by Keyword: Mapt
Sala-Jarque, Julia, Gil, Vanessa, Andres-Benito, Pol, Martinez-Soria, Ines, Picon-Pages, Pol, Hernandez, Felix, Avila, Jesus, Luis Lanciego, Jose, Nuvolone, Mario, Aguzzi, Adriano, Gavin, Rosalina, Ferrer, Isidro, Antonio del Rio, Jose, (2024). The cellular prion protein does not affect tau seeding and spreading of sarkosyl-insoluble fractions from Alzheimer's disease Scientific Reports 14, 21622 
The cellular prion protein (PrPC) plays many roles in the developing and adult brain. In addition, PrPC binds to several amyloids in oligomeric and prefibrillar forms and may act as a putative receptor of abnormal misfolded protein species. The role of PrPC in tau seeding and spreading is not known. In the present study, we have inoculated well-characterized sarkosyl-insoluble fractions of sporadic Alzheimer's disease (sAD) into the brain of adult wild-type mice (Prnp(+/+)), Prnp(0/0) (ZH3 strain) mice, and mice over-expressing the secreted form of PrPC lacking their GPI anchor (Tg44 strain). Phospho-tau (ptau) seeding and spreading involving neurons and oligodendrocytes were observed three and six months after inoculation. 3Rtau and 4Rtau deposits from the host tau, as revealed by inoculating Mapt(0/0) mice and by using specific anti-mouse and anti-human tau antibodies suggest modulation of exon 10 splicing of the host mouse Mapt gene elicited by exogenous sAD-tau. However, no tau seeding and spreading differences were observed among Prnp genotypes. Our results show that PrPC does not affect tau seeding and spreading in vivo.
JTD Keywords: Alpha-synuclein, Alzheimer's disease, Amyloid-beta oligomers, Expression, Impairmen, Mapt, Mice, Paired helical filaments, Pathological tau, Prnp, Propagation, Prpc, Seeding, Spreadin, Synaptic plasticity, Tau, Tauopathies
Casamitjana, M., Pérez, M. C., Aranda, J., Montseny, E., Martin, E. X., (2010). Reliable 3D reconstruction extending pixel-level certainty measures IEEE International Conference on Fuzzy 
2010 IEEE World Congress on Computational Intelligence , IEEE (Barcelona, Spain) , 1-7
A new method for obtaining a three-dimensional volumetric reconstruction from a set of views improving the classical Shape from Silhouette method (SFS) is presented. SFS approaches can be easily accelerated through hardware and software techniques but they are very sensible to errors arising during calibration and segmentation processes so they present difficulties when dealing with real images. This paper proposes a new algorithm which uses the information about pixel segmentation uncertainty contained in each view in order to get a reliable 3D reconstruction of the scene. Aggregation of the projected uncertainties permits to classify scene's voxels by means of a decision rule but also makes it possible to create a three-dimensional confidence map of the scene. As a consequence, the regions where more information is needed can be foreseen. Sample reconstructions from real image sets are presented and evaluated.
JTD Keywords: Calibration, Image classification, Image reconstruction, Image segmentation, 3D reconstruction, Calibration process, Decision rule, Hardware technique, Pixel segmentation, Pixel-level certainty measures, Scene voxel classification, Segmentation process, Shape from silhouette method, Software technique, Three-dimensional confidence map, Three-dimensional volumetric reconstruction
