Stimulated cells and cancer cells have widespread shortening of mRNA 3'-untranslated regions (3'UTRs) and switches to shorter mRNA isoforms due to usage of more proximal polyadenylation signals (PASs) in introns and last exons. U1 snRNP (U1), vertebrates' most abundant non-coding (spliceosomal) small nuclear RNA, silences proximal PASs and its inhibition with antisense morpholino oligonucleotides (U1 AMO) triggers widespread premature transcription termination and mRNA shortening. Here we show that low U1 AMO doses increase cancer cells' migration and invasion in vitro by up to 500%, whereas U1 over-expression has the opposite effect. In addition to 3'UTR length, numerous transcriptome changes that could contribute to this phenotype are observed, including alternative splicing, and mRNA expression levels of proto-oncogenes and tumor suppressors. These findings reveal an unexpected role for U1 homeostasis (available U1 relative to transcription) in oncogenic and activated cell states, and suggest U1 as a potential target for their modulation.

/pdf/u1-snrnp-regulates-cancer-cell-migration-and-invasion-in-4wdiaemkkl.pdf

U1 snRNP regulates cancer cell migration and invasion in vitro

Stimulated cells and cancer cells have widespread shortening of mRNA 3’-utranslated regions (3’UTRs) and switches to shorter mRNA isoforms due to usage of more proximal polyadenylation signals (PASs) in the last exon and in introns. U1 snRNA (U1), vertebrates’ most abundant non-coding (spliceosomal) small nuclear RNA, silences proximal PASs and its inhibition with antisense morpholino oligonucleotides (U1 AMO) triggers widespread mRNA shortening. Here we show that U1 AMO also modulates cancer cells’ phenotype, dose-dependently increasing migration and invasion in vitro by up to 500%, whereas U1 over-expression has the opposite effect. In addition to 3’UTR length, numerous transcriptome changes that could contribute to this phenotype are observed, including alternative splicing, and mRNA expression levels of proto-oncogenes and tumor suppressors. These findings reveal an unexpected link between U1 regulation and oncogenic and activated cell states, and suggest U1 as a potential target for their modulation.

/pdf/u1-snrnp-regulates-cancer-cell-migration-and-invasion-2qtpdxxd21.pdf

U1 snRNP regulates cancer cell migration and invasion

In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or even beating those provided by human performance. One of the benefits of DL is the ability to learn massive amounts of data. The DL field has grown fast in the last few years and it has been extensively used to successfully address a wide range of traditional applications. More importantly, DL has outperformed well-known ML techniques in many domains, e.g., cybersecurity, natural language processing, bioinformatics, robotics and control, and medical information processing, among many others. Despite it has been contributed several works reviewing the State-of-the-Art on DL, all of them only tackled one aspect of the DL, which leads to an overall lack of knowledge about it. Therefore, in this contribution, we propose using a more holistic approach in order to provide a more suitable starting point from which to develop a full understanding of DL. Specifically, this review attempts to provide a more comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field. In particular, this paper outlines the importance of DL, presents the types of DL techniques and networks. It then presents convolutional neural networks (CNNs) which the most utilized DL network type and describes the development of CNNs architectures together with their main features, e.g., starting with the AlexNet network and closing with the High-Resolution network (HR.Net). Finally, we further present the challenges and suggested solutions to help researchers understand the existing research gaps. It is followed by a list of the major DL applications. Computational tools including FPGA, GPU, and CPU are summarized along with a description of their influence on DL. The paper ends with the evolution matrix, benchmark datasets, and summary and conclusion.

/pdf/review-of-deep-learning-concepts-cnn-architectures-hpbk62qzc2.pdf

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Abstract Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele. 

/pdf/new-insights-into-the-genetic-etiology-of-alzheimers-disease-2xdh9agn.pdf

New insights into the genetic etiology of Alzheimer’s disease and related dementias

As a promising substitute for fossil fuels, hydrogen has emerged as a clean and renewable energy. A key challenge is the efficient production of hydrogen to meet the commercial-scale demand of hydrogen. Water splitting electrolysis is a promising pathway to achieve the efficient hydrogen production in terms of energy conversion and storage in which catalysis or electrocatalysis plays a critical role. The development of active, stable, and low-cost catalysts or electrocatalysts is an essential prerequisite for achieving the desired electrocatalytic hydrogen production from water splitting for practical use, which constitutes the central focus of this review. It will start with an introduction of the water splitting performance evaluation of various electrocatalysts in terms of activity, stability, and efficiency. This will be followed by outlining current knowledge on the two half-cell reactions, hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), in terms of reaction mechanisms in alkaline and acidic media. Recent advances in the design and preparation of nanostructured noble-metal and non-noble metal-based electrocatalysts will be discussed. New strategies and insights in exploring the synergistic structure, morphology, composition, and active sites of the nanostructured electrocatalysts for increasing the electrocatalytic activity and stability in HER and OER will be highlighted. Finally, future challenges and perspectives in the design of active and robust electrocatalysts for HER and OER towards efficient production of hydrogen from water splitting electrolysis will also be outlined.

/pdf/hydrogen-production-from-water-electrolysis-role-of-eoic6x42vo.pdf

Hydrogen production from water electrolysis: role of catalysts.

Genome-wide analyses of the effects of U1 snRNP inhibition in human cells shows that telescripting suppresses premature cleavage and polyadenylation in long introns to sustain expression of large genes important for cell cycle and development. U1 snRNP (U1) functions in splicing introns and telescripting, which suppresses premature cleavage and polyadenylation (PCPA). Using U1 inhibition in human cells, we show that U1 telescripting is selectively required for sustaining long-distance transcription elongation in introns of large genes (median 39 kb). Evidence of widespread PCPA in the same locations in normal tissues reveals that large genes incur natural transcription attrition. Underscoring the importance of U1 telescripting as a gene-size-based mRNA-regulation mechanism, small genes were not sensitive to PCPA, and the spliced-mRNA productivity of ∼1,000 small genes (median 6.8 kb) increased upon U1 inhibition. Notably, these small, upregulated genes were enriched in functions related to acute stimuli and cell-survival response, whereas genes subject to PCPA were enriched in cell-cycle progression and developmental functions. This gene size–function polarization increased in metazoan evolution by enormous intron expansion. We propose that telescripting adds an overarching layer of regulation to size–function-stratified genomes, leveraged by selective intron expansion to rapidly shift gene expression priorities.

U1 snRNP telescripting regulates a size-function-stratified human genome.

A Complex of U1 snRNP with Cleavage and Polyadenylation Factors Controls Telescripting, Regulating mRNA Transcription in Human Cells

Recent observations showed that nascent RNA polymerase II transcripts, pre-mRNAs, and noncoding RNAs are highly susceptible to premature 3'-end cleavage and polyadenylation (PCPA) from numerous intronic cryptic polyadenylation signals (PASs). The importance of this in gene regulation was not previously appreciated as PASs, despite their prevalence, were thought to be active in terminal exons at gene ends. Unexpectedly, antisense oligonucleotide interference with U1 snRNA base-pairing to 5' splice sites, which is necessary for U1 snRNP's (U1) function in splicing, caused widespread PCPA in metazoans. This uncovered U1's PCPA suppression activity, termed telescripting, as crucial for full-length transcription in thousands of vertebrate genes, providing a general role in transcription elongation control. Progressive intron-size expansion in metazoan evolution greatly increased PCPA vulnerability and dependence on U1 telescripting. We describe how these observations unfolded and discuss U1 telescripting's role in shaping the transcriptome.

/pdf/u1-snrnp-telescripting-suppression-of-premature-2owoyt4kfq.pdf

Christopher C. Venters

Papers

U1 snRNP regulates cancer cell migration and invasion in vitro

U1 snRNP regulates cancer cell migration and invasion

U1 snRNP telescripting regulates a size-function-stratified human genome.

A Complex of U1 snRNP with Cleavage and Polyadenylation Factors Controls Telescripting, Regulating mRNA Transcription in Human Cells

U1 snRNP Telescripting: Suppression of Premature Transcription Termination in Introns as a New Layer of Gene Regulation