Individually different weighting of multiple processes underlies effects of metacontrast masking

Switchable catalysis offers opportunities to control the rate or selectivity of a reaction via a stimulus such as pH or light. However, few examples of switchable catalytic systems that can facilitate multiple processes exist. Here we report a rare example of such dual-functional, switchable catalysis. Featuring an easily prepared, bench-stable cobalt(I) hydride complex in conjunction with pinacolborane, we can completely alter the reaction outcome between two widely employed transformations – olefin migration and hydroboration – with visible light as the sole trigger. This dichotomy arises from ligand photodissociation which leads to metamorphosis of the active catalytic site, resulting in divergent mechanistic pathways.

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The Predominant microRNAs in β-cell Clusters for Insulin Regulation and Diabetic Control

Current Drug Targets ◽

10.2174/1389450121666191230145848 ◽

2020 ◽

Vol 21 (7) ◽

pp. 722-734

Author(s):

Adele Soltani ◽

Arefeh Jafarian ◽

Abdolamir Allameh

Keyword(s):

Mirna Expression ◽

Expression Profiles ◽

Expression Patterns ◽

Diabetic Control ◽

In Vitro Proliferation ◽

Cell Functions ◽

Mirna Expression Profiles ◽

Multiple Processes ◽

The Impact

micro (mi)-RNAs are vital regulators of multiple processes including insulin signaling pathways and glucose metabolism. Pancreatic β-cells function is dependent on some miRNAs and their target mRNA, which together form a complex regulative network. Several miRNAs are known to be directly involved in β-cells functions such as insulin expression and secretion. These small RNAs may also play significant roles in the fate of β-cells such as proliferation, differentiation, survival and apoptosis. Among the miRNAs, miR-7, miR-9, miR-375, miR-130 and miR-124 are of particular interest due to being highly expressed in these cells. Under diabetic conditions, although no specific miRNA profile has been noticed, the expression of some miRNAs and their target mRNAs are altered by posttranscriptional mechanisms, exerting diverse signs in the pathobiology of various diabetic complications. The aim of this review article is to discuss miRNAs involved in the process of stem cells differentiation into β-cells, resulting in enhanced β-cell functions with respect to diabetic disorders. This paper will also look into the impact of miRNA expression patterns on in vitro proliferation and differentiation of β-cells. The efficacy of the computational genomics and biochemical analysis to link the changes in miRNA expression profiles of stem cell-derived β-cells to therapeutically relevant outputs will be discussed as well.

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Pieces from the Microbial Parts Bin Serve Various Functions in Multiple Processes

Microbe Magazine ◽

10.1128/microbe.5.216.1 ◽

2010 ◽

Vol 5 (5) ◽

pp. 216-216

Keyword(s):

Multiple Processes

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Stochastic Modeling of Hydroclimatic Processes Using Vine Copulas

Water ◽

10.3390/w13162156 ◽

2021 ◽

Vol 13 (16) ◽

pp. 2156

Author(s):

George Pouliasis ◽

Gina Alexandra Torres-Alves ◽

Oswaldo Morales-Napoles

Keyword(s):

Time Series ◽

Stochastic Modeling ◽

Copula Models ◽

Multiple Processes ◽

Spatial Dependencies ◽

Probabilistic Dependence ◽

Temporal And Spatial ◽

Vine Copula ◽

Synthetic Time Series ◽

Hydroclimatic Variables

The generation of synthetic time series is important in contemporary water sciences for their wide applicability and ability to model environmental uncertainty. Hydroclimatic variables often exhibit highly skewed distributions, intermittency (that is, alternating dry and wet intervals), and spatial and temporal dependencies that pose a particular challenge to their study. Vine copula models offer an appealing approach to generate synthetic time series because of their ability to preserve any marginal distribution while modeling a variety of probabilistic dependence structures. In this work, we focus on the stochastic modeling of hydroclimatic processes using vine copula models. We provide an approach to model intermittency by coupling Markov chains with vine copula models. Our approach preserves first-order auto- and cross-dependencies (correlation). Moreover, we present a novel framework that is able to model multiple processes simultaneously. This method is based on the coupling of temporal and spatial dependence models through repetitive sampling. The result is a parsimonious and flexible method that can adequately account for temporal and spatial dependencies. Our method is illustrated within the context of a recent reliability assessment of a historical hydraulic structure in central Mexico. Our results show that by ignoring important characteristics of probabilistic dependence that are well captured by our approach, the reliability of the structure could be severely underestimated.

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Metastasis is altered through multiple processes regulated by the E2F1 transcription factor

Scientific Reports ◽

10.1038/s41598-021-88924-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Matthew R. Swiatnicki ◽

Eran R. Andrechek

Keyword(s):

Breast Cancer ◽

Transgenic Mouse Models ◽

Cellular Processes ◽

Mouse Tumors ◽

Mutation Burden ◽

Multiple Processes ◽

Metastatic Process ◽

Cycle Regulation ◽

Bioinformatic Approach ◽

Complicated Nature

AbstractThe E2F family of transcription factors is important for many cellular processes, from their canonical role in cell cycle regulation to other roles in angiogenesis and metastasis. Alteration of the Rb/E2F pathway occurs in various forms of cancer, including breast cancer. E2F1 ablation has been shown to decrease metastasis in MMTV-Neu and MMTV-PyMT transgenic mouse models of breast cancer. Here we take a bioinformatic approach to determine the E2F1 regulated genomic alterations involved in the metastatic cascade, in both Neu and PyMT models. Through gene expression analysis, we reveal few transcriptome changes in non-metastatic E2F1−/− tumors relative to transgenic tumor controls. However investigation of these models through whole genome sequencing found numerous differences between the models, including differences in the proposed tumor etiology between E2F1−/− and E2F1+/+ tumors induced by Neu or PyMT. For example, loss of E2F1 within the Neu model led to an increased contribution of the inefficient double stranded break repair signature to the proposed etiology of the tumors. While the SNV mutation burden was higher in PyMT mouse tumors than Neu mouse tumors, there was no statistically significant differences between E2F WT and E2F1 KO mice. Investigating mutated genes through gene set analysis also found a significant number of genes mutated in the cell adhesion pathway in E2F1−/− tumors, indicating this may be a route for disruption of metastasis in E2F1−/− tumors. Overall, these findings illustrate the complicated nature of uncovering drivers of the metastatic process.

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