bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changes of the texture and volume of brain MRI in Suspected Non Alzheimer Pathology and Alzheimer’s disease
Authors: Kwon Min Jeong 
Published: December 2023

AbstractBackgroundSuspected Non Alzheimer Pathology (SNAP) is a biomarker‐defined syndrome that encompasses a group of individuals with neurodegeneration, but no evidence of amyloid deposition. However, it is still unclear whether SNAP represents distinct pathology separate from AD. We examined the differences in the volume and texture of key regions of interest (ROIs) in brain MRI between SNAP and AD to discuss the different causes of neurodegeneration.MethodWe enrolled all participants from dementia clinics of Seoul National University Bundang Hospital. We obtained three‐dimensional structural T1‐weighted magnetic resonance images of the participants using 3.0 Tesla Achieva Scanner and compared the texture and volume of ROIs between the groups using analysis of variance with Bonferroni post hoc comparisons.ResultThe SNAP group showed comparable volumes to the AD group in all ROIs. Compared with regional volume, regional texture showed different features between SNAP and AD. The SNAP group showed different texture in precuneus, posterior cingulate cortex, superior parietal cortex and inferior parietal cortex. In these regions, the entropy which reflects the randomness of spatial distribution of gray levels was higher in the AD group compared to the SNAP group.ConclusionThis study demonstrated that the texture change of SNAP was different from that of AD despite a similar volume change. In conclusion, our study suggests that MRI texture can be used for detection of microstructural changes in the early stage of the disease.
Dementia and Stroke Risk Associated with Brain Artery Luminal Diameters
Authors: Melgarejo Jesus D , Gurel Kursat , Compton Cassidy R. , Liu Minghua , Assuras Stephanie , Levin Bonnie , Sacco Ralph , Elkind Mitchell S.V. , Rundek Tatjana , Ikram M. Kamran , Kavousi Maryam , Ikram M. Arfan , Wright Clinton B. , Crivello Fabrice , Laurent Alexandre , Tzourio Christophe , Vernooij Meike W , Yu Zhang Zhen‐ , Bos Daniel , Gutierrez Jose 
Published: December 2023

AbstractBackgroundIt is unclear whether brain artery diameters measured on conventional T2‐weighted brain MRI images relate to dementia and stroke outcomes across distinct populations. We aimed this study to evaluate the association of T2‐weighted brain artery luminal diameters with dementia and stroke in three distinct population‐based studies.MethodsThree longitudinal population‐based studies with 8420 adults >40 years old (Northern Manhattan Study [NOMAS] from the United States, and the Rotterdam Study [RS], from the Netherlands, and Three‐City, from France) with brain MRI scans obtained between 1999 and 2015. The median follow‐up time for clinical events ranged between 7 and 12.5 years. We tested our hypothesis in each cohort separately due to local data‐sharing regulations. The exposure variable was brain carotid and basilar artery luminal diameters measured on MRI axial T2‐weighted scans. Multivariable hazard ratios (HRs) and their 95% confidence intervals (CI) expressed the risk of dementia and stroke (primary outcomes) associated with the lowest (<5th) and highest (>95th) percentiles of the rank‐normalized brain artery diameters compared to a reference group defined as the diameters distributed between the 5th and 95th percentiles. Secondary outcomes included total and vascular mortality, and fatal and nonfatal cardiovascular and coronary end points.ResultsAmong the three cohorts (mean age ranged from 65 to 73 y, ≥57% women), 335 participants developed dementia and 331 strokes. Compared with the reference group, participants with arterial diameters >95th percentile had a higher risk of dementia (HR range 1.15‐4.50) and any stroke (HR range 1.29‐2.03). For secondary outcomes, participants with arterial diameters >95th percentile had a consistent higher risk of coronary outcomes, vascular mortality and a composite of any vascular events. The results were less supportive of a higher risk of events among participants with arterial diameters <5th percentile except for vascular mortality.ConclusionsIndividuals with dilated brain arteries are at higher risk of dementia and vascular events. Our findings were consistency across distinct populations in spite of using a non‐enhanced, conventional T2‐weighted MRI sequence. Understanding the underlying physiopathology of the reported associations, particularly with dementia and stroke, might reveal novel vascular contributions to dementia
Neural correlates of episodic memory encoding and resilience to Alzheimer’s Disease in amyloid‐positive cognitively unimpaired individuals
Authors: Joseph Jane E , Warner Graham , Nowling Duncan , Bustos Nicholas , Barlis Katie L , Mintzer Jacobo , Brawman‐Mintzer Olga , Lawson Andrew , Dean Brian , Jensen Jens H. , Rodriguez‐Porcel Federico E , Turner Travis E , Benitez Andreana 
Published: December 2023

AbstractBackgroundEpisodic memory (EM) impairment is an important feature of early Alzheimer’s Disease and is related to well accepted biomarkers of AD. Monitoring healthy individuals for EM impairment may allow for early detection of risk for AD or a better understanding of resilience to cognitive decline. The present study used a functional magnetic resonance imaging (fMRI) EM task to examine whether neural substrates of EM are associated with classic features of AD.MethodHealthy adults (n = 120, 84 females, 45‐85 years of age) completed a 5‐minute fMRI EM encoding task which presented photographs of unfamiliar faces and objects with instructions to remember the items for later recognition. Following fMRI preprocessing using FSL, first‐level statistical analysis (using Feat) included an explanatory variable that modeled Items that were correctly remembered in the recognition phase to reflect successful encoding. Group‐level voxel‐wise analysis then examined which of a number of different AD features independently moderated fMRI response during successful encoding, including amyloid deposition from PET, hippocampal volume from MRI, APOE e4 status, and performance on neuropsychological tests (Craft story recall, Multi‐Lingual Naming Test: MINT, global cognition: MOCA). Age, sex and education were included as covariates in all voxel‐wise analyses and activation maps were cluster‐corrected using Z > 3.1, p = .05.ResultThe only AD marker that significantly moderated EM successful encoding was amyloid status. Amyloid+ individuals (n = 25) recruited an area of the left antero‐lateral temporal cortex (MNI coordinates: x = ‐68, y = ‐30, z = ‐14) more strongly than Amyloid‐ individuals (n = 94). A post‐hoc exploratory analysis (controlling for age, sex and education) revealed that in Amyloid+ individuals, activation in the dorsal aspect of this temporal region was associated with better delayed memory performance (partial r = .426, p = .048) and activation in the ventral aspect of this region was associated with greater left hippocampal volume (partial r = .489, p = .021). In contrast, in Amyloid‐ individuals, activation in the dorsal aspect of this temporal region was associated with better performance on the MINT (partial r = .288, p = .006).ConclusionRecruitment of left lateral temporal cortex during successful encoding in Amyloid+ individuals was associated with better delayed memory recall performance and greater hippocampal volume, suggesting a potential profile of resilience to AD.
Pathogenic motor neuron disease‐linked mutations distinctly alter TDP‐43 nanoscale dynamics
Authors: Bademosi Adekunle T. 
Published: December 2023

AbstractBackgroundThe hallmark of motor neuron disease (MND) pathology is the abnormal accumulation of insoluble proteins that form inclusions in motor neurons within the spinal cord and primary motor cortex. How, why, and when these proteins begin to aggregate has not been fully elucidated. In up to 97% of all MND cases, TAR DNA‐binding protein‐43 (TDP‐43) is a key protein that is mislocalised from its native nuclear presence into cytoplasmic inclusions. Furthermore, genetic mutations in TDP‐43 are implicated in familial MND, further linking the function of this protein to this neurodegenerative disease. The precise mechanism that drives the aggregation of TDP‐43 in MND is unknown, however identifying the changes in the dynamics of the protein within the nucleus could shed light on how the different mutations contribute to its altered function in MND.MethodWe applied nanoscale single‐molecule imaging to identify the changes in the dynamics and localisation of TDP‐43 caused by well characterised pathogenic‐causing mutation. This was done by tagging the proteins with the photoconvertible fluorescent protien ‐ mEOS3.2. Single molecule imaging was subsequently carried out in cells and neurons expressing the proteins.ResultWe observe that the different pathogenic mutations uniquely influence the mobility of TDP‐43. Most of the MND‐linked mutations inhibit the movement of TDP‐43 similar to how oxidative stressors such as arsenite induce inclusions of TDP‐43 thereby immobilising the molecules. Furthermore, our data indicates that post‐translational modifications in TDP‐43 such as acetylation similarly restricts its dynamics within the nucleus.ConclusionTogether, our data suggests that the confinement of mobility of TDP‐43 is a key step in the formation of toxic aggregates in disease.
ALLICIN PREVENTS MPTP‐INDUCED MOTOR DYSFUNCTION AND BIOCHEMICAL ABNORMALITIES IN WISTAR RATS
Authors: Attri Paras , Deshmukh Rahul Renukadas 
Published: December 2023

AbstractBackgroundParkinson’s disease (PD) is an age‐related progressive neurodegenerative disorder, characterized by loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) region of the brain. Dopaminergic degeneration involves the number of mechanisms such as oxidative stress and neuroinflammation. Allicin has been reported to exert various anti‐oxidative and anti‐inflammatory activities in in‐vitro and in‐vivo studies. Therefore, in the present study, we have investigated neuroprotective effect of allicin against MPTP induced Parkinson’s disease in rats.MethodRepeated intranigral infusion of MPTP at day 1st, 4th, and 7th produced significantly loss in body weight, locomotor activity, motor coordination, antioxidant defense enzymes (reduced glutathione) and significantly increase oxidative stress markers (lipid peroxidation and nitrite level) in the striatum. MPTP treatment also increased pro‐inflammatory cytokines (TNF‐α, IL‐6, and IL‐1β) level and decreased neurotransmitter level in the striatum. Allicin (5, 10 and 20mg/kg/day i.p.) treatment from day 8th to 21st significant reversed the behavioral, antioxidant defense enzymes, oxidative stress marker and pro‐inflammatory cytokines in MPTP infused rats.ResultAllicin (5, 10 and 20mg/kg/day i.p.) treatment from day 8th to 21st significant reversed the behavioral, antioxidant defense enzymes, oxidative stress marker and pro‐inflammatory cytokines in MPTP infused rats.ConclusionThe consequences of particular study suggest the beneficial effects of allicin in PD.
Chronobiology of nutrition and cognitive function
Authors: Scarmeas Nikolaos , Yannakoulia Mary 
Published: December 2023

AbstractCurrent literature on the association between nutrition and cognitive function has focused mainly on total daily dietary intake of nutrients, foods or dietary patterns, while there has been much less focus on the timing of intake, i.e. the distribution of intake throughout the day and/or during specific eating occasions. Meal timing interferes with the circadian clocks and it has been previously linked with several health outcomes, including obesity and glycemic control. At the same time, there are well established circadian rhythms in cognitive performance in humans, with worse performance in the early morning and late evening and best performance somewhere in the middle of the daytime.Literature of the chronobiology of nutrition (chrononutrition) in relation to cognitive function and decline is extremely limited and to a certain extend conflicting. For example, breakfast consumption has been associated with decreased odds of having Mild Cognitive Impairment (MCI) in some studies, while, according to other studies, individuals with Alzheimer’s Disease (AD) and MCI tend to prefer early (rather than late) day times for food intake. Overall, there is very little research on the effect on cognitive function of time of day or energy content or nutrient distribution of the consumed meals. Furthermore, even though certain biomarkers of neurodegeneration are known to exhibit circadian properties, their associations with aspects of chrononutrition have not been explored.In conclusion, there is growing interest in the field of chrononutrition, an emerging area of investigation that is revealing important insights into how the timing of meals and overall eating patterns can impact cognitive function in humans. Part of the reason that this field is still in its infancy is that not all methods of dietary assessment are suitable for such analyses: only the laborious and time‐consuming methods of 24h dietary recalls or food records, that collect information on the timing of each eating occasion, allow for the evaluation of intake (nutrient of foods) distribution during the day.Overall, much more investigational effort is needed to fully understand the mechanisms underlying potential associations of chrononutrition and cognition and to develop practical recommendations for maintaining cognitive health through dietary interventions.
The food metabolome for precision nutrition in dementia prevention
Authors: Samieri Cécilia 
Published: December 2023

AbstractUnderstanding which aspects of diet and lifestyle may predispose to the development of Alzheimer’s disease and identifying populations vulnerable to prevention by lifestyle modification is a critical asset for precision prevention. However, diet is a complex exposure that is extremely challenging to evaluate using questionnaires in human populations, and inherent measurement error in self‐reported dietary intake data has certainly hampered our way to study properly the impact of nutrition on brain health in epidemiological studies.Measuring markers of nutritional exposure in biological matrices represents a unique way to monitor nutrition and dietary intakes. Candidate biomarkers have been complemented recently by a comprehensive investigation in biological matrices of the chemicals derived from foods after digestion and metabolism, the so‐called food metabolome, that has started to reveal novel dietary biomarkers. High‐throughput metabolomics now enable the measurement of markers of food exposures in biological matrices with unprecedented depth, while capturing the heterogeneity in the response to dietary bioactives from diet across individuals and populations. Thus biomarkers are critical for precision nutrition, as they reflect nutritional status, a product of intakes and of endogenous metabolism, itself linked to many factors, including personal genetic background and microbiome.This “Perspectives” presentation will overview a few recent exploratory studies on signatures of healthy diets and brain health in the food metabolome as examples to discuss challenges and opportunities for further developments. We will also address opportunities of development of multi‐biomarker panels combining self‐reported nutritional intake data with biomarker data from biofluids (blood and urine) to improve assessment of healthy dietary patterns as preventive approaches in dementia.
Personalized Nutrition for APOE4 carriers: mechanisms and biomarkers that can inform future trials
Authors: Yassine Hussein N. 
Published: December 2023

AbstractCurrent studies suggest that the beneficial effects of increased polyunsaturated fat consumption (Mediterranean diet, fish consumption or long‐term DHA supplementation) on cognition are stronger in younger and middle aged APOE4 carriers. The efficacy of these nutritional interventions in APOE4 appears to wane with advancing age and cognitive disease. In addition, a recent systematic review revealed that ketogenic diets do not appear to have a beneficial effect on cognitive performance in APOE4 carriers compared to non‐carriers.In this talk, we focus on leading mechanisms of cerebral bioenergetic breakdown in the aging APOE4 brain that implicate neuroinflammation in several brain cell types including those of the blood‐brain barrier (BBB). We then address consequences of neuroinflammation and disturbed bioenergetics at the BBB on the delivery and brain metabolism of nutrients such as omega‐3s, nutrients and ketones. We provide examples of novel lipidomic biomarkers that can capture neuroinflammation in the Religious Order Study, DHA Brain Pilot Trial, and the ADCS DHA trial. Advances in brain imaging of polyunsaturated fatty acid brain uptake by PET are provided to obtain insights into APOE4 brain fatty acid consumption changes during the lifespan. Finally, we highlight how the ongoing PreventE4 trial is integrating measures of the gut microbiome to understand the effects of omega‐3 supplementation on the brain in individuals carrying the APOE4 allele and at risk for dementia.
The cerebrospinal fluid soluble TREM‐1 concentration in Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI)
Authors: Doroszkiewicz Julia , Kulczynska‐Przybik Agnieszka , Dulewicz Maciej , Borawska Renata , Slowik Agnieszka , Mroczko Barbara 
Published: December 2023

AbstractBackgroundThe most prevalent form of dementia in the world is Alzheimer Disease (AD), a common neurodegenerative condition. Amyloid peptides, phosphorylated tau proteins, and neuroinflammation are the disease’s hallmarks. Finding new biomarkers that can assist in early AD detection is crucial due to the late appearance of the disease symptoms. Triggering receptor expressed on myeloid cell 1 (TREM‐1) is hypothesized that may contribute to the development of AD by causing neuroinflammation. Due of its significance in inflammatory responses, it has been regarded as a promising biomarker. Literature data indicate that TREM‐1 could be potential biomarker of AD severity. Therefore the purpose of our research was to measure the concentration of soluble TREM‐1 in cerebrospinal fluid of AD and MCI patients and non‐demented controls and compare it with classical AD biomarkers.MethodThe concentrations of TREM‐1 were measured in cerebrospinal fluid (CSF) of 20 AD patients and 15 MCI patients as well as 11 non‐demented controls using multiplexing method. Classical biomarkers, such as Aβ‐42, Aβ‐42/Aβ‐40, tau and pTau181 were assessed by immunoenzyme assays.ResultTREM‐1 concentrations were significantly higher in AD and MCI patients in comparison to non‐demented controls. Moreover, in MCI patients, the levels of this protein were significantly higher than in AD patients. Additionally, increased CSF levels of TREM‐1 correlated positively with Tau, pTau181 in the whole study group.ConclusionFindings of our research suggest that TREM‐1 could be early indicator of AD pathology. However, follow‐up studies on larger study group are needed.
Artificial Intelligence and Machine Learning (AIML) approaches to empower genomics, drug, and biomarker discovery in ADRD
Authors: Thompson Paul M , Raj Towfique 
Published: December 2023

AbstractBackgroundIn 2021, the NIA launched the Artificial Intelligence and Machine Learning (AIML) Consortium, to develop novel AI and machine learning techniques to tackle pressing questions in Alzheimer’s disease research.MethodDrawing on vast repositories of data from the Alzheimer’s Disease Sequencing Project (ADSP) and other large public biobanks, the 8 awardees funded under this program meet monthly to present their innovations in data analytics in 4 main areas: (1) genome‐guided drug discovery and drug repositioning for AD; (2) discovery of novel genetic and molecular targets for AD therapeutics using whole genome and omics data; and (3) understanding the regulatory code of the genome using deep learning and bioinformatics, and (4) use of electronic health records (EHR) to study treatment outcomes in ADRD. A second branch of AIML activity draws on repositories of neuroimaging data (MRI/FLAIR, DTI, and amyloid‐ and tau‐sensitive PET) to (1) identify ADRD subtypes based on neuroimaging, clinical and neuropsychological data, that differ in terms of their genomic drivers and expected treatment response (for precision medicine and drug trial stratification), (2) perform genetic analysis of endophenotypes derived from brain images (such as longitudinal hippocampal volume changes, atrophy subtype scores, and PET or WMH signatures) for biomarker‐guided gene discovery, and (3) predict neuropathology (TDP‐43, CAA, LBD) from multimodal imaging using AI. The AIML initiative benefits from and helps the ADSP’s Phenotype Harmonization Consortium, as AI methods can also be used to adjust neuroimaging data for site and protocol effects (harmonization).ResultIn this overview of the AIML Consortium, we highlight some recent successes using (1) convolutional neural networks (CNNs), GANs and deep learning for ADRD subtyping and staging; (2) discovery of AD‐relevant motifs and networks in whole genome sequences and functional genomics data; (3) prognostic models of clinical outcomes based on WGS and biomarkers; and (4) novel methods from statistical physics, based on evolutionary action, which model the fitness effect of coding mutations analytically.ConclusionAIML investigators are hosting regular workshops at AAIC and upcoming genomics and clinical neurology conferences to disseminate and teach these approaches to the AD and broader scientific community.