Backbone resonance assignment in large protonated proteins using a combination of new 3D TROSY-HN(CA)HA, 4D TROSY-HACANH and 13C-detected HACACO experiments

A new method for backbone resonance assignment suitable for large proteins with the natural 1H isotope content is proposed based on a combination of the most sensitive TROSY-type triple-resonance experiments. These techniques include TROSY-HNCO, 13C′-detected 3D multiple-quantum HACACO and the newly developed 3D TROSY multiple-quantum-HN(CA)HA and 4D TROSY multiple-quantum-HACANH experiments. The favorable relaxation properties of the multiple-quantum coherences, signal detection using the 13C′ antiphase coherences, and the use of TROSY optimize the performance of the proposed set of experiments for application to large protonated proteins. The method is demonstrated with the 44 kDa uniformly 15N,13C-labeled and fractionally (35%) deuterated trimeric B. Subtilis Chorismate Mutase and is suitable for proteins with large correlation times but a relatively small number of residues, such as membrane proteins embedded in micelles or oligomeric protein

Two-dimensional concurrent HMQC-COSY as an approach for small molecule chemical shift assignment and compound identification

Chemical shift assignment is the first step toward the structure elucidation of natural products and other chemical compounds. We propose here the use of 2D concurrent HMQC-COSY as an experiment for rapid chemical shift assignment of small molecules. This experiment provides well-dispersed 1H–13C peak patterns that are distinctive for different functional groups plus 1H–1H COSY connectivities that serve to identify adjacent groups. The COSY diagonal peaks, which are phased to be absorptive, resemble 1H–13C HMQC cross peaks. We demonstrate the applicability of this experiment for rapidly and unambiguously establishing correlations between different functional groups through the analysis of the spectrum of a metabolite (jasmonic acid) dissolved in CDCl3. In addition, we show that the experiment can be used to assign spectra of compounds in a mixture of metabolites in D2O

Semantic-Aware Fine-Grained Correspondence

Establishing visual correspondence across images is a challenging and essential task. Recently, an influx of self-supervised methods have been proposed to better learn representations for visual correspondence. However, we find that these methods often fail to leverage semantic information and over-rely on the matching of low-level features. In contrast, human vision is capable of distinguishing between distinct objects as a pretext to tracking. Inspired by this paradigm, we propose to learn semantic-aware fine-grained correspondence. Firstly, we demonstrate that semantic correspondence is implicitly available through a rich set of image-level self-supervised methods. We further design a pixel-level self-supervised learning objective which specifically targets fine-grained correspondence. For downstream tasks, we fuse these two kinds of complementary correspondence representations together, demonstrating that they boost performance synergistically. Our method surpasses previous state-of-the-art self-supervised methods using convolutional networks on a variety of visual correspondence tasks, including video object segmentation, human pose tracking, and human part tracking.Comment: 26 page

Matrine Reverses the Warburg Effect and Suppresses Colon Cancer Cell Growth via Negatively Regulating HIF-1α.

The Warburg effect is a peculiar feature of cancer’s metabolism, which is an attractive therapeutic target that could aim tumor cells while sparing normal tissue. Matrine is an alkaloid extracted from the herb root of a traditional Chinese medicine, Sophora flavescens Ait. Matrine has been reported to have selective cytotoxicity toward cancer cells but with elusive mechanisms. Here, we reported that matrine was able to reverse the Warburg effect (inhibiting glucose uptake and lactate production) and suppress the growth of human colon cancer cells in vitro and in vivo . Mechanistically, we revealed that matrine significantly decreased the messenger RNA (mRNA) and protein expression of HIF-1α, a critical transcription factor in reprogramming cancer metabolism toward the Warburg effect. As a result, the expression levels of GLUT1, HK2, and LDHA, the downstream targets of HIF-1α in regulating glucose metabolism, were dramatically inhibited by matrine. Moreover, this inhibitory effect of matrine was significantly attenuated when HIF-1α was knocked down or exogenous overexpressed in colon cancer cells. Together, our results revealed that matrine inhibits colon cancer cell growth via suppression of HIF-1α expression and its downstream regulation of Warburg effect. Matrine could be further developed as an antitumor agent targeting the HIF-1α-mediated Warburg effect for colon cancer treatment