Miracle-dz/UniFAR-FTUs huggingface dataset:
Reelin deficiency exacerbates cocaine‐induced hyperlocomotion by enhancing neuronal activity in the dorsomedial striatum

The Reln gene encodes for the extracellular glycoprotein Reelin, which regulates several brain functions from development to adulthood, including neuronal migration, dendritic growth and branching, and synapse formation and plasticity. Human studies have implicated Reelin signaling in several neurodevelopmental and psychiatric disorders. Mouse studies using the heterozygous Reeler (HR) mice have shown that reduced levels of Reln expression are associated with deficits in learning and memory and increased disinhibition. Although these traits are relevant to substance use disorders, the role of Reelin in cellular and behavioral responses to addictive drugs remains largely unknown. Here, we compared HR mice to wild-type (WT) littermate controls to investigate the contribution of Reelin signaling to the hyper-locomotor and rewarding effects of cocaine. After a single cocaine injection, HR mice showed enhanced cocaine-induced locomotor activity compared to WT controls. After repeated injections of cocaine, Reelin deficiency also led to increased cocaine-induced locomotor sensitization, which persisted after withdrawal. In contrast, Reelin deficiency did not affect the rewarding effects of cocaine measured in the conditioned place preference assay. The elevated cocaine-induced hyper-locomotion in HR mice resulted in increased Fos expression in the dorsal medial striatum (DMS) compared to WT. Lastly, we found that Reln was highly co-expressed with the Drd1 gene, which encodes for the dopamine receptor D1, in the DMS. These findings demonstrated that Reelin signaling contributes to the locomotory effects of cocaine and improved our understanding of the neurobiological mechanisms underlying the cellular and behavioral effects of cocaine.
Effect of High Volume versus Low Volume Balance Training on Static and Dynamic Balance

T The purpose of this study was to investigate the effect of high volume versus low volume balance training on static and dynamic balance. Forty adolescent girls (mean ± SD: age 15.52 ± 1.7 years, height 1.723± 0.00891 m, body mass 65.259 ± 0.465 kg), who participated in interschool volleyball competition and in the Catch Them Young (CTY) programme organised by Guru Nanak Dev University, Amritsar volunteered to participate. All participants were informed about the study aim and methodology as well as about the possibility of immediate acceptance at any time of the experimentation. Subjects agreed to the above conditions in writing. They were randomly assigned into two groups: A (Training Group) and B (Control Group), n=20 each. The subjects from training group were subjected to a 6-week high volume versus low volume balance training programme. This lasted 6-weeks and consisted of daily sessions, lasting 40 min each. The students completed the stork stand and wobble board tests to determine static balance on the leg respectively. The static and dynamic balance significantly improved in training group compared with the control one. The high volume versus low volume balance training programme may be recommended to improve static and dynamic balance and may contribute to enhance concentration based performance. T Keywords: T Balance- Dynamic-Static-Training.
HER2 expression defines unique requirements for flotillin and c-Src for EGFR signaling

The epidermal growth factor receptor (EGFR) controls many cellular functions. Upon binding its ligand, the receptor undergoes dimerization, phosphorylation, and activation of signals including the phosphatidylinositol-3-kinase (PI3K)-Akt pathway. While some studies indicated that EGFR signaling may be controlled by signal enrichment within membrane raft nanodomains, others have found a limited effect of membrane raft disruption on EGFR signaling, suggesting that specific factor(s) may define context-specific control of EGFR signaling by membrane rafts. Ligand-bound EGFR can homodimerize, or instead undergo heterodimerization with the related receptor HER2 when the latter is expressed. We examined how EGFR signaling in the presence of HER2 distinctly requires membrane raft nanodomains. Induction of HER2 expression altered EGFR signaling duration consistent with EGFR/HER2 heterodimer formation. EGFR and c-Src localized within plasma membrane structures demarked by flotillin, a membrane raft protein, selectively in HER2-expressing cells. Consistently, HER2-expressing cells, but not cells lacking HER2, were dependent on flotillin and c-Src for EGFR signaling leading to Akt activation and cell proliferation. Hence, HER2 expression establishes the requirement of EGFR signaling for flotillin membrane rafts and c-Src, leading to Akt activation. Summary statement The role of membrane rafts in EGFR signaling may be context-specific. We find that the related receptor HER2 defines unique signaling requirements for EGFR for membrane rafts, flotillin, and c-Src.
Sensitivity to the slope of the amplitude spectrum is dependent on the spectral slopes of recently viewed environments: A visual adaptation study in modified reality

Scenes contain many statistical regularities that could benefit visual processing if accounted for by the visual system. One such statistic is the orientation-averaged slope (α) of the amplitude spectrum of natural scenes. Human observers show different discrimination sensitivity to α: sensitivity is highest for α values between 1.0 and 1.2 and decreases as α is steepened or shallowed. The range of α for peak discrimination sensitivity is concordant with the average α of natural scenes, which may indicate that visual mechanisms are optimized to process information at α values commonly encountered in the environment. Here we explore the association between peak discrimination sensitivity and the most viewed αs in natural environments. Specifically, we verified whether discrimination sensitivity depends on the recently viewed environments. Observers were immersed, using a Head-Mounted Display, in an environment that was either unaltered or had its average α steepened or shallowed by 0.4. Discrimination thresholds were affected by the average shift in α, but this effect was most prominent following adaptation to a shallowed environment. We modeled these data with a Bayesian observer and explored whether a change in the prior or a change in the likelihood best explained the psychophysical effects. Change in discrimination thresholds following adaptation could be explained by a shift in the central tendency of the prior concordant with the shift of the environment, in addition to a change in the likelihood. Our findings suggest that expectations on the occurrence of α that result from a lifetime of exposure remain plastic and able to accommodate for the statistical structure of recently viewed environments.
Risk modelling of single cell populations revealed the heterogeneity of immune infiltration in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common primary hepatic malignancies. E2F transcription factors play an important role in the tumorigenesis and progression of HCC, mainly through the RB/E2F pathway. Prognostic models for HCC based on gene signatures have been developed rapidly in recent years; however, their discriminating ability at the single cell level remains elusive, which could reflect the underlying mechanisms driving the sample bifurcation. In this study, we constructed and validated a predictive model based on E2F expression, successfully stratifying HCC patients into two groups with different survival risks. Then we used a single-cell dataset to test the discriminating ability of the predictive model on infiltrating T cells, demonstrating remarkable cellular heterogeneity as well as altered cell fates. We identified distinct cell subpopulations with diverse molecular characteristics. We also found that the distribution of cell subpopulations varied considerably across onset stages among patients, providing fundamental basis for patient-oriented precision evaluation. Moreover, single-sample gene set enrichment analysis revealed that subsets of CD8+ T cells with significantly different cell adhesion level could be associated with different patterns of tumor cell dissemination. Therefore, our findings linked the conventional prognostic gene signature to the immune microenvironment and cellular heterogeneity at the single-cell level, thereby providing deeper insights into the understanding of HCC tumorigenesis.
Thalamic control of sensory enhancement and sleep spindle properties in a biophysical model of thalamoreticular microcircuitry

Thalamoreticular circuitry is known to play a key role in attention, cognition and the generation of sleep spindles, and is implicated in numerous brain disorders, but the cellular and synaptic mechanisms remain intractable. Therefore, we developed the first detailed computational model of mouse thalamus and thalamic reticular nucleus microcircuitry that captures morphological and biophysical properties of ∼14,000 neurons connected via ∼6M synapses, and recreates biological synaptic and gap junction connectivity. Simulations recapitulate multiple independent network-level experimental findings across different brain states, providing a novel unifying cellular and synaptic account of spontaneous and evoked activity in both wakefulness and sleep. Furthermore, we found that: 1. ) inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness, in addition to its role in spindle generation; 2. ) thalamic interactions generate the characteristic waxing and waning of spindle oscillations; and 3. ) changes in thalamic excitability (e.g. due to neuromodulation) control spindle frequency and occurrence. The model is openly available and provides a new tool to interpret spindle oscillations and test hypotheses of thalamoreticular circuit function and dysfunction across different network states in health and disease.
Multiphasic calcium signatures in the cytosol and nucleus of Lotus japonicus roots unlock the early discrimination of fungal signals

Changes in intracellular calcium concentration are known to mediate plant responses to both beneficial and detrimental microorganisms. Increasing evidence suggests that boundaries between early signalling events in plant pathogenesis and symbiosis are less defined than previously thought, given the occurrence of Ca 2+ signals partially sharing subcellular location and dynamics. In this study we used differentially targeted aequorin-based Ca 2+ reporters to measure cytosolic and nuclear Ca 2+ signatures triggered in Lotus japonicus roots by putative symbiotic and pathogenic fungal molecules. By using mutants impaired in the Common Symbiotic Signalling Pathway, we dissected the multiphasic nature of the stimulus-specific Ca 2+ transients, highlighting significant differences in the genetic components underlying the cytosolic and nuclear Ca 2+ response to short-chain (CO4), long-chain (CO8) and lipidated (mycLCO) chitin oligomers. Moreover, a pharmacological approach shed light on the origin, modulation and interdependence of the observed Ca 2+ fluxes. Our analysis of the overall plant root response in terms of cytosolic and nuclear Ca 2+ changes helps disentangling the complex communication circuits in the pre-contact signal exchange phase and enhances our quantitative understanding of how plants can perceive and discriminate different fungal molecules.
Building a tissue‐unbiased brain template of fiber orientation distribution and tractography with multimodal registration

A brain template provides a standard space for statistical analysis of brain structure and function. For decades, the T1- and T2-weighted brain templates have been widely used for brain grey matter anatomical and functional analysis. However, T1- and T2-weighted templates provide very limited information about the axonal organization within the white matter. Recent advances in Diffusion MRI have enabled the detailed modelling of the axonal fibre orientation distribution (FOD) in white matter. Therefore, building a FOD template is essential for more robust white matter anatomy related analysis; however, it is important that this template aligns well with the cortical and subcortical structures. From such a FOD template, a tractography template can be also generated by fibre tracking algorithms, which can be used for subsequent applications, such as to perform the joint structural and functional analysis while ensuring rigorous fibre-to-fibre correspondence. In this paper, we explore the potential of generating the FOD template based on multimodal registration, in order to constrain the tempalte unbiased to both white and grey matter. We combine the information from T1-weighted, T2-weighted and Diffusion MRI to generate a coherent transformation for FOD registration and template generation. Our FOD template preserves the structural details at the white-grey matter boundary. To illustrate the benefit of this new approach, the resulting tractography template was used for joint structural-functional connectivity analysis.
ProFeatMap: a customizable tool for 2D feature representation of protein sets

Summary Here, we present ProFeatMap, an intuitive Python-based website allowing to quickly display protein features such as domains, repeats, post-translational modifications location and so forth, into a highly customizable graphical 2D map. Starting from a user-defined protein list, ProFeatMap automatically extracts the main protein features from the Uniprot database. The resulting high-quality maps can help to gain insights, e.g. feature redundancy, that were previously overlooked but which may be useful for the research project. ProFeatMap is freely accessible on the web at: https://profeatmap.pythonanywhere. com/ Availability Source code is freely accessible at https://github.com/profeatmap/ProFeatMap under the GPL license. Contact bichg@igbmc.fr, yves.nomine@igbmc.fr Supplementary information detailed user guide of ProFeatMap
BirdFlow: Learning Seasonal Bird Movements from Citizen Science Data

Large-scale monitoring of seasonal animal movement is integral to science, conservation, and outreach. However, gathering representative movement data across entire species ranges is frequently intractable. Citizen science databases collect millions of animal observations throughout the year, but it is challenging to infer individual movement behavior solely from observational data. We present BirdFlow , a probabilistic modeling framework that draws on citizen science data from the eBird database to model the population ﬂows of migratory birds. We apply the model to 11 species of North American birds, using GPS and satellite tracking data to tune and evaluate model performance. We show that BirdFlow models can accurately infer individual seasonal movement behavior directly from eBird relative abundance estimates. Supplementing the model with a sample of tracking data from wild birds improves performance. Researchers can extract a number of behavioral inferences from model results, including migration routes, timing, connectivty, and forecasts. The BirdFlow framework has the potential to advance migration ecology research, boost insights gained from direct tracking studies, and serve a number of applied functions in conservation, disease surveillance, aviation, and public outreach.
Proximal Exploration for Model-guided Protein Sequence Design

Designing protein sequences with a particular biological function is a long-lasting challenge for protein engineering. Recent advances in machine-learning-guided approaches focus on building a surrogate sequence-function model to reduce the burden of expensive in-lab experiments. In this paper, we study the exploration mechanism of model-guided sequence design. We leverage a natural property of protein fitness landscape that a concise set of mutations upon the wild-type sequence are usually sufficient to enhance the desired function. By utilizing this property, we propose Proximal Exploration (PEX) algorithm that prioritizes the evolutionary search for high-fitness mutants with low mutation counts. In addition, we develop a specialized model architecture, called Mutation Factorization Network (MuFacNet), to predict low-order mutational effects, which further improves the sample efficiency of model-guided evolution. In experiments, we extensively evaluate our method on a suite of in-silico protein sequence design tasks and demonstrate substantial improvement over baseline algorithms.
Human blood plasma proteins modeling and binding affinities with Δ9-tetrahydrocannabinol active metabolites: In silico approach

Tetrahydrocannabinol (THC) is a key psychotropic constituent of cannabis sativa. It is also known as Δ9-tetrahydrocannabinol (Δ9-THC). Previous study suggested that owing to its high lipophilicity, it piles up in adipose tissue and it is disseminated into blood stream for prolonged time. Research suggests that numerous diseases such as multiple sclerosis, neurodegenerative disorders, epilepsy, schizophrenia, osteoporosis, cancer, glaucoma and cardiovascular disorders can be treated using this substance. However, apart from having therapeutic potential, many studies have reported detrimental outcomes along with addiction of Δ9-THC for short-term and long-term consumption. Thus, in this study, we determined the binding affinities of Δ9-THC and its two active metabolites, 11-Hydroxy-Δ9-tetrahydrocannabinol (11-OH-Δ9-THC) and 8beta,11-dihydroxy-Δ9-tetrahydrocannabinol (8β,11-diOH-Δ9-THC) with 401 human blood plasma proteins using molecular docking analysis. Results show that Δ9-THC has greater binding potential with plasma proteins as compared to other two metabolites. Overall, ADGRE5, ALB, APOA5, APOD, CP, PON1 and PON3 proteins showed the highest binding affinities with three cannabis metabolites.
Inverse material parameter estimation of patient‐specific finite element models at the carotid bifurcation: The impact of excluding the zero‐pressure configuration and residual stress

The carotid bifurcation experiences a complex loading environment due to its anatomical structure. Previous in-vivo material parameter estimation methods often use simplified model geometries, isotropic hyperelastic constitutive equations or neglect key aspects of the vessel, such as the zero-pressure configuration or residual stress. These factors have independently been shown to alter the stress environment of the vessel wall. Characterising the location of high stress in the vessel wall has often been proposed as a potential indicator of structural weakness. However, excluding the afore-mentioned zero-pressure configuration, residual stress and patient specific material parameters can lead to an incorrect estimation of the true stress values observed, meaning stress alone as a risk indicator of rupture is insufficient. In this study, we investigate how the estimated material parameters and overall stress distributions in geometries of carotid bifurcations, extracted from in-vivo MR images, alter with the inclusion of the zero-pressure configuration and residual stress. This approach consists of the following steps: (1) geometry segmentation and hexahedral meshing from in-vivo MRI images at two known phases; (2) computation of the zero-pressure configuration and the associated residual stresses; (3) minimisation of an objective function built on the difference between the stress states of an “ almost true” stress field at two known phases and a “deformed” stress field by altering the input material parameters to determine patient specific material properties; and (4) comparison of the stress distributions throughout these carotid bifurcations for all cases with estimated material parameters. This numerical approach provides insights into the need for estimation of both the zero-pressure configuration and residual stress for accurate material property estimation and stress analysis for the carotid bifurcation, establishing the reliability of stress as a rupture risk metric. Graphical Abstract
Shell microelectrode arrays (MEAs) for brain organoids

Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells are widely utilized in biomedical engineering. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography (EEG) caps, we developed miniaturized chip-integrated MEA caps for organoids. The optically transparent shells are composed of self-folding polymer leaflets with conductive polymer-coated metal electrodes. Tunable folding of the minicaps’ polymer leaflets guided by mechanics simulations enables versatile recording from organoids of different sizes and we validate the feasibility of electrophysiology recording from 400-600 µm sized organoids for up to four weeks and in response to glutamate stimulation. Our studies suggest that 3D shell MEAs offer significant potential for high signal-to-noise and 3D spatiotemporal brain organoid recording.
Rats exhibit higher hepatic stress response pathway capacities compared with mice and humans

In order to minimise the occurrence of unexpected toxicities as a new medicine transitions from the preclinical to clinical phases of development, it is vital to understand fundamental similarities and differences between preclinical species and humans. The well-known difference in sensitivity of mice and rats to acetaminophen (APAP) liver injury has been related to differences in the fraction that is bioactivated to the reactive metabolite N-acetyl-p-benzoquinoneimine (NAPQI). We have used physiologically-based pharmacokinetic modelling to identify doses of APAP (300 and 1000 mg/kg in mice and rats, respectively) yielding similar hepatic burdens of NAPQI to enable the comparison of temporal liver tissue responses under conditions of equivalent chemical insult. Despite pharmacokinetic and biochemical verification of the equivalent NAPQI insult, serum biomarker and tissue histopathology analyses revealed that mice still exhibited a greater degree of liver injury than rats. Transcriptomic and proteomic analyses highlighted the stronger activation of stress response pathways (including the Nrf2 oxidative stress response and autophagy) in the livers of rats, indicative of a more robust transcriptional adaptation to the equivalent insult. Using RNA-Seq data, we also found that genes associated with these stress responses are expressed at a higher basal level in the livers of rats compared with both mice and humans. Taken together, these data indicate that rats possess a greater basal and adaptive capacity for hepatic stress responses than mice and humans. This has important implications for species selection in preclinical safety testing of drugs associated with reactive metabolite formation and other forms of chemical stress. and of injury