bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geomagnetically induced currents in the Irish power network during geomagnetic storms
Authors: Blake Seán P. , Gallagher Peter T. , McCauley Joe , Jones Alan G. , Hogg Colin , Campanyà Joan , Beggan Ciarán D. , Thomson Alan W. P. , Kelly Gemma S. , Bell David 
Published: November 2016

AbstractGeomagnetically induced currents (GICs) are a well‐known terrestrial space weather hazard. They occur in power transmission networks and are known to have adverse effects in both high‐latitude and midlatitude countries. Here we study GICs in the Irish power transmission network (geomagnetic latitude 54.7–58.5°N) during five geomagnetic storms (6–7 March 2016, 20–21 December 2015, 17–18 March 2015, 29–31 October 2003, and 13–14 March 1989). We simulate electric fields using a plane wave method together with two ground resistivity models, one of which is derived from magnetotelluric measurements (magnetotelluric (MT) model). We then calculate GICs in the 220, 275, and 400 kV transmission network. During the largest of the storm periods studied, the peak electric field was calculated to be as large as 3.8 V km−1, with associated GICs of up to 23 A using our MT model. Using our homogenous resistivity model, those peak values were 1.46 V km−1 and 25.8 A. We find that three 400 and 275 kV substations are the most likely locations for the Irish transformers to experience large GICs.
Demasking the integrated information of discharge: Advancing sensitivity analysis to consider different hydrological components and their rates of change
Authors: Guse Björn , Pfannerstill Matthias , Gafurov Abror , Fohrer Nicola , Gupta Hoshin 
Published: November 2016

AbstractDischarge as an integrated representation of all hydrological processes is the most common response variable used in sensitivity analyses. However, due to overlaying effects of all hydrological processes, the sensitivity signal of certain parameters to discharge can be masked. A more informative form of sensitivity analysis can be achieved by investigating how parameter sensitivities are related to individual modeled hydrological components. In our study, the TEDPAS (TEmporal Dynamics of PArameter Sensitivity) methodology is used to calculate daily sensitivities to modeled hydrological components and to detect temporal variations in dominant parameters. As a further enhancement to consider both magnitude and dynamics, temporal variations in parameter dominance are analyzed, both for magnitudes and rates of change of hydrological components. For this purpose, regime curves for parameter sensitivities are constructed. The results demonstrate that sensitivities of parameters increase when using the corresponding hydrological component instead of discharge as response variable. For each hydrological component, seasonal patterns of parameter dominance are detected using both magnitude and rate of change as response variable. Major differences are detected for certain capacity parameters, which are less pronounced using rates of change. Overall, we show that disentangling the diagnostic information hidden in the integrated signal of discharge can lead to a more informative signal regarding the sensitivity of hydrological components. Such advancements in sensitivity analysis can lead to a better understanding of how model parameters control the individual hydrological components in time.
Chromosome Mechanics
Authors: LeClair Renée J , Best Robert G 
Published: November 2016

Abstract

Chromosome mechanics describes the processes of chromosome replication and interactions during somatic cell division and gametogenesis. Mitosis can be divided into two phases consisting of nuclear and cytoplasmic division ultimately producing identical diploid somatic cells. Segregation during mitosis is largely dependent on chromosomal attachment to the mitotic spindle with a fully developed kinetochore structure. This is in contrast to meiosis where cells undergo two rounds of nuclear division to produce haploid germ cells. During this process, homologous chromosomes pair at the cellular midline allowing for exchange of deoxyribonucleic acid (DNA) between parental alleles and stabilisation of the chromosome structures during separation. Aberrations occurring in either mitosis or meiosis can result in numerical abnormalities (from nondisjunction events) which often result in nonviable offspring. However, there are some aneuploidies that are viable with trisomy 21 being the most common example of this. Similarly, unrepaired DNA damage resulting in chromosomal breakage and structural rearrangements. These large‐scale genetic changes reduce the genetic efficacy of a cell ultimately leading to cancer or cell death. In summary, mitosis and meiosis are integral parts of the cellular life cycle and both processes are essential at maintaining genomic stability within an organism.

Key Concepts

The cell cycle comprises two main phases: mitosis, where cell division occurs, and interphase, which includes DNA replication and the expression of many essential proteins. Interphase can be further divided into G1, S and G2.

Cyclin‐dependent kinases regulate progression through the cell cycle at three major checkpoints: G1, G2 and a spindle checkpoint during mitosis.

Mitosis is the process of cell division resulting in two identical diploid cells and can be divided into prophase, metaphase, anaphase and telophase.

Meiosis is the process of cell division that results in germline cells where following one round to DNA replication, the cell undergoes two cell divisions.

Meiosis in males results in four identical haploid cells, while meiosis in females produces a single mature ovum and three polar bodies.

Aberrations in either mitosis or meiosis can result in nondisjunction resulting in aneuploidy.

Defects in DNA repair mechanisms can also result in chromosome damage or breaking which will negatively impact the process of cell division.
Sequencing the Human Genome: Novel Insights into Its Structure and Function
Authors: Kehrer‐Sawatzki Hildegard , Cooper David N 
Published: November 2016

Abstract

The availability of the human genome sequence has had an enormous impact on biomedical research. New discoveries emanating directly from the elucidation of the human genome sequence have included the unexpectedly low total number of genes, the existence of numerous transcribed but noncoding sequences and the multiplicity of low‐copy repeats and segmental duplications. The Human Genome Project has also spawned new research projects such as Encyclopedia of DNA Elements (ENCODE), Haplotype Map (HapMap) 1000 Genomes Project and the Human Variome Project which together are helping to reveal the remarkable complexity and diversity of the human genome. Finally, comparison of the human reference genome sequence with the genomes of other human species such as the Neanderthal and Denisovan or with other vertebrates has opened up numerous research avenues in evolutionary biology.

Key Concepts

The Human Genome Project has yielded a high‐quality sequence of the human genome which has been available to researchers for more than 10 years.

The 3 billion nucleotide reference assembly has been a prerequisite for the annotation of >22 800 different protein‐coding genes as well as thousands of RNA genes and transcripts of unknown function.

Some 16 000 pseudogenes have also been identified, some of which could encode novel proteins or regulatory RNAs.

Tens of millions of single‐nucleotide polymorphisms have been described as well as tens of thousands of structural variants.

The genome has been found to contain a multitude of structural features such as segmental duplications, transposon‐derived repeats, processed pseudogenes, simple sequence repeats and the blocks of tandemly repeated sequences at the centromeres and telomeres.

Now that the basic structure of the human genome has been elucidated, the focus has switched to trying to understand the function of its components.

The human genome contains noncoding ultraconserved elements which may represent long‐range enhancers of gene expression. The recognition of such elements is serving to change our conception of the nature of the gene.
Pathological Variations in 3′‐Untranslated Regions of Human Genes
Authors: Pal Jayanta K , Chatterjee Sangeeta , Rao Shilpa J 
Published: November 2016

Abstract

The 3′‐untranslated regions (UTRs) of messenger ribonucleic acids (mRNAs) play a critical role in the stabilisation, localisation and translation of mRNAs. Mutations that disrupt functional elements of the 3′‐UTR of mRNAs such as polyadenylation signal, microribonucleic acid (miRNA) target sites and AU‐rich elements lead to production of nonfunctional proteins or reduced amounts of functional proteins. Genetic variations in the 3′‐UTR are associated with disease risk or diseases such as spinocerebellar ataxia 8, Parkinson disease, breast cancer, atopic dermatitis, papillary thyroid carcinoma and many others. With the advent of genetic counselling and promise of personalised medicine, genetic variation in this region of mRNAs is the focus of intense research. Current research shows that this region is of immense significance in the context of translational research.

Key Concepts

3′‐Untranslated regions (UTRs) are noncoding regions of mRNAs.

The 3′‐UTR is delimited by stop codon (UAA or UAG or UGA) at the 5′‐end and poly (A) tail at the 3′‐end.

Motifs such as AU‐rich elements, polyadenylation signal, iron responsive elements and others are involved in mRNA stability, localisation and translation.

Mutations are changes in the DNA/gene of an organism which are heritable.

Mutations in the AU‐rich elements lead to atypical stabilisation of mRNA and associated diseases.

Mutations that lead to abolition of canonical polyadenylation signal interfere with efficient transcription termination and polyadenylation of mRNA.

Mutations in the 3′‐UTR may alter the binding sites of interacting miRNAs or proteins resulting in deregulation of mRNA translation.

Single‐nucleotide polymorphisms (SNPs) in the 3′‐UTR are associated with individual's drug response and disease risk.
TLymphocytes: Plasticity of Subsets
Authors: Mosmann Tim R , Rebhahn Jonathan A 
Published: November 2016

AbstractThe initial characterisation of both mouse and human T cells described distinct and sharply defined cytokine patterns that were relatively stable and were functionally specialised for successfully attacking different pathogens. Additional phenotypes were then described, extending the range of functional types. However, more recently there have been many reports of further changes in cytokine patterns, and it is clear that all the recognised phenotypes were more plastic than originally thought. In particular, many intermediates between established subsets have been reported, for example Th1/Th17 cells expressing both IFNγ (interferon‐gamma) and IL (interleukin)‐17. This plasticity provides extra versatility for the immune system to adapt to changing infections and to altered requirements in different locations. A model of stochastic differentiation is presented, to visualise potential differentiation modes in the framework of a landscape model and to try to encourage discussion and experimentation regarding different mechanisms for plasticity.Key ConceptsInitial models of highly stable T‐cell subsets were useful but underestimated diversity.Flexibility is overlaid on partial stability.Many intermediate phenotypes can be induced.Several questions remain regarding temporary versus long‐term plasticity alterations.Models for visualising differentiation need to be modified to include flexibility around a theme.Incorporation of stochastic trends may give a more useful representation of differentiation.
Molecular Genetics of
DNA
Polymerase Gamma‐associated Neurodegeneration
Authors: Tzoulis Charalampos , Bindoff Laurence A 
Published: November 2016

Abstract

Polymerase gamma (POLG) mutations are a common cause of mitochondrial disease and have also been linked to neurodegeneration and ageing. POLG mutations impair the maintenance of mitochondrial deoxyribonucleic acid (mtDNA) in cells causing a combination of quantitative mtDNA depletion, which can present in infancy, and the accumulation of deletions and point mutations, which gradually build up over time. In neurones, this increased somatic mtDNA mutagenesis compromises neuronal respiration, primarily in the form of complex I deficiency, which in turn primes neurones for injury. These two distinct but overlapping biological processes are best described as acute on chronic neurodegeneration. The chronic process affects the cerebellum, deep nuclei such as the dopaminergic cells of the substantia nigra and spinal cord and is reflected clinically by progressive spinocerebellar ataxia. In contract, the acute cortical lesions associated with focal neuronal necrosis occur widely and appear to be triggered and or worsened by epileptic seizures.

Key Concepts

Polymerase gamma is the only enzyme that replicates and repairs mitochondrial DNA and comprises one catalytic subunit (pol γ A) encoded by the POLG gene and two accessory subunits (pol γ B) encoded by the POLG1 gene.

POLG dysfunction is a common cause of mitochondrial disease and has been associated with ageing and neurodegeneration.

POLG mutations impair mtDNA homeostasis.

MtDNA loss, depletion, is an early event often present from infancy, whereas deletions and point mutations accumulate gradually during the course of the disease.

Accumulating mtDNA damage leads to respiratory dysfunction and in particular complex I deficiency, compromising ATP production in neurones.

Neuronal populations that are most vulnerable to ATP deficiency, including those in the cerebellum, thalamus and substantia nigra, exhibit a chronic progressive neurodegeneration and a progressive spinocerebellar ataxia.

In spite of severe substantia nigra degeneration and nigrostriatal depletion, patients do not develop clinical parkinsonism, suggesting this is compensated by dysfunction elsewhere in the brain.

Acute cortical lesions appear to be triggered by epileptic seizures and underlie episodes with severe, rapidly progressive encephalopathy, focal neurological dysfunction and high morbidity and mortality.

The most important predictors of prognosis are the presence of a compound heterozygous genotype, an age of onset before 2 years and the presence of epilepsy; these are associated with severe disease, rapid progression and highest mortality rate.

No disease modulating therapy exists for POLG encephalopathy. Efficient control of the epilepsy is the cornerstone of treatment.
Molecular Genetics of Fibrodysplasia Ossificans Progressiva
Authors: Hüning Irina , Gillessen‐Kaesbach Gabriele 
Published: November 2016

Abstract

Fibrodysplasia ossificans progressiva (FOP, MIM 135100) is an autosomal‐dominant genetic disorder, caused by heterozygous mutations in the
ACVR1
gene. Its defining clinical feature is heterotopic (extraskeletal) ossifications (HO). Almost all patients show also fibular deviation and shortness of the great toes from birth. However, the phenotypes of FOP patients vary and there seem to be a genotype–phenotype correlation even if the number of patients is still small to definitely establish it. Recent literature data support that all of the identified
ACVR1
germ line missense mutations influence the postnatal induction of cartilage and bone cell differentiation. Moreover, it has been recently shown that the most common
ACVR1
mutation p.R206H leads to a protein which causes FOP by gaining responsiveness to the normally antagonistic ligand activin A, important discovery for new therapeutic approaches.

Key Concepts

FOP is caused by heterozygous missense activating mutations of the
ACVR1
gene.

A clear genotype–phenotype correlation in FOP is highly presumable, even though the number of patients is small.

Analysis of the mutations, different from the common R206H mutation supply FOP research with valuable knowledge of the mechanisms of disease and possible therapeutic approaches.

Understanding of molecular mechanisms causing FOP is a major key step for developing therapy concepts.

Understanding FOP and the pathomechanisms of this extremely rare disease may be very helpful for the understanding of other more common forms of heterotopic ossifications, such as Posttraumatic Heterotopic Ossification and Neurogenic Heterotopic Ossification.
Statistical Signal Processing
Authors: Kannan Nandini , Kundu Debasis 
Published: November 2016

AbstractStatistical signal processing is an important area of research with extensive applications in the fields of communication theory, array processing, seismology, and medical diagnosis. The goal of signal processing is to recover characteristics of the underlying process from observed data. The random nature of the signals underscores the need for statistical techniques in model formulation, estimation, and data analysis. A brief discussion of the different models that have been widely studied in the statistical signal‐processing literature is provided. In addition, different methods of estimation are presented, and some unique characteristics of these models are highlighted.
Gibbs Sampling
Authors: Christen José Andrés 
Published: November 2016

AbstractGibbs sampling is a Monte Carlo simulation tool for obtaining marginal distributions from a nonnormalized joint density (“nonnormalized” means that it has not yet been scaled to integrate to one) and is a particular case of Markov chain Monte Carlo (MCMC) methods. The Gibbs sampling was the first MCMC method of general use by statisticians and since its introduction into the mainstream statistical literature by the Gelfand and Smith 1990 paper, it has become a widely employed computational tool in Bayesian statistics as well as in other non‐Bayesian applications.This landmark paper set the foundations for a massive increase in the use of Bayesian methods and changed the statistical practice ever since. With the wide availability of high‐speed computing, the Gibbs sampler and, in fact, general sampling‐based approaches have become basic tools in current modern statistics.
Assessment of Probabilities
Authors: O'Hagan Anthony 
Published: November 2016

AbstractThis article addresses the situation where you are uncertain about the truth of a propositionAand wish to quantify your uncertainty in the form of a probability Pr() that is true, based on your current state of knowledge . A variety of approaches are considered for assessing such a probability value, including classical assessment, frequency assessment, direct assessment, scoring rules, elaborative assessment, and elicitation.
Data Management and Coordination
Authors: McFadden Eleanor T. 
Published: November 2016

AbstractAccurate and timely management of data is key to the success of any clinical trial. Data that is relevant to the objectives of the study must be defined and then collected in a way that minimizes the work at the participating sites and ensures the collection of accurate and meaningful data. This article describes general principles for data management and provides guidance on the steps that must be taken to ensure that the data collected can be used to answer the trial objectives.
Statistical Methods for Hospital Monitoring
Authors: Morton Anthony , Whitby Michael , Tierney Nicholas , Sibanda Nokuthaba , Mengersen Kerrie 
Published: November 2016

AbstractHospitals are complex adaptive systems that can display emergent behavior as the result of the interaction of many agents. This can be an unintended consequence of policy or staff action or can seem to appear spontaneously, so that its nature and consequences may be difficult or impossible to predict.Appropriate statistical approaches are required that accommodate important features of the data, such as rare adverse events following a power law distribution. Moreover, approaches are needed to seek to understand the combined effect of the numerous interacting agents in the system.
Reduced Major Axis Regression
Authors: Harper William V. 
Published: November 2016

AbstractThe theoretical underpinnings of standard least‐squares (LS) regression analysis are based on the assumption that the independent variable (often thought of asx) is measured without error as a design variable. The dependent variable (often labeledy) is modeled as having uncertainty or error. Both independent and dependent measurements may have multiple sources of error. Thus, the underlying least‐squares regression assumptions can be violated. Reduced major axis (RMA) regression is specifically formulated to handle errors in both thexandyvariables. It is an alternative to least squares and demonstrates the importance of understanding the assumptions underlying statistical procedures.
Copper and zinc isotope ratios in human bone and enamel
Authors: Jaouen Klervia , Herrscher Estelle , Balter Vincent 
Published: November 2016

AbstractObjectivesHere, we report Cu and Zn isotope ratios of bones and teeth of French people from various historical periods with the aim to understand how Cu and Zn isotope ratios of bone, a tissue that is continuously remodeled throughout life but that is prone to post‐mortem diagenesis, compare with that of tooth enamel, a tissue that forms once during childhood but that is more resistant to diagenesis. Specifically, we examine (1) the potential existence of sex‐related differences in the Cu isotope ratios (represented as δ65Cu) in the tooth enamel of identified men and women, and (2) a decrease of Zn isotope delta ratios (represented as δ66Zn) related to the increase of meat and fish consumption during the 20th century.MethodsFour series of material were studied: the archeological population of Saint‐Laurent de Grenoble (17th–18th centuries AD), an anatomical collection of skulls (19th century AD), a contemporary anatomical collection of bones never buried, and contemporary teeth samples. The metals were purified by liquid chromatography and their isotopic ratios measured by means of multicollector inductively coupled plasma mass spectrometry.ResultsWe describe a clear offset between bone and tooth enamel for Zn isotope ratios, as previously observed in animals. There is a similar offset for Cu isotope ratios. We did not observe any difference between the δ65Cu values of men and women when looking at dental enamel. For the contemporary samples, the δ66Zn values of bioapatite decreased, which might be explained by the increase of animal product consumption among the French people during this period, notably when the access to seafood became widespread.ConclusionsOur study demonstrates that the Cu and Zn isotope compositions of dental enamel are promising tools for childhood diet reconstruction. Meanwhile, the Cu isotope ratio of tooth enamel is unlikely to be useful for the identification of biological sex, even in the case of populations with early menarche. Further works are needed to understand the relationships between trophic level and Zn isotope ratios of human remains.