bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of decisional capacity in AD biomarker test candidates
Authors: Kim Jeong Eun , Sereika Susan M , Tamres Lisa K , Lingler Jennifer H 
Published: December 2023

AbstractBackgroundDeciding to learn one’s Alzheimer’s disease (AD) biomarker status requires comprehending and deliberating about complex and nuanced information. Assessing capacity to consent to AD biomarker testing and disclosure is further complicated when candidates have cognitive impairment and present with family care partners. The objective of this analysis was to identify predictors of decisional capacity for an amyloid PET disclosure study among persons with Mild Cognitive Impairment (PwMCI) and their care partners (CPs).MethodThis investigation was a secondary analysis, using baseline data of a randomized controlled trial of amyloid PET results disclosure. Multiple linear regression modeling was used to examine predictors of decisional capacity, measured by the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC). Focusing on PwMCI (n = 82), the predictor variables of interest were sociodemographic characteristics, and level of knowledge on MCI/AD and normal aging, global cognition measured by Mini Mental Status Exam (MMSE), and neuropsychological tests of language and executive functioning. Dyadic analyses were conducted with CP data (n = 82), using the Actor Partner Interdependence Model (APIM) to assess for presence of partner effects among key variables.ResultParticipants and CPs were mostly White (91.5%, 90.2%), highly educated (16.5, 15.5 years on average), with mean age 72.7 and 66.8 years, respectively. CPs tended to be female, and spouses of the participants (70.7%). MMSE scores (b = 0.215, SE = 0.082, p = 0.011) and MCI/AD knowledge scores (b = 0.241, SE = 0.101, p = 0.020) positively predicted decisional capacity for PwMCI. Dyadic analysis using APIM showed that level of MCI/AD knowledge (p = 0.019) and level of education (p<0.001) were highly correlated within the dyad. Furthermore, analyses revealed significant positive correlations for MCI/AD knowledge for actor relations for decisional capacity for both the participant (a11 = 0.328, p = 0.005) and the CP (a22 = 0.262, p = 0.025). CP’s level of MCI/AD knowledge had a negative association for partner effects for decisional capacity (p21 = ‐0.207, p = 0.043) of the PwMCI.ConclusionAssessment of decisional capacity is imperative when considering participation in AD research, including biomarker studies involving results disclosure. Our findings highlight that not only do individual characteristics put PwMCI at risk for lower decisional capacity, but dyadic effects from their CPs may also be present.
Apathy and dysfunction in Lewy Body Disease
Authors: Zhu Carolyn W , Grossman Hillel , Sano Mary 
Published: December 2023

AbstractBackgroundStudies in Alzheimer’s disease and frontal temporal lobe dementia have shown high prevalence and persistence of apathy at different disease stages and its strong association with functional decline. Here we use well‐established methods to examine the relationship between apathy and function in a cohort of well‐characterized patients with Lewy Body Disease (LBD) who had regular assessments over time.MethodSample includes participants in the National Alzheimer’s Coordinating Center Uniform Data Set (NACC‐UDS, 9/2005‐12/2019) who had at baseline (1) cognitive status of mild cognitive impairment (MCI) or dementia, (2) presumed etiologic diagnosis of LBD, and (3) ≥1 follow‐up. Baseline diagnosis of Parkinson’s disease (PD) was assessed. Apathy was identified using clinician judgment. Participants’ function was measured using the Functional Assessment Questionnaire (FAQ). Multivariable linear mixed model (LMM) was used to estimate relationships between apathy, cognitive status (baseline MCI vs dementia), and function over time.ResultThe sample included 339 participants with MCI and 748 with dementia. Average age = 72.7±8.3, 74% male, 86% non‐Hispanic white, 15.4±3.4 years of education, baseline MMSE = 23.7±5.8, with 3.4±1.7 years of follow‐up. Proportion of participants who reported difficulty with function at baseline ranged according to task complexity from 48% (Heating water, making a cup of coffee, turning off stove after use) to 85% (Assembling tax records, business affairs, or papers); with total FAQ = 13.0±9.1. Presence of apathy increased from 52% at baseline to 60% at visit 4. Across all follow‐ups, 24% of the participants were never apathetic, 13.7% had apathy intermittently (<50% of all visits), 28.3% persistently (≥50% of all visits), and 34.0% were apathetic at all visits. LMM estimation results showed that, compared to participants who were never apathetic, FAQ was 3.8±0.8 points higher, i.e., greater dysfunction, at baseline in participants who were always apathetic, and 3.3±0.7 points higher in those who had intermittent/persistent apathy (both p<0.001). Rate of functional decline was 0.41±0.3 points faster each year in those always apathetic compared to never apathetic (p<0.1).ConclusionApathy is highly prevalent in individuals with LBD. Independent of cognitive status, more persistent apathy was strongly associated with worse function.
A longitudinal study of care‐recipient relationship type on the quality of life in community‐dwelling older adults with dementia
Authors: Lai Aiping , Griffith Lauren E. , Kuspinar Ayse , Smith‐Turchyn Jenna , Richardson Julie 
Published: December 2023

AbstractBackgroundWith the prolongation of the human lifespan, dementia has become a significant public health issue. In 2050, the number of people living with dementia (PLWD) globally is projected to increase from 50 million in 2018 to 152 million ‐ a 204% increase1. Without a cure or effective treatment for these diseases, maintaining the quality of life (QoL) of PLWD has been identified as the primary goal of care services. In the current study, we used five rounds of National Health and Aging Trends Study (NHATS) data (Round 5 to Round 9) to evaluate how the care‐recipient relationship type influences changes in QoL of PLWD over time.MethodThis was a secondary analysis of longitudinal data. Older adults were categorized into different groups by the type of relationship: (1) spouse/partner; (2) adult child; (3) informal caregiver other than spouse/partner and adult child, such as child‐in‐law, sibling, friend, etc.; (4) If older adults indicated having multiple caregivers, they were assigned to the group of “multiple caregivers.” QoL was assessed in 4 domains: mental health (assessed by Patient Health Questionnaire for Depression and Anxiety, PHQ‐4), self‐reported physical health, pain (Yes/No) and functional limitations (i.e. number of ADLs assistance). Backward and forward stepwise regressions were used to determine the prediction of older adults’ socio‐demographics (age, sex, race, income, education, marital status, living arrangement) and dementia status (probable dementia, possible dementia, and no dementia) on their QoL over 4 years; the generalized estimating equation (GEE) approach was used to examine the prediction of relationship type on QoL across the 4 years.ResultOlder adults cared for by an adult‐child or multiple caregivers predicted increased risk for functional limitations after adjustment for their socio‐demographic and dementia status. The interaction between the type of relationship and education was significant, indicating that the effect of relationship types on functional limitations is not uniform across education levels.ConclusionThe relationship type between care recipients and caregivers is linked to QoL changes, particularly with functional limitations in PLWD. Socio‐demographics such as education attainment might shape the influence of care‐recipient relationship type on changes in functional limitations over time.
Promoting Workforce for dementia care in India
Authors: Sivakumar Palanimuthu Thangaraju 
Published: December 2023

AbstractThe population of older adults in India is increasing rapidly with the recent population estimate in 2022 indicating the population of older adults aged 60 years and above in India as 142 million. The prevalence of dementia in India is estimated as 8.8 million in 2016. More than 90% of persons with dementia remains undiagnosed and untreated. Majority of those getting diagnosed are likely to do so in the later stages of dementia. Specialized workforce for the care of persons with dementia is not available is most parts of India due to the scarcity of trained human resources as well as lack of specialized services. There is an urgent need to scale up the training of human resources in the public health system for promoting early diagnosis and intervention for persons with dementia as well as for risk reduction and prevention.Training of Accredited Social Health Activists (ASHA), Community Health Officers and Primary Care Physicians is essential to promote early diagnosis of dementia in the primary care as there is higher prevalence of dementia in rural areas. Expanding the focus of National Mental Health Program (NMHP) and National Program for Health Care of Elderly (NPHCE) to include dementia as an important component is required to enable secondary level care at the district level. The training of the multi‐disciplinary team comprising Psychiatrist, Psychologist, Social Worker in the NMHP and the Physician, Multipurpose Health Worker, Nurse in the NPHCE can augment the workforce for dementia care across the country.Development of specialized training courses in Geriatric Psychiatry, increase in the postgraduate training opportunities in Psychiatry, Neurology and Geriatric Medicine can also strengthen the human resources in tertiary care. Training of other stakeholders and promoting task sharing approach is essential in the low resource settings like India. This presentation will review the status of workforce development for dementia care in India and discuss the model initiatives implemented in the Geriatric Psychiatry Unit at National Institute of Mental Health and Neurosciences, Bengaluru to promote the workforce for dementia care.
Detection of Mild Cognitive Impairment Using Convergent Cross‐Mapping Based on Resting‐State EEG Signals among Community‐Dwelling African American Participants
Authors: Sun Boxin , Deng Jinxian , Li Tongtong , Kavcic Voyko , Giordani Bruno 
Published: December 2023

AbstractBackgroundAccurate and early detection of mild cognitive impairment (MCI) is critical for interventions to promote cognitive resiliency. EEG‐based detection of MCI is attracting considerable attention from the research community due to its accessibility, affordability and increasing accuracy.MethodOur research is based on resting‐state EEG (64‐channel, eye‐closed). The current dataset includes 90 consensus‐diagnosed, community‐dwelling African Americans (ages 60‐90 years, 51 normal cognition, NC; 39 Mild Cognitive Impairment, MCI) recruited through the Wayne State Institute of Gerontology Healthy Black Elders Center and the Michigan Alzheimer’s Disease Research Center, all with subjective cognitive complaints.From an information‐theoretic perspective, causality measures the effective connectivity or directed information transfer from one brain region to another. Convergent cross‐mapping has attracted considerable attention recently since it was proven to be able to detect causal coupling in both deterministic and random settings. In this research, we propose to develop an EEG‐based MCI detection model by exploiting cross‐mapping causality analysis.We first derived the current source density (CSD) from EEG signals and performed cross‐mapping based causality analysis between the CSD signals of all the possible pairs across the selected EEG regions of interest. We then conducted joint time‐frequency‐spatial analysis on the cross‐mapping causation and selected features which are likely to reflect the differences between NC and MCI. The selected features were then fed into a machine‐learning algorithm for discrimination of NC and MCI.ResultBy tuning the observing window size and the number of features used, we obtained a series of different configurations of the discrimination model between NC and MCI, each with its own estimation accuracy. The overall result is a combined output of the model under different configurations, which improve the reliability and sensitivity of the discrimination model. For the 90‐sample dataset we are working with, the leave‐one‐out cross‐validation accuracy of our model is 97.78%.ConclusionOur analysis indicates that, potentially, EEG‐based cross‐mapping causality analysis may serve as a promising assessment tool for early detection of people at risk of MCI and dementia, even when just relying on resting state EEG.Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic and NIH‐1R01AG054484‐01A1/Kavcic; NIH‐ P30AG05376004/Paulson
Role of Onset of Diabetes on Development of Cognitive Impairment in Rats
Authors: Goura Venkatesh , Kallepalli Rajesh , Abraham Renny , Jayarajan Pradeep , Nirogi Ramakrishna 
Published: December 2023

AbstractBackgroundThe risk of cognitive impairment in diabetic patients is increasing in day to day life. One of the reasons for cognitive impairment in diabetic patients is hyperglycemic condition. Hyperglycemia leads to amyloid beta accumulation in brain, aggravates oxidative stress, neuro‐inflammation, and results in mitochondrial dysfunction, which impairs neuronal integrity, and eventually neurodegeneration. These are possible working mechanisms in diabetes‐related cognitive impairment. Further, literature says that, earlier the development of diabetes, greater the chances of developing cognitive impairment.MethodDiabetes was induced using streptozotocin in juvenile (3‐6 weeks old), adult (8‐10 weeks old) and aged (30‐34 weeks old) rats. Blood glucose levels were monitored after 10 days of streptozotocin administration. Rats which showed cognitive impairment were treated with insulin or insulin + donepezil. Diabetic rats were evaluated for cognitive impairment in fear conditioning memory task at 3 and 6 weeks after the confirming diabetes.ResultThe total freezing time decreased in juvenile> adult > aged diabetic rats respectively, when compared with naïve rats. The cognitively impaired diabetic rats treated with insulin + donepezil showed improvement in the associative memory observed from increase in freezing behavior in fear conditioning task.ConclusionDiabetes in the early stages of life may have greater risk for developing cognitive impairment.
Associations of peripheral and neuronal insulin resistance with cognition and functional brain networks in older adults with obesity
Authors: McIntyre Clayton Connor , Lyday Robert , Macauley Shannon L , Deep Gagan , Su Yixin , Nicklas Barbara , Hugenschmidt Christina E 
Published: December 2023

AbstractBackgroundInsulin resistance (IR) in peripheral tissue is a risk factor for Alzheimer’s disease. A proposed method for isolating neural‐enriched extracellular vesicles (nEVs) may allow measurement of neuronal IR in living humans. The hippocampus may be particularly sensitive to insulin signaling. We assessed associations of peripheral and neuronal IR with cognition and resting‐state functional brain networks in sedentary adults aged 65+ with obesity.MethodsAnalyses were performed on baseline data in a subset of participants (n = 75) from the INFINITE study who had MMSE ≥ 24 and had obesity but not type 2 diabetes. HOMA2‐IR quantified peripheral IR. The proposed insulin resistance index for nEVs (nEV‐IR) quantified neuronal IR. Executive function was measured by a composite score calculated from the digit symbol coding task, Trail Making Test parts A and B, Stroop task, phonemic fluency, and semantic fluency. Immediate learning was measured by the summed score of Auditory Verbal Learning Test (AVLT) trials 1‐5. Associations between cognition and HOMA2‐IR or nEV‐IR were evaluated using linear regression adjusted for age, sex, education, and BMI. Functional networks were created from resting‐state fMRI. Associations between brain network features in the hippocampus (global efficiency (Eglob), local efficiency (Eloc), first‐step connections, community structure) and HOMA2‐IR or nEV‐IR were evaluated using a novel regression framework for brain network distance metrics. Brain network regression models controlled for age, sex, education, and BMI.ResultsHOMA2‐IR and nEV‐IR were not correlated (p = .682). HOMA2‐IR was negatively associated with the executive function composite (β = ‐0.752, SE = 0.329, p = .026) but not AVLT trials 1‐5 (p = .185) or MMSE (p = .099). nEV‐IR was not associated with the executive function composite (p = .861), AVLT trials 1‐5 (p = .725), or MMSE (p = .262). HOMA2‐IR was positively associated with hippocampal Eloc (β = 0.0035, SE = 0.0014, p = .011) but not Eglob (p = .724). nEV‐IR was not associated with Eloc (p = .782) or Eglob (p = .752). Neither HOMA2‐IR nor nEV‐IR was associated with hippocampal connectivity (HOMA2‐IR: p = .419, nEV‐IR: p = .187) or community structure (HOMA2‐IR: p = .670, nEV‐IR: p = .404).ConclusionMeasures of peripheral – but not neuronal – IR are associated with unfavorable cognitive outcomes and with higher local efficiency in the hippocampus. These findings add to ongoing debate over nEV‐IR as a neuronal IR assessment.
Level of blood Tau and p‐Tau : a non‐invasive approach for the diagnosis of Alzheimer’s Disease(AD)
Authors: Kumari Sakshi , Yadav Yudhishthir , Singh Abhinay Kumar , Kaur Priyajit , Chakrawarty Avinash , Dey Sharmistha 
Published: December 2023

AbstractBackgroundProminent expression of Tau and phosphorylated Tau in cerebrospinal fluid (CSF) is one of the well‐known hallmarks of the Alzheimer’s disease (AD). High levels of p‐Tau can easily differentiate AD from other neurodegenerative disease. However, the serum levels of these proteins in AD patients are not well explored. This study provides an alternative non‐invasive approach to diagnose the disease by evaluating the level of Tau and p‐Tau181 in serum samples.MethodBlood samples were collected from 39 AD patients, 37 MCI patients and 37 elderly individuals as controls. Quantification of tau and pTau in serum samples was done with the help of a label free real time Surface Plasmon Resonance technology, and further validated by Western Blot. Statistical analysis, including Receiver Operating Characteristic (ROC), was done for further affirmation.ResultThe concentrations of serum Tau and p‐Tau181 were significantly higher (p<0.00001) in AD (Tau; 47.49±9.00ng/µL, p‐Tau181; 0.161±0.04 ng/µL) compared to MCI (Tau; 39.26±7.78 ng/µL, p‐Tau181; 0.135±0.02 ng/µL) and were further compared to elderly controls (Tau; 34.92±6.58 ng/µL, p‐Tau181; 0.122±0.01 ng/ µL). A significant (p<0.0001) downhill correlation was found between Tau as well as p‐Tau181 levels with HMSE and MoCA score.ConclusionThis study for the first time reports the concentration of Tau and p‐Tau181 in serum of AD and MCI patients. The cut‐off values of Tau and p‐Tau181 of AD and MCI patients with sensitivity and specificity reveal that serum level of these proteins can be used as a predictive marker for AD and MCI.
The quality of visual entrainment correlates with forward traveling wave properties in human cortex
Authors: Lahijanian Mojtaba , Panjehpour Armin , Aghajan Hamid ,   Augmented Intelligence Research Lab (AIRLab)
Published: December 2023

AbstractBackgroundFlickering light stimulation has been shown to entrain the brain’s oscillatory activity at the input frequency and synchronize different cortical regions in that frequency (Herrmann et al., 2001; Lahijanian et al., 2021). Brain entrainment at gamma frequency has been proposed and shown promising results as a non‐pharmaceutical therapeutic approach for Alzheimer’s disease (Cimenser et al., 2021). Studying the effects of such stimulation on the brain’s neural activity can help explain the mechanisms that underlie the reported improvements. It is known that neural oscillations form traveling waves across the brain during various cognitive functions (Bhattacharya et al., 2022). In this study, we use different flickering light frequencies as entrainment input and investigate the spatiotemporal pattern of neural activity modulated by visual entrainment which appears as a traveling wave across the posterior‐frontal pathway.MethodEEG data recorded from young healthy adults were analyzed during multi‐trial flickering light stimulation at 10, 15, 20, 22, and 30Hz frequencies. In order to analyze the quality of posterior‐frontal waves, the spatiotemporal phase pattern was measured over the head midline. The wave quality was defined as the consistency of the spatiotemporal phase pattern during consecutive time intervals, and the quality of entrainment was defined as the intensity of the power spectral density at the input frequency.ResultDuring the resting state, different wave patterns traveling across the frontoparietal link are canceled out. However, visual stimulation invigorates the forward wave from the sensory (posterior – visual) region to the upstream area (frontal lobe) at the target frequency compared to the baseline. Meanwhile, in contrast to the forward wave, traveling wave in the backward direction does not show noticeable presence at the stimulation frequency. Furthermore, as the entrainment quality increases, the wave pattern consistency is improved for all stimulating frequencies (Figs. 1, 2).ConclusionThe forward wave induced during non‐invasive visual stimulation represents long‐range activity along the posterior‐frontal pathway known to be activated during sensory processing and inference. The observed correlation between the wave’s quality and the quality of entrainment at the target frequency points to the mechanism underlying the therapeutic effects of gamma entrainment.