A learnable Gabor Convolution kernel for vessel segmentation.

Vessel segmentation is significant for characterizing vascular diseases, receiving wide attention of researchers. The common vessel segmentation methods are mainly based on convolutional neural networks (CNNs), which have excellent feature learning capabilities. Owing to inability to predict learning direction, CNNs generate large channels or sufficient depth to obtain sufficient features. It may engender redundant parameters. Drawing on performance ability of Gabor filters in vessel enhancement, we built Gabor convolution kernel and designed its optimization. Unlike traditional filter using and common modulation, its parameters are automatically updated using gradients in the back propagation. Since the structural shape of Gabor convolution kernels is the same as that of regular convolution kernels, it can be integrated into any CNNs architecture. We built Gabor ConvNet using Gabor convolution kernels and tested it using three vessel datasets. It scored 85.06%, 70.52% and 67.11%, respectively, ranking first on three datasets. Results shows that our method outperforms advanced models in vessel segmentation. Ablations also proved that Gabor kernel has better vessel extraction ability than the regular convolution kernel.

Conductive Polymer Composites Fabricated by Disposable Face Masks and Multi-Walled Carbon Nanotubes: Crystalline Structure and Enhancement Effect

Influenced by recent COVID-19, wearing face masks to block the spread of the epidemic has become the simplest and most effective way. However, after the people wear masks, thousands of tons of medical waste by used disposable masks will be generated every day in the world, causing great pressure on the environment. Herein, conductive polymer composites are fabricated by simple melt blending of mask fragments (mask polypropylene, short for mPP) and multi-walled carbon nanotubes (MWNTs). MWNTs were used as modifiers for composites because of their high strength and high conductivity. The crystalline structure, mechanical, electrical and thermal enhancement effect of the composites were investigated. MWNTs with high thermal stability acted the role of promoting the crystallisation of mPP by expediting the crystalline nucleation, leading to the improvement of amount for crystalline nucleus. MWNTs fibers interpenetrate with each other in mPP matrix to form conducting network. With 2.0 wt% MWNTs loading, the tensile strength and electrical conductivity of the composites were increased by 809% and 7 orders of magnitude. MWNTs fibers interpenetrate with each other in mPP matrix to form conducting network. Thus, more conducting paths were constructed to transport carriers. The findings may open a way for high value utilization of the disposable masks.

Teaching Pupils to Design Comparative Experiments with Web-Based Inquiry Unit During COVID-19 Pandemic: A Pilot Study

The COVID-19 pandemic caused many students away from the classroom. Its affecting region was so large and the inquiry learning had to move to online from offline. Although many studies had investigated the effectiveness of web-based inquiry learning, few of them conducted that under the pandemic. The pandemic took many new characters into education, such as the demand for the Internet. Hence, we conducted the pre-posttest quasi-experiment to investigate the effectiveness of online science inquiry during the pandemic. Under the instruction of teachers online, 30 fifth-grade students (19 males and 11 females) in a Chinese city completed a web-based inquiry learning program in the Web-based Inquiry Science Environment (WISE) platform. The experimental design ability test (EDAT) was conducted before and after web-based inquiry learning as the pre-test and post-test. The students’ attitude to web-based inquiry learning was also measured. The results showed, different from the studies before, the students’ score on experimental design ability decreased after web-based inquiry learning, especially in Asking Questions and Making Hypotheses subscales of EDAT significantly. No significant gender difference was detected. The students showed not a high attitude toward web-based inquiry learning. The possible factors causing that results and implications were discussed.

Impact of Dose Delays and Alternative Dosing Regimens on Pertuzumab Pharmacokinetics.

PERJETA (pertuzumab), administered with Herceptin (trastuzumab), is used in the treatment of human epidermal growth factor receptor 2-positive breast cancer. Pertuzumab is currently approved with an initial loading dose of 840 mg, followed by a 420-mg maintenance dose intravenously every 3 weeks. A reloading dose is required if there is a ≥6-week delay in treatment. In response to the potential treatment disruption due to COVID-19, the impact of dose delays and alternative dosing regimens on intravenous pertuzumab for human epidermal growth factor receptor 2-positive breast cancer treatment is presented. Simulations were conducted by using the validated population pharmacokinetic model for pertuzumab, and included (1) 4-, 6-, and 9-week dose delays of the 840 mg/420 mg every 3 weeks dosing regimen and (2) 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks alternative dosing regimens. Simulations were compared with the currently approved pertuzumab dosing regimen. The simulations in 1000 virtual patients showed that a dose reload (840 mg) is required following a dose delay of ≥6 weeks to maintain comparable Ctrough (lowest concentration before the next dose is given) levels to clinical trials. The 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks alternative dosing regimens decrease median steady-state Ctrough by ≈40% compared with the approved regimen, and <90% of patients will be above the target Ctrough . Thus, the alternative 840 mg/420 mg every 4 weeks and 840 mg every 6 weeks pertuzumab dosing regimens are not recommended. Flexibility for intravenous PERJETA-based regimens is available with an alternative route of pertuzumab administration (subcutaneous vs intravenous).