bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management of work through the seasons of cancer survivorship
Authors: Duijts Saskia F.A. 
Published: November 2017

Purpose of review
Survival from cancer has expanded enormously over the past decades. It is estimated that 40–50% of all cancer survivors are of working age at time of diagnosis and thus potentially part of the labor force. The seasons of survivorship can be used as a steppingstone to describe issues regarding employability survivors are dealing with.

Recent findings
The acute survival stage begins at the point of diagnosis. Disclosure of diagnosis, and flexibility of both employers and (occupational) healthcare professionals are important factors in this stage. Extended survival starts when the survivor has completed the basic course of treatment. Survivors become aware that the old normality at work will be difficult to achieve. Problems like fear of recurrence, cognitive, and physical limitations might intensify during this stage and affect work ability. Permanent survival can be called long-term remission. Prospective studies on work-related outcomes and work-related interventions in this stage are rare.

Summary
It is important to improve our understanding of the seasons of survival and to explore concepts, such as employability, against the background of these seasons. This perspective may help both survivors and (occupational) healthcare professionals to develop better strategies for dealing with the difficult life event cancer represents in each specific stage.
Single-cell Map of Diverse Immune Phenotypes Driven by the Tumor Microenvironment
Authors: Azizi Elham , Carr Ambrose J. , Plitas George , Cornish Andrew E. , Konopacki Catherine , Prabhakaran Sandhya , Nainys Juozas , Wu Kenmin , Kiseliovas Vaidotas , Setty Manu , Choi Kristy , Fromme Rachel M. , Dao Phuong , McKenney Peter T. , Wasti Ruby C. , Kadaveru Krishna , Mazutis Linas , Rudensky Alexander Y. , Pe’er Dana 
Published: November 2017

SUMMARYKnowledge of immune cell phenotypes in the tumor microenvironment is essential for understanding mechanisms of cancer progression and immunotherapy response. We created an immune map of breast cancer using single-cell RNA-seq data from 45,000 immune cells from eight breast carcinomas, as well as matched normal breast tissue, blood, and lymph node. We developed a preprocessing pipeline, SEQC, and a Bayesian clustering and normalization method, Biscuit, to address computational challenges inherent to single-cell data. Despite significant similarity between normal and tumor tissue-resident immune cells, we observed continuous tumor-specific phenotypic expansions driven by environmental cues. Analysis of paired single-cell RNA and T cell receptor (TCR) sequencing data from 27,000 additional T cells revealed the combinatorial impact of TCR utilization on phenotypic diversity. Our results support a model of continuous activation in T cells and do not comport with the macrophage polarization model in cancer, with important implications for characterizing tumor-infiltrating immune cells.
A non-genetic meiotic repair program inferred from spore survival values in fission yeast wild isolates: a clue for an epigenetic ratchet-like model of ageing?
Authors: Marsellach Xavi 
Published: November 2017

1.AbstractWhat is the nature of the ageing process? What is the spore survival, that one would expect upon analysing a self-cross, in a wild fission yeast strain? Could this two research questions be, somehow, related? In this manuscript, I am describing some interesting observations obtained while studying fission yeast spore survival values upon genetic crosses. Early findings brought my attention into mainly studying self-crosses (intra-strain crosses in which any cell can be involved in by matting with a sibling cell). This study, yield some interesting findings. As a summary: 1) most fission yeast self-crosses do show low spore survival values; 2) clonally related strains show a high phenotypic variability in self-cross spore survival values; 3) differences in self-cross spore survival values can be detected when comparing zygotic and azygotic mattings; 4) self-cross spore survival values are highly affected by environmental factors, mainly producing a reduction in the spore survival values; 5) self-cross spore survival values are “recovered” when cells are subjected to several rounds of meiotic divisions; 6) signs of correlation between spore survival and vegetative cell survival (prior to the entry into meiosis) have been observed in this study. All those observations, among others, are discussed as part of an epigenetic variability that exist in fission yeast populations. A cyclical behaviour, of this epigenetic variability it is proposed, defining an underlying ratchet-like epigenetic mechanisms acting in all cells. In this manuscript, I propose that this mechanism, is, indeed, the main cause of the ageing process.
Ecological change points: The strength of density dependence and the loss of history
Authors: Ponciano José M. , Taper Mark L. , Dennis Brian 
Published: November 2017

AbstractChange points in the dynamics of animal abundances have extensively been recorded in historical time series records. Little attention has been paid to the theoretical dynamic consequences of such change-points. Here we propose a change-point model of stochastic population dynamics. This investigation embodies a shift of attention from the problem of detecting when a change will occur, to another non-trivial puzzle: using ecological theory to understand and predict the post-breakpoint behavior of the population dynamics. The proposed model and the explicit expressions derived here predict and quantify how density dependence modulates the influence of the pre-breakpoint parameters into the post-breakpoint dynamics. Time series transitioning from one stationary distribution to another contain information about where the process was before the change-point, where is it heading and how long it will take to transition, and here this information is explicitly stated. Importantly, our results provide a direct connection of the strength of density dependence with theoretical properties of dynamic systems, such as the concept of resilience. Finally, we illustrate how to harness such information through maximum likelihood estimation for state-space models, and test the model robustness to widely different forms of compensatory dynamics. The model can be used to estimate important quantities in the theory and practice of population recovery.
Re-arrangements in the cytoplasmic distribution of small RNAs following the maternal-to-zygotic transition inDrosophilaembryos
Authors: Cosacak Mehmet Ilyas , Yiğit Hatice , Akgül Bünyamin 
Published: November 2017

ABSTRACTSmall RNAs are known to regulate gene expression during early development. However, the dynamics of interaction between small RNAs and polysomes during this process is largely unknown. 0-1h and 7-8hDrosophilaembryos were fractionated on sucrose density gradients into four fractions based on A254reading (1) translationally inactive messengerribonucleoprotein (mRNP); (2) 60S; (3) monosome; and (4) polysome. Comparative analysis of deep-sequencing reads from fractionated and un-fractionated 0-1h and 8-h embryos revealed development-specific co-sedimentation pattern of small RNAs with the cellular translation machinery. Although most miRNAs did not have a specific preference for any state of the translational machinery, we detected fraction-specific enrichment of some miRNAs such as miR-1-3p, -184-39, 5-5p and 263-5p. More interestingly, we observed dysregulation of a subset of miRNAs in fractionated embryos despite no measurable difference in their amount in unfractionated embryos. Transposon-derived endosiRNAs are over-expressed in 7-8h embryos and are associated mainly with the mRNP fraction. However, transposon-derived piRNAs, which are more abundant in 0-1h embryos, co-sediment primarily with the polysome fractions. These results suggest that there appears to be a complex interplay among the small RNAs with respect to their polysome-cosedimention pattern during early development inDrosophila.
DDX3 is exploited by Arenaviruses to suppress type I interferons and favor their replication
Authors: Loureiro María Eugenia , Zorzetto-Fernandes Andre Luiz , Radoshitzky Sheli , Chi Xiaoli , Dallari Simone , Marooki Nuha , Lèger Psylvia , Foscaldi Sabrina , Sharma Sonia , López Nora , de la Torre Juan Carlos , Bavari Sina , Zúñiga Elina 
Published: November 2017

ABSTRACTSeveral arenaviruses cause hemorrhagic fever (HF) diseases that are associated with high morbidity and mortality in humans. Accordingly, HF arenaviruses have been listed as top-priority emerging diseases for which countermeasures are urgently needed. Because arenavirus nucleoprotein (NP) plays critical roles in both virus multiplication and immune-evasion, we used an unbiased proteomic approach to identify NP-interacting proteins in human cells. DDX3, a DEAD-box ATP-dependent-RNA-helicase, interacted with NP in both NP-transfected and virus-infected cells. Importantly, DDX3 deficiency compromised the propagation of both Old and New World arenaviruses, including the HF arenaviruses Lassa and Junin viruses. The DDX3 role in promoting arenavirus multiplication correlated with both a previously un-recognized DDX3 contribution to type I interferon suppression in arenavirus infected cells and a positive effect of DDX3 on viral RNA synthesis. Our results uncover novel mechanisms used by arenavirus to exploit the host machinery and subvert immunity, singling out DDX3 as a potential host target for developing new therapies against highly pathogenic arenaviruses.AUTHOR SUMMARYArenaviruses include severe clinical pathogens causing hemorrhagic fevers and have been recently incorporated by the World Health Organization in a list of critical emerging diseases for which additional research and identification of clinical targets is urgently required. A better understanding of how viral proteins interact with host cellular factors to favor arenavirus multiplication can illuminate novel pipelines on therapeutic strategies. Here we demonstrated that the ATP-dependent RNA helicase DDX3 interacted with the arenavirus nucleoprotein, which displays fundamental functions in different steps of the viral-cycle. Our work also revealed an unexpected new biology on the role that DDX3 might play during viral infections. In sharp contrast to previous studies showing DDX3 enhancement of IFN-I induction, we demonstrated that DDX3 suppressed IFN-I production at late time points after arenavirus infection, contributing to a DDX3 pro-viral effect. We also showed that early after infection, DDX3 pro-viral role was IFN-I independent and was mediated by DDX3 facilitation of viral RNA synthesis without affecting RNA translation. Altogether, our study established DDX3 as a critical host interacting partner of the arenavirus nucleoprotein and demonstrated two previously unrecognized DDX3-dependent strategies by which these deadly viruses exploit the host cellular machinery and suppress immunity.
Combining accurate tumour genome simulation with crowd-sourcing to benchmark somatic structural variant detection
Authors: Lee Anna Y. , Ewing Adam D. , Ellrott Kyle , Hu Yin , Houlahan Kathleen E. , Bare J.Christopher , G. Espiritu Shadrielle Melijah , Huang Vincent , Dang Kristen , Chong Zechen , Caloian Cristian , Yamaguchi Takafumi N. ,   ICGC-TCGA DREAM Somatic Mutation Calling Challenge Participants, Kellen Michael R. , Chen Ken , Norman Thea C. , Friend Stephen H. , Guinney Justin , Stolovitzky Gustavo , Haussler David , Margolin Adam A. , Stuart Joshua M. , Boutros Paul C. 
Published: November 2017

AbstractBackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries, however there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold-standards, extensive resource requirements and difficulties arising from the need to share personal genomic information.ResultsTo facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowd-sourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error-profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches.ConclusionsThe synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available athttps://github.com/adamewing/bamsurgeon.
Dose response relationships for gamma radiation induced chromosomal instability
Authors: Eidelman Y.A. , Slanina S.V. , Pyatenko V.S. , Khvostunov I.K. , Andreev S.G. 
Published: November 2017

ABSTRACTDifferent cell lines demonstrate various dose response for radiation-induced chromosomal instability (RICI). To clarify the origin of differences we analyzed own and published data on RICI for four cell lines, V79, TK6, WTK1 and CHO-K1 on the basis of the mechanistic RICI model. We conclude that observable dose-response shapes, both plateau-like and strong dose dependent behavior, may be jointly explained by the same model of RICI. Mechanistic modeling reveals that a variation of certain set of RICI parameters leads to strong modification of dose-response curve.
Antigen-induced but not innate memory CD8 T cells express NKG2D and are recruited to the lung parenchyma upon viral infection
Authors: Grau Morgan , Valsesia Séverine , Mafille Julien , Djebali Sophia , Tomkowiak Martine , Mathieu Anne-Laure , Laubreton Daphné , de Bernard Simon , Jouve Pierre-Emmanuel , Buffat Laurent , Walzer Thierry , Leverrier Yann , Marvel Jacqueline 
Published: November 2017

AbstractThe pool of memory-phenotype CD8 T cells is composed of antigen-induced (AI) and cytokine-induced innate (IN) cells. IN have been described as having similar properties to AI memory cells. However, we found that pathogen-induced AI memory cells can be distinguished from naturally-generated IN memory cells by surface expression of NKG2D. Using this marker, we described the increased functionalities of AI and IN memory CD8 T cells compared to naive cells, as shown by comprehensive analysis of cytokine secretion and gene expression. However, AI differed from IN memory CD8 T cells by their capacity to migrate to the lung parenchyma upon inflammation or infection, a process dependent on their expression of ITGA1/CD49a and ITGA4/CD49d integrins.
A global comparison of the nutritive values of forage plants grown in contrasting environments
Authors: Lee Mark A. 
Published: November 2017

AbstractForage plants are valuable because they maintain wild and domesticated herbivores, and sustain the delivery of meat, milk and other commodities. Forage plants contain different quantities of fibre, lignin, minerals and protein, and vary in the proportion of their tissue that can be digested by herbivores. These nutritive components are important determinants of consumer growth rates, reproductive success and behaviour. A dataset was compiled to quantify variation in forage plant nutritive values within- and between-plant species, and to assess variation between plant functional groups and bioclimatic zones. 1,255 geo-located records containing 3,774 measurements of nutritive values for 136 forage plant species grown in 30 countries were obtained from published articles. Spatial variability in forage nutritive values indicated that climate modified plant nutritive values. Forage plants grown in arid and equatorial regions generally contained less digestible material than those grown in temperate and tundra regions; containing more fibre and lignin, and less protein. These patterns may reveal why herbivore body sizes, digestion and migration strategies are different in warmer and drier regions. This dataset also revealed the capacity for variation in the nutrition provided by forage plants. The proportion of the plant tissue that was digestible ranged between species from 2-91%. The amount of fibre contained within plant material ranged by 23-90%, protein by 2-36%, lignin by 1-21% and minerals by 2-22%. Water contents also varied substantially; ranging from 3-89% of standing biomass. On average, grasses and tree foliage contained the most fibre, whilst herbaceous legumes contained the most protein and tree foliage contained the most lignin. However, there were individual species within each functional group that were highly nutritious. This dataset may be used to identify forage plant species with useful traits which can be cultivated to enhance livestock productivity and inform wild herbivore conservation strategies.
Binding of the integrated stress response inhibitor, ISRIB, reveals a regulatory site in the nucleotide exchange factor, elF2B
Authors: Zyryanova Alisa F. , Weis Félix , Faille Alexandre , Abo Alard Akeel , Crespillo-Casado Ana , Harding Heather P. , Allen Felicity , Parts Leopold , Fromont Christophe , Fischer Peter M. , Warren Alan J. , Ron David 
Published: November 2017

AbstractThe Integrated Stress Response (ISR) is a conserved eukaryotic translational and transcriptional program implicated in mammalian metabolism, memory and immunity. The ISR is mediated by stress-induced phosphorylation of translation initiation factor 2 (eIF2) that attenuates the guanine nucleotide exchange factor eIF2B. A chemical inhibitor of the ISR, ISRIB, a bis-O-arylglycolamide, reverses the attenuation of eIF2B by phosphorylated eIF2, protecting mice from neurodegeneration and traumatic brain injury. We report on a cryo-electron microscopy-based structure of ISRIB-bound human eIF2B revealing an ISRIB-binding pocket at the interface between the β and δ regulatory subunits. CRISPR/Cas9 mutagenesis of residues lining this pocket altered the hierarchical cellular response to ISRIB congenersin vivoand ISRIB-bindingin vitro, thus providing chemogenetic support for the functional relevance of ISRIB binding at a distance from known eIF2-eIF2B interaction sites. Our findings point to a hitherto unexpected allosteric site in the eIF2B decamer exploited by ISRIB to regulate translation.
Clusterdv, a simple density-based clustering method that is robust, general and automatic
Authors: Marques João C. , Orger Michael B. 
Published: November 2017

AbstractHow to partition a data set into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data varies widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, clusterdp, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. We propose an alternative approach, clusterdv, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide range of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental data sets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioral data.Author summarIt is common that natural phenomena produce groupings, or clusters, in data, that can reveal the underlying processes. However, the form of these clusters can vary arbitrarily, making it challenging to find a single algorithm that identifies their structure correctly, without prior knowledge of the number of groupings or their distribution. We describe a simple clustering algorithm that is fully automatic and is able to correctly identify the number and shape of groupings in data of many types. We expect this algorithm to be useful in finding unknown natural phenomena present in data from a wide range of scientific fields.
Scale-specific analysis of fMRI data on the irregular cortical surface
Authors: Chen Yi , Cichy Radoslaw Martin , Stannat Wilhelm , Haynes John-Dylan 
Published: November 2017

AbstractTo fully characterize the activity patterns on the cerebral cortex as measured with fMRI, the spatial scale of the patterns must be ascertained. Here we address this problem by constructing steerable bandpass filters on the discrete, irregular cortical mesh, using an improved Gaussian smoothing in combination with differential operators of directional derivatives. We demonstrate the utility of the algorithm in two ways. First, using modelling we show that our algorithm yields superior results in numerical precision and spatial uniformity of filter kernels compared to the most widely adopted approach for cortical smoothing. An important interim insight hereby was that the effective scales of information differ from the nominal filter sizes applied to extract them, and thus need to be calculated separately to compare different algorithms on par. Second, we applied the algorithm to an fMRI dataset to assess the scale and pattern form of cortical encoding of information about visual objects in the ventral visual pathway. We found that filtering by our method improved the detection of discriminant information about experimental conditions over previous methods, that the level of categorization (subordinate versus superordinate) of objects was differentially related to the spatial scale of fMRI patterns, and that the spatial scale at which information was encoded increased along the ventral visual pathway. In sum, our results indicate that the proposed algorithm is particularly suited to assess and detect scale-specific information encoding in cortex, and promises further insight into the topography of cortical encoding in the human brain.