A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations

Metabolic shift underlies recovery in reversible infantile respiratory chain deficiency

Reversible infantile respiratory chain deficiency (RIRCD) is a rare mitochondrial myopathy leading to severe metabolic disturbances in infants, which recover spontaneously after 6-months of age. RIRCD is associated with the homoplasmic m.14674T>C mitochondrial DNA mutation; however, only ~ 1/100 carriers develop the disease. We studied 27 affected and 15 unaffected individuals from 19 families and found additional heterozygous mutations in nuclear genes interacting with mt-tRNAGlu including EARS2 and TRMU in the majority of affected individuals, but not in healthy carriers of m.14674T>C, supporting a digenic inheritance. Our transcriptomic and proteomic analysis of patient muscle suggests a stepwise mechanism where first, the integrated stress response associated with increased FGF21 and GDF15 expression enhances the metabolism modulated by serine biosynthesis, one carbon metabolism, TCA lipid oxidation and amino acid availability, while in the second step mTOR activation leads to increased mitochondrial biogenesis. Our data suggest that the spontaneous recovery in infants with digenic mutations may be modulated by the above described changes. Similar mechanisms may explain the variable penetrance and tissue specificity of other mtDNA mutations and highlight the potential role of amino acids in improving mitochondrial disease

Caspase deficiency alters the murine gut microbiome

Caspases are aspartate-specific cysteine proteases that have an essential role in apoptosis and inflammation, and contribute to the maintenance of homeostasis in the intestine. These facts, together with the knowledge that caspases are implicated in host-microbe crosstalk, prompted us to investigate the effect of caspase (Casp)1, -3 and -7 deficiency on the composition of the murine gut microbiota. We observed significant changes in the abundance of the Firmicutes and Bacteroidetes phyla, in particular the Lachnospiraceae, Porphyromonodaceae and Prevotellacea families, when comparing Casp-1, -7 and -3 knockout mice with wild-type mice. Our data point toward an intricate relationship between these caspases and the composition of the murine gut microflora

Search for new particles in events with one lepton and missing transverse momentum in pp collisions at √s = 8 TeV with the ATLAS detector

This paper presents a search for new particles in events with one lepton (electron or muon) and missing transverse momentum using 20.3 fb−¹ of proton-proton collision data at √s=8 TeV recorded by the ATLAS experiment at the Large Hadron Collider. No significant excess beyond Standard Model expectations is observed. A W′ with Sequential Standard Model couplings is excluded at the 95% confidence level for masses up to 3.24 TeV. Excited chiral bosons (W*) with equivalent coupling strengths are excluded for masses up to 3.21 TeV. In the framework of an effective field theory limits are also set on the dark matter-nucleon scattering cross-section as well as the mass scale M* of the unknown mediating interaction for dark matter pair production in association with a leptonically decaying W

Computation, Cybernetics and the Law at the Origins of Legal Informatics

The present contribution aims to address the ways in which legal phi- losophy approached and conceptualised the emergence of information technologies between the 1960s and 1970s. We will do that by examining the contributions of four thinkers, coming from different philosophical and ideological backgrounds: Vittorio Frosini, Mario Losano, Luigi Lombardi Vallauri and Renato Borruso. These authors look into the evolution of law and technology from different perspectives that are representative of different approaches to legal theory: the evolutions of ide- alism (Frosini), analytic philosophy combined with positivism (Losano), anti-positivism in combination with ethical/axiological inquiry (Lombardi Vallauri), as well as the more practical policy-oriented approach of legal practitioners (Borruso)