Sehen, was Alzheimer nicht sah! : Demenz mit modernen bildgebenden und elektrophysiologischen Verfahren erforschen

Mit meisterhafter Präzision und einem zuverlässigen Gespür für das Außergewöhnliche seines Falles beschrieb Alois Alzheimer vor über 100 Jahren erstmals die feingeweblichen (histologischen) Veränderungen derjenigen Krankheit, die später seinen Namen tragen sollte. Gleichwohl konnte Alzheimer mithilfe des Mikroskops und der damals modernsten Färbetechniken nur wenig über den Zusammenhang zwischen den zu Lebzeiten des Patienten beobachteten Krankheitssymptomen und spezifischen Gehirnveränderungen aussagen. Heute ist zwar der histologische Befund noch immer für die zuverlässige Sicherung der Diagnose Morbus Alzheimer notwendig, aber moderne Schnittbild- sowie elektrophysiologische Verfahren erlauben es erstmals, neuroanatomische und neurofunktionelle Veränderungen zu Lebzeiten der Patienten zu erfassen. Neben ihrem unverzichtbaren Einsatz in der Ausschlussdiagnostik anderer schwerwiegender Gehirnerkrankungen wie Blutungen, Schlaganfälle und Tumore eröffnen diese Verfahren der klinischen Psychiatrie aufregende neue Forschungsperspektiven

Supersensitive PSA-Monitored neoadjuvant hormone treatment of clinically localized prostate cancer: Effects on positive margins, tumor detection and epithelial cells in bone marrow

Objective: The present study was done to investigate the effects of supersensitive PSA-controlled inductive treatment on positive margins, detection of tumor and epithelial cells in bone marrow of 101 patients with untreated and clinically localized prostatic carcinoma (cT1-3N0M0). Methods: Hormonal treatment was given until PSA (DPD Immulite(R) third-generation assay) reached 0.3 ng/ml in only 1 case. Of the 101 patients, 82 had a measurable hypoic lesion on initial transrectal ultrasound. 84% of these became smaller, 7.5% remained unchanged and 8.5% increased. Of the 101 prostatectomy specimens, 20 (20%) were margin-positive. The incidence of affected margins was relatively high (35% from 55 patients) with cT3 tumors, but almost negligible (2% from 46 patients) in cT1-2 tumor. Our pathologists, despite their great experience in evaluating hormonally treated prostates (>500 cases) and using immunohistochemical staining, were unable to detect carcinoma in 15 (15%) specimens. Whereas only 2 (4%) of the 55 cT3 specimens were without detectable tumor, this incidence rised to 28% (13 of 46 prostates) in patients with cT1-2 tumors. Of the initial 29 patients with epithelial cells in bone marrow, only 4 (14%) remained positive after controlled induction and all of them had fewer cells than before. Conclusion: Endocrine induction controlled by a supersensitive PSA assay and continued until reaching PSA nadir is highly effective in clearing surgical margins and eliminating tumor cells from bone marrow. It seems to be clearly superior to the conventional 3 months of pretreatment at least in cT1-2 tumors in respect to surgical margins and detectability of tumor in the resected prostate. A definitive statement about the value of endocrine induction can only be given by prospective randomized studies, with optimal drugs, doses and treatment time. But the conventional 3 months of pretreatment are far from exploiting the possibilities of this therapeutic option

Mild Cognitive Impairment in the Elderly is Associated with Volume Loss of the Cholinergic Basal Forebrain Region

Background Cholinergic neurons within the basal forebrain are assumed to be an early (preclinical) manifestation site of pathological changes in Alzheimer's disease (AD). Methods We used morphometric magnetic resonance imaging (MRI) to detect and quantify atrophic changes in the basal forebrain of subjects suffering from amnestic mild cognitive impairment (aMCI). Three Tesla magnetic resonance (MR) data of 26 aMCI patients, 46 cognitively normal elderly control subjects (CO), and 12 patients suffering from Alzheimer's dementia were analyzed, including segmentation and quantification of brain tissue as well as a segmentation of basal forebrain structures (substantia innominata [SI]). Results We found the volume of the SI to be significantly different between groups in that control subjects showed the largest SI volumes, followed by aMCI and AD patients. Conclusions These results are in line with the hypothesis that cell loss within the cholinergic basal forebrain regions occurs already in the early (predementia) stage of AD. In vivo quantification of these changes might be of use as a novel neuroimaging marker of cholinergic neurodegeneration in AD

Document Filtering for Long-tail Entities

Filtering relevant documents with respect to entities is an essential task in the context of knowledge base construction and maintenance. It entails processing a time-ordered stream of documents that might be relevant to an entity in order to select only those that contain vital information. State-of-the-art approaches to document filtering for popular entities are entity-dependent: they rely on and are also trained on the specifics of differentiating features for each specific entity. Moreover, these approaches tend to use so-called extrinsic information such as Wikipedia page views and related entities which is typically only available only for popular head entities. Entity-dependent approaches based on such signals are therefore ill-suited as filtering methods for long-tail entities. In this paper we propose a document filtering method for long-tail entities that is entity-independent and thus also generalizes to unseen or rarely seen entities. It is based on intrinsic features, i.e., features that are derived from the documents in which the entities are mentioned. We propose a set of features that capture informativeness, entity-saliency, and timeliness. In particular, we introduce features based on entity aspect similarities, relation patterns, and temporal expressions and combine these with standard features for document filtering. Experiments following the TREC KBA 2014 setup on a publicly available dataset show that our model is able to improve the filtering performance for long-tail entities over several baselines. Results of applying the model to unseen entities are promising, indicating that the model is able to learn the general characteristics of a vital document. The overall performance across all entities---i.e., not just long-tail entities---improves upon the state-of-the-art without depending on any entity-specific training data.Comment: CIKM2016, Proceedings of the 25th ACM International Conference on Information and Knowledge Management. 201

Feasibility and first results of a group program to increase the frequency of cognitively stimulating leisure activities in people with mild cognitive impairment (AKTIVA–MCI)

AKTIVA-MCI is a program for patients with mild cognitive impairment (MCI) that aims to enhance participation in cognitively stimulating leisure activities. Participation in cognitively stimulating activities seems to be a potential strategy for people with MCI delaying cognitive decline for a while. In total, 35 MCI patients were enrolled in the pilot study of whom 29 completed the whole program (16 female, 71.1±7.5 years; Mini Mental Status Examination score: 28±2.2). Daily activity protocols were used to measure the frequency of participation in cognitively stimulating activities during the program (12 sessions). Additional standardized psychometric tests and questionnaires were used to assess cognition, mood, and subjective memory decline. Analyses of the daily activity protocols showed that during the intervention participants increased the frequency of several cognitively stimulating leisure activities. Comparison of pre-post data indicates no changes in cognitive status, mood, and subjective memory decline. These findings indicate that the program is suitable for patients with MCI

ICA Cleaning procedure for EEG signals analysis: application to Alzheimer's disease detection

To develop systems in order to detect Alzheimer’s disease we want to use EEG signals. Available database is raw, so the first step must be to clean signals properly. We propose a new way of ICA cleaning on a database recorded from patients with Alzheimer's disease (mildAD, early stage). Two researchers visually inspected all the signals (EEG channels), and each recording's least corrupted (artefact-clean) continuous 20 sec interval were chosen for the analysis. Each trial was then decomposed using ICA. Sources were ordered using a kurtosis measure, and the researchers cleared up to seven sources per trial corresponding to artefacts (eye movements, EMG corruption, EKG, etc), using three criteria: (i) Isolated source on the scalp (only a few electrodes contribute to the source), (ii) Abnormal wave shape (drifts, eye blinks, sharp waves, etc.), (iii) Source of abnormally high amplitude (�100 �V). We then evaluated the outcome of this cleaning by means of the classification of patients using multilayer perceptron neural networks. Results are very satisfactory and performance is increased from 50.9% to 73.1% correctly classified data using ICA cleaning procedure

Associations between Changes in City and Address Specific Temperature and QT Interval - The VA Normative Aging Study

Background: The underlying mechanisms of the association between ambient temperature and cardiovascular morbidity and mortality are not well understood, particularly for daily temperature variability. We evaluated if daily mean temperature and standard deviation of temperature was associated with heart rate-corrected QT interval (QTc) duration, a marker of ventricular repolarization in a prospective cohort of older men. Methods: This longitudinal analysis included 487 older men participating in the VA Normative Aging Study with up to three visits between 2000–2008 (n = 743). We analyzed associations between QTc and moving averages (1–7, 14, 21, and 28 days) of the 24-hour mean and standard deviation of temperature as measured from a local weather monitor, and the 24-hour mean temperature estimated from a spatiotemporal prediction model, in time-varying linear mixed-effect regression. Effect modification by season, diabetes, coronary heart disease, obesity, and age was also evaluated. Results: Higher mean temperature as measured from the local monitor, and estimated from the prediction model, was associated with longer QTc at moving averages of 21 and 28 days. Increased 24-hr standard deviation of temperature was associated with longer QTc at moving averages from 4 and up to 28 days; a 1.9°C interquartile range increase in 4-day moving average standard deviation of temperature was associated with a 2.8 msec (95%CI: 0.4, 5.2) longer QTc. Associations between 24-hr standard deviation of temperature and QTc were stronger in colder months, and in participants with diabetes and coronary heart disease. Conclusion/Significance In this sample of older men, elevated mean temperature was associated with longer QTc, and increased variability of temperature was associated with longer QTc, particularly during colder months and among individuals with diabetes and coronary heart disease. These findings may offer insight of an important underlying mechanism of temperature-related cardiovascular morbidity and mortality in an older population

Residential Black Carbon Exposure and Circulating Markers of Systemic Inflammation in Elderly Males: The Normative Aging Study

Background: Traffic-related particles (TRPs) are associated with adverse cardiovascular events. The exact mechanisms are unclear, but systemic inflammatory responses likely play a role

Incremental value of biomarker combinations to predict progression of mild cognitive impairment to Alzheimer’s dementia

Background The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods We used 115 complete datasets from MCI patients of the “Dementia Competence Network”, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four- parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. Conclusion A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials