An Energy Matching Vessel Segmentation Framework in 3-D Medical Images.

Accurate vascular segmentation from High Resolution 3-Dimensional (HR3D) medical scans is crucial for clinicians to visualize complex vasculature and diagnose related vascular diseases. However, a reliable and scalable vessel segmentation framework for HR3D scans remains a challenge. In this work, we propose a High-resolution Energy-matching Segmentation (HrEmS) framework that utilizes deep learning to directly process the entire HR3D scan and segment the vasculature to the finest level. The HrEmS framework introduces two novel components. Firstly, it uses the real-order total variation operator to construct a new loss function that guides the segmentation network to obtain the correct topology structure by matching the energy of the predicted segment to the energy of the manual label. This is different from traditional loss functions such as dice loss, which matches the pixels between predicted segment and manual label. Secondly, a curvature-based weight-correction module is developed, which directs the network to focus on crucial and complex structural parts of the vasculature instead of the easy parts. The proposed HrEmS framework was tested on three in-house multi-center datasets and three public datasets, and demonstrated improved results in comparison with the state-of-the-art methods using both topology-relevant and volumetric-relevant metrics. Furthermore, a double-blind assessment by three experienced radiologists on the critical points of the clinical diagnostic processes provided additional evidence of the superiority of the HrEmS framework.

Improved Performance for the Electrochemical Sensing of Acyclovir by Using the rGO-TiO2-Au Nanocomposite-Modified Electrode.

An electrochemical sensor for sensitive sensing of acyclovir (ACV) was designed by using the reduced graphene oxide-TiO2-Au nanocomposite-modified glassy carbon electrode (rGO-TiO2-Au/GCE). Transmission electron microscopy, X-ray diffractometer, and X-ray photoelectron spectroscopy were used to confirm morphology, structure, and composition properties of the rGO-TiO2-Au nanocomposites. Cyclic voltammetry and linear sweep voltammetry were used to demonstrate the analytical performance of the rGO-TiO2-Au/GCE for ACV. As a result, rGO-TiO2-Au/GCE exerted the best response for the oxidation of ACV under the pH of 6.0 PB solution, accumulation time of 80 s at open-circuit, and modifier amount of 7 µl. The oxidation peak currents of ACV increased linearly with its concentration in the range of 1-100 µM, and the detection limit was calculated to be 0.3 µM (S/N = 3). The determination of ACV concentrations in tablet samples also demonstrated satisfactory results.

Enzymatic photoelectrochemical bioassay based on hierarchical CdS/NiO heterojunction for glucose determination.

The design and development of a 3D hierarchical CdS/NiO heterojunction and its application in a self-powered cathodic photoelectrochemical (PEC) bioanalysis is introduced. Specifically, NiO nanoflakes (NFs) were in situ formed on carbon fibers via a facile liquid-phase deposition method followed by an annealing step and subsequent integration with CdS quantum dots (QDs). The glucose oxidase (GOx) was then coated on the photocathode to allow the determination of glucose. Under 5 W 410 nm LED light and at a working voltage of 0.0 V (vs. Ag/AgCl), this method can assay glucose concentrations down to 1.77×10-9 M. The linear range was 5×10-7 M to 1×10-3 M, and the relative standard deviation (RSD) was below 5%. The photocathodic biosensor achieved target detection with high sensitivity and selectivity. This work is expected to stimulate more passion in the development of innovative hierarchical heterostructures for advanced self-powered photocathodic bioanalysis. Design of 3D hierarchical CdS/NiO heterojunction and its application in a self-powered cathodic photoelectrochemical (PEC) bioanalysis.

Au-Hg/rGO with enhanced peroxidase-like activity for sensitive colorimetric determination of H2O2.

The Au-Hg amalgam anchored on the surface of reduced graphene oxide nanosheets (Au-Hg/rGO) has been synthesized successfully and characterized by various techniques such as transmission electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The Au-Hg/rGO nanocomposites were found to possess excellent peroxidase-like catalytic activity and can quickly catalyze the oxidation of colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue oxTMB in the presence of H2O2. The obvious color change offered accurate determination of the H2O2 concentration by recording the absorbance at 652 nm using a UV-vis spectrophotometer. The linear response range for H2O2 was from 5 µM to 100 µM and the detection limit was 3.25 µM (S/N = 3). Furthermore, a kinetic study indicated that the catalytic behavior of Au-Hg/rGO nanocomposites followed the typical Michaelis-Menten theory and Au-Hg/rGO nanocomposites showed good affinity for H2O2. We envision that the simple and sensitive colorimetric detection system holds great promising applications in clinical diagnostics and food and environment monitoring.

A voltammetric sensor based on reduced graphene oxide-hemin-Ag nanocomposites for sensitive determination of tyrosine.

A novel voltammetric sensor was designed and used for the determination of l-tyrosine (l-Tyr) by surface modification of a glassy carbon electrode with reduced graphene oxide-hemin-Ag (rGO-H-Ag) nanocomposites. The nanocomposites were synthesized by a facile one-pot hydrothermal method and characterized by means of transmission electron microscopy and Raman spectroscopy. The determination of l-Tyr was investigated by cyclic voltammetry and further quantified using differential pulse voltammetry. The results revealed a significant enhanced electrochemical oxidation effect for l-Tyr at the nanocomposites modified electrode. Two linear ranges from 0.1 to 100 µM and 100 to 1000 µM as well as a low detection limit of 30 nM (S/N = 3) were obtained. In addition, the sensor also demonstrated good selectivity, reproducibility and stability.

BRAF activated non-coding RNA (BANCR) promoting gastric cancer cells proliferation via regulation of NF-κB1.

BACKGROUND AND OBJECTIVE: Long non-coding RNA, BANCR, has been demonstrated to contribute to the proliferation and migration of tumors. However, its molecular mechanism underlying gastric cancer is still unknown. In present study, we investigated whether BANCR was involved in the development of gastric cancer cells via regulation of NF-κB1. METHODS: Human gastric cancer tissues were isolated as well as human gastric cell lines MGC803 and BGC823 were cultured to investigate the role of BANCR in gastric cancer. RESULTS: BANCR expression was significantly up-regulated in gastric tumor tissues and gastric cell lines. Down-regulation of BANCR inhibited gastric cancer cell growth and promoted cell apoptosis, and it also contributed to a significant decrease of NF-κB1 (P50/105) expression and 3'UTR of NF-κB1 activity. Overexpression of NF-κB1 reversed the effect of BANCR on cancer cell growth and apoptosis. MiroRNA-9 (miR-9) targeted NF-κB1, and miR-9 inhibitor also reversed the effects of BANCR on gastric cancer cell growth and apoptosis. CONCLUSION: BANCR was highly expressed both in gastric tumor tissues and in cancer cells. NF-κB1 and miR-9 were involved in the role of BANCR in gastric cancer cell growth and apoptosis.