bluuebunny/crossref_metadata_2025_split huggingface dataset:
Military Service and Cognitive Decline after age 90: The LifeAfter90 Study
Authors: Lor Yi , George Kristen M. , Peterson Rachel L. , Gilsanz Paola , Corrada Maria M. , Meunier Claire C. , Soh Yenee , Kawas Claudia H. , DeCarli Charles S. , Whitmer Rachel A. 
Published: December 2022

AbstractBackgroundStudies have shown that military veterans are at higher risk of dementia. Less is known about cognitive aging and decline, especially among veterans who have survived past age 90. We investigated the association of military service with cognitive function and decline in the LifeAfter90 (LA90) cohort.MethodLA90 included Asian, Black, Latino, White, and multi‐racial individuals aged 90 years or more without a history of dementia diagnosis at recruitment. We assessed active US military service via self‐report at baseline. Due to the small number of women reporting military service (n = 5), analyses were restricted to men participants. Cognitive domains of executive function, verbal episodic memory, and semantic memory were assessed every six months using the Spanish and English Neuropsychological Assessment Scales (z‐standardized). Linear mixed models with random intercepts and slopes evaluated the association between military service with cognitive change over 3 visits (mean = 1.2 years), adjusting for years since baseline, baseline age, education, practice effects (indicator variables for visits 1 and 2), and interview mode (phone vs in‐person).ResultOf the 195 participants, 151 (77%) had served in the active military (Table 1). Those who served in the military had, on average, higher baseline executive function (β[95% CI] = 0.33[0.13, 0.54]) and semantic memory (β[95% CI] = 0.53[0.24, 0.82]) compared to those who did serve in the military; there was no difference in baseline verbal episodic memory (Table 2; Model 2). Those who served in the military had slower decline in verbal episodic memory (β[95% CI] = 0.35[0.07, 0.63]), compared to those who did not serve. Point estimates suggest slower decline in executive function and semantic memory for those who served in the military but were not significant.ConclusionAmong the oldest‐old men, military service was associated with higher baseline executive function and semantic memory, and slower decline in verbal episodic memory compared to not having served in the military. Future research may explore whether veteran benefits in educational or financial support, such as the GI Bill, help explain the apparent protective effects of veteran status.
Lysosomal ion homeostasis as a novel biomarker for Alzheimer's disease
Authors: Connolly Owen , Wahdan Malak , Deivasigamani Senthilkumar , Krishnan Yamuna , Modi Souvik 
Published: December 2022

AbstractBackgroundProtein clearance and neuronal homeostasis critically depend upon normal functioning of autophagy and endo‐lysosomal pathways (Nixon, 2020; Usenovic & Krainc, 2012). Multiple studies show that lysosomal dysfunction is associated with Alzheimer’s disease (AD), since impaired degradation of aggregate‐prone proteins can lead to pathological accumulations of Aβ plaques and neurofibrillary tau tangles (Baranello et al., 2015; Rajendran & Annaert, 2012). To leverage this paradigm shift in our understanding of AD pathology, we have invented a pioneering, ion‐imaging technology using DNA nanodevices to non‐invasively map lysosomes for early AD detection.MethodOur lysosomal ion reporters are short DNA duplexes that simultaneously measure the concentrations of two ions ratiometrically, such as H+ and Ca2+. We used dermal skin fibroblasts from a clinically diagnosed cohort of 120 samples comprising healthy individuals, AD, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s and Huntington’s disease patients. Using our lysosome mapping technology, we identified five distinct, AD‐related lysosomal features. A model probability score of predicting AD was calculated using a logistic binary regression.ResultLysosomal ion profiles in age‐matched control groups showed significant differences compared to AD patients. Firstly, lysosomes from AD samples were found to be significantly more acidic and harbored more calcium than healthy samples. Secondly, resolving lysosomes into populations based on their pH and Ca2+ levels revealed that two distinct lysosomal populations are significantly altered in AD. Our assay is 88% accurate (AUC: 0.91, 95% CI :0.84‐0.97) at identifying AD from other healthy and non‐AD related individuals with dementia. Further, we could detected AD‐related lysosomal dysfunction more than 19 years prior to symptom manifestation.ConclusionOur novel ion‐mapping technology reports the ionic composition of single lysosomes of cultured cells. This enables early detection of AD in individuals who are either pre‐symptomatic, AD symptomatic, or suffer from other non‐AD dementia. This unique technology will allow us to build a drug discovery pipeline where we can specifically monitor the effect of pharmacological interventions and their impact on selective lysosomal populations, enabling personalized medicine for AD and other neurodegenerative diseases.
Quantum Dot loaded BQCA‐Octadecylamine conjugate nanosystems for theranostic applications in Alzheimer’s Disease.
Authors: Chintamaneni Pavan Kumar , Krishnamurthy Praveen Thaggikuppe , Pindiprolu Saikiran S.S , Sathyamoorthy NandhaKumar 
Published: December 2022

AbstractBackgroundAlzheimer’s Disease (AD) is one of the most common types of dementias in the world and is characterized by progressive, irreversible neurodegeneration. Benzyl quinolone carboxylic acid was shown to have beneficial in management of AD. The current challenge with BQCA is its low brain half‐life, permeability and rapid elimination. The above challenge can be answered by formulating lipid drug conjugates of BQCA, with octadecyl amine (BQCA‐ODA). Quantum dots (QDs) with their unique optical properties, with high sensitivity and stability emerging as theranostic agents in several neurodegenerative diseases. Hypothesizing the co‐delivery of QDs and BQCA for the effective treatment of AD, in the present study we have formulated lipid nano carriers loaded with quantum dots (QDs) surface modified with Polysorbate 80, called PS80‐QD‐BQCA‐ODA‐NPs, for integrating imaging and therapy for effective management of AD.MethodBQCA was conjugated to Octadecyl amine (ODA), to form BQCA‐ODA LDC conjugate. The amphiphilic nature of the BQCA‐ODA conjugate allows the formation of self‐assembled nanoparticles. Here, we have employed solvent injection method followed by sonication, while addition of QDs in the organic phase and P80 in the aqueous phase to form PS80‐QD‐BQCA‐ODA‐NPs . The optimized formulation was evaluated for physicochemical properties (particle size, zeta potential and polydispersity index) surface morphology and in vitro drug release. The in vitro biocompatibility of the PS80‐QD‐BQCA‐ODA‐NPs was assessed on RBC and SHSY‐5Y cell lines. Further the application of PS80‐QD‐BQCA‐ODA‐NPs was assessed by in vivo imaging and behavioural studies on STZ induced mice models of AD.ResultThe formation of BQCA‐ODA conjugate formation was confirmed 13C‐NMR, 1H‐NMR, LC‐MS. The optimized PS80‐QD‐BQCA‐ODA‐NPs were found to have a near spherical shape with a particle size (PS) of 152.62 ± 1.82 nm, zeta potential (ZP) of 18.59 ± 0.56 mV and polydispersity index (PDI) of 0.214±0.08. PS80‐QD‐BQCA‐ODA‐NPs. The NPs shown improved brain permeability, with greater fluorescence intensity in mouse brains when compared to free QDs. In the in vivo efficiency studies PS80‐QD‐BQCA‐ODA‐NPs shown a significant improvement in memory in mice models.ConclusionThe PS80‐QD‐BQCA‐ODA‐NPs nanomedicine was successfully prepared, thoroughly characterized and has shown theronostic benefits in AD mice models.
Information Communication Technology as Instrumental Activities of Daily Living for Aging‐in‐Place in Chinese Older Adults with and without Cognitive Impairment
Authors: Ho‐yin Lai Frank 
Published: December 2022

AbstractBackgroundThe capability in applying information communication technology (ICT) is crucial to older peoples’ functional independence of community living nowadays. The proper assessment of individuals’ capability of ICT application is the corner stone for the future development of telemedicine in our aging population.MethodWith recruitment of 300 participants of different functional and social background in home‐living, hostel‐living and care‐and‐attention home living; and through assessing individuals’ ability in instrumental activities of daily living and cognitive assessments, this study aimed at capturing the content validity and construct validity of the Advanced Instrumental Activities of Daily Living (AIADL scale) and to assess the ability of older peoples’ in applying ICT and how the functional and social background affects their independence in aging‐in‐place.ResultThe AIADL scale showed good test‐retest reliability and good‐to‐excellent internal consistency. In determining if the AIADL scale’s items measure various aspects of community living, exploratory factor analysis revealed a two‐factor structure with “home living and management” and “community living”. Validity analysis with the known‐groups method showed a high overall accuracy of prediction of individuals’ capability of independent living in the community.ConclusionThe AIADL scale is a valid and reliable instrument to assess older adults’ ability in handling ICT as part of their instrumental activities in daily living. The scale can reflect older peoples’ capability in applying ICT. This instrument can serve as a reference in measuring individuals’ readiness in receiving tele‐medicine and their ability of aging‐in‐place.
Improving Early Detection of White Matter Degeneration in Aging and Dementia along the AD continuum
Authors: Moody Jason F , III Douglas C Dean , Kecskemeti Steven R , Johnson Sterling C. , Alexander Andrew L , Bendlin Barbara B. 
Published: December 2022

AbstractBackgroundDiffusion tensor imaging (DTI) has been commonly used to characterize microstructural changes associated with aging and Alzheimer’s disease (AD) dementia. However, DTI ignores non‐Gaussian diffusion, which limits its ability to describe the more restricted diffusion present within cellular structures. Neurite Orientation Dispersion and Density Imaging (NODDI) and Mean Apparent Propagator (MAP) MRI are two alternative diffusion MRI (DWI) models which can be used to calculate parameters that better characterize alterations observed in tissue microstructure.To investigate the sensitivity of DTI, NODDI, and MAP to white matter changes associated with aging and dementia, we examined the relationship between 15 DWI parameters, age, and AD clinical status in 418 aging adults along the AD continuum.Methods418 participants (328 cognitively unimpaired [CU], 60 Mild Cognitive Impairment [MCI], 30 AD) from the Wisconsin Registry for Alzheimer’s Prevention and the Wisconsin Alzheimer’s Disease Research Center were imaged with multi‐shell DWI (Table 1). 15 DWI parameters were extracted from the cingulum, including 4 DTI (FA, MD, RD, AxD), 3 NODDI (ODI, NDI, ISO) and 8 MAP (RTOP, RTAP, RTPP, MSD, QIV, NG, NG||, NG⊥) metrics. All measures were fit to the following linear model:Diffusion Metric = β0+β1
*(age)+ β2
*(sex)+β3
*(status)+β4*(age*status)+ΕResultsDWI age trajectories and model parameters are provided in Figures 1‐2 and Tables 2‐4, respectively. 12 of 15 DWI metrics were significantly associated with age, including all 8 MAP measures. Additionally, 6 metrics were associated with AD and 8 were associated with MCI. The interaction between age and AD was significant for RTOP, NDI, FA, and AxD, while the interaction between age and MCI was significant for RTOP, RTPP, MSD, NG, NG⊥, ISO, MD, RD, and AxD (Pcorr = 0.05).ConclusionThe significant effects of clinical status and interactions between age and clinical status, may indicate that these metrics are sensitive to microstructural alterations specific to dementia. Furthermore, the meaningful interactions between age and MCI in 5 of 8 MAP parameters suggests that MAP MRI may be particularly useful for detecting early WM degeneration along the AD continuum. Future work will translate this analysis to larger cohorts and assess MAP parameters in gray matter.
Speed of cognitive decline in biomarker stratified SCD subgroups
Authors: Jessen Frank , Kleineidam Luca , Wolfsgruber Steffen , Spottke Annika , Brosseron Frederic , Laske Christoph , Perneczky Robert , Schneider Anja , Wiltfang Jens , Teipel Stefan , Bürger Katharina , Priller Josef , Peters Oliver , Ramirez Alfredo , Boecker Henning , Heneka Michael T. , Wagner Michael , Duzel Emrah 
Published: December 2022

AbstractBackgroundSubjective cognitive decline (SCD) is associated with an increased risk of cognitive decline and dementia, specifically in cases in the Alzheimer’s continuum (amyloid positive, A+). In the present study we tested, if further stratification with additional markers is useful for identifying fast progressors within SCD‐A+.MethodThe analysis is based on 170 SCD case of the multicenter memory clinic based DELCODE study in Germany. The following markers were used as predictors of cognitive decline: number of SCDplus criteria, CSF Aß42/Aß42, tTau, pTau181, APOE status and hippocampal volume. The outcome was the preclinical Alzheimer’s cognitive composite 5 (PACC5) over up to 5 years. Univariate and multivariate hierarchical regression models were calculated with continuous (a) and dichotomized (b) variables.ResultIn the univariate analyses significant or close to significant associations of Aß42/Aß42 (a:p = 0.012; b:p = 0.040), tTau (a:p = 0.034; b:p = 0.053) and pTau181 (a:p = 0.057; b:p = 0.019) with cognitive decline were observed. In the hierarchical model with continuous variables, only Aß42/Aß40 reached significance (p = 0.016); while dichotomized variables Aß42/Aß40 (p = 0,074) and pTau181 (p = 0.068) reached trend level significance.ConclusionWithin SCD‐A+, those who are also pTau positive show greatest decline. This finding is in agreement with the concept of A+ and T+ indicating full Alzheimer’s disease pathology and is important for the design of clinical trials in SCD.
Impact of background strains and diet on metabolic profile in mouse model of Alzheimer’s disease
Authors: Kaur Harpreet , Dai Miko , Dunn Amy R , O'Connell Kristen MS , Hoffmann Brian , Kaczorowski Catherine C. 
Published: December 2022

AbstractBackgroundGenetic background is known to significantly affect the behavioral and molecular phenotypes in mice and has been well documented over many disease areas including Alzheimer’s disease (AD). However, how different background strains and their interaction with environmental factors such as high fat diet (HFD) could have an impact on metabolic phenotypes in AD not known.MethodTo determine how genetic background, diet, sex and age contributes to the metabolic profile in AD, 2.5 months old male and females 5xFAD mice on C57BL/6J (B6) and B6D2 background were fed either normal chow diet, or 45% high‐fat diet till 6 or14 months of age and compared to their age matched non‐transgenic littermate controls. Blood plasma samples were collected and a four‐mode discovery metabolomics approach on a Q‐Exactive Orbitrap coupled to an ultra‐high‐performance liquid chromatography (UHPLC) system was used to analyze metabolic changes.ResultFollowing the quality assessment of spectral data, the dataset contained a total of 21,746 features across C18 and HILIC columns run with negative and positive ionization. After further filtering for named metabolites, removing duplicates, and a Fragment Ion Search (FISh) Score > 10, a total of 3,199 unique metabolites with high confidence MS2 fragmentation remained. Using linear regression analysis on these unique metabolites, we found that diet has a substantial impact (of all the factors tested including diet, sex, age, background strain, genotype) on plasma metabolites in both the strains with and without 5XFAD genotype, both in positive and negative mode of C18 and HILIC columns. Further on examining the interactive effects of different factors, we found a stronger interaction effect of sex by diet on metabolic phenotype. Interestingly, background strain had a moderate influence on collective metabolites irrespective of sex and age of mice.ConclusionOur initial results suggest that HFD is a major factor in defining the metabolic profile in AD mice above background strain, that could affect AD pathophysiology. We are currently looking into various classes of metabolites altered following HFD feeding and performing metabolic pathway analysis to understand the underlying disease mechanisms.
Association Between Neuropsychiatric Symptoms and Blood‐Based Autoantibody Biomarkers
Authors: Emrani Sheina , DeMarshall Cassandra , Viviano Jeffrey , Godsey George , Sarkar Abhirup , Belinka Benjamin , Libon David , Nagele Robert 
Published: December 2022

AbstractBackgroundNeuropsychiatric symptoms are frequently observed along the Alzheimer disease (AD) continuum. Recent research has shown that blood‐based biomarkers are able to identify early AD‐related pathological changes associated with (1) preclinical AD (before the onset of clinical/functional symptoms), (2) mild cognitive impairment (MCI; with clinical symptoms and relatively spared functional decline), and (3) AD (obvious clinical and functional symptoms). Evidence for the potential diagnostic utility of serum autoantibodies has been extensively studied. The purpose of this study is to explore whether blood levels of specific autoantibodies used in the diagnostic biomarkers panels are linked with specific behavioral changes observed along the AD continuum.MethodUsing a customized panel of three AD‐specific autoantibody biomarkers and Luminex xMAP® technology, sera from patients (n=46; female = 30, mean age = 73.4) from the Memory and Aging Program at Rowan University were analyzed. All patients, irrespective of diagnosis (cognitively normal, MCI, AD) were included. The Neuropsychiatric Inventory (NPI) was used to gather data pertaining to neuropsychiatric symptoms. Partial correlations, controlling for age and education, for each neuropsychiatric symptom was employed.ResultTwo of the three autoantibody biomarkers showed an association with neuropsychiatric symptoms. Biomarkers 2 and 3 both showed a significant correlation with total neuropsychiatric score (r= .255, p= .047; r= .345, p= .01, respectively). Delusions, hallucinations, depression, anxiety, and irritability symptoms were not associated with either biomarker. Biomarker 2 was associated with apathy (r= .365, p=.007), agitation (r= .345, p= .011), disinhibition (r=.316, p=.018), and appetite changes (r= .302, p= .023). Biomarker 3 was associated with elation (r= .328, p= .015), aberrant motor behaviors (r= .331, p=.014), sleep behaviors (r= .483, p=.001), and appetite changes (r= .372, p=.006).ConclusionResults demonstrate an association between neuropsychiatric symptoms often observed in the AD continuum and specific blood‐based autoantibody biomarkers using Luminex xMAP® bead‐based technology. The autoantibody biomarker panel serves as an accurate, non‐invasive, and inexpensive diagnostic screener for preclinical AD, MCI, and AD. These biomarkers can not only distinguish different stages of AD, typically diagnosed using cognitive/functional assessments, increased blood levels of specific autoantibody biomarkers are also associated with commonly observed neuropsychiatric features.
Automated Analysis of Written Language in the Three Variants of Primary Progressive Aphasia
Authors: Josephy‐Hernandez Sylvia E. , Rezaii Neguine , Jones Amelia , Hochberg Daisy , Quimby Megan , Wong Bonnie , Dickerson Bradford C. 
Published: December 2022

AbstractBackgroundDespite the important role of written language in everyday life, abnormalities in functional written communication have been sparsely investigated in PPA.MethodWe developed a Python program which uses a language parser and quantifies content units (CU) and total utterances in language samples. The program was used to analyze written descriptions of the WAB Picnic scene, based on a pre‐defined CU corpus, from a cohort with 95 participants (20 controls, 28 nonfluent variant Primary Progressive Aphasia (nfvPPA), 30 logopenic variant (lvPPA), 17 semantic variant (svPPA)). We then compared written functional communication between the three PPA variants and controls. We analyzed the measurements in relation to aphasia severity (Progressive Aphasia Severity Scale Sum of Boxes (PASS SoB) and Clinical Dementia Rating Supplemental Language (CDR‐L) scores), and dementia severity (Clinical Dementia Rating Sum of Boxes (CDR SoB)).ResultThe reliability of the automated analysis was high as compared to manual scoring of 239 samples (99.6%). One‐way ANOVAs revealed patients with lvPPA and svPPA wrote fewer CU than controls (mean+/‐SD 11.97+/‐7.87 and 10+/‐4.5, vs 18.5+/‐9.32) (F(3, 91)=[4.897], p=0.003). There was a trend towards a decrease in CU in nfvPPA (13.89+/‐6.33) (p=0.144). Patients with all PPA subtypes (nfvPPA mean+/‐SD 34.64+/‐18.89; lvPPA 38+/‐24.54; svPPA 28.88+/‐20.36) wrote fewer total utterances than controls (61.7+/‐27.86) (F(3, 91)=[7.778], p<0.001). The CU/utterance ratio was higher in nfvPPA and svPPA than in controls and lvPPA (0.42+/‐0.14 and 0.43+/0.22 vs 0.3+/‐0.05 and 0.32+/‐0.12 respectively) (F(3, 91)=[5.592], p=0.001). Considering all PPA samples, regression analysis showed a decrease in CU relative to an increase in PASS SoB (R=0.24, p=0.04), CDR‐L (R=0.22, p=0.06), and CDR SoB (R=0.34, p=0.004).ConclusionAs expected, we found impairments in informative written language in patients with PPA. Automated CU analysis is a tool that can improve assessment of functional written communication, and may be an objective tool to track aphasia progression. More studies are required to assess individual changes over time and whether these findings could be extrapolated to other forms of cognitive impairment.