Hippocampus of the APPNL-G-F mouse model of Alzheimer’s disease exhibits region-specific tissue softening concomitant with elevated astrogliosis

Widespread neurodegeneration, enlargement of cerebral ventricles, and atrophy of cortical and hippocampal brain structures are classic hallmarks of Alzheimer’s disease (AD). Prominent macroscopic disturbances to the cytoarchitecture of the AD brain occur alongside changes in the mechanical properties of brain tissue, as reported in recent magnetic resonance elastography (MRE) measurements of human brain mechanics. Whilst MRE has many advantages, a significant shortcoming is its spatial resolution. Higher resolution “cellular scale” assessment of the mechanical alterations to brain regions involved in memory formation, such as the hippocampus, could provide fresh new insight into the etiology of AD. Characterization of brain tissue mechanics at the cellular length scale is the first stepping-stone to understanding how mechanosensitive neurons and glia are impacted by neurodegenerative disease-associated changes in their microenvironment. To provide insight into the microscale mechanics of aging brain tissue, we measured spatiotemporal changes in the mechanical properties of the hippocampus using high resolution atomic force microscopy (AFM) indentation tests on acute brain slices from young and aged wild-type mice and the APPNL–G–F mouse model. Several hippocampal regions in APPNL–G–F mice are significantly softer than age-matched wild-types, notably the dentate granule cell layer and the CA1 pyramidal cell layer. Interestingly, regional softening coincides with an increase in astrocyte reactivity, suggesting that amyloid pathology-mediated alterations to the mechanical properties of brain tissue may impact the function of mechanosensitive astrocytes. Our data also raise questions as to whether aberrant mechanotransduction signaling could impact the susceptibility of neurons to cellular stressors in their microenvironment

Comparison of Supine and Vertical Bioimpedance Measurements in Young Adults

Topics in Exercise Science and Kinesiology Volume 3: Issue 1, Article 11, 2022. Bioelectrical impedance analysis (BIA) methods estimate health parameters such as phase angle (PhA) and body fat percentage (%BF) from various positional and electrode configurations. PhA and %BF are known biological markers of cellular and physical health, respectively, and can be used to predict various health-related conditions and therefore require accurate assessment. The purpose of this study was to evaluate the effect of body position during BIA by investigating the difference and agreement between PhA and %BF using RJL (supine) and InBody (vertical) analyzers. Thirty-eight young adults (23.4±4.1 yrs.) volunteered and underwent body composition assessments by both analyzers. Difference and agreement in assessments of PhA and %BF between analyzers were assessed using paired samples t-tests and Lin’s concordance correlation coefficient (rc), respectively. RJL’s PhA (7.15±0.84°) exceeded InBody’s (6.11±0.74°), p\u3c0.001, and had poor agreement (rc =0.47). RJL’s %BF (23.0±6.8%) was similar to InBody’s (23.1±7.4%), p=0.813, and had substantial agreement (rc =0.95). Both analyzers estimated %BF similarly and may be interchangeable for this purpose, thus demonstrating no effect of body position on the estimation of %BF with these BIA devices. An individual\u27s PhA may be underestimated if measured in the vertical position and compared to supine reference values. Current reference values for PhA are based on measurements in the supine position, so until vertical reference values of PhA are available, caution is urged when interpreting PhA from vertical BIA assessments

Mechanobiology of the brain in ageing and Alzheimer's disease

Just as the epigenome, the proteome and the electrophysiological properties of a cell influence its function, so too do its intrinsic mechanical properties and its extrinsic mechanical environment. This is especially true for neurons of the central nervous system (CNS) as long‐term maintenance of synaptic connections relies on efficient axonal transport machinery and structural stability of the cytoskeleton. Recent reports suggest that profound physical changes occur in the CNS microenvironment with advancing age which, in turn, will impact highly mechanoresponsive neurons and glial cells. Here, we discuss the complex and inhomogeneous mechanical structure of CNS tissue, as revealed by recent mechanical measurements on the brain and spinal cord, using techniques such as magnetic resonance elastography and atomic force microscopy. Moreover, ageing, traumatic brain injury, demyelination and neurodegeneration can perturb the mechanical properties of brain tissue and trigger mechanobiological signalling pathways in neurons, glia and cerebral vasculature. It is, therefore, very likely that significant changes in cell and tissue mechanics contribute to age‐related cognitive decline and deficits in memory formation which are accelerated and magnified in neurodegenerative states, such as Alzheimer's disease. Importantly, we are now beginning to understand how neuronal and glial cell mechanics and brain tissue mechanobiology are intimately linked with neurophysiology and cognition

Hippocampus of the APPNL–G–F mouse model of Alzheimer’s disease exhibits region-specific tissue softening concomitant with elevated astrogliosis

Widespread neurodegeneration, enlargement of cerebral ventricles, and atrophy of cortical and hippocampal brain structures are classic hallmarks of Alzheimer’s disease (AD). Prominent macroscopic disturbances to the cytoarchitecture of the AD brain occur alongside changes in the mechanical properties of brain tissue, as reported in recent magnetic resonance elastography (MRE) measurements of human brain mechanics. Whilst MRE has many advantages, a significant shortcoming is its spatial resolution. Higher resolution “cellular scale” assessment of the mechanical alterations to brain regions involved in memory formation, such as the hippocampus, could provide fresh new insight into the etiology of AD. Characterization of brain tissue mechanics at the cellular length scale is the first stepping-stone to understanding how mechanosensitive neurons and glia are impacted by neurodegenerative disease-associated changes in their microenvironment. To provide insight into the microscale mechanics of aging brain tissue, we measured spatiotemporal changes in the mechanical properties of the hippocampus using high resolution atomic force microscopy (AFM) indentation tests on acute brain slices from young and aged wild-type mice and the APPNL–G–F mouse model. Several hippocampal regions in APPNL–G–F mice are significantly softer than age-matched wild-types, notably the dentate granule cell layer and the CA1 pyramidal cell layer. Interestingly, regional softening coincides with an increase in astrocyte reactivity, suggesting that amyloid pathology-mediated alterations to the mechanical properties of brain tissue may impact the function of mechanosensitive astrocytes. Our data also raise questions as to whether aberrant mechanotransduction signaling could impact the susceptibility of neurons to cellular stressors in their microenvironment

FACET: Fairness in Computer Vision Evaluation Benchmark

Computer vision models have known performance disparities across attributes such as gender and skin tone. This means during tasks such as classification and detection, model performance differs for certain classes based on the demographics of the people in the image. These disparities have been shown to exist, but until now there has not been a unified approach to measure these differences for common use-cases of computer vision models. We present a new benchmark named FACET (FAirness in Computer Vision EvaluaTion), a large, publicly available evaluation set of 32k images for some of the most common vision tasks - image classification, object detection and segmentation. For every image in FACET, we hired expert reviewers to manually annotate person-related attributes such as perceived skin tone and hair type, manually draw bounding boxes and label fine-grained person-related classes such as disk jockey or guitarist. In addition, we use FACET to benchmark state-of-the-art vision models and present a deeper understanding of potential performance disparities and challenges across sensitive demographic attributes. With the exhaustive annotations collected, we probe models using single demographics attributes as well as multiple attributes using an intersectional approach (e.g. hair color and perceived skin tone). Our results show that classification, detection, segmentation, and visual grounding models exhibit performance disparities across demographic attributes and intersections of attributes. These harms suggest that not all people represented in datasets receive fair and equitable treatment in these vision tasks. We hope current and future results using our benchmark will contribute to fairer, more robust vision models. FACET is available publicly at https://facet.metademolab.com

Evaluating the relation between ADHD symptoms and externalizing behaviors in children with Autism Spectrum Disorder

The risk for externalizing behaviors (Bos et al., 2018) complicates the comorbidity between autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). To investigate whether the relation between ASD status (ASD vs typical development, TD) and externalizing behaviors would vary by differences in ADHD symptoms, parent-child dyads (3-7yo), 127 TD (47.7% female) and 81 children with ASD (16.7% female), participated. The linear regression tested model with significant main and interaction effects explained 43.3% of variance, overall. Consistent with research, externalizing problems were higher for both groups when ADHD symptoms were also high compared to low, an effect stronger for TD children

Nonmalleable Digital Lockers and Robust Fuzzy Extractors in the Plain Model

We give the first constructions in the plain model of 1) nonmalleable digital lockers (Canetti and Varia, TCC 2009) and 2) robust fuzzy extractors (Boyen et al., Eurocrypt 2005) that secure sources with entropy below 1/2 of their length. Constructions were previously only known for both primitives assuming random oracles or a common reference string (CRS). Along the way, we define a new primitive called a nonmalleable point function obfuscation with associated data. The associated data is public but protected from all tampering. We use the same paradigm to then extend this to digital lockers. Our constructions achieve nonmalleability over the output point by placing a CRS into the associated data and using an appropriate non-interactive zero-knowledge proof. Tampering is protected against the input point over low-degree polynomials and over any tampering to the output point and associated data. Our constructions achieve virtual black box security. These constructions are then used to create robust fuzzy extractors that can support low-entropy sources in the plain model. By using the geometric structure of a syndrome secure sketch (Dodis et al., SIAM Journal on Computing 2008), the adversary’s tampering function can always be expressed as a low-degree polynomial; thus, the protection provided by the constructed nonmalleable objects suffices