Abstract The application of nanotechnology in drug delivery systems has attracted considerable scientific interest, particularly with respect to improving the therapeutic efficacy and safety profiles of pharmacological agents. This review critically examines nanotechnology-based drug delivery systems for the management of rheumatoid arthritis (RA), a chronic systemic autoimmune disease characterized by persistent synovial inflammation, progressive joint destruction, and significant extraarticular sequelae. Conventional pharmacological strategies such as non-steroidal anti-inflammatory drugs (NSAIDs), corticosteroids, conventional synthetic disease-modifying antirheumatic drugs (csDMARDs), and biological disease-modifying anti-rheumatic drugs (bDMARDs) provide disease control but are associated with significant adverse effects upon prolonged use, inadequate joint specific drug concentrations, and limited responsiveness in a subset of patients. Nanotechnology offers a compelling therapeutic solution by enabling targeted drug delivery to inflamed synovial tissue, thereby enhancing bioavailability, reducing systemic toxicity, and extending drug half-life. This review discusses diverse nanotechnology platforms, such as liposomes, dendrimers, polymeric nanoparticles, hydrogels, metal, inorganic nanoparticles, nucleic acid-based carriers, and stimuli-responsive nanocarriers evaluated for RA treatment. The evidence underscores the potential of these systems to overcome the limitations of traditional therapies and to facilitate precision therapeutics in RA. The review also addresses existing challenges in nanomedicine translation, such as inter-patient variability, protein corona formation, endosomes (as a barrier), biocompatibility, and the need for rigorous clinical validation, while outlining future directions including exosome mediated delivery, biomimetic nano-carriers, and stimuli-responsive platforms.
Abstract This study aims to investigate the effects of syringin on insulin resistance (IR) and its mechanisms using an IR model in HepG2 cells. IR was induced by 10 4 mol L –1 insulin for 24 h, followed by syringin treatment at various concentrations for 48 h. Levels of glucose, triglycerides, TNF-α, IL-6, and GRP78 were measured, and protein expression of IRS-1, p-IRS-1, PI3K, p-PI3K, AKT, p-AKT, FoxO1, and p-FoxO1 was analysed by Western blot. Compared with controls, the IR model showed significant increases in glucose, triglycerides, TNF-α, IL-6, GRP78, and decreases in p-IRS1/IRS1, p-PI3K/PI3K, and p-AKT/AKT, with increased p-FoxO1/FoxO1 (all p < 0.01). Syringin (50–200 μg mL –1 ) significantly lowered glucose, triglycerides, TNF-α, IL-6, and GRP78, and reversed these signalling changes by upregulating p-IRS1/IRS1, p-PI3K/PI3K, p-AKT/AKT and downregulating p-FoxO1/FoxO1 ( p < 0.05). Syringin effectively ameliorates insulin resistance in HepG2 cells, lowers glucose and triglycerides, and improves glucose-lipid metabolism, likely via the PI3K/AKT pathway.
Abstract This study conducted a retrospective disproportionality analysis of 50,031 adverse drug event (ADE) reports from the FDA Adverse Event Reporting System (FAERS) database spanning Q2 2009 to Q3 2025, in which golimumab was identified as the primary suspect drug. Four disproportionality algorithms were simultaneously applied: the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS). A total of 397 positive signals were identified across 25 system organ classes (SOCs). The SOCs with concordant positive signals across all four algorithms were identified for infections and infestations and surgical and medical procedures. High-frequency signals included pneumonia, lower respiratory tract infection, influenza, nasopharyngitis, sinusitis and cellulitis. Comparison with the current prescribing information revealed several previously undocumented ADEs, including urinary tract infection, ear infection, flavivirus infection, Zika virus infection and Dengue fever. Twenty-nine positive malignancy signals absent from the prescribing information were identified, including basal cell carcinoma, colorectal cancer, cervical cancer and breast cancer. Time-to-onset analysis revealed that the risk of ADEs was the highest within the first few months of treatment initiation. Clinicians should rigorously monitor for infectious complications and malignancies when prescribing golimumab to ensure patient safety.
Abstract This research introduces a first-in-class high-performance liquid chromatography with fluorescence detection (HPLC-FD) method for the reliable quantification of ROS in plasma. The method relies on the native fluorescence of ROS, with excitation and emission set at 280 nm and 340 nm, resp. Sample preparation involved a simple one-step protein precipitation with methanol. Chromatographic resolution of ROS and pemigatinib (PEM), which served as the internal standard (IS), was achieved using Zorbax Eclipse Plus C18 HPLC column. The mobile phase consisted of methanol and formate buffer solution. The method was validated in compliance with ICH M10 guidelines. It showed linearity across concentration range of 50–1,500 ng mL −1 ( R ² = 0.9991), with a lower limit of quantitation of 50 ng mL −1 . Accuracy ranged from 96.8 to 103.4 %, and intra- and inter-day precision (RSD) were between 3.2 and 6.1 %. The method was successfully applied to quantify ROS in plasma samples from rats following administration of a single oral dose (25 mg kg −1 ), enabling the determination of key pharmacokinetic parameters, including C max (361.31 ng mL −1 ), t max (1.75 h, t ½ (2.867 h), V d (0.077 L kg −1 ), CL (0.018 L h −1 kg −1 ), AUC (ng h mL −1 ) and and MRT (h). The greenness and practical applicability of the method were confirmed using four comprehensive independent metric tools. In comparison to previously reported bioanalytical approaches, the proposed method offers several practical advantages, such as reduced complexity and cost, a shorter run time, full validation, established greenness, and suitability for the clinical laboratory setting.
Abstract Keyhole limpet hemocyanin is a large metalloprotein present in hemolymph of the mollusk Megathura crenulata . This protein is highly immunogenic, making it very attractive to the biopharmaceutical industry, where it is used as a carrier protein for haptens, an adjuvant, or as a stand-alone biologic for the treatment of various cancer diseases. The structural complexity of such immunogenic protein makes its characterization and quality control very challenging. Here, we developed, optimized and validated a size exclusion chromatography approach for quality control of keyhole limpet hemocyanin products. The separation procedure was performed on an Acquity UPLC BEH450 SEC column with pore size of 450 Å in a mobile phase composed of 25 mmol L – 1 phosphate buffer (pH 6.8) with 250 mmol L – 1 NaCl. These conditions led to appropriate elution of the analysed protein. The developed method showed very promising values of validation parameters, such as coefficient of de termination ( R 2 = 0.9997), sensitivity (limit of detection 10.21 μg mL–1, limit of quantitation 31.25 μg mL – 1 ), precision (repeatability 0.3–2.5 %, intermediate precision 1.1–4.2 %), and accuracy (100.4–102.8 %). The developed method was used to determine the content of keyhole limpet hemocyanin in three commercially available samples obtained from various suppliers. The determined content ranged from 20.08 to 22.91 mg per vial.
