bluuebunny/crossref_metadata_2025_split huggingface dataset:
Support‐staging model for caregivers of adults with intellectual disability affected by dementia
Authors: Jokinen Nancy , Service Kathryn , Marsack‐Topolewski Christina , Janicki Matthew 
Published: December 2020

AbstractBackgroundAdults with intellectual disability (ID) and dementia are a sub‐population of persons who are often un‐ or underserved. Most adults with ID are integrated within the general community (living autonomously, or in apartments/group residences); but significant numbers also reside with their families, particularly adults with Down syndrome. Family help/counseling approaches, such as the New York University‐Caregiver Intervention (NYUCI), might benefit from a support‐staging model assessment focus on what specific aid a family requires to meet their needs. Patterns of such needs have been identified that can help with providing dementia‐capable care. Objective needs include: (a) information on signs and symptoms, (b) diagnostic advice, (c) understanding behavioral changes and managing dementia‐related behaviors, (d) adapting homes, (e) determining daily routines most conducive to calming, (f) planning for the future, (g) finding and navigating resources, and (h) responding to end‐of‐life needs. Subjective needs include: (a) being informed at time of diagnosis and throughout the course of dementia, (b) coping with a profound sense of loss from knowing the diagnosis, (c) fearing the future [including financial concerns], (d) formulating long‐term plans, (e) accessing community‐based coordinated care, (f) facing difficulties from the medical community, (g) feeling overwhelmed by caregiving demands, (h) feeling a sense of isolation and abandonment, and (i) facing end‐of‐life issues. A working group emanating from the 2016 Glasgow Summit on Intellectual Disability and Dementia organized a schema encapsulating these concerns into a support‐staging model. The schema suggested four fluid stages: Diagnostic (seeking cause of changes in function, abilities, personality), Explorative (exploring dementia capable interventions), Adaptive (coping with and managing the symptoms/changes), and Closure (resolving / relief from responsibilities). Using this schema, a process (utilizing the NYUCI) is underway to operationalize a support‐staging assessment instrument which would enable counseling staff to frame the state of a family’s concerns, build relationships through this knowledge of the caregiver and provide tailored services to them. The outcome will enable systematic coding and organizing both objective and subjective data so that specific interventions and counseling can be adapted to meet both intermittent and continuous caregiver needs.
Neuropsychiatric symptom burden across neurodegenerative disorders and its association with function
Authors: Kapustin Daniel , Zarei Shadi , Wang Wei , Black Sandra E. , Finger Elizabeth , Freedman Morris , Hink Heather , Kwan Donna , Lang Anthony , Masellis Mario , McLaughlin Paula , Pollock Bruce G. , Saposnik Gustavo , Strother Stephen C , Sunderland Kelly M , Swartz Richard H. , Tan Brian , Tang‐Wai David F. , Tartaglia Carmela , Turnbull John , Zinman Lorne , Rajji Tarek K. , Fischer Corinne E. , Kumar Sanjeev 
Published: December 2020

AbstractBackgroundNeuropsychiatric symptoms (NPS) are common in neurodegenerative disorders such as Alzheimer’s disease/Mild Cognitive Impairment (AD/MCI), Parkinson’s disease (PD), Frontotemporal Dementia (FTD), Amyotrophic Lateral Sclerosis (ALS) and in those with Cerebrovascular disease (CVD). The relationship between symptoms, cognition, and function in these cohorts is unclear.MethodData was obtained from the Ontario Neurodegenerative Disease Research Initiative study. We used the Neuropsychiatric Inventory Questionnaire‐ severity scale (NPIQ) to measure NPS, Montreal Cognitive Assessment (MoCA) for cognition, and Lawton’s informant based questionnaires to measure basic and instrumental activities of daily living (ADLs/iADLs). Linear regression was performed to investigate the effects of NPS on ADL and iADL function while controlling for age, education and cognition. Results were bootstrapped by resampling residuals (n=1,000) to control for non‐normal sample distribution.Result520 participants were enrolled: AD/MCI (n=126), VCD (n=161), PD (n=140), FTD (n=53), and ALS (n=40). There were significant differences between these cohorts on NPIQ scores (AD/MCI=16.77±0.18, VCD=16.94±0.12, PD=16.34±0.17, FTD=21.44±0.15, ALS=14.19±0.22, p < .001). Across combined cohorts, NPIQ was inversely correlated with MoCA (rs=‐0.15, p=.001), iADLs (rs=‐0.32, p<.001), and ADLs (rs=‐0.34, p<.001). NPIQ (alone) predicted iADLs in FTD, and (together with MoCA) in MCI/AD and PD (Corrected p values < .05) but not in CVD or ALS. Further, NPIQ alone predicted ADLs in AD/MCI, FTD and PD (Corrected p values < .05) but not in VCD or ALS.ConclusionNPS burden was different across neurodegenerative disease cohorts. NPS were the main determinants of function in FTD, and in AD/MCI and PD when combined with cognition. However, NPS did not determine function in VCD or ALS. These findings indicate the need for further research into biomarkers of NPS and function, and targets of clinical interventions in neurodegenerative disorders.
Geodesic path differences in neural networks in the Alzheimer's disease connectome project
Authors: Adluru Nagesh , Nair Veena A , Prabhakaran Vivek , Li Shi‐Jiang , Alexander Andrew L , Bendlin Barbara B 
Published: December 2020

AbstractBackgroundNeural networks derived from diffusion‐weighted MRI (DW‐MRI) may shed light on disease progression and pathology propagation in Alzheimer’s disease in vivo. In this work analysis of the path properties of such networks are presented. Geodesic or shortest paths are fundamental in understanding key network phenomenon such as the propagation rates of information, infection or pathology. For example, the ubiquitous small‐worldness property of natural occurring biological and social networks is based on having short paths between any pair of entities in the network.MethodConnectome protocol based DW‐MRI data acquired from n=68 participants (Table 1) were analyzed. Neural networks were extracted from the data using state‐of‐the‐art image processing and tractography algorithms available in MRtrix3 (overview panel in Figure‐1). The average geodesic path lengths between frontal, temporal, parietal, occipital, subcortical regions were computed using Dijkstra algorithm. The regions were identified based on the IIT‐Desikan gray matter atlas. The paths can be used to reason about the average efficiency of communication of electrical signals or propagation of pathology between brain lobes. Statistical analysis was performed to test the geodesic path length differences between the CU, MCI and the AD groups controlling for age and sex. The path lengths were normalized so that they were at unity for the AD group, and differences were considered significant at p<=0.05.ResultStatistical effects of consensus diagnosis on the relative geodesic path length (RGPL) differences between lobes are shown in Figure‐2. 80% of the connections showed statistically significant higher path lengths in AD compared to CU and 60% when compared to MCI. The distributions of the mean geodesic path lengths are shown in Figure‐3. For all the different pairs of lobes, the mean length was higher for the AD compared to the CU and MCI groups.ConclusionThe path lengths between all of the major lobes are higher for the AD group compared to both the CU and MCI groups. These findings suggest that network efficiency is reduced in AD and may explain cognitive dysfunction observed in the Alzheimer’s clinical syndrome. Future work entails incorporating better constraints on tractography using structural T1‐weighted images and separating disease groups by AD‐biomarker status.
A national dementia care pathway explored and compared
Authors: Palumbo Mary Val , Rambur Betty , McKenna Lori P 
Published: December 2020

AbstractBackgroundA national, systematic diagnosis and care pathway has the potential to alleviate pressing challenges experienced by individuals with dementia, their carers, and healthcare providers. International exemplars were sought to compare/contrast dementia care with current practice in the United States (US). Specifically, the 2013 New Zealand (NZ) Framework for Dementia Care was explored. The aim was to better understand this systematic, primary care‐led, home and community‐focused dementia management approach from the perspective of those delivering care. To better understand its potential for adoption, US providers were similarly studied.MethodMaximum variation purposive sampling was used in this qualitative descriptive study of 28 participants (18 New Zealand, 10 United States) including providers, case managers/social workers and government officials. Following review and approval by the IRB, investigator‐developed semi‐structured interviews were used, with recruitment of participants continuing until data saturation was reached. Data were then explored for themes using qualitative content analysis, the preferred approach for qualitative descriptive design, and supported by HyperResearch. Throughout the study, qualitative research quality enhancement strategies follow the classic approach of Guba and Lincoln (1994).ResultsNational standards in NZ provide a progressive pathway grounded in early primary care diagnoses and adaptable teams that foster caregiver support to decrease their burden (See Figure 1). The approach also ensures streamlined access to specialists by integrating dementia care in primary care. This is in contrast to the US, where a reactive rather than proactive approach requires providers to navigate unpredictability as they strive to weave together insufficient, inadequate, inconsistent, and inequitable resources to cobble a family’s foundation for an uncertain future.ConclusionCompared to the US where only 2.12% of the Medicare spend is on primary care (Bannow, 2019), NZ is grounded in a strong primary care foundation as are many of the world’s most highly functioning health care systems (Schneider, Sarnak, Squires, Shah & Doty, 2017). Individual states exploring total cost care models, do have the capacity to redesign primary care for enhanced capacity for dementia management both within practice and community settings and should take action. Further implications for translating promising practices to the US are detailed.
Clearance of seed‐dependent tau aggregation by lithium‐induced autophagy: Implications of strain‐specificity
Authors: Uddin Mohammad Nasir , Elahi Montasir , Shimonaka Shotaro , Kakuta Soichiro , Ishiguro Koichi , Motoi Yumiko , Hattori Nobutaka 
Published: December 2020

AbstractBackgroundTau protein aggregation is the major constituent of Alzheimer’s disease (AD) neurofibrillary tangles. Lithium, act as a drug to treat bipolar disorders, has been shown to have various neuroprotective effects including promoting autophagy and acting as an inhibitor of major tau kinase GSK‐3. Our laboratory previously reported that lithium treatment decreased the amount of insoluble tau and motor disturbance with increased LC3‐II positive puncta in tau transgenic mice (Neurobiol Dis, 2012.46). Here, we sought to examine whether lithium influences tau aggregation in different tauopathy via autophagy promotion using a seed‐dependent cell model.MethodsSH‐SY5Y cells were transfected by C‐terminal tau fragment, Tau‐CTF24 (243‐441), and introduced AD and other tauopathy brain seeds (Progressive supranuclear palsy [PSP], Corticobasal degeneration [CBD]). After 48‐hours LiCl treatments, sarkosyl‐insoluble fractions were prepared. For Transmission Electron Microscopy (TEM), cells were cultured on 35 mm dishes and stained with 2% OsO4. Double labeled cells harboring GFP‐CTF24 and mCherry‐LC3 were established.ResultsCells expressing Tau‐CTF24 exposed to AD seeds exhibited a profoundly decreased amount of insoluble tau accompanied with LC3‐II elevation upon treatment with 10 mM LiCl for 2 days. Electron microscopic analysis demonstrated the increase of multilamellar bodies and autophagic vacuoles (AVs). Therapeutic concentration of LiCl (0.2 ‐ 1.0 mM) also demonstrated decreased propensity of insoluble tau in a dose‐dependent manner. The number of puncta stained with both GFP‐CTF24 and mCherry‐LC3 were observed only in LiCl‐treated cell soma. An autophagy inhibitor, 3‐Methyladenine (3‐MA), antagonized LiCl effect. One of IMPase inhinbitor (L690, 330) decreased insoluble tau in cell models and subsequently decreased activity as well as elevated AVs, which mimics LiCl effcts Interestingly, the LiCl effect on insoluble tau reduction was much smaller in CBD than in AD, although reduction of aggregation by PSP is comparable with AD.ConclusionThese results suggest that aggregated tau protein is degraded by LiCl‐induced autophagy in a strain‐specific manner, implying that the mechanism might include IMPase signaling cascade.
Local senile amyloidosis in age‐related macular degeneration and Alzheimer's disease
Authors: Ermilov Victor Vladimirovich , Dorofeev Nikita Alekseevich 
Published: December 2020

AbstractBackgroundThe development of the eye and brain from one germ layer, the community of etiopathogenetic and morphological manifestations of age‐related macular degeneration (AMD) and Alzheimer's disease (AD), the common pathway of β‐amyloid precursor protein (APP) are associated with pathological aggregation of fibrillar β‐amyloid protein (Aβ ) and the development of β‐amyloidopathy in the structural elements of the eye and brain.MethodUsing electron microscopy and selective methods for detecting amyloid and its proteins, 111 eyes with morphological signs of AMD and a brain taken from 56 corpses were examined.ResultOur studies have shown that senile amyloidosis of the eye in combination with senile cerebral amyloidosis occurs in the eighth decade of life, and their frequency increases with age. The cumulative accumulation of β‐amyloid deposits in the structures of the eye and brain was detected in 50.6% of cases. Amyloid‐β deposits were specific for eye druses from AMD and for senile plaques in brain tissue in patients with AD (Fig. 1, 2). In AMD, amyloid deposits are most often found in the Bruch membrane (64.5%) (Fig. 3). Vascular vessels (61.2%) took second place in frequency of occurrence (Fig. 4, 5). The combination of local forms of amyloidosis was characterized by concomitant deposition of β‐amyloid in the vessels of the brain and vessels of the choroid (amyloid angiopathy), as well as in the structural elements of the back of the eye and brain with a typical histochemical characteristic of local forms of senile amyloidosis. Moreover, amyloid angiopathy was more pronounced in the vessels of the brain than in the vessels of the choroid (Fig. 6).ConclusionThe authors demonstrated that changes in the vessels of the brain and the structural elements of the retina and choroid in patients with AMD with AD can be considered as concomitant neurodegenerative processes in these two diseases, which are based on pathological aggregation of β‐amyloid protein. This view of the problem creates the prerequisites for the development of new strategies for the creation of ophthalmogeriatric and neuroprotective drugs that affect pathogenesis and include all stages of Aβ formation and pathological aggregation.
Depression and bone loss as risk factors for decline in cognitive function: A systematic review and meta‐analysis
Authors: Mehta Kanika , Thandavan Sathya Priya , Gupta Veer Bala 
Published: December 2020

AbstractBackgroundSeveral reports have postulated depression and bone loss as risk factors for dementia. However, these studies only focus on incidence of dementia as an outcome and non‐demented individuals who display prospective cognitive decline are often not included. Therefore, the present study investigates whether the presence of depression and/or bone loss among cognitively healthy individuals at baseline is associated with a decline in cognitive function (including presentation of dementia) during follow‐up assessment.MethodThe search was conducted in four databases; MEDLINE Complete, Embase, PsycINFO and CINAHL Complete on 28th November 2019. The search terms comprised 4 search blocks; Population (Adult), Exposure (Depression, Osteoporosis), Outcome (Cognitive decline) and Study design (Longitudinal). Additionally, in order to make the search comprehensive, database‐specific subject headings were incorporated in the search. The restrictions included English language, human studies and peer‐reviewed articles, however, no restriction was imposed on the publication period.ResultThe search yielded total 27,792 references and after duplicate removal 15,148 references remained. These references were subjected to ‘Title & Abstract screening’ in Covidence, a widely used web‐based platform for conducting systematic reviews. The references were screened by two independent reviewers and 380 selected studies were subjected to a full‐text review. Longitudinal studies including adult participants and with a minimum of 1 year follow‐up period were selected. Studies with cognitive impairment at baseline or studies in which the focus was on specific cognitive domains were excluded. Following the full‐text screening, data extraction and risk of bias assessment was conducted.ConclusionCurrently, the statistical analysis is under way. The effect size will be estimated as risk ratios or standardised mean differences for binary and continuous outcomes, respectively, for both depression and bone loss using a random‐effects model.
Blood‐brain barrier insulin resistance decreases insulin uptake and increases amyloid beta uptake in Alzheimer's disease brain
Authors: Zhou Andrew L , Swaminathan Suresh K , Gali Chaitanya C , Bruinsma Tyler J , Curran Geoffry L , Sarma Vidur V , Decklever Teresa , Sharda Nidhi , Wang Lushan , Min Paul H , Lowe Val J , Kandimalla Karunya K 
Published: December 2020

AbstractBackgroundDecreased brain insulin levels exacerbate cognitive decline in AD. Insulin in the brain is derived from systemic circulation via the blood‐brain barrier (BBB). We hypothesize that type II diabetes (T2D) sequelae and Aβ peptide exposure disrupt insulin signaling at the BBB and inhibit insulin delivery to brain. Further, we propose insulin signaling defects at the BBB contribute to Aβ accumulation in AD brain.MethodsThe following studies were performed in wild‐type (WT) mice on regular chow (RC) diet, WT mice on high fat (HF) diet (manifest insulin resistance), APP/PS1 transgenic mice on RC diet (overexpress Aβ), and APP/PS1 mice on HF diet (overexpress Aβ + insulin resistance). After femoral injection of 125I‐insulin or 125I‐Aβ42, the brain accumulation was monitored between 0‐40 min by dynamic SPECT/CT imaging. The brain influx clearance was estimated by the slope obtained from Gjedde‐Patlak graphical analysis. Cerebral microvessels were harvested, and reverse phase protein array (RPPA) was performed to examine insulin signaling changes. Differentially expressed targets were subsequently confirmed by western blot. The brain influx of 125I‐insulin and 125I‐Aβ42 were further assessed in WT‐RC mice after internal carotid infusion with AG1024, a kinase inhibitor of the insulin receptor (IR) and insulin‐like growth factor receptor (IGF‐1R).ResultsCompared to WT‐RC, 125I‐insulin influx was decreased in WT‐HF and APP/PS1‐RC, and was further decreased in APP/PS1‐HF (4.1, 3.4, 3.5 and 2.6*10‐4 mL/min, respectively). Compared to WT‐RC, 125I‐Aβ42 influx was increased in WT‐HF and APP/PS1‐RC (8.6, 28 and 23*10‐4 mL/min, respectively). RPPA analysis revealed global disruptions in BBB insulin signaling pathways. Western blots confirmed reduced expression of IR‐β, p‐AKT and p‐GSK3β in WT‐HF and APP/PS1‐RC compared to WT‐RC. Moreover, the largest decreases were observed in APP/PS1‐HF. Infusion with AG1024 was shown to decrease 125I‐insulin influx, but increase 125I‐Aβ42 influx.ConclusionsBoth T2D and AD mice exhibited decreased brain influx of insulin and increased influx of Aβ42. This was associated with altered expression/activity of insulin signaling kinases at the BBB. Further, IR and/or IGF‐1R kinase activity were shown to differentially regulate BBB trafficking of insulin and Aβ42. Thus, BBB insulin signaling is important for delivering insulin to brain and restricting pathological uptake of Aβ.
Screening peripheral biopsies for alpha‐synuclein pathology using deep machine learning
Authors: Signaevski Maxim , Prastawa Marcel , Tabish Nabil , Marami Bahram , Koenigsberg Daniel , Bryce Clare , Chahine Lana , Mollenhauer Brit , Mosovsky Sherri , Riley Lindsey , Dave Kuldip D , Eberling Jamie , Coffey Chris , Adler Charles , Serrano Geidy E , III Charles White , Koll John , Fernandez Gerardo , Zeineh Jack , Cordon‐Cardo Carlos , Beach Thomas G , Crary John F 
Published: December 2020

AbstractBackgroundPost‐mortem assessment remains the only option and a gold standard for a definitive diagnosis of Parkinson’s disease (PD). The antemortem diagnosis is challenging due to a variable clinical presentation and the abundance of mimicking conditions, obscuring the clinical picture and delaying the treatment. It is well established that while PD pathologically manifests in central nervous system with aggregation of α‐synuclein as Lewy bodies and Lewy neurites, this pathology is also found in the peripheral nervous system. Peripheral Lewy‐type synucleinopathy (LTS) is present in early PD, suggesting its utility as a diagnostic and prognostic biomarker. We have previously confirmed that detection of LTS in submandibular gland (SMG) biopsies is sensitive (.75) and specific (.90) for early PD. However, the assessment by a neuropathologist of multiple levels of such biopsy is laborious and time‐consuming.MethodHere work we applied two Convolutional Neural Networks (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total number of 8,386 LTS were annotated following the interrater reliability study with kappa=.7. We used transfer learning to train a CNN model to classify image patches (40‐by‐40 pixels at 20x) with and without presence of LTS objects.ResultThe trained CNNs showed the following performance on image patches: sensitivity: .982/.988, specificity: .998/.999, precision: .852/.950, accuracy: .995/.998, and F‐1 score .912/.968 for ResNet30/InceptionV4 respectively. On test WSI the sensitivity in detecting LTS was .963/.971 respectively.ConclusionThis work is first to demonstrate the practical utility of an CNN for screening for LTS, which can further translate into a practical screening tool facilitating the antemortem diagnosis of PD. We further plan to develop neural networks for accurate and precise detection and quantification of LTS in antemortem SMG biopsies. This, altogether, would offer a screening, confirmatory, prognostic, and quantitative tool for clinical assessment of early PD.