C.S.I.R - Institute of Himalayan Bioresource Technology or CSIR-IHBT established in 1983 is a constituent laboratory of Council of Scientific and Industrial Research. This institute located in Palampur, Kangra, Himachal Pradesh, India is engaged in various advanced research aspects of Himalayan Bio-resources and modern biology. It has also been imparting Ph.D. in Biological and Chemical Sciences.Situated among pristine environ in the lap of Dhauladhar ranges, CSIR-IHBT is the only laboratory of the Council of Scientific and Industrial Research in the State of Himachal Pradesh (H.P.), India. Institute has a focused research mandate on bioresources for catalysizing bioeconomy in a sustainable manner.The institute has state-of the art laboratories; remote sensing and mapping facilities; internationally recognised herbarium; animal house facility; pilot plants in nutraceuticals, essential oil and herbals; farms and polyhouses. The young and dynamic team of scientists propel the research and work dedicatedly to discover and find solutions to new challenging problems faced by the society. International collaborations further strengthens scientific interactions at a global scale. Promoting industrial growth through technological interventions is a constant endeavour and several technologies developed by the institute are transferred to industries. For socio- economic upliftment, regular training programmes and advisory services are rendered to farmers, floriculturists, tea planters and small entrepreneurs involved in food processing sector. Institute has been recognised as one of the Incubation Centres by MSME GoI and in the area of Affordable Health Care by DSIR. Institute encourages industries to share the technological problems faced them, such that efforts could be made in developing a viable solution. Confidentiality is strictly maintained. Work on plant adaptation studies and high altitude medicinal plants are further strengthened by the field lab ”Centre for High Altitude Biology (CeHAB) situated at Ribling in Lahaul & Spiti district of H.P. Through this centre, institute disseminates technologies by way of trainings and demonstrations that could transform the economy of the region and help in solving unique challenges faced by them. Institute fosters student-scientist interaction and school children are welcome to visit the institute. Post graduate students can do project and sharpen their research skills at CSIR-IHBT. Young researchers are welcome for to do Ph.D. in cutting edge areas under the able guidance of expert faculty. Institute passionately contribute its bit in the development of society, industry and environment..
The Himalayan alpine (Kullu Valley) ecosystem is increasingly vulnerable to ecological shifts driven by climatic variability and anthropogenic pressures. Despite widespread recognition of this vulnerability, systematic long-term assessments quantifying land use and land cover (LULC) transformations and their broader ecological impacts remain scarce. Addressing this critical gap, the present study investigates two decades (2004–2024) of LULC changes and projects future trajectories up to 2044. The research uniquely integrates LULC dynamics with terrestrial carbon stock assessment and ecosystem service valuation (ESV), offering novel insights into the ecological and economic consequences of landscape transformation in the high-altitude Himalayan (Kullu Valley) region. LULC classification was conducted using high-resolution satellite imagery processed through a Random Forest classifier, achieving 93
BACKGROUND:Safflower (Carthamus tinctorius L.) is a drought-resilient oilseed crop. Besides producing edible oil rich in oleic and linoleic acids, it is also used in biofuels, cosmetics, coloring dyes, pharmaceuticals, and nutraceuticals. Despite its significant economic uses, the availability of genetic and genomic resources in safflower is limited. RESULTS:We report an improved de novo genome assembly of safflower (Safflower_A2). A chromosome-level assembly of 1.15 Gb with telomeres and centromeric repeats was constructed using PacBio HiFi reads, optical maps, Illumina short reads, and Hi-C sequencing. Safflower_A2 shows better contiguity, completeness, and high-quality annotation than previous assemblies. The assembly was further validated with the help of a single-nucleotide polymorphism (SNP)-based linkage map. A genome-wide survey identified genes for comprehensive exploration of disease resistance in the safflower. Employing the de novo genome assembly as a reference, we used resequencing data of a global core collection of 123 accessions to carry out an SNP-based genome-wide association study, which identified significant associations for several traits and their haplotypes of agronomic value, including seed oil content. Resequencing data were also applied for a pan-genome analysis, which provided critical insights into genome diversity, identifying an additional ~11,000 genes and their functional enrichment that will be useful for region-specific breeding lines. CONCLUSION:Our study provides insights into the genomic architecture of safflower by leveraging an improved genome assembly and annotation. Additionally, resources, including a high-density linkage map, marker-trait associations, and pan-genome development in this study, provide valuable resources for use in breeding and crop improvement programs by the global research community.
Helical chirality is an important, but underrated form of chirality than other types of chirality. Molecules with helical chirality impart a crucial role in several biological phenomena as well as in modern materials applications. Classically, the generation of chiral helicity in organic molecules relies on a ring extension by means of cycloaddition and related reactions. Recently, the peri-functionalization approach paved a new pathway for the generation of chiral helical molecules. In this article, we highlight the key advancements in these parallel approaches for the generation of helical chiral architectures.
The repurposing of FDA-approved antimicrobial agents for oncology presents a promising therapeutic strategy to accelerate drug development and enhance clinical outcomes in cancer therapy. This strategy has gained significant interest because it is faster, more cost-effective, and involves fewer safety uncertainties than the traditional process for developing new molecular entities. Several established therapeutic agents, including minoxidil, raloxifene, propranolol, aspirin, chloroquine, and metformin, have been successfully repurposed to explore additional pharmacological applications. In cancer therapy, patients often have compromised immune systems, making them highly vulnerable to bacterial infections. Although antimicrobials do not directly boost immunity, they play a crucial role in preventing infections and, in some instances, exert direct anticancer effects by disrupting cellular pathways critical for tumor proliferation. Beyond their primary antimicrobial functions, several antibiotics, antivirals, antifungals, and anthelmintics show intrinsic anticancer activities through DNA intercalation, topoisomerase inhibition, mitochondrial dysfunction, reactive oxygen species (ROS) generation, and immunomodulation. These agents also exert antitumor effects by modulating key oncogenic pathways, such as Wnt/β-catenin, mTOR, and Hedgehog, and by selectively targeting cancer stem cells as well as tumor-associated microbiota. This review aims to explore the burgeoning potential of antimicrobial agents in oncology, highlighting their roles in reducing infection-related mortality, enhancing therapeutic effectiveness, and improving the overall quality of life in cancer patients.
Protein-protein interactions (PPIs) are molecular lego which define the physical states of cells. Accurately identifying PPIs remains challenging due to the interplay of several factors ranging from electrostatic to molecular geometry, topology, and physics. Existing computational approaches capture only fragments of this orchestra, limiting their generalizability across protein families and interaction types. Here, we present ProMaya, a hierarchical multi-scale Graph-transformer framework that integrates 3D atomic geometry, electronic distribution, residue-level structure and disorder, surface mass-density signatures, and large protein language-model embeddings of interacting proteins. Highly comprehensively benchmarked across nine species and 47 GB experimentally validated data, ProMaya achieved consistently >95% average accuracy, outperforming state-of-the-art tools by >12%. As driven by its explainability, the first time introduced atomic and protein language information dramatically boosted it to an outstanding level for PPI discovery in any species, potent to even bypass costly experiments. ProMaya system is freely accessible at https://scbb.ihbt.res.in/ProMaya/
