Metal artifacts reduction in kV-CT images with polymetallic dentures and complex metals based on MV-CBCT images in radiotherapy.

This paper proposes a metal artifact reduction method of using MV-CBCT images to correct metal artifacts in kV-CT images, especially for the complex metal artifacts caused by multi-metal interaction of patients with head and neck tumors. The different tissue regions are segmented in the MV-CBCT images to obtain template images and the metal region is segmented in the kV-CT images. Forward projection is performed to get sinogram of the template images, kV-CT images and metal region images. Artifact images can be reconstructed through those sonograms. Corrected images is generated by subtracting the artifact images from the original kV-CT images. After the first correction, the template images are generated again and brought into the previous step for iteration to get better correction result. CT data set of 7 patients are used in this study, compared with linear interpolation metal artifact (LIMAR) and normalized metal artifact reduction method, mean relative error of CT value is reduced by 50.5% and 63.3%, noise is reduced by 56.2% and 58.9%. The Identifiability Score of the tooth, upper/lower jaw, tongue, lips, masseter muscle and cavity in the corrected images by the proposed method have significantly improved (P < 0.05) than original images. The artifacts correction method proposed in this paper can effectively remove the metal artifacts in the images and greatly improve the CT value accuracy, especially in the case of multi-metal and complex metal implantation.

Boron concentration prediction from Compton camera image for boron neutron capture therapy based on generative adversarial network.

Prompt gamma monitoring for the prediction of boron concentration is valuable for the dose calculation of boron neutron capture therapy (BNCT). This work proposes to use generative adversarial network (GAN) to predict the boron distribution based on Compton camera (CC) imaging quickly and provide a scientific basis for its application in BNCT. The BNCT and Compton imaging process was simulated, then the image reconstructed from the simulation and the contour of skin from CT are used as input, and the distribution of boron concentration from PET data is set as the output to train the network. The structural similarity, peak signal-to-noise ratio, and root mean square error of the images generated by the trained network are improved significantly, and the ratio of the boron concentration between the tumor area and the normal tissue is improved from 1.55 to 3.85, which is much closer to the true value of 3.52. The trained network can optimize the original image within 0.83 s, which is much faster than iterative optimization. The proposed method could help to ease the current online monitoring problem of boron concentration on a computational level, thereby promoting the clinical development of BNCT technology.

A novel monitoring method for gamma irradiation facility based on radio-voltaic and photovoltaic effects.

This paper presents a novel monitoring method for gamma irradiation facility, which has the advantages of big view, accurate and working in event of a power outage. The state of radioactive source is monitored based on the property of electrical signal curves from photovoltaic devices when they are facing the source frame, and these electrical signals are generated by radio-voltaic and photovoltaic effects. GaAs based photovoltaic device was selected as the module to convert the rays near the radioactive source into electrical signals by the two above effects, and a Co-60 facility for irradiation processing was used as monitored object in this work. The influence of parameters such as the distance between the Co-60 frame and the photovoltaic device array, better electrical signals for forming curves on the monitoring effect were analyzed by Geant4. And the monitoring effect of the Co-60 frame in many cases was studied by Geant4 and experiment. Simulation results show that there are optimal parameters to achieve best monitoring effect, and the distribution of the Co-60 rods on the frame, the working condition and integrity of the Co-60 frame can be clearly reflected with this method. The consistency of the tendency of the electrical signal curves in verification experiment and Geant4 simulation verified the feasibility of this monitoring method. This method may provide new ideas for monitoring system designed for irradiation facility, nuclear power plants and other scenarios with rays.

D-Limonene Is a Potential Monoterpene to Inhibit PI3K/Akt/IKK-α/NF-κB p65 Signaling Pathway in Coronavirus Disease 2019 Pulmonary Fibrosis.

At the time of the prevalence of coronavirus disease 2019 (COVID-19), pulmonary fibrosis (PF) related to COVID-19 has become the main sequela. However, the mechanism of PF related to COVID (COVID-PF) is unknown. This study aimed to explore the key targets in the development of COVID-PF and the mechanism of d-limonene in the COVID-PF treatment. The differentially expressed genes of COVID-PF were downloaded from the GeneCards database, and their pathways were analyzed. d-Limonene was molecularly docked with related proteins to screen its pharmacological targets, and a rat lung fibrosis model was established to verify d-limonene's effect on COVID-PF-related targets. The results showed that the imbalance between collagen breakdown and metabolism, inflammatory response, and angiogenesis are the core processes of COVID-PF; and PI3K/AKT signaling pathways are the key targets of the treatment of COVID-PF. The ability of d-limonene to protect against PF induced by bleomycin in rats was reported. The mechanism is related to the binding of PI3K and NF-κB p65, and the inhibition of PI3K/Akt/IKK-α/NF-κB p65 signaling pathway expression and phosphorylation. These results confirmed the relationship between the PI3K-Akt signaling pathway and COVID-PF, showing that d-limonene has a potential therapeutic value for COVID-PF.

miR-21-5p promotes cell proliferation by targeting BCL11B in Thp-1 cells.

Acute myeloid leukemia (AML) is a highly heterogeneous disease that remains untreatable. MicroRNAs (miRNAs or miRs) play important roles in the pathogenesis of leukemia. miR-21 is highly expressed in multiple types of human cancer and displays oncogenic activities; however, the clinical significance of miR-21 in AML remains unclear. In the present study, it was demonstrated that miR-21 levels were high in patients with AML and in AML cell lines. Further experiments demonstrated that overexpression of miR-21 in Thp-1 human monocytes derived from acute mononuclear leukemia peripheral blood promoted cell proliferation, while downregulation of miR-21-5p, a mature sequence derived from the 5' end of the miR-21 stem-loop precursor (another mature sequence, miR-21-3p, is derived form 3' end of miR-21), inhibited cell proliferation. Specifically, it was observed that overexpression of miR-21 could promote the transition of Thp-1 cells into the S and G2/M phases of the cell cycle, as shown by flow cytometry. Furthermore, inhibition of miR-21-5p arrested cells in the S and G2/M phases. Finally, BCL11B was determined to be a functional target of miR-21-5p by luciferase assays. Our study revealed functional and mechanistic associations between miR-21 and BCL11B in Thp-1 cells, which could serve to guide clinical treatment of AML.

Catalpol Protects Against Pulmonary Fibrosis Through Inhibiting TGF-ß1/Smad3 and Wnt/ß-Catenin Signaling Pathways.

Idiopathic pulmonary fibrosis (IPF) is a fatal lung disease characterized by fibroblast proliferation and extracellular matrix remodeling; however, the molecular mechanisms underlying its occurrence and development are not yet fully understood. Despite it having a variety of beneficial pharmacological activities, the effects of catalpol (CAT), which is extracted from Rehmannia glutinosa, in IPF are not known. In this study, the differentially expressed genes, proteins, and pathways of IPF in the Gene Expression Omnibus database were analyzed, and CAT was molecularly docked with the corresponding key proteins to screen its pharmacological targets, which were then verified using an animal model. The results show that collagen metabolism imbalance, inflammatory response, and epithelial-mesenchymal transition (EMT) are the core processes in IPF, and the TGF-ß1/Smad3 and Wnt/ß-catenin pathways are the key signaling pathways for the development of pulmonary fibrosis. Our results also suggest that CAT binds to TGF-ßR1, Smad3, Wnt3a, and GSK-3ß through hydrogen bonds, van der Waals bonds, and other interactions to downregulate the expression and phosphorylation of Smad3, Wnt3a, GSK-3ß, and ß-catenin, inhibit the expression of cytokines, and reduce the degree of oxidative stress in lung tissue. Furthermore, CAT can inhibit the EMT process and collagen remodeling by downregulating fibrotic biomarkers and promoting the expression of epithelial cadherin. This study elucidates several key processes and signaling pathways involved in the development of IPF, and suggests the potential value of CAT in the treatment of IPF.