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Acute myeloid leukemia (AML) is prevalent in both adult and pediatric patients. Despite advances in patient categorization, the heterogeneity of AML remains a challenge. Recent studies have explored the use of gene expression data to enhance AML diagnosis and prognosis, however, alternative approaches rooted in physics and chemistry may provide another level of insight into AML transformation. Utilizing publicly available databases, we analyze 884 human and mouse blood and bone marrow samples. We employ a personalized medicine strategy, combining state-transition theory and surprisal analysis, to assess the RNA transcriptome of individual patients. The transcriptome is transformed into physical parameters that represent each sample's steady state and the free energy change (FEC) from that steady state, which is the state with the lowest free energy.We found the transcriptome steady state was invariant across normal and AML samples. FEC, representing active molecular processes, varied significantly between samples and was used to create patient-specific barcodes to characterize the biology of the disease. We discovered that AML samples that were in a transition state had the highest FEC. This disease state may be characterized as the most unstable and hence the most therapeutically targetable since a change in free energy is a thermodynamic requirement for disease progression. We also found that distinct sets of ongoing processes may be at the root of otherwise similar clinical phenotypes, implying that our integrated analysis of transcriptome profiles may facilitate a personalized medicine approach to cure AML and restore a steady state in each patient.

Membrane vesicle secretion was predicted earlier as a method of elimination of proteins, lipids, and RNA from the cell. At present vesicles are thought to be a brand-new type of intercellular communication and they are playing a crucial role in numerous physiological and pathological processes. However, in this expanding field, much remains unknown regarding the origin, biogenesis, secretion, target and fate of these vesicles. Vesicle research might become a more established field as a result of a complete understanding of the isolation and analysis techniques currently in use, making it possible to utilize membrane vesicles in therapeutic settings. Thus, standardization of the isolation of vesicles is in great need. This research article deals with the isolation and characterization of two distinct bacterial species-derived membrane vesicles namely, Lactobacillus acidophilus a human gut Bacterial MVs and Pseudomonas syringae, a model phytopathogen. [ABSTRACT FROM AUTHOR]

Streptomyces is amongst the most amenable genera for biotechnological applications, and it is extensively used as a scaffold for drug development. One of the most effective therapeutic applications in the treatment of cancer is targeted therapy. Small molecule therapy is one of them, and it has gotten a lot of attention recently. Streptomyces derived compounds namely streptenols A, C, and F–I and streptazolin were subjected for ADMET property assessment. Our computational studies based on molecular docking effectively displayed the synergistic effect of streptomyces-derived compounds on the gynecological cancer target PIK3CA. These compounds were observed with the highest docking scores as well as promising intermolecular interaction stability throughout the molecular dynamic simulation. Molecular docking and molecular dynamic modeling techniques were utilized to investigate the binding mode stability of drugs using a pharmacophore scaffold, as well as physicochemical and pharmacokinetic aspects linked to alpelisib. With a root mean square fluctuation of the protein backbone of less than 0.7 nm, they demonstrated a steady binding mode in the target binding pocket. They have also prompted hydrogen bonding throughout the simulations, implying that the chemicals have firmly occupied the active site. A comprehensive study showed that streptenol D, streptenol E, streptenol C, streptenol G, streptenol F, and streptenol B can be considered as lead compounds for PIK3CA-based inhibitor design. To warrant the treatment efficacy against cancer, comprehensive computational research based on proposed chemicals must be assessed through in vitro studies. [ABSTRACT FROM AUTHOR]