Effect of Arborvitae Seed on Cognitive Function and α7nAChR Protein Expression of Hippocampus in Model Rats with Alzheimer’s Disease

The aim was to investigate the effect of the arborvitae seed on cognitive function and α7-nicotinic acetylcholine receptor (α7nAChR) protein expression of the hippocampus in model rats with Alzheimer’s disease (AD). Thirty-six adult Wistar rats were randomly divided into the control, test, and drug groups. A dose of Aβ_1–40 was injected into the rats’ hippocampus in the test and drug groups and the control rats were injected with the same amount of normal saline. After the model was successful, the rats in the control and test groups were gavaged with sodium carboxymethyl cellulose (500 mg/kg) and the rats in the drug group were gavaged with arborvitae seed powder (500 mg/kg) for 15 days. The Morris water maze test was used for cognitive function. The effect of arborvitae seed on α7nAChR protein immunoreactivity on the hippocampus neurons was studied by the immunohistochemistry method. Behavioral tests showed that the mean escape latencies and search time of the test group were obviously longer than the control and drug groups. The percentage of the search distance of the test group was shorter than that of the control and drug groups. The immunohistochemistry results are as follows: α7nAChR-positive cells and optical density in the hippocampus of the rats in the test group are less than that of the rats in the control and drug groups (all P < 0.01). Arborvitae seed can treat AD by increased expression of α7nAChR.     

Novel Systems for Dynamically Assessing Insulin Action in Live Cells Reveals Heterogeneity in the Insulin Response

Regulated GLUT4 trafficking is a key action of insulin. Quantitative stepwise analysis of this process provides a powerful tool for pinpointing regulatory nodes that contribute to insulin regulation and insulin resistance. We describe a novel GLUT4 construct and workflow for the streamlined dissection of GLUT4 trafficking; from simple high throughput screens to high resolution analyses of individual vesicles. We reveal single cell heterogeneity in insulin action highlighting the utility of this approach – each cell displayed a unique and highly reproducible insulin response, implying that each cell is hard‐wired to produce a specific output in response to a given stimulus. These data highlight that the response of a cell population to insulin is underpinned by extensive heterogeneity at the single cell level. This heterogeneity is pre‐programmed within each cell and is not the result of intracellular stochastic events.     

DNA-COMPACT: DNA COMpression Based on a Pattern-Aware Contextual Modeling Technique

Genome data are becoming increasingly important for modern medicine. As the rate of increase in DNA sequencing outstrips the rate of increase in disk storage capacity, the storage and data transferring of large genome data are becoming important concerns for biomedical researchers. We propose a two-pass lossless genome compression algorithm, which highlights the synthesis of complementary contextual models, to improve the compression performance. The proposed framework could handle genome compression with and without reference sequences, and demonstrated performance advantages over best existing algorithms. The method for reference-free compression led to bit rates of 1.720 and 1.838 bits per base for bacteria and yeast, which were approximately 3.7% and 2.6% better than the state-of-the-art algorithms. Regarding performance with reference, we tested on the first Korean personal genome sequence data set, and our proposed method demonstrated a 189-fold compression rate, reducing the raw file size from 2986.8 MB to 15.8 MB at a comparable decompression cost with existing algorithms. DNAcompact is freely available at https://sourceforge.net/projects/dnacompact/for research purpose.     

A Kalman-Filter Based Approach to Identification of Time-Varying Gene Regulatory Networks

Motivation

Conventional identification methods for gene regulatory networks (GRNs) have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs.

Results

It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.     

MiR-30-Regulated Autophagy Mediates Angiotensin II-Induced Myocardial Hypertrophy

Dysregulated autophagy may lead to the development of disease. Role of autophagy and the diagnostic potential of microRNAs that regulate the autophagy in cardiac hypertrophy have not been evaluated. A rat model of cardiac hypertrophy was established using transverse abdominal aortic constriction (operation group). Cardiomyocyte autophagy was enhanced in rats from the operation group, compared with those in the sham operation group. Moreover, the operation group showed up-regulation of beclin-1 (an autophagy-related gene), and down-regulation of miR-30 in cardiac tissue. The effects of inhibition and over-expression of the beclin-1 gene on the expression of hypertrophy-related genes and on autophagy were assessed. Angiotensin II-induced myocardial hypertrophy was found to be mediated by over-expression of the beclin-1 gene. A dual luciferase reporter assay confirmed that beclin-1 was a target gene of miR-30a. miR-30a induced alterations in beclin-1 gene expression and autophagy in cardiomyocytes. Treatment of cardiomyocytes with miR-30a mimic attenuated the Angiotensin II-induced up-regulation of hypertrophy-related genes and decreased in the cardiomyocyte surface area. Conversely, treatment with miR-30a inhibitor enhanced the up-regulation of hypertrophy-related genes and increased the surface area of cardiomyocytes induced by Angiotensin II. In addition, circulating miR-30 was elevated in patients with left ventricular hypertrophy, and circulating miR-30 was positively associated with left ventricular wall thickness. Collectively, these above-mentioned results suggest that Angiotensin II induces down-regulation of miR-30 in cardiomyocytes, which in turn promotes myocardial hypertrophy through excessive autophagy. Circulating miR-30 may be an important marker for the diagnosis of left ventricular hypertrophy.     

Abnormal Organization of White Matter Network in Patients with No Dementia after Ischemic Stroke

Structural changes after ischemic stroke could affect information communication extensively in the brain network. It is likely that the defects in the white matter (WM) network play a key role in information interchange. In this study, we used graph theoretical analysis to examine potential organization alteration in the WM network architecture derived from diffusion tensor images from subjects with no dementia and experienced stroke in the past 5.4–14.8 months (N = 47, Mini-Mental Screening Examination, MMSE range 18–30), compared with a normal control group with 44 age and gender-matched healthy volunteers (MMSE range 26–30). Region-wise connectivity was derived from fiber connection density of 90 different cortical and subcortical parcellations across the whole brain. Both normal controls and patients with chronic stroke exhibited efficient small-world properties in their WM structural networks. Compared with normal controls, topological efficiency was basically unaltered in the patients with chronic stroke, as reflected by unchanged local and global clustering coefficient, characteristic path length, and regional efficiency. No significant difference in hub distribution was found between normal control and patient groups. Patients with chronic stroke, however, were found to have reduced betweenness centrality and predominantly located in the orbitofrontal cortex, whereas increased betweenness centrality and vulnerability were observed in parietal-occipital cortex. The National Institutes of Health Stroke Scale (NIHSS) score of patient is correlated with the betweenness centrality of right pallidum and local clustering coefficient of left superior occipital gyrus. Our findings suggest that patients with chronic stroke still exhibit efficient small-world organization and unaltered topological efficiency, with altered topology at orbitofrontal cortex and parietal-occipital cortex in the overall structural network. Findings from this study could help in understanding the mechanism of cognitive impairment and functional compensation occurred in patients with chronic stroke.     

Autophagic Impairment Contributes to Systemic Inflammation-Induced Dopaminergic Neuron Loss in the Midbrain

Background

Neuroinflammation plays an important role in the pathogenesis of Parkinson’s disease (PD), inducing and accelerating dopaminergic (DA) neuron loss. Autophagy, a critical mechanism for clearing misfolded or aggregated proteins such as α-synuclein (α-SYN), may affect DA neuron survival in the midbrain. However, whether autophagy contributes to neuroinflammation-induced toxicity in DA neurons remains unknown.

Results

Intraperitoneal injection of lipopolysaccharide (LPS, 5 mg/kg) into young (3-month-old) and aged (16-month-old) male C57BL/6J mice was observed to cause persistent neuroinflammation that was associated with a delayed and progressive loss of DA neurons and accumulation of α-SYN in the midbrain. The autophagic substrate-p62 (SQSTM1) persistently increased, whereas LC3-II and HDAC6 exhibited early increases followed by a decline. In vitro studies further demonstrated that TNF-α induced cell death in PC12 cells. Moreover, a sublethal dose of TNF-α (50 ng/ml) increased the expression of LC3-II, p62, and α-SYN, implying that TNF-α triggered autophagic impairment in cells.

Conclusion

Neuroinflammation may cause autophagic impairment, which could in turn result in DA neuron degeneration in midbrain.     

Induction of TGF-β1 Synthesis by Macrophages in Response to Apoptotic Cells Requires Activation of the Scavenger Receptor CD36

Background/Objective

Phosphatidylserine (PS) exposed on apoptotic cells has been shown to stimulate production of transforming growth factor-β (TGF-β) and promote anti-inflammatory responses. However, the PS receptor(s) responsible for this induction has not been clearly determined.

Methodology/Principal Findings

In the present study, using RAWTβRII cells in which a truncated dominant negative TGF-β receptor II was stably transfected in order to avoid auto-feedback induction of TGF-β, we show that TGF-β1 synthesis is initiated via activation of the scavenger receptor, CD36. The response requires exposure of PS on the apoptotic cell surface and was absent in macrophages lacking CD36. Direct activation of CD36 with an anti-CD36 antibody initiated TGF-β1 production, and signaling pathways involving both Lyn kinase and ERK1/2 were shown to participate in CD36-driven TGF-β1 expression.

Conclusion/Significance

Since CD36 has been previously implicated in activation of secreted latent TGF-β, the present study indicates its role in the multiple steps to generation of this important biological mediator.