Self-fields in thin superconducting tapes: implications to the thickness effect in coated conductors

Most applications of superconductors, such as power transmission lines, motors, generators, and transformers, require long cables through which large currents circulate. Impressive progress has recently been achieved in the current-carrying capability in conductors based on high-temperature superconductors. Coated conductors are likely the best examples, consisting of very good quality thin layers of YBCO superconductor grown on top of a metallic tape with some intermediate layers. However, there is an important problem for achieving large currents: a large decrease in transport critical-current density Jc when increasing film thickness has been observed in coated conductors made by all available techniques. Here, we theoretically explain the nature and the ubiquitous presence of this so-called thickness effect by analyzing the self-field created by the transport currents in the superconductor, assuming a realistic field-dependent Jc. This knowledge can help finding new ways to improve transport current in thick superconducting films.Comment: 7 pages, 3 figure

Cost-effectiveness of Alzheimer's disease CSF biomarkers and amyloid-PET in early-onset cognitive impairment diagnosis

This study aimed at determining the cost-effectiveness of amyloid-positron emission tomography (PET) compared to Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers (amyloid-?42, total-Tau and phosphorylated-Tau) for the diagnosis of AD in patients with early-onset cognitive impairment. A decision tree model using a national health care perspective was developed to compare the costs and effectiveness associated with Amyloid-PET and AD CSF biomarkers. Available evidence from the literature and primary data from Hospital Clínic de Barcelona were used to inform the model and calculate the efficiency of these diagnostic alternatives. Medical visits and diagnostic procedures were considered and reported in €2020. We calculated the incremental cost-effectiveness ratio to measure the cost per % of correct diagnoses detected and we perform one-way deterministic and probabilistic sensitivity analyses to assess the uncertainty of these results. Compared with AD CSF biomarkers, Amyloid-PET resulted in 7.40% more correctly diagnosed cases of AD, with an incremental total mean cost of €146,854.80 per 100 cases. We found a 50% of probability that Amyloid-PET was cost-effective for a willingness to pay (WTP) of €19,840.39 per correct case detected. Using a WTP of €75,000, the probability that it is cost-effective reached a maximum of 76.9%, thus leading to a conclusion that Amyloid-PET is not a cost-effective technique compared to AD CSF biomarkers, unless the funder is willing to pay a minimum of €19,840.39 to detect one more correct case. Furthermore, obtaining CSF provides simultaneous information on amyloid ? and tau biomarkers and allows other biomarkers to be analyzed at a relatively low cost.© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany

Cerebrospinal fluid biomarkers in human genetic transmissible spongiform encephalopathies

The 14-3-3 protein test has been shown to support the clinical diagnosis of sporadic Creutzfeldt-Jakob disease (CJD) when associated with an adequate clinical context, and a high differential potential for the diagnosis of sporadic CJD has been attributed to other cerebrospinal fluid (CSF) proteins such as tau protein, S100b and neuron specific enolase (NSE). So far there has been only limited information available about biochemical markers in genetic transmissible spongiform encephalopathies (gTSE), although they represent 10–15% of human TSEs. In this study, we analyzed CSF of 174 patients with gTSEs for 14-3-3 (n = 166), tau protein (n = 78), S100b (n = 46) and NSE (n = 50). Levels of brain-derived proteins in CSF varied in different forms of gTSE. Biomarkers were found positive in the majority of gCJD (81%) and insert gTSE (69%), while they were negative in most cases of fatal familial insomnia (13%) and Gerstmann-Sträussler-Scheinker syndrome (10%). Disease duration and codon 129 genotype influence the findings in a different way than in sporadic CJD

Design and validation of the 1-week memory battery for assessing episodic memory and accelerated long-term forgetting in cognitively unimpaired subjects

Subtle decline in memory is thought to arise in the preclinical phase of Alzheimer's disease (AD). However, detecting these initial cognitive difficulties cross-sectionally has been challenging, and the exact nature of the decline is still debated. Accelerated long-term forgetting (ALF) has been recently suggested as one of the earliest and most sensitive indicators of memory dysfunction in subjects at risk of developing AD. The objective of this study was to design and validate the 1-week memory battery (1WMB) for assessing episodic memory and ALF in cognitively unimpaired individuals.The 1WMB is unique in that it assesses multimodal memory and measures recall at both short delay (20 min) and at long term (1 week). Forty-five cognitively unimpaired subjects were assessed with 1WMB and standardized neuropsychological tests. Subjective cognitive decline (SCD), levels of anxiety and depression, and cognitive reserve were also measured.The tests of 1WMB showed a high internal consistency, and concurrent validity was observed with standard tests of episodic memory and executive functions. The analysis revealed a greater loss of information at 1 week compared to short-term forgetting (20 min). Performance in the 1WMB was affected by age and educational level, but was not associated with levels of anxiety and depression. Unlike standard tests, performance in the 1WMB correlated with measures of SCD.Our findings indicate that the 1WMB has good psychometric properties, and future studies are needed to explore its potential usefulness to assess cognitively unimpaired subjects at increased risk of developing AD. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Plasma levels of soluble TREM2 and neurofilament light chain in TREM2 rare variant carriers

Background: Results from recent clinical studies suggest that cerebrospinal fluid (CSF) biomarkers that are indicative of Alzheimer’s disease (AD) can be replicated in blood, e.g. amyloid-beta peptides (Aβ42 and Aβ40) and neurofilament light chain (NFL). Such data proposes that blood is a rich source of potential biomarkers reflecting central nervous system pathophysiology and should be fully explored for biomarkers that show promise in CSF. Recently, soluble fragments of the triggering receptor expressed on myeloid cells 2 (sTREM2) protein in CSF have been reported to be increased in prodromal AD and also in individuals with TREM2 rare genetic variants that increase the likelihood of developing dementia. / Methods: In this study, we measured the levels of plasma sTREM2 and plasma NFL using the MesoScale Discovery and single molecule array platforms, respectively, in 48 confirmed TREM2 rare variant carriers and 49 non-carriers. / Results: Our results indicate that there are no changes in plasma sTREM2 and NFL concentrations between TREM2 rare variant carriers and non-carriers. Furthermore, plasma sTREM2 is not different between healthy controls, mild cognitive impairment (MCI) or AD. / Conclusion: Concentrations of plasma sTREM2 do not mimic the recent changes found in CSF sTREM2

Cortical thickness modeling and variability in Alzheimer's disease and frontotemporal dementia

Alzheimer's disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC.We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14-3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity.We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability.We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.© 2023. The Author(s)

Classifying Alzheimer's disease and frontotemporal dementia using machine learning with cross-sectional and longitudinal magnetic resonance imaging data

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC

Multifocal Transcranial Direct Current Stimulation in Primary Progressive Aphasia Does Not Provide a Clinical Benefit Over Speech Therapy

Primary progressive aphasia (PPA) is a group of neurodegenerative disorders including Alzheimer's disease and frontotemporal dementia characterized by language deterioration. Transcranial direct current stimulation (tDCS) is a non-invasive intervention for brain dysfunction.To evaluate the tolerability and efficacy of tDCS combined with speech therapy in the three variants of PPA. We evaluate changes in fMRI activity in a subset of patients.Double-blinded, randomized, cross-over, and sham-controlled tDCS study. 15 patients with PPA were included. Each patient underwent two interventions: a) speech therapy + active tDCS and b) speech therapy + sham tDCS stimulation. A multifocal strategy with anodes placed in the left frontal and parietal regions was used to stimulate the entire language network. Efficacy was evaluated by comparing the results of two independent sets of neuropsychological assessments administered at baseline, immediately after the intervention, and at 1 month and 3 months after the intervention. In a subsample, fMRI scanning was performed before and after each intervention.The interventions were well tolerated. Participants in both arms showed clinical improvement, but no differences were found between active and sham tDCS interventions in any of the evaluations. There were trends toward better outcomes in the active tDCS group for semantic association and reading skills. fMRI identified an activity increase in the right frontal medial cortex and the bilateral paracingulate gyrus after the active tDCS intervention.We did not find differences between active and sham tDCS stimulation in clinical scores of language function in PPA patients

Digital biomarker-based individualized prognosis for people at risk of dementia

Background: Research investigating treatments and interventions for cognitive decline fail due to difficulties in accurately recognizing behavioral signatures in the presymptomatic stages of the disease. For this validation study, we took our previously constructed digital biomarker-based prognostic models and focused on generalizability and robustness of the models. Method: We validated prognostic models characterizing subjects using digital biomarkers in a longitudinal, multi-site, 40-month prospective study collecting data in memory clinics, general practitioner offices, and home environments. Results: Our models were able to accurately discriminate between healthy subjects and individuals at risk to progress to dementia within 3 years. The model was also able to differentiate between people with or without amyloid neuropathology and classify fast and slow cognitive decliners with a very good diagnostic performance. Conclusion: Digital biomarker prognostic models can be a useful tool to assist large-scale population screening for the early detection of cognitive impairment and patient monitoring over time