Aging Human Brain Research Articles

Linking Cognitive Integrity to Working Memory Dynamics in the Aging Human Brain.

Aging is accompanied by a decline of working memory, an important cognitive capacity that involves stimulus-selective neural activity that persists after stimulus presentation. Here, we unraveled working memory dynamics in older human adults (male and female) including those diagnosed with mild cognitive impairment (MCI) using a combination of behavioral modeling, neuropsychological assessment, and MEG recordings of brain activity. Younger adults (male and female) were studied with behavioral modeling only. Participants performed a visuospatial delayed match-to-sample task under systematic manipulation of the delay and distance between sample and test stimuli. Their behavior (match/nonmatch decisions) was fit with a computational model permitting the dissociation of noise in the internal operations underlying the working memory performance from a strategic decision threshold. Task accuracy decreased with delay duration and sample/test proximity. When sample/test distances were small, older adults committed more false alarms than younger adults. The computational model explained the participants' behavior well. The model parameters reflecting internal noise (not decision threshold) correlated with the precision of stimulus-selective cortical activity measured with MEG during the delay interval. The model uncovered an increase specifically in working memory noise in older compared with younger participants. Furthermore, in the MCI group, but not in the older healthy controls, internal noise correlated with the participants' clinically assessed cognitive integrity. Our results are consistent with the idea that the stability of working memory contents deteriorates in aging, in a manner that is specifically linked to the overall cognitive integrity of individuals diagnosed with MCI.

A ResNet mini architecture for brain age prediction.

The brain presents age-related structural and functional changes in the human life, with different extends between subjects and groups. Brain age prediction can be used to evaluate the development and aging of human brain, as well as providing valuable information for neurodevelopment and disease diagnosis. Many contributions have been made for this purpose, resorting to different machine learning methods. To solve this task and reduce memory resource consumption, we develop a mini architecture of only 10 layers by modifying the deep residual neural network (ResNet), named ResNet mini architecture. To support the ResNet mini architecture in brain age prediction, the brain age dataset (OpenNeuro #ds000228) that consists of 155 study participants(three classes) and the Alzheimer MRI preprocessed dataset that consists of 6400 images (four classes) are employed. We compared the performance of the ResNet mini architecture with other popular networks using the two considered datasets. Experimental results show that the proposed architecture exhibits generality and robustness with high accuracy and less parameter number.

Region-specific and age-related differences in astrocytes in the human brain

Astrocyte heterogeneity and its relation to aging in the normal human brain remain poorly understood. We here analyzed astrocytes in gray and white matter brain tissues obtained from donors ranging in age between the neonatal period to over 100 years. We show that astrocytes are differently distributed with higher density in the white matter. This regional difference in cellular density becomes less prominent with age. Additionally, we confirm the presence of morphologically distinct astrocytes, with gray matter astrocytes being morphologically more complex. Notably, gray matter astrocytes morphologically change with age, while white matter astrocytes remain relatively consistent in morphology. Using regional mass spectrometry-based proteomics, we did, however, identify astrocyte specific proteins with regional differences in abundance, reflecting variation in cellular density or expression level. Importantly, the expression of some astrocyte specific proteins region-dependently decreases with age. Taken together, we provide insights into region- and age-related differences in astrocytes in the human brain.

Specific exercise patterns generate an epigenetic molecular memory window that drives long-term memory formation and identifies ACVR1C as a bidirectional regulator of memory in mice

Exercise has beneficial effects on cognition throughout the lifespan. Here, we demonstrate that specific exercise patterns transform insufficient, subthreshold training into long-term memory in mice. Our findings reveal a potential molecular memory window such that subthreshold training within this window enables long-term memory formation. We performed RNA-seq on dorsal hippocampus and identify genes whose expression correlate with conditions in which exercise enables long-term memory formation. Among these genes we found Acvr1c, a member of the TGF ß family. We find that exercise, in any amount, alleviates epigenetic repression at the Acvr1c promoter during consolidation. Additionally, we find that ACVR1C can bidirectionally regulate synaptic plasticity and long-term memory in mice. Furthermore, Acvr1c expression is impaired in the aging human and mouse brain, as well as in the 5xFAD mouse model, and over-expression of Acvr1c enables learning and facilitates plasticity in mice. These data suggest that promoting ACVR1C may protect against cognitive impairment.

Single-cell multiplex chromatin and RNA interactions in ageing human brain

Dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA1–3. Chromatin complex compositions change during cellular differentiation and ageing, and are expected to be highly heterogeneous among terminally differentiated single cells4–7. Here we introduce the multinucleic acid interaction mapping in single cells (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression and RNA–chromatin associations within individual nuclei. When applied to 14 human frontal cortex samples from older donors, MUSIC delineated diverse cortical cell types and states. We observed that nuclei exhibiting fewer short-range chromatin interactions were correlated with both an ‘older’ transcriptomic signature and Alzheimer’s disease pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci and a promoter tends to be that in which these cis expression quantitative trait loci specifically affect the expression of their target gene. In addition, female cortical cells exhibit highly heterogeneous interactions between XIST non-coding RNA and chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploration of chromatin architecture and transcription at cellular resolution in complex tissues.

The genetic architecture of multimodal human brain age

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10−8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine.

Thermodynamic Analysis to Evaluate the Effect of Diet on Brain Glucose Metabolism: The Case of Fish Oil.

Inefficient glucose metabolism and decreased ATP production in the brain are linked to ageing, cognitive decline, and neurodegenerative diseases (NDDs). This study employed thermodynamic analysis to assess the effect of fish oil supplementation on glucose metabolism in ageing brains. Data from previous studies on glucose metabolism in the aged human brain and grey mouse lemur brains were examined. The results demonstrated that Omega-3 fish oil supplementation in grey mouse lemurs increased entropy generation and decreased Gibbs free energy across all brain regions. Specifically, there was a 47.4% increase in entropy generation and a 47.4 decrease in Gibbs free energy in the whole brain, indicating improved metabolic efficiency. In the human model, looking at the specific brain regions, supplementation with Omega-3 polyunsaturated fatty acids (n-3 PUFAs) reduced the entropy generation difference between elderly and young individuals in the cerebellum and particular parts of the brain cortex, namely the anterior cingulate and occipital lobe, with 100%, 14.29%, and 20% reductions, respectively. The Gibbs free energy difference was reduced only in the anterior cingulate by 60.64%. This research underscores that the application of thermodynamics is a comparable and powerful tool in comprehending the dynamics and metabolic intricacies within the brain.

Caloric Restriction and Intermittent Fasting: possible strategies for delaying brain aging in humans and animals

Calorie restriction (CR) is the strategy that hasdemonstrated a significant impact on slowing thebiological rate of aging and increasing both averageand maximum longevity in a variety of animals. Adiet plan known as intermittent fasting (IF) calls foreating habits that involve prolonged periods of lowor no-calorie intake. The morphology, architecture,vasculature, and cognition of the brain are known tochange as the organism ages. Oxidative stressplays a crucial role in the aging of the brain. Theeffects of oxidative stress include mitochondrialdysfunction, protein modification, membrane lipidperoxidation, nuclear DNA oxidation, and mitochondrial and mitochondrial DNA oxidation.These effects hasten brain aging, neuronal loss, andcognitive impairment. Cognitive ability, long-termmemory, and dementia are improved by CR andIF, which are beneficial for brain andneurodegenerative illnesses. The presented reviewarticle explores recent findings on how two dietaryapproaches, CR and IF, can support healthy agingand improve brain function. We will also explorehow the most studied CR mimetics affect aging andhow they might be used as treatments to promoteneuroprotection.

SARS-CoV-2 Omicron Variants Show Attenuated Neurovirulence Compared with the Wild-Type Strain in Elderly Human Brain Spheroids.

Infection with severe acute respiratory syndrome coronavirus 2 Omicron variants still causes neurological complications in elderly individuals. However, whether and how aging brains are affected by Omicron variants in terms of neuroinvasiveness and neurovirulence are unknown. Here, we utilize resected paracarcinoma brain tissue from elderly individuals to generate primary brain spheroids (BSs) for investigating the replication capability of live wild-type (WT) strain and Omicron (BA.1/BA.2), as well as the mechanisms underlying their neurobiological effects. We find that both WT and Omicron BA.1/BA.2 are able to enter BSs but weakly replicate. There is no difference between Omicron BA.1/BA.2 and WT strains in neurotropism in aging BSs. However, Omicron BA.1/BA.2 exhibits ameliorating neurological damage. Transcriptional profiling indicates that Omicron BA.1/BA.2 induces a lower neuroinflammatory response than WT strain in elderly BSs, suggesting a mechanistic explanation for their attenuated neuropathogenicity. Moreover, we find that both Omicron BA.1/BA.2 and WT strain infections disrupt neural network activity associated with neurodegenerative disorders by causing neuron degeneration and amyloid-β deposition in elderly BSs. These results uncover Omicron-specific mechanisms and cellular immune responses associated with severe acute respiratory syndrome coronavirus 2-induced neurological complications.

The Impact of Aging on Neurological Function and Cognitive Decline

This comprehensive analysis delves into the multifaceted impact of aging on neurological function and cognitive decline, incorporating insights from studies on music, video games, and mindfulness. It explores significant alterations in the peripheral nervous system (PNS) as individuals age, highlighting changes in nerve fibers, signal transmission, muscle strength, and sensory discrimination. The study also examines the brain's structural and functional evolution with age, particularly in the hippocampus and frontal lobe, and the resultant effects on cognitive abilities. It discusses the concept of brain resistance and resilience in the context of Alzheimer's disease, suggesting that certain individuals show a heightened ability to withstand or adapt to neurological pathologies. Investigating various lifestyle factors, the hypothesis presented is that an active lifestyle and specific activities, including musical engagement and video game training, can mitigate age-related cognitive decline. The study finds that musical activities improve mood, memory, and quality of life in people with dementia, while customized video games enhance multitasking abilities and cognitive control in older adults. However, mindfulness-based interventions, such as stress reduction and exercise, did not show significant improvement in cognitive functions in older adults. Intriguingly, cognitive abilities are impacted differently by age, with certain functions like vocabulary improving, while others such as memory and processing speed decline. The study also contrasts brain aging in humans with chimpanzees, revealing significant differences in brain structure changes over the lifespan, likely due to longer human lifespans. This research underscores the complex interplay of genetic, lifestyle, health, and intervention factors in aging and emphasizes the importance of tailored interventions such as using music therapy, video games, and life style changes to preserve neurological and cognitive health in older adults.

Oligodendrocytes and Oligodendrocyte Precursor Cells (OPCs) in aged human brain. A Neuropathology study.

AbstractBackgroundCerebral Small Vessel Disease (CSVD) represents a variety of pathological processes affecting the cerebrovascular system. We tested whether the populations of oligodendrocytes (OLs) and oligodendrocyte precursor cells (OPCs), associate with ageing and with CSVD.MethodWe examined deep subcortical white matter of individuals aged 78.5 (18.3) (mean (SD); range 20‐97, n = 24 (no information were given for 2 of them, only ‘young’)) with and without CSVD. All had minimal AD pathology (Braak stage II or less). Immunohistochemistry was performed, using the markers NogoA (specific for mature OLs), CD140A (for OPCs) and Sox10 (both OPCs and OLs) followed by digital image analysis.ResultAll samples had a substantial density of small, parenchymal cells with robust expression of each marker (NogoA, CD140A, Sox10). The density of NogoA‐positive cells was correlated with age (rs = 0.619, p = 0.011). There was a lower density of CD140A‐positive cells in individuals aged &gt;70 with CVSD compared to those without CVSD (p = 0.016).ConclusionOur results indicate that there may be changes in OL and OPC density with age, and in CSVD.

Effect of calcineurin/NFAT inhibitors on biomarkers and cognition in a canine model of Alzheimer disease

AbstractBackgroundCalcineurin/NFAT signaling increases in Alzheimer disease (AD) and is associated with neurodegeneration, neuroinflammation, amyloid‐β (Aβ) production, and cognitive decline. Hence, calcineurin/NFAT inhibitors (e.g., tacrolimus and Q134R) are attractive potential therapeutics to improve/prevent AD‐associated cognitive impairments. In AD mouse models, both tacrolimus and Q134R improved cognition and ameliorated neuroinflammation and synapse dysfunction.We hypothesized that 1) chronic low‐dose administration of tacrolimus and Q134R will delay cognitive decline over time in middle‐aged beagles, a model of human brain aging and AD; and 2) canine plasma and CSF biomarkers will be improved with treatment.MethodsCognitive outcomes were evaluated in 37 middle‐aged beagles at baseline and during follow‐up (years 1‐3) by assessing spatial learning [landmark‐discrimination (1, 2 and 4cm)], visual discrimination learning, reversal learning (executive function), and spatial working memory (20‐, 70‐, and 110‐second delays). Dogs were ranked for cognition at baseline and randomized into treatment groups: Control (n = 12; placebo), Q134R (n = 12; 8mg/day), and tacrolimus (n = 13; 0.075mg/kg/day). Concentrations of Aβ40, Aβ42, and NfL in plasma and CSF were measured using the Quanterix SIMOA.ResultsAccuracy at all landmark‐discrimination distances declined significantly among controls 20% faster than tacrolimus, and 15% faster than Q134R dogs, at the most difficult distance of 4cm. Accuracy on spatial working memory task declined 21% faster/year among controls than tacrolimus (years 2&amp;3); and 18% faster than Q134R dogs (year 1). Performance on visual discrimination and reversal tasks declined with age but there was no treatment effect.Biomarkers in plasma tended to increase over time with no significant differences between treatment groups. In CSF, relative decreases in Aβ40 and Aβ42 in tacrolimus (2.9 and 2, respectively) and Q134R (5.4 and 3.7, respectively) were less than in control dogs. Finally, relative increases of NfL in tacrolimus and Q134R were less than in control dogs (2.3 and 3.7, respectively).ConclusionBoth tacrolimus and Q134R showed beneficial preventative effects on age‐related decline in spatial functions and memory but not on associative learning nor executive function in a canine model of AD. Finally, only CSF biomarkers tended to improve relative to treatment and are suggestive of less Aβ deposition in brain and higher clearance.

Association of human brain‐age with genetically predicted plasma levels of brain rejuvenating and aging factors identified in mice

AbstractBackgroundAging is the primary risk factor for Alzheimer’s disease. Experiments in mice have identified circulating proteins with an “aging/rejuvenating” effect on the brain. However, whether these proteins have an effect on the human brain remains unknown. Here, we leverage genetic data to study links between the predicted plasma levels of these proteins and human brain age.MethodsThis study includes 1,394 cognitively unimpaired individuals of the ALFA study. Plasma proteins with an effect on mice brain aging were identified through a systematic review [Figure 1]. Summary statistics data of protein quantitative trait loci (pQTLs) associated to these proteins in human (inclusion threshold&lt;5×10−5) were acquired from a previous study (Pietzner et al.,2021), and used for computing protein genetic scores (pPRS). For each ALFA cohort participant, DeltaAge scores was calculated by subtracting chronological age from MRI‐based estimation of brain age (Cumplido et al.,2022). Positive values are interpreted as brain age older than chronological age, and viceversa. The associations between brain DeltaAge measurements and pPRSs were assessed through general linear regression models stratified by sex, amyloid‐β (Aβ) status (CSF‐Aβ42/40&lt;0.071 [Milà‐Alomà et al.,2020]) and APOE‐ε4 carriership. Results were reported for nominal and group‐correction (two experimental aging groups) level of significance (p&lt;0.05, p&lt;0.025, respectively). All pQTLs included in the significant pPRS were functionally annotated and an enrichment analysis was performed.ResultsGenetically predicted plasma levels of CSF2, VCAM1, HP, GHRH and BGLAP were associated with negative values of brain DeltaAge, while KLOTHO with positive values. Results for GHRH (Aβ+ and APOE‐ε4 non‐carriers) and BGLAP (APOE‐ε4 carriers) remained significant after p‐value correction, with an effect in agreement with their brain rejuvenation role as found in mice [Figure 2]. Enrichment analysis found immune response and complement activation processes associated with negative values of DeltaAge [Figure 3].ConclusionsThese results show that plasma levels of the brain aging/rejuvenating proteins discovered in mice may also influence human brain aging. In particular, genetically predicted levels of two rejuvenating factors in mice (BGLAP and GHRH) were associated with a younger brain age than chronological age. Follow‐up analyses will include protein level measurements to unravel the molecular complexity of brain aging.

Shifting from ependyma to choroid plexus epithelium and the changing expressions of aquaporin-1 and aquaporin-4.

The cells of the choroid plexus (CP) epithelium are specialized ependymal cells (ECs) but have distinct properties. The CP cells and ECs form single-cell sheets contiguous to each other at a transitional zone. The CP is underlined by a basal lamina and has barrier properties, whereas the ECs do not. The basal lamina of the CP is continuous with the glia limitans superficialis and, consequently, the CP stroma is continuous with the meninges along entering blood vessels. The CP has previously been reported to express aquaporin-1 (AQP1) mostly apically, and ECs show mostly basolateral aquaporin-4 (AQP4) expression. Recent evidence in various systems has shown that in changing conditions the expression and distribution of AQP4 can be modified, involving phosphorylation and calmodulin-triggered translocation. Studies on the human CP revealed that AQP4 is also expressed in some CP cells, which is likely to be increased during ageing based on mouse data. Moreover, subependymal astrocytic processes in the ependyma-CP transition, forming a glial plate around blood vessels and facing the CP stroma, were strongly positive for AQP4. We propose that the increased AQP4 expression might be a compensatory mechanism for the observed reduction in CSF production in the ageing human brain. The high AQP4 density in the transition zone might facilitate the transport of water into and out of the CP stroma and serve as a drainage and clearing pathway for metabolites in the CNS.

Senolytic therapy alleviates physiological human brain aging and COVID-19 neuropathology

Aging is a major risk factor for neurodegenerative diseases, and coronavirus disease 2019 (COVID-19) is linked to severe neurological manifestations. Senescent cells contribute to brain aging, but the impact of virus-induced senescence on neuropathologies is unknown. Here we show that senescent cells accumulate in aged human brain organoids and that senolytics reduce age-related inflammation and rejuvenate transcriptomic aging clocks. In postmortem brains of patients with severe COVID-19 we observed increased senescent cell accumulation compared with age-matched controls. Exposure of human brain organoids to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induced cellular senescence, and transcriptomic analysis revealed a unique SARS-CoV-2 inflammatory signature. Senolytic treatment of infected brain organoids blocked viral replication and prevented senescence in distinct neuronal populations. In human-ACE2-overexpressing mice, senolytics improved COVID-19 clinical outcomes, promoted dopaminergic neuron survival and alleviated viral and proinflammatory gene expression. Collectively our results demonstrate an important role for cellular senescence in driving brain aging and SARS-CoV-2-induced neuropathology, and a therapeutic benefit of senolytic treatments.

ADAR1 suppression causes interferon signaling and transposable element transcript accumulation in human astrocytes.

Neuroinflammation is a central mechanism of brain aging and Alzheimer's disease (AD), but the exact causes of age- and AD-related neuroinflammation are incompletely understood. One potential modulator of neuroinflammation is the enzyme adenosine deaminase acting on RNA 1 (ADAR1), which regulates the accumulation of endogenous double-stranded RNA (dsRNA), a pro-inflammatory/innate immune activator. However, the role of ADAR1 and its transcriptomic targets in astrocytes, key mediators of neuroinflammation, have not been comprehensively investigated. Here, we knock down ADAR1 in primary human astrocytes via siRNA transfection and use transcriptomics (RNA-seq) to show that this results in: (1) increased expression of type I interferon and pro-inflammatory signaling pathways and (2) an accumulation of transposable element (TE) transcripts with the potential to form dsRNA. We also show that our findings may be clinically relevant, as ADAR1 gene expression declines with brain aging and AD in humans, and this is associated with a similar increase in TE transcripts. Together, our results suggest an important role for ADAR1 in preventing pro-inflammatory activation of astrocytes in response to endogenous dsRNA with aging and AD.

Unbiased classification of the elderly human brain proteome resolves distinct clinical and pathophysiological subtypes of cognitive impairment

Cognitive impairment in the elderly features complex molecular pathophysiology extending beyond the hallmark pathologies of traditional disease classification. Molecular subtyping using large-scale -omic strategies can help resolve this biological heterogeneity. Using quantitative mass spectrometry, we measured ∼8000 proteins across >600 dorsolateral prefrontal cortex tissues with clinical diagnoses of no cognitive impairment (NCI), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia. Unbiased classification of MCI and AD cases based on individual proteomic profiles resolved three classes with expression differences across numerous cell types and biological ontologies. Two classes displayed molecular signatures atypical of AD neurodegeneration, such as elevated synaptic and decreased inflammatory markers. In one class, these atypical proteomic features were associated with clinical and pathological hallmarks of cognitive resilience. We were able to replicate these classes and their clinicopathological phenotypes across two additional tissue cohorts. These results promise to better define the molecular heterogeneity of cognitive impairment and meaningfully impact its diagnostic and therapeutic precision.

Tracking cell-type-specific temporal dynamics in human and mouse brains

Progenitor cells are critical in preserving organismal homeostasis, yet their diversity and dynamics in the aged brain remain underexplored. We introduced TrackerSci, a single-cell genomic method that combines newborn cell labeling and combinatorial indexing to characterize the transcriptome and chromatin landscape of proliferating progenitor cells invivo. Using TrackerSci, we investigated the dynamics of newborn cells in mouse brains across various ages and in a mouse model of Alzheimer's disease. Our dataset revealed diverse progenitor cell types in the brain and their epigenetic signatures. We further quantified aging-associated shifts in cell-type-specific proliferation and differentiation and deciphered the associated molecular programs. Extending our study to the progenitor cells in the aged human brain, we identified conserved genetic signatures across species and pinpointed region-specific cellular dynamics, such as the reduced oligodendrogenesis in the cerebellum. We anticipate that TrackerSci will be broadly applicable to unveil cell-type-specific temporal dynamics in diverse systems.

Comprehensive characterization of human brain-derived extracellular vesicles using multiple isolation methods: Implications for diagnostic and therapeutic applications.

Extracellular vesicles (EVs) have emerged as critical mediators of intercellular communication and promising biomarkers and therapeutics in the central nervous system (CNS). Human brain-derived EVs (BDEVs) provide a comprehensive snapshot of physiological changes in the brain's environment, however, the isolation of BDEVs and the comparison of different methods for this purpose have not been fully investigated. In this study, we compared the yield, morphology, subtypes and protein cargo composition of EVs isolated from the temporal cortex of aged human brains using three established separation methods: size-exclusion chromatography (SEC), phosphatidylserine affinity capture (MagE) and sucrose gradient ultracentrifugation (SG-UC). Our results showed that SG-UC method provided the highest yield and collected larger EVs compared to SEC and MagE methods as assessed by transmission electron microscopy and nanoparticle tracking analysis (NTA). Quantitative tandem mass-tag (TMT) mass spectrometry analysis of EV samples from three different isolation methods identified a total of 1158 proteins, with SG-UC showing the best enrichment of common EV proteins with less contamination of non-EV proteins. In addition, SG-UC samples were enriched in proteins associated with ATP activity and CNS maintenance, and were abundant in neuronal and oligodendrocytic molecules. In contrast, MagE samples were more enriched in molecules related to lipoproteins, cell-substrate junction and microglia, whereas SEC samples were highly enriched in molecules related to extracellular matrix, Alzheimer's disease and astrocytes. Finally, we validated the proteomic results by performing single-particle analysis using the super-resolution microscopy and flow cytometry. Overall, our findings demonstrate the differences in yield, size, enrichment of EV cargo molecules and single EV assay by different isolation methods, suggesting that the choice of isolation method will have significant impact on the downstream analysis and protein discovery.

Brain structure and working memory adaptations associated with maturation and aging in mice.

As the population skews toward older age, elucidating mechanisms underlying human brain aging becomes imperative. Structural MRI has facilitated non-invasive investigation of lifespan brain morphology changes, yet this domain remains uncharacterized in rodents despite increasing use as models of disordered human brain aging. Young (2m, n = 10), middle-age (10m, n = 10) and old (22m, n = 9) mice were utilized for maturational (young vs. middle-age) and aging-related (middle-age vs. old mice) comparisons. Regional brain volume was averaged across hemispheres and reduced to 32 brain regions. Pairwise group differences in regional volume were tested using general linear models, with total brain volume as a covariate. Sample-wide associations between regional brain volume and Y-maze performance were assessed using logistic regression, residualized for total brain volume. Both analyses corrected for multiple comparisons. Structural covariance networks were generated using the R package "igraph." Group differences in network centrality (degree), integration (mean distance), and segregation (transitivity, modularity) were tested across network densities (5-40%), using 5,000 (1,000 for degree) permutations with significance criteria of p < 0.05 at ≥5 consecutive density thresholds. Widespread significant maturational changes in volume occurred in 18 brain regions, including considerable loss in isocortex regions and increases in brainstem regions and white matter tracts. The aging-related comparison yielded 6 significant changes in brain volume, including further loss in isocortex regions and increases in white matter tracts. No significant volume changes were observed across either comparison for subcortical regions. Additionally, smaller volume of the anterior cingulate area (χ2 = 2.325, pBH = 0.044) and larger volume of the hippocampal formation (χ2 = -2.180, pBH = 0.044) were associated with poorer cognitive performance. Maturational network comparisons yielded significant degree changes in 9 regions, but no aging-related changes, aligning with network stabilization trends in humans. Maturational decline in modularity occurred (24-29% density), mirroring human trends of decreased segregation in young adulthood, while mean distance and transitivity remained stable. These findings offer a foundational account of age effects on brain volume, structural brain networks, and working memory in mice, informing future work in facilitating translation between rodent models and human brain aging.