Goats are uniquely equipped to cope with harsh environments, making them an important model for understanding genetic resilience to climate change. In this study, we explored genome-wide copy number variation regions (CNVRs) across diverse Indian goat breeds to uncover structural variants that may underlie key adaptive traits. We identified over 32,711 autosomal CNVRs, including breed-specific regions that varied notably in size and genomic coverage. These regions were enriched for genes involved in hormone signaling, immune function, and cellular transport namely, functions closely tied to growth, fertility, disease resistance, and overall adaptability. Notably, CNVRs associated with economically important traits such as coat color, fecundity, body weight, and milk production were identified through gene ontology and QTL annotations. By linking structural genomic variation with phenotypic diversity, our findings highlight the genetic mechanisms that contribute to the hardiness of Indian goat breeds. This study is the first to integrate CNVR mapping across 11 indigenous breeds with structural, functional as well as phenotypic annotations, bridging a critical gap in tropical goat genomics. This article aligns with SDG 3 (Good Health and Well-Being), and SDG 15 (Life on Land) of the UN Agenda for Sustainable Development, offering valuable foundation for climate-resilient breeding strategies aimed at sustaining goat productivity and health in changing environments.
Malnutrition affects billions of people, leading to challenging socio-economic conditions. Development of biofortified maize would provide a cost-effective and sustainable solution to alleviate malnutrition. A set of 24 Northern Himalaya-adapted maize inbreds was analysed in four diverse locations for variability of kernel provitamin-A (proA) and vitamin-E (vitE). The inbreds were also analysed for allelic diversity for crtRB1 and vte4 genes, besides SSR markers. ANOVA revealed significant variation for proA (0.93–9.46 ppm), vitE (α-tocopherol: 6.50–17.81 ppm) and grain yield (1887–3325 kg/h). BAJIM-BIO-8 possessed favourable allele of crtRB1, while BAJIM-08–26, BAJIM-BIO-6, LM-17, BAJIM-BIO-3 and LM-16 had favourable allele of vte4. PMI-PV1 and PMI-PV2 possessed favourable alleles of both crtRB1 and vte4. The mean proA and vitE among crtRB1 and vte4 favourable genotypes were 9.35 ppm and 15.27 ppm, respectively, compared to wild type genotypes (proA: 1.43 ppm, and vitE: 8.63 ppm), respectively. Molecular characterisation was undertaken using 150 SSRs spread evenly across entire genome of which 75 markers were polymorphic that generated 195 alleles and classified the genotypes into three major groups. Based on genetic dissimilarity, potential heterotic cross-combinations with higher proA (BAJIM-BIO-8 × PMI-PV1, BAJIM-BIO-8 × PMI-PV1 and PMI-PV1 × PMI-PV2) and vitE (BAJIM-08–26 × LM-17, BAJIM-08–26 × PMI-PV1, BAJIM-08–26 × PMI-PV2, LM-17 × BAJIM-BIO-6, LM-17 × PMI-PV1, PMI-PV2 × BAJIM-BIO-6 and PMI-PV1 × PMI-PV2) were identified. PMI-PV1 and PMI-PV2 proved to be high-yielding, multinutrient-rich inbred lines with both higher proA and vitE. The information generated here would help in developing proA and vitE-rich maize for alleviating malnutrition, thereby supporting SDG 2 (Zero Hunger) of the UN Agenda for Sustainable Development.
Magnoliids represent a phylogenetically distinct and economically important clade of flowering plants, renowned for their diverse terpenoid compounds that confer significant value as spices, medicines, and ornamentals. Terpene synthases (TPSs) are critical enzymes driving terpenoid biosynthesis. However, systematic characterization of the TPS gene family across the magnoliid clade remains lacking; current knowledge is fragmented and primarily derived from individual genome studies, which limits our understanding of their metabolic evolution. In this study, we conducted a genome-wide analysis across ten magnoliid species and identified 661 TPS genes, revealing significant lineage-specific expansions, particularly within the TPS-a and TPS-b subfamilies. Notably, we identified a potentially novel TPS-x clade and discovered the presence of the TPS-d3 group (previously considered gymnosperm-specific) in magnoliids and other angiosperms, supporting the possibility of a broader distribution of TPS-d3-like genes. Conserved protein domain analysis supports the functional identity of these clades, and our findings indicate that tandem duplication events served as the primary mechanism driving TPS family expansion. Furthermore, copy number variations in key upstream pathway genes suggest a coordinated genomic basis for terpenoid diversification in magnoliids. Ultimately, this study provides a crucial foundation for elucidating the evolutionary history and regulatory mechanisms of TPS genes in magnoliids. This article aligns with SDG 15 (Life on Land) of the UN Agenda for Sustainable Development.
Y-chromosomal short tandem repeats (Y-STRs) play an important role in forensic investigations and have served as a major contributor to case solving and sample resolution. Low-to-moderate mutating Y-STRs often fail to meet the requirements for male lineage distinction in inbred populations, whereas high-resolution rapidly mutating (RM) Y-STRs may occasionally produce exclusions within true paternal lineages due to their elevated mutation frequencies. Thus, integrating Y-STRs with low, moderate, and high mutation rates facilitates the distinction of male individuals and lineages during familial screening and genetic relationship research. The Ingenomics™ Y Profiler STR kit is a 6-dye multiplex assay that amplifies 33 male-specific Y-STR markers and one insertion/deletion marker, rs2032678 (Y-InDel), and includes small and large internal quality controls (IQCs). This kit is specifically designed for forensic applications, especially on sexual assault-related samples, where analysis is hampered by an abundance of female DNA relative to male DNA. With as little as 63 pg of input DNA, the assay can reliably produce complete and balanced profiles, while yielding full profiles with 32 pg of input DNA. The Ingenomics™ Y Profiler STR kit can also serve as a very efficient DNA database solution due to the inclusion of an extended set of Y-STR markers. Validated according to the Scientific Working Group on DNA Analysis Methods (SWGDAM) guidelines, the kit demonstrates species specificity, high sensitivity, and tolerance to common inhibitors. It is efficient in generating profiles from degraded DNA, resolving male mixtures, and supporting direct amplification. The data demonstrate that the Ingenomics™ Y Profiler STR kit is robust, sensitive, and reliable and can be used in human forensics, DNA databasing, and male lineage identification and thus well aligns with the SDG 3 (Good Health and Well-Being) and SDG 4 (Quality Education) of the UN Agenda for Sustainable Development.
Aflatoxin B1 (AFB1) is a potent mycotoxin that undergoes metabolic activation by cytochrome P450 enzymes, particularly CYP1A2, to form the genotoxic AFB1-8,9-epoxide. This study investigated the potential interactions of honey-derived phytochemicals with CYP1A2 using an integrated structural bioinformatics approach to explore their possible role in modulating AFB1 bioactivation. Raw honey was subjected to high-performance liquid chromatography (HPLC) to identify its bioactive constituents. Network pharmacology was employed to identify putative targets and biological pathways associated with honey phytochemicals and drug metabolism. Molecular docking and MM/GBSA binding free energy calculations were performed using the Maestro Schrödinger suite to evaluate the binding affinities of the identified compounds toward CYP1A2. Quercetin and apigenin emerged as the top-scoring phytochemicals and were compared with fluvoxamine, a well-established CYP1A2 inhibitor. Molecular dynamics simulations were conducted using GROMACS for the CYP1A2-ligand complexes, followed by trajectory analyses including root mean square deviation (RMSD), root mean square fluctuation (RMSF), molecular mechanics Poisson–Boltzmann surface area (MM/PBSA), principal component analysis (PCA), and free energy landscape (FEL). The simulations demonstrated stable ligand–protein interactions, favorable binding free energies, and conformational stability comparable to those observed for fluvoxamine. These findings provide computational evidence that selected honey-derived flavonoids have the potential to interact with CYP1A2 and may modulate AFB1 bioactivation. However, these results are predictive and hypothesis-generating, and experimental validation through enzyme inhibition assays, cell-based studies, and in vivo investigations is required to determine whether the predicted molecular interactions translate into functional CYP1A2 inhibition and biologically meaningful protection against AFB1 toxicity. This study supports United Nations Sustainable Developmental Goal SDG-3 (Good Health and Well-Being) by identifying honey-derived phytochemicals with the potential to modulate CYP1A2-mediated aflatoxin B1 bio-activation, providing a computational basis for future strategies to reduce aflatoxin-induced toxicity and improve public health.
RNA sequencing in tumors is advantageous for the direct investigation of Differential Gene Expression (DGE) and, indirectly, of the Tumor microenvironment (TME). Nonetheless, meeting these objectives demands substantial bioinformatic analysis of pre-processed raw data; however, the multitude of existing pipelines and tools may be overwhelming for non-bioinformatic researchers conducting independent analyses. In this study, we present a systematic, coherent, and broadly applicable framework for downstream DGE and TME analyses. For this, RNA-Seq was conducted on Gastric tumors and matched normal tissues (n = 26) obtained from human patients. Laboratory-generated data were analysed using various open-source R/Bioconductor packages and web-based tools to detect outliers and perform DGE, the results of which were validated via qRT-PCR. This was followed by Overrepresentation Analysis (ORA), Gene Set Enrichment Analysis (GSEA), and TME analysis. On analysis, the results revealed cancer-related features, such as enrichment of extracellular matrix (ECM) and cell adhesion-related biological processes and pathways, a feature very common in solid and aggressive tumors, justifying the bioinformatic analysis. Moreover, the high similarity among results from multiple methods used for ORA and GSEA validated the bioinformatic analysis. In terms of TME analysis, the high stromal infiltration observed further supported the findings from ORA and GSEA. Additionally, the correlation between stromal cell infiltration and ECM-related pathways allowed us to connect DGE analysis and TME, emphasizing the importance of exploring both. Overall, this framework provides a structured workflow for progressing from RNA-Seq raw count data to DGE and TME analyses, and is applicable across diverse cancer types and sequencing platforms. This article aligns with SDG 3 (Good Health and Well-Being) and SDG4 (promoting quality education in life sciences) of the UN Agenda for Sustainable Development.
Neuroblastoma is among the most biologically heterogeneous pediatric malignancies, and amplification of the MYCN oncogene remains a defining molecular hallmark of high-risk disease. Although MYCN amplification is firmly established as a powerful prognostic biomarker and oncogenic driver, copy number alone does not fully explain the marked variability in transcriptional output, cellular phenotype, therapeutic response, and clinical outcome observed among MYCN-amplified tumors. Recent advances in structural genomics, epigenomics, chromatin biology, and single-cell analysis have revealed that MYCN activity is shaped by the architecture of amplified DNA, enhancer composition, three-dimensional chromatin organization, developmental cell state, cooperating genomic alterations, and adaptive interactions with the tumor microenvironment. This review integrates these emerging concepts with established MYCN biology. It examines the molecular regulation and structural evolution of MYCN amplicons; the contribution of extrachromosomal DNA, homogeneously staining regions, and enhancer hijacking; cooperating alterations such as ALK activation, 1p36 loss, and 17q gain; alternative high-risk contexts characterized by 11q deletion or ATRX-associated alternative lengthening of telomeres; and the influence of adrenergic-mesenchymal plasticity, signaling crosstalk, metabolism, DNA damage responses, and immune regulation. The review further evaluates therapeutic strategies that target MYCN directly or exploit its transcriptional, epigenetic, metabolic, and replication-stress dependencies, with particular emphasis on resistance mechanisms, patient-selection biomarkers, and rational combination therapy. Collectively, current evidence supports a context-dependent model in which MYCN amplification establishes oncogenic potential, whereas genomic architecture, epigenetic regulation, developmental identity, and adaptive signaling determine tumor behavior. This framework provides a basis for next-generation biomarker development and precision therapeutic strategies in high-risk neuroblastoma. By advancing molecular understanding, therapeutic development, and knowledge dissemination in pediatric cancer, this article aligns with United Nations Sustainable Development Goal 3 (Good Health and Well-Being) and Goal 4 (Quality Education).
The accurate estimation of river discharge properties is challenging because of the lack of gauge data in inaccessible and remote regions, uneven distribution of gauge networks, and data-sharing complexities. To address these challenges, innovative integrated techniques must be evaluated. This study aimed to integrate geospatial (HEC-GEORAS), HEC-RAS, and river gauge data to quantify river flow properties, including the discharge rate, velocity, water level, and flow depth of a distributary of the Indus River in northwestern Pakistan. The study area is characterized by semi-arid conditions, experiencing water scarcity, and declining water levels. Such an integrated approach has never been used in the region, especially on any distributary of the Indus River, until now. The findings revealed that the peak flow velocity reached 1.8 m/s, and the spatial distribution varied from 0.3 to 1.3 m/s. The maximum depth was estimated at approximately 33 m in the upstream section and showed a declining trend of a few centimeters in the downstream section. River discharge decreases downstream (from 2.26 to 0.28 m3/s) due to infiltration, tributary water distribution, evaporation, and agricultural water use. The estimation of hydraulic parameters provides meaningful information for sustainable water resource management, such as domestic, agricultural, and industrial water allocations. Furthermore, the results can support flood risk assessment, irrigation planning, and adaptation to climate change strategies by improving our understanding of water availability and flow dynamics in semi-arid river systems.
The major histocompatibility complex (MHC) class II DRB1 locus is a key component of the vertebrate adaptive immune system, encoding the β-chain of the MHC class II molecule involved in presenting processed antigens to CD4+ T cells. In the present investigation, the coding sequence, nucleotide architecture, codon usage characteristics, amino acid composition, and phylogenetic relationships of the MHC DRB1 gene were examined in the Indian dromedary camel (Camelus dromedarius). Five gene fragments encompassing all six exons of the DRB1 gene were amplified through polymerase chain reaction–sequence-based typing (PCR-SBT) and subsequently sequenced using Sanger chain-termination technology. Assembly and annotation of the obtained sequences revealed a complete coding region of 813 bp, translating into a polypeptide comprising 270 amino acids. Nucleotide and protein composition, codon adaptation index (CAI), relative synonymous codon usage (RSCU), and effective number of codons (ENC) were evaluated using the CAIcal platform. Nucleotide composition analysis revealed a GC-rich coding sequence (58.92
Recombinase polymerase amplification (RPA) has emerged over the past two decades as one of the most promising alternatives to the polymerase chain reaction (PCR) for nucleic acid detection. RPA exploits enzymatic machinery derived from bacteriophage T4 to achieve exponential DNA amplification at a constant, near-physiological temperature of 37–42 °C, removing the need for thermal-cycling equipment entirely. The reaction typically produces detectable amplification products within 20–30 min and shows useful tolerance of the matrix inhibitors common in complex biological samples. This review provides a critical account of RPA’s molecular mechanism, kit formats, assay optimisation, and applications across pathogen detection, antimicrobial-resistance (AMR) surveillance, food safety and authenticity testing, and as a pre-amplification step coupled to CRISPR-based detection. Key performance data are summarised in comparative tables to facilitate at-a-glance appraisal. A direct comparison with PCR and loop-mediated isothermal amplification (LAMP) is provided, together with practical guidelines for primer/probe design and multiplexing. Persistent challenges, notably nonspecific amplification, limited quantification accuracy, and reagent cost, are critically evaluated alongside emerging solutions. This review supports the United Nations Sustainable Development Goals by contributing to SDG 3 (Good Health and Well-being) through the promotion of rapid, accessible molecular diagnostics for improved disease detection and surveillance, and to SDG 9 (Industry, Innovation and Infrastructure) by advancing innovative, portable diagnostic technologies for decentralized healthcare and public health preparedness.
The leptin (LEP) gene plays a key role in fat metabolism, energy balance, and reproductive performance in pigs. This study investigated two polymorphisms, g.3156C > T and g.4124A > G, in crossbred and indigenous Niang Megha pigs and evaluated their association with reproductive traits, including litter size at birth (LB), litter size at weaning (LW), average birth weight (ABW), and average weaning weight (AWW). Genotyping was performed using PCR–RFLP. The g.3156C > T SNP was polymorphic in both populations, with C and T allele frequencies of 0.385 and 0.615 in crossbred pigs, and 0.808 and 0.192 in Niang Megha pigs. In crossbreds, the C allele tended to be associated with reproductive traits, with sows carrying the CC genotype showing numerically higher ABW and AWW in later parities, although these differences were not statistically significant (P > 0.05). No significant associations were observed in the Niang Megha population. The g.4124A > G SNP was polymorphic only in crossbred pigs (A: 0.546, G: 0.454), whereas the Niang Megha population was monomorphic with only the GG genotype. In crossbreds, sows with the AA genotype exhibited higher weaning weight; however, the differences were not statistically significant (P > 0.05). These findings indicate that LEP gene polymorphisms may influence reproductive traits in a parity-dependent manner, particularly in crossbred pigs. However, the observed effects were generally non-significant and require further validation in larger and more diverse populations before their application in breeding programs. This article aligns with the United Nations Sustainable Development Goal (SDG 2: Zero Hunger) by supporting sustainable livestock production and genetic improvement strategies aimed at enhancing reproductive efficiency, productivity, and food security.
A novel green synthesis approach was developed for the fabrication of copper nanoparticles (CuNPs) using leaf extract of Justicia adhatoda (L) fam. Acanthaceace. The phytochemical constituents of J. adhatoda, including vasicine, vasicinone, and polyphenols, acted as dual reducing and capping agents, facilitating rapid nanoparticle formation without the need for additional stabilizers. The successful synthesis of CuNPs was confirmed by UV–Vis spectroscopy, which exhibited a characteristic surface plasmon resonance (SPR) peak at approximately 277 nm. FTIR spectra revealed the presence of plant-derived functional groups involved in nanoparticle stabilization. Morphological characterization by SEM and TEM demonstrated predominantly spherical, layered structures with an average particle size of 47 nm. Dynamic light scattering (DLS) analysis showed a narrow hydrodynamic size distribution, while the zeta potential (− 25.6 mV) indicated strong colloidal stability. The biosynthesized CuNPs exhibited significant, dose-dependent cytotoxicity against triple-negative breast cancer (MDA-MB-231) cells. Fluorescence microscopy further confirmed apoptosis-associated morphological alterations. To the best of our knowledge, this is the first report of J. adhatoda mediated CuNPs exhibiting potent anti-MDA-MB-231 activity, suggesting their potential as a sustainable and cost-effective nanomaterial for biomedical applications. This article aligns with SDG 3 (Good Health and Well-Being) of the UN Agenda for Sustainable Development.
Plant encounters several abiotic and biotic stresses during their life cycle which effect their growth and development. Some plants can withstand stresses because of the presence of well-equipped defense mechanisms that include proteins and metabolites. One such important protein is Late Embryogenesis Abundant (LEA) that helps plants to withstand against various abiotic stress, including cold, heat, salt, drought and osmotic stresses as well as biotic stress. This review comprehensively compiles the classification, structure and functional roles of various LEA protein families, emphasizing their protective mechanisms for retention of water, stabilization of protein, protection of membrane and reduction of oxidative stress. Moreover, LEA protein was found to be essential part of growth and development such as for seed development and dormancy. Recent findings also showed that the role of LEA proteins in developing climate-resilient crops, prolong the self-life of seeds for seed bank conservation and expand into medicinal as well as pharmaceutical applications due to their special ability to stabilize other biomolecules. This review offers insights into the biotechnological and agricultural uses of LEA proteins, making them viable targets for enhancing environmental adaptation of crops and global food security. This article aligns with SDG 15 (Life on Land) of the UN Agenda for Sustainable Development.
Quantum information processing is a promising way that deals with the aspects of superposition, entanglement, computation using coherence, communication, and sensing. This review is an analysis of how alkali Rydberg atoms can be used in quantum information processing. The leading candidates are the alkali atoms, as they have a simple electronic structure, transitions that are well characterized, and which can be laser-cooled and trapped. Important mechanisms, such as EIT, dipole-dipole interactions, and Rydberg blockade, are necessary to achieve high-fidelity quantum gates, photon-photon interactions, and long-lived quantum memories. Experimental devices such as magneto-optical traps, optical tweezers, optical lattices, and warm vapor cells have made it possible to use a controllable atom-photon interface and scalable architecture. In the recent development of laser and microwave control methods, the time of coherence, state-transfer, and single-atom addressability have been enhanced. Such challenges include decoherence due to spontaneous emission, motional dephasing, and technical issues in trapping stability and laser linewidth. This review concludes that alkali Rydberg atoms, especially rubidium and cesium, are of relevance in scalable fault-tolerant quantum computing and quantum simulation, and represent the meeting of basic quantum science with new technology uses.
Chromosome region maintenance 1 (CRM1) is a key nuclear export receptor that mediates the transport of numerous proteins and RNA species from the nucleus to the cytoplasm via the classical leucine-rich nuclear export signal (NES) pathway. In normal cells, CRM1 plays a critical role in maintaining cellular homeostasis by regulating the spatial and temporal distribution of important signaling molecules, transcription factors, and tumor suppressor proteins. However, dysregulation of CRM1 function is frequently observed during cancer progression. A deeper understanding of the biology of CRM1 and pathways associated with it in both healthy and cancerous contexts may provide novel opportunities for targeted intervention and improved clinical outcomes. This review discusses the functional relevance of CRM1 in different cancers and evaluates the potential of CRM1 inhibitors in anti-cancer therapy. This article aligns with SDG 3 (Good Health and Well-Being) of the UN Agenda for Sustainable Development.
Despite its temporal resolution and relatively low cost, electroencephalography (EEG) is one of the most popular methods for investigating brain dynamics because it is noninvasive. Nonetheless, the interpretation of EEG signals essentially relies on the solution of the forward problem, accounting weakly for the electrical activity produced in the brain and how it diffuses, thus arousing scalp potentials. Over the past few years, the development of computational neuroscience and numerical modeling has resulted in increasingly complex forward models using realistic head geometries, anisotropic tissue conductivities, and fine numerical solvers. This review provides an in-depth discussion of the latest forward numerical techniques applied in the analysis of EEG data, including Boundary Element Methods (BEM), Finite Element Methods (FEM), Finite Difference Methods (FDM), and hybrid-computational methods. Other strategies for head modeling, recent computer advances, and the importance of software structures for EEG modeling are also discussed in this review. In addition, it highlights existing issues, such as ambiguity with respect to conductivity, intersubject variability, and computational cost. Finally, new advances in physics-inspired and data-driven modeling techniques are addressed, and the evolution towards more realistic and explainable EEG forward answers is discussed. The review finds that although there have been tremendous advances, the discipline still requires better integration of anatomical realism, numerical stability, and computational efficiency. This review comprises recent advances in AI-supported forward modeling, physics-guided computational methods, and subject-specific conductivity estimation techniques published between 2020 and 2026, none of which have been summarized in any of the prior reviews on EEG forward modeling, which have mostly focused on numerical solutions only. Moreover, it compares classical and emerging numerical methods and presents their advantages and disadvantages, particularly in terms of their applicability to current neuroimaging and brain-computer interface systems.
Gastric cancer (GC) represents a major health burden in South Asia and Iran, with genetic susceptibility varying substantially across populations. We conducted a systematic meta-analysis of gene-based association studies to identify genetic risk factors for gastric cancer in South Asia and Iran, following PRISMA guidelines. PubMed and Google Scholar were searched for eligible studies. Heterogeneity was assessed using Cochran’s Q-test; meta-analyses employed fixed-effect and random-effects models with Benjamini–Hochberg false discovery rate (FDR) correction. We evaluated publication bias using Begg’s Funnel plots and Egger’s test for variants appearing in ≥ 10 studies. Subgroup analyses stratified by Helicobacter pylori infection status and sex; meta-regression assessed effect modification. Analysis of 48 studies (5396 cases; 8330 controls) identified 27 variants across 21 genes, of which 13 showed nominal associations (p < 0.05) and four remained significant after FDR correction (pFDR < 0.05). The rs2279744/MDM2 variant showed the most robust association, conferring consistently elevated GC risk across additive, dominant, and recessive inheritance models without evidence of publication bias. IL-1β polymorphisms (rs16944, rs1143627) were associated with risk specifically in H. pylori-positive patients, whereas rs2234663/IL-1RN was associated with H. pylori-negative cases. Four pharmacogenomic variants predicted chemotherapy outcomes, including rs1695/GSTP1 (oxaliplatin neuropathy), rs1799964/TNF (thrombocytopenia risk), rs1042522/TP53 (reduced cisplatin–paclitaxel efficacy), and rs13181/ERCC2 (improved response and survival). These findings identify population-specific genetic determinants of GC susceptibility and treatment response, supporting targeted prevention and personalized therapeutic strategies in South Asian populations. This article aligns with SDG 3 (Good Health and Well-Being) of the UN Agenda for Sustainable Development.
The interplay between autophagy and microRNAs (miRNAs) has emerged as a pivotal regulatory axis in the pathogenesis of kidney diseases, offering novel therapeutic targets for conditions such as renal ischemia–reperfusion injury (RIRI), acute kidney injury (AKI), diabetic nephropathy (DN), and renal cell carcinoma (RCC). Autophagy, a conserved cellular process, plays a dual role in kidney homeostasis, acting as both a protective mechanism and a contributor to disease progression depending on context. Dysregulation of autophagy is implicated in renal fibrosis, tubular cell apoptosis, and podocyte injury, while miRNAs, as post-transcriptional regulators, modulate autophagy pathways to influence disease outcomes. In RIRI and AKI, miRNAs such as miR-192-5p, miR-30a-5p, and miR-92a regulate autophagy to mitigate oxidative stress and inflammation, whereas in DN, miR-214 and miR-22 disrupt autophagic flux, exacerbating fibrosis and podocyte dysfunction. In RCC, oncogenic miRNAs like miR-204 and miR-30a-3p hijack autophagy to promote tumor survival and chemoresistance. Therapeutic strategies, including miRNA mimics/inhibitors, natural compounds (e.g., curcumin, oleanolic acid), and stem cell-derived exosomes, demonstrate promise in preclinical models by restoring autophagic balance. This review highlights the intricate crosstalk between miRNAs and autophagy in kidney diseases, elucidating underlying molecular mechanisms. This article aligns with SDG 3 (Good Health and Well-Being) of the UN Agenda for Sustainable Development.
This study presents a whole-genome re-sequencing (WGR) analysis of two genetically and functionally distinct indigenous Indian cattle breeds, Sahiwal and Kangayam, to explore genetic diversity, population structure, and selection signatures. High-quality sequencing data ( 8 × depth) generated over 21 million SNPs per breed, with 7.48
The squirrelfish family (Holocentridae) represents a ubiquitous and ecologically vital component of coral reef fauna. Their vast oceanic distribution across oceanic barriers in some species presents a unique opportunity to investigate karyotypic evolution on a vast spatial dimension. Here we conducted the first interpopulational cytogenetic analysis of Myripristis jacobus and Holocentrus adscensionis (Atlantic Ocean), and Sargocentron rubrum (Indian Ocean). Our approach integrates conventional cytogenetic techniques with fluorescence in situ hybridization (FISH) to provide a comprehensive view of their karyotypic structures. Sargocentron rubrum and M. jacobus presented 2n = 48 acrocentric chromosomes, while H. adscensionis exhibited 2n = 50 (2 m + 6sm + 16st + 26a, FN = 74). The 18S ribosomal DNA (18S rDNA)/nucleolar organizer regions stained with silver (Ag-NORs) sites were in a one chromosome pair in S. rubrum and M. jacobus, and in two pairs in H. adscensionis. FISH analysis revealed a single 5S rDNA locus per genome across all studied species. Tol2 elements are dispersed throughout the chromosomes, while Rex3 and the (GA)15 repeats form more conspicuous centromeric clusters. Cytogenetic comparisons among populations of H. adscensionis and M. jacobus did not show geographic variations, condition congruent with the high genetic connectivity reported for these species. The extensive geographic distribution of these species correlates with biological traits and historical contingencies underlying their karyotypic changes. Our findings provide new insights into karyotype evolution and highlight the need for expanded chromosomal studies in this family. This article aligns with SDG 14 (Life Below Water) of the UN Agenda for Sustainable Development Goals.
