bluuebunny/crossref_metadata_2025_split huggingface dataset:
Total neuron counts in vulnerable and resilient entorhinal subregions
Authors: Rosenblum Emma W , Augustinack Jean 
Published: January 2025

AbstractBackgroundNeuron loss exceeds tau tangle formation (Gomez‐Isla et al. 1997) and p‐tau vulnerability differs by layer and subfield in entorhinal cortex (Llamas‐Rodriguez et al., 2022). Some subfields succumb to tau early and other subfields later in Alzheimer’s disease. Investigating neuron loss by subfield is pivotal for early diagnosis.MethodWe applied the optical fractionator to count neurons (West, 1991) using Stereoinvestigator (MicroBrightField Inc) in layer II subfields, ER, EI, and ECs, in n = 14 postmortem samples. The samples were preclinical controls, including 6 females, 8 males. A sampling grid (450 µm x 450 µm) with 75 µm x 75 µm counting frame was randomly overlaid. The neurons were counted using a 100x objective (Figure 1). The disector height was 10 µm; with guard zones 3 µm each. Counting inclusion criteria were 1) nucleolus in focus, 2) within inclusion lines, 3) did not touch exclusion lines. The tissue thickness was collected at each counting site (average 20.4 µm). The average coefficient of error was 0.08.ResultTotal neuron counts in EI was 172,429, with ER at 133,161 and EC lower at 103,493 (averaged across samples). Total neuron counts for EI were significantly different than ECs (one‐way ANOVA, p = 0.0033, Tukey’s multiple comparison test, p = 0.0023). Total neuron number from summed subfields did not correlate with age (r = ‐0.2816). Total neuron count for males and females differed but difference was not significant (t‐test, p = 0.5669). No significant differences between total neuron number and the preclinical stages (control, Braak stage I and II samples, averaged) (ANOVA, p = 0.8732).ConclusionThese findings establish a baseline for total neuron number in specific entorhinal subregions of vulnerability (e.g., ECs) and resilience (e.g., ER, EI) at preclinical stage. These data support a previous report that total neuron number in frontal and temporal cortices does not decrease with age (Freeman et al.,2008). Related studies have applied the NvVref method (Gomez‐Isla et al. 1996, Gomez‐Isla et al. 1997, Freeman et al. 2008), but with varying tau pathology at this stage, optical fractionator is the ideal approach. The total neuron number was consistent with age, however, individual variability in the sample set was evident.
The SMOC1 proteomics network M42 controls multiple signaling modalities, brain homeostasis and toxicity in fly Alzheimer’s disease models
Authors: Li‐Kroeger David , Al‐Ramahi Ismael , Smith Nathaniel , Marella Aditi , Amoh Bismark K , Saladi Saathwik , Botas Juan , Seyfried Nicholas T , Levey Allan I. , Shulman Joshua M 
Published: January 2025

AbstractBackgroundAlzheimer’s disease (AD) has a complex etiology where insults in multiple pathways conspire to disrupt neuronal function, yet molecular changes underlying AD remain poorly understood. Previously, we performed mass‐spectrometry on post‐mortem human brain tissue to identify >40 protein co‐expression modules correlated to AD pathological and clinical traits. Module 42 has the strongest correlation to AD pathology and consists of 32 proteins including SMOC1, a predicted driver of network behavior and potential biomarker for AD. SMOC1 is a matrisomal protein with conserved roles in modulating TGF‐Beta and wnt signaling during development, yet remains unstudied in the brain.MethodsWe evaluate M42 using a high‐throughput robotic screening platform and video assisted software, enabling quantitative assessments of neurological function to identify proteins that modify Aβ‐ or tau‐induced neurodegeneration. We then focus on dSMOC1 using Drosophila genetics and cell biological approaches to determine its role in the brain. Finally, we use Mass Spectrometry to identify protein changes in the brains of dSMOC1‐/‐ flies.ResultsOur screening assay identified 20 genes from M42 that modify tau toxicity and 5 for Aβ, including dSMOC1 and components of Wnt and TGF‐β signaling pathways. We find dSMOC1‐/‐ null flies suffer severely decreased survival and climbing defects upon aging. In the brain, dSMOC1 expression occurs primarily in glial cells while protein localizes around neuronal cell bodies, consistent with its role as a matrisomal protein. We show alteration of glypican levels in dSMOC1‐/‐ brains. Glypicans modulate Wnt and TGF‐β signaling further supporting a role connecting M42 in AD biology. Finally, we used mass spectrometry to determine protein changes in brains of dSMOC1‐/‐ flies and found perturbations in ECM/receptor interactions, proteostasis, KREBs/TCA cycle, and oxidative phosphorylation. Additional data suggests an age dependent shift from oxidative phosphorylation to glycolysis may compensate for reduced ATP levels in dSMOC1‐/‐ flies.ConclusionThe M42 protein module contains multiple proteins with links to AD. Multiple M42 proteins interact with specific AD triggers including SMOC1, wnt and TGF‐β signaling components. The genetics, proteomics, and cell biological data combine to support a mechanistic hypothesis where changes in SMOC1 levels disrupt critical signaling pathways leading to disruptions in metabolism affecting neuronal function.
Single‐Microglia Transcriptomic Transition Network‐based Prediction and Real‐world Patient Data Validation Identifies Ketorolac as a Repurposable Drug for Alzheimer’s Disease
Authors: Xu Jielin , Danziger Michael , Xu Zhenxing , Zhang Chengxi , Zhou Yadi , Hou Yuan , Karavani Ehud , Shimoni Yishai , Pieper Andrew A. , Leverenz James B , Cummings Jeffrey L. , Hu Jianying , Wang Fei , Rosen‐Zvi Michal , Cheng Feixiong 
Published: January 2025

AbstractBackgroundMicroglia have been implicated as a key aspect of the pathology of Alzheimer’s disease (AD). However, high microglial heterogeneities, including disease‐associated microglia (DAM), tau microglia (tau‐pathology related), and neuroinflammation‐like microglia (NIM), hinder the development of microglia‐targeted treatment.MethodIn this study, we integrated ∼0.7 million single‐nuclei RNA (snRNA)‐seq transcriptomes derived from AD patient frozen brain samples using a variational autoencoder. We used trajectory analysis to identify microglial subtypes across AD progression, including DAM, tau microglia, and NIM. We conducted transition network analysis to identify putative molecular drivers of microglial subtypes across varying severities of AD and disease progression under the human protein‐protein interactome network. We prioritized candidate drugs by specifically targeting transition modules using drug‐gene signature enrichment analysis and we further validated drugs using two independent real‐world patient databases (MarketScan [172 million insured individuals] and INSIGHT Clinical Research Network [15 million patients]).ResultWe showed that tau microglia were significantly associated with synaptic processes. Compared to DAM, upregulated genes of NIM were significantly enriched with key immune pathways (e.g., toll‐like receptor). We identified potential AD pathobiological regulators (e.g., SYK, CTSB, PRKCA, INPP5D, and ADAM10) in transition networks between DAM and NIM. Via network‐based drug repurposing prediction by specifically targeting NIM subpopulations and real‐world patient data‐based validation, we identified that usage of ketorolac (anti‐inflammatory medicine) is significantly associated with reduced AD incidence in both MarketScan (hazard ratio [HR] = 0.81, 95% confidence interval [CI] 0.69‐0.91, p‐value = 0.002 after adjusting > 400 covariates) and INSIGHT (HR = 0.83, 95% CI 0.77‐0.92, p‐value = 0.004 after adjusting 267 covariates) patient databases.ConclusionThis study offers insights into pathobiology of AD‐relevant microglial subtypes and identifies ketorolac as a potential anti‐inflammatory treatment for AD.
Investigating the neural ensembles underlying sundowning in an Alzheimer’s disease mouse model
Authors: Jin Michelle , Hunsberger Holly C , Whye Alicia R , Ogundare Simon , Alvarado Nicole , Sorid Sophia , Lanio Marcos , Denny Christine Ann 
Published: January 2025

AbstractBackgroundAs high as 50% of Alzheimer’s disease (AD) patients experience “sundowning”, which refers to an increased severity of neuropsychiatric symptoms (NPS), including agitation, confusion, and anxiety, selectively in the evening. Although sundowning significantly influences the decision to institutionalize patients, few preclinical models of this phenomenon exist and the underlying neural mechanisms are unknown. Here, we establish a model of sundowning by phenotyping the sleep‐wake cycle and anxiety and exploratory behavior at different times of day in an AD mouse model. We then investigate differences in brain‐wide activity patterns present at sundown and sunrise time in AD and control (Ctrl) mice.MethodWe recorded sleep‐wake activity in control (Ctrl) and APP/PS1de9 (AD) mice across 2‐, 6‐, 12‐, and 24‐month‐old male and female mice. Next, we measured anxiety/locomotion in 2‐, 12‐, and 24‐month‐old Ctrl and AD mice during the murine evening (ZT22‐0, sundown) and murine morning (ZT12‐14, sunrise) using the elevated‐plus maze (EPM) and open field (OF) assays. To identify brain‐wide ensemble patterns mediating sundowning, we bred the ArcCreERT2 x EYFP activity‐dependent tagging strategy with the AD line, which allows for temporally precise labelling of two active neural populations. We then applied a custom pipeline to label and map ensembles active during exposure to the EPM at sundown and sunrise.ResultWe found a degradation in strength of sleep‐wake rhythms with aging selectively in AD mice. We further found that older AD mice (24‐month‐old males and 12‐ and 24‐month‐old females) preferentially explore the open arms of the EPM and display hyperlocomotion in the OF (24‐month‐old males and 24‐month‐old females) selectively during sundown. Network analysis of mapping results showed selective decreases in topological measures of connectivity, such as degree, clustering, and efficiency, in AD mice at sundown but not sunrise time when compared with Ctrl mice.ConclusionWe identified a striking behavioral abnormality in an AD mouse model resembling “nighttime wandering” and agitation seen in sundowning patients. Mapping of concurrent brain‐wide activity patterns showed global decreases in network connectivity at sundown time in contrast to sunrise time in AD mice, revealing novel insights about the neural patterns underlying this debilitating syndrome.
Neurocognitive Sequelae of COVID‐19 in Older African American Adults
Authors: Walker Tiffany A , Elchommali Jannah , Han Jenny E , Truong Alexander , Hajjar Ihab , Goldstein Felicia 
Published: January 2025

AbstractBackgroundAfrican Americans (AA) are disproportionately affected by Long COVID, highlighting the need for targeted research to understand the enduring consequences of COVID‐19 within this community. Among the array of symptoms associated with post‐acute sequelae of SARS‐CoV‐2 (PASC), cognitive impairments emerge as a significant concern affecting up to 19% of COVID survivors. In this study, our goal is to comprehensively characterize the specific cognitive domains impacted in older AA adults.MethodThis prospective, cohort study collected sociodemographic data and conducted a telephone‐based neurocognitive battery on AA adults aged ≥ 50 years with persistent symptoms ≥ 12 months following confirmed SARS‐CoV‐2 infection, measuring cognitive domains of global function (Blind Montreal Cognitive Assessment (MoCA)), attention (Blind MoCA Attention subscale, Number Span Forward), memory (Hopkins Verbal Learning Test (HVLT), Craft Story 21)), and executive function (Number Span Backward). Z‐scores were calculated based on the means and SDs of demographically comparable normative samples. Impaired performance was defined as z scores > ‐1.5.ResultWe enrolled 75 AAs with a median age of 58 years (range 51‐73); 65 (86%) were female, and 69 (92%) had a medium‐high social vulnerability index. Forty (53%) participants exhibited global impairment on Blind MOCA. 54 (72%) had impairment on ≥ 1 attention test, including 53 (70%) with impaired MoCA Attention subscale scores and 5 (6%) with impaired Number Span Forward testing. Fifty‐three (70%) had impairment on ≥ 1 memory test, including 42‐48% with impaired HVLT and 45‐48% with impaired Craft Story 21. Four (5%) had impaired executive function on Number Span Backwards testing.ConclusionWe demonstrate persistent COVID‐19 cognitive impairments impacting memory, attention, executive function, and global function within a socioeconomically disadvantaged older AA adult population. Limited access to healthcare resources in medically underserved areas can lead to delayed or inadequate COVID‐19 treatment, potentially increasing the risk of neurological complications and cognitive deficits in African American populations.
Mutations in Tau’s Proline Rich Domain Affect its Protein Interactions
Authors: Koutures Anne , Katz Brittany , Hwang Kaylin , Cohn Whitaker , Addo‐Osafo Kwaku , Vossel Keith 
Published: January 2025

AbstractBackgroundEpileptic activity is increasingly recognized as a contributor to Alzheimer’s Disease (AD) pathology. In AD models, endogenous tau contributes to epileptic activity and associated cognitive deficits through mechanisms that are not fully understood. Increased attention is being directed towards tau’s interactions with proteins that regulate neuronal activity, particularly tau’s proline rich domain and its binding to SH3‐containing proteins. However, the impact of mutations in tau’s proline‐rich region on other protein interactions remains unclear.MethodWe assessed mutations in tau’s proline rich domain in two mouse lines: AxxA6 (P‐to‐A substitutions in 6th PxxP motif in tau) and R221A (R‐to‐A substitution at amino acid corresponding to 221 in human 2N4R tau). These mutations block tau’s interactions with SH3‐containing proteins, including PLCγ1 and p85α/PI3K. Co‐immunoprecipitation (Co‐IP) of tau from cortical brain tissue was confirmed and analyzed by mass spectrometry. We compared protein abundance ratios to wild type tau mice within each mouse line. Significant (p<.05) tau‐baited protein interactions were further explored within literature and the String Database.ResultThe R221A line produced 143 and 120 significant proteins within the heterozygous and homozygous groups, respectively. Many identified proteins are strongly associated with processes such as microtubule organization, postsynaptic structure, and mitochondrial functions. The AxxA6 line produced 158 and 126 significant proteins within the heterozygous and homozygous groups, respectively. Many identified proteins are involved in cellular trafficking and are strongly associated with processes such as glutamate catabolic processes and microtubule protein localization. Notably, many proteins identified in both lines are involved in prion disease and vascular endothelial growth factor (VEGF) signaling pathways.ConclusionCo‐IP mass spectrometry of the R221A and AxxA6 mouse lines revealed that mutations in tau’s proline rich domain to affect tau’s interactions with multiple proteins. Of the significant proteins, multiple are related to microtubule, metabolic, synaptic, and mitochondrial activity, and many are found within prion disease pathways and VEGF signaling pathways. Interestingly, PLCγ1 and p85α/PI3K, are also implicated in VEGF signaling pathways. These findings highlight the importance of further investigating the possible relationships between noted cellular processes and biological pathways and tau‐protein interactions in familial AD.
Bi‐phasic Microtubule Defects in Tauopathy: Treatment Implications
Authors: Sun Xiaohuan , Baas Peter W , Karch Celeste M. , Qiang Liang 
Published: January 2025

AbstractBackgroundIn tauopathies, such as Frontotemporal Dementia (FTD), tau loses association with microtubules (MTs) and forms neurofibrillary tangles. Tau is an abundant MT‐associated protein in neurons, which essentially regulate MT properties. Because pathological tau binds less avidly to MTs, which was thought to reduce the levels and stability of axonal MTs. However, this idea is based on the dogma of functional tau as a MT stabilizer, which was challenged by some recent studies via tau‐knockdown strategies. The situation is further confounded in tauopathies because the pathological tau may elicit certain gain‐of‐toxicities on axonal MTs.MethodTo investigate this matter in a more disease‐relevant scenario, we used 1) cerebral organoids generated from an FTD‐patient derived induced pluripotent stem cells bearing a tau mutation (P301S/P301L/R406W) and their isogenic control corrected by CRISPR‐Cas9; and 2) postmortem brain tissues from a cohort of FTD patients, as our models.ResultElevated soluble tau was identified in tauP301S organoids during the early development with an increased ratio of mature/immature isoforms (4R‐tau/3R‐tau); whereas an overt reduction in soluble tau was identified in late‐stage developed organoids and postmortem FTD brains accompanied by increased aberrant PTM‐modifications of tau. Strikingly, MAP6, a bona fide MT stabilizer that competes with tau’s effects on MTs, presented opposite changes in its levels in tauP301S/R406W organoids at the early‐ and late‐developed stages also in the postmortem brain model as the late‐developed stage of disease. Such bi‐phasic changes in tau and MAP6 were consistently reflected by the predicted changes in MT dynamics. Interestingly, certain neurodegenerative features recapitulated in tauP301S organoids were ameliorated by novel corrective strategies such as tau antisense oligonucleotides in the early stage of disease.ConclusionWe conclude that the biphasic changes in tau pathology with the subsequent MT defects may underlie the progressive neurodegeneration in tauopathy. Thus, therapies to correct tau and MT abnormalities in tauopathy must be vetted for the specific stages of the disease
Unraveling the interplay between tau seeding and autophagy processes
Authors: Deckert Annika , Böddrich Annett , Diez Lisa , Schmitt Matthias Jürgen , Nevado Juan Carlos Company , Beetz Stephanie , Brusendorf Lydia , Serresi Michela , Wegmann Susanne , Gargiulo Gaetano , Wanker Erich 
Published: January 2025

AbstractBackgroundThe microtubule‐associated protein tau is the most commonly misfolded protein in neurodegenerative disorders including Alzheimer’s disease and other related tauopathies. These neurological illnesses are hypothesized to share a common mechanism of disease progression, where pathogenic aggregates or ‘seeds’ of the tau protein function as templates promoting misfolding of functional, soluble tau protein. Under this premise, therapeutic strategies that modulate the seeding cascade, have high potential to interfere with the disease process.MethodWhile increasing evidence is emerging that tau pathology progression is based on seeding and spreading mechanisms reminiscent of prion protein pathology, an in‐depth understanding of the cellular pathways and cofactors that drive disease progression is, however, still lacking. In order to identify tau seeding modulators, a previously described HEK293T biosensor cell line1 was applied, able to sensitively detect tau seeding. To understand the self‐propagation process, I exploited this cell model to performed a pooled genome‐wide loss‐of‐function CRISPR screen2, allowing the identification of proteins that robustly influence tau seeding.ResultAmongst the top hits were many genes involved in autophagy and specifically autophagosome formation. Building on these insights, I am working towards a mechanistic understanding how the loss of function of the ATG genes impacts tau seeding in mammalian cells and in a Drosophila melanogaster model.ConclusionTogether, my in vitro and in vivo studies are starting to unravel the molecular details of the interplay between tau seeding and autophagy. These studies have the ability to reveal novel strategies to reduce the toxicity of tau aggregates by stimulating the activity of the autophagic machinery. Research approaches addressing tau in general, and tau seeding more specifically, have enormous potential to provide highly innovative, disease‐modifying first‐in‐class therapeutics for AD.References1) Holmes BB et al. (2014) “Proteopathic tau seeding predicts tauopathy in vivo. Proc Natl Acad Sci USA. 111: E4376‐E43852) Doench JG et al. (2016) “Optimized sgRNA design to maximise activity and minimise off‐target effects of CRISPR‐Cas9.” Nat. Biotechnol. 34: 184‐191
Neuronal hypofunction and network dysfunction in a mouse model at early stage of tauopathy
Authors: Ji Changyi , Yang Xiaofeng , Lin Yan , Eleish Mohamed , Sigurdsson Einar M. 
Published: January 2025

AbstractBackgroundAbnormal neuronal activity was observed in awake and behaving tauopathy mice using two‐photon calcium imaging. Our previous study has revealed the relationship between tau pathology and altered neuronal calcium dynamics within the motor cortex of JNPL3 tauopathy mice at different stages of disease progression, specifically at 6 and 12 months of age (Wu Q et al, Neurobiol. Dis. 2021; Ji C et al, Alzheimers Dement 19, e074196; Ji C et al, Alzheimers Dement 18, e069415). However, network activity in tauopathy models remains less studied. Furthermore, the mechanisms responsible for the altered neuronal and network activity warrant further investigation.MethodsSomatic calcium activity in the motor cortex of 6‐month‐old homozygous JNPL3 mice and age‐matched wild‐type controls was imaged using two‐photon microscopy, when the animals were resting versus running. Neuronal Ca2+ activity profiles and synchrony were analyzed. To explore the mechanisms underlying the altered neuronal and network activity, neuronal excitability and synaptic transmission were assessed by electrophysiological recordings in acute brain slices.ResultsWe observed neuronal hypoactivity in the motor cortex of 6‐month‐old JNPL3 mice, when the animals were at rest or running on a treadmill. Neuronal Ca2+ activity exhibited enhanced synchrony and dysregulated responses to the running stimulus in JNPL3 mice. Furthermore, electrophysiological recordings in these motor cortical neurons of acute brain slices revealed a reduction in spontaneous excitatory synaptic transmission in pyramidal neurons and enhanced excitability of inhibitory neurons. These findings are likely linked to hypofunctional neurons and altered network activity in JNPL3 tauopathy mice.ConclusionIn the JNPL3 tauopathy mouse model, a reduction in neuronal Ca2+ activity was observed in the motor cortex of awake and behaving animals during the early stage of tauopathy. This neuronal deficit was more pronounced under running conditions. The presence of tau pathology affected the local neuronal circuitry, as evidenced by an increased basal Ca2+ activity synchrony and altered profiles of running‐related neuronal responses in the motor cortex. Underlying mechanisms may be linked to impairments in excitatory synaptic transmission and altered excitatory/inhibitory balance in this region, resulting from the accumulation of pathological tau.