bluuebunny/crossref_metadata_2025_split huggingface dataset:
The evolution of cooperation in the unidirectional division of labor on a tree network
Authors: Nirjhor Md Sams Afif , Nakamaru Mayuko 
Published: June 2023

AbstractDivision of labour on complex networks is rarely investigated using evolutionary game theory. We investigate a division of labour where divided roles are assigned to groups on the nodes of a general unidirectional finite tree graph network. From the network’s original node, a task flows and is divided along the branches. A player is randomly selected in each group of cooperators and defectors, who receives a benefit from a cooperator in the upstream group and a part of the task. A cooperator completes their part by paying a cost and then passing it downstream until the entire task is completed. Defectors do not do anything and the division of labour stops, causing all groups to suffer losses due to the incomplete task. We develop a novel method to analyse the local stability in this general tree. We discover that not the benefits but the costs of the cooperation influence the evolution of cooperation, and defections in groups that are directly related to that group’s task cause damage to players in that group. We introduce two sanction systems one of which induces the evolution of cooperation more than the system without sanctions and promote the coexistence of cooperator and defector groups.
Timecourse and source localization of abstract and concrete semantic representations
Authors: Vignali Lorenzo , Xu Yangwen , Turini Jacopo , Collignon Olivier , Crepaldi Davide , Bottini Roberto 
Published: June 2023

AbstractDual coding theories of knowledge suggest that meaning is represented in the brain by a double code, which comprises language-derived representations in the Anterior Temporal Lobe and sensory-derived representations in perceptual and motor regions. This approach predicts that concrete semantic features should activate both codes, whereas abstract features rely exclusively on the linguistic code. Using magnetoencephalography (MEG), we adopted a temporally resolved multiple regression approach to identify the contribution of abstract and concrete semantic predictors to the underlying brain signal. Results evidenced early involvement of anterior-temporal and inferior-frontal brain areas in both abstract and concrete semantic information encoding. At later stages, occipito-temporal regions showed greater responses to concrete compared to abstract features. The present findings shed new light on the temporal dynamics of abstract and concrete semantic representations in the brain and suggest that the concreteness of words processed first with a transmodal/linguistic code, housed in frontotemporal brain systems, and only after with an imagistic/sensorimotor code in perceptual and motor regions.
A weighted generative model of the human connectome
Authors: Akarca Danyal , Schiavi Simona , Achterberg Jascha , Genc Sila , Jones Derek K. , Astle Duncan E. 
Published: June 2023

AbstractProbabilistic generative network models have offered an exciting window into the constraints governing the human connectome’s organization. In particular, they have highlighted the economic context of network formation and the special roles that physical geometry and self-similarity likely play in determining the connectome’s topology. However, a critical limitation of these models is that they do not consider the strength of anatomical connectivity between regions. This significantly limits their scope to answer neurobiological questions. The current work draws inspiration from the principle of redundancy reduction to develop a novel weighted generative network model. This weighted generative network model is a significant advance because it not only incorporates the theoretical advancements of previous models, but also has the ability to capture the dynamic strengthening or weakening of connections over time. Using a state-of-the-art Convex Optimization Modelling for Microstructure-Informed Tractography (COMMIT) approach, in a sample of children and adolescents (n= 88, aged 8 to 18 years), we show that this model can accurately approximate simultaneously the topology and edge-weights of the connectome (specifically, the MRI signal fraction attributed to axonal projections). We achieve this at both sparse and dense connectome densities. Generative model fits are comparable to, and in many cases better than, published findings simulating topology in the absence of weights. Our findings have implications for future research by providing new avenues for exploring normative developmental trends, models of neural computation and wider conceptual implications of the economics of connectomics supporting human functioning.
Multi-trait GWAS for diverse ancestries: Mapping the knowledge gap
Authors: Troubat Lucie , Fettahoglu Deniz , Henches Léo , Aschard Hugues , Julienne Hanna 
Published: June 2023

AbstractBackgroundApproximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.MethodsHere, we extend and assess the potential limitations and gain of our multi-trait GWAS pipeline,JASS(JointAnalysis ofSummaryStatistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), South-East Asian (SAS)).ResultsWe detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multitrait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome thep.vivaxinduced malaria.ConclusionsMulti-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.
Phenotypic Switching of Vascular Smooth Muscle Cells in Duchenne Muscular Dystrophy
Authors: Xuan Wanling , Cheng Feng , Han Xiaowei , Tipparaju Srinivas M. , Ashraf Muhammad 
Published: June 2023

AbstractBackgroundExtensive studies have been conducted in skeletal muscle and myocardium affected by Duchenne Muscular Dystrophy (DMD) disease but there is a significant gap of research in the role of vascular smooth muscle cells (VSMCs) in DMD. Here, we investigated the role of dystrophin deficiency in the maintenance of VSMCs contractile phenotype.Methods12-14 months old mdx mice and DMD induced pluripotent stem cells (iPSC) derived VSMCs were used as disease models. Morphological and immunohistochemistry analyses were performed to determine histological changes and the expression of contractile markers. Transmission Electron Microscopy (TEM) was used to assess ultrastructural changes in the VSMCs. Mito-tracker staining and TUNEL staining were performed to determine mitochondria fission-fusion and apoptosis respectively. mRNA Sequencing for normal iPSC derived VSMCs (WT-VSMCs) and DMD iPSC derived VSMCs (DMD-VSMCs) with or without oxidative stress was performed. KEGG signaling pathway enrichment, Go function enrichment and Gene set enrichment analysis (GESA) were conducted to explore the potential mechanism responsible for these changes. In addition, transcription factor enrichment analysis was performed to unravel mechanistic pathways of regulatory networks.ResultsSpontaneous abnormal VSMCs proliferation, loss of vascular structure and degenerative changes occurred in VSMCs in aorta from 12-14 months old mdx mice. The DMD-VSMCs showed maturation defect, loss of mitochondrial hemostasis, and increased vulnerability to oxidative stress compared with WT-VSMCs. Transcriptome analysis revealed dysregulation of smooth muscle proliferation, differentiation, and vascular development in DMD-VSMCs. Transcriptional factor, target, and motif discovery analysis of the dysregulated gene set suggested potential contributions of transcriptional factors GADD45A, SOX9, TIA1, RBBP9 and FOXM to the phenotypes of DMD-VSMCs. Under oxidative stress, initiation of apoptotic process was significantly enhanced in DMD-VSMCs while their response to hypoxia and oxidative stress was downregulated.ConclusionsDystrophin deficiency induced VSMCs phenotype switching and disrupted mitochondrial metabolism. The findings in this study underscore the importance of vascular dysfunction in DMD disease and therapeutic interventions to restore VSMC phenotype may ameliorate the propensity of disease progression. It is suggested that the transcriptome analysis may allow the discovery of potential signaling pathways involved in the dysregulation of transcription factors.
The Na+leak channel NALCN controls spontaneous activity and mediates synaptic modulation by α2-adrenergic receptors in auditory neurons
Authors: Ngodup Tenzin , Irie Tomohiko , Elkins Sean , Trussell Laurence O. 
Published: June 2023

AbstractCartwheel interneurons of the dorsal cochlear nucleus (DCN) potently suppress multisensory signals that converge with primary auditory afferent input, and thus regulate auditory processing. Noradrenergic fibers from locus coeruleus project to the DCN, and α2-adrenergic receptors inhibit spontaneous spike activity but simultaneously enhance synaptic strength in cartwheel cells, a dual effect leading to enhanced signal- to-noise for inhibition. However, the ionic mechanism of this striking modulation is unknown. We generated a glycinergic neuron-specific knockout of the Na+leak channel NALCN, and found that its presence was required for spontaneous firing in cartwheel cells. Activation of α2-adrenergic receptors inhibited both NALCN and spike generation, and this modulation was absent in the NALCN knockout. Moreover, α2-dependent enhancement of synaptic strength was also absent in the knockout. GABABreceptors mediated inhibition through NALCN as well, acting on the same population of channels as α2 receptors, suggesting close apposition of both receptor subtypes with NALCN. Thus, multiple neuromodulatory systems determine the impact of synaptic inhibition by suppressing the excitatory leak channel, NALCN.
BRG1 establishes the neuroectodermal chromatin landscape to restrict dorsal cell fates
Authors: Hoffman Jackson A , Muse Ginger W , Langer Lee F , Gandara Isabella , Ward James M , Archer Trevor K 
Published: June 2023

SUMMARYCell fate decisions are achieved with gene expression changes driven by lineage-specific transcription factors (TFs). These TFs depend on chromatin remodelers including the BAF complex to activate target genes. BAF complex subunits are essential for development and frequently mutated in cancer. Thus, interrogating how BAF complexes contribute to cell fate decisions is critical for human health. We examined the requirement for the catalytic BAF subunit BRG1 in neural progenitor cell (NPC) specification from human embryonic stem cells. During the earliest stages of differentiation, BRG1 was required to establish chromatin accessibility at neuroectoderm-specific enhancers. BRG1 depletion resulted in abnormal NPC populations that differentially expressed neuroectodermal TFs, were more prone to neuronal differentiation, and precociously formed neural crest lineages. These findings demonstrate that BRG1 mediates NPC specification by ensuring proper expression of lineage-specific TFs and appropriate activation of their transcriptional programs.
Deep neural networks for predicting single cell responses and probability landscapes
Authors: Klumpe Heidi E. , Lugagne Jean-Baptiste , Khalil Ahmad S. , Dunlop Mary J. 
Published: June 2023

AbstractEngineering biology relies on the accurate prediction of cell responses. However, making these predictions is challenging for a variety of reasons, including the stochasticity of biochemical reactions, variability between cells, and incomplete information about underlying biological processes. Machine learning methods, which can model diverse input-output relationships without requiringa priorimechanistic knowledge, are an ideal tool for this task. For example, such approaches can be used to predict gene expression dynamics given time-series data of past expression history. To explore this application, we computationally simulated single cell responses, incorporating different sources of noise and alternative genetic circuit designs. We showed that deep neural networks trained on these simulated data were able to correctly infer the underlying dynamics of a cell response even in the presence of measurement noise and stochasticity in the biochemical reactions. The training set size and the amount of past data provided as inputs both affected prediction quality, with cascaded genetic circuits that introduce delays requiring more past data. We also tested prediction performance on a bistable auto-activation circuit, finding that our initial method for predicting a single trajectory was fundamentally ill-suited for multimodal dynamics. To address this, we updated the network architecture to predict the entire distribution of future states, showing it could accurately predict bimodal expression distributions. Overall, these methods can be readily applied to the diverse prediction tasks necessary to predict and control a variety of biological circuits, a key aspect of many synthetic biology applications.
Chronic Stress Increases Adiposity and Anxiety in Rats with Decreased Expression ofKrtcap3
Authors: Szalanczy Alexandria , Fitzpatrick Mackenzie , Beeson Angela , Bui Trangdai , Dyson Christina , Eller Seth , Landry Julia , Scott Christina , Grzybowski Michael , Klotz Jason , Geurts Aron M , Weiner Jeff L , Redei Eva E , Solberg Woods Leah C 
Published: June 2023

AbstractWe previously identifiedKeratinocyte-associated protein 3,Krtcap3, as a novel adiposity gene but subsequently found that its impact on adiposity may depend on environmental stress. To more thoroughly understand the connection betweenKrtcap3, adiposity, and stress, we exposed wild-type (WT) andKrtcap3knock-out (KO) rats to chronic stress then measured adiposity and behavioral outcomes. We found that KO rats displayed lower basal stress than WT rats under control conditions and exhibited the expected responses to chronic stress exposure. Specifically, stress-exposed KO rats gained more weight, consumed more food when socially isolated, and displayed more anxiety-like behaviors relative to control KO rats. Meanwhile, there were minimal differences between control and stressed WT rats. At study conclusion stress-exposed KO rats had increased corticosterone (CORT) relative to control KO rats with no differences between WT rats. In addition, KO rats, independent of prior stress exposure, had an increased CORT response to removal of their cage-mate (psychosocial stress), which was only seen in WT rats when exposed to chronic stress. Finally, we found differences in expression of the glucocorticoid receptor,Nr3c1, in the pituitary and colon between control and stress-exposed KO rats that were not present in WT rats. These data support thatKrtcap3expression affects stress response, potentially via interactions withNr3c1, with downstream effects on adiposity and behavior. Future work is necessary to more thoroughly understand the role ofKrtcap3in the stress response.
Parametric modeling of mechanical effects on circadian oscillators
Authors: Kennedy Keith E. , Abenza Juan F. , Rossetti Leone , Trepat Xavier , Villoslada Pablo , Garcia-Ojalvo Jordi 
Published: June 2023

Circadian rhythms are archetypical examples of nonlinear oscillations. While these oscillations are usually attributed to circuits of biochemical interactions among clock genes and proteins, recent experimental studies reveal that they are also affected by the cell’s mechanical environment. Here we extend a standard biochemical model of circadian rhythmicity to include mechanical effects in a parametric manner. Using experimental observations to constrain the model, we suggest specific ways in which the mechanical signal might affect the clock. Additionally, a bifurcation analysis of the system predicts that these mechanical signals need to be within an optimal range for circadian oscillations to occur.Cells are nonlinear dynamical elements, which in multicellular tissues are commonly coupled to one another. Much work has been done, both theoretically and experimentally, to understand this coupling and to identify its dynamical consequences from a biochemical viewpoint. In contrast, much less is known about how the mechanical interactions between cells affect these dynamics. Recent work has shown, for instance, that circadian oscillations degrade substantially in populations of cellsin vitrowhen cell density decreases sufficiently. Here we use this fact to constrain a standard model of circadian oscillations, and propose a way through which external mechanical signals and internal biochemical interactions could combine in clock cells.
Development of building defects dashboards and stochastic models for multi-storey buildings in Victoria, Australia
Authors: Gurmu Argaw , Hosseini M. Reza , Arashpour Mehrdad , Lioeng Wellia 
Published: June 2023

Purpose
Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

Design/methodology/approach
In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings
Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

Originality/value
The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.
Class cleavage electoral structuring in Western Europe (1871–2020)
Authors: EMANUELE VINCENZO 
Published: June 2023

AbstractDespite the huge amount of studies on cleavages, scholars have never elaborated a dynamic model to conceptualize and measure the stages of electoral development of the class cleavage and, specifically, the stage corresponding to its full electoral structuring. To fill this gap, by combining some key electoral properties of the class cleavage, I build a model that returns, for each country in each election, the current stage of electoral development of the class cleavage. I test this model in 20 Western European countries from the late 19th century to 2020. Results show that an electorally structured class cleavage has characterized most of Western Europe's electoral history. However, contrary to conventional wisdom, it is not merely a product of socio‐structural factors that have been experiencing an irreversible decline. Conversely, its demise or resilience is a matter of the national political context, as it mostly depends upon specific party system characteristics.
Racial and ethnic differences in the consequences of school suspension for arrest
Authors: Fisher Benjamin W. , Widdowson Alex O. 
Published: June 2023

AbstractA growing body of literature has demonstrated that when schools suspend students, the suspension acts not as a deterrent but as an amplifier of future punishment. Labeling theory has emerged as the predominant explanation for this phenomenon, suggesting that the symbolic label conferred along with a suspension shapes how other people perceive and respond to labeled students. Few studies, however, have attended to racial/ethnic differences in this process even though critical race theory suggests the consequences of suspension likely differ across racial/ethnic groups due to prevailing racial/ethnic stereotypes. This study uses six waves of data from the National Longitudinal Study of Youth 1997 (N = 8,634) to examine how the relationship between suspension and subsequent arrest differs for White, Black, and Hispanic students. Using a series of within‐person analyses that control for time‐stable personal characteristics, this study finds that suspension amplifies Black and Hispanic students’ risk of arrest relative to that of White students. White students’ risk of arrest was not amplified by suspension and, in some models, was diminished. This study's findings underscore the importance of understanding the labeling process as different by race/ethnicity and indicate that suspension is particularly harmful for Black and Hispanic relative to White students.
Acetobacter pasteurianus BP2201 alleviates alcohol‐induced hepatic and neuro‐toxicity and modulate gut microbiota in mice
Authors: Wen Xin , Wang Zheng , Liu Qi , Lessing Duncan James , Chu Weihua 
Published: June 2023

AbstractThe excessive consumption of alcohol results in a dysbiosis of the gut microbiota, which subsequently impairs the gut microbiota‐brain/liver axes and induces cognitive dysfunction and hepatic injury. This study aimed to investigate the potential effect of Acetobacter pasteurianus BP2201 in reducing the negative effects of alcohol consumption on cognitive function and liver health by modulating the gut microbiota‐brain/liver axes. Treatment with A. pasteurianus BP2201 improved alcohol‐induced hippocampal damage, suppressed neuroinflammation, promoted neuroprotein expression in the hippocampus and enhanced cognitive function. At the same time, A. pasteurianus BP2201 can also reduce serum lipid levels, relieve oxidative stress, inhibit TLR4/MyD88/NF‐κB pathway, reduce the secretion of TNF‐α and IL‐1β, so as to improve alcoholic liver injury. Concomitantly, the treatment with A. pasteurianus BP2201 leads to a shift in the intestinal microbiota structure towards that of healthy individuals, inhibiting the proliferation of harmful bacteria and promoting the recovery of beneficial bacteria. In addition, it also improves brain cognitive dysfunction and liver health by affecting the gut microbiota‐brain/liver axes by promoting the synthesis of relevant amino acids and the metabolism of nucleotide base components. These findings demonstrate the potential of regulating the gut microbiome and gut microbiota‐brain/liver axes to mitigate alcohol‐induced disease.