On Cancer Cell Cycle and Universal Apoptosis Parameters Signaling Unravelled In Silico

Here, cell cycle in higher eukaryotes and their molecular networks signals both in G1/S and G2/M transitions are in silico replicated. Systems control theory is employed to design multi-nestled digital layers to simulate protein-toprotein activation and inhibition in the cancer cell cycle dynamics in presence of damaged genome. Sequencing and controlling the digital process of four micro-scale species networks (p53/Mdm2/DNA damage; p21mRNA/cyclin-CDK complex; CDK/CDC25/wee1/SKP2/APC/CKI and apoptosis target genes system) paved the way for unravelling the participants and their by-products having the task to execute (or not) cell death. The results of the proposed cell digital multi-layers give reason to believe in the existence of an universal apoptotic mechanism. We identified and selected cell checkpoints, sizers, timers and specific target genes dynamics both for influencing mitotic process and avoiding cancer proliferation as much as for leading the cancer cell(s) to collapse into a steady stable apoptosis phase

Experimental and computational analyses reveal that environmental restrictions shape HIV-1 spread in 3D cultures

Here, using an integrative experimental and computational approach, Imle et al. show how cell motility and density affect HIV cell-associated transmission in a three-dimensional tissue-like culture system of CD4+ T cells and collagen, and how different collagen matrices restrict infection by cell-free virions

The Utility of Graph Clustering of 5S Ribosomal DNA Homoeologs in Plant Allopolyploids, Homoploid Hybrids, and Cryptic Introgressants

Introduction: Ribosomal DNA (rDNA) loci have been widely used for identification of allopolyploids and hybrids, although few of these studies employed high-throughput sequencing data. Here we use graph clustering implemented in the RepeatExplorer (RE) pipeline to analyze homoeologous 5S rDNA arrays at the genomic level searching for hybridogenic origin of species. Data were obtained from more than 80 plant species, including several well-defined allopolyploids and homoploid hybrids of different evolutionary ages and from widely dispersed taxonomic groups. Results: (i) Diploids show simple circular-shaped graphs of their 5S rDNA clusters. In contrast, most allopolyploids and other interspecific hybrids exhibit more complex graphs composed of two or more interconnected loops representing intergenic spacers (IGS). (ii) There was a relationship between graph complexity and locus numbers. (iii) The sequences and lengths of the 5S rDNA units reconstituted in silico from k-mers were congruent with those experimentally determined. (iv) Three-genomic comparative cluster analysis of reads from allopolyploids and progenitor diploids allowed identification of homoeologous 5S rRNA gene families even in relatively ancient (c. 1 Myr) Gossypium and Brachypodium allopolyploids which already exhibit uniparental partial loss of rDNA repeats. (v) Finally, species harboring introgressed genomes exhibit exceptionally complex graph structures. Conclusion: We found that the cluster graph shapes and graph parameters (k-mer coverage scores and connected component index) well-reflect the organization and intragenomic homogeneity of 5S rDNA repeats. We propose that the analysis of 5S rDNA cluster graphs computed by the RE pipeline together with the cytogenetic analysis might be a reliable approach for the determination of the hybrid or allopolyploid plant species parentage and may also be useful for detecting historical introgression events

Enhancing MRI Reconstruction Efficiency Through Multi-GPU Parallelization

Dynamic cardiac MRI (cMRI) is essential for diagnosing cardiovascular diseases, demanding high resolution and image quality. However, achieving superior quality increases data volume and reconstruction time. To tackle this, we propose a solution using parallel imaging and Compressed Sensing (CS) with high-capacity computing devices (e.g., GPUs) for accelerated reconstruction of undersampled data. GPU mem- ory limitations, especially in 3D cMRI, present challenges. Our scalable approach splits the reconstruction problem and employs multiple GPUs (or multiple multi-core CPUs) to per- form multiple optimizations in parallel using the well-known NESTA algorithm, while preserving smoothness between ad- jacent frames in the temporal dimension. Preliminary results on 5D cMRI reconstruction show that our parallel proposal achieves equivalent reconstruction quality in less time, en- abling larger data processing and cost reduction with smaller, more affordable GPUs, as opposed to a single, highly expensive GPU. Moreover, the adoption of the OpenCLIPER frame- work eliminates proprietary GPU technologies. Exploration of adaptability to other sampling schemes opens new possibilities in this field.This work is partially supported by MINECO under grants TEC2017-82408-R, PRE2018-086922, and by the Agencia Estatal de Investigación under grants PID2020- 115339RB-I00 and TED2021-130090B-I00

Scientific teaching targeting faculty from diverse institutions

We offered four annual professional development workshops called STAR (for Scientific Teaching, Assessment, and Resources) modeled after the National Academies Summer Institute (SI) on Undergraduate Education in Biology. In contrast to the SI focus on training faculty from research universities, STAR\u27s target was faculty from community colleges, 2-yr campuses, and public and private research universities. Because of the importance of community colleges and 2-yr institutions as entries to higher education, we wanted to determine whether the SI model can be successfully extended to this broader range of institutions. We surveyed the four cohorts; 47 STAR alumni responded to the online survey. The responses were separated into two groups based on the Carnegie undergraduate instructional program categories, faculty from seven associate\u27s and associate\u27s-dominant institutions (23) and faculty from nine institutions with primarily 4-yr degree programs (24). Both groups expressed the opinion that STAR had a positive impact on teaching, student learning, and engagement. The two groups reported using techniques of formative assessment and active learning with similar frequency. The mix of faculty from diverse institutions was viewed as enhancing the workshop experience. The present analysis indicates that the SI model for training faculty in scientific teaching can successfully be extended to a broad range of higher education institutions. © 2013 C. S. Gregg et al

Fluorescence-activated multi-organelle mapping of subcellular plant hormone distribution

Auxins and cytokinins are two major families of phytohormones that control most aspects of plant growth, development and plasticity. Their distribution in plants has been described, but the importance of cell- and subcellular-type specific phytohormone homeostasis remains undefined. Herein, we revealed auxin and cytokinin distribution maps showing their different organelle-specific allocations within the Arabidopsis plant cell. To do so, we have developed Fluorescence-Activated multi-Organelle Sorting (FAmOS), an innovative subcellular fractionation technique based on flow cytometric principles. FAmOS allows the simultaneous sorting of four differently labelled organelles based on their individual light scatter and fluorescence parameters while ensuring hormone metabolic stability. Our data showed different subcellular distribution of auxin and cytokinins, revealing the formation of phytohormone gradients that have been suggested by the subcellular localization of auxin and cytokinin transporters, receptors and metabolic enzymes. Both hormones showed enrichment in vacuoles, while cytokinins were also accumulated in the endoplasmic reticulum