Biomechanical properties analysis of posterior lumbar interbody fusion with transpedicular oblique screw fixation.

Objective: An alternative to conventional posterior lumbar interbody fusion (PLIF) is a PLIF with transpedicular oblique screw fixation system. An assessment of new fixation system's viability and efficacy is conducted through a comparison of its biomechanical properties with those of conventional PLIF.

Method: A comprehensive finite element model (FEM) of the lumbar regions L1-L5 was developed and the surgical segment L3-L4 was chosen to comprise the surgical models of both traditional PLIF and new PLIF.

Prosthesis optimization and mechanical analysis of artificial lumbar disc replacement.

Background: Artificial lumbar disc replacement is an effective method for the treatment of lumbosacral degenerative diseases. An appropriate artificial intervertebral disc device is of great significance for the maintenance of spinal stability and activity.

Methods: Two finite element models of ProDisc-L prosthesis replacement and improved prosthesis replacement were constructed by using the finite element model of complete lumbar L1-L5 segment established by CT image data.

Assembling High-Quality Lymph Node Clinical Target Volumes for Cervical Cancer Radiotherapy Using a Deep Learning-Based Approach.

Aim: The study aimed to explore an approach for accurately assembling high-quality lymph node clinical target volumes (CTV) on CT images in cervical cancer radiotherapy with the encoder-decoder 3D network.

Methods: 216 cases of CT images treated at our center between 2017 and 2020 were included as a sample, which were divided into two cohorts, including 152 cases and 64 controls, respectively. Para-aortic lymph node, common iliac, external iliac, internal iliac, obturator, presacral, and groin nodal regions were delineated as sub-CTV manually in the cohort including 152 cases.

Shrub and precipitation interactions shape functional diversity of nematode communities on the Qinghai-Tibet Plateau.

Land use and climate change alter biodiversity patterns and ecosystem functioning worldwide. Land abandonment with consequent shrub encroachment and changes in precipitation gradients are known factors in global change. Yet, the consequences of interactions between these factors on the functional diversity of belowground communities remain insufficiently explored.

[The Effects of Different Adaptive Statistical Iterative Reconstruction-V and Convolution Kernel Parameters on Auto-Segmentation Stability in CT Images].

The study aims to investigate the effects of different adaptive statistical iterative reconstruction-V（ ASiR-V） and convolution kernel parameters on stability of CT auto-segmentation which is based on deep learning. Twenty patients who have received pelvic radiotherapy were selected and different reconstruction parameters were used to establish CT images dataset. Then structures including three soft tissue organs (bladder, bowelbag, small intestine) and five bone organs (left and right femoral head, left and right femur, pelvic) were segmented automatically by deep learning neural network.

Cd and pb Co-Pollution Increased Ecological Risk and Changed Rhizosphere Characteristics of Arabidopsis Thaliana During Phytoremediation.

Previous studies have reported that co-contamination can result in more complex effects on the phytoremediation efficiency of plants relative to those of a single pollutant. However, the effect of co-contamination on plant rhizosphere characteristics has rarely been revealed. This study was carried out to assess the changes in soil pH, the content and fractionation of dissolved organic matter (DOM), and the metal solubility in the rhizosphere of Arabidopsis thaliana when treated with Cd and Pb simultaneously.

Quantitative Comparisons of Deep-learning-based and Atlas-based Auto- segmentation of the Intermediate Risk Clinical Target Volume for Nasopharyngeal Carcinoma.

Background: Manual segment target volumes were time-consuming and inter-observer variability couldn't be avoided. With the development of computer science, auto-segmentation had the potential to solve this problem.

Objective: To evaluate the accuracy and stability of Atlas-based and deep-learning-based auto-segmentation of the intermediate risk clinical target volume, composed of CTV2 and CTVnd, for nasopharyngeal carcinoma quantitatively.

[Using stacked neural network to improve the auto-segmentation accuracy of Graves' ophthalmopathy target volumes for radiotherapy].

Compared with the previous automatic segmentation neural network for the target area which considered the target area as an independent area, a stacked neural network which uses the position and shape information of the organs around the target area to regulate the shape and position of the target area through the superposition of multiple networks and fusion of spatial position information to improve the segmentation accuracy on medical images was proposed in this paper. Taking the Graves' ophthalmopathy disease as an example, the left and right radiotherapy target areas were segmented by the stacked neural network based on the fully convolutional neural network. The volume Dice similarity coefficient (DSC) and bidirectional Hausdorff distance (HD) were calculated based on the target area manually drawn by the doctor.

[Feasibility Study on Location of CT Images Using Convolutional Neural Networks].

Objective: To locate CT images by using the deep learning model based on convolutional neural network.

Methods: The AlexNet network was used as a deep learning model, which was preset by the transfer learning approach. Training samples were divided into 4 categories according to the vertebral body parts and labeled, and the data augmentation was used to improve the classification accuracy.

Exploring the community phylogenetic structure along the slope aspect of subalpine meadows in the eastern Qinghai-Tibetan Plateau, China.

Exploring the community assembly has been important for explaining the maintenance mechanisms of biodiversity and species coexistence, in that it is a central issue in community ecology. Here, we examined patterns of the community phylogenetic structure of the subalpine meadow plant community along the slope gradient in the Qinghai-Tibetan Plateau of China. We surveyed all species and constructed the phylogenetic tree of the plant community based on data from the Angiosperm Phylogeny Group III.

Degradation of bisphenol A in aqueous solution by persulfate activated with ferrous ion.

Degradation of bisphenol A (BPA) in aqueous solution was studied with high-efficiency sulfate radical (SO4(-·)), which was generated by the activation of persulfate (S2O8(2-)) with ferrous ion (Fe(2+)). S2O8(2-) was activated by Fe(2+) to produce SO4(-·), and iron powder (Fe(0)) was used as a slow-releasing source of dissolved Fe(2+). The major oxidation products of BPA were determined by liquid chromatography-mass spectrometer.

Photocatalytic degradation of 4-tert-octylphenol in a spiral photoreactor system.

A spiral photoreactor system (SPS) was developed for the degradation of 4-tert-octylphenol (4-t-OP) in aqueous phase. 4-t-OP was previously considered as a endocrine disrupting compound frequently present in water. The direct photodegradation reaction caused by the SPS was found to accord with the characteristic of apparent first-order reaction with reaction rate constant k = 4.