63 research outputs found
Quality of Computationally Inferred Gene Ontology Annotations
Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation
The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing.
Microbial ecology is plagued by problems
of an abstract nature. Cell sizes are so
small and population sizes so large that
both are virtually incomprehensible. Niches
are so far from our everyday experience
as to make their very definition elusive.
Organisms that may be abundant and
critical to our survival are little understood,
seldom described and/or cultured,
and sometimes yet to be even seen. One
way to confront these problems is to use
data of an even more abstract nature:
molecular sequence data. Massive environmental
nucleic acid sequencing, such
as metagenomics or metatranscriptomics,
promises functional analysis of microbial
communities as a whole, without prior
knowledge of which organisms are in the
environment or exactly how they are
interacting. But sequence-based ecological
studies nearly always use a comparative
approach, and that requires relevant
reference sequences, which are an extremely
limited resource when it comes to
microbial eukaryotes.
In practice, this means sequence databases
need to be populated with enormous
quantities of data for which we have
some certainties about the source. Most
important is the taxonomic identity of
the organism from which a sequence is
derived and as much functional identification
of the encoded proteins as possible. In
an ideal world, such information would be
available as a large set of complete, well curated,
and annotated genomes for all the
major organisms from the environment
in question. Reality substantially diverges
from this ideal, but at least for bacterial
molecular ecology, there is a database
consisting of thousands of complete genomes
from a wide range of taxa,
supplemented by a phylogeny-driven approach
to diversifying genomics [2]. For
eukaryotes, the number of available genomes
is far, far fewer, and we have relied
much more heavily on random growth of
sequence databases, raising the
question as to whether this is fit for
purpose
Self-medication of migraine and tension-type headache: summary of the evidence-based recommendations of the Deutsche Migräne und Kopfschmerzgesellschaft (DMKG), the Deutsche Gesellschaft für Neurologie (DGN), the Österreichische Kopfschmerzgesellschaft (ÖKSG) and the Schweizerische Kopfwehgesellschaft (SKG)
The current evidence-based guideline on self-medication in migraine and tension-type headache of the German, Austrian and Swiss headache societies and the German Society of Neurology is addressed to physicians engaged in primary care as well as pharmacists and patients. The guideline is especially concerned with the description of the methodology used, the selection process of the literature used and which evidence the recommendations are based upon. The following recommendations about self-medication in migraine attacks can be made: The efficacy of the fixed-dose combination of acetaminophen, acetylsalicylic acid and caffeine and the monotherapies with ibuprofen or naratriptan or acetaminophen or phenazone are scientifically proven and recommended as first-line therapy. None of the substances used in self-medication in migraine prophylaxis can be seen as effective. Concerning the self-medication in tension-type headache, the following therapies can be recommended as first-line therapy: the fixed-dose combination of acetaminophen, acetylsalicylic acid and caffeine as well as the fixed combination of acetaminophen and caffeine as well as the monotherapies with ibuprofen or acetylsalicylic acid or diclofenac. The four scientific societies hope that this guideline will help to improve the treatment of headaches which largely is initiated by the patients themselves without any consultation with their physicians
Pregnancy-related pelvic girdle pain: an update
A large number of scientists from a wide range of medical and surgical disciplines have reported on the existence and characteristics of the clinical syndrome of pelvic girdle pain during or after pregnancy. This syndrome refers to a musculoskeletal type of persistent pain localised at the anterior and/or posterior aspect of the pelvic ring. The pain may radiate across the hip joint and the thigh bones. The symptoms may begin either during the first trimester of pregnancy, at labour or even during the postpartum period. The physiological processes characterising this clinical entity remain obscure. In this review, the definition and epidemiology, as well as a proposed diagnostic algorithm and treatment options, are presented. Ongoing research is desirable to establish clear management strategies that are based on the pathophysiologic mechanisms responsible for the escalation of the syndrome's symptoms to a fraction of the population of pregnant women
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe
Organic matter from Artic sea ice loss alters bacterial community structure and function
Continuing losses of multi-year sea ice (MYI) across the Arctic are resulting in first-year ice (FYI) dominating the Arctic ice pack. Melting FYI provides a strong seasonal pulse of dissolved organic matter (DOM) into surface waters; however, the biological impact of this DOM input is unknown. Here we show that DOM additions cause significant and contrasting changes in under-ice bacterioplankton abundance, production and species composition. Utilization of DOM was influenced by molecular size, with 10-100 kDa and >100 kDa DOM fractions promoting rapid growth of particular taxa, while uptake of sulfur and nitrogen-rich low molecular weight organic compounds shifted bacterial community composition. These results demonstrate the ecological impacts of DOM released from melting FYI, with wideranging consequences for the cycling of organic matter across regions of the Arctic Ocean transitioning from multi-year to seasonal sea ice as the climate continues to warm
The benefits of strength training on musculoskeletal system health: practical applications for interdisciplinary care
Global health organizations have provided recommendations regarding exercise for the general population. Strength training has been included in several position statements due to its multi-systemic benefits. In this narrative review, we examine the available literature, first explaining how specific mechanical loading is converted into positive cellular responses. Secondly, benefits related to specific musculoskeletal tissues are discussed, with practical applications and training programmes clearly outlined for both common musculoskeletal disorders and primary prevention strategies
Conference Record of the IEEE Photovoltaic Specialists Conference
Luminescence imaging is a widely used characterization technique for silicon photovoltaics. However, the tools used to acquire images typically utilize a silicon CCD array for detection, which is a poor absorber at silicon luminescence wavelengths. This leads to a smearing effect in the measured image which can be characterized by a point spread function (PSF). If the true PSF is known then the measured image can be restored through deconvolution. Several methods exist for determining a PSF for a particular imaging system and different extraction techniques can lead to variations in the PSF result, yet no studies have provided comprehensive analysis of PSF deconvolution accuracy when applied to luminescence imaging. In this work, several new techniques have been designed and investigated in order to test PSF deconvolution results, with a view to quantifying improvement or errors generated and potentially leading towards improved image restoration
2017 IEEE 44th Photovoltaic Specialist Conference, PVSC 2017
© 2017 IEEE. Luminescence imaging is a widely used characterization technique for silicon photovoltaics. However, the tools used to acquire images typically utilize a silicon CCD array for detection, which is a poor absorber at silicon luminescence wavelengths. This leads to a smearing effect in the measured image which can be characterized by a point spread function (PSF). If the true PSF is known then the measured image can be restored through deconvolution. Several methods exist for determining a PSF for a particular imaging system and different extraction techniques can lead to variations in the PSF result, yet no studies have provided comprehensive analysis of PSF deconvolution accuracy when applied to luminescence imaging. In this work, several new techniques have been designed and investigated in order to test PSF deconvolution results, with a view to quantifying improvement or errors generated and potentially leading towards improved image restoration
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