Cortical degeneration in frontotemporal lobar degeneration with TDP-43 proteinopathy caused by progranulin gene mutation

Familial frontotemporal lobar degeneration with transactive response (TAR) DNA-binding protein of 43 kDa (TDP-43) proteinopathy (FTLD-TDP) is most commonly caused by progranulin (GRN) gene mutation. To characterize cortical degeneration in these cases, changes in density of the pathology across the cortical laminae of the frontal and temporal lobe were studied in seven cases of FTLD-TDP with GRN mutation using quantitative analysis and polynomial curve fitting. In 50% of gyri studied, neuronal cytoplasmic inclusions (NCI) exhibited a peak of density in the upper cortical laminae. Most frequently, neuronal intranuclear inclusions (NII) and dystrophic neurites (DN) exhibited a density peak in lower and upper laminae, respectively, glial inclusions (GI) being distributed in low densities across all laminae. Abnormally enlarged neurons (EN) were distributed either in the lower laminae or were more uniformly distributed across the cortex. The distribution of all neurons present varied between cases and regions, but most commonly exhibited a bimodal distribution, density peaks occurring in upper and lower laminae. Vacuolation primarily affected the superficial laminae and density of glial cell nuclei increased with distance across the cortex from pia mater to white matter. The densities of the NCI, GI, NII, and DN were not spatially correlated. The laminar distribution of the pathology in GRN mutation cases was similar to previously reported sporadic cases of FTLD-TDP. Hence, pathological changes initiated by GRN mutation, and by other causes in sporadic cases, appear to follow a parallel course resulting in very similar patterns of cortical degeneration in FTLD-TDP.

Corticobasal degeneration and dementia

Corticobasal degeneration is a rare, progressive neurodegenerative disorder which significantly impairs movement. The most common initial symptom is asymmetric limb clumsiness with or without accompanying rigidity or tremor. Subsequently, the disease progresses to affect gait and there is a slow progression to influence ipsilateral arms and legs. Apraxia and dementia are the most common cortical signs. Clinical diagnosis of the disorder is difficult as the symptoms resemble those of related neurodegenerative disorders. Histopathologically, there is widespread neuronal and glial pathology including tau-immunoreactive neuronal cytoplasmic inclusions, neuropil threads, oligodendroglial inclusions, astrocytic plaques, together with abnormally enlarged ‘ballooned’ neurons. Corticobasal degeneration has affinities both with the parkinsonian syndromes including Parkinson’s disease, progressive supranuclear palsy, and multiple system atrophy and with the fronto-temporal dementias. Treatment of corticobasal degeneration involves managing and reducing the effect of symptoms.

Perturbed Proximal Point Algorithm with Nonquadratic Kernel

Let H be a real Hilbert space and T be a maximal monotone operator on H. A well-known algorithm, developed by R. T. Rockafellar [16], for solving the problem (P) ”To find x ∈ H such that 0 ∈ T x” is the proximal point algorithm. Several generalizations have been considered by several authors: introduction of a perturbation, introduction of a variable metric in the perturbed algorithm, introduction of a pseudo-metric in place of the classical regularization, . . . We summarize some of these extensions by taking simultaneously into account a pseudo-metric as regularization and a perturbation in an inexact version of the algorithm.

Differential Equations in Abstract Cones

We extend the method of quasilinearization to differential equations in abstract normal cones. Under some assumptions, corresponding monotone iterations converge to the unique solution of our problem and this convergence is superlinear or semi–superlinear

The Perturbed Generalized Tikhonov's Algorithm

We work on the research of a zero of a maximal monotone operator on a real Hilbert space. Following the recent progress made in the context of the proximal point algorithm devoted to this problem, we introduce simultaneously a variable metric and a kind of relaxation in the perturbed Tikhonov’s algorithm studied by P. Tossings. So, we are led to work in the context of the variational convergence theory.

Pathology of the dentate gyrus in neurodegenerative disease

The dentate gyrus (DG) is an important part of the hippocampal formation and is believed to be involved in a variety of brain functions including episodic and spatial memory and the exploration of novel environments. In several neurodegenerative disorders, significant pathology occurs in the DG which may be involved in the development of clinical dementia. Based on the abundance of pathological change, neurodegenerative disorders can be divided into three groups: (1) those in which high densities of neuronal cytoplasmic inclusions (NCI) are present in DG granule cells, e.g., Pick’s disease (PiD), frontotemporal lobar degeneration with TDP-43-immunoreactive inclusions (FTLD-TDP), and neuronal intermediate filament inclusion disease (NIFID), (2) those in which aggregated protein deposits are distributed throughout the hippocampal formation including the molecular layer of the DG, e.g., Alzheimer’s disease (AD), Down’s syndrome (DS), and variant Creutzfeldt-Jakob disease (vCJD), and (3) those in which in there is significantly less pathology in the DG, e.g., Parkinson’s disease dementia (PD-Dem), dementia with Lewy bodies (DLB), progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), multiple system atrophy (MSA), and sporadic CJD (sCJD). Hence, DG pathology varies significantly among disorders which could contribute to differences in clinical dementia. Pathological differences among disorders could reflect either differential vulnerability of the DG to specific molecular pathologies or variation in the degree of spread of pathological proteins into the hippocampal formation from adjacent regions.

Generalized Variational Inequalities for Upper Hemicontinuous and Demi Operators with Applications to Fixed Point Theorems in Hilbert Spaces

∗ The final version of this paper was sent to the editor when the author was supported by an ARC Small Grant of Dr. E. Tarafdar.

A Random Evolution Inclusion of Subdifferential Type in Hilbert Spaces

In this paper we study a nonlinear evolution inclusion of subdifferential type in Hilbert spaces. The perturbation term is Hausdorff continuous in the state variable and has closed but not necessarily convex values. Our result is a stochastic generalization of an existence theorem proved by Kravvaritis and Papageorgiou in [6].

Somme Ponctuelle D'operateurs Maximaux Monotones

∗ Cette recherche a été partiellement subventionnée, en ce qui concerne le premier et le dernier auteur, par la bourse OTAN CRG 960360 et pour le second auteur par l’Action Intégrée 95/0849 entre les universités de Marrakech, Rabat et Montpellier.

The Boundary Descriptors of the n-dimensional Unit Cube Subset Partitioning

* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

Comparative quantitative study of ‘signature’ pathological lesions in the hippocampus and adjacent gyri of 12 neurodegenerative disorders

The hippocampus (HC) and adjacent gyri are implicated in dementia in several neurodegenerative disorders. To compare HC pathology among disorders, densities of ‘signature’ pathological lesions were measured at a standard location in eight brain regions of 12 disorders. Principal components analysis of the data suggested that the disorders could be divided into three groups: (1) Alzheimer’s disease (AD), Down’s syndrome (DS), sporadic Creutzfeldt–Jakob disease, and variant Creutzfeldt–Jakob disease in which either β-amyloid (Aβ) or prion protein deposits were distributed in all sectors of the HC and adjacent gyri, with high densities being recorded in the parahippocampal gyrus and subiculum; (2) Pick’s disease, sporadic frontotemporal lobar degeneration with TDP-43 immunoreactive inclusions, and neuronal intermediate filament inclusion disease in which relatively high densities of neuronal cytoplasmic inclusions were present in the dentate gyrus (DG) granule cells; and (3) Parkinson’s disease dementia, dementia with Lewy bodies, progressive supranuclear palsy, corticobasal degeneration, and multiple system atrophy in which densities of signature lesions were relatively low. Variation in density of signature lesions in DG granule cells and CA1 were the most important sources of neuropathological variation among disorders. Hence, HC and adjacent gyri are differentially affected in dementia reflecting either variation in vulnerability of hippocampal neurons to specific molecular pathologies or in the spread of pathological proteins to the HC. Information regarding the distribution of pathology could ultimately help to explain variations in different cognitive domains, such as memory, observed in various disorders.

Generating More Boundary Elements of Subset Projections

Composition problem is considered for partition constrained vertex subsets of n dimensional unit cube E^n . Generating numerical characteristics of E^n subsets partitions is considered by means of the same characteristics in 1 − n dimensional unit cube, and construction of corresponding subsets is given for a special particular case. Using pairs of lower layer characteristic vectors for E^(1-n) more characteristic vectors for E^n are composed which are boundary from one side, and which take part in practical recognition of validness of a given candidate vector of partitions.

Semi-Smooth Newton Methods for the Time Optimal Control of Nonautonomous Ordinary Differential Equations

AMS Subj. Classification: 49J15, 49M15

Well-Posedness, Conditioning and Regularization of Minimization, Inclusion and Fixed-Point Problems

AMS subject classification: 65K10, 49M07, 90C25, 90C48.

Viability Kernels of Higher Order

AMS subject classification: Primary 34A60, Secondary 49K24.