Local readout enhancement for detuned signal-recycling interferometers

Motivated by the optical-bar scheme of Braginsky, Gorodetsky and Khalili, we propose to add to a high power detuned signal-recycling interferometer a local readout scheme which measures the motion of the arm-cavity front mirror. At low frequencies this mirror moves together with the arm-cavity end mirror, under the influence of gravitational waves. This scheme improves the low-frequency quantum-noise-limited sensitivity of optical-spring interferometers significantly and can be considered as a incorporation of the optical-bar scheme into currently planned second-generation interferometers. On the other hand it can be regarded as an extension of the optical bar scheme. Taking compact-binary inspiral signals as an example, we illustrate how this scheme can be used to improve the sensitivity of the planned Advanced LIGO interferometer, in various scenarios, using a realistic classical-noise budget. We also discuss how this scheme can be implemented in Advanced LIGO with relative ease

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

Application of Benchtop-magnetic resonance imaging in a nude mouse tumor model

<p>Abstract</p> <p>Background</p> <p>MRI plays a key role in the preclinical development of new drugs, diagnostics and their delivery systems. However, very high installation and running costs of existing superconducting MRI machines limit the spread of MRI. The new method of Benchtop-MRI (BT-MRI) has the potential to overcome this limitation due to much lower installation and almost no running costs. However, due to the low field strength and decreased magnet homogeneity it is questionable, whether BT-MRI can achieve sufficient image quality to provide useful information for preclinical in vivo studies. It was the aim of the current study to explore the potential of BT-MRI on tumor models in mice.</p> <p>Methods</p> <p>We used a prototype of an in vivo BT-MRI apparatus to visualise organs and tumors and to analyse tumor progression in nude mouse xenograft models of human testicular germ cell tumor and colon carcinoma.</p> <p>Results</p> <p>Subcutaneous xenografts were easily identified as relative hypointense areas in transaxial slices of NMR images. Monitoring of tumor progression evaluated by pixel extension analyses based on NMR images correlated with increasing tumor volume calculated by calliper measurement. Gd-BOPTA contrast agent injection resulted in a better differentiation between parts of the urinary tissues and organs due to fast elimination of the agent via kidneys. In addition, interior structuring of tumors could be observed. A strong contrast enhancement within a tumor was associated with a central necrotic/fibrotic area.</p> <p>Conclusions</p> <p>BT-MRI provides satisfactory image quality to visualize organs and tumors and to monitor tumor progression and structure in mouse models.</p

Depth of Encoding Through Observed Gestures in Foreign Language Word Learning

Word learning is basic to foreign language acquisition, however time consuming and not always successful. Empirical studies have shown that traditional (visual) word learning can be enhanced by gestures. The gesture benefit has been attributed to depth of encoding. Gestures can lead to depth of encoding because they trigger semantic processing and sensorimotor enrichment of the novel word. However, the neural underpinning of depth of encoding is still unclear. Here, we combined an fMRI and a behavioral study to investigate word encoding online. In the scanner, participants encoded 30 novel words of an artificial language created for experimental purposes and their translation into the subjects\u2019 native language. Participants encoded the words three times: visually, audiovisually, and by additionally observing semantically related gestures performed by an actress. Hemodynamic activity during word encoding revealed the recruitment of cortical areas involved in stimulus processing. In this study, depth of encoding can be spelt out in terms of sensorimotor brain networks that grow larger the more sensory modalities are linked to the novel word. Word retention outside the scanner documented a positive effect of gestures in a free recall test in the short term

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

Correlation between weather and incidence of selected ophthalmological diagnoses: a database analysis

Purpose: Our aim was to correlate the overall patient volume and the incidence of several ophthalmological diseases in our emergency department with weather data. Patients and methods: For data analysis, we used our clinical data warehouse and weather data. We investigated the weekly overall patient volume and the average weekly incidence of all encoded diagnoses of "conjunctivitis", "foreign body", "acute iridocyclitis", and "corneal abrasion". A Spearman's correlation was performed to link these data with the weekly average sunshine duration, temperature, and wind speed. Results: We noticed increased patient volume in correlation with increasing sunshine duration and higher temperature. Moreover, we found a positive correlation between the weekly incidences of conjunctivitis and of foreign body and weather data. Conclusion: The results of this data analysis reveal the possible influence of external conditions on the health of a population and can be used for weather-dependent resource allocation

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