Aim: To investigate genes and pathways involved in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using RNA sequencing. Methods: Using paired human donor eyes, human organ-cultured anterior segment (HOCAS) was established in one eye to characterize GC responsiveness based on intra ocular pressure (IOP) change and, in the other eye, primary HTM cell culture was established. For RNA sequencing, total RNA extracted from GC-responder (GC-R) and non-responder (GC-NR) cells after dexamethasone (DEX) or ethanol (ETH) treatment for 7d was used. Differentially expressed genes (DEGs) were compared among five groups and validated. Results: In total, 616 and 216 genes were identified as significantly dysregulated in Group #1 and #2 (#1: ETH vs. DEX-treated GC-R; #2: ETH vs. DEX-treated GC-NR), respectively. Around 80 genes were commonly dysregulated in Group #3 (overlapping DEGs between #1 and #2), whereas 536 and 136 genes were uniquely expressed in GC-R (#4) and GC-NR HTM (#5) cells, respectively. Pathway analysis revealed that WNT signaling, drug metabolism cytochrome p450, cell adhesion, TGF-β signaling, and MAPK signaling were associated with GC responsiveness. Conclusion: This is the first study reporting distinct gene signatures and their associated pathways for GC-R and GC-NR HTM cells. WNT and MAPK signaling are potential therapeutic targets for the management of GC-induced glaucoma.

The prolonged use of antibiotics results in drug resistance in pathogenic microorganisms. This necessitates the identification of novel drug targets that are useful for the development of effective antimicrobial drugs. In the post-genomic era, computational tools and methods have contributed immensely in identifying such novel targets, thereby accelerating the drug discovery process. In the present study, an extensive in silico analysis of the proteome of the pathogenic yeast, Candida tropicalis was performed to identify potential drug targets. The complete proteome of C. tropicalis retrieved from Uniprot was analysed using the CD-HIT algorithm followed by BLAST for eliminating proteins homologous to human proteome. The selected proteins were then analyzed using DEG database for identifying critical genes for the survival. The identified essential proteins were subjected to pathway analysis using KEGG to predict their involvement in metabolism. This approach resulted in the identification of 20 potential drug targets present in C. tropicalis.

Glucocorticoids (GCs) are known to regulate several physiological processes and are the mainstay in the management of inflammatory eye diseases. The long-term use of GC causes raised intraocular pressure (IOP) or ocular hypertension (OHT) in about 30–50% of the susceptible individuals depending on the route of administration, and can lead to steroid-induced secondary glaucoma. The present study aims to understand the role of microRNAs (miRNAs) in differential glucocorticoid (GC) responsiveness in human trabecular meshwork (HTM) cells using small RNA sequencing. The human organ-cultured anterior segment (HOCAS) model was used to identify whether donor eyes were from GC-responders (GC-R; n = 4) or GC-non-responders (GC-NR; n = 4) following treatment with either 100 nM dexamethasone (DEX) or ethanol (ETH) for 7 days. The total RNA was extracted from cultured HTM cells with known GC responsiveness, and the differentially expressed miRNAs (DEMIRs) were compared among the following five groups: Group #1: ETH vs. DEX-treated GC-R; #2: ETH vs. DEX-treated GC-NR; #3: overlapping DEGs between Group #1 and #2; #4: Unique DEMIRs of GC-R; #5: Unique DEMIRs of GC-NR; and validated by RT-qPCR. There were 13 and 21 DEMIRs identified in Group #1 and Group #2, respectively. Seven miRNAs were common miRNAs dysregulated in both GC-R and GC-NR (Group #3). This analysis allowed the identification of DEMIRs that were unique to GC-R (6 miRNAs) and GC-NR (14 miRNAs) HTM cells, respectively. Ingenuity Pathway Analysis identified enriched pathways and biological processes associated with differential GC responsiveness in HTM cells. This is the first study to reveal a unique miRNA signature between GC-R and GC-NR HTM cells, which raises the possibility of developing new molecular targets for the management of steroid-OHT/glaucoma.

Aim: In silico approach was used to predict cytotoxic T lymphocyte (CTL) epitopes from the proteome of all four dengue serotypes. Methods: The immune epitope database analysis resource was used to analyze the CTL epitopes of dengue serotypes. The prediction of epitopes was done against nine high frequency HLA class I alleles occurring worldwide. Results: A total of 2784 epitopes were predicted from all four dengue virus proteomes. Immune epitope database analysis resource tool predicted 202 epitopes as positive for immunogenecity. A total of 39 of 257 consensus epitopes predicted were present in all four serotypes. This study identified nine new class I-restricted epitopes. Conclusion: Mapping of these potentially immunogenic dengue epitopes paves the way for future investigation of their utility as vaccine candidates to prevent or treat dengue virus infections.

Candida tropicalis, the etiological agent of candidiasis evades the immune system and survive in the human host for decades. Currently there are not many drugs available in the market to treat these fungal infections. The increasing number of fungal infections necessitates the need for new drug candidates that can be used to treat fungal infections such as candida. Many natural products available in plants, animals and microorganisms exhibit potent anti-microbial activity; but they are not explored to their potential. Virtual screening of anti-microbials against known targets accelerates the process of drug discovery and development. In the present study, a total of 27 compounds of natural origin such as plants, microbes and marine sponges were evaluated for their ability to interact with four of the new targets. The study revealed the effectiveness of 3 compounds with improved binding affinity against the four target proteins; that could be used as lead compounds in designing new drug candidates.

Integration of 3D printing technology into medical education marks a significant evolution in pedagogical practices. This survey investigates the potential of 3D-printed molecular models to enhance the understanding of intricate biochemical structures among medical students. Through a proof of concept, 3D models of maltose and the insulin hexamer were developed, focusing on key structural features vital for education. Blender was utilized for model design, and Cura was employed for model preparation, leading to the creation of 3D-printed models using PLA filament on an FDM printer. These models were implemented in small group teaching sessions for MBBS students. The survey ensures that 3D-printed models provide a more interactive and tangible learning experience, aiding in the comprehension of complex molecular structures and their functions. This survey highlights the transformative potential of 3D-printed models in medical education and practical application of theoretical concepts.