Yenepoya University

The transformation of a normal cell state to malignant cell is a multifactorial process, as cancer is a complex network of diseases. There are various types of cancer, each with its own underlying mechanisms and symptoms. The rise in modernization has significantly limited the mobility and has also altered the diets, leading to an increased rate of cancer mortality worldwide. The treatment options in cancer therapy, such as chemotherapy and radiotherapy, result in compromising the well-being of patients with cancer. Nanoformulation has emerged as convincing tools in cancer drug delivery. In order to gather pertinent information on Nanoformulations in Cancer Patents and Clinical Trials from the year 2000 to 2026, the majority of the electronic databases including Google Scholar, Embase, Web of Science, Scopus, and PubMed/MEDLINE were searched. The key benefits of nanoformulation lie in their ability to enhance the water solubility of drugs, thereby overcoming the limitations of traditional drug formulations. The nanoformulation facilitates efficiency and enhances therapeutic efficacy. The perfection portrayed by nanoformulation in carrying the therapeutics with better performance. This article provides comprehensive details on nanoformulation-based patents and clinical trials of various cancer conditions and draws attention to novel formulation of drugs that has been designed to target specific diseases. The article will likely discuss the outcomes of the clinical trials that evaluated the effectiveness of the formulations. The current nanoformulation-based therapies can be a potential source to address the unmet medical needs that advance the patient outcomes.

Microbiology Society journals contain high-quality research papers and topical review articles. We are a not-for-profit publisher and we support and invest in the microbiology community, to the benefit of everyone. This supports our principal goal to develop, expand and strengthen the networks available to our members so that they can generate new knowledge about microbes and ensure that it is shared with other communities.

Congenital heart defects (CHDs) remain a leading cause of infant morbidity and mortality worldwide, with current treatments largely focused on symptomatic management rather than addressing underlying genetic causes. This study evaluates the effectiveness, therapeutic potential, and clinical feasibility of CRISPR-based gene-editing interventions in the personalized treatment of CHDs. Using a quantitative research design, data were collected from clinical trials, laboratory experiments, and genomic datasets, with stratified sampling to ensure representation across different CHD types and genetic mutations. Statistical analyses assessed gene correction rates, improvements in cardiac function, survival, symptom reduction, and quality of life, alongside safety metrics including adverse effects, off-target mutations, and immune responses. Results indicate that advanced CRISPR techniques such as base editing and prime editing—achieved high mutation correction rates (72%–88%) with low off-target effects (1.5%–6%) and meaningful improvements in cardiac function (60%–75%). Personalized approaches, including patient-specific guide RNAs, iPSC-based ex vivo editing, genomic profiling-guided prime editing, and AI-assisted targeting, led to increased survival (30%–40%), reduced symptoms (55%–65%), decreased hospital readmissions, and enhanced quality of life (65%–75%), with all findings statistically significant (p < 0.05). Safety evaluation demonstrated acceptable adverse effect rates (6%–14%) and moderate immune responses (4%–9%), while ethical compliance and clinical feasibility scores were high (7.0–9.0 and 6.5–8.5, respectively). These findings suggest that CRISPR-based therapies are both effective and clinically feasible for personalized CHD treatment, supporting a shift from symptom-based interventions to curative, gene-targeted strategies. Future research should focus on optimizing delivery systems, ensuring long-term safety, and developing scalable clinical protocols to advance precision medicine for CHDs.

Alzheimer's disease (AD) is a catastrophic neurodegenerative disorder marked by progressive decline of cognitive function, memory loss, and neuronal death. Its pathology is characterized by the formation of extracellular amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles from tau hyperphosphorylation. Despite extensive research, current treatments are limited to symptomatic relief and are associated with significant side effects. This accentuates the critical need for alternative therapeutic strategies with potent neuroprotective effects and minimal toxicity. This study investigates the neuroprotective potential of glycyrrhizic acid, as the precise molecular mechanisms by which it might improve AD pathology remain poorly understood. Using an Aβ42-induced IMR-32 cell model of AD, our research revealed that Aβ42 treatment caused significant protein alterations associated with AD pathology, mitochondrial dysfunction, cell cycle re-entry, and synaptic activity. Co-treatment with glycyrrhizic acid not only restored these protein levels, but also mitigated the hyperactivation of several key signaling pathways and rescued neurons from apoptosis. These findings suggest that glycyrrhizic acid exerts neuroprotective effects by preventing mitochondrial dysfunction and apoptosis via modulation of critical signaling pathways. This study provides strong evidence for glycyrrhizic acid's neuroprotective properties in AD, paving the way for further research into its potential as a promising therapeutic agent for Alzheimer's disease.

Accurate and early detection of bone cancer is critical for improving patient outcomes, yet conventional radiographic interpretation remains limited by subjectivity and variability. Conventional AI models often struggle with complex multi-modal noise distributions, non-convex and topologically entangled latent manifolds, extreme class imbalance in rare oncological conditions, and heterogeneous data fusion constraints. To address these challenges, we present a Quantum-Inspired Classical Convolutional Neural Network (QC-CNN) inspired by quantum analogies for automated bone cancer detection in radiographic images. The proposed architecture integrates classical convolutional layers for hierarchical feature extraction with a classical variational layer motivated by high-dimensional Hilbert space analogies for enhanced pattern discrimination. A curated and annotated dataset of bone X-ray images was utilized, partitioned into training, validation, and independent test cohorts. The QC-CNN was optimized using stochastic gradient descent (SGD) with adaptive learning rate scheduling, and regularization strategies were applied to mitigate overfitting. Quantitative evaluation demonstrated superior diagnostic performance, achieving high accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). Results highlight the ability of classical CNN with quantum-inspired design to capture non-linear correlations and subtle radiographic biomarkers that classical CNNs may overlook. This study establishes QC-CNN as a promising framework for quantum-analogy motivated medical image analysis, providing evidence of its utility in oncology and underscoring its potential for translation into clinical decision-support systems for early bone cancer diagnosis. All computations in the present study are performed using classical algorithms, with quantum-inspired concepts serving as a conceptual framework for model design and motivating future extensions.

Lung inflammation, injury, and fibrosis are interconnected facets of respiratory health. Damage to the inherent lung architecture and tissue scarring resulting from excessive extracellular matrix deposition are the most important characteristics of lung injury and fibrosis. Although the current treatment strategy like Pirfenidone and Nintedanib, is effective in slowing the disease progression, they do not offer a complete cure. To suppress inflammation and pulmonary fibrosis progression, a variety of phytochemical drugs (Polyphenols, alkaloids, terpenoids, and carotenoids) have been investigated in the last decade. The bare administration of phytochemical drugs results in lower efficacy due to their low bioavailability, non-specific release, and inadequate absorption in the lungs. With recent advancements in nanotechnology-based drug delivery systems, researchers are highlighting the advantages of phytochemical drug delivery through a nanomedicine approach, with enhanced lung targetability and efficacy. In this review, the role of phytochemical drugs and the current status of phytochemical delivery using various nanocarriers (Polymeric, lipid, inclusion complexes, metal-organic frameworks, hybrid, and lung targetable nanocarriers) for treating lung inflammation and fibrosis are presented.

Abstract Gastric cancer is driven by aberrant kinase signaling that promotes uncontrolled proliferation and malignant progression. Calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2) is overexpressed in gastric cancer; however, the global phosphorylation networks downstream of CAMKK2 remain incompletely defined. In this study, we investigated the functional and signaling consequences of CAMKK2 inhibition in gastric cancer cells using an integrated phenotypic and quantitative phosphoproteomics approach. Pharmacological inhibition of CAMKK2 using STO-609 in AGS cells significantly suppressed proliferation, clonogenic growth, migration, and invasion, and induced defects in nuclear morphology indicative of impaired cell cycle progression. Tandem mass tag (TMT) based phosphoproteomic profiling identified over 10,500 phosphopeptides and revealed extensive phosphoproteome remodeling following CAMKK2 inhibition, characterized predominantly by hypophosphorylation of proteins involved in nuclear signaling, RNA processing, and cell cycle regulation. Kinase substrate enrichment and motif analyses demonstrated coordinated attenuation of CDK, MAPK, and mitotic kinase-associated signaling pathways, with convergence on E2F regulated transcriptional programs. Collectively, these findings establish CAMKK2 as a central regulator of kinase signaling networks that sustain proliferative and malignant phenotypes in gastric cancer and highlight CAMKK2 inhibition as a potential therapeutic strategy.

Malaria is associated with decreased semen quality, oligozoospermia, necrozoo-spermia/azoospermia. Antimalarial-drugs have adverse-effects on re¬productive functions. (40-90) % of male infertility is due to scarce sperm production of obscure source. This review was undertaken to understand the effects of malaria/dengue and antimalarial drugs on reproductive health. A broad systematic exploration was steered, using electronic databases, limiting to articles (English) using words- "Infertility", "Malaria", "Preterm birth", "Dengue" etc., (2013-2024), to identify relevant studies. Malaria causes decreased semen quality in men; higher rates of miscarriage, intrauterine demise, premature delivery, LBW, neonatal deaths, anemia and maternal deaths in pregnancy. Antimalarial-drugs (chloroquine, quinine, quinacrine, pyrimethamine) cause male infertility. Acute dengue infection leads to temporary alterations in sperm but not long-term infertility; during pregnancy it causes an increased risk of premature delivery, fetal death, and hemorrhagic complications. Malaria/dengue affect reproductive health in humans, indirect effect being infertility due to antimalarial-drugs.