Is the scope of phonological planning constrained by the syntactical role of the utterance constituents?

Five experiments looked the effect of repeated phonemes in the production of color adjective+noun phrases in English ("green gun"), or noun+color adjective phrases in Spanish and French. Whereas phoneme repetition sped up naming latencies in the case of prenominal color adjectives, it induced inhibition in the postnominal case. We argue that these dissociation is not compatible with a genuine crosslinguistic difference in the scope of phonological encoding. Rather we explain it in terms of the interplay between an activation gradient, coding word order, and an activation bias, coding the syntactical role of the utterance constituents

The Role of the Mechanotransducer YAP/TAZ on Cell Volume Regulation

For years, how mammalian cells control and regulate their size has remain poorly understood. This is in part due to difficulties on accurately quantifying cell volume in a high throughput manner. Many questions remain unanswered on how cells maintain their size uniformity throughout healthy tissue. In this thesis, by developing our own microdevice based on the fluorescence exclusion method, we have approached the subject of cell size from different perspectives with the unique goal to understand the mechanics of cell volume determination. We first developed a theoretical and experimental framework to study how cells adjust their volume to varying stiffness. We found that this relationship is non-trivial but can be predicted quantitatively from the distribution of active myosin throughout the cell cortex. Once we established the mechanics of cell volume determination, we pursued the metabolic pathway that could be related to cell size homeostasis. We quantified the activity of the mechanosensitive transcriptional regulators YAP (Yes-associated protein) and TAZ (transcriptional coactivator with PDZ-binding motif), widely known mechanotransducers of the Hippo pathway related to cell proliferation and organ size determination. Interestingly, we found that YAP/TAZ is positively correlated to the expression of active myosin as well as cell volume in all the conditions examined. To further prove the role of YAP/TAZ in cell volume regulation, we worked with CRISPR knockouts across the Hippo pathway and demonstrated that YAP and TAZ are novel regulators of single cell volume. We report that the role of YAP/TAZ in cell volume regulation must go beyond its influence on total cell cycle duration or the cell shape to explain the observed changes in volume. Moreover, in our context volume regulation by YAP/TAZ is independent of the mammalian target of rapamycin (mTOR), often perceived as the master regulator of cell volume. Instead, we find YAP/TAZ directly impacts the cell division volume. Based on the principle that YAP/TAZ is a mechanosensor, we find that inhibiting the assembly of myosin and cell tension slows cell cycle progression from G1 to S. We pose the idea that YAP/TAZ and the Hippo pathway may be modulating the cell volume in combination with tension during a cell cycle checkpoint

AttentionDDI: Siamese attention‑based deep learning method for drug–drug interaction predictions

Background: Drug-drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those observed when drugs are administered by themselves. Due to the massive number of possible drug pairs, it is nearly impossible to experimentally test all combinations and discover previously unobserved side effects. Therefore, machine learning based methods are being used to address this issue. Methods: We propose a Siamese self-attention multi-modal neural network for DDI prediction that integrates multiple drug similarity measures that have been derived from a comparison of drug characteristics including drug targets, pathways and gene expression profiles. Results: Our proposed DDI prediction model provides multiple advantages: (1) It is trained end-to-end, overcoming limitations of models composed of multiple separate steps, (2) it offers model explainability via an Attention mechanism for identifying salient input features and (3) it achieves similar or better prediction performance (AUPR scores ranging from 0.77 to 0.92) compared to state-of-the-art DDI models when tested on various benchmark datasets. Novel DDI predictions are further validated using independent data resources. Conclusions: We find that a Siamese multi-modal neural network is able to accurately predict DDIs and that an Attention mechanism, typically used in the Natural Language Processing domain, can be beneficially applied to aid in DDI model explainability. Keywords: Attention; Deep learning; Drug–drug interactions; Prediction; Side effect

Juvenile polyautoimmunity in a rheumatology setting

Q1Q1Paciente jovenOvert polyautoimmunity (PolyA) corresponds to the presence of more than one well-defined autoimmune disease (AD) manifested clinically in a single patient. The current study aimed to describe the main characteristics of juvenile PolyA in a pediatric rheumatology setting and analyze the chronological aspects, index cases, familial autoimmunity, and clustering pattern. This was a cross-sectional and multicenter study in which 313 children with overt PolyA were included. Patients were systematically interviewed and their medical records reviewed using a questionnaire that sought information about demographic, clinical, immunological, and familial characteristics. A hierarchical cluster analysis was done to determine similarities between autoimmune diseases based on PolyA. PolyA occurred simultaneously in 138 (44%) patients. Multiple autoimmune syndrome was observed in 62 (19.8%) patients. There were 25 index diseases of which, systemic lupus erythematosus (SLE, n = 134, 42.8%), juvenile idiopathic arthritis (JIA, n = 40, 12.7%), Hashimoto's thyroiditis (HT, n = 24, 7.66%), immune thrombocytopenic purpura (ITP n = 20, 6.39%), antiphospholipid syndrome (APS, n = 15, 4.79%), and vitiligo (VIT, n = 15, 4.79%) were the most frequent and represented 79.23% of the total number of patients. Familial autoimmunity influenced PolyA. A high aggregation of autoimmunity was observed (λr = 3.5). Three main clusters were identified, of which SLE and APS were the most similar pair of diseases (based on the Jaccard index) followed by HT and JIA, which were related to ITP and Sjögren's syndrome. The third cluster was composed of localized scleroderma and VIT. Our findings may assist physicians to make an early diagnosis of this frequent condition. Pediatric patients with ADs should be systematically assessed for PolyA.Revista Nacional - Indexad

Vision transformer assisting rheumatologists in screening for capillaroscopy changes in systemic sclerosis: an artificial intelligence model

OBJECTIVES: The first objective of this study was to implement and assess the performance and reliability of a vision transformer (ViT)-based deep-learning model, an 'off-the-shelf' artificial intelligence solution, for identifying distinct signs of microangiopathy in nailfold capilloroscopy (NFC) images of patients with SSc. The second objective was to compare the ViT's analysis performance with that of practising rheumatologists. METHODS: NFC images of patients prospectively enrolled in our European Scleroderma Trials and Research group (EUSTAR) and Very Early Diagnosis of Systemic Sclerosis (VEDOSS) local registries were used. The primary outcome investigated was the ViT's classification performance for identifying disease-associated changes (enlarged capillaries, giant capillaries, capillary loss, microhaemorrhages) and the presence of the scleroderma pattern in these images using a cross-fold validation setting. The secondary outcome involved a comparison of the ViT's performance vs that of rheumatologists on a reliability set, consisting of a subset of 464 NFC images with majority vote-derived ground-truth labels. RESULTS: We analysed 17 126 NFC images derived from 234 EUSTAR and 55 VEDOSS patients. The ViT had good performance in identifying the various microangiopathic changes in capillaries by NFC [area under the curve (AUC) from 81.8% to 84.5%]. In the reliability set, the rheumatologists reached a higher average accuracy, as well as a better trade-off between sensitivity and specificity compared with the ViT. However, the annotators' performance was variable, and one out of four rheumatologists showed equal or lower classification measures compared with the ViT. CONCLUSIONS: The ViT is a modern, well-performing and readily available tool for assessing patterns of microangiopathy on NFC images, and it may assist rheumatologists in generating consistent and high-quality NFC reports; however, the final diagnosis of a scleroderma pattern in any individual case needs the judgement of an experienced observer

Vision transformer assisting rheumatologists in screening for capillaroscopy changes in systemic sclerosis: an artificial intelligence model.

OBJECTIVES The first objective of this study was to implement and assess the performance and reliability of a vision transformer (ViT)-based deep-learning model, an 'off-the-shelf' artificial intelligence solution, for identifying distinct signs of microangiopathy in nailfold capilloroscopy (NFC) images of patients with SSc. The second objective was to compare the ViT's analysis performance with that of practising rheumatologists. METHODS NFC images of patients prospectively enrolled in our European Scleroderma Trials and Research group (EUSTAR) and Very Early Diagnosis of Systemic Sclerosis (VEDOSS) local registries were used. The primary outcome investigated was the ViT's classification performance for identifying disease-associated changes (enlarged capillaries, giant capillaries, capillary loss, microhaemorrhages) and the presence of the scleroderma pattern in these images using a cross-fold validation setting. The secondary outcome involved a comparison of the ViT's performance vs that of rheumatologists on a reliability set, consisting of a subset of 464 NFC images with majority vote-derived ground-truth labels. RESULTS We analysed 17 126 NFC images derived from 234 EUSTAR and 55 VEDOSS patients. The ViT had good performance in identifying the various microangiopathic changes in capillaries by NFC [area under the curve (AUC) from 81.8% to 84.5%]. In the reliability set, the rheumatologists reached a higher average accuracy, as well as a better trade-off between sensitivity and specificity compared with the ViT. However, the annotators' performance was variable, and one out of four rheumatologists showed equal or lower classification measures compared with the ViT. CONCLUSIONS The ViT is a modern, well-performing and readily available tool for assessing patterns of microangiopathy on NFC images, and it may assist rheumatologists in generating consistent and high-quality NFC reports; however, the final diagnosis of a scleroderma pattern in any individual case needs the judgement of an experienced observer

Velocity Dispersions and Stellar Populations of the Most Compact and Msssive early-Type Galaxies at Redshift similar to 1

We present Gran-Telescopio-Canarias/OSIRIS optical spectra of four of the most compact and massive early-type galaxies (ETGs) in the Groth Strip Survey at redshift z similar to 1, with effective radii R-e = 0.5-2.4 kpc and photometric stellarmasses M-star = (1.2-4) x 10(11)M(circle dot). We find that these galaxies have velocity dispersions sigma = 156-236 km s(-1). The spectra are well fitted by single stellar population models with approximately 1 Gyr of age and solar metallicity. We find that (1) the dynamical masses of these galaxies are systematically smaller by a factor of similar to 6 than the published stellarmasses using BRIJK photometry, and (2) when estimating stellarmasses as 0.7xM(dyn), a combination of passive luminosity fading with mass/size growth due to minor mergers can plausibly evolve our objects to match the properties of the local population of ETGs

Functional Recovery and Serum Angiogenin Changes According to Intensity of Rehabilitation Therapy After Stroke

Angiogenina; Terapia intensiva; RehabilitaciónAngiogenin; Intensive therapy; RehabilitationAngiogenina; Teràpia intensiva; RehabilitacióBackground: Rehabilitation is still the only treatment available to improve functional status after the acute phase of stroke. Most clinical guidelines highlight the need to design rehabilitation treatments considering starting time, intensity, and frequency, according to the tolerance of the patient. However, there are no homogeneous protocols and the biological effects are under investigation. Objective: To investigate the impact of rehabilitation intensity (hours) after stroke on functional improvement and serum angiogenin (ANG) in a 6-month follow-up study. Methods: A prospective, observational, longitudinal, and multicenter study with three cohorts: strokes in intensive rehabilitation therapy (IRT, minimum 15 h/week) vs. conventional therapy (NO-IRT, <15 h/week), and controls subjects (without known neurological, malignant, or inflammatory diseases). A total of seven centers participated, with functional evaluations and blood sampling during follow-up. The final cohort includes 62 strokes and 43 controls with demographic, clinical, blood samples, and exhaustive functional monitoring. Results: The median (IQR) number of weekly hours of therapy was different: IRT 15 (15–16) vs. NO-IRT 7.5 (5–9), p < 0.01, with progressive and significant improvements in both groups. However, IRT patients showed earlier improvements (within 1 month) on several scales (CAHAI, FMA, and FAC; p < 0.001) and the earliest community ambulation achievements (0.89 m/s at 3 months). There was a significant difference in ANG temporal profile between the IRT and NO-IRT groups (p < 0.01). Additionally, ANG was elevated at 1 month only in the IRT group (p < 0.05) whereas it decreased in the NO-IRT group (p < 0.05). Conclusions: Our results suggest an association of rehabilitation intensity with early functional improvements, and connect the rehabilitation process with blood biomarkers.NG-R holds a VHIR fellowship and MO-G a Joan Margarit VHIR fellowship. Research grants: from the Instituto de Salud Carlos III and European Regional Development Funds (PI16/00981, PI19/00186, RD16/0019/0021, and RD16/0019/0008), 2017-SGR-1427 program from the Generalitat de Catalunya-AGAUR, and Clinical Translational Program for Regenerative Medicine in Catalonia (P-CMR [C])

Novel anti-invasive properties of a Fascin1 inhibitor on colorectal cancer cells

Tumor invasion and metastasis involve processes in which actin cytoskeleton rearrangement induced by Fascin1 plays a crucial role. Indeed, Fascin1 has been found overexpressed in tumors with worse prognosis. Migrastatin and its analogues target Fascin1 and inhibit its activity. However, there is need for novel and smaller Fascin1 inhibitors. The aim of this study was to assess the effect of compound G2 in colorectal cancer cell lines and compare it to migrastatin in in vitro and in vivo assays. Molecular modeling, actin-bundling, cell viability, inmunofluorescence, migration, and invasion assays were carried out in order to test anti-migratory and anti-invasive properties of compound G2. In addition, the in vivo effect of compound G2 was evaluated in a zebrafish model of invasion. HCT-116 cells exhibited the highest Fascin1 expression from eight tested colorectal cancer cell lines. Compound G2 showed important inhibitory effects on actin bundling, filopodia formation, migration, and invasion in different cell lines. Moreover, compound G2 treatment resulted in significant reduction of invasion of DLD-1 overexpressing Fascin1 and HCT-116 in zebrafish larvae xenografts; this effect being less evident in Fascin1 known-down HCT-116 cells. This study proves, for the first time, the in vitro and in vivo anti-tumoral activity of compound G2 on colorectal cancer cells and guides to design improved compound G2-based Fascin1 inhibitors. Key messages center dot Fascin is crucial for tumor invasion and metastasis and is overexpressed in bad prognostic tumors. center dot Several adverse tumors overexpress Fascin1 and lack targeted therapy. center dot Anti-fascin G2 is for the first time evaluated in colorectal carcinoma and compared with migrastatin. center dot Filopodia formation, migration activity, and invasion in vitro and in vivo assays were performed. center dot G2 blocks actin structures, migration, and invasion of colorectal cancer cells as fascin-dependent.Peer reviewe