In December 2019, a new and highly pathogenic coronavirus emerged—coronavirus disease 2019 (COVID-19), a disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), quickly spread throughout the world. In response to this global pandemic, a few vaccines were allowed for emergency use, beginning in November 2020, of which the mRNA-based vaccines by Moderna (Moderna, Cambridge, MA, USA) and BioNTech (BioTech, Mainz, Germany)/Pfizer (Pfizer, New York, NY, USA) have been identified as the most effective ones. The mRNA platform allowed rapid development of vaccines, but their global use is limited by ultracold storage requirements. Most resource-poor countries do not have cold chain storage to execute mass vaccination. Therefore, determining strategies to increase stability of mRNA-based vaccines in relatively higher temperatures can be a game changer to address the current global pandemic and upcoming new waves. In this review, we summarized the current research strategies to enhance stability of the RNA vaccine delivery system.

Lignin nanoparticles (LNPs) were prepared with the objective of evaluating their application as a novel oral drug delivery system. Curcumin, a polyphenolic natural compound, was used as a lipophilic drug model, as its poor solubility and low oral bioavailability limit its therapeutic efficacy. Optimized nanoparticles were prepared using phase separation and stabilized by citric acid crosslinking. Physicochemical properties of the prepared curcumin-loaded nanoparticles, including particle size, size distribution, morphology, and encapsulation efficiency were characterized. The average particle diameter of curcumin-loaded LNPs was 104 nm, whereas the encapsulation efficiency of curcumin in the nanoparticles was 92%. Stability analyses of curcumin-loaded nanoparticles demonstrated enhanced protection of the entrapped curcumin under storage conditions. Furthermore, in vitro release assays revealed that curcumin-loaded LNPs have high stability in simulated gastric fluid and slow release under intestinal conditions as desirable. To evaluate absorption and bioavailability, we also investigated cellular uptake and transepithelial permeability of curcumin-loaded LNPs using Caco-2 cell monolayers. Cell viability studies revealed that curcumin-loaded LNPs did not induce toxicity in Caco-2 cells. The nanoparticle formulation enhanced curcumin cellular uptake and intestinal permeation compared to free curcumin. Incubation of LNPs on a Caco-2 cell monolayer led to a fivefold increase in apparent permeability compared to free curcumin. Furthermore, in vivo pharmacokinetics experiments showed that the LNP system increased the bioavailability of curcumin by ten-fold compared with the administration of unformulated curcumin. Overall, our findings indicate that the novel LNPs have great potential to be applied as an effective oral drug delivery system, especially for drug molecules with low solubility and limited bioavailability.

Artificial intelligence (AI) is rapidly transforming healthcare by enhancing diagnostics, personalized medicine, and clinical decision-making. In medical education, AI chatbots have the potential to be used as virtual tutors or learning assistants. Despite AI's growing impact, its integration into medical education remains limited. AI is not a standard component of medical curricula, which could leave many future healthcare professionals unprepared for an AI-driven workplace. To address this significant gap, this editorial describes the development of a mini-course to integrate AI training for first-year medical students. The course was focused on the fundamentals of AI, prompt engineering, practical applications of chatbots as learning assistants, and ethical use of generative AI.

Introduction Virtual reality (VR) is a powerful tool in health professional education. It has been successfully implemented in various domains of education with positive learning outcomes. The three-dimensional (3D) visualization offered by VR can potentially be applied to learn complex pharmacology topics. This study aims to investigate whether VR technology can improve the learning of complex pharmacological concepts. Methods A VR learning module on cardiovascular drugs was developed using Kern’s six-step framework. 32 medical students participated in the pilot study. Their pharmacology knowledge was assessed using pre- and post-intervention tests. Additionally, feedback from the participants were collected through a post-intervention survey that assessed learner satisfaction, ease of use, perceived usefulness, quality of visual elements, intention to use, and comfort level during the VR experience. Results Participants scored significantly higher in the post-intervention test than in the pre-intervention test (p <0.05). A majority of the participants (90%) were satisfied with the VR module, finding it easy to use, and time efficient. A minority of participants (15%) preferred a traditional learning format while some participants (20%) experienced discomfort in VR. Conclusion Our findings suggest that VR enhances pharmacology knowledge in medical students and is well-received as an innovative educational tool. By providing immersive 3D visualization of complex drug actions, VR has the potential to transform pharmacology education into an engaging and effective learning experience.

ChatGPT by OpenAI is an AI model designed to generate human-like responses based on diverse datasets. Our study evaluated ChatGPT-3.5’s capability to generate pharmacology multiple-choice questions adhering to the NBME guidelines for USMLE Step exams. The initial findings show ChatGPT’s rapid adoption and potential in healthcare education and practice. However, concerns about its accuracy and depth of understanding prompted this evaluation. Using a structured prompt engineering process, ChatGPT was tasked to generate questions across various organ systems, which were then reviewed by pharmacology experts. ChatGPT consistently met the NBME criteria, achieving an average score of 13.7 out of 16 (85.6%) from expert 1 and 14.5 out of 16 (90.6%) from expert 2, with a combined average of 14.1 out of 16 (88.1%) (Kappa coefficient = 0.76). Despite these high scores, challenges in medical accuracy and depth were noted, often producing “pseudo vignettes” instead of in-depth clinical questions. ChatGPT-3.5 shows potential for generating NBME-style questions, but improvements in medical accuracy and understanding are crucial for its reliable use in medical education. This study underscores the need for AI models tailored to the medical domain to enhance educational tools for medical students.

Autoinducers AI-1 and AI-2 play an important role in bacterial quorum sensing (QS), a form of chemical communication between bacteria. The autoinducer N-octanoyl-L-Homoserinehomoserine lactone (C8-HSL) serves as a major inter- and intraspecies communicator or ‘signal’, mainly for Gram-negative bacteria. C8-HSL is proposed to have immunogenic properties. The aim of this project is to evaluate C8-HSL as a potential vaccine adjuvant. For this purpose, a microparticulate formulation was developed. The C8-HSL microparticles (MPs) were formulated by a water/oil/water (W/O/W) double-emulsion solvent evaporation method using PLGA (poly (lactic-co-glycolic acid)) polymer. We tested C8-HSL MPs with two spray-dried bovine serum albumin (BSA)-encapsulated bacterial antigens: colonization factor antigen I (CFA/I) from Escherichia coli (E. coli.) and the inactive protective antigen (PA) from Bacillus anthracis (B. anthracis). We formulated and tested C8-HSL MP to determine its immunogenicity potential and its ability to serve as an adjuvant with particulate vaccine formulations. An in vitro immunogenicity assessment was performed using Griess’s assay, which indirectly measures the nitric oxide radical (NOˑ) released by dendritic cells (DCs). The C8-HSL MP adjuvant was compared with FDA-approved adjuvants to determine its immunogenicity potential. C8-HSL MP was combined with particulate vaccines for measles, Zika and the marketed influenza vaccine. The cytotoxicity study showed that MPs were non-cytotoxic toward DCs. Griess’s assay showed a comparable release of NOˑ from DCs when exposed to CFA and PA bacterial antigens. Nitric oxide radical (NOˑ) release was significantly higher when C8-HSL MPs were combined with particulate vaccines for measles and Zika. C8-HSL MPs showed immunostimulatory potential when combined with the influenza vaccine. The results showed that C8-HSL MPs were as immunogenic as FDA-approved adjuvants such as alum, MF59, and CpG. This proof-of-concept study showed that C8-HSL MP displayed adjuvant potential when combined with several particulate vaccines, indicating that C8-HSL MPs can increase the immunogenicity of both bacterial and viral vaccines.