bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptional response to host chemical cues underpins expansion of host range in a fungal plant pathogen lineage
Authors: Kusch Stefan , Larrouy Justine , Ibrahim Heba M. M. , Gasset Noémie , Navaud Olivier , Mbengue Malick , Zanchetta Catherine , Lopez-Roques Celine , Donnadieu Cecile , Raffaele Sylvain 
Published: October 2020

AbstractThe host range of parasites is an important factor in assessing the dynamics of disease epidemics. The evolution of pathogens to accommodate new hosts may lead to host range expansion, a process the molecular bases of which are largely enigmatic. The fungusSclerotinia sclerotiorumparasitizes more than 400 plant species from diverse eudicot families while its close relative,S. trifoliorum, is restricted to plants from theFabaceaefamily. We analyzedS. sclerotiorumglobal transcriptome reprogramming on hosts from six botanical families and reveal a flexible, host-specific transcriptional program driven by core and host-response co-expression (SPREx) gene clusters. We generated a chromosome-level genome assembly forS. trifoliorumand found near-complete gene space conservation in broad and narrow host rangeSclerotiniaspecies. However,S. trifoliorumshowed increased sensitivity to theBrassicaceaedefense compound camalexin. Inter-specific transcriptome analyses revealed a lack of transcriptional response to camalexin inS. trifoliorumand provide evidence thatcis-regulatory variation associates with the genetic accommodation ofBrassicaceaein theSclerotiniahost range. Our work demonstrates adaptive plasticity of a broad host range pathogen with specific responses to different host plants and demonstrates the co-existence of signatures for generalist and polyspecialist life styles in the genome of a plant pathogen. We reason that this mechanism enables the emergence of new disease with no or limited gene flow between strains and species, and could underlie the emergence of new epidemics originating from wild plants in agricultural settings.
Large-scale single-cell analysis reveals critical immune characteristics of COVID-19 patients
Authors: Ren Xianwen , Wen Wen , Fan Xiaoying , Hou Wenhong , Su Bin , Cai Pengfei , Li Jiesheng , Liu Yang , Tang Fei , Zhang Fan , Yang Yu , He Jiangping , Ma Wenji , He Jingjing , Wang Pingping , Cao Qiqi , Chen Fangjin , Chen Yuqing , Cheng Xuelian , Deng Guohong , Deng Xilong , Ding Wenyu , Feng Yingmei , Gan Rui , Guo Chuang , Guo Weiqiang , He Shuai , Jiang Chen , Liang Juanran , Li Yi-min , Lin Jun , Ling Yun , Liu Haofei , Liu Jianwei , Liu Nianping , Liu Yang , Luo Meng , Ma Qiang , Song Qibing , Sun Wujianan , Wang GaoXiang , Wang Feng , Wang Ying , Wen Xiaofeng , Wu Qian , Xu Gang , Xie Xiaowei , Xiong Xinxin , Xing Xudong , Xu Hao , Yin Chonghai , Yu Dongdong , Yu Kezhuo , Yuan Jin , Zhang Biao , Zhang Tong , Zhao Jincun , Zhao Peidong , Zhou Jianfeng , Zhou Wei , Zhong Sujuan , Zhong Xiaosong , Zhang Shuye , Zhu Lin , Zhu Ping , Zou Bin , Zou Jiahua , Zuo Zengtao , Bai Fan , Huang Xi , Bian Xiuwu , Zhou Penghui , Jiang Qinghua , Huang Zhiwei , Bei Jin-Xin , Wei Lai , Liu Xindong , Cheng Tao , Li Xiangpan , Zhao Pingsen , Wang Fu-Sheng , Wang Hongyang , Su Bing , Zhang Zheng , Qu Kun , Wang Xiaoqun , Chen Jiekai , Jin Ronghua , Zhang Zemin 
Published: October 2020

SUMMARYDysfunctional immune response in the COVID-19 patients is a recurrent theme impacting symptoms and mortality, yet the detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 205 COVID-19 patients and controls to create a comprehensive immune landscape. Lymphopenia and active T and B cell responses were found to coexist and associated with age, sex and their interactions with COVID-19. Diverse epithelial and immune cell types were observed to be virus-positive and showed dramatic transcriptomic changes. Elevation of ANXA1 and S100A9 in virus-positive squamous epithelial cells may enable the initiation of neutrophil and macrophage responses via the ANXA1-FPR1 and S100A8/9-TLR4 axes. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis and designing effective therapeutic strategies for COVID-19.HIGHLIGHTSLarge-scale scRNA-seq analysis depicts the immune landscape of COVID-19Lymphopenia and active T and B cell responses coexist and are shaped by age and sexSARS-CoV-2 infects diverse epithelial and immune cells, inducing distinct responsesCytokine storms with systemic S100A8/A9 are associated with COVID-19 severity
Gender stereotype and the scientific career of women: Evidence from biomedical research centers
Authors: Montalvo Jose G. , Alimonti Daniele , Reiland Sonja , Vernos Isabelle 
Published: October 2020

AbstractWomen are underrepresented in the top ranks of the scientific career, including the biomedical disciplines. This is not generally the result of explicit and easily recognizable gender biases but the outcome of decisions with many components of unconscious nature that are difficult to assess. Evidence suggests that implicit gender stereotypes influence perceptions as well as decisions. To explore these potential reasons of women’s underrepresentation in life sciences we analyzed the outcome of gender-science and gender-career Implicit Association Tests (IAT) taken by 2,589 scientists working in high profile biomedical research centers. We found that male-science association is less pronounced among researchers than in the general population (34% below the level of the general population). However, this difference is mostly explained by the low level of the IAT score among female researchers. Despite the highly meritocratic view of the academic career, male scientists have a high level of male-science association (261% the level among women scientists), similar to the general population.
Distinct cellular immune profiles in the airways and blood of critically ill patients with COVID-19
Authors: Saris Anno , Reijnders Tom D.Y. , Nossent Esther J. , Schuurman Alex R. , Verhoeff Jan , van Asten Saskia D. , Bontkes Hetty J. , Blok Siebe G. , Duitman Janwillem , Bogaard Harm Jan , Heunks Leo , Lutter Rene , van der Poll Tom , Garcia Vallejo Juan J. ,   on behalf of the ArtDECO consortium and the Amsterdam UMC COVID study group
Published: October 2020

AbstractOur understanding of the coronavirus disease-19 (COVID-19) immune response is almost exclusively derived from studies that examined blood. To gain insight in the pulmonary immune response we analysed BALF samples and paired blood samples from 17 severe COVID-19 patients. Macrophages and T cells were the most abundant cells in BALF. In the lungs, both CD4 and CD8 T cells were predominantly effector memory cells and expressed higher levels of the exhaustion marker PD-1 than in peripheral blood. Prolonged ICU stay associated with a reduced proportion of activated T cells in peripheral blood and even more so in BALF. T cell activation in blood, but not in BALF, was higher in fatal COVID-19 cases. Increased levels of inflammatory mediators were more pronounced in BALF than in plasma. In conclusion, the bronchoalveolar immune response in COVID-19 has a unique local profile that strongly differs from the immune profile in peripheral blood.SummaryThe bronchoalveolar immune response in severe COVID-19 strongly differs from the peripheral blood immune profile. Fatal COVID-19 associated with T cell activation blood, but not in BALF.
BIO-LGCA: a cellular automaton modelling class for analysing collective cell migration
Authors: Deutsch Andreas , Nava-Sedeño Josué Manik , Syga Simon , Hatzikirou Haralampos 
Published: October 2020

1AbstractCollective dynamics in multicellular systems such as biological organs and tissues plays a key role in biological development, regeneration, and pathological conditions. Collective tissue dynamics - understood as population behaviour arising from the interplay of the constituting discrete cells - can be studied with on- and off-lattice agent-based models. However, classical on-lattice agent-based models, also known as cellular automata, fail to replicate key aspects of collective migration, which is a central instance of collective behaviour in multicellular systems.To overcome drawbacks of classical on-lattice models, we introduce an on-lattice, agent-based modelling class for collective cell migration, which we call biological lattice-gas cellular automaton (BIO-LGCA). The BIO-LGCA is characterised by synchronous time updates, and the explicit consideration of individual cell velocities. While rules in classical cellular automata are typically chosen ad hoc, rules for cell-cell and cell-environment interactions in the BIO-LGCA can also be derived from experimental cell migration data or biophysical laws for individual cell migration. We introduce elementary BIO-LGCA models of fundamental cell interactions, which may be combined in a modular fashion to model complex multicellular phenomena. We exemplify the mathematical mean-field analysis of specific BIO-LGCA models, which allows to explain collective behaviour. The first example predicts the formation of clusters in adhesively interacting cells. The second example is based on a novel BIO-LGCA combining adhesive interactions and alignment. For this model, our analysis clarifies the nature of the recently discovered invasion plasticity of breast cancer cells in heterogeneous environments. A Python package which implements various interaction rules and visualisations of BIO-LGCA model simulations we have developed is available athttps://github.com/sisyga/BIO-LGCA.2Author summaryPattern formation during embryonic development and pathological tissue dynamics, such as cancer invasion, emerge from individual inter-cellular interactions. In order to study the impact of single cell dynamics and cell-cell interactions on tissue behaviour, one needs to develop space-time-dependent on- or off-lattice agent-based models (ABMs), which consider the behaviour of individual cells. However, classical on-lattice agent-based models also known as cellular automata fail to replicate key aspects of collective migration, which is a central instance of collective behaviour in multicellular systems. Here, we present the rule- and lattice-based BIO-LGCA modelling class which allows for (i) rigorous derivation of rules from biophysical laws and/or experimental data, (ii) mathematical analysis of collective migration, and (iii) computationally efficient simulations.
Rules of nature’sFormula Run: Muscle mechanics during late stance is the key to explaining maximum running speed
Authors: Günther Michael , Rockenfeller Robert , Weihmann Tom , Haeufle Daniel F. B. , Götz Thomas , Schmitt Syn 
Published: October 2020

AbstractThe maximum running speed of legged animals is one evident factor for evolutionary selection—for predators and prey. Therefore, it has been studied across the entire size range of animals, from the smallest mites to the largest elephants, and even beyond to extinct dinosaurs. A recent analysis of the relation between animal mass (size) and maximum running speed showed that there seems to be an optimal range of body masses in which the highest terrestrial running speeds occur. However, the conclusion drawn from that analysis—namely, that maximum speed is limited by the fatigue of white muscle fibres in the acceleration of the body mass to some theoretically possible maximum speed—was based on coarse reasoning on metabolic grounds, which neglected important biomechanical factors and basic muscle-metabolic parameters. Here, we propose a generic biomechanical model to investigate the allometry of the maximum speed of legged running. The model incorporates biomechanically important concepts: the ground reaction force being counteracted by air drag, the leg with its gearing of both a muscle into a leg length change and the muscle into the ground reaction force, as well as the maximum muscle contraction velocity, which includes muscle-tendon dynamics, and the muscle inertia—with all of them scaling with body mass. Put together, these concepts’ characteristics and their interactions provide a mechanistic explanation for the allometry of maximum legged running speed. This accompanies the offering of an explanation for the empirically found, overall maximum in speed: In animals bigger than a cheetah or pronghorn, the time that any leg-extending muscle needs to settle, starting from being isometric at about midstance, at the concentric contraction speed required for running at highest speeds becomes too long to be attainable within the time period of a leg moving from midstance to lift-off. Based on our biomechanical model we, thus, suggest considering the overall speed maximum to indicate muscle inertia being functionally significant in animal locomotion. Furthermore, the model renders possible insights into biological design principles such as differences in the leg concept between cats and spiders, and the relevance of multi-leg (mammals: four, insects: six, spiders: eight) body designs and emerging gaits. Moreover, we expose a completely new consideration regarding the muscles’ metabolic energy consumption, both during acceleration to maximum speed and in steady-state locomotion.
Is the radial growth of irrigated urban trees more strongly correlated to light and temperature than water?
Authors: Griffin Kevin L. , Harris Thomas G. , Bruner Sarah , McKenzie Patrick , Hise Jeremy 
Published: October 2020

AbstractBackgroundReal-time monitoring of tree growth can provide novel information about trees in urban/suburban areas and the myriad ecosystem services they provide. By monitoring irrigated specimen trees we test the hypothesis that in trees with sufficient water, growth is governed by environmental factors regulating energy gain rather than by factors related to water use.MethodsInternet enabled, high-resolution dendrometers were installed on three trees in Southampton, NY. The instruments, along with a weather station, streamed data to a project web page that was updated once an hour. (https://ecosensornetwork.com). Growing periods were determined using a Hidden Markov Model based on Zweifel et al.’s (2016) zero-growth model. Linear models and conditional inference trees correlated environmental variables to growth magnitude and rate of growth.ResultsGrowth was governed by the interacting environmental variables of air temperature, soil moisture, VPD and took place primarily at night. Radial growth of spruce began April 14 after the accumulation of 69.7 °C growing degrees days and ended September 7th. Cedar growth began later (April 26th), after the accumulation of 160.6 °C and ended later (November 3rd). During the observation period, these three modest suburban trees sequestered 108.3 kg of CO2.ConclusionsThough irrigated, residential tree growth in our experiment was affected by environmental factors relating to both water use and energy gain through photosynthesis. Linking tree growth to fluctuations in environmental conditions facilitates the development of a predictive understanding useful for ecosystem management and growth forecasting across future altering climates.
Altering CLC stoichiometry by reducing non-polar side-chains at the dimerization interface
Authors: Mersch Kacey , Ozturk Tugba N. , Park Kunwoong , Lim Hyun-Ho , Robertson Janice L. 
Published: October 2020

ABSTRACTCLC-ec1 is a Cl-/H+antiporter that forms stable homodimers in lipid bilayers, with a free energy of −10.9 kcal/mole relative to the 1 subunit/lipid standard state in 2:1 POPE/POPG lipid bilayers. The dimerization interface is formed by four transmembrane helices: H, I, P and Q, that are lined by non-polar side-chains that come in close contact, yet it is unclear as to whether their interactions drive dimerization. To investigate whether non-polar side-chains are required for dimer assembly, we designed a series of constructs where side-chain packing in the dimer state is significantly reduced by making 4-5 alanine substitutions along each helix (H-ala, I-ala, P-ala, Q-ala). All constructs are functional and three purify as stable dimers in detergent micelles despite the removal of significant side-chain interactions. On the other hand, H-ala shows the unique behavior of purifying as a mixture of monomers and dimers, followed by a rapid and complete conversion to monomers. In lipid bilayers, all four constructs are monomeric as examined by single-molecule photobleaching analysis. Further study of the H-helix shows that the single mutation L194A is sufficient to yield monomeric CLC-ec1 in detergent micelles and lipid bilayers. X-ray crystal structures of L194A reveal the protein re-assembles to form dimers, with a structure that is identical to wild-type. Altogether, these results demonstrate that non-polar membrane embedded side-chains play an important role in defining dimer stability, but the stoichiometry is highly contextual to the solvent environment. Furthermore, we discovered that L194 is a molecular hot-spot for defining dimerization of CLC-ec1.
Non-canonical Activation of Human Group 2 Innate Lymphoid Cells by TLR4 Signaling
Authors: She Li , Alanazi Hamad H. , Wang Jingwei , Chupp Daniel P. , Xu Yijiang , Zan Hong , Xu Zhenming , Sun Yilun , Xiong Na , Zhang Nu , Zhang Xin , Liu Yong , Li Xiao-Dong 
Published: October 2020

AbstractGroup 2 innate lymphoid cells (ILC2) are emerging as a critical player in type 2 immunity at barrier sites in response to microbial infections and allergen exposures. Although their classical activators are known to be host epithelial-derived alarmin cytokines IL-33, IL-25 or TSLP, it remains elusive whether ILC2 cells can be activated by directly sensing microbial ligands via pattern-recognition receptors such as toll-like receptors (TLRs). Here we report that toll-like receptor 4 (TLR4) is a potent activating receptor of human ILC2. We found that among many microbial ligands examined, lipopolysaccharides (LPS) from multiple species of Gram-negative bacteria, was found to potently stimulate human, but not murine ILC2, to proliferate and produce massive amounts of type 2 effector cytokines IL-4, IL-5, and IL-13. LPS-activated ILC2 also had greatly enhanced the CD40 ligand (CD154) expression and were able to promote the proliferation and antibody production of human B cells in culture. In a humanized mouse model, LPS activated the adoptively transferred human ILC2 in mouse lungs. Both NF-kB and JAK pathways, but not the IL-33-ST2 pathway, were required for LPS to activate human ILC2. RNA-seq data further revealed that LPS induced a large set of genes overlapped significantly with those induced by IL-33. Collectively, these findings support a non-classical mode of activating human ILC2 cells via the LPS-TLR4 signaling axis. Thus, targeting TLR4 signaling pathway might be developed as a new approach by modulating ILC2 activation in treating various type 2 immunity-associated diseases.
A prospective longitudinal study shows putamen volume is associated with moderate amphetamine use and resultant cognitive impairments
Authors: Kendrick Keith M , Daumann Joerg , Wagner Daniel , Koester Philip , Tittgemeyer Marc , Luo Qiang , Gouzoulis-Mayfrank Euphrosyne , Becker Benjamin 
Published: October 2020

AbstractBackgroundAmphetamine-type stimulants (ATS) have become a critical public health issue. Animal models have indicated a clear neurotoxic potential of ATSs. In humans, chronic use has been associated with cognitive deficits and structural brain abnormalities. However, cross-sectional retrospective designs in chronic users cannot truly determine the causal direction of the effects.MethodsIn a prospective-longitudinal study design cognitive functioning and brain structure were assessed at baseline and at 12-months follow-up in occasional ATS users (cumulative lifetime use <10 units at baseline).ResultsExamination of change-scores between the initial examination and follow-up revealed declined verbal memory performance and putamen volume in users with high relative to low interim ATS exposure. In the entire sample interim ATS use, memory decline and putamen volume reductions were strongly associated.ConclusionsThe present findings support the hypothesis that ATS use is associated with deficient dorsal striatal morphology which might reflect alterations in dopaminergic pathways. More importantly, these findings strongly suggest that even occasional, low-dose ATS use disrupts striatal integrity and cognitive functioning.
Supervised Application of Internal Validation Measures to Benchmark Dimensionality Reduction Methods in scRNA-seq Data
Authors: Koch Forrest C , Sutton Gavin J , Voineagu Irina , Vafaee Fatemeh 
Published: October 2020

AbstractA typical single-cell RNA sequencing (scRNA-seq) experiment will measure on the order of 20,000 transcripts and thousands, if not millions, of cells. The high dimensionality of such data presents serious complications for traditional data analysis methods and, as such, methods to reduce dimensionality play an integral role in many analysis pipelines. However, few studies benchmark the performance of these methods on scRNA-seq data, with existing comparisons assessing performance via downstream analysis accuracy measures which may confound the interpretation of their results. Here, we present the most comprehensive benchmark of dimensionality reduction methods in scRNA-seq data to date, utilizing over 300,000 compute hours to assess the performance of over 25,000 low dimension embeddings across 33 dimensionality reduction methods and 55 scRNA-seq datasets (ranging from 66-27,500 cells). We employ a simple-yet-novel approach which does not rely on the results of downstream analyses. Internal validation measures (IVMs), traditionally used as an unsupervised method to assess clustering performance, are repurposed to measure how well-formed biological clusters are after dimensionality reduction. Performance was further evaluated using nearly 200,000,000 iterations of DBSCAN, a density-based clustering algorithm, showing that hyperparameter optimization using IVMs as the objective function leads to near-optimal clustering. Methods were also assessed on the extent to which they preserve the global structure of the data, and on their computational memory and time requirements across a large range of sample sizes. Our comprehensive benchmarking analysis provides a valuable resource for researchers and aims to guide best practice for dimensionality reduction in scRNA-seq analyses, and we highlight LDA (Latent Dirichlet Allocation) and PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) as high-performing algorithms.