bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reduction and Prevention of Agitation in Patients with Neurocognitive Disorders: An International Psychogeriatric Association Consensus Algorithm
Authors: Cummings Jeffrey ,   IPA agitation algorithm work group
Published: December 2022

AbstractBackgroundThe International Psychogeriatric Association (IPA) extends its commitment to serving those with psychiatric and behavioral manifestation in the presence of cognitive impairment and dementia with this introduction of an agitation reduction and prevention algorithm that builds on the definition of agitation developed by IPA.MethodThis presentation describes a review of literature, treatment guidelines, to recommend an algorithm for care and a reiterative integration of expert opinion within the context of an IPA Agitation Work group, a panel of international experts on agitation. The outcome is an integration of available information into a comprehensive algorithm.ResultThe IPA Agitation Work Group recommends the Investigate, Plan, and Assess (IPA) approach to agitation reduction and prevention. A thorough investigation of the behavior is followed by planning and implementation with an emphasis on shared decision‐making; the success of the plan in assessed and adjusted as needed. The process is repeated until agitation is reduced to an acceptable level and prevention of recurrence is optimized. Nonpharmacologic interventions are part of every plan and are continued throughout the process. Pharmacologic interventions are organized into panels of choices for nocturnal agitation, mild‐moderate agitation or agitation with prominent mood features, moderate‐severe agitation, and severe agitation with threatened harm to the patient or others. Therapeutic alternatives are presented for each panel. The occurrence of agitation in a different venues is considered (home, nursing home, emergency depaThe IPA definition of agitation is operationalized into an agitation management algorithm emphasizing the integration of non‐pharmacologic and pharmacologic interventions, reiterative assessment of response to treatment, adjustment of therapeutic approaches to reflect the clinical situation, and shared decision‐making. rtment, hospice), with adjustments to the therapeutic approach.ConclusionThe IPA definition of agitation is operationalized into an agitation management algorithm emphasizing the integration of non‐pharmacologic and pharmacologic interventions, reiterative assessment of response to treatment, adjustment of therapeutic approaches to reflect the clinical situation, and shared decision‐making.
Raindrop animation: Visualizing change in longitudinal biomarker data
Authors: Saef Benjamin A. , Henson Rachel L. , Volluz Katherine , Yarasheski Kevin E. , West Tim , Kirmess Kris , Meyer Matthew R. , Gordon Brian A. , Benzinger Tammie L.S. , Morris John C. , Fagan Anne M. , Schindler Suzanne E. 
Published: December 2022

AbstractBackgroundThe Knight ADRC has collected fluid biomarker data from some participants over more than >15 years, affording a unique opportunity to explore trends in the progression of Alzheimer disease biomarkers. Evaluation of intra‐individual change provides a uniquely powerful approach to understanding the development of Alzheimer disease pathophysiology, notably non‐linear changes in biomarkers. To facilitate understanding of longitudinal analyses, an approach was developed to visualize longitudinal change in biomarkers.MethodSamples from ADRC participants enrolled in studies of memory and aging were analyzed for CSF Aβ40, Aβ42, total tau, and phospho‐tau181 using the fully automated LUMIPULSE assay platform (Fujirebio). Plasma Aβ40 and Aβ42 were measured via a high‐precision immunoprecipitation‐mass spectrometry assay (C2N Diagnostics). Brain amyloid burden was measured within two years of fluid collection via amyloid PET. Biomarker values between measurements were estimated by linear regression. A Shiny application was written in R to visualize estimated longitudinal biomarker values on a granular time scale.ResultThe R Shiny and ggplot2 packages were used to create interactive animated plots of biomarker changes over time. This application utilizes CSF, plasma, and amyloid PET data to display within‐participant longitudinal change of the selected biomarkers as a function of other baseline biomarker measurements. The estimated biomarker value at a timepoint after the baseline is shown as a larger point, and the estimated values from the previous year are shown as smaller points, giving the visual appearance of one raindrop for each individual. The interface allows for users to select the biomarkers represented on each axis, color coding by longitudinal or baseline biomarker values, and biomarker cut‐offs. The user can animate the customized graph to show changes over >15 years of accumulated longitudinal data.ConclusionOur web‐based application allows for visualization of biomarker changes over time. This tool allows for comparison of CSF, plasma, and imaging markers in an interactive format, facilitating the creation of novel hypotheses by observation of longitudinal trends.
Insomnia symptoms and markers of preclinical Alzheimer’s disease in the community
Authors: Nicolazzo Jessica , Cavuoto Marina G. , Gibson Madeline , Rowsthorn Ella , Buckley Rachel F. , Yassi Nawaf , Yiallourou Stephanie , Brodtmann Amy , Hamilton Garun S , Naughton Matthew T , Lim Yen Ying , Pase Matthew P 
Published: December 2022

AbstractBackgroundAmyloid production increases during wakefulness before being cleared during sleep. Insomnia is one of the commonest sleep disorders, yet its relationship to core markers of preclinical Alzheimer’s disease remains unknown. We investigated the cross‐sectional relationship between insomnia symptom severity, APOE e4 carriage, and cerebrospinal spinal fluid (CSF) concentrations of Alzheimer’s disease biomarkers in a non‐demented community‐sample aged 43‐67 years.Method66 participants from the Healthy Brain Project Biomarker Sub‐study (age = 58±6 years; MMSE = 29±7; 68% women) completed a lumbar puncture, two weeks of actigraphy to measure sleep and wake patterns, and the Insomnia Severity Index (ISI) to measure insomnia symptom severity over the past two weeks. The ISI was split into two groups (normal vs. high [>7]) based on established cut‐off values (42% of the sample were high). Two core insomnia features were captured: Difficulty initiating sleep (prolonged sleep onset latency) and difficulty maintaining sleep (high wake after sleep onset (WASO) duration and number of awakenings), with each variable classified as the top 25th percentile versus the remainder of the sample. Analysis of covariance was used to compare CSF amyloid‐beta 42 (Aβ42), phosphorylated tau 181 (p‐tau181), total‐tau, and neurofilament light chain protein (NfL) across each of the sleep groups, adjusting for age and sex.ResultPersons with high insomnia symptom severity had higher CSF Aβ42 levels (p=0.033, d=0.58). Difficulty maintaining sleep (both high WASO and number of awakenings) was also associated with higher Aβ42 levels (p=0.023, d=0.77 for WASO; p=0.013, d=0.92 for awakenings), whereas difficulty initiating sleep was not (p= 0.776, d=0.08). The sleep variables were not associated with p‐tau181, total‐tau, or NfL levels (p>0.05). APOE e4 modified the association between WASO and Aβ42. The strength of the relationship between higher WASO (versus normal) and Aβ42 was stronger in e4 carriers, compared to non‐carriers (F(df) = 6.94 (1, 44), p=0.012).ConclusionIn this relatively young sample, symptoms and features of insomnia were associated with higher CSF Aβ42 levels. These findings may reflect increased amyloid production due to acute sleep disruption. Longitudinal studies are needed to determine whether sustained sleep disruption associates with amyloid accumulation over time.
Rates of cortical thinning in Alzheimer’s disease signature regions: pathological influences and cognitive consequences in members of the 1946 British birth cohort
Authors: Keuss Sarah E , Cash David M , Nicholas Jennifer M , Parker Thomas D , Lane Christopher A , Keshavan Ashvini , Buchanan Sarah M , Wagen Aaron Z , Storey Mathew , Harris Matthew J , Lu Kirsty , James Sarah‐Naomi , Street Rebecca E , Barnes Jo , Malone Ian B , Sudre Carole H , Thomas David L , Dickson John , Murray‐Smith Heidi , Freiberger Tamar , Wong Andrew , Crutch Sebastian J , Richards Marcus , Fox Nick C , Schott Jonathan M , Coath William 
Published: December 2022

AbstractBackgroundConsistent patterns of reduced cortical thickness (so‐called signature regions) have been identified in early Alzheimer’s disease (AD), including in the pre‐dementia stages, but studies investigating the pathological underpinnings and cognitive consequences of longitudinal changes in these regions have been limited.Method337 cognitively normal participants (mean [SD] age 70.5 [0.6] years) underwent 18F‐florbetapir amyloid‐ß PET, volumetric MRI, and cognitive assessment as part of Insight 46, a sub‐study of the 1946 British birth cohort (Table 1 for characteristics). Baseline and follow‐up T1‐weighted MRI (mean [SD] interval 2.4 [0.2] years) were processed using Freesurfer’s longitudinal stream (v.7.1.0) and cortical thickness was derived in two AD signatures (Table 2 footnote for details). Linear regression was used to test whether rates of change in AD signature cortical thickness were influenced by baseline amyloid‐ß deposition (positive/negative status or continuous SUVR) or white matter hyperintensity volume (WMHV; a marker of presumed cerebrovascular disease), and whether they were related to longitudinal cognitive change as measured using the Preclinical Alzheimer Cognitive Composite (PACC). Covariates included sex, age at baseline scan, childhood cognition, educational attainment, and socioeconomic position. Interaction terms were added to test whether associations with longitudinal cognitive change differed by baseline amyloid‐ß status.ResultHigher baseline WMHV was associated with faster rates of cortical thinning in AD signature regions, but baseline amyloid‐ß status and SUVR were not (Table 2; Figure 1). There were differential effects of rates of change in AD signature cortical thickness by baseline amyloid‐ß status, whereby greater rates of AD signature cortical thinning predicted faster rates of PACC decline in amyloid‐ß positive participants only (Table 3; Figure 2).ConclusionCortical thinning in AD signature regions may arise via non‐amyloid‐ß pathways in cognitively normal elderly. However, the presence of amyloid‐ß may make individuals more susceptible to the effects of faster rates of cortical thinning in these regions (or vice versa) since these factors interact to influence rates of cognitive decline. These findings provide insight into processes that might underlie progression to dementia in later life and have implications for the utility of AD signature cortical thickness as a biomarker in the preclinical phase of AD.
Single and chronic administration of cellulose ethers rescue memory deficit in a transgenic mouse model of Alzheimer’s disease
Authors: Ali Tahir , Klein Antonia N. , Vu Alex , Doh‐ura Katsumi , Gilch Sabine 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is an incurable neurodegenerative disease and the major cause of dementia. Recent studies including our findings showed that cellulose ethers (CEs) derivative (TC‐5RW) treatment as a single subcutaneous (SC) dose (4g/kg) have therapeutic effects in neurodegenerative diseases via inhibiting the aggregation of misfolded proteins such as prions and amyloid beta (Aβ). CEs are approved by the FDA as safe, inactive ingredients in foods and pharmaceuticals. Therefore, in this study we aimed to test whether single and repeated treatment with the CE TC‐5RW improves cognitive functions in an animal model of AD.MethodsWe used the 5xFAD mouse model, which harbours five familial AD mutations. The 5xFAD mice co‐overexpress human amyloid precursor protein and presenilin‐1, resulting in overproduction of Aβ and memory deficit. At the age of 6 weeks, one group of 5xFAD mice was treated with a single dose of TC‐5RW (4g/kg/SC) while another group of mice was treated weekly with TC‐5RW (4g/kg/SC) until 7 months of age. Two other groups of mice, wild type (WT) of same background and non‐treated 5xFAD mice were included as controls in our experiment. After completion of TC‐5RW treatment, behavioral studies (novel object recognition (NOR), Y‐maze and contextual fear conditioning (CFC) tests) were performed.ResultsIn the NOR and Y‐maze tests, we observed a reduced percentage of recognition index and spontaneous alteration behavior in 5xFAD mice compared to WT mice. The TC‐5RW treatment at single and chronic dosage significantly increased the percentage of recognition index and spontaneous alteration behavior in 5xFAD mice compared to non‐treated 5xFAD mice. Similarly, the CFC test results showed a lower percentage of time freezing in 5xFAD mice compared to WT mice. Interestingly, TC‐5RW at both dosage regimen significantly improved the percentage of time freezing in 5xFAD mice compared to non‐treated 5xFAD mice.ConclusionIn summary, single and chronic administration of TC‐5RW induce beneficial effects via improving learning and memory functions of 5xFAD mice. These results demonstrate that CE based compounds might be valuable and emerging therapeutics for the prevention and treatment of AD.
Circulating plasminogen activator inhibitor‐1 (PAI‐1) levels in the preclinical stage of Alzheimer’s disease
Authors: Eruysal Emily , Iadecola Costantino , Ishii Makoto 
Published: December 2022

AbstractBackgroundPlasminogen activator inhibitor‐1 (PAI‐1), a secreted glycoprotein and member of the serine protease inhibitor family, has been implicated to have a role in Alzheimer’s disease (AD) pathogenesis by regulating amyloid‐beta (Aβ) accumulation (Neurobiol Aging 32:1079,2011; J Alzheimers Dis. 64:447,2018). A recent study found that plasma PAI‐1 was differentially expressed in subjects with Aβ pathology and neurodegeneration (A+TN+) compared to A‐TN‐ subjects, with decreased plasma PAI‐1 levels in clinical AD compared to cognitively normal controls (Alzheimers Dement 17:1452,2021). However, whether circulating PAI‐1 levels are altered during the preclinical stage of AD, where there is Aβ and tau pathology but no significant cognitive impairment, remains unclear.MethodCognitively normal (Clinical Dementia Rating of 0) volunteers from the Healthy Aging & Senile Dementia and Adult Children Study (Missouri, USA) with body mass index < 30, fasting plasma and cerebrospinal fluid (CSF) samples were included in this cross‐sectional study. Preclinical AD was defined by previously established CSF criteria (preclinical AD: 29 men, 26 women; control: 35 men, 65 women). Plasma PAI‐1 levels were measured by a commercially available immunoassay (MilliporeSigma) and log transformed.ResultIn men, plasma PAI‐1 levels were significantly lower in preclinical AD compared to control subjects (p=0.029) and were associated with CSF Aβ42 and p‐tau181 levels (CSF Aβ42: age‐adjusted beta coefficient 0.38, p=0.007; CSF p‐tau181: age‐adjusted beta coefficient ‐0.32, p=0.026) but not CSF tau levels (p>0.05). In women, there was no significant difference in plasma PAI‐1 levels between preclinical AD and control subjects (p>0.05).ConclusionThese studies raise the possibility that, in men, alterations in peripheral PAI‐1 occur during the earliest stages of AD. Studies in larger cohorts will be needed to confirm these observations and to determine their clinical utility and the underlying mechanisms of any sex differences.
Human microRNA‐298 plays a vital role in maintaining APP and tau homeostasis and IL‐induced inflammation: Implication in Alzheimer’s disease.
Authors: Wang Ruizhi , Maloney Bryan , Long Justin M , Sambamurti Kumar , Counts Scott E. , Lahiri Debomoy K 
Published: December 2022

AbstractBackgroundAlzheimer’s disease (AD) is marked by neurofibrillary tangles mainly composed of hyperphosphorylated microtubule‐associated protein tau; senile plaques comprising amyloid β (Aβ) peptides; and neuroinflammation. How these pathological changes are regulated remains unclear. Genetic, epigenetic, and environmental factors play important roles in disease progression. MicroRNA (miRNA), a group of small non‐coding RNAs, regulates multiple biological and pathological processes by binding to target mRNAs and altering translation levels. Disrupting this process could contribute to AD pathogenesis. We hypothesize that miR‐298 plays a vital role in maintaining APP and tau homeostasis and IL‐induced inflammation, particularly gliosis.MethodWe performed miR‐298 treatments and blockade by antisense‐miR298 (antagomiRs) in 3’UTR‐reporter clone‐transfected cultures and protein levels from target native mRNAs (Chopra et al‐Mol. Psychiatry‐2021). We transfected human astrocyte cells with miR‐298 mimics or antagomiRs. We analyzed culture media and lysates for protein and mRNA. We performed ELISA and real‐time‐qPCR assays to determine cytokines, APP and tau levels. We analyzed autopsy brain tissues from non‐cognitively impaired (NCI) and AD subjects by measuring levels of miR‐298, target mRNAs and proteins in cortical samples, as we described (Wang et al‐Mol. Psychiatry‐2022).ResultWe identified putative sites for miR‐298 in mRNAs encoding APP, BACE1, MAPT, IL1α, and IL6. Treatment by miR‐298 significantly increased production and secretion of multiple pro‐inflammatory cytokines, specifically IL‐1, IL‐6 and TNF‐α in human astrocyte cultures. Furthermore, treatment by miR‐298 reduced tau, APP and BACE1 protein and mRNA levels in astrocyte cultures. Levels of miR‐298 varied in postmortem human temporal lobe between AD patients and age‐matched NCI controls.ConclusionMiR‐298 induced a variety of pro‐inflammatory cytokines without administration of other challenges. Induction of multiple cytokines may be due to combinations of direct miRNA activity and regulation of upstream signaling pathways. MiR‐298 may play an important biological role in AD by reducing APP, BACE1 and tau expression while increasing the physiologic production of IL cytokines. This apparent paradox is resolved by noting that early‐stage (prodromal) gliosis may contribute to the clearance of toxic aggregates. We plan to test miR‐298 in AD animal models, including human tau‐overexpressing transgenic mice.We appreciate NIH‐NIA grants: (R01AG051086, R21AG056007, R56AG072810, P01AG014449, P30AG072976).
Classification of amyloid positivity in PET imaging using end‐to‐end deep learning: a multi‐cohort, multi‐tracer analysis
Authors: Fan Shuyang , Ha Sung Min , Chakrabarty Satrajit , Lee John , Flores Shaney , LaMontagne Pamela , Gordon Brian A. , Raji Cyrus A. , Benzinger Tammie L.S. , Morris John C. , Ances Beau M , Marcus Daniel S. , Sotiras Aristeidis 
Published: December 2022

AbstractBackgroundPositron emission tomography (PET) imaging with amyloid‐specific tracers is the gold standard for assessing amyloid positivity in vivo. However, visual interpretation of PET images is limited by availability of clinicians and interobserver variability. Classification of amyloid status typically requires calculation of standardized uptake value ratios (SUVRs), Correspondence with neuroanatomy from magnetic resonance imaging, and additional complex, computationally intensive preprocessing steps requiring specialized software. We developed a deep learning model that can automatically classify unprocessed PET images as amyloid positive or negative.MethodFlorbetapir (AV45), florbetaben (FBB), and Pittsburgh compound B (PiB) images from the Alzheimer’s Disease Neuroimaging Association (ADNI), AV45 and PiB images from the Open Access Series of Imaging Studies 3 (OASIS3), and FBB, flutametamol (FMT), and flutafuranol (NAV4694) images from the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL) were used (Table 1). Each image was resized to isotropic 2 mm voxels, and voxel intensities between the 5th and 95th percentile were normalized to zero mean and unit variance. We trained and internally validated a convolutional neural network (CNN) on AV45 images from ADNI before testing it on images from an independent cohort and/or acquired with a different tracer.ResultThe model achieved an AUC of 0.98 [0.97, 1.0] on test AV45 images from ADNI and generalized well to AV45 images from OASIS3, achieving an AUC of 0.95 [0.92, 0.97] (Table 2). Critically, the model’s performance remained robust even when evaluating imaging from different tracers, including FBB, FMT, PiB, and NAV4694, scoring an AUC of at least 0.97 on each and demonstrating its ability to learn a tracer‐agnostic pattern of abnormality. Similar conclusions can be drawn from other performance metrics.ConclusionWe developed a deep learning model that can classify amyloid PET scans with a high degree of accuracy. We demonstrated that the model generalizes well to unseen images acquired from an independent cohort, under a different protocol, and/or with tracers unseen during training. Our model may usefully provide concise metrics for amyloid research as well as support clinical assessment of amyloid‐specific PET when expertise or computational resources are limited.
How Researchers Can Build Research‐Strengthening Partnerships Through Centering the Lived Experiences of Self‐Identified Members of African American/Black Communities
Authors: Aggarwal Neelum T. , Glover Crystal M 
Published: December 2022

AbstractBackgroundPersons who self‐identify as Black or African American comprise more than 14% of the population in the United States of America, with Black persons populating the entire globe. Notably, heterogeneity and within‐group diversity exist, especially due to geographic location, migration, and immigration. However, researchers continue to conduct studies that do not adequately represent this critical group of individuals with a higher risk of Alzheimer’s disease and related dementias (ADRD) coupled with salient experiences of negative structural and social determinants of health. ADRD research requires diverse participant perspectives to ensure that research findings – from educational materials to lifestyle interventions and pharmacologic discoveries are safe and relevant to all of us. This presentation will feature a panelist with both lived dementia experience and who identifies as African American/Black. The panelist will provide their perspectives and input to identify and address barriers, and amplify facilitators of ADRD research participation.MethodResearchers at the Rush Alzheimer’s Disease Center will work with community partners to identify the panelist to share their perspectives regarding such topics as ADRD diagnosis, care, and research participation. The panelist will also share their input on how researchers can build better partnerships within African American/ Black communities and subsequent study participants and partners.ResultThis session will benefit researchers and the field of ADRD by offering the opportunity to hear and understand the lived experiences of a member of the African American/Black community, and discuss strategies to meaningfully engage with demographically diverse communities and their heterogenous members.ConclusionThe voices of individuals identifying as African American/Black are essential to consider and incorporate throughout the research process ‐ from determining the research purpose and discussing research priorities to study conduct and finding dissemination ‐ and addressing challenges to facilitate demographically diverse participation in ADRD research.