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The discovery of early, non-invasive biomarkers for the identification of \"preclinical\" or \"pre-symptomatic\" Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals. We enrolled 96 participants (age range 50-75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features. Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI. Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption.

Numerical abilities are fundamental in our society. As a consequence, poor numerical skills might have a great impact on daily living. This study analyzes the extent to which the numerical deficit observed in young adults with Developmental Dyscalculia (DD) impacts their activities of everyday life. For this purpose, 26 adults with DD and 26 healthy controls completed the NADL, a standardized battery that assesses numerical skills in both formal and informal contexts. The results showed that adults with DD had poorer arithmetical skills in both formal and informal settings. In particular, adults with DD presented difficulties in time and measure estimation as well as money usage in real-world numerical tasks. In contrast, everyday tasks regarding distance estimation were preserved. In addition, the assessment revealed that adults with DD were aware of their numerical difficulties, which were often related to emotional problems and negatively impacted their academic and occupational decisions. Our study highlights the need to design innovative interventions and age-appropriate training for adults with DD to support their numerical skills as well as their social and emotional well-being.

To assess the diagnostic and prognostic value of serum neurofilament light (NfL) and serum phospho-Tau (p-Tau ) in a large cohort of patients with frontotemporal lobar degeneration (FTLD). In this retrospective study, performed on 417 participants, we analysed serum NfL and p-Tau concentrations with an ultrasensitive single molecule array (Simoa) approach. We assessed the diagnostic values of serum biomarkers in the differential diagnosis between FTLD, Alzheimer's disease (AD) and healthy ageing; their role as markers of disease severity assessing the correlation with clinical variables, cross-sectional brain imaging and neurophysiological data; their role as prognostic markers, considering their ability to predict survival probability in FTLD. We observed significantly higher levels of serum NfL in patients with FTLD syndromes, compared with healthy controls, and lower levels of p-Tau compared with patients with AD. Serum NfL concentrations showed a high accuracy in discriminating between FTLD and healthy controls (area under the curve (AUC): 0.86, p<0.001), while serum p-Tau showed high accuracy in differentiating FTLD from patients with AD (AUC: 0.93, p<0.001). In FTLD, serum NfL levels correlated with measures of cognitive function, disease severity and behavioural disturbances and were associated with frontotemporal atrophy and indirect measures of GABAergic deficit. Moreover, serum NfL concentrations were identified as the best predictors of survival probability. The assessment of serum NfL and p-Tau may provide a comprehensive view of FTLD, aiding in the differential diagnosis, in staging disease severity and in defining survival probability.

ObjectiveTo assess the diagnostic and prognostic value of serum neurofilament light (NfL) and serum phospho-Tau181 (p-Tau181) in a large cohort of patients with frontotemporal lobar degeneration (FTLD).MethodsIn this retrospective study, performed on 417 participants, we analysed serum NfL and p-Tau181 concentrations with an ultrasensitive single molecule array (Simoa) approach. We assessed the diagnostic values of serum biomarkers in the differential diagnosis between FTLD, Alzheimer’s disease (AD) and healthy ageing; their role as markers of disease severity assessing the correlation with clinical variables, cross-sectional brain imaging and neurophysiological data; their role as prognostic markers, considering their ability to predict survival probability in FTLD.ResultsWe observed significantly higher levels of serum NfL in patients with FTLD syndromes, compared with healthy controls, and lower levels of p-Tau181 compared with patients with AD. Serum NfL concentrations showed a high accuracy in discriminating between FTLD and healthy controls (area under the curve (AUC): 0.86, p<0.001), while serum p-Tau181 showed high accuracy in differentiating FTLD from patients with AD (AUC: 0.93, p<0.001). In FTLD, serum NfL levels correlated with measures of cognitive function, disease severity and behavioural disturbances and were associated with frontotemporal atrophy and indirect measures of GABAergic deficit. Moreover, serum NfL concentrations were identified as the best predictors of survival probability.ConclusionsThe assessment of serum NfL and p-Tau181 may provide a comprehensive view of FTLD, aiding in the differential diagnosis, in staging disease severity and in defining survival probability.

Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (GRN), microtubule-associated protein tau (MAPT), or chromosome 9 open reading frame 72 (C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test −0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all −0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference −0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference −0·2, SE 0·1). Structural imaging and cognitive changes can be identified 5–10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. Centres of Excellence in Neurodegeneration.

Background and aims: To describe the clinical and neuropsychological features of a large group of cognitively intact persons subjected to brain high-resolution magnetic resonance (MR), to compare them with the general population, and to set norms for medial temporal atrophy and white matter lesions. Methods: Participants in the Italian Brain Normative Archive (IBNA) study were 483 consecutive volunteers undergoing MR for reasons unrelated to cognition (migraine or headache, visual and balance or auditory disturbances, paresthesias, and others) and showing no brain damage. Manual tracing of hippocampal and amygdalar volumes and visual rating of white matter lesions were made. The whole study group was stratified by age (≤60 and 60+ yrs) and by the reason for MR prescription. Results: In the whole group, mean age and education were 52.4±13.7 and 9.8±4.2 years, respectively, and the prevalence of women was 63%. Clinical, neuropsychological and morphometric features were similar in the stratified subgroups. Neuropsychological features were those expected for age and education based on Italian normative values. Hippocampal and amygdalar volumes were not associated with age, except for the right amygdala (B −0.159, 95% CI −0.28 to −0.03, p=0.016). Conclusions: Persons in the IBNA study had clinical and neuropsychological features consistent with that of the general population. Their brain morphometric features may be used as normative references for patients with suspected neurodegenerative disorders.

This paper proposes RUR53: an Unmanned Ground Vehicle able to autonomously navigate through, identify, and reach areas of interest; and there recognize, localize, and manipulate work tools to perform complex manipulation tasks. The proposed contribution includes a modular software architecture where each module solves specific sub-tasks and that can be easily enlarged to satisfy new requirements. Included indoor and outdoor tests demonstrate the capability of the proposed system to autonomously detect a target object (a panel) and precisely dock in front of it while avoiding obstacles. They show it can autonomously recognize and manipulate target work tools (i.e., wrenches and valve stems) to accomplish complex tasks (i.e., use a wrench to rotate a valve stem). A specific case study is described where the proposed modular architecture lets easy switch to a semi-teleoperated mode. The paper exhaustively describes description of both the hardware and software setup of RUR53, its performance when tests at the 2017 Mohamed Bin Zayed International Robotics Challenge, and the lessons we learned when participating at this competition, where we ranked third in the Gran Challenge in collaboration with the Czech Technical University in Prague, the University of Pennsylvania, and the University of Lincoln (UK).