Early chronic suppression of microglial p38α in a model of Alzheimer's disease does not significantly alter amyloid-associated neuropathology.

The p38 alpha mitogen-activated protein kinase (p38α) is linked to both innate and adaptive immune responses and is under investigation as a target for drug development in the context of Alzheimer's disease (AD) and other conditions with neuroinflammatory dysfunction. While preclinical data has shown that p38α inhibition can protect against AD-associated neuropathology, the underlying mechanisms are not fully elucidated. Inhibitors of p38α may provide benefit via modulation of microglial-associated neuroinflammatory responses that contribute to AD pathology. The present study tests this hypothesis by knocking out microglial p38α and assessing early-stage pathological changes. Conditional knockout of microglial p38α was accomplished in 5-month-old C57BL/6J wild-type and amyloidogenic AD model (APPswe/PS1dE9) mice using a tamoxifen-inducible Cre/loxP system under control of the Cx3cr1 promoter. Beginning at 7.5 months of age, animals underwent behavioral assessment on the open field, followed by a later radial arm water maze test and collection of cortical and hippocampal tissues at 11 months. Additional endpoint measures included quantification of proinflammatory cytokines, assessment of amyloid burden and plaque deposition, and characterization of microglia-plaque dynamics. Loss of microglial p38α did not alter behavioral outcomes, proinflammatory cytokine levels, or overall amyloid plaque burden. However, this manipulation did significantly increase hippocampal levels of soluble Aß42 and reduce colocalization of Iba1 and 6E10 in a subset of microglia in close proximity to plaques. The data presented here suggest that rather than reducing inflammation per se, the net effect of microglial p38α inhibition in the context of early AD-type amyloid pathology is a subtle alteration of microglia-plaque interactions. Encouragingly from a therapeutic standpoint, these data suggest no detrimental effect of even substantial decreases in microglial p38α in this context. Additionally, these results support future investigations of microglial p38α signaling at different stages of disease, as well as its relationship to phagocytic processes in this particular cell-type.

Exogenous Short Chain Fatty Acid Effects in APP/PS1 Mice.

Elucidating the impact of the gut microbiome on Alzheimer's Disease (AD) is an area of intense interest. Short chain fatty acids (SCFAs) are major microbiota metabolites that have been implicated as a mediator of gut microbiome effects in the brain. Here, we tested the effects of SCFA-treated water vs. saline-treated water on APPswe/PSEN1dE9 mice maintained under standard laboratory conditions. Mice were treated with SCFAs from five months of age until ten months of age, when they were evaluated for microbiome profile, impaired spatial memory as evaluated with the radial arm water maze, astrocyte activation as measured by Gfap expression and amyloid burden as assessed by histochemistry and MSD ELISA. We report that SCFA treatment increased alpha-diversity and impacted the gut microbiome profile by increasing, in part, the relative abundance of several bacteria that typically produce SCFAs. However, SCFA treatment did not significantly affect behavior. Similarly, SCFAs did not affect cortical or hippocampal astrocyte activation observed in the APP/PS1 mice. Lastly, although robust levels of soluble and insoluble amyloid were present in the APP/PS1 mice, SCFA treatment had no effect on these indices. Overall, our findings are that SCFA treatment modifies the microbiome in a fashion that may increase further SCFA production. However, SCFA treatment did not alter behavior, astrocyte activation, nor amyloid neuropathology in APP/PS1 mice maintained with a conventional microbiome.

Theory of Fast Walking With Human-Driven Load-Carrying Robot Exoskeletons.

Reaching and maintaining high walking speeds is challenging for a human when carrying extra weight, such as walking with a heavy backpack. Robotic limbs can support a heavy backpack when standing still, but accelerating a backpack within a couple of steps to race-walking speeds requires limb force and energy beyond natural human ability. Here, we conceive a human-driven robot exoskeleton that could accelerate a heavy backpack faster and maintain top speeds higher than what the human alone can when not carrying a backpack. The key components of the exoskeleton are the mechanically adaptive but energetically passive spring limbs. We show that by optimally adapting the stiffness of the limbs, the robot can achieve near-horizontal center of mass motion to emulate the load-bearing mechanics of the bicycle. We find that such an exoskeleton could enable the human to accelerate one extra body weight up to top race-walking speeds in ten steps. Our finding predicts that human-driven mechanically adaptive robot exoskeletons could extend human weight-bearing and fast-walking ability without using external energy.

Therapeutic treatment with the anti-inflammatory drug candidate MW151 may partially reduce memory impairment and normalizes hippocampal metabolic markers in a mouse model of comorbid amyloid and vascular pathology.

Alzheimer's disease (AD) is the leading cause of dementia in the elderly, but therapeutic options are lacking. Despite long being able to effectively treat the ill-effects of pathology present in various rodent models of AD, translation of these strategies to the clinic has so far been disappointing. One potential contributor to this situation is the fact that the vast majority of AD patients have other dementia-contributing comorbid pathologies, the most common of which are vascular in nature. This situation is modeled relatively infrequently in basic AD research, and almost never in preclinical studies. As part of our efforts to develop small molecule, anti-inflammatory therapeutics for neurological injury and disease, we have recently been exploring potentially promising treatments in preclinical multi-morbidity contexts. In the present study, we generated a mouse model of mixed amyloid and hyperhomocysteinemia (HHcy) pathology in which to test the efficacy of one of our anti-inflammatory compounds, MW151. HHcy can cause cerebrovascular damage and is an independent risk factor for both AD dementia and vascular contributions to cognitive impairment and dementia. We found that MW151 was able to partially rescue hippocampal-dependent spatial memory and learning deficits in this comorbidity context, and further, that the benefit is associated with a normalization of hippocampal metabolites detectable via magnetic resonance spectroscopy. These findings provide evidence that MW151 in particular, and potentially anti-inflammatory treatment more generally, may be beneficial in AD patients with comorbid vascular pathology.

Microglial-associated responses to comorbid amyloid pathology and hyperhomocysteinemia in an aged knock-in mouse model of Alzheimer's disease.

BACKGROUND: Elevated blood homocysteine levels, termed hyperhomocysteinemia (HHcy), is a prevalent risk factor for Alzheimer's disease (AD) in elderly populations. While dietary supplementation of B-vitamins is a generally effective method to lower homocysteine levels, there is little if any benefit to cognition. In the context of amyloid pathology, dietary-induced HHcy is known to enhance amyloid deposition and certain inflammatory responses. Little is known, however, about whether there is a more specific effect on microglia resulting from combined amyloid and HHcy pathologies. METHODS: The present study used a knock-in mouse model of amyloidosis, aged to 12 months, given 8 weeks of B-vitamin deficiency-induced HHcy to better understand how microglia are affected in this comorbidity context. RESULTS: We found that HHcy-inducing diet increased amyloid plaque burden, altered the neuroinflammatory milieu, and upregulated the expression of multiple damage-associated and "homeostatic" microglial genes. CONCLUSIONS: Taken together, these data indicate complex effects of comorbid pathologies on microglial function that are not driven solely by increased amyloid burden. Given the highly dynamic nature of microglia, their central role in AD pathology, and the frequent occurrence of various comorbidities in AD patients, it is increasingly important to understand how microglia respond to mixed pathological processes.

Optimization and validation of a modified radial-arm water maze protocol using a murine model of mild closed head traumatic brain injury.

Cognitive impairments can be a significant problem after a traumatic brain injury (TBI), which affects millions worldwide each year. There is a need for establish reproducible cognitive assays in rodents to better understand disease mechanisms and to develop therapeutic interventions towards treating TBI-induced impairments. Our goal was to validate and standardize the radial arm water maze (RAWM) test as an assay to screen for cognitive impairments caused by TBI. RAWM is a visuo-spatial learning test, originally designed for use with rats, and later adapted for mice. The present study investigates whether test procedures, such us the presence of extra-maze cues influences learning and memory performance. C57BL/6 mice were tested in an 8-arm RAWM using a four-day protocol. We demonstrated that two days of training, exposing the mice to extra-maze cues and a visible platform, influenced learning and memory performance. Mice that did not receive training performed poorer compared to mice trained. To further validate our RAWM protocol, we used scopolamine. We, also, demonstrated that a single mild closed head injury (CHI) caused deficits in this task at two weeks post-CHI. Our data supported the use of 7 trials per day and a spaced training protocol as key factor to unmask memory impairment following CHI. Here, we provide a detailed standard operating procedure for RAWM test, which can be applied to a variety of mouse models including neurodegenerative diseases and pathology, as well as when pharmacological approaches are used.

How to run 50% faster without external energy.

Technological innovations may enable next-generation running shoes to provide unprecedented mobility. But how could a running shoe increase the speed of motion without providing external energy? We found that the top speed of running may be increased more than 50% using a catapult-like exoskeleton device, which does not provide external energy. Our finding uncovers the hidden potential of human performance augmentation via unpowered robotic exoskeletons. Our result may lead to a new-generation of augmentation devices developed for sports, rescue operations, and law enforcement, where humans could benefit from increased speed of motion.

Multiphase and Multivariable Linear Controllers That Account for the Joint Torques in Normal Human Walking.

OBJECTIVE: The objective of this paper is to investigate whether a small number of sequentially composed multivariable linear controllers can be used to recover a defining relation between the joint torques, angles, and velocities hidden in the walking data of multiple human subjects. METHODS: We solve a mixed integer programming problem that defines the optimal multivariable and multiphase relation between the torques, angles, and velocities for the hip, knee, and ankle joints. RESULTS: Using the data of seven healthy subjects, we show that the aforementioned relation can be remarkably well represented by four sequentially composed and independently activated multivariable linear controllers; the controllers account for [Formula: see text] (mean ± sem) of the variance in the joint torques across subjects, and [Formula: see text] of the variance for a new subject. We further show that each controller is associated with one of the four phases of the gait cycle, separated by toe-off and heel-strike. CONCLUSION: The proposed controller generalizes previously developed multiphase single variable, and single phase multivariable controllers, to a multiphase multivariable controller that better explains the walking data of multiple subjects, and better generalizes to new subjects. SIGNIFICANCE: Our result provides strong support to extend previously developed decoupled single joint controllers to coupled multijoint multivariable controllers for the control of human assistive and augmentation devices.

Genetic knockout of myosin light chain kinase (MLCK210) prevents cerebral microhemorrhages and attenuates neuroinflammation in a mouse model of vascular cognitive impairment and dementia.

The blood-brain barrier (BBB) is critical in maintenance of brain homeostasis, and loss of its functional integrity is a key feature across a broad range of neurological insults. This includes both acute injuries such as traumatic brain injury and stroke, as well as more chronic pathologies associated with aging, such as vascular cognitive impairment and dementia (VCID). A specific form of myosin light chain kinase (MLCK210) is a major regulator of barrier integrity in general, including the BBB. Studies have demonstrated the potential of MLCK210 as a therapeutic target for peripheral disorders involving tissue barrier dysfunction, but less is known about its potential as a target for chronic neurologic disorders. We report here that genetic knockout (KO) of MLCK210 protects against cerebral microhemorrhages and neuroinflammation induced by chronic dietary hyperhomocysteinemia. Overall, the results are consistent with an accumulating body of evidence supporting MLCK210 as a potential therapeutic target for tissue barrier dysfunction and specifically implicate it in BBB dysfunction and neuroinflammation in a model of VCID.

Enhancing Mobility With Quasi-Passive Variable Stiffness Exoskeletons.

Shoes were invented to provide user comfort using rubber soles, despite marginal improvement in human mobility. Unlike shoes, current lower-limb exoskeletons use fixed stiffness springs to store and recycle energy to improve mobility. However, the maximum kinetic energy a human can accumulate when augmented with a fixed stiffness spring is limited by the maximum deflection and the ability of the limbs to generate force; tying the advantage of fixed stiffness exoskeletons to biological constraints. Here, we propose a method for improving mobility using quasi-passive variable stiffness spring exoskeletons, where the maximum kinetic energy accumulated by a human is independent of the limb deflection and the ability of the limb to generate force. This is achieved by a variable stiffness augmentation of the human, where the exoskeleton does not provide mechanical work. The theoretical advantage provided by this new augmentation method can be useful in demanding tasks, where humans could benefit from increased speed and reduced energy cost of motion.

A Phase-Invariant Linear Torque-Angle-Velocity Relation Hidden in Human Walking Data.

Human walking is a sequential composition of gait cycles. Each gait cycle can be divided into four motion phases separated by heel strike and toe off. A classical conjecture in the control of lower limb assistive devices, state-of-the-art prostheses, and exoskeletons, is that each motion phase requires a different controller, such that adequate control of locomotion requires at least four distinct controllers. In this paper, we show that the joint torque versus joint angle and velocity relation hidden in the normal human walking data can be remarkably well represented with a single linear controller. In particular, based on the analysis of seven healthy subjects, we show that a one phase 20±5% sparse linear relation between the joint torques, angles and velocities explains 96.1±0.4% (mean±sem) of the normal human walking data (sparsity defines the percentage of zero control parameters). This result is comparable to what can be achieved using a significantly more complex four-phase non-sparse linear controller which explains 98.7±0.2% of the walking data, and is significantly better than a one-phase fully sparsified linear controller that could only explain 11.9±0.2% of the same data. Based on these results, we posit that the proposed phase-invariant sparse linear controller provides one of the simplest representations that can adequately explain the joint torque, angle and velocity relation present in the human walking data. The resulting control structure may be useful in developing simple yet competent phase-invariant controllers for next-generation prostheses and exoskeleton devices used for human assistance and augmentation.

In vivo Brainstem Imaging in Alzheimer's Disease: Potential for Biomarker Development.

The dearth of effective treatments for Alzheimer's disease (AD) is one of the largest public health issues worldwide, costing hundreds of billions of dollars per year. From a therapeutic standpoint, research efforts to date have met with strikingly little clinical success. One major issue is that trials begin after substantial pathological change has occurred, and it is increasingly clear that the most effective treatment regimens will need to be administered earlier in the disease process. In order to identify individuals within the long preclinical phase of AD who are likely to progress to dementia, improvements are required in biomarker development. One potential area of research that might prove fruitful in this regard is the in vivo detection of brainstem pathology. The brainstem is known to undergo pathological changes very early and progressively in AD. With an updated and harmonized AD research framework, and emerging advances in neuroimaging technology, the potential to leverage knowledge of brainstem pathology into biomarkers for AD will be discussed.

Sex-related responses after traumatic brain injury: Considerations for preclinical modeling.

Traumatic brain injury (TBI) has historically been viewed as a primarily male problem, since men are more likely to experience a TBI because of more frequent participation in activities that increase risk of head injuries. This male bias is also reflected in preclinical research where mostly male animals have been used in basic and translational science. However, with an aging population in which TBI incidence is increasingly sex-independent due to falls, and increasing female participation in high-risk activities, the attention to potential sex differences in TBI responses and outcomes will become more important. These considerations are especially relevant in designing preclinical animal models of TBI that are more predictive of human responses and outcomes. This review characterizes sex differences following TBI with a special emphasis on the contribution of the female sex hormones, progesterone and estrogen, to these differences. This information is potentially important in developing and customizing TBI treatments.

Conditional Depletion of Hippocampal Brain-Derived Neurotrophic Factor Exacerbates Neuropathology in a Mouse Model of Alzheimer's Disease.

Damage occurring to noradrenergic neurons in the locus coeruleus (LC) contributes to the evolution of neuroinflammation and neurodegeneration in a variety of conditions and diseases. One cause of LC damage may be loss of neurotrophic support from LC target regions. We tested this hypothesis by conditional unilateral knockout of brain-derived neurotrophic factor (BDNF) in adult mice. To evaluate the consequences of BDNF loss in the context of neurodegeneration, the mice harbored familial mutations for human amyloid precursor protein and presenilin-1. In these mice, BDNF depletion reduced tyrosine hydroxylase staining, a marker of noradrenergic neurons, in the rostral LC. BDNF depletion also reduced noradrenergic innervation in the hippocampus, the frontal cortex, and molecular layer of the cerebellum, assessed by staining for dopamine beta hydroxylase. BDNF depletion led to an increase in cortical amyloid plaque numbers and size but was without effect on plaque numbers in the striatum, a site with minimal innervation from the LC. Interestingly, cortical Iba1 staining for microglia was reduced by BDNF depletion and was correlated with reduced dopamine beta hydroxylase staining. These data demonstrate that reduction of BDNF levels in an LC target region can cause retrograde damage to LC neurons, leading to exacerbation of neuropathology in distinct LC target areas. Methods to reduce BDNF loss or supplement BDNF levels may be of value to reduce neurodegenerative processes normally limited by LC noradrenergic activities.

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information.

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Optimal Parametric Feedback Excitation of Nonlinear Oscillators.

An optimal parametric feedback excitation principle is sought, found, and investigated. The principle is shown to provide an adaptive resonance condition that enables unprecedentedly robust movement generation in a large class of oscillatory dynamical systems. Experimental demonstration of the theory is provided by a nonlinear electronic circuit that realizes self-adaptive parametric excitation without model information, signal processing, and control computation. The observed behavior dramatically differs from the one achievable using classical parametric modulation, which is fundamentally limited by uncertainties in model information and nonlinear effects inevitably present in real world applications.

Adaptive steady-state stabilization for nonlinear dynamical systems.

By means of LaSalle's invariance principle, we propose an adaptive controller with the aim of stabilizing an unstable steady state for a wide class of nonlinear dynamical systems. The control technique does not require analytical knowledge of the system dynamics and operates without any explicit knowledge of the desired steady-state position. The control input is achieved using only system states with no computer analysis of the dynamics. The proposed strategy is tested on Lorentz, van der Pol, and pendulum equations.