bluuebunny/crossref_metadata_2025_split huggingface dataset:
Graphicacy across age, education, and culture: a new tool to assess intuitive graphics skills
Authors: Ciccione Lorenzo , Sablé-Meyer Mathias , Boissin Esther , Josserand Mathilde , Potier-Watkins Cassandra , Caparos Serge , Dehaene Stanislas 
Published: October 2022

ABSTRACTData plots are widely used in science, journalism and politics, since they efficiently allow to depict a large amount of information. Graphicacy, the ability to understand graphs, thus became a fundamental cultural skill. Here, we introduce a new measure of graphicacy that assesses the ability to detect a trend in noisy scatterplots (“does this graph go up or down?”). In 3943 educated participants, responses vary as a sigmoid function of thet-value that a statistician would compute to detect a significant trend. We find a minimum level of core graphicacy even in unschooled participants living in remote Namibian villages (N=87) and 6-year-old 1st-graders who never read a graph (N=27). However, the sigmoid slope (the “graphicacy index”) varies across participants, increases with education, and tightly correlates with statistical knowledge, showing that experience contributes to refining graphical intuitions. Our tool is publicly available online and allows to quickly evaluate intuitive graphics skills.STATEMENT OF RELEVANCEThe rising cost of gas, the number of Covid deaths, the evolution of temperatures during the summer months: we often face graphs depicting these phenomena. The scientific literature has shown that human adults can intuit, within milliseconds, the statistical trend of these graphs. However, we do not know if these intuitions generalized to unschooled people and, most importantly, how to measure their variations in the population. In this study we show that intuitive graphics skills are present even in 6-year-old children who never saw a graph and in the Himba of Namibia, an indigenous people with no access to formal schooling. Furthermore, we developed a quantitative assessment of such intuitive graphics skills (which we called the “graphicacy index”), that everyone can easily obtain for free, through a short (10 minutes) online test:https://neurospin-data.cea.fr/exp/lorenzo-ciccione/graphicacy-index/. In summary, our study provides the first attempt to formally quantify human intuitions of statistical graphs.
Extremely-fast construction and querying of compacted and colored de Bruijn graphs with GGCAT
Authors: Cracco Andrea , Tomescu Alexandru I. 
Published: October 2022

AbstractCompacted de Bruijn graphs are one of the most fundamental data structures in computational genomics. Colored compacted graphs Bruijn graphs are a variant built on acollectionof sequences, and associate to eachk-mer the sequences in which it appears. We present GGCAT, a tool for constructing both types of graphs, based on a new approach merging thek-mer counting step with the unitig construction step, and on numerous practical optimizations.For compacted de Bruijn graph construction, GGCAT achieves speed-ups of 3–21× compared to the state-of-the-art tool Cuttlefish 2 (Khan and Patro, Genome Biology, 2022). When constructing the colored variant, GGCAT achieves speed-ups of 5–39× compared to the state-of-the-art tool BiFrost (Holley and Melsted, Genome Biology, 2020). Additionally, GGCAT is up to 480× faster than BiFrost for batch sequence queries on colored graphs.
Over two orders of magnitude difference in rate of single chromosome loss among sundew (DroseraL., Droseraceae) lineages
Authors: Mohn Rebekah A. , Zenil-Ferguson Rosana , Krueger Thilo A. , Fleischmann Andreas S. , Cross Adam T. , Yang Ya 
Published: October 2022

AbstractChromosome number change is a driver of speciation in eukaryotic organisms. Carnivorous sundews, the plant genusDroseraL., exhibit single chromosome number variation among and within species, especially in the AustralianDroserasubg.ErgaleiumD.C., potentially linked to the presence of holocentromeres. We reviewed literature, verified chromosome counts, and using anrbcL chronogram, tested alternate models where the gain, loss, and doubling rates (+1, −1, ×2) were the same or different betweenD. subg.Ergaleiumand the other subgenera. Ancestral chromosome number estimations were performed, and the distributions of self-compatibility and genome size were visualized across the genus. The best model for chromosome evolution had equal rates of polyploidy (0.014 per million years; Myr) but higher rates of single chromosome number gain (0.19 and 0.027 per Myr) and loss (0.23 and 0.00059 per Myr) inD. subg.Ergaleiumcompared to the other subgenera. We found no evidence for differences in single chromosome evolution to be due to differences in diploidization after polyploidy or to holocentromeres as had been proposed. This study highlights the complexity of factors influencing rates of chromosome number evolution.
A general approach for selection of epitope-directed binders to proteins
Authors: Zhou Jie , Le Chau Q. , Zhang Yun , Wells James A. 
Published: October 2022

AbstractDirecting antibodies to a particular epitope among many possible on a target protein is a significant challenge. Here we present a simple and general method for epitope-directed selection (EDS) using a differential phage selection strategy. This involves engineering the protein of interest (POI) with the epitope of interest (EOI) mutated using a systematic bioinformatics algorithm to guide the local design of an EOI decoy variant. Using several alternating rounds of negative selection with the EOI decoy variant followed by positive selection on the wild-type (WT) POI, we were able to identify highly specific and potent antibodies to five different EOI antigens that bind and functionally block known sites of proteolysis. Among these we developed highly specific antibodies that target the proteolytic site on the CUB domain containing protein 1 (CDCP1) to prevent its proteolysis allowing us to study the cellular maturation of this event that triggers malignancy. We generated antibodies that recognize the junction between the pro and catalytic domains for four different matrix metalloproteases (MMPs), such as MMP1, MMP3, and MMP9, that selectively block activation of each of these enzymes and impairs cell migration. We targeted a proteolytic epitope on the cell surface receptor, EPH Receptor A2, that is known to transform it from a tumor suppressor to an oncoprotein. We believe the EDS method greatly facilitates the generation antibodies to specific EOIs on a wide range of proteins and enzymes for broad therapeutic and diagnostic applications.SignificanceWe have developed a highly efficient platform to facilitate the directed selectionin vitroof antibodies to a wide range of functional epitopes on proteins. This method uses a bioinformatic program to guide mutations in the local site of interest to create a decoy antigen that can effectively remove antibodies not binding the site of interest by negative selection, followed by positive selection with the WT antigen to identify antibodies to the epitope of interest. We demonstrate the generality and versatility of this method by successfully producing functional antibodies to block specific proteolytically sensitive epitopes on five different proteins including enzymes important in cancer. The epitope-directed selection (EDS) approach greatly facilitates the identification of binders to specific sites of interest on proteins to probe function and as potential immunotherapeutics.
Graves’ disease-associated TSHR gene is demethylated and expressed in human regulatory T cells
Authors: Salumets Ahto , Tserel Liina , Kasela Silva , Limbach Maia , Milani Lili , Peterson Hedi , Kisand Kai , Peterson Pärt 
Published: October 2022

AbstractEpigenetic changes at specific genetic loci and the activation of transcriptional repressor FOXP3 are needed to establish and maintain the regulatory T cell (Treg) lineage. Here we studied the DNA methylation profiles in CD4+CD25+Tregs and CD4+CD25−conventional T cells (Tconvs) from healthy individuals and identified a wide range of differentially methylated CpG sites (DMPs). Overall, Tregs had more hypomethylated DMPs and contained more CpG sites, which on the cell population level were less defined in their methylation status. We identified top hypomethylated CpGs in Tregs close to CENPM, IKZF2, and LYST and hypermethylated sites at the THEMIS, SCML4, and ADD3 genes. Among others, DMPs were enriched for the transcriptional repressor Kaiso binding motifs. Interestingly, in Tregs we found hypomethylation and increased expression of the TSHR gene, which is a risk gene for Graves’ disease (GD). However, subsequent DNA methylation profiling in healthy individuals and GD patients revealed only 19 DMPs and no change at the TSHR locus, indicating that Tregs in GD patients share a similar methylation pattern with healthy controls. Together, we show Treg-specific hypomethylation and expression of the TSHR gene, prompting additional scenarios to explain the genetic link and role of anti-TSHR autoantibodies in GD.
GBP1 promotes killing of multidrug-resistantAcinetobacter baumanniiand promotes host protection via interferon signalling and inflammasome activation
Authors: Li Fei-Ju , Starrs Lora , Mathur Anukriti , Enosi Tuipulotu Daniel , Man Si Ming , Burgio Gaetan 
Published: October 2022

AbstractMultidrug resistant (MDR)Acinetobacter baumanniiare of major concern worldwide due to their resistance to last resort carbapenem and polymyxin antibiotics. To develop an effective treatment strategy, it is critical to better understand how anA. baumanniiMDR bacterium interacts with its mammalian host. Pattern-recognition receptors sense microbes, and activate the inflammasome pathway, leading to pro-inflammatory cytokine production and programmed cell death. Here, we found that MDRA. baumanniiactivate the NLRP3 inflammasome complex predominantly via the non-canonical caspase-11-dependent pathway. We show that caspase-11-deficient mice are protected from a virulent MDRA. baumanniistrain by maintaining a balance between protective and deleterious inflammation via IL-1. Caspase-11-deficient mice also compromise between effector cell recruitment, phagocytosis, and programmed cell death in the lung during infection. Importantly, we found that cytosolic immunity - mediated by guanylate-binding protein 1 (GBP1) and type I interferon signalling - orchestrates caspase-11-dependent inflammasome activation. This exerts a bactericidal activity against carbapenem- and colistin-resistant, lipooligosaccharide (LOS)- deficient bacteria. Together, our results suggest that developing therapeutic strategies targeting GBP1 might pave the way as a host-directed therapy to overcome multidrug resistance inA. baumanniiinfection.
DeepSelectNet: Deep Neural Network Based Selective Sequencing for Oxford Nanopore Sequencing
Authors: Senanayake Anjana , Gamaarachchi Hasindu , Herath Damayanthi , Ragel Roshan 
Published: October 2022

AbstractBackground:Nanopore sequencing allows selective sequencing, the ability to programmatically reject unwanted reads in a sample. Selective sequencing has many present and future applications in genomics research and the classification of species from a pool of species is an example. Existing methods for selective sequencing for species classification are still immature and the accuracy highly varies depending on the datasets. For the five datasets we tested, the accuracy of existing methods varied in the range of ~77%-97% (average accuracy <89%). Here we present DeepSelectNet, an accurate deep-learning-based method that can directly classify nanopore current signals belonging to a particular species. DeepSelectNet utilizes novel data preprocessing techniques and improved neural network architecture for regularization.Results:For the five datasets tested, DeepSelectNet’s accuracy varied between ~91%-99% (average accuracy ~95%). At its best performance, DeepSelectNet achieved a nearly 12% accuracy increase compared to its deep learning-based predecessor SquiggleNet. Furthermore, precision and recall evaluated for DeepSelectNet on average were always >89% (average ~95%). In terms of execution performance, DeepSelectNet outperformed SquiggleNet by ~13% on average. Thus, DeepSelectNet is a practically viable method to improve the effectiveness of selective sequencing.Conclusions:Compared to base alignment and deep learning predecessors, DeepSelectNet can significantly improve the accuracy to enable real-time species classification using selective sequencing. The source code of DeepSelectNet is available athttps://github.com/AnjanaSenanayake/DeepSelectNet.
Weddell seals near the fastest melting glacier in Antarctica prefer shallow, coastal and partially ice-covered waters
Authors: Bortolotto Guilherme A. , Heywood Karen J. , Boehme Lars 
Published: October 2022

AbstractAntarctic ice-shelves melting is accelerating, and the highest rates for the continent are observed in the Amundsen Sea, where Weddell seals are understudied. By modelling an unrivalled telemetry tracking dataset, we show that this top predator in the area is more likely found in shallower waters, closer to the coast, half-covered by ice and where the temperature at the ocean bottom is around 0.5°C or colder. Their distribution during winter is more restricted to coastal areas in the eastern Amundsen Sea and spread out in warmer months. That fluctuation reflects the drastic variation in their habitat illustrating their potential sensitivity to the upcoming impacts of climate changes. We discuss their overlap with Antarctic toothfish fisheries in the area and the potential consequences of global warming to the ecology of the seals.
Alternative culture systems for bovine oocytein vitromaturation: liquid marbles and differentially shaped 96-well plates
Authors: Fernández-Montoro Andrea , Angel-Velez Daniel , Benedetti Camilla , Azari-Dolatabad Nima , Pascottini Osvaldo Bogado , Pavani Krishna Chaitanya , Van Soom Ann 
Published: October 2022

AbstractIn vivomatured oocytes exhibit higher developmental competence than those maturedin vitro, but mimicking thein vivoenvironment byin vitroconditions has been challenging. Till now, conventional two-dimensional (2D) systems have been used forin vitromaturation of bovine cumulus-oocytes-complexes (COCs). However, using such systems may cause cell flattening and does not allow cumulus expansion in all dimensions, which is less physiological. Therefore, implementing a low-cost and highly effectivein vivo-like microenvironment methodology may help to optimize oocytein vitromaturation. Here, we used two different systems to culture COCs and evaluate their potential influence on embryo development and quality. In the first system, we used treated fumed silica particles to create a 3D microenvironment (liquid marbles; LM) to mature COCs. In the second system, we cultured COCs in 96-well plates with different dimensions (flat, ultra-low attachment round-bottom, and V-shaped 96-well plates). In both systems, the nuclear maturation rate remained similar to the control in 2D, showing that most oocytes reached metaphase II. However, the subsequent blastocyst rate remained lower in the liquid marble system compared to 96-well plates and control 2D systems. Interestingly, a lower total cell number was found in the resulting embryos from both systems (LM and 96-well plates) compared to the control. In conclusion, oocytes matured in liquid marbles or 96-well plates showed no remarkable change in terms of meiotic resumption, embryo development, and quality in both systems. None of the surface geometries influenced embryo development. These findings provide important inferences in many aspects of oocyte and embryo development. Further investigation is needed to determine other aspects like toxicity testing and ultrastructural changes in oocytes.
The geometry of hidden representations of protein language models
Authors: Valeriani Lucrezia , Cuturello Francesca , Ansuini Alessio , Cazzaniga Alberto 
Published: October 2022

AbstractProtein language models (pLMs) transform their input into a sequence of hidden representations whose geometric behavior changes across layers. Looking at fundamental geometric properties such as the intrinsic dimension and the neighbor composition of these representations, we observe that these changes highlight a pattern characterized by three distinct phases. This phenomenon emerges across many models trained on diverse datasets, thus revealing a general computational strategy learned by pLMs to reconstruct missing parts of the data. These analyses show the existence of low-dimensional maps that encode evolutionary and biological properties such as remote homology and structural information. Our geometric approach sets the foundations for future systematic attempts to understand thespaceof protein sequences with representation learning techniques.
Accuratede novoprediction of RNA 3D structure with transformer network
Authors: Feng Chenjie , Wang Wenkai , Han Renmin , Wang Ziyi , Ye Lisa , Du Zongyang , Wei Hong , Zhang Fa , Peng Zhenling , Yang Jianyi 
Published: October 2022

ABSTRACTRNA 3D structure prediction remains challenging though after years of efforts. Inspired by the recent breakthrough in protein structure prediction, we developed trRosettaRNA, a novel deep learning-based approach tode novoprediction of RNA 3D structure. Like trRosetta, the trRosettaRNA pipeline comprises two major steps: 1D and 2D geometries prediction by a transformer network; and full-atom 3D structure folding by energy minimization with constraints from the predicted geometries. We benchmarked trRosettaRNA on two independent datasets. The results show that trRosettaRNA outperforms other conventional methods by a large margin. For example, on 25 targets from the RNA-Puzzles experiments, the mean RMSD of the models predicted by trRosettaRNA is 5.5 Å, compared with 10.5 Å from the state-of-the-art human group (i.e., Das). Further comparisons with two recently released deep learning-based methods (i.e., DeepFoldRNA and RoseTTAFoldNA) show that all three methods have similar accuracy. However, trRosettaRNA yields more accurate and physically more realistic side-chain atoms than DeepFoldRNA and RoseTTAFoldNA. Finally, we apply trRosettaRNA to predict the structures for the Rfam families that do not have known structures. Analysis shows that for 263 families, the predicted structure models are estimated to be accurate with RMSD < 4 Å. The trRosettaRNA server and the package are available at:https://yanglab.nankai.edu.cn/trRosettaRNA/.
Fear of missing out (FOMO) associates with reduced cortical thickness in core regions of the posterior default mode network and higher levels of problematic smartphone and social media use
Authors: Wang Lan , Zhou Xinqi , Song Xinwei , Gan Xianyang , Zhang Ran , Liu Xiqin , Xu Ting , Jiao Guojuan , Ferraro Stefania , Bore Mercy Chepngetich , Yu Fangwen , Zhao Weihua , Montag Christian , Becker Benjamin 
Published: October 2022

AbstractFear of missing out (FOMO) promotes the desire or urge to stay continuously connected with a social reference group and updated on their activities, which may result in escalating and potentially addictive smartphone and social media use. The present study aimed to determine whether the neurobiological basis of FOMO encompasses core regions of the reward or social brain, and the associations with the level of problematic smartphone or social media use. We capitalized on a dimensional neuroimaging approach to examine cortical thickness and subcortical volume associations in a comparably large sample of healthy young individuals (n = 167). Meta-analytic network and behavioral decoding were employed to further characterize the identified regions. Higher levels of FOMO associated with lower cortical thickness in the precuneus. In contrast, no associations between FOMO and variations in striatal morphology were observed. Meta-analysis decoding revealed that the identified precuneus region exhibited a strong functional interaction with the default mode network (DMN) engaged in social cognitive and self-referential domains. Together the present findings suggest that individual variations in FOMO are associated with the brain structural architecture of the right precuneus, a core hub within a large-scale functional network resembling the DMN involved in social and self-referential processes. FOMO may promote escalating social media and smartphone use via social and self-referential processes rather than reward-related processes per se.
Cholinergic Modulation Shifts the Response of CA1 Pyramidal Cells to Depolarizing Ramps via TRPM4 Channels with Potential Implications for Place Field Firing
Authors: Combe Crescent , Upchurch Carol , Canavier Carmen C. , Gasparini Sonia 
Published: October 2022

AbstractA synergistic combination ofin vitroelectrophysiology and multicompartmental modeling of rat CA1 pyramidal neurons identified TRPM4 channels as major drivers of cholinergic modulation of the firing rate during a triangular current ramp, which emulates the bump in synaptic input received while traversing the place field. In control, fewer spikes at lower frequencies are elicited on the down-ramp compared to the up-ramp due to long-term inactivation of the NaVchannel. The cholinergic agonist carbachol (CCh) removes or even reverses this spike rate adaptation, causing more spikes to be elicited on the down-ramp than the up-ramp. CCh application during Schaffer collateral stimulation designed to simulate a ramp produces similar shifts in the center of mass of firing to later in the ramp. The non-specific TRP antagonist flufenamic acid and the TRPM4-specific blockers CBA and 9-phenanthrol, but not the TRPC-specific antagonist SKF96365, reverse the effect of CCh; this implicates the Ca2+-activated nonspecific cation current, ICAN, carried by TRPM4 channels. The cholinergic shift of the center of mass of firing is prevented by strong intracellular Ca2+buffering but not by antagonists for IP3and ryanodine receptors, ruling out a role for known mechanisms of release from intracellular Ca2+stores. Pharmacology combined with modeling suggest that [Ca2+] in a nanodomain near the TRPM4 channel is elevated through an unknown source that requires both muscarinic receptor activation and depolarization-induced Ca2+influx during the ramp. Activation of the regenerative inward TRPM4 current in the model qualitatively replicates and provides putative underlying mechanisms for the experimental observations.
A Process Model Account of the Role of Dopamine in Intertemporal Choice
Authors: Soutschek Alexander , Tobler Philippe N. 
Published: October 2022

AbstractTheoretical accounts disagree on the role of dopamine in intertemporal choice and assume that dopamine either promotes delay of gratification by increasing the preference for larger rewards or that dopamine reduces patience by enhancing the sensitivity to waiting costs. Here, we reconcile these conflicting accounts by providing empirical support for a novel process model according to which dopamine contributes to two dissociable components of the decision process, evidence accumulation and starting bias. We re-analyzed a previously published data set where intertemporal decisions were made either under the D2 antagonist amisulpride or under placebo by fitting a hierarchical drift diffusion model that distinguishes between dopaminergic effects on the speed of evidence accumulation and the starting point of the accumulation process. Blocking dopaminergic neurotransmission not only strengthened the sensitivity to whether a reward is perceived as worth the delay costs during evidence accumulation (drift rate) but also attenuated the impact of waiting costs on the starting point of the evidence accumulation process (bias). Taken together, our findings support a novel, process-based account of the role of dopamine for cost-benefit decision making, highlight the potential benefits of process-informed analyses and advance our understanding of dopaminergic contributions to decision making.