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A neurological condition that worsens over time, Alzheimer’s disease (AD) is typified by memory loss, cognitive decline, and functional degradation. Traditional diagnostic techniques such as neuroimaging, cerebrospinal fluid biomarkers, and neuropsychological testing are often intrusive, costly, or insensitive in the early stages. Recent years have seen the emergence of AI and ML as game-changing technologies for AD risk assessment, early detection, and customized prevention. Using sophisticated models such as deep learning, convolutional neural networks (CNNs), and graph-based algorithms, AI-driven methods achieve high performance: CNNs, for example, have reached diagnostic accuracies of 94–99% for early AD and mild cognitive impairment using multimodal MRI and PET data. However, most reported performance metrics are derived from retrospective analyses and internal validation cohorts, with limited external validation across diverse populations. These methods include multimodal data integration from neuroimaging, genetics, and clinical records. Years before symptoms appear, AI-based frameworks can predict disease progression, identify modifiable risk factors, and guide individualized treatment plans. Future developments in federated learning and explainable AI (XAI) are promising, although data privacy, algorithmic bias, and ethical ramifications are concerns. Overall, AI and ML have a great deal of promise to transform the prevention of AD, enabling precision therapy and enhancing the lives of those who are at risk. Graphical Abstract

Cancer continues to pose a global health challenge, with conventional therapies often limited by non-specific toxicity, drug resistance, and an inadequate therapeutic index. Nanotechnology offers transformative opportunities by enabling targeted drug delivery, improved pharmacokinetics, and integrated diagnostic-therapeutic platforms (termed nanotheranostics). This review highlights key nanocarrier systems including liposomes, polymeric nanoparticles, dendrimers, inorganic nanostructures, carbon-based materials, extracellular vesicles, and hybrid platforms with a focus on human studies and clinical translation. Design strategies (such as passive and active tumor targeting, biomimicry, and stimuli-responsive release mechanisms) are discussed in the context of improving tumor selectivity and minimizing systemic toxicity. Recent innovations, including AI-supported nanomedicine design, smart nanorobots, and cell-mediated delivery systems, are also examined. Although multiple nano-formulations such as Doxil®, Abraxane®, and Vyxeos® have reached clinical use, challenges remain including large-scale manufacturing, regulatory pathways, long-term safety evaluation, and cost-effective global accessibility. This review provides a critical appraisal of current evidence, translational bottlenecks, and emerging opportunities to guide future nanomedicine development. Nanotechnology is poised to become a cornerstone of precision oncology, enabling personalized, safe, and effective cancer treatment paradigms.

Pediatric cancers (PC) require treatments that maintain cure rates while minimizing long-term toxicity and non-communicable diseases. Yet, conventional dosing, adult-oriented formulations, and high treatment burden remain major limitations in childhood cancer care. This review synthesizes the current evidence using artificial intelligence (AI) and 3D nano printing as emerging tools to support personalized pediatric oncology. A structured literature search of PubMed, Scopus, Web of Science, and Google Scholar (2005-2024) identified English-language studies related to pediatric cancer, nanomedicine (NM), 3D printing, precision dosing, and pharmacogenomics, and relevant findings were organized by cancer type, clinical application, and potential impact on toxicity, adherence, and survivorship. Across leukemia, neuroblastoma, brain tumors, bone sarcoma, and lymphoma, AI-supported platforms were found to improve individualized chemotherapy exposure, anticipate toxicity based on clinical or pharmacogenomic markers, and assist clinicians towards modifying early treatment. At the same time, 3D nano printing enabled child-friendly medicines, multi-drug polypills, and controlled-release formulations that reduced dosing errors and improved treatment adherence. Early hospital-based experience with Bayesian therapeutic drug monitoring and on-demand pediatric drug printing suggested high feasibility for real clinical settings. Overall, AI-guided dosing and nano-printed formulations enhanced precision, lowering acute and late toxicities that support healthier long-term outcomes in children with cancer, particularly when linked to disease-specific needs. Further multicenter pediatric studies, regulatory development, and expansion of hospital 3D printing capacity are recommended to enable safe and equitable translation of these technologies into routine clinical care.

Stem cells are the basis of organogenesis and regeneration, providing cellular support during the development, maintenance, and repair of tissues. This review provides a brief overview of the major stem cell types and their sources, as well as the key stages of organogenesis that depend on stem cell activity. This review highlights critical signalling pathways, including Wnt, Notch, Hedgehog, and BMP. These pathways regulate the fate and lineage specification of stem cells. The review identifies the roles of embryonic stem cells and induced pluripotent stem cells in organ formation as well as the newly arising methods for directed differentiation. Mesenchymal stem cells play a crucial role in tissue regeneration and therapeutic repair. Organoids are potent experimental models for studying development and disease. The impact of stem cell niches and microenvironmental regulation is discussed, along with the cellular and molecular processes that underlie recovery after damage. The review encompasses the translational progress of stem-cell-based therapies, current clinical trials, and the challenges in safety and efficacy. Moreover, the review also explores the introduction of advanced technologies, such as CRISPR, 3D bioprinting, and synthetic biology, as well as theoretical considerations, including future directions and ethical issues. Together, these insights provide a comprehensive overview of stem cell biology and highlight their potential for clinical translation. Graphical Abstract

Anthracnose, caused by the fungus Colletotrichum lindemuthianum , is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.

Enzymes are essential biocatalysts involved in all biochemical and metabolic reactions, widely used across industries, especially in food processing. Historically utilized to enhance food production, these enzymes aid in breaking down food for better digestion while improving taste, texture, and aroma. They are derived from animals, plants, or microorganisms, with microbial sources being the most preferred due to their cost-effectiveness, stability, ease of cultivation, and potential for large-scale production. Advances in biotechnology, molecular biology, and enzyme engineering have significantly deepened our understanding of microbial enzymes and enhanced their applications in the food industry. The integration of recombinant DNA technology and process engineering has further optimized enzyme-producing microbes for industrial use. However, continued research is essential to address challenges and fully harness their potential. This review focuses on microbial enzyme sources, production techniques, strain improvement methods, and their diverse applications in food processing. Graphical Abstract

Diabetic neuropathy (DN) is a common and debilitating complication of diabetes mellitus, often presenting with chronic pain and sensory or motor deficits. Current treatment options provide only partial symptomatic relief and are frequently associated with adverse effects, underscoring the need for more effective and targeted approaches. Microneedle (MN) technology has emerged as a minimally invasive, highly efficient, transdermal-delivery strategy offering increased drug absorption, sustained drug release, and patient compliance. Different designs of MN, such as solid, coated, dissolving, and hydrogel-based, are available and provide specific strategies in DN management. The patient-specific and solid microneedles, like the lipid-cast microneedles functionalized with the lidocaine and dexamethasone, have demonstrated the possibility to provide long-term pain relief. Emulsion formulations of microneedles made of hydrogel loaded with nerve growth factor show potential in enhancing nerve repair. Biodegradable polymers such as polyvinyl alcohol (PVA) and polyvinylpyrrolidone (PVP) can be dosed well. Still, more advanced materials, such as polylactide (PLA) and polycaprolactone (PCL), need to be engineered for scalable and cost-efficient production. It has its main obstacles that include drug stability and production, mass culturing, and complicated regulatory processes. The combination of MN platforms, nanomedicine and advanced delivery systems could provide synergistic therapeutic effects that could be the next step towards personalised, effective, and endurable DN treatment. This review identifies new developments, limitations, and areas to explore in terms of using microneedle technology as a method of targeted drug delivery for diabetic neuropathy. Graphical abstract

Common bean (Phaseolus vulgaris L.) is one of the most important grain legume crops in the world. The beans grown in north-western Himalayas possess huge diversity for seed color, shape and size but are mostly susceptible to Anthracnose disease caused by seed born fungus Colletotrichum lindemuthianum. Dozens of QTLs/genes have been already identified for this disease in common bean world-wide. However, this is the first report of gene/QTL discovery for Anthracnose using bean germplasm from north-western Himalayas of state Jammu & Kashmir, India. A core set of 96 bean lines comprising 54 indigenous local landraces from 11 hot-spots and 42 exotic lines from 10 different countries were phenotyped at two locations (SKUAST-Jammu and Bhaderwah, Jammu) for Anthracnose resistance. The core set was also genotyped with genome-wide (91) random and trait linked SSR markers. The study of marker-trait associations (MTAs) led to the identification of 10 QTLs/genes for Anthracnose resistance. Among the 10 QTLs/genes identified, two MTAs are stable (BM45 & BM211), two MTAs (PVctt1 & BM211) are major explaining more than 20% phenotypic variation for Anthracnose and one MTA (BM211) is both stable and major. Six (06) genomic regions are reported for the first time, while as four (04) genomic regions validated the already known QTL/gene regions/clusters for Anthracnose. The major, stable and validated markers reported during the present study associated with Anthracnose resistance will prove useful in common bean molecular breeding programs aimed at enhancing Anthracnose resistance of local bean landraces grown in north-western Himalayas of state Jammu and Kashmir.

Lung cancer is a heterogeneous group of malignancies with high incidence worldwide. It is the most frequently occurring cancer in men and the second most common in women. Due to its frequent diagnosis and variable response to treatment, lung cancer was reported as the top cause of cancer-related deaths worldwide in 2020. Many aberrant signaling cascades are implicated in the pathogenesis of lung cancer, including those involved in apoptosis (B cell lymphoma protein, Bcl-2-associated X protein, first apoptosis signal ligand), growth inhibition (tumor suppressor protein or gene and serine/threonine kinase 11), and growth promotion (epidermal growth factor receptor/proto-oncogenes/phosphatidylinositol-3 kinase). Accordingly, these pathways and their signaling molecules have become promising targets for chemopreventive and chemotherapeutic agents. Recent research provides compelling evidence for the use of plant-based compounds, known collectively as phytochemicals, as anticancer agents. This review discusses major contributing signaling pathways involved in the pathophysiology of lung cancer, as well as currently available treatments and prospective drug candidates. The anticancer potential of naturally occurring bioactive compounds in the context of lung cancer is also discussed, with critical analysis of their mechanistic actions presented by preclinical and clinical studies.

From past several years the conventional methods are generally employed in plant material extraction that include Soxhlet, reflux apparatus but the method is time consuming and requires solvent in large quantity. To overcome this problem the novel extraction technique are nowadays used for the extraction of the plant material. The Microwave assisted extraction technique offers several advantages over conventional method i.e. low solvent consumption, shortened extraction time with increased purity and yield of bioactive phytoconstituents. Operculina turpethum (Convolvulaceae) found throughout India at an altitude of about 1000m and commercially cultivated in Ceylon, tropical America, Mauritius, Philippines, Australia and tropical Africa. In India it is sometimes grown in gardens as an ornamental plant. The roots/ rhizomes of the Operculina turpethum was extracted by conventional and microwave assistant extraction using various solvents pet. ether, ethyl acetate, methanol, hydroalcholic and aqueous solvents. The result indicates that the microwave extraction process gives high yield of phytoconstituent when compared with conventional methods. The extracts obtained by both the process were further evaluated for assessment of total phenolic, flavonoid and saponin content. The research findings suggest that the microwave assisted extraction techniques has remarkably increased the phenolic, flavonoid and saponin content in the extract. Furthermore, microwave irradiation method proved to be a rapid and improved system for the plant extraction.