Abstract
Background
Locating technologies are a subtype of assistive technology that aim to support persons with dementia by helping manage spatial orientation impairments and provide aid to care ...partners by intervening when necessary. Although a variety of locating devices are commercially available, their adoption has remained low in the past years. Several studies have explored barriers to the adoption of assistive technologies from the perspective of professional stakeholders, but in-depth explorations for locating technologies are sparse. Additionally, the inputs of business professionals are lacking. The aim of this study was to expand knowledge on barriers to the adoption of locating technologies from a multi-stakeholder professional perspective, and to explore strategies to optimize adoption.
Methods
In total, 22 professionals working in business (
n
= 7), healthcare (
n
= 6) and research (
n
= 9) fields related to gerontology and gerontechnology participated in our focus group study. Perceptions on the value of using locating technologies for dementia care, barriers to their adoption, as well as salient services and information dissemination strategies were explored. After verbatim transcription, transcripts were analysed following an inductive data-driven content analysis approach in MAXQDA.
Results
Six key adoption barriers centering on: (1) awareness-, (2) technological-, (3) product characteristic- and (4) capital investment-based limitations, (5) unclear benefits, as well as (6) ethical concerns emerged. The interplay between barriers was high. Five core themes on services and information dissemination strategies centering on: (1) digital autonomy support, (2) emergency support, (3) information dissemination actors, (4) product acquisition, and (5) product advertising were extracted.
Conclusions
Our study with interdisciplinary stakeholders expands knowledge on barriers to the adoption of locating technologies for dementia care, and reinforces recommendations that an interdisciplinary strategy is needed to optimize adoption. Also, our findings show that focusing on services to increase digital autonomy and on information dissemination strategies has been largely overlooked and may be particularly effective.
Abstract One important target in the treatment of major depressive disorder (MDD) is the serotonin (5-hydroxytryptamine, 5-HT) system. Selective serotonin reuptake inhibitors (SSRI) are used to treat ...MDD. Yet, the mode of action of these drugs is not completely understood. There is evolving evidence for a role of glutamate in mood disorder and its signaling. Astrocytes are involved in glutamate metabolism and play an active role in memory processing but their role in mood disorders is still largely unknown. A modulation of astrocytic signaling by SSRIs or 5-HT has not been investigated up to now. We investigated astrocytic calcium signaling with the calcium indicator dye Fluo-4. Using a confocal microscope, we imaged astrocytes in the medial prefrontal cortex of acute mouse brain slices after the application of the SSRIs citalopram and fluoxetine. In the same way, we studied the effects of serotonin and the modulation of this signaling by glutamate in astrocytes. We found that astrocyte calcium signaling can be elicited by 5-HT. Also, the SSRIs citalopram and fluoxetine induce calcium signals in about 1/3 of all astrocytes, even when neuronal signal propagation is inhibited. Astrocytic responses to 5-HT have a unique pattern and they could mostly not be evoked twice. We determined that glutamate is a substance that can interfere with 5-HT-induced calcium signals in astrocytes since after stimulation by glutamate, astrocytes did not show a response to 5-HT. Astrocytic calcium signaling is elicited by SSRIs and 5-HT. They may serve as integrators, linking the serotonergic and glutamatergic signaling pathways.
Local governments are highly relevant for the just-starting socio-ecological transformation. Living up to this role requires new or adapted forms of governance. The German case provides a vivid ...example of how the UN Sustainable Development Goals (SDGs) provide a useful framework for this transformation. In our policy-oriented contribution, we focus on the question whether the SDGs themselves are innovation drivers in local sustainability governance. We motivate this idea with the theoretical framework of public sector innovation and provide comprehensive examples of the most prevalent current approaches to SDG-related innovations at the German local government level, covering local government sustainability reporting, strategies, budgets, and financing. Our central finding is that a small group of early-innovating German local governments has already begun to govern sustainability with the help of SDG-driven innovations and that this became possible because of publicly funded support projects and accessible pre-defined localised SDGs.
While some individuals age without pathological memory impairments, others develop age‐associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, ...they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study, we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3‐microRNA signature that reflects key processes linked to neural homeostasis and inform about cognitive status. We furthermore provide evidence that expression changes in this signature represent multiple mechanisms deregulated in the aging and diseased brain and are a suitable target for RNA therapeutics.
SYNOPSIS
Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation.
Circulating microRNAs are linked to cognitive function in young and healthy humans.
A circulating 3‐microRNA signature is identified using a longitudinal mouse model of age‐associated memory decline.
The expression of the 3‐microRNA signature is increased in patients with mild cognitive impairment (MCI) and is associated with future conversion from MCI to AD.
Targeting all 3‐ microRNAs using anti‐miRs ameliorates cognitive decline in AD mice.
Alzheimer’s disease (AD) is usually diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. This study aimed to identify a minimally invasive biomarker that can help to identify individuals at risk for cognitive decline before clinical manifestation.
Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer's disease (AD). Current research is focusing on a refined assessment of specific SCD features ...associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers.
We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers.
Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181.
Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.
Introduction
Apolipoprotein E (apoE) is a carrier for brain lipids and the most important genetic risk factor for Alzheimer's disease (AD). ApoE binds the receptor sortilin, which mediates uptake of ...apoE‐bound cargo into neurons. The significance of this uptake route for brain lipid homeostasis and AD risk seen with apoE4, but not apoE3, remains unresolved.
Methods
Combining neurolipidomics in patient specimens with functional studies in mouse models, we interrogated apoE isoform–specific functions for sortilin in brain lipid metabolism and AD.
Results
Sortilin directs the uptake and conversion of polyunsaturated fatty acids into endocannabinoids, lipid‐based neurotransmitters that act through nuclear receptors to sustain neuroprotective gene expression in the brain. This sortilin function requires apoE3, but is disrupted by binding of apoE4, compromising neuronal endocannabinoid metabolism and action.
Discussion
We uncovered the significance of neuronal apoE receptor sortilin in facilitating neuroprotective actions of brain lipids, and its relevance for AD risk seen with apoE4.
Participation in multimodal leisure activities, such as playing a musical instrument, may be protective against brain aging and dementia in older adults (OA). Potential neuroprotective correlates ...underlying musical activity remain unclear.
This cross-sectional study investigated the association between lifetime musical activity and resting-state functional connectivity (RSFC) in three higher-order brain networks: the Default Mode, Fronto-Parietal, and Salience networks.
We assessed 130 cognitively unimpaired participants (≥ 60 years) from the baseline cohort of the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study. Lifetime musical activity was operationalized by the self-reported participation in musical instrument playing across early, middle, and late life stages using the Lifetime of Experiences Questionnaire (LEQ). Participants who reported musical activity during all life stages (n = 65) were compared to controls who were matched on demographic and reserve characteristics (including education, intelligence, socioeconomic status, self-reported physical activity, age, and sex) and never played a musical instrument (n = 65) in local (seed-to-voxel) and global (within-network and between-network) RSFC patterns using pre-specified network seeds.
Older participants with lifetime musical activity showed significantly higher local RSFC between the medial prefrontal cortex (Default Mode Network seed) and temporal as well as frontal regions, namely the right temporal pole and the right precentral gyrus extending into the superior frontal gyrus, compared to matched controls. There were no significant group differences in global RSFC within or between the three networks.
We show that playing a musical instrument during life relates to higher RSFC of the medial prefrontal cortex with distant brain regions involved in higher-order cognitive and motor processes. Preserved or enhanced functional connectivity could potentially contribute to better brain health and resilience in OA with a history in musical activity.
German Clinical Trials Register (DRKS00007966, 04/05/2015).
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Background
Age-associated deterioration of the immune system contributes to a chronic low-grade inflammatory state known as “inflammaging” and is implicated in the pathogenesis of late-onset ...Alzheimer's disease (LOAD). Whether changes in the tissue environment caused by circulatory factors associated with aging may alter the innate immune response is unknown. Monocyte-derived macrophages (Mo-MФs) infiltrating the brain alongside microglia are postulated to play a modulatory role in LOAD and both express triggering receptor expressed on myeloid cells 2 (TREM2). Apolipoprotein E (APOE) acts as a ligand for TREM2, and their role in amyloid beta (Aβ) clearance highlights their importance in LOAD. However, the influence of the patient's own milieu (autologous serum) on the synthesis of TREM2 and APOE in infiltrating macrophages remains unknown.
Objectives
To functionally assess patient-specific TREM2 and APOE synthesis, we designed a personalized assay based on Mo-MФs using monocytes from LOAD patients and matched controls (CO). We assessed the influence of each participant’s own milieu, by examining the effect of short- (1 day) and long- (10 days) term differentiation of the cells in the presence of the donor´s autologous serum (AS) into M1-, M2- or M0-macrophages. Additionally, sex differences and Aβ-uptake ability in short- and long-term differentiated Mo-MФs were assessed.
Results
We showed a time-dependent increase in TREM2 and APOE protein levels in LOAD- and CO-derived cells. While AS did not differentially modulate TREM2 compared to standard fetal calf serum (FCS), AS decreased APOE levels in M2 macrophages but increased levels in M1 macrophages. Interestingly, higher levels of TREM2 and lower levels of APOE were detected in female- than in male- LOAD patients. Finally, we report decreased Aβ-uptake in long-term differentiated CO- and LOAD-derived cells, particularly in APOEε4(+) carriers.
Conclusions
We demonstrate for the first time the suitability of a personalized Mo-MФ cell culture-based assay for studying functional TREM2 and APOE synthesis in a patient's own aged milieu. Our strategy may thus provide a useful tool for future research on diagnostic and therapeutic aspects of personalized medicine.
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-beta
(Aβ42), amyloid-beta
(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.
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%.
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.
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.
Although convolutional neural networks (CNNs) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet ...applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap as they allow the visualization of key input image features that drive the decision of the model. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge.
We trained a CNN for the detection of AD in N = 663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including in total N = 1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps, thereby allowing intuitive model inspection.
Across the three independent datasets, group separation showed high accuracy for AD dementia versus controls (AUC ≥ 0.91) and moderate accuracy for amnestic MCI versus controls (AUC ≈ 0.74). Relevance maps indicated that hippocampal atrophy was considered the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r ≈ -0.86, p < 0.001).
The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels. The high hippocampus relevance scores as well as the high performance achieved in independent samples support the validity of the CNN models in the detection of AD-related MRI abnormalities. The presented data-driven and hypothesis-free CNN modeling approach might provide a useful tool to automatically derive discriminative features for complex diagnostic tasks where clear clinical criteria are still missing, for instance for the differential diagnosis between various types of dementia.
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