bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systematic evaluation during early-phase ischemia predicts outcomes in middle cerebral artery occlusion mice
Authors: Xiao Xiang-Tian , Luo Chun , Yuan Yuan , Xiao Li , Qu Wen-Sheng 
Published: November 2020

Identifying outcome predictors for ischemic stroke is beneficial for choosing correct intervention protocols. Thus, it is necessary to systemically evaluate histological outcome-associated changes such as hemodynamics, behavior, and body weight during the early phase of ischemia. Here, 50 mice were subjected to 45-min middle cerebral artery occlusion (MCAO) using Longa’s method. Hemodynamic changes were monitored by Doppler laser probe, and behaviors were evaluated by scales while the tissues were visualized by staining. The results by correlation analysis demonstrated that with a probe located near the posterior boundary zone of MCA territory, the latency of anoxic depolarization, as well as the cerebral blood flow reduction during MCAO were confirmed to be predictors for the infarct volume on day 3 post-ischemia; histology showed that the risk of a space-occupying secondary hemorrhage was significantly correlated with the increase of infarct volume versus the traditional Bederson’s neurological deficit scale, a renewed combined behavioral scoring method performed nicely to reflect the severity of tissue lesions. Weight loss was a valuable metric for the enlargement of both infarct volume and secondary hemorrhage. Monitoring changes during early-phase ischemia may benefit the optimization of ischemia models and the discovery of potential intervention targets.
See Video Abstract, http:/links.lww.com/WNR/A601).
Coronary Artery Disease Risk of Familial Hypercholesterolemia Genetic Variants Independent of Historical Cholesterol Exposure
Authors: Clarke Shoa L. , Tcheandjieu Catherine , Hilliard Austin , Lee Kyung Min , Lynch Julie , Chang Kyong-Mi , Miller Donald ,   VA Million Veteran Program, Knowles Joshua W. , O’Donnell Christopher , Tsao Phil , Rader Daniel J. , Wilson Peter W. , Sun Yan V. , Gaziano Michael , Assimes Themistocles L. 
Published: November 2020

AbstractAimsFamilial hypercholesterolemia (FH) genetic variants confer risk for coronary artery disease (CAD) even after adjusting for low-density lipoprotein cholesterol (LDL-C) levels, using a single measurement. This study evaluated whether multiple historical measures of LDL-C observed in the electronic health record (EHR) can account for the risk associated with FH variants.Methods and ResultsWe analyzed 418,790 participants in the Million Veteran Program with EHR data spanning up to 15 years prior to and 7 years after enrollment, including ∼6.3 million LDL-C measurements. FH variants in LDLR, APOB, and PCSK9 were identified using a custom genotype array. We implemented a nested case-control design, using incidence density sampling to match etiologic exposure windows and measure CAD risk while adjusting for LDL-C exposure. In a cohort of 23,091 primarily prevalent cases and 230,910 matched controls, FH variants conferred increased risk for CAD (odds ratio: 1.53; 95% confidence interval: 1.24 to 1.89; p: 7.8×10−5). Adjusting for mean LDL-C exposure prior to the index date attenuated this risk more than adjusting for a single measurement, but significant risk remained (odds ratio: 1.33; 95% confidence interval: 1.08 to 1.64; p = 8.4×10−3). The pattern was also apparent in stratified analyses by sex and ancestry, and we found evidence of an interaction between sex and FH carrier status.ConclusionThe risk associated with FH variants cannot be fully captured by the LDL-C data available in the EHR, even when considering multiple LDL-C measurements spanning more than a decade.
Impact of oseltamivir treatment on influenza A and B dynamics in human volunteers
Authors: Hooker Kyla L. , Ganusov Vitaly V. 
Published: November 2020

AbstractInfluenza viruses infect millions of humans every year causing an estimated 400,000 deaths globally. Due to continuous virus evolution current vaccines provide only limited protection against the flu. Several antiviral drugs are available to treat influenza infection, and one of the most most commonly used drugs is oseltamivir (Tamiflu). While the mechanism of action of oseltamivir as a neuraminidase inhibitor is well understood, the impact of oseltamivir on influenza virus dynamics in humans has been controversial. Many clinical trials with oseltamivir have been done by pharmaceutical companies such as Roche but the results of these trials until recently have been reported as summary reports or papers. Typically, such reports included median virus shedding curves for placebo and drug-treated influenza virus infected volunteers often indicating high efficacy of the early treatment. However, median shedding curves may be not accurately representing drug impact in individual volunteers. Importantly, due to public pressure clinical trials data testing oseltamivir efficacy has been recently released in the form of redacted PDF documents. We digitized and re-analyzed experimental data on influenza virus shedding in human volunteers from three previously published trials: on influenza A (1 trial) or B viruses (2 trials). Given that not all volunteers exposed to influenza viruses actually start virus shedding we found that impact of oseltamivir on the virus shedding dynamics was dependent on i) selection of volunteers that were infected with the virus, and ii) the detection limit in the measurement assay; both of these details were not well articulated in the published studies. By assuming that any viral measurement is above the limit of detection we could match previously published data on median influenza A virus (flu A study) shedding but not on influenza B virus shedding (flu B study B) in human volunteers. Additional analyses confirmed that oseltamivir had an impact on the duration of shedding and overall shedding (defined as area under the curve) but this result was varied by the trial. Interestingly, treatment had no impact on the rates at which shedding increased or declined with time in individual volunteers. Additional analyses showed that oseltamivir impacted the kinetics of the start and end of viral shedding and in about 20-40% of volunteers treatment had no impact on viral shedding duration. Our results suggest an unusual impact of oseltamivir on influenza viruses shedding kinetics and caution about the use of published median data or data from a few individuals for inferences. Furthermore, we call for the need to publish raw data from critical clinical trials that can be then independently analyzed.
Local Ancestry Prediction withPyLAE
Authors: Smetanin Alexander , Moshkov Nikita , Tatarinova Tatiana V. 
Published: November 2020

AbstractSummaryWe developed PyLAE - a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimation of many parameters, it can process thousands of genomes within a day. Computational efficiency, straightforward presentation of results, and an ease of installation makesPyLAEa useful tool to study admixed populations.Availability and implementationThe source code and installation manual are available athttps://github.com/smetam/pylae.
SCNIC: Sparse Correlation Network Investigation for Compositional Data
Authors: Shaffer Michael , Thurimella Kumar , Sterrett John D. , Lozupone Catherine A. 
Published: November 2020

ABSTRACTBackgroundMicrobiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves.ResultsTo address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them.ConclusionsSCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.
Fast Alignment-Free Similarity Estimation By Tensor Sketching
Authors: Joudaki Amir , Rätsch Gunnar , Kahles André 
Published: November 2020

AbstractThe sharp increase in next-generation sequencing technologies’ capacity has created a demand for algorithms capable of quickly searching a large corpus of biological sequences. The complexity of biological variability and the magnitude of existing data sets have impeded finding algorithms with guaranteed accuracy that efficiently run in practice. Our main contribution is the Tensor Sketch method that efficiently and accurately estimates edit distances. In our experiments, Tensor Sketch had 0.956 Spearman’s rank correlation with the exact edit distance, improving its best competitor Ordered MinHash by 23%, while running almost 5 times faster. Finally, all sketches can be updated dynamically if the input is a sequence stream, making it appealing for large-scale applications where data cannot fit into memory.Conceptually, our approach has three steps: 1) represent sequences as tensors over their sub-sequences, 2) apply tensor sketching that preserves tensor inner products, 3) implicitly compute the sketch. The sub-sequences, which are not necessarily contiguous pieces of the sequence, allow us to outperformk-mer-based methods, such as min-hash sketching over a set ofk-mers. Typically, the number of sub-sequences grows exponentially with the sub-sequence length, introducing both memory and time overheads. We directly address this problem in steps 2 and 3 of our method. While the sketching of rank-1 or super-symmetric tensors is known to admit efficient sketching, the sub-sequence tensor does not satisfy either of these properties. Hence, we propose a new sketching scheme that completely avoids the need for constructing the ambient space.Our tensor-sketching technique’s main advantages are three-fold: 1) Tensor Sketch has higher accuracy than any of the other assessed sketching methods used in practice. 2) All sketches can be computed in a streaming fashion, leading to significant time and memory savings when there is overlap between input sequences. 3) It is straightforward to extend tensor sketching to different settings leading to efficient methods for related sequence analysis tasks. We view tensor sketching as a framework to tackle a wide range of relevant bioinformatics problems, and we are confident that it can bring significant improvements for applications based on edit distance estimation.
Sharing the burden? Earthworms and woodlice show seasonal complementarity in peak abundances in soil in an oak-beech temperate woodland
Authors: Carpenter Daniel , Sherlock Emma , Inward Kelly , Carroway Kerry , Lidgett Angela , Eggleton Paul 
Published: November 2020

AbstractComplementarity between functional analogues can confer resistance and resilience on ecosystems in the face of environmental change. High biodiversity can lead to increased ecosystem functionality through complementary effects. Earthworms, woodlice and millipedes can have high densities in leaf litter and soils, but little is known about their seasonal patterns. The two groups play important roles in the breakdown and incorporation of organic matter into soils. Differences in peak abundance could affect the rates of litter break down and incorporation in different seasons. We sampled earthworms, woodlice and millipedes from leaf litter soil every month for ten years in a New Forest woodland. We used non-parametric regression to explore monthly and yearly variation in the abundance of decomposer organisms and soil temperature and moisture. Earthworms have a distinct seasonal peak in density different from woodlice and millipedes. Earthworm peak density is in the winter and spring and is correlated with greatest soil moisture. Woodlice (and millipede) have their peak density is in the summer and is correlated with the highest soil temperatures. This means that earthworms, woodlice and millipedes have complementary peaks in abundance. These two groups have similar functional roles in litter decomposition and these data imply ecological complementarity in this important ecological process. This effect is likely to be widespread in lowland woodland in the UK and Europe, with only extreme temperatures and low pH limiting the distribution. Increased summer drought as a result of climate change may lead to changes in the relative abundance of these three groups and in particular local extinctions of earthworms which will in turn affect litter decomposition.
Facilitated transition in HIV drug trial closure: a conceptual model for HIV post-trial care
Authors: Nalubega Sylivia , Cox Karen , Mugerwa Henry , Evans Catrin 
Published: November 2020

AbstractWithin the HIV clinical trial field, there are gaps in existing ethical regulations in relation to post-trial care. There is need to develop post-trial care guidelines that are flexible and sensitive to local contexts and to the specific needs of different groups of participants, particularly in low income contexts. Evidence regarding HIV trial closure and post-trial care is required to underpin the development of appropriate policies in this area. This article reports research from Uganda that develops a new model of ‘Facilitated Transition’ to conceptualize the transition process of HIV positive trial participants from ‘research’ to ‘usual care’ health facilities after trial conclusion. This was a qualitative grounded theory study that included 21 adult HIV positive post-trial participants and 22 research staff, undertaken between October 2014 and August 2015. The findings showed that trial closure is a complex process for HIV positive participants which includes three phases: the pre-closure, trial-closure, and post-trial phases. The model highlights a range of different needs of research participants and suggests specific and person-centred interventions that can be delivered at different phases with the aim of improving health outcomes and experiences for trial participants in low income settings during trial closure. Further research needs to be done to verify the model in other contexts and for other conditions.
Differentially expressed circular RNAs in peripheral blood mononuclear cells of PD patients
Authors: Ravanidis Stylianos , Bougea Anastasia , Karampatsi Dimitra , Papagiannakis Nikolaos , Maniati Matina , Stefanis Leonidas , Doxakis Epaminondas 
Published: November 2020

ABSTRACTBackgroundNew noninvasive and affordable molecular approaches that will complement current practices and increase the accuracy of PD diagnosis are urgently needed. CircRNAs are highly stable non-coding RNAs that accumulate with aging in neurons and are increasingly shown to regulate all aspects of neuronal development and function.ObjectivesThe aims of the present study were to identify differentially expressed circRNAs in PBMCs of idiopathic PD patients and explore the competing endogenous RNA networks affected.MethodsEighty-seven circRNAs were initially selected based on relatively high gene expression in the human brain. Over half of these were readily detectable in PBMCs using RT-qPCR. Comparative expression analysis was then performed in PBMCs from sixty controls and sixty idiopathic subjects with PD.ResultsSix circRNAs derived from MAPK9, HOMER1, SLAIN1, DOP1B, REPS1, and PSEN1 transcripts were significantly downregulated in PD patients. The classifier that best distinguished PD consisted of four circRNAs with an AUC of 0.84. CLIP-Seq data revealed that the RNA binding proteins bound by most of the deregulated circRNAs include the neurodegeneration-associated FUS, TDP43, FMR1 and ATXN2. MicroRNAs predicted to be sequestered by most deregulated circRNAs had the GOslim categories ‘Protein modification’, ‘Transcription factor activity’ and ‘Cytoskeletal protein binding’ mostly enriched.ConclusionsThis is the first study that identifies circRNAs deregulated in the peripheral blood of PD patients. They may serve as diagnostic biomarkers and since they are highly expressed in the brain and are derived from genes with essential brain functions, they may also hint on the PD pathways affected.
Measuring diversity from space: a global view of the free and open source rasterdiv R package under a coding perspective
Authors: Thouverai Elisa , Marcantonio Matteo , Bacaro Giovanni , Da Re Daniele , Iannacito Martina , Ricotta Carlo , Tattoni Clara , Vicario Saverio , Rocchini Duccio 
Published: November 2020

AbstractThe variation of species diversity over space and time has been widely recognised as a key challenge in ecology. However, measuring species diversity over large areas might be difficult for logistic reasons related to both time and cost savings for sampling, as well as accessibility of remote ecosystems. In this paper, we present a newRpackage -rasterdiv- to calculate diversity indices based on remotely sensed data, by discussing the theory beyond the developed algorithms. Obviously, measures of diversity from space should not be viewed as a replacement of in-situ data on biological diversity, but they are rather complementary to existing data and approaches. In practice, they integrate available information of Earth surface properties, including aspects of functional (structural, biophysical and bio-chemical), taxonomic, phylogenetic and genetic diversity. Making use of therasterdivpackage can result useful in making multiple calculations based on reproducible open source algorithms, robustly rooted in Information Theory.
Active elimination of intestinal cells drives oncogenic growth in organoids
Authors: Garcia Ana Krotenberg , Fumagalli Arianna , Le Huy Quang , Sansom Owen J. , van Rheenen Jacco , Suijkerbuijk Saskia J.E. 
Published: November 2020

AbstractCompetitive cell-interactions play a crucial role in quality control during development and homeostasis. Here we show that cancer cells use such interactions to actively eliminate wild-type intestine cells in enteroid monolayers and organoids. This apoptosis-dependent process boosts proliferation of intestinal cancer cells. The remaining wild-type population activates markers of primitive epithelia and transits to a fetal-like state. Prevention of this cell fate transition avoids elimination of wild-type cells and, importantly, limits the proliferation of cancer cells. JNK signalling is activated in competing cells and is required for cell fate change and elimination of wild-type cells. Thus, cell competition drives growth of cancer cells by active out-competition of wild-type cells through forced cell death and cell fate change in a JNK dependent manner.
The white matter is a pro-differentiative microenvironment for glioblastoma
Authors: Brooks Lucy J. , Clements Melanie P. , Burden Jemima J. , Kocher Daniela , Richards Luca , Devesa Sara Castro , Woodberry Megan , Ellis Michael , Zakka Leila , Jaunmuktane Zane , Brandner Sebastian , Morrison Gillian , Pollard Steven M. , Dirks Peter B. , Marguerat Samuel , Parrinello Simona 
Published: November 2020

SummaryGlioblastomas are hierarchically organised tumours driven by glioma stem cells that retain partial differentiation potential. Glioma stem cells are maintained in specialised microenvironments, but how they undergo lineage progression outside of these niches remains unclear. Here we identify the white matter as a differentiative niche for glioblastomas with oligodendrocyte lineage competency. Tumour cells in contact with white matter acquire pre-oligodendrocyte-like fate, resulting in decreased proliferation and invasion. Differentiation is a response to white matter injury, which is caused by tumour infiltration itself in a tumoursuppressive feedback loop. Mechanistically, tumour cell differentiation is driven by selective white matter upregulation of SOX10, a master regulator of normal oligodendrogenesis. SOX10 overexpression or treatment with myelination-promoting agents that upregulate endogenous SOX10, mimic this response, leading to white matter-independent pre-oligodendrocyte-like differentiation and tumour suppressionin vivo. Thus, glioblastoma recapitulates an injury response and exploiting this latent programme may offer treatment opportunities for a subset of patients.
Capturing in-field root system dynamics with the RootTracker
Authors: Aguilar Jeffrey J. , Moore Matt , Johnson Logan , Greenhut Rachel F. , Rogers Eric , Walker Drew , O’Neil Fletcher , Edwards Jake L. , Thystrup Jake , Farrow Sam , Windle Jesse B. , Benfey Philip N. 
Published: November 2020

AbstractOptimizing root system architecture offers a promising approach to developing stress tolerant cultivars in the face of climate change, as root systems are critical for water and nutrient uptake as well as mechanical stability. However, breeding for optimal root system architecture has been hindered by the difficulty in measuring root growth in the field. Here, we describe a technology, the RootTracker (RT), which employs capacitance touch sensors to monitor in-field root growth over time. Configured in a cylindrical shutter-like fashion around a planted seed, 264 electrodes are individually charged multiple times over the course of an experiment. Signature changes in the measured capacitance and resistance readings indicate when a root has touched or grown close to an electrode. Using the RootTracker, we have measured root system dynamics of commercial maize hybrids growing in both typical Midwest field conditions and under different irrigation regimes. We observed rapid responses of root growth to water deficits and found evidence for a “priming response” in which an early water deficit causes more and deeper roots to grow at later time periods. There was genotypic variation among hybrid maize lines in their root growth in response to drought, indicating a potential to breed for root systems adapted for different environments.