Nature versus number : monocytes in cardiovascular disease

Monocytes play a key role in cardiovascular disease (CVD) as their influx into the vessel wall is necessary for the development of an atherosclerotic plaque. Monocytes are, however, heterogeneous differentiating from classical monocytes through the intermediate subset to the nonclassical subset. While it is recognized that the percentage of intermediate and nonclassical monocytes are higher in individuals with CVD, accompanying changes in inflammatory markers suggest a functional impact on disease development that goes beyond the increased proportion of these ‘inflammatory’ monocyte subsets. Furthermore, emerging evidence indicates that changes in monocyte proportion and function arise in dyslipidemia, with lipid lowering medication having some effect on reversing these changes. This review explores the nature and number of monocyte subsets in CVD addressing what they are, when they arise, the effect of lipid lowering treatment, and the possible implications for plaque development. Understanding these associations will deepen our understanding of the clinical significance of monocytes in CVD

Modeling geometric-temporal context with directional pyramid co-occurrence for action recognition

In this paper, we present a new geometric-temporal representation for visual action recognition based on local spatio-temporal features. First, we propose a modified covariance descriptor under the log-Euclidean Riemannian metric to represent the spatio-temporal cuboids detected in the video sequences. Compared with previously proposed covariance descriptors, our descriptor can be measured and clustered in Euclidian space. Second, to capture the geometric-temporal contextual information, we construct a directional pyramid co-occurrence matrix (DPCM) to describe the spatio-temporal distribution of the vector-quantized local feature descriptors extracted from a video. DPCM characterizes the co-occurrence statistics of local features as well as the spatio-temporal positional relationships among the concurrent features. These statistics provide strong descriptive power for action recognition. To use DPCM for action recognition, we propose a directional pyramid co-occurrence matching kernel to measure the similarity of videos. The proposed method achieves the state-of-the-art performance and improves on the recognition performance of the bag-of-visual-words (BOVWs) models by a large margin on six public data sets. For example, on the KTH data set, it achieves 98.78% accuracy while the BOVW approach only achieves 88.06%. On both Weizmann and UCF CIL data sets, the highest possible accuracy of 100% is achieved

Multi-view multi-instance learning based on joint sparse representation and multi-view dictionary learning

In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm (M2IL) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse "-graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the M2IL. Experiments and analyses in many practical applications prove the effectiveness of the M2IL

An analog of glibenclamide selectively enhances autophagic degradation of misfolded α1-antitrypsin Z

The classical form of α1-antitrypsin deficiency (ATD) is characterized by intracellular accumulation of the misfolded variant α1-antitrypsin Z (ATZ) and severe liver disease in some of the affected individuals. In this study, we investigated the possibility of discovering novel therapeutic agents that would reduce ATZ accumulation by interrogating a C. elegans model of ATD with high-content genome-wide RNAi screening and computational systems pharmacology strategies. The RNAi screening was utilized to identify genes that modify the intracellular accumulation of ATZ and a novel computational pipeline was developed to make high confidence predictions on repurposable drugs. This approach identified glibenclamide (GLB), a sulfonylurea drug that has been used broadly in clinical medicine as an oral hypoglycemic agent. Here we show that GLB promotes autophagic degradation of misfolded ATZ in mammalian cell line models of ATD. Furthermore, an analog of GLB reduces hepatic ATZ accumulation and hepatic fibrosis in a mouse model in vivo without affecting blood glucose or insulin levels. These results provide support for a drug discovery strategy using simple organisms as human disease models combined with genetic and computational screening methods. They also show that GLB and/or at least one of its analogs can be immediately tested to arrest the progression of human ATD liver disease.</div

Terahertz oscillations in an In_0.53Ga_0.47As submicron planar gunn diode

The length of the transit region of a Gunn diode determines the natural frequency at which it operates in fundamental mode – the shorter the device, the higher the frequency of operation. The long-held view on Gunn diode design is that for a functioning device the minimum length of the transit region is about 1.5μm, limiting the devices to fundamental mode operation at frequencies of roughly 60 GHz. Study of these devices by more advanced Monte Carlo techniques that simulate the ballistic transport and electron-phonon interactions that govern device behaviour, offers a new lower bound of 0.5μm, which is already being approached by the experimental evidence that has shown planar and vertical devices exhibiting Gunn operation at 600nm and 700nm, respectively. The paper presents results of the first ever THz submicron planar Gunn diode fabricated in In&lt;sub&gt;0.53&lt;/sub&gt;Ga&lt;sub&gt;0.47&lt;/sub&gt;A on an InP substrate, operating at a fundamental frequency above 300 GHz. Experimentally measured rf power of 28 µW was obtained from a 600 nm long ×120 µm wide device. At this new length, operation in fundamental mode at much higher frequencies becomes possible – the Monte Carlo model used predicts power output at frequencies over 300 GHz

Mammalian expression of the human sex steroid-binding protein of plasma (SBP or SHBG) and testis (ABP) Characterization of the recombinant protein

AbstractA full-length 1,209 bp cDNA encoding the human sex steroid-binding protein of plasma (SBP or SHBG) and testis (ABP) was constructed and expressed in BHK-21 cells. The sequence agrees with the published gene and protein sequences. The cells were found to secrete SBP following transfection and G418r selection. The recombinant protein binds 5α-dihydrotestosterone with a Kd of 0.28 nM. It also binds testosterone and 17β-estradiol but not progesterone, estrone or cortisol revealing a steroid-binding specificity identical to that of human SBP, SDS-PAGE patterns are less complex than human SBP and show a monomeric molecular weight of about 43 kDa

Interaction-aware spatio-temporal pyramid attention networks for action classification

For CNN-based visual action recognition, the accuracy may be increased if local key action regions are focused on. The task of self-attention is to focus on key features and ignore irrelevant information. So, self-attention is useful for action recognition. However, the current self-attention methods usually ignore correlations among local feature vectors at spatial positions in feature maps in CNNs. In this paper, we propose an effective interaction-aware self-attention model which can extract information about the interactions between feature vectors to learn attention maps. Since the different layers in a network capture feature maps at different scales, we introduce a spatial pyramid with the feature maps at different layers to attention modeling. The multi-scale information is utilized to obtain more accurate attention scores. These attention scores are used to weight the local feature vectors and the feature maps and then calculate the attention feature maps. Since the number of feature maps input to the spatial pyramid attention layer is unrestricted, we easily extend this attention layer to a spatial-temporal version. Our model can be embedded into any general CNN to form a video-level end-to-end attention network for action recognition. Besides using the RGB stream alone, several methods are investigated to combine the RGB and flow streams for the final prediction of the classes of human actions. Experimental results show that our method achieves state-of-the-art results on the datasets UCF101, HMDB51, Kinetics-400 and untrimmed Charades

Patterned expression of neurotrophic factors and receptors in human limbal and corneal regions

PURPOSE: To evaluate the expression patterns of neurotrophic factors (NTFs) and their receptors in the human cornea with the intention of exploring the role of NTFs in maintaining corneal epithelial stem cells in the limbus. METHODS: Fresh human corneoscleral tissues were prepared for frozen sections. Immunofluorescent staining was performed with primary antibodies against six members of three NTF families and their six receptors. To confirm the specificity of NTF primary antibodies, neutralization experiments with their corresponding peptides and western blot analysis were performed. RESULTS: Based on spatial and differential immuno-localization, three patterns of NTF expression were potentially involved in epithelial-mesenchymal interaction on the ocular surface: (1) the epithelial type: nerve growth factor (NGF) and glial cell-derived neurotrophic factor (GDNF); (2) the paracrine type: neurotrophin (NT)-3 and NT-4/5; and (3) the reciprocal type: brain-derived neurotrophic factor (BDNF). The stem cell-enriched basal cells of the limbal epithelium expressed three unique staining patterns for NTFs: (1) exclusively positive for NGF, GDNF, and their corresponding receptors, TrkA and GDNF family receptor alpha (GFR)-1; (2) relatively high levels of BDNF; and (3) negative for NT-3 and NT-4. Additionally, the neurotrophin common low-affinity receptor, p75NTR, was mainly expressed by the basal layer of the entire corneal and limbal epithelia, and TrkB and TrkC were evenly expressed by the entire corneal and limbal epithelia. BDNF, p75NTR, TrkB, and TrkC are also abundantly expressed by limbal stroma cells. No specific immunoreactivity to ciliary neurotrophic factor (CNTF) and its receptor, CNTFR, was detected in cornea tissue in situ. CONCLUSIONS: Our findings revealed patterned expression of NTFs and their receptors in the human ocular surface, suggesting that they may play a vital role in maintaining corneal epithelial stem cells in the limbus. NGF, GDNF, GFR-1, TrkA, and BDNF may serve as new limbal basal cell markers defining the corneal epithelial stem cell phenotype.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000250807800002&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Biochemistry &amp; Molecular BiologyOphthalmologySCI(E)42ARTICLE217-191934-19411

Melatonin Alters Age-Related Changes in Transcription Factors and Kinase Activation

Male mice were fed 40 ppm melatonin for 2 months prior to sacrifice at age 26 months, and compared with both 26 and 4 month-old untreated controls. The nuclear translocation of NF-κB increased with age in both brain and spleen and this was reversed by melatonin only in brain. Another transcription factor, AP-1 was increased with age in the spleen and not in brain and this could be blocked by melatonin treatment. The fraction of the active relative to the inactive form of several enabling kinases was compared. The proportion of activated ERK was elevated with age in brain and spleen but this change was unresponsive to melatonin. A similar age-related increase in glial fibrillary acidic protein (GFAP) was also refractory to melatonin treatment. The cerebral melatonin M1 receptor decreased with age in brain but increased in spleen. The potentially beneficial nature of melatonin for the preservation of brain function with aging was suggested by the finding that an age-related decline in cortical synaptophysin levels was prevented by dietary melatonin

Electron-Spin Excitation Coupling in an Electron Doped Copper Oxide Superconductor

High-temperature (high-Tc) superconductivity in the copper oxides arises from electron or hole doping of their antiferromagnetic (AF) insulating parent compounds. The evolution of the AF phase with doping and its spatial coexistence with superconductivity are governed by the nature of charge and spin correlations and provide clues to the mechanism of high-Tc superconductivity. Here we use a combined neutron scattering and scanning tunneling spectroscopy (STS) to study the Tc evolution of electron-doped superconducting Pr0.88LaCe0.12CuO4-delta obtained through the oxygen annealing process. We find that spin excitations detected by neutron scattering have two distinct modes that evolve with Tc in a remarkably similar fashion to the electron tunneling modes in STS. These results demonstrate that antiferromagnetism and superconductivity compete locally and coexist spatially on nanometer length scales, and the dominant electron-boson coupling at low energies originates from the electron-spin excitations.Comment: 30 pages, 12 figures, supplementary information include