Combined Imaging Markers Dissociate Alzheimer's Disease and Frontotemporal Lobar Degeneration – An ALE Meta-Analysis

To compare and dissociate the neural correlates of Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), we combine and synthesize here recent comprehensive meta-analyses. Systematic and quantitative meta-analyses were conducted according to the QUOROM statement by calculating anatomical likelihood estimates (ALE). AD (n = 578) and the three subtypes of FTLD, frontotemporal dementia, semantic dementia (SD), and progressive non-fluent aphasia (n = 229), were compared in conjunction analyses, separately for atrophy and reductions in glucose metabolism. Atrophy coincided in the amygdala and hippocampal head in AD and the FTLD subtype SD. The other brain regions did not show any overlap between AD and FTLD subtypes for both atrophy and changes in glucose metabolism. For AD alone (n = 826), another conjunction analysis revealed a regional dissociation between atrophy and hypoperfusion/hypometabolism, whereby hypoperfusion and hypometabolism coincided in the angular/supramarginal gyrus and inferior precuneus/posterior cingulate gyrus. Our data together with other imaging studies suggest a specific dissociation of AD and FTLD if, beside atrophy, additional imaging markers in AD such as abnormally low parietal glucose utilization and perfusion are taken into account. Results support the incorporation of standardized imaging inclusion criteria into future diagnostic systems, which is crucial for early individual diagnosis and treatment in the future

Age Correction in Dementia – Matching to a Healthy Brain

In recent research, many univariate and multivariate approaches have been proposed to improve automatic classification of various dementia syndromes using imaging data. Some of these methods do not provide the possibility to integrate possible confounding variables like age into the statistical evaluation. A similar problem sometimes exists in clinical studies, as it is not always possible to match different clinical groups to each other in all confounding variables, like for example, early-onset (age<65 years) and late-onset (age≥65) patients with Alzheimer's disease (AD). Here, we propose a simple method to control for possible effects of confounding variables such as age prior to statistical evaluation of magnetic resonance imaging (MRI) data using support vector machine classification (SVM) or voxel-based morphometry (VBM). We compare SVM results for the classification of 80 AD patients and 79 healthy control subjects based on MRI data with and without prior age correction. Additionally, we compare VBM results for the comparison of three different groups of AD patients differing in age with the same group of control subjects obtained without including age as covariate, with age as covariate or with prior age correction using the proposed method. SVM classification using the proposed method resulted in higher between-group classification accuracy compared to uncorrected data. Further, applying the proposed age correction substantially improved univariate detection of disease-related grey matter atrophy using VBM in AD patients differing in age from control subjects. The results suggest that the approach proposed in this work is generally suited to control for confounding variables such as age in SVM or VBM analyses. Accordingly, the approach might improve and extend the application of these methods in clinical neurosciences

Face Masks Protect From Infection but May Impair Social Cognition in Older Adults and People With Dementia.

The coronavirus disease 2019 (COVID-19) pandemic will have a high impact on older adults and people with Alzheimer's disease and other dementias. Social cognition enables the understanding of another individual's feelings, intentions, desires and mental states, which is particularly important during the COVID-19 pandemic. To prevent further spread of the disease face masks have been recommended. Although justified for prevention of this potentially devastating disease, they partly cover the face and hamper emotion recognition and probably mindreading. As social cognition is already affected by aging and dementia, strategies must be developed to cope with these profound changes of communication. Face masking even could accelerate cognitive decline in the long run. Further studies are of uppermost importance to address face masks' impact on social cognition in aging and dementia, for instance by longitudinally investigating decline before and in the pandemic, and to design compensatory strategies. These issues are also relevant for face masking in general, such as in medical surroundings-beyond the COVID-19 pandemic

Mood Disorders Are Glial Disorders: Evidence from In Vivo Studies

It has recently been suggested that mood disorders can be characterized by glial pathology as indicated by histopathological postmortem findings. Here, we review studies investigating the glial marker S100B in serum of patients with mood disorders. This protein might act as a growth and differentiation factor. It is located in, and may actively be released by, astro- and oligodendrocytes. Studies consistently show that S100B is elevated in mood disorders; more strongly in major depressive than bipolar disorder. Successful antidepressive treatment reduces S100B in major depression whereas there is no evidence of treatment effects in mania. In contrast to the glial marker S100B, the neuronal marker protein neuron-specific enolase is unaltered. By indicating glial alterations without neuronal changes, serum S100B studies confirm specific glial pathology in mood disorders in vivo. S100B can be regarded as a potential diagnostic biomarker for mood disorders and as a biomarker for successful antidepressive treatment

Combined Evaluation of FDG-PET and MRI Improves Detection and Differentiation of Dementia

INTRODUCTION: Various biomarkers have been reported in recent literature regarding imaging abnormalities in different types of dementia. These biomarkers have helped to significantly improve early detection and also differentiation of various dementia syndromes. In this study, we systematically applied whole-brain and region-of-interest (ROI) based support vector machine classification separately and on combined information from different imaging modalities to improve the detection and differentiation of different types of dementia. METHODS: Patients with clinically diagnosed Alzheimer's disease (AD: n = 21), with frontotemporal lobar degeneration (FTLD: n = 14) and control subjects (n = 13) underwent both [F18]fluorodeoxyglucose positron emission tomography (FDG-PET) scanning and magnetic resonance imaging (MRI), together with clinical and behavioral assessment. FDG-PET and MRI data were commonly processed to get a precise overlap of all regions in both modalities. Support vector machine classification was applied with varying parameters separately for both modalities and to combined information obtained from MR and FDG-PET images. ROIs were extracted from comprehensive systematic and quantitative meta-analyses investigating both disorders. RESULTS: Using single-modality whole-brain and ROI information FDG-PET provided highest accuracy rates for both, detection and differentiation of AD and FTLD compared to structural information from MRI. The ROI-based multimodal classification, combining FDG-PET and MRI information, was highly superior to the unimodal approach and to the whole-brain pattern classification. With this method, accuracy rate of up to 92% for the differentiation of the three groups and an accuracy of 94% for the differentiation of AD and FTLD patients was obtained. CONCLUSION: Accuracy rate obtained using combined information from both imaging modalities is the highest reported up to now for differentiation of both types of dementia. Our results indicate a substantial gain in accuracy using combined FDG-PET and MRI information and suggest the incorporation of such approaches to clinical diagnosis and to differential diagnostic procedures of neurodegenerative disorders

S100B Serum Levels in Schizophrenia Are Presumably Related to Visceral Obesity and Insulin Resistance

Elevated blood levels of S100B in schizophrenia have so far been mainly attributed to glial pathology, as S100B is produced by astro- and oligodendroglial cells and is thought to act as a neurotrophic factor with effects on synaptogenesis, dopaminergic and glutamatergic neutrotransmission. However, adipocytes are another important source of S100B since the concentration of S100B in adipose tissue is as high as in nervous tissue. Insulin is downregulating S100B in adipocytes, astrocyte cultures and rat brain. As reviewed in this paper, our recent studies suggest that overweight, visceral obesity, and peripheral/cerebral insulin resistance may be pivotal for at least part of the elevated S100B serum levels in schizophrenia. In the context of this recently identified framework of metabolic disturbances accompanying S100B elevation in schizophrenia, it rather has to be attributed to systemic alterations in glucose metabolism than to be considered a surrogate marker for astrocyte-specific pathologies

Speech motor profiles in primary progressive aphasia

Purpose: Previous research on motor speech disorders (MSDs) in primary progressive aphasia (PPA) has largely focused on patients with the nonfluent/agrammatic variant of PPA (nfvPPA), with few systematic descriptions of MSDs in variants other than nfvPPA. There has also been an emphasis on studying apraxia of speech, whereas less is known about dysarthria or other forms of MSDs. This study aimed to examine the qualitative and quantitative characteristics of MSDs in a prospective sample of individuals with PPA independent of subtype. Method: We included 38 participants with a root diagnosis of PPA according to current consensus criteria, including one case with primary progressive apraxia of speech. Speech tasks comprised various speech modalities and levels of complexity. Expert raters used a novel protocol for auditory speech analyses covering all major dimensions of speech. Results: Of the participants, 47.4% presented with some form of MSD. Individual speech motor profiles varied widely with respect to the different speech dimensions. Besides apraxia of speech, we observed different dysarthria syndromes, special forms of MSDs (e.g., neurogenic stuttering), and mixed forms. Degrees of severity ranged from mild to severe. We also observed MSDs in patients whose speech and language profiles were incompatible with nfvPPA. Conclusions: The results confirm that MSDs are common in PPA and can manifest in different syndromes. The findings emphasize that future studies of MSDs in PPA should be extended to all clinical variants and should take into account the qualitative characteristics of motor speech dysfunction across speech dimensions

Multiple ionization and fragmentation dynamics of molecular iodine studied in IR-XUV pump-probe experiments

The ionization and fragmentation dynamics of iodine molecules (I-2) are traced using very intense (similar to 10(14) W cm(-2)) ultra-short (similar to 60 fs) light pulses with 87 eV photons of the Free-electron LASer at Hamburg (FLASH) in combination with a synchronized femtosecond optical laser. Within a pump-probe scheme the IR pulse initiates a molecular fragmentation and then, after an adjustable time delay, the system is exposed to an intense FEL pulse. This way we follow the creation of highly-charged molecular fragments as a function of time, and probe the dynamics of multi-photon absorption during the transition from a molecule to individual atoms