A novel front in sustainable microbial management: computational analysis of curcumin and mangiferin's synergistic action against Bacillus anthracis.

Background: Microorganisms are crucial in our ecosystem, offering diverse functions and adaptability. The UNGA Science Summit has underscored the importance of understanding microbes in alignment with the UN Sustainable Development Goals. Bacillus anthracis poses significant challenges among various microorganisms due to its harmful effects on both soil and public health. Our study employed computational techniques to investigate the inhibitory effects of curcumin and mangiferin on Bacillus anthracis, with the aim of presenting a novel bio-based approach to microbial management. Methods: Employing high-throughput screening, we identified potential binding sites on B. anthracis. Molecular docking revealed that curcumin and mangiferin, when synergistically combined, exhibited strong binding affinities at different sites on the bacterium. Our findings demonstrated a significant drop in binding free energy, indicating a stronger interaction when these compounds were used together. Findings: Results of Molecular docking indicated binding energies of -8.45 kcal/mol for mangiferin, -7.68 kcal/mol for curcumin, and a notably higher binding energy of -19.47 kcal/mol for the combination of mangiferin and curcumin with CapD protein. Molecular dynamics simulations further validated these interactions, demonstrating increased stability and structural changes in the bacterium. Conclusion: This study highlights the effectiveness of natural compounds like curcumin and mangiferin in microbial management, especially against challenging pathogens like B. anthracis. It emphasizes the potential of sustainable, nature-based solutions and calls for further empirical research to expand upon these findings.

Enhancing drought tolerance in cauliflower (Brassica oleracea var. botrytis) by targeting LFY transcription factor modulation via the ethylene precursor, ACCA: an innovative computational approach.

Background: Brassica oleracea var. botrytis is an annual or biennial herbaceous vegetable plant in the Brassicaceae family notable for its edible blossom head. A lot of effort has gone into finding defense-associated proteins in order to better understand how cauliflower and pathogens interact. Endophytes are organisms that live within the host plant and reproduce. Endophytes are bacteria and fungi that reside in plant tissues and can either help or harm the plant. Several species have aided molecular biologists and plant biotechnologists in various ways. Water is essential for a healthy cauliflower bloom. When the weather is hot, this plant dries up, and nitrogen scarcity can be detrimental to cauliflower growth. Objective: The study sought to discern plant growth promoting (PGP) compounds that can amplify drought resilience and boost productivity in cauliflower. Methods: Investigations were centered on endophytes, microorganisms existing within plant tissues. The dual role of beneficial and detrimental Agrobacterium was scrutinized, particularly emphasizing the ethylene precursor compound, 1-amino-cyclopropane-1-carboxylic acid (ACCA). Results: ACCA possessed salient PGP traits, particularly demonstrating a pronounced enhancement of drought resistance in cauliflower plants. Specifically, during the pivotal marketable curd maturity phase, which necessitates defense against various threats, ACCA showcased a binding energy of -8.74 kcal/mol. Conclusion: ACCA holds a significant promise in agricultural productivity, with its potential to boost drought resistance and cauliflower yield. This could be particularly impactful for regions grappling with high temperatures and possible nitrogen shortages. Future research should explore ACCA's performance under diverse environmental settings and its applicability in other crops.

Hymenopteran parasitoid complex and fall armyworm: a case study in eastern India.

Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) has significantly affected maize crop yields, production efficiency, and farmers' incomes in the Indian Eastern Gangetic Plains region since it was first observed in India in 2018. A lack of awareness by maize growers of the appropriate selection, method, and timing of insecticide application not only creates a barrier to sustainable FAW control but also contributes to increased environmental pollution, reduced human health and increased production costs. We demonstrated that FAW inflicted the most damage in early whorl growth stage of maize, regardless of whether chemical insecticides were applied. FAW egg masses and larvae collected from maize fields in which no insecticides had been sprayed showed high parasitism rates by parasitoid wasps; in contrast fields that had been sprayed had much lower rates of parasitism on FAW. Ten hymenopteran parasitoids were observed in maize fields across the study region, suggesting a diversity of natural methods to suppress FAW in maize at different growth stages. These included two FAW egg parasitoids and eight FAW larval parasitoids. Microplitis manilae Ashmead was the most abundant FAW larval parasitoid species, and Telenomus cf. remus was the dominant FAW egg parasitoid species. Endemic FAW parasitoids such as those observed in this study have great potential as part of a sustainable, cost-effective agroecological management strategy, which can be integrated with other methods to achieve effective control of FAW.

Estimating optimum and base selection indices in plant and animal breeding programs by development new and simple SAS and R codes.

Selection of desirable genotypes or progenies is perhaps the most important practical method in plant and animal breeding programs. The selection index method is the most useful method to choose superior genotypes based on using simultaneous several traits. The optimum and base selection indices are the two indicators that are most used in plant and animal breeding. In this paper, a simple and practical code was developed for the analysis of optimum, base, and Pesek and Baker selection indices. Four different criteria were used to evaluate the selection index, and the phenotypic and genotypic variance-covariance matrix of traits was obtained based on statistical or genetical design. Moreover, an index that was more efficient on these coefficients was used for the breeding program. The results showed that simultaneous selection for the important traits desired by the breeder through economic values such as heritability, genetic, or phenotypic correlation is the most effective method for selecting the best genotypes. Therefore, the best progeny or genotype can be selected to use in breeding programs. This program provides detailed information on selection indices of segregation and natural populations involving any number of individuals or genotypes. These codes are much easier and simpler than other programs and provide more information than other programs. This code is easy to execute in both R and SAS programs.

Lupenone, a wonder chemical obtained from Euphorbia segetalis to boost affinity for the transcriptional factor escalating drought-tolerance in Solanum Lycopersicum: A cutting-edge computational biology approach.

Drought is the single greatest abiotic factor influencing crop yield worldwide. Plants remain in one area for extended periods, making them vulnerable to natural and man-made influences. Understanding plant drought responses will help us develop strategies for breeding drought-resistant crops. Large proteome analysis revealed that leaf and root tissue proteins respond to drought differently depending on the plant's genotype. Commonly known as tomatoes, Solanum Lycopersicum is a globally important vegetable crop. However, drought stress is one of the most significant obstacles to tomato production, making the development of cultivars adapted to dry conditions an essential goal of agricultural biotechnology. Breeders have put quite a lot of time and effort into the tomato to increase its productivity, adaptability, and resistance to biotic and abiotic challenges. However, conventional tomato breeding has only improved drought resistance due to the complexity of drought traits. The resilience of tomatoes under drought stress has been the subject of extensive study. Using contemporary sequencing approaches like genomics, transcriptomics, proteomics, and metabolomics has dramatically aided in discovering drought-responsive genes. One of the most prominent families of plant transcription factors, WRKY genes, plays a crucial role in plant growth and development in response to natural and abiotic stimuli. To develop plants that can withstand both biotic and abiotic stress, understanding the relationships between WRKY-proteins (transcription factors) and other proteins and ligands in plant cells is essential. This is despite the fact that tomatoes have a long history of domestication. This research aims to utilize Lupenone, a hormone produced in plant roots in response to stress, to increase drought resistance in plants. Lupenone exhibits a strong affinity for the WRKY protein at -9.64 kcal/mol. Molecular docking and modeling studies show that these polyphenols have a significant role in making Solanum Lycopersicum drought-resistant and improving the quality of its fruit. As a result of climate change, droughts are occurring more frequently and persisting for more extended periods, making it necessary to breed crops resistant to drought. While considerable variability for tolerance exists in wild cousins, little is known about the processes and essential genes influencing drought tolerance in cultivated tomato species.

Evaluation of basil (Ocimum basilicum) accessions under different drought conditions based on yield and physio-biochemical traits.

BACKGROUND: Basil is one of the most famous herbs, which has broad usage as a fresh vegetable and therapeutic and pharmaceutical services. The main abiotic stress limiting basil production globally is drought. As a result, appropriate drought screening-which effectively separates high-yielding but drought-sensitive genotypes from drought-tolerant genotypes-is necessary for the optimal selection of high-yielding basil cultivars under drought stress conditions. So, a split plot experiment with three replications based on a completely randomized design were carried out in a pot under field conditions for this investigation. Water levels (full irrigation or control, moderate stress, and severe stress) were assigned as main plots, while 22 basil accessions were given as sub-plots. In this study, leaf yield as well as physio-biochemical traits had measured on accessions. RESULTS: Our results revealed large variation in yield, essential oil (%), protein, proline, chlorophyll, total phenol and flavonoids traits across the 22 accessions. The percentage of leaf yield reduction in moderate drought stress than normal conditions showed that G1 (-6.5%), G17 (-7.05%), G20 (-9.01%), and G12 (-10.9%) accessions had the least changes, respectively. Although in severe drought stress than normal conditions, the G1 (-32.01%), G12 (-33.12%), G4 (-33.24%), G7 (-34.11%), and G17 (-34.93%) accessions had the least amount of change in plant leaf yield, respectively. Furthermore, the highest yield reduction occurred in moderate and severe stress conditions in G18 (-25.36%) and G8 (-42.98%) accessions, respectively. Cluster analysis based on the ward method in both conditions (moderate and severe drought conditions) placed the accessions in three groups, and accessions were identified as tolerant, whose average traits in that group were higher than the total average. The principal component analysis also showed that in moderate drought conditions, the first two components explained about 95.28% of the total variation, while in severe drought conditions, these two components explained about 96.37% of the total variation. CONCLUSIONS: The different multivariate analyses (cluster analysis, PCA, mean comparison) were used to identify tolerant and sensitive accessions based on all traits. The accessions G3, G4, G6, and G7 were found to be tolerant to stress, while G10, G15, G16, and G20 were found to be sensitive to drought. These accessions are a useful step in producing drought-tolerant, high-yielding accessions and can be utilized in breeding programs for basil.

Unveiling a novel terpolymer-metal complex: A detailed exploration of synthesis, characterization, and its potential as an antimicrobial and antioxidant agent.

In an innovative approach to push the boundaries of antimicrobial and antioxidant strategies, we present the synthesis and characterization of a novel terpolymer derived from N-Phenyl-p-phenylenediamine and 2-aminopyrimidine with formaldehyde in the presence of dimethylformamide as a reaction medium through polycondensation technique. Leveraging this terpolymer as a ligand, we introduce an intriguing terpolymer-metal complex, created with Ni (II) metal ion. In our pursuit to validate the structure and properties of these substances, we performed meticulous characterizations using important spectral studies such as FTIR, electronic, and 1H NMR spectroscopy. This provided us with a unique fingerprint for the (N-Phenyl-p-phenylenediamine-2-aminopyrimidine-formaldehyde) terpolymeric ligand (PAF) and its metal complex. In addition, the molecular weights of PAF terpolymer were established using gel permeation chromatography. Upon investigation, PAF terpolymer and PAF-Ni complex exhibited impressive antimicrobial activity, tested by the disc-diffusion technique. Both demonstrated potency against a range of harmful bacterial and fungal strains, including Staphylococcus aureus, Escherichia coli, Candida albicans, and Aspergillus niger. In an extension to their biological applications, we evaluated the free radical scavenging activity of PAF terpolymer and PAF-Ni complex using the DPPH assay. The complex PAF-Ni showcased an enhanced scavenging activity 73.94% (IC50 = 17.58) compared to the ligand PAF 63.06% (IC50 = 27.61) at 100 µg/ml indicating its potential role in oxidative stress management.

Optimizing hybrid vigor: a comprehensive analysis of genetic distance and heterosis in eggplant landraces.

Introduction: This study explored the molecular characterization of 14 eggplant (brinjal) genotypes to evaluate their genetic diversity and the impact of heterosis. As eggplant is a vital horticultural crop with substantial economic and nutritional value, a comprehensive understanding of its genetic makeup and heterosis effects is essential for effective breeding strategies. Our aim was not only to dissect the genetic diversity among these genotypes but also to determine how genetic distance impacts heterotic patterns, which could ultimately help improve hybrid breeding programs. Methods: Genetic diversity was assessed using 20 SSR markers, and the parental lines were grouped into five clusters based on the Unweighted Pair Group Method of Arithmetic Means (UPGMA). Heterosis was examined through yield and yield-related traits among parents and hybrids. Results: Polymorphisms were detected in eight out of the twenty SSR markers across the parental lines. Notably, a high genetic distance was observed between some parents. The analysis of yield and yield-related traits demonstrated significant heterosis over mid, superior, and standard parents, particularly in fruit yield per plant. Two crosses (RKML-26 X PPC and RKML1 X PPC) displayed substantial heterosis over mid and better parents, respectively. However, the positive correlation between genetic distance and heterosis was only up to a certain threshold; moderate genetic distance often resulted in higher heterosis compared to very high genetic distance. Discussion: These findings emphasize the critical role of parental selection in hybrid breeding programs. The results contribute to the understanding of the relationship between genetic distance and heterosis, and it is suggested that future research should delve into the genetic mechanisms that drive heterosis and the effect of genetic distance variance on heterosis. The insights drawn from this study can be harnessed to enhance crop yield and economic value in breeding programs.

Exploring the efficacy of 1-amino-cyclopropane-1-carboxylic acid (ACCA) as a natural compound in strengthening maize resistance against biotic and abiotic stressors: an empirical computational study.

Objective: This study aims to understand plant-bacteria interactions that enhance plant resistance to environmental stressors, with a focus on maize (Zea mays L.) and its vulnerability to various pathogenic organisms. We examine the potential of 1-amino-cyclopropane-1-carboxylic acid (ACCA) as a compound to boost maize's resilience against stressors and pathogens. Background: With the growing global population and increased food demand, the study of endophytes, comprising bacteria and fungi, becomes crucial. They reside within plant tissues, affecting their hosts either beneficially or detrimentally. Agrobacteria are of specific interest due to their potential to contribute to developing strategies for plant resistance enhancement. Methods: We conducted exhaustive research on the defense-related proteins and mechanisms involved in maize-pathogen interactions. The efficacy of ACCA as a natural-compound that could enhance maize's resistance was examined. Results: Our research indicates that ACCA, having a binding energy of -9.98 kcal/mol, successfully strengthens maize resistance against pathogenic assaults and drought stress. It plays a crucial protective role in maize plants as they mature, outperforming other ligands in its effectiveness to improve productivity and increase yield. Conclusion: Applying ACCA to maize plants has considerable potential in enhancing their resilience and tolerance to stress, proving to be an effective strategy to boost crop yield and productivity. This could help address the increasing global food demand. However, more research is needed to optimize ACCA application methods and to gain a comprehensive understanding of its long-term effects on maize cultivations and the environment.

Morphometric frequency and spectrum of gamma-ray-induced chlorophyll mutants identified by phenotype and development of novel variants in lentil (Lens culinaris Medik.).

Genetic variations are a crucial source of germplasm heterogeneity, as they contribute to the development of new traits for plant breeding by offering an allele resource. Gamma rays have been widely used as a physical agent to produce mutations in plants, and their mutagenic effect has attracted much attention. Nonetheless, few studies have examined the whole mutation spectrum in large-scale phenotypic evaluations. To comprehensively investigate the mutagenic effects of gamma irradiation on lentils, biological consequences on the M1 generation and substantial phenotypic screening on the M2 generation were undertaken. Additionally, the study followed the selected mutants into the M3 generation to evaluate the agronomic traits of interest for crop improvement. Seeds of lentil variety Moitree were irradiated with a range of acute gamma irradiation doses (0, 100, 150, 200, 250, 300, and 350 Gy) to induce unique genetic variability. This research focused on determining the GR50 value while considering seedling parameters and examining the status of pollen fertility while comparing the effects of the gamma irradiation dosages. The GR50 value was determined to be 217.2 Gy using the seedling parameters. Pollens from untreated seed-grown plants were approximately 85% fertile, but those treated with the maximum dosage (350 Gy) were approximately 28% fertile. Numerous chlorophyll and morphological mutants were produced in the M2 generation, with the 300 Gy -treated seeds being the most abundant, followed by the 250 Gy -treated seeds. This demonstrated that an appropriate dosage of gamma rays was advantageous when seeking to generate elite germplasm resources for one or multiple traits. Selected mutants in the M3 generation showed improved agronomic traits, including plant height, root length, number of pods per plant, and yield per plant. These investigations will contribute to a comprehensive understanding of the mutagenic effects and actions of gamma rays, providing a basis for the selection and design of suitable mutagens. This will facilitate the development of more controlled mutagenesis protocols for plant breeding and help guide future research directions for crop improvement using radiation-induced mutation breeding techniques.

Action of the plant-based essential oil-derived compound Taxol for improvising drought tolerance in Eucalyptus by modulating the VIT1 channel protein: a cutting-edge computational approach.

Background: Drought poses a significant threat to the growth and survival of woody plants, especially Eucalyptus grandis, which is known for its slow and steady growth. Understanding the physiological and molecular responses of E. grandis to abiotic stress is essential for developing strategies to improve its drought resistance. This study focuses on the potential vulnerability of E. grandis during the initial months of root system proliferation and investigates the role of the essential oil-derived compound Taxol in enhancing its drought resistance. Methodology: A comprehensive analysis was performed on various aspects of E. grandis, including morphological features, photosynthetic rates, pigment concentrations, nitrogenous components, and lipid peroxidation. Furthermore, the study examined the accumulation of soluble carbohydrates, proline, and antioxidant enzymes as part of the tree's response to drought stress. Molecular docking and molecular dynamics simulations were conducted to determine the binding affinity of Taxol, an essential oil derived from Taxus brevifolia, with the VIT1 protein in E. grandis. Results: E. grandis displayed remarkable resilience to drought by accumulating vast reserves of soluble carbohydrates, proline, and antioxidant enzymes. The essential oil-derived compound Taxol exhibited a strong binding affinity with the VIT1 protein (-10.23 kcal/mol), suggesting its potential role in enhancing the tree's drought resistance. Conclusion: This study reveals the pivotal role of Taxol in augmenting the resilience of E. grandis against drought stress and improving its therapeutic oil properties. Emphasizing the tree's inherent tolerance during its susceptible early stages is crucial in promoting sustainable agriculture and forestry practices. The findings underscore the importance of advanced scientific research in uncovering the concealed capabilities of robust trees like E. grandis as we continue our pursuit of a sustainable future.

Enriching drought resistance in Solanum lycopersicum using Abscisic acid as drought enhancer derived from Lygodium japonicum: A new-fangled computational approach.

Introduction: Drought is the largest abiotic factor impacting agriculture. Plants are challenged by both natural and artificial stressors because they are immobile. To produce drought-resistant plants, we need to know how plants react to drought. A largescale proteome study of leaf and root tissue found drought-responsive proteins. Tomato as a vegetable is grown worldwide. Agricultural biotechnology focuses on creating drought-resistant cultivars. This is important because tomato drought is so widespread. Breeders have worked to improve tomato quality, production, and stress resistance. Conventional breeding approaches have only increased drought tolerance because of drought's complexity. Many studies have examined how tomatoes handle drought. With genomics, transcriptomics, proteomics, metabolomics, and modern sequencing technologies, it's easier to find drought-responsive genes. Method: Biotechnology and in silico studies has helped demonstrate the function of drought-sensitive genes and generate drought-resistant plant types. The latest tomato genome editing technology is another. WRKY genes are plant transcription factors. They help plants grow and respond to both natural and artificial stimuli. To make plants that can handle stress, we need to know how WRKY-proteins, which are transcription factors, work with other proteins and ligands in plant cells by molecular docking and modeling study. Result: Abscisic acid, a plant hormone generated in stressed roots, was used here to make plants drought-resistant. Abscisic acid binds WRKY with binding affinity -7.4kcal/mol and inhibitory concentration (Ki) 0.12 microM. Discussion: This study aims to modulate the transcription factor so plants can handle drought and stress better. Therefore, polyphenols found to make Solanum lycopersicum more drought-tolerant.

The Enhanced Affinity of WRKY Reinforces Drought Tolerance in Solanum lycopersicum L.: An Innovative Bioinformatics Study.

In the scenario of global climate change, understanding how plants respond to drought is critical for developing future crops that face restricted water resources. This present study focuses on the role of WRKY transcription factors on drought tolerance in tomato, Solanum lycopersicum L., which is a significant vegetable crop. WRKY transcription factors are a group of proteins that regulate a wild range of growth and developmental processes in plants such as seed germination and dormancy and the stress response. These transcription factors are defined by the presence of a DNA-binding domain, namely, the WRKY domain. It is well-known that WRKY transcription factors can interact with a variety of proteins and therefore control downstream activities. It aims to simulate the effect of curcumin, a bioactive compound with regulatory capacity, on the protein-protein interaction events by WRKY transcription factors with an emphasis on drought stress. It was found that curcumin binds to WRKY with an energy of -11.43 kcal/mol with inhibitory concentration (Ki) 0.12 mM and has the potential to improve fruit quality and reinforce drought tolerance of S. lycopersicum, according to the results based on bioinformatics tools. The root means square deviation (RMSD) of the C-α, the backbone of 2AYD with ligand coupled complex, displayed a very stable structure with just a little variation of 1.89 Å. MD simulation trajectory of Cα atoms of 2AYD bound to Curcumin revealed more un-ordered orientation in PC1 and PC10 modes and more toward negative correlation from the initial 400 frames during PCA. Establishing the binding energies of the ligand-target interaction is essential in order to characterize the compound's binding affinity to the drought transcription factor. We think we have identified a phyto-agent called curcumin that has the potential to enhance the drought tolerance. Compared to the part of the mismatch repair-base technique that can be used to fix drought related genes, curcumin performed better in a drop-in crop yield over time, and it was suggested that curcumin is a potential candidate factor for improving drought tolerance in tomatoes, and it needs future validation by experiments in laboratory and field.

Wheat ergot fungus-derived and modified drug for inhibition of intracranial aneurysm rupture due to dysfunction of TLR-4 receptor in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a form of dementia that strikes elderly people more frequently than it does younger people. The cognitive skills and memory of Alzheimer's sufferers continue to deteriorate over time. Recent studies have shown that patients with AD have greater amounts of inflammatory markers in their bodies, which suggests that inflammation occurs early on in the progression of the disease. There is a possibility that Aß oligomers and fibrils can be recognised by TLRs, in addition to the microglial receptors CD14, CD36, and CD47. When Aß binds to either CD36 or TLR4, it sets off a chain reaction of inflammatory chemokines and cytokines that ultimately results in neurodegeneration. Diabetes and Alzheimer's disease have both been recently related to TLR4. The activation of TLR4 has been connected to a variety of clinical difficulties that are associated with diabetes, in addition to the internal environment of the body and the microenvironment of the brain. TLR4 inhibitors have been shown in clinical investigations to not only lessen the likelihood of getting sick but also to increase the average longevity. RESULT: In this work we used molecular docking and molecular dynamics modelling to investigate the effectiveness of FDA-approved antidiabetic plant derived drugs in combating the TLR4 receptor. Molecular docking experiments were used to make a prediction regarding the most important interactions involving 2-Bromoergocryptine Mesylate. With a binding affinity of -8.26 kcal/mol, it stood out from the other candidates as the one with the greatest potential. To verify the interaction pattern that takes place between 2-Bromoergocryptine Mesylate and the TLR4 receptor, a molecular dynamic simulation was run at a time scale of 150 nanoseconds. Because of this, 2-Bromoergocryptine Mesylate was able to make substantial contact with the active site, which led to increased structural stability during the process of the complex's dynamic development. CONCLUSION: As a result of this, the results of our research may be relevant for future research into the efficacy of 2-bromoergocryptine mesylate as a potential lead treatment for TLR4 receptors in intracranial aneurysm rupture in AD.

Enhancing plant-derived smart nano inhibitor in targeting mammalian target of rapamycin (mTOR) in breast cancer using Curcuma longa-derived compound curcumin.

Breast cancer is a diverse female malignancy; its classification is based on clinical evidence and pathological elucidation. Large public drug screening data databases combined with transcriptome measures have helped develop predictive computational models. Breast cancer is frequent among women worldwide. Several genes increase breast cancer risk. The Mammalian Target of Rapamycin (popularly known as mTOR) is a risk factor mutated in numerous breast carcinoma types. This has caught the scientific community's focus, which is attempting to generate creative, potent, and bio-available ligands for future anti-cancer treatments to establish a practical therapeutic approach. mTOR is a protein kinase involved in cell proliferation, survival, metabolism, and immune response. Activating mTOR promotes cancer growth and spread. To generate a bioavailable and effective mTOR inhibitor, we used computer-aided drug design to study chromones and flavonoids, two naturally occurring chemicals with many biological activities. We used Curcuma longaderived tiny nano-molecules, which can be coated using liposomes to target mTOR to prevent breast cancer growth. The significant interactions of Curcumin were anticipated using molecular docking. It had the highest binding affinity at -12.26 kcal/mol. 100 nanoseconds of molecular dynamic modelling confirmed Curcumin and mTOR receptor interaction. Liposomes are a form of medicine carrier. To improve healthcare, more liposome-like nanostructures are being made. Nanostructures' interactions with living creatures are being studied. Half-life, tissue accumulation, and toxicity have been studied. Future medication distribution may use nanocarriers having a liposome-like form, enabling targeted nano-delivery. Curcumin's interaction with the active site increased the complex's structural stability during its expansion. Our results may help future investigations of Curcumin's efficacy as a possible lead treatment targeting mTOR receptors in breast cancer. Using Curcumin as a potential anti-cancer drug with lipid-coated nano-particles allows for tailored administration.

Yield stability and economic heterosis analysis in newly bred sunflower hybrids throughout diverse agro-ecological zones.

Exploration of heterosis is a strategy for enhancing sunflower yield and productivity. In India, the greatest constraints on sunflower production are stagnant and inconsistent yields. By raising them in a variety of ecological conditions, stable per-se performance with the highest yielding potential sunflower hybrids were selected. Sustainable agriculture requires the use of desirable hybrids with high seed yields and oil content too. By making three distinct crossing sets from 32 sunflower genotypes, 11 cytoplasmic male sterility (CMS), and 21 restorer lines, a total of 124 hybrids were developed (comprising both lines and tester). After extensive field evaluation of all hybrids, only eight superior F1s belonging to all three sets, as well as the three national control hybrids KBSH-53, LSFH-171, and DRSH-1, were selected for stability analysis in four agro-ecological regions of West Bengal, India viz., Nimpith, Baruipur, Bankura, and Berhapore. The genetic stability of several phenotypic characters was assessed using statistical models that examine genotype-environment interaction (G × E) in multi-locational yield trials. In this experiment, the performance of hybrids under various environmental circumstances over two-year periods was measured using regression coefficient (bi) and deviations from regression (S2di). With the exception of genotypes CMS-852A × EC-601751 for volume weight (0.9335) and CMS-302A × EC-623011 for head diameter (0.0905) and volume weight (0.6425), all sunflower genotypes for all concerned traits had extremely minor and negligible deviations from regression (S2di), which showed significant values. The genotypes having insignificant values of S2di were more stable. The economic heterosis of these novel hybrids was also quantified. CMS-302A × EC-623011 in which seed yield was recorded 20.90, 20.91, 20.95 and 20.90% higher than DRSH-1 at Nimpith, Baruipur, Bankura and PORS (Berhampur), respectively. The research revealed that CMS-302A × EC-623011, CMS-853A × EC-623027 and P-2-7-1A × EC-512682 exhibited good seed production and stability for critical agronomic parameters in addition to oil content. As a result, the current researches enlighten to find out how stable the expression of important economic traits in sunflower hybrids is.

An exopolysaccharide-producing novel Agrobacterium pusense strain JAS1 isolated from snake plant enhances plant growth and soil water retention.

A peculiar bacterial growth was very often noticed in leaf-initiated tissue cultures of Sansevieria trifasciata, a succulent belonging to the Asparagaceae family. The isolate left trails of some highly viscous material on the walls of the suspension vessels or developed a thick overlay on semisolid media without adversities in plant growth. FTIR identified this substance to be an extracellular polysaccharide. Various morphological, biochemical tests, and molecular analyses using 16S rRNA, atpD, and recA genes characterized this isolate JAS1 as a novel strain of Agrobacterium pusense. Its mucoidal growth over Murashige and Skoog media yielded enormous exopolysaccharide (7252 mg l-1), while in nutrient agar it only developed fast-growing swarms. As a qualifying plant growth-promoting bacteria, it produces significant indole-3-acetic acid (86.95 mg l-1), gibberellic acid (172.98 mg l-1), ammonia (42.66 µmol ml-1). Besides, it produces siderophores, 1-aminocyclopropane-1-carboxylic acid deaminase, fixes nitrogen, forms biofilms, and productively solubilizes soil inorganic phosphates, and zinc. Under various treatments with JAS1, wheat and chickpea resulted in significantly enhanced shoot and root growth parameters. PGP effects of JAS1 positively enhanced plants' physiological growth parameters reflecting significant increments in overall chlorophyll, carotenoids, proline, phenols, flavonoids, and sugar contents. In addition, the isolated strain maintained both plant and soil health under an intermittent soil drying regime, probably by both its PGP and EPS production attributes, respectively.

A comprehensive review and meta-analysis of recent advances in biotechnology for plant virus research and significant accomplishments in human health and the pharmaceutical industry.

Secondary metabolites made by plants and used through their metabolic routes are today's most reliable and cost-effective way to make pharmaceuticals and improve health. The concept of genetic engineering is used for molecular pharming. As more people use plants as sources of nanotechnology systems, they are adding to this. These systems are made up of viruses-like particles (VLPs) and virus nanoparticles (VNPs). Due to their superior ability to be used as plant virus expression vectors, plant viruses are becoming more popular in pharmaceuticals. This has opened the door for them to be used in research, such as the production of medicinal peptides, antibodies, and other heterologous protein complexes. This is because biotechnological approaches have been linked with new bioinformatics tools. Because of the rise of high-throughput sequencing (HTS) and next-generation sequencing (NGS) techniques, it has become easier to use metagenomic studies to look for plant virus genomes that could be used in pharmaceutical research. A look at how bioinformatics can be used in pharmaceutical research is also covered in this article. It also talks about plant viruses and how new biotechnological tools and procedures have made progress in the field.

Principal Component and Path Analysis for Trait Selection Based on the Assessment of Diverse Lentil Populations Developed by Gamma-Irradiated Physical Mutation.

Lentil is a notable legume crop valued for its high protein, vitamin, mineral, and amino acid (lysine and tryptophan) content. This crop has a narrow genetic base due to the formation of gene pool barriers during interspecific hybridization within and across species. Mutagenesis may be seen as a novel and alternative breeding technique for the production of new diversity. For the identification of new alleles, the creation of mutants followed by selection in subsequent generations would be necessary. Induction of mutation in lentil cv. Moitree by gamma rays therefore produced high variation for the majority of quantitative measures examined. Henceforth, principal component analysis (PCA) and path coefficient analysis were conducted to identify and exclude redundant mutant genotypes with similar traits as the success of breeding is dependent on understanding the relationship between morpho-agronomic traits and seed yield. As shown by the findings of this research, the total quantity of pods per mutant plant should be given considerable priority. The identified mutant genotypes, such as lines 24, 43, 28, 33, and 10, may be used as parents in future breeding or released directly following trials.

Multichannel CNN Model for Biomedical Entity Reorganization.

Biomedical researchers and biologists often search a large amount of literature to find the relationship between biological entities, such as drug-drug and compound-protein. With the proliferation of medical literature and the development of deep learning, the automatic extraction of biological entity interaction relationships from literature has shown great potential. The fundamental scope of this research is that the approach described in this research uses technologies like dynamic word vectors and multichannel convolution to learn a larger variety of relational expression semantics, allowing it to detect more entity connections. The extraction of biological entity relationships is the foundation for achieving intelligent medical care, which may increase the effectiveness of intelligent medical question answering and enhance the development of precision healthcare. In the past, deep learning methods have achieved specific results, but there are the following problems: the model uses static word vectors, which cannot distinguish polysemy; the weight of words is not considered, and the extraction effect of long sentences is poor; the integration of various models can improve the sample imbalance problem, the model is more complex. The purpose of this work is to create a global approach for eliminating different physical entity links, such that the model can effectively extract the interpretation of the expression relationship without having to develop characteristics manually. To this end, a deep multichannel CNN model (MC-CNN) based on the residual structure is proposed, generating dynamic word vectors through BERT (Bidirectional Encoder Representation from Transformers) to improve the accuracy of lexical semantic representation and uses multihead attention to capture the dependencies of long sentences and by designing the Ranking loss function to replace the multimodel ensemble to reduce the impact of sample imbalance. Tested on multiple datasets, the results show that the proposed method has good performance.