Introduction: Hepatocellular Carcinoma (HCC) remains a highly lethal malignancy with limited therapeutic options, particularly in advanced stages. Yindan Pinggan Capsule (YDPG), a Traditional Chinese Medicine (TCM) formulation with hepatoprotective properties, has shown potential in liver diseases; however, its anti-tumor effects against HCC and the underlying mechanisms remain unclear. This study aimed to evaluate the anti-tumor effects of YDPG against HCC, elucidate its molecular mechanisms, and investigate its potential synergistic effects with Sorafenib. Methods: Network pharmacology was performed to predict potential targets and pathways of YDPG against HCC. Anti-tumor effects were evaluated in vitro using CCK-8, colony formation, and flow cytometry assays, and in vivo using subcutaneous allograft, orthotopic liver tumor, and Diethylnitrosamine (DEN)/ carbon tetrachloride (CCl4)-induced HCC mouse models. RNA sequencing, RT-qPCR, Western blot, immunofluorescence, mass spectrometry, and agonist treatment assays were conducted to elucidate the underlying mechanisms. Results: Network pharmacology analysis identified cell cycle-related pathways and proliferation-associated genes, including Ccnd1 and Myc, as potential targets of YDPG. YDPG markedly inhibited HCC cell proliferation and induced G1/S phase arrest in vitro, and significantly suppressed tumor growth in mouse models in vivo. Mechanistically, YDPG activated G protein-coupled bile acid receptor 1 (TGR5), thereby inhibiting YAP nuclear translocation and suppressing Gli1 expression, ultimately downregulating the downstream oncogenic regulators c-Myc and Cyclin D1. Notably, YDPG exhibited synergistic anti-tumor effects with low-dose Sorafenib, achieving comparable efficacy to that of high-dose Sorafenib alone. Discussion: By activating TGR5 and inhibiting YAP and Hedgehog pathways, YDPG functions as a multitargeting agent with a distinct mechanism from conventional HCC therapies. Its synergy with low-dose Sorafenib offers a potential strategy to reduce targeted therapy-related toxicity without compromising efficacy, supporting the integration of mechanistically characterized TCM into conventional HCC treatment. Conclusion: These findings demonstrate that YDPG suppresses HCC progression through activation of TGR5 and simultaneous inhibition of the YAP and Hedgehog signaling pathways. Moreover, YDPG enhances the anti-tumor efficacy of Sorafenib, highlighting its translational potential as an adjuvant therapeutic strategy for HCC.
Introduction: Transdermal delivery of prednisolone using solid-lipid nanoparticles (SLN) offers a promising strategy to enhance drug administration by enabling direct transport through the skin into the systemic circulation. However, the impact of processing conditions on the physicochemical properties and release mechanisms of prednisolone‑loaded SLN remains insufficiently explored. Methods: The present study developed prednisolone-loaded SLN using an emulsification–homogenization– ultrasonication approach. Key process parameters, namely homogenization stirring speed and duration, as well as ultrasonication time, temperature, and power, were systematically refined based on particle size, polydispersity index (PDI), and zeta potential. The selected formulation was further characterized for entrapment efficiency (EE), drug loading (DL), attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, differential scanning calorimetry (DSC), transmission electron microscopy (TEM), and in vitro drug release. Results: The experimentally determined DL ranged from 8.52 ± 0.55 to 9.89 ± 1.73%, corresponding to 85-99% of the intended loading, indicating minimal processing loss. Formulation H3, selected for further characterization based on its physicochemical profile, was homogenized at 10,000 rpm for 4 minutes, followed by ultrasonication at 60°C and 60 W for 4 minutes. H3 exhibited a particle size of 319.00 ± 56.15 nm, a PDI of 0.48 ± 0.022, a zeta potential of −19.86 ± 9.56 mV, and an EE of 98.25 ± 0.49%. All formulations demonstrated sustained drug release over 24 h with no statistically significant differences observed among them (p = 0.148). Discussion: Kinetic modeling showed that both Higuchi and Korsmeyer–Peppas models adequately described the release profile of H3, suggesting heterogeneous release behavior involving overlapping diffusion- and matrix- related mechanisms. ATR-FTIR and DSC analyses indicated alterations in intermolecular interactions and lipid packing behavior following nanoparticle formation, while TEM confirmed spherical morphology and absence of visible aggregation, consistent with successful formation of the SLN system. conclusion: This study suggested prednisolone-loaded SLN as a potential transdermal drug delivery system, with sustained drug release profiles. Conclusion: Prednisolone-loaded SLN prepared using emulsification–homogenization–ultrasonication demonstrated favorable physicochemical properties and sustained release behavior governed by combined diffusion and matrix-related processes. Further studies on long-term stability, as well as ex vivo and in vivo skin permeation, are required to confirm their suitability for transdermal application.
INTRODUCTION:Ulcerative Colitis (UC) is a chronic inflammatory disease. Fructus Ailanthi is traditionally known for its anti-inflammatory properties; however, the exact active ingredients and the mechanisms by which it alleviates UC remain incompletely understood. The study comprehensively analyzed the chemical components of Fructus Ailanthi and quantified its total polyphenol and flavonoid contents. Furthermore, network pharmacology and molecular docking were employed to elucidate the mechanisms and potential targets of Fructus Ailanthi in the treatment of ulcerative colitis. METHODS:Qualitative analysis of the components was conducted using preliminary chemical tests and UPLCQ- Orbitrap-MS. Total polyphenols were determined by the Folin-phenol method, and flavonoids were measured using the aluminum nitrate-sodium nitrite colorimetric method. RESULTS:The findings indicated components including phenols, flavonoids, carboxylic acids, and terpenes. The total polyphenol content was 16.46 ± 0.13 mg·g⁻1, and the total flavonoid content was 14.80 ± 0.41 mg·g⁻¹. Components such as stigmast-4-en-3,6a-diol, kaempferol, and quercetin were identified. Key targets included IL6, TP53, SRC, TNF, and HSP90AA1, and these targets were enriched in the PI3K-Akt, MAPK, and NF-κB signaling pathways. The molecular docking analysis indicated that the active compounds in Fructus Ailanthi exhibited a strong affinity for core targets. DISCUSSION:This research elucidated the underlying mechanisms by which Fructus Ailanthi combats ulcerative colitis. Nonetheless, the network of component-target-pathway is grounded in chemical analysis and simulation prediction of components; it is crucial to perform additional cell and animal experiments for validation. CONCLUSION:Fructus Ailanthi regulates ulcerative colitis through the mechanism of multi-component-targetpathway synergy. These findings provide a theoretical basis for the development and utilization of Fructus Ailanthi.
INTRODUCTION/OBJECTIVE:The KRAS G12D mutation is a significant oncogenic factor that promotes cell proliferation and tumor development, particularly in pancreatic cancer. Inhibiting the mutated form of the KRAS protein is a critical strategy in cancer treatment. While molecules like MRTX1133 show promise, the limited efficacy and safety of current treatment options highlight the need to discover new and safer therapeutic candidates. METHODS:Approximately 1000 plant-derived bioactive compounds downloaded from the literature and Dr. Duke's database were filtered according to Lipinski's Rules and pharmacokinetic properties to create a set of 425 candidate molecules. Geometry optimization and QSAR parameters were calculated using Spartan software, and molecular docking and binding affinities were calculated using AutoDock Vina. MRTX1133 was used as a reference in the evaluations. Protein-ligand interaction maps were generated, and key interaction residues were identified using BIOVIA Discovery Studio. Molecular dynamics simulations of 200 ns were performed using Schrödinger-Desmond for the six compounds with the best binding affinities, and MMGBSA binding free energy calculations were performed. RESULTS:The results showed that Isochlorogenic acid, Coniferin, Neochlorogenic acid, Cryptochlorogenic acid, Gamma-L-glutamyl-L-phenylalanine, and Chlorogenic acid demonstrated good bonding affinity to KRAS G12D with -11.0, -9.8, -9.5, -9.1, -9, and -8.9 Kcal.mol-1, respectively, compared to MRTX1133 (-8.3 Kcal.mol-1), exhibiting favorable physicochemical profiles and revealing their potential as KRAS G12D inhibitors. Based on bonding scores and QSAR data, four of the six selected molecules (Coniferin, Gamma-Lglutamyl- L-phenylalanine, Isochlorogenic acid, and Neochlorogenic acid) formed stable protein-ligand complexes with mean RMSD values < 2.5 Å during 200 ns MD simulations. MMGBSA analysis confirmed the binding free energies, and the compound giving the strongest interaction was determined to be Coniferin with ΔG_bind = -72.53 ± 5.24 Kcal.mol-1. Superior docking scores and stable MD trajectories demonstrate that the selected plant-derived compounds, especially Coniferin, effectively interact with the KRAS G12D binding pocket via suitable hydrophobic and hydrogen-bond contacts. These findings suggest that natural compounds can provide structurally diverse and potentially safer alternatives compared to synthetic inhibitors; however, experimental validation is necessary to confirm their inhibitory potential and selectivity. DISCUSSION:According to the MMGBSA results, these compounds have suitable binding free energy values comparable to the reference, with Coniferin as the strongest plant-derived candidate with ΔGbind = -72.53 ± 5.24 Kcal/mol-. CONCLUSION:As a result of this in silico study, coniferin, neochlorogenic acid, and chlorogenic acid have been identified as potential precursor molecules for KRAS G12D inhibition. Isochlorogenic acid was excluded due to its dynamic instability. These plant-derived compounds require further experimental validation as potential anticancer agents targeting KRAS G12D mutations.
Abstract: Alzheimer’s Disease (AD) is a neurodegenerative disease that causes significant clinical, social, and economic burden worldwide. Despite improvements in understanding its multifaceted pathogenesis, current treatments are mostly symptomatic and ineffective across varied patient populations. To overcome these constraints, AI–driven precision medicine allows tailored risk assessment, treatment selection, and disease monitoring. This review covers AI's role in AD precision medicine, focusing on drug repurposing, digital therapies and clinical decision support systems. Machine and deep learning models are used to predict medication response, integrate heterogeneous data sources such as genomics, transcriptomics, neuroimaging and electronic health records, and uncover pharmacogenomic treatment success factors. The paper covers AIenabled precision pharmacology, including tailored dosing algorithms, adaptive therapeutic monitoring, and adverse drug reaction prediction. Bioinformatics-based target identification, network pharmacology, graphbased AI models, virtual screening, and real-world and clinical data validation are emphasized in AI-driven medication repurposing. AI-powered digital treatments like personalized cognitive training platforms, wearable- derived digital biomarkers, virtual and mixed reality interventions, adherence monitoring, and digital twins for therapy optimization have been discussed. AI-based clinical decision support systems are also thoroughly assessed for clinical value, accuracy, and explainability in disease subtyping, trajectory prediction, and risk stratification in preclinical and prodromal AD. Despite these promises, data heterogeneity, algorithmic bias, legal barriers, and privacy concerns exist. Federated learning enables safe multi-center collaboration and hybrid AI–human approaches, and it represents the future. AI's ability to alter AD care opens the door to precision medicine paradigms that use repurposed medications, digital tools and intelligent decision-making to improve patient outcomes.
INTRODUCTION:Ornidazole is an antiprotozoal and antibacterial agent used to treat intestinal infections. However, its clinical use is limited by modest first-pass metabolism and poor aqueous solubility. These characteristics make it a suitable candidate for incorporation into a pH-responsive interpenetrating polymer network (IPN) hydrogel system for potential colon-targeted delivery. This study aimed to prepare, characterize, and evaluate chitosan-polyacrylic acid IPN composite hydrogels as carriers for ornidazole. METHODS:Chitosan-polyacrylic acid IPN composite hydrogels incorporating ornidazole were prepared using N, N'-methylene bisacrylamide and glutaraldehyde as cross-linking agents. Polymer formation, drug entrapment, and drug-polymer interactions were investigated using Fourier Transform Infrared (FTIR) spectroscopy, Differential Scanning Calorimetry (DSC), and Powder X-ray Diffraction (PXRD). These analyses confirmed successful polymer formation and the absence of significant chemical alterations in the entrapped drug. The hydrogels were further evaluated for swelling behavior and in vitro drug release. Morphological changes before and after dissolution were examined using Scanning Electron Microscopy (SEM). RESULTS:The hydrogels exhibited a production yield of 86.39 ± 4.23% and drug loading of 92.39 ± 2.16%. They demonstrated pronounced pH-sensitive swelling behavior, showing minimal swelling under acidic conditions and rapid swelling in alkaline media. In vitro release studies indicated that drug release was dependent on hydrogel swelling and followed a biphasic release pattern with non-Fickian diffusion kinetics at higher pH values. SEM analysis of the optimized formulation revealed the formation of large, open channel-like pores after dissolution. DISCUSSION:The synthesized chitosan-polyacrylic acid IPN hydrogels showed high production yield and drug loading with stable physicochemical characteristics. Their pH-dependent swelling and release behaviour confirmed minimal drug release in acidic media and enhanced release at intestinal/colonic pH. Formulation F9 was identified as the optimized formulation. FTIR, DSC, and XRD analyses confirmed successful IPN formation and amorphous dispersion of ORNI without chemical incompatibility. Overall, the system demonstrated effective controlled, colon-targeted delivery potential for improving the oral bioavailability of Ornidazole. However, further studies including biological evaluation and in vivo validation are required to confirm colontargeting efficiency. CONCLUSION:Chitosan-polyacrylic acid IPN hydrogel with its biodegradable nature and pH-sensitive release of ornidazole is an attractive option to be further explored for targeted controlled drug delivery formulations for the drug.
Introduction: Polycystic Ovarian Disease (PCOD) is a complicated endocrine-metabolic disorder affecting about one-quarter of women of reproductive age in the world and a major cause of infertility. This disorder is characterised by hyperandrogenism, anovulation, insulin resistance and metabolic abnormalities that pose challenges for timely diagnosis and management. Standardised criteria and symptom variability often limit traditional diagnostic strategies. Objective: This study aims to evaluate the role of artificial intelligence (AI) technologies in enhancing the diagnosis, prediction and management of PCOD. Methods: The systematic literature review was performed following PRISMA guidelines and included studies from 2021 to 2025. We reviewed more than 140 peer-reviewed publications in the clinical, biochemical, imaging, and multi-omics domains. The review covers machine learning (ML), deep learning (DL), hybrid AI models, explainable AI (XAI), federated learning (FL), quantum machine learning (QML), Edge AI, and generative adversarial networks (GANs). Results: The results demonstrate the superior performance of ML, DL, and hybrid AI frameworks compared to conventional diagnostic methods in PCOD classification and prediction of metabolic and reproductive risks. XAI provided transparency into the model, and FL facilitated privacy-preserving sharing of data from multiple institutions. QML and integration of multi-omics showed promise for biomarker discovery. The challenges of limited datasets and real-time screening were addressed through GAN-based augmentation and Edge AI. Discussion: These findings underscore the growing clinical relevance of AI in enhancing diagnostic accuracy and facilitating personalised decision-making. However, routine clinical implementation is still hindered by limitations such as data heterogeneity and imbalance, limited external validation, and lack of standardised datasets. Conclusion: AI-based methods present enormous potential to revolutionise the diagnosis and management of PCOD by providing accurate, interpretable, and personalised care. Future work should be based on large multicentre datasets, standardised validation protocols, and development of clinically interpretable models.
Introduction: Diabetic Cardiomyopathy (DCM) is a diabetes-specific cardiac complication characterized by a complex network of pathogenic mechanisms and lacks effective drugs at present. Traditional Chinese Medicine (TCM) offers a holistic and multi-target therapeutic strategy; however, its clinical translation remains challenging. This review provides a comprehensive overview of the current evidence and challenges associated with TCM for DCM, aiming to promote its clinical application and translation. Methods: Preclinical and clinical studies published between 2004 and 2026 were retrieved from Google Scholar, PubMed, ScienceDirect, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang Data. The literature search was conducted using the following keywords: “diabetic cardiomyopathy”, “DCM”, “traditional Chinese medicine”, “Chinese herbal formulas”, and “active components of Chinese herbs”. Results: Preclinical evidence has demonstrated that both TCM formulas and monomers exert significant cardioprotective effects in DCM. These agents act on multiple key pathogenic pathways, particularly by attenuating oxidative stress, inhibiting fibrosis, alleviating endoplasmic reticulum stress, and modulating gut microbiota dysbiosis, thereby effectively preventing cellular injury and death. However, clinical trials and evidence remain limited. Discussion: The multi-target therapeutic profile of TCM closely matches the multifactorial pathogenesis of DCM, representing a potential paradigm shift from conventional single-target interventions. Furthermore, high-quality trials of TCM in other cardiovascular disorders have demonstrated the feasibility of rigorous randomized and blinded study designs, providing a solid methodological foundation for future translational and clinical research on TCM-based therapies for DCM. Conclusion: TCM provides an innovative therapeutic strategy for DCM by simultaneously intervening in cascaded pathogenic pathways that single-target drugs fail to address adequately. Despite solid preclinical efficacy support, sufficient clinical verification is absent. Conducting high-quality translational research and multicenter randomized controlled trials is critical to translate laboratory outcomes into clinical practice and integrate TCM into standardized DCM treatment regimens.
INTRODUCTION:Radiotherapy remains a fundamental modality in cancer treatment; however, its efficacy is frequently compromised by inherent tumor radioresistance and the collateral damage to normal tissues at curative doses. Phloretin, a dihydrochalcone flavonoid, exhibits extensive antitumor effects in both in vitro and in vivo settings; however, its clinical application is limited due to low water solubility and rapid metabolic processing. Silver nanoparticles (AgNPs) have been recognized as agents that enhance radiation-induced oxidative damage. Accordingly, this study synthesized phloretin-conjugated AgNPs (Ph-AgNPs) and evaluated their potential as a safe, tumor-selective radiosensitizer in a murine model of solid Ehrlich carcinoma. METHODS:Ph-AgNPs were synthesized through an environmentally friendly reduction process and subsequently characterized utilizing UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FT-IR), dynamic light scattering, and transmission electron microscopy. The acute oral toxicity (LD₅₀) and hepatorenal safety profiles were assessed in healthy Swiss albino mice. Mice bearing solid Ehrlich ascites carcinoma (EAC) were randomly divided into six groups (n = 6 per group) for antitumor evaluation: Normal control, Normal+Ph-AgNPs, EAC (control), EAC + γ-irradiation (γ-IR; 6 Gy), EAC + Ph-AgNPs (98.5 mg), and EAC + Ph-AgNPs + γ-IR. The parameters assessed were tumor growth, blood indices, serum liver transaminases (ALT, AST, ALP), renal function (urea and creatinine levels), biomarkers of oxidative stress in the tumor tissue (GSH, SOD and MDA), signaling pathways associated with apoptosis (p-AMPK, Bax and Bcl-2) and cell cycle regulators (CDK2/CDK6/p53), evaluated by biochemical assays, quantitative real-time PCR (RT-qPCR) or western blot analysis. Molecular docking studies were also conducted to visualize the binding interactions of phloretin with CDK2, CDK6, and p53. RESULTS:Ph-AgNPs were monodisperse spheres with an average diameter of 85.89 nm and a zeta potential of -12.35 mV, maintaining stability in physiological media. At the therapeutic dosage, Ph-AgNPs exhibited no hepatorenal toxicity in normal mice and significantly mitigated the transient elevations in hepatic and renal markers induced solely by irradiation. The combined application of Ph-AgNPs and γ-irradiation yielded the most pronounced tumor suppression, resulting in a 59.7% reduction in mean tumor mass and a 69.6% decrease in tumor volume compared to EAC controls. This outcome was associated with GSH and SOD depletion, increased MDA levels, elevated p-AMPK levels, and an increased Bax/Bcl-2 ratio, along with coordinated downregulation of CDK2 and CDK6 and upregulation of p53, as confirmed at the protein level. Docking analyses indicated strong, energetically favorable interactions of phloretin within the active sites of CDK2, CDK6, and p53. DISCUSSION:Ph-AgNPs appear to enhance tumor sensitivity to radiation through multiple mechanisms, including concurrent oxidative stress, mitochondrial apoptosis, and p53-mediated cell-cycle arrest. CONCLUSION:This study finds that Ph-AgNPs are nano-radiosensitizers that can be combined with γ-ray irradiation, are well tolerated, and significantly enhance the therapeutic efficacy of γ-ray-mediated therapy for solid EAC tumors. This rationale underpins our multi-mechanistic approach, which combines the enhanced phloretin delivery and radiosensitizing properties of AgNPs to radiosensitive and radioresistant cells.
INTRODUCTION:Integrated therapeutic strategies for Chronic Obstructive Pulmonary Disease (COPD) combined with sarcopenia remain limited. This study evaluated the effect of Modified Shenling Baizhu Powder (MSBP) on readmission rates in stable COPD patients with secondary sarcopenia and explored its potential mechanisms. METHODS:In this retrospective cohort study with propensity score matching (1:1), 131 patients received MSBP combined with Western medicine (exposure group), and 114 received Western medicine alone (control group). Primary outcomes were the 1-year readmission rate and interval. Mechanisms were explored via network pharmacology, transcriptomics, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), and molecular docking. RESULTS:The readmission rate was significantly lower in the exposure group than in the control group (24.4% vs. 43.9%, p < 0.05), with a longer median readmission interval (319 vs. 272 days, p < 0.05). MSBP was an independent protective factor (OR = 0.202, p < 0.05). Network pharmacology and transcriptomics identified the PI3K/AKT pathway as a key mechanism. UPLC-MS identified five flavonoid components; kaempferol-3- O-rutinoside showed strong binding affinity to PI3K/AKT proteins in docking studies. DISCUSSION:MSBP combined with Western medicine effectively reduces hospital readmissions in this population. The therapeutic mechanism likely involves PI3K/AKT pathway activation by flavonoid components, particularly kaempferol-3-O-rutinoside. CONCLUSION:MSBP offers clinical benefits for COPD with secondary sarcopenia. The PI3K/AKT pathway and specific flavonoids represent potential mechanistic targets warranting further investigation.
Abstract: The gut microbiota produces a wide variety of metabolites that are essential for host–microbe communication and play a critical role in regulating host physiology, metabolism, and immunity. Among the most important of these metabolites are Short-Chain Fatty Acids (SCFAs), bile acid derivatives, tryptophan metabolites, polyamines, vitamins, and polyphenol-derived compounds. These bioactive metabolites regulate energy homeostasis, glucose and lipid metabolism, intestinal barrier integrity, immune signaling, and gene expression. Moreover, they influence systemic physiological processes, including cardiovascular and neuroendocrine functions, while playing a pivotal role in regulating hepatic and adipose tissue metabolism and maintaining intestinal homeostasis. Dysbiosis-induced alterations in microbial metabolic activity have been associated with the development of several chronic diseases, including obesity, type 2 diabetes mellitus, nonalcoholic fatty liver disease, cardiovascular diseases, cancer, autoimmune disorders, and neurological conditions. Consequently, therapeutic strategies aimed at modulating microbial metabolism, such as probiotics, prebiotics, postbiotics, dietary interventions, faecal microbiota transplantation, and synthetic biology-based approaches, are being extensively investigated, with microbial metabolites emerging as promising pharmacological targets. Despite these advances, significant challenges remain regarding their mechanistic understanding, standardisation, safety, and successful translation into clinical practice. The integration of multi-omics technologies, artificial intelligence, and precision microbiome-based interventions is expected to accelerate the development of personalized therapeutic strategies and enhance the clinical applicability of microbial metabolite research.
Transforming growth factor β (TGF-β) signaling is essential for early embryonic development, tissue and organ formation, immune surveillance, tissue repair, and maintaining homeostasis in adults. The three isoforms of TGF-β, TGF-β1/2/3, share a structurally conserved secretion signal peptide and activate various downstream signaling pathways. While much research has focused on TGF-β1, there is increasing recognition of the important roles that TGF-β3 plays in cancer biology. TGF-β3 exhibits dual functions. It can inhibit tumors in the early stages of cancer but can promote tumor growth in more advanced stages. Understanding the unique characteristics of TGF-β3 is crucial for unraveling the complexities of tumor development and the tumor microenvironments. Targeting TGF-β signaling is considered a promising strategy for cancer treatment, and developing drugs aimed at TGF-β3 holds significant potential. In the future, TGF-β3 targeted therapies are expected to gain more attention as a means to enhance therapeutic outcomes and address poor prognoses in cancer patients.
INTRODUCTION:Aggressive breast cancer subtypes, including Triple-Negative Breast Cancer (TNBC) and HER2-positive tumours, remain clinically challenging due to poor prognosis, high therapeutic resistance, and limited targeted treatment options, highlighting the urgent need for novel and more effective therapeutic strategies. METHODS:This study presents a narrative review of preclinical and mechanistic studies evaluating the anticancer potential of melittin, a bioactive peptide derived from bee venom, with emphasis on molecular mechanisms and advancements in targeted delivery systems. RESULTS:Preclinical studies have demonstrated that melittin has potent anticancer activity through membrane disruption, induction of apoptosis, and inhibition of EGFR/HER2 signalling pathways. Reported IC₅₀ values range from approximately 0.8-2.0 μM in aggressive breast cancer cell lines, whereas targeted delivery systems, such as nanoparticles and liposomes, reduce haemolysis from ~40-60% to <10%, significantly improving therapeutic selectivity. Additionally, melittin has enhanced chemosensitivity and modulates tumour-associated immune responses, including PD-L1 downregulation. DISCUSSION:The multi-modal mechanisms of melittin, combined with advances in targeted delivery platforms, position it as a promising candidate for overcoming therapeutic resistance and toxicity limitations in aggressive breast cancer. CONCLUSION:Melittin-based therapies, particularly when integrated with advanced delivery systems, represent a promising translational strategy for aggressive breast cancer. Further research should prioritise well-designed clinical trials, optimisation of dosing strategies, and validation of targeted delivery platforms to enable safe and effective clinical application.
Atopic dermatitis (AD) is a chronic, relapsing inflammatory skin disease affecting 1-3% of adults and 20% of children. It is characterized by type 2 immune dysregulation and epidermal barrier dysfunction. The pathophysiology involves loss-of-function mutations in the filaggrin gene (FLG), tight junction defects, and altered intercellular lipid composition, leading to increased transepidermal water loss (TEWL) and sensitization to environmental allergens. Current treatments, including topical corticosteroids (TCS), calcineurin inhibitors (TCI), and emerging biologics, are limited by cutaneous atrophy, systemic absorption, and poor patient adherence. This review critically examines lipid-based nanocarrier systems, specifically solid lipid nanoparticles (SLNs), nanostructured lipid carriers (NLCs), liposomes, ethosomes, transferosomes, and nanoemulsions, as advanced topical delivery platforms. These systems enhance drug bioavailability through prolonged skin retention, targeted epidermal delivery, and controlled release kinetics, while minimizing systemic exposure. We analyze comparative efficacy data, mechanistic insights into skin penetration pathways, and discuss stability considerations, safety profiles, and regulatory challenges. The integration of personalized nanomedicine approaches represents a paradigm shift toward precision therapeutics in AD management, offering improved clinical outcomes and reduced long-term disease burden.
Gene editing has enormous potential in biomedical fields, including cancer and personalized medicine. CRISPR-Cas9 is a gene-editing system in which the Cas9 enzyme, guided by RNA derived from short palindromic repeats, alters DNA sequences to inhibit oncogenes through base and prime editing, thereby suppressing tumor growth. Despite significant advancements in anticancer therapies, limitations such as off-target effects, ethical concerns, and challenges in targeted delivery restrict its potential clinical applications. In the present review, we explore the mechanisms of CRISPR-Cas9 gene editing, recent technological advancements, and prospects for cancer management. We also provide insights into strategies for precise delivery, improved targeting accuracy, and the regulatory considerations surrounding CRISPR-Cas9 for oncological applications. Additionally, this review examines the potential of CRISPR-Cas9 in personalized cancer therapy and discusses approaches to enhance tumor-specific targeting and facilitate clinical translation.
Introduction: Glioblastoma multiforme is an extremely deadly, aggressive primary brain tumor, distinguished by poor prognosis, and the rapid development of resistance to temozolomide might be the cause of low survival. Novel adjunctive strategies are needed to enhance therapeutic efficacy. Mumio (Shilajit), rich in fulvic acid and bioactive compounds, has shown antioxidant and anticancer effects, but its role in glioblastoma remains unclear. This study evaluated its anticancer potential and its ability to enhance temozolomide efficacy. Methods: Mumio extract was tested in U87 (sensitive) and LN-18 (resistant) glioblastoma cell lines. Cell viability and clonogenicity were assessed by MTT and colony formation assays. Fluorescent staining evaluated mitochondrial function, reactive oxygen species, and lipid accumulation. Western blotting analyzed apoptotic (PARP, Caspase-3, PTEN), ferroptosis-related (NRF2, FTH1), and Akt signaling proteins. Combination treatments were also examined. Results: Mumio reduced cell viability in a dose- and time-dependent manner, with stronger effects in U87 cells. It increased reactive oxygen species, disrupted mitochondrial function, and induced apoptosis, as shown by increased cleaved PARP and Caspase-3. Ferroptosis-related changes, including reduced FTH1 in LN-18 cells, were observed. Mumio also enhanced temozolomide-induced cytotoxicity and reduced clonogenic survival. Discussion: These findings suggest that Mumio exerts anticancer effects through oxidative stress-mediated apoptosis and modulation of ferroptosis pathways. Its ability to enhance temozolomide efficacy, particularly in resistant cells, indicates a potential role in overcoming chemoresistance Conclusion: Mumio triggers apoptosis in glioblastoma cells and induces changes consistent with ferroptosis, while also chemosensitizing cells to temozolomide, suggesting its potential use alongside standard therapy
Introduction: This study aimed to investigate whether there were potential drug-drug interactions (DDI) of oxcarbazepine in elderly patients with epilepsy during clinical combination therapy and explore the optimal initial dosage regimen of oxcarbazepine for elderly patients with epilepsy. Methods: The effectiveness of oxcarbazepine was mainly determined by measuring the concentrations of its active metabolite, 10-hydroxycarbazepine (MHD). The study developed an MHD population pharmacokinetic (PPK) model for elderly patients with epilepsy using nonlinear mixed-effect modelling (NONMEM). Results: It was found that no combined medications significantly affected the pharmacokinetic processes of MHD. Further, we simulated and recommended the optimal initial dosages of oxcarbazepine suitable for elderly patients with epilepsy. Dosages of 20, 15, 10, and 5 mg/kg oxcarbazepine were recommended for elderly patients with epilepsy who weighed 40-46 kg, 46-55 kg, 55-76 kg, and 76-100 kg, respectively. At the same time, in accordance with the above administration plan, the probabilities of achieving the target concentrations of the oxcarbazepine active metabolite in elderly patients with epilepsy were 99.0-99.4%, 99.0-99.5%, 98.7-99.6%, and 98.7-99.7%, respectively. Discussion: The study explored potential DDIs and the initial dosage administration of oxcarbazepine in elderly patients with epilepsy for the first time. Combined medications did not cause DDI when used by elderly patients with epilepsy for treatment, demonstrating the high safety of oxcarbazepine in the treatment of elderly patients with epilepsy. Conclusion: This study recommended the initial dosages of oxcarbazepine for elderly patients with epilepsy. To achieve the same therapeutic concentration ranges, the dosages for elderly patients with epilepsy may need to be reduced.
Drug discovery is a tedious process that takes a long time and incurs high costs in developing an approved drug for clinical use. The long time and high expenditure are due to various phases of drug discovery and do not guarantee the success of the drug for clinical use, and about 90% of potential drug candidates suffer failure in phase-I clinical trials. The drug molecule qualifying for phase I clinical trial after passing through the preclinical stages is a significant milestone for both research institutes and pharmaceutical companies. Therefore, there is a need to explore alternatives for the drug discovery process. In this regard, Artificial Intelligence may provide significant assistance in different processes of drug discovery. This review discusses the applications of AI in diverse and prominent processes of drug discovery, like identification of a diseased state, identification of target, development of lead compounds, virtual screening, and drug toxicity. AI has proved its potential in the cheaper, easier, and timely development of drugs for different ailments. The application of AI not only enhances the quality of the drug development process but also assures better safety in the treatment and diagnosis of disease. AI introduces automation in drug development and clinical trials, minimizing the chances of human error. Focusing on the quality and quantity of the data, ethical consideration of the patient data may help in revolutionizing the process of synthetic drug development and treatment.
BACKGROUND:Docetaxel (DTX) is the first-line treatment for androgen-deprived prostate cancer. Its long-term therapeutic stress provokes therapeutic resistance via compensatory pathways. Several phenolic compounds have demonstrated synergistic effects on DTX chemosensitization; these quantitative measures have not yet been addressed. This study aims to identify the best adjunct phenolic compound that demonstrates synergy with DTX chemosensitization. METHODS:A comprehensive search was conducted in accordance with the PRISMA 2020 guidelines. Independent authors searched six databases for in vitro or in vivo studies until September 2025. The outcomes measured included the mean combination index (CoI), the fold-change in IC50, apoptosis, proliferation, migration, and tumor volume inhibition. Their results were pooled in a random-effects model to estimate the standard mean difference relative to control studies. The risk of bias was assessed using SciRAP for in vitro studies and ARRIVE 2.0 for in vivo xenograft studies. RESULTS:Twelve preclinical studies met the eligibility criteria. The phenolic compounds with synergistic effects in combination with DTX were Curcumin (CCM), Quercetin (QUR), Caffeic Acid Phenethyl Ester (CAPE), and Honokiol (HKI). The meta-analysis study revealed significant apoptosis induction (SMD = 1.83; 95% CI: 0.92-2.75), IC50 values (SMD=2.00; 95% CI:0.88, 4.52), and tumor growth reduction (SMD = -3.15; 95% CI: -4.62 -1.68). The mechanisms of resistance reversal pathways identified included NF-κB, PI3K/AKT, and STAT3 inhibition, as well as blocking, reversing, and downregulating the P-glycoprotein efflux pump to overcome DTX resistance. DISCUSSION:Among the tested compounds, CCM and CAPE demonstrated the highest synergistic potency, as indicated by combination index values and fold-change in IC50. QUR showed superior anti-proliferative activity in DTX-resistant cell lines, and HKI achieved the most significant in vivo tumor regression (SMD = -7.56). RES showed predominantly additive activity and is included for comparative analysis. However, the combination index was the lowest for CCM, demonstrating the highest synergistic activity among the methods and models employed. Curcuminoids, such as calebin A, tetrahydrocurcumin, and hispolon, are recommended for further in vitro studies. The risk of bias assessment indicated high methodological reliability among the in vitro studies and moderate quality in the animal studies. CONCLUSION:Overall, phenolic compounds were found to be credible adjuncts to the DTX combination. Among them, CCM was found to be the most synergistic agent across all tested methods. However, further clinical studies are warranted in prostate cancer patients.
Herbal creams have gained significant prominence in dermatology for their safety, sustainability, and biologically active alternatives to conventional chemical-based formulations. Composed of plant-derived bioactive compounds, these preparations exhibit diverse pharmacological properties, including antiinflammatory, antimicrobial, antioxidant, and wound-healing effects. Key botanicals such as Aloe vera, turmeric, chamomile, tea tree oil, calendula, and liquorice contribute to the management of various skin disorders, including eczema, psoriasis, acne, and chronic wounds. Incorporation of advanced formulation strategies such as liposomes, nanoemulsions, and nanostructured lipid carriers has further enhanced dermal penetration, bioavailability, and therapeutic outcomes of herbal actives. Despite these advancements, concerns persist regarding the stability, purity, and safety of herbal creams, as natural origin alone does not guarantee the absence of adverse effects or contamination. Regulatory inconsistencies across global markets further complicate quality assurance, emphasising the need for harmonised guidelines encompassing Good Manufacturing Practices (GMP), Good Agricultural and Collection Practices (GACP), and advanced analytical validation. Sustainable sourcing, scientific standardisation, and clinical substantiation are essential to ensure reproducibility and consumer safety. The convergence of phytochemistry, nanotechnology, and regulatory science is poised to establish herbal creams as effective, evidence-based therapeutic options in modern dermatological practice.
