bluuebunny/crossref_metadata_2025_split huggingface dataset:
OncoLoop: A network-based precision cancer medicine framework
Authors: Vasciaveo Alessandro , Zou Min , Arriaga Juan Martín , de Almeida Francisca Nunes , Douglass Eugene F. , Shibata Maho , Rodriguez-Calero Antonio , de Brot Simone , Mitrofanova Antonina , Chua Chee Wai , Karan Charles , Realubit Ron , Pampou Sergey , Kim Jaime Y. , Corey Eva , Alvarez Mariano J. , Rubin Mark A. , Shen Michael M. , Califano Andrea , Abate-Shen Cory 
Published: February 2022

AbstractAt present, prioritizing cancer treatments at the individual patient level remains challenging, and performing co-clinical studies using patient-derived models in real-time is often not feasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict and validate drug sensitivity in human tumors and their pre-existing high-fidelity (cognate) model(s) by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer (PCa) using a series of genetically-engineered mouse models (GEMMs) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of published cohorts using Master Regulator (MR) conservation analysis revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one cognate patient-derived xenograft (PDX). OncoLoop is a highly generalizable framework that can be extended to other cancers and potentially other diseases.Significance StatementOncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround co-clinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available.
Improved Predictions of MHC-Peptide Binding using Protein Language Models
Authors: Hashemi Nasser , Hao Boran , Ignatov Mikhail , Paschalidis Ioannis , Vakili Pirooz , Vajda Sandor , Kozakov Dima 
Published: February 2022

AbstractMajor histocompatibility complex (MHC) molecules bind to peptides from exogenous antigens, and present them on the surface of cells, allowing the immune system (T cells) to detect them. Elucidating the process of this presentation is essential for regulation and potential manipulation of the cellular immune system [1]. Predicting whether a given peptide will bind to the MHC is an important step in the above process, motivating the introduction of many computational approaches. NetMHCPan [2], a pan-specific model predicting binding of peptides to any MHC molecule, is one of the most widely used methods which focuses on solving this binary classification problem using a shallow neural network. The successful results of AI methods, especially Natural Language Processing (NLP-based) pretrained models in various applications including protein structure determination, motivated us to explore their use in this problem as well. Specifically, we considered fine-tuning these large deep learning models using as dataset the peptide-MHC sequences. Using standard metrics in this area, and the same training and test sets, we show that our model outperforms NetMHCpan4.1 which has been shown to outperform all other earlier methods [2].
Spatiotemporal mapping of the neural markers of prediction error processing across multisensory and unisensory modalities
Authors: Ghosh Priyanka , Talwar Siddharth , Banerjee Arpan 
Published: February 2022

ABSTRACTPrediction errors in the brain are indexed by two event-related potentials – MMN and P300, which are elicited upon violation of regularity in the occurrence of repetitive stimuli. While MMN reflects the brain’s ability to perform automatic comparisons between consecutive stimuli and provides an electrophysiological index of sensory error detection, P300 is associated with cognitive processes such as update in working memory. Till date, there has been extensive research on the roles of MMN and P300 individually, because of their potential to be used as clinical markers of consciousness and attention, respectively. However, the relationship between these two ERPs, specifically in terms of their underlying cortical generators, in context of prediction error propagation along the hierarchical brain across multiple modalities is an open question. Our objective in this article is two-fold. First, we reconfirm previous reports regarding the generators of MMN and P300 in sensor space through source-space analysis using an accurate individual subject level co-registration of MRI and EEG data collected from healthy humans. We demonstrate that in multisensory environments, MMN and P300 markers represent “modality-specific” and “modality-independent” information processing, respectively. Advancing an earlier understanding that multisensory contexts speed upearly sensory processing, our study reveals that this temporal facilitation extends to even the later components ofprediction error processing, using custom-designed experiments that allow comparisons across different modality combinations. Such knowledge can be of immense value in clinical research for determining the stages of various treatments in aging, schizophrenia and depression, and their efficacy on cognitive function.
Alpha-Amylase increases predict a freezing-like response and cortical alpha oscillations
Authors: Luther Lisa , Jensen Ole , Hagenaars Muriel A. 
Published: February 2022

AbstractIndividual differences in the reactivity of the sympathetic nervous system in response to stressful situations are thought to be an important predictor for psychological well-being and the focus of current scientific investigations. Here, we explored whether increased sympathetic nervous activity (SNA) was associated with reduced alpha power and with increased freezing-like behaviour (i.e., body sway) while watching threatening stimuli, reflecting enhanced attention. Salivary alpha-amylase (sAA) was used as a proxy for sympathetic nervous activity, which is elevated in stressful situations. A passive viewing task with affective pictures (unpleasant, neutral, pleasant) was carried out, and pre- and post- task sAA samples were taken. Oscillatory brain activity in the EEG and body sway were assessed simultaneously during the task. The results point to an increase in sAA being associated with reduced alpha power decrease to the unpleasant compared to the neutral pictures as well as increased freezing-like behaviour (i.e., reduction in body sway for unpleasant versus neutral pictures). It appears that an increase in SNA is linked to less attentional valence differentiation. Furthermore, our study corroborates findings from the animal literature in that the SNA increase is linked to a freezing-like response.
pkgndep: a tool for heaviness analysis on R package dependencies
Authors: Gu Zuguang , Hübschmann Daniel 
Published: February 2022

AbstractSummaryNumerous R packages have been developed for bioinformatics analysis in the last decade and dependencies among packages have become critical issues to consider. In this work, we proposed a new metric named dependency heaviness that measures the number of unique dependencies that a parent brings to a package, and we proposed possible solutions for reducing the complexity of dependencies by optimizing the use of heavy parents. We implemented the metric in a new R package pkgndep which provides an intuitive way for dependency heaviness analysis. Based on pkgndep, we additionally performed a global analysis of dependency heaviness on CRAN and Bioconductor ecosystems and we revealed top packages that have significant contributions of high dependency heaviness to their child packages.Availability and implementationThe package pkgndep and documentations are freely available from the Comprehensive R Archive Network (CRAN) https://cran.r-project.org/package=pkgndep. The dependency heaviness analysis for all 21,741 CRAN and Bioconductor packages retrieved on 2021-10-28 are available at https://pkgndep.github.io/.
Proprioceptive and visual feedback responses in macaques exploit goal redundancy
Authors: Cross Kevin P. , Guang Hui , Scott Stephen H. 
Published: February 2022

AbstractA common problem in motor control concerns how to generate patterns of muscle activity when there are redundant solutions to attain a behavioural goal. Optimal feedback control is a theory that has guided many behavioural studies exploring how the motor system incorporates task redundancy. This theory predicts that kinematic errors that deviate the limb should not be corrected if one can still attain the behavioural goal. Several studies in humans demonstrate that the motor system can flexibly integrate visual and proprioceptive feedback of the limb with goal redundancy within 90ms and 70ms, respectively. Here we show monkeys (Macaca mulatta) demonstrate similar abilities to exploit goal redundancy. We trained four male monkeys to reach for a goal that was either a narrow square or a wide, spatially redundant rectangle. Monkeys exhibited greater trial-by-trial variability when reaching to the wide goal consistent with exploiting goal redundancy. On random trials we jumped the visual feedback of the hand and found monkeys corrected for the jump when reaching to the narrow goal and largely ignored the jump when reaching for the wide goal. In a separate set of experiments, we applied mechanical loads to the monkey’s arm and found similar corrective responses based on goal shape. Muscle activity reflecting these different corrective responses were detected for the visual and mechanical perturbations starting at ∼90 and ∼70ms, respectively. Thus, rapid motor responses in macaques can exploit goal redundancy similar to humans, creating a paradigm to study the neural basis of goal-directed motor action and motor redundancy.
Navigation of Ultrasound-controlled Swarmbots under Physiological Flow Conditions
Authors: Fonseca Alexia D.C. , Kohler Tobias , Ahmed Daniel 
Published: February 2022

AbstractNavigation of microrobots in living vasculatures is essential in realizing targeted drug delivery and advancing non-invasive surgeries. We developed acoustically-controlled “swarmbots” based on the self-assembly of clinically-approved microbubbles. Ultrasound is noninvasive, penetrates deeply into the human body, and is well-developed in clinical settings. Our propulsion strategy relies in two forces: the primary radiation force and secondary Bjerknes force. Upon ultrasound activation, the microbubbles self-assemble into microswarms, which migrate towards and anchor at the containing vessel’s wall. A second transducer, which produces an acoustic field parallel to the channel, propels the swarms along the wall. We demonstrated cross- and upstream navigation of the swarmbots at 3.27 mm/s and 0.53 mm/s, respectively, against physiologically-relevant flow rates of 4.2 – 16.7 cm/s. Additionally, we showed swarm controlled manipulation within mice blood and under pulsatile flow conditions of 100 beats per minute. This capability represents a much-needed pathway for advancing preclinical research.TeaserNavigation of ultrasound-guided microrobots inside artificial blood vessels overcoming physiological conditions, including high flow rates, pulsatile flow regimes, and high cell concentrations of blood.
Selection of Synthetic Proteins to Modulate the Human Frataxin Function
Authors: Pignataro María Florencia , Herrera María Georgina , Fernández Natalia , Aran Martín , Bataglini Fernando , Santos Javier 
Published: February 2022

ABSTRACTFrataxin is a kinetic activator of the mitochondrial supercomplex for iron–sulfur cluster assembly. Low frataxin expression or a decrease in its functionality results in Friedreich’s Ataxia (FRDA). With the aim of creating new molecular tools to study this metabolic pathway, and ultimately, to explore new therapeutic strategies, we have investigated the possibility of obtaining small proteins exhibiting a high affinity for frataxin. In this study, we applied the ribosome display approach, using human frataxin as the target. We focused on Affi_224, one of the proteins that we were able to select after five selection rounds. We have studied the interaction between both proteins and discussed some applications of this specific molecular tutor, concerning the modulation of supercomplex activity. Affi_224 and frataxin showed a KD value in the nanomolar range, as judged by surface plasmon resonance analysis. Most likely, it binds to the frataxin acidic ridge, as suggested by the analysis of chemical shift perturbations (NMR) and computational simulations. Affi_224 was able to increase Cys NFS1 desulfurase activation exerted by the FRDA frataxin variant G130V. Our results suggest quaternary addition may be a new tool to modulate frataxin function in vivo. Nevertheless, more functional experiments under physiological conditions should be carried out to evaluate Affi_224 effectiveness in FRDA cell models.
Computer vision for assessing species color pattern variation from web-based community science images
Authors: Hantak Maggie M. , Guralnick Robert P. , Zare Alina , Stucky Brian J. 
Published: February 2022

SummaryOpenly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a workflow and computer vision model for automatically categorizing species color pattern from community science images. Our work is focused on documenting the striped/unstriped color polymorphism in the Eastern Red-backed Salamander (Plethodon cinereus). We used an ensemble convolutional neural network model to analyze this polymorphism in 20,318 iNaturalist images. Our model was highly accurate (∼98%) despite image heterogeneity. We used the resulting annotations to document extensive niche overlap between morphs, but wider niche breadth for striped morphs at the range-wide scale. Our work showcases key design principles for using machine learning with heterogeneous community science image data to address questions at an unprecedented scale.
Patterns of item nonresponse behavior to survey questionnaires are systematic and have a genetic basis
Authors: Mignogna Gianmarco , Carey Caitlin E. , Wedow Robbee , Baya Nikolas , Cordioli Mattia , Pirastu Nicola , Bellocco Rino , Nivard Michel G. , Neale Benjamin M. , Walters Raymond K. , Ganna Andrea 
Published: February 2022

ABSTRACTResponse to survey questionnaires is vital for social and behavioral research, and most analyses assume full and accurate response by survey participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behavior across 109 questionnaire items from the UK Biobank (UKB) (N=360,628). Phenotypic factor scores for two participant-selected nonresponse answers, “Prefer not to answer” (PNA) and “I don’t know” (IDK), each predicted participant nonresponse in follow-up surveys, controlling for education and self-reported general health. We performed genome-wide association studies on these factors and identified 39 genome-wide significant loci, and further validated these effects with polygenic scores in an independent study (N=3,414), gaining information that we could not have had from phenotypic data alone. PNA and IDK were highly genetically correlated with one another and with education, health, and income, although unique genetic effects were also observed for both PNA and IDK. We discuss how these effects may bias studies of traits correlated with nonresponse and how genetic analyses can further enhance our understanding of nonresponse behaviors in survey research, for instance by helping to correct for nonresponse bias.
Bacterial outer-membrane polysaccharide export (OPX) proteins occupy three structural classes with selective β-barrel porin requirements for polymer secretion
Authors: Saïdi Fares , Mahanta Utkarsha , Panda Adyasha , Jolivet Nicolas Y. , Bitazar Razieh , John Gavin , Martinez Matthew , Mellouk Abdelkader , Calmettes Charles , Chang Yi-Wei , Sharma Gaurav , Islam Salim T. 
Published: February 2022

ABSTRACTSecretion of high-molecular-weight polysaccharides across the bacterial envelope is ubiquitous as it enhances prokaryotic survival in (a)biotic settings. Such polymers are often assembled by Wzx/Wzy- or ABC transporter-dependent schemes that implicate outer-membrane (OM) polysaccharide export (OPX) proteins in polymer translocation to the cell surface. In the social predatory bacterium Myxococcus xanthus, exopolysaccharide (EPS)-pathway WzaX, major spore coat (MASC)-pathway WzaS, and biosurfactant polysaccharide-pathway WzaB were herein found to be truncated OPX homologues of Escherichia coli Wza lacking OM-spanning α-helices. Comparative genomics across all bacteria, complemented with cryo-electron tomography cell- envelope analyses, revealed WzaX/S/B architecture to be the most common amongst three defined OPX-protein structural classes independent of periplasmic thickness. Fold-recognition and deep- learning analyses revealed the conserved M. xanthus proteins MXAN_7418/3226/1916 (encoded adjacent to WzaX/S/B) to be integral OM β-barrels, with structural homology to the poly-N-acetyl-D- glucosamine synthase-dependent pathway porin PgaA. Such porins were identified in bacteria near numerous genes for all three OPX-protein classes. Interior MXAN_7418/3226/1916 β-barrel electrostatics were found to match known properties of their associated polymers. With MXAN_3226 essential for MASC export, and MXAN_7418 absence shown herein to compromise EPS translocation, these data support a novel secretion paradigm for Wzx/Wzy-dependent pathways in which those containing an OPX component that cannot span the OM instead utilize a β-barrel porin to mediate polysaccharide transport across the OM.
Genomic characterization of a wild-like tomato accession from Arizona
Authors: Barnett Jacob , Buonauro Gina , Kuipers April , Sapkota Manoj , van der Knaap Esther , Razifard Hamid 
Published: February 2022

AbstractTomato domestication history has been revealed to be a highly complex story. A major contributor to this complexity is an evolutionary intermediate group (Solanum lycopersicum var. cerasiforme (Alef.) Voss; SLC) between the cultivated tomato (Solanum lycopersicum var. lycopersicum L.; SLL) and its wild relative (Solanum pimpinellifolium L.; SP). SLC includes accessions with a broad spectrum of genomic and phenotypic characteristics. Some of the SLC accessions were previously hypothesized to be spreading northward from South America into Mesoamerica and that migration probably entailed reversal to wild-like phenotypes such as smaller fruits. Prior to this study, the northernmost confirmed extension of the SLC was limited to northern Mexico.In this study, we employed genomic methods to investigate the origin of a wild-like tomato found in a garden in Scottsdale Arizona, USA. The so-called “Arizona tomato” featured a vigorous growth habit and carried small fruits weighing 2-3 grams. Our phylogenomic analyses revealed the identity of the Arizona tomato as a member of the Mexican SLC population (SLC MEX). To our knowledge, this is the first report of an SLC accession, confirmed using genomics, growing spontaneously in Arizona. This finding could have implications for conservation biology as well as agriculture.
A critique of common methods for comparing the scaling of vertical force production in flying insects
Authors: Burnett Nicholas P. , Keliher Emily , Combes Stacey A. 
Published: February 2022

AbstractMaximum vertical force production (Fvert) is an integral measure of flight performance that generally scales with size. Numerous methods of measuring Fvert and body size exist, but few studies have compared how these methods affect the conclusions of scaling analyses. We compared two common techniques for measuring Fvert in bumblebees (Bombus impatiens) and mason bees (Osmia lignaria), and examined Fvert scaling using five size metrics. Fvert results were similar with incremental or asymptotic load-lifting, but scaling analyses were sensitive to the size metric used. Analyses based on some size metrics indicated similar scaling exponents and coefficients between species, whereas other metrics indicated different coefficients. Furthermore, Fvert showed isometry with body lengths and fed and starved masses, but negative allometry with dry mass. We conclude that Fvert can be measured using either incremental or asymptotic loading but choosing a size metric for scaling studies requires careful consideration.
Comparative single-cell transcriptional atlases ofBabesiaspecies reveal conserved and species-specific expression profiles
Authors: Rezvani Yasaman , Keroack Caroline D , Elsworth Brendan , Arriojas Argenis , Gubbels Marc-Jan , Duraisingh Manoj T , Zarringhalam Kourosh 
Published: February 2022

ABSTRACTBabesiais a genus of Apicomplexan parasites that infect red blood cells in vertebrate hosts. Pathology occurs during rapid replication cycles in the asexual blood-stage of infection. Current knowledge ofBabesiareplication cycle progression and regulation is limited and relies mostly on comparative studies with related parasites. Due to limitations in synchronizingBabesiaparasites, fine-scale time-course transcriptomic resources are not readily available. Single-cell transcriptomics provides a powerful unbiased alternative for profiling asynchronous cell populations. Here, we applied single-cell RNA sequencing to threeBabesiaspecies (B. divergens, B. bovis, andB. bigemina). We used analytical approaches and algorithms to map the replication cycle and construct pseudo-synchronized time-course gene expression profiles. We identify clusters of co-expressed genes showingjust-in-timeexpression profiles, with gradually cascading peaks throughout asexual development. Moreover, clustering analysis of reconstructed gene curves reveals coordinated timing of peak expression in epigenetic markers and transcription factors. Using a regularized Gaussian Graphical Model, we reconstructed co-expression networks and identified conserved and species-specific nodes. Motif analysis of a co-expression interactome of AP2 transcription factors identified specific motifs previously reported to play a role in DNA replication inPlasmodiumspecies. Finally, we present an interactive web-application to visualize and interactively explore the datasets.
Synthetic memory circuits for programmable cell reconfiguration in plants
Authors: Lloyd James P B , Ly Florence , Gong Patrick , Pflüger Jahnvi , Swain Tessa , Pflüger Christian , Khan Muhammad Adil , Kidd Brendan , Lister Ryan 
Published: February 2022

AbstractPlant biotechnology predominantly relies on a restricted set of genetic parts with limited capability to customize spatiotemporal and conditional expression patterns. Synthetic gene circuits have the ability to integrate multiple customizable input signals through a processing unit constructed from biological parts, to produce a predictable and programmable output. Here, we present a suite of functional recombinase-based gene circuits for use in plants. We first established a range of key gene circuit components compatible with plant cell functionality. We then used these to develop a range of operational logic gates using the identify function (activation) and negation function (repression) in Arabidopsis protoplasts and in vivo, demonstrating their utility for programmable manipulation of transcriptional activity in a complex multicellular organism. Through utilization of genetic recombination these circuits create stable long-term changes in expression and recording of past stimuli. This highly-compact programmable gene circuit platform provides new capabilities for engineering sophisticated transcriptional programs and previously unrealised traits into plants.