bluuebunny/crossref_metadata_2025_split huggingface dataset:
M1 muscarinic acetylcholine receptor positive allosteric modulators do not disrupt sleep in aged cynomolgus macaques
Authors: Gould Robert W , Lekander Alex D , Curry C Ryan , Lavalley Nina , Russell Jason K , Newhouse Paul A , Nader Michael A , Jones Carrie K 
Published: December 2022

AbstractBackgroundAge‐related changes in sleep may directly contribute to cognitive dysfunction and underlying pathological progression contributing to Alzheimer’s Disease or related dementias (AD/ADRDs). While acetylcholinesterase inhibitors (AChEIs) are FDA‐approved for the treatment of AD‐related cognitive impairments, these drugs also disrupt sleep. Positive allosteric modulators (PAMs) targeting the M1 muscarinic acetylcholine receptor (M1 mAChR) have produced cognitive and arousal enhancing as well as sleep‐modifying effects in aged and/or AD rodents models. The present study provided the first comparison of baseline sleep measures in young and old monkeys, then examined the effects of novel M1 mAChR PAMs VU0486846 and VU0453595, compared with the AChEI, Donepezil on sleep in aged monkeys.MethodEight young adult (4 male/4 female, 6‐8 years old) and 10 aged cynomolgus macaques (6 males/4 females, 19‐25 years old) were implanted with subcranial electrodes and a wireless transmitter (L04, DSI) for undisturbed telemetric recording of electroencephalography (EEG) from their home cage. After baseline sleep assessments, aged monkeys were tested once weekly with donepezil (3.0‐10 mg/kg, PO), VU0486846 (3.0‐30 mg/kg, PO), or VU0453595 (1.0‐10 mg/kg, PO), administered 2 hours prior to lights out (0600:1800 light:dark schedule). EEG was recorded and sleep stages including total sleep time (TST), % TST in rapid eye movement sleep (REM), N1, N2, and N3 non‐REM sleep were determined and summed across the 12 hour dark period.ResultAged monkeys showed significantly less % TST in N3 and REM sleep and increased N1 sleep compared to young monkeys. Donepezil dose‐dependently reduced TST, increased % REM and trended toward a decrease in N2 and N3 stage sleep. In contrast, M1 PAMs, within dose ranges known to be physiologically active in monkeys, did not alter sleep parameters.ConclusionAged‐related and donepezil‐mediated sleep disruptions in aged monkeys are consistent with the clinical literature. Lack of effects by M1 mAChR PAMs in aged monkeys when dosed prior to lights out may suggest fewer disruptive effects compared to AChEIs or that there is insufficient cholinergic tone for an M1 PAM to alter sleep. Future studies will assess the arousal enhancing effects of M1 PAMs when dosed during waking periods in aged monkeys.Funding: AG054622, DA017763
Lithium boosts neuronal bioenergetics in Alzheimer’s disease
Authors: Adlimoghaddam Aida , Andreazza Ana C. , Albensi Benedict C 
Published: December 2022

AbstractBackgroundAlzheimer's disease (AD) is characterized by the accumulations of amyloid beta and neurofibrillary tangles in brain tissue; however, AD is multifactorial and different etiopathogenic mechanisms involves that can affect mitochondrial function that are associated with AD. In the current study, we investigated the effect of lithium on mitochondrial function in AD.MethodNeuronal cells were isolated separately from hippocampal of brain tissue of control mice (C57BL/6) and 3xTg model of AD. Mitochondrial oxygen consumption rate (OCR), mitochondrial Cytochrome C Oxidase (COX) activity, and total ATP activity were measured in control vs. AD neurons after one day and seven days dose‐dependent treatment with lithium.ResultIn the present study, short and long term lithium treatment significantly increased (p<0.05) mitochondrial OCR, COX, and total ATP level in 3xTg neurons. However, lithium had no effect on energy metabolism in control neurons. Together, these data indicate that lithium improves mitochondrial function under pathological states.ConclusionOverall, these results have important implications for the treatment of disorders in which brain energy regulation are compromised, including AD. Particularly, our results highlight a role for lithium in regulating bioenergetics in early stage AD and suggest that neuronal cells may be a crucial therapeutic target for preventing AD.
Risk factors and cognitive domain markers of progression in Subjective Cognitive Decline
Authors: Bubu Omonigho Michael M , Mbah Alfred , Masurkar Arjun V 
Published: December 2022

AbstractBackgroundSubjective cognitive decline (SCD) is considered a preclinical stage of Alzheimer’s disease, but drivers and nature of progression remain unclear. We evaluated risk factor differences between SCD decliners and non‐decliners related to demographics, genetics, and presence of comorbidities. We also investigated cognitive domain markers associated with progression over time.MethodA longitudinal analysis was performed on subjects with SCD at baseline from the NYU Alzheimer’s Disease Research Center. We included subjects classified as non‐decliners (n = 27), who remained stable for six annual visits, and decliners (n = 24), who progressed to mild cognitive impairment or worse between the second to sixth follow‐up visits. Generalized linear models examined group differences in demographic and genetic (presence of APOE4 or APOE2 allele) risk factors. Linear and logistic mixed‐effects models with random intercept and slope examined associations of psychometric test performance and comorbidities with longitudinal decline, comparing decliners to non‐decliners. Models included age, sex, education, Hispanic ethnicity, baseline psychometric data, APOE status, and their interactions with time. Time was operationalized as years from baseline for each participant.ResultMean (SD) age was 68.5 (11.3) vs. 66.3 (7.1) years (p = 0.41), and follow‐up time was 3.7 (1.97) vs. 6.3 (1.60) years, (p <0.001) for decliners vs. non‐decliners. Subjects with lower years of education (14.9 (3.2) vs. 17.3 (2.1)) and those of Hispanic ethnicity (52.2% vs. 47.8%) were more likely to be decliners (p ≤ 0.004 for both). There were no differences in APOE2 or APOE4 status between decliners vs. non‐decliners. Decliners were approximately 7 times more likely (aOR: 6.67; 95% CI: 1.30 – 33.33, p = 0.002) to have hypercholesterolemia compared to non‐decliners. SCD decliners were at increased risk for psychometric changes in memory, executive, and language domains (p < 0.001 for all).ConclusionIn this cohort, lower education, Hispanic ethnicity, and hypercholesterolemia are risk factors for progression in SCD, whereas APOE status is not. Although SCD has been primarily defined with regard to concern about memory, SCD decliners are at increased risk for both amnestic and non‐amnestic cognitive decline. This supports further work to relate risk factors to SCD outcomes.
Identification of Mild Cognitive Impairment Among Black and White Community Dwelling Older Adults Using NIH‐Toolbox Cognition Tablet Battery
Authors: Rigby Taylor , Gregoire Allyson , Reader Jonathan M , Kairys Anson , Bhaumik Arijit K , Rahman‐Filipiak Annalise , Hampstead Benjamin M. , Kavcic Voyko , Giordani Bruno 
Published: December 2022

AbstractBackgroundNIH Toolbox‐Cognition Battery (NIHTB‐CB) is a computerized cognitive assessment battery frequently used in clinical research. However, the utility of the tablet adaptation has not been well established for clinical characterization, nor have possible racial differences been examined. We aim to identify which of the NIHTB‐CB subtests best differentiate healthy controls (HC) from those with mild cognitive impairment (MCI), as well as examine possible differences in diagnostic identification between Black/African‐American (B/AA) and white older adults.MethodParticipants were community‐dwelling adults 65 years and up (HC = 96; MCI = 63), recruited through affiliated studies within the Michigan Alzheimer’s Disease Research Center (NIA/NIH‐P30AG053760) and diagnosed by consensus conference through National Alzheimer’s Coordinating Center criteria. They then completed the NIHTB‐CB tablet version for iPad. Discriminant function analysis was used to determine which cognitive tests best differentiated clinical diagnoses in the total sample and separately for B/AA (n = 81) and white participants (n = 78).ResultIn the total sample, 78% of cases were correctly identified with Picture Sequence Memory (PSM; Standardized Coefficient (SC) = ‐.73) being the strongest predictor. The cross‐validated model correctly identified 79.2% of HCs and 60.3% of MCIs. Analyses were then stratified by race. In the B/AA sample, the model was able to correctly identify 60% of HCs and 68.4% of MCIs, with PSM (SC = .68) being the strongest predictor followed by List Sorting Working Memory (LSWM; SC = .42). In the white sample, 83% of HCs and 44% of MCIs were correctly identified and PSM (SC = .84) was the strongest predictor.ConclusionAs more treatments become available for Alzheimer’s disease, it is increasingly important to identify preclinical stages, such as MCI, so that we may intervene as early as possible in the disease process. NIHTB‐CB is one tool that may aid in identification. The memory subtest PSM was the best predictor of diagnosis in each model. While the overall model was fairly accurate at predicting clinical diagnosis, the models proved less accurate when cross validated and stratified by race. Thus, our results suggest that it may be important to consider race and other aspects in identifying specific diagnostic groups.
How Can Pet Robots Be Embedded Into Nursing Homes as Part of Routine Dementia Care?
Authors: Koh Wei Qi , Casey Dympna , Toomey Elaine 
Published: December 2022

AbstractBackgroundIn the last decades, pet robots have started to gain traction as a technology‐based alternatives for animal‐assisted therapy. Several studies have been conducted to evaluate the effectiveness of pet robots for people living with dementia, particularly in residential care settings. Despite findings of their potential to deliver psychosocial benefits for nursing home residents with dementia, the knowledge translation from research to clinical practice remains slow, and the uptake of pet robots in clinical practice remains low. The purpose of this study was to identify strategies to guide the implementation of pet robots into routine dementia care in nursing homes.MethodA preceding qualitative inquiry and a scoping review was conducted to identify determinants of implementing pet robots. To ensure that the multilevel nature of implementation was captured, the Consolidated Framework of Implementation Research (CFIR) was used to guide the conceptualisation and conduct of the both studies. Next, we identifed implementation strategies to address the identified determinants. This was done by mapping determinants to the Expert Recommendations for Implementation (ERIC), a taxonomy of 73 implementation strategies, using the CFIR‐ERIC mapping tool. Findings from the preceding studies were used to contextualised the identified strategies. Finally, we consulted with key stakeholders and a Patient and Public Involvement member to further refine the list of implementation strategies.ResultImplementation determinants were mapped to all nine clusters of implementation strategies in the ERIC taxonomy. Most implementation strategies were focused on the development of stakeholder relationships, such as conducting local consensus discussions to identify the need or priority of having pet robots, training and educating stakeholders such as conducting educational meetings, and the use of evaluative and iterative strategies such as conducting a local needs assessments.ConclusionTo the best of our knowledge, this is the first study to identify implementation strategies for embedding pet robots into nursing homes for routine dementia care. Findings from this study have practical utility for clinical researchers, organisations and clinicians to guide the translation of the research on pet robots into real‐world practice.
Evaluation of the performance of alternative models in analyzing longitudinal data for Alzheimer clinical trials compared to MMRM
Authors: Wang Guoqiao , Li Yan , Xiong Chengjie , Liu Lei , Kennedy Richard E , Schneider Lon S. , Natanegara Fanni , McDade Eric , Bateman Randall J. 
Published: December 2022

AbstractBackgroundSecondary prevention clinical trials (stage 2) for Alzheimer disease (AD) typically employs a cognitive composite score, consisting of multiple cognitive test scores, as the primary endpoint because of its sensitivity to subtle cognitive change. The underlying assumptions of using a composite score are that: (i) the treatment if effective will lead to similar treatment effects in each of its component (e.g., ∼25% reduction in the placebo progression); and (ii) the estimated treatment is an average of the treatment effects across the components regardless the satisfaction of assumption (i). The composite is typically analyzed using mixed models for repeated measurements (MMRM). Under the same assumptions, we proposed to analyze the composite using the multivariate MMRM (mMMRM) and the proportional mMMRM (PmMMRM). On the other hand, CDR SB is often used as the primary endpoint in early‐stage AD trials (stage 3), however, 20% to 30% of the placebo patients demonstrated no progression during an 18‐month follow‐up. These non‐progression participants would dilute the treatment effect comparison under the MMRM analysis. Because CDR SB is an ordinal rank measure, we propose to analyze it using the Cox proportional hazards model for recurrent events, where a recurrent event is defined as any ordinal increment over the previous visit. The goal of this study is to evaluate the performance (i.e., power) of these alternative models relative to MMRM.MethodWe evaluate the performance using both simulated data and the real trial data from the EXPEDITION 1 and EXPEDITION‐2 placebo arms.ResultBased on simulated data, for the cognitive composite, mMMRM yielded similar power to MMRM and PmMMRM led to 5‐8% power improvement over MMRM for a two‐component composite. PmMMRM’s power advantage is expected to increase with the number of components in the composite. For CDR SB, Cox model for recurrent events yielded up to 20% greater power than MMRM. Comprehensive evaluation will be reported based on real trial data.ConclusionAlternative models such as PmMMRM or Cox model with the same underlying assumption as or analyzing the data with a different angle from MMRM should be explored to obtain greater power.
Preliminary Analysis of Aspects of Caregiving among Spousal Caregivers and Adult Child Caregivers for Persons with Dementia
Authors: Lewis Nicole E. , Papazyan Anna , Flatt Jason D. , Kietzman Kathryn G. , Song Yeonsu 
Published: December 2022

AbstractBackgroundWhile dementia caregiving experiences may vary across individuals, many studies have focused on the negative aspects of caregiving and reducing caregiver burden and stress. Understanding both positive and negative aspects of caregiving is essential, particularly between different caregiver types. This study aimed to compare positive and negative caregiving experiences between spousal and adult child caregivers. We also examined whether the caregiver type (spousal caregivers vs. adult child caregivers) is a significant factor predicting these caregiving experiences.MethodWe analyzed baseline data from an ongoing trial to manage sleep problems among persons with dementia (PwD) and their caregivers. Demographic data, Positive Aspects of Caregiving (PAC), Zarit Burden Interview (ZBI), and Center for Epidemiological Studies of Depression (CESD) data were collected from 39 caregivers (n = 27 spouses, n = 12 adult children; 82% women, 54% Whites). Descriptive and bivariate analyses and multiple regression models were conducted.ResultAdult child caregivers reported that providing care for their loved one made them feel more appreciated than spousal caregivers (4.25±1.21 vs. 3.48±0.97, respectively); however, they felt more stress when caring for the PwD and trying to meet other family and work responsibilities (2.75±0.86 vs. 2.07±0.99, respectively) and felt they should be doing more for the PwD (2.17±0.71 vs. 1.30±1.07, respectively; all p<0.05) than did spousal caregivers. No significant differences were found in the PAC and the ZBI total scores by caregiver type. In a separate regression model, CESD total score was the only significant factor predicting PAC and ZBI total scores, controlling for caregiver type, race (Whites vs. others), level of education, employment status, and years of caregiving. However, only the model predicting the ZBI total score was statistically significant (p<0.01, adjusted R2 = 54%).ConclusionThese preliminary findings suggest a critical need to better understand positive and negative caregiving experiences, particularly among adult child caregivers. Assessment of depressive symptoms should be included when examining caregiving experiences among spousal and adult child caregivers. Future studies are warranted to test whether characteristics of PwD or support received by caregivers would contribute to positive or negative caregiving experiences across caregiver types.
MCI performance classification improves with a brief vocabulary test
Authors: Woods David L. , Hall Kathleen , Williams Garrett , Baldo Juliana , Chok Jas M. , Lwi Sandy J. , Blank Michael , Geraci Kristi , Herron Tim , Schendel Krista , Johnson David K 
Published: December 2022

AbstractBackgroundScores on cognitive tests in the bottom 7% of normative distributions are consistent with the possible diagnosis of mild cognitive impairment (MCI). The identification of patients with MCI is improved by correcting for the influence of demographic factors such as Age, Education, and Gender (AEG), on performance. Here, we evaluated whether estimates of premorbid verbal IQ derived from a brief vocabulary test would further improve classification accuracy.MethodWe obtained vocabulary scores from 441 healthy adults (mean age = 65.1 ±14.4) using the 4‐min vocabulary subtest of the California Cognitive Assessment Battery (CCAB). The vocabulary subtest included 24 multiple choice items that adapted in difficulty based on the examinee responses using a 2:1 staircase with adjustable step sizes (Figure 1). Tests were telemedically administered in participants’ homes by an experienced proctor who monitored performance via a web‐based interface.ResultUnlike cognitive measures of fluid intelligence, vocabulary scores improved significantly with Age (r = 0.25, p < 0.001, Figure 2). Scores were also higher for participants with more education and female gender. Vocabulary z‐scores were therefore calculated after correcting for the influence of Age, Education, and Gender. Vocabulary z‐scores correlated significantly with total recall scores on the Bay Area Verbal Learning Test (BAVLT, n = 398 participants, r = 0.35, p < 0.001) and significantly improved model fit when added to AEG regressors (z = 2.1, p< 0.02 one tailed)L the AEG model accounted for 25.6% of BAVLT score variance, whereas the AEG+vocabulary (AEG+V) model accounted for 34.7% of variance. AEG and AEG+V models classified different participants in the MCI performance range: 44% of participants in the lowest 7% of scores in the AEG+V model fell within the normal range in the AEG model, while 32% of participants classified as MCI in the AEG model fell within the normal range on the AEG+V model (Figure 3).ConclusionThe current results suggest that a brief vocabulary test improves MCI classification accuracy among older participants.
FTD Disorders Registry (FTDDR) Research Readiness Survey: Assessing awareness and attitudes towards participation in research
Authors: Reddy Sweatha , Harlass Sherry , Vincent Lakecia , Wheaton Dianna K.H. 
Published: December 2022

AbstractBackgroundFTDDR is a web‐based, contact and research registry to amplify the patient/family voice and facilitate research for frontotemporal degeneration (FTD), a rare group of early‐onset dementia disorders. FTD not only alters cognition but also impacts behavior, personality, language, and movement. No treatments or cures are currently available, underscoring the need for research participation.MethodThe Research Readiness Survey was designed to assess knowledge of basic research principals and index perceptions of the value of research studies and clinical trials among the lay community. The 23‐question survey was administered online to FTDDR participants between March 2017 and January 2022 using a multiple‐choice and True/False‐style format.ResultRespondents (n = 750) were 80% caregivers/biological family members and 20% FTD diagnosed persons responding independently or with care partner/helper assistance (31% male, 69% female; age range = 50‐74 years). FTD diagnoses represented among the respondents were behavioral variant FTD (bvFTD 55%), primary progressive aphasia (PPA 17%) progressive supranuclear palsy (PSP 9%), corticobasal degeneration/syndrome (CBD/CBS 7%), FTD with motor neuron disease (FTD‐ALS 4%), and other/diagnosis pending (8%). Research studies were viewed positively by the majority of respondents (85%) and this was similarly reflected by a high willingness to participate (84%) in a research study/clinical trial, especially if it was about treating or preventing disease. 64% of respondents ranked their understanding of clinical trial concepts as knowledgeable‐to‐very knowledgeable which was subsequently supported by 87% correctly answering 8 of 10 questions about principals of research. Barriers to participation in research included fear that the study would be too difficult physically/emotionally (28%), concern about time off from work (25%) and lack of reimbursement for travel expenses (20%). Most respondents (68%) reported that additional information and education about research studies/clinical trials would increase their ability to evaluate participation.ConclusionSurvey results indicated that while FTDDR members have a positive perception of research and are relatively knowledgeable about principals of participation, there is a strong desire for additional information and education to empower informed decision‐making. Understanding and addressing perceived barriers as well as creating person‐centric studies with emphasis on participant‐facing educational materials may increase research study participation.