An entropic feature selection method in perspective of Turing formula

Health data are generally complex in type and small in sample size. Such domain-specific challenges make it difficult to capture information reliably and contribute further to the issue of generalization. To assist the analytics of healthcare datasets, we develop a feature selection method based on the concept of Coverage Adjusted Standardized Mutual Information (CASMI). The main advantages of the proposed method are: 1) it selects features more efficiently with the help of an improved entropy estimator, particularly when the sample size is small, and 2) it automatically learns the number of features to be selected based on the information from sample data. Additionally, the proposed method handles feature redundancy from the perspective of joint-distribution. The proposed method focuses on non-ordinal data, while it works with numerical data with an appropriate binning method. A simulation study comparing the proposed method to six widely cited feature selection methods shows that the proposed method performs better when measured by the Information Recovery Ratio, particularly when the sample size is small

EpiAlign: an alignment-based bioinformatic tool for comparing chromatin state sequences.

The availability of genome-wide epigenomic datasets enables in-depth studies of epigenetic modifications and their relationships with chromatin structures and gene expression. Various alignment tools have been developed to align nucleotide or protein sequences in order to identify structurally similar regions. However, there are currently no alignment methods specifically designed for comparing multi-track epigenomic signals and detecting common patterns that may explain functional or evolutionary similarities. We propose a new local alignment algorithm, EpiAlign, designed to compare chromatin state sequences learned from multi-track epigenomic signals and to identify locally aligned chromatin regions. EpiAlign is a dynamic programming algorithm that novelly incorporates varying lengths and frequencies of chromatin states. We demonstrate the efficacy of EpiAlign through extensive simulations and studies on the real data from the NIH Roadmap Epigenomics project. EpiAlign is able to extract recurrent chromatin state patterns along a single epigenome, and many of these patterns carry cell-type-specific characteristics. EpiAlign can also detect common chromatin state patterns across multiple epigenomes, and it will serve as a useful tool to group and distinguish epigenomic samples based on genome-wide or local chromatin state patterns

CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection

Task driven object detection aims to detect object instances suitable for affording a task in an image. Its challenge lies in object categories available for the task being too diverse to be limited to a closed set of object vocabulary for traditional object detection. Simply mapping categories and visual features of common objects to the task cannot address the challenge. In this paper, we propose to explore fundamental affordances rather than object categories, i.e., common attributes that enable different objects to accomplish the same task. Moreover, we propose a novel multi-level chain-of-thought prompting (MLCoT) to extract the affordance knowledge from large language models, which contains multi-level reasoning steps from task to object examples to essential visual attributes with rationales. Furthermore, to fully exploit knowledge to benefit object recognition and localization, we propose a knowledge-conditional detection framework, namely CoTDet. It conditions the detector from the knowledge to generate object queries and regress boxes. Experimental results demonstrate that our CoTDet outperforms state-of-the-art methods consistently and significantly (+15.6 box AP and +14.8 mask AP) and can generate rationales for why objects are detected to afford the task.Comment: Accepted by ICCV 202

Myomegalin regulates Hedgehog pathway by controlling PDE4D at the centrosome

Mutations in the hedgehog (Hh) signaling are implicated in birth defects and cancers, including medulloblastoma (MB), one of the most malignant pediatric brain tumors. Current Hh inhibitors face the challenge of drug resistance and tumor relapse, urging new insights in the Hh pathway regulation. Our previous study revealed how PDE4D controls global levels of cAMP in the cytoplasm to positively regulate Hh signaling; in the present study, we found that a specific isoform PDE4D3 is tethered to the centrosome by Myomegalin (Mmg), a centrosome/Golgi-associated protein. Mmg loss dislocates PDE4D3 from the centrosome, leading to local PKA overactivation and inhibition of the Hh signaling, leaving other PKA-related pathways unaffected. Mmg loss suppresses the proliferation of granule neuron precursors and blocks the growth of MB in mouse model. Our findings specify a new regulatory mechanism of the Hh pathway and highlight an exciting therapeutic avenue for Hh-related cancers with reduced side effects

Utilisation of Lactiplantibacillus plantarum and propionic acid to improve silage quality of amaranth before and after wilting: fermentation quality, microbial communities, and their metabolic pathway

ObjectiveThe aim of this study was to investigate the effects of Lactiplantibacillus plantarum (L. plantarum) and propionic acid (PA) on fermentation characteristics and microbial community of amaranth (Amaranthus hypochondriaus) silage with different moisture contents.MethodsAmaranth was harvested at maturity stage and prepared for ensiling. There were two moisture content gradients (80%: AhG, 70%: AhS; fresh material: FM) and three treatments (control: CK, L. plantarum: LP, propionic acid: PA) set up, and silages were opened after 60 d of ensiling.ResultsThe results showed that the addition of L. plantarum and PA increased lactic acid (LA) content and decreased pH of amaranth after fermentation. In particular, the addition of PA significantly increased crude protein content (p < 0.05). LA content was higher in wilted silage than in high-moisture silage, and it was higher with the addition of L. plantarum and PA (p < 0.05). The dominant species of AhGLP, AhSCK, AhSLP and AhSPA were mainly L. plantarum, Lentilactobacillus buchneri and Levilactobacillus brevis. The dominant species in AhGCK include Enterobacter cloacae, and Xanthomonas oryzae was dominated in AhGPA, which affected fermentation quality. L. plantarum and PA acted synergistically after ensiling to accelerate the succession of dominant species from gram-negative to gram-positive bacteria, forming a symbiotic microbial network centred on lactic acid bacteria. Both wilting and additive silage preparation methods increased the degree of dominance of global and overview maps and carbohydrate metabolism, and decreased the degree of dominance of amino acid metabolism categories.ConclusionIn conclusion, the addition of L. plantarum to silage can effectively improve the fermentation characteristics of amaranth, increase the diversity of bacterial communities, and regulate the microbial community and its functional metabolic pathways to achieve the desired fermentation effect

一种基于铁纳米簇的新型可视化葡萄糖传感器

In this paper, a novel fluorescent sensor for glucose detection based on fluorescent iron clusters (Fe NCs) and glucose oxidase is developed. With the increase of glucose concentration, the red fluorescence of iron nanoclusters decreases gradually, and the glucose content can be detected in the range of 0– 100 μmol·L–1. In addition, in order to facilitate the detection of glucose, this paper investigated the coating of Fe NCs and glucose oxidase by agarose and further preparation of agarose gel test strip for glucose detection. Under ultraviolet lamp, the change of glucose content can be identified through the color change of agarose gel

Atomic-scale structure and nonlinear optical absorption of two-dimensional GeS

info:eu-repo/semantics/publishedVersio

High density lipoprotein downregulates angiotensin II type 1 receptor and inhibits angiotensin II-induced cardiac hypertrophy

Angiotensin II (AngII) and its type receptor (AT1-R) play important roles in the development of cardiac hypertrophy. Low level of high density lipoprotein (HDL) is also an independent risk factor for cardiac hypertrophy. We therefore investigated in the present study whether HDL inhibits cardiac hypertrophy relatively to inhibition of AngII and AT1-R in both in vitro and in vivo experiments. Stimulation of cultured cardiomyocytes of neonatal rats with AngII for 24 h and infusion of AngII in mice for 2 weeks resulted in marked cardiac hypertrophic responses including increased protein synthesis, enlarged sizes of cardiomyocytes and hearts, upregulated phosphorylation levels of protein kinases and reprogrammed expression of specific genes, all of which were significantly attenuated by the treatment with HDL. Furthermore, AngII-treatment induced upregulation of AT-R expression either in cultured cardiomyocytes or in hearts of mice and HDL significantly suppressed the upregulation of AT1-R. Our results suggest that HDL may abrogate AngII-induced cardiac hypertrophy through downregulation of AT1-R expression. (C) 2010 Elsevier Inc. All rights reserved

3D Unet-based Kidney and Kidney Tumer Segmentation with Attentive Feature Learning

To study the kidney diseases and kidney tumor from Computed Tomography(CT) imaging data, it is helpful to segment the region of interest through computer aided auto-segmentation tool. In the KiTs 2019 challenge [1], we are provided 3D volumetric CT data to train a model for kidney and kidney tumor segmentation. We introduce an improved deep 3D Unet by enriching the feature representation in CT images using an attention module. We achieve 1.5% improvement in the segmentation accuracy when evaluated on the validation set

MDM2 inhibitor APG-115 synergizes with ABT-199 to induce cell apoptosis in chronic lymphocytic leukemia

Although clinical outcomes in chronic lymphocytic leukemia (CLL) have greatly improved with several approved small molecular inhibitors, acquired resistance does occur, leading to disease progression and eventual death. Thus, the effort to explore novel inhibitors and combination therapeutic regimens is needed. The inhibition of MDM2-p53 interaction to restore p53 function has been regarded as a potential strategy for treating different cancers. We investigated the effects of novel MDM2 inhibitor APG-115 in CLL. We found that APG-115 treatment upregulated the expression of p53, MDM2, and p21 at the mRNA and protein level. APG-115 inhibited cell proliferation, induced apoptosis, and arrested the cell cycle at G0/G1 stage. Moreover, APG-115 inhibited the expression of BCL-2, BCL-xL, and MCL-1, and suppressed the activation of AKT and ERK signaling pathways. APG-115 combined with the BCL2 inhibitor, ABT-199 (venetoclax), led to further inhibition of the expression of BCL-2 family anti-apoptotic proteins and consequently enhanced cell death. Collectively, this study demonstrates that APG-115 activates p53 and thus inhibits multiple pro-survival mechanisms, which provides a rational explanation for APG-115 efficiency in inducing cell apoptosis in CLL. The synergistic effect of APG-115 with ABT-199 suggested a potential combination application in CLL therapy