Position-Regulated Electrostatic Interactions for Single Amino Acid Revealed by Aspartic Acid-Scanning Mutagenesis.

We have examined in this contribution the electrostatic interactions between single arginine and aspartic acid by analyzing the peptide-peptide binding characteristics involving arginine-aspartic acid, arginine-glycine, arginine-tryptophan and tryptophan-glycine interactions. The results of aspartic acid mutagenesis revealed that the interactions between arginine and aspartic acid have significant dependence on the position and composition of amino acids. While the primary interaction can be attributed to arginine-tryptophan contacts originated from the indole moieties with the main chains of 14-mers containing N-H and C=O moieties, pronounced enhancement could be identified in association with the electrostatic side-chain-side-chain interactions between arginine and aspartic acid.

Altered microbiome of serum exosomes in patients with acute and chronic cholecystitis.

Background: This study aimed to investigate the differences in the microbiota composition of serum exosomes from patients with acute and chronic cholecystitis.

Method: Exosomes were isolated from the serum of cholecystitis patients through centrifugation and identified and characterized using transmission electron microscopy and nano-flow cytometry. Microbiota analysis was performed using 16S rRNA sequencing.

Prevalence of inappropriateness of elemene injection for hospitalized cancer patients: a multicenter retrospective study.

Elemene injection could provide clinical benefit for the treatment of various cancers, but the clinical evidence is weak. Thus, its wide use in China has raised concerns about the appropriateness of its use. This was a multicenter retrospective study to evaluate the prevalence of inappropriateness of elemene injection for hospitalized cancer patients.

Unsupervised Tracklet Person Re-Identification.

Most existing person re-identification (re-id) methods rely on supervised model learning on per-camera-pair manually labelled pairwise training data. This leads to poor scalability in a practical re-id deployment, due to the lack of exhaustive identity labelling of positive and negative image pairs for every camera-pair. In this work, we present an unsupervised re-id deep learning approach.

WITHDRAWN: Epigenetic silence of HOTAIR contributes to the metastasis of pancreatic cancer via targeting miR-138.

Ahead of Print article withdrawn by publisher.