Perisynaptic astroglia provide critical molecular and structural support to regulate synaptic transmission and plasticity in the nanodomain of the axon-spine interface. Three-dimensional reconstruction from serial section electron microscopy (3DEM) was used to investigate relationships between perisynaptic astroglia and dendritic spine synapses undergoing plasticity in the adult hippocampus. Delta-burst stimulation (DBS) of the medial perforant pathway induced long-term potentiation (LTP) in the middle molecular layer and concurrent long-term depression (cLTD) in the outer molecular layer of the dentate gyrus in awake male rats. The contralateral hippocampus received baseline stimulation as a within-animal control. Brains were obtained 30 min or 2 h after DBS onset. An automated 3DEM pipeline was developed to enable unbiased quantification of astroglial coverage at the perimeter of the axon-spine interface. Under all conditions, >85% of synapses had perisynaptic astroglia processes within 120 nm of some portion of the perimeter. LTP broadened the distribution of spine sizes while reducing the presence and proximity of perisynaptic astroglia near the axon-spine interface of large spines. In contrast, cLTD transiently reduced the length of the axon-spine interface perimeter without substantially altering astroglial apposition. The postsynaptic density was discovered to be displaced from the center of the axon-spine interface, with this offset increasing during LTP and decreasing during cLTD. Astroglial access to the postsynaptic density was diminished during LTP and enhanced during cLTD, in parallel with changes in spine size. Thus, access of perisynaptic astroglia to synapses is dynamically modulated during LTP and cLTD alongside synaptic remodeling.

Long-term potentiation (LTP) is a widely studied form of synaptic plasticity engaged during learning and memory. Here the ultrastructural evidence is reviewed that supports an elevated and sustained increase in the probability of vesicle release and recycling during LTP. In hippocampal area CA1, small dense-core vesicles and tethered synaptic vesicles are recruited to presynaptic boutons enlarging active zones. By 2 h during LTP, there is a sustained loss of vesicles, especially in presynaptic boutons containing mitochondria and clathrin-coated pits. This decrease in vesicles accompanies an enlargement of the presynaptic bouton, suggesting they supply membrane needed for the enlarged bouton surface area. The spatial relationship of vesicles to the active zone varies with functional status. Tightly docked vesicles contact the presynaptic membrane and are primed for release of neurotransmitter upon the next action potential. Loosely docked vesicles are located within 8 nm of the presynaptic membrane. Non-docked vesicles comprise recycling and reserve pools. Vesicles are tethered to the active zone via filaments composed of molecules engaged in docking and release processes. Electron tomography reveals clustering of docked vesicles at higher local densities in active zones after LTP. Furthermore, the tethering filaments on vesicles at the active zone are shorter, and their attachment sites are shifted closer to the active zone. These changes suggest more vesicles are docked, primed and ready for release. The findings provide strong ultrastructural evidence for a long-lasting increase in release probability following LTP.

As humans age, some experience cognitive impairment while others do not. When impairment occurs, it varies in severity across individuals. Translationally relevant models are critical for understanding the neurobiological drivers of this variability, which is essential to uncovering the mechanisms underlying the brain’s susceptibility to aging. The common marmoset has emerged as an advantageous non-human primate model to investigate the biological consequences of aging due to shared behavioral, neuroanatomical, and age-related neuropathological features with humans, and a short lifespan that facilitates longitudinal studies. Despite growing popularity as a model, robust cognitive phenotyping of marmosets, particularly as a function of age and across multiple cognitive domains, is lacking. To address this major limitation for the development and evaluation of the marmoset as a model of cognitive aging, we developed a comprehensive touchscreen-based neuropsychological test battery. We use this battery to longitudinally assess cognitive aging trajectories in marmosets across the lifespan. To characterize synaptic ultrastructure as a function of aging and cognitive status, we used electron microscopy. Similar to humans, we find that marmosets show age-related impairment in motor speed, motivation, cognitive flexibility, and working memory, with a remarkable degree of heterogeneity. We also find that aged marmosets show synapse loss in the dorsolateral prefrontal cortex at a level consistent with aged macaques. Though synapse loss is widely considered a key determinant of cognitive impairment with age, we find an equivalent degree of synapse loss in aged cognitively unimpaired and aged cognitively impaired marmosets. Our findings indicate that the coordinated scaling of the sizes of synapses and mitochondria with associated boutons is crucial for preserving working memory with age. However, failure of synaptic mitochondria to scale with presynaptic boutons selectively underlies age-related working memory impairment. We posit that failed scaling results in mismatched energy supply and demand, leading to impaired synaptic transmission. This novel mechanism of synapse dysfunction differentiates aged marmosets with cognitive impairment from those without. Together, this work demonstrates the importance of comprehensive cognitive phenotyping to uncover the neurobiological consequences of aging, and firmly establishes the common marmoset as an advantageous model for age-related cognitive impairment.

As the serial section community transitions to volume electron microscopy, tools are needed to balance rapid segmentation efforts with documenting the fine detail of structures that support cell function. New annotation applications should be accessible to users and meet the needs of the neuroscience and connectomics communities while also being useful across other disciplines. Issues not currently addressed by a single, modern annotation application include 1) built-in curation systems with utilities for expert intervention to provide quality assurance, 2) integrated alignment features that allow for image registration on-the-fly as image flaws are found during annotation, 3) simplicity for nonspecialists within and beyond the neuroscience community, 4) a system to store experimental metadata with annotation data in a way that researchers remain masked regarding condition to avoid potential biases, 5) local management of large datasets appropriate for circuit-level analyses, and 6) fully open-source codebase allowing development of new tools, and more. Here, we present PyReconstruct, a modern successor to the Reconstruct annotation tool. PyReconstruct operates in a field-agnostic manner, runs on all major operating systems, breaks through legacy RAM limitations, features an intuitive and collaborative curation system, and employs a flexible and dynamic approach to image registration. It can be used to analyze, display, and publish experimental or connectomics data. PyReconstruct is suited for generating ground truth to implement in automated segmentation, outcomes of which can be returned to PyReconstruct for proofreading and quality control.

Producing dense 3D reconstructions from biological imaging data is a challenging instance segmentation task that requires significant ground-truth training data for effective and accurate deep learning-based models. Generating training data requires intense human effort to annotate each instance of an object across serial section images. Our focus is on the especially complicated brain neuropil, comprising an extensive interdigitation of dendritic, axonal, and glial processes visualized through serial section electron microscopy. We developed a novel deep learning-based method to generate dense 3D segmentations rapidly from sparse 2D annotations of a few objects on single sections. Models trained on the rapidly generated segmentations achieved similar accuracy as those trained on expert dense ground-truth annotations. Human time to generate annotations was reduced by three orders of magnitude and could be produced by non-expert annotators. This capability will democratize generation of training data for large image volumes needed to achieve brain circuits and measures of circuit strengths.

Synapses form trillions of connections in the brain. Long-term potentiation (LTP) and long-term depression (LTD) are cellular mechanisms vital for learning that modify the strength and structure of synapses. Three-dimensional reconstruction from serial section electron microscopy reveals three distinct pre- to post-synaptic arrangements: strong active zones (AZs) with tightly docked vesicles, weak AZs with loose or non-docked vesicles, and nascent zones (NZs) with a postsynaptic density but no presynaptic vesicles. Importantly, LTP can be temporarily saturated preventing further increases in synaptic strength. At the onset of LTP, vesicles are recruited to NZs, converting them to AZs. During recovery of LTP from saturation (1-4 h), new NZs form, especially on spines where AZs are most enlarged by LTP. Sentinel spines contain smooth endoplasmic reticulum (SER), have the largest synapses and form clusters with smaller spines lacking SER after LTP recovers. We propose a model whereby NZ plasticity provides synapse-specific AZ expansion during LTP and loss of weak AZs that drive synapse shrinkage during LTD. Spine clusters become functionally engaged during LTP or disassembled during LTD. Saturation of LTP or LTD probably acts to protect recently formed memories from ongoing plasticity and may account for the advantage of spaced over massed learning. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Hippocampal interneurons form a large, heterogeneous group with differing structural, physiological, and chemical phenotypes. Most CA1 interneuron dendrites, however, lack spines. To investigate structural synaptic plasticity along interneuron dendrites, we generated three-dimensional (3D) reconstructions from serial section electron microscopy (EM) of excitatory synapses along aspiny dendrites in CA1 stratum radiatum of young adult rats under control conditions and at 2 h during LTP induced with theta-burst stimulation. In total, 43 aspiny dendritic segments and their synapses were identified and reconstructed in 3D. Aspiny dendrites were categorized as smooth or varicose based on dendritic volume contours along each segment. We further sub-segmented varicose dendrites varicosities and inter-varicose regions using automated and manual methods. We found synapses and total synaptic input per length were distributed uniformly along smooth dendrites. Synapses along varicose dendrites, however, occurred preferentially at varicosities. While synaptic input per length along varicosities was similar to that along smooth dendrites, both synapse number and total synaptic input per length along inter-varicose regions were lower. Dendritic segments were also analyzed for mitochondria and glycogen content. We found that mitochondria and glycogen were also distributed uniformly along smooth dendrites. In varicose dendrites, however, mitochondrial volume and glycogen granule numbers were highest in varicosities, while inter-varicose regions were comparatively devoid of these resources. The spatial distribution of synapses and dendritic resources in both smooth and varicose dendrites was preserved at 2 h during LTP when compared to control conditions. These findings suggest that synapses occur along interneuron dendrites where dendritic resources are most available. When dendritic resources are distributed uniformly throughout the dendrite, as occurs in smooth dendrites, synapse distribution is also uniform. Varicosities, on the other hand, represent resource-rich sites along varicose dendrites where synaptic clustering occurs. This work was supported by the National Science Foundation (NSF 1707356, NSF 2014862) and the National Institutes of Health (R01 5R01MH09598). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Variation in the strength of synapses can be quantified by measuring the anatomical properties of synapses. Quantifying precision of synaptic plasticity is fundamental to understanding information storage and retrieval in neural circuits. Synapses from the same axon onto the same dendrite have a common history of coactivation, making them ideal candidates for determining the precision of synaptic plasticity based on the similarity of their physical dimensions. Here, the precision and amount of information stored in synapse dimensions were quantified with Shannon information theory, expanding prior analysis that used signal detection theory (Bartol et al., 2015). The two methods were compared using dendritic spine head volumes in the middle of the stratum radiatum of hippocampal area CA1 as well-defined measures of synaptic strength. Information theory delineated the number of distinguishable synaptic strengths based on nonoverlapping bins of dendritic spine head volumes. Shannon entropy was applied to measure synaptic information storage capacity (SISC) and resulted in a lower bound of 4.1 bits and upper bound of 4.59 bits of information based on 24 distinguishable sizes. We further compared the distribution of distinguishable sizes and a uniform distribution using Kullback-Leibler divergence and discovered that there was a nearly uniform distribution of spine head volumes across the sizes, suggesting optimal use of the distinguishable values. Thus, SISC provides a new analytical measure that can be generalized to probe synaptic strengths and capacity for plasticity in different brain regions of different species and among animals raised in different conditions or during learning. How brain diseases and disorders affect the precision of synaptic plasticity can also be probed.

Extracellular vesicles (EVs) have emerged as potential biomarkers for diagnosing a range of diseases without invasive procedures. Extracellular vesicles also offer advantages compared to synthetic vesicles for delivery of various drugs; however, limitations in segregating EVs from other particles and soluble proteins have led to inconsistent EV retrieval rates with low levels of purity. Here, we report a new high-yield (88.47 %) and rapid (<20 min) EV isolation method termed size exclusion – fast protein liquid chromatography (SE-FPLC). We show SE-FPLC can effectively isolate EVs from multiple sources including EVs derived from human and mouse cells and serum samples. The results indicate that SE-FPLC can successfully remove highly abundant protein contaminants such as albumin and lipoprotein complexes, which can represent a major hurdle in large scale isolation of EVs. The high-yield nature of SE-FPLC allows for easy industrial scaling up of EV production for various clinical utilities. SE-FPLC also enables analysis of small volumes of blood for use in point-of-care diagnostics in the clinic. Collectively, SE-FPLC offers many advantages over current EV isolation methods and offers rapid clinical translation.

Long-term potentiation (LTP) has become a standard model for investigating synaptic mechanisms of learning and memory. Increasingly, it is of interest to understand how LTP affects the synaptic information storage capacity of the targeted population of synapses. Here, structural synaptic plasticity during LTP was explored using three-dimensional reconstruction from serial section electron microscopy. Storage capacity was assessed by applying a new analytical approach, Shannon information theory, to delineate the number of functionally distinguishable synaptic strengths. LTP was induced by delta-burst stimulation of perforant pathway inputs to the middle molecular layer of hippocampal dentate granule cells in adult rats. Spine head volumes were measured as predictors of synaptic strength and compared between LTP and control hemispheres at 30 min and 2 hr after the induction of LTP. Synapses from the same axon onto the same dendrite were used to determine the precision of synaptic plasticity based on the similarity of their physical dimensions. Shannon entropy was measured by exploiting the frequency of spine heads in functionally distinguishable sizes to assess the degree to which LTP altered the number of bits of information storage. Outcomes from these analyses reveal that LTP expanded storage capacity; the distribution of spine head volumes was increased from 2 bits in controls to 3 bits at 30 min and 2.7 bits at 2 hr after the induction of LTP. Furthermore, the distribution of spine head volumes was more uniform across the increased number of functionally distinguishable sizes following LTP, thus achieving more efficient use of coding space across the population of synapses.

Functional and structural elements of synaptic plasticity are tightly coupled, as has been extensively shown for dendritic spines. Here, we interrogated structural features of presynaptic terminals in 3DEM reconstructions from CA1 hippocampal axons that had undergone control stimulation or theta-burst stimulation (TBS) to produce long-term potentiation (LTP). We reveal that after LTP induction, the synaptic vesicle (SV) cluster is less dense, and SVs are more dispersed. The distances between neighboring SVs are greater in less dense terminals and have more SV-associated volume. We characterized the changes to the SV cluster by measuring distances between neighboring SVs, distances to the active zone, and the dispersion of the SV cluster. Furthermore, we compared the distribution of SVs with randomized ones and provided evidence that SVs gained mobility after LTP induction. With a computational model, we can predict the increment of the diffusion coefficient of the SVs in the cluster. Moreover, using a machine learning approach, we identify presynaptic terminals that were potentiated after LTP induction. Lastly, we show that the local SV density is a volume-independent property under strong regulation. Altogether, these results provide evidence that the SV cluster is undergoing a transition during LTP. ### Competing Interest Statement The authors have declared no competing interest.

Homozygous deletion of MTAP occurs in about 15% of all human cancers, such as glioblastoma, pancreatic cancer, mesothelioma, urothelial bladder carcinoma, and lung squamous cell carcinoma. PRMT5 inhibitors show activity against MTAP-deleted cancer cells in culture and xenografts with a mechanism that relies on the significant elevation of the MTAP substrate, methylthioadenosine (MTA). Previously, we have shown that unlike cells in culture, MTA levels in MTAP-deleted primary human GBM tumors are not significantly higher than in MTAP-intact tumors. Therefore, combining the PRMT5 inhibitor with another drug may be required to increase the therapeutic window and clinical efficacy of a PRMT5 inhibitor in MTAP-deleted patients. Here, we identified a natural small molecular chemical compound with a good safety profile that synergizes with a PRMT5-MTA complex inhibitor, which boosts the efficacy of MTAP-deleted selective cell killing in the presence of MTA sequestering cells. This combination therapy significantly increases the potency of PRMT5 inhibitor treatment in MTAP-deleted cells across various tumor cell lines and lowers the IC50 of PRMT5 inhibitor treatment. In vivo, PRMT5 inhibitor combination treatment leads to smaller tumor volumes in MTAP-deleted CDX tumors (U87, glioma cell line) compared to PRMT5 inhibitor monotherapy. In summary, our proposed combination therapy of PRMT5 inhibition with a natural compound may increase the therapeutic window and clinical efficacy of PRMT5 inhibitors leading to better treatment options for patients harboring MTAP-deleted cancer. Citation Format: Yasaman Barekatain, Kyle LaBella, Hikaru Sugimoto, Kristen Harris, Sunada Khadka, Florian Muller, Raghu Kalluri. PRMT5 inhibition synergizes with a natural small molecule compound to kill MTAP-deleted cells and suppress tumor growth [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1073.

Dendritic spines can be directly connected to both inhibitory and excitatory presynaptic terminals, resulting in nanometer-scale proximity of opposing synaptic functions. While dually innervated spines (DiSs) are observed throughout the central nervous system, their developmental timeline and functional properties remain uncharacterized. Here we used a combination of serial section electron microscopy, live imaging, and local synapse activity manipulations to investigate DiS development and function in rodent hippocampus. Dual innervation occurred early in development, even on spines where the excitatory input was locally silenced. Synaptic NMDA receptor currents were selectively reduced at DiSs through tonic GABAB receptor signaling. Accordingly, spine enlargement normally associated with long-term potentiation on singly innervated spines (SiSs) was blocked at DiSs. Silencing somatostatin interneurons or pharmacologically blocking GABABRs restored NMDA receptor function and structural plasticity to levels comparable to neighboring SiSs. Thus, hippocampal DiSs are stable structures where function and plasticity are potently regulated by nanometer-scale GABAergic signaling.

Morphology and function of the dorsolateral prefrontal cortex (dlPFC), and corresponding working memory performance, are affected early in the aging process, but nearly half of aged individuals are spared of working memory deficits. Translationally relevant model systems are critical for determining the neurobiological drivers of this variability. The common marmoset (Callithrix jacchus) is advantageous as a model for these investigations because, as a non-human primate, marmosets have a clearly defined dlPFC that enables measurement of prefrontal-dependent cognitive functions, and their short (∼10 year) lifespan facilitates longitudinal studies of aging. Previously, we characterized working memory capacity in a cohort of marmosets that collectively covered the lifespan, and found age-related working memory impairment. We also found a remarkable degree of heterogeneity in performance, similar to that found in humans. Here, we tested the hypothesis that changes to synaptic ultrastructure that affect synaptic efficacy stratify marmosets that age with cognitive impairment from those that age without cognitive impairment. We utilized electron microscopy to visualize synapses in the marmoset dlPFC and measured the sizes of boutons, presynaptic mitochondria, and synapses. We found that coordinated scaling of the sizes of synapses and mitochondria with their associated boutons is essential for intact working memory performance in aged marmosets. Further, lack of synaptic scaling, due to a remarkable failure of synaptic mitochondria to scale with presynaptic boutons, selectively underlies age-related working memory impairment. We posit that this decoupling results in mismatched energy supply and demand, leading to impaired synaptic transmission. We also found that aged marmosets have fewer synapses in dlPFC than young, though the severity of synapse loss did not predict whether aging occurred with or without cognitive impairment. This work identifies a novel mechanism of synapse dysfunction that stratifies marmosets that age with cognitive impairment from those that age without cognitive impairment. The process by which synaptic scaling is regulated is yet unknown and warrants future investigation.

Extracellular Vesicles (EVs) have emerged as potential biomarkers for diagnosing a range of diseases without invasive procedures. Extracellular vesicles also offer an advantage compared to synthetic vesicles, for delivery of various drugs. However, limitations in segregating EVs from soluble proteins have led to inconsistent EV retrieval rates with low levels of purity. Here, we report a new high-yield (>95%) and rapid (<20 min) EV isolation method called S ize E xclusion – F ast P erformance L iquid C hromatography (SE-FPLC). We show SE-FPLC can effectively isolate EVs from multiple sources including EVs derived from human and mouse cells and serum. The results indicate that SE-FPLC can successfully remove highly abundant protein contaminants such as albumin and lipoprotein complexes, which can represent a major hurdle in large scale isolation of EVs for clinical translation. Additionally, the high-yield nature of SE- FPLC allows for easy industrial upscaling of extracellular vesicles production for various clinical utilities. Moreover, SE-FPLC enables analysis of very small volumes of blood for use in point-of-care diagnostics in the clinic. Collectively, SE-FPLC offers many advantages over current EV isolation methods and offers rapid clinical utility potential.

Microtubules deliver essential resources to and from synapses. Three-dimensional reconstructions in rat hippocampus reveal a sampling bias regarding spine density that needs to be controlled for dendrite caliber and resource delivery based on microtubule number. The strength of this relationship varies across dendritic arbors, as illustrated for area CA1 and dentate gyrus. In both regions, proximal dendrites had more microtubules than distal dendrites. For CA1 pyramidal cells, spine density was greater on thicker than thinner dendrites in stratum radiatum, or on the more uniformly thin terminal dendrites in stratum lacunosum moleculare. In contrast, spine density was constant across the cone shaped arbor of tapering dendrites from dentate granule cells. These differences suggest that thicker dendrites supply microtubules to subsequent dendritic branches and local dendritic spines, whereas microtubules in thinner dendrites need only provide resources to local spines. Most microtubules ran parallel to dendrite length and associated with long, presumably stable mitochondria, which occasionally branched into lateral dendritic branches. Short, presumably mobile, mitochondria were tethered to microtubules that bent and appeared to direct them into a thin lateral branch. Prior work showed that dendritic segments with the same number of microtubules had elevated resources in subregions of their dendritic shafts where spine synapses had enlarged, and spine clusters had formed. Thus, additional microtubules were not required for redistribution of resources locally to growing spines or synapses. These results provide new understanding about the potential for microtubules to regulate resource delivery to and from dendritic branches and locally among dendritic spines.

Background: In recent years, pregnancy-related mortality rates in the US have increased, with cardiovascular disease accounting for a third of all pregnancy-related mortality. The association between cardiometabolic (CM) health and social determinants of health have not been well understood. Objectives: We sought to investigate the relationship between social vulnerability and prevalence of CM risk factors in pregnant women in the US. Methods: In this cross-sectional analysis, we linked natality files including all pregnancies resulting in live births in the US (aggregated 2016-2020) with county-level social vulnerability index (SVI), a composite metric of social risk factors with four major domains: socioeconomic, household composition/disability, minority status/language, and housing type/transportation. We investigated the association between SVI and its subdomains with county-level prevalence of maternal pre-pregnancy diabetes, pre-pregnancy hypertension, tobacco use, and obesity. Results: A total of 18,953,511 pregnancies were analyzed across 577 counties. All CM risk factors were associated with SVI and/or its 4 subcomponents to varying degrees. Obesity was strongly associated with overall SVI (R=0.52, P<0.001) with an even stronger relationship with socioeconomic vulnerability (R=0.6, P<0.001) and household composition/disability (R=0.66, P<0.001). The rate of pre-pregnancy diabetes was associated with overall SVI (R=0.27, p<0.001), with similar association with socioeconomic vulnerability (R=0.26, P<0.001) and household composition/disability (R=0.28, P<0.001). Chronic hypertension was weakly associated with overall SVI (R=0.15, P<0.001) with similar association with socioeconomic vulnerability (R=0.19, P<0.001) and household composition/disability (R=0.22, P<0.001). Tobacco use was not associated with overall SVI (R=0.034, p=0.41), but was strongly associated with minority status/language (R=-0.71, P<0.001). Conclusion: Social vulnerability and its domains are associated with prevalence of CM risk factors in pregnant women in the US. Further studies are needed to investigate the impact of targeting social determinants of health to improve CM risk and mortality in pregnant women.

Working memory relies critically on the dorsolateral prefrontal cortex (dlPFC). Morphology and function of the dlPFC, and corresponding working memory performance, are affected early in the aging process. However, these effects are heterogeneous, with nearly half of aged individuals spared of working memory deficits. Translationally relevant model systems are critical for investigating the neurobiological drivers of this variability and identifying why some people experience age-related working memory impairment while others do not. The common marmoset (Callithrix jacchus) is advantageous as a model in which to investigate the biological underpinnings of aging because, as a nonhuman primate, marmosets have a clearly defined dlPFC facilitating investigations of prefrontal-dependent cognitive functions, including working memory, and their short (~10 year) lifespan facilitates longitudinal studies of aging. Here, we conduct the first investigation of synaptic ultrastructure in the dlPFC of the marmoset and investigate whether there are changes to synaptic ultrastructure that are unique to aging with and without working memory impairment. To do this, we characterized working memory capacity in a cohort of marmosets that collectively covered their short lifespan, and found age-related working memory impairment. We also found a remarkable degree of heterogeneity in performance, similar to that found in humans. Utilizing three dimensional reconstruction from serial section electron microscopy, we visualized structural correlates of synaptic efficacy including boutons, mitochondria, and synapses in layer III of the dlPFC of three marmosets: one young adult (YA), one aged cognitively unimpaired (AU), and one aged cognitively impaired (AI). We find that aged marmosets have fewer synapses in dlPFC than young, and this is due to selective vulnerability of small synapses. Next, we tested the hypothesis that violation of the ultrastructural size principle underlies age-related working memory impairment. The ultrastructural size principle states that synaptic efficacy relies on coordinated scaling of synaptic components (e.g., synapses, mitochondria) with presynaptic boutons. While synapses and mitochondria scaled proportionally and were strongly correlated with presynaptic boutons in the YA and AU marmosets, the ultrastructural characteristics of the AI marmoset were alarmingly different. We found that age-related working memory impairment was associated with disproportionately large synapses compared to presynaptic boutons, specifically in those with mitochondria. Remarkably, presynaptic mitochondria and these boutons were completely decorrelated. We posit that this decorrelation results in mismatched energy supply and demand, leading to impaired synaptic transmission. This is the first report of age-related synapse loss in the marmoset, and the first demonstration that violation of the ultrastructural size principle underlies age-related working memory impairment.

OBJECTIVES:Adults with diabetes are at an increased risk of atherosclerotic cardiovascular disease (ASCVD), and food insecurity may be a major and underappreciated risk compounder in this population. We sought to analyze the prevalence of food insecurity and its association with ASCVD in adults with diabetes. METHODS:A total of 6424 participants with diabetes were included from the 2019 and 2020 National Health Interview Survey. Food insecurity was determined with a 10-question U.S. Adult Food Security Survey Module, and classified as high, marginal, low, and very low. ASCVD was defined as a self-reported history of coronary artery disease, myocardial infarction, or stroke. RESULTS:Of the 6424 included participants (weighted: n = 21 690 217), 5 405 543 (24.4%) reported a history of ASCVD and 2 946 061 (13.3%) were identified as food insecure (low or very low food security). Adults with food insecurity were more likely to have ASCVD than adults who were food secure (28.9% vs 23.7%; P = 0.008). In the multivariate analyses adjusted for traditional cardiovascular risk factors, all levels of food insecurity were associated with ASCVD compared with food-secure adults (marginal security: odds ratio [OR]: 1.60; 95% confidence interval [CI], 1.18-2.18]; P = 0.003; low security: OR: 2.09; 95% CI, 1.58-2.74]; P < 0.001; very low security: OR: 1.69; 95% CI, 1.22-2.34]; P = 0.001). The association persisted when adjusted for income, location, education, and insurance status. In adults with diabetes and ASCVD, income was a negative factor for food insecurity (OR: 0.71; 95% CI, 0.62-0.80; P < 0.001), but female sex and smoking were positive factors (OR: 1.90; 95% CI, 1.29-2.80; P = 0.001; and OR: 1.97; 95% CI, 1.23-3.18; P = 0.005; respectively). At younger ages, the prevalence of food insecurity increased, especially in adults with ASCVD. CONCLUSIONS:We showed that 13% of U.S. adults with diabetes are food insecure, which was associated with ASCVD independent of traditional and socioeconomic risk factors. Our findings emphasize the importance of recognizing food insecurity as a driver of ASCVD in adults with diabetes, and encourage future efforts at reducing this disparity.

The phosphonate group is a key pharmacophore in many anti-viral, anti-microbial, and anti-neoplastic drugs. Due to its high polarity and short retention time, detecting and quantifying such phosphonate-containing drugs with LC/MS-based methods is challenging and requires derivatization with hazardous reagents. Given the emerging importance of phosphonate-containing drugs, developing a practical, accessible, and safe method for their quantitation in pharmacokinetics (PK) studies is desirable. NMR-based methods are often employed in drug discovery but are seldom used for compound quantitation in PK studies. Here, we show that proton-phosphorous ( 1 H- 31 P) heteronuclear single quantum correlation (HSQC) NMR allows for quantitation of the phosphonate-containing enolase inhibitor HEX in plasma and tissue at micromolar concentrations. Although mice were shown to rapidly clear HEX from circulation (over 95% in <1 hr), the plasma half-life of HEX was more than 1hr in rats and nonhuman primates. This slower clearance rate affords a significantly higher exposure of HEX in rat models compared to mouse models while maintaining a favorable safety profile. Similar results were observed for the phosphonate-containing antibiotic, fosfomycin. Our study demonstrates the applicability of the 1 H- 31 P HSQC method to quantify phosphonate-containing drugs in complex biological samples and illustrates an important limitation of mice as preclinical model species for phosphonate-containing drugs.