Despite an enormous research effort, most cases of late-onset Alzheimer's disease (LOAD) still remain unexplained and the current biomedical science is still a long way from the ultimate goal of ...revealing clear risk factors that can help in the diagnosis, prevention and treatment of the disease. Current theories about the development of LOAD hinge on the premise that Alzheimer's arises mainly from heritable causes. Yet, the complex, non-Mendelian disease etiology suggests that an epigenetic component could be involved. Using MALDI-TOF mass spectrometry in post-mortem brain samples and lymphocytes, we have performed an analysis of DNA methylation across 12 potential Alzheimer's susceptibility loci. In the LOAD brain samples we identified a notably age-specific epigenetic drift, supporting a potential role of epigenetic effects in the development of the disease. Additionally, we found that some genes that participate in amyloid-beta processing (PSEN1, APOE) and methylation homeostasis (MTHFR, DNMT1) show a significant interindividual epigenetic variability, which may contribute to LOAD predisposition. The APOE gene was found to be of bimodal structure, with a hypomethylated CpG-poor promoter and a fully methylated 3'-CpG-island, that contains the sequences for the epsilon4-haplotype, which is the only undisputed genetic risk factor for LOAD. Aberrant epigenetic control in this CpG-island may contribute to LOAD pathology. We propose that epigenetic drift is likely to be a substantial mechanism predisposing individuals to LOAD and contributing to the course of disease.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In this work, we propose a novel adaptive spatially-regularized correlation filters (ASRCF) model to simultaneously optimize the filter coefficients and the spatial regularization weight. First, this ...adaptive spatial regularization scheme could learn an effective spatial weight for a specific object and its appearance variations, and therefore result in more reliable filter coefficients during the tracking process. Second, our ASRCF model can be effectively optimized based on the alternating direction method of multipliers, where each subproblem has the closed-from solution. Third, our tracker applies two kinds of CF models to estimate the location and scale respectively. The location CF model exploits ensembles of shallow and deep features to determine the optimal position accurately. The scale CF model works on multi-scale shallow features to estimate the optimal scale efficiently. Extensive experiments on five recent benchmarks show that our tracker performs favorably against many state-of-the-art algorithms, with real-time performance of 28fps.
Hepatocellular carcinoma (HCC)-the most common form of liver cancer-is an aggressive malignancy with few effective treatment options
. Lenvatinib is a small-molecule inhibitor of multiple receptor ...tyrosine kinases that is used for the treatment of patients with advanced HCC, but this drug has only limited clinical benefit
. Here, using a kinome-centred CRISPR-Cas9 genetic screen, we show that inhibition of epidermal growth factor receptor (EGFR) is synthetic lethal with lenvatinib in liver cancer. The combination of the EGFR inhibitor gefitinib and lenvatinib displays potent anti-proliferative effects in vitro in liver cancer cell lines that express EGFR and in vivo in xenografted liver cancer cell lines, immunocompetent mouse models and patient-derived HCC tumours in mice. Mechanistically, inhibition of fibroblast growth factor receptor (FGFR) by lenvatinib treatment leads to feedback activation of the EGFR-PAK2-ERK5 signalling axis, which is blocked by EGFR inhibition. Treatment of 12 patients with advanced HCC who were unresponsive to lenvatinib treatment with the combination of lenvatinib plus gefitinib (trial identifier NCT04642547) resulted in meaningful clinical responses. The combination therapy identified here may represent a promising strategy for the approximately 50% of patients with advanced HCC who have high levels of EGFR.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Permeable reactive bio-barrier (PRBB), an innovative technology, could treat many contaminants via the natural gradient flow of groundwater based on immobilization or transformation of pollutants ...into less toxic and harmful forms. In this field study, we developed an innovative PRBB system comprising immobilized Dehalococcoides mccartyi (Dhc) and Clostridium butyricum embedded into the silica gel for long-term treatment of trichloroethene (TCE) polluted groundwater. Four injection wells and two monitoring wells were installed at the downstream of the TCE plume. Without PRBB, results showed that the TCE (6.23 ± 0.43 μmole/L) was converted to cis-dichloroethene (0.52 ± 0.63 μmole/L), and ethene was not detected, whereas TCE was completely converted to ethene (3.31 μmole/L) with PRBB treatment, indicating that PRBB could promote complete dechlorination of TCE. Noticeably, PRBB showed the long-term capability to maintain a high dechlorinating efficiency for TCE removal during the 300-day operational period. Furthermore, with qPCR analysis, the PRBB application could stably maintain the populations of Dhc and functional genes (bvcA, tceA, and vcrA) at >108 copies/L within the remediation course and change the bacterial communities in the contaminated groundwater. We concluded that our PRBB was first set up for cleaning up TCE-contaminated groundwater in a field trial.
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•A novel PRBB with bioaugmented Dhc in silica gel was first set up in situ.•The application of the PRBB system in complete dechlorination was demonstrated.•The PRBB system can be reused long-term, with an operational period of 300 days.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
As a leading cause of death, second only to heart disease, cancer has always been one of the burning topics in medical research. When targeting multiple signal pathways in tumorigenesis ...chemoprevention, using natural or synthetic anti-cancer drugs is a vital strategy to reduce cancer damage. However, toxic effects, multidrug resistance (MDR) as well as cancer stem cells (CSCs) all prominently limited the clinical application of conventional anticancer drugs. With low side effects, strong biological activity, unique mechanism, and wide range of targets, natural products derived from plants are considered significant sources for new drug development. Nobiletin is one of the most attractive compounds, a unique flavonoid primarily isolated from the peel of citrus fruits. Numerous studies in vitro and in vivo have suggested that nobiletin and its derivatives possess the eminent potential to become effective cancer chemoprevention agents through various cellular and molecular levels. This article aims to comprehensively review the anticancer efficacy and specific mechanisms of nobiletin, enhancing our understanding of its chemoprevention properties and providing the latest research findings. At the end of this review, we also give some discussion and future perspectives regarding the challenges and opportunities in nobiletin efficient exploitation.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
In this paper, we propose an effective person re-identification method with latent variables, which represents a pedestrian as the mixture of a holistic model and a number of flexible models. Three ...types of latent variables are introduced to model uncertain factors in the re-identification problem, including vertical misalignments, horizontal misalignments and leg posture variations. The distance between two pedestrians can be determined by minimizing a given distance function with respect to latent variables, and then be used to conduct the re-identification task. In addition, we develop a latent metric learning method for learning the effective metric matrix, which can be solved via an iterative manner: once latent information is specified, the metric matrix can be obtained based on some typical metric learning methods; with the computed metric matrix, the latent variables can be determined by searching the state space exhaustively. Finally, extensive experiments are conducted on seven databases to evaluate the proposed method. The experimental results demonstrate that our method achieves better performance than other competing algorithms.
In this paper, we analyze the spatial information of deep features, and propose two complementary regressions for robust visual tracking. First, we propose a kernelized ridge regression model wherein ...the kernel value is defined as the weighted sum of similarity scores of all pairs of patches between two samples. We show that this model can be formulated as a neural network and thus can be efficiently solved. Second, we propose a fully convolutional neural network with spatially regularized kernels, through which the filter kernel corresponding to each output channel is forced to focus on a specific region of the target. Distance transform pooling is further exploited to determine the effectiveness of each output channel of the convolution layer. The outputs from the kernelized ridge regression model and the fully convolutional neural network are combined to obtain the ultimate response. Experimental results on two benchmark datasets validate the effectiveness of the proposed method.
For visual tracking, an ideal filter learned by the correlation filter (CF) method should take both discrimination and reliability information. However, existing attempts usually focus on the former ...one while pay less attention to reliability learning. This may make the learned filter be dominated by the unexpected salient regions on the feature map, thereby resulting in model degradation. To address this issue, we propose a novel CF-based optimization problem to jointly model the discrimination and reliability information. First, we treat the filter as the element-wise product of a base filter and a reliability term. The base filter is aimed to learn the discrimination information between the target and backgrounds, and the reliability term encourages the final filter to focus on more reliable regions. Second, we introduce a local response consistency regular term to emphasize equal contributions of different regions and avoid the tracker being dominated by unreliable regions. The proposed optimization problem can be solved using the alternating direction method and speeded up in the Fourier domain. We conduct extensive experiments on the OTB-2013, OTB-2015 and VOT-2016 datasets to evaluate the proposed tracker. Experimental results show that our tracker performs favorably against other state-of-the-art trackers.
Protein lysine methyltransferases G9a and GLP modulate the transcriptional repression of a variety of genes via dimethylation of Lys9 on histone H3 (H3K9me2) as well as dimethylation of non-histone ...targets. Here we report the discovery of UNC0638, an inhibitor of G9a and GLP with excellent potency and selectivity over a wide range of epigenetic and non-epigenetic targets. UNC0638 treatment of a variety of cell lines resulted in lower global H3K9me2 levels, equivalent to levels observed for small hairpin RNA knockdown of G9a and GLP with the functional potency of UNC0638 being well separated from its toxicity. UNC0638 markedly reduced the clonogenicity of MCF7 cells, reduced the abundance of H3K9me2 marks at promoters of known G9a-regulated endogenous genes and disproportionately affected several genomic loci encoding microRNAs. In mouse embryonic stem cells, UNC0638 reactivated G9a-silenced genes and a retroviral reporter gene in a concentration-dependent manner without promoting differentiation.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Twin studies have provided the basis for genetic and epidemiological studies in human complex traits. As epigenetic factors can contribute to phenotypic outcomes, we conducted a DNA methylation ...analysis in white blood cells (WBC), buccal epithelial cells and gut biopsies of 114 monozygotic (MZ) twins as well as WBC and buccal epithelial cells of 80 dizygotic (DZ) twins using 12K CpG island microarrays. Here we provide the first annotation of epigenetic metastability of ∼6,000 unique genomic regions in MZ twins. An intraclass correlation (ICC)-based comparison of matched MZ and DZ twins showed significantly higher epigenetic difference in buccal cells of DZ co-twins (P = 1.2 × 10−294). Although such higher epigenetic discordance in DZ twins can result from DNA sequence differences, our in silico SNP analyses and animal studies favor the hypothesis that it is due to epigenomic differences in the zygotes, suggesting that molecular mechanisms of heritability may not be limited to DNA sequence differences.
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