bluuebunny/crossref_metadata_2025_split huggingface dataset:
Racial differences in white matter hyperintensity load in aging, MCI, and AD
Authors: Morrison Cassandra , Dadar Mahsa , Collins Louis D 
Published: December 2022

AbstractBackgroundCerebral small vessel disease (CSVD), often measured using white matter hyperintensities (WMHs) is a pathological change to the brain that increases ones’ risk for both age‐related cognitive decline and dementia. Several studies have noted that there is greater risk of CSVD in African Americans than in Caucasians. However, limited research has examined WMHs as a proxy of CSVD in an ethnically diverse sample. The goal of this research was to determine whether WMH load differs between African Americans and Caucasians.MethodsParticipants for this study were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1, GO, 2, and 3). They were included if they had baseline WMH measurements and a baseline diagnosis. WMHs were segmented using a previously validated automatic technique (Dadar et al., 2018). A total of 91 African Americans and 1846 Caucasians were included in this analysis. To compare samples, 91 Caucasian participants were randomly matched to African Americans based on age, sex, education, and diagnosis. This random selection was completed 1000 times using bootstrap resampling. A linear mixed effects was completed to examine the influence of race on WMH load: WMH ∼ Race + Age + Sex + Education + Diagnosis. The 95% confidence limits of the t‐statistics distributions for the 1000 samples were examined to determine whether the differences were statistically significant.ResultsThe following figure shows the t‐statistic, 95% confidence intervals, and p‐value distributions of the 1000 bootstrapped samples. The 95% confidence intervals are between t=‐3.06 and t=‐0.89 for total WMH load, indicating significance, as the limits do not include 0.ConclusionsAccounting for age, sex, education, and diagnostic status, racial differences were observed for total WMH load. That is, African Americans had higher total WMH load than Caucasians. Future research should examine whether these findings are observed longitudinally and if they influence cognition in an ethnically diverse sample.
Spousal caregiver burden among patient with cognitive impairment: effects on nutrition and other lifestyle factors
Authors: Jeon So Yeon , Kim Jeong Lan 
Published: December 2022

AbstractBackgroundAmong old adults, caring for a spouse with cognitive decline is well‐known to be associated with significant risk to the caregiver`s health such as cardiovascular disease, depression and, especially, cognitive impairment. It is important to understand the caregiving‐related risk factors for caregiver`s cognitive decline. Therefore, in this study, we examined the impact of caregiver`s burden on the lifestyle factors (malnutrition, sleep, depression, and physical activity) influencing cognitive decline among SCGs, focusing on nutritional status which contribute to SCG’s cognitive decline.MethodFrom May 2020 to May 2021, clinical evaluation and blood tests were conducted for patients who visited Chungnam National University Hospital Geriatric Neuropsychiatric Clinic with their spouse. A total of 51 subjects were included in the analysis. As clinical assessment, we evaluated the care burden (Zait burden interview), depression(Geriatric‐Depression‐Scale), sleep quality (Pittsburgh‐Sleep‐Quality‐Index), cognitive function(Mini‐Mental‐state‐exmination) physical activity(International‐Physical‐Activity‐Questionnaire), and dietary habits (Mini‐Nutrional‐Assessment).ResultAs the care‐recipient’s cognitive function declined, the caregiver`s burden were increased (β = ‐0.66, p < 0.001). In linear regression analysis adjusted for age and sex, the SCG`s burden was significantly associated with the worse dietary habits (β = ‐3.194, p = 0.003) and increased level of depressed mood (β = 0.525, p < 0.001). The SCG`s burden showed a trend level association with sleep quality (β = 0.292, p = 0.050) but no significant relationship with physical activity (β = ‐0.053, p = 0.742). The results were unchanged after excluding care‐recipients with normal cognition (n = 7).ConclusionThis study provides substantial evidence that SCGs are at risk for depression and malnutrition, which can further affect cognitive decline. As such, these factors should be well assessed and monitored among SCGs for patient with cognitive impairment.
Effective Connectivity Is A More Promising Biomarker for Brain Health in Middle‐Aged Adults Than Functional Connectivity: Bogalusa Heart Study
Authors: Chuang Kai‐Cheng , Pillai Sreekrishna R. , Bazzano Lydia , Carmichael Owen T. 
Published: December 2022

AbstractBackgroundEffective connectivity, the causal influence that functional activity in a source brain location exerts over functional activity in a target brain location, has the potential to provide richer information about brain networks than functional connectivity, which only quantifies activity synchrony between regions. However, head‐to‐head comparisons of effective and functional connectivity from functional MRI data are rare, especially among diverse cognitively healthy middle aged and older adults.Method100 Bogalusa Heart Study participants performed a Stroop task during functional MRI (Table 1). Effective connectivity and functional connectivity among 24 regions of interest (ROIs) previously identified as activated by this task [1] were calculated using deep stacking networks [2] and Pearson correlation, respectively. Graph metrics were then calculated from directed graphs resulting from effective connectivity and undirected graphs resulting from functional connectivity. Linear regression models related graph metrics to demographic, cardiometabolic, and cognitive measures.ResultFigure 1 shows the group‐consensus effective and functional connectivity graphs. Systolic blood pressure (SBP) was associated with effective connectivity based characteristic path length (Pearson’s r = 0.22, p‐value = 0.038) and modularity (r = 0.25, p‐value = 0.02) (Figure 2). Diastolic blood pressure (DBP) was associated with effective connectivity based degree, density, clustering coefficient, modularity, transitivity, characteristic path length, and global efficiency (|r| = 0.26 ‐ 0.35, maximum p‐value = 0.013) (Figure 2). Word reading and vocabulary scores from the Wide Range Achievement Test (WRAT) were associated with effective connectivity based degree, density, clustering coefficient, transitivity, characteristic path length, modularity, and global efficiency (|r| = 0.21 ‐ 0.27, maximum p‐value = 0.049). Logical Memory II Recognition scores associated with effective connectivity based assortativity (r = 0.24, p‐value = 0.025). Associations between functional connectivity based graph metrics and demographic, cardiometabolic, and cognitive measures were not significant.ConclusionIn a diverse, cognitively healthy, middle‐aged community sample, graph metrics derived from effective connectivity based directed graphs tracked more closely with recognized indicators of brain health than traditional functional connectivity based undirected graph metrics. References: [1] Sheu, L. K. et al. (2012). Psychophysiology. [2] Chuang, K.‐C. et al. (2021). Machine Learning in Clinical Neuroimaging.
Gut microbiota regulates neuroinflammation and progression of neurodegeneration in a mouse model of tauopathy
Authors: Seo Dong‐oh , O'Donnell David , Jain Nimansha , Ulrich Jason D , Herz Jasmin , Lemieux Mackenzie , Stanley Jack G. , Franke Emily , Serrano Javier R. , Bao Xin , Karlsson Maria , Meier Marty , Desai Chandani , Lelwala‐Guruge Janaki , Li Yuhao , Shi Yang , Wang Chao , Cheng Jiye , de Lima Kalil Alves , Dodiya Hemraj B. , Hibberd Matthew , Griffin Nicholas , Handley Scott , Kipnis Jonathan , Sisodia Sangram S. , Gordon Jeffrey I. , Holtzman David M. 
Published: December 2022

AbstractBackgroundAlthough mounting evidence supports that an unbalanced gut microbiota (GM) is linked to amyloid‐β deposition, the contribution of the GM to tau‐mediated neurodegeneration (TN) is poorly characterized. Our preliminary data have shown that the GM manipulations, using either treatment with a combination of antibiotics (ABX) or raising animals in germ‐free (GF) conditions, regulate TN (Seo, et al., AAIC 2021). However, further investigation is needed to sort out the underlying mechanisms that are involved in the interaction between GM and TN. Here, we explore neuroinflammation as a potential mediator in the interaction between GM and TN.MethodP301S tau transgenic mice were crossed with human ApoE knock‐in mice (ApoE3 or ApoE4) or ApoE knockout mice (EKO) to generate P301S::ApoE3/E3, ApoE4/E4, or P301S/EKO mice, termed TE3F, TE4F, and TEKO, respectively. Each group was gavaged with either ABX or H2O from postnatal day 16‐22, housed in a specific pathogen‐free facility, and euthanized at 9.5 months of age. A separate group of TE4F mice was housed under GF conditions. Collected brains were sectioned and used for immunohistochemistry analysis.ResultsIn agreement with brain atrophy measurements that we previously reported, TE3F mice treated with a short‐term ABX showed significantly lower phosphorylated tau (p‐tau) staining compared to the H2O‐treated group (p < 0.01), but not TE4F and TEKO mice treated with ABX. GF‐TE4F mice also showed a marked decrease in p‐tau staining compared to conventionally‐raised animals (p < 0.01). Further quantification of gliosis, as measured by GFAP and Iba1 immunostaining, did not reveal any ABX treatment effects. However, when we assessed the expression of clec7a+ microglia, which marks reactive microglia, ABX treated animals showed significantly lower clec7a+ staining across the different APOE isoform groups (p < 0.01). Furthermore, microglial morphology analysis revealed that ABX treatment drive microglia to a more homeostatic‐like state in TE3F mice, but not in TE4F nor TEKO mice. Remarkably, GF‐TE4F mice showed a marked decrease in both GFAP and Iba1 expression compared to the control TE4F mice (p < 0.05).ConclusionOur results support the hypothesis that GM manipulation modulates tau‐mediated neurodegeneration via influencing a neuroinflammatory mechanism.
PDE5 inhibitors against synaptic and cognitive impairment in Alzheimer’s disease and related dementia
Authors: Arancio Ottavio , Zuccarello Elisa , Fiorito Jole , Acquarone Erica , Argyrousi Elentina , Staniszewski Agnieszka , Calcagno Elisa , Puzzo Daniela , Deng Shi‐Xian , Landry Donald 
Published: December 2022

AbstractBackgroundGene transcription mechanisms leading to synaptic plasticity and memory formation, including phosphorylation of the transcription factor CREB, are perturbed in Alzheimer’s disease (AD). In this regard, cyclic guanosine monophosphate (cGMP), which activates cGMP‐dependent protein kinases that, in turn, phosphorylate CREB, has been implicated in the memory and synaptic plasticity impairment occurring in the disease. Sildenafil (Viagra®), the well‐known FDA approved inhibitor of phosphodiesterase 5 (PDE5I), the enzyme that degrades cGMP, has shown efficacy in AD animal models (Zuccarello et al, Biochem Pharmacol. 2020) and was recently significantly associated with a reduced risk of AD in an unbiased study including 7.23 million individuals (Fang et al, Nat. Aging 2020).MethodFollowing the development of a library of small molecules inhibiting phosphodiesterase 5 (PDE5), compound efficacy was tested in different animal models of Aβ and tau elevation. Specifically, these animals were tested using a combination of biochemical (western blotting of proteins involved with gene transcription machinery), electrophysiological [analysis of long‐term potentiation (LTP), a type of synaptic plasticity thought to underlie memory formation], and behavioral (assessment of spatial and associative memory through radial arm water maze and fear conditioning) techniques.ResultStructure activity relationship (SAR) analysis of existing PDEI scaffolds led to the design and synthesis of compound 7a, a quinoline customized for AD with improved physiochemical properties compared to existing inhibitors. The molecule has outstanding inhibitory activity against PDE5 (IC50 = 0.27nM) and selectivity against all other PDE isoforms (PDE5/PDEs > 1000). It also crosses the blood brain barrier (AUC0‐tratio = 0.41) and has similar Tmax values in the brain and plasma, indicating that its distribution to the brain is fast. Moreover, similar to other PDE5Is, 7a re‐established normal LTP and both spatial and associative memory after Aβ and tau elevation. Finally, the compound re‐established normal increase of CREB phosphorylation and cGMP levels after memory induction in the presence of Aβ and tau.ConclusionUp‐regulation of CREB activation through PDE5 inhibitors might be beneficial against Aβ and tau‐induced synaptic and memory dysfunctions.
Does tadalafil increase brain blood flow? The PASTIS trial
Authors: Hainsworth Atticus H , Pauls Mathilde , Binnie Lauren , Benjamin Philip , Betteridge Shai , Clarke Brian , Dhillon Mohani‐Preet , Ghatala Rita , Hainsworth Fearghal , Howe Franklyn , Khan Usman , Kruuse Christina , Madigan Jeremy , Moynihan Barry , Patel Bhavini , Pereira Anthony , Rostrup Egill , Shtaya Anan , Spilling Catherine A , Trippier Sarah , Williams Rebecca , Young Robin , Barrick Thomas R , Isaacs Jeremy D 
Published: December 2022

AbstractBackgroundThis trial tested the hypothesis that the PDE5 inhibitor tadalafil, a widely‐used vasodilator, increases cerebral blood flow (CBF) in older people with symptomatic small vessel disease, the main cause of vascular cognitive impairment.MethodIn a double‐blinded, placebo‐controlled, cross‐over trial, female and male participants received tadalafil (20mg) and placebo on two visits at least 7 days apart (randomized to order of treatment). The primary endpoint was change in subcortical CBF, with secondary outcome measures including change in cortical CBF and a panel of neuropsychological assays of cognition. The Perfusion by Arterial Spin Labelling Following Single Dose Tadalafil in Small Vessel Disease (PASTIS) trial was funded by the ADDF and the UK Alzheimer’s Society (Clinical trial registration: clinicaltrials.gov/ct2/show/NCT02450253; eudract.ema.europa.eu/2015‐001235‐20).ResultTadalafil increased CBF non‐significantly in all subcortical areas (N = 55, age: 66.8 (8.6) years) with greatest treatment effect within white matter hyperintensities (+9.8%, P = 0.0960). There were incidental treatment effects on systolic and diastolic blood pressure (‐7.8, ‐4.9 mmHg respectively; P<0.001). No serious adverse events were observed.ConclusionThe PASTIS trial did not identify a significant treatment effect of single‐administration tadalafil on subcortical CBF. To detect treatment effects may require different dosing regimens.
Automating the verbal paired associates test to assess memory remotely and at scale
Authors: Cormack Francesca K , Kaula Alexander J , Taptiklis Nick 
Published: December 2022

AbstractBackgroundVerbal neuropsychological tests are sensitive to the early signs of neurodegeneration in older adults. However, their dependence on in‐person testing and manual scoring make them unsuitable for large‐scale screening and home‐based monitoring. To address this, we have developed a fully automated verbal paired associate learning (VPA) test. Here we describe the program of work to refine and validate this task, and ensure suitability of the test for remote, repeat administration.MethodsTwo phases of data collection were carried out. In the first, data was collected from 3,264 participants aged 17–86 years (M = 34.5, SD = 12.32) at home and on their own devices. The automated VPA task comprises eight word‐pairs, learned over three attempts. Automatic speech recognition (ASR) scores responses in real‐time, using the Neurovocalix platform. Following this phase, the task was refined to better enable repeat testing. This included producing a large corpus of algorithmically generated pairs, controlling for important linguistic features (e.g. frequency and concreteness), and adding brief familiarisation to the first visit to increase reliability and stability. We assessed: 1) the accuracy of automated scoring 2) the impact of participant characteristics and task design on performance and consistency 3) participant feedback.ResultsData from the first phase showed excellent correspondence between human and automated scoring of VPA, with a correlation .93 (p < 0.001), and the expected sensitivity to ageing number of task performance. Participant demographics and technology choice did not impact correspondence between ASR scoring and manual scoring. In the second phase data collection, we compared VPA performance in participants with (N = 190) and without (N = 186) prior familiarisation. Familiarisation dramatically improved consistency of participant performance, eliminating the significant effect of task order on performance (F > 100, p < 0.001). Participants reported that they found the task engaging and easy to understand, and repeated testing over five sessions in older adults was well tolerated.ConclusionsTogether, these results demonstrate that remote, automated, voice‐based, cognitive assessments are feasible and acceptable. These methods may therefore be useful in the context of home‐based screening or monitoring in remote clinical trials, enabling longitudinal assessment of memory in AD.
Generative Adversarial Network‐Enhanced Ultra‐low‐dose [18F]‐PI‐2620 Tau PET/MR Imaging
Authors: Chen Kevin , Tesfay Robel , Koran Mary Ellen , Ouyang Jiahong , Shams Sara , Liang Tie , Khalighi Mehdi , Mormino Elizabeth C. , Zaharchuk Greg 
Published: December 2022

AbstractBackgroundIn neurodegenerative diseases such as Alzheimer’s disease, simultaneous PET/MRI provides a “one‐stop shop” to acquire biomarkers as outlined by the AT(N) criteria. However, to enable large‐scale imaging studies of dementia with frequent follow‐ups, a reduction of injected radiotracer dose and the enhancement of the degraded image quality after reconstruction needs to be addressed.With deep learning‐based methods, we have previously demonstrated the use of U‐Net‐based methods that incorporate spatially correlated PET/MRI information to produce high quality 18F‐florbetaben amyloid PET images from scan protocols with markedly reduced injected radiotracer dose (as low as ∼1% dose). However, for tau radiotracers, where the uptake is focal, has greater image noise, and the signal is weaker than that of amyloid, we also aim to investigate whether a generative adversarial network (GAN) can enhance ultra‐low‐dose tau PET images and whether the generated images are of diagnostic quality.Method44 participants (18 female, 70.2±7.5 years) were recruited to train the ultra‐low‐dose tau GAN; 221±61 MBq of the tau radiotracer 18F‐PI‐2620 was injected. T1‐weighted and T2‐FLAIR MRI were acquired simultaneously. A subset of the list mode consisting of 1/20 of the events (simulating 5% dose) was reconstructed to produce an ultra‐low‐dose PET image and used as inputs along with the MR images to train the GAN.The image quality of the enhanced PET and the ultra‐low‐dose PET images were compared to the original full‐dose image using three image‐based metrics ; the mean and standard deviation of uptake in the medial temporal lobe and inferior temporal cortex as well as SUVRs were also calculated. Three clinicians were recruited to evaluate tracer uptake on various regions of interest.ResultThe enhanced images showed significant noise reduction compared to the low‐dose image (Figure); uptake patterns in the low‐dose and enhanced images were read accurately (Gwet’s AC1>0.84 for all relevant regions) compared to their full‐dose counterparts.ConclusionThe deep learning‐enhanced images had marked noise reduction and were able to be read clinically for regional uptake patterns of tau accumulation similarly as the full‐dose images. This technique can potentially increase the utility of hybrid PET/MR imaging in clinical diagnoses and longitudinal studies.
Dementia Analytics Research User Group (DARUG) ‐ A Model for meaningful stakeholder engagement in dementia research
Authors: Carlin Paul , Wallace Jonathan , Moore Adrian , Hughes Catherine , Black Michaela , Rankin Deborah , Hoey Leane , McNulty Helene 
Published: December 2022

AbstractBackgroundThe importance of involving stakeholders in research is widely recognised but few studies provide details to implementation in practice. The use of real‐time technology involving patients, carers and professionals in project design, monitoring, delivery and reporting could maximise contribution. Stakeholder engagement was included as part of a Dementia Analytics Research User Group project which applied machine learning to the Trinity‐Ulster‐Department of Agriculture (TUDA) data set, identifying clinical and lifestyle factors associated with cognitive health in 5000 community‐dwelling older Irish adults.MethodAn innovative model for engagement (ENGAGE) was used1 ‐ a methodological and technology platform, that gains insight into group thinking and consensus. Developed by Ulster University, this produces a report in real time for sharing to all stakeholders, thus ensuring active involvement in defining the research question. Using a Personal and Public Involvement (PPI) approach, representatives from patient and carer groups (including TUDA participants ), charities (e.g., Alzheimer’s UK), as well as professionals, were invited to attend one of three scoping events. Each event commenced with an overview by the project team of the value of data analytics and initial data analysis. The PPI groups were then invited to answer specific questions relating to risk factors for dementia and were asked to articulate their expectations on the potential outcomes from the project. These responses were analysed using ENGAGE and word clouds generated for discussion to help refine the project going forward.ResultsParticipants (n=87) Lifestyle, Genetics, Stress and were the dominant emerging themes for risk factors of dementia. Prevention, Help and Information/ Research emerged as strong themes, with the mind maps showing stimulus, understanding and awareness as key outputs of this project. The outcomes of this engagement model were utilised to successfully inform the subsequent data analytics portion of the study2.ConclusionThe model performed well, capturing discussions in real time. Feedback was positive and helped to focus and inform the research team’s thinking. What was not so successful was the longer‐term inclusion in the project, with engagement through remote channels tending to drift over time, somewhat exacerbated by COVID 19 restrictions. The team aim to follow up on this aspect.