Miracle-dz/UniFAR-FTUs huggingface dataset:
Attentional Fluctuations Influence the Neural Fidelity and Connectivity of Stimulus Representations

Attention is thought to facilitate both the representation of task-relevant features and the communication of these representations across large-scale brain networks. However, attention is not “all or none,” but rather it fluctuates between stable/accurate (in-the-zone) and variable/error-prone (out-of-the-zone) states. Here we ask how different attentional states relate to the neural processing and transmission of task-relevant information. Specifically, during in-the-zone periods: (1) Do neural representations of task stimuli have greater fidelity? (2) Is there increased communication of this stimulus information across large-scale brain networks? Finally, (3) can the influence of performance-contingent reward be differentiated from zone-based fluctuations? To address these questions, we used fMRI and representational similarity analysis during a visual sustained attention task (the gradCPT). Participants (n = 16) viewed a series of city or mountain scenes, responding to cities (90% of trials) and withholding to mountains (10%). Representational similarity matrices, reflecting the similarity structure of the city exemplars (n = 10), were computed from visual, attentional, and default mode networks. Representational fidelity (RF) and representational connectivity (RC) were quantified as the interparticipant reliability of representational similarity matrices within (RF) and across (RC) brain networks. We found that being in the zone was characterized by increased RF in visual networks and increasing RC between visual and attentional networks. Conversely, reward only increased the RC between the attentional and default mode networks. These results diverge with analogous analyses using functional connectivity, suggesting that RC and functional connectivity in tandem better characterize how different mental states modulate the flow of information throughout the brain.
Changes in Heart Rate and Its Regulation by the Autonomic Nervous System Do Not Differ Between Forced and Voluntary Exercise in Mice

Most exercise studies in mice have relied on forced training which can introduce psychological stress. Consequently, the utility of mouse models for understanding exercise-mediated effects in humans, particularly autonomic nervous system (ANS) remodeling, have been challenged. We compared the effects of voluntary free-wheel running vs. non-voluntary swimming on heart function in mice with a focus on the regulation of heart rate (HR) by the ANS. Under conditions where the total excess O2 consumption associated with exercise was comparable, the two exercise models led to similar improvements in ventricular function as well as comparable reductions in HR and its control by parasympathetic nervous activity (PNA) and sympathetic nervous activity (SNA), compared to sedentary mice. Both exercise models also increased HR variability (HRV) by similar amounts, independent of HR reductions. In all mice, HRV depended primarily on PNA, with SNA weakly affecting HRV at low frequencies. The differences in both HR and HRV between exercised vs. sedentary mice were eliminated by autonomic blockade, consistent with the similar intrinsic beating rates observed in atria isolated from exercised vs. sedentary mice. In conclusion, both forced and voluntary exercise induce comparable ventricular physiological remodeling as well as HR reductions and HR-independent enhancements of HRV which were both primarily dependent on increased PNA. New and noteworthy –No previous mouse studies have compared the effects of forced and voluntary exercise on the heart function and its modulation by the autonomic nervous system (ANS). –Both voluntary free-wheel running and forced swimming induced similar improvements in ventricular contractile function, reductions in heart rate (HR) and enhancements of HR variability (HRV). –HR regulation in exercised mice was linked to increased parasympathetic nerve activity and reduced sympathetic nerve activity. – HRV was independent of HR and depended primarily on PNA in both exercised and sedentary mice. – Complete cardiac autonomic blockade eliminated differences in both HR and HRV between exercised and sedentary mice.
Multiscale examination of cytoarchitectonic similarity and human brain connectivity

The human brain comprises an efficient communication network, with its macroscale connectome organization argued to be directly associated with the underlying microscale organization of the cortex. Here, we further examine this link in the human brain cortex by using the ultrahigh-resolution BigBrain dataset; 11,660 BigBrain profiles of laminar cell structure were extracted from the BigBrain data and mapped to the MRI based Desikan–Killiany atlas used for macroscale connectome reconstruction. Macroscale brain connectivity was reconstructed based on the diffusion-weighted imaging dataset from the Human Connectome Project and cross-correlated to the similarity of laminar profiles. We showed that the BigBrain profile similarity between interconnected cortical regions was significantly higher than those between nonconnected regions. The pattern of BigBrain profile similarity across the entire cortex was also found to be strongly correlated with the pattern of cortico-cortical connectivity at the macroscale. Our findings suggest that cortical regions with higher similarity in the laminar cytoarchitectonic patterns have a higher chance of being connected, extending the evidence for the linkage between macroscale connectome organization and microscale cytoarchitecture. Author Summary The human brain connectome organization has been suggested to associate with cytoarchitecture similarity. Here, we utilize the state-of-the-art ultrahigh-resolution BigBrain dataset and diffusion-weighted imaging dataset to examine this association. Our results show that cortical regions with higher cytoarchitecture similarity are more likely to be connected, as well as connected by stronger white matter tracts. This work further extends our understanding of the interaction between macroscale cortico-cortical connectivity organization and microscale cortical cytoarchitecture.
Fatty Acid-Induced Lipotoxicity in Pancreatic Beta-Cells During Development of Type 2 Diabetes

Type 2 diabetes is caused by chronic insulin resistance and progressive decline in beta-cell function. Optimal beta-cell function and mass is essential for glucose homeostasis and beta-cell impairment leads to the development of diabetes. Elevated levels of circulating fatty acids (FAs) and disturbances in lipid metabolism regulation are associated with obesity, and they are major factors influencing the increase in the incidence of type 2 diabetes. Chronic free FA (FFA) treatment induces insulin resistance and beta-cell dysfunction; therefore, reduction of elevated plasma FFA levels might be an important therapeutic target in obesity and type 2 diabetes. Lipid signals via receptors, and intracellular mechanisms are involved in FFA-induced apoptosis. In this paper, we discuss lipid actions in beta cells, including effects on metabolic pathways and stress responses, to help further understand the molecular mechanisms of lipotoxicity-induced type 2 diabetes.
Improving on Q & A Recurrent Neural Networks Using Noun-Tagging

Often, more time is spent on finding a model that works well, rather than tuning the model and working directly with the dataset. Our research began as an attempt to improve upon a simple Recurrent Neural Network for answering "simple" first-order questions (QA-RNN), developed by Ferhan Ture and Oliver Jojic, from Comcast Labs, using the SimpleQuestions dataset. Their baseline model, a bidirectional, 2-layer LSTM RNN and a GRU RNN, have accuracies of 0.94 and 0.90, for entity detection and relation prediction, respectively. We fine tuned these models by doing substantial hyper-parameter tuning, getting resulting accuracies of 0.70 and 0.80, for entity detection and relation prediction, respectively. An accuracy of 0.984 was obtained on entity detection using a 1-layer LSTM, where preprocessing was done by removing all words not part of a noun chunk from the question. 100% of the dataset was available for relation prediction, but only 20% of the dataset, was available for entity detection, which we believe to be much of the reason for our initial difficulties in replicating their result, despite the fact we were able to improve on their entity detection results.
Polydatin, Natural Precursor of Resveratrol, Promotes Osteogenic Differentiation of Mesenchymal Stem Cells

Bone loss and fractures are consequences of aging, diseases or traumas. Furthermore the increased number of aged people, due to the rise of life expectancy, needs more strategies to limit the bone loss and regenerate the lost tissue, ameliorating the life quality of patients. A great interest for non-pharmacological therapies based on natural compounds is emerging and focusing on the oligostilbene Polydatin, present in many kinds of fruits and vegetables, when resveratrol particularly in red wines. These molecules have been extensively studied due to their antioxidant and anti-inflammatory effects, showing more recently Resveratrol the ability to enhance osteogenic differentiation and bone formation. However, the clinical applications of Resveratrol are limited due to its low bioavailability and rapid metabolism, while its natural glycosilated precursor Polydatin shows better metabolic stability and major abundance in fresh fruits and vegetables. Nevertheless the role of Polydatin on osteogenic differentiation is still unexplored. Mesenchymal stem cells (MSCs) from dental tissues, such as dental bud stem cells (DBSCs), are able to differentiate toward osteogenic lineage: thus we investigated how Resveratrol and Polydatin influence the differentiation of DBSCs, eventually affecting bone formation. Our results showed that Polydatin increases MSCs osteogenic differentiation sharing similar properties with Resveratrol. These results encourage to deepen the effects of this molecule on bone health and its associated mechanisms of action, wishing for the future a successful use in bone loss prevention and therapy.
Integration of RNAi and RNA-seq Reveals the Immune Responses of Epinephelus coioides to sigX Gene of Pseudomonas plecoglossicida

Pseudomonas plecoglossicida is an important pathogen for aquaculture and causes high mortality in various marine fishes. Expression of sigX was found significantly up-regulated at 18°C than at 28°C, which was verified by quantitative real-time PCR (qRT-PCR). RNAi significantly reduced the content of sigX mRNA of P. plecoglossicida, whether in in vitro or in the spleen at all sampling time points. Compared with the wild-type strain, the infection of sigX-RNAi strain resulted in the onset time delay, and 20% reduction in mortality of Epinephelus coioides, as well as alleviates in the symptoms of E. coioides spleen. Compared with wild-type strain, the gene silence of sigX in P. plecoglossicida resulted in a significant change in transcriptome of infected E. coioides. The result of gene ontology and KEGG analysis on E. coioides showed that genes of serine-type endopeptidase and chemokine signaling pathway, coagulation and complement system, and intestinal immune network for IgA production pathway were mostly affected by sigX of P. plecoglossicida. Meanwhile, the immune genes were associated with different number of miRNA and lncRNA, and some miRNAs were associated with more than one gene at the same time. The results indicated that sigX was a virulent gene of P. plecoglossicida. The up-regulation of the immune pathways made E. coioides more likely to kill sigX-RNAi strain than the wild-type strain of P. plecoglossicida, while the immune genes were regulated by miRNA and lncRNA by a complex mode.
The Role of Autoimmunity in the Pathogenesis of Sudden Sensorineural Hearing Loss

Sudden sensorineural hearing loss (SSHL) is a clinically common acute symptom in otolaryngology. Although the incidence of SSHL has increased around the world in recent years, the etiology of the disease is still unclear. It has been reported that infections, ototoxic drugs, membrane labyrinth rupture, carcinomas, circulatory system diseases, autoimmune diseases, brain lesions, mental diseases, congenital or inherited diseases, and so on, are all risk factors for SSHL. Here, we discuss the autoimmune mechanisms behind SSHL, which might be induced by type II–IV allergic reactions. We also introduce the main immunosuppressive medications that have been used to treat SSHL, which will help us to identify potential targets for immune therapy.
Common and Contrasting Areas of Activation for Abstract and Concrete Concepts: An H215O PET Study

Lesion studies indicate that the lateral and inferior temporal cortex is a critical area of semantic memory storage, but little is known about the cortical organization of semantics within this area. One proposition has been that dominant physical characteristics of objects (structure, motility) are determining factors. A positron emission tomography experiment using the H215O bolus method was performed to test this hypothesis by contrasting activation for concrete and abstract concepts. Unlike previous studies that considered this question, the task required explicit word meaning judgments, and blocks of trials were designed to be of equal difficulty for the two word classes. The task required elderly participants to read aloud the pair of words that was closer in meaning (e.g., spadeshovel vs. spadecarpet). Subtraction analyses that compared the semantic judgment tasks with a baseline condition indicated that both abstract and concrete concepts activated the left lateral temporal cortex. A direct comparison of abstract versus concrete scans indicated differences in the lateralization of fusiform activation. We conclude that although concreteness might be a critical factor in the fusiform cortex, it is not dominant in the lateral temporal cortex. A multistudy overview suggests that tasks that focus on one concept per trial activate areas posterior to y = 40, whereas those that invoke several concepts, as in the present study, activate areas anterior to this. Increased processing complexity may proceed in a posterior anterior direction in the lateral temporal cortex.
Native Language Identification With Classifier Stacking and Ensembles

Ensemble methods using multiple classifiers have proven to be among the most successful approaches for the task of Native Language Identification (NLI), achieving the current state of the art. However, a systematic examination of ensemble methods for NLI has yet to be conducted. Additionally, deeper ensemble architectures such as classifier stacking have not been closely evaluated. We present a set of experiments using three ensemble-based models, testing each with multiple configurations and algorithms. This includes a rigorous application of meta-classification models for NLI, achieving state-of-the-art results on several large data sets, evaluated in both intra-corpus and cross-corpus modes.
Managing Successional Stage Heterogeneity to Maximize Landscape-Wide Biodiversity of Aquatic Vegetation in Ditch Networks

The presence of a high diversity of different successional stages in a landscape may help to conserve and promote landscape-wide biodiversity. A strategy to achieve this is using Cyclic Rejuvenation through Management (CRM), an approach employed in a variety of different ecosystems. CRM periodically resets the successional stages in a landscape. For aquatic systems this constitutes vegetation removal and dredging. For this approach to be useful (a) successional stages are required to be different in community composition and (b) these differences need to be caused by true replacement of species between stages. While potentially valid, these assumptions are not generally tested prior to application of CMR. In this study we test these assumptions to explore the usefulness of managing on successional stage heterogeneity for maximizing landscape-wide aquatic plant diversity. We carried out vegetation surveys in the ditch networks of 21 polder landscapes in Netherlands, each containing 24 ditch reaches. Using a clustering approach combined with insight from literature on vegetation succession in these systems we assigned our sampled communities to defined successional stages. After partitioning landscape diversity into its alpha and beta components, we quantified the relative importance of replacement among successional stages. Next, through scenario analyses based on simulations we studied the effects of reducing successional stage heterogeneity on landscape-wide biodiversity. Results showed that differences in community composition among successional stages were a potentially important factor contributing to landscape diversity. Early successional stages were characterized by higher replacement of species compared to late successional stages. In a scenario of gradual decrease of heterogeneity through the systematic loss of the earliest successional stages we found 20% of the species richness in a polder was lost, pointing toward the importance of maintaining early successional stages in a polder. This makes a compelling case for application of CRM within agricultural drainage ditch landscapes to maximize regional aquatic plant diversity. While applied to drainage ditch systems, our data-driven approach is broadly applicable to other systems and may help in providing first indications of the potential of the CRM approach. We argue that CRM may maintain and promote regional biodiversity without compromising the hydrological function of the systems.
The latest gossip on BFT consensus

The paper presents Tendermint, a new protocol for ordering events in a distributed network under adversarial conditions. More commonly known as Byzantine Fault Tolerant (BFT) consensus or atomic broadcast, the problem has attracted significant attention in recent years due to the widespread success of blockchain-based digital currencies, such as Bitcoin and Ethereum, which successfully solved the problem in a public setting without a central authority. Tendermint modernizes classic academic work on the subject and simplifies the design of the BFT algorithm by relying on a peer-to-peer gossip protocol among nodes.
Maintaning maximal matching with lookahead

In this paper we study the problem of fully dynamic maximal matching with lookahead. In a fully dynamic $n$-vertex graph setting, we have to handle updates (insertions and removals of edges), and answer queries regarding the current graph, preferably with a better time bound than that when running the trivial deterministic algorithm with worst-case time of $O(m)$ (where $m$ is the all-time maximum number of the edges) and recompute the matching from scratch each time a query arrives. We show that a maximal matching can be maintained in an (undirected) general graph with a deterministic amortized update cost of $O(\log m)$, provided that a lookahead of length $m$ is available, i.e. we can ``take a peek'' at the next $m$ update operations in advance.
Blood Gene Expression and Vascular Function Biomarkers in Professional Saturation Diving

Saturation diving is an established way to conduct subsea operations with human intervention. While working, the divers must acclimatize to the hyperbaric environments. In this study, genome-wide gene expression and selected plasma biomarkers for vascular function were investigated. We also examined whether antioxidant vitamin supplements affected the outcome. The study included 20 male professional divers, 13 of whom took vitamin C and E supplements in doses of 1,000 and 30 mg daily during saturation periods that lasted 7–14 days. The dives were done in a heliox atmosphere with 40 kPa oxygen partial pressure (ppO2) to a depth of 100–115 m of sea-water (msw), from which the divers performed in-water work excursions to a maximum depth of 125 msw with 60 kPa ppO2. Venous blood was collected immediately before and after saturation. Following gene expression profiling, post-saturation gene activity changes were analyzed. Protein biomarkers for inflammation, endothelial function, and fibrinolysis: Il-6, CRP, ICAM-1, fibrinogen, and PAI-1, were measured in plasma. Post-saturation gene expression changes indicated acclimatization to elevated ppO2 by extensive downregulation of factors involved in oxygen transport, including heme, hemoglobin, and erythrocytes. Primary endogenous antioxidants; superoxide dismutase 1, catalase, and glutathione synthetase, were upregulated, and there was increased expression of genes involved in immune activity and inflammatory signaling pathways. The antioxidant vitamin supplements had no effect on post-saturation gene expression profiles or vascular function biomarkers, implying that the divers preserved their homeostasis through endogenous antioxidant defenses.
Subject specificity of the correlation between large-scale structural and functional connectivity

Structural connectivity (SC), the physical pathways connecting regions in the brain, and functional connectivity (FC), the temporal co-activations, are known to be tightly linked. However, the nature of this relationship is still not understood. In the present study, we examined this relation more closely in six separate human neuroimaging datasets with different acquisition and preprocessing methods. We show that using simple linear associations, the relation between an individual’s SC and FC is not subject-specific for five of the datasets. Subject-specificity of SC-FC fit is achieved only for one of the six datasets, the multi-modal Glasser HCP parcellated dataset. We show that subject-specificity of SC-FC correspondence is limited across datasets due to relatively small variability between subjects in SC compared to the larger variability in FC.
Optimized connectome architecture for sensory-motor integration

The intricate connectivity patterns of neural circuits support a wide repertoire of communication processes and functional interactions. Here we systematically investigate how neural signaling is constrained by anatomical connectivity in the mesoscale Drosophila (fruit fly) brain network. We use a spreading model that describes how local perturbations, such as external stimuli, trigger global signaling cascades that spread through the network. Through a series of simple biological scenarios we demonstrate that anatomical embedding potentiates sensory-motor integration. We find that signal spreading is faster from nodes associated with sensory transduction (sensors) to nodes associated with motor output (effectors). Signal propagation was accelerated if sensor nodes were activated simultaneously, suggesting a topologically mediated synergy among sensors. In addition, the organization of the network increases the likelihood of convergence of multiple cascades towards effector nodes, thereby facilitating integration prior to motor output. Moreover, effector nodes tend to coactivate more frequently than other pairs of nodes, suggesting an anatomically enhanced coordination of motor output. Altogether, our results show that the organization of the mesoscale Drosophila connectome imparts privileged, behaviorally relevant communication patterns among sensors and effectors, shaping their capacity to collectively integrate information.Author SummaryThe complex network spanned by neurons and their axonal projections promotes a diverse set of functions. In the present report, we study how the topological organization of the fruit fly brain supports sensory-motor integration. Using a simple communication model, we demonstrate that the topology of this network allows efficient coordination among sensory and motor neurons. Our results suggest that brain network organization may profoundly shape the functional repertoire of this simple organism.