Miracle-dz/UniFAR-FTUs huggingface dataset:
Unrestricted Solar Energetic Particle Access to the Moon While Within the Terrestrial Magnetotail

This study presents observations of Solar Energetic Particle (SEP) protons that have penetrated Earth's magnetotail to reach the lunar environment. We apply data from Wind as an upstream monitor and compare to observations from THEMIS‐ARTEMIS within the tail to show clear signatures of SEPs at the Moon during two events. Combining modeling and data analysis, we show that SEPs above energies of ∼25 keV gain access to the Moon's position deep within the magnetotail through field lines that are open on one end to the solar wind. These results contradict previous studies that have suggested that the magnetotail is effective in shielding the Moon from SEPs with energies up to 1 GeV. Instead, we highlight that Earth's magnetosphere provides poor protection to the Moon from SEPs, which irradiate the lunar surface even within the tail. Our results have important implications regarding the safety of astronauts during upcoming lunar missions.
Stable Carbon Isotope Signature of Methane Released From Phytoplankton

Aquatic ecosystems play an important role in global methane cycling and many field studies have reported methane supersaturation in the oxic surface mixed layer (SML) of the ocean and in the epilimnion of lakes. The origin of methane formed under oxic condition is hotly debated and several pathways have recently been offered to explain the “methane paradox. ” In this context, stable isotope measurements have been applied to constrain methane sources in supersaturated oxygenated waters. Here we present stable carbon isotope signatures for six widespread marine phytoplankton species, three haptophyte algae and three cyanobacteria, incubated under laboratory conditions. The observed isotopic patterns implicate that methane formed by phytoplankton might be clearly distinguished from methane produced by methanogenic archaea. Comparing results from phytoplankton experiments with isotopic data from field measurements, suggests that algal and cyanobacterial populations may contribute substantially to methane formation observed in the SML of oceans and lakes.
Absorption of THz electromagnetic wave in two mono-layers of graphene

Nearly 100% absorption of an electromagnetic (EM) wave in terahertz (THz) frequency is proposed for a system consisting of two mono-layers of graphene. Here, we demonstrate that the system can almost perfectly absorb an EM wave with frequency of 2 THz, even though we have a low electron mobility of roughly 1000 cm2 Vs−1. The absorption probability is calculated by using the transfer matrix method. We show that the two mono-layers of the graphene system is needed to obtain nearly 100% absorption when the graphene has a relatively low Fermi energy. The absorption dependence on the distance between the graphene layers is also discussed.
Huntingtin loss in hepatocytes is associated with altered metabolism, adhesion, and liver zonation

Lifelong huntingtin loss in mouse hepatocytes is associated with altered metabolism, adhesion, and liver zonation which mimics the phenotypes caused by impaired B-catenin function. Huntington’s disease arises from a toxic gain of function in the huntingtin (HTT) gene. As a result, many HTT-lowering therapies are being pursued in clinical studies, including those that reduce HTT RNA and protein expression in the liver. To investigate potential impacts, we characterized molecular, cellular, and metabolic impacts of chronic HTT lowering in mouse hepatocytes. Lifelong hepatocyte HTT loss is associated with multiple physiological changes, including increased circulating bile acids, cholesterol and urea, hypoglycemia, and impaired adhesion. HTT loss causes a clear shift in the normal zonal patterns of liver gene expression, such that pericentral gene expression is reduced. These alterations in liver zonation in livers lacking HTT are observed at the transcriptional, histological, and plasma metabolite levels. We have extended these phenotypes physiologically with a metabolic challenge of acetaminophen, for which the HTT loss results in toxicity resistance. Our data reveal an unexpected role for HTT in regulating hepatic zonation, and we find that loss of HTT in hepatocytes mimics the phenotypes caused by impaired hepatic β-catenin function.
Closed-loop optogenetic perturbation of macaque oculomotor cerebellum: evidence for an internal saccade model

Internal models are essential for the production of accurate movements. The accuracy of saccadic eye movements is thought to be mediated by an internal model of oculomotor mechanics encoded in the cerebellum. The cerebellum may also be part of a feedback loop that predicts the displacement of the eyes and compares it to the desired displacement in real time to ensure that saccades land on target. To investigate the role of the cerebellum in these two aspects of saccade production, we delivered saccade-triggered light pulses to channelrhodopsin-2-expressing Purkinje cells in the oculomotor vermis (OMV) of two macaque monkeys. Light pulses delivered during the acceleration phase of ipsiversive saccades slowed the deceleration phase. The long latency of these effects and their scaling with light pulse duration are consistent with an integration of neural signals at or downstream of the stimulation site. In contrast, light pulses delivered during contraversive saccades reduced saccade velocity at short latency and were followed by a compensatory reacceleration which caused gaze to land near or on the target. We conclude that the contribution of the OMV to saccade production depends on saccade direction; the ipsilateral OMV is part of a forward model that predicts eye displacement, whereas the contralateral OMV is part of an inverse model that creates the force required to move the eyes with optimal peak velocity for the intended displacement. Significance Statement Theory and experiment suggest that saccade production involves an internal model of oculomotor mechanics that resides inside the cerebellum. How cerebellar neurons implement this model is poorly understood. To illuminate this issue, we stimulated Purkinje cells in the oculomotor vermis (OMV) optogenetically during saccades and examined the resultant movement deviations. Stimulation of the contralateral OMV affected saccade dynamics at short latency, suggesting that the contralateral OMV is part of the feedforward pathway that produces the saccade motor command. In contrast, perturbation of the ipsilateral OMV affected saccade dynamics at longer latency, prolonging the saccade deceleration phase and leading to hypermetria. These effects are consistent with perturbation of the eye displacement integrator in the feedback loop of the saccade generator.
Speech recognition from MEG data using covariance filters

Speech recognition from EEG and MEG data is the first step in the development of BCI and AI systems for further use in the decoding of inner speech. Great achievements in this direction have been made with the use of ECoG and stereo-EEG. At the same time, there are few works on this topic on the analysis of data obtained by nonin-vasive methods of brain activity registration. Our approach is based on the evaluation of connections in the sensor space with the extraction of the MEG connectivity pattern specific to a given segment of speech. We tested our method on 7 subjects. In all cases, our processing pipeline was sufficiently reliable and worked either without recognition errors or with few errors. After ”training” the algorithm is able to recognize a fragment of spoken speech in a single presentation. For recognition, we used MEG recording segments of 50-1200 ms from the beginning of the word. A segment of at least 600 ms was required for high-quality recognition. Intervals longer than 1200 ms degraded the quality of recognition. Band-pass filtering of MEG showed that the quality of recognition is higher when using the gamma frequency range compared to the low-frequency range of the analyzed signal.
The activation of INF2 by Piezo1/Ca2+ is required for mesenchymal to amoeboid transition in confined environments

To invade heterogenous tissues, transformed cells may undergo a mesenchymal to amoeboid transition (MAT). However, the molecular mechanisms regulating this transition are poorly defined. In invasive melanoma cells, we demonstrate that intracellular [Ca2+] increases with the degree of confinement in a Piezo1 dependent fashion. Moreover, Piezo1/Ca2+ is found to drive amoeboid and not mesenchymal migration in confined environments. Consistent with a model in which Piezo1 senses tension at the plasma membrane, the percentage of cells using amoeboid migration is further increased in undulating microchannels. Surprisingly, amoeboid migration was not promoted by myosin light chain kinase (MLCK), which is sensitive to intracellular [Ca2+]. Instead, we report that Piezo1/Ca2+ activates inverted formin-2 (INF2) to induce widespread actin cytoskeletal remodeling. Strikingly, the activation of INF2 is found to promote de-adhesion, which in turn facilitates MAT. Using micropatterned surfaces, we demonstrate that cells require INF2 to effectively migrate in environments with challenging mechanochemical properties. Summary Statement Migrating melanoma cells are found to rely on the activation of inverted formin-2 (INF2) by Piezo1/Ca2+ for mesenchymal to amoeboid transition (MAT) in confined environments.
Generation of a robust reference gut microbiome dataset for an urban population in Argentina optimized by a machine learning approach

Robust human microbiome analysis requires robust reference datasets obtained from a population that presents similar habits to the one we are trying to assess. We reported here the construction of a robust reference dataset of healthy individuals from urban and surrounding rural areas of the Argentine population. We screened 200 volunteers with strict inclusion/exclusion criteria. Volunteers were also screened with routine blood clinical test analysis and a complete metabolome profile from blood and urine to remove outliers before inclusion in the Next Generation Sequencing dataset. Sequencing was done on an Illumina MiSeq using the V3-V4 16S rRNA. Using these data, we performed de novo community structure prediction by applying clustering methodology based on seven distance and dissimilarity metrics and two clustering methods to the reference set. Using this approach, we discovered four different enterotypes in this community structure. We then trained a model for the classification of any new sample into the structure of the reference set. Once the new sample was classified, it was compared to the reference ranges of both the enterotype-specific subset and the whole reference set. Finally, we challenged the robustness of this methodology using samples from two test case volunteers with clinically proven gut dysbiosis in a time-series sampling with dietary interventions. Our results pointed to the need to carefully analyze the results of gut microbiome in the context of enterotype-specific rather than to a whole population dataset.
A multi-layered integrative analysis reveals a cholesterol metabolic program in outer radial glia with implications for human brain evolution

The definition of molecular and cellular mechanisms contributing to evolutionary divergences in brain ontogenetic trajectories is essential to formulate hypotheses about the emergence of our species. Yet the functional dissection of evolutionary modifications derived in the Homo sapiens lineage at an appropriate level of granularity remains particularly challenging. Capitalizing on recent single-cell sequencing efforts that have massively profiled neural stem cells from the developing human cortex, we develop an integrative computational framework in which we perform (i) trajectory inference and gene regulatory network reconstruction, (ii) (pseudo)time-informed non-negative matrix factorization for learning the dynamics of gene expression programs, and (iii) paleogenomic analysis for a higher-resolution mapping of the regulatory landscape where our species acquired derived mutations in comparison to our closest relatives. We provide evidence for cell type-specific activation and regulation of gene expression programs during indirect neurogenesis. In particular, our analysis uncovers a zinc-finger transcription factor, KLF6, as a key regulator of a cholesterol metabolic program specifically in outer radial glia. Our strategy allows us to further probe whether the (semi)discrete gene expression programs identified have been under selective pressures in our species lineage. A cartography of the regulatory landscape impacted by Homo sapiens-derived transcription factor binding site disruptions reveals signals of selection clustering around regulatory regions associated with GLI3, a well-known regulator of the radial glial cell cycle. As a whole, our study contributes to the evidence of significant changes impacting metabolic pathways in recent human brain evolution.
Synaptic vesicle glycoprotein 2C enhances vesicular storage of dopamine and counters dopaminergic toxicity

Dopaminergic neurons of the substantia nigra exist in a persistent state of vulnerability resulting from high baseline oxidative stress, high energy demand, and broad unmyelinated axonal arborizations. Impairments in the storage of dopamine compound this stress due to cytosolic reactions that transform the vital neurotransmitter into an endogenous neurotoxicant, and this toxicity is thought to contribute to the dopamine neuron degeneration that occurs Parkinson’s disease. We have previously identified synaptic vesicle glycoprotein 2C (SV2C) as a modifier of vesicular dopamine function, demonstrating that genetic ablation of SV2C in mice results in decreased dopamine content and evoked dopamine release in the striatum. Here, we adapted a previously published in vitro assay utilizing false fluorescent neurotransmitter 206 (FFN206) to visualize how SV2C regulates vesicular dopamine dynamics and determined that SV2C promotes the uptake and retention of FFN206 within vesicles. In addition, we present data indicating that SV2C enhances the retention of dopamine in the vesicular compartment with radiolabeled dopamine in vesicles isolated from immortalized cells and from mouse brain. Further, we demonstrate that SV2C enhances the ability of vesicles to store the neurotoxicant 1-methyl-4-phenylpyridinium (MPP+) and that genetic ablation of SV2C results in enhanced 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced vulnerability in mice. Together, these findings suggest that SV2C functions to enhance vesicular storage of dopamine and neurotoxicants, and helps maintain the integrity of dopaminergic neurons.
Glucose-stimulated KIF5B-driven microtubule sliding organizes microtubule networks in pancreatic beta cells

In pancreatic islet beta cells, molecular motors use cytoskeletal polymers microtubules as tracks for intracellular transport of insulin secretory granules. Beta-cell microtubule network has a complex architecture and is non-directional, which provide insulin granules at the cell periphery for rapid secretion response, yet to avoid over-secretion and subsequent hypoglycemia. We have previously characterized a peripheral sub-membrane microtubule array, which is critical for withdrawal of excessive insulin granules from the secretion sites. Microtubules in beta cells originate at the Golgi in the cell interior, and how the peripheral array is formed is unknown. Using real-time imaging and photo-kinetics approaches in clonal mouse pancreatic beta cells MIN6, we now demonstrate that kinesin KIF5B, a motor protein with a capacity to transport microtubules as cargos, slides existing microtubules to the cell periphery and aligns them to each other along the plasma membrane. Moreover, like many physiological beta-cell features, microtubule sliding is facilitated by a high glucose stimulus. These new data, together with our previous report that in high glucose sub-membrane MT array is destabilized to allow for robust secretion, indicate that MT sliding is another integral part of glucose-triggered microtubule remodeling, likely replacing destabilized peripheral microtubules to prevent their loss over time and beta-cell malfunction.
Impact of random 50-base sequences inserted into an intron on splicing in Saccharomyces cerevisiae

Intron splicing is a key regulatory step in gene expression in eukaryotes. Three sequence elements required for splicing – 5’ and 3’ splice sites and a branch point – are especially well- characterized in Saccharomyces cerevisiae, but our understanding of additional intron features that impact splicing in this organism is incomplete, due largely to its small number of introns. To overcome this limitation, we constructed a library in S. cerevisiae of random 50-nucleotide elements (N50) individually inserted into the intron of a reporter gene and quantified canonical splicing and the use of cryptic splice sites by sequencing analysis. More than 70% of approximately 140,000 N50 elements reduced splicing by at least 20% compared to the intron control. N50 features, including higher GC content, presence of GU repeats and stronger predicted secondary structure of its pre-mRNA, correlated with reduced splicing efficiency. A likely basis for the reduced splicing of such a large proportion of variants is the formation of RNA structures that pair N50 bases – such as the GU repeats – with other bases specifically within the reporter pre-mRNA analyzed. However, neither convolutional neural network nor linear models were able to explain more than a small fraction of the variance in splicing efficiency across the library, suggesting that complex non-linear interactions in RNA structures are not accurately captured by RNA structure prediction methods given the limited number of variants. Our results imply that the specific context of a pre-mRNA may determine the bases allowable in an intron to prevent secondary structures that reduce splicing.
Comparison and evaluation of datasets for off-angle iris recognition

In this paper, we investigated the publicly available iris recognition datasets and their data capture procedures in order to determine if they are suitable for the stand-off iris recognition research. Majority of the iris recognition datasets include only frontal iris images. Even if a few datasets include off-angle iris images, the frontal and off-angle iris images are not captured at the same time. The comparison of the frontal and off-angle iris images shows not only differences in the gaze angle but also change in pupil dilation and accommodation as well. In order to isolate the effect of the gaze angle from other challenging issues including dilation and accommodation, the frontal and off-angle iris images are supposed to be captured at the same time by using two different cameras. Therefore, we developed an iris image acquisition platform by using two cameras in this work where one camera captures frontal iris image and the other one captures iris images from off-angle. Based on the comparison of Hamming distance between frontal and off-angle iris images captured with the two-camera- setup and one-camera-setup, we observed that Hamming distance in two-camera-setup is less than one-camera-setup ranging from 0.05 to 0.001. These results show that in order to have accurate results in the off-angle iris recognition research, two-camera-setup is necessary in order to distinguish the challenging issues from each other.
Placebo effect after visual restitution training: no eye-tracking controlled perimetric improvement after visual border stimulation in late subacute and chronic visual field defects after stroke

Introduction A significant number of Restitution Training (RT) paradigms claim to ameliorate visual field loss after stroke by re-activating neuronal connections in the residual visual cortex due to repeated bright light-stimulation at the border of the blind and intact fields. However, the effectiveness of RT has been considered controversial both in science and clinical practice for years. The main points of the controversy are (1) the reliability of perimetric results which may be affected by compensatory eye movements and (2) heterogeneous samples consisting of patients with visual field defects and/or visuospatial neglect. Methods By means of our newly developed and validated Virtual Reality goggles Salzburg Visual Field Trainer (SVFT) 16 stroke patients performed RT on a regular basis for 5 months. By means of our newly developed and validated Eye Tracking Based Visual Field Analysis (EFA), we conducted a first-time full eye-movement-controlled perimetric pre-post intervention study. Additionally, patients subjectively rated the size of their intact visual field. Results Analysis showed that patients’ mean self-assessment of their subjective visual field size indicated statistically significant improvement while, in contrast, objective eye tracking controlled perimetric results revealed no statistically significant effect. Discussion Bright-light detection RT at the blind-field border solely induced a placebo effect and did not lead to training-induced neuroplasticity in the visual cortex of the type needed to ameliorate the visual field size of stroke patients.
Plasma metabolomics by nuclear magnetic resonance reveals biomarkers and metabolic pathways associated with the control of HIV-1 infection/progression

How the human body reacts to the exposure of HIV-1 is an important research goal. Frequently, HIV exposure leads to infection, but some individuals show natural resistance to this infection; they are known as HIV-1-exposed but seronegative (HESN). Others, although infected but without antiretroviral therapy, control HIV-1 replication and progression to AIDS; they are named controllers, maintaining low viral levels and an adequate count of CD4+ T lymphocytes. Biological mechanisms explaining these phenomena are not precise. In this context, metabolomics emerges as a method to find metabolites in response to pathophysiological stimuli, which can help to establish mechanisms of natural resistance to HIV-1 infection and its progression. We conducted a cross-sectional study including 30 HESN, 14 HIV-1 progressors, 14 controllers and 30 healthy controls. Plasma samples (directly and deproteinized) were analyzed through Nuclear Magnetic Resonance (NMR) metabolomics to find biomarkers and altered metabolic pathways. The metabolic profile analysis of progressors, controllers and HESN demonstrated significant differences with healthy controls when a discriminant analysis (PLS-DA) was applied. In the discriminant models, 13 metabolites associated with HESN, 14 with progressors and 12 with controllers were identified, which presented statistically significant mean differences with healthy controls. In progressors, the metabolites were related to high energy expenditure (creatinine), mood disorders (tyrosine) and immune activation (lipoproteins), phenomena typical of the natural course of the infection. In controllers, they were related to an inflammation-modulating profile (glutamate and pyruvate) and a better adaptive immune system response (acetate) associated with resistance to progression. In the HESN group, with anti-inflammatory (lactate and phosphocholine) and virucidal (lactate) effects which constitute a protective profile in the sexual transmission of HIV. Concerning the significant metabolites of each group, we identified 24 genes involved in HIV-1 replication or virus proteins that were all altered in progressors but only partially in controllers and HESN. In summary, our results indicate that exposure to HIV-1 in HESN, as well as infection in progressors and controllers, affects the metabolism of individuals and that this affectation can be determined using NMR metabolomics.