bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accuracy of automated scoring of verbal paired associates in a remote data collection context
Authors: Cormack Francesca K , Barnett Jennifer H , Dawson Monty , Taptiklis Nick 
Published: December 2020

AbstractBackgroundThe validation of remote testing methodologies has increased in relevance, given the impact of COVID‐19 on clinical trials. Verbal cognitive testing, which requires skilled raters, has not previously been feasible for remote testing. In previous research we had demonstrated that remote verbal cognitive testing using automatic speech recognition (ASR) was possible and showed the expected pattern of results. Here, we manually score responses to a verbal paired associates (VPA) test and explore the impact participant‐level demographic and technology related factors on scoring accuracy.MethodsFrom a pool of 5,742 recordings of participants aged 17–86 years, 150 were randomly selected for manual review (age 30–70, M = 52.5). Participants were all fluent English speakers, and completed the VPA test via a device‐agnostic web‐app on their own devices. We recorded participant demographics and information regarding the operating system, browser and device on which the tasks were completed. Manual scoring was completed off‐line by trained raters through the Neurovocalix system.ResultsThere was excellent agreement between the human scoring and ASR, with a Spearman correlation of 0.93 (p<0.0001) and an ICC(A,1) agreement of 1 (F(148,148) = 6951, p = <0.0001). The distribution of ASR errors was skewed, with a median of 0 and a mean of 0.97. The maximum number of scoring errors was 10, observed in two cases, where the ASR system did not detect correct responses due to very high levels of background noise or poor audio quality. We found no significant effect of age, gender, education or device on scoring errors. Key themes reported by raters as affecting the scoring accuracy were 1) slowness in responding, meaning that not the whole word was recorded, 2) the presence of significant background noise or poor audio quality 3) certain accents leading to miss‐recognition of specific words.ConclusionThese results represent a comprehensive evaluation of the accuracy of automated scoring of verbal responses from data collected in a remote context. Overall, there is excellent accuracy. These results both demonstrate the potential utility of this approach to remote data collection as well as suggesting avenues for increasing accuracy of automated scoring.
Caregivers’ limited rights to legally act on behalf of Alzheimer patients: Learning from the Brazilian experience
Authors: Gozzo Débora 
Published: December 2020

AbstractBackgroundThe Brazilian law 13.146/2015 implemented the UNO’s Convention on the Rights of Persons with Disabilities in 2016. It modified the private law rules concerning a person’s ability to legally act, and it does not acknowledge the concept of “total disability” anymore, but only “partial disability” or “restricted legal capacity” (with the exception of minors who continue to be legally incompetent). Other persons with limited intellectual or physical capacities are now legally “partially disabled”. The reason for this change of paradigm was the legislators’ aim to follow the Convention and to strengthen the principle of human dignity, one major foundation of the constitutional system. The law was certainly meant well, but it does, however, not allow any difference among the many kinds of disabilities. Whether being physical, intellectual, mental (as Alzheimer) or else, they are indiscriminately considered as one unique disability. The legislators created a problem for patients with Alzheimer: they cannot be considered totally disabled now, even if in fact they are. The (family) caregivers are now only in charge of the economic sphere of the disabled person. Thus, every aspect of personal life is legally left for the disabled (and often helpless) person to decide, whether it factually can, or not. Caring family members could not change the circumstances. However; the Supreme Court of the State of São Paulo has recently applied a wide interpretation of the law, extending caregivers’ rights to decide about the personal sphere of the patients.MethodsThe presentation will offer a brief comparative overview over the range of the problem, thus aiming to produce the followingResultsAn indiscriminate application of well‐meant rules can be counterproductive in the case of Alzheimer patients.ConclusionsThe UN Convention and national legislation should be taken from the Procrustean bed of absoluteness and instead softened and rethought in a way that caregivers can be enabled to act in the best interest of the patients.
Plasma amyloid‐β 42/40 as a predictor of cognitive decline among community‐dwelling older adults: MAPT study
Authors: Giudici Kelly V , Barreto Philipe de Souto , Li Yan , Bateman Randall J , Vellas Bruno ,   the MAPT/DSA group
Published: December 2020

AbstractBackgroundPlasma measures of amyloid‐β (Aβ) peptides recently emerged as a potential equivalent to brain positron‐emission tomography (PET) imaging and cerebrospinal fluid (CSF) measurements in determining Aβ status. Low plasma Aβ42/40 has been associated with Alzheimer’s disease. However, further studies are needed to validate its use for predicting cognitive impairment. This study aimed to investigate the associations between plasma Aβ42/40 and cognitive decline over time among community‐dwelling older adults.MethodObservational study using data of 483 subjects ≥70 years (mean age 76.9 years, SD = 4.5; 59.2% women), volunteers from the Multidomain Alzheimer Preventive Trial (MAPT), who were followed for 5 years. Plasma Aβ42 and Aβ40 were measured at 12 months for 92.8% of participants and at 24 months for the rest. Participants were classified as low Aβ42/40 (≤0.107) or normal Aβ42/40. Cognitive function was assessed at 12, 24, 36, 48 and 60 months of follow‐up, by a composite cognitive score (based on four tests); Mini Mental State Examination (MMSE); Clinical Dementia Rating (CDR) sum of boxes; Alzheimer's Disease Cooperative Study ‐ Activities of Daily Living (ADCS‐ADL). Linear mixed models were performed. Potential confounders included age, sex, education, body mass index, ApoE ε4 genotype and MAPT groups.ResultFrom the total, 33.3% (n = 161) were classified as low plasma Aβ42/40. After adjusting for potential confounders, low plasma Aβ42/40 was associated with higher decline in composite cognitive score, decline in MMSE score and with higher increase in CDR sum of boxes after 4 years, compared to the normal Aβ42/40 group. Those with low Aβ42/40 had approximately 2‐fold acceleration in outcomes evolution. Sensitivity analysis considering the 25th percentile of Aβ42/40 (≤0.103) as an alternative cutoff provided similar findings.ConclusionLow plasma Aβ42/40 was associated with higher impairment in cognitive function (measured by multiple outcomes) over time among community‐dwelling older adults. Findings points towards the use of this inexpensive measure to quickly identify people at risk of Alzheimer’s disease and other neurodegenerative diseases, over more complex and expensive measures such as PET or CSF. Further studies with long follow‐ups are needed to confirm its utility in clinical practice and public health.
Absolute quantification of tau isoforms in human brain by mass spectrometry
Authors: Zola Nathalie Kyalu Ngoie , Herinckx Gaëtan , dit Ruys Sébastien Pyr , Vertommen Didier , Rider Mark H , Hanseeuw Bernard J 
Published: December 2020

AbstractBackgroundTauopathies are neurodegenerative disorders characterized by the brain deposition of tau protein. Characterizing the biochemical alterations of tau in vivo is challenging given its low concentration in human fluids. Immunoassays can detect tau in the cerebrospinal fluid (CSF), but cannot provide a thorough characterization (isoforms, post‐translational modifications (Fig1). Mass Spectrometry (MS) allows in vivo detection with high sensitivity and absolute quantification of any biochemical characteristics of interest. We aim to characterize tau in the CSF using MS in patients using both CSF and brain samples available. We present here preliminary results on the first brain sample analysed.MethodFrozen brain samples of an AD patient (Braak stage VI) were obtained from the UCLouvain donation centre. We prepared a neocortical homogenate (200 mg of wet weight/ml) that we ultra‐centrifugated to separate sarkosyl‐soluble tau from insoluble tau aggregates (Diner et al., 2017). Sarkosyl‐soluble tau was isolated by immunoprecipitation with 0.5 to 4 µg of mouse monoclonal HJ8.7 antibody. Immunoprecipitated tau was eluted with 0.1 % formic acid, dried and digested with 250ng trypsin. Liquid Chromatography (LC)‐MS/MS analysis was performed using parallel reaction monitoring (PRM) to identify tau isoforms. Specific peptides for each isoform were targeted to ensure selective and sensitive detection. In parallel, we diluted this extract 5000 times (2µl in 10 ml) and harvested 1 ml of sample into which we spiked 300pg of recombinant isotopically labelled full‐length (2N‐4R) tau protein (15N labelling). This allowed us to detect 15N isotopologues of 2N and 4R isoforms and quantify endogenous tau via intensity ratios.ResultWe detected all tau isoforms (0N, 1N, 2N, 3R, 4R) by post‐acquisition analysis of the data with Skyline (Fig.2). We absolutely quantified isoforms 2N and 4R separately from other isoforms in our sarkosyl‐soluble protein extract using 15N‐tau and obtained 150 pg/µl of tau 2N and 390 pg/µl of tau 4R (Fig.3).ConclusionThis targeted MS analysis proved to be effective for detecting and quantifying tau isoforms in the brain of one AD patient. We will soon compare this result with CSF coming from the same patient, and test CSF and brain samples coming from patients presenting non‐AD tauopathies.
Mild disease course in cognitively impaired oldest old individuals with COVID‐19: A description of two cases
Authors: Tsuang Debby W. , Payne Sarah , Jankowski Adrienne , Shutes‐David Andrew , Ritchey Katherine 
Published: December 2020

AbstractBackgroundThe COVID‐19 pandemic has swept across the world, causing a staggering number of deaths, particularly among older individuals. The most common symptoms of COVID‐19 are fever, dry cough, and shortness of breath, but delirium has been reported in older adults, including those with preexisting neurodegenerative disorders. Some research has suggested that the role of neuropsychiatric sequelae in COVID‐19, especially delirium, has been underreported and that the lack of fever and respiratory distress in this population may exacerbate underdiagnosis and subsequent mortality. Here, we discuss the variable course of COVID‐19 by detailing the course of illness in two individuals who are age 90+ with mild COVID‐19.MethodWe conducted chart reviews and telephone interviews in two patients who were age 90+. Case 1 had an outpatient follow‐up visit via teleconferencing. Due to COVID‐19 protocols, in‐person research assessments were not completed. Both were on hospice due to underlying terminal medical conditions.ResultBoth cases are age 90+ patients with dementia who receive hospice care for multiple underlying medical comorbidities. Case 1 presented at home with a low‐grade temperature that was below the CDC COVID‐19 guidelines for fever at that time; he experienced cough, confusion, and functional decline and was admitted to a COVID‐19 unit after testing positive for the disease. His workup also included a COVID‐19 laboratory panel, which was mostly abnormal (including extremely elevated brain natriuretic peptide) but had normal WBC. He did not experience further deterioration, and 22 days later, after testing COVID‐19 negative, he was discharged to a skilled nursing facility (SNF), followed by discharge to home 15 days later. Case 2 had metastatic carcinoma and a preexisting diagnosis of probable dementia with Lewy bodies. COVID‐19 was diagnosed through all‐resident screening at his SNF. He did not exhibit respiratory symptoms or fever at that time. While nursing staff reported confusion, agitation, and restlessness, these symptoms could not be differentiated from complications related to his underlying dementia. This patient was isolated within the SNF and was not hospitalized.ConclusionThese two cases demonstrate the variability of symptom manifestation in COVID‐19 in this high‐risk population.
Multidisciplinary evaluation in cognitive behavioral sleep medicine: Leveraging behavioral neurology and sleep medicine expertise
Authors: Karageorgiou Elissaios , Sykara Konstantina , Ramirez Jeronimo Martin , Andronas Nikolaos , Mavragani Evdoxia , Mougias Michalis , Tsekou Hara , Karageorgiou Klimentini E 
Published: December 2020

AbstractBackgroundCognitive Behavioral Sleep Medicine is a rapidly growing discipline that aims at the comprehensive evaluation and treatment of people with cognitive or sleep symptoms, established on the bidirectional relationship between sleep disorders and neurodegeneration. On this basis, we established a comprehensive evaluation protocol for deep phenotyping of cognitive‐sleep syndromes, and present first results on its feasibility and novel cognitive to sleep associations.MethodWe enrolled 29 patients (age: 71.5 ± 11.7; education: 9.6 ± 2.8 years) with minor or major neurocognitive disorder due to predicted Alzheimer’s disease with various degrees of vascular comorbidity (MMSE = 26.0 ± 4.3) through the Sleep & Memory Center of the Neurological Institute of Athens. All patients underwent comprehensive clinical evaluations, including cognitive (Cognitive Behavioral Symptoms [CBS] score) and sleep questionnaires (Insomnia Severity Index [ISI]; Epworth Sleepiness Scale [ESS]), biochemical, imaging, and within‐day neuropsychological testing, whereas six patients have further completed novel sleep‐mediated neuropsychological tests, actigraphy and polysomnography. Exploratory analyses using Pearson ρ or Kendall τ, accordingly, were performed to examine associations of subjective complaints and daily functioning to objective cognitive and sleep metrics.ResultNon‐memory cognitive CBS scores were highly correlated to sleep CBS scores (ρ,τ ∼ 0.51 ‐ 0.71), as well as ISI (0.56) and ESS (0.54). Memory CBS complaints in contrast correlated more with subjective insomnia symptoms (0.72 to ISI) but not hypersomnia (‐0.15 to ESS). Additionally, the CBS total score was associated to sleep‐mediated 9‐item recall (0.81) and to sleep‐mediated phonemic fluency (‐0.55), an association also noted between ESS to sleep‐mediated 9‐item recall (0.71). Of note, subjective cognitive and sleep complaints were not well correlated to within‐day neuropsychological testing (e.g., 0.13 ‐ 0.36 to MMSE). Patients who underwent actigraphy and polysomnography tolerated all procedures, and those diagnosed with sleep apnea or insomnia are effectively pursuing CPAP treatment and Cognitive Behavioral Therapy for Insomnia respectively.ConclusionComprehensive evaluation of sleep and cognitive symptoms is feasible in patients with neurocognitive disorders and allows for deep phenotyping of neurodegenerative diseases. Finally, sleep‐mediated cognitive tests seem to be more sensitive than within‐day tests in reflecting real‐life symptoms, highlighting their potential utility.
A deep CNN‐based approach for predicting MCI to AD conversion
Authors: Casti Paola , Giovannetti Antonio , Susi Gianluca , Mencattini Arianna , Pusil Sandra Angelica , García María Eugenia López , Natale Corrado Di , Martinelli Eugenio 
Published: December 2020

AbstractBackgroundDeep convolutional neural networks (CNNs) have demonstrated a considerable ability to decode various biomedical signals, including 2D and 3D neuroimaging data. Magnetoencephalography‐based functional connectivity (MEG‐FC) is proven to be a useful tool in predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD), since early signs of AD may be hidden in the way neuronal activity is spatially distributed and coordinated among different brain regions. In the present work, we propose a deep learning approach for the early diagnosis of AD, able to capture the electrophysiological anomalies occurring before the conversion by exploit an image‐based coding of MEG‐FC data. The proposed approach has been tested on a set of resting‐state MEG recordings, from a longitudinal study (24 months between 2 MEG scans for each subject) involving 54 participants: 27 'progressive' patients (i.e., MCI at the time of the 1st scan converted to AD at the time of the 2nd scan), and 27 'static' patients (i.e., MCI at the time of the 1st scan remained MCI at the time of the 2nd scan).MethodMEG and MRI data have been gathered from the 54 patients using an Elekta Vectorview system and a General Electric 1.5T MRI scanner, respectively. Source reconstruction was performed with LCMV beamformer. The obtained neural MEG sources were anatomically parcellated into 90 ROIs according to the AAL atlas. Considering the signals stemming from the 90 ROIs we extracted the MEG‐FC measures (PLV and COR), for different frequency bands [Hz]: θ(4‐8), α(8‐12), β(12‐30), and γ(30‐55). MEG‐FC has been then coded into image‐based representations and hierarchically decomposed by means of the CNN layers of 'AlexNet'. Finally, different classification techniques have been tested as predictive modules.ResultWith the proposed approach we obtained an accuracy of 0.9 in discriminating ‘static’ from ‘progressive’ patients using MEG‐FC data from the first scan. The best classification results have been obtained using the Linear Discriminant Analysis and Support Vector Machine techniques.ConclusionThe classification of FC profiles mediated by hierarchical CNNs decomposition is a promising method for detecting the early neurophysiological anomalies characterizing the progression to AD.
Care for you at home
Authors: Patel Neela K , Davila Angelica , de Erausquin Gabriel A , Seshadri Sudha 
Published: December 2020

AbstractBackgroundClinical outcomes for older adults are often suboptimal because of frequent transitions among clinical settings, numerous specialists and lack of coordination of care, resulting in higher utilization and costs of care. The CARIÑO (Spanish for fondness, affection, tenderness, and love) Approach represents a highly complex set of related activities that can occur alone or be integrated to meet the patients’ needs. This approach, developed in the process of transformation into a patient centered medical home (PCMH), avoids “silos” of care and facilitates shifting to patient‐ and family‐centered care that results in patient‐driven, value‐based care and improved outcomes. Relationship building is intentional and continuous. The elements of this approach are as follows: Comprehensive, coordinated, compassionate care across various clinical settings that meets the older adults’ needs beyond the office walls; Advocating for patients and families by collaborating and maintaining relationships with other clinicians and health care partners; Respecting what matters most to your older patients (e.g., meals, mobility, money, and medicines5); Intentional activities and processes in your practice that are specific to meet the needs of older adults; Nurtured relationships with families, social service agencies, and community partners; Older adults are wise and know what they want: Listen to what they say (CARINO). Under CARINO, all coordination and relationship building with patients, caregivers, and all health care providers occurs at the clinic. CARIÑO en Su Casa takes the approach one step further, taking it into patient homes. The CARIÑO en Su Casa approach recognizes the unique needs of elderly patients that are often overlooked, particularly of underserved Hispanic elderly who lack resources such as transportation or insurance, and for whom barriers such as language and communication, and understanding how to navigate a complex health system are very significant. Such health disparities and issues with trust building and relationship building are prominent in underserved Hispanic groups in south Texas. Therefore, establishing relationships with underserved communities, as achieved by the CARIÑO approach, is crucial to improving clinical outcomes and advancing research in dementia care.
Role of sex and diet in hypothalamic disturbances in wild‐type mice and the 3xTg‐AD mouse model of familial Alzheimer’s disease
Authors: Robison Lisa S , Gannon Olivia J , Salinero Abigail E , Thomas Melissa A , Zuloaga Kristen L 
Published: December 2020

AbstractBackgroundHypothalamic dysfunction occurs early in the clinical course of Alzheimer’s disease (AD), likely contributing to disturbances in feeding behavior and metabolic function that are often observable years prior to the onset of cognitive symptoms. Late‐life weight loss and low BMI are associated with increased risk of dementia and faster progression of disease. However, high fat diet and metabolic disease (e.g. obesity, type 2 diabetes), particularly in mid‐life, are associated with increased risk of AD, as well as exacerbated AD pathology and behavioral deficits in animal models. In the current study, we explored possible relationships between hypothalamic function, diet/metabolic status, and AD. Considering the sex bias in AD, with women representing two‐thirds of AD patients, we sought to determine whether these relationships may vary by sex.MethodsWT and 3xTg‐AD male and female mice were fed a control (10% fat) or high fat (HF; 60% diet) diet from ∼3‐7 months of age, then tested for metabolic and hypothalamic disturbances.ResultsOn control diet, male 3xTg‐AD mice displayed increased expression of genes indicative of inflammation in the hypothalamus, including Iba1 (+34%), GFAP (+53%), TNF‐α (+46%) and IL‐1β (∼6‐fold increase) compared to WT. Male 3xTg‐AD mice on control diet also model what is seen clinically in AD in terms of metabolic disturbances (decreased body weight, reduced fat mass, hypoleptinemia). In contrast, female 3xTg‐AD mice on control diet displayed metabolic disturbances opposite that of 3xTg‐AD males (increased body and fat mass, impaired glucose tolerance). HF diet resulted in expected metabolic alterations across groups (increased body and fat mass; glucose intolerance; increased plasma insulin and leptin, decreased ghrelin), though HF diet alone did not alter hypothalamic expression of inflammatory markers in WT mice, nor did it exacerbate hypothalamic inflammation in 3xTg‐AD males. HF diet resulted in the greatest metabolic disturbances in 3xTg‐AD females, in addition to markedly increased hypothalamic expression of GFAP and IL‐1β (+99% and ∼5‐fold increase, respectively, vs. WT control females).ConclusionsThese findings provide further evidence for the roles of hypothalamic and metabolic dysfunction in AD, which in the 3xTg‐AD mouse model appears to be dependent on both sex and diet.