Investigation of Metalloproteins Utilizing High Resolution Mass Spectrometry

Copper ions (Cu⁺, Cu²⁺) play important roles in many biological processes (i.e., oxidation, dioxygen transport, and electron transfer); many of the functions in these processes result from copper ions interacting with proteins and peptides. Previous studies using matrix assisted laser desorption/ionization (MALDI) mass spectrometry (MS) have shown that Cu⁺ ions preferentially bind to electron rich groups in gas phase (i.e., N-terminal amino group, the side-chains of lysine, histidine and arginine). For peptides with more than one Cu⁺ ligand, the interaction between Cu⁺ ions and ligands is described in terms of competitive binding; however, Cu⁺ coordination chemistry for multiple Cu⁺-containing proteins and peptides in gas phase is still not fully understood. In addition, no studies on the fragmentation chemistry for multiple Cu⁺-binding peptides, such as [M + 2Cu - H]⁺ ions, have been reported. The synthesized dinuclear copper complex (alpha-cyano-4-hydroxycinnamic acid (CHCA) copper salt (CHCA)₄Cu₂) enhances the ion abundances for [M + xCu - (x-1)H]⁺ (x = 1-6) ions in gas-phase when used as a MALDI matrix. Using this matrix we have investigated site-specific copper binding of several peptides using fragmentation chemistry of [M + Cu]⁺ and [M + 2Cu - H]⁺ ions. The fragmentation studies reveal that the binding of a single Cu⁺ ion and two Cu⁺ ions are different, and these differences are explained in terms of intramolecular interactions of the peptide-Cu ionic complex. The competitive Cu⁺ binding to C-terminus (i.e., amide, carboxyl, methyl ester) versus lysine, as well as cysteine (SH/SO₃H) versus arginine (guanidino), was also examined by MALDI MS and theoretical calculations (Density Functional Theory (DFT)). For example, results from theoretical and experimental (fragmentation reactions) studies on [M + Cu]⁺ and [M + 2Cu - H]⁺ ions suggest that cysteine side chains (SH/SO₃H) are important Cu⁺ ligands. Note that, the proton of the SH/SO₃H group is mobile and can be transferred to the arginine guanidino group. For [M + 2Cu - H]⁺ ions, deprotonation of the -SH/SO₃H group is energetically more favorable than that of the carboxyl group, and the resulting thiolate/sulfonate group plays an important role in the coordination structure of [M + 2Cu - H]⁺ ions

GII Representation-Based Cross-View Gait Recognition by Discriminative Projection With List-Wise Constraints

Remote person identification by gait is one of the most important topics in the field of computer vision and pattern recognition. However, gait recognition suffers severely from the appearance variance caused by the view change. It is very common that gait recognition has a high performance when the view is fixed but the performance will have a sharp decrease when the view variance becomes significant. Existing approaches have tried all kinds of strategies like tensor analysis or view transform models to slow down the trend of performance decrease but still have potential for further improvement. In this paper, a discriminative projection with list-wise constraints (DPLC) is proposed to deal with view variance in cross-view gait recognition, which has been further refined by introducing a rectification term to automatically capture the principal discriminative information. The DPLC with rectification (DPLCR) embeds list-wise relative similarity measurement among intraclass and inner-class individuals, which can learn a more discriminative and robust projection. Based on the original DPLCR, we have introduced the kernel trick to exploit nonlinear cross-view correlations and extended DPLCR to deal with the problem of multiview gait recognition. Moreover, a simple yet efficient gait representation, namely gait individuality image (GII), based on gait energy image is proposed, which could better capture the discriminative information for cross view gait recognition. Experiments have been conducted in the CASIA-B database and the experimental results demonstrate the outstanding performance of both the DPLCR framework and the new GII representation. It is shown that the DPLCR-based cross-view gait recognition has outperformed the-state-of-the-art approaches in almost all cases under large view variance. The combination of the GII representation and the DPLCR has further enhanced the performance to be a new benchmark for cross-view gait recognition

Sequence Level Semantics Aggregation for Video Object Detection

Video objection detection (VID) has been a rising research direction in recent years. A central issue of VID is the appearance degradation of video frames caused by fast motion. This problem is essentially ill-posed for a single frame. Therefore, aggregating features from other frames becomes a natural choice. Existing methods rely heavily on optical flow or recurrent neural networks for feature aggregation. However, these methods emphasize more on the temporally nearby frames. In this work, we argue that aggregating features in the full-sequence level will lead to more discriminative and robust features for video object detection. To achieve this goal, we devise a novel Sequence Level Semantics Aggregation (SELSA) module. We further demonstrate the close relationship between the proposed method and the classic spectral clustering method, providing a novel view for understanding the VID problem. We test the proposed method on the ImageNet VID and the EPIC KITCHENS dataset and achieve new state-of-the-art results. Our method does not need complicated postprocessing methods such as Seq-NMS or Tubelet rescoring, which keeps the pipeline simple and clean.Comment: ICCV 2019 camera read

Heavy metal induced ecophysiological function alterations in the euhalophyte Suaeda salsa

Heavy metal accumulation affects the physiological status of plants. Suaeda salsa L. is used to investigate the toxic effects of cadmium (Cd) and lead (Pb) either alone or mixtures under the static test conditions. Cd-Pb mixture exposure can decrease lignin content and weaken the increase. Mitochondrial calcium content significantly reduced at 30 µM Cd and Pb exposure. Cd-Pb mixture exposure can increase calcium content under the same concentration exposure. Soluble sugar levels noted a significant decrease in Cd, Pb and Cd-Pb mixture exposure. The accumulations of Cd, Pb in S. salsa were significantly increased with exposure time. Soluble protein (SP) in S. salsa at 30 µM concentration treatments decreased with exposure time. Heat shock protein 70 (HSP70) was enhanced lightly along with the increase of added Cd-Pb from 30 to 70 &3181;M and then decreased below the controls which present a synergistic effect. Heat shock protein 60 (HSP60) increased slightly with the increase of Cd-Pb from 30 to 110 µM, and then decreased hereafter and significantly inhibited at 150 ƒÊM (p<0.05). Moreover, Cd-Pb mixture exposure significantly increased the Rubisco activity under lower concentration and presented antagonistic effect. At the same time, the viability percent decreased as increase Cd-Pb concentration exposure (p0.05), it presents a dose-dependent manner. Mitochondrial cells treated with Cd-Pb exposure obviously reduced the reactive oxygen species (ROS) levels in mitochondrial cells.Key words: Suaeda salsa, heavy metal, ecophysiological function

Toxicological responses in alfalfa (Medicago sativa) under joint stress of cadmium and napropamide

Joint effects of Cd2+ and napropamide in seeds, roots or leaves of alfalfa were investigated under different treatments. It was shown that single stress of Cd2+ or napropamide decreased chlorophyll content after 30 days of treatment in different concentrations. The decrease in chlorophyll content became insignificant under joint stress of Cd2+ and napropamide. It can be concluded that the interaction of Cd2+ and napropamide would aggravate the toxic effects on chlorophyll synthesis in leaves of alfalfa. The joint effect of Cd2+ and napropamide was markedly significant (p < 0.05) on the change of SP content in leaves in all treatment. Moreover, Cd2+ and napropamide mixture exposure can increase lignin content and present synergistic effect. In a mixture treated with Cd2+ and napropamide, 52% decrease in β-carotene content contrasted with the control in young leaves. The contents of protein thiols and non-protein thiols in the roots of alfalfa were significantly increased by Cd2+ treatment in all treatment levels. In contrast, increasing napropamide supply did not have any significant effect on the protein thiols and non-protein thiols content. The Cd2+ induced accumulation of O2•- in seeds could be increased by treatment with different Cd2+ concentration. Production of H2O2 and O2•- was also higher in the napropamide treatments than in the control. The addition of napropamide significantly increased the H2O2 and O2•- level in the seeds of alfalfa.Key words: Alfalfa, joint stress, cadmium, napropamide

Expanding Scene Graph Boundaries: Fully Open-vocabulary Scene Graph Generation via Visual-Concept Alignment and Retention

Scene Graph Generation (SGG) offers a structured representation critical in many computer vision applications. Traditional SGG approaches, however, are limited by a closed-set assumption, restricting their ability to recognize only predefined object and relation categories. To overcome this, we categorize SGG scenarios into four distinct settings based on the node and edge: Closed-set SGG, Open Vocabulary (object) Detection-based SGG (OvD-SGG), Open Vocabulary Relation-based SGG (OvR-SGG), and Open Vocabulary Detection + Relation-based SGG (OvD+R-SGG). While object-centric open vocabulary SGG has been studied recently, the more challenging problem of relation-involved open-vocabulary SGG remains relatively unexplored. To fill this gap, we propose a unified framework named OvSGTR towards fully open vocabulary SGG from a holistic view. The proposed framework is an end-toend transformer architecture, which learns a visual-concept alignment for both nodes and edges, enabling the model to recognize unseen categories. For the more challenging settings of relation-involved open vocabulary SGG, the proposed approach integrates relation-aware pre-training utilizing image-caption data and retains visual-concept alignment through knowledge distillation. Comprehensive experimental results on the Visual Genome benchmark demonstrate the effectiveness and superiority of the proposed framework.Comment: 10 pages, 4 figures, 6 table