Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a cumulative science of vocal markers of autism: a cross-linguistic meta-analysis-based investigation of acoustic markers in American and Danish autistic children

Acoustic atypicalities in speech production are argued to be potential markers of clinical features in Autism Spectrum Disorder (ASD). A recent meta-analysis highlighted shortcomings in the field, in particular small sample sizes and study heterogeneity (Fusaroli et al., 2017). Wae showcase a cumulative (i.e., explicitly building on previous studies both conceptually and statistically) yet self-correcting (i.e., critically assessing the impact of cumulative statistical techniques) approach to prosody in ASD to overcome these issues. We relied on the recommendations contained in the meta-analysis to build and analyzed a cross-linguistic corpus of multiple speech productions in 77 autistic and 72 neurotypical children and adolescents (>1000 recordings in Danish and US English). We used meta-analytically informed and skeptical priors, with informed priors leading to more generalizable. We replicated findings of a minimal cross-linguistically reliable distinctive acoustic profile for ASD (higher pitch and longer pauses) with moderate effect sizes. We identified novel reliable differences between the two groups for normalized amplitude quotient, maxima dispersion quotient, and creakiness. However, the differences were small, and there is likely no one acoustic profile characterizing all autistic individuals. We identified reliable relations of acoustic features with individual differences (age, gender), and clinical features (speech rate and ADOS sub-scores). Besides cumulatively building our understanding of acoustic atypicalities in ASD, the study shows how to use systematic reviews and meta-analyses to guide the design and analysis of follow-up studies. We indicate future directions: larger and more diverse cross-linguistic datasets, focus on heterogeneity, self-critical cumulative approaches and open science. Lay Summary Autistic individuals are reported to speak in distinctive ways. Distinctive vocal production can affect social interactions and social development and could represent a noninvasive way to support the assessment of ASD. We systematically checked whether acoustic atypicalities highlighted in previous articles could be actually found across multiple recordings and two languages. We find a minimal acoustic profile of ASD: higher pitch, longer pauses, increased hoarseness and creakiness of the voice. However, there is much individual variability (by age, sex, language, and clinical characteristics). This suggests that the search for one common “autistic voice” might be naive and more fine-grained approaches are needed.
Hepatoblastomas with carcinoma features represent a biological spectrum of aggressive neoplasms in children and young adults

Malignant hepatocellular cancers are the most common primary liver malignancies in children, and hepatoblastomas (HBs) account for more than two-thirds of these cases. While most HBs respond to chemotherapy and have favorable outcomes, the 3-year overall survival rate for high-risk HBs is below 50% and guidelines for their classification and treatment are still evolving. HB risk-stratification efforts using clinical, histological, and molecular parameters have been reported to help identify patients that require more or less aggressive therapies in retrospective studies, and are being validated in clinical trials. However, risk assessment is particularly challenging for cancers with certain histologies, including tumors in the recently proposed provisional hepatocellular neoplasm not otherwise specified (HCN NOS) category. HCN NOSs exhibit either intermediate or combined HB and hepatocellular carcinoma (HCC) histological features, and while neoplasms with such features were observed over a decade ago, only a handful have been characterized and little is known about their biology and clinical features. Here, we molecularly characterized a series of clinically annotated HCN NOSs that demonstrated either intermediate HB/HCC histology or distinct coexisting areas with HB and HCC histological features. In addition, molecular profiling of HBs demonstrating focal pleomorphism or anaplasia (HB FPA) revealed underlying biological features previously observed in HCCs. Our study suggested that HCN NOSs and HB FPAs are aggressive tumors, irrespective of patient age or resectability. Consequently, we designated them collectively as HBs with carcinoma features (HBCs) and outlined histological and molecular characteristics for their diagnosis and treatment. In our single-institution study, transplanted HBC patients were significantly and more than twice as likely to have good outcomes, highlighting the importance of molecular testing and aggressive early intervention.
Histone H3 deacetylation promotes host cell viability for efficient infection by Listeria monocytogenes

For many intracellular bacterial pathogens manipulating host cell survival is essential for maintaining a replicative niche, and is a common strategy used to promote infection. The bacterial pathogen Listeria monocytogenes is well known to hijack host machinery for its own benefit, such as targeting the host histone H3 for modification by SIRT2. However, in what way this modification benefits infection, as well as the molecular players involved, remain unknown. Here we show that SIRT2 activity supports Listeria intracellular survival by maintaining genome integrity and host cell viability. This protective effect is dependent on H3K18 deacetylation, which safeguards the host genome by counteracting infection-induced DNA damage. Mechanistically, infection causes SIRT2 to interact with the nucleic acid binding protein TDP-43 and localise to genomic R-loops, where H3K18 deacetylation occurs. This work highlights novel functions of TDP-43 and R-loops during bacterial infection and identifies the mechanism through which L. monocytogenes co-opts SIRT2 to allow efficient infection.
A New Pipeline for the Normalization and Pooling of Metabolomics Data

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through PC-PR2 analysis; (iii) application of linear mixed models to remove unwanted variability, including samples’ originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.
Induced Nanoscale Membrane Curvature Bypasses Clathrin’s Essential Endocytic Function

During membrane trafficking, flat membrane is rapidly remodeled to produce nanometer-scale vesicles. The mechanisms underlying this shape change are not completely understood, but coat proteins such as clathrin are implicated. Clathrin’s ability to bind to membranes of many different geometries casts uncertainty on its specific role in curvature generation and stabilization. Here, we used nanopatterning to produce substrates of ideal optical properties for live-cell imaging, with U-shaped features that bend a cell’s ventral plasma membrane into shapes characteristic of the energetically-unfavorable intermediate of clathrin- mediated endocytosis (CME). This induced plasma membrane curvature recruits the endocytic machinery, promoting productive endocytosis. Upon clathrin or AP2 disruption, CME sites on flat substrates are diminished. However, induced curvature rescues the localization, turnover and transferrin cargo uptake activities of CME sites after clathrin, but not AP2, disruption. These data establish that clathrin’s essential function during CME is to facilitate the evolution of membrane curvature rather than to scaffold CME protein recruitment. Summary Cail et al. demonstrate that induced nanoscale membrane curvature recruits endocytic sites and produces vesicles in cells lacking the coat protein clathrin, while the adaptor protein AP2 is still required, showing that clathrin’s essential function is to facilitate curvature development of the nascent vesicle.
Comprehensive taxon sampling and vetted fossils help clarify the time tree of shorebirds (Aves, Charadriiformes)

Shorebirds (Charadriiformes) are a globally distributed clade of modern birds and, due to their ecological and morphological disparity, a frequent subject of comparative studies. While molecular phylogenies have been instrumental to resolving the suprafamilial backbone of the charadriiform tree, several higher-level relationships, including the monophyly of plovers (Charadriidae) and the phylogenetic positions of several monotypic families, have remained unclear. The timescale of shorebird evolution also remains uncertain as a result of extensive disagreements among the published divergence dating studies, stemming largely from different choices of fossil calibrations. Here, we present the most comprehensive non-supertree phylogeny of shorebirds to date, based on a total-evidence dataset comprising 336 ingroup taxa (89% of all extant species), 24 loci (15 mitochondrial and 9 nuclear), and 69 morphological characters. Using this phylogeny, we clarify the charadriiform evolutionary timeline by conducting a node-dating analysis based on a subset of 8 loci tested to be clock-like and 16 carefully selected, updated, and vetted fossil calibrations. Our concatenated, species-tree, and total-evidence analyses consistently support plover monophyly and are generally congruent with the topologies of previous studies, suggesting that the higher-level relationships among shorebirds are largely settled. However, several localized conflicts highlight areas of persistent uncertainty within the gulls (Laridae), true auks (Alcinae), and sandpipers (Scolopacidae). At shallower levels, our phylogenies reveal instances of genus-level nonmonophyly that suggest changes to currently accepted taxonomies. Our node-dating analyses consistently support a mid-Paleocene origin for the Charadriiformes and an early diversification for most major subclades. However, age estimates for more recent divergences vary between different relaxed clock models, and we demonstrate that this variation can affect phylogeny-based macroevolutionary studies. Our findings demonstrate the impact of fossil calibration choice on the resulting divergence time estimates, and the sensitivity of diversification rate analyses to the modeling assumptions made in time tree inference.
Phylogenetic profiling suggests early origin of the core subunits of Polycomb Repressive Complex 2 (PRC2)

Polycomb Repressive Complex 2 (PRC2) is involved in establishing transcriptionally silent chromatin states through its ability to methylate lysine 27 of histone H3 by the catalytic subunit Enhancer of zeste [E(z)]. Polycomb group (PcG) proteins play a crucial role in the maintenance of cell identity and in developmental regulation. Previously, the diversity of PRC2 subunits within some eukaryotic lineages has been reported and its presence in early eukaryotic evolution has been hypothesized. So far however, systematic survey of the presence of PRC2 subunits in species of all eukaryotic lineages is missing. Here, we report the diversity of PRC2 core subunit proteins in different eukaryotic supergroups with emphasis on the early-diverged lineages and explore the molecular evolution of PRC2 subunits by phylogenetics. In detail, we investigate the SET-domain protein sequences and their evolution across the four domains of life and particularly focus on the structural diversity of the SET-domain subfamily containing E(z), the catalytic subunit of PRC2. We show that PRC2 subunits are already present in early eukaryotic lineages, strengthening the support for PRC2 emergence prior to diversification of eukaryotes. We identify a common presence of E(z) and ESC, suggesting that Su(z)12 may have emerged later and/or may be dispensable from the evolutionarily conserved functional core of PRC2. Furthermore, our results broaden our understanding of the E(z) evolution within the SET-domain protein family, suggesting possibilities of function evolution. Through this, we shed light on a possible emerging point of the PRC2 and the evolution of its function in eukaryotes.
Lower Cognitive Set Shifting Ability Is Associated With Stiffer Balance Recovery Behavior and Larger Perturbation-Evoked Cortical Responses in Older Adults

The mechanisms underlying associations between cognitive set shifting impairments and balance dysfunction are unclear. Cognitive set shifting refers to the ability to flexibly adjust behavior to changes in task rules or contexts, which could be involved in flexibly adjusting balance recovery behavior to different contexts, such as the direction the body is falling. Prior studies found associations between cognitive set shifting impairments and severe balance dysfunction in populations experiencing frequent falls. The objective of this study was to test whether cognitive set shifting ability is expressed in successful balance recovery behavior in older adults with high clinical balance ability (N=19, 71 ± 7 years, 6 female). We measured cognitive set shifting ability using the Trail Making Test and clinical balance ability using the miniBESTest. For most participants, cognitive set shifting performance (Trail Making Test B-A = 37 ± 20s) was faster than normative averages (46s for comparable age and education levels), and balance ability scores (miniBESTest = 25 ± 2 / 28) were above the threshold for fall risk (23 for people between 70-80 years). Reactive balance recovery in response to support-surface translations in anterior and posterior directions was assessed in terms of body motion, muscle activity, and brain activity. Across participants, lower cognitive set shifting ability was associated with smaller peak center of mass displacement during balance recovery, lower directional specificity of late phase balance-correcting muscle activity (i.e., greater antagonist muscle activity 200-300ms after perturbation onset), and larger cortical N1 responses (100-200ms). None of these measures were associated with clinical balance ability. Our results suggest that cognitive set shifting ability is expressed in balance recovery behavior even in the absence of profound clinical balance disability. Specifically, our results suggest that lower flexibility in cognitive task performance is associated with lower ability to incorporate the directional context into the cortically-mediated later phase of the motor response. The resulting antagonist activity and stiffer balance behavior may help explain associations between cognitive set shifting impairments and frequent falls.
Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection

Genetic differences between different Mycobacterium tuberculosis complex (MTBC) strains determine their ability to transmit within different host populations, their latency times, and their drug-resistance profiles. Said differences usually emerge through de novo mutations and are maintained or discarded by the balance of evolutionary forces. Using a dataset of ~5,000 strains representing global MTBC diversity, we determined the past and present selective forces that have shaped the current variability observed in the pathogen population. We identified regions that have evolved under changing types of selection since the time of the MTBC common ancestor. Our approach highlighted striking differences in the genome regions relevant for host-pathogen interaction and, in particular, suggested an adaptive role for the sensor protein of two-component systems. In addition, we applied our approach to successfully identify potential determinants of resistance to drugs administered as second-line tuberculosis treatments.
Mining bacterial NGS data vastly expands the complete genomes of temperate phages

Temperate phages (active prophages induced from bacteria) help control pathogenicity, modulate community structure, and maintain gut homeostasis1. Complete phage genome sequences are indispensable for understanding phage biology. Traditional plaque techniques are inapplicable to temperate phages due to the lysogenicity of these phages, which curb the identification and characterization of temperate phages. Existing in silico tools for prophage prediction usually fail to detect accurate and complete temperate phage genomes2–5. In this study, by a novel computational method mining both the integrated active prophages and their spontaneously induced forms (temperate phages), we obtained 192,326 complete temperate phage genomes from bacterial next-generation sequencing (NGS) data, hence expanded the existing number of complete temperate phage genomes by more than 100-fold. The reliability of our method was validated by wet-lab experiments. The experiments demonstrated that our method can accurately determine the complete genome sequences of the temperate phages, with exact flanking sites (attP and attB sites), outperforming other state-of-the-art prophage prediction methods. Our analysis indicates that temperate phages are likely to function in the evolution of microbes by 1) cross-infecting different bacterial host species; 2) transferring antibiotic resistance and virulence genes; and 3) interacting with hosts through restriction-modification and CRISPR/anti-CRISPR systems. This work provides a comprehensive complete temperate phage genome database and relevant information, which can serve as a valuable resource for phage research.
Low dose AKT inhibitor miransertib cures PI3K-related vascular malformations in preclinical models of human disease

Low-flow vascular malformations are congenital overgrowths composed by abnormal blood vessels potentially causing pain, bleeding, and obstruction of different organs. These diseases are caused by oncogenic mutations in the endothelium which result in overactivation of the PI3K/AKT pathway. Lack of robust in vivo preclinical data has prevented the development and translation into clinical trials of specific molecular therapies for these diseases. Here, we describe a new reproducible preclinical in vivo model of PI3K-driven vascular malformations using the postnatal mouse retina. This model reproduces human disease with Pik3ca activating mutations expressed in a mosaic pattern and vascular malformations formed in veins and capillaries. We show that active angiogenesis is required for the pathogenesis of vascular malformations caused by activating Pik3ca mutations. Using this model, we demonstrate that low doses of the AKT inhibitor miransertib both prevents and induces the regression of PI3K-driven vascular malformations. We confirmed miransertib efficacy in isolated human endothelial cells with genotypes spanning most of human low-flow vascular malformations. Graphical abstract Low-flow vascular malformations are caused by PI3K signalling overactivation in endothelial cells. We have generated an optimised and robust preclinical system of PI3K-driven vascular malformations by inducing the mosaic expression of Pik3caH1047R in the retinal angiogenic endothelium. This preclinical model displays traits constituting the main hallmarks of the pathogenesis of low-flow blood vascular malformations: overactivation of PI3K signalling (high phospho-S6), vascular compartment specificity, loss of pericyte coverage, and endothelial cell hyperproliferation. Using this preclinical model we report that low dose AKT inhibitor miransertib prevents and regress PI3K-driven vascular malformations.
Time cell encoding in deep reinforcement learning agents depends on mnemonic demands

The representation of “what happened when” is central to encoding episodic and working memories. Recently discovered hippocampal time cells are theorized to provide the neural substrate for such representations by forming distinct sequences that both encode time elapsed and sensory content. However, little work has directly addressed to what extent cognitive demands and temporal structure of experimental tasks affect the emergence and informativeness of these temporal representations. Here, we trained deep reinforcement learning (DRL) agents on a simulated trial-unique nonmatch-to-location (TUNL) task, and analyzed the activities of artificial recurrent units using neuroscience-based methods. We show that, after training, representations resembling both time cells and ramping cells (whose activity increases or decreases monotonically over time) simultaneously emerged in the same population of recurrent units. Furthermore, with simulated variations of the TUNL task that controlled for (1) memory demands during the delay period and (2) the temporal structure of the episodes, we show that memory demands are necessary for the time cells to encode information about the sensory stimuli, while the temporal structure of the task only affected the encoding of “what” and “when” by time cells minimally. Our findings help to reconcile current discrepancies regarding the involvement of time cells in memory-encoding by providing a normative framework. Our modelling results also provide concrete experimental predictions for future studies.