Cognitive prognosis of acquired brain injury patients using machine learning techniques

The cognitive prognosis of acquired brain injury (ABI) patients is a valuable tool for an improved and personalized treatment. In this paper, we explore the task of automatic cognitive prognosis of ABI patients via machine learning techniques. Based on a set of pre-treatment assessments, distinct classifiers are trained to predict whether the patient will improve in one or any of three cognitive areas: attention, memory, and executive functioning. Results show that variables such as the age at the moment of the injury, the patient's etiology, or the neuropsychological evaluation scores obtained before the treatment are relevant for prognosis and easily yield statistically significant accuracies. Additionally, the prognostic relevance of these and other variables is studied by means of standard feature selection methodologies. The outputs of the present paper add to the discussion on current cognitive rehabilitation practices and push towards the exploitation of existing technologies for improving medical evaluations and treatments.We thank all the patients and staff from Institut Guttmann who cooperated in data collection. This work has been partially funded by TIN-2012-38450-C03-03 from the Spanish Government (all authors), JAEDOC069/2010 from Consejo Superior de Investigaciones Cientıficas (J.S.), and 2009-SGR-1434 from Generalitat de CatalunyaPeer Reviewe

La geometria del còdex 80 (s. XII) de la catedral de Tortosa

The geometry in codex 80 of the Capitular Archive has traditionally been understood as a complete text and attributed to Gerbert of Aurillac (c. 940-1003). From a new reading of the text, we can say that it is a miscellaneous writing about geometry, composed of three independent parts: one containing the Geometria Incerti Auctoris apocryphical by Gerbert of Aurillac (c. 940-1003); another one is a fragment of De Nuptiis Philologiae et Mercurii by Martianus Capella (fl . 430) from Ergasticis Schematibus of Book VII of the Geometry; and finally there is a gloss to the Elementa by Euclides (c. 325-c. 265 bC.) by Al-Ḥajjāj ibn Yūsuf ibn Maṭar (786-833). The interpretation of the geometrical propositions provides knowledge about the indirect measure of places which are inaccessible using medieval instrumental, the astrolabe, mirrors, cane and squares.[ct] La geometria del còdex 80 de l’Arxiu Capitular de Tortosa ha estat tradicionalment atribuïda, com un text únic, a Gerbert d’Orlhac (c. 940-1003). Una nova lectura del text ens permet assegurar que es tracta d’un text de caràcter miscel·lani de geometria, compost per tres textos independents: una part pertany a la Geometria Incerti Auctoris apòcrifa de Gerbert d’Orlhac; una altra, al fragment De Nuptiis Philologiae et Mercurii de Marcià Capella (fl . 430) Ergasticis Schematibus, del llibre VII de la Geometria; i, finalment, s’hi llegeix una glossa als Elementa d’Euclides (c. 325-c. 265 aC.) d’Al-Ḥajjāj ibn Yūsuf ibn Maṭar (786-833). La interpretació de les proposicions de la geometria dóna el coneixement de la mesura indirecta de llocs als quals no es pot accedir amb l’instrumental medieval, és a dir, amb astrolabi, miralls, bastons i escaires

A deletion at Adamts9-magi1 Locus is associated with psoriatic arthritis risk

Objective: Copy number variants (CNVs) have been associated with the risk to develop multiple autoimmune diseases. Our objective was to identify CNVs associated with the risk to develop psoriatic arthritis (PsA) using a genome-wide analysis approach. Methods: A total of 835 patients with PsA and 1498 healthy controls were genotyped for CNVs using the Illumina HumanHap610 BeadChip genotyping platform. Genomic CNVs were characterised using CNstream analysis software and analysed for association using the χ2 test. The most significant genomic CNV associations with PsA risk were independently tested in a validation sample of 1133 patients with PsA and 1831 healthy controls. In order to test for the specificity of the variants with PsA aetiology, we also analysed the association to a cohort of 822 patients with purely cutaneous psoriasis (PsC). Results: A total of 165 common CNVs were identified in the genome-wide analysis. We found a highly significant association of an intergenic deletion between ADAMTS9 and MAGI1 genes on chromosome 3p14.1 (p=0.00014). Using the independent patient and control cohort, we validated the association between ADAMTS9-MAGI1 deletion and PsA risk (p=0.032). Using next-generation sequencing, we characterised the 26 kb associated deletion. Finally, analysing the PsC cohort we found a lower frequency of the deletion compared with the PsA cohort (p=0.0088) and a similar frequency to that of healthy controls (p>0.3). Conclusions: The present genome-wide scan for CNVs associated with PsA risk has identified a new deletion associated with disease risk and which is also differential from PsC risk