SYNTHESIS OF DYE LIBRARIES FOR NEURODEGENERATIVE DISEASE AND UNIQUE FRET STUDY

Ph.DDOCTOR OF PHILOSOPH

Synthesis and systematic evaluation of dark resonance energy transfer (DRET)-based library and its application in cell imaging

10.1002/asia.201403257Chemistry - An Asian Chemistry103581-58

A fast responsive chromogenic and near-infrared fluorescence lighting-up probe for visual detection of toxic thiophenol in environmental water and living cells

Thiophenols as high toxic environmental pollutants are poisonous for animals and aquatic organisms. Therefore, it is indispensable to monitor thiophenols in the environment. Herein, a novel near-infrared fluorescent probe was developed for the detection of thiophenols, which was easily prepared by one-step coupling of 2,4-dini trobenzenesulfonyl chloride with Nile blue. The probe showed a significant near infrared (∼675 nm) fluores cence “turn-on” response to thiophenols with some good features including chromogenic reaction, high sensi tivity and selectivity, fast response, near-infrared emission along with low detection limit (1.8 nM). The probe was employed to rapidly and visually determine thiophenols in several industrial wastewaters with good re coveries (90–110%). Moreover, this probe has been demonstrated good capability for imaging thiophenol in HeLa cellsinfo:eu-repo/semantics/publishedVersio

The development of a highly photostable and chemically stable zwitterionic near-infrared dye for imaging applications

Chemical Communications51193989-399

Seasonal and spatial variations of heavy metalsin surface sediments collected from the BaoxiangRiver in the Dianchi Watershed, China

To explore potential ecological hazards due to heavy metals in the Dianchi Lake Watershed, a three-stage European Community Bureau of Reference (BCR) sequential extraction procedure was applied to examine the spatial distributions and relative speciation ratios of Zn, Cu, Ni, Pb, and Cr in Baoxiang River sediments during wet and dry seasons. The metal species have similar spatial variations during different seasons. In the upstream reaches of the Baoxiang River, heavy metals reside primarily in the non-extractable residual fraction (72&ndash;90%). In the midstream, the residual fraction (35&ndash;89%) remains dominant, but the extractable fraction increases, featuring especially notable increases in the reducible fraction (5&ndash;40%). Downstream, the Cu, Ni, Pb, and Cr residual fractions remain high (46&ndash;80%) and the extractable fractions increase rapidly; the Zn extractable fraction is quite high (65.5%). Anthropogenic sources drive changes in heavy metal speciation. Changes in the river environment, such as pH and oxidation-reduction potential, also affect speciation. The reducible fraction of heavy metals in Baoxiang River sediments is most sensitive to pH. Potential ecological risk assessments for these five elements indicate that risks from Zn and Pb are mild to moderate in the middle and lower reaches of the river.<br style="line-height: normal; text-align: -webkit-auto; text-size-adjust: auto;" /

AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression

Multi-person pose estimation generally follows top-down and bottom-up paradigms. Both of them use an extra stage ($\boldsymbol{e.g.,}$ human detection in top-down paradigm or grouping process in bottom-up paradigm) to build the relationship between the human instance and corresponding keypoints, thus leading to the high computation cost and redundant two-stage pipeline. To address the above issue, we propose to represent the human parts as adaptive points and introduce a fine-grained body representation method. The novel body representation is able to sufficiently encode the diverse pose information and effectively model the relationship between the human instance and corresponding keypoints in a single-forward pass. With the proposed body representation, we further deliver a compact single-stage multi-person pose regression network, termed as AdaptivePose. During inference, our proposed network only needs a single-step decode operation to form the multi-person pose without complex post-processes and refinements. We employ AdaptivePose for both 2D/3D multi-person pose estimation tasks to verify the effectiveness of AdaptivePose. Without any bells and whistles, we achieve the most competitive performance on MS COCO and CrowdPose in terms of accuracy and speed. Furthermore, the outstanding performance on MuCo-3DHP and MuPoTS-3D further demonstrates the effectiveness and generalizability on 3D scenes. Code is available at https://github.com/buptxyb666/AdaptivePose.Comment: Submit to IEEE TCSVT; 11 pages. arXiv admin note: text overlap with arXiv:2112.1363