242 research outputs found
Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions
Technology solutions must effectively balance economic growth, social equity,
and environmental integrity to achieve a sustainable society. Notably, although
the Internet of Things (IoT) paradigm constitutes a key sustainability enabler,
critical issues such as the increasing maintenance operations, energy
consumption, and manufacturing/disposal of IoT devices have long-term negative
economic, societal, and environmental impacts and must be efficiently
addressed. This calls for self-sustainable IoT ecosystems requiring minimal
external resources and intervention, effectively utilizing renewable energy
sources, and recycling materials whenever possible, thus encompassing energy
sustainability. In this work, we focus on energy-sustainable IoT during the
operation phase, although our discussions sometimes extend to other
sustainability aspects and IoT lifecycle phases. Specifically, we provide a
fresh look at energy-sustainable IoT and identify energy provision, transfer,
and energy efficiency as the three main energy-related processes whose
harmonious coexistence pushes toward realizing self-sustainable IoT systems.
Their main related technologies, recent advances, challenges, and research
directions are also discussed. Moreover, we overview relevant performance
metrics to assess the energy-sustainability potential of a certain technique,
technology, device, or network and list some target values for the next
generation of wireless systems. Overall, this paper offers insights that are
valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the
Communications Societ
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Genome-wide determination of drug localization
A vast number of small-molecule ligands, including therapeutic drugs under development and in clinical use, elicit their effects by binding specific proteins associated with the genome. An ability to map the direct interactions of a chemical entity with chromatin genome-wide could provide new and important insights into chemical perturbation of cellular function. Here we describe a method that couples ligand-affinity capture and massively parallel DNA sequencing (Chem-seq) to identify the sites bound by small chemical molecules throughout the human genome. We show how Chem-seq can be combined with ChIP-seq to gain unique insights into the interaction of drugs with their target proteins throughout the genome of tumor cells. These methods provide a powerful approach to enhance understanding of therapeutic action and characterize the specificity of chemical entities that interact with DNA or genome-associated proteins
Methods to study splicing from high-throughput RNA Sequencing data
The development of novel high-throughput sequencing (HTS) methods for RNA
(RNA-Seq) has provided a very powerful mean to study splicing under multiple
conditions at unprecedented depth. However, the complexity of the information
to be analyzed has turned this into a challenging task. In the last few years,
a plethora of tools have been developed, allowing researchers to process
RNA-Seq data to study the expression of isoforms and splicing events, and their
relative changes under different conditions. We provide an overview of the
methods available to study splicing from short RNA-Seq data. We group the
methods according to the different questions they address: 1) Assignment of the
sequencing reads to their likely gene of origin. This is addressed by methods
that map reads to the genome and/or to the available gene annotations. 2)
Recovering the sequence of splicing events and isoforms. This is addressed by
transcript reconstruction and de novo assembly methods. 3) Quantification of
events and isoforms. Either after reconstructing transcripts or using an
annotation, many methods estimate the expression level or the relative usage of
isoforms and/or events. 4) Providing an isoform or event view of differential
splicing or expression. These include methods that compare relative
event/isoform abundance or isoform expression across two or more conditions. 5)
Visualizing splicing regulation. Various tools facilitate the visualization of
the RNA-Seq data in the context of alternative splicing. In this review, we do
not describe the specific mathematical models behind each method. Our aim is
rather to provide an overview that could serve as an entry point for users who
need to decide on a suitable tool for a specific analysis. We also attempt to
propose a classification of the tools according to the operations they do, to
facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde
Targeting transcription regulation in cancer with a covalent CDK7 inhibitor
Tumour oncogenes include transcription factors that co-opt the general transcriptional machinery to sustain the oncogenic state, but direct pharmacological inhibition of transcription factors has so far proven difficult. However, the transcriptional machinery contains various enzymatic cofactors that can be targeted for the development of new therapeutic candidates, including cyclin-dependent kinases (CDKs). Here we present the discovery and characterization of a covalent CDK7 inhibitor, THZ1, which has the unprecedented ability to target a remote cysteine residue located outside of the canonical kinase domain, providing an unanticipated means of achieving selectivity for CDK7. Cancer cell-line profiling indicates that a subset of cancer cell lines, including human T-cell acute lymphoblastic leukaemia (T-ALL), have exceptional sensitivity to THZ1. Genome-wide analysis in Jurkat T-ALL cells shows that THZ1 disproportionally affects transcription of RUNX1 and suggests that sensitivity to THZ1 may be due to vulnerability conferred by the RUNX1 super-enhancer and the key role of RUNX1 in the core transcriptional regulatory circuitry of these tumour cells. Pharmacological modulation of CDK7 kinase activity may thus provide an approach to identify and treat tumour types that are dependent on transcription for maintenance of the oncogenic state.National Institutes of Health (U.S.) (Grant HG002668)National Institutes of Health (U.S.) (Grant CA109901
Normalizing single-cell RNA sequencing data: challenges and opportunities
Single-cell transcriptomics is becoming an important component of the molecular biologist's toolkit. A critical step when analyzing data generated using this technology is normalization. However, normalization is typically performed using methods developed for bulk RNA sequencing or even microarray data, and the suitability of these methods for single-cell transcriptomics has not been assessed. We here discuss commonly used normalization approaches and illustrate how these can produce misleading results. Finally, we present alternative approaches and provide recommendations for single-cell RNA sequencing users
Recurrent somatic mutations in POLR2A define a distinct subset of meningiomas
RNA polymerase II mediates the transcription of all protein-coding genes in eukaryotic cells, a process that is fundamental to life. Genomic mutations altering this enzyme have not previously been linked to any pathology in humans, which is a testament to its indispensable role in cell biology. On the basis of a combination of next-generation genomic analyses of 775 meningiomas, we report that recurrent somatic p.Gln403Lys or p.Leu438_His439del mutations in POLR2A, which encodes the catalytic subunit of RNA polymerase II (ref. 1), hijack this essential enzyme and drive neoplasia. POLR2A mutant tumors show dysregulation of key meningeal identity genes including WNT6 and ZIC1/ZIC4. In addition to mutations in POLR2A, NF2, SMARCB1, TRAF7, KLF4, AKT1, PIK3CA, and SMO4 we also report somatic mutations in AKT3, PIK3R1, PRKAR1A, and SUFU in meningiomas. Our results identify a role for essential transcriptional machinery in driving tumorigenesis and define mutually exclusive meningioma subgroups with distinct clinical and pathological features
Histone H3 globular domain acetylation identifies a new class of enhancers
Histone acetylation is generally associated with active chromatin, but most studies have focused on the acetylation of histone tails. Various histone H3 and H4 tail acetylations mark the promoters of active genes. These modifications include acetylation of histone H3 at lysine 27 (H3K27ac), which blocks Polycomb-mediated trimethylation of H3K27 (H3K27me3). H3K27ac is also widely used to identify active enhancers, and the assumption has been that profiling H3K27ac is a comprehensive way of cataloguing the set of active enhancers in mammalian cell types. Here we show that acetylation of lysine residues in the globular domain of histone H3 (lysine 64 (H3K64ac) and lysine 122 (H3K122ac)) marks active gene promoters and also a subset of active enhancers. Moreover, we find a new class of active functional enhancers that is marked by H3K122ac but lacks H3K27ac. This work suggests that, to identify enhancers, a more comprehensive analysis of histone acetylation is required than has previously been considered
Cornelia-de Lange syndrome-associated mutations cause a DNA damage signalling and repair defect
Cornelia de Lange syndrome is a multisystem developmental disorder typically caused by mutations in the gene encoding the cohesin loader NIPBL. The associated phenotype is generally assumed to be the consequence of aberrant transcriptional regulation. Recently, we identified a missense mutation in BRD4 associated with a Cornelia de Lange-like syndrome that reduces BRD4 binding to acetylated histones. Here we show that, although this mutation reduces BRD4-occupancy at enhancers it does not affect transcription of the pluripotency network in mouse embryonic stem cells. Rather, it delays the cell cycle, increases DNA damage signalling, and perturbs regulation of DNA repair in mutant cells. This uncovers a role for BRD4 in DNA repair pathway choice. Furthermore, we find evidence of a similar increase in DNA damage signalling in cells derived from NIPBL-deficient individuals, suggesting that defective DNA damage signalling and repair is also a feature of typical Cornelia de Lange syndrome
Applied screening tests for the detection of superior face recognition.
In recent years there has been growing interest in the identification of people with superior face recognition skills, for both theoretical and applied investigations. These individuals have mostly been identified via their performance on a single attempt at a tightly controlled test of face memory-the long form of the Cambridge Face Memory Test (CFMT+). The consistency of their skills over a range of tests, particularly those replicating more applied policing scenarios, has yet to be examined systematically. The current investigation screened 200 people who believed they have superior face recognition skills, using the CFMT+ and three new, more applied tests (measuring face memory, face matching and composite-face identification in a crowd). Of the sample, 59.5% showed at least some consistency in superior face recognition performance, although only five individuals outperformed controls on overall indices of target-present and target-absent trials. Only one participant outperformed controls on the Crowds test, suggesting that some applied face recognition tasks require very specific skills. In conclusion, future screening protocols need to be suitably thorough to test for consistency in performance, and to allow different types of superior performer to be detected from the outset. Screening for optimal performers may sometimes need to directly replicate the task in question, taking into account target-present and target-absent performance. Self-selection alone is not a reliable means of identifying those at the top end of the face recognition spectrum
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