sacrificed for safety during woody resprout regrowth after crown removal is not well understood. We measured leaf water potential (ψleaf ) at predawn (ψpd ) and midday (ψmid ), leaf maximum hydraulic conductance (Kleaf-max ), ψleaf at induction 50% loss of Kleaf-max (Kleaf P50 ), leaf area-specific whole-plant hydraulic conductance (LSC), leaf vein structure and turgor loss point (πtlp ) in 1- to 13-year-old resprouts of the aridland shrub (Caragana korshinskii). ψpd was similar, ψmid and Kleaf P50 became more negative, and Kleaf-max decreased in resprouts with the increasing age; thus, leaf hydraulic efficiency clearly traded off against safety. The difference between ψmid and Kleaf P50 , leaf hydraulic safety margin, increased gradually with increasing resprout age. More negative ψmid and Kleaf P50 were closely related to decreasing LSC and more negative πtlp , respectively, and the decreasing Kleaf-max arose from the lower minor vein density and the narrower midrib xylem vessels. Our results showed that a clear trade-off between leaf hydraulic efficiency and safety helps C. korshinskii resprouts adapt to increasing water stress as they approach final size.

Ozone Induced Stomatal Regulations, MAPK and Phytohormone Signaling in Plants.

Ozone (O3) is a gaseous environmental pollutant that can enter leaves through stomatal pores and cause damage to foliage. It can induce oxidative stress through the generation of reactive oxygen species (ROS) like hydrogen peroxide (H2O2) that can actively participate in stomatal closing or opening in plants. A number of phytohormones, including abscisic acid (ABA), ethylene (ET), salicylic acid (SA), and jasmonic acid (JA) are involved in stomatal regulation in plants. The effects of ozone on these phytohormones' ability to regulate the guard cells of stomata have been little studied, however, and the goal of this paper is to explore and understand the effects of ozone on stomatal regulation through guard cell signaling by phytohormones. In this review, we updated the existing knowledge by considering several physiological mechanisms related to stomatal regulation after response to ozone. The collected information should deepen our understanding of the molecular pathways associated with response to ozone stress, in particular, how it influences stomatal regulation, mitogen-activated protein kinase (MAPK) activity, and phytohormone signaling. After summarizing the findings and noting the gaps in the literature, we present some ideas for future research on ozone stress in plants.

GABA: A Key Player in Drought Stress Resistance in Plants.

γ-aminobutyric acid (GABA) is a non-protein amino acid involved in various physiological processes; it aids in the protection of plants against abiotic stresses, such as drought, heavy metals, and salinity. GABA tends to have a protective effect against drought stress in plants by increasing osmolytes and leaf turgor and reducing oxidative damage via antioxidant regulation. Guard cell GABA production is essential, as it may provide the benefits of reducing stomatal opening and transpiration and controlling the release of tonoplast-localized anion transporter, thus resulting in increased water-use efficiency and drought tolerance. We summarized a number of scientific reports on the role and mechanism of GABA-induced drought tolerance in plants. We also discussed existing insights regarding GABA's metabolic and signaling functions used to increase plant tolerance to drought stress.

Confidence intervals and prediction intervals for two-parameter negative binomial distributions.

Problems of finding confidence intervals (CIs) and prediction intervals (PIs) for two-parameter negative binomial distributions are considered. Simple CIs for the mean of a two-parameter negative binomial distribution based on some large sample methods are proposed and compared with the likelihood CIs. Proposed CIs are not only simple to compute, but also better than the likelihood CIs for moderate sample sizes. Prediction intervals for the mean of a future sample from a two-parameter negative binomial distribution are also proposed and evaluated for their accuracy. The methods are illustrated using two examples with real life data sets.

Enriched-Fe maize kernels to prevent dietary Fe deficiency in humans.

Iron (Fe) biofortification of edible organs without influencing crop yield is challenging, and potential solutions are largely unknown. Recently, Yan et al. identified a key regulator NAC78 (NAM/ATAF/CUC DOMAIN TRANSCRIPTION FACTOR 78) that enriches Fe in maize kernels without compromising crop yield. This may provide new crop yield management strategies for Fe acquisition and nutritional security.

Small ubiquitin-like modifiers E3 ligases in plant stress.

Plants regularly encounter various environmental stresses such as salt, drought, cold, heat, heavy metals and pathogens, leading to changes in their proteome. Of these, a post-translational modification, SUMOylation is particularly significant for its extensive involvement in regulating various plant molecular processes to counteract these external stressors. Small ubiquitin-like modifiers (SUMO) protein modification significantly contributes to various plant functions, encompassing growth, development and response to environmental stresses. The SUMO system has a limited number of ligases even in fully sequenced plant genomes but SUMO E3 ligases are pivotal in recognising substrates during the process of SUMOylation. E3 ligases play pivotal roles in numerous biological and developmental processes in plants, including DNA repair, photomorphogenesis, phytohormone signalling and responses to abiotic and biotic stress. A considerable number of targets for E3 ligases are proteins implicated in reactions to abiotic and biotic stressors. This review sheds light on how plants respond to environmental stresses by focusing on recent findings on the role of SUMO E3 ligases, contributing to a better understanding of how plants react at a molecular level to such stressors.

Designing and development of efficient multi-epitope-based peptide vaccine candidate against emerging avian rotavirus strains: A vaccinomic approach.

BACKGROUND: Enteric avian rotavirus (ARV) is the etiological agent of several health problems that pose a global threat to commercial chickens. Therefore, to avoid these widespread epidemics and high mortality rates, only vaccine and strict biosecurity are required. METHOD: The present study employs computational techniques to design a unique multi-epitope-based vaccine candidate that successfully activates immune cells against the ARV by combining adjuvant, linker, and B and T-cell epitopes. Starting, homologous sequences in the various ARV serotypes were revealed in the NCBI BLAST database, and then the two surface proteins (VP4 and VP7) of the ARV were retrieved from the UniprotKB database. The Clustal Omega server was then used to identify the conserved regions among the homologous sequences, and the B and T-cell epitopes were predicted using IEDB servers. Then, superior epitopes-2 MHC-1 epitopes, 2 MHC-2 epitopes, and 3B-cell epitopes-were combined with various adjuvants to create a total of four unique vaccine candidates. Afterward, the designed vaccine candidates underwent computational validation to assess their antigenicity, allergenicity, and stability. The vaccine candidate (V2) that demonstrated non-antigenicity, a high VaxiJen score, and non-allergenicity was ultimately chosen for molecular docking and dynamic simulation. RESULTS: Although the V2 and V4 vaccine candidates were highly immunogenic, V2 had a higher solubility rate. The predicted values of the aliphatic index and GRAVY value were 30.4 and 0.417, respectively. In terms of binding energy, V2 outperformed V4. Being successfully docked with TLRs, V2 was praised as the finest. After adaptation, the sequence's 50.73 % GC content outside of the BglII or ApaI restriction sites indicated that it was equivalently safe to clone. The chosen sequence was then inserted into the pET28a(+) vector within the BglII and ApaI restriction sites. This resulted in a final clone that was 4914 base pairs long, with the inserted sequence accounting for 478 bp and the vector accounting for the remainder. CONCLUSIONS: The immune-mediated simulation results for the selected vaccine construct showed significant response; thus, the study confirmed that the selected V2 vaccine candidate could enhance the immune response against ARV.

Unveiling the therapeutic potential: Evaluation of anti-inflammatory and antineoplastic activity of Magnolia champaca Linn's stem bark isolate through molecular docking insights.

Magnolia champaca Linn. has traditionally been used for medicinal activity in Asia for treating various chronic diseases as well as a source of food, medicines, and other commodities. Due to the long-used history of this plant, the present study was designed to explore the in vitro, in vivo and in silico anti-inflammatory and antineoplastic properties of the methanolic extract and fractions and the pure compound isolated from the most active chloroform fraction (CHF) of the stem bark of the plant. The isolated compound from the most active CHF was characterized and identified as a glycoside, trans-syringin, through chromatographic and spectroscopic (1H-NMR and 13C-NMR) analyses. In the in vitro anti-inflammatory assay, CHF was most effective in inhibiting inflammation and hemolysis of RBCs by 73.91 ± 1.70% and 75.92 ± 0.14%, respectively, induced by heat and hypotonicity compared to standard acetylsalicylic acid. In the egg albumin denaturation assay, CME and CHF showed the highest inhibition by 56.25 ± 0.82% and 65.82 ± 3.52%, respectively, contrasted with acetylsalicylic acid by 80.14 ± 2.44%. In an in vivo anti-inflammatory assay, statistically significant (p < 0.05) decreases in the parameters of inflammation, such as paw edema, leukocyte migration and vascular permeability, were recorded in a dose-dependent manner in the treated groups. In the antineoplastic assay, 45.26 ± 2.24% and 68.31 ± 3.26% inhibition of tumor cell growth for pure compound were observed compared to 73.26 ± 3.41% for standard vincristine. Apoptotic morphologic alterations, such as membrane and nuclear condensation and fragmentation, were also found in EAC cells after treatment with the isolated bioactive pure compound. Such treatment also reversed the increased WBC count and decreased RBC count to normal values compared to the untreated EAC cell-bearing mice and the standard vincristine-treated mice. Subsequently, in silico molecular docking studies substantiated the current findings, and the isolated pure compound and standard vincristine exhibited -6.4 kcal/mol and -7.3 kcal/mol binding affinities with topoisomerase-II. Additionally, isolated pure compound and standard diclofenac showed -8.2 kcal/mol and -7.6 kcal/mol binding affinities with the COX-2 enzyme, respectively. The analysis of this research suggests that the isolated bioactive pure compound possesses moderate to potent anti-inflammatory and antineoplastic activity and justifies the traditional uses of the stem bark of M. champaca. However, further investigations are necessary to analyze its bioactivity, proper mechanism of action and clinical trials for the revelation of new drug formulations.

Salicylic Acid Priming Improves Cotton Seedling Heat Tolerance through Photosynthetic Pigment Preservation, Enhanced Antioxidant Activity, and Osmoprotectant Levels.

The escalating global temperatures associated with climate change are detrimental to plant growth and development, leading to significant reductions in crop yields worldwide. Our research demonstrates that salicylic acid (SA), a phytohormone known for its growth-promoting properties, is crucial in enhancing heat tolerance in cotton (Gossypium hirsutum). This enhancement is achieved through modifications in various biochemical, physiological, and growth parameters. Under heat stress, cotton plants typically show significant growth disturbances, including leaf wilting, stunted growth, and reduced biomass. However, priming cotton plants with 1 mM SA significantly mitigated these adverse effects, evidenced by increases in shoot dry mass, leaf-water content, and chlorophyll concentrations in the heat-stressed plants. Heat stress also prompted an increase in hydrogen peroxide levels-a key reactive oxygen species-resulting in heightened electrolyte leakage and elevated malondialdehyde concentrations, which indicate severe impacts on cellular membrane integrity and oxidative stress. Remarkably, SA treatment significantly reduced these oxidative stresses by enhancing the activities of critical antioxidant enzymes, such as catalase, glutathione S-transferase, and ascorbate peroxidase. Additionally, the elevated levels of total soluble sugars in SA-treated plants enhanced osmotic regulation under heat stress. Overall, our findings reveal that SA-triggered protective mechanisms not only preserve photosynthetic pigments but also ameliorate oxidative stress and boost plant resilience in the face of elevated temperatures. In conclusion, the application of 1 mM SA is highly effective in enhancing heat tolerance in cotton and is recommended for field trials before being commercially used to improve crop resilience under increasing global temperatures.

Antioxidant activity of Schiff base ligands using the DPPH scavenging assay: an updated review.

Schiff base ligands, formed from primary amines and carbonyl compounds, are potential antioxidants because they scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH) radicals via hydrogen atom transfer (HAT) and single electron transfer (SET) routes. This review aims to help design, synthesize, and discuss the antioxidant activity of Schiff base ligands based on their structure. This study critically discussed the solvent effect and the structural changes of Schiff base ligands responsible for DPPH scavenging activity, such as proton donating, electron-donating, and electron-withdrawing substituents, conjugation and ring structure. The ligands with electron-donating substituent groups in the phenolic ring demonstrated greater activity by readily stabilizing the radical and some of them showed higher activity than the standard. The activity also depends on the solvent used; the activity increases in those solvents that promote the proton and electron donation of the Schiff base. Schiff bases are most important due to their versatile applications, which can be explained by their antioxidant activity. The data led to the conclusion that the Schiff base ligand will serve as a source of synthetic antioxidants. There should be lots of scope for research on the antioxidant activity of Schiff bases. This review will assist researchers in studying Schiff base-based antioxidants and their applications. All the data analyzed in this paper was found from in vitro tests; for more clearance supplementary tests and in vivo investigations are crucial.

Evaluating the Brexit and COVID-19's influence on the UK economy: A data analysis.

The economic landscape of the United Kingdom has been significantly shaped by the intertwined issues of Brexit, COVID-19, and their interconnected impacts. Despite the country's robust and diverse economy, the disruptions caused by Brexit and the COVID-19 pandemic have created uncertainty and upheaval for both businesses and individuals. Recognizing the magnitude of these challenges, academic literature has directed its attention toward conducting immediate research in this crucial area. This study sets out to investigate key economic factors that have influenced various sectors of the UK economy and have broader economic implications within the context of Brexit and COVID-19. The factors under scrutiny include the unemployment rate, GDP index, earnings, and trade. To accomplish this, a range of data analysis tools and techniques were employed, including the Box-Jenkins method, neural network modeling, Google Trend analysis, and Twitter-sentiment analysis. The analysis encompassed different periods: pre-Brexit (2011-2016), Brexit (2016-2020), the COVID-19 period, and post-Brexit (2020-2021). The findings of the analysis offer intriguing insights spanning the past decade. For instance, the unemployment rate displayed a downward trend until 2020 but experienced a spike in 2021, persisting for a six-month period. Meanwhile, total earnings per week exhibited a gradual increase over time, and the GDP index demonstrated an upward trajectory until 2020 but declined during the COVID-19 period. Notably, trade experienced the most significant decline following both Brexit and the COVID-19 pandemic. Furthermore, the impact of these events exhibited variations across the UK's four regions and twelve industries. Wales and Northern Ireland emerged as the regions most affected by Brexit and COVID-19, with industries such as accommodation, construction, and wholesale trade particularly impacted in terms of earnings and employment levels. Conversely, industries such as finance, science, and health demonstrated an increased contribution to the UK's total GDP in the post-Brexit period, indicating some positive outcomes. It is worth highlighting that the impact of these economic factors was more pronounced on men than on women. Among all the variables analyzed, trade suffered the most severe consequences in the UK. By early 2021, the macroeconomic situation in the country was characterized by a simple dynamic: economic demand rebounded at a faster pace than supply, leading to shortages, bottlenecks, and inflation. The findings of this research carry significant value for the UK government and businesses, empowering them to adapt and innovate based on forecasts to navigate the challenges posed by Brexit and COVID-19. By doing so, they can promote long-term economic growth and effectively address the disruptions caused by these interrelated issues.

Phytocytokine SCREWs increase plant immunity through actively reopening stomata.

Plants secreted phytocytokine SMALL PHYTOCYTOKINES REGULATING DEFENSE AND WATER LOSS (SCREWs) and its receptor PLANT SCREW UNRESPONSIVE RECEPTOR (NUT) to counter abscisic acid (ABA)- and pathogen-induced stomatal closure (Liu et al.). This novel signaling process provides plants with a new strategy to increase immunity through disrupting an aqueous habitat for pathogen colonization.

Light: a crucial factor for rhizobium-induced root nodulation.

Wang et al. recently showed that, in soybean (Glycine max), root nodule formation is induced by a light-triggered signal that moves from the upper part of the plant to the roots. This novel signaling process opens a new area of research aimed to optimize the carbon-nitrogen balance in plant-rhizobium symbiosis.

Exogenous Nitric Oxide and Silicon Applications Alleviate Water Stress in Apricots.

Many plants confront several environmental stresses including heat, water stress, drought, salinity and high-metal concentrations that are crucial in defining plant productivity at different stages of their life cycle. Nitric oxide (NO) and Silicon (Si) are very effective molecules related in most of them and in varied biochemical events that have proven to be protective during cellular injury caused by some stress conditions like water stress. In the current work, we studied the effect of Si and NO alone and NO + Si interactive application on the response of plants exposed to water deficiency and well-watered plants for the Milord apricot variety. Water stress caused a reduce in chlorophyll content, dry and fresh weight, leaf area, stomatal conductivity, leaf relative water content and nutrient elements, while it caused an increase in leaf temperature, leaf proline, leaf malondialdehyde (MDA) content and membrane permeability. Si, NO and Si + NO combination treatments under water stress conditions significantly decreased the adverse effects of water stress on leaf temperature, leaf area, dry and fresh weight, stomata conductivity, relative water content, membrane permeability, L-proline and MDA content. The shoot dry weight, chlorophyll content, stomata conductivity and leaf relative water content in Si + NO treated apricot saplings increased by 59%, 55%, 12% and 8%, respectively. Combined treatment (Si + NO) was detected to be more effective than single applications (Si or NO) on some physiological, biochemical, morphological and nutritional properties of apricot under water stress conditions.

Robust and efficient COVID-19 detection techniques: A machine learning approach.

The devastating impact of the Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) pandemic almost halted the global economy and is responsible for 6 million deaths with infection rates of over 524 million. With significant reservations, initially, the SARS-CoV-2 virus was suspected to be infected by and closely related to Bats. However, over the periods of learning and critical development of experimental evidence, it is found to have some similarities with several gene clusters and virus proteins identified in animal-human transmission. Despite this substantial evidence and learnings, there is limited exploration regarding the SARS-CoV-2 genome to putative microRNAs (miRNAs) in the virus life cycle. In this context, this paper presents a detection method of SARS-CoV-2 precursor-miRNAs (pre-miRNAs) that helps to identify a quick detection of specific ribonucleic acid (RNAs). The approach employs an artificial neural network and proposes a model that estimated accuracy of 98.24%. The sampling technique includes a random selection of highly unbalanced datasets for reducing class imbalance following the application of matriculation artificial neural network that includes accuracy curve, loss curve, and confusion matrix. The classical approach to machine learning is then compared with the model and its performance. The proposed approach would be beneficial in identifying the target regions of RNA and better recognising of SARS-CoV-2 genome sequence to design oligonucleotide-based drugs against the genetic structure of the virus.