Miracle-dz/UniFAR-FTUs huggingface dataset:
Everyday sound exposure and the association with human heart rate: evidence 1 from real-world data logging

Prolonged acoustic noise negatively affects human cardiovascular health. However, noise is 15 typically defined by acoustic intensity (i.e. pressure levels) alone, which neglect other dimensions 16 of the sound associated with e.g. the ease of listening. 17 In this study, we used in-market data from hearing aid users to investigate the longitudinal 18 association between multidimensional characteristics of everyday sound logged by the hearing aids 19 and continuous mean heart rate measures logged by the user’s own wearable. 20 We find that increases in ambient sound intensity are significantly related to increases in mean heart 21 rates, corroborating prior laboratory and short-term real-world data. In addition, however, and not 22 previously recognized, we find that increases in the ambient sound quality - that is, the difference 23 between sound signal and noise - are associated with decreases in mean heart rates. 24 Our findings document a mixed influence of everyday sounds on cardiovascular stress, and that the 25 relationship is more complex than is seen from examination of sound intensity alone. In addition, 26 our findings highlight the importance of including environmental sounds to models predicting 27 human physiology.
The organizational principles of de-differentiated topographic maps

Topographic maps are a fundamental feature of cortex architecture in the mammalian brain. One common theory is that the de-differentiation of topographic maps links to impairments in everyday behavior due to less precise functional map readouts. Here, we tested this theory by characterizing de-differentiated topographic maps in primary somatosensory cortex (SI) of younger and older adults by means of ultra-high resolution functional magnetic resonance imaging together with perceptual finger individuation and hand dexterity. Older adults’ SI maps showed similar amplitude, size, and levels of stimulus-related noise than younger adults’ SI maps, but presented with less representational similarity between distant fingers. Larger population receptive field sizes in older adults’ maps did not correlate with behavior, whereas reduced cortical distances related to better hand dexterity. Our data uncover the drawbacks of a simple de-differentiation model of topographic map function, and motivate the introduction of a feature-based model of cortical reorganization.
Sensing and seeing associated with overlapping occipitoparietal activation in simultaneous EEG-fMRI

The presence of a change in a visual scene can influence brain activity and behaviour, even in the absence of full conscious report. It may be possible for us to sense that such a change has occurred, even if we cannot specify exactly where or what it was. Despite existing evidence from electroencephalogram (EEG) and eye-tracking data, it is still unclear how this partial level of awareness relates to fMRI BOLD activation. Using EEG, functional magnetic resonance imaging (fMRI), and a change blindness paradigm, we found multi-modal evidence to suggest that sensing a change is distinguishable from being blind to it. Specifically, trials during which participants could detect the presence of a colour change but not identify the location of the change (sense trials), were compared to those where participants could both detect and localise the change (localise or see trials), as well as change blind trials. In EEG, late parietal positivity and N2 amplitudes were larger for localised changes only, when compared to change blindness. However, ERP-informed fMRI analysis found no voxels with activation that significantly co-varied with fluctuations in single-trial late positivity amplitudes. In fMRI, a range of visual (BA17,18), parietal (BA7,40), and midbrain (anterior cingulate, BA24) areas showed increased fMRI BOLD activation when a change was sensed, compared to change blindness. These visual and parietal areas are commonly implicated as the storage sites of visual working memory, and we therefore argue that sensing may not be explained by a lack of stored representation of the visual display. Both seeing and sensing a change were associated with an overlapping occipitoparietal network of activation when compared to blind trials, suggesting that the quality of the visual representation, rather than the lack of one, may result in partial awareness during the change blindness paradigm.
Phylogenomics of 8,839 Clostridioides difficile genomes reveals recombination-driven evolution and diversification of toxin A and B

Clostridioides difficile is the major worldwide cause of antibiotic-associated gastrointestinal infection. A pathogenicity locus (PaLoc) encoding one or two homologous toxins, toxin A (TcdA) and toxin B (TcdB) is essential for C. difficile pathogenicity. However, toxin sequence variation poses major challenges for the development of diagnostic assays, therapeutics, and vaccines. Here, we present a comprehensive phylogenomic analysis 8,839 C. difficile strains and their toxins including 6,492 genomes that we assembled from the NCBI short read archive. A total of 5,175 tcdA and 8,022 tcdB genes clustered into 7 (A1-A7) and 12 (B1-B12) distinct subtypes, which form the basis of a new method for toxin-based subtyping of C. difficile. We developed a haplotype coloring algorithm to visualize amino acid variation across all toxin sequences, which revealed that TcdB has diversified through extensive homologous recombination throughout its entire sequence, and formed new subtypes through distinct recombination events. In contrast, TcdA varies mainly in the number of repeats in its C-terminal repetitive region, suggesting that recombination-mediated diversification of TcdB provides a selective advantage in C. difficile evolution. The application of toxin subtyping is then validated by classifying 351 C. difficile clinical isolates from Brigham and Women’s Hospital in Boston, demonstrating its clinical utility. Subtyping partitions TcdB into binary functional and antigenic groups generated by intragenic recombinations, including two distinct cell-rounding phenotypes, whether recognizing frizzled proteins as receptors, and whether it can be efficiently neutralized by monoclonal antibody bezlotoxumab, the only FDA-approved therapeutic antibody. Our analysis also identifies eight universally conserved surface patches across the TcdB structure, representing ideal targets for developing broad-spectrum therapeutics. Finally, we established an open online database (DiffBase) as a central hub for collection and classification of C. difficile toxins, which will help clinicians decide on therapeutic strategies targeting specific toxin variants, and allow researchers to monitor the ongoing evolution and diversification of C. difficile.
Pairwise Interactions in Adjuvant Combinations Dictate Immune Responses and Inform Cancer Immunotherapy Design

The immune system makes decisions in response to complex combinations of microbial inputs. We do not understand the combinatorial logic that governs how the interplay between higher-order combinations of microbial or adjuvant signals shape immune responses, which hampers the rational design of vaccines and immunotherapies. Here, using in vitro coculture experiments and statistical analyses, we discover a general property for the combinatorial sensing of microbial signals, whereby the effects of triplet combinations of adjuvants on immune responses can be explained by the effects of single and pairwise stimulations. Mechanistically, we find that adjuvant singles and pairs dictate the information signaled by triplets in mouse and human DCs at the levels of transcription, chromatin and protein secretion. Furthermore, we exploit this simplifying property to develop and characterize cell-based immunotherapies using adjuvant combinations with anti-tumor properties in mouse models. We conclude that the processing of complex mixtures of microbial or adjuvant inputs by immune cells is governed by pairwise effects, which will inform the rationale combination of immunomodulatory agents such as adjuvants to manipulate immunity.
Rapid degradation of GRASP55 and GRASP65 reveals their immediate impact on the Golgi structure

GRASP65 and GRASP55 have been implicated in stacking of Golgi cisternae and lateral linking of stacks within the Golgi ribbon. However, loss of gene function approaches by RNAi or gene knockout to dissect their respective roles often resulted in conflicting conclusions. Here, we gene-edited GRASP55 and/or GRASP65 with a degron tag in human fibroblasts, allowing for the induced rapid degradation by the proteasome. We show that acute depletion of either GRASP55 or GRASP65 does not affect the Golgi ribbon, while chronic degradation of GRASP55 disrupts lateral connectivity of the Golgi ribbon. Acute double depletion of both GRASPs coincides with the loss of the vesicle tethering proteins GM130, p115 and Golgin-45 from the Golgi and compromises ribbon linking. Furthermore, neither GRASP55 and/or GRASP65 are required for maintaining stacks or de novo assembly of stacked cisternae at the end of mitosis. These results demonstrate that both GRASPs are dispensable for Golgi stacking, but are involved in maintaining the integrity of Golgi ribbon together with GM130 and Golgin-45.
Chytridiomycosis Widespread in Anurans of Northeastern United States

Abstract An emerging disease of amphibians caused by the chytrid fungus Batrachochytrium dendrobatidis has been associated with morbidity, mortality, and extinction of species. Typically, researchers have detected B. dendrobatidis only when examining amphibians for causes of mortalities; few data exist on infection rates where mortalities are lacking. During May–September 2000–2002 we obtained amphibian specimens killed by vehicles and others collected at remote off-road sites throughout Maine, USA, and from federal lands in 5 states in the Northeast. We detected infected specimens, mostly green frogs (Rana clamitans), at 5 of 7 national wildlife refuges, a federal waterfowl production area, and Acadia National Park. Seven of 9 species, including all Ranidae species, were infected throughout Maine; rates ranged from 14.6% in American toads (Bufo americanus) to 25.7% in northern leopard frogs (Rana pipiens). We did not detect any infections in 50 eastern gray tree frogs (Hyla versicolor) or 21 spring peepers (Pseudacris crucifer). Species that hibernate in terrestrial habitats seem to have lower rates of infection than species that hibernate in aquatic habitats. Infections peaked in spring and autumn and were associated with air temperatures optimal for B. dendrobatidis growth. The relatively high infection rates among species without documented die-offs suggest that either losses have occurred undetected, that the fungus is endemic and species have attained a level of resistance to infections becoming lethal, or that climatic conditions of the Northeast have a role in preventing infections from being lethal. Data on prevalence and distribution of this chytrid fungus in the Northeast may be useful in modeling its origins and predicting long-term ecosystem effects involving anurans.
A PP2A-Integrator complex fine-tunes transcription by opposing CDK9

Gene expression is tightly controlled by Cyclin-dependent kinases (CDKs) which regulate the RNA Polymerase II (RNAPII) transcription cycle at discrete checkpoints. RNAPII pausing is a CDK9-controlled rate-limiting process that occurs shortly after initiation and is required for spatio-temporal control of transcription in multicellular organisms. We discovered that CDK9-mediated RNAPII pause-release is functionally opposed by a protein phosphatase 2A (PP2A) complex. PP2A dynamically competes for key CDK9 substrates, DSIF and RNAPII, and is recruited to transcription pausing sites by INTS6, a subunit of the Integrator complex. INTS6 depletion disrupts the Integrator-PP2A association and confers resistance to CDK9 inhibition. This results in unrestrained activity of CDK9 and dysregulation of acute transcriptional responses. Pharmacological PP2A activation amplifies RNAPII pausing mediated by CDK9 inhibitors and synergizes therapeutically in a model of MLL-rearranged leukemia. These data demonstrate that finely-tuned gene expression relies on the delicate balance of kinase and phosphatase activity throughout the transcription cycle. HIGHLIGHTS Loss of INTS6 confers resistance to CDK9 inhibition INTS6 recruits PP2A to Integrator and chromatin PP2A/INTS6 complexes functionally oppose CDK9 PP2A/INTS6 fine-tune acute transcriptional responses Synergistic anti-cancer activity between PP2A activators and CDK9 inhibitors
The phylogeny and evolution of the genus Claviceps

Phylogenetic trees of 16 Claviceps species were constructed based on alignments of 5.8S rDNA and the adjacent ITS1 and ITS2 spacers. Two highly supported clades were found: (1) C. paspali, C. zizaniae, C. grohii, C. sulcata, C. fusiformis , and C. purpurea ; and (2) C. citrina, C. phalaridis , two unidentified Claviceps spp. (isolates PM and SG), C. sorghicola, C. gigantea, C. sorghi, C. africana, C. viridis , and C. pusilla. No relationship was found between the species placement and its morphological markers. The probe from C. purpurea gene cpd1 for dimethylallyl tryptophan synthase, the first enzyme of alkaloid biosynthesis, was hybridized to Pst 1 digested genomes of the above species under non-stringent conditions. Hybridizing DNA was present in all species of clade 1, although the signal of the C. paspali gene was weaker. In clade 2, only C. africana, C. gigantea , and C. pusilla gave weak positive signals. Colorimetric detection found small amounts of alkaloids in cultures of Claviceps sp. SG and PM but despite that, no cpd1 hybridizing bands were found. The occurrence of two major clades of Claviceps and their biogeography suggests, that the genus originates from South America and that the evolution of its species was influenced by comigration with their hosts and with the global climatic changes that influenced spreading of grass subfamilies.
ASIC1a is required for neuronal activation via low-intensity ultrasound stimulation in mouse brain

Accumulating evidence has shown transcranial low-intensity ultrasound can be potentially a non-invasive neural modulation tool to treat brain diseases. However, the underlying mechanism remains elusive, because the majority of studies on animal models applying rather high-intensity ultrasound that cannot be safely used in humans. Here we showed low-intensity ultrasound was able to activate neurons in the mouse brain and repeated ultrasound stimulation resulted in adult neurogenesis in specific brain regions. In vitro calcium imaging studies showed that a specific ultrasound stimulation mode, which combined with both ultrasound-induced pressure and acoustic streaming mechanotransduction, is required to activate cultured cortical neurons. ASIC1a and the tether-mode mechanotransduction were involved in the low-intensity ultrasound-mediated mechanotransduction and cultured neuron activation, which was inhibited by ASIC1a blockade and cytoskeleton-modified agents. In contrast, the inhibition of mechanical sensitive channels involved in bilayer-model mechanotransduction like Piezo or TRP proteins did not affect the ultrasound-mediated neuronal activation. SIGNIFICANCE CNS neurons have no sensory function, protected by the skull. For this reason, brain neuromodulation by ultrasound were either done at a high intensity or through auditory nerves. We demonstrate in this study CNS neurons react to ultrasound stimulation at an intensity (5 mW/cm2) far lower than typical therapeutic ultrasound (>30 mW/cm2). Using micropipette ultrasound in calcium imaging, we show the reactions of CNS neurons to ultrasound is through ASIC1a channels, pointing to the molecular basis for direct ultrasound neuromodulation at low intensity. Furthermore, we also show evidence of neurogenesis with the same ultrasound stimulation, suggesting potential therapeutic translation.
Normalizing single-cell RNA sequencing data with internal spike-in-like genes

Normalization with respect to sequencing depth is a crucial step in single-cell RNA sequencing preprocessing. Most methods normalize data using the whole transcriptome based on the assumption that the majority of transcriptome remains constant and are unable to detect drastic changes of the transcriptome. Here, we develop an algorithm based on a small fraction of constantly expressed genes as internal spike-ins to normalize single cell RNA sequencing data. We demonstrate that the transcriptome of single cells may undergo drastic changes in several case study datasets and accounting for such heterogeneity by ISnorm improves the performance of downstream analyzes.
Enhanced COVID-19 data for improved prediction of survival

The current COVID-19 pandemic, caused by the rapid world-wide spread of the SARS-CoV-2 virus, is having severe consequences for human health and the world economy. The virus effects individuals quite differently, with many infected patients showing only mild symptoms, and others showing critical illness. To lessen the impact of the pandemic, one important question is which factors predict the death of a patient? Here, we construct an enhanced COVID-19 dataset by processing two existing databases (from Kaggle and WHO) and using natural language processing methods to enhance the data by adding local weather conditions and research sentiment. Author summary In this study, we contribute an enhanced COVID-19 dataset, which contains 183 samples and 43 features. Application of Extreme Gradient Boosting (XGBoost) on the enhanced dataset achieves 95% accuracy in predicting patients survival, with country-wise research sentiment, and then age and local weather, showing the most importance. All data and source code are available at http://ab.inf. uni-tuebingen.de/publications/papers/COVID-19.
A data-driven method to identify frequency boundaries in multichannel electrophysiology data

Background Electrophysiological recordings of the brain often exhibit neural oscillations, defined as narrowband bumps that deviate from the background power spectrum. These narrowband dynamics are grouped into frequency ranges, and the study of how activities in these ranges are related to cognition and disease is a major part of the neuroscience corpus. Frequency ranges are nearly always defined according to integer boundaries, such as 4-8 Hz for the theta band and 8-12 Hz for the alpha band. New method A data-driven multivariate method is presented to identify empirical frequency boundaries based on clustering of spatiotemporal similarities across a range of frequencies. The method, termed gedBounds, identifies patterns in covariance matrices that maximally separate narrowband from broadband activity, and then identifies clusters in the correlation matrix of those spatial patterns over all frequencies, using the dbscan algorithm. Those clusters are empirically derived frequency bands, from which boundaries can be extracted. Results gedBounds recovers ground truth results in simulated data with high accuracy. The method was tested on EEG resting-state data from Parkinson’s patients and control, and several features of the frequency components differed between patients and controls. Comparison with existing methods The proposed method offers higher precision in defining subject-specific frequency boundaries compared to the current standard approach. Conclusions gedBounds can increase the precision and feature extraction of spectral dynamics in electrophysiology data.
Cortical Localization of the Sensory-Motor Transformation in a Whisker Detection Task in Mice

Abstract Responding to a stimulus requires transforming an internal sensory representation into an internal motor representation. Where and how this sensory-motor transformation occurs is a matter of vigorous debate. Here, we trained male and female mice in a whisker detection go/no-go task in which they learned to respond (lick) following a transient whisker deflection. Using single unit recordings, we quantified sensory-related, motor-related, and choice-related activities in whisker primary somatosensory cortex (S1), whisker region of primary motor cortex (wMC), and anterior lateral motor cortex (ALM), three regions that have been proposed to be critical for the sensory-motor transformation in whisker detection. We observed strong sensory encoding in S1 and wMC, with enhanced encoding in wMC, and a lack of sensory encoding in ALM. We observed strong motor encoding in all three regions, yet largest in wMC and ALM. We observed the earliest choice probability in wMC, despite earliest sensory responses in S1. Based on the criteria of having both strong sensory and motor representations and early choice probability, we identify whisker motor cortex as the cortical region most directly related to the sensory-motor transformation. Our data support a model of sensory encoding originating in S1, sensory amplification and sensory-motor transformation occurring within wMC, and motor signals emerging in ALM after the sensory-motor transformation.
Bayesian Decoder Models with a Discriminative Observation Process

The Bayesian state-space neural encoder-decoder modeling framework is an established solution to reveal how changes in brain dynamics encode physiological covariates like movement or cognition. Although the framework is increasingly being applied to progress the field of neuroscience, its application to modeling high-dimensional neural data continues to be a challenge. Here, we propose a novel solution that avoids the complexity of encoder models that characterize high-dimensional data as a function of the underlying state processes. We build a discriminative model to estimate state processes as a function of current and previous observations of neural activity. We then develop the filter and parameter estimation solutions for this new class of state-space modeling framework called the “direct decoder” model. We apply the model to decode movement trajectories of a rat in a W-shaped maze from the ensemble spiking activity of place cells and achieve comparable performance to modern decoding solutions, without needing an encoding step in the model development. We further demonstrate how a dynamical auto-encoder can be built using the direct decoder model; here, the underlying state process links the high-dimensional neural activity to the behavioral readout. The dynamical auto-encoder can optimally estimate the low-dimensional dynamical manifold which represents the relationship between brain and behavior.
JAK/STAT pathway promotes Drosophila neuroblast proliferation via the direct CycE regulation

How neural stem cells regulate their proliferative potential and lineage diversity is a central problem in developmental neurobiology. Drosophila Mushroom bodies (MBs), centers of olfactory learning and memory, are generated by a specific set of neuroblasts (Nbs) that are born in the embryonic stage and continuously proliferate till the end of the pupal stage. Although MB presents an excellent model for studying neural stem cell proliferation, the genetic and molecular mechanisms that control the unique proliferative characteristics of the MB Nbs are largely unknown. Further, the signaling cues controlling cell cycle regulators to promote cell cycle progression in MB Nbs remain poorly understood. Here, we report that JAK/STAT signaling pathway is required for the proliferation activity and maintenance of MB Nbs. Loss of JAK/STAT activity severely reduces the later-born MB neuron types and leads to premature neuroblast termination, which can be rescued by tissue-specific overexpression of CycE and diap1. Higher JAK/STAT pathway activity in MB results in more neurons, without producing supernumerary Nbs. Furthermore, we show that JAK/STAT signaling effector Stat92E directly regulates CycE transcription in MB Nbs. Finally, MB Nb clones of loss or excess CycE phenocopy those of decreased or increased JAK/STAT signaling pathway activities. We conclude that JAK/STAT signaling controls MB Nb proliferative activity through directly regulating CycE expression to control cell cycle progression.