bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bridging cell-scale simulations and radiologic images to explain short-time intratumoral oxygen fluctuations
Authors: Kingsley Jessica L. , Costello James R. , Raghunand Natarajan , Rejniak Katarzyna A. 
Published: March 2021

AbstractRadiologic images provide a way to monitor tumor development and its response to therapies in a longitudinal and minimally invasive fashion. However, they operate on a macroscopic scale (average value per voxel) and are not able to capture microscopic scale (cell level) phenomena. Nevertheless, to examine the causes of frequent fast fluctuations in tissue oxygenation, the models simulating individual cells’ behavior are needed. Here, we provided a link between the average data value recorded for radiologic image voxels and the cellular and vascular architecture of the tissue that fills these voxels. Using hybrid agent-based modeling, we generated a set of tissue morphologies capable of reproducing tissue oxygenation levels observed in radiologic images. We applied this approach to investigate whether oxygen fluctuations can be explained by changes in vascular oxygen supply or by modulations in cellular oxygen absorption. Our studies showed that intravascular changes in oxygen supply can reproduce the observed fluctuations in tissue oxygenation in all considered regions of interest. However, large magnitude fluctuations cannot be recreated by modifications in cellular absorption of oxygen in biologically feasible manner. Additionally, we developed a procedure to identify plausible tissue morphologies for a given temporal series of average data from radiology images. In future applications this approach can be used to generate a set of tissues representative for radiology images and to simulate tumor response to various anti-cancer treatments on the tissue-scale level.Authors SummaryLow levels of oxygen, called hypoxia, are observable in many solid tumors. They are associated with more aggressive malignant cells which are resistant to chemo-, radio- and immunotherapies. Recently developed imaging techniques provide a way to measure the magnitude of frequent short-term oxygen fluctuation, however they operate on a macro-scale voxel level. To examine the causes of rapid oxygen fluctuations on the cell level, we developed a hybrid agent-based mathematical model. We tested two different mechanisms that could be responsible for these cyclic effects in tissue oxygenation: variations in vascular influx of oxygen and modulations in cellular oxygen absorption. Additionally, we developed a procedure to identify plausible tissue morphologies from data collected from radiological images. This will also provide a bridge between the micro-scale simulations with individual cells and the longitudinal medical images containing average voxel values. In the future applications, this approach can be used to generate a set of tissues representative of radiology images and to simulate tumor response to various anticancer treatments on the cell-scale level.
Multimodal characterization of Yucatan minipig behavior and physiology through maturation
Authors: Netzley Alesa H. , Hunt Ryan D. , Franco-Arellano Josue , Arnold Nicole , Munoz Kirk A. , Colbath Aimee C. , Bush Tamara Reid , Pelled Galit 
Published: March 2021

AbstractBrain injuries that are induced by external forces are particularly challenging to model experimentally. In recent decades, the domestic pig has been gaining popularity as a highly relevant animal model to address the pathophysiological mechanisms and the biomechanics associated with head injuries. Understanding cognitive, motor, and sensory aspects of pig behavior throughout development is crucial for evaluating cognitive and motor deficits after injury. We have developed a comprehensive battery of tests to characterize the behavior and physiological function of the Yucatan minipig throughout maturation. Behavioral testing included assessments of learning and memory, executive functions, circadian rhythms, gait analysis, and level of motor activity. We applied traditional behavioral apparatus and analysis methods, as well as state-of-the-art sensor technologies to report on motion and activity, and artificial intelligent approaches to analyze behavior. We studied pigs from 16 weeks old through sexual maturity at 35 weeks old. The results show multidimensional characterization of minipig behavior, and how it develops and changes with age. This animal model may capitulate the biomechanical consideration and phenotype of head injuries in the developing brain and can drive forward the field of understanding pathophysiological mechanisms and developing new therapies to accelerate recovery in children who have suffered head trauma.
Assortative Mating Biases Marker-based Heritability Estimators
Authors: Border Richard , O’Rourke Sean , de Candia Teresa , Goddard Michael E. , Visscher Peter M. , Yengo Loic , Jones Mathew , Keller Matthew C. 
Published: March 2021

AbstractMany complex traits are subject to assortative mating (AM), with recent molecular genetic findings confirming longstanding theoretical predictions that AM alters genetic architecture by inducing long range dependence across causal variants. However, all marker-based heritability estimators assume mating is random. We provide mathematical and simulation-based evidence demonstrating that both method-of-moments estimators and likelihood-based estimators produce biased estimates in the presence of AM and that common approaches to account for population structure fail to mitigate this bias. Then, examining height and educational attainment in the UK Biobank, we demonstrate that these biases affect real world traits. Finally, we derive corrected heritability estimators for traits under equilibrium AM.
SC1: A Tool for Interactive Web-Based Single Cell RNA-Seq Data Analysis
Authors: Moussa Marmar , Măndoiu Ion I. 
Published: March 2021

AbstractSingle cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. Here, we presentSC1a web-based highly interactive scRNA-Seq data analysis tool publicly accessible athttps://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on Term-Frequency Inverse-Document-Frequency (TF-IDF) scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single cell omics data modalities like TCR-Seq and supports several single cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.
Plasticity in gustatory and nociceptive neurons controls decision making inC. eleganssalt navigation
Authors: Dekkers Martijn P.J. , Salfelder Felix , Sanders Tom , Umuerri Oluwatoroti , Cohen Netta , Jansen Gert 
Published: March 2021

AbstractA conventional understanding of perception assigns sensory organs the role of capturing the environment. Better sensors result in more accurate encoding of stimuli, allowing for cognitive processing downstream. Here we show that plasticity in sensory neurons mediates a behavioral switch inC. elegansbetween attraction to NaCl in naïve animals and avoidance of NaCl in preconditioned animals, called gustatory plasticity. Ca2+imaging in ASE and ASH NaCl sensing neurons reveals multiple cell-autonomous and distributed circuit adaptation mechanisms. A computational model quantitatively accounts for observed behaviors and reveals roles for sensory neurons in the control and modulation of motor behaviors, decision making and navigational strategy. Sensory adaptation dynamically alters the encoding of the environment. Rather than encoding the stimulus directly, therefore, we propose that theseC. eleganssensors dynamically encode a context-dependent value of the stimulus. Our results demonstrate how adaptive sensory computation can directly control an animal’s behavioral state.
More pests but less treatments: ambivalent effect of landscape complexity on Conservation Biological Control
Authors: Zamberletti Patrizia , Sabir Khadija , Opitz Thomas , Bonnefon Olivier , Gabriel Edith , Papaïx Julien 
Published: March 2021

AbstractIn agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and auxiliary species, the underlying landscape structure, and their interaction may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that SNH boost predator population, but predator movement from hedges to fields is fundamental for an efficient pest regulation by auxiliaries and to decrease pesticide treatments. Moreover landscape elements may lead to different effects on pest reduction depending on the considered scale. Integration of species behaviors and traits with landscape structure at multiple scales are needed to provide useful insights for CBC.
Predicting TCR-epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning
Authors: Luu Alan M. , Leistico Jacob R. , Miller Tim , Kim Somang , Song Jun S. 
Published: March 2021

ABSTRACTUnderstanding the recognition of specific epitopes by cytotoxic T cells is a central problem in immunology. Although predicting binding between peptides and the class I Major Histocompatibility Complex (MHC) has had success, predicting interactions between T cell receptors (TCRs) and MHC class I-peptide complexes (pMHC) remains elusive. This paper utilizes a convolutional neural network model employing deep metric learning and multimodal learning to perform two critical tasks in TCR-epitope binding prediction: identifying the TCRs that bind a given epitope from a TCR repertoire, and identifying the binding epitope of a given TCR from a list of candidate epitopes. Our model can perform both tasks simultaneously and reveals that inconsistent preprocessing of CDR3B sequences can confound binding prediction. Applying a neural network interpretation method identifies key amino acid sequence patterns and positions within the TCR important for binding specificity. Contrary to the common assumption, known crystal structures of TCR-pMHC complexes show that the predicted salient amino acid positions are not necessarily the closest to the epitopes, implying that physical proximity may not be a good proxy for importance in determining TCR-epitope specificity. Our work thus provides insight into the learned predictive features of TCR-epitope binding specificity and advances associated classification tasks.
Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0 identifies proteins enriched within inflammatory lesions in tissue sections and human clinical biopsies
Authors: Yin Bocheng , Caggiano Laura R , Li Rung-Chi , McGowan Emily , Holmes Jeffery W , Ewald Sarah E 
Published: March 2021

ABSTRACTTissue microenvironment properties like blood flow, extracellular matrix or proximity to immune infiltrate are important regulators of cell biology. However, methods to study regional protein expression in context of the native tissue environment are limited. To address this need we have developed a novel approach to visualize, purify and measure proteins in situ using Automated Spatially Targeted Optical Micro Proteomics (AutoSTOMP) 2.0. We previously implemented AutoSTOMP to identify proteins localized to the vacuoles of obligate intracellular microbes at the 1-2 μm scale within infected host cells1. Here we report custom codes in SikuliX to specify regions of heterogeneity in a tissue section and then biotin tag and identify proteins belonging to specific cell types or structures within those regions. To enrich biotinylated targets from fixed tissue samples we developed a biochemical protocol compatible with LC-MS. These tools were applied to a) identify inflammatory proteins expressed by CD68+ macrophages in rat cardiac infarcts and b) characterize inflammatory proteins enriched in IgG4+ lesions in esophageal tissue. These data indicate that AutoSTOMP is a flexible approach to determine regional protein expression in situ on a range of primary tissues and clinical biopsies where current tools are limited.
CCL28 modulates neutrophil responses during infection with mucosal pathogens
Authors: Perez-Lopez Araceli , Silva Steven , Lee Michael H. , Dillon Nicholas , Brandt Stephanie L. , Gerner Romana R. , Melchior Karine , Walker Gregory T. , Sosa-Hernandez Victor A. , Cervantes-Diaz Rodrigo , Romero-Ramirez Sandra , Maravillas-Montero Jose L. , Nuccio Sean-Paul , Nizet Victor , Raffatellu Manuela 
Published: March 2021

AbstractThe chemokine CCL28 is highly expressed in mucosal tissues, but its role during infection is not well understood. Here we show that CCL28 promotes neutrophil accumulation to the gut of mice infected withSalmonellaand to the lung of mice infected withAcinetobacter. Neutrophils isolated from the infected mucosa expressed the CCL28 receptors CCR3 and, to a lesser extent, CCR10, on their surface. The functional consequences of CCL28 deficiency were different between the two infections, asCcl28-/-mice were highly susceptible toSalmonellagut infection, but highly resistant to otherwise lethalAcinetobacterlung infection.In vitro, unstimulated neutrophils harbored pre-formed intracellular CCR3 that was rapidly mobilized to the cell surface following phagocytosis or inflammatory stimuli. Moreover, CCL28 stimulation enhanced neutrophil antimicrobial activity, production of reactive oxygen species, and formation of extracellular traps, all processes that were largely dependent on CCR3. Consistent with the different outcomes in the two infection models, neutrophil stimulation with CCL28 boosted the killing ofSalmonellabut not ofAcinetobacter. CCL28 thus plays a critical role in the immune response to mucosal pathogens by increasing neutrophil accumulation and activation, which can enhance pathogen clearance but also exacerbate disease depending on the mucosal site and the infectious agent.
An equine tendon model for studying intra-tendinous shear in tendons that have more than one muscle contribution
Authors: Yin Nai-Hao , McCarthy Ian , Birch Helen L. 
Published: March 2021

AbstractHuman Achilles tendon is composed of three smaller sub-tendons and exhibits non-uniform internal displacements, which decline with age and after injury, suggesting a potential role in the development of tendinopathies. Studying internal sliding behaviour is therefore important but difficult in human Achilles tendon. Here we propose the equine deep digital flexor tendon (DDFT) and its accessory ligament (AL) as a model to understand the sliding mechanism. The AL-DDFT has a comparable sub-bundle structure, is subjected to high and frequent asymmetric loads and is a natural site of injury similar to human Achilles tendons. Equine AL-DDFT were collected and underwent whole tendon level (n=7) and fascicle level (n=7) quasi-static mechanical testing. Whole tendon level testing was performed by sequentially loading through the proximal AL and subsequently through the proximal DDFT and recording regional strain in the free structures and joined DDFT and AL. Fascicle level testing was performed with focus on the inter-sub-bundle matrix between the two structures at the junction. Our results demonstrate a significant difference in the regional strain between the joined DDFT and AL and a greater transmission of force from the AL to the DDFT than vice versa. These results can be partially explained by the mechanical properties and geometry of the two structures and by differences in the properties of the interfascicular matrices. In conclusion, this tendon model successfully demonstrates that high displacement discrepancy occurs between the two structures and can be used as an easy-access model for study intra-tendinous shear mechanics at the sub-tendon level.
Effects of cover crops on beetle assemblages in tea plantations
Authors: Chen Li-Lin , Pozsgai Gabor , Li Xiang-Yu , Li Lei , Reddy Gadi V.P. , You Min-Sheng 
Published: March 2021

AbstractBeetles are visible members of food webs in tea plantations, with high species richness and abundance. Many tea pests, as well as natural enemies, are members of this order, so a knowledge of how groundcovers affect beetles can aid pest management. We collected beetles in a replicated field experiment in the Wuyi Mountains, Fujian Province China. Tea was intercropped withPaspalum notatumorChamaecrista rotundifolia,or rows were cleared to bare ground, or in the control they were left unmanaged to allow weeds to grow naturally. Sampling, done by sweep netting and vegetation beating, was conducted monthly, between May 2006 and April 2008, and Coleoptera abundance, biomass, species richness and assemblage structures were compared between groundcover treatments. Total beetle abundance and species richness were significantly higher in tea intercropped withC. rotundifoliaand bare ground than in naturally grown weedy control. Whilst there was no difference between predator assemblages among treatments for any measure, herbivores were more abundant, weighed more, and were more diverse inC. rotundifoliatreatments than in weedy control. Biomass and species richness were also greater in plots withP. notatumgroundcover than those in weedy control. We found that beetle assemblages varied both seasonally and with ground cover treatment, but the potential pest control impact of more species-rich beetle assemblages was mixed, and further work is needed to gain information on trophic groups with potential benefits for use in non-insecticidal pest management.
The middle lipin (M-Lip) domain is a new dimeric protein fold that binds membranes
Authors: Gu Weijing , Gao Shujuan , Wang Huan , Fleming Kaelin D. , Hoffmann Reece M. , Yang Jong Won , Patel Nimi M. , Choi Yong Mi , Burke John E. , Reue Karen , Airola Michael V. 
Published: March 2021

AbstractPhospholipid synthesis and fat storage as triglycerides is regulated by lipin phosphatidic acid phosphatases (PAPs), whose enzymatic PAP function requires association with cellular membranes. Using hydrogen deuterium exchange mass spectrometry, we find mouse lipin 1 binds membranes through an N-terminal amphipathic helix and a middle lipin (M-Lip) domain that is conserved in mammalian and mammalian-like lipins. Crystal structures of the M-Lip domain reveal a previously unrecognized and novel protein fold that dimerizes. The isolated M-Lip domain binds membranes both in vitro and in cells through conserved basic and hydrophobic residues. Deletion of the M-Lip domain in full-length lipin 1 influences PAP activity, membrane binding, subcellular localization, oligomerization, and adipocyte differentiation, but does not affect transcriptional co-activation. This establishes the M-Lip domain as a new dimeric protein fold that binds membranes and is critical for full functionality of mammalian lipins.
A Weighted Network Analysis Framework for the Hourglass Effect — and its Application in the C. Elegans Connectome
Authors: Batta Ishaan , Yao Qihang , Sabrin Kaeser M. , Dovrolis Constantine 
Published: March 2021

ABSTRACTUnderstanding hierarchy and modularity in natural as well as technological networks is of utmost importance. A major aspect of such analysis involves identifying the nodes that are crucial to the overall processing structure of the network. More recently, the approach of hourglass analysis has been developed for the purpose of quantitatively analyzing whether only a few intermediate nodes mediate the information processing between a large number of inputs and outputs of a network. We develop a new framework for hourglass analysis that takes network weights into account while identifying the core nodes and the extent of hourglass effect in a given weighted network. We use this framework to study the structural connectome of theC. elegansand identify intermediate neurons that form the core of sensori-motor pathways in the organism. Our results show that the neurons forming the core of the connectome show significant differences across the male and hermaphrodite sexes, with most core nodes in the male concentrated in sex-organs while they are located in the head for the hermaphrodite. Our work demonstrates that taking weights into account for network analysis framework leads to emergence of different network patterns in terms of identification of core nodes and hourglass structure in the network, which otherwise would be missed by unweighted approaches.
EffectorO: motif-independent prediction of effectors in oomycete genomes using machine learning and lineage-specificity
Authors: Nur Munir , Wood Kelsey , Michelmore Richard 
Published: March 2021

AbstractOomycete plant pathogens cause a wide variety of diseases, including late blight of potato, sudden oak death, and downy mildews of plants. These pathogens are major contributors to loss in numerous food crops. Oomycetes secrete effector proteins to manipulate their hosts to the advantage of the pathogen. Plants have evolved to recognize effectors, resulting in an evolutionary cycle of defense and counter-defense in plant–microbe interactions. This selective pressure results in highly diverse effector sequences that can be difficult to computationally identify using only sequence similarity. We developed a novel effector prediction tool, EffectorO, that uses two complementary approaches to predict effectors in oomycete pathogen genomes: (1) a machine learning-based pipeline that predicts effector probability based on the biochemical properties of the N-terminal amino acid sequence of a protein and (2) a pipeline based on lineage-specificity to find proteins that are unique to one species or genus, a sign of evolutionary divergence due to adaptation to the host. We tested EffectorO onBremia lactucae, which causes lettuce downy mildew, andPhytophthora infestans, which causes late blight of potato and tomato, and predicted many novel effector candidates, while recovering the majority of known effector candidates. EffectorO will be useful for discovering novel families of oomycete effectors without relying on sequence similarity to known effectors.