DIS-EMBODIED LANGUAGE: L'ACQUISIZIONE LINGUISTICA IN ASSENZA DI RIFERIMENTI ORO-ARTICOLATORI. L'ELOQUIO DEL BAMBINO DISPRASSICO ITALIANO.

La tesi fornisce una prima classificazione sistematica dei fenomeni fonetico-fonologici che caratterizzano l'eloquio del bambino, di lingua italiana, affetto da disprassia verbale in età evolutiva. Presenta, inoltre, un'ipotesi di lettura della patologia dal punto da un punto di vista "embodied" ed ipotesi di ricerca attinenti

Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-b, more advanced stages (AT) of AD pathology and APOE-e4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging related to markers of AD and neurodegeneration.The project leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004 and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). Additional support has been received from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2017-SGR-892 and the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033. FB is supported by the NIHR biomedical research center at UCLH. MSC receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 948677), the Instituto de Salud Carlos III (PI19/00155), and from a fellowship from ”la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648 (LCF/BQ/PR21/11840004).Report de recerca signat per 27 autors/es: Irene Cumplido-Mayoral 1,2; Marina García-Prat 1; Grégory Operto 1,3,4; Carles Falcon 1,3,5; Mahnaz Shekari 1,2,3; Raffaele Cacciaglia 1,3,4; Marta Milà-Alomà 1,2,3,4; Luigi Lorenzini 6; Silvia Ingala 6; Alle Meije Wink 6; Henk JMM Mutsaerts 6; Carolina Minguillón 1,3,4; Karine Fauria 1,4; José Luis Molinuevo 1; Sven Haller 7; Gael Chetelat 8,10; Adam Waldman 9; Adam Schwarz 10; Frederik Barkhof 6,11; Ivonne Suridjan 12, 11; Gwendlyn Kollmorgen 13; Anna Bayfield 13; Henrik Zetterberg 14,15,16,17,18; Kaj Blennow 14,15 12; Marc Suárez-Calvet 1,3,4,19; Verónica Vilaplana 20; Juan Domingo Gispert 1,3,5; ALFA study; EPAD study; ADNI study; OASIS study // 1) Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; 2) Universitat Pompeu Fabra, Barcelona, Spain; 3) IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; 4) CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain; 5) Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain; 6) Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; 7) CIRD Centre d'Imagerie Rive Droite, Geneva, Switzerland; 8) Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France; 9) Centre for Dementia Prevention, Edinburgh Imaging, and UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK; 10) Takeda Pharmaceutical Company Ltd, Cambridge, MA, USA; 11) Institutes of Neurology and Healthcare Engineering, University College London, London, UK; 12) Roche Diagnostics International Ltd, Rotkreuz, Switzerland; 13) Roche Diagnostics GmbH, Penzberg, Germany; 14) Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden; 15) Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; 16) Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, United Kingdom; 17) UK Dementia Research Institute at UCL, London, United Kingdom; 18) Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China; 19) Servei de Neurologia, Hospital del Mar, Barcelona, Spain; 20) Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, Barcelona, Spain.Preprin

Nerve Growth Factor Biodelivery: A Limiting Step in Moving Toward Extensive Clinical Application?

Nerve growth factor (NGF) was the first-discovered member of the neurotrophin family, a class of bioactive molecules which exerts powerful biological effects on the CNS and other peripheral tissues, not only during development, but also during adulthood. While these molecules have long been regarded as potential drugs to combat acute and chronic neurodegenerative processes, as evidenced by the extensive data on their neuroprotective properties, their clinical application has been hindered by their unexpected side effects, as well as by difficulties in defining appropriate dosing and administration strategies. This paper reviews aspects related to the endogenous production of NGF in healthy and pathological conditions, along with conventional and biomaterial-assisted delivery strategies, in an attempt to clarify the impediments to the clinical application of this powerful molecule

Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's disease and neurodegeneration stratified by sex

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer's disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD, and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain-age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury

Comparison and combination of a hemodynamics/biomarkers-based model with simplified PESI score for prognostic stratification of acute pulmonary embolism: findings from a real world study

Background: Prognostic stratification is of utmost importance for management of acute Pulmonary Embolism (PE) in clinical practice. Many prognostic models have been proposed, but which is the best prognosticator in real life remains unclear. The aim of our study was to compare and combine the predictive values of the hemodynamics/biomarkers based prognostic model proposed by European Society of Cardiology (ESC) in 2008 and simplified PESI score (sPESI).Methods: Data records of 452 patients discharged for acute PE from Internal Medicine wards of Tuscany (Italy) were analysed. The ESC model and sPESI were retrospectively calculated and compared by using Areas under Receiver Operating Characteristics (ROC) Curves (AUCs) and finally the combination of the two models was tested in hemodinamically stable patients. All cause and PE-related in-hospital mortality and fatal or major bleedings were the analyzed endpointsResults: All cause in-hospital mortality was 25% (16.6% PE related) in high risk, 8.7% (4.7%) in intermediate risk and 3.8% (1.2%) in low risk patients according to ESC model. All cause in-hospital mortality was 10.95% (5.75% PE related) in patients with sPESI score ≥1 and 0% (0%) in sPESI score 0. Predictive performance of sPESI was not significantly different compared with 2008 ESC model both for all cause (AUC sPESI 0.711, 95% CI: 0.661-0.758 versus ESC 0.619, 95% CI: 0.567-0.670, difference between AUCs 0.0916, p=0.084) and for PE-related mortality (AUC sPESI 0.764, 95% CI: 0.717-0.808 versus ESC 0.650, 95% CI: 0.598-0.700, difference between AUCs 0.114, p=0.11). Fatal or major bleedings occurred in 4.30% of high risk, 1.60% of intermediate risk and 2.50% of low risk patients according to 2008 ESC model, whereas these occurred in 1.80% of high risk and 1.45% of low risk patients according to sPESI, respectively. Predictive performance for fatal or major bleeding between two models was not significantly different (AUC sPESI 0.658, 95% CI: 0.606-0.707 versus ESC 0.512, 95% CI: 0.459-0.565, difference between AUCs 0.145, p=0.34). In hemodynamically stable patients, the combined endpoint in-hospital PE-related mortality and/or fatal or major bleeding (adverse events) occurred in 0% of patients with low risk ESC model and sPESI score 0, whilst it occurred in 5.5% of patients with low-risk ESC model but sPESI ≥1. In intermediate risk patients according to ESC model, adverse events occurred in 3.6% of patients with sPESI score 0 and 6.65% of patients with sPESI score ≥1.Conclusions: In real world, predictive performance of sPESI and the hemodynamic/biomarkers-based ESC model as prognosticator of in-hospital mortality and bleedings is similar. Combination of sPESI 0 with low risk ESC model may identify patients with very low risk of adverse events and candidate for early hospital discharge or home treatment.

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk

Heat transfer for a Giesekus fluid in a rotating concentric annulus

Annular flow of a viscoelastic fluid described by the Giesekus model has received some attention over the years, both concerning the fluid mechanical and thermal aspects, yet no investigation has been carried out using the analytical solution for the velocity profile in the energy equation to determine temperature distribution and heat transfer characteristics. Moreover, viscous dissipation, when accounted for, is usually defined by a formulation of the Brinkman number which proves inconsistent when applied to non-Newtonian fluids. In this work the purely tangential flow of a Giesekus fluid in an annulus with rotating inner wall subject to thermal boundary conditions of the first kind (imposed temperature) at the walls is investigated employing the analytical solution for the velocity profile. Viscous dissipation is accounted for by first deriving a consistent Brinkman number which is easily related to the one usually employed in previous studies and the temperature profiles are obtained for different values of the Deborah number and the non-dimensional mobility factor. Results for the Nusselt numbers at the inner and outer wall are also discussed

Temporal integration for amplitude modulation in childhood: Interaction between internal noise and memory

International audienc

Molecular Mechanisms, Biomarkers and Emerging Therapies for Chemotherapy Resistant TNBC

Triple-negative breast cancer (TNBC) is associated with high recurrence rates, high incidence of distant metastases, and poor overall survival (OS). Taxane and anthracycline-containing chemotherapy (CT) is currently the main systemic treatment option for TNBC, while platinum-based chemotherapy showed promising results in the neoadjuvant and metastatic settings. An early arising of intrinsic or acquired CT resistance is common and represents the main hurdle for successful TNBC treatment. Numerous mechanisms were uncovered that can lead to the development of chemoresistance. These include cancer stem cells (CSCs) induction after neoadjuvant chemotherapy (NACT), ATP-binding cassette (ABC) transporters, hypoxia and avoidance of apoptosis, single factors such as tyrosine kinase receptors (EGFR, IGFR1), a disintegrin and metalloproteinase 10 (ADAM10), and a few pathological molecular pathways. Some biomarkers capable of predicting resistance to specific chemotherapeutic agents were identified and are expected to be validated in future studies for a more accurate selection of drugs to be employed and for a more tailored approach, both in neoadjuvant and advanced settings. Recently, based on specific biomarkers, some therapies were tailored to TNBC subsets and became available in clinical practice: olaparib and talazoparib for BRCA1/2 germline mutation carriers larotrectinib and entrectinib for neurotrophic tropomyosin receptor kinase (NTRK) gene fusion carriers, and anti-trophoblast cell surface antigen 2 (Trop2) antibody drug conjugate therapy for heavily pretreated metastatic TNBC (mTNBC). Further therapies targeting some pathologic molecular pathways, apoptosis, miRNAS, epidermal growth factor receptor (EGFR), insulin growth factor 1 receptor (IGF-1R), and androgen receptor (AR) are under investigation. Among them, phosphatidylinositol 3 kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR) and EGFR inhibitors as well as antiandrogens showed promising results and are under evaluation in Phase II/III clinical trials. Emerging therapies allow to select specific antiblastics that alone or by integrating the conventional therapeutic approach may overcome/hinder chemoresistance