bluuebunny/crossref_metadata_2025_split huggingface dataset:
CNS Immune Surveillance in Alzheimer’s Disease
Authors: Elyaman Wassim 
Published: December 2023

AbstractBackgroundThe etiology of Alzheimer’s disease (AD) is currently unknown, but several risk factors have been associated with AD including infectious agents. The central nervous system (CNS) is continuously monitored by immune cells, many of which circulate through the cerebrospinal fluid and the meninges. Meningeal immune cells respond to CNS‐intrinsic perturbations, such as neuroinflammation or neurodegeneration as well as to CNS‐extrinsic challenges, such as systemic infection. The goal of the study is to analyze the profile of meningeal immune cells and T cell clonality in AD in comparison with other neurodegenerative diseases.MethodWe used single‐cell RNA and T‐cell receptor (TCR) sequencing to characterize CD45+ immune cells from fresh leptomeninges from AD, Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).ResultWe identified multiple myeloid and lymphoid clusters in all neurodegenerative samples including meningeal macrophages expressing CD14 and C1QA and the resident meningeal macrophage marker LYVE‐1. Lymphoid populations represented the majority of total cells and were composed of both CD8+ effector memory T‐cells and a mixed population of NK cells and NK‐like T‐cells. Ligand/receptor network analyses identified several significant intercellular interactions including osteopontin signaling between meningeal macrophages and both clonally expanded cytotoxic CD8 T and NK/NK‐like T‐cells. TCR sequence analysis revealed up to 500 unique TCR clonotypes in each sample, many of which were hyperexpanded with 25‐50% of the TCR repertoire being occupied by the top 20 clonotypes and some of which had high TCRa chain sequence homology to EBV‐specific TCRs.ConclusionWe provide evidence for disrupted myeloid homeostasis and broad T‐cell clonal expansion in the leptomeninges of AD patients. Network analyses suggest that meningeal macrophages in neurodegeneration may promote long‐term clonally expanded T‐cell survival through osteopontin signaling. These data recapitulate findings across several animal studies and will be useful in developing immunomodulatory interventions to treat neurodegeneration.
Self‐harm in people with dementia – assessing risk factors, health profiles and healthcare pathways using big data
Authors: Reppermund Simone , Walker Adrian , Cvejic Rachael , Srasuebkul Preeyaporn , Wand Anne , Draper Brian , Trollor Julian N 
Published: December 2023

AbstractBackgroundDementia is often associated with poorer mental health and higher rates of self‐harm compared to older people without dementia. This study investigated risk factors for self‐harm in dementia and risk factors for developing dementia following self‐harm. A further aim was to elucidate the health profiles and healthcare pathways of individuals with dementia who self‐harm as a critical step to develop effective prevention strategies.MethodUsing linked health data from hospital admissions, emergency department presentations and ambulatory mental health visits, we established a population‐based cohort of individuals with dementia and self‐harm in New South Wales, Australia spanning 13 years. The project was guided by an advocate advisory group, including people with dementia and care‐partners who inform all stages of the project.ResultThe cohort included 154,811 people with dementia, of which 652 (0.4%) had a subsequent diagnosis of self‐harm. People with dementia who self‐harmed were younger at the time of their dementia diagnosis (median age 69.6 (IQR 52.7‐80.1) versus 83.5 (IQR 78.0‐88.1)) and had a lower proportion of females (39.4% versus 59.6%) compared to people with dementia without self‐harm. A diagnosis of self‐harm most often occured within 24 months after a dementia diagnosis. Men living with dementia, and people with complex psychiatric profiles had the greatest risk of self‐harm. People with dementia and self‐harm had more comorbidities compared to those without self‐harm. The most frequent comorbidities in people with dementia and self‐harm were drug/alcohol use (19.9%), depression (13.5%), anxiety (11.8%), and psychotic disorder (10.9%); these comorbidities were observed in 2.7%, 2.7%, 2.2% and 2.1% of people with dementia without self‐harm, respectively. People with dementia and self‐harm had more ambulatory mental health visits, ED presentations and involuntary admissions in the year before a dementia diagnosis compared to those without self‐harm.ConclusionThe health profiles and healthcare pathways are significantly different for people with dementia who self‐harm versus those who do not. Poor mental health, dementia, and self‐harm are substantially intertwined in older adults. Post‐diagnostic counselling and support should be provided following a dementia diagnosis. This project will inform strategies for health services to better meet the needs of people with dementia who self‐harm.
TauFlowNet: Uncovering Spreading Pathways of Tau Aggregates by Neural Transport Equation
Authors: Wu Guorong , Dan Tingting 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is characterized by the propagation of tau aggregates throughout the brain in a prion‐like manner. Since current pathology imaging technologies only provide a spatial mapping of tau accumulation, computational modeling becomes indispensable in analyzing the spatial‐temporal propagation patterns of widespread tau aggregates.MethodCurrent state‐of‐the‐art works focus on the change of focal patterns, lacking a system‐level understanding of the tau propagation mechanism that can explain and forecast the cascade of tau accumulation. To address this limitation, we conceptualize that the inter‐cellular spreading of tau pathology forms a dynamic system where each node (brain region) is ubiquitously wired with other nodes while interacting with the build‐up of pathological burdens. In this context, we formulate the biological process of tau spreading in a principled potential energy transport model (constrained by brain network topology), which allows us to develop an explainable neural network for uncovering the spatial‐temporal dynamics of tau propagation from the longitudinal tau‐PET scans. Specifically, we first translate the transport equation into a backbone of graph neural network (GNN), where the spreading flows are essentially driven by the potential energy of tau accumulation at each node.ResultFirst, our physics‐informed deep model yields more accurate prediction of future tau aggregates. Second, we generate the population‐wise brain mapping of tau spreading through the brain. Sub‐cortex to cortex flows are the predominant patterns in the early stage of AD while the spreading patterns turn to cortex‐to‐cortex propagation as the disease progresses.ConclusionOur physics‐informed deep model outperforms existing state‐of‐the‐art methods in terms of prediction accuracy and model explainability. Since the region‐to‐region spreading flow provides rich information for understanding the tau propagation mechanism, our learning‐based method has great applicability in current AD studies.
Regulation of insulin entry into the brain
Authors: Rhea Elizabeth 
Published: December 2023

AbstractBackgroundCentral nervous system (CNS) insulin has repeatedly been shown to play a role in cognition. Little, if any, insulin is synthesized in the brain and therefore requires navigation of the blood‐brain barrier (BBB) to act. The BBB is a unique structure in the brain that regulates the entry of serum substrates and can act as both a barrier and signaling structure. We hypothesize the BBB is a critical structure involved in the regulation of CNS insulin signaling and CNS insulin availability. We have investigated the regulation of insulin BBB transport and interactions under various conditions including exercise, brain insulin resistance, and have begun to explore the mechanisms for insulin transport across the BBB.MethodFor exercise, male and female mice were habituated to locked voluntary running wheels. After habituation, wheels were unlocked in some cages (exercise) for 24 hours while remaining locked (sedentary) in the others. For brain insulin resistance, mice were treated with an intracerebroventricular delivery of the insulin receptor antagonist, S961. For mechanisms involved in insulin BBB transport and interactions, endocytosis inhibitors were used to differentiate between clathrin and caveolin endocytosis. Following manipulation, insulin BBB pharmacokinetics were assessed with the quantitative multiple‐time regression analysis using radioactively labeled insulin and albumin, a marker for vascular space. Mice were injected intravenously or perfused in situ with the radiolabeled substrates and at timepoints up to 10 min, blood and brains collected and radioactivity measured. 125I‐insulin entry and binding to the BBB was assessed.ResultExercise enhanced 125I‐insulin interactions at the BBB. Specifically, exercise increased insulin BBB transport by two‐fold in males and increased insulin binding at the BBB in females. Brain insulin resistance impaired 125I‐insulin transport across the BBB, particularly in females. Lastly, caveolin‐mediated endocytosis may be involved in hypothalamic 125I‐insulin BBB transport.ConclusionWe have shown insulin BBB transport is highly regulated and can be impacted by exercise, brain insulin resistance, and may involve various endocytic pathways in a regional‐dependent manner. Continued investigation on the pathways involved in insulin BBB transport is warranted to aid in treating or preventing brain insulin resistance as occurs in Alzheimer’s disease.
Imaging the brain to assess brain insulin action
Authors: Kullmann Stephanie 
Published: December 2023

AbstractBackgroundEver since the brain was identified as an insulin‐sensitive organ, it was quickly appreciated that insulin action in the brain affects cognitive and metabolic processes [1]. Epidemiological evidence suggests a strong link between reduced peripheral insulin sensitivity and age‐related neurodegenerative processes, including Alzheimer’s disease (AD) [2].MethodCharacterization of brain insulin resistance in humans is challenging and relies on different neuroimaging methods in combination with insulin stimulation techniques. In my talk, I will focus on the administration of intranasal insulin, which has been established over the last decades to disentangle peripheral from brain insulin effects [1]. In combination with functional neuroimaging, I will show recent data on the quantification of brain insulin sensitivity non‐invasively in humans of different age and weight groups [3].ResultWe could show that intranasal insulin can affect region‐specific activity and functional connectivity of the human brain. These diverse central insulin responses largely depend on its action in the hypothalamus, amygdala, hippocampus, striatum and parts of the insula and prefrontal cortex and influences a variety of metabolic and cognitive processes [3]. Specifically, I will show that disrupted brain insulin action can result in increased accumulation of visceral fat and altered reward learning in persons at high risk to develop T2D [4], but also in healthy individuals after overconsumption of high caloric foods (unpublished). Moreover, I will show that the effect of intranasal insulin in the hippocampus decreases with age in women but not men and that brain insulin responsivity is affected by the menstrual cycle (unpublished). Moreover, just recently, we could link enhanced brain insulin action in the mesocorticolimbic circuitry with improved cognitive and metabolic functions [5].ConclusionAs brain insulin acts on striatal dopamine function and hippocampal plasticity, enhancing brain insulin action could lead to new treatment options in diabetes and aging‐associated diseases.References1. Hallschmid, M. J Neuroendocrinol, 2021. 33(4): p. e12934.2. Frazier, H.N., et al. Exp Neurol, 2019. 313: p. 79‐87.3. Kullmann, S., et al. Lancet Diabetes Endocrinol, 2020. 8(6): p. 524‐534.4. Kullmann, S., et al. Nat Commun, 2020. 11(1): p. 1841.5. Kullmann, S., et al. JCI Insight, 2022. 7(18).
Development of NLRP3 PET Radiotracers for Alzheimer’s disease
Authors: Xu Yiming , Xu Yulong , Biby Savannah , Wang Changning , Zhang Shijun ,   Medicinal Chemistry, VCU
Published: December 2023

AbstractBackgroundNovel PET tracers were designed and tested to target the NLRP3 inflammasome in the brain to develop biomarkers for neuroinflammation in AD.MethodA novel chemical scaffold was rationally designed based on our previously developed NLRP3 inhibitors. One of the compounds, YM8, was radiolabeled with C‐11, and radiotracer was characterized in mouse models and non‐human primates (NHPs).ResultThe studies in wild type and nlrp3‐/‐ mouse brain tissues demonstrated that [11C]YM8 is a NLRP3 specific PET tracer with Bmax/Kd > 10, hinting to be a suitable CNS PET tracer. Studies in mice revealed rapid and high brain uptake of [11C]YM8. PET/MR studies of [11C]YM8 in NHPs demonstrated excellent brain uptake and radiometabolism stability as well as fast washout from blood.ConclusionA novel C‐11 labeled NRP3 PET radiotracer was developed and demonstrated to serve as a suitable CNS PET tracer to monitor inflammatory responses in the brain.
Nutrition in Alzheimer’s Disease: A Review of an Underappreciated Pathophysiological Mechanism
Authors: Jiang Jiwei , Shi Hanping , Li Wenyi , Xu Jun 
Published: December 2023

AbstractBackgroundPharmacy therapy of Alzheimer’s disease (AD) is one of the areas that are well funded, but where little progress has been made due to the complex pathogenesis. The gut‐microbiota‐brain axis has gained tremendous traction in the pathogenesis of AD through bidirectional communication with multiple neural, immune, and metabolic pathways, providing new insights into novel therapeutic strategies. Dietary nutrition is an important and profound environmental factor that influences the composition and function of the microbiota. The Nutrition for Dementia Prevention Working group recently found that dietary nutrition can affect the cognition of AD‐related dementia directly or indirectly through complex interactions of behavioral, genetic, systemic, and brain factors. This review aimed to emphasize the knowledge gaps to provide direction for future research and to establish optimal nutrition‐based intervention strategies for AD.MethodThis review discusses the associated evidence between malnutrition and the onset and development of AD for modifying the potentially reversible nutrition‐related risk factors of AD, describe the potential pathogenesis underlying the role of nutrition in the progression of AD and emphasize the current knowledge gaps for further research.ResultThe role and effects that nutrition and diet have on AD are more pervasive than previously believed. We identified and highlighted a novel vicious cycle comprising malnutrition, development of AD, and heavy caregiver burden (Figure 1). As pharmacological approaches demonstrate limited benefits for improving the symptoms of AD, early nutritional intervention for preventing or delaying the progression of AD are worth attempting. The mechanisms underlying the effect of nutrition on the development of AD remain uncertain, including genetics and epigenetics, AD‐specific biomarkers, metabolic pathways, the gut‐microbiota‐inflammation‐brain axis, and their complex interactions (Figure 2).ConclusionThese potential nutrition‐related pathogenic pathways can be exploited as an important environmental factor and could be the focus of targeted AD interventions. Future research is needed to fill in the discussed gaps in knowledge, including prospective studies to identify nutritional biomarkers that can predict AD, multi‐omics studies to elucidate the exact mechanisms by which nutrition influences AD, and clinical trials to identify the best nutritional intervention strategies to prevent and improve cognitive and behavioral disturbances in the AD population.
Connected speech efficiency and lexical diversity are associated with PET amyloid and tau in a cognitively unimpaired sample
Authors: Hale Madeline R , Van Hulle Carol A. , Langhough Rebecca E , Basche Kristin E , Chin Nathaniel A. , Christian Bradley T. , Betthauser Tobey J , Hermann Bruce P , Johnson Sterling C. , Mueller Kimberly D 
Published: December 2023

AbstractBackgroundChanges in connected speech (CS; language used in everyday conversations) have been documented throughout the Alzheimer’s disease (AD) spectrum, including the very early stages of disease. Our group identified four factors comprised of 10 measures of CS: fluency, semantic content, lexical diversity, and grammatical complexity. We demonstrated that fluency and semantic content were associated with subclinical cognitive decline (Mueller et al., 2018a). However, the relationship between these connected speech factors and AD biomarkers in preclinical AD is unknown.MethodCognitively unimpaired (CU) Wisconsin Registry for Alzheimer’s Prevention participants with positron emission tomography (PET) amyloid (A) and tau (T) were identified; 26 were A+/T+; an equal number matched 1:1 using nearest neighbor propensity score matching for age, sex, literacy, and race were selected from A‐/T‐ and A+/T‐ subsets (n = 78). A priori power calculation based on similar matched designs revealed >80% power to detect a medium effect size. We analyzed CS samples from a picture description task (Cookie Theft) at the neuropsychological visit closest to the most recent PET scans (median visit number = 6). Language measures were extracted from transcripts and transformed into standardized z‐scores that were used to create the factors (details in Mueller et al. (2018b)). ANOVA models investigated whether factor scores and two exploratory individual measures of CS efficiency (content information units per minute (CIU/Min) and semantic unit idea density (SUID)) differed across PET biomarker profiles (A‐/T‐ = reference group). Post‐hoc pairwise comparisons were then completed, and Cohen’s d characterized effect sizes.ResultThe mean(sd) years between CS sample and PET scan was 2.3(1.8) for amyloid and 2.1(1.7) for tau (Table 1). The lexical factor was associated with PET biomarker status, such that participants who were A+/T+ had lower lexical diversity than the A‐/T‐ group. Lower SUID was associated with both A+/T‐ and A+/T+ classification (Figure 1). Associations did not change when analyses were repeated without outliers. Effect sizes were highest for SUID (Table 2).ConclusionOf four previously derived language factors, lexical diversity was associated with PET biomarker status. However, a measure of connected speech efficiency (SUID) was also associated with biomarker status in this preclinical, CU sample. Replication in additional cohorts is needed.
APOE‐dependent and ‐independent polygenic pathways determining early Alzheimer’s Disease pathological changes in CSF and MRI
Authors: Lorenzini Luigi , Collij Lyduine E. , Tesi Niccoló , Ingala Silvia , Sudre Carole H , Wolz Robin , Haller Sven , Blennow Kaj , Frisoni Giovanni B , Payoux Pierre , Martinez‐Lage Pablo , Ewers Michael , Chetelat Gael , Ritchie Craig W , Gispert Juan Domingo , Mutsaerts Henk‐Jan , Altmann Andre , Tijms Betty M. , Wink Alle Meije , Visser Pieter Jelle , Barkhof Frederik 
Published: December 2023

AbstractBackgroundLittle is known about the genetic factors and downstream molecular pathways determining individual variability in fluid and imaging biomarkers associated with Alzheimer’s disease(AD). We studied polygenic risk scores (PRS) and pathway‐specific PRS in relationship with AD fluid and imaging biomarkers, in non‐demented individuals from the European Prevention of Alzheimer’s Dementia (EPAD) cohort.MethodEPAD inclusion criteria were age>50 and Clinical Dementia Rating≤0.5 (n = 1886, Table 1). AD‐PRS was based on 85 previously identified loci, including and excluding APOE (PRSAPOE, PRSnoAPOE)[1]. Using gene‐variant and variant‐pathway mapping[2], six pathway‐specific PRSnoAPOE were identified:1) immune‐activation, 2) signal‐transduction, 3) inflammatory‐response, 4) migration, 5) amyloid‐production, and 6) clearance. Linear models were used to assess the relationship of all PRS with fluid AD biomarkers, including Aβ1‐42, p‐Tau181, and t‐tau; and several imaging biomarkers, including hippocampal volume, global and lobar white matter hyperintensities (WMH) volumes, fractional anisotropy (FA) in 14 regions of interest from diffusion tensor imaging, and 10 resting‐state network connectivity from functional MRI. Models were adjusted for age, sex, site, and multiple comparisons.ResultModels’ coefficients are reported in Table 2. PRSAPOE was significantly associated with decreased Aβ1‐42, and increased p‐Tau181 and t‐Tau. PRSnoAPOE showed a weaker, but still significant, negative association with Aβ1‐42 levels, and a significant positive association with p‐Tau181 and t‐Tau. Aβ1‐42 was only significantly associated with the migration, amyloid, and clearance pathways, while all pathways were significantly positively associated with p‐Tau181 and t‐Tau.Hippocampal volume was only significantly associated with PRSAPOE. Regarding WMH load, PRSAPOE showed a positive association with global, frontal periventricular, and parietal deep lobes. Furthermore, the clearance pathway was related to WMH load in all regions, most strongly in periventricular areas.Only the migration pathway was related to increases in FA in the splenium, body, and genu of the corpus callosum. Only the PRSAPOE was related to reduced functional connectivity (FC) in the default mode, control, and visual networks.ConclusionWe show that genetic risk beyond APOE facilitates the manifestation of AD related pathologies. Moreover, clearance and migration pathways were associated with neuroimaging measures of white matter integrity, while FC and hippocampal volume were associated with overall AD genetic risk.
Pathogenic α‐synuclein triggers focal tau pathology, developing to various brain areas in Parkinson disease
Authors: Hadi Fatemeh , Shahpasand Koorosh , Akrami Hassan , Totonchi Mehdi , Barzegar Abdolrazagh , Nabavi Seyed Massood 
Published: December 2023

AbstractBackgroundParkinson disease (PD) is the second most common neurodegenerative disorder, whose prevalence is 2∼3% in the population over 65. Recent studies have reported enhancing confirmation of tau pathology in PD, however, α‐synuclein accumulation is the significant pathological hallmark of PD. Despite extensive considerations, thus far, the actual spreading mechanism of neurodegeneration has remained elusive in a PD brain. This study aimed to further clarification the development of α‐synuclein and tau pathologies.MethodWe employed several PD models, containing cultured neurons treated with either 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP) or with recombinant α‐synuclein. Furthermore, we examined dopaminergic neurons of cytokine Interferon‐β knock‐out. Moreover, we tested rats administrated with 6‐hydroxydopamine, Rhesus monkeys injected with MPTP neurotoxin, and then human post‐mortem brains.ResultWe observed the α‐synuclein phosphorylation triggers tau pathogenicity. Moreover, we found more widespread phosphorylated tau than α‐synuclein with prion‐like nature in various brain areas. We optionally omitted P‐tau or P‐α‐synuclein from cytokine interferon‐β knock out with respective monoclonal antibodies. We observed that tau immunotherapy prevented neurodegeneration more than α‐synuclein exclusion.ConclusionOur observations show that the pathogenic tau could be one of the prominent causes of extensive neurodegeneration triggered by PD. Consequently, we could recommend an impressive therapeutic aims to fight the devastating disorder.