Effect of Cold Deformation on the Microstructural and Property Uniformity of AlO/Cu Composites.

Copper matrix composites (Cu-MCs) have garnered significant attention due to their exceptional electrical, wear-resistant, and mechanical properties. Among them, AlO/Cu composites, reinforced with AlO, are a focal point in the field of high-strength, high-conductivity copper alloys, owing to their high strength, excellent electrical conductivity, and superior resistance to high-temperature softening. Cold deformation is an effective method for enhancing the mechanical properties of AlO/Cu composites.

Automatic grading of knee osteoarthritis with a plain radiograph radiomics model: combining anteroposterior and lateral images.

Objectives: To establish a radiomics-based automatic grading model for knee osteoarthritis (OA) and evaluate the influence of different body positions on the model's effectiveness.

Materials And Methods: Plain radiographs of a total of 473 pairs of knee joints from 473 patients (May 2020 to July 2021) were retrospectively analyzed. Each knee joint included anteroposterior (AP) and lateral (LAT) images which were randomly assigned to the training cohort and the testing cohort at a ratio of 7:3.

Codelivery of anti-CD47 antibody and chlorin e6 using a dual pH-sensitive nanodrug for photodynamic immunotherapy of osteosarcoma.

Osteosarcoma is a malignant tumor originating from bone tissue that progresses rapidly and has a poor patient prognosis. Immunotherapy has shown great potential in the treatment of osteosarcoma. However, the immunosuppressive microenvironment severely limits the efficacy of osteosarcoma treatment.

Use of MRI-based deep learning radiomics to diagnose sacroiliitis related to axial spondyloarthritis.

Objectives: This study aimed to evaluate the performance of a deep learning radiomics (DLR) model, which integrates multimodal MRI features and clinical information, in diagnosing sacroiliitis related to axial spondyloarthritis (axSpA).

Material & Methods: A total of 485 patients diagnosed with sacroiliitis related to axSpA (n = 288) or non-sacroiliitis (n = 197) by sacroiliac joint (SIJ) MRI between May 2018 and October 2022 were retrospectively included in this study. The patients were randomly divided into training (n = 388) and testing (n = 97) cohorts.

Effects of Cold Rolling Reduction Rate on the Microstructure and Properties of Cu-1.16Ni-0.36Cr Alloy after Thermo-Mechanical Treatment.

In this paper, a Cu-Ni-Cr alloy was prepared by adding a Ni-Cr intermediate alloy to copper. The effects of the cold rolling reduction rate on the microstructure and properties of the Cu-1.16Ni-0.

Deep Learning-Based Automated Magnetic Resonance Image Segmentation of the Lumbar Structure and Its Adjacent Structures at the L4/5 Level.

(1) Background: This study aims to develop a deep learning model based on a 3D Deeplab V3+ network to automatically segment multiple structures from magnetic resonance (MR) images at the L4/5 level. (2) Methods: After data preprocessing, the modified 3D Deeplab V3+ network of the deep learning model was used for the automatic segmentation of multiple structures from MR images at the L4/5 level. We performed five-fold cross-validation to evaluate the performance of the deep learning model.

Effects of biochar and zero valent iron on the bioavailability and potential toxicity of heavy metals in contaminated soil at the field scale.

Heavy metals (HMs) such as copper, nickel and chromium are toxic, so soil contaminated with these metals is of great concern. In situ HM immobilization by adding amendments can decrease the risk of contaminants being released. A five-month field-scale study was performed to assess how different doses of biochar and zero valent iron (ZVI) affect HM bioavailability, mobility, and toxicity in contaminated soil.

Homocysteine induces ferroptosis in endothelial cells through the systemXc/GPX4 signaling pathway.

Objectives: To investigate whether ferroptosis is involved in HCY-induced endothelial injury and the possible mechanism of HCY-induced ferroptosis.

Methods: EA. hy926 cells were cultured in vitro.

Deep learning-assisted knee osteoarthritis automatic grading on plain radiographs: the value of multiview X-ray images and prior knowledge.

Background: Knee osteoarthritis (OA) is harmful to people's health. Effective treatment depends on accurate diagnosis and grading. This study aimed to assess the performance of a deep learning (DL) algorithm based on plain radiographs in detecting knee OA and to investigate the effect of multiview images and prior knowledge on diagnostic performance.

Automatic Image Segmentation and Grading Diagnosis of Sacroiliitis Associated with AS Using a Deep Convolutional Neural Network on CT Images.

Ankylosing spondylitis (AS) is a chronic inflammatory disease that causes inflammatory low back pain and may even limit activity. The grading diagnosis of sacroiliitis on imaging plays a central role in diagnosing AS. However, the grading diagnosis of sacroiliitis on computed tomography (CT) images is viewer-dependent and may vary between radiologists and medical institutions.

[Evaluation of Energy Saving and Carbon Reduction Effect of Air Pollution Prevention and Control Action Plan and Innovation Intermediary Effect].

In order to evaluate the effect and mechanism of energy saving and carbon reduction of the Air Pollution Prevention and Control Action Plan (the Policy), on the basis of measuring the energy consumption and CO emissions of GDP per unit area in 281 prefecture-level cities and above from 2003 to 2017, the influence, intermediary effect of innovation, and urban heterogeneity of the Policy on energy saving and carbon reduction were explored by using a difference-in-difference model. The results showed that:① the Policy promoted a significant reduction of 17.60% in the energy consumption intensity and 19.

Sex-specific bone and muscular morphological features in ischiofemoral impingement: A three-dimensional study.

The study aimed to investigate how hip bone and muscular morphology features differ between ischiofemoral impingement (IFI) patients and healthy subjects among males and females. Three-dimensional models were reconstructed based on magnetic resonance imaging images from IFI patients and healthy subjects of different sexes. Bone morphological parameters and the cross-sectional area of the hip abductors were measured.

Ultrashort echo time magnetization transfer imaging of knee cartilage and meniscus after long-distance running.

Objective: To assess the detection of changes in knee cartilage and meniscus of amateur marathon runners before and after long-distance running using a 3D ultrashort echo time MRI sequence with magnetization transfer preparation (UTE-MT).

Methods: We recruited 23 amateur marathon runners (46 knees) in this prospective cohort study. MRI scans using UTE-MT and UTE-T2* sequences were performed pre-race, 2 days post-race, and 4 weeks post-race.

Comprehensive assessment of osteoporosis in lumbar spine using compositional MR imaging of trabecular bone.

Objectives: To comprehensively assess osteoporosis in the lumbar spine, a compositional MR imaging technique is proposed to quantify proton fractions for all the water components as well as fat in lumbar vertebrae measured by a combination of a 3D short repetition time adiabatic inversion recovery prepared ultrashort echo time (STAIR-UTE) MRI and IDEAL-IQ.

Methods: A total of 182 participants underwent MRI, quantitative CT, and DXA. Lumbar collagen-bound water proton fraction (CBWPF), free water proton fraction (FWPF), total water proton fraction (TWPF), bone mineral density (BMD), and T-score were calculated in three vertebrae (L2-L4) for each subject.

Analysis of influencing factors for prognosis of patients with ventricular septal perforation: A single-center retrospective study.

Background: Ventricular septal rupture (VSR) is a type of cardiac rupture, usually complicated by acute myocardial infarction (AMI), with a high mortality rate and often poor prognosis. The aim of our study was to investigate the factors influencing the long-term prognosis of patients with VSR from different aspects, comparing the evaluation performance of the Gensini score, Sequential Organ Failure Assessment (SOFA) score and European Heart Surgery Risk Assessment System II (EuroSCORE II) score systems.

Methods: This study retrospectively enrolled 188 patients with VSR between Dec 9, 2011 and Nov 21, 2021at the First Affiliated Hospital of Zhengzhou University.

Fine-Grained Assessment of COVID-19 Severity Based on Clinico-Radiological Data Using Machine Learning.

Background: The severe and critical cases of COVID-19 had high mortality rates. Clinical features, laboratory data, and radiological features provided important references for the assessment of COVID-19 severity. The machine learning analysis of clinico-radiological features, especially the quantitative computed tomography (CT) image analysis results, may achieve early, accurate, and fine-grained assessment of COVID-19 severity, which is an urgent clinical need.

Automated Magnetic Resonance Image Segmentation of Spinal Structures at the L4-5 Level with Deep Learning: 3D Reconstruction of Lumbar Intervertebral Foramen.

Objective: 3D reconstruction of lumbar intervertebral foramen (LIVF) has been beneficial in evaluating surgical trajectory. Still, the current methods of reconstructing the 3D LIVF model are mainly based on manual segmentation, which is laborious and time-consuming. This study aims to explore the feasibility of automatically segmenting lumbar spinal structures and increasing the speed and accuracy of 3D lumbar intervertebral foramen (LIVF) reconstruction on magnetic resonance image (MRI) at the L4-5 level.