bluuebunny/crossref_metadata_2025_split huggingface dataset:
Habitat loss causes long transients in small trophic chains
Authors: Vidiella Blai , Fontich Ernest , Valverde Sergi , Sardanyés Josep 
Published: May 2020

AbstractTransients in ecology are extremely important since they determine how equilibria are approached. The debate on the dynamic stability of ecosystems has been largely focused on equilibrium states. However, since ecosystems are constantly changing due to climate conditions or to perturbations such as the climate crisis or anthropogenic actions (habitat destruction, deforestation, or defaunation), it is important to study how dynamics can proceed till equilibria. In this contribution we investigate dynamics and transient phenomena in small food chains using mathematical models. We are interested in the impact of habitat loss in ecosystems with vegetation undergoing facilitation. We provide a thorough dynamical study of a small food chain system given by three trophic levels: vegetation, herbivores, and predators. The dynamics of the vegetation alone suffers a saddle-node bifurcation, causing extremely long transients. The addition of a herbivore introduces a remarkable number of new phenomena. Specifically, we show that, apart from the saddle node involving the extinction of the full system, a transcritical and a supercritical Hopf-Andronov bifurcation allow for the coexistence of vegetation and herbivores via non-oscillatory and oscillatory dynamics, respectively. Furthermore, a global transition given by a heteroclinic bifurcation is also shown to cause a full extinction. The addition of a predator species to the previous systems introduces further complexity and dynamics, also allowing for the coupling of different transient phenomena such as ghost transients and transient oscillations after the heteroclinic bifurcation. Our study shows how the increase of ecological complexity via addition of new trophic levels and their associated nonlinear interactions may modify dynamics, bifurcations, and transient phenomena.
The scientific basis for currently proposed management options for Hector’s and Maui dolphins: a critique
Authors: Slooten Elisabeth , Dawson Stephen Michael 
Published: May 2020

ABSTRACTNew Zealand’s Ministry for Primary Industries (MPI) developed a risk analysis for Hector’s and Maui dolphins, in order to inform protection options being considered by the Ministers of Fisheries and Conservation. Unfortunately, MPI’s risk analysis combines several estimates that are biased, and the biases consistently act together to underestimate the level of bycatch and overestimate the species’ ability to sustain impacts. In essence, the approach uses abundance estimates that are likely biased high, multiplies them by a reproductive rate that has been arbitrarily raised, multiplied by an assumed figure for calf survival, to reach a number of dolphins that would be added each year if the population were to remain stable. From this number, they subtract their estimates of bycatch, which are almost certainly biased low. The remaining number of dolphins is apportioned a cause of death according to autopsy data from 55 Hector’s and Maui dolphins found dead on beaches. This is then compared to estimates of what level of takes would be sustainable, calculated using a formula that is not well understood and less conservative than the international standard (PBR, developed by the US National Marine Fisheries Service). This is a poor basis for rational management of an endangered, endemic marine mammal. A key problem with the MPI approach is that its definition of “risk” does not relate to the risk of population decline or extinction, and is inconsistent with the modern understanding of the behaviour of meta-populations. The approach defines risk as the likelihood of capture, which is apportioned to different areas according to fishing effort and the habitat model’s outputs for dolphin distribution. The protection options are therefore targeted where high densities of dolphins and high fishing effort coincide. Large populations are allocated the highest level of protection, while small populations remain poorly protected. This approach is likely to increase the risk of local extinctions, contractions of dolphin distribution, population fragmentation, loss of genetic variability and result in increased risk to the species as a whole. Many of these points were made by an International Expert Panel in 2018. MPI have failed to provide a list of recommendations from the Expert Panel Report with their responses (if any) to those recommendations. This standard step in scientific practice, following peer review (e.g. response to reviewers’ comments) has not been followed.
Let it bud: an ultrastructural study ofCryptococcus neoformanssurface during budding events
Authors: Araújo Glauber R. de S. , Alcantara Carolina de L. , Rodrigues Noêmia , de Souza Wanderley , Pontes Bruno , Frases Susana 
Published: May 2020

AbstractCryptococcus neoformansis a fungal pathogen that causes life-threatening infections in immunocompromised individuals. It is surrounded by three concentric structures that separate the cell from the extracellular space: the plasma membrane, the cell wall and the polysaccharide capsule. Although several studies have revealed the chemical composition of these structures, little is known about their ultrastructural organization and remodeling duringC. neoformansbudding event. Here, by combining the state-of-the-art in light and electron microscopy techniques we describe the morphological remodeling that occurs synergistically among the capsule, cell wall and plasma membrane during budding inC. neoformans. Our results show that the cell wall deforms to generate a specialized budding region at one of the cell’s poles. This region subsequently begins to break into layers that are slightly separated from each other and with thick tips. We also observe a reduction in density of the capsular polysaccharide around these specialized regions. Daughter cells present a distinct spatial organization, with polysaccharide fibers aligned in the direction of budding. In addition, to control the continuous openings between mother and daughter cells, the latter developed a strategy to shield themselves by forming multilamellar membrane structures in conjunction with their capsules. Together, our findings provide compelling ultrastructural evidence for a dynamicC. neoformanssurface remodeling during budding and may have important implications for future studies exploring these remodeled specialized regions as drug-targets against cryptococcosis.
A Novel Xenonucleic Acid Mediated Molecular Clamping Technology for Early Colorectal Cancer Screening
Authors: Sun Qing , Pastor Larry , Du Jinwei , Powell Michael J. , Zhang Aiguo , Bodmer Walter , Wu Jianzhong , Zheng Shu , Sha Michael Y. 
Published: May 2020

ABSTRACTBackgroundColorectal cancer (CRC) is one of the leading causes of cancer-related death. Early detection is critical to reduce CRC morbidity and mortality. In order to meet this need, we developed a molecular clamping assay called the ColoScape ™ for early colorectal cancer diagnostics.MethodsNineteen mutations in four genes APC, KRAS, BRAF and CTNNB1 associated with early events in CRC pathogenesis are targeted in the ColoScape™ assay. Xenonucleic Acid (XNA) mediated qPCR clamping technology was applied to minimize the wild-type background amplification in order to improve assay sensitivity of CRC mutation detection. The assay analytical performance was verified and validated, cfDNA and FFPE CRC patient samples were evaluated, and a ROC cure was applied to evaluate its performance.ResultsThe data showed that the assay analytical sensitivity is 0.5% Variant Allele Frequency, corresponding to ~7-8 copies of mutant DNA with 5ng total DNA input per test. This assay is highly reproducible with intra-assay CV <3% and inter-assay <5%. We have investigated 380 clinical samples including plasma cfDNA and FFPE samples from patients with precancerous and different stages of CRC. The preliminary assay clinical specificity and sensitivity for CRC cfDNA were 100% (95% CI, 80.3-97.5%) and 92.2% (95% CI, 94.7-100%) respectively with AUC being about 0.96; and 96% (95% CI, 77.6-99.7%) specificity and 92% (95% CI, 86.1-95.6%) sensitivity with AUC 0.94 for CRC FFPE; and 95% specificity (95% CI, 82.5%-99.1%) and 62.5% sensitivity (95% CI, 35.8%-83.7%) with AUC 0.79 for precancerous lesions cfDNA.ConclusionsXNA mediated molecular clamping assay is a rapid, precise, and sensitive assay for the detection of precancerous lesions cfDNA and CRC cfDNA or FFPE samples.
Pair-wise Interactions in Gene Expression Determine a Hierarchical Transcription Profile of the Human Brain
Authors: Hua Jiaojiao , Yang Zhengyi , Jiang Tianzi , Yu Shan 
Published: May 2020

AbstractOrchestrated expressions of tens of thousands of genes give rise to the complexity of the brain. However, it is unclear what is the structure governing these myriads of gene-gene interactions. By analyzing the transcription data obtained from more than 3000 sites in human brains, we found that pair-wise interactions between genes are sufficient to accurately predict both the transcription pattern of the whole genome for individual brain areas and the transcription profile of the entire brain, suggesting a surprisingly simple interaction structure of the transcriptome itself. We further revealed that the strength of gene-gene interaction observed empirically allows the nearly maximal number of transcriptionally similar clusters of areas to form, which may account for the functional and structural richness of the brain.One Sentence SummaryPairwise interactions among genes shape the overall structure of human brain transcriptome.
Robust scan synchronized force-fluorescence imaging
Authors: Schmidt Patrick , Lajoie John , Sivasankar Sanjeevi 
Published: May 2020

AbstractSimultaneous atomic force microscope (AFM) and sample scanning confocal fluorescence microscope measurements are widely used to obtain mechanistic and structural insights into protein dynamics in live cells. However, the absence of a robust technique to synchronously scan both AFM and confocal microscope piezo stages makes it difficult to visualize force-induced changes in fluorescent protein distribution in cells. To address this challenge, we have built an integrated AFM-confocal fluorescence microscope platform that implements a synchronous scanning method which eliminates image artifacts from piezo motion ramping, produces intuitive, accurate pixel binning and enables the collection of a scanned image of a sample while applying force to the sample. As proof of principle, we use this instrument to monitor the redistribution of fluorescent E-cadherin, an essential transmembrane protein, in live cells, upon application of mechanical force.
Accurate prediction of cis-regulatory modules reveals a prevalent regulatory genome of humans
Authors: Ni Pengyu , Su Zhengchang 
Published: May 2020

AbstractAnnotating all cis-regulatory modules (CRMs) and transcription factor (TF) binding sites(TFBSs) in genomes remains challenging. We tackled the task by integrating putative TFBSs motifs found in available 6,092 datasets covering 77.47% of the human genome. This approach enabled us to partition the covered genome regions into a CRM candidate (CRMC) set (56.84%) and a non-CRMC set (43.16%). Intriguingly, like known enhancers, the predicted 1,404,973 CRMCs are under strong evolutionary constraints, suggesting that they might be cis-regulator. In contrast, the non-CRMCs are largely selectively neutral, suggesting that they might not be cis-regulatory. Our method substantially outperforms three state-of-the-art methods (GeneHancers, EnhancerAtlas and ENCODE phase 3) for recalling VISTA enhancers and ClinVar variants, as well as by measurements of evolutionary constraints. We estimated that the human genome might encode about 1.46 million CRMs and 67 million TFBSs, comprising about 55% and 22% of the genome, respectively; for both of which, we predicted 80%. Therefore, the cis-regulatory genome appears to be more prevalent than originally thought.
Guiding and interpreting brain network classification with transcriptional data
Authors: Li Mengbo , Kessler Daniel , Arroyo Jesús , Freytag Saskia , Bahlo Melanie , Levina Elizaveta , Yang Jean 
Published: May 2020

AbstractThe investigation of brain networks has yielded many insights that have helped to characterise many neurological and psychiatric disorders. In particular, network classification of functional magnetic resonance imaging (fMRI) data is an important tool for the identification of prognostic and diagnostic biomarkers of brain connectivity disorders such as schizophrenia and depression. However, existing generic network classification methods provide no direct information on the underlying molecular mechanisms of the selected functional connectivity features when applied to fMRI data. To address this, we propose a novel fMRI network classification method that incor-porates brain transcriptional data using a user-specified gene set collection (GSC) to construct feature groups for use in classification of brain connectivity data. The use of GSCs are an opportunity to incorporate knowledge of potential molecular mechanisms which may be associated with a disease. The inclusion of transcriptional data yields improved prediction accuracy on publicly available schizophrenia fMRI data for several of the GSCs we consider. We also introduce a post-hoc interpretation framework to provide transcriptional-data-guided biological interpretations for discriminative functional connectivity features identified by existing fMRI network classification methods.
HB-PLS: An algorithm for identifying biological process or pathway regulators by integrating Huber loss and Berhu penalty with partial least squares regression
Authors: Deng Wenping , Zhang Kui , Wei Zhigang , Wang Lihu , He Cheng , Liu Sanzhen , Wei Hairong 
Published: May 2020

AbstractGene expression data features high dimensionality, multicollinearity, and the existence of outlier or non-Gaussian distribution noise, which make the identification of true regulatory genes controlling a biological process or pathway difficult. In this study, we embedded the Huber-Berhu (HB) regression into the partial least squares (PLS) framework and created a new method called HB-PLS for predicting biological process or pathway regulators through construction of regulatory networks. PLS is an alternative to ordinary least squares (OLS) for handling multicollinearity in high dimensional data. The Huber loss is more robust to outliers than square loss, and the Berhu penalty can obtain a better balance between theℓ2penalty and theℓ1penalty. HB-PLS therefore inherits the advantages of the Huber loss, the Berhu penalty, and PLS. To solve the Huber-Berhu regression, a fast proximal gradient descent method was developed; the HB regression runs much faster than CVX, a Matlab-based modeling system for convex optimization. Implementation of HB-PLS to real transcriptomic data fromArabidopsisand maize led to the identification of many pathway regulators that had previously been identified experimentally. In terms of its efficiency in identifying positive biological process or pathway regulators, HB-PLS is comparable to sparse partial least squares (SPLS), a very efficient method developed for variable selection and dimension reduction in handling multicollinearity in high dimensional genomic data. However, HB-PLS is able to identify some distinct regulators, and in one case identify more positive regulators at the top of output list, which can reduce the burden for experimental test of the identified candidate targets. Our study suggests that HB-PLS is instrumental for identifying biological process and pathway genes.
A cell competition-based drug screen identifies a novel compound that induces dual c-Myc depletion and p53 activation
Authors: Tadele Dagim Shiferaw , Robertson Joseph , Crispin Richard , Herrera Maria C. , Chlubnova Marketa , Piechaczyk Laure , Ayuda-Durán Pilar , Singh Sachin Kumar , Gedde-Dahl Tobias , Fløisand Yngvar , Skavland Jørn , Wesche Jørgen , Gjertsen Bjørn-Tore , Enserink Jorrit M. 
Published: May 2020

AbstractBCR-Abl is a driver oncogene that causes chronic myeloid leukemia and a subset of acute lymphoid leukemias. Although tyrosine kinase inhibitors provide an effective treatment for these diseases, they generally do not kill leukemic stem cells. Leukemic stem cells are cancer-initiating cells that compete with normal hematopoietic stem cells for the bone marrow niche. Using BCR-Abl as a model oncogene, we performed a drug screen based on competition between isogenic untransformed cells and BCR-Abl-transformed cells, and identified several compounds that selectively target BCR-Abl-transformed cells. Systems-level analysis of one of these novel compounds, DJ34, revealed that it induced depletion of c-Myc and activation of p53. c-Myc depletion occurred in a wide range of tumor types, including leukemia, lymphoma, lung, glioblastoma and breast cancer. Further analyses revealed that DJ34 interferes with c-Myc synthesis at the level of transcription, and we provide data showing that DJ34 is a DNA intercalator and topoisomerase II inhibitor. Physiologically, DJ34 induced apoptosis, cell cycle arrest and cell differentiation, and primary leukemic stem cells were particularly sensitive to DJ34. Taken together, we have identified a novel compound that dually targets c-Myc and p53 in a wide variety of cancers, and with particularly strong activity against leukemic stem cells.
Plasma metabolomics of presymptomaticPSEN1-H163Y mutation carriers: A pilot study
Authors: Natarajan Karthick , Ullgren Abbe , Khoshnood Behzad , Johansson Charlotte , Laffita-Mesa José Miguel , Pannee Josef , Zetterberg Henrik , Blennow Kaj , Graff Caroline 
Published: May 2020

AbstractBackground and ObjectivePSEN1-H163Y carriers, at the presymptomatic stage, have reduced18FDG-PET binding in the cerebrum of the brain [1]. This could imply dysfunctional energy metabolism in the brain. In this study, plasma of presymptomaticPSEN1mutation carriers was analyzed to understand associated metabolic changes.MethodsWe analyzed plasma from non-carriers (NC, n=8) and presymptomaticPSEN1-H163Y mutation carriers (MC, n=6) via untargeted metabolomics using gas and liquid chromatography coupled with mass spectrometry, which identified 1199 metabolites. All the metabolites were compared between MC and NC using univariate analysis, as well as correlated with the ratio of Aβ1-42/Aβ1-40, using Spearman’s correlation. Altered metabolites were subjected to Ingenuity Pathways Analysis (IPA).ResultsWhen comparing between presymptomatic MC and NC, the levels of 116 different metabolites were altered. Out of 116, only 23 were annotated metabolites, which include amino acids, fatty acyls, bile acids, hexoses, purine nucleosides, carboxylic acids, and glycerophosphatidylcholine species. 1-docosapentaenoyl-GPC, glucose and uric acid were correlated with the ratio of plasma Aβ1-42/Aβ1-40(p < 0.05).ConclusionThis study finds dysregulated metabolite classes, which are changed before the disease onset. Also, it provides an opportunity to compare with sporadic Alzheimer’s Disease. Observed findings in this study need to be validated in a larger and independent Familial Alzheimer’s Disease (FAD) cohort.Graphical abstract
Mechanistic modeling of the SARS-CoV-2 and immune system interplay unravels design principles for diverse clinicopathological outcomes
Authors: Sahoo Sarthak , Hari Kishore , Jhunjhunwala Siddharth , Jolly Mohit Kumar 
Published: May 2020

AbstractThe disease caused by SARS-CoV-2 is a global pandemic that threatens to bring long-term changes worldwide. Approximately 80% of infected patients are asymptomatic or have mild symptoms such as fever or cough, while rest of the patients have varying degrees of severity of symptoms, with 3-4% mortality rate. Severe symptoms such as pneumonia and Acute Respiratory Distress Syndrome can be caused by tissue damage mostly due to aggravated and unresolved innate and adaptive immune response, often resulting from a cytokine storm. However, the mechanistic underpinnings of such responses remain elusive, with an incomplete understanding of how an intricate interplay among infected cells and cells of innate and adaptive immune system can lead to such diverse clinicopathological outcomes. Here, we use a dynamical systems approach to dissect the emergent nonlinear intra-host dynamics among virally infected cells, the immune response to it and the consequent immunopathology. By mechanistic analysis of cell-cell interactions, we have identified key parameters affecting the diverse clinical phenotypes associated with COVID-19. This minimalistic yet rigorous model can explain the various phenotypes observed across the clinical spectrum of COVID-19, various co-morbidity risk factors such as age and obesity, and the effect of antiviral drugs on different phenotypes. It also reveals how a fine-tuned balance of infected cell killing and resolution of inflammation can lead to infection clearance, while disruptions can drive different severe phenotypes. These results will help further the case of rational selection of drug combinations that can effectively balance viral clearance and minimize tissue damage simultaneously.Significance StatementThe SARS-CoV-2 pandemic has already infected millions of people, and thousands of lives have been lost to it. The pandemic has already tested the limits of our public healthcare systems with a wide spectrum of clinicopathological symptoms and outcomes. The mechanistic underpinnings of the resultant immunopathology caused by the viral infection still remains to be elucidated. Here we propose a minimalistic but rigorous description of the interactions of the virus infected cells and the core components of the immune system that can potentially explain such diversity in the observed clinical outcomes. Our proposed framework could enable a platform to determine the efficacy of various treatment combinations and can contributes a conceptual understanding of dynamics of disease pathogenesis in SARS-CoV-2 infections.
Genome-wide identification and characterization ofSolanum tuberosum BiPgenes reveals the role of the promoter architecture in BiP gene diversity
Authors: Herath Venura , Gayral Mathieu , Adhikari Nirakar , Miller Rita , Verchot Jeanmarie 
Published: May 2020

AbstractThe endoplasmic reticulum (ER) immunoglobulin binding proteins (BiPs) are molecular chaperones involved in normal protein maturation and refolding malformed proteins through the unfolded protein response (UPR). Plants BiPs belong to a multi-gene family contributing to development, immunity, and responses to environmental stresses. This study identified threeBiPhomologues in theSolanum tuberosum(potato) genome using phylogenetic, amino acid sequence, 3-D protein modeling and gene structure analysis. These analyses revealed thatStBiP1andStBiP2grouped withAtBiP2, whereasStBiP3grouped withAtBiP3. While the protein sequences and folding structures are highly similar, theseStBiPsare distinguishable by their expression patterns in different tissues and in response to environmental stressors such as treatment with heat, chemicals, or virus elicitors of UPR.Ab initiopromoter analysis revealed that potato and ArabidopsisBiP1andBiP2promoters were highly enriched with cis regulatory elements (CREs) linked to developmental processes, whereasBiP3promoters were enriched with stress-related CREs. The frequency and linear distribution of these CREs produced two phylogenetic branches that further resolve the groups identified through gene phylogeny and exon/intron phase analysis. These data reveal that the CRE architecture ofBiPpromoters potentially define their spatio -temporal expression patterns under developmental and stress related cues.