Carbon-coated selenium nanoparticles for photothermal therapy in choriocarcinoma cells.

Choriocarcinoma can be cured by chemotherapy, but this causes resistance and severe side effects that bring about physical and psychological consequences for patients. Therefore, there is still an urgent need to find other alternative minimally invasive therapies to halt the progression of choriocarcinoma. Novel carbon-coated selenium nanoparticles (C-Se) were successfully synthesized for choriocarcinoma photothermal therapy. C-Se combined with near-infrared laser irradiation can inhibit the proliferation of human choriocarcinoma (JEG-3) cells and induce cell apoptosis. C-Se killed cells and produced ROS under near-infrared laser irradiation. Finally, the therapeutic mechanism of C-Se + laser was explored showing that C-Se + laser influenced numerous biological processes. Taken together, C-Se exhibited significant potential for choriocarcinoma photothermal therapy.

A siamese network-based approach for vehicle pose estimation.

We propose a deep learning-based vehicle pose estimation method based on a monocular camera called FPN PoseEstimateNet. The FPN PoseEstimateNet consists of a feature extractor and a pose calculate network. The feature extractor is based on Siamese network and a feature pyramid network (FPN) is adopted to deal with feature scales. Through the feature extractor, a correlation matrix between the input images is obtained for feature matching. With the time interval as the label, the feature extractor can be trained independently of the pose calculate network. On the basis of the correlation matrix and the standard matrix, the vehicle pose changes can be predicted by the pose calculate network. Results show that the network runs at a speed of 6 FPS, and the parameter size is 101.6 M. In different sequences, the angle error is within 8.26° and the maximum translation error is within 31.55 m.

A Time Sequence Images Matching Method Based on the Siamese Network.

The similar analysis of time sequence images to achieve image matching is a foundation of tasks in dynamic environments, such as multi-object tracking and dynamic gesture recognition. Therefore, we propose a matching method of time sequence images based on the Siamese network. Inspired by comparative learning, two different comparative parts are designed and embedded in the network. The first part makes a comparison between the input image pairs to generate the correlation matrix. The second part compares the correlation matrix, which is the output of the first comparison part, with a template, in order to calculate the similarity. The improved loss function is used to constrain the image matching and similarity calculation. After experimental verification, we found that it not only performs better, but also has some ability to estimate the camera pose.

Efficacy and safety of PARP inhibitors in the treatment of advanced ovarian cancer: An updated systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Poly-ADP-ribose polymerase (PARP) inhibitors have emerged as a novel class of therapeutics for ovarian cancer (OC); however, PARP inhibitors present a class effect adverse-event profile. METHODS: A comprehensive literature review was performed for phase II or III randomized controlled trials (RCTs) published up to and including January 2020. We analyzed relevant clinical trials reporting the efficacy and toxicity profile of PARP inhibitors in patients with advanced OC. We estimated hazard ratios (HRs), incidences, risk ratios (RRs) and relative 95 % confidence intervals (95 % CI) for progression-free survival (PFS) and selected adverse events, using Stata 12.0 software package. RESULTS: The systematic review process yielded 10 eligible trials comprising 4,241 patients with advanced OC for survival analysis and 4553 patients for evaluation of toxicity profile. The pooled HR (PARP inhibitor vs control group) for PFS was 0.41 (95 % CI, 0.35-0.50) in overall patients, 0.51 (95 % CI, 0.40-0.64) in unselected setting, 0.32 (95 % CI, 0.26-0.39) in BRCA mutation setting, and 0.57 (95 % CI, 0.41-0.78) in wild-type setting. Patients treated with PARP inhibitors exhibited higher risks of all-grade and high-grade haematological toxicities, including anemia, leucopenia, neutropenia, thrombocytopenia (P < 0.05), and also presented higher risks of all-grade gastrointestinal side effects, including constipation, diarrhea, nausea, and vomiting as well as high-grade nausea and vomiting (P < 0.05). CONCLUSIONS: This study indicated that the use of PARP inhibitor provided substantial progression-free survival (PFS) benefits, irrespective of BRCA mutation status; however, treatment with PARP inhibitor was associated with increased risks of selected treatment-related adverse events.