Miracle-dz/UniFAR-FTUs huggingface dataset:
Photothrombosis induced cortical stroke produces electrographic epileptic biomarkers in mice

Objective Interictal epileptiform spikes, high-frequency ripple oscillations, and their co-occurrence (spike ripples) in human scalp or intracranial voltage recordings are well-established epileptic biomarkers. While clinically significant, the neural mechanisms generating these electrographic biomarkers remain unclear. To reduce this knowledge gap, we introduce a novel photothrombotic stroke model in mice that reproduces focal interictal electrographic biomarkers observed in human epilepsy. Methods We induced a stroke in the motor cortex of C57BL/6 mice unilaterally (N=7) using a photothrombotic procedure previously established in rats. We then implanted intracranial electrodes (2 ipsilateral and 2 contralateral) and obtained intermittent local field potential (LFP) recordings over several weeks in awake, behaving mice. We evaluated the LFP for focal slowing and epileptic biomarkers - spikes, ripples, and spike ripples - using both automated and semi-automated procedures. Results Delta power (1-4 Hz) was higher in the stroke hemisphere than the non-stroke hemisphere in all mice (p<0.001). Automated detection procedures indicated that compared to the non-stroke hemisphere, the stroke hemisphere had an increased spike ripple (p=0.006) and spike rates (p=0.039), but no change in ripple rate (p=0.98). Expert validation confirmed the observation of elevated spike ripple rates (p=0.008) and a trend of elevated spike rate (p=0.055) in the stroke hemisphere. Interestingly, the validated ripple rate in the stroke hemisphere was higher than the non-stroke hemisphere (p=0.031), highlighting the difficulty of automatically detecting ripples. Finally, using optimal performance thresholds, automatically detected spike ripples classified the stroke hemisphere with the best accuracy (sensitivity 0.94, specificity 0.94). Significance Cortical photothrombosis-induced stroke in commonly used C57BL/6 mice produces electrographic biomarkers as observed in human epilepsy. This model represents a new translational cortical epilepsy model with a defined irritative zone, which can be broadly applied in transgenic mice for cell type specific analysis of the cellular and circuit mechanisms of pathologic interictal activity. Key Points Cortical photothrombosis in mice produces stroke with characteristic intermittent focal delta slowing. Cortical photothrombosis stroke in mice produces the epileptic biomarkers spikes, ripples, and spike ripples. All biomarkers share morphological features with the corresponding human correlate. Spike ripples better lateralize to the lesional cortex than spikes or ripples. This cortical model can be applied in transgenic mice for mechanistic studies.
Brain orchestra under spontaneous conditions: Identifying communication modules from the functional architecture of area V1

We used two-photon imaging to record from granular and supragranular layers in mouse primary visual cortex (V1) under spontaneous conditions and applied an extension of the spike time tiling coefficient (STTC; introduced by Cutts and Eglen) to map functional connectivity architecture within and across layers. We made several observations: Approximately, 19-34% of neuronal pairs within 300 µm of each other exhibit statistically significant functional connections, compared to 10% at distances of 1mm or more. As expected, neuronal pairs with similar tuning functions exhibit a significant, though relatively small, increase in the fraction of functional inter-neuronal correlations. In contrast, internal state as reflected by pupillary diameter or aggregate neuronal activity appears to play a much stronger role in determining inter-neuronal correlation distributions and topography. Overall, inter-neuronal correlations appear to be slightly more prominent in layer 4. The first-order functionally connected (i.e., direct) neighbors of neurons determine the hub structure of the V1 microcircuit. Layer 4 exhibits a nearly flat degree of connectivity distribution, extending to higher values than seen in supragranular layers, whose distribution drops exponentially. In all layers, functional connectivity exhibits small-world characteristics and network robustness. The probability of firing of layer 2/3 pyramidal neurons can be predicted as a function of the aggregate activity in their first-order functionally connected partners within layer 4, which represent their putative input group. The functional form of this prediction conforms well to a ReLU function, reaching up to firing probability one in some neurons. Interestingly, the properties of layer 2/3 pyramidal neurons differ based on the size of their layer 4 functional connectivity group. Specifically, layer 2/3 neurons with small layer-4 degrees of connectivity appear to be more sensitive to the firing of their layer 4 functional connectivity partners, suggesting they may be more effective at transmitting synchronous activity downstream from layer 4. They also appear to fire largely independently from each other, compared to neurons with high layer-4 degrees of connectivity, and are less modulated by changes in pupil size and aggregate population dynamics. Information transmission is best viewed as occurring from neuronal ensembles in layer 4 to neuronal ensembles in layer 2/3. Under spontaneous conditions, we were able to identify such candidate neuronal ensembles, which exhibit high sensitivity, precision, and specificity for L4 to L2/3 information transmission. In sum, functional connectivity analysis under spontaneous activity conditions reveals a modular neuronal ensemble architecture within and across granular and supragranular layers of mouse primary visual cortex. Furthermore, modules with different degrees of connectivity appear to obey different rules of engagement and communication across the V1 columnar circuit.
Pervasive mitochondrial tRNA gene loss in the clade B of haplosclerid sponges (Porifera, Demospongiae)

Mitochondrial tRNA gene loss and cytosolic tRNA import to mitochondria are two common phenomena in mitochondrial biology, but their importance is often under-appreciated in animals. This is because most bilaterally symmetrical animals (Bilateria) encode a complete set of tRNAs needed for mitochondrial translation. By contrast, studies of mitochondrial genomes in non-bilaterian animals have shown a reduced tRNA gene content in several lineages, necessitating tRNA import. Interestingly, in most of these lineages tRNA gene content appears to be set early in the evolution of the group and conserved thereafter. Here we demonstrate that Clade B of Haplosclerid Sponges (CBHS) represent an exception to this pattern. We determined mt-genome sequences for eight species from this group and analyzed them with six that had been previously available. In addition, we determined mt-genome sequences for two species of haploslerid sponges outside the CBHS and used them with eight previously available sequences as outgroups. We found that tRNA gene content varied widely among CBHS species: from three in an undescribed Haliclona species (Haliclona sp. TLT785) to 25 in Xestospongia muta and X. testudinaria. Furthermore, we found that all CBHS species outside the genus Xestospongia lacked atp9, while some also lacked atp8. Analysis of nuclear sequences from Niphates digitalis revealed that both atp8 and atp9 had transferred to the nuclear genome, while the absence of mt-tRNA genes represented their genuine loss. Overall, CBHS can be a useful animal system to study mt-tRNA genes loss, mitochondrial import of cytosolic tRNA, and the impact of both of these processes on mitochondrial evolution. Significance statement It is generally believed that the gene content is stable in animal mitochondrial (mt) DNA. Indeed, mtDNA in most bilaterally symmetrical animals encompasses a conserved set of 37 genes coding for 13 proteins, two rRNAs and 22 tRNAs. By contrast, mtDNA in non-bilaterian animals shows more variation in mt gene content, in particular in the number of tRNA genes. However, most of this variation occurs between major non-bilaterian lineages. Here we demonstrate that a group of demosponges called Clade B of Haplosclerid Sponges (CBHS) represents a fascinating exception to this pattern, with species experiencing recurrent losses of up to 22 mt-tRNA genes. We argue that this group constitutes a promising system to investigate the effects of tRNA gene loss on evolution of mt-genomes as well as mitochondrial tRNA import machinery.
Strategies for Inducing and Validating Zinc Deficiency and Zinc Repletion

Given the growing interest in the role of zinc in the onset and progression of diseases, there is a crucial demand for reliable methods to modulate zinc homeostasis. Using a dietary approach, we provide validated strategies to alter whole-body zinc in mice, applicable across species. For confirmation of zinc status, animal growth rates as well as plasma and urine zinc levels were evaluated. The accessible and cost-effective methodology outlined will increase scientific rigor, ensuring reproducibility in studies exploring the impact of zinc deficiency and repletion on the onset and progression of diseases. New and Noteworthy This methods paper details 1) dietary approaches to alter zinc homeostasis in rodents, and 2) qualitative and quantitative methods to ensure the zinc status of experimental animals. The outlined accessible and cost-effective protocol will elevate scientific rigor, ensuring reproducibility in studies exploring the impact of zinc deficiency and repletion on the onset and progression of a multitude of health conditions and diseases. Graphical Abstract
Characterization of early and late events of adherens junction assembly

Cadherins are transmembrane adhesion receptors. Cadherin ectodomains form adhesive 2D clusters through cooperative trans and cis interactions, whereas its intracellular region interacts with specific cytosolic proteins, termed catenins, to anchor the cadherin-catenin complex (CCC) to the actin cytoskeleton. How these two types of interactions are coordinated in the formation of specialized cell-cell adhesions, adherens junctions (AJ), remains unclear. We focus here on the role of the actin-binding domain of α-catenin (αABD) by showing that the interaction of αABD with actin generates actin-bound CCC oligomers (CCC/actin strands) incorporating up to six CCCs. The strands are primarily formed on the actin-rich cell protrusions. Once in cell-cell interface, the strands become involved in cadherin ectodomain clustering. Such combination of the extracellular and intracellular oligomerizations gives rise to the composite oligomers, trans CCC/actin clusters. To mature, these clusters then rearrange their actin filaments using several redundant pathways, two of which are characterized here: one depends on the α-catenin-associated protein, vinculin and the second one depends on the unstructured C-terminus of αABD. Thus, AJ assembly proceeds through spontaneous formation of trans CCC/actin clusters and their successive reorganization.
Treatment with both TGF-β1 and PDGF-BB disrupts the stiffness-dependent myofibroblast differentiation of corneal keratocytes

During corneal wound healing, stromal keratocytes transform into a repair phenotype that is driven by the release of cytokines, like transforming growth factor-beta 1 (TGF-β1) and platelet-derived growth factor-BB (PDGF-BB). Previous work has shown that TGF-β1 promotes the myofibroblast differentiation of corneal keratocytes in a manner that depends on PDGF signaling. In addition, changes in mechanical properties are known to regulate the TGF-β1-mediated differentiation of cultured keratocytes. While PDGF signaling acts synergistically with TGF-β1 during myofibroblast differentiation, how treatment with multiple growth factors affects stiffness-dependent differences in keratocyte behavior is unknown. Here, we treated primary corneal keratocytes with PDGF-BB and TGF-β1 and cultured them on polyacrylamide (PA) substrata of different stiffnesses. In the presence of TGF-β1 alone, the cells underwent stiffness-dependent myofibroblast differentiation. On stiff substrata, the cells developed robust stress fibers, exhibited high levels of ⍺-SMA staining, formed large focal adhesions (FAs), and exerted elevated contractile forces, whereas cells in a compliant microenvironment showed low levels of ⍺-SMA immunofluorescence, formed smaller focal adhesions, and exerted decreased contractile forces. When the cultured keratocytes were treated simultaneously with PDGF-BB however, increased levels of ⍺-SMA staining and stress fiber formation were observed on compliant substrata, even though the cells did not exhibit elevated contractility or focal adhesion size. Pharmacological inhibition of PDGF signaling disrupted the myofibroblast differentiation of cells cultured on substrata of all stiffnesses. These results indicate that treatment with PDGF-BB can decouple molecular markers of myofibroblast differentiation from the elevated contractile phenotype otherwise associated with these cells, suggesting that crosstalk in the mechanotransductive signaling pathways downstream of TGF-β1 and PDGF-BB can regulate the stiffness-dependent differentiation of cultured keratocytes. Statement of Significance In vitro experiments have shown that changes in ECM stiffness can regulate the differentiation of myofibroblasts. Typically, these assays involve the use of individual growth factors, but it is unclear how stiffness-dependent differences in cell behavior are affected by multiple cytokines. Here, we used primary corneal keratocytes to show that treatment with both TGF-β1 and PDGF-BB disrupts the dependency of myofibroblast differentiation on substratum stiffness. In the presence of both growth factors, keratocytes on soft substrates exhibited elevated ⍺-SMA immunofluorescence without a corresponding increase in contractility or focal adhesion formation. This result suggests that molecular markers of myofibroblast differentiation can be dissociated from the elevated contractile behavior associated with the myofibroblast phenotype, suggesting potential crosstalk in mechanotransductive signaling pathways downstream of TGF-β1 and PDGF-BB.
Collective intelligence facilitates emergent resource partitioning through frequency dependent learning

Deciding where to forage must not only account for variation in habitat quality, but also where others might forage. Recent studies have suggested that when individuals remember recent foraging outcomes, negative frequency-dependent learning can allow them to avoid resources exploited by others (indirect competition). This process can drive the emergence of consistent differences in resource use (resource partitioning) at the population level. However, indirect cues of competition can be difficult for individuals to sense. Here, we propose that information pooling through collective decision-making—i.e. collective intelligence—can allow populations of group-living animals to more effectively partition resources relative to populations of solitary animals. We test this hypothesis by simulating (i) individuals preferring to forage where they were recently successful, and (ii) cohesive groups that choose one resource using a majority rule. While solitary animals can partially avoid indirect competition through negative frequency-dependent learning, resource partitioning is more likely to emerge in populations of group-living animals. Populations of larger groups also better partition resources than populations of smaller groups, especially in environments with more choices. Our results give insight into the value of long- vs. short-term memory, home range sizes, and the evolution of specialisation, optimal group sizes, and territoriality.
Socio-demographic determinants of the knowledge of diabetes mellitus in Onitsha-North Local Government Area , Anambra State , Nigeria

Background: The main objective of the study was to determine the level of knowledge of diabetes mellitus in relation to its causes, symptoms, diagnosis, complications, treatment modalities and risk factors. Civil servants were chosen for this study because they are prone to sedentary lifestyles. Methodology: A cross-sectional study design was done. The study population comprised employees of Onitsha-North Local Government Area, Anambra State, Nigeria. The instrument used for the collection of data was self-administered pre-tested questionnaire. A total of 150 copies were distributed and 143 were returned and analyzed. The data were presented in frequency tables and analyzed using Fisher’s Exact Tests and logistic regression analysis. Statistical significance was set at p-value
Impoverished Language Technology: The Lack of (Social) Class in NLP

Since Labov's (1964) foundational work on the social stratification of language, linguistics has dedicated concerted efforts towards understanding the relationships between socio-demographic factors and language production and perception. Despite the large body of evidence identifying significant relationships between socio-demographic factors and language production, relatively few of these factors have been investigated in the context of NLP technology. While age and gender are well covered, Labov's initial target, socio-economic class, is largely absent. We survey the existing Natural Language Processing (NLP) literature and find that only 20 papers even mention socio-economic status. However, the majority of those papers do not engage with class beyond collecting information of annotator-demographics. Given this research lacuna, we provide a definition of class that can be operationalised by NLP researchers, and argue for including socio-economic class in future language technologies.
Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning

Mean Field Games (MFGs) have the ability to handle large-scale multi-agent systems, but learning Nash equilibria in MFGs remains a challenging task. In this paper, we propose a deep reinforcement learning (DRL) algorithm that achieves population-dependent Nash equilibrium without the need for averaging or sampling from history, inspired by Munchausen RL and Online Mirror Descent. Through the design of an additional inner-loop replay buffer, the agents can effectively learn to achieve Nash equilibrium from any distribution, mitigating catastrophic forgetting. The resulting policy can be applied to various initial distributions. Numerical experiments on four canonical examples demonstrate our algorithm has better convergence properties than SOTA algorithms, in particular a DRL version of Fictitious Play for population-dependent policies.
Collision Avoidance Verification of Multiagent Systems with Learned Policies

For many multiagent control problems, neural networks (NNs) have enabled promising new capabilities. However, many of these systems lack formal guarantees (e.g., collision avoidance, robustness), which prevents leveraging these advances in safety-critical settings. While there is recent work on formal verification of NN-controlled systems, most existing techniques cannot handle scenarios with more than one agent. To address this research gap, this paper presents a backward reachability-based approach for verifying the collision avoidance properties of Multi-Agent Neural Feedback Loops (MA-NFLs). Given the dynamics models and trained control policies of each agent, the proposed algorithm computes relative backprojection sets by solving a series of Mixed Integer Linear Programs (MILPs) offline for each pair of agents. Our pair-wise approach is parallelizable and thus scales well with increasing number of agents, and we account for state measurement uncertainties, making it well aligned with real-world scenarios. Using those results, the agents can quickly check for collision avoidance online by solving low-dimensional Linear Programs (LPs). We demonstrate the proposed algorithm can verify collision-free properties of a MA-NFL with agents trained to imitate a collision avoidance algorithm (Reciprocal Velocity Obstacles). We further demonstrate the computational scalability of the approach on systems with up to 10 agents.
Improving the characterization of the seismic source in Bebedouro, Paraná Basin, Brazil: further evidence of seismicity triggered by hydraulic stimulation in water wells

S U M M A R Y We investigate a long series of small earthquakes (magnitude < 3) with annual cycles between 2004 and 2010 that occurred in the northeastern Paraná Basin, Brazil. These events were attributed to pore pressure increase in a fractured aquifer caused by the drilling of several water wells down to depths of ∼200 m. Because of the poor depth constraints of the initial study, we relocated ∼1000 microtremors recorded by the local seismographic network using a more accurate velocity model. To better relocate the events, we based the velocity model on geophysical survey data obtained using several techniques, including seismic refraction, surface wave dispersion, vertical electrical sounding, high-frequency receiver functions and the time-domain electromagnetic method. The best 1-D model was calibrated using a simultaneous inversion of hypocentres and a velocity model including station corrections. The resulting focal depths, which are mostly between 100 and 175 m, place the events at depths consistent with the confined aquifer within the basaltic pack. This result confirms that the earthquakes are related to geological stress disturbances (pore pressures) in pre-existing fracture zones within the basalt layer caused by the perforation of water wells used for irrigation. We used a combination of cross-correlations and arrival times to analyse a cluster of 19 earthquakes. The improved hypocentre distribution of this cluster allowed the determination of a clear faultplane solution, which indicates a normal fault striking WNW-ESE and dipping to the north, with an NNE-SSW extension (T-axis). This mechanism complements stress data collected in southeastern Brazil and is consistent with the regional stress regime.
Verified Training for Counterfactual Explanation Robustness under Data Shift

Counterfactual explanations (CEs) enhance the interpretability of machine learning models by describing what changes to an input are necessary to change its prediction to a desired class. These explanations are commonly used to guide users' actions, e.g., by describing how a user whose loan application was denied can be approved for a loan in the future. Existing approaches generate CEs by focusing on a single, fixed model, and do not provide any formal guarantees on the CEs' future validity. When models are updated periodically to account for data shift, if the generated CEs are not robust to the shifts, users' actions may no longer have the desired impacts on their predictions. This paper introduces VeriTraCER, an approach that jointly trains a classifier and an explainer to explicitly consider the robustness of the generated CEs to small model shifts. VeriTraCER optimizes over a carefully designed loss function that ensures the verifiable robustness of CEs to local model updates, thus providing deterministic guarantees to CE validity. Our empirical evaluation demonstrates that VeriTraCER generates CEs that (1) are verifiably robust to small model updates and (2) display competitive robustness to state-of-the-art approaches in handling empirical model updates including random initialization, leave-one-out, and distribution shifts.