bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is A+T‐ Alzheimer’s disease or not? A combined CSF and pathology study
Authors: Vromen Ellen M. , de Boer Sterre C.M. , Teunissen Charlotte E. , Rozemuller Annemieke J.M. , Visser Pieter Jelle , Bouwman Femke H. , Tijms Betty M. ,   for the Alzheimer's Disease Neuroimaging Initiative
Published: December 2021

AbstractBackgroundThe biological definition of Alzheimer’s disease (AD) based on cerebrospinal fluid (CSF) biomarkers requires both abnormal amyloid (A) and p‐tau (T). However, previous studies showed that up to 32% of individuals with autopsy‐confirmed AD show normal p‐tau levels in CSF in vivo. We studied in two independent cohorts how often individuals with abnormal CSF amyloid and normal p‐tau levels had autopsy‐confirmed AD, and whether these individuals differed in pathological amyloid and tau scores compared to individuals with both abnormal CSF amyloid and p‐tau levels.MethodIn total we included 118 individuals with CSF collection and autopsy from the Amsterdam Dementia Cohort (ADC) (n=75, mean±SD age 62±9 years, 26 (35%) female, 37 (49%) with AD at autopsy) and from ADNI (n=43, mean±SD age 77±7 years, 9 (21%) female, 31 (72%) with AD at autopsy). The mean time between CSF collection and death was 4.5±2.9 years in ADC and 5.1±2.5 years in ADNI. Biomarker profiles were based on dichotomized CSF Aβ42 and p‐tau (ApT) (ADC: Innotest ELISA, ADNI: Elecsys). We assessed the diagnostic accuracy of ApT profiles to detect autopsy‐confirmed AD, and investigated differences in degree of AD neuropathology (based on A‐score for Thal stage, B‐score for Braak stage and C‐score for CERAD score; available in n=36 (48%) ADC individuals and all ADNI individuals) between A+pT+ and A+pT‐ individuals with and without autopsy‐confirmed AD.ResultAll individuals with an A+pT+ profile had AD at autopsy (27/27 in ADC, 23/23 in ADNI). Of individuals with an A+pT‐ profile 7/13 (54%) individuals in ADC and 5/8 A+pT‐ (64%) in ADNI had AD at autopsy. In both cohorts, CSF amyloid status showed the highest accuracy to detect autopsy‐confirmed AD (86‐88%) and the addition of CSF p‐tau status did not improve this (81%‐87%). Comparing individuals on A, B and C neuropathological scores, we observed no differences in degree of AD neuropathology between A+pT‐ and A+pT+ individuals with autopsy‐confirmed AD. A+pT‐ individuals without AD at autopsy had low neuropathological scores.ConclusionOur results indicate that a normal p‐tau concentration in the presence of an abnormal amyloid marker does not exclude the presence of AD at autopsy.
Preventing cognitive decline in older adults with mild cognitive impairment using integrated Korean and Western treatments: Initial results
Authors: Lee Ji Hyun , Kim Do Yeun , Kim Man Gi , Kang Hakmook , Shin Hye‐Won , Kim Kwong Ki , Koo Byung Soo 
Published: December 2021

AbstractBackgroundDespite the rapidly rising incidence of cognitive impairment, no current medications have proven effective for mild cognitive impairment (MCI). The Integrated dementia clinic at Dongguk University Ilsan Hospital is a nationally recognized Korean‐Western (KW) clinic that provides the integrated medical service via co‐consultation by both neurologists and Korean medicine neuropsychologists.ObjectiveThe purpose of this study is to examine whether the integrated KW treatment prevents cognitive decline in patients with MCI as measured by changes in the Mini Mental State Examination (MMSE) scores over time.MethodWe retrospectively examined the medical records of patients from May 2015 to June 2020. Of 19 patients who were diagnosed as MCI, twelve MCI patients underwent MMSE at their initial visit to the clinic and at least once more over a period of up to 5 years. These twelve MCI patients divided into two groups: MMSE improvement group vs. MMSE worsening group. We performed the Wilcoxon rank sum test to compare the group achieving improvement in MMSE to decrease in MMSE. We also used the same test to assess the difference in the median length of follow‐up between the two groups.ResultThe prevalence of MCI seen during the review period was 23% (19/82). The baseline characteristics of patients with MCI were shown in Table 1. Among those twelve MCI patients who received integrated KW treatment, 67 % (8/12) of them achieved improvement in MMSE score, which was statistically significant (p‐value = 0.008) compared to those showing a decrease in MMSE score while the length of follow‐up was not significantly different between the two groups. The detailed treatment and changes in MMSE presented in Table 2. For treatment from Western medicine, anticonvulsants were most commonly prescribed, and donepezil was given to 63%. Acupuncture (100%), Moxibustion (100%), and herbal medicine (Gagam‐sohabhwangwon: 6/8,62.5 %) were most prescribed Korean medicine.ConclusionsThis study demonstrates, for the first time, that integrated KW treatment positively affects cognitive function in MCI patients with increases in MMSE scores over time. Further research with a larger data set, needs to be conducted to validate the effectiveness of integrative approach.
Biological activity identification of newly synthesized plumbagin‐lipoic acid conjugate: In vitro and in silico analyses of interaction with acetylcholinesterase and butyrylcholinesterase
Authors: Sakayanathan Penislusshiyan , Loganathan Chitra , Iruthayaraj Ancy , Thayumanavan Palvannan 
Published: December 2021

AbstractBackgroundIdentification of novel compounds with inhibitory potential against cholinesterases (ChEs) such as acetylcholinesterase (AChE) and butrylcholinesterase (BChE) is considered important strategy to overcome Alzheimer’s disease (AD). The ratio of major globular tetrameric form of AChE (G4) to the minor lower species (G1; monomers and G2; dimers) is decreased in the AD brain. Also, in recent time, the involvement of BChE in progression of AD is recognized. Hence, it is imperative to understand the inhibitory potential of any new compound against BChE and various globular forms of AChE to identify as lead molecule to further explored for AD treatment. Keeping this view, plumbagin (PLU) and lipoic acid (LA) conjugate was synthesized and characterized for its inhibition against AChE and BChE. Further in silico analysis was carried out to get an insight into the interaction of PLU‐LA with the AChE and BChE.MethodNewly synthesized PLU‐LA conjugate by esterification reaction was characterized by nuclear magnetic resonance spectroscopy (NMR) and mass spectroscopy (MS). The synthesized PLU‐LA was studied for the inhibition against BChE and different molecular forms of AChE. Kinetic analysis was carried out to determine the type of inhibition and inhibitor constant. In silico analysis such as molecular docking and molecular dynamics simulation was carried out using AutoDock and Desmond, respectively.ResultPLU‐LA synthesized was confirmed by NMR and MS analysis. PLU‐LA inhibited the different molecular forms (G2 and G4) of AChE at micromolar concentration. Kinetic analysis revealed the type of inhibition with low Ki value. Molecular docking analysis revealed the orientation of PLU‐LA at the active site of human AChE and BChE forming interaction with catalytic site amino acid. Molecular dynamics simulation confirmed the stable binding of PLU‐LA with ChEs.ConclusionPLU‐LA was synthesized and it’s inhibition against ChEs (AChE and BChE) is understood. In silico analysis highlighted the interaction of PLU‐LA within the active site gorge of the ChEs.
Metabolic syndrome and its effect in dementia: Not your typical memory loss symptoms
Authors: Rodriguez‐Santiago María A. , Jiménez‐Velazquez Ivonne Z. , Maldonado Aleyda , Valentin Eric Miranda , Rivera Horacio Serrano 
Published: December 2021

AbstractBackgroundAlzheimer Disease (AD) is the most prevalent form of dementia and the fourth cause of death in Puerto Rico (1). While perhaps there are no treatments for AD, treating modifiable risk factors offers opportunities for prevention of dementia concomitantly. Objective: Primary end point was to find an association between the Metabolic Syndrome (MetS), its individual component, and dementia in a puertorrican population ≥ 65 years old. The secondary end point was to determine which aspects of cognition (Memory, Orientation, Judgment, Community affairs, Home/hobbies and Personal care) are mostly affected.MethodCross sectional study with 135 puertorricans ≥ 65 y/o with family history of Early Onset Alzheimer’s Disease (EOAD) who were divided by having MetS (n=47) vs without (n=88). MetS was defined by the National Cholesterol Education Program criteria. Waist circumference measurement was adapted with body mass index ≥ 30 kg/m2. Cognition function was assessed by the Clinical Dementia Rating (CDR) Scale.ResultOur study revealed no significant statistical association between MetS and moderate dementia in the participants ≥65 years old with family history of EOAD using the CDR Scale. Nonetheless, BMI ≥ 30 kg/m2 in participants with MetS was found to have a significant statistical association, or a trend towards significance, with moderate dementia in 5 out of 6 domains of cognitive performance, as per CDR ≥2: Memory (p= 0.066), Orientation (p=0.21), Community‐interactions (p= 0.040), Judgment (p=0.040) and Hobbies/Home (p= 0.099).ConclusionMetS had no statistical association with dementia. However, BMI ≥30 kg/m2 was associated with dementia, mostly affecting orientation, judgment and community tasks, not necessarily the typical memory loss. BMI’s ideal goal needs to be achieved and must be considered a priority in the patient’s primary care management. Clinically, ≥65 y/o puertorrican patients with MetS should be screened for dementia assessing the capacities to perform activities of daily living (ADL’s) not only memory tests, as part of preventive medicine.
Automated prescreening of MCI through deep learning models based on wearable inertial sensors data
Authors: Lee Hyeonil , Shahzad Ahsan , Kim Kiseon 
Published: December 2021

AbstractBackgroundDuring mild cognitive impairment (MCI), a precursor of dementia, often the mild symptoms go unnoticed and are assumed as normal aging signs by elderly people, resulting in late diagnosis and progression to dementia. Recently, several studies investigated the potential of behavioral analysis (ADL assessment, speech analysis etc.) based biomarkers for automated early screening of MCI in home settings. In this work, different deep learning models with walking data have been examined and a 2D‐CNN‐GRU model for automatic diagnosis of MCI based on wearable inertial sensors gait data is proposed.MethodSixty subjects (30 Cognitively Normal‐CN and 30 MCI) recruited from National Research Center of Dementia Database, Gwangju, South Korea, underwent comprehensive medical assessments by Chosun hospital doctors. The gait data of each participant was recorded using Shimmer3 inertial sensors under dual‐task settings. The subjects wore 7 shimmer3 sensors at five different body locations, i.e. waist, each thigh, each shank and each foot and performed 5 trials of dual‐task walking. For each experiment trials, the subject walked straight 10m and returned 10m while naming animals, food, fruits, colors and plants. Out of 10 meters, the central 6m stable walking signals were extracted and used for post processing. A total of eight features utilized for deep learning models’ training were, angular velocity along each axis of tri‐axial gyroscope sensor, 3‐axis acceleration data, and the signal vector magnitude of both sensors. In order to learn the gait pattern and time series characteristics for each step, the proposed model was built using six Convolutional Neural Networks‐(CNNs) as input for three Gated Recurrent Units‐(GRUs). Finally, the Leave One subject Out (LOO) Cross‐Validation (CV) was used to report the model's performance.ResultAs compared to individual representative deep learning models, the proposed combined model 2D‐CNN‐GRU proved to be more effective in MCI detection by learning discriminating walk signal characteristics and achieved Sensitivity 83.33%, Accuracy 73.33 % and Specificity 63.34% (Refer Table below).ConclusionThis research work is the pioneer to investigate deep learning approaches for MCI diagnostic research using inertial sensor data and has the potential to facilitate early detection of MCI in home settings.
Differentiation of dementia with Lewy bodies from normal elderly and Alzheimer’s disease: A DLB Resemblance Atrophy Index
Authors: Liu Wanting , Luo Yishan , Shi Lin , Mok Vincent C.T. ,   National Alzheimer’s Coordinating Center
Published: December 2021

AbstractBackgroundIt is sometimes challenging for clinicians to differentiate Dementia with Lewy Bodies (DLB) from normal elderly and Alzheimer’s disease (AD), particularly at the early stage. Since structural difference in multiple brain regions exists between DLB and normal elderly and AD, we aimed to derive a single severity index by combining these multiple MRI features from machine learning and explored the performance of this index (DLB resemblance atrophy index [DLB‐RAI]) in differentiating mild DLB from normal elderly and AD.Method61 DLB subjects, 128 AD subjects (mean clinical dementia rating [CDR]=0.852 vs 0.953, p=0.248) and 128 normal controls (NC) with age matched were recruited from the National Alzheimer’s Coordinating Center (NACC) database. All MRI images were postprocessed by an MRI‐based volumetry segmentation tool (AccuBrain®). We analyzed the whole brain structural difference between DLB and AD and NC subgroups. All brain features were utilized to derive a DLB‐RAI. We obtained the optimal cutoff of DLB‐RAI and used 10‐fold cross‐validation method to validate the performance of DLB‐RAI among the three subgroups.ResultThe optimal cutoff of DLB‐RAI in the differentiation of mild DLB from NC and AD was 0.5. The accuracy of DLB‐RAI (≥0.5) in distinguishing DLB from NC was 83.0% (AUC=0.87, Figure 1) with an optimal sensitivity of 0.83 and specificity of 0.86, while the accuracy in differentiating between DLB and AD was 75.10% (AUC=0.77, Figure 2). Amygdala, caudate, putamen, midbrain, medulla and cerebellum were significantly different between DLB and AD (p < 0.05).ConclusionDLB‐RAI may aid the differential diagnosis of mild DLB, normal elderly and AD. It may have the potential to be utilized in the clinical practice.
Differential discordance of informant‐ and self‐rated depression and apathy in Black, Hispanic, and White participants in the NACC dataset
Authors: Wyman Mary F. , Burke Shanna L , Paukner Mitchell J. , Umucu Emre , Naseh Mitra , Grudzien Adrienne , Zuelsdorff Megan , Walaszek Art , Chappell Richard J. , Gleason Carey E. 
Published: December 2021

AbstractBackgroundEvidence points to racial and ethnic differences in prevalence of neuropsychiatric syndromes (NPS) and interpretation of symptoms by patients and family. Although Alzheimer’s and related dementia (ADRD) research and clinical assessment relies heavily on family report, agreement of self and informant NPS ratings has not been examined in racially diverse cohorts. We used cross‐sectional data from the National Alzheimer’s Coordinating Center (NACC) Uniform Dataset to assess concordance in depression and apathy by race/ethnicity, across cognitive status categories.MethodsThe analytic dataset included 28,165 non‐Hispanic Whites (NHW), 5177 non‐Hispanic Blacks (NHB), and 2943 Hispanics age 45 and older, with baseline cognitive status of normal cognition, mild cognitive impairment (MCI), impaired‐not‐MCI, or dementia. Rates of depression and apathy were calculated using self‐report (Geriatric Depression Scale; GDS‐12 and GDS‐3 subscales) and informant report (Neuropsychiatric Inventory‐Questionnaire (NPI‐Q)). Next, using previously‐validated cutpoints on GDS subscales, concordance of dichotomously‐coded self‐ and informant ratings was examined by race/ethnicity within each cognitive status category.ResultsHispanics were slightly younger and reported fewer years of formal education, while NHB were more likely to be female (Table 1). Self‐rated apathy and depression levels were higher in Hispanic participants compared to their non‐Hispanic counterparts (p<.0001). NHB and NHW did not differ on apathy scores, but NHW endorsed more depression compared to NHB (p=.0006). Rates of informant‐rated apathy and depression were highest in the Hispanic group and lowest in NHB (all comparisons p<.0001). Across cognitive status categories, informants were more likely to identify depression compared to self‐ratings (Figure 1). However, self‐reported rates of apathy were higher than informant report, except in the dementia group (Figure 2). Overall, discordance of report was statistically significant in all race/ethnic groups. Interestingly, reports of depression in Hispanic participants (n=198) adjudicated as impaired/not MCI were not discordant.ConclusionsIn this diverse NACC cohort, discordance between informant and self‐report of depression and apathy was revealed across race/ethnicity and cognitive status, but the direction of discordance differed by symptom. Future research should examine the impact of other demographic characteristics on observed differences, explore use of different cutpoints, and examine neuropsychiatric symptoms in additional racial groups.
Vision‐based gait analysis system utilizing deep learning algorithms in idiopathic normal‐pressure hydrocephalus patients
Authors: Kang Kyunghun , Jeong Sungmoon , Yu Hosang , Park Jaechan 
Published: December 2021

AbstractBackgroundIdiopathic normal‐pressure hydrocephalus (INPH) is a rare neurological disorder. It is an idiopathic adult‐onset syndrome involving nonobstructive enlargement of cerebral ventricles, and it is known by its symptoms of cognitive impairment, gait disturbance, and urinary dysfunction. While INPH can present with any of these classic clinical symptoms in varying degrees, the most frequent and important INPH clinical feature is gait disturbance. A vision‐based gait analysis method using monocular videos was proposed to estimate temporo‐spatial gait parameters by leveraging deep learning algorithms. This study aimed to validate vision‐based gait analysis using GAITRite as the reference system and analyze relationships between Frontal Assessment Battery (FAB) scores and gait variability measured by vision‐based gait analysis in INPH patients.MethodGait data from 46 patients were simultaneously collected from the vision‐based system utilizing deep learning algorithms and the GAITRite system.ResultThere was a strong correlation in 11 gait parameters between our vision‐based gait analysis method and the GAITRite gait analysis system. Our results also demonstrated excellent agreement between the two measurement systems for all parameters except stride time variability after the cerebrospinal fluid tap test. Our data showed that stride time and stride length variability measured by the vision‐based gait analysis system were correlated with FAB scores.ConclusionVision‐based gait analysis utilizing deep learning algorithms can provide comparable data to GAITRite when assessing gait dysfunction in INPH. Frontal lobe functions may be associated with gait variability measurements using vision‐based gait analysis for INPH patients.
Compromised immunity rather than specific microbe may increase vulnerability to Alzheimer’s disease, and vaccines with beneficial off‐target effects may support immunity and prevent AD
Authors: Ukraintseva Svetlana , Yashkin Arseniy Pavlovich , Akushevich Igor , Arbeev Konstantin , Duan Matt , Tropsha Alex , Stallard Eric , Yashin Anatoliy 
Published: December 2021

AbstractBackgroundDiverse pathogens (viral, bacterial, fungal) were linked to Alzheimer’s disease (AD) suggesting that compromised immunity may play role in AD. Chronic infections could be signs of weakened immune system favoring AD risk, while vaccines with beneficial off‐target effects might support immunity and protect against AD.MethodsWe estimated effects of diagnosed herpes simplex, zoster (shingles), pneumonia, recurrent mycoses, and vaccinations against shingles and pneumonia, on AD onset in pseudorandomized sample of Health and Retirement Study participants aged 75+.ResultsHerpesviruses and recurrent mycoses increased AD risk by 25%‐42%. Pneumococcal and shingles vaccines received between ages 65‐75 lowered consequent AD risk by 15%‐21%.ConclusionHerpes and fungal infections increased AD risk, while vaccinations against shingles and pneumonia were protective, supporting the idea that AD is linked to compromised immunity rather than to specific microbe, and repurposing vaccines with beneficial off‐target effects on immune robustness/resilience might be useful for AD prevention. The study was supported by NIH grants 2RF1AG046860, 1R01AG062623 and 1R01AG063971.
Exploring the unmet needs facing individuals with Alzheimer’s disease and related dementias during the COVID‐19 pandemic
Authors: Benjenk Ivy , Chen Jie 
Published: December 2021

AbstractBackgroundMany adults with ADRD rely on support from friends, family members, social service agencies, and their communities to meet their basic needs. It is unclear if COVID‐19 mitigation policies have made it more difficult for individuals with ADRD to receive this support. The objective of this study was to explore the types of unmet needs experienced by adults with ADRD in the United States during the COVID‐19 pandemic as well as the characteristics of adults with ADRD that are experiencing unmet needs.MethodWe performed a cross‐sectional analysis of the Medicare Current Beneficiary Survey (MCBS) summer and fall 2020 COVID‐19 supplemental surveys. The MCBS uses complex survey design to provide a nationally representative sample of Medicare beneficiaries. There were 20,800 survey participants in total and 4.07% have received a diagnosis with ADRD. Logistic regression was used to examine the characteristics of those reporting one or more unmet need.Result16.61% Medicare beneficiaries with ADRD reported having one or more unmet needs during the COVID‐19 pandemic (vs. 16.52% Medicare beneficiaries without ADRD, p=0.956). While beneficiaries with and without ADRD had no difference in unmet needs surrounding rent/mortgage, food, supplies, and medications, adults with ADRD had higher rates of unmet need for healthcare services (8.86% vs. 5.77%, p=0.008). Adults with ADRD were more likely to report having an unmet need between March‐June than between July‐November (18.10% vs. 7.84%, p<0.001). Among those with ADRD, individuals with depression (AOR=2.25, p=0.001) and multimorbidity (AOR=1.79, p=0.030) reported significantly higher unmet need, after controlling for age, sex, race/ethnicity, insurance, and geographic location. As compared with individuals without ADRD, individuals with co‐existing ADRD and depression (p<0.001) or co‐existing ADRD and multimorbidity (p<0.001) reported higher likelihood of having unmet needs.ConclusionMany adults with ADRD experienced unmet need during the first 4 months of the COVID‐19 pandemic. We also found that the ADRD patients with depression and complex health needs who require greatest number of healthcare services were more likely to voice unmet needs. The residual impact of unmet needs during the early pandemic months and on‐high risk subpopulations is currently unknown.