bluuebunny/crossref_metadata_2025 huggingface dataset:
Social control is associated with increased reproductive skew in a wild mammal
Authors: Maldonado-Chaparro Adriana A. , Philson Conner S. , Zhang Xinping , Blumstein Daniel T.
Published: June 2024

In group-living species, reproductive variation among individuals of the same sex is widespread. By identifying the mechanisms underlying this reproductive skew, we gain fundamental insights into the evolution and maintenance of sociality. A common mechanism, social control, is typically studied by quantifying dominance, which is one of many attributes of sociality that describes how individuals exert influence on others and is an incomprehensive measure of social control as it accounts only for direct relationships. Here, we use the global reaching centrality (GRC), which quantifies the degree of hierarchy in a social network by accounting for both direct and indirect social relationships. Using a wild, free-living population of adult female yellow-bellied marmots (
Marmota flaviventris
), we found a positive relationship between the reproductive skew index and GRC: more despotic social groups have higher reproductive skew. The GRC was stronger predictor for skew than traditional measures of social control (i.e. dominance). This allows deeper insights into the diverse ways individuals control other group members’ reproduction, a core component in the evolution of sociality. Future studies of skew across taxa may profit by using more comprehensive, network-based measures of social control.
Metabolic scaling of an invasive mussel depends on temperature and chemical cues from an invasive predator
Authors: Gjoni V. , Marchessaux G. , Glazier D. S. , Wesner J. S. , Bosch-Belmar M. , Mancuso F. P. , Tantillo M. F. , Marsiglia N. , Sarà G.
Published: June 2024

Metabolism drives various biological processes, potentially influencing the ecological success and evolutionary fitness of species. Understanding diverse metabolic rates is fundamental in biology. Mechanisms underlying adaptation to factors like temperature and predation pressure remain unclear. Our study explored the role of temperature and predation pressure in shaping the metabolic scaling of an invasive mussel species (
Brachidontes pharaonis
). Specifically, we performed laboratory-based experiments to assess the effects of phenotypic plasticity on the metabolic scaling by exposing the mussels to water conditions with and without predator cues from another invasive species (the blue crab,
Callinectes sapidus
) across various temperature regimes. We found that temperature effects on metabolic scaling of the invasive mussels are mediated by the presence of chemical cues of an invasive predator, the blue crab. Investigating temperature–predator interactions underscores the importance of studying the ecological effects of global warming. Our research advances our understanding of how environmental factors jointly impact physiological processes.
The speed of neutral evolution on graphs
Authors: Gao Shun , Liu Yuan , Wu Bin
Published: June 2024

The speed of evolution on structured populations is crucial for biological and social systems. The likelihood of invasion is key for evolutionary stability. But it makes little sense if it takes long. It is far from known what population structure slows down evolution. We investigate the absorption time of a single neutral mutant for all the 112 non-isomorphic undirected graphs of size 6. We find that about three-quarters of the graphs have an absorption time close to that of the complete graph, less than one-third are accelerators, and more than two-thirds are decelerators. Surprisingly, determining whether a graph has a long absorption time is too complicated to be captured by the joint degree distribution. Via the largest sojourn time, we find that echo-chamber-like graphs, which consist of two homogeneous graphs connected by few sparse links, are likely to slow down absorption. These results are robust for large graphs, mutation patterns as well as evolutionary processes. This work serves as a benchmark for timing evolution with complex interactions, and fosters the understanding of polarization in opinion formation.
Characterization of Aspergillus fumigatus secretome during sublethal infection of Galleria mellonella larvae
Authors: Curtis Aaron , Dobes Pavel , Marciniak Jacek , Hurychova Jana , Hyrsl Pavel , Kavanagh Kevin
Published: June 2024

Introduction. The fungal pathogen Aspergillus fumigatus can induce prolonged colonization of the lungs of susceptible patients, resulting in conditions such as allergic bronchopulmonary aspergillosis and chronic pulmonary aspergillosis.

Hypothesis. Analysis of the A. fumigatus secretome released during sub-lethal infection of G. mellonella larvae may give an insight into products released during prolonged human colonisation.

Methodology.
Galleria mellonella larvae were infected with A. fumigatus, and the metabolism of host carbohydrate and proteins and production of fungal virulence factors were analysed. Label-free qualitative proteomic analysis was performed to identify fungal proteins in larvae at 96 hours post-infection and also to identify changes in the Galleria proteome as a result of infection.

Results. Infected larvae demonstrated increasing concentrations of gliotoxin and siderophore and displayed reduced amounts of haemolymph carbohydrate and protein. Fungal proteins (399) were detected by qualitative proteomic analysis in cell-free haemolymph at 96 hours and could be categorized into seven groups, including virulence (n = 25), stress response (n = 34), DNA repair and replication (n = 39), translation (n = 22), metabolism (n = 42), released intracellular (n = 28) and cellular development and cell cycle (n = 53). Analysis of the Gallerial proteome at 96 hours post-infection revealed changes in the abundance of proteins associated with immune function, metabolism, cellular structure, insect development, transcription/translation and detoxification.

Conclusion. Characterizing the impact of the fungal secretome on the host may provide an insight into how A. fumigatus damages tissue and suppresses the immune response during long-term pulmonary colonization.
Symmetry and Generalization in Local Learning of Predictive Representations
Authors: Keck Janis , Barry Caswell , Doeller Christian F. , Jost Jürgen
Published: June 2024

In spatial cognition, the Successor Representation (SR) from reinforcement learning provides a compelling candidate of how predictive representations are used to encode space. In particular, hippocampal place cells are hypothesized to encode the SR. Here, we investigate how varying the temporal symmetry in learning rules influences those representations. To this end, we use a simple local learning rule which can be made insensitive to the temporal order. We analytically find that a symmetric learning rule rule results in a successor representation under a symmetrized version of the experienced transition structure. We then apply this rule to a two-layer neural network model loosely resembling hippocampal subfields CA3 - with a symmetric learning rule and recurrent weights - and CA1 - with an asymmetric learning rule and no recurrent weights. Here, when exposed repeatedly to a linear track, neurons in our model in CA3 show less shift of the centre of mass than those in CA1, in line with existing empirical findings. Investigating the functional benefits of such symmetry, we find that using a symmetric learning rule yields representations which afford better generalization, when a model is probed to navigate to a new target without relearning the SR. This effect is reversed when the state space is not symmetric anymore. Thus, our results hint at a potential benefit of the inductive bias afforded by symmetric learning rules in areas employed in spatial navigation, where there naturally is a symmetry in the state space.
Identification of Recurrent Dynamics in Distributed Neural Populations
Authors: Osuna-Orozco Rodrigo , Castillo Edward , Harris Kameron Decker , Santacruz Samantha R.
Published: June 2024

Large-scale recordings of neural activity over broad anatomical areas with high spatial and temporal resolution are increasingly common in modern experimental neuroscience. Recently, recurrent switching dynamical systems have been used to tackle the scale and complexity of these data. However, an important challenge remains in providing insights into the existence and structure of recurrent linear dynamics in neural time series data. Here we test a scalable approach to time-varying autoregression with low-rank tensors to recover the recurrent dynamics in stochastic neural mass models with multiple stable attractors. We demonstrate that the sparse representation of time-varying system matrices in terms of temporal modes can recover the attractor structure of simple systems via clustering. We then consider simulations based on a human brain connectivity matrix in high and low global connection strength regimes, and reveal the hierarchical clustering structure of the dynamics. Finally, we explain the impact of the forecast time delay on the estimation of the underlying rank and temporal variability of the time series dynamics. This study illustrates that prediction error minimization is not sufficient to recover meaningful dynamic structure and that it is crucial to account for the three key timescales arising from dynamics, noise processes, and attractor switching.
The functional and pathogenic consequences of fibrinogen on human oligodendroglia
Authors: Blaszczyk Gabriela J. , Weng Chao , Mohammadnia Abdulshakour , Cui Qiao-Ling , Giurleo Arianna , Groh Adam M.R. , Plouffe Chloe , Sirois Julien , Piscopo Valerio E. C. , Yaqubi Moein , Taqvi Asad , Cassidy Erin , Hall Jeffery A. , Dudley Roy W.R. , Srour Myriam , Zandee Stephanie E J , Klement Wendy , Larouche Sandra , Prat Alexandre , Durcan Thomas M. , Stratton Jo Anne , Antel Jack P. , Moore G. R. Wayne
Published: June 2024

Objective

Multiple sclerosis is an inflammatory demyelinating disorder associated with blood-brain-barrier breakdown, where myelin repair is reduced and ultimately fails. Our aim was to investigate the effect of a systemically circulating molecule fibrinogen, which is abnormally present in the central nervous system as a result of blood-brain barrier breakdown on human oligodendrocyte lineage cells.

Methods

In situ immunofluorescence was performed using anti-fibrinogen and anti-SOX10 antibodies. Mature oligodendrocytes and late progenitors were derived from brain tissue from pediatric and adult donors. Early progenitors were generated from human induced pluripotent stem cells. Following fibrinogen addition to each of these cultures, cell viability and functional capacity was evaluated. Downstream signalling following fibrinogen exposure was confirmed by immunofluorescence microscopy and bulk RNA sequencing.

Results

In situ studies showed fibrinogen on SOX10-positive oligodendroglia in multiple sclerosis, both in plaques and normal-appearing white matter, and white matter in amyotrophic lateral sclerosis. In response to in vitro exposure to fibrinogen, mature oligodendrocytes from adults showed increased ensheathment capacity and upregulation of lipid synthesis, whereas pediatric-age late oligodendrocyte precursors showed a decrease. Early precursors were unable to differentiate but expressed astrocytic markers and increased proliferation. Fibrinogen-exposed cells show bone morphogenetic protein signalling, more prominently in mature oligodendrocytes.

Interpretation

We demonstrate that fibrinogen is deposited on oligodendrocytes in multiple sclerosis and has distinct functional consequences dependent on cell lineage stage. Our findings derived using human OL lineage cells suggest fibrinogen may benefit myelin maintenance by mature oligodendrocytes, while preventing earlier lineage cells from differentiating and repairing multiple sclerosis lesions.
Fibroblasts carrying intermediateC9orf72hexanucleotide repeat expansions from iNPH patients show impaired energy metabolism but no cell pathologies
Authors: Hoffmann Dorit , Korhonen Ville , Rostalski Hannah , Huber Nadine , Heikkinen Sami , Hietanen Tomi , Wittrahm Rebekka , Leskelä Stina , Hartikainen Päivi , Rauramaa Tuomas , Solje Eino , Portaankorva Anne M. , Hiltunen Mikko , Leinonen Ville , Haapasalo Annakaisa
Published: June 2024

LongC9orf72hexanucleotide repeat expansions (C9-HRE) are the most common genetic cause of frontotemporal dementia (FTD), a group of neurodegenerative syndromes leading to cognitive dysfunction and frontal and temporal atrophy. FTD is a potential comorbidity of idiopathic normal pressure hydrocephalus (iNPH) and carrying the C9-HRE can modify the age-of-onset in iNPH patients. While intermediate-length C9-HRE (<30 repeats) are often considered non-pathogenic, the exact pathological cutoff is unclear. In this study, we assessed whether fibroblasts from iNPH patients carrying intermediate C9-HRE display C9-HRE-associated pathological hallmarks and changes in cellular function. C9-HRE-associated RNA foci were not detected in the intermediate carriers. The number of p62-positive puncta was significantly increased only in long C9-HRE carrier fibroblasts, in line with p62-positive intracellular inclusions observed in a brain biopsy from the patient. Specific parameters of mitochondrial respiration were significantly reduced in both the long and intermediate C9-HRE carrier fibroblasts. Fibroblasts from the intermediate C9-HRE carriers showed upregulated glycolytic activity, possibly to counteract the reduced mitochondrial respiration, which could not be observed in the long C9-HRE carriers. In conclusion, these data suggest that while the long C9-HRE leads to more severe cellular pathologies than intermediate C9-HRE, the latter might predispose cells to pathological changes.
Multiscale Modes of Functional Brain Connectivity
Authors: Farahibozorg S Rezvan , Harrison Samuel J , Bijsterbosch Janine D , Woolrich Mark W , Smith Stephen M
Published: June 2024

Information processing in the brain spans from localised sensorimotor processes to higher-level cognition that integrates across multiple regions. Interactions between and within these subsystems enable multiscale information processing. Despite this multiscale characteristic, functional brain connectivity is often either estimated based on 10-30 distributed modes or parcellations with 100-1000 localised parcels, both missing across-scale functional interactions. We present Multiscale Probabilistic Functional Modes (mPFMs), a new mapping which comprises modes over various scales of granularity, thus enabling direct estimation of functional connectivity within- and across-scales. Crucially, mPFMs emerged from data-driven multilevel Bayesian modelling of large functional MRI (fMRI) populations. We demonstrate that mPFMs capture both distributed brain modes and their co-existing subcomponents. In addition to validating mPFMs using simulations and real data, we show that mPFMs can predict ~900 personalised traits from UK Biobank more accurately than current standard techniques. Therefore, mPFMs can offer a paradigm shift in functional connectivity modelling and yield enhanced fMRI biomarkers for traits and diseases.
Lattice ultrasensitivity amplifies signals inE. coliwithout fine-tuning
Authors: Sherry Derek M. , Graf Isabella R. , Bryant Samuel J. , Emonet Thierry , Machta Benjamin B.
Published: June 2024

TheE. colichemosensory lattice, consisting of receptors, kinases, and adaptor proteins, is an important test case for biochemical signal processing. Kinase output is characterized by precise adaptation to a wide range of background ligand levels and large gain in response to small relative changes in concentration. Existing models of this lattice achieve their gain through allosteric interactions between either receptors or core units of receptors and kinases. Here we introduce a model which operates through an entirely different mechanism in which receptors gate inherently far from equilibrium enzymatic reactions between neighboring kinases. Our lattice model achieves gain through a mechanism more closely related to zero-order ultrasensitivity than to allostery. Thus, we call it lattice ultrasensitivity (LU). Unlike other lattice critical models, the LU model can achieve arbitrarily high gain through time-scale separation, rather than through finetuning. The model also captures qualitative experimental results which are difficult to reconcile with existing models. We discuss possible implementations in the lattice’s baseplate where long flexible linkers could potentially mediate interactions between neighboring core units.
EndoGPT: A Proof-of-concept Large Language Model Based Assistant for the Management of Thyroid Nodules
Authors: Shah Meghal , Kuo Eric J. , Kuo Jennifer H. , Hsu Shawn , McManus Catherine , Liou Rachel , Lee James A. , Sathe Tejas S.
Published: June 2024

Large language models (LLMs) are increasingly being explored for their potential to simulate clinical reasoning. Here, we demonstrate our initial experience using the GPT-4o LLM along with prompt engineering and knowledge retrieval to develop EndoGPT, a clinical decision support tool for the management of thyroid nodules. In a pilot study of 50 cases, EndoGPT demonstrated an 83% concordance rate with expert surgeons’ assessments and plans. The highest concordance was in diagnosis (93%), followed by the need for an operation (82%) and type of operation (69%). This work suggests that LLM-based assistants may play a useful role in assisting clinicians in the future.
Targeting complement C3a receptor resolves mitochondrial hyperfusion and subretinal microglial activation in progranulin-deficient frontotemporal dementia
Authors: Tan Li Xuan , Oertel Frederike Cosima , Cheng An , Cobigo Yann , Keihani Azeen , Bennett Daniel J , Abdelhak Ahmed , Montes Shivany Condor , Chapman Makenna , Chen Robert Y , Cordano Christian , Ward Michael E. , Casaletto Kaitlin , Kramer Joel H. , Rosen Howard J , Boxer Adam , Miller Bruce L , Green Ari J , Elahi Fanny M , Lakkaraju Aparna
Published: June 2024

Mutations in progranulin (GRN) cause frontotemporal dementia (GRN-FTD) due to deficiency of the pleiotropic protein progranulin.GRN-FTD exhibits diverse pathologies including lysosome dysfunction, lipofuscinosis, microgliosis, and neuroinflammation. Yet, how progranulin loss causes disease remains unresolved. Here, we report that non-invasive retinal imaging ofGRN-FTD patients revealed deficits in photoreceptors and the retinal pigment epithelium (RPE) that correlate with cognitive decline. Likewise,Grn−/−mice exhibit early RPE dysfunction, microglial activation, and subsequent photoreceptor loss. Super-resolution live imaging and transcriptomic analyses identified RPE mitochondria as an early driver of retinal dysfunction. Loss of mitochondrial fission protein 1 (MTFP1) inGrn−/−RPE causes mitochondrial hyperfusion and bioenergetic defects, leading to NF-kB-mediated activation of complement C3a-C3a receptor signaling, which drives further mitochondrial hyperfusion and retinal inflammation. C3aR antagonism restores RPE mitochondrial integrity and limits subretinal microglial activation. Our study identifies a previously unrecognized mechanism by which progranulin modulates mitochondrial integrity and complement-mediated neuroinflammation.
The Emergence of Non-Linear Evolutionary Trade-offs and the Maintenance of Genetic Polymorphisms
Authors: Hulse Samuel V. , Bruns Emily L.
Published: June 2024

Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modelers to specify a function linking costs to benefits. The choice of trade-off function is often consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to evolutionary branching. Despite their importance, we still lack a strong theoretical foundation to base the choice of trade-off function. To address this gap, we explore how trade-off functions can emerge from the genetic architecture of a quantitative trait. We developed a multi-locus model of disease resistance, assuming each locus had random antagonistic pleiotropic effects on resistance and fecundity. We used this model to generate genotype landscapes and explored how additive versus epistatic genetic architectures influenced the shape of the trade-off function. Regardless of epistasis, our model consistently led to accelerating costs. We then used our genotype landscapes to build an evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms at equilibrium. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously believed.
D-Serine inhibits non-ionotropic NMDA receptor signaling
Authors: Barragan Eden V. , Anisimova Margarita , Vijayakumar Vishnu , Coblentz Azariah C. , Park Deborah K. , Salaka Raghava Jagadeesh , Nisan Atheer F.K. , Petshow Samuel , Dore Kim , Zito Karen , Gray John A.
Published: June 2024

NMDA-type glutamate receptors (NMDARs) are widely recognized as master regulators of synaptic plasticity, most notably for driving long-term changes in synapse size and strength that support learning. NMDARs are unique among neurotransmitter receptors in that they require binding of both neurotransmitter (glutamate) and co-agonist (e.g.d-serine) to open the receptor channel, which leads to the influx of calcium ions that drive synaptic plasticity. Over the past decade, evidence has accumulated that NMDARs also support synaptic plasticity via ion flux-independent (non-ionotropic) signaling upon the binding of glutamate in the absence of co-agonist, although conflicting results have led to significant controversy. Here, we hypothesized that a major source of contradictory results can be attributed to variable occupancy of the co-agonist binding site under different experimental conditions. To test this hypothesis, we manipulated co-agonist availability in acute hippocampal slices from mice of both sexes. We found that enzymatic scavenging of endogenous co-agonists enhanced the magnitude of LTD induced by non-ionotropic NMDAR signaling in the presence of the NMDAR pore blocker, MK801. Conversely, a saturating concentration ofd-serine completely inhibited both LTD and spine shrinkage induced by glutamate binding in the presence of MK801. Using a FRET-based assay in cultured neurons, we further found thatd-serine completely blocked NMDA-induced conformational movements of the GluN1 cytoplasmic domains in the presence of MK801. Our results support a model in whichd-serine inhibits ion flux-independent NMDAR signaling and plasticity, and thusd-serine availability could serve to modulate NMDAR signaling even when the NMDAR is blocked by magnesium.

Significance Statement

NMDARs are glutamate-gated cation channels that are key regulators of neurodevelopment and synaptic plasticity and unique in their requirement for binding of a co-agonist (e.g.d-serine) in order for the channel to open. NMDARs have been found to drive synaptic plasticity via non-ionotropic (ion flux-independent) signaling upon the binding of glutamate in the absence of co-agonist, though conflicting results have led to controversy. Here, we found thatd-serine inhibits non-ionotropic NMDAR-mediated LTD and LTD-associated spine shrinkage. Thus, a major source of the contradictory findings might be attributed to experimental variability ind-serine availability. In addition, the developmental regulation ofd-serine levels suggests a role for non-ionotropic NMDAR plasticity during critical periods of plasticity.
Chimeric Origins and Dynamic Evolution of Central Carbon Metabolism in Eukaryotes
Authors: Molina Carlos Santana , Williams Tom A , Snel Berend , Spang Anja
Published: June 2024

The origin of eukaryotes was a key event in the history of life. Current leading hypotheses propose that a symbiosis between an asgardarchaeal host cell and an alphaproteobacterial endosymbiont represented a crucial step in eukaryotic origins and invoke a central role for syntrophic interactions - that is, metabolic cross-feeding between the partners as the basis for their subsequent evolutionary integration. A major unanswered question is whether the metabolism of modern eukaryotes bears any vestige of this ancestral interaction. To investigate this question in detail, we systematically analyze the evolutionary origins of the eukaryotic gene repertoires mediating central carbon metabolism. Our phylogenetic and sequence analyses reveal that this gene repertoire is chimeric, with ancestral contributions from Asgardarchaeota and Alphaproteobacteria operating predominantly in glycolysis and TCA, respectively. Furthermore, our analyses reveal diverse additional contributions from other prokaryotic sources as well as the extent to which this ancestral metabolic interplay has been remodeled via gene loss, transfer, and subcellular retargeting in the >2Ga since the origin of eukaryotic cells. Together, our work demonstrates that in contrast to previous assumptions, the eukaryotic metabolism preserves information about the nature of the original asgardarchaeal-alphaproteobacterial interactions, and supports syntrophy scenarios on the origin of the eukaryotic cell.
Optical Torque Calculations and Measurements for DNA Torsional Studies
Authors: Hong Yifeng , Ye Fan , Qian Jin , Gao Xiang , Inman James T. , Wang Michelle D.
Published: June 2024

The angular optical trap (AOT) is a powerful instrument for measuring the torsional and rotational properties of a biological molecule. Thus far, AOT studies of DNA torsional mechanics have been carried out using a high numerical aperture oil-immersion objective, which permits strong trapping, but inevitably introduces spherical aberrations due to the glass-aqueous interface. However, the impact of these aberrations on torque measurements is not fully understood experimentally, partly due to a lack of theoretical guidance. Here, we present a numerical platform based on the finite element method to calculate forces and torques on a trapped quartz cylinder. We have also developed a new experimental method to accurately determine the shift in the trapping position due to the spherical aberrations by using a DNA molecule as a distance ruler. We found that the calculated and measured focal shift ratios are in good agreement. We further determined how the angular trap stiffness depends on the trap height and the cylinder displacement from the trap center and found full agreement between predictions and measurements. As further verification of the methodology, we showed that DNA torsional properties, which are intrinsic to DNA, could be determined robustly under different trap heights and cylinder displacements. Thus, this work has laid both a theoretical and experimental framework that can be readily extended to investigate the trapping forces and torques exerted on particles with arbitrary shapes and optical properties.

SIGNIFICANCE

We developed a simulation platform based on the finite element method for force and torque calculation for particles in an angular optical trap (AOT), with considerations of tightly focused Gaussian beam, spherical aberrations, and optically anisotropic particles. Experimental measurements of focal shift ratio, force, and torque under multiple conditions were in good agreement with predictions from the simulations. We also demonstrated that intrinsic DNA torsional properties can be robustly measured under different AOT measurement conditions, strongly validating our simulations and calibrations. Our platform can facilitate trapping particle design for single-molecule assays using the AOT.
Behavioral impairments are linked to neuroinflammation in mice with Cerebral Cavernous Malformation disease
Authors: Offenberger Joseph , Chen Bianca , Rossitto Leigh-Ana , Jin Irisa , Conaboy Liam , Gallego-Gutierrez Helios , Nelsen Bliss , Frias-Anaya Eduardo , Gonzalez David J. , Anagnostaras Stephan , Lopez-Ramirez Miguel Alejandro
Published: June 2024

Background

Cerebral Cavernous Malformations (CCMs) are neurovascular abnormalities in the central nervous system (CNS) caused by loss of function mutations in KRIT1 (CCM1), CCM2, or PDCD10 (CCM3) genes. One of the most common symptoms in CCM patients is associated with motor disability, weakness, seizures, stress, and anxiety, and the extent of the symptom or symptoms may be due to the location of the lesion within the CNS or whether multiple lesions are present. Previous studies have primarily focused on understanding the pathology of CCM using animal models. However, more research has yet to explore the potential impact of CCM lesions on behavioral deficits in animal models, including effects on short-term and long-term memory, motor coordination, and function.

Methods

We used the accelerating RotaRod test to assess motor and coordination deficits. We also used the open field test to assess locomotor activity and pathology-related behavior and Pavlovian fear conditioning to assess short—and long-term memory deficits. Our behavioral studies were complemented by proteomics, histology, immunofluorescence, and imaging techniques. We found that neuroinflammation is crucial in behavioral deficits in male and female mice with neurovascular CCM lesions (Slco1c1-iCreERT2; Pdcd10fl/fl; Pdcd10BECKO).

Results

Functional behavior tests in male and femalePdcd10BECKOmice revealed that CCM lesions cause sudden motor coordination deficits associated with the manifestation of profound neuroinflammatory lesions. Our findings indicate that maturation of CCM lesions inPdcd10BECKOmice also experienced a significant change in short- and long-term memory compared to their littermate controls,Pdcd10fl/flmice. Proteomic experiments reveal that as CCM lesions mature, there is an increase in pathways associated with inflammation, coagulation, and angiogenesis, and a decrease in pathways associated with learning and plasticity. Therefore, our study shows thatPdcd10BECKOmice display a wide range of behavioral deficits due to significant lesion formation in their central nervous system and that signaling pathways associated with neuroinflammation and learning impact behavioral outcomes.

Conclusions

Our study found that CCM animal models exhibited behavioral impairments such as decreased motor coordination and amnesia. These impairments were associated with the maturation of CCM lesions that displayed a neuroinflammatory pattern.
Cortex deviates from criticality during action and deep sleep: a temporal renormalization group approach
Authors: Sooter J. Samuel , Fontenele Antonio J. , Ly Cheng , Barreiro Andrea K. , Shew Woodrow L.
Published: June 2024

The hypothesis that the brain operates near criticality explains observations of complex, often scale-invariant, neural activity. However, the brain is not static, its dynamical state varies depending on what an organism is doing. Neurons often become more synchronized (ordered) during unconsciousness and more desynchronized (disordered) in highly active awake conditions. Are all these states equidistant from criticality; if not, which is closest? The fundamental physics of how systems behave near criticality came from renormalization group (RG) theory, but RG for neural systems remains largely undeveloped. Here we developed a temporal RG (tRG) theory for analysis of typical neuroscience data. We mathematically identified multiple types of criticality (tRG fixed points) and developed tRG-driven data analytic methods to assess proximity to each fixed point based on relatively short time series. Unlike traditional methods for studying criticality in neural systems, our tRG approach allows time-resolved measurements of distance from criticality in experiments at behaviorally relevant timescales. We apply our approach to recordings of spike activity in mouse visual cortex, showing that the relaxed, awake state is closest to criticality. When arousal shifts away from this state – either increasing in more active awake states or decreasing in deep sleep – cortical dynamics deviate from criticality.
Benchmarking Deep Learning-based Image Retrieval of Oral Tumor Histology
Authors: Herdiantoputri Ranny Rahaningrum , Komura Daisuke , Ochi Mieko , Fukawa Yuki , Kayamori Kou , Tsuchiya Maiko , Kikuchi Yoshinao , Ushiku Tetsuo , Ikeda Tohru , Ishikawa Shumpei
Published: June 2024

Oral tumors necessitate a dependable computer-assisted pathological diagnosis system considering their rarity and diversity. A content-based image retrieval (CBIR) system using deep neural networks has been successfully devised for digital pathology. No CBIR system for oral pathology has been investigated because of the lack of an extensive image database and feature extractors tailored to oral pathology. This study uses a large CBIR database constructed from 30 categories of oral tumors to compare deep learning methods as feature extractors. The highest average area under the receiver operating curve (AUC) was achieved by models trained on database images using self-supervised learning (SSL) methods (0.900 with SimCLR; 0.897 with TiCo). The generalizability of the models was validated using query images from the same cases taken with smartphones. When smartphone images were tested as queries, both models yielded the highest mean AUC (0.871 with SimCLR and 0.857 with TiCo). We ensured the retrieved image result would be easily observed by evaluating the top-10 mean accuracy and checking for an exact diagnostic category and its differential diagnostic categories. Therefore, training deep learning models with SSL methods using image data specific to the target site is beneficial for CBIR tasks in oral tumor histology to obtain histologically meaningful results and high performance. This result provides insight into the effective development of a CBIR system to help improve the accuracy and speed of histopathology diagnosis and advance oral tumor research in the future.
Differential risk of healthcare workers versus the general population during outbreak, war and pandemic crises
Authors: Ioannidis John P.A.
Published: June 2024

Healthcare workers may have different risk for severe outcomes compared with the general population during diverse crises. This paper introduces the concept of healthcare worker versus population hazard (HPH), the risk of an outcome of interest in active healthcare workers compared with the general population they serve. HPH can be expressed with relative risk (HPH(r)) and absolute risk difference (HPH(a)) metrics. Illustrative examples are drawn from infectious outbreaks, war, and the COVID-19 pandemic on death outcomes. HPH can be extreme for lethal outbreaks (HPH(r)=30 to 143, HPH(a)=8 to 91 per 1000 for Ebola deaths in 3 Western African countries in 2013-5), and modestly high in relative terms and very high in absolute terms for protracted, major armed conflicts (HPH(r)=1.38 and HPH(a)=10.2 for Syria during 2011-2024). Conversely, healthcare workers had 8-12-fold lower risk than the population they served for pandemic excess deaths (physicians in USA) or COVID-19 deaths (physicians in Ontario, healthcare workers in Finland), while healthcare workers in Indonesia did not have this advantage for COVID-19 deaths versus the general population. HPH is susceptible to data inaccuracies in numbers of at-risk populations and of outcomes of interest. Importantly, inferences about healthcare worker risk can be misleading, if deaths of retired healthcare workers contaminate the risk calculations – as in the case of misleading early perceptions of exaggerated COVID-19 risk for healthcare professionals. HPH can offer useful insights for risk assessment to healthcare professionals, the general public, and policy makers and may be useful to monitor for planning and interventions during crises.
Shape-Biased Learning by Thinking Inside the Box
Authors: Müller Niklas , Snoek Cees G. M. , Groen Iris I. A. , Scholte H. Steven
Published: June 2024

Deep Neural Networks (DNNs) may surpass human-level performance on vision tasks such as object recognition and detection, but their model behavior still differs from human behavior in important ways. One prominent example of this difference, and the main focus of our paper, is that DNNs trained on ImageNet exhibit an object texture bias, while humans are consistently biased towards shape. DNN shape-bias can be increased by data augmentation, but next to being computationally more expensive, data augmentation is a biologically implausible method of creating texture-invariance. We present an empirical study on texture-shape-bias in DNNs showcasing that high texture-bias correlates with high background-object ratio. In addition, DNNs trained on tight object bounding boxes of ImageNet images are sub-stantially more biased towards shape than models trained on the full images. Using a custom dataset of high-resolution, object annotated scene images, we show that (I) shape-bias systematically varies with training on bounding boxes, (II) removal of global object shape as a result of commonly applied cropping during training increases texture bias, (III) shape-bias is negatively correlated with test accuracy on ImageNet while being positively correlated on cue-conflict images created using bounding boxes, following the trend of humans. Overall, we show that an improved supervision signal that better reflects the visual features that truly belong to the to-be-classified object increases the shape-bias of deep neural networks. Our results also imply that simultaneous human alignment on both classification accuracy and strategy can not be achieved on default ImageNet images, suggesting the need for new assessments of both shape-bias and behavioural alignment between DNNs and humans.
Benzylic Trifluoromethyl Accelerates 1,6-Elimination Toward Rapid Probe Activation
Authors: Wang Liming , Sivakumar Aditya , Zhang Rui , Cho Sarah , Kim Yuhyun , Aggarwal Tushar , Wang Lu , Izgu Enver Cagri
Published: June 2024

Activity-based detection of hydrogen sulfide in live cells can expand our understanding of its reactivity and complex physiological effects. We have discovered a highly efficient method for fluorescent probe activation, which is driven by H2S-triggered 1,6-elimination of an α-CF3-benzyl to release resorufin. In detecting intracellular H2S, 4-azido-(α-CF3)-benzyl resorufin offers significantly faster signal generation and improved sensitivity compared to 4-azidobenzyl resorufin. Computed free energy profiles for the 1,6-elimination process support the hypothesis that a benzylic CF3group can reduce the activation energy barrier toward probe activation. This novel probe design allows for near-real-time detection of H2S in HeLa cells under stimulation conditions.
Selection of sheep skin bacteria to reduce blood-feeding by biting midges under laboratory conditions
Authors: Brok Paula S. , Jost Stéphanie M. , Verhulst Niels O.
Published: June 2024

Biting midges of the genus Culicoides (Diptera: Ceratopogonidae) are of huge veterinary importance, mainly as vectors of pathogens, such asBluetongue virus. Currently, there are no effective methods to protect animals against biting midges since insecticides have limited or short-lived efficacy. Biting midges are attracted to hosts by carbon dioxide and by their body odours, which are mainly produced by skin bacteria. In humans, it has been shown that differences in attractiveness between individuals to mosquitoes is mediated by these skin bacterial volatiles. This opens the possibility to protect individuals from biting insects by supplementing their skin microbiome with probiotics. In this study, we investigated this approach by culturing sheep skin bacteria on different media and assessed their effects against field-caught Culicoides (overwhelmingly Obsoletus group species) as well as laboratory-rearedCulicoides nubeculosus(Meigen).Aerococcus urinaeeequi,Bacillus safensis,Bacillus subtilis,Jeotgalicoccus psychrophilus,Micrococcussp. andStaphylococcus equorumwere selected to be tested in a dual-choice Y-tube olfactometer, assessing their behavioural effects towards biting midges. We revealed an avoidance effect towards laboratory-rearedC. nubeculosuswhen testingB. safensis(P ≤ 0.001) andB. subtilis(P ≤ 0.001).Bacillus safensis(P = 0.006) andMicrococcussp. (P ≤ 0.001) yielded significant repellent potential towards field-caught Culicoides. These two candidates were subsequently tested in a membrane blood feeding assay. When the bacterial speciesB. safensiswas applied to the membrane, a feeding reduction of 83 % was observed with field-caught Culicoides.
Delta-Conotoxin Structure Prediction and Analysis through Large-scale Comparative and Deep Learning Modeling Approaches
Authors: Gonen Shane , McCarthy Stephen
Published: June 2024

The delta-conotoxins, a class of peptide produced in the venom of cone snails, are of interest due to their ability to inhibit the inactivation of voltage-gated sodium channels causing paralysis and other neurological responses, but difficulties in their isolation and synthesis have made structural characterization challenging. Taking advantage of recent breakthroughs in computational algorithms for structure prediction that have made modeling especially useful when experimental data is sparse, this work uses both the deep-learning based algorithm AlphaFold and comparative modeling method RosettaCM to model and analyze 18 previously uncharacterized delta-conotoxins derived from piscivorous, vermivorous, and molluscivorous cone snails. The models provide useful insights into structural aspects of these peptides and suggest features likely to be significant in influencing their binding and different pharmacological activities against their targets, with implications for drug development. Additionally, the described protocol provides a roadmap for the modeling of similar disulfide-rich peptides by these complementary methods.
A bipartite interaction with the processivity clamp potentiates Pol IV-mediated TLS
Authors: Chang Seungwoo , Laureti Luisa , Thrall Elizabeth S. , Kay Marguerite S , Philippin Gaëlle , Jergic Slobodan , Pagès Vincent , Loparo Joseph J
Published: June 2024

Processivity clamps mediate polymerase switching for translesion synthesis (TLS). All threeE. coliTLS polymerases interact with the β2processivity clamp through a conserved clamp-binding motif (CBM), which is indispensable for TLS. Notably, Pol IV also makes a unique secondary contact with the clamp through non-CBM residues. However, the role of this “rim contact” in Pol IV-mediated TLS remains poorly understood. Here we show that the rim contact is critical for TLS past strong replication blocks. Inin vitroreconstituted Pol IV-mediated TLS, ablating the rim contact compromises TLS past 3-methyl dA, a strong block, while barely affecting TLS past N2-furfuryl dG, a weak block. Similar observations are also made inE. colicells bearing a single copy of these lesions in the genome. Within lesion-stalled replication forks, the rim interaction and ssDNA binding protein cooperatively poise Pol IV to better compete with Pol III for binding to a cleft through its CBM. We propose that this bipartite clamp interaction enables Pol IV to rapidly resolve lesion-stalled replication through TLS at the fork, which reduces damage induced mutagenesis.
X-linked multi-ancestry meta-analysis reveals tuberculosis susceptibility variants
Authors: Schurz Haiko , Kinnear Craig J , van Helden Paul D , Tromp Gerard , Hoal Eileen G ,   International Tuberculosis Host Genetics Consortium, Möller Marlo
Published: June 2024

Globally, tuberculosis (TB) presents with a clear male bias that cannot be completely accounted for by environment, behaviour, socioeconomic factors, or the impact of sex hormones on the immune system. This suggests that genetic and biological differences, which may be mediated by the X chromosome, further influence the observed male sex bias. The X chromosome is heavily implicated in immune function and yet has largely been ignored in previous association studies. Here we report the first multi-ancestry X chromosome specific meta-analysis on TB susceptibility. We identified X- linked TB susceptibility variants using seven genotyping data sets and 20,255 individuals from diverse genetic ancestries. Sex-specific effects were also identified in polygenic heritability between males and females along with enhanced concordance in direction of genetic effects for males but not females. These sex-specific genetic effects were supported by a sex-stratified and combined meta- analysis conducted using the X chromosome specific XWAS software and a multi-ancestry analysis using the MR-MEGA software. Seven significant associations were identified. Two in the overall analysis (rs6610096, rs7888114) and a second for the female specific analysis (rs4465088) including all data sets. For the ancestry specific meta-analysis three significant associations were identified for males in the Asian cohorts (rs1726176, rs5939510, rs1726203) and one in females for the African cohort (rs2428212). Several genomic regions previously associated with TB susceptibility were reproduced in this study, along with strong ancestry-specific effects. These results support the hypothesis that the X chromosome and sex-specific effects could significantly impact the observed male bias in TB incidence rates globally.
Genomic prediction of individual inbreeding levels for the management of genetic diversity in populations with small effective size
Authors: Forneris Natalia Soledad , Bosse Mirte , Gautier Mathieu , Druet Tom
Published: June 2024

In populations of small effective size (Ne), such as those in conservation programs, companion animals or livestock species, management of diversity and inbreeding is essential. Homozygosity-by-descent (HBD) segments provide relevant information in that context, as they allow efficient estimation of the inbreeding coefficient, provide locus-specific information and their length is informative about the “age” of inbreeding. Therefore, our objective was to evaluate tools for predicting HBD in future offspring based on parental genotypes, a problem equivalent to identifying segments identical-by-descent (IBD) among the four parental chromosomes. In total, we reviewed and evaluated 16 approaches using simulated and real data with small Ne. The methods included model-based approaches, mostly hidden Markov models (HMMs), which considered up to 15 IBD configurations among the four parental chromosomes, as well as more computationally efficient rule-based approaches. The accuracy of the methods was then evaluated, including with low-density marker panels, genotyping-by-sequencing data and small groups of individuals, typical features in such populations. Two HMMs performed consistently well, while two rule-based approaches proved efficient for genome-wide predictions. The model-based approaches were particularly efficient when information was reduced (low marker density, locus-specific estimation). Methods using phased data proved to be more efficient, while some approaches relying on unphased genotype data proved to be sensitive to the allele frequencies used. In some settings, pedigree information was competitive in predicting recent inbreeding levels. Finally, we showed that our evaluation is also informative about the accuracy of the methods for estimating relatedness and identifying IBD segments between pairs of individuals.