Ganpat University

Nanotechnology has significantly transformed the field of cancer diagnostics and therapeutics by introducing advanced biomedical devices. These nanotechnology-based devices exhibit remarkable capabilities in detecting and treating various cancers, addressing the limitations of traditional approaches, such as limited specificity and sensitivity. This review aims to explore the advancements in nanotechnology-driven biomedical devices, emphasizing their role in the diagnosis and treatment of cancer. Through a comprehensive analysis, we evaluate various nanotechnology-based devices across different cancer types, detailing their diagnostic and therapeutic effectiveness. The review also discusses FDA-approved nanotechnology products, patents, and regulatory trends, highlighting the innovation and clinical impact in oncology. Nanotechnology-based devices, including nanobots, smart pills, and multifunctional nanoparticles, enable precise targeting and treatment, reducing adverse effects on healthy tissues. Devices such as DNA-based nanorobots, quantum dots, and biodegradable stents offer noninvasive diagnostic and therapeutic options, showing high efficacy in preclinical and clinical settings. FDA-approved products underscore the acceptance of these technologies. Nanotechnology-based biomedical devices offer a promising future for oncology, with the potential to revolutionize cancer care through early detection, targeted treatment, and minimal side effects. Continued research and technological improvements are essential to fully realize their potential in personalized cancer therapy. Graphical abstract

The selective estrogen receptor modulator (SERM) raloxifene hydrochloride (RLH) is used extensively in the management and prevention of breast cancer and osteoporosis. Recent clinical studies show the repurposing of RLH in various diseases based on its structure and some clinical trials studies. Optimizing the clinical effectiveness of this important drug requires a thorough review of the formulation techniques, patent environment, and analytical procedures. The purpose of this study is to give a thorough understanding of dug repurposing with the most recent formulation strategies, patents, and analytical methods related to RLH. Highlighting recent developments, pointing out current issues, and suggesting future lines of inquiry and development are the objectives. A thorough literature analysis was carried out with an emphasis on repurposing of RLH for various diseases and analytical techniques employed in the measurement and quality control of RLH. These techniques included spectroscopic, chromatographic, and electrochemical approaches. Key advancements and trends were found by analyzing patent databases. The evaluation also looked into formulation techniques intended to improve the medicine’s therapeutic efficacy and bioavailability, notably cutting-edge drug delivery methods. For the study of RLH, the review identifies several sophisticated analytical techniques that provide increased accuracy and robustness. Significant innovation has been revealed by the patent landscape, particularly in formulations targeted at enhancing solubility and bioavailability. Notable formulation techniques that overcome the drawbacks of conventional techniques include transdermal patches, nanoparticulate systems, and various drug delivery techniques. Graphical Abstract

Targeted therapy for colorectal cancer (CRC) appears to have great potential with lipid nanoparticles (LNPs). The advances in LNP-based techniques, such as liposomes, exosomes, micelles, solid lipid nanoparticles (SLNs), nano-cubosomes, and plant- derived LNPs (PDLNPs), are explored in detail in this thorough review. Every platform provides distinct advantages: liposomes enable precise drug release and improved delivery; exosomes function as organic nanocarriers for focused treatment; SLNs offer greater stability; micelles enhance drug solubility and resistance; nano-cubosomes tackle low bioavailability; and PDLNPs offer biocompatible substitutes. The mechanisms, benefits, drawbacks, and therapeutic potential of these LNP platforms in the treatment of colorectal cancer are highlighted in the review. The review highlights how crucial it is to use these technologies for efficient CRC management and looks at potential future developments for them. The controlled release properties of liposomes and solid liposome nanoparticles (SLNs) improve the stability and bioavailability of medicinal compounds. On the other hand, exosomes and micelles provide answers for medication resistance and solubility issues, respectively. Novel strategies for resolving bioavailability problems and enhancing biocompatibility include nano-cubosomes and PDLNPs. These LNP-based systems are promising in clinical applications for boosting therapeutic efficacy, decreasing systemic toxicity, and facilitating tailored drug delivery. By incorporating these nanotechnologies into CRC treatment plans, present therapeutic approaches may be completely changed, and more individualized and efficient treatment choices may be provided. To completely comprehend the advantages and drawbacks of these LNP systems in therapeutic settings, as well as to and optimize them, more study is recommended by the review. Treatment for colorectal cancer may be much improved in the future thanks to developments in LNP-based drug delivery systems. These technologies hold great promise for improving patient outcomes and advancing the field of oncology by tackling important issues related to medication delivery and bioavailability.

Nanotechnology has experienced significant advancements, attracting considerable attention in various biomedical applications. This innovative study synthesizes and characterizes Ge/PLA/AuNCs (gelatin/PLA/gold nanocomposites) using Syzygium cumini extract to evaluate their various biomedical applications. The UV–Visible spectroscopy results in an absorption peak at 534 nm were primarily confirmed by Ge/PLA/AuNCs synthesis. The FTIR spectrum showed various functional groups and the XRD patterns confirmed the crystalline shape and structure of nanocomposites. The FESEM and HRTEM results showed a oval shape of Ge/PLA/AuNCs with an average particle size of 21 nm. The Ge/PLA/AuNC’s remarkable antioxidant activity, as evidenced by DPPH (70.84 ± 1.64%), ABTS activity (86.17 ± 1.96%), and reducing power activity (78.42 ± 1.48%) at a concentration of 100 μg/mL was observed. The zone of inhibition against Staphylococcus aureus (19.45 ± 0.89 mm) and Echericia coli (20.83 ± 0.97 mm) revealed the excellent antibacterial activity of Ge/PLA/AuNCs. The anti-diabetic activity of Ge/PLA/AuNCs was supported by inhibition of α-amylase (82.56 ± 1.49%) and α-glucosidase (80.27 ± 1.57%). The anti-Alzheimer activity was confirmed by inhibition of the AChE (76.37 ± 1.18%) and BChE (85.94 ± 1.38%) enzymes. In vivo studies of zebrafish embryos showed that Ge/PLA/AuNCs have excellent biocompatibility and nontoxicity. The SH-SY5Y cell line study demonstrated improved cell viability (95.27 ± 1.62%) and enhanced neuronal cell growth following Ge/PLA/AuNCs treatment. In conclusion, the present study highlights the cost-effective and non-toxic properties of Ge/PLA/AuNCs. Furthermore, it presents an attractive and promising approach for various future biomedical applications.

The investigation of computational techniques to forecast the bioactivity of natural substances has been spurred by the growing interest in utilizing their medicinal potential. A branch of artificial intelligence called deep learning has been particularly useful for predicting outcomes in a variety of fields, such as bioactivity prediction and drug discovery, by evaluating large amounts of complex data. An overview of current developments in the application of deep learning techniques to the prediction of natural chemical bioactivity has been presented in this article. The advantages provided by deep learning approaches, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and graph neural networks (GNNs), have been highlighted, and the difficulties connected with conventional methods of bioactivity prediction have been examined. Moreover, a variety of molecular representations-such as molecular fingerprints, graph representations, and molecular descriptors-that are fed into deep learning models have been studied. Additionally, included in this study is the integration of many data sources, including omics data, chemical structures , and biological tests, to enhance the precision and resilience of bioactivity prediction models. Furthermore, this review covers the uses of deep learning in target prediction, virtual screening, and poly-pharmacology study of natural substances. The paper concludes by discussing the field's present issues and potential paths forward, such as the requirement for standardized benchmark datasets, the interpretability of deep learning models, and the incorporation of experimental validation techniques. All things considered, this study sheds light on the most recent developments in deep learning techniques for estimating the bioactivity of natural substances and their possible effects on drug development and discovery.

Aims This study aimed to develop Imatinib Mesylate (IMT)-loaded Poly Lactic-co-Glycolic Acid (PLGA)-D-α-tocopheryl polyethylene glycol succinate (TPGS)- Polyethylene glycol (PEG) hybrid nanoparticles (CSLHNPs) with optimized physicochemical properties for targeted delivery to glioblastoma multiforme. Background Glioblastoma multiforme (GBM) is the most destructive type of brain tumor with several complications. Currently, most treatments for drug delivery for this disease face challenges due to the poor blood-brain barrier (BBB) and lack of site-specific delivery. Imatinib Mesylate (IMT) is one of the most effective drugs for GBM, but its primary issue is low bioavailability. Therefore, nanotechnology presents a promising solution for targeted IMT delivery to GBM. This article primarily explores the fabrication of IMT-loaded core-shell lipid-polymer hybrid nanoparticles (CSLHNPs) to achieve enhanced brain delivery with therapeutic efficacy. Objective The primary objective of this study is to develop optimized, stable IMT-loaded hybrid nanoparticles with an encapsulated polymer matrix and to evaluate these nanoparticles using sophisticated instruments such as SEM and TEM to achieve smooth, spherical nanoparticles in a monodispersed phase. Method The enhanced stable formulation yielded a notable increase in entrapment efficiency, reaching 58.89 ± 0.5%. The physical stability analysis of nanoparticles was assessed over 30 days under conditions of 25 ± 2°C and 60 ± 5% relative humidity. Hemolytic assays affirmed the biocompatibility and safety profile of the nanoparticles. in vitro drug release kinetics revealed a sustained IMT release over 48 hours. Results The formulated CSLHNPs achieved a narrow size distribution with a mean vesicle diameter of 155.03 ± 2.41 nm and a low polydispersity index (PDI) of 0.23 ± 0.4, indicating monodispersity. A high negative zeta potential of -23.89 ± 3.47 mV ensured excellent colloidal stability in physiological conditions. XRD analysis confirmed the successful encapsulation of IMT within the nanoparticle matrix, with the drug transitioning to an amorphous state for enhanced dissolution. During Cell-Cell viability assays on LN229, glioblastoma cells were treated with IMT-loaded nanoparticles and showed a significantly enhanced inhibitory effect compared to free IMT. These hybrid nanoparticles demonstrated potential in reducing oxidative stress-induced cellular damage by mitigating reactive oxygen species (ROS). Thus, the prepared IMT hybrid nanoparticles showed higher cellular uptake and superior cytotoxicity compared to the plain drug. Conclusion This study posits the IMT-PLGA-TPGS-DSPE PEG 2000-CSPLHNPs as a formidable and innovative drug delivery system for Glioblastoma Multiforme (GBM) treatment, warranting further exploration into their clinical application potential. Future work could involve conducting in vivo studies to evaluate the pharmacokinetics, biodistribution, and therapeutic efficacy of the IMT-PLGA-TPGS-DSPE PEG 2000-CSPLHNPs in animal models of Glioblastoma Multiforme (GBM). Additionally, further research may focus on optimizing the nanoparticle formulation for enhanced targeting capabilities, investigating long-term stability under varied storage conditions, exploring potential combination therapies to synergize with the nanoparticles, and assessing the scalability and manufacturability of the developed drug delivery system for potential clinical translation. Integration of advanced imaging techniques for real- time tracking and visualization of nanoparticle distribution within tumours could also be a promising direction for future investigations.

Therapeutic hurdles persist in the fight against lung cancer, although it is a leading cause of cancer-related deaths worldwide. Results are still not up to par, even with the best efforts of conventional medicine, thus new avenues of investigation are required. Examining how immunotherapy, precision medicine, and AI are being used to manage lung cancer, this review shows how these tools can change the game for patients and increase their chances of survival. In the fight against cancer, immunotherapy has demonstrated encouraging results, especially in cases of small cell lung cancer [SCLC] and non-small cell lung cancer [NSCLC]. A key component in improving T cell responses against tumours is the use of immune checkpoint inhibitors, which include PD-1/PD-L1 and CTLA-4 blockers. Cancer vaccines and CAR T-cell therapy are two examples of adoptive cell therapies that might be used to boost the immune system's ability to eliminate tumours. In order to improve surgical results and decrease recurrence, neoadjuvant immunotherapy is being investigated for its ability to preoperatively reduce tumours. Precision medicine tailors treatment based on individual genetic profiles and tumour features, boosting therapeutic efficacy and avoiding unwanted effects. For certain types of non-small cell lung cancer [NSCLC], targeted treatments based on mutations in genes including EGFR, ALK, and ROS1 have shown excellent results. When it comes to optimizing treatment regimens, biomarker-driven approaches guarantee that the patients most likely to benefit from particular medicines are selected. Artificial intelligence [AI] is revolutionizing lung cancer care through increased diagnostic accuracy, prognostic assessments, and therapy planning. Machine learning algorithms examine enormous information to detect trends and forecast outcomes, permitting individualized treatment techniques. AI-driven imaging tools enable early diagnosis and monitoring of disease progression, while predictive models assist in evaluating therapy responses and potential toxicity. The convergence of these advanced technologies holds promise for overcoming the constraints of conventional therapy. Combining immunotherapy with targeted treatments and utilizing AI for precision medicine delivers a multimodal approach that tackles the heterogeneous and dynamic nature of lung cancer. The incorporation of these new tactics into clinical practice demands cross-disciplinary collaboration and continuing study to develop and confirm their effectiveness. The synergistic application of immunotherapy, precision medicine, and AI constitutes a paradigm shift in lung cancer management. These discoveries provide a robust basis for individualized and adaptable therapy, potentially altering the prognosis for lung cancer patients. Ongoing research and clinical studies are vital to unlocking the full potential of these technologies, paving the way for enhanced therapeutic outcomes and improved quality of life for people battling this tough disease.

This review assesses the antiviral capabilities of antimicrobial peptides (AMPs) against SARS-CoV-2 and other respiratory viruses, focussing on their therapeutic potential. AMPs, derived from natural sources, exhibit promising antiviral properties by disrupting viral membranes, inhibiting viral entry, and modulating host immune responses. Preclinical studies demonstrate that peptides such as defensins, cathelicidins, and lactoferrin can effectively reduce SARS-CoV-2 replication and inhibit viral spread. In addition, AMPs have shown potential in enhancing the host’s antiviral immunity. Despite these promising outcomes, several challenges require assessments before transforming into clinical translation. Several issues related to peptide stability, cytotoxicity, and efficient delivery systems pose significant limitations to their therapeutic application. Recent advancements in peptide engineering, nanotechnology-based delivery systems, and peptide conjugation strategies have improved AMPs stability and bioavailability; however, further optimization is essential. Moreover, whilst AMPs are safe, their effects on host cells and tissues need a thorough investigation to minimise potential adverse reactions. This review concludes that whilst AMPs present a promising route for antiviral therapies, particularly in targeting SARS-CoV-2, extensive clinical trials and additional studies are required to overcome current limitations. Future research should focus on developing more stable, less toxic AMPs formulations with enhanced delivery mechanisms, aiming to integrate AMPs into viable therapeutic options for respiratory viral diseases, including COVID-19 and other emerging infections.

The central nervous system is affected by multiple sclerosis (MS), a chronic autoimmune illness characterized by axonal destruction, demyelination, and inflammation. This article summarizes the state of the field, highlighting its complexity and significant influence on people's quality of life. The research employs a network pharmacological approach, integrating systems biology, bioinformatics, and pharmacology to identify biomarkers associated with MS. Utilizing Nelumbo Nucifera (Lotus) seeds, the study involves toxicity assessments, biomolecule screening, and target prediction. Advanced computational methodologies are employed, including molecular docking and dynamic simulations, to assess potential therapeutic interactions. Biomolecule screening identifies eight active compounds from Lotus seeds, including Anonaine and Liriodenine. Target prediction reveals 264 common targets with MS-related genes. Protein-protein interaction analysis establishes a complex network, identifying central targets like SRC and AKT1. Bioinformatics enrichment analysis uncovers potential therapeutic candidates and pathways. A Biomolecule-Target-Pathway network diagram visualizes interactions, with Anonaine and Liriodenine exhibiting strong binding affinities in molecular docking studies. Molecular dynamics simulations provide insights into dynamic interactions. In conclusion, through advanced computational techniques, it unveils molecular interactions, potential therapies, and pathways, bridging predictions with practical applications. Anonaine and Liriodenine show promise in curbing MS biomarkers.

Microplastic pollution has become a significant environmental concern globally, particularly in urban water bodies due to the discharge of plastic waste and runoff from various sources. The global distribution of microplastic, predominant polymer constituents, and variability in concentration are explored, emphasizing the need for standardized monitoring protocols and increased research efforts. This chapter provides a comprehensive examination of microplastic pollution in urban water bodies, focusing on its resources, detection, characterization, and implication for ecosystem health and human well-being. Furthermore, the chapter addresses emerging concerns regarding microplastic contamination in sources, highlighting the necessity for improved quality assurance in sampling and analysis. Traditional methods for assessing microplastic pollution often rely on visual identification, which can be time-consuming and prone to errors. Polymer analysis offers a promising approach to overcome these limitations by providing precise identification and quantification of microplastic in water samples. This chapter explores the principles and techniques of polymer analysis for assessing microplastic pollution in urban water bodies, highlighting its importance in understanding the extent and sources of contamination. Advanced analytical methods such as FTIR, Raman spectroscopy, SEM-EDS, and thermo-analytical methods are critically evaluated alongside innovative approaches like tagging methods and liquid chromatography. Furthermore, the chapter discusses the integration of polymer analysis with statistical modeling and geographic information systems (GIS) for comprehensive spatial mapping and risk assessment of microplastic pollution hotspots. Overall, this chapter provides valuable insights into the role of polymer analysis in advancing our knowledge of microplastic pollution and promoting sustainable management practices in urban water bodies.

Nanobots are incredibly tiny, autonomously operating, and driven electronic devices or tiny robots that can be designed or remotely instructed to do some particular functions like detection, drug delivery, or diagnosis. They have been recognized as an innovative tool to be used in the biomedical industry. The field of nanobotics has become increasingly interested in the growing efforts to create miniature automated systems that can effectively convert energy into functional movement. Smart nanobots, which differ from traditional huge mechanical robots, provide their application in gene therapy, cancer treatment, surgery, and disease diagnosis. The total command over the bots at all times and the extremely low likelihood of any negative effects are the major characteristics that set nanobots apart from other traditional or new dosing forms. Micro- and nanobots have the ability to deliver medications to the desired locations. In this review, we have discussed nanobots, their design, types, working in the body, and applications in pharmaceuticals.

The development of precise and reliable cancer treatments has been a long-standing goal in oncology. Conventional therapies often affect healthy tissues, leading to significant side effects. To overcome these challenges, researchers are exploring new methodologies that combine advanced drug delivery systems with state-of-the-art imaging technologies to target tumors more effectively. This study aims to investigate a novel approach that integrates smart drug delivery systems with real-time imaging modalities. The goal is to enhance the targeted delivery of therapeutic agents to cancer cells, minimizing damage to healthy tissues while improving the overall efficacy of cancer treatments. Smart drug delivery systems are designed to transport medications directly to tumor sites, enhancing treatment precision. When combined with real-time imaging tools such as MRI, CT, PET, and molecular imaging, these systems offer real-time data on the tumor’s location, size, and response to treatment. This allows for immediate adjustments in therapy, ensuring optimal drug delivery and reducing side effects. However, the implementation of this approach also faces challenges, including the need for stringent safety protocols and adherence to regulatory standards. The integration of advanced drug delivery systems with cutting-edge imaging technologies presents a promising approach to cancer therapy. By enabling more precise treatment targeting and reducing adverse effects, this strategy has the potential to significantly improve patient outcomes in the fight against cancer.

The growth of nanostructured lipid carriers for brain targeting shows a promising strategy for escalating the therapeutic efficacy of antiepileptic drugs such as carbamazepine (CBZ). CBZ is a drug of choice in the management of epilepsy and trigeminal neuralgia. However, CBZ oral administration is associated with poor bioavailability, successive dose adjustments, and long-term adverse effects. The current research was intended to develop brain-targeted CBZ-loaded nanostructured lipid carriers (CBZ-NLCs) with the help of the design of experiments to improve anti-epileptic potential. The CBZ-NLCs were fabricated by using an ultrasonication approach using different surfactants such as Tween 80, Compritol ATO 888, and oleic acid. The different formulation variables were screened with the help of the Plackett–Burman design which significantly affects the development of CBZ-NLCs. The Box-Behnken design is employed to assess the interactions between these formulation parameters and the variability between the different batches. In the Plackett–Burman design, Pareto ranking analyses indicated that the amount of solid lipid, concentration of surfactant, speed of homogenization, and homogenization time significantly affected the formulation of CBZ-NLCs. These variables were further evaluated employing the Box-Behnken design. The outcome of the Box-Behnken design was authenticated by preparing the recommended optimized solution, which yielded 205 ± 0.87 nm particle size along with an adequately superior entrapment efficiency of 75.21 ± 0.98% and 74.89 ± 1.01% cumulative drug release in 24 h. The plasma concentration, along with the absorption rate, was greater compared to that of the CBZ solution. AUC for the fabricated formulation was 985.32 ± 21.25 µg h/ml while 245 ± 1.11 µg h/ml for CBZ. The groups treated with CBZ-NLCs and diazepam had a 100% survival rate, and the groups treated with saline and CBZ dispersion had 100% and 30% fatality rates, respectively. It could be concluded that the application of experimental design is a helpful tool for the development of CBZ-NLCs. The prepared formulation could be administered via the non-invasive nasal route and shall be effective in the management of epilepsy.

The delivery of therapeutic agents to the eye presents significant challenges due to various anatomical and physiological barriers, leading to low bioavailability in conventional formulations. Polymeric nanoparticles (PNPs) offer a promising solution for overcoming these obstacles in ocular drug delivery. These submicron-sized particles, composed of biocompatible and biodegradable polymers, can encapsulate a wide range of therapeutic compounds, including proteins, genes, and small molecules, allowing for targeted and sustained delivery to specific ocular tissues. The advantages of PNPs include enhanced drug bioavailability, prolonged retention time, and reduced systemic side effects, which are critical in treating major ocular diseases such as glaucoma, cataracts, age-related macular degeneration, dry eye syndrome, and diabetic retinopathy. The selection of polymers like chitosan, polyethylene glycol, and poly (lactic-co-glycolic acid) is crucial due to their biocompatibility and biodegradability, ensuring safe and effective ocular treatment. Moreover, surface modifications, such as PEGylation and ligand attachment, enhance the targeting and therapeutic efficacy of PNPs. Despite these advancements, challenges in drug encapsulation efficiency, stability during storage, and maintaining sterility remain. Nonetheless, the development of PNP-based formulations represents a significant advancement in ophthalmic therapeutics, offering the potential for improved patient outcomes in the management of ocular diseases. Graphical Abstract

Diabetes is a medical condition, which belongs to the group of chronic diseases that affects how body processes glucose, the primary source of energy for cells. Glucose comes indirectly from the consumed food and is carried by bloodstream to various cells in body. Insulin, a hormone synthesized by pancreas play a vital role in conversion of glucose to energy. Managing diabetes involves regular monitoring of blood sugar levels, adopting a healthy diet, engaging in regular physical activity, and taking medications or insulin as prescribed by a healthcare provider. Proper management of diabetes may lead to prevention or delay of diabetic complications may further sever other diseases associated impediment. Drug delivery in the management of diabetes is designed to administer insulin or other diabetes medications in a controlled and convenient manner. Recently several natural products have been studied and reported for their potential role in managing diabetes. While they may not replace standard medical treatments, some of these natural products could complement existing therapies and support overall diabetes management. In this review phyto‐pharmacological aspect of bioactive in the management of diabetes has been elaborated. Moreover, their fortification within nanocarriers was further taken in discussions with update information on clinical trial study.

Cephalosporins, a widely utilized class of antibiotics in clinical settings for bacterial infections, are the focus of this critical analysis. This examination aims to provide a comprehensive description, encompassing their range, generational distinctions, and therapeutic applications. Renowned for their versatility against both Gram-positive and Gram-negative bacteria, cephalosporins have evolved over generations, enhancing efficacy and addressing resistance patterns. Each generation possesses unique characteristics crucial for clinical utility. Primarily targeting Gram-positive cocci, first-generation cephalosporins exhibit a broadened spectrum in subsequent generations, encompassing Gram-negative species. Advancements in penetration into tissues and resistance against beta-lactamases contribute to increased effectiveness as generations progress. Clinically, cephalosporins find application across diverse medical disciplines, from intricate hospital environments to community-acquired illnesses. A comprehensive understanding of each generation's distinct features empowers clinicians to tailor treatment regimens, optimizing therapeutic outcomes and mitigating resistance risks. This meticulous examination consolidates the latest available information on cephalosporins, serving as an invaluable resource for medical professionals involved in antibiotic prescription and infection management. A profound understanding of cephalosporin characteristics and generations proves indispensable in navigating the dynamic landscape of bacterial resistance, ultimately enhancing patient care.

] Cystic fibrosis (CF) is a hereditary disorder characterized by mutations in the CFTR gene, leading to impaired chloride ion transport and subsequent thickening of mucus in various organs, particularly the lungs. Despite significant progress in CF management, current treatments focus mainly on symptom relief and do not address the underlying genetic defects. Stem cell and gene therapies present promising avenues for tackling CF at its root cause. Stem cells, including embryonic, induced pluripotent, mesenchymal, hematopoietic, and lung progenitor cells, offer regenerative potential by differentiating into specialized cells and modulating immune responses. Similarly, gene therapy aims to correct CFTR gene mutations by delivering functional copies of the gene into affected cells. Various approaches, such as viral and nonviral vectors, gene editing with CRISPR-Cas9, small interfering RNA (siRNA) therapy, and mRNA therapy, are being explored to achieve gene correction. Despite their potential, challenges such as safety concerns, ethical considerations, delivery system optimization, and long-term efficacy remain. This review provides a comprehensive overview of the current understanding of CF pathophysiology, the rationale for exploring stem cell and gene therapies, the types of therapies available, their mechanisms of action, and the challenges and future directions in the field. By addressing these challenges, stem cell and gene therapies hold promise for transforming CF management and improving the quality of life of affected individuals.

This study aimed to develop and optimize glimepiride microparticles (GM) using the solvent evaporation technique, employing polymers like ethyl cellulose, Eudragit RL100, and RS100 in various ratios. The optimized GM formulation (F2) demonstrated a mean particle size of 1.75 μm, a polydispersity index (PDI) of 0.59, and a zeta potential of 1.396 mV. In vitro drug release studies revealed that formulation F2 achieved 83.26% drug release over 8 h. FTIR analysis confirmed no significant interaction between the drug and excipients, while DSC and XRD analyses indicated an amorphous nature of the GM. SEM analysis showed a smooth and spherical particle surface. In vivo studies on a zebrafish model demonstrated that GM exhibited a significant antidiabetic effect with no observable toxicity, suggesting that GM is a promising candidate for enhancing the oral bioavailability and therapeutic efficacy of Glimepiride. Graphical Abstract