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The complexity of data has burgeoned to such an extent that scientists of every realm are encountering the incessant challenge of data management. Modern-day analytical approaches with the help of free source tools and programming languages have facilitated access to the context of the various domains as well as specific works reported. Here, with this article, an attempt has been made to provide a systematic analysis of all the available reports at PubMed on Proteome using text mining. The work is comprised of scientometrics as well as information extraction to provide the publication trends as well as frequent keywords, bioconcepts and most importantly gene–gene co-occurrence network. Out of 33,028 PMIDs collected initially, the segregation of 24,350 articles under 28 Medical Subject Headings (MeSH) was analyzed and plotted. Keyword link network and density visualizations were provided for the top 1000 frequent Mesh keywords. PubTator was used, and 322,026 bioconcepts were able to extracted under 10 classes (such as Gene, Disease, CellLine, etc.). Co-occurrence networks were constructed for PMID-bioconcept as well as bioconcept–bioconcept associations. Further, for creation of subnetwork with respect to gene–gene co-occurrence, a total of 11,100 unique genes participated with mTOR and AKT showing the highest (64) number of connections. The gene p53 was the most popular one in the network in accordance with both the degree and weighted degree centrality, which were 425 and 1414, respectively. The present piece of study is an amalgam of bibliometrics and scientific data mining methods looking deeper into the whole scale analysis of available literature on proteome.

The liver is not only involved in metabolism and detoxification, but also participate in innate immune function and thus exposed to frequent target Thus, they are the frequent target of physical injury. Interestingly, liver has the unique ability to regenerate and completely recoup from most acute, non-iterative situation. However, multiple conditions, including viral hepatitis, non-alcoholic fatty liver disease, long term alcohol abuse and chronic use of medications can cause persistent injury in which regenerative capacity eventually becomes dysfunctional resulting in hepatic scaring and cirrhosis. Despite the recent therapeutic advances and significant development of modern medicine, hepatic diseases remain a health problem worldwide. Thus, the search for the new therapeutic agents to treat liver disease is still in demand. Many synthetic drugs have been demonstrated to be strong radical scavengers, but they are also carcinogenic and cause liver damage. Present day various hepatic problems are encountered with number of synthetic and plant based drugs. Nexavar (sorafenib) is a chemotherapeutic medication used to treat advanced renal cell carcinoma associated with several side effects. There are a few effective varieties of herbal preparation like Liv-52, silymarin and Stronger neomin phages (SNMC) against hepatic complications. Plants are the huge repository of bioactive secondary metabolites viz; phenol, flavonoid, alkaloid etc. In this review we will try to present exclusive study on phenolics with its mode of action mitigating liver associated complications. And also its future prospects as new drug lead.

Chrysanthemums, commonly referred to as “mums” or “chrysanths,” represent a taxonomically diverse genus within the family Asteraceae, renowned for their multifunctional applications in ornamental horticulture, phytochemical industries, and ethnobotanical use. Despite the genus’s widespread cultivation and economic importance, its auxiliary improvement still hinges on modern breeding and biotechnological interventions. Such innovations are vital for the development of a resilient floriculture sector amid climatic and post-harvest challenges. Developing strategic roadmaps and policies requires evidence-based evaluations of research progress, scientific hotspots, and existing knowledge gaps. In the current investigation, bibliometric analytics and scientometric mapping were employed using metadata extracted from keywords, titles, abstracts, and journal sources to visualize research dynamics and trend trajectories in chrysanthemum research using PubMed-indexed literature up to June 2025. The annual publication growth rate is 3.33%, with a notable surge over the past two decades. China, South Korea, and Japan emerge as dominant contributors to chrysanthemum research, driven by strong cultural affinity, state-supported floricultural R&D infrastructure, and accelerated breeding programs. China also serves as a central node in international collaborative networks, particularly in multi-authored, cross-border publications. Keyword co-occurrence analysis reveals “morifolium” as the most frequently cited species, reflecting its global dominance in terms of cultivation. Thematic cluster analysis underscores an emerging research avenue exploring chrysanthemums as nutraceutical-rich edible flowers, contributing to functional foods and dietary diversification. However, reports also flag potential toxicity risks upon unregulated consumption, especially for companion animals and sensitive populations. Bio-concept mining and knowledge graph modeling stratified the research corpus into four primary domains. These domains reflect the convergence of multidisciplinary efforts in chrysanthemum research, including metabolomics, transcriptomics, and stress physiology. The co-occurrence networks of emerging concepts indicate promising frontiers and highlight existing literature voids, thereby providing a foundation for targeted investigations to unlock the genus’s biotechnological, agronomic, and industrial potential.

Major abiotic stress factors such as drought, salinity, hypoxia, and extreme temperatures along with rapid global climate change have had a huge negative impact on agricultural productivity. Understanding the abiotic stress-responsive molecular mechanisms and its associated proteins is extremely important to advance our knowledge towards developing multiple abiotic stress tolerance in plants. Firstly, basic understanding at transient level would be a vital foundation to accomplish this goal. Therefore, our present study aimed at understanding the sub-cellular localization of Eukaryotic Initiation Factor 4A-III (AteIF4A-III), a key DEAD-box RNA helicase, and Always Early 4 (AtALY4), an mRNA export factor, and their in vivo protein-protein interaction with major abiotic stress–associated proteins under control and multiple abiotic stress conditions. AteIF4A-III and AtALY4 were localized to the nucleus as evident by transient protoplast assay. AteIF4A-III has shown strong interaction with a negative regulator of multiple abiotic stresses, Stress Response Suppressor 1 (AtSTRS1) in Bi-FC assay. Further, the flow cytometry analysis has shown the strong interaction between them. Interestingly, under multiple abiotic stress treatment, the interacting partners were rapidly re-localized from nucleus to cytoplasm and cytoplasmic space. Similar results were observed when N- and C-terminal fusions of AteIF4A-III and AtALY4 treated under multiple abiotic stresses. Our study reveals that AteIF4A-III, AtALY4, and abiotic stress–associated protein AtSTRS1 are among the key proteins associated with multiple abiotic stress responses in plants.

The affiliation 2 in the published article was Academy of Scientific and Innovative Research (AcSIR), CSIR-NEIST Campus, Jorhat, Assam 785,006, India.

The NADPH-dependent HC-toxin reductases (HCTR1 and 2) encoded by enzymatic class of disease resistance homologous genes (Hm1 and Hm2) protect maize by detoxifying a cyclic tetrapeptide, HC-toxin, secreted by the fungus Cochliobolus carbonum race 1(CCR1). Unlike the other classes' resistance (R) genes, HCTR-mediated disease resistance is an inimitable mechanism where the avirulence (Avr) component from CCR1 is not involved in toxin degradation. In this study, we attempted to decipher cofactor (NADPH) recognition and mode of HC-toxin binding to HCTRs through molecular docking, molecular dynamics (MD) simulations and binding free energy calculation methods. The rationality and the stability of docked complexes were validated by 30-ns MD simulation. The binding free energy decomposition of enzyme-cofactor complex was calculated to find the driving force behind cofactor recognition. The overall binding free energies of HCTR1-NADPH and HCTR2-NADPH were found to be -616.989 and -16.9749 kJ mol-1 respectively. The binding free energy decomposition revealed that the binding of NADPH to the HCTR1 is mainly governed by van der Waals and nonpolar interactions, whereas electrostatic terms play dominant role in stabilizing the binding mode between HCTR2 and NADPH. Further, docking analysis of HC-toxin with HCTR-NADPH complexes showed a distinct mode of binding and the complexes were stabilized by a strong network of hydrogen bond and hydrophobic interactions. This study is the first in silico attempt to unravel the biophysical and biochemical basis of cofactor recognition in enzymatic class of R genes in cereal crop maize.

In view of the celebration of the ‘International Year of Millets,’ millets are popularizing sustainable agricultural output amid challenging climates and nourishing adequately as food and feed. The extent of scientific intervention is the foundation for designing, promoting and popularizing neglected crops on social platforms. Planning future directions and adaptive strategies largely require regular evaluation of research efforts to identify hotspots and research gaps, as identified in the present study by creating a robust text-mining approach that integrates scientometrics using PubMed citation data. Keyword mining reveals that India and China are the leading publication centres on millets, possibly due to their large proportion of cultivation and indigenous nature. It further reveals that the pearl millet is the predominant one, followed by foxtail and finger millet, suggesting that most research is confined to them only; however, other millets, still have a research gap in comparison. The word abiotic stress is associated with high frequency in millet research due to its adaptive nature amid climate change. Thematic representation explored the novel concept of millet's utility as a probiotic and millet bran to ensure nutrient–cereal properties based on the persistency of keywords throughput research progression; however, incurious consumption is associated with harmful ochratoxin. Bio-concept mining and knowledge graph generation divided the millet research output into four large domains, which provides a largely covered bio-concepts for millet research and co-concurrence of emerging bio-concepts to intense progress and finds an adequate literature gap to improve millet research for sustained growth and equilibrate biodiversity.

Anthropogenic stressors can disrupt cetacean foraging ability and reduce energy available for reproduction. Predicting such ecological consequences is limited by our understanding of cetacean energy metabolism. We here show that cetaceans have undergone substantial evolutionary changes in nutrient signaling metabolic pathways, rendering mechanistic physiological frameworks derived from model organisms inappropriate. Abstract Foraging disruption caused by human activities is emerging as a key issue in cetacean conservation because it can affect nutrient levels and the amount of energy available to individuals to invest into reproduction. Our ability to predict how anthropogenic stressors affect these ecological processes and ultimately population trajectory depends crucially on our understanding of the complex physiological mechanisms that detect nutrient availability and regulate energy metabolism, foraging behavior and life-history decisions. These physiological mechanisms are likely to differ considerably from terrestrial mammalian model systems. Here, we examine nucleotide substitution rates in cetacean and other artiodactyl genomes to identify signatures of selection in genes associated with nutrient sensing pathways. We also estimated the likely physiological consequences of adaptive amino acid substitutions for pathway functions. Our results highlight that genes involved in the insulin, mTOR and NF-ĸB pathways are subject to significant positive selection in cetaceans compared to terrestrial artiodactyla. These genes may have been positively selected to enable cetaceans to adapt to a glucose-poor diet, to overcome deleterious effects caused by hypoxia during diving (e.g. oxidative stress and inflammation) and to modify fat-depot signaling functions in a manner different to terrestrial mammals. We thus show that adaptation in cetaceans to an aquatic lifestyle significantly affected functions in nutrient sensing pathways. The use of fat stores as a condition index in cetaceans may be confounded by the multiple and critical roles fat has in regulating cetacean metabolism, foraging behavior and diving physiology.

Advances in transcriptome sequencing provide fast, cost-effective and reliable approach to generate large expression datasets especially suitable for non-model species to identify putative genes, key pathway and regulatory mechanism. Citronella ( Cymbopogon winterianus ) is an aromatic medicinal grass used for anti-tumoral, antibacterial, anti-fungal, antiviral, detoxifying and natural insect repellent properties. Despite of having number of utilities, the genes involved in terpenes biosynthetic pathway is not yet clearly elucidated. The present study is a pioneering attempt to generate an exhaustive molecular information of secondary metabolite pathway and to increase genomic resources in Citronella. Using high-throughput RNA-Seq technology, root and leaf transcriptome was analysed at an unprecedented depth (11.7 Gb). Targeted searches identified majority of the genes associated with metabolic pathway and other natural product pathway viz . antibiotics synthesis along with many novel genes. Terpenoid biosynthesis genes comparative expression results were validated for 15 unigenes by RT-PCR and qRT-PCR. Thus the coverage of these transcriptome is comprehensive enough to discover all known genes of major metabolic pathways. This transcriptome dataset can serve as important public information for gene expression, genomics and function genomics studies in Citronella and shall act as a benchmark for future improvement of the crop.

(1) Background: To assess the genetic makeup among the agro-economically important members of Euphorbiaceae, the present study was conducted to identify and characterize high-quality single-nucleotide polymorphism (SNP) markers and their comparative distribution in exonic and intronic regions from the publicly available expressed sequence tags (ESTs). (2) Methods: Quality sequences obtained after pre-processing by an EG assembler were assembled into contigs using the CAP3 program at 95% identity; the mining of SNP was performed by QualitySNP; GENSCAN (standalone) was used for detecting the distribution of SNPs in the exonic and intronic regions. (3) Results: A total of 25,432 potential SNPs (pSNP) and 14,351 high-quality SNPs (qSNP), including 2276 indels, were detected from 260,479 EST sequences. The ratio of quality SNP to potential SNP ranged from 0.22 to 0.75. A higher frequency of transitions and transversions was observed more in the exonic than the intronic region, while indels were present more in the intronic region. C↔T (transition) was the most dominant nucleotide substitution, while in transversion, A↔T was the dominant nucleotide substitution, and in indel, A/- was dominant. (4) Conclusions: Detected SNP markers may be useful for linkage mapping; marker-assisted breeding; studying genetic diversity; mapping important phenotypic traits, such as adaptation or oil production; or disease resistance by targeting and screening mutations in important genes.