Occurrence of Acute Pulmonary Embolism in COVID-19—A case series

[No abstract available

New deep-water cnidarian sites in the southern Adriatic Sea

Recent ROV (Remotely Operated Vehicle) exploration and bottom sampling in the southern Adriatic Sea (Apulian and Montenegrin margins) resulted in the discovery of cnidarian-rich deep-sea habitats in the depth range of ca. 400-700 m. In particular, ROV inspection of Montenegrin canyons reveals the existence of megabenthic communities dominated by a variety of cnidarians, including scleractinians (Madrepora oculata, Lophelia pertusa, Dendrophyllia cornigera),antipatharians (Leiopathes glaberrima) and gorgonians (Callogorgia verticillata) as major habitat forming taxa, often in association with sponges and, subordinately, serpulids. All such cnidarians are new records for the south-eastern side of the Adriatic Sea. Our investigation indicates that an almost continuous belt of patchy cold water coral sites occurs along the entire south-western margin (Apulian),basically connecting the Adriatic populations with those inhabiting the Ionian margin (Santa Maria di Leuca coral province)

A Network of MicroRNAs and mRNAs Involved in Melanosome Maturation and Trafficking Defines the Lower Response of Pigmentable Melanoma Cells to Targeted Therapy

Simple Summary Selective inhibitors of mutant BRAFV600E (BRAFi) have revolutionized the treatment of metastatic melanoma patients and represent a powerful example of the efficacy of targeted therapy. However, one of the main limitations of BRAFi is that treated cells put in place several adaptive response mechanisms, which initially confer drug tolerance and later provide a gateway for the insurgence of genetically acquired resistance mechanisms. We previously discovered that pigmentation is one of these adaptive response mechanisms. Upon BRAFi treatment, those cells that increase their pigmentation level are more resistant to BRAFi than those that do not. Here, we demonstrate that pigmentation limits BRAFi activity through an increase in the number of intracellular mature melanosomes. We also show that this increase derives from increased maturation and/or trafficking. In addition, we identify the miRNAs and mRNAs that are involved in these biological processes. Finally, we provide the rationale for testing a new combinatorial therapeutic strategy that aims at increasing BRAFi efficacy by blocking the adaptive responses that they elicit. This strategy is based on the combined use of BRAFi with inhibitors of pigmentation, specifically inhibitors of melanosome maturation and/or trafficking. Background: The ability to increase their degree of pigmentation is an adaptive response that confers pigmentable melanoma cells higher resistance to BRAF inhibitors (BRAFi) compared to non-pigmentable melanoma cells. Methods: Here, we compared the miRNome and the transcriptome profile of pigmentable 501Mel and SK-Mel-5 melanoma cells vs. non-pigmentable A375 melanoma cells, following treatment with the BRAFi vemurafenib (vem). In depth bioinformatic analyses (clusterProfiler, WGCNA and SWIMmeR) allowed us to identify the miRNAs, mRNAs and biological processes (BPs) that specifically characterize the response of pigmentable melanoma cells to the drug. Such BPs were studied using appropriate assays in vitro and in vivo (xenograft in zebrafish embryos). Results: Upon vem treatment, miR-192-5p, miR-211-5p, miR-374a-5p, miR-486-5p, miR-582-5p, miR-1260a and miR-7977, as well as GPR143, OCA2, RAB27A, RAB32 and TYRP1 mRNAs, are differentially expressed only in pigmentable cells. These miRNAs and mRNAs belong to BPs related to pigmentation, specifically melanosome maturation and trafficking. In fact, an increase in the number of intracellular melanosomes-due to increased maturation and/or trafficking-confers resistance to vem. Conclusion: We demonstrated that the ability of pigmentable cells to increase the number of intracellular melanosomes fully accounts for their higher resistance to vem compared to non-pigmentable cells. In addition, we identified a network of miRNAs and mRNAs that are involved in melanosome maturation and/or trafficking. Finally, we provide the rationale for testing BRAFi in combination with inhibitors of these biological processes, so that pigmentable melanoma cells can be turned into more sensitive non-pigmentable cells

Nothing in (sponge) biology makes sense - except when based on holotypes

Sponge species are infamously difficult to identify for non-experts due to their high morphological plasticity and the paucity of informative morphological characters. The use of molecular techniques certainly helps with species identification, but unfortunately it requires prior reference sequences. Holotypes constitute the best reference material for species identification, however their usage in molecular systematics and taxonomy is scarce and frequently not even attempted, mostly due to their antiquity and preservation history. Here we provide case studies in which we demonstrate the importance of using holo-type material to answer phylogenetic and taxonomic questions. We also demonstrate the possibility of sequencing DNA fragments out of century-old holotypes. Furthermore we propose the deposition of DNA sequences in conjunction with new species descriptions

Circulating microRNAs in metastatic colorectal cancer (mCRC) patients (pts) treated with regorafenib

Abstract not availabl

The landscape of BRAF transcript and protein variants in human cancer

Background: The BRAF protein kinase is widely studied as a cancer driver and therapeutic target. However, the regulation of its expression is not completely understood. Results: Taking advantage of the RNA-seq data of more than 4800 patients belonging to 9 different cancer types, we show that BRAF mRNA exists as a pool of 3 isoforms (reference BRAF, BRAF-X1, and BRAF-X2) that differ in the last part of their coding sequences, as well as in the length (BRAF-ref: 76 nt; BRAF-X1 and BRAF-X2: up to 7 kb) and in the sequence of their 3'UTRs. The expression levels of BRAF-ref and BRAF-X1/X2 are inversely correlated, while the most prevalent among the three isoforms varies from cancer type to cancer type. In melanoma cells, the X1 isoform is expressed at the highest level in both therapy-naïve cells and cells with acquired resistance to vemurafenib driven by BRAF gene amplification or expression of the Δ[3-10] splicing variant. In addition to the BRAF-ref protein, the BRAF-X1 protein (the full length as well as the Δ[3-10] variant) is also translated. The expression levels of the BRAF-ref and BRAF-X1 proteins are similar, and together they account for BRAF functional activities. In contrast, the endogenous BRAF-X2 protein is hard to detect because the C-terminal domain is selectively recognized by the ubiquitin-proteasome pathway and targeted for degradation. Conclusions: By shedding light on the repertoire of BRAF mRNA and protein variants, and on the complex regulation of their expression, our work paves the way to a deeper understanding of a crucially important player in human cancer and to a more informed development of new therapeutic strategies

MicroRNAs can generate thresholds in target gene expression

MicroRNAs (miRNAs) are short, highly conserved noncoding RNA molecules that repress gene expression in a sequence-dependent manner. We performed single-cell measurements using quantitative fluorescence microscopy and flow cytometry to monitor a target gene's protein expression in the presence and absence of regulation by miRNA. We find that although the average level of repression is modest, in agreement with previous population-based measurements, the repression among individual cells varies dramatically. In particular, we show that regulation by miRNAs establishes a threshold level of target mRNA below which protein production is highly repressed. Near this threshold, protein expression responds sensitively to target mRNA input, consistent with a mathematical model of molecular titration. These results show that miRNAs can act both as a switch and as a fine-tuner of gene expression.National Institutes of Health (U.S.). Director's Pioneer Award (1DP1OD003936)National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)United States. Public Health Service (Grant R01-CA133404)United States. Public Health Service (Grant R01-GM34277)National Cancer Institute (U.S.) (PO1-CA42063)National Cancer Institute (U.S.) Cancer Center Support (Grant P30-CA14051)Howard Hughes Medical Institute. Predoctoral FellowshipCleo and Paul Schimmel Foundation. FellowshipNatural Sciences and Engineering Research Council of Canada PGS Scholarshi

Genome Analysis of the Domestic Dog (Korean Jindo) by Massively Parallel Sequencing

Although pioneering sequencing projects have shed light on the boxer and poodle genomes, a number of challenges need to be met before the sequencing and annotation of the dog genome can be considered complete. Here, we present the DNA sequence of the Jindo dog genome, sequenced to 45-fold average coverage using Illumina massively parallel sequencing technology. A comparison of the sequence to the reference boxer genome led to the identification of 4 675 437 single nucleotide polymorphisms (SNPs, including 3 346 058 novel SNPs), 71 642 indels and 8131 structural variations. Of these, 339 non-synonymous SNPs and 3 indels are located within coding sequences (CDS). In particular, 3 non-synonymous SNPs and a 26-bp deletion occur in the TCOF1 locus, implying that the difference observed in cranial facial morphology between Jindo and boxer dogs might be influenced by those variations. Through the annotation of the Jindo olfactory receptor gene family, we found 2 unique olfactory receptor genes and 236 olfactory receptor genes harbouring non-synonymous homozygous SNPs that are likely to affect smelling capability. In addition, we determined the DNA sequence of the Jindo dog mitochondrial genome and identified Jindo dog-specific mtDNA genotypes. This Jindo genome data upgrade our understanding of dog genomic architecture and will be a very valuable resource for investigating not only dog genetics and genomics but also human and dog disease genetics and comparative genomics

Comparing Artificial Neural Networks, General Linear Models and Support Vector Machines in Building Predictive Models for Small Interfering RNAs

Exogenous short interfering RNAs (siRNAs) induce a gene knockdown effect in cells by interacting with naturally occurring RNA processing machinery. However not all siRNAs induce this effect equally. Several heterogeneous kinds of machine learning techniques and feature sets have been applied to modeling siRNAs and their abilities to induce knockdown. There is some growing agreement to which techniques produce maximally predictive models and yet there is little consensus for methods to compare among predictive models. Also, there are few comparative studies that address what the effect of choosing learning technique, feature set or cross validation approach has on finding and discriminating among predictive models.Three learning techniques were used to develop predictive models for effective siRNA sequences including Artificial Neural Networks (ANNs), General Linear Models (GLMs) and Support Vector Machines (SVMs). Five feature mapping methods were also used to generate models of siRNA activities. The 2 factors of learning technique and feature mapping were evaluated by complete 3x5 factorial ANOVA. Overall, both learning techniques and feature mapping contributed significantly to the observed variance in predictive models, but to differing degrees for precision and accuracy as well as across different kinds and levels of model cross-validation.The methods presented here provide a robust statistical framework to compare among models developed under distinct learning techniques and feature sets for siRNAs. Further comparisons among current or future modeling approaches should apply these or other suitable statistically equivalent methods to critically evaluate the performance of proposed models. ANN and GLM techniques tend to be more sensitive to the inclusion of noisy features, but the SVM technique is more robust under large numbers of features for measures of model precision and accuracy. Features found to result in maximally predictive models are not consistent across learning techniques, suggesting care should be taken in the interpretation of feature relevance. In the models developed here, there are statistically differentiable combinations of learning techniques and feature mapping methods where the SVM technique under a specific combination of features significantly outperforms all the best combinations of features within the ANN and GLM techniques

Circular RNAs Are the Predominant Transcript Isoform from Hundreds of Human Genes in Diverse Cell Types

Most human pre-mRNAs are spliced into linear molecules that retain the exon order defined by the genomic sequence. By deep sequencing of RNA from a variety of normal and malignant human cells, we found RNA transcripts from many human genes in which the exons were arranged in a non-canonical order. Statistical estimates and biochemical assays provided strong evidence that a substantial fraction of the spliced transcripts from hundreds of genes are circular RNAs. Our results suggest that a non-canonical mode of RNA splicing, resulting in a circular RNA isoform, is a general feature of the gene expression program in human cells