bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Stimulus-Computable Model for Audiovisual Perception and Spatial Orienting in Mammals
Authors: Parise Cesare V. 
Published: January 2024

AbstractDespite recent progress in multisensory research, the absence of stimulus-computable perceptual models fundamentally limits our understanding of how the brain extracts and combines task-relevant cues from the continuous flow of natural multisensory stimuli. In previous research, we demonstrated that a correlation detector initially proposed for insect motion vision can predict the temporal integration of minimalistic audiovisual signals. Here, we demonstrate how a population of such units can process natural audiovisual stimuli and accurately account for human, monkey, and rat behaviour, across simulations of 69 classic psychophysical, eye-tracking, and pharmacological experiments. Given only the raw audiovisual stimuli (i.e., real-life footage) as input, our population model could replicate observed responses with an average correlation exceeding 0.97. Despite relying on as few as 0 to 4 free parameters, our population model provides an end-to-end account of audiovisual integration in mammals—from individual pixels and audio samples to behavioural responses. Remarkably, the population response to natural audiovisual scenes generates saliency maps that predict spontaneous gaze direction, Bayesian causal inference, and a variety of previously reported multisensory illusions. This study demonstrates that the integration of audiovisual stimuli, regardless of their complexity, can be accounted for in terms of elementary joint analyses of luminance and sound level. Beyond advancing our understanding of the computational principles underlying multisensory integration in mammals, this model provides a bio-inspired, general-purpose solution for multimodal machine perception.
Impaired microglial phagocytosis promotes seizure development
Authors: Bosco Dale B. , Kremen Vaclav , Haruwaka Koichiro , Zhao Shunyi , Wang Lingxiao , Ebner Blake A. , Zheng Jiaying , Dheer Aastha , Perry Jadyn F. , Xie Manling , Nguyen Aivi T. , Worrell Gregory A. , Wu Long-Jun 
Published: January 2024

AbstractIn the central nervous system, triggering receptor expressed on myeloid cells 2 (TREM2) is exclusively expressed by microglia and is critical for microglial proliferation, migration, and phagocytosis. TREM2 plays an important role in neurodegenerative diseases, such as Alzheimer’s disease and amyotrophic lateral sclerosis. However, little is known about the role TREM2 plays in epileptogenesis. To investigate this, we utilized TREM2 knockout (KO) mice within the murine intra-amygdala kainic acid seizure model. Electroencephalographic analysis, immunocytochemistry, and RNA sequencing revealed that TREM2 deficiency significantly promoted seizure-induced pathology. We found that TREM2 KO increased both acutestatus epilepticusand spontaneous recurrent seizures characteristic of chronic focal epilepsy. Mechanistically, phagocytic clearance of damaged neurons by microglia was impaired in TREM2 KO mice and the reduced phagocytic capacity correlated with increased spontaneous seizures. Analysis of human tissue from patients who underwent surgical resection for drug resistant temporal lobe epilepsy also showed a negative correlation between microglial phagocytic activity and focal to bilateral tonic-clonic generalized seizure history. These results indicate that microglial TREM2 and phagocytic activity may be important to epileptogenesis and the progression of focal temporal lobe epilepsy.One Sentence SummaryPhagocytic activity of microglia may impact generalized seizure development within both mice and humans.
Translating phenotypic prediction models from big to small anatomical MRI data using meta-matching
Authors: Wulan Naren , An Lijun , Zhang Chen , Kong Ru , Chen Pansheng , Bzdok Danilo , Eickhoff Simon B , Holmes Avram J , Yeo B. T. Thomas 
Published: January 2024

AbstractIndividualized phenotypic prediction based on structural MRI is an important goal in neuroscience. Prediction performance increases with larger samples, but small-scale datasets with fewer than 200 participants are often unavoidable. We have previously proposed a “meta-matching” framework to translate models trained from large datasets to improve the prediction of new unseen phenotypes in small collection efforts. Meta-matching exploits correlations between phenotypes, yielding large improvement over classical machine learning when applied to prediction models using resting-state functional connectivity as input features. Here, we adapt the two best performing meta-matching variants (“meta-matching finetune” and “meta-matching stacking”) from our previous study to work with T1-weighted MRI data by changing the base neural network architecture to a 3D convolution neural network. We compare the two meta-matching variants with elastic net and classical transfer learning using the UK Biobank (N = 36,461), Human Connectome Project Young Adults (HCP-YA) dataset (N = 1,017) and HCP-Aging dataset (N = 656). We find that meta-matching outperforms elastic net and classical transfer learning by a large margin, both when translating models within the same dataset, as well as translating models across datasets with different MRI scanners, acquisition protocols and demographics. For example, when translating a UK Biobank model to 100 HCP-YA participants, meta-matching finetune yielded a 136% improvement in variance explained over transfer learning, with an average absolute gain of 2.6% (minimum = -0.9%, maximum = 17.6%) across 35 phenotypes. Overall, our results highlight the versatility of the meta-matching framework.
A General-Purpose Non-invasive Neurotechnology Research Platform
Authors: Schalk Gerwin , Shao Shiyun , Xiao Kewei , Li Jintao , Xie Jiaxin , Guan Yinkui , Wu Zehan , Chen Liang , Zhong Xingyi , Xu Ce , Li Guangye , Yu Huan 
Published: January 2024

AbstractThis article describes our initial work toward a general-purpose platform for non-invasive neurotechnology research. This platform consists of a multi-modal wireless recording device, an associated software API, and full integration into BCI2000 software. The device is placed on the forehead and features two electroencephalographic (EEG) sensors, an inertial movement sensor (IMU), a photoplethysmogram (PPG) sensor, a microphone, and vibration-based feedback. Herein, we demonstrate different technical characteristics of our platform and its use in the context of sleep monitoring/modulation, simultaneous and synchronized recordings from different hardware, and evoked potentials. With further development and widespread dissemination, our platform could become an important tool for research into new non-invasive neurotechnology protocols in humans.
A geometric parameterization for beta turns
Authors: Newell Nicholas E. 
Published: January 2024

AbstractBeta turns, in which the protein backbone abruptly changes direction over four amino acid residues, are the most common type of protein secondary structure after alpha helices and beta sheets and play many key structural and functional roles. Previous work has produced classification systems for turn backbone geometry at multiple levels of precision, but these all operate in backbone dihedral-angle (Ramachandran) space, and the absence of a local Euclidean-space coordinate system and structural alignment for turns, or of any systematic Euclidean-space characterization of turn backbone shape, presents challenges for the visualization, comparison and analysis of the wide range of turn conformations and the design of turns and the structures that incorporate them. This work derives a local coordinate system that implicitly aligns turns, together with a simple geometric parameterization for turn backbone shape that describes modes of structural variation not explicitly captured by existing systems. These modes are shown to be meaningful by the demonstration of clear relationships between parameter values and the electrostatic energy of the beta-turn H-bond, the overrepresentation of key side-chain motifs, and the structural contexts of turns. Geometric turn parameters, which complement existing Ramachandran-space classifications, can be used to tune turn structures for compatibility with particular side-chain interactions or contexts, and they should prove valuable in applications, such as protein design, where an enhanced Euclidean-space description of turns may improve understanding or performance. The web-based tools ExploreTurns, MapTurns and ProfileTurn, available atwww.betaturn.com, incorporate turn-local coordinates and turn parameters and demonstrate their utility.
Control of ciliary transcriptional programs during spermatogenesis by antagonistic transcription factors
Authors: Wang Weihua , Xing Junqiao , Zhang Xiqi , Liu Hongni , Liu Xingyu , Jiang Haochen , Xu Cheng , Zhao Xue , Hu Zhangfeng 
Published: January 2024

AbstractExistence of cilia in the last eukaryotic common ancestor (LECA) raises a fundamental question in biology: how the transcriptional regulation of ciliogenesis has evolved? One conceptual answer to this question is by an ancient transcription factor regulating ciliary gene expression in both unicellular and multicellular organisms, but examples of such transcription factors in eukaryotes are lacking. Previously, we showed that an ancient transcription factor XAP5 is required for flagellar assembly inChlamydomonas. Here, we show that XAP5 and XAP5L are two conserved pairs of antagonistic transcription regulators that control ciliary transcriptional programs during spermatogenesis. Male mice lacking either XAP5 or XAP5L display infertility, as a result of meiotic prophase arrest and sperm flagella malformation, respectively. Mechanistically, XAP5 positively regulates the ciliary gene expression by activating the key regulators including FOXJ1 and RFX families during the early stage of spermatogenesis. In contrast, XAP5L negatively regulates the expression of ciliary genes via repressing these ciliary transcription factors during the spermiogenesis stage. Our results provide new insights into the mechanisms by which temporal and spatial transcription regulators are coordinated to control ciliary transcriptional programs during spermatogenesis.
Predicting functionally important breast cancer SNPs using pleiotropy, conservation, and protein structure
Authors: Carpenter Meredith A. , Cheng Alan C. 
Published: January 2024

AbstractMotivationWith over 24,000 SNPs associated with breast cancer in ClinVar, there is a need to prioritize the subset most likely to be causally linked to diagnostic, prognostic, and other clinical outcomes of disease. Building off currently known breast cancer oncogenes and SNPs, we identify the subset of SNPs with pleiotropic effects, with the goal of identifying mutations functionally relevant to disease progression. We further use sequence and structure analysis to prioritize missense mutations most likely to impact protein function.ResultsFrom the known breast cancer SNPs, we identified co-associated mutations located at evolutionarily conserved positions and contributing significant protein stability as potential focal points for disease biomarkers, protein function studies, and therapeutic intervention. To identify regions likely integral to protein function, we plotted genomic intervals where multiple disease density peaks overlap. Of the breast cancer SNPs, 1,714 were co-associated in-frame mutations, of which 930 occurred at conserved residue positions (Shannon Entropy <1.0) and 833 were also missense mutations. Building structure-based models of the 277 SNPs with available protein structure resulted in identification of 133 SNPs that are calculated to affect protein thermostability by >100-fold (>3 kcal/mol). The workflow we built can be applied to other diseases to help identify functional mutations.AvailabilityPython code for the integrated analysis workflow available athttp://github.com/mcarpenter-brandeis/brc-pleiotropyand detailed data tables available in Supplemental Information.Contactacheng@brandeis.edu,meredith.a.carpenter@gmail.coms
ThermoFinder: A sequence-based thermophilic proteins prediction framework
Authors: Yu Han , Luo Xiaozhou 
Published: January 2024

AbstractMotivationThermophilic proteins are important for academic research and industrial processes, and various computational methods have been developed to identify and screen them. However, their performance has been limited due to the lack of high-quality labeled data and efficient models for representing protein. Here, we proposed a novel sequence-based thermophilic proteins prediction framework, called ThermoFinder.ResultsIn this study, we demonstrated that ThermoFinder outperforms previous state-of-the-art tools on two benchmark datasets, and feature ablation experiments confirmed the effectiveness of our approach. Additionally, ThermoFinder exhibited exceptional performance and consistency across two newly constructed datasets, one of these was specifically constructed for the regression-based prediction of temperature optimum values directly derived from protein sequences. The feature importance analysis, using shapley additive explanations, further validated the advantages of ThermoFinder. We believe that ThermoFinder will be a valuable and comprehensive framework for predicting thermophilic proteins.
The genome ofLolium multiflorumreveals the genetic architecture of paraquat resistance
Authors: Brunharo Caio A. , Short Aidan W. , Bobadilla Lucas K. , Streisfeld Matthew A. 
Published: January 2024

SUMMARY- Herbicide resistance in agricultural weeds has become one of the greatest challenges for sustainable crop production. The repeated evolution of herbicide resistance provides an excellent opportunity to study the genetic and physiological basis of the resistance phenotype and the evolutionary responses to human-mediated selection pressures.Lolium multiflorumis a ubiquitous weed that has evolved herbicide resistance repeatedly around the world in various cropping systems.- We assembled and annotated a chromosome-scale genome forL. multiflorumand elucidated the genetic architecture of paraquat resistance by performing quantitative trait loci analysis, genome-wide association studies, genetic divergence analysis, and transcriptome analyses from paraquat-resistant and -susceptibleL. multiflorumpopulations.- Results suggested that two regions of chromosome 5 were associated with paraquat resistance. The regions contain candidate genes that encode cellular transport functions, including a novel multidrug and toxin extrusion (MATE) protein, and a cation transporter previously shown to interact with polyamines.- Our results reveal the genetic architecture of paraquat resistance and identified promising candidate genes for future functional studies. Given thatL. multiflorumis a weed and a cultivated crop species, the genomic resources generated will prove valuable to a wide spectrum of the plant science community.
Identification of a chromatin-bound ERRα interactome network in mouse liver
Authors: Scholtes Charlotte , Dufour Catherine Rosa , Pleynet Emma , Kamyabiazar Samaneh , Hutton Phillipe , Baby Reeba , Guluzian Christina , Giguère Vincent 
Published: January 2024

AbstractObjectiveEstrogen-related-receptor α (ERRα) plays a critical role in the transcriptional regulation of cellular bioenergetics and metabolism, and perturbations in its activity have been associated with metabolic diseases. While several coactivators and corepressors of ERRα have been identified to date, a knowledge gap remains in understanding the extent to which ERRα cooperates with coregulators in the control of gene expression. Herein, we mapped the primary chromatin-bound ERRα interactome in mouse liver.MethodsRIME (Rapid Immuno-precipitation Mass spectrometry of Endogenous proteins) analysis using mouse liver samples from two circadian time points was used to catalog ERRα-interacting proteins on chromatin. The genomic crosstalk between ERRα and its identified cofactors in the transcriptional control of precise gene programs was explored through cross-examination of genome-wide binding profiles from chromatin immunoprecipitation-sequencing (ChIP-seq) studies. The dynamic interplay between ERRα and its newly uncovered cofactor Host cell factor C1 (HCFC1) was further investigated by loss-of-function studies in hepatocytes.ResultsCharacterization of the hepatic ERRα chromatin interactome led to the identification of 48 transcriptional interactors of which 42 were previously unknown including HCFC1. Interrogation of available ChIP-seq binding profiles highlighted oxidative phosphorylation (OXPHOS) under the control of a complex regulatory network between ERRα and multiple cofactors. While ERRα and HCFC1 were found to bind to a large set of common genes, only a small fraction showed their co-localization, found predominately near the transcriptional start sites of genes particularly enriched for components of the mitochondrial respiratory chain. Knockdown studies demonstrated inverse regulatory actions of ERRα and HCFC1 on OXPHOS gene expression ultimately dictating the impact of their loss-of-function on mitochondrial respiration.ConclusionsOur work unveils a repertoire of previously unknown transcriptional partners of ERRα comprised of chromatin modifiers and transcription factors thus advancing our knowledge of how ERRα regulates metabolic transcriptional programs.
The asymmetric transfers of visual perceptual learning determined by the stability of geometrical invariants
Authors: Yang Yan , Zhuo Yan , Zuo Zhentao , Zhuo Tiangang , Chen Lin 
Published: January 2024

AbstractWe quickly and accurately recognize the dynamic world by extracting invariances from highly variable scenes, a process can be continuously optimized through visual perceptual learning (VPL). While it is widely accepted that the visual system prioritizes the perception of more stable invariants, the influence of the structural stability of invariants on VPL remains largely unknown. In this study, we designed three geometrical invariants with varying levels of stability for VPL: projective (e.g., collinearity), affine (e.g., parallelism), and Euclidean (e.g., orientation) invariants, following the Klein’s Erlangen program. We found that learning to discriminate low-stability invariant transferred asymmetrically to those with higher stability, and that training on high-stability invariants enabled location transfer. To explore learning-associated plasticity in the visual hierarchy, we trained deep neural networks (DNNs) to model this learning procedure. We reproduced the asymmetric transfer between different invariants in DNN simulations and found that the distribution and time course of plasticity in DNNs suggested a neural mechanism similar to the reverse hierarchical theory (RHT), yet distinct in that invariant stability—not task difficulty or precision—emerged as the key determinant of learning and generalization. We propose that VPL for different invariants follows the Klein hierarchy of geometries, beginning with the extraction of high-stability invariants in higher-level visual areas, then recruiting lower-level areas for the further optimization needed to discriminate less stable invariants.
FveDAD2 negatively regulates branch crowns by affecting abscisic acid metabolism through FveHB7 in woodland strawberry
Authors: Sun Hongying , Zhang Junxiang , Li Weijia , Wang Yan , Zhang Zhihong 
Published: January 2024

AbstractStrigolactones (SLs) are a significant hormone in plant growth response, crucial for regulating branching. DECREASED APICAL DOMINANCE2 (DAD2) is a novel receptor of SL. Here, FveDAD2 in woodland strawberries (Fragaria vesca) as the receptor for SL was identified, and three FveDAD2-RNAi transgenic lines that exhibited the phenotype of multi-branched crowns and smaller fruits were obtained. Gene expression, phenotypic analysis, and yeast assays were used to investigate the function of FveDAD2 in regulating branch crowns in strawberries. Like the alpha/beta hydrolase D14, FveDAD2 interacts with FveSMXL7 and depends on SL. Furthermore, the yeast single-hybrid, GUS activity assay, and LUC assay results demonstrate that FveSMXL7 binds to the promoter ofFveHB7and repress its transcription. FveHB7, a homeobox transcription factor, negatively regulates the transcription ofFveABA8’OH1, which encodes the enzyme that catabolizes abscisic acid (ABA). ABA contents were reduced in the shoot tips of the FveDAD2-RNAi lines, while treating wide-type plants with 20 μM ABA significantly suppressed the number of branches. In conclusion, we discovered a novel pathway of SL signaling to regulate branching through ABA.One-sentence summaryFveDAD2 negatively regulates branch crowns by affecting abscisic acid levels by interacting with FveSMXL7 to regulate the expression ofFveABA8’OH1via the transcription factor FveHB7.
Effects of long-term high dose aspartame on body mass, bone strength, femoral geometry, and microbiota composition in a young and aged cohort of male and female mice
Authors: Cyphert Erika L. , Liu Chongshan , Morales Angie L. , Nixon Jacob C. , Blackford Emily , Garcia Matthew , Cevallos Nicolas , Turnbaugh Peter J. , Brito Ilana L. , Booth Sarah L. , Hernandez Christopher J. 
Published: January 2024

AbstractBackground:Recent reassessment of the safety of aspartame has prompted increased evaluation of its effect on the health of a range of tissues. The gut microbiome is altered by oral aspartame. One prior study suggested that changes in the microbiome caused by aspartame could influence the strength of bone in young skeletally developing mice. Here we ask how aspartame influences bone in mice of different age and sex.Objective:The objective of this study was to determine the effect of aspartame on the bone strength and gut microbiota of young and aged mice.Methods:Male and female C57Bl/6J mice were untreated or treated with a high dose of aspartame in their drinking water from 1 month of age until 4 (young cohort; n = 80) or 22 months (aged cohort; n = 52).Results:In aged males, mice treated with aspartame had greater body mass, whole bone strength, and femoral geometry relative to untreated. Specifically, in aged males, aspartame led to 9% increase in body mass (p < 0.001), 22% increase in whole bone strength (p = 0.006), and 17% increase in section modulus (p < 0.001) relative to untreated mice. Aged males and females receiving aspartame had a different microbiota than untreated mice and a decreased abundance ofOdoribacter. No differences in body mass, whole bone strength, or femoral geometry were associated with aspartame dosing in young males or young or aged females.Conclusions:Aspartame treated aged males had greater whole bone strength and the effect appeared to be explained by greater body mass. Aspartame treatment did not alter whole bone strength in young males or young or aged females despite the aspartame having a similar effect on the microbiota of both aged males and females.