bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metabolomics profiling reveals distinct signatures in the serum and brain metabolomes in mouse models of Alzheimer’s Disease
Authors: Pandey Ravi S , Hoffmann Brian , Arnold Matthias , Greene Andrew S , Kaddurah‐Daouk Rima F. , Carter Gregory W 
Published: December 2022

AbstractBackgroundProgress in development of efficacious therapies for Alzheimer’s disease (AD) is hampered due to our limited understanding of underlying pathological mechanisms. Increasing evidence suggests that metabolic impairments prior to symptom development can contribute to disease mechanisms and subsequent dementia. Signals in metabolomic pathways conserved across species could provide a promising entry point to translate experimental findings in preclinical mouse models to humans.MethodIn this study, first we systematically investigated sex‐stratified differences of serum and brain metabolites between the APOE4.Trem2*R47H and the 5XFAD mouse models of AD to C57BL/6J controls at six months of age. Metabolite levels were measured using the targeted AbsoluteIDQ®‐p180 platform (Biocrates AG, Innsbruck, Austria). Next, we did P500 panel and supplemented it with four mode discovery metabolomics for the C57BL/6J controls, APOE4.Trem2*R47H, and hAPP.APOE4.Trem2*R47H mouse models at 12 months of age.ResultWe identified strong metabolic sex differences for several classes of metabolites, such as glycerophospholipids, sphingolipids, and amino acids. Further, we identified that serum levels of glycerophospholipids were reduced in APOE4.Trem2R47H mice compared to C57BL/6J controls, while levels of these metabolites in the same animals were greater in both male and female brains of APOE4.Trem2R47H and 5XFAD mice. Several of these findings were consistent with recent results in humans, which suggested a similar decrease in the same metabolites in serum of APOE4 carriers and indicates a serum‐based effect of APOE genotype in the ADNI and ROSMAP cohorts. We simultaneously observed an increase in the same metabolites in brain, consistent across humans and mice. Further, we observed comparable results across different metabolic platforms.ConclusionOverall, metabolomic signatures were notably different between brain and serum in mouse models. The 5xFAD mice exhibited stronger effects in brain, whereas the APOE4.Trem2R47H mouse showed more pronounced effects in serum. These findings are consistent with high levels of amyloid pathology in 5xFAD mouse brains and the modifications of serum biomarkers in APOE4.Trem2R47H mice. We were able to identify patterns of metabolic changes related to human AD in our mice models. Our work thus represents a first roadmap towards translating metabolic dysregulation from model organisms to human AD.
Asymmetries in the theta/beta ratio distinguish cognitively normal elderly from those with mild cognitive impairment
Authors: Martin Tim , Giordani Bruno , Kavcic Voyko 
Published: December 2022

AbstractBackgroundThe search for psychophysiological markers that distinguish normal from abnormal aging has produced many candidate EEG dynamics, but relatively little research has been done (or at least reported) on the theta/beta ratio or brain wave asymmetries.MethodsWe previously reported frontal asymmetries (frontal alpha and frontal beta asymmetry) originally investigated in the context of anxiety and approach‐avoidance motivation that distinguish MCI from healthy, cognitively normal persons (HC). Another potentially more cognitively‐involved marker, the ratio of theta to beta frequencies (TBR), originally investigated as a marker of attention deficits, might also usefully distinguish cognitive HC from MCI. We took advantage of a previously collected data set to conduct an exploratory analysis of the pattern of TBR in HC and MCI participants. Resting state EEG (rsEEG) was measured before and after a simple motion direction discrimination task. We investigated the standard frontal TBR as measured at frontal electrode FZ. We estimated power spectral density in the resting state (eyes closed) for both pre‐ and post‐task, extracting estimates of TBR at electrode Fz.ResultsWe found that MCI had significantly higher TBR than cognitively normal elderly, F(1,95)=4.98, p=0.028, with no effect of timepoint and no interaction. We then explored the possibility that TBR itself has meaningful asymmetries, calculating the TBR asymmetry at the following electrode pairs: F3‐F4, C3‐C4, CP3‐CP4, P3‐P4, PO3‐PO4. This analysis revealed an interesting pattern, with group (HC vs. MCI) interacting with location, F(4,380)=5.25, p<0.001. Relative to HC, MCI participants had higher TBR on the right (positive TBR asymmetry) in frontal electrodes (F3‐F4), but higher TBR on the left (negative TBR asymmetry) over parietal‐occipital sites (P3‐P4 and PO3‐PO4). The parietal asymmetry may reflect the early spread of lesions from inferior temporal regions to areas subserving language and visuospatial processing, but the frontal asymmetry is less obviously tied to known progression of brain lesions, and may reflect heterogeneity in the underlying pathogenesis of this sample of people with MCI.ConclusionTBR asymmetries obtained in rsEEG can contribute significantly to successful discrimination of older persons with MCI from those with normal cognitive functioning.
Analytical Validation of the Quanterix Neurofilament Light Chain (NfL) Advantage Assay in Plasma
Authors: Figdore Daniel , Campbell Michelle R , Syrjanen Jeremy A. , Mielke Michelle M. , Petersen Ronald C. , Bornhorst Joshua A , Algeciras‐Schimnich Alicia 
Published: December 2022

AbstractBackgroundNeurofilament light chain (NfL) is an emerging blood‐based biomarker useful for assessing neuro‐axonal injury in several neurological conditions. Plasma NfL concentrations reflect the extent of axonal damage, making it a general marker of neurodegenerative disease progression. This study evaluates the analytical performance characteristics of the Quanterix NfL Advantage method in EDTA‐plasma.MethodThe assay was performed per manufacturer’s instructions on the Quanterix Simoa HD‐X Analyzer. Analytical validation included analyte stability, imprecision, lower limit of quantification (LLOQ), analytical measurement range (AMR), accuracy, and interferences. One‐sided reference intervals were established using quantile regression methods among 1100 cognitive normal individuals, age 20 to 95 years without known chronic kidney disease, stroke, or myocardial infarction.ResultNfL was stable in plasma three days ambient, seven days refrigerate, 90 days frozen (‐20C), and over 3 freeze/thaw cycles. Intra and inter‐assay imprecision, expressed as % coefficient of variation (%CV), ranged from 3.4 – 6.0% and 5.9 – 11.6% respectively. The LLOQ was evaluated using patient plasma pools at concentrations of 1.7 and 3.6 pg/mL. %CVs were 16.8% and 9.7% respectively, and the LLOQ was set at 3.0 pg/mL. Accuracy was assessed by spiking 5 plasma samples with NfL calibratoran 87% average recovery (range 81‐94%) was observed. The AMR of 3.0 – 1500 pg/mL was verified with a regression slope of 0.93 and r2 > 0.99. Additionally, plasma admixtures covering the AMR showed acceptable linear response (slope of 1.02 and r² >0.99). The assay was not affected by icterus to 100 mg/dL, lipemia to 1000 mg/dL, hemolysis to 1000 mg/dL at NfL concentrations >30 pg/mL or to 200 mg/dL at NfL concentrations ≤30 pg/mL. NfL increased with age but did not differ by sex. The data supported age‐based reference intervals broken down into 10‐year intervals. The 97.5th percentile limits were: 20s: ≤8.4 pg/mL, 30s: ≤11.4 pg/mL, 40s: ≤15.4 pg/mL, 50s: ≤20.8 pg/mL, 60s: ≤28.0 pg/mL, 70s: ≤37.9 pg/mL, 80+: ≤51.2 pg/mL.ConclusionThe analytical performance characteristics of the plasma Quanterix NfL advantage assay were deemed acceptable for clinical laboratory implementation. The establishment of NfL reference intervals will aid in the clinical interpretation of patient plasma NfL concentrations.
Recognizing human functional patterns in IADLs through hand detection and artificial intelligence
Authors: Babatope Eyitomilayo Yemisi , Rodriguez Mario Lopez , García‐Vázquez Mireya Saraí , Álvaro Ramírez‐Acosta Alejandro 
Published: December 2022

AbstractBackgroundCognitive impairment is one of the characteristics shown by patients with Alzheimer's dementia (Montenegro et al., 2020; Kelley & Petersen, 2007). This affects the executive functions of most of these patients from the early stage (Guarino et al., 2019) and consequently, have difficulty in carrying out their daily activities (Dubbelman et al., 2020). These activities require precise coordination of the person's movements and interaction with their environment, so instrumental activities of daily living (IADLs) are predictors of such impairment (Barberger‐Gateau & Dartigues, 1993), as several research studies have shown(Brovelli et al., 2017). Therefore, assessing the performance of IADLs by analyzing human biomechanical markers such as hand movements is of great interest. This, together with the application of artificial intelligence techniques, in particular deep learning, will allow the development of technological tools for the creation of an automated model to support the early diagnosis of Alzheimer's disease.MethodThis work was inspired by the development of Alejandro Acosta et al, where human biomechanical markers were analyzed throughout the performance of IADL activities to recognize the human functional pattern (Acosta‐Franco et al., 2021). To improve the accuracy of the baseline model, we propose a hand detection algorithm based on a probabilistic approach considering skin color as a descriptor. To test the proposed algorithm, we used the dataset of egocentric videos containing the performance of IADL activities, which is organized into four classes, based on the prehensile patterns of the hands: force and precision, and on the kinematics of the instruments: displacement and manipulation.ResultWith the improvement made to the base model we obtained an accuracy higher than 74% in recognizing movement patterns of displacement and manipulation of objects, and a good prediction of the depth of the anatomical planes.ConclusionOur improved model obtained a good percentage of recognition accuracy for the instrument's kinematics, which can help in the development of technological tools for the creation of an automated model to support the diagnosis of early Alzheimer's disease.
Alzheimer’s Disease in Bilingual Latinos: Clinical Decisions for Diagnosis and Treatment Planning
Authors: Diaz‐Santos Mirella , Yanez Janet J , Suarez Paola A 
Published: December 2022

AbstractEarly and accurate identification of cognitive and functional decline in bilingual Latino/a older adults with Alzheimer's disease and related dementias continues to be a substantial public health concern. This paper highlights the heterogeneity in the clinical expression of Alzheimer's disease among bilingual Latino/as, the clinical decisions leading to a culturally and linguistically congruent neuropsychological assessment, and the interdisciplinary, multi‐setting partnerships needed to ensure a healthy longevity post‐diagnosis for the patient, the caregiver, and the family. Psychologists play an important role in advocating for the best standard of care, as the patients and families endure the long journey of care with dignity and respect.
What does it take to get a diagnosis? Dementia recognition and diagnosis pathways among Indigenous peoples
Authors: Jacklin Kristen , Ketcher Dana , Blind Melissa J , Lambrou Nickolas H. , Pederson Collette , Johnson January , Hill Annamarie , Dertinger Melinda , Koski Jessica , Trudeau Rhonda , Pitawanakwat Karen , Strong Lois , Summers Marlene , Martin Wesley , Warry Wayne , Lewis Jordan P , Zuelsdorff Megan , Gleason Carey E. 
Published: December 2022

AbstractBackgroundPatients, caregivers, and providers face an oftentimes‐confusing healthcare terrain around dementia diagnostics and care given the lack of standardization for screening and evaluation of neurocognitive disorders. This can be further compounded by systemic healthcare inequalities and historical and present‐day marginalization faced by Indigenous populations.MethodWe present a segment of a pilot study (NIH R56 AG 62307) which sought to explore the impact of Alzheimer’s disease and related dementias (ADRDs) in Indigenous populations across four diverse settings, three in the United States and one in Canada. Community‐based researchers conducted key informant interviews with healthcare providers (n = 20) and sequential focus groups (SFGs) with local health care staff and formal caregivers (14 sessions, n = 17). Data were coded based on research questions and objectives in consultation with project leaders, coders, and community‐based researchers.ResultIn recognizing a cognitive change, all participants identified the importance of family members who often brought their concerns to the attention of a healthcare provider. Additionally, participants in the US and Canada identified events like hospital admissions as a “catastrophic event” (e.g., injury, missed medication, physical decline) as another route for diagnosis. A unique pathway that Canadian participants identified was the role of personal support workers (PSWs) and community nurses in noticing cognitive changes among individuals they served. Finally, providers mentioned various pathways for receiving a dementia diagnosis. While all providers mentioned taking steps to rule out other reasons for cognitive decline, the specific next step for the diagnosis varied widely. The possible professionals to see for a diagnosis included social workers, family doctors, tribal dementia care specialists, behavioral health specialists, psychiatrists, and neurologists.ConclusionFamily members are crucial in recognizing the changes associated with ADRDs. A strength of the Canadian healthcare system is that PSWs and community nurses can also help identify changes, potentially before hazardous “catastrophic events” bring people to the hospital. Once a cognitive change has been identified, the diagnostic pathway is complicated, non‐standardized, and irregular – in other words difficult to navigate. Policies and procedures need to be put in place, delineating standardized protocols to better help family caregivers and patients dealing with ADRDs.
Aligning PCPS and Patients with Alzheimer’s Research Efforts: MyAlliance for Cognitive Health
Authors: Burns Jeffrey M. , Niedens Michelle , Perales Jaime , Moore W. Todd , Peltzer Jill , Barton Kelli , Berkley‐Patton Jannette , Vidoni Eric D 
Published: December 2022

AbstractBackgroundFailure to engage and enroll participants from diverse backgrounds is among the biggest challenges slowing generalizable research efforts to treat and prevent Alzheimer’s disease and related dementias. Pivoting to a ‘service first’ approach for engaging all communities may increase research participation by improving the value proposition.MethodThe University of Kansas Alzheimer’s Disease Research Center is taking a programmatic approach to accelerate participation in research and emphasize reaching under‐represented groups (URG: predominantly African Americans, Latinos, and rural residents in the region). The program is a community and service‐oriented strategy for engaging a diverse population through 1) a PCP Network to improve dementia care through a financially‐sustainable Chronic Care Management program, 2) a Patient Network (MyAlliance Research Registry, derived from patients in the PCP network), and 3) a Community Network of diverse stakeholders delivering robust outreach and education. We hypothesized that the sustaining value of this approach would increase enrollee diversity.ResultTo date, MyAlliance has provided social work support to 71 practices and 1169 unique individuals with dementia and their families. Over 2100 individuals receive our weekly communications, and 4 community organizations have trained more than 80 staff members in dementia‐capable engagement with the community. The result has been that since implementation of MyAlliance, 29% of enrollments (255 of 868) identify as URG, double the URG enrollment prior to implementation (14.5%, 658 of 4551).ConclusionService‐based approaches that emphasize community needs and community access points may increase enrollment and enrich the diversity of the participants.
A novel whole‐brain imaging pipeline for high resolution spatial and temporal measurements of amyloid‐beta plaque dynamics in pre‐clinical Alzheimer’s Disease animal models
Authors: Ragan Tim , Ferron Gianna , Linehan Stefan T , Sasner Michael , Garceau Dylan , Elk Kevin J 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) has a strong spatial‐temporal component to its progression, where different brain regions are affected by amyloid‐beta (Aβ) plaque deposition at varying time points. Standard imaging and analysis platforms can neglect these details, as they lack the ability to pair high‐yield whole‐brain imaging with region‐specific quantitation. Furthermore, many Aβ analyses require homogenization of tissue, prohibiting secondary analysis. To address this gap, we have developed a novel high‐throughput whole‐brain imaging pipeline for pre‐clinical AD models to quantitatively track plaque progression as a function of brain region across time while producing indexed tissue sections for secondary staining and analysis.MethodAβ plaques in the well characterized 5XFAD mouse model of AD were labeled with Methoxy‐X04, an Aβ plaque‐specific compound, prior to transcardial perfusion and whole‐brain excision. The brains were processed on the TissueCyte Serial Two‐Photon Plus (STP2) imaging platform to produce fully aligned multi‐channel volumetric datasets, yielding high resolution 3D models of each brain. Registration to the Allen Mouse Brain Common Coordinate Framework (CCFv3) and region‐specific plaque analysis were conducted to determine plaque size, density, and total number per animal brain. The regional density of dystrophic neurites (Lamp1) and microglia (Iba1) were segmented and quantified through secondary analysis to evaluate the signal in high and low Aβ growth rate regions for select sections and remapped to the original 3D whole‐brain dataset.ResultThe analysis of whole‐brain plaque distribution in the 5XFAD mouse model revealed distinct spatial‐temporal changes across the brains (Figure 1, Figure 2). STP2 imaging, combined with CCFv3 mapping and secondary analysis of Lamp1 and Iba1 allowed for targeted evaluation of Aβ plaques, and a comparison of regional molecular changes between models.ConclusionOur novel technology has great promise for quantifying the spatial‐temporal Aβ plaque efficacy of AD animal models, and the production of translatable pre‐clinical AD drug discovery data. The high sensitivity and precision of the STP2 platform can benefit region‐specific disease progression compared to standard laboratory approaches.
Tailoring Recruitment Communication using Virtual Human Technology to Increase Participation of Older Minority Adults in Clinical Trials
Authors: Krieger Janice , Anton Stephen 
Published: December 2022

AbstractBackgroundOlder adult minorities are an underserved population, who are at a particularly high risk for developing chronic health conditions and are significantly underrepresented in clinical research. Well‐known barriers, including research‐related mistrust (e.g., belief that participants lack choice, mistrust of white researchers), complicated messaging, lack of cultural diversity/sensitivity among clinical trials staff, and the exclusion of decisional support providers in decision‐ making could impede older adult minority participation in clinal trials.Tailoring content and source preferences to be patient‐ centered, culturally sensitive (i.e., promote feelings of comfort, trust, respect), simple to understand, and personally relevant to the receivers (patients and caregivers) has been linked to positive health behaviors among older adult minorities. Additionally, tailoring is critical to improving comprehension, clear and complete understanding of the messaging. However, tailoring has not been systematically studied as a strategy to increase clinical trial participation rates of older adult minorities, including those with cognitive challenges. Our long‐term goal is to increase clinical trial participation among older adult minorities (Black/African American, Hispanic/Latinx, and/or rural adults over the age of 50) using virtual human technology (VHT). Specifically, we are using community‐based participatory research principles to develop virtual humans that can interact with receivers to deliver tailored intervention content.MethodIn Aim 1, we will conduct focus groups with older adult minorities to redesign ALEX to develop culturally sensitive messages designed specifically for older adults, including those with subjective cognitive difficulties. In Aim 2, we will disseminate the intervention and track engagement of older adult minority participants into active, NIH‐funded clinical trials across different modalities for remotely delivering ALEX. In Aim 3, we will compare whether using ALEX to deliver interactive and tailored clinical trial content is more effective than standard (e.g., static) recruitment materials for enrolling older minorities into NIH‐funded clinical trials.ResultWe will describe patient and caregiver preferences for intervention modality and content.ConclusionAchievement of these project aims is expected to result in an adaptable, minimally tailored VHT recruitment intervention for increasing older adult minority participation rates in active NIH‐funded clinical trials.