Deux niveaux et deux outils d'analyse pour une meilleure segmentation de données audio

- Dans cet article, nous abordons le problème de la segmentation de données audio. Nous proposons un processus de segmentation à deux niveaux qui permet de diviser les pistes audio en courtes séquences qui sont étiquetées dans différentes classes. La segmentation est effectuée en calculant différentes caractéristiques pour chaque séquence audio. Ces caractéristiques sont calculées soit sur un segment audio complet, soit sur une trame (ensemble d'échantillons) qui est un sous-ensemble d'un segment audio. L'approche proposée pour la microsegmentation des données audio consiste en une combinaison d'un classifieur K-Means au niveau des segments et d'un système de chaînes de Markov cachées multidimensionnelles utilisant une décomposition du signal en trames. Une première classification est obtenue en utilisant le classifieur K-Means et les caractéristiques relatives aux segments. Le résultat final est alors fourni par l'utilisation des chaînes de Markov cachées multidimensionnelles et les caractéristiques relatives aux trames, en se basant sur les résultats intermédiaires fournis par la première étape. Les chaînes de Markov cachées multidimensionnelles sont une extension des chaînes de Markov cachées classiques qui permet la prise en compte de données multicomposantes. Elles sont particulièrement adaptées dans notre cas où chaque segment audio peut être représenté par plusieurs caractéristiques de différentes natures

Application of Diffusion Tensor Imaging Parameters to Detect Change in Longitudinal Studies in Cerebral Small Vessel Disease.

Cerebral small vessel disease (SVD) is the major cause of vascular cognitive impairment, resulting in significant disability and reduced quality of life. Cognitive tests have been shown to be insensitive to change in longitudinal studies and, therefore, sensitive surrogate markers are needed to monitor disease progression and assess treatment effects in clinical trials. Diffusion tensor imaging (DTI) is thought to offer great potential in this regard. Sensitivity of the various parameters that can be derived from DTI is however unknown. We aimed to evaluate the differential sensitivity of DTI markers to detect SVD progression, and to estimate sample sizes required to assess therapeutic interventions aimed at halting decline based on DTI data. We investigated 99 patients with symptomatic SVD, defined as clinical lacunar syndrome with MRI confirmation of a corresponding infarct as well as confluent white matter hyperintensities over a 3 year follow-up period. We evaluated change in DTI histogram parameters using linear mixed effect models and calculated sample size estimates. Over a three-year follow-up period we observed a decline in fractional anisotropy and increase in diffusivity in white matter tissue and most parameters changed significantly. Mean diffusivity peak height was the most sensitive marker for SVD progression as it had the smallest sample size estimate. This suggests disease progression can be monitored sensitively using DTI histogram analysis and confirms DTI's potential as surrogate marker for SVD

Subunit asymmetry and roles of conformational switching in the hexameric AAA+ ring of ClpX

The hexameric AAA+ ring of Escherichia coli ClpX, an ATP-dependent machine for protein unfolding and translocation, functions with the ClpP peptidase to degrade target substrates. For efficient function, ClpX subunits must switch between nucleotide-loadable (L) and nucleotide-unloadable (U) conformations, but the roles of switching are uncertain. Moreover, it is controversial whether working AAA+-ring enzymes assume symmetric or asymmetric conformations. Here, we show that a covalent ClpX ring with one subunit locked in the U conformation catalyzes robust ATP hydrolysis, with each unlocked subunit able to bind and hydrolyze ATP, albeit with highly asymmetric position-specific affinities. Preventing U↔L interconversion in one subunit alters the cooperativity of ATP hydrolysis and reduces the efficiency of substrate binding, unfolding and degradation, showing that conformational switching enhances multiple aspects of wild-type ClpX function. These results support an asymmetric and probabilistic model of AAA+-ring activity.National Institutes of Health (U.S.) (Grant GM-101988)Massachusetts Institute of Technology (Poitras Predoctoral Fellowship

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

An aberrant NOTCH2-BCR signaling axis in B cells from patients with chronic GVHD

B-cell receptor (BCR)-activated B cells contribute to pathogenesis in chronic graft-versus-host disease (cGVHD), a condition manifested by both B-cell autoreactivity and immune deficiency. We hypothesized that constitutive BCR activation precluded functional B-cell maturation in cGVHD. To address this, we examined BCR-NOTCH2 synergy because NOTCH has been shown to increase BCR responsiveness in normal mouse B cells. We conducted ex vivo activation and signaling assays of 30 primary samples from hematopoietic stem cell transplantation patients with and without cGVHD. Consistent with a molecular link between pathways, we found that BCR-NOTCH activation significantly increased the proximal BCR adapter protein BLNK. BCR-NOTCH activation also enabled persistent NOTCH2 surface expression, suggesting a positive feedback loop. Specific NOTCH2 blockade eliminated NOTCH-BCR activation and significantly altered NOTCH downstream targets and B-cell maturation/effector molecules. Examination of the molecular underpinnings of this “NOTCH2-BCR axis” in cGVHD revealed imbalanced expression of the transcription factors IRF4 and IRF8, each critical to B-cell differentiation and fate. All-trans retinoic acid (ATRA) increased IRF4 expression, restored the IRF4-to-IRF8 ratio, abrogated BCR-NOTCH hyperactivation, and reduced NOTCH2 expression in cGVHD B cells without compromising viability. ATRA-treated cGVHD B cells had elevated TLR9 and PAX5, but not BLIMP1 (a gene-expression pattern associated with mature follicular B cells) and also attained increased cytosine guanine dinucleotide responsiveness. Together, we reveal a mechanistic link between NOTCH2 activation and robust BCR responses to otherwise suboptimal amounts of surrogate antigen. Our findings suggest that peripheral B cells in cGVHD patients can be pharmacologically directed from hyperactivation toward maturity

Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits

Mycorrhizal fungi are mutualists that play crucial roles in nutrient acquisition in terrestrial ecosystems. Mycorrhizal symbioses arose repeatedly across multiple lineages of Mucoromycotina, Ascomycota, and Basidiomycota. Considerable variation exists in the capacity of mycorrhizal fungi to acquire carbon from soil organic matter. Here, we present a combined analysis of 135 fungal genomes from 73 saprotrophic, endophytic and pathogenic species, and 62 mycorrhizal species, including 29 new mycorrhizal genomes. This study samples ecologically dominant fungal guilds for which there were previously no symbiotic genomes available, including ectomycorrhizal Russulales, Thelephorales and Cantharellales. Our analyses show that transitions from saprotrophy to symbiosis involve (1) widespread losses of degrading enzymes acting on lignin and cellulose, (2) co-option of genes present in saprotrophic ancestors to fulfill new symbiotic functions, (3) diversification of novel, lineage-specific symbiosis-induced genes, (4) proliferation of transposable elements and (5) divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild. Mycorrhizal symbioses have evolved repeatedly in diverse fungal lineages. A large phylogenomic analysis sheds light on genomic changes associated with transitions from saprotrophy to symbiosis, including divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild.Peer reviewe

SeamlessM4T-Massively Multilingual & Multimodal Machine Translation

What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages? While recent breakthroughs in text-based models have pushed machine translation coverage beyond 200 languages, unified speech-to-speech translation models have yet to achieve similar strides. More specifically, conventional speech-to-speech translation systems rely on cascaded systems that perform translation progressively, putting high-performing unified systems out of reach. To address these gaps, we introduce SeamlessM4T, a single model that supports speech-to-speech translation, speech-to-text translation, text-to-speech translation, text-to-text translation, and automatic speech recognition for up to 100 languages. To build this, we used 1 million hours of open speech audio data to learn self-supervised speech representations with w2v-BERT 2.0. Subsequently, we created a multimodal corpus of automatically aligned speech translations. Filtered and combined with human-labeled and pseudo-labeled data, we developed the first multilingual system capable of translating from and into English for both speech and text. On FLEURS, SeamlessM4T sets a new standard for translations into multiple target languages, achieving an improvement of 20% BLEU over the previous SOTA in direct speech-to-text translation. Compared to strong cascaded models, SeamlessM4T improves the quality of into-English translation by 1.3 BLEU points in speech-to-text and by 2.6 ASR-BLEU points in speech-to-speech. Tested for robustness, our system performs better against background noises and speaker variations in speech-to-text tasks compared to the current SOTA model. Critically, we evaluated SeamlessM4T on gender bias and added toxicity to assess translation safety. Finally, all contributions in this work are open-sourced and accessible at https://github.com/facebookresearch/seamless_communicatio

Systemic Biomarkers of Neutrophilic Inflammation, Tissue Injury and Repair in COPD Patients with Differing Levels of Disease Severity

The identification and validation of biomarkers to support the assessment of novel therapeutics for COPD continues to be an important area of research. The aim of the current study was to identify systemic protein biomarkers correlated with measures of COPD severity, as well as specific protein signatures associated with comorbidities such as metabolic syndrome. 142 protein analytes were measured in serum of 140 patients with stable COPD, 15 smokers without COPD and 30 non-smoking controls. Seven analytes (sRAGE, EN-RAGE, NGAL, Fibrinogen, MPO, TGF-α and HB-EGF) showed significant differences between severe/very severe COPD, mild/moderate COPD, smoking and non-smoking control groups. Within the COPD subjects, univariate and multivariate analyses identified analytes significantly associated with FEV1, FEV1/FVC and DLCO. Most notably, a set of 5 analytes (HB-EGF, Fibrinogen, MCP-4, sRAGE and Sortilin) predicted 21% of the variability in DLCO values. To determine common functions/pathways, analytes were clustered in a correlation network by similarity of expression profile. While analytes related to neutrophil function (EN-RAGE, NGAL, MPO) grouped together to form a cluster associated with FEV1 related parameters, analytes related to the EGFR pathway (HB-EGF, TGF-α) formed another cluster associated with both DLCO and FEV1 related parameters. Associations of Fibrinogen with DLCO and MPO with FEV1/FVC were stronger in patients without metabolic syndrome (r  =  −0.52, p  = 0.005 and r  =  −0.61, p  = 0.023, respectively) compared to patients with coexisting metabolic syndrome (r  =  −0.25, p  = 0.47 and r  =  −0.15, p  = 0.96, respectively), and may be driving overall associations in the general cohort. In summary, our study has identified known and novel serum protein biomarkers and has demonstrated specific associations with COPD disease severity, FEV1, FEV1/FVC and DLCO. These data highlight systemic inflammatory pathways, neutrophil activation and epithelial tissue injury/repair processes as key pathways associated with COPD

White matter hyperintensities and normal-appearing white matter integrity in the aging brain

AbstractWhite matter hyperintensities (WMH) of presumed vascular origin are a common finding in brain magnetic resonance imaging of older individuals and contribute to cognitive and functional decline. It is unknown how WMH form, although white matter degeneration is characterized pathologically by demyelination, axonal loss, and rarefaction, often attributed to ischemia. Changes within normal-appearing white matter (NAWM) in subjects with WMH have also been reported but have not yet been fully characterized. Here, we describe the in vivo imaging signatures of both NAWM and WMH in a large group of community-dwelling older people of similar age using biomarkers derived from magnetic resonance imaging that collectively reflect white matter integrity, myelination, and brain water content. Fractional anisotropy (FA) and magnetization transfer ratio (MTR) were significantly lower, whereas mean diffusivity (MD) and longitudinal relaxation time (T1) were significantly higher, in WMH than NAWM (p < 0.0001), with MD providing the largest difference between NAWM and WMH. Receiver operating characteristic analysis on each biomarker showed that MD differentiated best between NAWM and WMH, identifying 94.6% of the lesions using a threshold of 0.747 × 10−9 m2s−1 (area under curve, 0.982; 95% CI, 0.975–0.989). Furthermore, the level of deterioration of NAWM was strongly associated with the severity of WMH, with MD and T1 increasing and FA and MTR decreasing in NAWM with increasing WMH score, a relationship that was sustained regardless of distance from the WMH. These multimodal imaging data indicate that WMH have reduced structural integrity compared with surrounding NAWM, and MD provides the best discriminator between the 2 tissue classes even within the mild range of WMH severity, whereas FA, MTR, and T1 only start reflecting significant changes in tissue microstructure as WMH become more severe

Genetic architecture of subcortical brain structures in 38,851 individuals

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease