Transcriptional profiling predicts running promotes cerebrovascular remodeling in young but not midlife mice.

BACKGROUND: The incidence of dementia and cognitive decline is increasing with no therapy or cure. One of the reasons treatment remains elusive is because there are various pathologies that contribute to age-related cognitive decline. Specifically, with Alzheimer\u27s disease, targeting to reduce amyloid beta plaques and phosphorylated tau aggregates in clinical trials has not yielded results to slow symptomology, suggesting a new approach is needed. Interestingly, exercise has been proposed as a potential therapeutic intervention to improve brain health and reduce the risk for dementia, however the benefits throughout aging are not well understood. RESULTS: To better understand the effects of exercise, we preformed transcriptional profiling on young (1-2 months) and midlife (12 months) C57BL/6 J (B6) male mice after 12 weeks of voluntary running. Data was compared to age-matched sedentary controls. Interestingly, the midlife running group naturally broke into two cohorts based on distance ran - either running a lot and more intensely (high runners) or running less and less intensely (low runners). Midlife high runners had lower LDL cholesterol as well as lower adiposity (%fat) compared to sedentary, than midlife low runners compared to sedentary suggesting more intense running lowered systemic markers of risk for age-related diseases including dementias. Differential gene analysis of transcriptional profiles generated from the cortex and hippocampus showed thousands of differentially expressed (DE) genes when comparing young runners to sedentary controls. However, only a few hundred genes were DE comparing either midlife high runners or midlife low runners to midlife sedentary controls. This indicates that, in our study, the effects of running are reduced through aging. Gene set enrichment analyses identified enrichment of genes involved in extracellular matrix (ECM), vascular remodeling and angiogenesis in young runners but not midlife runners. These genes are known to be expressed in multiple vascular-related cell types including astrocytes, endothelial cells, pericytes and smooth muscle cells. CONCLUSIONS: Taken together these results suggest running may best serve as a preventative measure to reduce risk for cerebrovascular decline. Ultimately, this work shows that exercise may be more effective to prevent dementia if introduced at younger ages

Transcriptional control of retinal ganglion cell death after axonal injury.

Injury to the axons of retinal ganglion cells (RGCs) is a key pathological event in glaucomatous neurodegeneration. The transcription factors JUN (the target of the c-Jun N-terminal kinases, JNKs) and DDIT3/CHOP (a mediator of the endoplasmic reticulum stress response) have been shown to control the majority of proapoptotic signaling after mechanical axonal injury in RGCs and in other models of neurodegeneration. The downstream transcriptional networks controlled by JUN and DDIT3, which are critical for RGC death, however, are not well defined. To determine these networks, RNA was isolated from the retinas of wild-type mice and mice deficient in Jun, Ddit3, and both Jun and Ddit3 three days after mechanical optic nerve crush injury (CONC). RNA-sequencing data analysis was performed and immunohistochemistry was used to validate potential transcriptional signaling changes after axonal injury. This study identified downstream transcriptional changes after injury including both neuronal survival and proinflammatory signaling that were attenuated to differing degrees by loss of Ddit3, Jun, and Ddit3/Jun. These data suggest proinflammatory signaling in the retina might be secondary to activation of pro-death pathways in RGCs after acute axonal injury. These results determine the downstream transcriptional networks important for apoptotic signaling which may be important for ordering and staging the pro-degenerative signals after mechanical axonal injury

Transcriptome profiling of brain myeloid cells revealed activation of Itgal, Trem1, and Spp1 in western diet-induced obesity.

BACKGROUND: Environmental factors are critical in the development of age-related cognitive decline and dementia. A western diet (WD) can cause nutrient deficiency and inflammation that could impact cognition directly. It is increasingly recognized that innate immune responses by brain myeloid cells, such as resident microglia, and infiltrating peripheral monocytes/macrophages may represent an essential link between a WD, cognitive decline, and dementia. Our previous data demonstrated that chronic consumption of a WD induced inflammation through brain myeloid cells in aging mice and a mouse model of Alzheimer\u27s disease (AD). However, the subtypes of myeloid cells that contribute to the WD-induced inflammation remain unclear. METHODS: C57BL/6J (B6), myeloid cell reporter mice (B6.Ccr2 RESULTS: Ccr2::RFP expressing myeloid cells were significantly increased in brains of WD- compared to CD-fed mice, but were not elevated in Ccr2-deficient WD-fed mice. The percent of CD11b+CD45 CONCLUSIONS: These data further support the model that peripheral myeloid cells enter the brain in response to diet-induced obesity. Elucidating their contribution to age-related cognitive decline and age-related neurodegenerative diseases should offer new avenues for therapeutic intervention in Alzheimer\u27s disease and related dementias, where diet/obesity are major risk factors

PARK16 rs708730 Polymorphism Decreases Parkinson’s Disease Risk in European Ancestry Population: A Meta-analysis

Parkinson’s disease (PD) is a complex fatal chronic neurodegenerative disease most common in elderly people. The early genome-wide association studies (GWAS) found that the minor allele variant of PARK16 rs708730 polymorphism is a significant protective factor for PD in Caucasian populations. However, these results cannot be repeated by the following studies in Caucasian populations and other populations. We considered that the inconsistency of the findings may be caused by the small-scale samples or the heterogeneity among different populations. Therefore, in this study, we synthesized the previous related GWAS studies through three authoritative sources, and used the large-scale samples (10,645 PD cases and 30,499 controls) to reevaluate the association between rs708730 polymorphism and PD. The results showed that there is no association between them in Asian ancestry population. While, in European ancestry population, we found that the minor allele variant (G) of rs708730 polymorphism is significantly associated with a decreased risk of PD. Collectively, our findings further verified the association of rs708730 with PD and show its genetic heterogeneity among different populations, which can help to develop a better understanding of the PD’s pathogenesis

Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer\u27s disease.

Genetic and genome-wide association studies suggest a central role for microglia in Alzheimer\u27s disease (AD). However, single-cell RNA sequencing (scRNA-seq) of microglia in mice, a key preclinical model, has shown mixed results regarding translatability to human studies. To address this, scRNA-seq of microglia from C57BL/6J (B6) and wild-derived strains (WSB/EiJ, CAST/EiJ, and PWK/PhJ) with and without APP/PS1 demonstrates that genetic diversity significantly alters features and dynamics of microglia in baseline neuroimmune functions and in response to amyloidosis. Results show significant variation in the abundance of microglial subtypes or states, including numbers of previously identified disease-associated and interferon-responding microglia, across the strains. For each subtype, significant differences in the expression of many genes are observed in wild-derived strains relative to B6, including 19 genes previously associated with human AD including Apoe, Trem2, and Sorl1. This resource is critical in the development of appropriately targeted therapeutics for AD and other neurological diseases

Three-dimensional reconstruction optimization of tunnel face and intelligent extraction of discontinuity orientation based on binocular stereo vision

In the process of grading and dynamically optimizing the design and construction parameters of the surrounding rock mass of a rock tunnel face, efficiently and accurately acquiring the geometrical parameters of the rock discontinuities is an important basic task. To address the problems of time consuming, low accuracy, and high danger associated with traditional methods of obtaining the structural information of rock mass, this paper proposes a method for three-dimensional reconstruction and intelligent information extraction of tunnel face based on binocular stereo vision (BSV). First, the parallel binocular device with a single camera was improved, calibrated using the checkerboard calibration method. By integrating with the semi-global matching algorithm, the BSV based method for the three-dimensional reconstruction of the rock mass of the tunnel face was optimized. Furthermore, based on the results from on-site engineering applications, this study leveraged two parameters, point cloud density and algorithm runtime, to determine the optimal values for the disparity range and window size parameters within the semi-global stereo matching algorithm. This enhancement improved the performance of the 3D reconstruction method based on binocular stereo vision. Finally, efficient and refined intelligent methods for extracting structural parameters of the rock mass were proposed based on k-nearest neighbor search and kernel density estimation. The research results can provide reliable technical support for the intelligent and efficient acquisition of rock mass structural information in rock tunnel engineering faces

Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer\u27s disease progression.

Introduction: Genome-wide association studies (GWAS) for late onset Alzheimer\u27s disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity. Methods: We use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer\u27s Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression. Results: CNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, Discussion: This is the first attempt to show that non-invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring

Selenium-Containing Polysaccharide-Protein Complex in Se-Enriched Ulva fasciata Induces Mitochondria-Mediated Apoptosis in A549 Human Lung Cancer Cells

The role of selenium (Se) and Ulva fasciata as potent cancer chemopreventive and chemotherapeutic agents has been supported by epidemiological, preclinical, and clinical studies. In this study, Se-containing polysaccharide-protein complex (Se-PPC), a novel organoselenium compound, a Se-containing polysaccharide-protein complex in Se-enriched Ulva fasciata, is a potent anti-proliferative agent against human lung cancer A549 cells. Se-PPC markedly inhibited the growth of cancer cells via induction of apoptosis which was accompanied by the formation of apoptotic bodies, an increase in the population of apoptotic sub-G1 phase cells, upregulation of p53, and activation of caspase-3 in A549 cells. Further investigation on intracellular mechanisms indicated that cytochrome C was released from mitochondria into cytosol in A549 cells after Se-PPC treatment. Se-PPC induced depletion of mitochondrial membrane potential (ΔΨm) in A549 cells through regulating the expression of anti-apoptotic (Bcl-2, Bcl-XL) and pro-apoptotic (Bax, Bid) proteins, resulting in disruption of the activation of caspase-9. This is the first report to demonstrate the cytotoxic effect of Se-PPC on human cancer cells and to provide a possible mechanism for this activity. Thus, Se-PPC is a promising novel organoselenium compound with potential to treat human cancers

Data-Driven Optimal Test Selection Design for Fault Detection and Isolation Based on CCVKL Method and PSO

International audienceAccurate fault detection and isolation (FDI) relies on the information collection. This can be done by the optimal test selection which can also reduce the life cost of engineering systems. In recent years, some researchers have made lots of achievement on solving the test selection design (TSD) problem. However, few of them concerned a method to deal with the ambiguity problem caused by the multiple fault modes. In this article, a data-driven-based method for test selection is proposed to build an accurate TSD model. Then, we propose a copula function on cross validation-based Kullback–Leibler divergence (CCVKL) method to construct an accurate constraint model. An improved discrete binary particle swarm optimization (IBPSO) algorithm is used to obtain the optimal test design solution. The proposed method also in comparison to three other existing methods are performed in an electrical circuit