Miracle-dz/UniFAR-FTUs huggingface dataset:
Total Hemispherical Emissivity of Grade 91 Ferritic Alloy with Various Surface Conditions

Abstract For very-high-temperature reactors (VHTRs), the ability of structural components, specifically the reactor pressure vessel, to dissipate heat by radiation is an important design criterion. Thus, in selecting components for VHTR applications, it is necessary to measure the emissivity of all structural materials being considered. With the standard ASTM C835-06 test method, the total hemispherical emissivity of A387 Grade 91 steel, a leading candidate alloy for VHTR structural applications, was measured under four distinct surface conditions: (1) mild abrasion following electrical discharge machining, (2) increased surface roughness via sandblasting, (3) coating with NBG-18 graphite powder, and (4) oxidization in air. A detailed account of experimental methods and procedures, as well as the results of the total hemispherical emissivity measurements, are presented.
Emergent Myxobacterial Behaviors Arise from Reversal Suppression Induced by Kin Contacts

In many species, large populations exhibit emergent behaviors whereby all related individuals move in unison. For example, fish in schools can all dart in one direction simultaneously to avoid a predator. ABSTRACT A wide range of biological systems, from microbial swarms to bird flocks, display emergent behaviors driven by coordinated movement of individuals. To this end, individual organisms interact by recognizing their kin and adjusting their motility based on others around them. However, even in the best-studied systems, the mechanistic basis of the interplay between kin recognition and motility coordination is not understood. Here, using a combination of experiments and mathematical modeling, we uncover the mechanism of an emergent social behavior in Myxococcus xanthus. By overexpressing the cell surface adhesins TraA and TraB, which are involved in kin recognition, large numbers of cells adhere to one another and form organized macroscopic circular aggregates that spin clockwise or counterclockwise. Mechanistically, TraAB adhesion results in sustained cell-cell contacts that trigger cells to suppress cell reversals, and circular aggregates form as the result of cells’ ability to follow their own cellular slime trails. Furthermore, our in silico simulations demonstrate a remarkable ability to predict self-organization patterns when phenotypically distinct strains are mixed. For example, defying naive expectations, both models and experiments found that strains engineered to overexpress different and incompatible TraAB adhesins nevertheless form mixed circular aggregates. Therefore, this work provides key mechanistic insights into M. xanthus social interactions and demonstrates how local cell contacts induce emergent collective behaviors by millions of cells. IMPORTANCE In many species, large populations exhibit emergent behaviors whereby all related individuals move in unison. For example, fish in schools can all dart in one direction simultaneously to avoid a predator. Currently, it is impossible to explain how such animals recognize kin through brain cognition and elicit such behaviors at a molecular level. However, microbes also recognize kin and exhibit emergent collective behaviors that are experimentally tractable. Here, using a model social bacterium, we engineer dispersed individuals to organize into synchronized collectives that create emergent patterns. With experimental and mathematical approaches, we explain how this occurs at both molecular and population levels. The results demonstrate how the combination of local physical interactions triggers intracellular signaling, which in turn leads to emergent behaviors on a population scale.
De novo Mutations in Domestic Cat are Consistent with an Effect of Reproductive Longevity on Both the Rate and Spectrum of Mutations

The mutation rate is a fundamental evolutionary parameter with direct and appreciable effects on the health and function of individuals. Here, we examine this important parameter in the domestic cat, a beloved companion animal as well as a valuable biomedical model. We estimate a mutation rate of 0.86 × 10-8 per bp per generation for the domestic cat (at an average parental age of 3.8 years). We find evidence for a significant paternal age effect, with more mutations transmitted by older sires. Our analyses suggest that the cat and the human have accrued similar numbers of mutations in the germline before reaching sexual maturity. The per-generation mutation rate in the cat is 28% lower than what has been observed in humans, but is consistent with the shorter generation time in the cat. Using a model of reproductive longevity, which takes into account differences in the reproductive age and time to sexual maturity, we are able to explain much of the difference in per-generation rates between species. We further apply our reproductive longevity model in a novel analysis of mutation spectra and find that the spectrum for the cat resembles the human mutation spectrum at a younger age of reproduction. Together, these results implicate changes in life-history as a driver of mutation rate evolution between species. As the first direct observation of the paternal age effect outside of rodents and primates, our results also suggest a phenomenon that may be universal among mammals.
Assessing bivalve phylogeny using Deep Learning and Computer Vision approaches

Phylogenetic analyses using morphological data currently require hand-crafted character matrices, limiting the number of taxa that can be included. Here I explore how Deep Learning and Computer Vision approaches typically applied to image classification tasks, may be used to infer phylogenetic relationships among bivalves. A convolutional neural network (CNN) was trained on thousands of images showing species of 75 bivalve families. The predictions of the CNN on a large number of bivalve images are then interpreted as an indication of how similar these bivalves are to each other, are averaged by the families to which the species belonged, and visualized in a cluster diagram. In this cluster diagram, significantly more families clustered with members of their subclasses than expected by chance, confirming the feasibility of the approach. To address the issue of convergent evolution, two further CNNs were trained, on the same images but grouped by the orders and subclasses to which the species belonged. Combining predictions for the same images but on different taxonomic levels improved the inferred phylogenetic relationships also of families that the CNNs had not been trained on. Finally, this combined tree is merged with five published phylogenetic trees into a supertree, representing the largest single phylogeny of the Bivalvia to date, encompassing 128 families, including six exclusively fossil families and nine extant families for which presently no molecular data are available. Issues inherent to the approach and suggestions for future directions are discussed.
Photodynamic Inactivation reduces the diversity and changes the composition of bacterial and fungal communities associated with leaf surfaces

Plant surfaces are colonized by a myriad of microorganisms including mutualistic strains and pathogens. Particularly in agricultural systems applications are required that protect the plants against pathogens without negative side effects on the environment and humans. Photodynamic Inactivation (PDI) has been demonstrated to be a promising approach to efficiently fight plant pathogens. Based on its mechanism of action, the light-induced and photosensitizer-mediated overproduction of reactive oxygen species in target cells, PDI is likely to generally inactivates microorganisms on plants irrespective of their pathogenicity. In order to prove this hypothesis we used next-generation 16S rRNA gene amplicon sequencing to characterize the bacterial and fungal communities associated with leaf surfaces of Arabidopsis thaliana before and after the photodynamic treatment using the chlorine e6 derivative B17-0024 as photoactive compound and showed that this treatment reduced the microbial richness and altered the microbial community composition. These findings may help to develop effective pathogen-control strategies and may also stimulate research on plant-microbe interactions exploiting the potential of PDI.
Interactions between SARS-CoV-2 N-Protein and α-Synuclein Accelerate Amyloid Formation

First cases that point at a correlation between SARS-CoV-2 infections and the development of Parkinson’s disease have been reported. Currently it is unclear if there also is a direct causal link between these diseases. To obtain first insights into a possible molecular relation between viral infections and the aggregation of α-synuclein protein into amyloid fibrils characteristic for Parkinson’s disease, we investigated the effect of the presence of SARS-CoV-2 proteins on α-synuclein aggregation. We show, in test tube experiments, that SARS-CoV-2 S-protein has no effect on α-synuclein aggregation while SARS-CoV-2 N-protein considerably speeds up the aggregation process. We observe the formation of multi-protein complexes, and eventually amyloid fibrils. Microinjection of N-protein in SHSY-5Y cells disturbed the α-synuclein proteostasis and increased cell death. Our results point toward direct interactions between the N-protein of SARS-CoV-2 and α-synuclein as molecular basis for the observed coincidence between SARS-CoV-2 infections and Parkinsonism.
Prediction and Evolution of the Molecular Fitness of SARS-CoV-2 Variants: Introducing SpikePro

The understanding of the molecular mechanisms driving the fitness of the SARS-CoV-2 virus and its mutational evolution is still a critical issue. We built a simplified computational model, called SpikePro, to predict the SARS-CoV-2 fitness from the amino acid sequence and structure of the spike protein. It contains three contributions: the viral transmissibility predicted from the stability of the spike protein, the infectivity computed in terms of the affinity of the spike protein for the ACE2 receptor, and the ability of the virus to escape from the human immune response based on the binding affinity of the spike protein for a set of neutralizing antibodies. Our model reproduces well the available experimental, epidemiological and clinical data on the impact of variants on the biophysical characteristics of the virus. For example, it is able to identify circulating viral strains that, by increasing their fitness, recently became dominant at the population level. SpikePro is a useful instrument for the genomic surveillance of the SARS-CoV-2 virus, since it predicts in a fast and accurate way the emergence of new viral strains and their dangerousness. It is freely available in the GitHub repository github.com/3BioCompBio/SpikeProSARS-CoV-2.
State-dependent egocentric and allocentric heading representation in the monarch butterfly brain

Head direction can be represented in a self-centered egocentric or a viewpoint-invariant allocentric reference frame. Using the most efficient representation is especially crucial for migrating animals, like monarch butterflies (Danaus plexippus) that use the sun for orientation. With tetrode recordings from the brain of tethered flying monarch butterflies, we examined the reference frame in which insects encode heading. We show that compass neurons switch their reference frame in a state-dependent manner. In quiescence, they encode sun-bearing angles, allowing the butterfly to map the environment within an egocentric frame. However, during flight, the same neurons encode heading within an allocentric frame. This switch converts the sun from a local to a global cue, an ideal strategy for maintaining a migratory heading over large distance. One-Sentence Summary Heading information is encoded in different state-dependent reference frames in the monarch butterfly central complex
What is a supercoiling-sensitive gene? Insights from topoisomerase I inhibition in the Gram-negative bacterium Dickeya dadantii

DNA supercoiling is an essential mechanism of bacterial chromosome compaction, whose level is mainly regulated by topoisomerase I and DNA gyrase. Inhibiting either of these enzymes with antibiotics leads to global supercoiling modifications and subsequent changes in global gene expression. In previous studies, genes responding to DNA relaxation induced by gyrase inhibition were categorised as “supercoiling-sensitive”. Here, we studied the opposite variation of DNA supercoiling in the phytopathogen Dickeya dadantii using the non-marketed antibiotic seconeolitsine. We showed that the drug is active against topoisomerase I from this species, and analysed the first transcriptomic response of a Gram-negative bacterium to topoisomerase I inhibition. We find that the responding genes essentially differ from those observed after DNA relaxation, and further depend on the growth phase. We characterised these genes at the functional level, and also detected distinct patterns in terms of expression level, spatial and orientational organisation along the chromosome. Altogether, these results highlight that the supercoiling-sensitivity is a complex feature, which depends on the action of specific topoisomerases, on the physiological conditions, and on their genomic context. Based on previous in vitro expression data of several promoters, we propose a qualitative model of SC-dependent regulation that accounts for many of the contrasting transcriptomic features observed after gyrase or topoisomerase I inhibition.
Highly-potent, synthetic APOBEC3s restrict HIV-1 through deamination-independent mechanisms

The APOBEC3 (A3) genes encode cytidine deaminase proteins with potent antiviral and anti-retroelement activity. This locus is characterized by duplication, recombination, and deletion events that gave rise to the seven A3s found in primates. These include three single deaminase domain A3s (A3A, A3C, and A3H) and four double deaminase domain A3s (A3B, A3D, A3F, and A3G). The most potent of the A3 proteins against HIV-1 is A3G. However, it is not clear if double deaminase domain A3s have a generalized functional advantage to restrict HIV-1. In order to test whether superior restriction factors could be created by genetically linking single A3 domains into synthetic double domains, we combined A3C and A3H single domains in novel combinations. We found that A3C/A3H double domains acquired enhanced antiviral activity that is at least as potent, if not better than, A3G. These synthetic double domain A3s have more efficiency of packaging into budding virions than their respective single domains, but this does not fully explain their gain of antiviral potency. The antiviral activity is conferred both by cytidine-deaminase dependent and independent mechanisms, with the latter correlating to an increase in RNA binding affinity. T cell lines expressing this A3C-A3H super restriction factor are able to control replicating HIV-1ΔVif infection to similar levels as A3G. Together, these data show that novel combinations of A3 domains are capable of gaining potent antiviral activity to levels similar to the most potent genome-encoded A3s, via a primarily non-catalytic mechanism. Author Summary Antiviral genes are encoded by all organisms to help protect them from viral infections, including proteins encoded by primates to protect them from viruses similar to HIV-1. These antiviral proteins are also called “restriction factors”. Some restriction factors are broadly acting, while others are very specific. During the course of evolution, some of these genes have expanded into multiple copies and rearranged in different versions to give them new activities. However, not all versions of these genes have been sampled in nature. In this paper, we validated the hypothesis that one particular antiviral gene family, called the APOBEC3 family, has the capability of making novel combinations of antiviral genes with as great, or greater, potency against HIV-1 as the most potent natural member of this family. By combining parts of the APOBEC3 proteins into novel combinations, we created potent antiviral versions that act through a mechanism distinct from existing APOBEC3 proteins.
Detection of sleep apnea from single-channel electroencephalogram (EEG) using an explainable convolutional neural network (CNN)

Sleep apnea (SA) is a common disorder involving the cessation of breathing during sleep. It can cause daytime hypersomnia, accidents, and, if allowed to progress, serious, chronic conditions. Continuous positive airway pressure is an effective SA treatment. However, long waitlists impede timely diagnosis; overnight sleep studies involve trained technicians scoring a polysomnograph, which comprises multiple physiological signals including multi-channel electroencephalography (EEG). Therefore, it is important to develop simplified and automated approaches to detect SA. We have developed an explainable convolutional neural network (CNN) to detect SA from single-channel EEG recordings which generalizes across subjects. The network architecture consisted of three convolutional layers. We tuned hyperparameters using the Hyperband algorithm, optimized parameters using Adam, and quantified network performance with subjectwise 10-fold cross-validation. Our CNN performed with an accuracy of 76.7% and a Matthews correlation coefficient (MCC) of 0.54. This performance was reliably above the conservative baselines of 50% (accuracy) and 0.0 (MCC). To explain the mechanisms of our trained network, we used critical-band masking (CBM): after training, we added bandlimited noise to test recordings; we parametrically varied the noise band center frequency and noise intensity, quantifying the deleterious effect on performance. We reconciled the effects of CBM with lesioning, wherein we zeroed the trained network’s 1st-layer filter kernels in turn, quantifying the deleterious effect on performance. These analyses indicated that the network learned frequency-band information consistent with known SA biomarkers, specifically, delta and beta band activity. Our results indicate single-channel EEG may have clinical potential for SA diagnosis.
The males of the parasitoid wasp, Nasonia vitripennis, can identify which fly hosts contain females

The reproductive success of a male is limited by the number of females it can mate with. Thus, males deploy elaborate mate-finding strategies to maximize access to females. In the haplodiploid wasp genus, Nasonia, which are parasitoids of cyclorrhaphous flies, mate-finding is restricted to the natal patch, where males compete for access to females. This study investigates whether there are any additional mate finding strategies of males, especially, whether they can identify the presence of adult females which are still inside the fly host. Results reveal that only one out of the four species, N. vitripennis, can distinguish which hosts specifically have adult female wasps indicating a species-specific unique mate-finding capability. Behavioral assays revealed that the cues used by N. vitripennis males are olfactory in nature and not auditory or visual. GC-MS analyses show that these olfactory cues are female-specific cuticular hydrocarbons (CHCs), possibly emanating from within the fly puparium. Further assays indicated that N. vitripennis males can also detect differences in the concentrations of compounds to identify female-specific cues from male-specific ones. This study, therefore, uncovers a previously unknown mate-finding strategy in one of the most widely studied parasitoid wasp.
E2F/Dp inactivation in fat body cells triggers systemic metabolic changes

The E2F transcription factors play a critical role in controlling cell fate. In Drosophila, the inactivation of E2F in either muscle or fat body results in lethality, suggesting an essential function for E2F in these tissues. However, the cellular and organismal consequences of inactivating E2F in these tissues are not fully understood. Here, we show that the E2F loss exerts both tissue-intrinsic and systemic effects. The proteomic profiling of E2F-deficient muscle and fat body revealed that E2F regulates carbohydrate metabolism, a conclusion further supported by metabolomic profiling. Intriguingly, animals with E2F-deficient fat body had a lower level of circulating trehalose and reduced storage of fat. Strikingly, a sugar supplement was sufficient to restore both trehalose and fat levels, and subsequently, rescued animal lethality. Collectively, our data highlight the unexpected complexity of E2F mutant phenotype, which is a result of combining both tissue-specific and systemic changes that contribute to animal development.
Mutation rate dynamics reflect ecological change in an emerging zoonotic pathogen

While mutation is often deleterious, it can also be adaptive. Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study we investigate two factors that are predicted to influence the trade-off between the costs and benefits of mutation: ecology and genome size. To investigate the relationship between these factors and mutation rate we conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact ecology can have on the adaptive potential of bacterial pathogens.
Enteric pathogens induce tissue tolerance and prevent neuronal loss from subsequent infections

The enteric nervous system (ENS) controls several intestinal functions including motility and nutrient handling, which can be disrupted by infection-induced neuropathies or neuronal cell death. We investigated possible tolerance mechanisms preventing neuronal loss and disruption in gut motility after pathogen exposure. We found that following enteric infections, muscularis macrophages (MMs) acquire a tissue-protective phenotype that prevents neuronal loss and dysmotility during subsequent challenge with unrelated pathogens. Bacteria-induced neuroprotection relied on activation of gut-projecting sympathetic neurons and signaling via β2-adrenergic receptors (β2AR) on MMs. In contrast, helminth-mediated neuroprotection was dependent on T cells and systemic production of interleukin (IL)-4 and -13 by eosinophils, which induced arginase-expressing MMs that prevented neuronal loss from an unrelated infection located in a different intestinal region. Collectively, these data suggest that distinct enteric pathogens trigger a state of disease- or tissue tolerance that preserves ENS number and functionality.