Superior University

Conventional chemotherapy is limited by premature drug leakage, systemic toxicity, and inefficient intracellular co-delivery, leading to reduced therapeutic efficacy and the development of drug resistance. To address these limitations, thermoresponsive solid lipid nanoparticles (TR-SLN) were developed for controlled co-delivery of cisplatin (CIS) and epirubicin (EPI) by integrating a sustained-release Kollidon® SR matrix with a PEG-functionalized stearic acid lipid core. Nine formulations were prepared using a modified hot homogenization technique and systematically characterized. Drug-polymer interactions were studied by Fourier transform Infrared Spectroscopy. Particle size, PDI and zeta potential were determined using dynamic light scattering measurements. Morphology of nanoparticles was assessed by Scanning electron microscopy. Thermal behavior of nanoformulations was investigated using DSC and TGA. XRD studies were performed to assess physical state of drugs in nanoparticles. The cytotoxic effects of the formulations were evaluated in-vitro using the MCF-7 human breast cancer cell line. The optimized formulation, TR-SLN-9, exhibited high entrapment efficiency (CIS 93.4 ± 2.2

In 21st-century learning, students' second-language (L2) writing competence should be grounded in the principle of lifelong learning, with teachers recognising the urgency of self-directed learning. By encouraging autonomy, this principle and praxis enable students to improve their writing abilities outside the conventional classroom, helping them succeed in various situations, including international communication. This mixed-method study involved 40 participants from one university in Indonesia. This study aimed to (1) describe the implementation of self-directed learning through automated written corrective feedback and (2) reveal the students' perceptions of automated written corrective feedback in EFL writing classrooms. Classroom observation, writing test, and semi-structured interviews were used to collect research data. The quantitative data were analyzed statistically using SPSS version 25. In contrast, the qualitative data were analyzed using triangulation following the concurrent activity flows comprising data condensation, data display, and drawing and verifying conclusions. The study's findings revealed that teachers and students intensely monitored the implementation of self-directed learning through automated written corrective feedback during writing activities. Students' writing scores met the minimum completeness criteria. The subsequent finding reflected students' positive perceptions of self-directed learning style in a writing project that could improve their proficiency.

Research on allergy treatments depends heavily on the ability to predict the chemical and biological characteristics of pharmaceutical compounds. The evaluation of drug efficacy, safety, and biological activity is supported by topological indices (TIs), which provide insightful information about molecular structures. This study investigates the use of degree-based TIs for a range of anti-allergic drugs, such as cetirizine, epinephrine, diphenhydramine, and loratadine. We determine TIs for these medications using edge partitioning, and we use linear, quadratic, and cubic regression to estimate properties like density, molar volume, molar refractivity, boiling point, vapor pressure, and flash point using quantitative structure-property relationship (QSPR) models. We use three multi-criteria decision-making (MCDM) techniques ENTROPY, VIKOR, and COPRAS to improve drug selection decision-making. By comparing possible drug candidates, these techniques enable a thorough ranking of options according to TIs and physicochemical characteristics. The findings show how useful TIs and MCDM techniques are in promoting drug development and discovery for the treatment of allergies, providing a strong framework for choosing the most promising substances with the best therapeutic profiles.

Rheumatologic diseases present very specific but often unnoticed complexities for anesthesiologists, pain management specialists and critical care providers. The varied systemic consequences of rheumatologic diseases, chronic inflammation, pain processing abnormalities and immunosuppression impact perioperative care, pain management and critical care outcome. Patients with rheumatoid arthritis, axial spondyloarthropathy, systemic lupus erythematosus, systemic vasculitis and systemic sclerosis possess a high risk of perioperative complications related to intricate airway, cardiopulmonary and infectious disease issues, as well as chronic pain. This editorial focuses on the interplay between rheumatology and anesthesia as an ever-evolving field, with particular regard to the importance of a multi-disciplinary approach to perioperative pain management and critical care outcome.

Urban wind environments are characterized by low and turbulent flow, limiting the performance of conventional horizontal-axis wind turbines that require high and unidirectional wind speeds. This study presents the Wind Tree Mill, a biomimetic vertical-axis wind turbine (VAWT) system inspired by natural tree morphology, designed for efficient energy capture in low-speed urban conditions. Multiple blade profiles were modeled and optimized in SolidWorks to improve aerodynamic performance. Comparative simulation analysis revealed that the optimized curved-leaf blade design achieved a 32.8% increase in starting torque and a 27.4% reduction in drag coefficient relative to the baseline straight-blade Savonius model. Each turbine module is equipped with an independent DC generator, forming a modular micro-generation array capable of scalable deployment. Real-time performance monitoring using LabVIEW showed that, under average urban wind speeds of $3-5 \mathrm{m} / \mathrm{s}$, the Wind Tree Mill achieved an average electrical conversion efficiency of 18.6%, outperforming conventional VAWTs by 22% in equivalent wind conditions. Experimental validation demonstrated stable self-starting capability and sustained operation across multidirectional wind inflows. The compact, tree-like structure allows integration into confined commercial and residential spaces, promoting both aesthetic and functional synergy with urban architecture. The results confirm the feasibility of bio-inspired VAWT systems for decentralized renewable power generation and establish a framework for future development of smart, sensor-integrated wind harvesting systems within urban energy networks.