Designing a vehicle-free anti-bacterial topical hydrogel from Fmoc-diphenylalanine.

A supramolecular synthon-based salt formation strategy has been employed to afford an anti-bacterial topical hydrogel from Fmoc-diphenylalanine (FmocFF). The nontrivial steps (pH/solvent switch along with heat-cool protocol) required for making the hydrogel from FmocFF were successfully avoided following this strategy.

Phenylalanine conjugated supramolecular hydrogels developed from the mafenide and flurbiprofen multidrug for biological applications.

A well-known nonsteroidal anti-inflammatory drug (NSAID), flurbiprofen (FLR), was first conjugated individually with two naturally occurring amino acids such as L-phenylalanine (PHE) and L-alanine (ALA). These covalent amidic bioconjugates were further reacted individually with mafenide (a drug for treating burn wounds) and amantadine (an antiviral drug) to develop primary ammonium monocarboxylate (PAM) salts. Interestingly, both the PHE-containing multidrug salts exhibited significant gelation ability with various solvents including biologically potent water or methyl salicylate (MS). The isolated hydrogel (HG) as well as all the organogels obtained from multidrug gelators were extensively characterized by dynamic rheology and rheoreversibility studies. The hydrogel of FLR·PHE·MAF and MS gels of FLR·PHE·AMN/FLR·AMN were also selectively characterized by table-top and FEG-TEM analyses. The temperature-dependent 1H-NMR spectroscopy of the selected HG further provided insights into the gelation mechanism and the only isolated single-crystal of the weakly diffracted gelator FLR·AMN also revealed the presence of 1D hydrogen-bonded networks. The pure hydrogelator FLR·PHE·MAF salt (which is also an ambidextrous gelator) was found to be promising in both mechanical (rheoreversible) and biological applications and was found to be effective in cytotoxicity, biocompatibility, anti-cancer activity (MTT and cell migration assay), antibacterial response (zone inhibition, turbidity, INT, and resazurin assay) and haemolysis studies.

Integrative network-based approaches identified systems-level molecular signatures associated with gallbladder cancer pathogenesis from gallstone diseases.

Gallbladder cancer (GBC) is one of the most fatal malignancies of the biliary tract system and is ranked sixth among the neoplasms of the gastrointestinal tract. Gallstone disease (GSD) is considered the major risk factor for GBC. However, the underlying molecular mechanism of GBC pathogenesis from different stages of GSD is not yet clearly understood. We analyzed transcriptomic datasets of GBC with reference to GSD of three different follow-up periods, i.e.,GBC vs. GSD3 (1-3 years), GBCvs. GSD5 (5-10 years), andGBC vs. GSD10 (more than 10 years). We identified overlapping and specific molecular signatures in GBC compared with GSD at three different follow-up periods. Using integrative network biology approaches, such as protein-protein interaction network analysis, transcriptional regulatory network analysis, and miRNA-target gene network analysis, we have identified a few hub genes. The hub genes identified from GBC vs. GSD3, GBC vs. GSD5, and GBC vs. GSD10 were directly or indirectly associated with cancer progression and initiation from GSD. Functional enrichment analysis indicated significant correlation between GSD and GBC pathogenesis. The identified hub genes can be used for future targeted validation to develop potential diagnostic, prognostic, or therapeutic biomarkers in GBC.

An Integrative Systems Biology Approach Identifies Molecular Signatures Associated with Gallbladder Cancer Pathogenesis.

Gallbladder cancer (GBC) has a lower incidence rate among the population relative to other cancer types but is a major contributor to the total number of biliary tract system cancer cases. GBC is distinguished from other malignancies by its high mortality, marked geographical variation and poor prognosis. To date no systemic targeted therapy is available for GBC. The main objective of this study is to determine the molecular signatures correlated with GBC development using integrative systems level approaches. We performed analysis of publicly available transcriptomic data to identify differentially regulated genes and pathways. Differential co-expression network analysis and transcriptional regulatory network analysis was performed to identify hub genes and hub transcription factors (TFs) associated with GBC pathogenesis and progression. Subsequently, we assessed the epithelial-mesenchymal transition (EMT) status of the hub genes using a combination of three scoring methods. The identified hub genes including, CDC6, MAPK15, CCNB2, BIRC7, L3MBTL1 were found to be regulators of cell cycle components which suggested their potential role in GBC pathogenesis and progression.

Identification of Systems Level Molecular Signatures from Glioblastoma Multiforme Derived Extracellular Vesicles.

Glioblastoma multiforme (GBM) is one of the most lethal malignancies of the central nervous system characterized by high mortality rate. The complexity of GBM pathogenesis, progression, and prognosis is not fully understood yet. GBM-derived extracellular vesicles (EVs) carry several oncogenic elements that facilitate GBM progression. The purpose of this study was to identify systems level molecular signatures from GBM-derived EVs using integrative analysis of publicly available transcriptomic data generated from plasma and serum samples. The dataset contained 19 samples in total, of which 15 samples were from plasma (11 GBM patients and 4 healthy samples) and 4 samples were from serum (2 GBM and 2 healthy samples). We carried out statistical analysis to identify differentially expressed genes (DEGs), functional enrichment analysis of the DEGs, protein-protein interaction networks, module analysis, transcription factors and target gene regulatory networks analysis, and identification of hub genes. The differential expression of the identified hub genes were validated with the independent TCGA-GBM dataset. We have identified a few crucial genes and pathways associated with GBM prognosis and therapy resistance. The DEGs identified from plasma were associated with inflammatory processes and viral infection. On the other hand, the hub genes identified from the serum samples were significantly associated with protein ubiquitinylation processes and cytokine signaling regulation. The findings indicate that GBM-derived plasma and serum DEGs may be associated with distinct cellular processes and pathways which facilitate GBM progression. The findings will provide better understanding of the molecular mechanisms of GBM pathogenesis and progression. These results can further be utilized for developing and validating minimally invasive diagnostic and therapeutic molecular biomarkers for GBM.