MDM2 up-regulates the energy metabolism in NSCLC in a p53-independent manner.

Although an E3 ligase MDM2 is the major negative regulator of the p53 tumor suppressor, a growing body of evidence suggests its p53-independent oncogenic properties. In particular, MDM2 has been shown to regulate serine metabolism independently of p53 status in several types of neoplasia, including NSCLC. Using the GSEA approach and publicly available molecular data on NSCLC tumors, our bioinformatics data suggest that MDM2 affects a number of metabolic genes, particularly those encoding components of the electron transport chain (ETC).

Fibro-adipogenic progenitor cells in skeletal muscle unloading: metabolic and functional impairments.

Background: Skeletal muscle resident fibro-adipogenic progenitor cells (FAPs) control skeletal muscle regeneration providing a supportive role for muscle stem cells. Altered FAPs characteristics have been shown for a number of pathological conditions, but the influence of temporary functional unloading of healthy skeletal muscle on FAPs remains poorly studied. This work is aimed to investigate how skeletal muscle disuse affects the functionality and metabolism of FAPs.

Probiotic B-1895 Improved Growth of Juvenile Trout.

The aim of this study was to evaluate a new B-1895 probiotic as a feed additive for farmed trout. Final weight, absolute and average daily gain of fish, and average daily growth rate were higher in the group that received the probiotic than in the control group (p<0.05).

Duvelisib plus romidepsin in relapsed/refractory T cell lymphomas: a phase 1b/2a trial.

PI3K-δ inhibitors have shown impressive activity in lymphoid malignancies but have been hampered by autoimmune and infectious toxicities, leading to market withdrawals. We previously demonstrated activity of the PI3K-δγ inhibitor duvelisib in T cell lymphomas (TCLs) that was associated with inflammatory adverse events. As reported here, we conducted a phase 1b/2a study of duvelisib in combination with either romidepsin (n = 66) or bortezomib (n = 32) in patients with relapsed/refractory TCL and found that the addition of romidepsin, but not bortezomib, appeared to increase efficacy while attenuating PI3K inhibitor-driven toxicity.

Procrustes is a machine-learning approach that removes cross-platform batch effects from clinical RNA sequencing data.

With the increased use of gene expression profiling for personalized oncology, optimized RNA sequencing (RNA-seq) protocols and algorithms are necessary to provide comparable expression measurements between exome capture (EC)-based and poly-A RNA-seq. Here, we developed and optimized an EC-based protocol for processing formalin-fixed, paraffin-embedded samples and a machine-learning algorithm, Procrustes, to overcome batch effects across RNA-seq data obtained using different sample preparation protocols like EC-based or poly-A RNA-seq protocols. Applying Procrustes to samples processed using EC and poly-A RNA-seq protocols showed the expression of 61% of genes (N = 20,062) to correlate across both protocols (concordance correlation coefficient > 0.

Molecular effects of cardiac contractility modulation in patients with heart failure of ischemic aetiology uncovered by transcriptome analysis.

Cardiac contractility modulation (CCM) is based on electrical stimulation of the heart without alteration of action potential and mechanical activation, the data on its fundamental molecular mechanisms are limited. Here we demonstrate clinical and physiological effect of 12 months CCM in 29 patients along with transcriptomic molecular data. Based on the CCM effect the patients were divided into two groups: responders ( = 13) and non-responders ( = 16).

Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities.

Microbial communities thrive through interactions and communication, which are challenging to study as most microorganisms are not cultivable. To address this challenge, researchers focus on the extracellular space where communication events occur. Exometabolomics and interactome analysis provide insights into the molecules involved in communication and the dynamics of their interactions.

Untargeted metabolomics to expand the chemical space of the marine diatom .

Diatoms (Bacillariophyceae) are aquatic photosynthetic microalgae with an ecological role as primary producers in the aquatic food web. They account substantially for global carbon, nitrogen, and silicon cycling. Elucidating the chemical space of diatoms is crucial to understanding their physiology and ecology.

The Epidemiological and Economic Impact of COVID-19 in Kazakhstan: An Agent-Based Modeling.

Background: Our study aimed to assess how effective the preventative measures taken by the state authorities during the pandemic were in terms of public health protection and the rational use of material and human resources.

Materials And Methods: We utilized a stochastic agent-based model for COVID-19's spread combined with the WHO-recommended COVID-ESFT version 2.0 tool for material and labor cost estimation.

Biosynthesis of Functional Silver Nanoparticles Using Callus and Hairy Root Cultures of .

This study delves into the novel utilization of cultured cells for extracellular silver nanoparticles (AgNPs) synthesis without the need for additional substances. The presence of elemental silver has been verified using energy-dispersive X-ray spectroscopy, while distinct surface plasmon resonance peaks were revealed by UV-Vis spectra. Transmission and scanning electron microscopy indicated that the AgNPs, ranging in size from 10 to 40 nm, exhibited a spherical morphology.

Artificial intelligence for natural product drug discovery.

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature.

Enhanced Production of Nitrogenated Metabolites with Anticancer Potential in Hairy Root Cultures.

is a relic liana, which is widely used in traditional Chinese herbal medicine and is endemic to the Manchurian floristic region. Since this plant is rare and slow-growing, alternative sources of its valuable compounds could be explored. Herein, we established hairy root cultures of transformed with root oncogenic loci ( and genes.

Is It Possible to Predict COVID-19? Stochastic System Dynamic Model of Infection Spread in Kazakhstan.

Background: Since the start of the COVID-19 pandemic, scientists have begun to actively use models to determine the epidemiological characteristics of the pathogen. The transmission rate, recovery rate and loss of immunity to the COVID-19 virus change over time and depend on many factors, such as the seasonality of pneumonia, mobility, testing frequency, the use of masks, the weather, social behavior, stress, public health measures, etc. Therefore, the aim of our study was to predict COVID-19 using a stochastic model based on the system dynamics approach.

MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry.

Mapping the chemical space of compounds to chemical structures remains a challenge in metabolomics. Despite the advancements in untargeted liquid chromatography-mass spectrometry (LC-MS) to achieve a high-throughput profile of metabolites from complex biological resources, only a small fraction of these metabolites can be annotated with confidence. Many novel computational methods and tools have been developed to enable chemical structure annotation to known and unknown compounds such as in silico generated spectra and molecular networking.

Multicenter phase 2 study of oral azacitidine (CC-486) plus CHOP as initial treatment for PTCL.

Peripheral T-cell lymphomas (PTCL) with T-follicular helper phenotype (PTCL-TFH) has recurrent mutations affecting epigenetic regulators, which may contribute to aberrant DNA methylation and chemoresistance. This phase 2 study evaluated oral azacitidine (CC-486) plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) as initial treatment for PTCL. CC-486 at 300 mg daily was administered for 7 days before C1 of CHOP, and for 14 days before CHOP C2-6.

Effect of Stress Signals and Ib-rolB/C Overexpression on Secondary Metabolite Biosynthesis in Cell Cultures of Ipomoea batatas.

is a vital root crop and a source of caffeoylquinic acid derivatives (CQAs) with potential health-promoting benefits. As a naturally transgenic plant, contains cellular T-DNA (cT-DNA) sequence homologs of the open reading frame (ORF)14, ORF17n, rooting locus (Rol)B/RolC, ORF13, and ORF18/ORF17n of unknown function. This study aimed to evaluate the effect of abiotic stresses (temperature, ultraviolet, and light) and chemical elicitors (methyl jasmonate, salicylic acid, and sodium nitroprusside) on the biosynthesis of CQAs and cT-DNA gene expression in cell culture as a model system.

IRAA: A statistical tool for investigating a protein-protein interaction interface from multiple structures.

Understanding protein-protein interactions (PPIs) is fundamental to infer how different molecular systems work. A major component to model molecular recognition is the buried surface area (BSA), that is, the area that becomes inaccessible to solvent upon complex formation. To date, many attempts tried to connect BSA to molecular recognition principles, and in particular, to the underlying binding affinity.

Tuberculosis incidence and its socioeconomic determi-nants: developing a parsimonious model.

Background: Tuberculosis is a widespread communicable disease, which is one of the top 10 causes of demise globally. Several regression models have been built, and then utilized for the Tuberculosis incidence projections. However, when fitting a multiple linear regression model, an analysis must account for multicollinearity aspects.

The LOTUS initiative for open knowledge management in natural products research.

Contemporary bioinformatic and chemoinformatic capabilities hold promise to reshape knowledge management, analysis and interpretation of data in natural products research. Currently, reliance on a disparate set of non-standardized, insular, and specialized databases presents a series of challenges for data access, both within the discipline and for integration and interoperability between related fields. The fundamental elements of exchange are referenced structure-organism pairs that establish relationships between distinct molecular structures and the living organisms from which they were identified.