bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of mutated in colorectal cancer evolution history indicate a putative role in Th17/Treg differentiation
Authors: Kubick Norwin , Bieńkowska Irmina , Horbańczuk Jarosław Olav , Sacharczuk Mariusz , Mickael Michel Edwar 
Published: October 2022

AbstractThe MCC family of genes plays a role in colorectal cancer development through various immunological pathways, including the Th17/Treg axis. We have previously shown that MCC1 and not MCC2 play a role in Treg differentiation. Our understanding of the genetic divergence patterns and evolutionary history of the MCC family in relation to its function, in general, and the Th17/Treg axis, in particular, remains incomplete. In this investigation, we explored 12 species’ genomes to study the phylogenetic origin, structure, and functional specificity of this family. In vertebrates, both MCC1 and MCC2 homologs have been discovered, while invertebrates have a single MCC homolog. We found MCC homologs as early as Cnidarians and Trichoplax, suggesting that the MCC family first appeared 741 million years ago (Ma), whereas MCC divergence into MCC1 and MCC2 families occurred at 540 Ma. In general, we did not detect significant positive selection regulating MCC evolution. Our investigation, based on MCC1 structural similarity, suggests that they may play a role in the evolutionary changes in Tregs’ emergence towards complexity, including the ability to utilize calcium for differentiation through the use of the EFH calcium-binding domain. We also found that the motif NPSTGE was highly conserved in MCC1 but not in MCC2. The NPSTGE motif binds KEAP1 with high affinity, suggesting an Nrf2-mediated function for Nrf2. In the case of MCC2, we found that the “Modifier of rudimentary” motif is highly conserved. This motif contributes to the regulation of alternative splicing. Overall, our study sheds light on how the evolution of the MCC family is connected to its function in regulating the Th17/Treg axis.
Investigating the attentional focus to workplace-related soundscapes in a complex audio-visual-motor task using EEG
Authors: Rosenkranz Marc , Cetin Timur , Uslar Verena , Bleichner Martin G. 
Published: October 2022

AbstractIn demanding work situations (e.g., during a surgery) the processing of complex soundscapes varies over time and can be a burden for medical personnel. Here we study, using mobile electroencephalography (EEG), how humans process workplace-related soundscapes while performing a complex audio-visual-motor task (3D Tetris). Specifically, we wanted to know how the attentional focus changes the processing of the soundscape as a whole. Participants played a game of 3D Tetris in which they had to use both hands to control falling blocks. At the same time, participants listened to a complex soundscape, similar to what is found in an operating room (i.e., sound of machinery, people talking in the background, alarm sounds, and instructions). In this within-subject design, participants had to react to instructions (e.g., “place the next Block in the upper left corner”) and to sounds depending on the experimental condition, either to a specific alarm sound originating from a fixed location or to a beep sound that originated from varying locations. Attention to the alarm reflected a narrow attentional focus, as it was easy to detect and most of the soundscape could be ignored. Attention to the beep reflected a wide attentional focus, as it required the participants to monitor multiple different sound streams. Results show the robustness of the N1 and P3 event related potential response during this dynamic task with a complex auditory soundscape. Furthermore, we used temporal response functions to study auditory processing to the whole soundscape. This work is a step towards studying workplace-related sound processing in the operating room using mobile EEG.
Mapping potential malaria vector larval habitats for larval source management: Introduction to multi-model ensembling approaches
Authors: Zhou Guofa , Lee Ming-Chieh , Wang Xiaoming , Zhong Daibin , Yan Guiyun 
Published: October 2022

AbstractMosquito larval source management (LSM) is a viable supplement to the currently implemented first-line malaria control tools for use under certain conditions for malaria control and elimination. Implementation of larval source management requires a carefully designed strategy and effective planning. Identification and mapping of larval sources is a prerequisite. Ensemble modeling is increasingly used for prediction modeling, but it lacks standard procedures. We proposed a detailed framework to predict potential malaria vector larval habitats using ensemble modeling, which includes selection of models, ensembling method and predictors; evaluation of variable importance; prediction of potential larval habitats; and assessment of prediction uncertainty. The models were built and validated based on multi-site, multi-year field observations and climatic/environmental variables. Model performance was tested using independent multi-site, multi-year field observations. Overall, we found that the ensembled model predicted larval habitats with about 20% more accuracy than the average of the individual models ensembled. Key larval habitat predictors were elevation, geomorphon class, and precipitation 2 months prior. Mapped distributions of potential malaria vector larval habitats showed different prediction errors in different ecological settings. This is the first study to provide a detailed framework for the process of multi-model ensemble modeling. Mapping of potential habitats will be helpful in LSM planning.Author’s summaryMosquito larval source management (LSM) is a viable supplement to the currently implemented first-line malaria control tools. Implementation of LSM requires a carefully designed strategy and effective planning. Identification and mapping of larval sources is a prerequisite. Ensemble modeling is increasingly used for prediction modeling, but it lacks standard procedures. We proposed a detailed framework for such a process, including selection of models, ensembling methods and predictors; evaluation of variable importance; and assessment of prediction uncertainty. We used predictions of potential malaria vector larval habitats as an example to demonstrate how the procedure works, specifically, we used multi-site multi-year field observations to build and validate the model, and model performance was further tested using independent multi-site multi-year field observations – this training-validation-testing is often missing from previous studies. The proposed ensemble modeling procedure provides a framework for similar biological studies.
A geometric approach to quantifying the neuromodulatory effects of persistent inward currents on single motor unit discharge patterns
Authors: Beauchamp James. A. , Pearcey Gregory E. P. , Khurram Obaid U. , Chardon Matthieu , Wang Curtis , Powers Randall K. , Dewald Julius P.A. , Heckman CJ. 
Published: October 2022

ABSTRACTObjectiveAll motor commands flow through motoneurons, which entrain control of their innervated muscle fibers, forming a motor unit (MU). Owing to the high fidelity of action potentials within MUs, their discharge profiles detail the organization of ionotropic excitatory/inhibitory as well as metabotropic neuromodulatory commands to motoneurons. Neuromodulatory inputs (e.g., norepinephrine, serotonin) enhance motoneuron excitability and facilitate persistent inward currents (PICs). PICs introduce quantifiable properties in MU discharge profiles by augmenting depolarizing currents upon activation (i.e., PIC amplification) and facilitating discharge at lower levels of excitatory input than required for recruitment (i.e., PIC prolongation). Approach: Here, we introduce a novel geometric approach to estimate neuromodulatory and inhibitory contributions to MU discharge through exploiting discharge non-linearities introduced by PIC amplification during time-varying linear tasks. In specific, we quantify the deviation from linear discharge (“brace height”) and the rate of change in discharge (i.e., acceleration slope, attenuation slope, angle). We further characterize these metrics on a simulated motoneuron pool with known excitatory, inhibitory, and neuromodulatory inputs and on human MUs (Tibialis Anterior: 1448, Medial Gastrocnemius: 2100, Soleus: 1062, First Dorsal Interosseus: 2296).Main ResultIn the simulated motor pool, we found brace height and attenuation slope to consistently indicate changes in neuromodulation and the pattern of inhibition (excitation-inhibition coupling), respectively, whereas the paired MU analysis (ΔF) was dependent on both neuromodulation and inhibition pattern. Furthermore, we provide estimates of these metrics in human MUs and show comparable variability in ΔF and brace height measures in MUs matched across multiple trials.SignificanceSpanning both datasets, we found brace height quantification to provide an intuitive method for achieving graded estimates of neuromodulatory and inhibitory drive to MUs on a single unit level. This complements common techniques and provides an avenue for decoupling changes in the level of neuromodulatory and pattern of inhibitory motor commands.
The striatum drives the ergogenic effects of caffeine
Authors: de Bem Alves Ana Cristina , Speck Ana Elisa , Resende Farias Hémelin , Martins Leo Meira , dos Santos Naiara Souza , Pannata Gabriela , Tavares Ana Paula , de Oliveira Jade , Tomé Ângelo R. , Cunha Rodrigo A. , Aguiar Aderbal S 
Published: October 2022

AbstractCaffeine is one of the main ergogenic resources used in exercise and sports. Previously, we reported the ergogenic mechanism of caffeine through neuronal A2AR antagonism in the central nervous system [1]. We now demonstrate that the striatum rules the ergogenic effects of caffeine through neuroplasticity changes. Thirty-four Swiss (8-10 weeks, 47 ± 1.5 g) and twenty-four C57BL/6J (8-10 weeks, 23.9 ± 0.4 g) adult male mice were studied behaviorly and electrophysiologically using caffeine and energy metabolism was studied in SH-SY5Y cells. Systemic (15 mg/kg, i.p.) or striatal (bilateral, 15 μg) caffeine was psychostimulant in the open field (p< 0.05) and increased grip efficiency (p< 0.05). Caffeine also shifted long-term depression (LTD) to potentiation (LTP) in striatal slices and increased the mitochondrial mass (p< 0.05) and membrane potential (p< 0.05) in SH-SY5Y dopaminergic cells. Our results demonstrate the role of the striatum in the ergogenic effects of caffeine, with changes in neuroplasticity and mitochondrial metabolism.
Integrated global analysis in spider-flowers illuminates features underlying the evolution and maintenance of C4 photosynthesis
Authors: Zhao Wei , Li Jun , Sun Xingchao , Zheng Qiwei , Hua Wei , Liu Jun 
Published: October 2022

ABSTRACTThe carbon concentrating mechanism—C4 photosynthesis—represents a classic example of convergent evolution. While how this important trait originated and evolved remains largely enigmatic. Here we present a high-quality chromosome-scale annotated genome assembly of the spider-flower Gynandropsis gynandra, a valuable leafy vegetable crop and medicinal plant that has also been recognized as an emerging C4 model species. Repetitive elements occupy up to 71.91% of its genome, and over half are LTR-RTs derived from recent bursts, contributing to genome size expansion. Strikingly, LTR-RT explosion also played a critical role in C4 evolution by altering expression features of photosynthesis-associated genes via preferential insertion in promoters. Synteny analysis in the Cleome genus unveils that an independent species-specific whole-genome duplication in G. gynandra, which we name Gg-α, occurred after divergence from its close relative C3 plant Tarenaya hassleriana. Integrated multi-omics profiling demonstrates that Gg-α, gene family expansion, recent LTR-RT amplification and more recent species-specific tandem duplication events have all facilitated the evolution of C4 photosynthesis, revealing uniqueness of C4 evolution in this lineage. Moreover, high leaf vein density and heat stress resilience are associated with shifted gene expression patterns. Altogether, this mode of C3-to-C4 transition yields new insights into evolutionary convergence of a complex plant trait.
Improving cell-type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning
Authors: Alsaggaf Ibrahim , Buchan Daniel , Wan Cen 
Published: October 2022

ABSTRACTCell-type identification is an important task for single-cell RNA-seq (scRNA-seq) data analysis. In this work, we proposed a novel Gaussian noise augmented scRNA-seq contrastive learning framework (GsRCL) to learn a type of discriminative feature representations for cell-type prediction tasks. The experimental results suggest that the feature representations learned by GsRCL successfully improved the accuracy of cell-type prediction using scRNA-seq expression profiles.
Epigenetic CpG Duplex Marks Probed by an Evolved DNA Reader via a Well-Tempered Conformational Plasticity
Authors: Singh Himanshu , Das Chandan K. , Buchmuller Benjamin C. , Eppmann Simone , Schäfer Lars V. , Summerer Daniel , Linser Rasmus 
Published: October 2022

Abstract5-methylcytosine (mC) and its TET-oxidized derivatives exist in CpG dyads of mammalian DNA and regulate cell fate, but how their individual combinations in the two strands of a CpG act as distinct regulatory signals is poorly understood. Readers that selectively recognize such novel “CpG duplex marks” could be versatile tools for studying their biological functions, but their design represents an unprecedented selectivity challenge. By mutational studies, NMR relaxation, and MD simulations, we here show that the selectivity of the first designer reader for an oxidized CpG duplex mark hinges on precisely tempered conformational plasticity of the scaffold adopted during directed evolution. Our observations reveal the critical aspect of defined motional features in this novel reader for affinity and specificity in the DNA/protein interaction, providing unexpected prospects for further design progress in this novel area of DNA recognition.
Subcortical coding of predictable and unsupervised sound-context associations
Authors: Chen Chi , Cruces-Solís Hugo , Ertman Alexandra , de Hoz Livia 
Published: October 2022

AbstractOur environment is made of a myriad of stimuli present in combinations often patterned in predictable ways. For example, there is a strong association between where we are and the sounds we hear. Like so many environmental patterns, sound-context associations are learned implicitly, in an unsupervised manner, and are highly informative and predictive of normality. Yet, we know little about where and how unsupervised sound-context associations are coded in the brain. Here we measured plasticity in the auditory midbrain of mice living over days in a naturalistic environment designed to present sound-context associations with different degrees of predictability. Plasticity in the auditory midbrain, a hub of auditory input and multimodal feedback, developed over days and reflected learning of contextual information in a manner that depended on the predictability of the sound-context association and not on reinforcement. Plasticity took the form of broad frequency shifts in tuning in auditory midbrain neurons. These shifts were paralleled by an increase in response gain and correlated with an increase in neuronal frequency discrimination. Thus, the auditory midbrain codes for unsupervised predictable sound-context associations, revealing a subcortical engagement in the detection of contextual sounds. This detection might facilitate the processing of behaviorally relevant foreground information described to occur in cortical auditory structures.
NetLCP: An R package for prioritizing combinations of regulatory elements in the heterogeneous network with variant ‘switches’ detection
Authors: Ran Mingyu , Xu Jiankai 
Published: October 2022

SummaryNumerous independent networks of regulatory elements, including lncRNA, circRNA and pathway, have been developed to crucial roles in computational systems biology. Crosstalks among those networks as a bridge to build and decode heterogeneous networks from multidimensional biological knowledge, aids to highlight regulatory elements. And combinations of regulatory elements (CREs) in the local area of heterogeneous network have been a hot issue due to its crucial role in biological processes. We introduce NetLCP, an R package with command and shiny-based GUI modes, for prioritizing CREs with variant ‘switches’ detection.Availability and implementationThe NetLCP package and documentations are freely available at https://github.com/mortyran/NetLCP.Supplementary informationSupplementary data are available online
Embracing fine-root system complexity to improve the predictive understanding of ecosystem functioning
Authors: Wang Bin , McCormack M. Luke , Ricciuto Daniel M. , Yang Xiaojuan , Iversen Colleen M. 
Published: October 2022

AbstractProjecting the functioning of the biosphere requires a holistic consideration of whole-ecosystem processes. Although improving leaf and canopy processes has been the focus of ecosystem model development since the 1970s, the arbitrary homogenization of fine-root systems into a single pool is at odds with observations. This discrepancy has increased in the last two decades as accelerated conceptual and empirical advances have revealed functional differentiation and cooperation conferred by the hierarchical structure of fine-root orders and associations with mycorrhizal fungi in fine-root systems. To close this model-data gap, we propose a 3-pool structure comprising Transport and Absorptive fine roots with Mycorrhizal fungi (TAM) to model vertically resolved fine-root systems across organizational and spatial-temporal scales. A comparison of TAM to the single fine-root structure in a state-of-the-art Earth System Model using the ‘big-leaf’ approach demonstrates robust impacts on carbon cycling in temperate forests, lending further quantitative support to the empirical and theoretical basis for TAM. Strong support in both theory and practice therefore suggests a move beyond the useful but incorrect paradigm of single-pool homogenization, echoing a broad trend of embracing ecological complexities in terrestrial ecosystem modelling. Although challenges lay ahead towards realizing TAM in ecologically realistic demography models simulating emergent functioning from pattern and diversity, adoption of TAM by both modelers and empiricists holds promise to build a better predictive understanding of ecosystem functioning in the context of global change.
Microbiome network connectivity and composition linked to disease resistance in strawberry plants
Authors: Hassani M. Amine , Gonzalez Omar , Hunter Samuel S. , Holmes Gerald J. , Hewavitharana Shashika S. , Ivors Kelly , Lazcano Cristina 
Published: October 2022

AbstractPlant recruit diverse microbial communities from the soil biota. Inter-microbial interactions and connectivity in the root microbiome could play essential roles in plant health by promoting resistance to soil-borne pathogens. Yet, understanding these interactions under field conditions is still scarce. Using a strawberry crop model, we characterized the prokaryotic and fungal communities in the rhizosphere and roots of three strawberry cultivars displaying varying resistance degrees to the soil-borne fungal pathogen Macrophomina phaseolina. We tested the hypothesis that resistant cultivars assemble distinct bacterial and fungal communities that foster microbial connectivity and mediate disease resistance. Our results show that the soil-borne pathogen, M. phaseolina, does not perturb the root microbiome of the strawberry cultivars. Microbiome comparative analysis indicated that the highly susceptible cultivar, Sweet Ann, assembles a distinct microbiome that shows reduced network connectivity, whereas more resistant cultivars were enriched in potential beneficial microbes and showed higher network connectivity. Collectively, these results suggest the role of plant genetic traits in the assembly of beneficial microbiome members. Our study reinforces the eminent role of the plant microbiome as trait of selection in breeding programs and stresses further understandings of the genetic and biological mechanisms that mediate microbiome assembly. Uncovering these mechanisms will be key for future plant breeding programs.
National Institutes of Health Research Project Grant Inflation 1998 to 2021
Authors: Lauer Michael , Wang Joy , Roychowdhury Deepshikha 
Published: October 2022

AbstractWe analyzed changes in total costs for National Institutes of Health (NIH) awarded Research Project Grants issued from 1998 to 2003. The NIH uses a data-driven price index – the Biomedical Research and Development Price Index (BRDPI) – to account for inflation based increases in grant costs. The BRDPI was higher than the general rate of inflation from 1998 until 2012; since then, the rate of inflation for NIH-funded research has been similar to the general rate of inflation. Despite increases in nominal costs, recent years have seen increases in the absolute numbers of RPG and R01 awards. Real (BRDPI-adjusted) average and median RPG costs increased during the NIH-doubling (1998 to 2003), but have remained relatively stable since. Of note, though, the degree of variation of RPG costs has changed over time, with more marked extremes observed on both higher and lower levels of cost. On both ends of the cost spectrum, the agency is funding a greater proportion of solicited projects, with nearly half of RPG money going towards solicited projects. After adjusting for potential confounders in a wholly non-parametric machine learning regression, we find no independent association of time with BRDPI-adjusted costs.
Multiplex HDR for Disease and Correction Modeling of SCID by CRISPR Genome Editing in Human HSPCs
Authors: Iancu Ortal , Allen Daniel , Knop Orli , Zehavi Yonathan , Breier Dor , Arbiv Adaya , Lev Atar , Lee Yu Nee , Beider Katia , Nagler Arnon , Somech Raz , Hendel Ayal 
Published: October 2022

AbstractSevere combined immunodeficiency (SCID) is a group of monogenic primary immunodeficiencies caused by mutations in genes involved in the process of lymphocyte maturation and function. CRISPR-Cas9 gene editing of the patient’s own hematopoietic stem and progenitor cells (HSPCs) ex vivo could provide a therapeutic alternative to allogeneic hematopoietic stem cell transplantation (HSCT), the current gold standard for treatment of SCID. Using CRISPR-Cas9/rAAV6 gene-editing, we engineered genotypes in healthy donor (HD)-derived CD34+ HSPCs, thus eliminating the need for rare patient samples, to model both SCID and the therapeutic outcomes of gene-editing therapies for SCID via multiplexed homology directed repair (HDR). Firstly, we developed a SCID disease model via knock-out of both alleles of genes critical to the development of lymphocytes; and secondly, we established a knock-in/knock-out (KI-KO) strategy to develop a proof-of-concept single-allelic gene correction. Since SCID is a recessive disorder, correction of only one allele is enough to cure the patient. Based on these results, we performed gene correction of RAG2-SCID patient-derived CD34+ HSPCs that successfully developed into CD3+ T cells with diverse TCR repertoires in an in vitro T-cell differentiation (IVTD) platform. By using CRISPR-Cas9, multiplexed HDR, HD-derived CD34+ HSPCs, and an IVTD system we outline an approach for the study of human lymphopoiesis. We present both a way for researchers to determine the optimal configuration for CRISPR-Cas9 gene correction of SCID and other recessive blood disorders, and the feasibility of translating these techniques to perform gene correction in patient-derived CD34+ HSPCs.