bluuebunny/crossref_metadata_2025_split huggingface dataset:
In vivo structural MRI-based atlas of human thalamic nuclei
Authors: Saranathan Manojkumar , Iglehart Charles , Monti Martin , Tourdias Thomas , Rutt Brian 
Published: August 2020

AbstractThalamic nuclei play critical roles in regulation of neurological functions like sleep and wakefulness. They are increasingly implicated in neurodegenerative and neurological diseases such as multiple sclerosis and essential tremor. However, segmentation of thalamic nuclei is difficult due to their poor visibility in conventional MRI scans. Sophisticated methods have been proposed which require specialized MRI acquisitions and complex post processing. There are very few digital MRI thalamic atlases and they have been constructed using a small number of post-mortem brains. The goal of this work is the development of a structural thalamic atlas at high spatial resolution based on manual segmentation of 20 subjects that include healthy subjects and patients with multiple-sclerosis. Using data analysis from healthy subjects as well as patients with multiple-sclerosis and essential tremor and at 3T and 7T MRI, we demonstrate the utility of this atlas to provide fast and accurate segmentation of thalamic nuclei when only conventional T1 weighted images are available.
Neural Mechanisms of Acceptance and Commitment Therapy for Chronic Pain: A Network-Based fMRI Approach
Authors: Aytur Semra A. , Ray Kimberly L. , Meier Sarah K. , Campbell Jenna , Gendron Barry , Waller Noah , Robin Donald A. 
Published: August 2020

AbstractOver 100 million Americans suffer from chronic pain (CP), which causes more disability than any other medical condition in the U.S. at a cost of $560-$635 billion per year (IOM, 2011). Opioid analgesics are frequently used to treat CP. However, long term use of opioids can cause brain changes such as opioid-induced hyperalgesia that, over time, increase pain sensation. Also, opioids fail to treat complex psychological factors that worsen pain-related disability, including beliefs about and emotional responses to pain. Cognitive behavioral therapy (CBT) can be efficacious for CP. However, CBT generally does not focus on important factors needed for long-term functional improvement, including attainment of personal goals and the psychological flexibility to choose responses to pain.Acceptance and Commitment Therapy (ACT) has been recognized as an effective, non-pharmacologic treatment for a variety of CP conditions. However, little is known about the neurologic mechanisms underlying ACT. We conducted an ACT intervention in women (n=9) with chronic musculoskeletal pain. Functional magnetic resonance imaging (fMRI) data were collected pre- and post-ACT, and changes in functional connectivity (FC) were measured using Network-Based Statistics (NBS). Behavioral outcomes were measured using validated assessments such as the Acceptance & Action Questionnaire (AAQ-II), the Chronic Pain Acceptance Questionnaire (CPAQ), the Center for Epidemiologic Studies Depression Scale (CES-D), and the NIH Toolbox Neuro-QoL™ (Quality of Life in Neurological Disorders) scales.Results suggest that, following the four-week ACT intervention, participants exhibited reductions in brain activation within and between key networks including self-reflection (default mode, DMN), emotion (salience, SN), and cognitive control (frontal parietal, FPN). These changes in connectivity strength were correlated with changes in behavioral outcomes including decreased depression and pain interference, and increased participation in social roles. This study is one of the first to demonstrate that improved function across the DMN, SN, and FPN may drive the positive outcomes associated with ACT. This study contributes to the emerging evidence supporting the use of neurophysiological indices to characterize treatment effects of alternative and complementary mind-body therapies.PerspectiveThis article identifies neural mechanisms that may mediate behavioral changes associated with Acceptance and Commitment Therapy (ACT) in persons with chronic musculoskeletal pain. This information could potentially help clinicians to determine which mind-body therapies may benefit specific patients as part of an integrative pain management approach.
Deciphering the state of immune silence in fatal COVID-19 patients
Authors: Bost Pierre , De Sanctis Francesco , Canè Stefania , Ugel Stefano , Donadello Katia , Castellucci Monica , Eyal David , Fiore Alessandra , Anselmi Cristina , Barouni Roza Maria , Trovato Rosalinda , Caligola Simone , Lamolinara Alessia , Iezzi Manuela , Facciotti Federica , Mazzariol Anna Rita , Gibellini Davide , De Nardo Pasquale , Tacconelli Evelina , Gottin Leonardo , Polati Enrico , Schwikowski Benno , Amit Ido , Bronte Vincenzo 
Published: August 2020

AbstractSince the beginning of the SARS-CoV-2 pandemic, COVID-19 has appeared as a unique disease with unconventional tissue and systemic immune features. While COVID-19 severe forms share clinical and laboratory aspects with various pathologies such as hemophagocytic lymphohistiocytosis, sepsis or cytokine release syndrome, their exact nature remains unknown. This is severely impeding the ability to treat patients facing severe stages of the disease. To this aim, we performed an in-depth, single-cell RNA-seq analysis of more than 150.000 immune cells isolated from matched blood samples and broncho-alveolar lavage fluids of COVID-19 patients and healthy controls, and integrated it with clinical, immunological and functionalex vivodata. We unveiled an immune signature of disease severity that correlated with the accumulation of naïve lymphoid cells in the lung and an expansion and activation of myeloid cells in the periphery. Moreover, we demonstrated that myeloid-driven immune suppression is a hallmark of COVID-19 evolution and arginase 1 expression is significantly associated with monocyte immune regulatory features. Noteworthy, we found monocyte and neutro-phil immune suppression loss associated with fatal clinical outcome in severe patients. Additionally, our analysis discovered that the strongest association of the patients clinical outcome and immune phenotype is the lung T cell response. We found that patients with a robust CXCR6+ effector memory T cell response have better outcomes. This result is line with the rs11385942 COVID-19 risk allel, which is in proximity to the CXCR6 gene and suggest effector memory T cell are a primary feature in COVID-19 patients. By systemically quantifying the viral landscape in the lung of severe patients, we indeed identified Herpes-Simplex-Virus 1 (HSV-1) as a potential opportunistic virus in COVID-19 patients. Lastly, we observed an unexpectedly high SARS-CoV-2 viral load in an immuno-compromised patient, allowing us to study the SARS-CoV-2in-vivolife cycle. The development of myeloid dysfunctions and the impairment of lymphoid arm establish a condition of immune paralysis that supports secondary bacteria and virus infection and can progress to “immune silence” in patients facing death.
Risk of fomite-mediated transmission of SARS-CoV-2 in child daycares, schools, and offices: a modeling study
Authors: Kraay Alicia N.M. , Hayashi Michael A. L. , Berendes David M. , Sobolik Julia S. , Leon Juan S. , Lopman Benjamin A. 
Published: August 2020

AbstractSARS-CoV-2 can persist on surfaces, suggesting that surface-based transmission might be important for this pathogen. We find that fomites may be a substantial source of risk, particularly in schools and child daycares. Combining surface cleaning and decontamination with strategies to reduce pathogen shedding on surfaces can help mitigate this risk.
Chemotactic Migration of Bacteria in Porous Media
Authors: Bhattacharjee T. , Amchin D. B. , Ott J. A. , Kratz F. , Datta S. S. 
Published: August 2020

AbstractChemotactic migration of bacteria—their ability to direct multicellular motion along chemical gradients—is central to processes in agriculture, the environment, and medicine. However, studies are typically performed in homogeneous media, despite the fact that many bacteria inhabit heterogeneous porous media such as soils, sediments, and biological gels. Here, we directly visualize the migration ofEscherichia colipopulations in 3D porous media. We find that pore-scale confinement is a strong regulator of chemotactic migration. Strikingly, cells use a different primary mechanism to direct their motion in confinement than in bulk liquid. Further, confinement markedly alters the dynamics and morphology of the migrating population—features that can be described by a continuum model, but only when standard motility parameters are substantially altered from their bulk liquid values. Our work thus provides a framework to predict and control the migration of bacteria, and active matter in general, in heterogeneous environments.Statement of SignificanceTypical studies of bacterial motility focus on cells in homogeneous media; however, many bacteria inhabit tight porous media such as soils, sediments, and biological gels. This paper demonstrates how confinement in a porous medium fundamentally alters the chemotactic migration ofEscherichia coli. We find that cells use a different primary mechanism to direct their motion in confinement than in bulk liquid. Further, confinement markedly alters the overall dynamics and morphology of a migrating population—features that can be described by a continuum model, but only when standard motility parameters are substantially altered from their bulk liquid values. This work thus provides a framework to predict and control the migration of bacteria, and active matter in general, in heterogeneous porous environments.
Autophagy is required for lipid homeostasis during dark-induced senescence in Arabidopsis
Authors: Barros Jessica A. S. , Magen Sahar , Lapidot-Cohen Taly , Rosental Leah , Brotman Yariv , Araújo Wagner L. , Avin-Wittenberg Tamar 
Published: August 2020

AbstractAutophagy is an evolutionarily conserved mechanism that mediates the degradation of cytoplasmic components in eukaryotic cells. In plants, autophagy has been extensively associated with the recycling of proteins during carbon starvation conditions. Even though lipids constitute a significant energy reserve, our understanding of the function of autophagy in the management of cell lipid reserves and components remains fragmented. To further investigate the significance of autophagy in lipid metabolism, we performed an extensive lipidomic characterization of Arabidopsis (Arabidopsis thaliana) autophagy mutants (atg) submitted to dark-induced senescence conditions. Our results revealed an altered lipid profile inatgmutants, suggesting that autophagy affects the homeostasis of multiple lipid components under dark-induced senescence. The acute degradation of chloroplast lipids coupled with the differential accumulation of triacylglycerols (TAGs) and plastoglobuli indicates an alternative metabolic reprogramming towards lipid storage inatgmutants. The imbalance of lipid metabolism compromises the production of cytosolic lipid droplets and the regulation of peroxisomal lipid oxidation pathways inatgmutants.One-sentence summaryAutophagy is required for the mobilization of membrane lipid components and lipid droplet dynamics during extended darkness inArabidopsis.
Endocast and bony labyrinth of a stem gnathostome shed light on the earliest diversification of jawed vertebrates
Authors: Zhu You-an , Giles Sam , Young Gavin , Hu Yuzhi , Bazzi Mohamad , Ahlberg Per E. , Zhu Min , Lu Jing 
Published: August 2020

AbstractOur understanding of the earliest evolution of jawed vertebrates depends on a credible phylogenetic assessment of the jawed stem gnathostomes collectively known as ‘placoderms’. However, their relationships, and even whether ‘placoderms’ represent a single radiation or a paraphyletic array, remain contentious. Here we describe the endocranial cavity and inner ear ofBrindabellaspis stensioi, commonly recovered as a taxon of uncertain affinity branching near the base of ‘placoderms’. While some features of its braincase and endocast resemble those of jawless vertebrates, its inner ear displays a repertoire of crown gnathostome characters. Both parsimony and Bayesian analyses suggest that established hypotheses of ‘placoderm’ relationships are unstable, with newly-revealed anatomy pointing to a potentially radical revision of early gnathostome evolution. Our results call into question the appropriateness of fusiform ‘placoderms’ as models of primitive gnathostome anatomy and raise questions of homology relating to key cranial features.One Sentence SummaryThe skull of a 400-million-year old fossil fish suggests that hypotheses of early jawed vertebrate relationships might have to be turned on their head.
Tutorial: Assessing metagenomics software with the CAMI benchmarking toolkit
Authors: Meyer Fernando , Lesker Till-Robin , Koslicki David , Fritz Adrian , Gurevich Alexey , Darling Aaron E. , Sczyrba Alexander , Bremges Andreas , McHardy Alice C. 
Published: August 2020

AbstractComputational methods are key in microbiome research, and obtaining a quantitative and unbiased performance estimate is important for method developers and applied researchers. For meaningful comparisons between methods, to identify best practices, common use cases, and to reduce overhead in benchmarking, it is necessary to have standardized data sets, procedures, and metrics for evaluation. In this tutorial, we describe emerging standards in computational metaomics benchmarking derived and agreed upon by a larger community of researchers. Specifically, we outline recent efforts by the Critical Assessment of Metagenome Interpretation (CAMI) initiative, which supplies method developers and applied researchers with exhaustive quantitative data about software performance in realistic scenarios and organizes community-driven benchmarking challenges. We explain the most relevant evaluation metrics to assess metagenome assembly, binning, and profiling results, and provide step-by-step instructions on how to generate them. The instructions use simulated mouse gut metagenome data released in preparation for the second round of CAMI challenges and showcase the use of a repository of tool results for CAMI data sets. This tutorial will serve as a reference to the community and facilitate informative and reproducible benchmarking in microbiome research.
Single-cell lineage and transcriptome reconstruction of metastatic cancer reveals selection of aggressive hybrid EMT states
Authors: Simeonov Kamen P , Byrns China N , Clark Megan L , Norgard Robert J , Martin Beth , Stanger Ben Z , McKenna Aaron , Shendure Jay , Lengner Christopher J 
Published: August 2020

AbstractMetastatic cancer remains largely incurable due to an incomplete understanding of how cancer cells disseminate throughout the body. However, tools for probing metastatic dissemination and associated molecular changes at high resolution are lacking. Here we present multiplexed, activatable, clonal, and subclonal GESTALT (macsGESTALT), an inducible lineage recorder with concurrent single cell readout of transcriptional and phylogenetic information. By integrating multiple copies of combined static barcodes and evolving CRISPR/Cas9 barcodes, macsGESTALT enables clonal tracing and subclonal phylogenetic reconstruction, respectively. High barcode editing and recovery rates produce deep lineage reconstructions, densely annotated with transcriptomic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we reconstruct dissemination of tens-of-thousands of single cancer cells representing 95 clones and over 6,000 unique subclones across multiple distant sites, e.g. liver and lung metastases. Transcriptionally, cells exist along a continuum of epithelial-to-mesenchymal transition (EMT)in vivowith graded changes in associated signaling, metabolic, and regulatory processes. Lineage analysis reveals that from a majority of non-metastatic, highly epithelial clones, a single dominant clone that has progressed along EMT drives the majority of metastasis. Within this dominant clone a parallel process occurs, where a small number of aggressive subclones drive clonal outgrowth. By precisely mapping subclones along the EMT continuum, we find that size and dissemination gradually increase, peaking at late-hybrid EMT states but precipitously falling once subclones are highly mesenchymal. Late-hybrid EMT states are selected from a predominately epithelial ancestral pool, enabling rapid metastasis but also forcing extensive and continuous population bottlenecking. Notably, late-hybrid gene signatures are associated with decreased survival in human pancreatic cancer, while epithelial, early-hybrid, and highly mesenchymal states are not. Our findings illuminate features of metastasis and EMT with the potential for therapeutic exploitation. Ultimately, macsGESTALT provides a powerful, accessible tool for probing cancer and stem cell biologyin vivo.
Integrative inference of transcriptional networks in Arabidopsis yields novel ROS signalling regulators
Authors: De Clercq Inge , Van de Velde Jan , Luo Xiaopeng , Liu Li , Storme Veronique , Van Bel Michiel , Pottie Robin , Vaneechoutte Dries , Breusegem Frank Van , Vandepoele Klaas 
Published: August 2020

ABSTRACTGene regulation is a dynamic process in which transcription factors (TFs) play an important role to control spatiotemporal gene expression. While gene regulatory networks describe the interactions between TFs and their target genes, our global knowledge about the complexity of TF control for different genes and biological processes is incomplete. To enhance our global understanding of regulatory interactions inArabidopsis thaliana, different regulatory input networks capturing complementary information about DNA motifs, open chromatin, TF binding and expression-based regulatory interactions, were combined using a supervised learning approach, resulting in an integrated gene regulatory network (iGRN) covering 1,491 TFs and 31,393 target genes (1.7 million interactions). This iGRN outperforms the different input networks to predict known regulatory interactions and has a similar performance to recover functional interactions compared to state-of-the-art experimental methods like yeast one-hybrid and ChIP-seq. The iGRN correctly inferred known functions for 681 TFs and predicted new gene functions for hundreds of unknown TFs. For regulators predicted to be involved in reactive oxygen species stress regulation, we confirmed in total 75% of TFs with a function in ROS and/or physiological stress responses. This includes 13 novel ROS regulators, previously not connected to any ROS or stress function, that were experimentally validated in our ROS-specific phenotypic assays of loss- or gain-of-function lines. In conclusion, the presented iGRN offers a high-quality starting point to enhance our understanding of gene regulation in plants by integrating different experimental data types at the network level.
Highly-parallel microfluidics-based force spectroscopy on single cytoskeletal motors
Authors: Urbanska Marta , Lüdecke Annemarie , Walter Wim J. , van Oijen Antoine M. , Duderstadt Karl E. , Diez Stefan 
Published: August 2020

AbstractCytoskeletal motors transform chemical energy into mechanical work to drive essential cellular functions. Optical trapping experiments have provided crucial insights into the operation of these molecular machines under load. However, the throughput of such force spectroscopy experiments is typically limited to one measurement at a time. Here, we introduce a highly-parallel, microfluidics-based method that allows for rapid collection of force-dependent motility parameters of cytoskeletal motors with two orders of magnitude improvement in throughput compared to currently available methods. We apply tunable hydrodynamic forces to stepping kinesin-1 motors via DNA-tethered beads and utilize a large field of view to simultaneously track the velocities, run lengths and interaction times of hundreds of individual kinesin-1 molecules under varying resisting and assisting loads. Importantly, the 16-μm long DNA tethers between the motors and the beads significantly reduces the vertical component of the applied force pulling the motors away from the microtubule. Our approach is readily applicable to other molecular systems and constitutes a new methodology for parallelized single-molecule force studies on cytoskeletal motors.
A flexible Bayesian framework for unbiased estimation of timescales
Authors: Zeraati Roxana , Engel Tatiana A. , Levina Anna 
Published: August 2020

AbstractTimescales characterize the pace of change for many dynamic processes in nature. Timescales are usually estimated by fitting the exponential decay of data autocorrelation in the time or frequency domain. We show that this standard procedure often fails to recover the correct timescales due to a statistical bias arising from the finite sample size. We develop an alternative approach to estimating timescales by fitting the sample autocorrelation or power spectrum with a generative model based on a mixture of Ornstein-Uhlenbeck processes using adaptive Approximate Bayesian Computations. Our method accounts for finite sample size and noise in data and returns a posterior distribution of timescales that quantifies the estimation uncertainty and can be used for model selection. We demonstrate the accuracy of our method on synthetic data and illustrate its application to recordings from the primate cortex. We provide a customizable Python package implementing our framework with different generative models suitable for diverse applications.
Humans can visually judge grasp quality and refine their judgments through visual and haptic feedback
Authors: Maiello Guido , Schepko Marcel , Klein Lina K. , Paulun Vivian C. , Fleming Roland W. 
Published: August 2020

AbstractHow humans visually select where to grasp objects is determined by the physical object properties (e.g., size, shape, weight), the degrees of freedom of the arm and hand, as well as the task to be performed. We recently demonstrated that human grasps are near-optimal with respect to a weighted combination of different cost functions that make grasps uncomfortable, unstable or impossible e.g., due to unnatural grasp apertures or large torques. Here, we ask whether humans can consciously access these rules. We test if humans can explicitly judge grasp quality derived from rules regarding grasp size, orientation, torque, and visibility. More specifically, we test if grasp quality can be inferred (i) by using motor imagery alone, (ii) from watching grasps executed by others, and (iii) through performing grasps, i.e. receiving visual, proprioceptive and haptic feedback. Stimuli were novel objects made of 10 cubes of brass and wood (side length 2.5 cm) in various configurations. On each object, one near-optimal and one sub-optimal grasp were selected based on one cost function (e.g. torque), while the other constraints (grasp size, orientation, and visibility) were kept approximately constant or counterbalanced. Participants were visually cued to the location of the selected grasps on each object and verbally reported which of the two grasps was best. Across three experiments, participants could either (i) passively view the static objects, (ii) passively view videos of other participants grasping the objects, or (iii) actively grasp the objects themselves. Our results show that participants could already judge grasp optimality from simply viewing the objects, but were significantly better in the video and grasping session. These findings suggest that humans can determine grasp quality even without performing the grasp—perhaps through motor imagery—and can further refine their understanding of how to correctly grasp an object through sensorimotor feedback but also by passively viewing others grasp objects.