Miracle-dz/UniFAR-FTUs huggingface dataset:
Viruses encode tRNA and anti-retron to evade bacterial immunity

Retrons are bacterial genetic retroelements that encode reverse transcriptase capable of producing multicopy single-stranded DNA (msDNA) and function as antiphage defense systems. Phages employ several strategies to counter the host defense systems, but no mechanisms for evading retrons are known. Here, we show that tRNATyr and Rad (retron anti-defense) of T5 phage family inhibit the defense activity of retron 78 and a broad range of retrons, respectively. The effector protein of retron 78, ptuAB, specifically degraded tRNATyr leading abortive infection, but phage countervailed this defense by supplying tRNATyr. Rad inhibited retron function by degrading noncoding RNA, the precursor of msDNA. In summary, we demonstrated that viruses encode at least two independent strategies for overcoming bacterial defense systems: anti-defense, such as Rad, and defense canceler, like tRNA.
Novel VCP activator reverses multisystem proteinopathy nuclear proteostasis defects and enhances TDP-43 aggregate clearance

Pathogenic variants in VCP cause multisystem proteinopathy (MSP), a disease characterized by multiple clinical phenotypes including inclusion body myopathy, Paget’s disease of the bone, and frontotemporal dementia (FTD). How such diverse phenotypes are driven by pathogenic VCP variants is not known. We found that these diseases exhibit a common pathologic feature, ubiquitinated intranuclear inclusions affecting myocytes, osteoclasts and neurons. Moreover, knock-in cell lines harboring MSP variants show a reduction in nuclear VCP. Given that MSP is associated with neuronal intranuclear inclusions comprised of TDP-43 protein, we developed a cellular model whereby proteostatic stress results in the formation of insoluble intranuclear TDP-43 aggregates. Consistent with a loss of nuclear VCP function, cells harboring MSP variants or cells treated with VCP inhibitor exhibited decreased clearance of insoluble intranuclear TDP-43 aggregates. Moreover, we identified four novel compounds that activate VCP primarily by increasing D2 ATPase activity whereby pharmacologic VCP activation appears to enhance clearance of insoluble intranuclear TDP-43 aggregate. Our findings suggest that VCP function is important for nuclear protein homeostasis, that MSP may be the result of impaired nuclear proteostasis, and that VCP activation may be potential therapeutic by virtue of enhancing the clearance of intranuclear protein aggregates.
Limits to the adaptation of herbivorous spider mites to metal accumulation in homogeneous and heterogeneous environments

Metal accumulation is used by some plants as a defence against herbivores. Yet, herbivores may adapt to these defences, becoming less susceptible. Moreover, ecosystems often contain plants that do and do not accumulate metals, and such heterogeneity may affect herbivore adaptation. Surprisingly, few studies have tested this. Tomato plants accumulate cadmium, affecting the performance of the herbivorous spider mite Tetranychus evansi. Here, we performed experimental evolution to test whether these mites adapt to plants with high cadmium concentrations, in homogeneous (plants with cadmium) or heterogeneous (plants with and without cadmium) environments. We measured fecundity, hatching rate and the number of adult offspring after 12 and 33 generations and habitat choice after 14 and 51 generations, detecting no trait change, which implies absence of adaptation. We then tested whether this absence of adaptation was due to a lack of genetic variation in the traits measured and, indeed, additive genetic variance was low for the measured traits. Possibly, we did not measure the traits that contributed to population persistence on plants with cadmium. Interestingly, despite no signs of adaptation we observed a decrease in fecundity and number of adult offspring produced in cadmium-free plants, in the populations evolving in environments with cadmium. Being this the case, evolving in environments with cadmium may reduce the growth rate of spider mite populations on non-accumulating plants as well. Nevertheless, adaptation to metal accumulation may occur via herbivore traits not commonly measured, which calls for broader studies on this topic.
Fast layer-fMRI VASO with short stimuli and event-related designs at 7T

Layers and columns are the dominant processing units in the human (neo)cortex at the meso-scopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical sur-face. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing com-plementary information of locally specific changes in cerebral blood volume (CBV). Specifically, VASO is not subject to unwanted sensitivity amplifications of large draining veins. Because of constrained sampling efficiency, it has been mainly applied in combination with efficient block task designs and long trial durations. However, to study cognitive processes in neuroscientific contexts, or probe vascular reactivity, short stimulation periods are often necessary. Here, we developed a VASO acquisition procedure with a short acquisition period (895 ms volume acqui-sition) and sub-millimetre resolution. During visual event-related stimulation, we show reliable responses in visual cortices within a reasonable number of trials (∼20). Furthermore, the short TR and high spatial specificity of our VASO implementation enabled us to show differences in laminar reactivity and onset times. Finally, we explore the generalizability to a different stimu-lus modality (somatosensation). With this, we showed that CBV-sensitive VASO provides the means to capture layer-specific haemodynamic responses with high spatio-temporal resolution and is able to be used with event-related paradigms.
NEURD: automated proofreading and feature extraction for connectomics

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present “NEURD”, a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows for state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other features that can enable many downstream analyses of neural morphology and connectivity. NEURD can make these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.
An evolutionary epigenetic clock in plants

Molecular clocks are the basis for dating the divergence between lineages over macro-evolutionary timescales (~105-108 years). However, classical DNA-based clocks tick too slowly to inform us about the recent past. Here, we demonstrate that stochastic DNA methylation changes at a subset of cytosines in plant genomes possess a clock-like behavior. This ‘epimutation-clock’ is orders of magnitude faster than DNA-based clocks and enables phylogenetic explorations on a scale of years to centuries. We show experimentally that epimutation-clocks recapitulate known topologies and branching times of intra-species phylogenetic trees in the selfing plant A. thaliana and the clonal seagrass Z. marina, which represent two major modes of plant reproduction. This discovery will open new possibilities for high-resolution temporal studies of plant biodiversity.
Burn conditions stabilization with artificial neural networks of subignited thermonuclear reactors with scaling law uncertainties

In this work it is demonstrated that robust burn control in long-pulse operations of subignited thermonuclear reactors can be achieved with radial basis neural networks (RBNNs) composed of Gaussian nodes in the hidden layer and sigmoidal units in the output layer. The results reported here correspond to a volume-averaged zero-dimensional nonlinear model of a subignited fusion reactor with design parameters corresponding to those of the ITER-EDA group. The control actions are implemented through the concurrent modulation of the D-T refuelling rate, a neutral 4He beam and an auxiliary heating power, constrained to lie below maximum allowable levels. It is shown that the resulting network provides feedback stabilization over a wide range of energy confinement times for plasma density and temperature excursions significantly far from their nominal operating values. The results show that the RBNN feedback-controlled nonlinear system is stable regardless of any particular scaling law, as long as the confinement time lies within the scope of the training region. In addition, it also shows robustness with respect to noise in the energy confinement time value fed into the controller during simulated transients of a thermonuclear system using a particular ELMy scaling law, as well as with respect to the thermalization time of the alpha particles produced by fusion.
Public engagement with biomedical science: An analysis of Black, Hispanic, and General Population adults in the United States

The COVID-19 pandemic has highlighted the need to better understand public engagement with biomedical science across groups–especially those that have been historically marginalized by the medical science community. However, common approaches to studying group differences in science attitudes are often limited by small sample sizes or by categorizing individuals based on demographic variables, which may obscure meaningful variability within a given population. We recruited three probability-based samples of Black (N = 963), General Population (N = 957), and Hispanic (N = 964) adults living in the U.S. (October 21 - November 5, 2021). Employing a novel application of a non-negative matrix factorization model to conduct an attitudinal-based segmentation that categorized individuals based on distinct orientations toward biomedical science, our analysis revealed 10 unique mindsets across the three surveyed populations. Overall, our work underscores the value of recruiting independent samples from underserved and marginalized communities by revealing underexplored variation in how different publics orient toward biomedical science. Teaser Using a values-based segmentation approach, we uncover 10 unique biomedical mindsets in the general, Black, and Hispanic adult populations in the U.S.
3DMolMS: prediction of tandem mass spectra from 3D molecular conformations

Motivation Tandem mass spectrometry is an essential technology for characterizing chemical compounds at high sensitivity and throughput, and is commonly adopted in many fields. However, computational methods for automated compound identification from their MS/MS spectra are still limited, especially for novel compounds that have not been previously characterized. In recent years, in silico methods were proposed to predict the MS/MS spectra of compounds, which can then be used to expand the reference spectral libraries for compound identification. However, these methods did not consider the compounds’ three-dimensional (3D) conformations, and thus neglected critical structural information. Results We present the 3D Molecular Network for Mass Spectra Prediction (3DMolMS), a deep neural network model to predict the MS/MS spectra of compounds from their 3D conformations. We evaluated the model on the experimental spectra collected in several spectral libraries. The results showed that 3DMolMS predicted the spectra with the average cosine similarity of 0.687 and 0.475 with the experimental MS/MS spectra acquired in positive and negative ion modes, respectively. Furthermore, 3DMolMS model can be generalized to the prediction of MS/MS spectra acquired by different labs on different instruments through minor fine-tuning on a small set of spectra. Finally, we demonstrate that the molecular representation learned by 3DMolMS from MS/MS spectra prediction can be adapted to enhance the prediction of chemical properties such as the elution time (ET) in the liquid chromatography and the Collisional Cross Section (CCS) measured by ion mobility spectrometry (IMS), both of which are often used to improve compound identification. Contact hatang@indiana.edu Supplementary information The codes of 3DMolMS is available at https://github.com/JosieHong/3DMolMS and the web service is at https://spectrumprediction.gnps2. org.
Endophyte genomes support greater metabolic gene cluster diversity compared with non-endophytes in Trichoderma

Trichoderma is a cosmopolitan genus with diverse lifestyles and nutritional modes, including mycotrophy, saprophytism, and endophytism. Previous research has reported greater metabolic gene repertoires in endophytic fungal species compared to closely-related non-endophytes. However, the extent of this ecological trend and its underlying mechanisms are unclear. Some endophytic fungi may also be mycotrophs and have one or more mycoparasitism mechanisms. Mycotrophic endophytes are prominent in certain genera like Trichoderma, therefore, the mechanisms that enable these fungi to colonize both living plants and fungi may be the result of expanded metabolic gene repertoires. Our objective was to determine what, if any, genomic features are overrepresented in endophytic fungi genomes in order to undercover the genomic underpinning of the fungal endophytic lifestyle. Here we compared metabolic gene cluster and mycoparasitism gene diversity across a dataset of thirty-eight Trichoderma genomes representing the full breadth of environmental Trichoderma’s diverse lifestyles and nutritional modes. We generated four new Trichoderma endophyticum genomes to improve the sampling of endophytic isolates from this genus. As predicted, endophytic Trichoderma genomes contained, on average, more total biosynthetic and degradative gene clusters than non-endophytic isolates, suggesting that the ability to create/modify a diversity of metabolites potential is beneficial or necessary to the endophytic fungi. Still, once the phylogenetic signal was taken in consideration, no particular class of metabolic gene cluster was independently associated with the Trichoderma endophytic lifestyle. Several mycoparasitism genes, but no chitinase genes, were associated with endophytic Trichoderma genomes. Most genomic differences between Trichoderma lifestyles and nutritional modes are difficult to disentangle from phylogenetic divergences among species, suggesting that Trichoderma genomes maybe particularly well-equipped for lifestyle plasticity. We also consider the role of endophytism in diversifying secondary metabolism after identifying the horizontal transfer of the ergot alkaloid gene cluster to Trichoderma.
Exploring intermediary practices of collaboration in university–industry innovation: A practice theory approach

The intensity of the global and distributed economy requires innovative efforts that single organizations often cannot develop alone. Collaborative innovation is traditionally studied in terms of collaborative process to maintain and outcomes to implement. However, collaborations relating to innovation often take place in difficult-to-explore spaces in-between. This study adopts a practice-based approach to explore practices of collaboration developed by the university as an intermediary in innovative projects. Drawing on a case study, we identify four micro-practices that appear crucial to initiating and sustaining collaboration: networking, partnering, culture making and supporting. We outline the purpose and constituent objects, doings and knowledge of each practice. This article contributes to ongoing debate around improving the effectiveness of collaborative innovation and provides insights into how a set of apparently insignificant, routinized micro-practices contribute to intermediaries' success in initiating and sustaining collaborations.
Bayes Factors in Practice

Computational advances have facilitated application of various Bayesian methods, including the assessment of evidence in favor of a scientific theory. This is accomplished by calculating a Bayes factor. It is important to recognize, however, that the value of a Bayes factor may be sensitive to the choice of priors on parameters appearing in the competing models. This sensitivity is illustrated and discussed. The Schwarz criterion remains a crude yet useful approximation, but more accurate methods will generally require determination of priors and subjective sensitivity analysis.
Convective and Rotational Parameters Associated with Three Tornado Episodes in Northern and Central California

Abstract An overview of the synoptic and subsynoptic controls on three tornado episodes (seven tornadoes) in northern and central California during December 1992 is presented and compared to the “prototype” documented for the 24 September 1986 mesocyclone-induced F2 event in the Sacramento Valley. Convective and rotational parameters calculated interactively on the Skew T/Hodograph Analysis and Research Programs supported anecdotal evidence that the tornadoes considered in this study were mesocyclone induced. The study indicates that careful subsynoptic analyses and evaluation of buoyancy and shear parameters can establish a mesoscale focus for supercellular development in California “cold sector,” low buoyancy-moderate shear thunderstorm environments.
Harbor seals respond with aversion to 69‐kHz pings: Implications for weighting procedures for marine mammal noise metrics.

Author Shane tracked cultured white seabass (Atractoscion nobilis) instrumented with 69‐kHz ultrasonic coded transmitters (UCTs) in the vicinity of harbor seals (Phoca vitulina), later finding the bones of fish associated with UCTs. This led the authors to suspect that seals had targeted and eaten instrumented fish. To determine whether seals could detect pings, four harbor seals and a ringed seal at SeaWorld San Diego were exposed to pings from two 69‐kHz and one 83‐kHz UCTs and their spontaneous responses observed. The seals were not expected to respond strongly because most of the energy in the pings was close to the upper limit of hearing, but three of the four harbor seals reacted with aversion to the 69‐kHz pinger with the highest source level (147 dB re 1 μPa), swimming into a refuge pool or jumping out of the water. The received level at the closest point of approach was estimated at 20 dB above sensation level or less. The results suggest that seals may be especially responsive to high‐frequency tonal signals, and that broadband weighting functions may not consistently yield efficient exposure metrics. [Funded by NOAA; in‐kind support from SeaWorld San Diego. ]
Parameterized Updraft Mass Flux as a Predictor of Convective Intensity

Abstract Parameterized updraft mass flux, available as a unique predictive field from the Kain–Fritsch (KF) convective parameterization, is presented as a potentially valuable predictor of convective intensity. The KF scheme is described in some detail, focusing on a version that is currently being run semioperationally in an experimental version of the Eta Model. It is shown that updraft mass flux computed by this scheme is a function of the specific algorithm that it utilizes and is very sensitive to the thermodynamic characteristics of input soundings. These same characteristics appear to be related to the severity of convection, suggesting that updraft mass flux predicted by the KF scheme has value for predicting severe weather. This argument is supported by anecdotal evidence and a case study.
Turnout in Serbian parliamentary elections during the two decades after the end of Milošević’s rule

Methodological uniformity and the relatively small number of studies concerning election turnout in Serbia strikingly detract from the social importance of the topic. The goal was to reduce this disparity by studying turnout in the 21st century under a statistically atypical approach that uses objective, publicly available data at the municipalities/cities level. Beginning in 2012, the trend of a worrying, almost linear decrease in turnout was found. Canonical correlation analysis showed that socio-demographic-economic variables are highly predictive of voter turnout. Six pairs of statistically significant canonical factors were isolated from the space of socio-demographic-economic characteristics and corresponding variables of electoral participation. It was indirectly established that the analytically extracted types of environments whose inhabitants exhibit specific electoral-participative behavior also show specific constellations of electoral preferences. The findings were then discussed in light of the regression to Vučić’s hybrid regime.
Understanding CSR Campaigns Through the Lens of Culture Values and Moral Emotion

This study aimed to examine the persuasive influences of moral emotions on younger consumers’ judgments and decision-making and the roles of culture and self-construal in processing corporate social responsibility (CSR) campaigns. This study employed a between-subjects experiment where American and Chinese participants viewed one of the two CSR advertisement campaigns designed with ego-focused (e.g., an advertisement elicited anger emotion) and other-focused appeals (e.g., an advertisement elicited guilt emotion). By employing an elaboration likelihood persuasion model (ELM), the results indicated that negative moral emotions had significant positive influences on attitudes toward the advertisements and purchase intention through the peripheral route. In addition, results revealed the interaction effects between guilt emotion and cultural values (i.e., country) on attitudes. This study also highlighted the moderating role of self-construal individual values in the relationship between guilt and attitudes toward the campaign. This research provides insights for communication practitioners on designing effective CSR campaigns to reach culturally diverse target audiences.
Neutrino transport and the prompt mechanism for type II supernovae

La possibilite que, durant l'effondrement stellaire, une equation d'etat nucleaire douce et l'hydrodynamique relativiste peuvent aider a produire une onde de choc avec une force suffisante pour se propager directement a travers un noyau de fer a masse faible est etudiee. Le modele numerique utilise l'equation d'etat de Cooperstein J. (1985, Nucl. Phys. A, 429) avec les parametrisations pour les densites supernucleaires de Baron E.A. , Cooperstein J. et Kahana S. (1985, Phys. Rev. Letters, 55; 1985, Nucl. Phys. A, 440) et une approximation de diffusion multigroupe pour le transport des neutrinos