Aloe vera L. leaves possess bioactive principles, such as polyphenols, anthraglycosides, free anthraquinones, mono- and polysaccharides, polypeptides, terpenoids, sterols, chromones, lectins, fatty, amino and organic acids, enzymes, and saponins. A. vera waste (leaves without aloe gel) is also rich in amino acids, organic acids, flavonoids, anthraquinones, lipids, minerals, vitamins, carbohydrates, pigments, as well as volatile organic components. Hence, the aloe by-product is recognized as being of significant worth after the extraction of its bioactives and their potential implementation in food and cosmetic products. The encapsulation of the mentioned bioactive compounds can improve their stability, bioavailability, activity, and prolonged release in various formulations. Therefore, liposomes with aloe leaf waste extract were prepared using phospholipids and the pro-liposome technique, and their size, polydispersity index (PDI), and antioxidant potential before and after UV irradiation were examined using photon correlation spectroscopy and ABTS and DPPH assays, respectively. The vesicle size of aloe waste extract-loaded liposomal particles was 335.00±20.55 nm (non-treated liposomes) and 326.63±3.43 nm (after UV irradiation), whereas the PDI values were very high, 0.505±0.056 and 0.712±0.045, respectively. The data mentioned above confirm the existence of nanoliposome vesicles in the non-uniform system. The anti-ABTS activity was 100.27±2.08 µmol Trolox equivalent (TE)/L (non-treated liposomes) and 103.11±4.01 µmol TE/L (after UV irradiation). The IC₅₀ value (the concentration of the sample required to scavenge 50% of free radicals) of non-treated liposomes with aloe waste extract was 59.77±1.08 µg/mL, while the IC₅₀ for the UV-irradiated sample was 57.81±1.59 µg/mL. Thus, UV irradiation did not cause changes in the size and antioxidant capacity of aloe waste extract-loaded liposomes, while the mentioned treatment caused a significant increase in the PDI value. Since UV irradiation did not cause a decrease in the antioxidant activity of the sample, it can be concluded that the liposomal membrane effectively protects sensitive aloe waste antioxidants from UV degradation.

Background: The cholinergic deficit in Alzheimer’s disease (AD) is treated symptomatically with acetylcholinesterase (AChE) inhibitors, yet current drugs suffer from limited brain penetration and adverse effects. 5,6-Dimethoxyindanone constitutes the pharmacophore of donepezil; conjugation with piperazine yields analogues with promising activity. Methods: IC₅₀ values for fifteen dimethoxyindanone–piperazine derivatives were extracted from a study employing the Ellman assay and converted to pIC₅₀ for modelling. Three-dimensional geometries were energy-minimised (MM⁺ → PM3), and 4 885 Dragon descriptors calculated. After statistical filtering (low variance, excessive missing data, inter-correlation r ≥ 0.95), 843 descriptors remained. Stepwise selection isolated four key variables—Mor22v, HATS8p, VE1_B(p) and C-006—encoding molecular volume, spatial polarizability, electronic distribution and CH₂RX fragments. An artificial neural network (MLP 4-3-1, BFGS) was trained on nine compounds, validated on three and externally tested on a further three. Results: The model reproduced experimental activity with R² = 0.961, Q² = 0.999 and MAE = 0.001 µM; external prediction yielded R²test = 0.928. Sensitivity analysis ranked C-006 as the dominant contributor, indicating that strategic CH₂RX substitution at the indanone core drives potency, while Mor22v and VE1_B(p) emphasised the favourable impact of molecular volume and electron-withdrawing groups. Conclusions: This concise ANN-QSAR model delivers accurate, mechanism-based predictions and provides tangible design rules—enhanced polarizability, optimal volume and selective halogenation—for next-generation, brain-penetrant AChE inhibitors. The workflow is fully transferable to larger libraries and multi-target optimisation, paving the way for rapid, cost-effective exploration of indanone-based chemotypes in AD drug discovery.

Background: Acetylcholinesterase (AChE) remains a clinically validated target for symptomatic treatment of Alzheimer’s disease (AD), yet current inhibitors display only moderate brain penetration and dose-limiting adverse effects. Ferulic acid (FA) exhibits neuroprotective properties and weak AChE inhibition, encouraging structural optimisation. Methods: The chemical structures and Ellman-assay IC₅₀ values for twenty FA derivatives were taken as reported in a previous external study. Three-dimensional geometries were energy-minimised (MM⁺→PM3) and analysed in Dragon 7 to generate 4,885 molecular descriptors. After variance/multicollinearity filtering, 918 descriptors remained. Stepwise feature selection identified four informative variables—nCL, SpMax2_Bh(p), Mor16s, SpMax7_Bh(s)—capturing halogen content, electronic distribution, and 3‑D shape. An artificial neural network (MLP 4‑8‑1, BFGS optimisation) was trained on a 14‑compound set and validated by leave‑one‑out cross‑validation and an external three‑compound test set. Results: The model reproduced experimental data with R² = 0.959, Q² = 0.956 and MAE = 1.43 µM; external prediction yielded R² = 0.927. Sensitivity analysis revealed SpMax2_Bh(p) as the principal driver of potency, while nCL highlighted the favourable impact of chloro‑substitution. Conclusions: A concise ANN‑QSAR model delivers accurate, mechanism‑based predictions of AChE inhibition for FA derivatives and offers clear design rules—enhanced π‑cloud polarisability and selective halogenation—for the next generation of brain‑penetrant AChE inhibitors. The workflow shortens the discovery timeline for AD therapeutics and can be expanded to larger libraries and multi‑target optimisation.

Background: Lysine-specific demethylase-1 (LSD1/KDM1A) erases mono- and dimethyl marks on histone H3 and is over-expressed in prostate, breast, and lung tumours, making it an increasingly attractive epigenetic target for anticancer therapy. Although the natural polyphenol curcumin inhibits LSD1 only weakly, its modular scaffold lends itself to systematic optimisation through computational chemistry. Methods: A previously published study compiled chemical structures and Ellman-assay IC₅₀ values for nineteen curcumin analogues. After three-dimensional geometry optimisation (MM⁺ → PM3), 4,885 Dragon descriptors were calculated; variance, missing-value, and multicollinearity filters (r ≥ 0.95) reduced the pool to 763. Stepwise selection retained four informative descriptors—P_VSA_s_5, JGI8, H2s, and SpPosA_A—reflecting polar surface area, eighth-order topological charge, spatial polarizability, and positive fragment surface. A radial-basis-function artificial neural network (4-6-1 architecture) was trained on thirteen compounds, internally validated by leave-one-out cross-validation, and externally evaluated on a three-compound test set. Results: The model reproduced experimental potency with R² = 0.999, Q² = 0.9996, and MAE = 0.11 log units; external prediction yielded R²test = 0.928. Sensitivity analysis identified P_VSA_s_5 as the dominant contributor, indicating that enlarging the polar surface area in specific atomic states enhances enzyme binding, while the JGI8 descriptor underscored the importance of charge distribution. Conclusions: This compact, rigorously validated QSAR model offers accurate, mechanism-based predictions and actionable design rules—optimal polar surface area, favourable charge topology, and judicious halogenation—for next-generation LSD1 inhibitors, thereby accelerating epigenetic drug discovery pipelines.

This study presents a machine learning-driven framework to optimize critical quality attributes (CQAs) of mRNA-lipid nanoparticle (LNP) vaccines, addressing challenges in microfluidic manufacturing process efficiency and formulation stability. mRNA-LNP formulations (n = 24) were developed to evaluate the interplay of material attributes (ionizable lipids, phospholipids, PEGylated lipids), process parameters (flow rate ratio: 3–5; total flow rate: 12–20 mL/min), and lipid ratios (ionizable-to-cholesterol: 1.08–1.33; phospholipid-to-PEG: 3.76–6.67; N/P: 6–10) using I-optimal design of experiments (DOE). Key outcomes—including particle size (PS), polydispersity index (PDI), encapsulation efficiency (EE), and thermal stability—were analyzed using XGBoost/Bayesian optimization for microfluidic condition tuning (accuracy >94%) and a self-validated ensemble model (SVEM) for lipid mixture prediction (accuracy >97%). Results demonstrated that ionizable lipid selection significantly influenced LNP size: formulations with DOTAP achieved larger nanoparticles (94–96 nm) with high EE (95.5%), while MC3 produced smaller LNPs (51–57 nm) with reduced EE (79–85%). SVEM outperformed traditional models, with predicted PS (95–97 nm) closely matching experimental outcomes (94–96 nm). Furthermore, dual optimization of lipid ratios and process parameters enabled 96.6% encapsulated mRNA recovery and stabilized thermal profiles (heat trend cycle: −25°C to −10°C). Sucrose incorporation during lyophilization inhibited eutectic crystallization, maintaining PS within ±2 nm post-freezing. This work highlights the first application of SVEM for simultaneous lipid/process optimization in mRNA-LNP production, offering a quality-by-design (QbD) approach to accelerate scalable, continuous manufacturing. The framework’s >97% predictive accuracy supports rapid virtual screening of formulations, reducing experimental costs by 40%, and paves the way for robust, thermally stable vaccines tailored for diverse therapeutic applications.

Introduction

Diabetic retinopathy (DR) and age-related macular degeneration (AMD) are leading causes of vision loss, primarily driven by pathological angiogenesis mediated by vascular endothelial growth factor (VEGF). Sunitinib, a multi-targeted tyrosine kinase inhibitor, offers potent anti-angiogenic activity but is limited by systemic toxicity and rapid degradation. This research aimed to develop and evaluate biocompatible, biodegradable elastomeric implants for the sustained intraocular delivery of sunitinib, thereby reducing injection frequency, maintaining therapeutic drug levels, and improving ocular tolerability.

Methodology

Implants were formulated using poly(diol-co-tricarballylate) elastomers via thermal crosslinking, incorporating sunitinib either through solvent casting or direct mixing. In vitro characterization included FTIR, DSC, XRD, drug release kinetics, and cytocompatibility on ARPE-19 cells. In vivo studies were conducted in rabbits, assessing ocular pharmacokinetics, fundoscopic examination, and histopathological analysis over a 42-day period following intravitreal implantation. Quantification of drug levels in vitreous humor and tissues was performed using validated LC-MS/MS.

Results

The elastomeric implants demonstrated amorphous drug dispersion, slow degradation, and pH-stable, diffusion-driven release extending up to 222 days. No burst effect was observed. Drug release followed Higuchi kinetics, with higher loading (1000 µg) resulting in increased release rates. Cytotoxicity studies revealed that controlled-release systems significantly reduced sunitinib-induced cell apoptosis and preserved proliferation in ARPE-19 cells. In vivo, all sunitinib implants were well tolerated with no significant vitreous hemorrhage or inflammation. Pharmacokinetic analysis confirmed sustained intraocular drug presence, with the highest levels seen in the 1000 µg implants.

Conclusion

This study successfully demonstrates the feasibility of using biodegradable elastomeric implants for long-term, controlled intraocular delivery of sunitinib. The system offers enhanced therapeutic duration, minimized dosing frequency, and improved safety compared to conventional injection-based therapies. These findings hold strong translational potential for treating neovascular retinal diseases such as DR and AMD, addressing the unmet clinical need for prolonged, cost-effective, and minimally invasive ocular drug delivery solutions.

Hydrogel is the first biomaterial designed for biomedical use. Polysaccharide based hydrogels are receiving much attention in the past few years, as intelligent materials due to their properties for biomaterials. One of the extensively studied approaches for controlling drug delivery is the encapsulation of drug within polymer chains which sluggish the release on the basis of its crosslinked network. Discontinuous volume variations in hydrogels upon changes of environmental parameters, like polymer composition, temperature, pH, etc., are named multi-responsive hydrogels.

Bioinspired functional hydrogels are prepared using chitosan and polyvinyl pyrrolidone with varying quantities of aminopropyl diethoxy methylsilane via solution casting protocol. Prepared hydrogels were evaluated by different physical and analytical characterization techniques. Swelling indices were examined in distilled water (247.52 g/g), different buffer and electrolyte solutions. Fourier transform infrared spectroscopy was conducted to confirm functional groups and to prove the proposed physical and chemical interactions between polymers and crosslinker. Thermogravimetric analysis was used to assess the response of prepared hydrogels against temperature and found maximum thermal stability up to 23.94% in terms of residue. Contact angle and X-ray diffraction analysis were conducted to investigate the hydrophilicity which was (71°) and crystalline properties, respectively. Extensively, in vitro studies including biodegradation, antimicrobial and cytotoxic properties were examined. Maximum biodegradation was achieved up to 6.4% in seven days and cytotoxicity was 2.64% in terms of mortality using brine shrimp lethality assay. Hydrogels showed antimicrobial properties against E. Coli using liquid diffusion method. Accumulative release of benzocaine was checked in phosphate buffer saline solution at 37 °C at pH 7.4 and observed that almost whole drug was released in 150 min. Hence, based on the aforementioned results, prepared hydrogels are proposed to be used for controlled drug release applications.

Phytomedicine has moved beyond being seen only as a folklore remedy and has become an important part of modern therapeutics. Aloe-emodin (AE), a phytoconstituents present in Aloe, is a naturally occurring anthraquinone, exhibits notable anti-inflammatory, antimicrobial, and wound-healing properties. However, its clinical potential is limited by poor aqueous solubility and inadequate skin permeability. To overcome these challenges, an AE-loaded gel (AMEG) was developed to enhance topical delivery and therapeutic efficacy in diabetic wound management. The formulation was optimized using a D-optimal mixture design, selecting Capryol 90 as the oil phase, Labrasol and Tween 80 as surfactants, and Transcutol P as the co-surfactant. A stable gel matrix was formed by incorporating konjac glucomannan (KGM) and carbopol 940, improving skin adherence and drug retention. The optimized AMEG demonstrated nanoscale droplet size, high zeta potential, and excellent clarity. In vitro and ex vivo studies confirmed sustained drug release and enhanced transdermal penetration. In vivo application in diabetic rats significantly accelerated wound healing, accompanied by modulation of key inflammatory and oxidative markers, including IL-1, IL-6, NF-kB, TNF-α, MDA, and AGEs. Histopathological assessments revealed full re-epithelialization and organized collagen deposition. The combined effect of AE and KGM underscores the potential of AMEG as a promising, non-invasive therapeutic approach for diabetic wound care, leveraging the advantages of herbal compounds in enhancing healing and reducing inflammation.

Proteolysis-targeting chimeras (PROTACs) are heterobifunctional molecules consisting of two linked substructures: protein-of-interest-binding ligand (POI ligand) and the E3 ubiquitin ligase-binding ligand. In this case, POI is the epidermal growth factor receptor (EGFR). EGFR is a transmembrane protein involved in cellular proliferation, angiogenesis, apoptosis and cancer metastasis in case of overexpression (particularly in lung cancer). Simultaneous binding of the PROTAC to both the EGFR and the E3 ligase leads to the ubiquitylation of the EGFR, thus marking it for degradation via the ubiquitin proteosome system. First EGFR PROTACs were developed in 2001, but all early synthetic PROTACs exhibited similar issues- high molecular weight and hooking effect, leading to poor ADMET properties of ligands.

To address those issues on a broad scale, scientists investigated whether PROTAC linker structure impacts biodegradation efficacy and PROTAC pharmacokinetics. However, the impact of linker structure on PROTACs’ DMPK properties is still not well understood. In this research we employed literature research to understand the current practices in EGFR PROTAC synthesis with improved ADMET properties. Based on theoretical findings, we have designed EGFR PROTAC structures employing one of the following linker modifications: i) linker length; ii) linker rigidity; iii) number of hydrogen donors in linker; iv) number of introduced heteroatoms. All compounds were tested in silico for the evaluation of their ADMET properties, using freely available online ADMET Tools: SwissADME, ADMETlab 2.0, pkCSM6, ADMET-AI, Simulations Plus ADMET Predictor.

Obtained results show that the AI tools have a higher precision in predicting ADMET properties of drugs not conforming to the rule of 5. The increase in linker length for EGFR PROTACs leads to improved bioavailability and decreased carcinogenicity, and higher linker rigidity causes increased plasma protein binding. Higher number of HBD leads to decreased oral acute toxicity, and the higher number of heteroatoms causes a decrease in hERG blocking.

Ferrocene is an organometallic compound that consists of an iron(II) ion linked to two cyclopentadienyl rings in a sandwich structure. This unique arrangement gives ferrocene remarkable stability and properties that make it valuable for various applications, including bioorganometallic chemistry. Several ferrocenyl-containing pharmacophores have been studied, such as ferrocifens, analogues of the anticancer tamoxifen, and ferroquine, an analogue of antimalarial chloroquine. Besides the specific activity of the organic portion of the ferrocene derivatives, such molecules are able to generate reactive oxygen species (ROS): Fe(II)/Fe(III) + H₂O₂ → Fe(III)/Fe(II) + HO^•/HOO^• + H₂O.

ROS play a paradoxical role in disease progression: while elevated ROS levels are implicated in the onset of various pathologies, they act as tumor-suppressive agents involved in the mechanism of action of many chemotherapeutics. ROS generation is involved in many forms of programmed cell death, a group of self-protective cellular mechanisms triggered by external stimuli. Therefore, a fragile equilibrium is operating in healthy cells, where ROS can either promote or inhibit tumor development.

The activation of cell death pathways (i.e., apoptosis, necroptosis and ferroptosis) by ferrocene (Fc) and its monopositive cation ferrocenium (Fc⁺) has been investigated in triple-negative breast cancer MCF-7 cells using immunofluorescence, flow cytometry, and transmission electron microscopy.

The distinct capabilities of Fc and Fc⁺ to generate ROS and trigger oxidative stress were evident through the activation of apoptosis, along with morphological changes following treatment of MCF-7 cells, particularly with Fc⁺. Fc⁺ induced ferroptosis within 2 h exposure, whereas Fc did not. Conversely, the more stable Fc initiated necroptosis after prolonged treatment.

Differences in cell death mechanisms and timing of Fc and Fc⁺ may arise from the rapid interconversion between Fe(II) and Fe(III). Fc and Fc⁺ can be promising candidates to address the limitations of conventional apoptosis-based cancer therapies.