bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of ICT‐Based Multicomponent Program on Body Composition and Cognitive Function in Older Adults: A Randomized Controlled Clinical Study
Authors: Kim Duri , Chang Jae Hyeok , Song Seunghwan , Tak Young Jin , Huh Up , Cho Jeong Su , Sung Min‐ji , Jang Minwoo , Park Jong‐Hwan 
Published: December 2022

AbstractBackgroundInformation and communication technology (ICT)‐based training devices for older adults’ care related to dementia are being developed to enhance older adults’ cognitive functions. Older adults who require bicycle training devices can improve muscle strength and balance of lower limbs by continuously contracting and relaxing lower‐limb muscles and improving cognitive function to prevent dementia. This study was conducted to investigate the effects of an ICT‐based multicomponent program on body composition and cognitive function in older adults.MethodIn a randomized controlled intervention test on 20 people over the age of 60 (exercise group: n = 10; control: n = 10), the multicomponent program was applied to the exercise group twice per week, once per day for 12 weeks, at 30 min per session, whereas the control group was advised to maintain their usual daily activities.ResultComparing body composition changes and cognitive function changes before and after intervention exhibited statistically significant differences in skeletal muscle mass (P = 0.01) and modified Alzheimer’s disease assessment scale–cognitive score (P = 0.01) between the two groups.ConclusionIt can be difficult to be engaged in a simple repetitive exercise program. Therefore, to meet older adults’ interests and expectations, a customized ICT‐based multicomponent program, which can improve body composition and cognitive function in older adults and is believed to help prevent dementia, is recommended.
Post‐stroke dementia and its determinant factors among Ethiopian stroke survivors: A cross‐sectional study
Authors: Zewde Yared Z 
Published: December 2022

AbstractBackgroundStroke and dementia convene risks for each other and share some of the same, largely modifiable, risk factors.MethodAdult stroke survivors, who visited the outpatient stroke clinic in Tikur Anbessa Specialized Teaching Hospital in Addis Ababa University, Ethiopia was assessed for cognitive decline. Beside Montreal Cognitive Assessment‐Basic (MOCA‐B) tool, functional recovery and depression were measured using modified Rankin Scale (mRS) and Patient Health Questionnaire (PHQ‐9).ResultFrom 67 stroke survivors (mean age: 52.1 ± 12.7 years, 40.3 % female, 25.3% illiterate, rural dwellers 32.8%, 37.3% stoke onset < 45‐year), 68.7% had cognitive impairment in at least one domain and 25.3% had dementia. Hospitalization [OR = 0.22 (0.06 ‐0.74)], right hemisphere stroke location [OR = 0.21 (0.06‐0.77)] and poor function recovery with mRS ³3 [OR = 1.4 (1.06‐1.74)] were independently associated with post stroke cognitive impairment and dementia.ConclusionThe frequency of post stroke dementia was high in Ethiopia and poor functional recovery negatively impact cognitive outcome.
HIVEP3 variant is associated with increased amyloid deposition and lower hippocampal volume in cognitively unimpaired subjects.
Authors: Dauar Marina Tedeschi , Picard Cynthia , Breitner John , Villeneuve Sylvia , Poirier Judes ,   Prevent‐AD Research Group,   ADNI study
Published: December 2022

AbstractBackgroundA GWAS performed in a Canadian cohort identified, for the first time, the polymorphism rs10493098 C in the HIVEP3 gene to be associated with increased risk for late‐onset Alzheimer’s disease (AD). HIVEP3 is a transcription factor that regulates inflammatory response, neuroregeneration, cell growth and apoptosis. In this project, we examined three different population cohorts (PREVENT‐AD, ROSMAP and ADNI cohorts) to investigate the role of the rs10493098 C polymorphism in the pathophysiology of AD.MethodIn the PREVENT‐AD cohort, 18F‐NAV4694 PET was used to measure amyloid burden, and participants were followed for at least four years. In the autopsied‐confirmed ROSMAP cohort, Aß load and NFT density in the cortex were measured by immunohistorychemistry. Participants were followed throughout most of their adult life, until death. In the ADNI cohort, hippocampal volume was assessed with magnetic resonance imaging, and we evaluated follow‐up for 1 year.ResultIn the Prevent‐AD cohort, participants who are homozygous for the HIVEP3 C variant had higher amyloid index score compared to non‐carriers (p=0.004) (Fig 1). There is an interaction between APOE4 and HIVEP3, and participants who are APOE4 positive and homozygous for the HIVEP3 C variant exhibit even higher amyloid deposition compared to non‐carriers (p<0.001) (Fig 1). Participants who are homozygous for the HIVEP3 C variant have a higher risk of having an amyloid positive scan than participants who are non‐carriers (p=0.04) (Fig 1). There was no association between the HIVEP3 rs10493098 C variant and Braak or Cerad stages in the ROSMAP population. In the ADNI cohort, considering only the participants who had normal cognition, subjects who are homozygous for the HIVEP3 rs10493098 C variant display lower right hippocampus volume compared to heterozygous and non‐carriers (p=0.032) (Fig 2).ConclusionThe HIVEP3 rs10493098 C variant is associated with higher amyloid deposition and lower hippocampal volume in cognitively unimpaired individuals
Humanoid robots coming to aid in dementia care provision: 16 humanoid robots working to augment care in 8 nursing homes across Minnesota
Authors: Khan Arshia a 
Published: December 2022

AbstractBackgroundDementia is a growing problem that is the cause for an increase in care provision needs. Staff shortages are having an adverse effect by creating an atmosphere where the people affected with dementia feel neglected and isolated. This is resulting in reduced quality of life for the people residing in assisted living facilities and nursing homes. Family members and caregivers have been forced to reduce contact with the residents due to the fear of infection given the vulnerability of the residents. The residents are losing emotional stimulation and this is adversely affecting their disease progression.MethodFreeing caregivers of mundane caregiving activities that require more patience and less caregiving in activities such as reminding/prompting, watching and monitoring can allow them to focus on activities that require more attention and will benefit the residents. Repetitive activities such as prompting, reminding of daily living activities such as brushing teeth and hair, washing hands, keeping the oxygen or face mask on etc. can be repetitive and stressful for caregivers. If these activities can be performed by a humanoid robot that can repeat the same activity or prompt without getting frustrated or changing the tone, the caregivers will have more time to tend to activities that require more attention such as medication management, tending to finances, medical followup appointments etc. University of Minnesota is collaborating with nursing homes in deploying robots to help augment care in the domains of emotion, cognition and physical wellbeing. These robots will have tasks assigned to them that they will perform throughout the day. They work in conjunction with sensors that will provide them with stimulation and feedback for tracking and monitoring activities of daily living. The sensors will also track the physiological well being to ensure the residents are not adversely affected by the robots.ResultHumanoid robots are being deployed in nursing homes. A combination of humanoid robots and wearable and spatial sensors track and monitor care provision for residents at nursing homes.ConclusionThe humanoid robots are helping fill staff shortage gaps. Most importantly residents feel more engaged and have an improved sense of wellbeing.
Deep learning to harmonize MRI scans for better diagnosis and prognosis in multi‐center studies
Authors: Gebre Robel K , Senjem Matthew L. , Schwarz Christopher G. , Gunter Jeffrey L. , Kantarci Kejal , Graff‐Radford Jonathan , Knopman David S. , Petersen Ronald C. , Jack Clifford R. , Vemuri Prashanthi 
Published: December 2022

AbstractBackgroundData heterogeneity due to cross‐scanner variations is a major challenge in multi‐center aging and dementia studies. Brain structural measures for the same participant can vary due to scanner differences (manufacturer, scanner age/technology, signal‐to‐noise ratio, pulse sequence design, contrast, resolution) and result in biomarker variability. In this work, we applied basic image processing and deep learning methods (style transfer (ST) and generative adversarial networks (GANs)) for harmonizing T1‐weighted MRI scans across change in vendors (GE to Siemens) and resolution (1x1x1.2mm to 0.8x0.8x0.8mm) and test whether this harmonization improved compatibility of AD biomarker measures.MethodWe utilized training (n=814) and test (n=113 same participants scanned on two scanners close‐in‐time, typically on the same day, with different resolution) data from cognitively impaired and unimpaired participants scanned on GE and Siemens scanners from Mayo Clinic Study of Aging and Mayo ADRC. The harmonization was conducted to translate GE to Siemens. All scans were affine transformed to the same template space, resampled to 1.5 mm3, and bias corrected. Histogram matching was performed using cumulative density functions. A ResNet18 was trained for the ST’s content and style layers. Two types of GANs, conditional GANs (cGAN) and cycle‐consistent GANs (cycleGAN), were constructed. We then measured regional cortical thickness from each image using FreeSurfer‐7.1.1 and compared the thickness measurements from the original and translated scans using intraclass‐correlation (ICC) and Deming regression.ResultIn the test dataset, ST and cycleGAN showed the best performances when comparing the translated GE to Siemens. With ST, the ICC increased (vs. the original scans) slightly for the temporal meta‐ROI (0.956 from 0.954) and more substantially for the frontal pole ROI (0.706 from 0.594). The cycleGAN showed an increase in ICC for the frontal pole ROI (0.610 from 0.594) but not the meta‐ROI (Fig. 1).ConclusionEach method leveraged a different strength. Histogram matching captures contrast, ST extracts textural information, and GANs learn combination of contrast, edge and texture properties. We found that deep learning is a promising approach to cross‐scanner variability. Our comparisons revealed anatomical differences across methods; thus, disease specific measure should be considered for selection of the scanner harmonization method.
Longitudinal increase of sTREM2 in CSF and its relationship with other biomarkers and cognition along the evolution of autosomal dominant Alzheimer’s disease
Authors: Morenas‐Rodriguez Estrella , Haass Christian , Network Dominantly Inherited Alzheimer 
Published: December 2022

AbstractBackgroundTherapeutic modulation of TREM2‐dependent microglial function provides an additional strategy to slow progression of Alzheimer’s disease (AD). Although studies on animal models suggest that TREM2 is protective, clinical biomarker studies reach different conclusions regarding TREM2 effect on tau pathology and its potential beneficial role in human AD. The longitudinal study of cerebrospinal fluid (CSF) soluble TREM2 (sTREM2) as a biomarker of TREM2 signalling during the evolution of autosomal dominant AD and its relationship with different biomarkers shed additional light on these controversies.MethodWe measured sTREM2 by a novel MSD‐immunoassay selectively detecting ADAM10/17 generated sTREM2 in longitudinal CSF samples from 93 non‐carriers (NC) and 155 mutation carriers (MC) ‐presenilin 1, presenilin 2 and amyloid precursor protein genes‐, participating in the Dominantly Inherited Alzheimer Network (DIAN) observational study, and with available longitudinal data on amyloid‐β (Aβ) and tau‐related CSF biomarkers, structural MRI, Pittsburgh compound B PET (PIB‐PET) and cognition. We based our statistical analysis on univariate and bivariate linear mixed effects models.ResultOur recent results showed that longitudinal sTREM2 increase was predicted by the earliest Aβ‐aggregation captured by lower CSF‐Aβ42, but not yet by a higher cortical uptake in PiB‐PET. In line with previous cross‐sectional studies, higher sTREM2 increase rate was associated with slower Aβ‐deposition, as measured by CSF Aβ42 in presymptomatic MC, and by PIB‐PET in symptomatic MC. Furthermore, MC with high or low sTREM2 increase rates had opposite associations between CSF Aβ42 and PiB‐PET longitudinal changes, further suggesting that TREM2 modifies Aβ‐plaque deposition and compaction. Regarding tau‐related pathology, we found that lower sTREM2 increase rate enhanced the increase of CSF p‐tau associated with PiB‐PET signal increase. Finally, higher sTREM2 increase rate in presymptomatic MC was associated with slower cortical shrinkage in the precuneus and slower cognitive decline.ConclusionThe most novel results on longitudinal sTREM2 in CSF position the TREM2 response right after the first pathological changes in Aβ‐aggregation and support its beneficial effect on Aβ‐deposition, Aβ‐dependent tau pathology, cortical shrinkage, and cognitive decline. These findings strongly support ongoing efforts to develop TREM2‐boosting therapies and suggest sTREM2 as a key marker for clinical trial design and interpretation.
Proxy measures of cognitive reserve and trajectories of gait and cognitive decline in older adults
Authors: Jayakody Shanika Oshadi , Ayers Emmeline , Verghese Joe , Weiss Erica , Barzilai Nir , Milman Sofiya , Blumen Helena M 
Published: December 2022

AbstractBackgroundLifestyle interventions are an emerging area of interest in dementia prevention. Education, physical activity, and social interactions are potentially modifiable lifestyle factors that are considered proxies of cognitive reserve. People with greater cognitive reserve could be protected against decline in gait and cognition, two interrelated problems associated with dementia, by coping better with age‐ or pathology‐related brain changes. We examined whether decline in gait and cognitive functions are different in those with higher versus lower levels of education, physical activity, and social interactions.MethodGait and cognitive performance in 1,095 LonGenity study participants (mean age = 75.4±6.7 years) that were free of dementia at baseline were examined up to 12 years. Gait speed was measured during usual pace (single‐task walking, STW‐speed) and walking‐while‐talking (WWT‐speed). Cognitive performance was measured with standard neuropsychological tests and a standardized composite global cognitive measure was derived. Years of education, number of blocks walked per day, living with someone and engaging in paid or volunteer work (markers of social interactions) were obtained from self‐report. Linear mixed‐effects models adjusted for sex, parental longevity, cognitive impairment, and global health were used to examine age‐associated changes in gait and cognition in those with and without greater cognitive reserve.ResultSTW‐speed and WWT‐speed did not vary as a function of education, physical activity, or social interactions. Greater number of blocks walked per day was associated with slower decline in global cognition, Trail Making Test (TMT)‐A, TMT‐interference, digit symbol substitution, logical memory, figure recall, free recall, category and phonemic fluency tests. Higher education was associated with slower decline in global cognition, TMT‐interference, TMT‐A and figure copy task. Living with someone was associated with slower decline in global cognition, digit symbol substitution and logical memory. Paid or volunteer work was associated slower decline in global cognition.ConclusionHaving higher education, more physical activity and social interactions appear to protect against cognitive, but not gait decline, potentially by building up cognitive reserve. The multifaceted etiology and relatively earlier decline of gait may render it less influenced by potentially modifiable risk factors in late life than cognition.
Participant FIRST: Improving Communication With and Support For Participants in Trials that End Early
Authors: Largent Emily A. , Walter Sarah , Edelmayer Rebecca M. ,   The Participant FIRST Work Group
Published: December 2022

AbstractBackgroundIn 2019, multiple AD/ADRD trials ended earlier than planned. Participants subsequently stepped forward explaining they first learned their trial ended via news coverage, rather than from a site investigator or research staff. As a result, the issue of participant notification—and the emotional impact of being in a trial that stops early—gained attention. This led to calls to identify better ways to communicate with and support participants after trials end early.MethodThe multidisciplinary Participant Follow‐Up Improvement in Research Studies and Trials (Participant FIRST) Work Group met throughout 2021. Members included research participants and study partners, clinical trialists and study personnel, as well as representatives from academia, industry, patient advocacy organizations, and the National Institutes of Health. The work group’s goals were: (1) improving communication with research participants and study partners when trials end early and (2) identifying supports for those affected by early stopping.ResultsThe Participant FIRST Work Group identified 17 key recommendations. Pre‐trial recommendations focus on developing a patient‐centered communication plan and ensuring that participants and study partners understand early stopping (e.g., role of DSMBs, stopping rules) and securities laws that shape companies’ announcements of trial stopping and, thus, how disclosure occurs. Mid‐trial recommendations focus on maintaining up‐to‐date contact information; helping participants and study partners build support networks; and reinforcing education on early stopping. Post‐trial recommendations focus on rapidly communicating with participants via multiple modalities; scheduling a personalized close‐out meeting to provide key information about the trial and discuss next steps; collaborating with patient advocacy organizations to provide support to participants (e.g., via a patient hotline); and ensuring that participants receive top‐line results. The work group calls for funders and sponsors to ensure adequate time and resources are available to communicate with and support participants when trials end early.ConclusionParticipants and study partners invest time, effort, and hope in their AD/ADRD research participation. The research community should hold itself accountable and take intentional steps towards better means of communicating with and supporting participants when clinical trials end early. The Participant FIRST recommendations are a practical guide for researchers and sponsors embarking on that journey.
Participant experience in a longitudinal online research registry: Associations between ethnocultural identity, educational attainment, and participant feedback in the Brain Health Registry
Authors: Ashford Miriam T. , Eichenbaum Joseph , Jin Chengshi , Neuhaus John , Ulbricht Aaron , Camacho Monica R , Fockler Juliet , Flenniken Derek , Truran‐Sacrey Diana , Mackin R Scott , Maruff Paul , Weiner Michael W. , Nosheny Rachel L 
Published: December 2022

AbstractBackgroundResearch registries focused on brain diseases, such as Alzheimer’s disease and related dementias (ADRD), have been developed to accelerate clinical study recruitment. Completion of registry components can affect the representativeness of registry populations and data, especially where retention is critical. This study aims to provide insights for online research and retention by studying participants’ perceptions of the Brain Health Registry (BHR), with a focus on those from different ethnocultural and socioeconomic backgrounds.MethodBHR is a public online registry for recruitment and longitudinal assessment focused on cognitive aging and ADRD research. Participants can provide feedback to the study team about their overall experience at any time using a questionnaire and are asked to complete feedback questionnaires after completing the Cogstate Brief Battery (CBB) (Table 1). Multivariable ordinal logistic regression estimated associations between sociodemographic characteristics (ethnocultural identity and education attainment) and feedback responses. All analyses covaried for age and gender.ResultOf all participants (N = 89,673), 5,469 (6.1%) provided feedback about their overall BHR experience and 14,676 (16.4%) provided feedback about CBB (Table 2). See Table 3 for associations between sociodemographic characteristics and feedback responses. Identifying as Latino was associated with a poorer experience with the cognitive assessment. Identifying as Latino or non‐White was associated with perceiving the cognitive assessment instructions as less clear and rating that additional help for cognitive assessment instructions would be useful. Higher educational attainment was associated with perceiving BHR site as easier to use and the instructions as clearer, as well as rating additional help for cognitive assessment instructions as less useful.ConclusionOur findings highlight the need to improve and/or tailor online cognitive assessment design and instructions to better suit the needs of diverse ethnocultural and educational populations. More research is needed to deepen insight into improvements in cognitive assessment design to facilitate engagement and retention of diverse populations.
Multigraph Cluster Analysis of AD Candidate Genes via Human Brain Mapping
Authors: Wu Ruiming Ray , Bao Jingxuan , Kim Mansu , Saykin Andrew J. , Moore Jason H , Shen Li ,   for the ADNI
Published: December 2022

AbstractBackgroundBrain imaging genetics examines associations between imaging quantitative traits (QTs) and genetic factors such as single nucleotide polymorphisms (SNPs) to provide important insights into the pathogenesis of Alzheimer’s diseases (AD). Given the high dimensionality, the individual level SNP‐QT signals typically have small effect sizes and are hard to be detected and replicated. To overcome this limitation, this work proposes a new approach to identify high‐level imaging genetic associations through applying multi‐graph clustering to SNP‐QT association maps.MethodsParticipants include 255 cognitive normal (CN) and 218 late mild cognitive impairment (LMCI) subjects from the ADNI data. Linear regression is performed to regress regional AV‐45 measures on each of the 54 AD SNPs to obtain a brain association map across 116 AAL‐ROIs. To quantify the similarity between each SNP pair, 5 scoring functions are used to calculate 5 different similarity measures between the respective brain maps of the two SNPs. Each scoring function yields a similarity graph of all 54 SNPs. Multigraph min‐max clustering is applied to 5 different graphs simultaneously to group similar SNPs together. Functional annotation is performed on each SNP cluster and the corresponding average brain association map to provide high level interpretations.ResultsFigure 1 shows the genetic effect on regional AV‐45 measures for each pair of SNP and ROI. The multi‐graph clustering result is shown in Figure 2, where 54 AD‐related SNPs are clustered into two groups. Figure 3a shows the results of Enrichr Elsevier pathway analysis. SNP group 1 is associated with pathways such as amyloid beta clearance, while SNP group 2 is associated with pathways including amyloid beta formation and APP processing in AD. Figure 3b shows the NeuroSynth annotation of the average brain effect maps associated with the two SNP clusters, respectively.ConclusionWe proposed an approach that transforms individual level imaging genetic associations (SNP vs ROI) to high‐level associations (i.e., SNP cluster vs brain association map), and applied it to an LMCI study. These high‐level findings have the potential to provide valuable insights into relevant genetic pathways and brain circuits, which can help form new hypotheses for more detailed imaging and genetics studies in independent cohorts.