Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative Brain Age Is Associated with Socioeconomic Status and Anxiety/Depression Problems in Youth

Socioeconomic status (SES) has been linked to differences in brain structure and psychiatric risk across the lifespan. Despite many neuropsychiatric disorders emerging in childhood, few studies have examined the influence of SES on brain aging and psychopathology in youth. We re-analyzed relative brain age (RBA) data from the Healthy Brain Network to examine the influence of SES components (parent education, occupation, household income-to-needs ratio (INR), public assistance enrollment) on RBA. RBA was previously determined using covariation patterns for cortical morphology, white, and subcortical gray matter volumes without SES in predictive models. We also examined associations between RBA and psychiatric symptoms (child behavior checklist). Full case analysis included 470 youth (5-17 years; 61.3% male), self-identifying as White (55%), African American (15%), Hispanic (9%), or multiracial (17.2%). Mean household income was 3.95±2.33 (Mean±SD) times the federal poverty threshold. Multiple linear regression examined if 1) SES components associated with RBA, and 2) RBA associated with psychiatric symptoms. Models covaried for sex, scan location, and parent psychiatric diagnoses. RBA associated with public assistance (p = 0.03), parent occupation (p = 0.01), and parent psychiatric diagnosis (p = 0.01), but not with INR and parent education. Parent occupation (p = 0.02) and RBA (p = 0.04) associated with CBCL anxiety/depression scores. Components of SES associated with brain aging, underscoring the risk of omitting these factors in developmental brain research. Further, delayed brain aging was associated with low parental occupational prestige and child anxiety/depression scores, suggesting a possible biological pathway from SES to mental health risk.
Brassinosteroid gene regulatory networks at cellular resolution

Brassinosteroids (BRs) are plant steroid hormones that regulate diverse processes such as cell division and cell elongation. BRs control thousands of genes through gene regulatory networks that vary in space and time. By using time-series single-cell RNA-sequencing to identify BR-responsive gene expression specific to different cell types and developmental stages of the Arabidopsis root, we uncovered the elongating cortex as a site where BRs trigger a shift from proliferation to elongation associated with increased expression of cell wall-related genes. Our analysis revealed HAT7 and GTL1 as BR-responsive transcription factors that regulate cortex cell elongation. These results establish the cortex as an important site for BR-mediated growth and unveil a BR signaling network regulating the transition from proliferation to elongation, illuminating new aspects of spatiotemporal hormone response.
Unlocking the Hidden Genetic Diversity of Varicosaviruses, the Neglected Plant Rhabdoviruses

The genus Varicosavirus is one of six genera of plant-infecting rhabdoviruses. Varicosaviruses have nonenveloped flexuous rod-shaped virions and a negative-sense, single-stranded RNA genome. A distinguishing feature of varicosaviruses, that is shared with dichorhaviruses, is a bi-segmented genome. Before 2017, a sole varicosavirus was known and characterized, then two more varicosaviruses were identified through high-throughput sequencing in 2017 and 2018. More recently, the number of known varicosaviruses has substantially increased in concert with the extensive use of high-throughput sequencing platforms and data mining approaches. The novel varicosaviruses revealed not only sequence diversity but also plasticity in terms of genome architecture, including a virus with a tentatively unsegmented genome. Here, we report the discovery of 45 novel varicosavirus genomes, which were identified in publicly available metatranscriptomic data. Identification, assembly, and curation of raw Sequence Read Archive reads resulted in 39 viral genome sequences with full-length coding regions and 6 with nearly complete coding regions. Highlights of the obtained sequences include eight varicosaviruses with unsegmented genomes, linked to a phylogenetic clade associated with gymnosperms. These findings resulted in the most complete phylogeny of varicosaviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant rhabdoviruses. Thus, the extensive use of sequence data mining for virus discovery has allowed unlocking of the hidden genetic diversity of varicosaviruses, the largely neglected plant rhabdoviruses.
LOST IN THE FOREST

To date, there remains no satisfactory solution for absent levels in random forest models. Absent levels are levels of a predictor variable encountered during prediction for which no explicit rule exists. Imposing an order on nominal predictors allows absent levels to be integrated and used for prediction. The ordering of predictors has traditionally been via class probabilities with absent levels designated the lowest order. Using a combination of simulated data and pathogen source-attribution models using whole-genome sequencing data, we examine how the method of ordering predictors with absent levels can (i) systematically bias a model, and (ii) affect the out-of-bag error rate. We show that the traditional approach is systematically biased and underestimates out-of-bag error rates, and that this bias is resolved by ordering absent levels according to the a priori hypothesis of equal class probability. We present a novel method of ordering predictors via principal coordinates analysis (PCO) which capitalizes on the similarity between pairs of predictor levels. Absent levels are designated an order according to their similarity to each of the other levels in the training data. We show that the PCO method performs at least as well as the traditional approach of ordering and is not biased.
Using pressure-driven flow systems to evaluate laser speckle contrast imaging

Significance Microfluidic flow phantom studies are commonly used for characterizing the performance of laser speckle contrast imaging (LSCI) instruments. The selection of the flow control system is critical for the reliable generation of flow during testing. The majority of recent LSCI studies using microfluidics used syringe pumps for flow control. Aim We quantified the uncertainty in flow generation for a syringe pump and a pressure-regulated flow system. We then assessed the performance of both LSCI and multi-exposure speckle imaging (MESI) using the pressure-regulated flow system across a range of flow speeds. Approach The syringe pump and pressure-regulated flow systems were evaluated during stepped flow profile experiments in a microfluidic device using an inline flow sensor. The uncertainty associated with each flow system was calculated and used to determine the reliability for instrument testing. The pressure-regulated flow system was then used to characterize the relative performance of LSCI and MESI during stepped flow profile experiments while using the inline flow sensor as reference. Results The pressure-regulated flow system produced much more stable and reproducible flow outputs compared to the syringe pump. The expanded uncertainty for the syringe pump was 8–20× higher than that of the pressure-regulated flow system across the tested flow speeds. Using the pressure-regulated flow system, MESI outperformed single-exposure LSCI at all flow speeds and closely mirrored the flow sensor measurements, with average errors of 4.6 ± 2.6% and 15.7 ± 4.6%, respectively. Conclusions Pressure-regulated flow systems should be used instead of syringe pumps when assessing the performance of flow measurement techniques with microfluidic studies. MESI offers more accurate relative flow measurements than traditional LSCI across a wide range of flow speeds.
Distributed Coding of Evidence Accumulation across the Mouse Brain Using Microcircuits with a Diversity of Timescales

Abstract The gradual accumulation of noisy evidence for or against options is the main step in the perceptual decision-making process. Using brain-wide electrophysiological recording in mice (Steinmetz et al., 2019), we examined neural correlates of evidence accumulation across brain areas. We demonstrated that the neurons with drift-diffusion model (DDM)-like firing rate activity (i.e., evidence-sensitive ramping firing rate) were distributed across the brain. Exploring the underlying neural mechanism of evidence accumulation for the DDM-like neurons revealed different accumulation mechanisms (i.e., single and race) both within and across the brain areas. Our findings support the hypothesis that evidence accumulation is happening through multiple integration mechanisms in the brain. We further explored the timescale of the integration process in the single and race accumulator models. The results demonstrated that the accumulator microcircuits within each brain area had distinct properties in terms of their integration timescale, which were organized hierarchically across the brain. These findings support the existence of evidence accumulation over multiple timescales. Besides the variability of integration timescale across the brain, a heterogeneity of timescales was observed within each brain area as well. We demonstrated that this variability reflected the diversity of microcircuit parameters, such that accumulators with longer integration timescales had higher recurrent excitation strength.
Dimethyl fumarate modulates the Duchenne muscular dystrophy disease program following short-term treatment in mdx mice

New medicines are urgently required to treat the fatal neuromuscular disease, Duchenne muscular dystrophy (DMD). DMD involves progressive muscle damage and weakness, which are preceded by oxidative stress, inflammation, and mitochondrial dysfunction. Dimethyl fumarate (DMF) is a potent small molecule nuclear erythroid 2-related factor 2 (Nrf2) activator with current clinical utility in the treatment of multiple sclerosis and psoriasis. Pharmaceutical targeting of Nrf2 by DMF has strong translational potential for DMD, given it: (1) promotes antioxidant defence systems; (2) has a potent immuno-modulatory profile; and (3) can be rapidly re-purposed into clinical care strategies for DMD patients. Here, we tested two weeks of daily 100mg/kg DMF versus 5mg/kg standard care prednisone (PRED) treatment during the peak muscle degeneration period in juvenile mdx mice, the gold standard murine DMD model. Both drugs modulated seed genes driving the DMD disease program and improved muscle force production in fast-twitch muscle. However, only DMF showed pro-mitochondrial effects that protected contracting muscles from fatigue, improved histopathology and augmented clinically compatible muscle function tests. In contrast, PRED treatment stunted mouse growth, worsened histopathology and modulated many normally expressed inflammatory and extracellular matrix (ECM) genes consistent with pan immunosuppression. These findings suggest DMF could be a more selective modulator of the DMD disease program with better efficacy and fewer side effects than standard care PRED therapy warranting follow-up studies to progress clinical translation.
Fragile X Mental Retardation Protein (FMRP) expression in human nociceptor axons of the spinal dorsal horn— Implications for RNA targeting and localized translation

Fragile X Mental Retardation Protein (FMRP) regulates activity-dependent RNA localization and local translation to modulate synaptic plasticity throughout the CNS. Mutations in the FMR1 gene that hinder or ablate FMRP function cause Fragile X Syndrome (FXS), a disorder associated with sensory processing dysfunction. FXS pre-mutations are associated with increased FMRP expression and neurological impairments including sex dimorphic presentations of chronic pain. In mice, FMRP ablation causes dysregulated DRG neuron excitability and synaptic vesicle exocytosis, spinal circuit activity, and decreased translation-dependent nociceptive sensitization. Activity-dependent, local translation is a key mechanism for enhancing primary nociceptor excitability which promotes pain in animals and humans. These works indicate that FMRP likely regulates nociception and pain at the level of the primary nociceptor or spinal cord. Therefore, we sought to better understand FMRP expression in the human dorsal root ganglion (DRG) and spinal cord using immunostaining in organ donor tissues. We find that FMRP is highly expressed in DRG and spinal neuron subsets with substantia gelatinosa exhibiting the most abundant immunoreactivity in spinal synaptic fields. Here, it is expressed in nociceptor axons. FMRP puncta colocalized with Nav1.7 and TRPV1 receptor signals suggesting a pool of axoplasmic FMRP localizes to plasma membrane-associated loci in these branches. Interestingly, FMRP puncta exhibited notable colocalization with calcitonin gene-related peptide (CGRP) immunoreactivity selectively in female spinal cord. Our results support a regulatory role for FMRP in human nociceptor axons of the dorsal horn and implicate it in the sex dimorphic actions of CGRP signaling in nociceptive sensitization and chronic pain.
Bet hedging is not sufficient to explain germination patterns of a winter annual plant

Bet hedging consists of life history strategies that buffer against environmental variability by trading off immediate and long-term fitness. Delayed germination in annual plants is a classic example of bet hedging, and is often invoked to explain low germination fractions. We examined whether bet hedging explains low and variable germination fractions among 20 populations of the winter annual plant Clarkia xantiana ssp. xantiana that experience substantial variation in reproductive success among years. Leveraging 15 years of demographic monitoring and 3 years of field germination experiments, we assessed the fitness consequences of seed banks and compared optimal germination fractions from a density-independent bet-hedging model to observed germination fractions. We did not find consistent evidence of bet hedging or the expected trade-off between arithmetic and geometric mean fitness, though delayed germination increased long-term fitness in 7 of 20 populations. Optimal germination fractions were 2 to 5 times higher than observed germination fractions, and among-population variation in germination fractions was not correlated with risks across the life cycle. Our comprehensive test suggests that bet hedging is insufficient to explain the observed germination patterns. Understanding variation in germination strategies will likely require integrating bet hedging with complementary forces shaping the evolution of delayed germination.
A family of novel immune systems targets early infection of nucleus-forming jumbo phages

Jumbo bacteriophages of the ⌽KZ-like family are characterized by large genomes (>200 kb) and the remarkable ability to assemble a proteinaceous nucleus-like structure. The nucleus protects the phage genome from canonical DNA-targeting immune systems, such as CRISPR-Cas and restriction-modification. We hypothesized that the failure of common bacterial defenses creates selective pressure for immune systems that target the unique jumbo phage biology. Here, we identify the “jumbo phage killer” (Juk) immune system that is deployed by a clinical isolate of Pseudomonas aeruginosa to resist ⌽KZ. Juk immunity rescues the cell by preventing early phage transcription, DNA replication, and nucleus assembly. Phage infection is first sensed by JukA (formerly YaaW), which localizes rapidly to the site of phage infection at the cell pole, triggered by ejected phage factors. The effector protein JukB is recruited by JukA, which is required to enable immunity and the subsequent degradation of the phage DNA. JukA homologs are found in several bacterial phyla and are associated with numerous other putative effectors, many of which provided specific anti-⌽KZ activity when expressed in P. aeruginosa. Together, these data reveal a novel strategy for immunity whereby immune factors are recruited to the site of phage protein and DNA ejection to prevent phage progression and save the cell.
ortho_seqs: A Python tool for sequence analysis and higher order sequence–phenotype mapping

Motivation An important goal in sequence analysis is to understand how parts of DNA, RNA, or protein sequences interact with each other and to predict how these interactions result in given phenotypes. Mapping phenotypes onto underlying sequence space at first- and higher order levels in order to independently quantify the impact of given nucleotides or residues along a sequence is critical to understanding sequence–phenotype relationships. Results We developed a Python software tool, ortho_seqs, that quantifies higher order sequence-phenotype interactions based on our previously published method of applying multivariate tensor-based orthogonal polynomials to biological sequences. Using this method, nucleotide or amino acid sequence information is converted to vectors, which are then used to build and compute the first- and higher order tensor-based orthogonal polynomials. We derived a more complete version of the mathematical method that includes projections that not only quantify effects of given nucleotides at a particular site, but also identify the effects of nucleotide substitutions. We show proof of concept of this method, provide a use case example as applied to synthetic antibody sequences, and demonstrate the application of ortho_seqs to other other sequence–phenotype datasets. Availability https://github.com/snafees/ortho_seqs & documentation https://ortho-seqs.readthedocs. io/
The cingulo-opercular network is composed of two distinct sub-systems

The cingulo-opercular (CO) network and its two best studied regions – the dorsal anterior cingulate and anterior insula – have been linked to task control, but also implicated in many additional processes across cognitive, social, and emotional domains. However, most prior work investigating the CO network has used a group-average approach, which may mix signals across nearby regions that vary across individuals. Here, we reevaluate the CO network’s role in task control with both task and rest fMRI, using regions with a high probability of CO network agreement across individuals. Hierarchical clustering analyses suggest heterogeneity in the CO network’s task response properties, with one sub-system (CO1) showing consistency with prior task control characterizations while another sub-system (CO2) has weak task control responses, but preserved ties to pain and motor functions. Resting-state connectivity confirms subtle differences in the architecture of these two sub-systems. This evidence suggests that, when individual variation in network locations is addressed, the CO network includes (at least) two linked sub-systems with differential roles in task control and other cognitive/motor/interoceptive responses, which may help explain varied accounts of its functions. We propose that this fractionation may reflect expansion of primary CO body-oriented control functions to broader domain-general contexts.
To be and not to be: wide-field Ca2+ imaging reveals neocortical functional segmentation combines stability and flexibility

The stability and flexibility of the functional parcellation of the cerebral cortex is fundamental to how familiar and novel information is both represented and stored. We leveraged new advances in Ca2+ sensors and microscopy to understand the dynamics of functional segmentation in the dorsal cerebral cortex. We performed wide-field Ca2+ imaging in head-fixed mice and used spatial Independent Component Analysis (ICA) to identify independent spatial sources of Ca2+ fluorescence. The imaging data were evaluated over multiple timescales and discrete behaviors including resting, walking, and grooming. When evaluated over the entire dataset, a set of template independent components (ICs) were identified that were common across behaviors. Template ICs were present across a range of timescales, from days to 30 seconds, although with lower occurrence probability at shorter timescales, highlighting the stability of the functional segmentation. Importantly, unique ICs emerged at the shorter duration timescales that could act to transiently refine the cortical network. When data were evaluated by behavior, both common and behavior-specific ICs emerged. Each behavior is composed of unique combinations of common and behavior-specific ICs. These observations suggest that cerebral cortical functional segmentation exhibits considerable spatial stability over time and behaviors while retaining the flexibility for task-dependent reorganization.
B cell receptor induced IL-10 production from neonatal CD19+CD43- cells depends on STAT5 mediated IL-6 secretion

Newborns are unable to reach the adult-level humoral immune response partly due to the potent immunoregulatory role of IL-10. Increased IL-10 production by neonatal B cells has been attributed to the larger population of IL-10-producting CD43+ B-1 cells in neonates. Here, we show that neonatal CD43- non-B-1 cells also produce substantial amounts of IL-10 following B cell antigen receptor (BCR) activation. In neonatal CD43- non-B-1 cells, BCR engagement activated STAT5 under the control of phosphorylated forms of signaling molecules Syk, Btk, PKC, FAK and Rac1. STAT5 activation led to IL-6 production, which in turn was responsible for IL-10 production in an autocrine/paracrine fashion through the activation of STAT3. In addition to the increased IL-6 production in response to BCR stimulation, elevated expression of IL-6Rα expression in neonatal B cells rendered them highly susceptible to IL-6 mediated STAT3 phosphorylation and IL-10 production. Finally, IL-10 secreted from neonatal CD43- non-B-1 cells was sufficient to inhibit TNF-α secretion by macrophages. Our results unveil a distinct mechanism of IL-6-dependent IL-10 production in BCR-stimulated neonatal CD19+CD43- B cells.
WikiGOA: Gene set enrichment analysis based on Wikipedia and the Gene Ontology

Gene sets curated to Gene Ontology terms are widely used by the transcriptomics community Presence in Wikipedia is a common proxy for the relevance of a concept. In this work, we describe the use of Wikidata to generate a dataset comprising only gene sets with a corresponding Wikipedia page. We refer to the dataset as “WikiGOA”, standing for “Wikipedia Gene Ontology Annotations” We use the dataset to analyze gene expression data and show that it provides readily understandable results. We envision WikiGOA to be useful for exploring complex biological datasets both in academic research and educational contexts. Note This report was written in a non-standard, experimental format, where assertions are expressed in bullet points. This was done to clarify statements and assumptions, simplify reading and pave the way for conversion to structured formats (e.g., nanopublications). [1]