bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gradient-k: Improving the Performance of K-Means Using the Density Gradient
Authors: Ciuparu Andrei , Mureșan Raul C. 
Published: April 2022

AbstractWe introduce Gradient-k, an upgrade of the k-means algorithm that improves clustering accuracy and reduces the number of iterations required for convergence. This is achieved by correcting the distance used in the k-means algorithm by a factor based on the angle between the density gradient and the direction to the cluster center. We show that this correction allows the algorithm to go beyond the traditional tessellation obtained by k-means, enabling the creation of nonlinear separation boundaries. The correction also provides the ability to distinguish clusters having non-normal shapes and of varying densities. Furthermore, Gradient-k has a lower computational complexity for datasets with many samples. We compare the performance of Gradient-k with that of k-means and of DBSCAN on several benchmark datasets, as well as on a more realistic dataset in the context of neural spike sorting.
Performance and limitations of linkage-disequilibrium-based methods for inferring the genomic landscape of recombination and detecting hotspots: a simulation study
Authors: Raynaud Marie , Gagnaire Pierre-Alexandre , Galtier Nicolas 
Published: April 2022

AbstractKnowledge of recombination rate variation along the genome provides important insights into genome and phenotypic evolution. Population genomic approaches offer an attractive way to infer the population-scaled recombination rate ρ=4Nerusing the linkage disequilibrium information contained in DNA sequence polymorphism data. Such methods have been used in a broad range of plant and animal species to build genome-wide recombination maps. However, the reliability of these inferences has only been assessed under a restrictive set of conditions. Here, we evaluate the ability of one of the most widely used coalescent-based programs,LDhelmet, to infer a genomic landscape of recombination with the biological characteristics of a human-like landscape including hotspots. Using simulations, we specifically assessed the impact of methodological (sample size, phasing errors, block penalty) and evolutionary parameters (effective population size (Ne), demographic history, mutation to recombination rate ratio) on inferred map quality. We report reasonably good correlations between simulated and inferred landscapes, but point to limitations when it comes to detecting recombination hotspots. False positive and false negative hotspots considerably confound fine-scale patterns of inferred recombination under a wide range of conditions, particularly whenNeis small and the mutation/recombination rate ratio is low, to the extent that maps inferred from populations sharing the same recombination landscape appear uncorrelated. We thus address a message of caution for the users of these approaches, at least for genomes with complex recombination landscapes such as in humans.
The dynamical Matryoshka model: 2. Modeling of local lipid dynamics at the sub-nanosecond timescale in phospholipid membranes
Authors: Cisse Aline , Matsuo Tatsuhito , Plazanet Marie , Natali Francesca , Koza Michael Marek , Ollivier Jacques , Bicout Dominique J. , Peters Judith 
Published: April 2022

AbstractBiological membranes are generally formed by lipids and proteins. Often, the membrane properties are studied through model membranes formed by phospholipids only. They are molecules composed by a hydrophilic head group and hydrophobic tails, which can present a panoply of various motions, including small localized movements of a few atoms up to the diffusion of the whole lipid or collective motions of many of them. In the past, efforts were made to measure these motions experimentally by incoherent neutron scattering and to quantify them, but with upcoming modern neutron sources and instruments, such models can now be improved. In the present work, we expose a quantitative and exhaustive study of lipid dynamics on DMPC and DMPG membranes, using the Matryoshka model recently developed by our group. The model is confronted here to experimental data collected on two different membrane samples, at three temperatures and two instruments. Despite such complexity, the model describes reliably the data and permits to extract a series of parameters. The results compare also very well to other values found in the literature.Abstract FigureFigure 1:Graphical abstract.Highlights- The Matryoshka model brings a new general description of local lipid dynamics.- Phospholipid membranes on various conditions are compared in this novel framework.- Effects of main phase transition, membrane geometry or motion direction are probed.- Despite high number of parameters, overfitting is avoided by a global fit strategy.
Fear memory in humans is consolidated over time independent of sleep
Authors: Pavlov Yuri G. , Pavlova Nadezhda V. , Diekelmann Susanne , Kotchoubey Boris 
Published: April 2022

AbstractFear memories can be altered after acquisition by processes such as fear memory consolidation or fear extinction, even without further exposure to the fear-eliciting stimuli, but factors contributing to these processes are not well understood. Sleep is known to consolidate, strengthen and change newly acquired declarative and procedural memories. However, evidence on the role of time and sleep in the consolidation of fear memories is inconclusive. Here, we used highly sensitive electrophysiological measures to examine the development of fear-conditioned responses over time and sleep in humans. We assessed event-related brain potentials (ERP) in 18 healthy young individuals during fear conditioning before and after a 2-hour afternoon nap or a corresponding wake interval in a counterbalanced within-subject design. The procedure involved pairing a neutral tone (CS+) with a highly unpleasant sound (US). As a control, another neutral tone (CS-) was paired with a neutral sound. Fear responses were examined before the interval during a habituation phase and an acquisition phase as well as after the interval during an extinction phase and a re-acquisition phase. Differential fear conditioning during acquisition was evidenced by a more negative slow ERP component (stimulus-preceding negativity) developing before the unconditioned stimulus (loud noise). This differential fear response was even stronger after the interval during re-acquisition compared to initial acquisition, but this effect was similarly pronounced after sleep and wakefulness. These findings suggest that fear memories are consolidated over time, with this effect being independent of intervening sleep.
Painters in chromatin: a unified quantitative framework to systematically characterize epigenome regulation and memory
Authors: Abdulla Amith Z. , Vaillant Cédric , Jost Daniel 
Published: April 2022

AbstractIn eukaryotes, many stable and heritable phenotypes arise from the same DNA sequence, owing to epigenetic regulatory mechanisms relying on the molecular cooperativity of “reader-writer” enzymes. In this work, we focus on the fundamental, generic mechanisms behind the epigenome memory encoded by post-translational modifications of histone tails. Based on experimental knowledge, we introduce a unified modeling framework, the painter model, describing the mechanistic interplay between sequence-specific recruitment of chromatin regulators, chromatin-state-specific reader-writer processes and long-range spreading mechanisms. A systematic analysis of the model building blocks highlights the crucial impact of tridimensional chromatin organization and state-specific recruitment of enzymes on the stability of epigenomic domains and on gene expression. In particular, we show that enhanced 3D compaction of the genome and enzyme limitation facilitate the formation of ultra-stable, confined chromatin domains. The model also captures how chromatin state dynamics impact the intrinsic transcriptional properties of the region, slower kinetics leading to noisier expression. We finally apply our framework to analyze experimental data, from the propagation of γH2AX around DNA breaks in human cells to the maintenance of heterochromatin in fission yeast, illustrating how the painter model can be used to extract quantitative information on epigenomic molecular processes.
Plant-invertebrate interactions across a forested retrogressive chronosequence
Authors: Kempel Anne , Allan Eric , Gossner Martin M. , Jochum Malte , Wardle David A. 
Published: April 2022

AbstractIn the long-term absence of disturbance, ecosystems often enter a decline or retrogressive phase which leads to reductions in primary productivity, plant biomass, nutrient cycling and foliar quality. However, the consequences of ecosystem retrogression for higher trophic levels such as herbivores and predators, are less clear. Using a post-fire forested island-chronosequence across which retrogression occurs, we show that nutrient availability strongly controls invertebrate herbivore biomass when predators are few, but that there is a switch from bottom-up to top-down control when predators are common. This trophic flip in herbivore control probably arises because invertebrate predators respond to alternative energy channels from the adjacent aquatic matrix, which were independent of plant biomass. Our results suggest that effects of nutrient limitation, following ecosystem retrogression, on trophic cascades are modified by independent variation in predator abundance, which requires a more holistic approach to trophic ecology to better understand herbivore effects on plant communities.
Cross-neutralization of Omicron BA.1 against BA.2 and BA.3 SARS-CoV-2
Authors: Zou Jing , Kurhade Chaitanya , Xia Hongjie , Liu Mingru , Xie Xuping , Ren Ping , Shi Pei-Yong 
Published: April 2022

AbstractThe Omicron SARS-CoV-2 has three distinct sublineages, among which sublineage BA.1 is responsible for the initial Omicron surge and is now being replaced by BA.2 world-wide, whereas BA.3 is currently at a low frequency. The ongoing BA.1-to-BA.2 replacement underscores the importance to understand the cross-neutralization among the three Omicron sublineages. Here we tested the neutralization of BA.1-infected human sera against BA.2, BA.3, and USA/WA1-2020 (a strain isolated in late January 2020). The BA.1-infected sera neutralized BA.1, BA.2, BA.3, and USA/WA1-2020 SARS-CoV-2s with geometric mean titers (GMTs) of 445, 107, 102, and 16, respectively. Thus, the neutralizing GMTs against heterologous BA.2, BA.3, and USA/WA1-2020 were 4.2-, 4.4-, and 28.4-fold lower than the GMT against homologous BA.1, respectively. These findings have implications in COVID-19 vaccine strategy.
The dynamical Matryoshka model: 3. Diffusive nature of the atomic motions contained in a new dynamical model for deciphering local lipid dynamics
Authors: Matsuo Tatsuhito , Cisse Aline , Plazanet Marie , Natali Francesca , Koza Michael Marek , Ollivier Jacques , Bicout Dominique J. , Peters Judith 
Published: April 2022

AbstractIn accompanying papers [Bicout et al., BBA – Biomembr. Submitted; Cissé et al., BBA – Biomembr. Submitted], a new model called Matryoshka model has been proposed to describe the geometry of atomic motions in phospholipid molecules in bilayers and multilamellar vesicles based on their quasielastic neutron scattering (QENS) spectra. Here, in order to characterize the relaxational aspects of this model, the energy widths of the QENS spectra of the samples were analyzed first in a model-free way. The spectra were decomposed into three Lorentzian functions, which are classified as slow, intermediate, and fast motions depending on their widths. The analysis provides the diffusion coefficients, residence times, and geometrical parameters for the three classes of motions. The results corroborate the parameter values such as the amplitudes and the mobile fractions of atomic motions obtained by the application of the Matryoshka model to the same samples. Since the current analysis was carried out independently of the development of the Matryoshka model, the present results enhance the validity of the model. The model will serve as a powerful tool to decipher the dynamics of lipid molecules not only in model systems, but also in more complex systems such as mixtures of different kinds of lipids or natural cell membranes.
Computational design of dynamic receptor—peptide signaling complexes applied to chemotaxis
Authors: Jefferson RE , Oggier A , Füglistaler A , Camviel N , Hijazi M , Rico Villarreal A , Arber C , Barth P 
Published: April 2022

AbstractEngineering protein biosensors that sensitively respond to specific biomolecules by triggering precise cellular responses is a major goal of diagnostics and synthetic cell biology. Previous biosensor designs have largely relied on binding structurally well-defined molecules. In contrast, approaches that couple the sensing of flexible compounds to intended cellular responses would greatly expand potential biosensor applications. Here, to address these challenges, we develop a computational strategy for designing signaling complexes between conformationally dynamic proteins and peptides. To demonstrate the power of the approach, we create ultrasensitive chemotactic receptor—peptide pairs capable of eliciting potent signaling responses and strong chemotaxis in primary human T cells. Unlike traditional approaches that engineer static binding complexes, our dynamic structure design strategy optimizes contacts with multiple binding and allosteric sites accessible through dynamic conformational ensembles to achieve unprecedented signaling efficacy and potency. Our study suggests that a conformationally adaptable binding interface coupled to a robust allosteric transmission region is a key evolutionary determinant of peptidergic GPCR signaling systems. The approach lays a foundation for designing peptide-sensing receptors and signaling peptide ligands for basic and therapeutic applications.
Mathematical modeling to guide experimental design: T cell clustering as a case study
Authors: Rajakaruna Harshana , Ganusov Vitaly V. 
Published: April 2022

AbstractMathematical modeling provides a rigorous way to quantify immunological processes and to discriminate between alternative mechanisms driving specific biological phenomena. It is typical that mathematical models of immunological phenomena are developed by modellers to explain specific sets of experimental data after the data have been collected by experimental collaborators. Whether the available data are sufficient to accurately estimate model parameters or to discriminate between alternative models is not typically investigated. While previously collected data may be sufficient to guide development of alternative models and help estimating model parameters, such data often do not allow to discriminate between alternative models. As a case study we develop a series of power analyses to determine optimal sample sizes that allow for accurate estimation of model parameters and for discrimination between alternative models describing clustering of T cells around Plasmodium liver stages. In our typical experiments, mice are infected intravenously with Plasmodium sporozoites that invade hepatocytes (liver cells), and then activated CD8 T cells are transferred into the infected mice. The number of T cells found in the vicinity of individual infected hepatocytes at different times after T cell transfer is counted using intravital microscopy. We previously developed a series of mathematical models aimed to explain highly variable number of T cells per parasite; one of such model, the density-dependent recruitment (DDR) model, fitted the data from preliminary experiments better than the alternative models, such as the density-independent exit (DIE) model. Here we show that the ability to discriminate between these alternative models depends on the number of parasites imaged in the analysis; analysis of about n = 50 parasites at 2, 4, and 8 hours after T cell transfer will allow for over 95% probability to select the correct model. The type of data collected also has an impact; following T cell clustering around individual parasites over time (called as longitudinal (LT) data) allows for a more precise and less biased estimates of the parameters of the DDR model than that generated from a more traditional way of imaging individual parasites in different liver areas/mice (cross-sectional (CS) data). However, LT imaging comes at a cost of a need to keep the mice alive under the microscope for hours which may be ethically unacceptable. We finally show that the number of time points at which the measurements are taken also impacts the precision of estimation of DDR model parameters; in particular, measuring T cell clustering at one time point does not allow accurately estimating all parameters of the DDR model. Using our case study, we propose a general framework on how mathematical modeling can be used to guide experimental designs and power analyses of complex biological processes.
Improved Centromere Assemblies for RefGen_v4
Authors: Laspisa Daniel J. , Schneider Kevin L. , Presting Gernot G. 
Published: April 2022

AbstractGenome assemblies based on long read sequencing technology have revolutionized the assembly of repeat-rich centromere regions. However, because maize centromeres are highly enriched for the tandem repeat CentC and centromeric retrotransposons (CR), automated genome assembly left gaps even in the excellent B73 RefGen_v4 reference genome constructed from long-read data. Manual editing of >140 Mb spanning the ten centromeres of maize inbred B73 resulted in the closure of 127 sequence gaps and the addition of >8.4 Mb of previously unanchored sequence (unitigs and reads) containing 24 genes, 2 Mb of CR repeat and 887 kb of CentC without including any additional sequence data. The functional centromeres of five maize chromosomes were closed completely, including a 7 Mb region spanning the extremely CR2-rich CEN2. This improved assembly, B73 RefGen_v4CEN, was completed in February 2019 and has been available at https://doi.org/10.25739/7y1p-5169, both as pseudomolecules and as centromere assemblies alone. Thus, the manual editing of existing sequence data significantly improved the centromere regions of the B73 RefGen_v4 reference genome. These data were used for centromere analyses until the release of RefGen_v5.
Hand–foot coordination is significantly influenced by motion direction in individuals with autism spectrum disorder
Authors: Umesawa Yumi , Matsushima Kanae , Fukatsu Reiko , Terao Yasuo , Ide Masakazu 
Published: April 2022

Abstract and keywordsGenerally, when individuals attempt to move two limbs rhythmically in the opposite direction (e.g., flex the left hand and extend the left foot along the sagittal plane), the movements tend to be instead performed in the same direction. This phenomenon, known as directional constraint, can be harnessed to examine the difficulties in movement coordination exhibited by most individuals with autism spectrum disorder (ASD). While such difficulties have already been investigated through standardized clinical assessments, they have not been examined through kinematic methods. Thus, we employed a clinical assessment scale in an experimentally controlled environment to investigate whether stronger directional constraint during the rhythmic movement of two limbs is more pronounced and associated with decreased movement coordination in individuals with ASD. ASD and typically developing (TD) participants were asked to rhythmically move two limbs either in the same or opposite directions. In addition, the coordination skills of participants were assessed using the Bruininks-Oseretsky Test of Motor Proficiency Second Edition (BOT-2). Subjects with ASD showed significantly stronger directional constraint than TD participants during the contralateral and ipsilateral movement of the hand and foot. According to the pooled data from both groups, participants who showed stronger directional constraint during these two movement conditions also exhibited poorer coordinated movement skills in the BOT-2. Furthermore, stronger directional constraint was associated with severe autistic traits. These results suggest that people with ASD may have difficulties in inhibiting the neural signals that synchronize the direction of inter-limb movements, thus resulting in coordination disabilities.Lay SummaryIndividuals with autism spectrum disorder (ASD) often exhibit difficulties in coordinated movements. We asked those with ASD and healthy participants to move two limbs (e.g., left hand and left foot) either in the same or the opposite direction. Results demonstrated that participants with ASD had more difficulties in counteracting the tendency of their hand and foot to synchronously move in the same direction. Our findings suggested that difficulties to suppress synchronized movements of the hand and foot result in coordination disabilities.
Rigorous benchmarking of T cell receptor repertoire profiling methods for cancer RNA sequencing
Authors: Peng Kerui , Nowicki Theodore Scott , Campbell Katie , Peng Dandan , Nagareddy Anish , Huang Yu-Ning , Karlsberg Aaron , Miller Zachary , Brito Jaqueline , Pak Victoria M. , Abedalthagafi Malak S. , Burkhardt Amanda M. , Alachkar Houda , Ribas Antoni , Mangul Serghei 
Published: April 2022

AbstractThe ability to identify and track T cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile T cell receptor repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data is limited compared to RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across four cancer cohorts including both T cell rich and poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as to provide relative frequencies of clonotypes in T cell rich tissues and monoclonal repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T cell poor tissues, especially in polyclonal repertoires of T cell poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate the RNA-Seq into immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.