Biology subjects

Smith, S. M.

Publications and source records attributed to Smith, S. M..

At least 19 recordsLinked to original sources

bioRxiv2026

Large-scale population neuroimaging reveals latent subgroup structure in functional brain organisation

Large-scale functional MRI datasets provide resources to understand inter-individual variation in human brain function and relate this variation to behaviour and health. However, most existing approaches fail to bridge the gap between population-average and individual-specific modelling, limiting the identification of structured subgroup heterogeneity across individuals. Here we develop a scalable framework for unsupervised subgroup discovery in population-scale resting-state fMRI data from 19,993 UK Biobank participants. Using stochastic Probabilistic Functional Modes, we estimate population-informed individualised spatial topographies of resting-state networks and derive high-dimensional functional fingerprints for each participant. We then identify latent subgroups by applying Gaussian mixture modelling independently to each fingerprint feature, yielding hundreds of reproducible subgroup definitions across 1,000 functional dimensions. We report approximately 5,700 significant differences between subgroups in a range of non-imaging phenotypes related to cognition, lifestyle, physical and mental health. Spatial organisation of the brain networks reveals distinct subgroup differences in sensory-motor and higher-order cognitive systems, in addition to correspondence with regional patterns of genetic variability across the brain. Together, these results demonstrate that large-scale functional neuroimaging contains rich latent subgroup structure linked to behavioural and biological variation. Our framework provides an interpretable and scalable basis for stratified models of human brain function and population neuroscience.

neuroscience↗

bioRxiv2026

Brain Connectivity Modelling Through Joint Estimation of Parcels and Gradients

This paper presents a framework for modelling the topography of whole-brain connectivity in resting-state functional MRI. The aim is to disentangle functional segregation, which manifests as abrupt changes in connectivity, from so-called gradients, i.e., smooth variations in connectivity across the brain. Our core assumption is that functional segregation leads to low-rank structure in the dense (point-to-point) connectome, whereas connectivity gradients imply a sparse and non-low-rank structure in the dense connectome. Our method thus decomposes the connectome into low-rank and sparse components, enabling the integration of local-nonlinear and global-linear embedding strategies. We show that this hybrid model approximates the empirical dense connectome more effectively than purely low-rank or purely gradient approaches. We also find that connectivity gradients derived from this model exhibit strong correspondence with task-based topographic maps. We hope that this approach can provide insight into the organisational principles of brain regions where gradients remain poorly characterised.

neuroscience↗

bioRxiv2026

Invasion history reconstruction and potential distribution of the ambrosia beetles Euwallacea fornicatus and E. perbrevis (Coleoptera: Scolytinae), two global emerging pests

The global spread of invasive insects poses serious ecological and economic threats to forest ecosystems. Euwallacea fornicatus and E. perbrevis are cryptic ambrosia beetles native to Southeast Asia that have invaded multiple regions worldwide, damaging diverse woody hosts through gallery formation and fungal symbiont inoculation. We compiled confirmed and novel occurrence records to describe their global distributions, reconstruct invasion histories and likely origins using mitochondrial COI phylogenies, and compare their potential distributions through models based on bioclimatic variables. Euwallacea fornicatus has expanded rapidly over the past decades, establishing in North America (2003), Israel (2009), South Africa (2016), South America (2020), Australia (2021), Europe (2022) and Turkey (2024). In contrast, E. perbrevis has an earlier but slower invasion history, with establishments in Hawaii (1918), Central America (1979), Oceania (1982), and North America (2004). Phylogenetic analyses revealed at least six independent introductions for each species. Euwallacea fornicatus primarily originated from native populations in China, Taiwan and Vietnam, whereas E. perbrevis from Indonesia and Thailand, with additional introductions from unknown sources. Secondary spread from invaded regions is also likely. Distribution models indicated distinct climatic niches. Euwallacea fornicatus tolerates broader thermal ranges and drier conditions, enabling establishment from subtropical to temperate regions, whereas E. perbrevis appears restricted to tropical climates. Only 32% of predicted suitable habitat overlapped, indicating low coexistence potential. The broader climatic tolerance and faster recent spread of E. fornicatus highlights a higher invasion risk and greater management challenges. These findings provide key insights to strengthen biosecurity strategies aimed at preventing further spread. Key messageO_LIWe updated the global distribution and likely invasion routes of two cryptic ambrosia beetles. C_LIO_LIWe identified multiple independent and secondary introductions worldwide. C_LIO_LIWe revealed distinct climatic niches and limited habitat overlap. C_LIO_LIWe showed higher invasion risk for E. fornicatus due to broader climatic tolerance. C_LIO_LIWe identified high-risk regions for surveillance based on climate suitability. C_LI

ecology↗

bioRxiv2026

A novel mouse model of rare neurodevelopmental disorder, TBCK Syndrome

TBCK Syndrome is a rare Mendelian disorder caused by variants in the TBCK gene. Although symptoms affect multiple organ systems, hallmark features include intellectual and developmental disability, craniofacial differences, hypotonia, and premature death. At the cellular level, TBCK has been implicated in mTOR signaling, autophagy, mitophagy, and mRNA trafficking; however, the mechanisms underlying disease onset and progression remain unclear. To address this gap, we characterized a mouse model of TBCK Syndrome. These mice lack exon 5 of the TBCK gene, resulting in a whole-body knockout of Tbck, modeling the most severe known variant. We performed a comprehensive battery of developmental assays, along with microcomputed tomography and histological analyses, which revealed systemic alterations consistent with those observed in affected individuals. Notably, phenotypic changes arising from Tbck loss emerge early and are detectable in the brain, indicating a primary neurodevelopmental origin of disease pathology. Rigorous characterization of this Tbck-deficient mouse establishes the first in vivo platform to investigate disease mechanisms and provides a foundation for preclinical evaluation of gene and targeted pharmacological therapy strategies. Summary StatementThis study establishes a rigorously validated animal model recapitulating systemic features of TBCK Syndrome, enabling targeted investigation of disease biology and preclinical assessment of candidate therapies.

genetics↗

bioRxiv2026

Bi-cross-validation: a data-driven method to evaluate dynamic functional connectivity models in fMRI

Dynamic functional connectivity (dFC) models have become increasingly popular over the past decade for characterising time-varying interactions between brain regions. However, assessing and comparing dFC models remains challenging. Here, we introduce bi-cross-validation as a general framework for evaluating dFC models and selecting key hyperparameters, such as the number of states. By jointly partitioning the data across subjects and brain regions, bi-cross-validation enables out-of-sample evaluation without re-estimating latent states on the same data used for testing, thereby avoiding circularity. Using simulated data with known ground-truth dynamics, we show that bi-cross-validation favours models that accurately capture the underlying state structure. Applying the framework to real resting-state fMRI data, we demonstrate that bi-cross-validation naturally balances goodness-of-fit against model complexity, with performance improving and then declining as model complexity increases. Finally, we use bi-cross-validation to directly compare static and dynamic FC models, showing that dynamic models underperform static models at low spatial dimensionality, but outperform static models at sufficiently high dimensionality. Together, these results establish bi-cross-validation as a principled tool for dFC model selection, evaluation, and comparison.

neuroscience↗

bioRxiv2026

Chromosome-level genome sequence of the C4 grass Themeda triandra reveals karyotype orthology with sorghum and genetic variation in accessions adapted to diverse environments

Themeda triandra (family Andropogoneae) is a pan-continental grass occurring throughout Australia. Recognising its remarkable adaptive capacity, we assembled the nuclear genome sequence of a diploid accession from eastern Australia, finding all ten chromosomes of the 755 Mb assembly highly syntenic with those of Sorghum bicolor. Genotyping and cytometry of range-wide accessions suggested several historical radiation events, with polyploids dominating in arid regions, apart from a notable diploid lineage from the arid north-west of Australia (PAN). A detailed comparison of PAN with two diploids from temperate south-eastern Australia through whole-genome resequencing revealed extensive copy number variation and polymorphism, with changes in genes for heat-shock proteins and flowering regulation reflecting their environmental origin. Exploration of the rich genetic diversity in T. triandra with respect to environmental adaptation is expected to benefit grassland management programs and enable introgression of novel genes into Andropogoneae crops for climate resilience.

genomics↗

bioRxiv2026

A holistic survey of small mammal diversity across an iconic Madrean Sky Island (Santa Catalina Mountains, Arizona, USA)

The Santa Catalina Mountains are an iconic member of the Madrean Sky Islands, rising above Tucson, Arizona, USA, where the Catalina Highway connects Sonoran desertscrub to stands of conifer forest nearly 2,800 meters in elevation. As one of the [~]54 forested mountain areas in this system, the Santa Catalinas host unique biotic communities relative to the surrounding lowlands. However, most of these sky islands lack the surveys of resident small mammals (either historical or recent) needed for studying biodiversity in the context of changing climate and habitat use. From 2021 to 2023, we surveyed 10 localities on the north and south slopes of the Santa Catalina Mountains using holistic sampling methods to document terrestrial small mammal diversity and preserve multiple tissue types. Here we summarize these new collections relative to previous voucher specimens and human observations, identifying gaps for future work to address. Our survey recorded the presence of 15 species, preserved 150 voucher specimens paired with a suite of flash-frozen tissues, and non-lethally sampled another 219 individuals (ear tissue, feces, ectoparasites, and measurements) to provide populational data from sites where vouchering occurred. Despite the road accessibility and long history of sampling in the Santa Catalina Mountains, our surveys extended the known elevational range for 8 species, including the first known specimen of Reithrodontomys fulvescens from the area. Our use of a transect-based survey design, which maximizes species diversity across biotic communities, paired with holistic specimen preservation techniques, provides a model for surveying patterns of population genetic and parasite sharing relationships across other Madrean Sky Islands, bridging a [~]40 year lull in specimen preservation while adding new data dimensions that promote integrative studies of small mammal biodiversity. With more complete sampling, other mountains will offer promising replicates for studying eco-evolutionary impacts of the regions episodic habitat connectivity. Teaser textSurveying the terrestrial small mammals of the Santa Catalina Mountains, part of the Madrean Sky Islands, we analyze modern occurrences relative to previous records and demonstrate the potential value of holistically surveying sky island small mammals.

zoology↗

bioRxiv2026

Rapid reversible RNA isoform switching during loss and recovery of turgor in Arabidopsis thaliana

Plant genes can each produce multiple RNA isoforms, but little is known about when and how they are produced, or their functions. We conducted a detailed time course analysis of rapid changes in abundance of RNA isoforms in response to transient water deficit in Arabidopsis thaliana seedlings. We identified 95,104 transcripts in total, 21,935 of which were differentially expressed. Strikingly, 1,258 differentially expressed genes were identified only by means of RNA isoform analysis and would have been missed by conventional analysis. Several hundred genes exhibited a very rapid and reversible switch in the most abundant RNA isoform, with timings corresponding to defined changes in seedling water potential. In most cases it is predicted that RNA isoform switching would generate new protein products. Many of these genes encoded proteins of RNA metabolism and splicing, while others potentially function more directly in the response to water deficit. We propose a model in which very rapid RNA processing mechanisms come into play within minutes of imposition of the stress, changing the RNA isoform population including RNAs that encode components of the RNA processing apparatus itself. These changes together with subsequent changes in transcription facilitate further changes in the RNA isoform population as part of the stress and recovery responses. More broadly we propose that responses to abiotic stress involve substantial changes in gene function through the production of RNA isoforms, and we present a detailed approach to identifying such genome-wide RNA isoform switching.

plant biology↗

bioRxiv2026

Temperature impacts on mating and oviposition of the emerald ash borer, Agrilus planipennis Fairmaire (Coleoptera: Buprestidae)

Local temperatures can shape the ability of introduced species to flourish and disrupt novel environments. The emerald ash borer (EAB), Agrilus planipennis Fairmaire (Coleoptera: Buprestidae), is an invasive beetle that threatens ash trees in North America and Europe. To assess the role of temperature on EAB reproduction, we reared groups of adult beetles at one of four temperatures (12, 15, 18, and 21 {degrees}C) and measured reproductive success (laying fertilized eggs and egg hatching). There was no effect of rearing temperature on EAB female lifespans but no eggs laid at 15 or 18 {degrees}C hatched, suggesting these temperatures disrupt the reproductive process of EAB. Females reared at 21 {degrees}C, however, consistently laid eggs that hatched. We then used these results to assess the likelihood of reproductive success over the previous ten years in eight cities in Canada that host EAB. All locations experienced temperatures of [≥] 21 {degrees}C, but the number of hours and the number of days above this critical temperature were highly variable. There were ample opportunities in all locations for EAB to reproduce, but EAB in cooler cities would experience thermal limitations thus slowing the spread of EAB populations.

ecology↗

bioRxiv2025

Independent Filter Analysis for Group Discrimination in fMRI

Traditional group-level fMRI analysis approaches, such as Independent Component Analysis (ICA), often rely on unsupervised dimensionality reduction to map subjects into a common feature space. While effective for capturing common variance across all subjects, the preservation of discriminative features between groups of participants is not guaranteed. To address this limitation, we introduce Independent Filter Analysis (IFA), a supervised extension of group ICA that explicitly models group-discriminative information as part of the dimensionality reduction steps. Prior to unmixing, IFA constructs a subspace that simultaneously retains both shared and group-specific information, enhancing sensitivity to group effects while preserving biological interpretability. We validated IFA using simulated data and paired condition comparisons from three Human Connectome Project (HCP) tasks. In the simulation, IFA achieved 95% classification accuracy, outperforming group ICA, which failed to detect subtle group differences. On the HCP data, IFA increased network matrix classification accuracy by up to 15% and produced spatial maps that more precisely reflected task-relevant differences.

neuroscience↗

bioRxiv2025

Distinguishing Lifelong Individual Differences from Divergent Aging Trajectories of Adult Brain Volumes

Individual differences in the volumes of brain structures are often linked to various conditions, including Alzheimers disease, schizophrenia, and overall brain health. However, it remains unclear to what extent these differences reflect individual levels present from young adulthood or diverging aging trajectories from later ages. In this study, we analyze the aging dynamics of the volumes of six brain structures based on magnetic resonance imaging (MRI) scans from a large cross-cohort longitudinal sample of cognitively healthy adults (n = 8,311 with 18,520 MRIs, ages from 18 to 97 years). From general assumptions about structural brain dynamics and measurement noise, a stochastic dynamical model was fitted to the data to estimate both the variability and persistence of structural changes across adulthood. Using this model, we calculated how much of the variance of volumetric differences between individuals can be attributed to stable levels from young adulthood versus systematic changes at older ages, as well as the theoretical sensitivity of longitudinal studies to detect individual differences in change. The findings were as follows: 1) Before age 60 years, inter-individual differences in neuroanatomical volumes almost exclusively reflect stable differences between individuals, while the influence from systematic differences in rate-of-change increases thereafter; up to 50 % of the variation being due to differences in change at 80 years. In contrast, ventricular volume reflects differences in change from early adulthood. 2) Current brain-age models are unlikely to be sensitive to detect differences in aging trajectories. 3) Imaging studies have low reliability in detecting inter-individual brain changes before age 60. After 60 years, the study reliability increases sharply with longer intervals between scans and more modestly with additional intermediate observations. In conclusion, our results reinforce the view that it is critical to distinguish stable early-adulthood levels from systematic differences in change when studying adult brain aging.

neuroscience↗

bioRxiv2025

Unreliable homeostatic action potential broadening in cultured dissociated neurons

Homeostatic plasticity preserves neuronal activity against perturbations. Recently, somatic action potential broadening was proposed as a key homeostatic adaptation to chronic inactivity in neocortical neurons. Since action potential shape critically controls calcium entry and neuronal function, broadening provides an attractive homeostatic feedback mechanism to regulate activity. Here, we report that chronic inactivity induced by sodium channel block does not broaden action potentials in neocortical neurons under a wide range of conditions. In contrast, action potentials were broadened in CA3 neurons of organotypic hippocampal cultures by chronic sodium channel block and in hippocampal dissociated cultures by chronic synaptic block. Mechanistically, BK-type potassium channels were proposed to underly inactivity-induced action potential broadening. However, BK channels did not affect action potential duration in our recordings. Our results indicate that action potential broadening can occur in specific neurons and conditions but is not a general mechanism of homeostatic plasticity in cultured neurons.

neuroscience↗

bioRxiv2025

Automatic Individual Cortical Parcellation for the Human Connectome Project

The original Human Connectome Project multimodal cortical parcellation (HCP_MMP1.0) used MRI-derived local features and long-distance functional connectivity measures to define a multimodal parcellation at the group level, accompanied by an automated areal classifier, to create subject-specific mappings of the human cerebral cortex. These mappings, referred to as individual (cortex) parcellations, aim to capture individual variability in areal organization by learning from both structural and functional data. However, a strict supervised learning approach using the group parcellation as labels would have no incentive to learn individual differences that registration is unable to reconcile (e.g., atypical 55b topologies). Furthermore, there are many types of resting state network (RSN) feature maps, and it is unclear which type would most accurately or effectively classify areas, or even what should be the primary criteria for evaluating classification performance. Here, we introduce an Areal Recognition Ensemble with Nested Approach (ARENA) classifier that learns from uncertain labels, using a novel application of weakly supervised learning to this type of problem. Additionally, in comparing multiple candidate RSN decompositions, temporal ICA and PROFUMO maps outperformed the original spatial ICA-based approach based on objective criteria. With these refinements, the ensemble classifier achieved a reliable individual variability score of 8380, an average areal detection rate of 97.8%, and test-retest reproducibility of 73.3%, outperforming a retrained version of the original Multi-layer Perceptron (MLP) model (whose reliable individual variability score was 3128, average areal detection rate was 97.2%, and test-retest reproducibility was 71.6% on the same dataset). Furthermore, the ARENA classifier demonstrated stronger generalization for all three measures when applied to task fMRI data that were not part of the training dataset. Using the refined classifier and leveraging all 1071 HCP-Young Adult subjects, we identified new types of atypical organization of language-related area 55b. Here we provide the fully data-driven HCP_MMP1.0_1071_MPM (Maximum Probability Map) group parcellation and a summary of area 55b organization in both hemispheres. Our automated individual parcellation pipeline powered by the novel ARENA classifier is now integrated into the HCP pipelines, offering a user-friendly tool for the neuroimaging community.

neuroscience↗

bioRxiv2025

Development of a 24-Channel 3T Phased-Array Coil for fMRI in Awake Monkeys - Mitigating Spatiotemporal Artifacts in Ferumoxytol-Weighted Functional Connectivity Estimation

Functional magnetic resonance imaging (fMRI) of awake macaque monkeys holds promise for advancing our understanding of primate brain organization, including humans. However, estimating functional connectivity in awake animals is challenging due to the limited duration of imaging sessions and the relatively low sensitivity to neural activity. To overcome these challenges, we developed a 24-channel 3T receive radiofrequency (RF) coil optimized for parallel imaging of awake macaques. This enabled the acquisition of multiband and GRAPPA-accelerated ferumoxytol-weighted resting-state fMRI. The Human Connectome Project-style data processing pipelines were adapted to address the unique preprocessing demands of cerebral blood volume-weighted (CBVw) imaging, including motion correction, functional-to-structural image co-registration, and training a multi-run independent component analysis-based X-noiseifier (ICA-FIX) classifier for removal of structured artifacts. Our CBVw fMRI approach resulted in an elevated contrast-to-noise ratio compared to blood oxygenation level dependent (BOLD) imaging in anesthetized macaques. However, structured imaging artifacts still contributed more variance to the functional timeseries than neural activity. By applying the ICA-FIX classifier, we achieved highly reproducible parcellated functional connectivity at the single-subject level. At the group-level, we identified dense functional networks with spatial features homologous to those observed in humans. The developed RF receive coil, image acquisition protocols, and data analysis pipelines are publicly available, providing the broader scientific community with tools to leverage these advances for further research.

neuroscience↗

bioRxiv2025

Convergent strigolactone perception via independent horizontal gene transfer of pre-adapted α/β-hydrolases

Strigolactones (SLs) are not only phytohormones that influence multiple aspects of plant growth and development, but also signaling molecules for interactions between plants and certain fungi or bacteria. In plants, the SL receptor is an /{beta}-hydrolase (ABH) encoded by the D14/KAI2 gene family, which is known to be derived from proteobacterial RsbQ through horizontal gene transfer (HGT). Here we show that the CpD14-like (CDL) gene family, which encodes another ABH exhibiting SL receptor functions in fungi, was acquired from actinobacteria via an independent HGT event. X-ray crystallographic experiments reveal that CDL and D14/KAI2/RsbQ (DKR) proteins have distinctive lid structures but maintain the same core /{beta} fold and catalytic triad. Biochemical assays further show that both actinobacterial CDL and proteobacterial RsbQ can recognize and hydrolyze SLs, suggesting that they are pre-adapted for SL perception. This work demonstrates that independent HGT of pre-adapted genes can trigger convergent evolution of key innovations and provides insights into how SLs are sensed by organisms across kingdoms.

evolutionary biology↗

bioRxiv2025

Characterising ongoing brain aging from cross-sectional data

"Brain age delta" is the difference between age estimated from brain imaging data and actual age. Positive delta in adults is normally interpreted as implying that an individual is aging (or has aged) faster than the population norm, an indicator of unhealthy aging. Unfortunately, from cross-sectional (single timepoint) imaging data, it is impossible to know whether a single individuals positive delta reflects a state of faster ongoing aging, or an unvarying trait (in other words, a "historical baseline effect" in the context of the population being studied). However, for a cross-sectional dataset comprising many individuals, one could attempt to disambiguate varying aging rates from fixed baseline effects. We present a method for doing this, and show that for the common approach of estimating a single delta per subject, baseline effects are likely to dominate. If instead one estimates multiple biologically distinct modes of brain aging, we find that some modes do reflect aging rates varying strongly across subjects. We demonstrate this, and verify our modelling, using longitudinal (two timepoint) data from 4,400 participants in UK Biobank. In addition, whereas previous work found incompatibility between cross-sectional and longitudinal brain aging, we show that careful data processing does show consistency between cross-sectional and longitudinal results.

neuroscience↗

bioRxiv2024

Shape-constrained, changepoint additive models for time series omics data with cpam

Time series omics experiments are critical for the study of a wide range of biological processes such as cell differentiation and developmental programs or responses to pathogens and environmental cues. While statistical tools for differential analysis across static conditions have matured, comparable comprehensive methodology is lacking for time series data. Here, we introduce cpam, a novel time series method and user-friendly software that performs temporal differential analysis of omics data for case-only or case-control time series, incorporating quantification uncertainty. Powerful features of cpam include changepoint detection and shape-constrained temporal trend estimation to allocate omics data into similar clusters. Performance evaluation shows that cpam outperforms existing time series methods in terms of control of the false discovery rate versus power to detect temporal changes and accurate changepoint estimation. In particular, we find that trend-based models provide superior performance compared to pairwise comparisons, even with as few as six time points. The software provides an interactive interface with modern customizable visualisations, offering both graphical and statistical insight into complex molecular processes. Application to published transcriptome data illustrates RNA isoform-level modelling together with high resolution clustering during human embryogenesis and the identification of 910 novel genes differentially expressed in response to excess light in Arabidopsis. This method has the potential for application to a range of omics data, including single-cell analyses via pseudobulked data, providing the analytical power to reveal complex temporal patterns of gene expression in any biological system.

bioinformatics↗

bioRxiv2024

Alcohol induces p53-mediated apoptosis in neural crest by stimulating the AMPK-mediated suppression of TORC1, p70/S6K, and ribosomal biogenesis.

Prenatal alcohol exposure is a leading cause of permanent neurodevelopmental disability and can feature distinctive craniofacial deficits that partly originate from the apoptotic deletion of craniofacial progenitors, a stem cell lineage called the neural crest (NC). We recently demonstrated that alcohol causes nucleolar stress in NC through its suppression of ribosome biogenesis (RBG) and this suppression is causative in their p53/MDM2-mediated apoptosis. Here, we show that this nucleolar stress originates from alcohols activation of AMPK, which suppresses TORC1 and the p70/S6K-mediated stimulation of RBG. Alcohol-exposed cells of the pluripotent, primary cranial NC line O9-1 were evaluated with respect to their S6K, TORC1, and AMPK activity. The functional impact of these signals with respect to RBG, p53, and apoptosis were assessed using gain-of-function constructs and small molecule mediators. Alcohol rapidly (<2hr) increased pAMPK, pTSC2, and pRaptor, and reduced both total and pS6K in NC cells. These changes persisted for at least 12hr to 18hr following alcohol exposure. Attenuation of these signals via gain- or loss-of-function approaches that targeted AMPK, S6K, or TORC1 prevented alcohols suppression of rRNA synthesis and the induction of p53-stimulated apoptosis. We conclude that alcohol induces ribosome dysbiogenesis and activates their p53/MDM2-mediated apoptosis via its activation of pAMPK, which in turn activates TSC2 and Raptor to suppress the TORC1/S6K-mediated promotion of ribosome biogenesis. This represents a novel mechanism underlying alcohols neurotoxicity and is consistent with findings that TORC1/S6K networks are critical for cranial NC survival.

pharmacology and toxicology↗