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Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

The magnetic resonance imaging (MRI) Core has been operating since Alzheimer's Disease Neuroimaging Initiative's (ADNI) inception, providing 20 years of data including reliable, multi-platform standardized protocols, carefully curated image data, and quantitative measures provided by expert investigators. The overarching purposes of the MRI Core include: (1) optimizing and standardizing MRI acquisition methods, which have been adopted by many multicenter studies and trials worldwide and (2) providing curated images and numeric summary values from relevant MRI sequences/contrasts to the scientific community. Over time, ADNI MRI has become increasingly complex. To remain technically current, the ADNI MRI protocol has changed substantially over the past two decades. The ADNI 4 protocol contains nine different imaging types (e.g., three dimensional [3D] T1-weighted and fluid-attenuated inversion recovery [FLAIR]). Our view is that the ADNI MRI data are a greatly underutilized resource. The purpose of this paper is to educate the scientific community on ADNI MRI methods and content to promote greater awareness, accessibility, and use. HIGHLIGHTS: The MRI Core provides multi-platform standardized protocols, carefully curated image data, and quantitative analysis by expert groups. The ADNI MRI protocol has undergone major changes over the past two decades to remain technically current. As of April 25, 2024, the following numbers of image series are available: 17,141 3D T1w; 6877 FLAIR; 3140 T2/PD; 6623 GRE; 3237 dMRI; 2846 ASL; 2968 TF-fMRI; and 2861 HighResHippo (see Table 1 for abbreviations). As of April 25, 2024, the following numbers of quantitative analyses are available: FreeSurfer 10,997; BSI 6120; tensor based morphometry (TBM) and TBM-SYN 12,019; WMH 9944; dMRI 1913; ASL 925; TF-fMRI NFQ 2992; and medial temporal subregion volumes 2726 (see Table 4 for abbreviations). ADNI MRI is an underutilized resource that could be more useful to the research community.

ObjectivesIncreasingly diverse caregiver populations have prompted studies examining culture and caregiver outcomes. Still, little is known about the influence of sociocultural factors and how they interact with caregiving context variables to influence psychological health. We explored the role of caregiving and acculturation factors on psychological distress among a diverse sample of adults.DesignSecondary data analysis of the California Health Interview Survey (CHIS).ParticipantsThe 2009 CHIS surveyed 47,613 adults representative of the population of California. This study included Latino and Asian American Pacific Islander (AAPI) caregivers and non-caregivers (n = 13,161).MeasurementsMultivariate weighted regression analyses examined caregiver status and acculturation variables (generational status, language of interview, and English language proficiency) and their associations with psychological distress (Kessler-6 scale). Covariates included caregiving context (e.g., support and neighborhood factors) and demographic variables.ResultsFirst generation caregivers had more distress than first-generation non-caregivers (β=0.92, 95% CI: (0.18, 1.65)); the difference in distress between caregivers and non-caregivers was smaller in the third than first generation (β=-1.21, 95% CI: (-2.24, -0.17)). Among those who did not interview in English (β=1.17, 95% CI: (0.13, 2.22)) and with low English proficiency (β=2.60, 95% CI: (1.21, 3.98)), caregivers reported more distress than non-caregivers.ConclusionsNon-caregivers exhibited the "healthy immigrant effect," where less acculturated individuals reported less distress. In contrast, caregivers who were less acculturated reported more distress.

Abstract: Forests are a large carbon sink and could serve as natural climate solutions that help moderate future warming. Thus, establishing forest carbon baselines is essential for tracking climate‐mitigation targets. Western US forests are natural climate solution hotspots but are profoundly threatened by drought and altered disturbance regimes. How these factors shape spatial patterns of carbon storage and carbon change over time is poorly resolved. Here, we estimate live and dead forest carbon density in 19 forested western US ecoregions with national inventory data (2005–2019) to determine: (a) current carbon distributions, (b) underpinning drivers, and (c) recent trends. Potential drivers of current carbon included harvest, wildfire, insect and disease, topography, and climate. Using random forests, we evaluated driver importance and relationships with current live and dead carbon within ecoregions. We assessed trends using linear models. Pacific Northwest (PNW) and Southwest (SW) ecoregions were most and least carbon dense, respectively. Climate was an important carbon driver in the SW and Lower Rockies. Fire reduced live and increased dead carbon, and was most important in the Upper Rockies and California. No ecoregion was unaffected by fire. Harvest and private ownership reduced carbon, particularly in the PNW. Since 2005, live carbon declined across much of the western US, likely from drought and fire. Carbon has increased in PNW ecoregions, likely recovering from past harvest, but recent record fire years may alter trajectories. Our results provide insight into western US forest carbon function and future vulnerabilities, which is vital for effective climate change mitigation strategies.

Acute poisoning with organophosphorus cholinesterase inhibitors (OPs), such as OP nerve agents and pesticides, can cause life threatening cholinergic crisis and status epilepticus (SE). Survivors often experience significant morbidity, including brain injury, acquired epilepsy, and cognitive deficits. Current medical countermeasures for acute OP poisoning include a benzodiazepine to mitigate seizures. Diazepam was long the benzodiazepine included in autoinjectors used to treat OP-induced seizures, but it is now being replaced in many guidelines by midazolam, which terminates seizures more quickly, particularly when administered intramuscularly. While a direct correlation between seizure duration and the extent of brain injury has been widely reported, there are limited data comparing the neuroprotective efficacy of diazepam versus midazolam following acute OP intoxication. To address this data gap, we used non-invasive imaging techniques to longitudinally quantify neuropathology in a rat model of acute intoxication with the OP diisopropylfluorophosphate (DFP) with and without post-exposure intervention with diazepam or midazolam. Magnetic resonance imaging (MRI) was used to monitor neuropathology and brain atrophy, while positron emission tomography (PET) with a radiotracer targeting translocator protein (TSPO) was utilized to assess neuroinflammation. Animals were scanned at 3, 7, 28, 65, 91, and 168 days post-DFP and imaging metrics were quantitated for the hippocampus, amygdala, piriform cortex, thalamus, cerebral cortex and lateral ventricles. In the DFP-intoxicated rat, neuroinflammation persisted for the duration of the study coincident with progressive atrophy and ongoing tissue remodeling. Benzodiazepines attenuated neuropathology in a region-dependent manner, but neither benzodiazepine was effective in attenuating long-term neuroinflammation as detected by TSPO PET. Diffusion MRI and TSPO PET metrics were highly correlated with seizure severity, and early MRI and PET metrics were positively correlated with long-term brain atrophy. Collectively, these results suggest that anti-seizure therapy alone is insufficient to prevent long-lasting neuroinflammation and tissue remodeling.

Acute intoxication with organophosphate (OP) cholinesterase inhibitors poses a significant public health risk. While currently approved medical countermeasures can improve survival rates, they often fail to prevent chronic neurological damage. Therefore, there is need to develop effective therapies and quantitative metrics for assessing OP-induced brain injury and its rescue by these therapies. In this study we used a rat model of acute intoxication with the OP, diisopropylfluorophosphate (DFP), to test the hypothesis that T2 measures obtained from brain magnetic resonance imaging (MRI) scans provide quantitative metrics of brain injury and therapeutic efficacy. Adult male Sprague Dawley rats were imaged on a 7T MRI scanner at 3, 7 and 28 days post-exposure to DFP or vehicle (VEH) with or without treatment with the standard of care antiseizure drug, midazolam (MDZ); a novel antiseizure medication, allopregnanolone (ALLO); or combination therapy with MDZ and ALLO (DUO). Our results show that mean T2 values in DFP-exposed animals were: (1) higher than VEH in all volumes of interest (VOIs) at day 3; (2) decreased with time; and (3) decreased in the thalamus at day 28. Treatment with ALLO or DUO, but not MDZ alone, significantly decreased mean T2 values relative to untreated DFP animals in the piriform cortex at day 3. On day 28, the DUO group showed the most favorable T2 characteristics. This study supports the utility of T2 mapping for longitudinally monitoring brain injury and highlights the therapeutic potential of ALLO as an adjunct therapy to mitigate chronic morbidity associated with acute OP intoxication.

Abstract: Acute intoxication with organophosphorus (OP) cholinesterase inhibitors can produce seizures that rapidly progress to life-threateningstatus epilepticus. Significant research effort has been invested investigating the involvement of muscarinic acetylcholine receptors (mAChRs) in OP-induced seizure activity. In contrast, there has been far less effort focused on nicotinic AChRs (nAChRs) in this context. Here, we address this data gap using a combination ofin vitroandin vivomodels. Pharmacological antagonism and genetic deletion of α4, but not α7, nAChR subunits prevented or significantly attenuated OP-induced electrical spike activity in acute hippocampal slices and seizure activity in mice, indicating that α4 nAChR activation is necessary for neuronal hyperexcitability triggered by acute OP exposures. These findings not only suggest that therapeutic strategies for inhibiting the α4 nAChR subunit warrant further investigation as prophylactic and acute treatments for acute OP-induced seizures, but also provide mechanistic insight into the role of the nicotinic cholinergic system in seizure generation.

Acute intoxication with cholinesterase inhibiting organophosphates (OP) can produce life-threatening cholinergic crisis and status epilepticus (SE). Survivors often develop long-term neurological consequences, including spontaneous recurrent seizures (SRS) and impaired cognition. Numerous studies implicate OP-induced neuroinflammation as a pathogenic mechanism contributing to these chronic sequelae; however, little is known about the inflammatory phenotype of innate immune cells in the brain following acute OP intoxication. Thus, the aim of this study was to characterize the natural history of microglial and astrocytic inflammatory phenotypes following acute intoxication with the OP, diisopropylfluorophosphate (DFP). Adult male and female Sprague-Dawley rats were administered a single dose of DFP (4 mg/kg, sc) followed by standard medical countermeasures. Within minutes, animals developed benzodiazepine-resistant SE as determined by monitoring seizures using a modified Racine scale. At 1, 3, 7, 14, and 28 d post-exposure (DPE), neuroinflammation was assessed using translocator protein (TSPO) positron emission tomography (PET) and magnetic resonance imaging (MRI). In both sexes, we observed consistently elevated radiotracer uptake across all examined brain regions and time points. A separate group of animals was euthanized at these same time points to collect tissues for immunohistochemical analyses. Colocalization of IBA-1, a marker for microglia, with iNOS or Arg1 was used to identify pro- and anti-inflammatory microglia, respectively; colocalization of GFAP, a marker for astrocytes, with C3 or S100A10, pro- and anti-inflammatory astrocytes, respectively. We observed shifts in the inflammatory profiles of microglia and astrocyte populations during the first month post-intoxication, largely in hyperintense inflammatory lesions in the piriform cortex and amygdala regions. In these areas, iNOS+ proinflammatory microglial cell density peaked at 3 and 7 DPE, while anti-inflammatory Arg1+ microglia cell density peaked at 14 DPE. Pro- and anti-inflammatory astrocytes emerged within 7 DPE, and roughly equal ratios of C3+ pro-inflammatory and S100A10+ anti-inflammatory astrocytes persisted at 28 DPE. In summary, microglia and astrocytes adopted mixed inflammatory phenotypes post-OP intoxication, which evolved over one month post exposure. These activated cell populations were most prominent in the piriform and amygdala areas and were more abundant in males compared to females. The temporal relationship between microglial and astrocytic responses suggests that initial microglial activity may influence delayed, persistent astrocytic responses. Further, our findings identify putative windows for inhibition of OP-induced neuroinflammatory responses in both sexes to evaluate the therapeutic benefit of anti-inflammation in this context.

Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveraging a machine learning (ML) pipeline to perform a granular quantification of Aβ deposits and assess their distribution in the temporal lobe. Utilizing 131 whole-slide-images from consecutive autopsied cases at the University of California Davis Alzheimer Disease Research Center, our objectives were threefold: (1) Validate an automatic workflow for Aβ deposit quantification in white matter (WM) and gray matter (GM); (2) define the distributions of different Aβ deposit types in GM and WM, and (3) investigate correlates of Aβ deposits with dementia status and the presence of mixed pathology. Our methodology highlights the robustness and efficacy of the ML pipeline, demonstrating proficiency akin to experts' evaluations. We provide comprehensive insights into the quantification and distribution of Aβ deposits in the temporal GM and WM revealing a progressive increase in tandem with the severity of established diagnostic criteria (NIA-AA). We also present correlations of Aβ load with clinical diagnosis as well as presence/absence of mixed pathology. This study introduces a reproducible workflow, showcasing the practical use of ML approaches in the field of neuropathology, and use of the output data for correlative analyses. Acknowledging limitations, such as potential biases in the ML model and current ML classifications, we propose avenues for future research to refine and expand the methodology. We hope to contribute to the broader landscape of neuropathology advancements, ML applications, and precision medicine, paving the way for deep phenotyping of AD brain cases and establishing a foundation for further advancements in neuropathological research.

IntroductionThe role of lipopolysaccharide binding protein (LBP), an inflammation marker of bacterial translocation from the gastrointestinal tract, in Alzheimer's disease (AD) is not clearly understood.MethodsIn this study the concentrations of LBP were measured in n = 79 individuals: 20 apolipoprotein E (APOE)3/E3 carriers with and 20 without AD dementia, and 19 APOE3/E4 carriers with and 20 without AD dementia. LBP was found to be enriched in the 1.21-1.25 g/mL density fraction of plasma, which has previously been shown to be enriched in intestinally derived high-density lipoproteins (HDL). LBP concentrations were measured by ELISA.ResultsLBP was significantly increased within the 1.21-1.25 g/mL density fraction of plasma in APOE3/E3 AD patients compared to controls, but not APOE3/E4 patients. LBP was positively correlated with Clinical Dementia Rating (CDR) and exhibited an inverse relationship with Verbal Memory Score (VMS).DiscussionThese results underscore the potential contribution of gut permeability to bacterial toxins, measured as LBP, as an inflammatory mediator in the development of AD, particularly in individuals with the APOE3/E3 genotype, who are genetically at 4-12-fold lower risk of AD than individuals who express APOE4.

High-density lipoproteins (HDLs) are key regulators of cellular cholesterol homeostasis but are functionally altered in many chronic diseases. The factors that cause HDL functional loss in chronic disease are not fully understood. It is also unknown what roles antioxidant carotenoids play in protecting HDL against functional loss. The aim of this study was to measure how various disease-associated chemical factors including exposure to (1) Cu2+ ions, (2) hypochlorous acid (HOCL), (3) hydrogen peroxide (H2O2), (4) sialidase, (5) glycosidase, (6) high glucose, (7) high fructose, and (8) acidic pH, and the carotenoid antioxidants (9) lutein and (10) zeaxanthin affect HDL functionality. We hypothesized that some of the modifications would have stronger impacts on HDL particle structure and function than others and that lutein and zeaxanthin would improve HDL function. HDL samples were isolated from generally healthy human plasma and incubated with the corresponding treatments listed above. Cholesterol efflux capacity (CEC), lecithin-cholesterol acyl transferase (LCAT) activity, and paraoxonase-1 (PON1) activity were measured in order to determine changes in HDL functionality. Median HDL particle diameter was increased by acidic pH treatment and reduced by HOCl, high glucose, high fructose, N-glycosidase, and lutein treatments. Acidic pH, oxidation, and fructosylation all reduced HDL CEC, whereas lutein, zeaxanthin, and sialidase treatment improved HDL CEC. LCAT activity was reduced by acidic pH, oxidation, high fructose treatments, and lutein. PON1 activity was reduced by sialidase, glycosidase, H2O2, and fructose and improved by zeaxanthin and lutein treatment. These results show that exposure to oxidizing agents, high fructose, and low pH directly impairs HDL functionality related to cholesterol efflux and particle maturation, whereas deglycosylation impairs HDL antioxidant capacity. On the other hand, the antioxidants lutein and zeaxanthin improve or preserve both HDL cholesterol efflux and antioxidant activity but have no effect on particle maturation.

Acute intoxication with high levels of organophosphate (OP) cholinesterase inhibitors can cause cholinergic crisis, which is associated with acute, life-threatening parasympathomimetic symptoms, respiratory depression and seizures that can rapidly progress to status epilepticus (SE). Clinical and experimental data demonstrate that individuals who survive these acute neurotoxic effects often develop significant chronic morbidity, including behavioral deficits. The pathogenic mechanism(s) that link acute OP intoxication to chronic neurological deficits remain speculative. Cellular senescence has been linked to behavioral deficits associated with aging and neurodegenerative disease, but whether acute OP intoxication triggers cellular senescence in the brain has not been investigated. Here, we test this hypothesis in a rat model of acute intoxication with the OP diisopropylfluorophosphate (DFP). Adult male Sprague-Dawley rats were administered DFP (4 mg/kg, s.c.). Control animals were administered an equal volume (300 µL) of sterile phosphate-buffered saline (s.c.). Both groups were subsequently injected with atropine sulfate (2 mg/kg, i.m.) and 2-pralidoxime (25 mg/kg, i.m.). DFP triggered seizure activity within minutes that rapidly progressed to SE, as determined using behavioral seizure criteria. Brains were collected from animals at 1, 3, and 6 months post-exposure for immunohistochemical analyses of p16, a biomarker of cellular senescence. While there was no immunohistochemical evidence of cellular senescence at 1-month post-exposure, at 3- and 6-months post-exposure, p16 immunoreactivity was significantly increased in the CA3 and dentate gyrus of the hippocampus, amygdala, piriform cortex and thalamus, but not the CA1 region of the hippocampus or the somatosensory cortex. Co-localization of p16 immunoreactivity with cell-specific biomarkers, specifically, NeuN, GFAP, S100β, IBA1 and CD31, revealed that p16 expression in the brain of DFP animals is neuron-specific. The spatial distribution of p16-immunopositive cells overlapped with expression of senescence associated β-galactosidase and with degenerating neurons identified by FluoroJade-C (FJC) staining. The co-occurrence of p16 and FJC was positively correlated. This study implicates cellular senescence as a novel pathogenic mechanism underlying the chronic neurological deficits observed in individuals who survive OP-induced cholinergic crisis.

BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P

Acute organophosphate (OP) intoxication can trigger seizures that progress to status epilepticus (SE), and survivors often develop chronic morbidities, including spontaneous recurrent seizures (SRS). The pathogenic mechanisms underlying OP-induced SRS are unknown, but increased BBB permeability is hypothesized to be involved. Previous studies reported BBB leakage following OP-induced SE, but key information regarding time and regional distribution of BBB impairment during the epileptogenic period is missing. To address this data gap, we characterized the spatiotemporal progression of BBB impairment during the first week post-exposure in a rat model of diisopropylfluorophosphate-induced SE, using MRI and albumin immunohistochemistry. Increased BBB permeability, which was detected at 6 h and persisted up to 7 d post-exposure, was most severe and persistent in the piriform cortex and amygdala, moderate but persistent in the thalamus, and less severe and transient in the hippocampus and somatosensory cortex. The extent of BBB leakage was positively correlated with behavioral seizure severity, with the strongest association identified in the piriform cortex and amygdala. These findings provide evidence of the duration, magnitude and spatial breakdown of the BBB during the epileptogenic period following OP-induced SE and support BBB regulation as a viable therapeutic target for preventing SRS following acute OP intoxication.

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration.

The field of cell biology has seen major advances in both cellular imaging modalities and the development of automated image analysis platforms that increase rigor, reproducibility, and throughput for large imaging data sets. However, there remains a need for tools that provide accurate morphometric analysis of single cells with complex, dynamic cytoarchitecture in a high-throughput and unbiased manner. We developed a fully automated image-analysis algorithm to rapidly detect and quantify changes in cellular morphology using microglia cells, an innate immune cell within the central nervous system, as representative of cells that exhibit dynamic and complex cytoarchitectural changes. We used two preclinical animal models that exhibit robust changes in microglia morphology: (1) a rat model of acute organophosphate intoxication, which was used to generate fluorescently labeled images for algorithm development; and (2) a rat model of traumatic brain injury, which was used to validate the algorithm using cells labeled using chromogenic detection methods. All ex vivo brain sections were immunolabeled for IBA-1 using fluorescence or diaminobenzidine (DAB) labeling, images were acquired using a high content imaging system and analyzed using a custom-built algorithm. The exploratory data set revealed eight statistically significant and quantitative morphometric parameters that distinguished between phenotypically distinct groups of microglia. Manual validation of single-cell morphology was strongly correlated with the automated analysis and was further supported by a comparison with traditional stereology methods. Existing image analysis pipelines rely on high-resolution images of individual cells, which limits sample size and is subject to selection bias. However, our fully automated method integrates quantification of morphology and fluorescent/chromogenic signals in images from multiple brain regions acquired using high-content imaging. In summary, our free, customizable image analysis tool provides a high-throughput, unbiased method for accurately detecting and quantifying morphological changes in cells with complex morphologies.

Introduction: Understanding how abundance, productivity and distribution of individual species may respond to climate change is a critical first step towards anticipating alterations in marine ecosystem structure and function, as well as developing strategies to adapt to the full range of potential changes. Methods: This study applies the NOAA (National Oceanic and Atmospheric Administration) Fisheries Climate Vulnerability Assessment method to 64 federally-managed species in the California Current Large Marine Ecosystem to assess their vulnerability to climate change, where vulnerability is a function of a species’ exposure to environmental change and its biological sensitivity to a set of environmental conditions, which includes components of its resiliency and adaptive capacity to respond to these new conditions. Results: Overall, two-thirds of the species were judged to have Moderate or greater vulnerability to climate change, and only one species was anticipated to have a positive response. Species classified as Highly or Very Highly vulnerable share one or more characteristics including: 1) having complex life histories that utilize a wide range of freshwater and marine habitats; 2) having habitat specialization, particularly for areas that are likely to experience increased hypoxia; 3) having long lifespans and low population growth rates; and/or 4) being of high commercial value combined with impacts from non-climate stressors such as anthropogenic habitat degradation. Species with Low or Moderate vulnerability are either habitat generalists, occupy deep-water habitats or are highly mobile and likely to shift their ranges. Discussion: As climate-related changes intensify, this work provides key information for both scientists and managers as they address the long-term sustainability of fisheries in the region. This information can inform near-term advice for prioritizing species-level data collection and research on climate impacts, help managers to determine when and where a precautionary approach might be warranted, in harvest or other management decisions, and help identify habitats or life history stages that might be especially effective to protect or restore.

Glycosylation has been found to be altered in the brains of individuals with Alzheimer's disease (AD). However, it is unknown which specific glycosylation-related pathways are altered in AD dementia. Using publicly available RNA-seq datasets covering seven brain regions and including 1724 samples, we identified glycosylation-related genes ubiquitously changed in individuals with AD. Several differentially expressed glycosyltransferases found by RNA-seq were confirmed by qPCR in a different set of human medial temporal cortex (MTC) samples (n = 20 AD vs. 20 controls). N-glycan-related changes predicted by expression changes in these glycosyltransferases were confirmed by mass spectrometry (MS)-based N-glycan analysis in the MTC (n = 9 AD vs. 6 controls). About 80% of glycosylation-related genes were differentially expressed in at least one brain region of AD participants (adjusted p-values

The lack of psychometrically sound outcome measures has been a barrier to evaluating the efficacy of treatments proposed for core symptoms of intellectual disability (ID). Research on Expressive Language Sampling (ELS) procedures suggest it is a promising approach to measuring treatment efficacy. ELS entails collecting samples of a participant's talk in interactions with an examiner that are naturalistic but sufficiently structured to ensure consistency and limit examiner effects on the language produced. In this study, we extended previous research on ELS by analyzing an existing dataset to determine whether psychometrically adequate composite scores reflecting multiple dimensions of language can be derived from ELS procedures administered to 6- to 23-year-olds with fragile X syndrome (n = 80) or Down syndrome (n = 78). Data came from ELS conversation and narration procedures administered twice in a 4-week test-retest interval. We found that several composites emerged from variables indexing syntax, vocabulary, planning processes, speech articulation, and talkativeness, although there were some differences in the composites for the two syndromes. Evidence of strong test-retest reliability and construct validity of two of three composites were obtained for each syndrome. Situations in which the composite scores would be useful in evaluating treatment efficacy are outlined.

Research has found that genes specific to microglia are among the strongest risk factors for Alzheimer's disease (AD) and that microglia are critically involved in the etiology of AD. Thus, microglia are an important therapeutic target for novel approaches to the treatment of AD. High-throughput in vitro models to screen molecules for their effectiveness in reversing the pathogenic, pro-inflammatory microglia phenotype are needed. In this study, we used a multi-stimulant approach to test the usefulness of the human microglia cell 3 (HMC3) cell line, immortalized from a human fetal brain-derived primary microglia culture, in duplicating critical aspects of the dysfunctional microglia phenotype. HMC3 microglia were treated with cholesterol (Chol), amyloid beta oligomers (AβO), lipopolysaccharide (LPS), and fructose individually and in combination. HMC3 microglia demonstrated changes in morphology consistent with activation when treated with the combination of Chol + AβO + fructose + LPS. Multiple treatments increased the cellular content of Chol and cholesteryl esters (CE), but only the combination treatment of Chol + AβO + fructose + LPS increased mitochondrial Chol content. Microglia treated with combinations containing Chol + AβO had lower apolipoprotein E (ApoE) secretion, with the combination of Chol + AβO + fructose + LPS having the strongest effect. Combination treatment with Chol + AβO + fructose + LPS also induced APOE and TNF-α expression, reduced ATP production, increased reactive oxygen species (ROS) concentration, and reduced phagocytosis events. These findings suggest that HMC3 microglia treated with the combination of Chol + AβO + fructose + LPS may be a useful high-throughput screening model amenable to testing on 96-well plates to test potential therapeutics to improve microglial function in the context of AD.

Accurate measurement of Alzheimer's disease (AD) pathology in older adults without significant clinical impairment is critical to assessing intervention strategies aimed at slowing AD-related cognitive decline. The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (POINTER) is a 2-year randomized controlled trial to evaluate the effect of multicomponent risk reduction strategies in older adults (60-79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting tau-PET ([18F]MK6240), beta-amyloid (Aβ)-PET ([18F]florbetaben [FBB]) and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at-risk sample. Here 481 participants (70.0±5.0; 66% F) with baseline MK6240, FBB and structural MRI scans were included. PET scans were coregistered to the structural MRI which was used to create FreeSurfer-defined reference regions and target regions of interest (ROIs). We also created off-target signal (OTS) ROIs to examine the magnitude and distribution of MK6240 OTS across the brain as well as relationships between OTS and age, sex, and race. OTS was unimodally distributed, highly correlated across OTS ROIs and related to younger age and sex but not race. Aiming to identify an optimal processing approach for MK6240 that would reduce the influence of OTS, we compared our previously validated MRI-guided standard PET processing and 6 alternative approaches. The alternate approaches included combinations of reference region erosion and meningeal OTS masking before spatial smoothing as well as partial volume correction. To compare processing approaches we examined relationships between target ROIs (entorhinal cortex (ERC), hippocampus or a temporal meta-ROI (MetaROI)) SUVR and age, sex, race, Aβ and a general cognitive status measure, the Modified Telephone Interview for Cognitive Status (TICSm). Overall, the processing approaches performed similarly, and none showed a meaningful improvement over standard processing. Across processing approaches we observed previously reported relationships with MK6240 target ROIs including positive associations with age, an Aβ+> Aβ- effect and negative associations with cognition. In sum, we demonstrated that different methods for minimizing effects of OTS, which is highly correlated across the brain within subject, produced no substantive change in our performance metrics. This is likely because OTS contaminates both reference and target regions and this contamination largely cancels out in SUVR data. Caution should be used when efforts to reduce OTS focus on target or reference regions in isolation as this may exacerbate OTS contamination in SUVR data.

BackgroundTo evaluate the association between the dietary inflammatory index (DII®) and incident cardiovascular disease (CVD) in Hispanic women from the Women's Health Initiative (WHI), and to determine if body mass index (BMI) interacted with the DII scores.MethodsSecondary analysis of baseline dietary data and long-term CVD outcomes among 3,469 postmenopausal women who self-identified as Hispanic enrolled in WHI. DII scores were calculated from self-administered food frequency questionnaires. The CVD outcomes included coronary heart disease (CHD) and stroke. Stratified Cox regression models were used to assess the relationship between DII scores and CVD in women with and without obesity. Models were adjusted for age, lifestyle risk factors, known risk factors, and neighborhood socioeconomic status.ResultsThe incidence of CHD was 3.4 and 2.8% for stroke after a median follow-up of 12.9 years. None of the DIIs were associated with CVD risk in this sample of Hispanic women. BMI interacted with the DII (p

Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change-rather than accurately predict specific outcomes-it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.

BackgroundHispanics are a heterogeneous population with differences in the prevalence of cardiovascular disease (CVD) and its related risk factors among ethnic sub-groups. This study evaluated the association of genetic admixture and CVD in self-identified Hispanic women from the Women's Health Initiative (WHI).MethodsData came from the WHI Observational Study and the Clinical Trial Components conducted among postmenopausal women. The CVD outcomes included coronary heart disease (CHD) and stroke. The proportions of European (EUR), sub-Saharan African (AFR), and Amerindian (AMI) admixture were estimated using 92 ancestry-informative markers. Cox regression models were used to assess the relationship between genetic admixture and CVD adjusting for age, lifestyle risk factors, known risk factors, and neighborhood socioeconomic status.ResultsAmong 5195 participants EUR ancestry was associated with a lower CHD risk after adjusting for age (HR 0.41, p = 0.02), and in the fully adjusted model (HR 0.40, p = 0.03). AFR ancestry was associated with a higher CHD risk after adjusting for age (HR 2.91, p = 0.03), but it only showed a trend in in the fully adjusted model (HR 2.46, p = 0.10). AMI ancestry was not statistically significantly associated with CHD and none of the genetic admixture proportions were statistically significantly associated with stroke (p > 0.05).ConclusionEUR ancestry was associated with a lower risk of CHD in Hispanic women. This highlights the need to account for genetic admixture in future CVD studies to consider different heritage groups to understand the role that genetic, neighborhood socioeconomic status, and environmental factors contribute to CVD health disparities in Hispanic women.

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

In planning randomized clinical trials (RCTs) for diseases such as Alzheimer's disease (AD), researchers frequently rely on the use of existing data obtained from only two time points to estimate sample size via the subtraction of baseline from follow-up measurements in each subject. However, the inadequacy of this method has not been reported. The aim of this study is to discuss the limitation of sample size estimation based on the subtraction of available data from only two time points for RCTs. Mathematical equations are derived to demonstrate the condition under which the obtained data pairs with variable time intervals could be used to adequately estimate sample size. The MRI-based hippocampal volume measurements from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Monte Carlo simulations (MCS) were used to illustrate the existing bias and variability of estimates. MCS results support the theoretically derived condition under which the subtraction approach may work. MCS also show the systematically under- or over-estimated sample sizes by up to 32.27 % bias. Not used properly, such subtraction approach outputs the same sample size regardless of trial durations partly due to the way measurement errors are handled. Estimating sample size by subtracting two measurements should be treated with caution. Such estimates can be biased, the magnitude of which depends on the planned RCT duration. To estimate sample sizes, we recommend using more than two measurements and more comprehensive approaches such as linear mixed effect models.