On the spectrum of operators concerned with the reduced singular Cauchy integral

We investigate spectrums of the reduced singular Cauchy operator and its real and imaginary components

Direct grafting of tetraaniline via perfluorophenylazide photochemistry to create antifouling, low bio-adhesion surfaces.

Conjugated polyaniline has shown anticorrosive, hydrophilic, antibacterial, pH-responsive, and pseudocapacitive properties making it of interest in many fields. However, in situ grafting of polyaniline without harsh chemical treatments is challenging. In this study, we report a simple, fast, and non-destructive surface modification method for grafting tetraaniline (TANI), the smallest conjugated repeat unit of polyaniline, onto several materials via perfluorophenylazide photochemistry. The new materials are characterized by nuclear magnetic resonance (NMR) and electrospray ionization (ESI) mass spectroscopy. TANI is shown to be covalently bonded to important carbon materials including graphite, carbon nanotubes (CNTs), and reduced graphene oxide (rGO), as confirmed by transmission electron microscopy (TEM). Furthermore, large area modifications on polyethylene terephthalate (PET) films through dip-coating or spray-coating demonstrate the potential applicability in biomedical applications where high transparency, patternability, and low bio-adhesion are needed. Another important application is preventing biofouling in membranes for water purification. Here we report the first oligoaniline grafted water filtration membranes by modifying commercially available polyethersulfone (PES) ultrafiltration (UF) membranes. The modified membranes are hydrophilic as demonstrated by captive bubble experiments and exhibit extraordinarily low bovine serum albumin (BSA) and Escherichia coli adhesions. Superior membrane performance in terms of flux, BSA rejection and flux recovery after biofouling are demonstrated using a cross-flow system and dead-end cells, showing excellent fouling resistance produced by the in situ modification

MiR-143 enhances adipogenic differentiation of 3T3-L1 cells through targeting the coding region of mouse pleiotrophin

AbstractAdipogenic differentiation of preadipocytes is a complex process regulated by various factors including miRNAs and cytokines. MiR-143 is a well known miRNA that enhances adipogenesis. Pleiotrophin (PTN), a heparin-binding growth factor, plays a negative role in adipogenesis. In this investigation, we demonstrate that PTN is a target gene of miR-143 during adipogenic differentiation in 3T3-L1 preadipocytes. MiR-143 down regulates PTN expression through interaction with a target site of miR-143 in the coding region of mouse PTN. The rare codons upstream of the target site regulate miR143-induced translational knockdown of PTN, which provides more insight into the mechanism of adipogenic differentiation

Retrieval-based face annotation by weak label regularized local coordinate coding

Singapore National Research Foundatio

HelixFold-Single: MSA-free Protein Structure Prediction by Using Protein Language Model as an Alternative

AI-based protein structure prediction pipelines, such as AlphaFold2, have achieved near-experimental accuracy. These advanced pipelines mainly rely on Multiple Sequence Alignments (MSAs) as inputs to learn the co-evolution information from the homologous sequences. Nonetheless, searching MSAs from protein databases is time-consuming, usually taking dozens of minutes. Consequently, we attempt to explore the limits of fast protein structure prediction by using only primary sequences of proteins. HelixFold-Single is proposed to combine a large-scale protein language model with the superior geometric learning capability of AlphaFold2. Our proposed method, HelixFold-Single, first pre-trains a large-scale protein language model (PLM) with thousands of millions of primary sequences utilizing the self-supervised learning paradigm, which will be used as an alternative to MSAs for learning the co-evolution information. Then, by combining the pre-trained PLM and the essential components of AlphaFold2, we obtain an end-to-end differentiable model to predict the 3D coordinates of atoms from only the primary sequence. HelixFold-Single is validated in datasets CASP14 and CAMEO, achieving competitive accuracy with the MSA-based methods on the targets with large homologous families. Furthermore, HelixFold-Single consumes much less time than the mainstream pipelines for protein structure prediction, demonstrating its potential in tasks requiring many predictions. The code of HelixFold-Single is available at https://github.com/PaddlePaddle/PaddleHelix/tree/dev/apps/protein_folding/helixfold-single, and we also provide stable web services on https://paddlehelix.baidu.com/app/drug/protein-single/forecast