bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and current palaeobiological understanding of “Keratosa”-type non-spicular demosponge fossils in carbonates: with a new example from the lowermost Triassic, Armenia
Authors: Luo Cui , Pei Yu , Richoz Sylvain , Li Qijian , Reitner Joachim 
Published: July 2022

AbstractFossilised fibrous skeletons of non-spicular demosponges have been reported in carbonates throughout the Phanerozoic and recently from rocks dated back to 890 Ma ago. These records expanded our understanding of metazoans in multiple aspects, including their early evolution, the cryptic ecology in fossil reefs, and recovery after mass extinction events. However, debates and confusion persist on the differentiation of these fossils from other biogenic or abiotic structures. Here we propose six identification criteria based on established taphonomical models and biological characteristics of these sponges (“Keratosa”sensuMinchin, 1900). Besides, sponge fossils of this kind from the lowermost Triassic of Chanakhchi (Armenia) are described with a 3-D reconstruction to exemplify the application of these criteria in the recognition of such organisms. Subsequently, the state-of-the-art understanding of the taxonomy and evolution of these fossil sponges, a previously poorly addressed topic, is summarized. The morphology of the Triassic Chanakhchi fossils indicates an affinity with Verongimorphs, a group that may have evolved by the Cambrian Age 3. Other than that, more efforts are still required to explore the taxonomic diversity and evolutionary details in the accumulating data of these fossil non-spicular demosponges.
Bird assemblages in a peri-urban landscape in eastern India
Authors: Karjee Ratnesh , Palei Himanshu Shekhar , Konwar Abhijit , Gogoi Anshuman , Mishra Rabindra Kumar 
Published: July 2022

AbstractAcross the tropics, human settlements and agricultural lands have rapidly replaced the natural habitat; however, our understanding of the biodiversity value in such human-dominated landscapes is limited. To study the effects of heterogeneous habitats on bird diversity in the peri-urban landscape, we surveyed four different habitat types (residential areas, cropland and wasteland, water bodies, and sal forest) from February 2018 to January 2019. During the survey, 117 bird species were recorded belonging to 48 families and 98 genera in the study area. We observed that cropland and wasteland harboured rich avian diversity, among other sites. Both the Non-parametric Multidimensional Scale (NMDS) and one-way ANOVA Significant Test showed significant variations in bird species composition among habitats. Our study could be helpful in future conservation and management of the birds’ diversity to make peri-urban habitats more favorable.
Discovering functionally important sites in proteins
Authors: Cagiada Matteo , Bottaro Sandro , Lindemose Søren , Schenstrøm Signe M. , Stein Amelie , Hartmann-Petersen Rasmus , Lindorff-Larsen Kresten 
Published: July 2022

AbstractProteins play important roles in biology, biotechnology and pharmacology, and missense variants are a common cause of disease. Discovering functionally important sites in proteins is a central but difficult problem because of the lack of large, systematic data sets. Sequence conservation can highlight residues that are functionally important but is often convoluted with a signal for preserving structural stability. We here present a machine learning method to predict functional sites by combining statistical models for protein sequences with biophysical models of stability. We train the model using multiplexed experimental data on variant effects and validate it broadly. We show how the model can be used to discover active sites, as well as regulatory and binding sites. We illustrate the utility of the model by prospective prediction and subsequent experimental validation on the functional consequences of missense variants inHPRT1which may cause Lesch-Nyhan syndrome, and pinpoint the molecular mechanisms by which they cause disease.
Sleep cycle-dependent vascular dynamics enhance perivascular cerebrospinal fluid flow and solute transport
Authors: Bojarskaite Laura , Bjørnstad Daniel M. , Vallet Alexandra , Binder Kristin M. Gullestad , Cunen Céline , Heuser Kjell , Kuchta Miroslav , Mardal Kent-Andre , Enger Rune 
Published: July 2022

ABSTRACTPerivascular spaces (PVS) are important highways for fluid and solute transport in the brain enabling efficient waste clearance during sleep. Using two-photon imaging of naturally sleeping mice we demonstrate sleep cycle-dependent PVS dynamics – slow, large-amplitude oscillations in NREM, a reduction in REM and an enlargement upon awakening at the end of a sleep cycle. By biomechanical modeling we demonstrate that these sleep cycle-dependent PVS dynamics drive fluid flow and solute transport.
EEG frequency tagging evidence of intact social interaction recognition in adults with autism
Authors: Oomen Danna , Cracco Emiel , Brass Marcel , Wiersema Jan R. 
Published: July 2022

AbstractTo explain the social difficulties in autism, a large amount of research has been conducted on the neural correlates of social perception. However, this research has mostly used basic social stimuli (e.g. eyes, faces, hands, single agent), not resembling the complexity of what we encounter in our daily social lives, and as such, the situations people with autism experience difficulties in. A more complex stimulus that we do come across often and is also highly relevant for social functioning is that of third-party social interactions. Here, we investigated if individuals with and without autism process third-party social interactions differently. More specifically, we measured neural responses to social scenes depicting either social interaction or not with an electroencephalogram (EEG) frequency tagging task and compared these responses between adults with and without autism (N = 61). The results revealed an enhanced response to social scenes with interaction, replicating previous findings in a neurotypical sample (Oomen et al., 2022). Crucially, this effect was found in both groups with no difference between them. This suggest that social interaction recognition is not anomalous in adults with autism and cannot explain the social difficulties adults with autism experience.Lay abstractPeople with autism have social difficulties and are thought to experience the world differently. To better understand these differences, research has studied how the brain of people with and without autism processes social stimuli. However, this research has mostly used basic social stimuli (e.g. eyes, faces, hands, and single agents). Such stimuli do not resemble the complexity of daily life, where we typically do not come across isolated body parts, but instead have to make sense of complex social scenes with multiple people. To do so, it is imperative that we are able to recognize social interaction. Hence, if social interaction processing is anomalous, this could have pervasive consequences for social functioning more generally. Here, we used brain imaging to test if adults with autism process social interaction scenes differently than adults without autism. In line with previous findings from a neurotypical sample (Oomen et al. (2022), we found that social scenes depicting interaction elicited stronger brain responses than social scenes not depicting interaction. Crucially, this effect was found in both groups with no difference between them. These findings suggest that the fundamental process of social interaction recognition is not anomalous in adults with autism.
The functional form of value normalization in human reinforcement learning
Authors: Bavard Sophie , Palminteri Stefano 
Published: July 2022

AbstractReinforcement learning research in humans and other species indicates that rewards are represented in a context-dependent manner. More specifically, reward representations seem to be normalized as a function of the value of the alternative options. The dominant view postulates that value context-dependence is achieved via a divisive normalization rule, inspired by perceptual decision-making research. However, behavioral and neural evidence points to another plausible mechanism: range normalization. Critically, previous experimental designs were ill-suited to disentangle the divisive and the range normalization accounts, which generate similar behavioral predictions in many circumstances. To address this question, we designed a new learning task where we manipulated, across learning contexts, the number of options and the value ranges. Behavioral and computational analyses falsify the divisive normalization account and rather provide support for the range normalization rule. Together, these results shed new light on the computational mechanisms underlying context-dependence in learning and decision-making.
Emphasis on peripheral vision is accompanied by pupil dilation
Authors: Vilotijević Ana , Mathôt Sebastiaan 
Published: July 2022

AbstractPeople are best able to detect stimuli in peripheral vision when their pupils are large, and best able to discriminate stimuli in central vision when their pupils are small. However, it is unclear whether our visual system makes use of this by dilating the pupils when attention is directed towards peripheral vision. Therefore, we tested whether pupil size adapts to the ‘breadth’ of attention. We found that pupils dilate with increasing attentional breadth, both when attention is diffusely spread and when attention is directed at specific locations in peripheral vision. We further found a correlation with performance, suggesting a functional benefit of this effect. Based on our results and others, we propose that cognitively driven pupil dilation is not an epiphenomenal marker of Locus Coeruleus activity, as is often assumed, but rather is an adaptive response that reflects an emphasis on peripheral vision.
The Phylotranscriptomic Hourglass Pattern in Fungi: An Updated Model
Authors: Xie Yichun , Kwan Hoi Shan , Chan Po Lam , Wu Wen Jie , Chiou Jiachi , Chang Jinhui 
Published: July 2022

AbstractThe “developmental hourglass” describes the morphological convergence to a conserved form at mid-stages of animal embryogenesis. The molecular hourglass pattern during embryogenesis was also identified across kingdoms. Previously, we reported young fruiting body as the conserved “waist” in mushroom-forming “developmental hourglass”. However, its robustness is doubted because of the fungal diversity. Additionally, fungi lack embryogenesis, and develop directly from spore to hyphae with morphological similarities during the transition. Here, we updated the “developmental hourglass” model in the life cycle of fungi, namely, spore germination, vegetative growth, and sexual reproduction. Germinating spores, both sexual and asexual, showed the strongest transcriptomic conservation signals across the phyla Mucoromycota, Ascomycota and Basidiomycota. Cross kingdom comparisons revealed high expression levels of “information storage and processing” genes at the waist stages of embryonic and non-embryonic developments in animals, plants, and fungi. The “developmental hourglass” might reflect the mutual transcriptome switches on developmental transitions in eukaryotes that are additional to embryonic organogenesis.HighlightsUpdated fungal molecular “developmental hourglass” model in the life cycle of fungiGerminating spores are the evolutionarily conserved “waist” across fungal phylaHigh expression levels of “information storage and processing” genes at the waist stages in the embryonic and non-embryonic hourglasses across kingdoms“Developmental hourglass” may reflect the mutual transcriptome switches on developmental transitions in eukaryotes
Individual-level Functional Connectivity Predicts Cognitive Control Efficiency
Authors: Deck Benjamin L. , Kelkar Apoorva , Erickson Brian , Erani Fareshte , McConathey Eric , Sacchetti Daniela , Faseyitan Olu , Hamilton Roy , Medaglia John D. 
Published: July 2022

AbstractCognitive control (CC) is a vital component of cognition associated with problem-solving in everyday life. Many neurological and neuropsychiatric conditions have deficits associated with CC. CC is composed of multiple behaviors including switching, inhibiting, and updating. The fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON) and the dorsal default-mode network (dorsal-DMN) have been associated with switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about CC behaviors is still unclear. In the current study, participants performed two in-scanner tasks that required switching and inhibiting. We then used a series of support vector regression (SVR) models containing individually-estimated functional connectivity between the networks of interest derived during tasks and at rest to predict inhibition and switching behaviors in individual subjects. We observed that the combination of between-network connectivity from these individually estimated functional networks predicted accurate and timely inhibition and switching behaviors in individuals. We also observed that the relationships between canonical task-positive and task-negative networks predicted inhibiting and switching behaviors. Finally, we observed a functional dissociation between the FPCN-A and FPCNB during rest, and task performance predicted inhibiting and switching behaviors. These results suggest that individually estimated networks can predict individual CC behaviors, that between-network functional connectivity estimated within individuals is vital to understanding how CC arises, and that the fractionation of the FPCN and the DMN may be associated with different behaviors than their canonically accepted behaviors.
leptin b and its regeneration enhancer illustrate the regenerative features of zebrafish hearts
Authors: Shin Kwangdeok , Begeman Ian J. , Cao Jingli , Kang Junsu 
Published: July 2022

AbstractZebrafish possess a remarkable regenerative capacity, which is mediated by the induction of various genes upon injury. Injury-dependent transcription is governed by the tissue regeneration enhancer elements (TREEs). Here, we utilized leptin b (lepb), an injury-specific factor, and its TREE to dissect heterogeneity of non-cardiomyocytes (CMs) in regenerating zebrafish hearts. Our single-cell RNA sequencing (scRNA-seq) analysis demonstrated that the endothelium/endocardium(EC) is activated to induce distinct subpopulations upon cardiac injury. We demonstrated that lepb can be utilized as a regeneration-specific marker to subset injury-activated ECs. lepb+ ECs robustly induce pro-regenerative factors, implicating lepb+ ECs as a signaling center to interact with other cardiac cells. Our scRNA-seq analysis identified that lepb is also produced by specific subpopulation of epicardium (Epi) and epicardium-derived cells (EPDCs). To determine lepb labels injury-emerging non-CM cells, we tested the activity of lepb-linked regeneration enhancer (LEN) with chromatin accessibility profiles and transgenic lines. While non-detectable in uninjured hearts, LEN directs EC and Epi/EPDC expression upon injury. The endogenous LEN activity was assessed using LEN deletion lines, demonstrating that LEN deletion abolished injury-dependent expression of lepb, but not other nearby genes. Our integrative analyses identify regeneration-emerging cell types and factors, leading to the discovery of regenerative features of hearts.
Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint
Authors: Kloster Michael , Burfeid-Castellanos Andrea M. , Langenkämper Daniel , Nattkemper Tim W. , Beszteri Bánk 
Published: July 2022

AbstractDiatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly used in aquatic ecology and biomonitoring. One key step in emerging digital variants of such investigations is segmentation, a task that has been addressed before, but usually in manually captured megapixel-sized images of individual diatom cells with a mostly clean background. In this paper, we applied deep learning-based segmentation methods to gigapixel-sized, high-resolution scans of diatom slides with a realistically cluttered background. This setup requires large slide scans to be subdivided into small images (tiles) to apply a segmentation model to them. This subdivision (tiling), when done using a sliding window approach, often leads to cropping relevant objects at the boundaries of individual tiles. We hypothesized that in the case of diatom analysis, reducing the amount of such cropped objects in the training data can improve segmentation performance by allowing for a better discrimination of relevant, intact frustules or valves from small diatom fragments, which are considered irrelevant when counting diatoms. We tested this hypothesis by comparing a standard sliding window / fixed-stride tiling approach with two new approaches we term object-based tile positioning with and without object integrity constraint. With all three tiling approaches, we trained Mask-R-CNN and U-Net models with different amounts of training data and compared their performance. Object-based tiling with object integrity constraint led to an improvement in pixel-based precision by 12–17 percentage points without substantially impairing recall when compared with standard sliding window tiling. We thus propose that training segmentation models with object-based tiling schemes can improve diatom segmentation from large gigapixel-sized images but could potentially also be relevant for other image domains.
Organization and Dynamics of Crosslinked Actin Filaments in Confined Environments
Authors: Akenuwa Oghosa H. , Abel Steven M. 
Published: July 2022

ABSTRACTThe organization of the actin cytoskeleton is impacted by the interplay between physical confinement, features of crosslinking proteins, and deformations of semiflexible actin filaments. Some crosslinking proteins preferentially bind filaments in parallel, while others bind more indiscriminately. However, a quantitative understanding of how the mode of binding influences the assembly of actin networks in confined environments is lacking. Here we employ coarse-grained computer simulations to study the dynamics and organization of semiflexible actin filaments in confined regions upon the addition of crosslinkers. We characterize how the emergent behavior is influenced by the system shape, the number and type of crosslinking proteins, and the length of filaments. Structures include isolated clusters of filaments, highly connected filament bundles, and networks of interconnected bundles and loops. Elongation of one dimension of the system promotes the formation of long bundles that align with the elongated axis. Dynamics are governed by rapid crosslinking into aggregates, followed by a slower change in their shape and connectivity. Crosslinking decreases the average bending energy of short or sparsely connected filaments by suppressing shape fluctuations. However, it increases the average bending energy in highly connected networks because filament bundles become deformed and small numbers of filaments exhibit long-lived, highly unfavorable configurations. Indiscriminate crosslinking promotes the formation of high-energy configurations due to the increased likelihood of unfavorable, difficult-to-relax configurations at early times. Taken together, this work demonstrates physical mechanisms by which crosslinker binding and physical confinement impact the emergent behavior of actin networks, which is relevant both in cells and in synthetic environments.SIGNIFICANCEThe actin cytoskeleton is vital for intracellular transport, yet it remains challenging to understand how its organization is impacted by the interplay between physical confinement and the crosslinking of semiflexible actin filaments. In this study, we explore how the mode of crosslinker binding and the shape of the confining region impact the assembly and organization of actin filaments. The dynamics are governed by rapid crosslinking of spatially proximal filaments into aggregates, followed by slower relaxation of their shape and connectivity. Indiscriminate crosslinking promotes more highly connected networks, greater curvature of long filament bundles, and a subset of filaments in highly unfavorable configurations. The results provide insight into mechanisms influencing the cytoskeleton in cells and in reconstituted systems.
Changes in adenosine and neurotrophic signaling in the SOD1G93A mouse model of amyotrophic lateral sclerosis: modulation by chronic caffeine intake
Authors: Rei Nádia , Valente Cláudia A. , Vaz Sandra H. , Farinha-Ferreira Miguel , Ribeiro Joaquim A. , Sebastião Ana M. 
Published: July 2022

AbstractAmyotrophic lateral sclerosis (ALS) is characterized by the progressive degeneration of corticospinal tract motor neurons. Previous studies showed that adenosine-mediated neuromodulation is disturbed in ALS and that vascular endothelial growth factor (VEGF) has a neuroprotective function in ALS mouse models. We evaluated how adenosine (A1R and A2AR) and VEGF (VEGFA, VEGFB, VEGFR-1 and VEGFR-2) system markers are altered in the cortex and spinal cord of pre-symptomatic and symptomatic SOD1G93A mice. We then assessed if/how chronic treatment of SOD1G93A mice with a widely consumed adenosine receptor antagonist, caffeine, modulates VEGF system and/or the levels of Brain-derived Neurotrophic Factor (BDNF), known to be under control of A2AR. We found out decreases in A1R and increases in A2AR levels even before disease onset. Concerning the VEGF system, we detected increases of VEGFB and VEGFR-2 levels in the spinal cord at pre-symptomatic stage, which reverses at the symptomatic stage, and decreases of VEGFA levels in the cortex, in very late disease states. Chronic treatment with caffeine rescued cortical A1R levels in SOD1G93A mice, bringing them to control levels, while rendering VEGF signaling nearly unaffected. In contrast, BDNF levels were significantly affected in SOD1G93A mice treated with caffeine, being decreased in the cortex and increased in spinal the cord. Altogether, these findings suggest an early dysfunction of the adenosinergic system in ALS and highlights the possibility that the negative influence of caffeine previously reported in ALS animal models results from interference with BDNF rather than with the VEGF signaling molecules.
Autism excitation-inhibition imbalance linked to brain hyperconnectivity: An analysis based on 657 autistic subjects
Authors: Rasero Javier , Jimenez-Marin Antonio , Diez Ibai , Toro Roberto , Hasan Mazahir T. , Cortes Jesus M. 
Published: July 2022

AbstractThe large heterogeneity in autism spectrum disorder (ASD) is a major drawback for the development of therapies. Here, we apply consensus-subtyping strategies based on functional connectivity patterns to a population of N=657 quality-assured autistic subjects. We found two major subtypes (each divided hierarchically into several minor subtypes): Subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing controls) and subtype 2, hyperconnectivity. The two subtypes did not differ in structural imaging metrics in any of the regions analyzed (64 cortical and 14 subcortical), nor in any of the behavioral scores (including Intelligence Quotient, ADI and ADOS). Finally, we used the Allen Human Brain Atlas of gene transcription to show that subtype 2, corresponding with about 42% of all patients, had significant enrichment (after multiple comparisons correction) to excitation-inhibition (E/I) imbalance, a leading reported mechanism in the developmental pathophysiology of ASD. Altogether, our results support a link between E/I imbalance and brain hyperconnectivity in ASD, an association that does not exist in hypoconnected autistic subjects.