Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal neural mechanisms of context-based object recognition

Objects can be recognized based on their intrinsic features, including shape, color, and texture. In daily life, however, such features are often not clearly visible, for example when objects appear in the periphery, in clutter, or at a distance. Interestingly, object recognition can still be highly accurate under these conditions when objects are seen within their typical scene context. What are the neural mechanisms of context-based object recognition? According to parallel processing accounts, context-based object recognition is supported by the parallel processing of object and scene information in separate pathways. Output of these pathways is then combined in downstream regions, leading to contextual benefits in object recognition. Alternatively, according to feedback accounts, context-based object recognition is supported by (direct or indirect) feedback from scene-selective to object-selective regions. Here, in three pre-registered transcranial magnetic stimulation (TMS) experiments, we tested a key prediction of the feedback hypothesis: that scene-selective cortex causally and selectively supports context-based object recognition before object-selective cortex does. Early visual cortex (EVC), object-selective lateral occipital cortex (LOC), and scene-selective occipital place area (OPA) were stimulated at three time points relative to stimulus onset while participants categorized degraded objects in scenes and intact objects in isolation, in different trials. Results confirmed our predictions: relative to isolated object recognition, context-based object recognition was selectively and causally supported by OPA at 160-200 ms after onset, followed by LOC at 260-300 ms after onset. These results indicate that context-based expectations facilitate object recognition by disambiguating object representations in visual cortex.
Thermal and Chemical Freeze-out in Heavy Ion Collisions

I have studied single particle spectra of hadrons produced in the high energy heavy ion collisions. Experimental data of the present interest have been obtained by the NA44 momentum focussing spectrometer at the CERN-SPS. The particle source produced in these collisions has a very high energy density and therefore high temperature and immediately begins to expand and cool. When the expansion reaches to a certain extent, eventually the temperature decreases at a point where hadrons stop interacting with each other. The particle ratios are fixed at this point and we refer to this state of particle source as a chemical freeze-out. There is another type of freeze-out, that is, after further expansion and cooling, the temperature goes down to a point where the final state interactions between hadrons are no longer effective. This is referred to as a thermal freeze-out. In this thesis, absolute values of single particle spectra are determined for pions, kaons, protons and antiprotons as functions of transverse mass (mT ) near mid-rapidity in 158 A GeV/c Pb+Pb collisions. From the particle mass dependence for the observed mT distributions, we are able to deduce a value of about 130 MeV for the temperature at the thermal freeze-out. On the other hand, from the observed ratio of the rapidity densities, we are able to determine values of the chemical potential for light and strange quarks to be approximately 65 and 15 MeV, respectively, as well as a value of about 140 MeV for the temperature of the chemical freeze-out. These values seem to justify our scenario, that is, in heavy ion collisions at CERN-SPS energies, the particle source of very high energy density, a kind of fire ball of high energy density, is produced. It then cools due to fast expansion. During the expansion, the fire ball reaches the chemical freeze-out at first and finally goes to the thermal freeze-out. It is also noted that if we believe in a usual model of quark-gluon plasma, the values of chemical potentials and chemical freeze-out temperature determined above suggest that the state of the fire ball immediately after the collision is rather close to the state of the quark gluon plasma.
Modeling breast cancer by grafting patient tumor samples in the avian embryo: an in vivo platform for therapy evaluation coupled to large scale molecular analyses

Lack of preclinical patient-derived xenograft (PDX) cancer models in which to conduct large scale molecular studies seriously impairs the development of effective personalized therapies. We report here on an in vivo concept consisting of implanting human tumor cells in targeted tissues of an avian embryo, delivering therapeutics, evaluating their efficacy by measuring tumors using light sheet confocal microscopy, and conducting large scale RNAseq analysis to characterize therapeutic-induced changes in gene expression. The model was established to recapitulate triple negative breast cancer (TNBC) and validated using TNBC standards of care (SOCs) and an investigational therapeutic agent.
How adaptation, training, and customization contribute to benefits from exoskeleton assistance

Exoskeletons can enhance human mobility, but we still know little about why they are effective. For example, we do not know the relative importance of training, how much is required, or what type is most effective; how people adapt with the device; or the relative benefits of customizing assistance. We conducted experiments in which naïve users learned to walk with ankle exoskeletons under one of three training regimens characterized by different levels of variation in device behavior. Assistance was also customized for one group. Following moderate-variation training, the benefits of customized assistance were large; metabolic rate was reduced by 39% compared to walking with the exoskeleton turned off. Training contributed about half of this benefit and customization about one quarter; a generic controller reduced energy cost by 10% before training and 31% afterwards. Training required much more exposure than typical of exoskeleton studies, about 109 minutes of assisted walking. Type of training also had a strong effect; the low-variation group required twice as long as the moderate-variation group to become expert, while the high-variation group never acquired this level of expertise. Curiously, all users adapted in a way that resulted in less mechanical power from the exoskeleton as they gained expertise. Customizing assistance required less time than training for all parameters except peak torque magnitude, which grew slowly over the study, suggesting a longer time-scale adaptation in the person. These results underscore the importance of training to the benefits of exoskeleton assistance and suggest the topic deserves more attention.
Escitalopram Administration, Neuroplastic Effects and Relearning: A Diffusion Tensor Imaging Study in Healthy Individuals

Background Neuroplastic processes are influenced by selective serotonergic reuptake inhibitors, while learning in conjunction with the administration of serotonergic agents alters white matter microstructure in humans. The goal of this double-blind, placebo-controlled imaging study was to investigate the influence of escitalopram on white matter plasticity during (re)learning. Methods Seventy-one healthy individuals (age = 25.6±5.0, 43 females) underwent 3 diffusion magnetic resonance imaging sessions: at baseline, after 3-weeks of associative learning (emotional/non-emotional content) and after relearning shuffled associations for an additional 3 weeks. During the relearning phase, subjects received daily escitalopram 10 mg or placebo orally. Data were analyzed using the FMRIB Software Library (FSL) and the implemented Tract-Based Spatial Statistics (TBSS) approach. Results The TBSS analysis revealed widespread decreases in fractional anisotropy metrics in subjects that received escitalopram. In addition, axial diffusivity decreases were mainly found in the corpus callosum and in areas within the internal capsule. In subjects receiving placebo, we did not find such effects, nor did our results show diffusivity changes related to learning or relearning. Conclusion Diffusivity changes were found within several tracts in the escitalopram group, while we observed no changes in the placebo group. Although previous studies examining the effects of SSRIs on white matter tracts in humans are underrepresented, our results suggest a relationship between serotonergic agents and diffusivity parameters. The findings of this study implicate that escitalopram may directly or indirectly impact white matter microstructures in healthy subjects. Nevertheless, we did not find a relationship between serotonergic modulation, neuroplastic effects and relearning.
A closed-loop stimulation approach with real-time estimation of the instantaneous phase of neural oscillations by a Kalman filter

We propose a novel method to estimate the instantaneous oscillatory phase to implement a real-time system for closed-loop sensory stimulation in electroencephalography (EEG) experiments. The method uses Kalman filter-based prediction to estimate current and future EEG signals. We tested the performance of our method in a real-time situation. We demonstrate that the performance of our method shows higher accuracy in predicting the EEG phase than the conventional autoregressive model-based method. A Kalman filter allows us to easily estimate the instantaneous phase of EEG oscillations based on the automatically estimated autoregressive model implemented in a real-time signal processing machine. The proposed method has a potential for versatile applications targeting the modulation of EEG phase dynamics and the plasticity of brain networks in relation to perceptual or cognitive functions.
Epigenetic reprogramming by TET enzymes impacts co-transcriptional R-loops

DNA oxidation by ten-eleven translocation (TET) family enzymes is essential for epigenetic reprogramming. The conversion of 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) initiates developmental and cell-type-specific transcriptional programs through mechanisms that include changes in the chromatin structure. Here, we show that the presence of 5hmC in the transcribed DNA promotes the annealing of the nascent RNA to its template DNA strand, leading to the formation of an R-loop. The genome-wide distribution of 5hmC and R-loops show a positive correlation in mouse and human embryonic stem cells and overlap in half of all active genes. Moreover, R-loop resolution leads to differential expression of a subset of genes that are involved in crucial events during stem cell proliferation. Altogether, our data reveal that epigenetic reprogramming via TET activity promotes co-transcriptional R-loop formation, and disclose novel links between R-loops and the regulation of gene expression programs in stem cells.
Systematic analysis of Epstein-Barr virus genes and their individual contribution to virus production and composition

Epstein-Barr virus (EBV), a member of the large herpesvirus family is a very complex human γ-herpesvirus. Its complexity with respect to viral gene regulation, its preferred latent life style and technical difficulties are major obstacles, which hinder efficient virus generation in vitro to mass-produce or establish recombinant wild-type EBV or mutant derivatives. To explore conditions optimizing and improving virus production, we established and tested an EBV gene library with 77 expression plasmids and a set of designed shRNAs. With this tool set we investigated the contributions of individual viral genes in the context of virus synthesis and virion functions. Engineered virus stocks were systematically analyzed with respect to physical and bioparticle concentration, virus titer and virus uptake by primary human B cells, EBV’s target cells in vivo. To quantitate virus uptake by these cells, we developed a novel ß-lactamase-based assay that can monitor fusion events of the viral envelope with membranes of recipient cells at the level of single cells. Based on our findings, EBV does not encode a dominant regulator that governs virus production, but our results identified several EBV genes such as BALF4, BVLF1 and BKRF4, encoding a viral glycoprotein, a transcriptional regulator of late viral genes, and a possible tegument protein, respectively, that improve virus production regarding virus yield, virus composition and quality, and virus uptake by primary human B cells. Importance For more than 20 years HEK293 cells have been instrumental to produce virus stocks of recombinant EBV. The identification of this cell line as a source of infectious EB virions was unexpected because HEK293 cells are very distant from B cells and in particular plasma cells which produce EBV progeny in vivo. To our knowledge, no systematic analysis has addressed the fundamental question whether virus yield with respect to virus concentration, virion composition and functionality can be improved to produce recombinant EBV stocks in HEK293 cells. We tackled this question and analyzed 77 individual EBV genes for their possible contribution to virus yield. To analyze and compare different virus stocks we used established and developed novel assays to characterize important parameters of EB virions and their functions.
Evolution of a cytoplasmic determinant: evidence for the biochemical basis of functional evolution of a novel germ line regulator

Germ line specification is essential in sexually reproducing organisms. Despite their critical role, the evolutionary history of the genes that specify animal germ cells is heterogeneous and dynamic. In many insects, the gene oskar is required for the specification of the germ line. However, the germ line role of oskar is thought to be a derived role resulting from co-option from an ancestral somatic role. To address how evolutionary changes in protein sequence could have led to changes in the function of Oskar protein that enabled it to regulate germ line specification, we searched for oskar orthologs in 1565 publicly available insect genomic and transcriptomic datasets. The earliest-diverging lineage in which we identified an oskar ortholog was the order Zygentoma (silverfish and firebrats), suggesting that oskar originated before the origin of winged insects. We noted some order-specific trends in oskar sequence evolution, including whole gene duplications, clade-specific losses, and rapid divergence. An alignment of all known 379 Oskar sequences revealed new highly conserved residues as candidates that promote dimerization of the LOTUS domain. Moreover, we identified regions of the OSK domain with conserved predicted RNA binding potential. Furthermore, we show that despite a low overall amino acid conservation, the LOTUS domain shows higher conservation of predicted secondary structure than the OSK domain. Finally, we suggest new key amino acids in the LOTUS domain that may be involved in the previously reported Oskar-Vasa physical interaction that is required for its germ line role.
Mechanical phenotyping of acute promyelocytic leukemia reveals unique biomechanical responses in retinoic acid-resistant populations

While all-trans retinoic acid (ATRA) is an essential therapy in the treatment of acute promyelocytic leukemia (APL), an aggressive subtype of acute myeloid leukemia, nearly 20% of APL patients are resistant to ATRA. As no biomarkers for ATRA resistance yet exist, we investigated whether cell mechanics could be associated with this pathological phenotype. Using mechano-node-pore sensing, a single-cell mechanical phenotyping platform, and patient-derived APL cell lines, NB4 (ATRA-sensitive) and AP-1060 (ATRA-resistant), we discovered that ATRA-resistant APL cells are less mechanically pliable. By investigating how different subcellular components of APL cells contribute to whole-cell mechanical phenotype, we determined that nuclear mechanics strongly influence an APL cell’s mechanical response. By arresting APL cells in S-phase or M-phase in the cell cycle, we found cell pliability to be inversely related to DNA content. In addition to DNA content affecting cell pliability, we observed that chromatin condensation also affects nuclear mechanics: decondensing chromatin with trichostatin A is especially effective in softening ATRA-resistant APL cells. RNA-Seq allowed us to compare the transcriptomic differences between ATRA-resistant and ATRA-responsive APL cells and highlighted gene expression changes that could be associated with mechanical changes. Overall, we demonstrate the potential of “physical” biomarkers in identifying APL resistance.
Phospholipid exchange shows insulin receptor activity is supported by both the propensity to form wide bilayers and ordered domains (rafts)

Using efficient methyl-alpha-cyclodextrin mediated lipid exchange, we studied the effect of altering plasma membrane outer leaflet phospholipid composition upon the activity of insulin receptor (IR) in mammalian cells. After substitution of endogenous lipids with lipids having an ability to form liquid ordered (Lo) domains (sphingomyelins) or liquid disordered (Ld) domains (unsaturated phosphatidylcholines (PCs)), we found that the propensity of lipids to form ordered domains is required for high IR activity. Additional substitution experiments using a series of saturated PCs showed that IR activity increased substantially with increasing acyl chain length. Increasing acyl chain length increases both bilayer width and the propensity to form ordered domains. To distinguish the effects of membrane width and domain formation, we incorporated purified IR into alkyl maltoside micelles with increasing hydrocarbon lengths. IR activity increases with increased chain length, but more modestly than by increasing lipid acyl chain length in cells. This suggests that the ability to form Lo domains as well as wide bilayer width contributes to increased IR activity. Inhibition of phosphatases with sodium orthovanadate showed that some of the lipid dependence of IR activity upon lipid structure reflected protection from phosphatases by lipids that support Lo domain formation. The results are consistent with a model in which a combination of bilayer width and ordered domain formation modulate IR activity via effects upon IR conformation and accessibility to phosphatases. Significance This study shows how methyl-α-cyclodextrin mediated lipid exchange can be used to probe the influence of lipid structure upon the functioning of a transmembrane receptor. Plasma membranes having a propensity to form Lo domains are required to support a high level of IR activity. The studies indicate this may reflect an effect of lipid environment upon IR domain localization, which in turn alters its conformation and vulnerability to phosphatases. Alterations in lipid composition could conceivably regulate IR activity in vivo.
Diversity of free-living prokaryotes on terrestrial and marine Antarctic habitats

Microorganisms in Antarctica are recognized for having crucial roles in ecosystems functioning and biogeochemical cycles. In order to explore the diversity and composition of microbial communities through different terrestrial and marine Antarctic habitats, we analyze 16S rRNA sequence datasets from fumarole and marine sediments, soil, snow and seawater environments. We obtained measures of alpha- and beta-diversities, as well as we have identified the core microbiome and the indicator microbial taxa of a particular habitat. Our results showed a unique microbial community structure according to each habitat, including specific taxa composing each microbiome. Marine sediments harbored the highest microbial diversity among the analyzed habitats. In the fumarole sediments, the core microbiome was composed mainly by thermophiles and hyperthermophilic Archaea, while in the majority of soil samples Archaea was absent. In the seawater samples, the core microbiome was mainly composed by cultured and uncultured orders usually identified on Antarctic pelagic ecosystems. Snow samples exhibited common taxa in comparison to the habitats from the Antarctic Peninsula, which suggests long-distance dispersal processes occurring from the Peninsula to the Continent. This study contributes as a baseline for further efforts on evaluating the microbial responses to environmental conditions and future changes.
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson’s disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement kinematics. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS. Significance Statement Neurotechnology will revolutionize the treatment of neurological and psychiatric patients, promising novel treatment avenues for previously intractable brain disorders. However, optimal surgical and computational approaches and their interactions with neurological disorders are unknown. How can recent advances in machine learning and connectomics aid the precision and performance of invasive brain signal decoding strategies? Do the brain disorders treated with such approaches have impact on decoding performance? We propose a real time compatible advanced machine learning pipeline for invasively recorded brain signals in Parkinson’s disease (PD) patients. We report optimal movement decoding strategies with respect to signal source, model architecture and connectomic fingerprint and demonstrate that PD pathophysiology significantly and negatively impacts movement decoding. Our study has broad impacts for the development of smart brain implants for the treatment of PD and other brain disorders.