The dihydropyrimidinase-like 3 (DPYSL3) or Collapsin Response Mediator Protein 4a (CRMP4a) expression is modified in neurodegeneration and is involved in several ALS-associated pathways including axonal transport, glutamate excitotoxicity, and oxidative stress. The objective of the study was to analyze CRMP4 as a risk factor for ALS. We analyzed the DPYSL3/CRMP4 gene in French ALS patients (n = 468) and matched-controls (n = 394). We subsequently examined a variant in a Swedish population (184 SALS, 186 controls), and evaluated its functional effects on axonal growth and survival in motor neuron cell culture. The rs147541241:A>G missense mutation occurred in higher frequency among French ALS patients (odds ratio = 2.99) but the association was not confirmed in the Swedish population. In vitro expression of mutated DPYSL3 in motor neurons reduced axonal growth and accelerated cell death compared with wild type protein. Thus, the association between the rs147541241 variant and ALS was limited to the French population, highlighting the geographic particularities of genetic influences (risks, contributors). The identified variant appears to shorten motor neuron survival through a detrimental effect on axonal growth and CRMP4 could act as a key unifier in transduction pathways leading to neurodegeneration through effects on early axon development.
The main contribution of this paper is a new method for classifying document images by combining textual features extracted with the Bag of Words (BoW) technique and visual features extracted with the Bag of Visual Words (BoVW) technique. The BoVW is widely used within the computer vision community for scene classification or object recognition but few applications for the classification of entire document images have been submitted. While previous attempts have been showing disappointing results by combining visual and textual features with the Borda-count technique, we're proposing here a combination through learning approach. Experiments conducted on a 1925 document image industrial database reveal that this fusion scheme significantly improves the classification performances. Our concluding contribution deals with the choosing and tuning of the BoW and/or BoVW techniques in an industrial context.
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