bluuebunny/crossref_metadata_2025_split huggingface dataset:
Plasma neuregulin 1 as a synaptic biomarker in Alzheimer’s disease
Authors: Vrillon Agathe , Mouton‐Liger Francois , Martinet Matthieu , Cognat Emmanuel , Hourregue Claire , Dumurgier Julien , Amar Elodie Bouaziz , Brinkmalm Ann , Blennow Kaj , Zetterberg Henrik , Hugon Jacques , Paquet Claire 
Published: June 2023

AbstractBackgroundSynaptic dysfunction is an early core feature of Alzheimer’s disease (AD), closely associated with cognitive symptoms. Neuregulin 1 (NRG1) is a growth and differentiation factor with a key role in the development and maintenance of synaptic transmission. Previous reports have shown that changes in cerebrospinal fluid (CSF) NRG1 concentration are associated with cognitive status and biomarker evidence of AD pathology. Plasma biomarkers reflecting synaptic impairment would be of great clinical interest. Our oubjective was to measure plasma NRG1 concentration in AD patients in comparison with other neurodegenerative disorders and neurological controls (NC) and to study its association with cerebrospinal fluid (CSF) core AD and synaptic biomarkers.MethodThis retrospective study enrolled 127 participants including patients with AD at mild cognitive impairment stage (AD‐MCI, n = 27) and at dementia stage (n = 35), non‐AD dementia (n = 26, Aβ‐negative), non‐AD MCI (n = 19) and neurological controls (n = 20). Plasma and CSF NRG1, as well as CSF core AD biomarkers (Aβ 42/Aβ 40 ratio, phospho‐tau and total tau), were measured using ELISA. CSF synaptic markers were measured using ELISA for GAP‐43 and neurogranin and through immunoprecipitation mass spectrometry for SNAP‐25.ResultPlasma NRG1 concentration was higher in AD‐MCI and AD dementia patients compared with neurological controls (respectively P = 0.005 and P<0.001). Plasma NRG1 differentiated AD MCI patients from neurological controls with an area under the curve of 88.3%, and AD dementia patients from NC with an area under the curve of 87.3%. Plasma NRG1 correlated with CSF NRG1 (β = 0.372, P = 0.0056, adjusted on age and sex). Plasma NRG1 was associated with AD CSF core biomarkers in the whole cohort and in Aβ‐positive patients (β = ‐0.197‐ 0.423). Plasma NRG1 correlated with CSF GAP‐43, neurogranin and SNAP‐25 (β = 0.278‐0.355). Plasma NRG1 concentration correlated inversely with MMSE in the whole cohort and in Aβ‐positive patients (all, β = ‐0.188, P = 0.038; Aβ+: β = ‐0.255, P = 0.038).ConclusionPlasma NRG1 concentration is increased in AD patients and correlates with CSF core AD and synaptic biomarkers, and cognitive status. Thus, plasma NRG1 is a promising non‐invasive biomarker to monitor synaptic impairment in AD.
Testamentary Capacity Assessment Tool (TCAT): An update report
Authors: Voskou Panagiota , Douzenis Athanasios , Economou Alexandra , Papageorgiou Sokratis G. 
Published: June 2023

AbstractBackgroundTCAT is a recently developed short instrument (15 minutes are required for its administration), with good psychometric properties, specialized for the assessment of testamentary capacity (TC) in dementia. It assesses memory, perception of financial parameters and judgment. The present study reports all studies about TCAT.MethodPubmed database as well as unpublished data by the authors of the TCAT have been used.ResultAs of now, there are no other specialized TC assessment instruments with measured psychometric properties in the scientific literature. Unpublished data on amnestic mild cognitive impairment (aMCI) performance using the TCAT show no difference of aMCI in comparison to healthy adults at any part of the tool. Another unpublished study has examined the correlation between the three parts of TCAT and the expert opinion regarding TC in patients with dementia. It has shown that Part C “financial parameters” demonstrates the highest correlation with the expert opinion. Validation and standardization of the TCAT in the Greek population is under way. The preliminary results show that age, and not educational level or gender, predicts the performance in TCAT. Validation and normative data of the TCAT in an Italian population of 323 healthy adults is provided in a recent published study showing that it is useful as an adjuvant instrument for TC assessment in the elderly.ConclusionWhile the TCAT is a useful tool, more studies are needed in different cultures, both in healthy adults and cognitively impaired adults, for its standardized use in forensic and clinical settings.
Predicting Alzheimer’s disease progression in healthy and MCI subjects using multi‐modal deep learning approach
Authors: Mirabnahrazam Ghazal , Ma Da , Beaulac Cédric , Lee Sieun , Popuri Karteek , Lee Hyunwoo , Cao Jiguo , Wang Lei , Galvin James E , Beg Mirza Faisal 
Published: June 2023

AbstractBackgroundAlzheimer’s disease (AD) is a complex disorder influenced by many factors, but it is unclear how each factor contributes to disease progression. An in‐depth examination of these factors may yield an accurate estimate of time‐to‐conversion to AD for patients at various disease stages. Recent advances in deep learning have enabled researchers to predict patient’s disease onset time by exploring the influencing factors in AD progression.MethodWe used 543 subjects with 63 features from 3 data modalities from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The following modalities were used: 1) MRI, 2) genetic and 3) DTC (Demographic, cognitive Tests and Cerebrospinal fluid). The 21 most important features were automatically selected for the three modalities.We used a Deep Learning‐based survival analysis model that extends the classic Cox regression model to predict the subjects' disease onset time. Here we re‐define the non‐AD‐progression as “survivor”, and AD‐progression as “non‐survivor”. The subjects were divided into two groups: progressive subjects (non‐survivor), who were either healthy or diagnosed with Mild Cognitive Impairment (MCI) at initial clinical visit and later developed AD, and non‐progressive subjects ("survivor”), who were either healthy or MCI at initial visit but did not develop AD later. We used 10 random sub‐samples, selecting 80% of the subjects for training and 20% for testing each time; 20% of training data was used for internal validation.ResultFigure 1 shows the estimated survival rates over 10 years. Both groups had a high survival chance at the start. The progressive group’s survival chance dropped much faster and fell below 20% by the end of the period. The non‐progressive group’s survival chance remained around 50%.Feature importance analysis is displayed in Figure 2. Eight of the top ten most important features are from the cognitive tests, demonstrating their importance in survival analysis. Amygdala and Hippocampus regions, as well as age, are also notable features.ConclusionOur study demonstrated that using powerful predictive models on multi‐modal data can improve prediction of time‐to‐conversion. This not only leads to a better understanding of AD, but also provides essential tools for practitioners who wish to follow their patients' disease progression.
Language, cognitive and neuroimaging determinants of Primary Progressive Aphasia in Hebrew Speakers, a case series
Authors: keret Ophir , Glik Amir , Friedmann Naama 
Published: June 2023

AbstractBackgroundPrimary progressive aphasias (PPA) are a group of neurocognitive disorders caused by neurodegenerative diseases and defined by progressive deterioration of language capabilities. PPA are traditionally classified into three predominant variants: nonfluent‐agrammatic, semantic, and logopenic. Emerging studies suggest an individual’s spoken language impacts the clinical presentation of PPA variants, potentially leading to misdiagnosis in languages underrepresented in research. We aimed at phenotyping PPA in native speakers of Hebrew, a Semitic language, with unique characteristics such as: under‐representation of vowels in the orthography, which makes it easier to detect various types of dyslexia, rich inflectional and derivational morphology, making it easier to identify morphosyntactic impairments, and, together with object case, making word order more flexible, enabling the examination of various syntactic deficits (e.g. in syntactic‐movement).MethodsFour native Hebrew speakers diagnosed with PPA (Mesulam 2001 criteria), aged 58‐68, complaint duration prior to assessment 10‐60 months, underwent assessment in Rabin Medical Center, Israel. Each participant underwent neurological evaluation, brain magnetic resonance imaging (MRI), and multi‐domain cognitive testing. Regional brain atrophy on T1 weighted MRI was rated with validated visual atrophy scales. All participants subsequently underwent Hebrew language evaluation using Norm‐referenced tests, assessing syntax, lexical retrieval, reading (including words and nonwords sensitive to various dyslexia types), semantic and conceptual abilities tasks, and phonology.ResultsParticipant’s presenting complaint was word finding difficulty (n = 3) and non‐fluent speech (n = 1). All participants exhibited deficits in the comprehension and production of syntactic movement including one participant with no other language deficits on formal testing and no brain atrophy. Three participants exhibited various dyslexias including morphological deficits,attentional dyslexia, vowel dyslexia, and surface dyslexia. As expected, poor scores on tests of lexical retrieval and syntax were observed in subjects with severe left anterior‐temporal and left fronto‐insular atrophy respectively.ConclusionTo our knowledge, this is the first case series of PPA in native Hebrew speakers. Errors in syntactic movement and various dyslexia types were common in all subjects suggesting they may be useful in early‐stage diagnosis. Full results (language, cognitive and neuroimaging), including additional eight cases will be presented in the AAIC conference.
Evaluating the impact of facilitated discussion series in improving dementia caregiver stress, resiliency and well‐being
Authors: Bonifas Robin P , Cohen Wendy 
Published: June 2023

AbstractBackgroundEmotional stress stemming from the complex grief associated with dementia care takes a greater toll on a family caregiver’s health than the physical effort of providing care. Finding Meaning and Hope is a 10‐week workshop for caregivers of persons with dementia, designed to promote understanding of grief and teach self‐care concepts that help mitigate stress. Each video session features Dr. Pauline Boss, author of Loving Someone Who Has Dementia: How to Find Hope While Coping with Stress and Grief, sharing self‐care strategies with real‐life caregivers, and is followed by a facilitator‐led discussion. Home practice activities help caregivers incorporate focal self‐care strategies into their daily lives. This research aimed to assess the relationship between participating in the workshops and caregiver outcomes in stress and well‐being.Methods108 caregivers, 85 percent age 60 and older, completed the workshops during 2019. Two standardized instruments were administered before and after workshop participation: the 12‐item Caregiver Self‐Assessment Questionnaire (American Medical Association, 2015) and the 11‐item Sense of Competence Questionnaire (Vernooij‐Dassen, 2008). Changes in scores were assessed using Analysis of Variance or Difference of Proportions.ResultsParticipation in more than half the sessions had a positive impact on stress management, emotional well‐being, and coping, but fewer gains were made by caregivers with health limitations and those who began the workshops with lower emotional well‐being. The workshops can be strengthened by supporting consistent session attendance and individually tailoring self‐care strategies to caregivers’ unique needs.ConclusionFamily caregivers’ mental and emotional health has been negatively impacted by the COVID‐19 pandemic (Czeisler et al. 2020). Strategies that foster caregivers’ ability to manage stress and bolster well‐being are vital in enabling them to continue care provision during a time when isolation may exacerbate the challenges of caregiving. Interventions like Finding Meaning and Hope offer a promising approach.
Associations of sleep disturbances with cognitive function and plasma Alzheimer’s biomarkers in Chinese rural‐dwelling older adults: A population‐based study
Authors: Tang Shi , Liu Rui , Wang Yongxiang , Dong Yi , Qin Yu , Ren Juan , Hou Tingting , Cong Lin , Du Yifeng , Qiu Chengxuan 
Published: June 2023

AbstractBackgroundSleep disturbances have been associated with cognitive impairment, but their associations with plasma Alzheimer’s disease (AD) biomarkers have been rarely explored. We sought to investigate the relationships of self‐reported and cardiopulmonary coupling (CPC)‐assessed sleep disturbances, cognitive function, and plasma AD biomarkers among rural‐dwelling older adults in China.MethodThis population‐based cross‐sectional study included 1987 dementia‐free individuals (age ≥60 years, 55.0% women) who participated in the CPC‐substudy as part of the baseline assessments of the MIND‐China Study; of these, 830 had data on plasma Aβ42, Aβ40, total‐tau, and neurofilament light chain (NfL) that were measured using the single molecule array (SIMOA) technology. We collected data via face‐to‐face interviews, clinical examinations, and neuropsychological test. Sleep disturbances were assessed using the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the self‐administered Berlin Questionnaire, and the ECG‐based CPC analysis. We used the neuropsychological test battery to assess memory, language, attention, and executive function. Data were analyzed using logistic and general linear regression models.ResultOf the 1987 participants, CPC‐measured total sleep time (TST) >8 hours/night (vs. 5‐8 hours) was significantly associated with a lower composite z‐score of memory (β = ‐0.080; 95% CI = ‐0.160 ‐ ‐0.001), language (‐0.114; ‐0.186 ‐ ‐0.042), attention (‐0.104; ‐0.175 ‐ ‐0.033), and executive function (‐0.117; ‐0.193 ‐ ‐0.041). Self‐reported poor sleep quality was associated with a lower composite z‐score of attention function (β = ‐0.077; 95% CI = ‐0.143 ‐ ‐0.011). Self‐reported excessive daytime sleepiness (EDS) was associated with a lower composite z‐score of memory (β = ‐0.217; 95% CI = ‐0.350 ‐ ‐0.084), language (‐0.182; ‐0.303 ‐ ‐0.061), and attention function (‐0.162; ‐0.282 ‐ ‐0.041). In the plasma biomarker subsample, CPC‐measured TST >8 hours/night was significantly associated with lower plasma Aβ42/Aβ40 ratio (β = ‐0.522; 95% CI = ‐0.764‐ ‐0.281) and higher plasma concentrations of Aβ40 (13.419; 6.515‐20.323), total‐tau (0.216; 0.071‐0.360), and NfL (0.071; 0.002‐0.140). There was no significant association between CPC‐measured apnea hypopnea index (AHI) and plasma AD biomarkers (P>0.05).ConclusionLong sleep duration and self‐reported EDS were associated with poor memory, language, and attention function among older adults, in which AD pathology and neurodegeneration may be the common pathways linking sleep disturbances with cognitive impairment.
Multi‐branch convolutional neural network for Alzheimer’s Disease versus normal control classification using PET images
Authors: Sharma Rishabh , Sibille Ludovic , Fahmi Rachid 
Published: June 2023

AbstractBackgroundBrain PET imaging techniques provide in‐vivo information about brain metabolism and the density/distribution of amyloid and tau proteins, the two hallmarks of Alzheimer’s disease (AD). Combination of such imaging biomarkers has led to improved performances of deep‐learning models designed for disease‐classification and prediction of disease‐progression. However, training such networks is often a challenge, especially when subjects have missing imaging markers at given time‐points. Such incomplete data is often excluded from the training process. We propose a “multibranch”‐convolutional‐neural‐network architecture to cope with this issue and make use of all available data for better AD vs. normal‐controls (NC) classification performance.MethodWe obtained multi‐time point ADNI FDG‐ and AV45‐PET scans corresponding to 257 NC and 222 AD subjects. N = 124 subjects had only one PET scan available at different time‐points. We designed a CNN with three training “branches”, taking as input either FGD, AV45, or a combination of the two when available (see Fig.1). In total, 1832 scans (786 singles and 523 pairs) were used as input for training. Branches are weighted differently (with 0 or 1) to control how training weights are updated. When both imaging‐biomarkers are available, each branch is fed with the appropriate input and contributes to the overall training. The overall network architecture is shown on Fig.1. For each branch, the calculated loss is multiplied by the associated weight and backpropagated through the network to update its training parameters. For comparison purposes, we independently trained a CNN with the same image pairs as above.ResultFor validation, we only used cases with both scans available to assess the performance of each branch on the same number of inputs. Classification sensitivity, specificity, accuracy, and area‐under‐the‐curve averaged over 10 folds were: (i) FDG‐branch: 93.11%, 88.88%, 91.35%, and 0.954, (ii) AV45‐branch: 96.53%, 74.87%, 90.27%, and 0.941, (iii) Multimodal‐branch: 94.43%, 86.50%, 91.56%, and 0.961, iv) Independent multi‐input CNN: 93.71%, 71.80%, 88.60%, and 0.959.ConclusionWe designed a multibranch‐CNN to handle missing data when training a multimodal classification CNN. Better classification accuracy was achieved with the multi‐input branch compared to the independently trained multi‐modal CNN. We will test our network on other type and/or number of modalities.
Validity of CSF alpha‐synuclein to predict psychosis in prodromal Alzheimer´s disease
Authors: Monge‐Argilés José Antonio , Monge‐García Sonia , Cortés‐Gómez Mariangeles , Sánchez‐Payá José , Gasparini‐Berenguer Ruth , Sáez‐Valero Javier , García‐Ayllón María‐Salud 
Published: June 2023

AbstractBackgroundThe emergence of psychotic symptoms (PS) in Alzheimer´s disease (AD) involves a poor prognosis of the illness and may be related with different genetic, personal, environmental and caregiver factors, as well as unbalances in key neural proteins. In this last group, an alteration in the alpha‐synuclein (AS) metabolism may be included. Aim: To study the diagnostic validity of AS in CSF, to predict the emergence of PS in prodromal AD patients.MethodMild cognitive impairment patients (according to Petersen 2006) from the out‐patient consultation of Alicante University General Hospital (Spain) were recruited between 2010‐2018. All the patients followed NIA‐AA 2018 criteria for AD biomarkers. At inclusion, all of them had MMSE higher than 22, Neuropsychiatric Inventory lower than 10, Lawton‐Brody scale higher than 7, IQCODE lower than 80, Barthel index higher than 95 and a follow‐up higher than 2 years. All patients were treated with anticholinesterasic drugs from the diagnostic was made. The Pittsburgh sleep quality index and the Cummings criteria for psychosis (2020) were applied and the requirement of neuroleptic drugs was necessary to consider the inclusion in the psychosis group. Core AD biomarkers and AS were measured in CSF obtained in the prodromal phase of the illness. Different comparisons were made between the groups and subgroups following the time of emergence of PS.Result130 prodromal AD were included. 50 of them (38.4%) accomplished the psychosis criteria into the 8 years follow‐up. In every comparison made between groups and subgroups, AS was the best CSF biomarker to differentiate psychotic versus non psychotic groups. The level of AS 1257 pg/mL reached at least 80% of sensitivity to differentiate between both groups. A negative predictive value of 80% was found to differentiate between groups.ConclusionThe measurement of AS in CSF is the most valid biomarker used in this study to predict the emergence of PS during the 8 years after the prodromal phase of AD. These results must be confirmed in a larger population but, in our knowledge, is the first time that a CSF biomarker shows a diagnostic validity to predict PS in prodromal AD.
A comprehensive literature search of digital health technology use in dementia: Digital tools to support dementia caregivers
Authors: Spreadbury John , Young Alexandra , Kipps Christopher 
Published: June 2023

AbstractBackgroundDementia can negatively impact the well‐being and quality of life of patients and informal caregivers. Digital self‐management tools have the potential to support those living with dementia. The aim of this review was to identify digital tools used in dementia care, investigate how they support users, and highlight pertinent clinical and psychosocial outcomes.MethodSix databases were searched (i.e. CINAHL, EMBASE, MEDLINE, PsycINFO, Web of Science, and the Cochrane Review) using free text and equivalent database‐controlled vocabulary terms.ResultTwenty‐six articles were identified reporting 21 digital tools focused mainly on caregivers ‐ thus caregivers form the focus of this review. The digital tools promoted self‐management and support through five main functions: Supporting psychoeducation and self‐help; improving competency and ability; sustaining and promoting well‐being; encouraging behaviour change and providing motivation; and facilitating contact and communication with healthcare professionals and other users. There was mixed‐to‐limited evidence to support a positive influence of digital tools on mental health, burden, quality of life, and caregiver perceived ability.ConclusionDigital health technology has the potential to support caregivers, however areas such as mental health, burden, and quality of life may be resistant to some digital interventions. It is important to understand issues around accessibility, uptake, and continued use of digital tools and their potential to be integrated within dementia care pathways and routine clinical care.