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High-permittivity dielectric pads, i.e., thin, flexible slabs, usually consisting of mixed ceramic powders and liquids, have been previously shown to increase the magnetic field at high and ultra high-fields in regions of low efficiency of transmit coils, thus improving the homogeneity of images. However, their material parameters can change with time, and some materials they contain are bio incompatible. This article presents an alternative approach replacing ceramic mixtures with a low-cost and stable artificial dielectric slab. The latter comprises a stack of capacitive grids realized using multiple printed-circuit boards. Results in this article show that the proposed artificial dielectric structure can obtain the same increase in the local transmit radiofrequency magnetic field distribution in a head phantom at 7 T as the conventional dielectric pad.

Oxidative stress plays a critical role in pulmonary fibrosis after acute lung injury (ALI), and epithelial-mesenchymal transition (EMT) events are involved in this process. The purpose of this study was to investigate the protective effects of melatonin, a natural antioxidant, on lipopolysaccharide (LPS)-induced EMT in human alveolar epithelial cells.

Human type II alveolar epithelial cell-derived A549 cells were incubated with LPS and melatonin alone or in combination for up to 24 h. The morphological changes of the treated cells were evaluated as well as indexes of oxidative stress. EMT-related proteins and the Nrf2 signaling pathway were detected by western blot analysis and immunofluorescence staining, respectively. To further investigate the underlying mechanisms, the effects of melatonin on cells transfected Nrf2 short hairpin RNA (shRNA) and the PI3K / GSK-3β signaling pathway were evaluated.

Treatment with melatonin upregulated Nrf2 expression, inhibited LPS-induced cell morphological change, rerotect human alveolar epithelial cells against oxidative stress by effectively inhibiting LPS-induced EMT, which was mostly dependent on upregulation of the Nrf2 pathway via the PI3K/GSK-3β axis. Further studies are warranted to investigate the role of melatonin for the treatment of oxidative stress-associated diseases, as well as pulmonary fibrosis after ALI.As a common ocular complication and microangiopathy of type 2 diabetic mellitus, diabetic retinopathy (DR) can lead to vision loss or even blindness in diabetic patients. At present, the treatment methods of DR mainly include laser and anti-VEGF therapies. Nevertheless, the higher cost and obvious side effects seriously disturb the normal life of DR patients. Promisingly, traditional Chinese medicine (TCM) has been demonstrated to be effective in treating DR by tonifying Qi and nourishing Yin, as well clearing heat and breeding body fluids, thus activating blood and removing blood stasis. Therefore, we screened the literatures on TCM treatment of DR through the web of science, ScienceDirect, PubMed, Google scholar and CNKI online databases. The representative prescriptions, herbs and extracts, and identified compounds for treatment of DR were further summarized and analyzed. Moreover, the detailed mechanisms and involved network pathways of herbs-compounds-targets were visualized by Cytoscape software. Meanwhile, we discussed the existing limitations and deficiencies of TCM on treatment of DR and gave corresponding measures. In conclusion, TCM could significantly ameliorate DR via anti-inflammation, anti-oxidative stress, anti-angiogenesis and anti-apoptosis.

Cardiovascular disease (CVD) is the leading cause of mortality and poses challenges for healthcare providers globally. Risk-based approaches for the management of CVD are becoming popular for recommending treatment plans for asymptomatic individuals. Several conventional predictive CVD risk models based do not provide an accurate CVD risk assessment for patients with different baseline risk profiles. Artificial intelligence (AI) algorithms have changed the landscape of CVD risk assessment and demonstrated a better performance when compared against conventional models, mainly due to its ability to handle the input nonlinear variations. Further, it has the flexibility to add risk factors derived from medical imaging modalities that image the morphology of the plaque. The integration of noninvasive carotid ultrasound image-based phenotypes with conventional risk factors in the AI framework has further provided stronger power for CVD risk prediction, so-called "integrated predictive CVD risk models."

of the review The objective of this review is (i) to understand several aspects in the development of predictive CVD risk models, (ii) to explore current conventional predictive risk models and their successes and challenges, and (iii) to refine the search for predictive CVD risk models using noninvasive carotid ultrasound as an exemplar in the artificial intelligence-based framework.

Conventional predictive CVD risk models are suboptimal and could be improved. This review examines the potential to include more noninvasive image-based phenotypes in the CVD risk assessment using powerful AI-based strategies.

Conventional predictive CVD risk models are suboptimal and could be improved. This review examines the potential to include more noninvasive image-based phenotypes in the CVD risk assessment using powerful AI-based strategies.Coronavirus Disease 2019 (COVID-19) is an infectious illness caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), originally identified in Wuhan, China (December 2019) and has since expanded into a pandemic. Here, we investigate metabolites present in several common spices as possible inhibitors of COVID-19. Specifically, 32 compounds isolated from 14 cooking seasonings were examined as inhibitors for SARS-CoV-2 main protease (Mpro), which is required for viral multiplication. Using a drug discovery approach to identify possible antiviral leads, in silico molecular docking studies were performed. Docking calculations revealed a high potency of salvianolic acid A and curcumin as Mpro inhibitors with binding energies of -9.7 and -9.2 kcal/mol, respectively. Binding mode analysis demonstrated the ability of salvianolic acid A and curcumin to form nine and six hydrogen bonds, respectively with amino acids proximal to Mpro's active site. Stabilities and binding affinities of the two identified natural spices were calculated over 40 ns molecular dynamics simulations and compared to an antiviral protease inhibitor (lopinavir). Molecular mechanics-generalized Born surface area energy calculations revealed greater salvianolic acid A affinity for the enzyme over curcumin and lopinavir with energies of -44.8, -34.2 and -34.8 kcal/mol, respectively. Using a STRING database, protein-protein interactions were identified for salvianolic acid A included the biochemical signaling genes ACE, MAPK14 and ESR1; and for curcumin, EGFR and TNF. This study establishes salvianolic acid A as an in silico natural product inhibitor against the SARS-CoV-2 main protease and provides a promising inhibitor lead for in vitro enzyme testing.This paper presents an automatic classification segmentation tool for helping screening COVID-19 pneumonia using chest CT imaging. The segmented lesions can help to assess the severity of pneumonia and follow-up the patients. In this work, we propose a new multitask deep learning model to jointly identify COVID-19 patient and segment COVID-19 lesion from chest CT images. Three learning tasks segmentation, classification and reconstruction are jointly performed with different datasets. 1-Methyl-3-nitro-1-nitrosoguanidine Our motivation is on the one hand to leverage useful information contained in multiple related tasks to improve both segmentation and classification performances, and on the other hand to deal with the problems of small data because each task can have a relatively small dataset. Our architecture is composed of a common encoder for disentangled feature representation with three tasks, and two decoders and a multi-layer perceptron for reconstruction, segmentation and classification respectively. The proposed model is evaluated and compared with other image segmentation techniques using a dataset of 1369 patients including 449 patients with COVID-19, 425 normal ones, 98 with lung cancer and 397 of different kinds of pathology. The obtained results show very encouraging performance of our method with a dice coefficient higher than 0.88 for the segmentation and an area under the ROC curve higher than 97% for the classification.Small cell lung cancer (SCLC), an aggressive and devastating malignancy, is characterized by rapid growth and early metastasis. Although most patients respond to first-line chemotherapy, the majority of patients rapidly relapse and have a relatively poor prognosis. Fortunately, immunotherapy, mainly including antibodies that target the cytotoxic T lymphocyte antigen-4 (CTLA-4), checkpoints programmed death-1 (PD-1), and programmed death-ligand 1 (PD-L1) to block immune regulatory checkpoints on tumor cells, immune cells, fibroblasts cells and endothelial cells, has achieved the milestone in several solid tumors, such as melanoma and non-small-cell lung carcinomas (NSCLC). In recent years, immunotherapy has made progress in the treatment of patients with SCLC, while its response rate is relatively low to monotherapy. Interestingly, the combination of immunotherapy with other therapy, such as chemotherapy, radiotherapy, and targeted therapy, preliminarily achieve greater therapeutic effects for treating SCLC. Combining different immunotherapy drugs may act synergistically because of the complementary effects of the two immune checkpoint pathways (CTLA-4 and PD-1/PD-L1 pathways). The incorporation of chemoradiotherapy in immunotherapy may augment antitumor immune responses because chemoradiotherapy can enhance tumor cell immunogenicity by rapidly inducing tumor lysis and releasing tumor antigens. In addition, since immunotherapy drugs and the molecular targets drugs act on different targets and cells, the combination of these drugs may achieve greater therapeutic effects in the treatment of SCLC. In this review, we focused on the completed and ongoing trials of the combination therapy for immunotherapy of SCLC to find out the rational combination strategies which may improve the outcomes for SCLC.Vibrio cholerae causes cholera and other infections, especially in children under five years of age. Cholera toxin (CT), toxin-coregulated pilus (TCP) and outer membrane protein W (OmpW) are three major virulence factors of this bacterium. The emergence of antimicrobial-resistant (AMR) strains and the absence of a comprehensive and flawless vaccine, has prompted other treatments. There are several advantages of egg yolk antibodies (IgY) over other immunotherapy agents, such as economic feasibility, high yield simple production, and better immune responsiveness to mammalian antigens due to phylogenetic distance. Accordingly, in the present study, IgYs against recombinant proteins CtxB (responsible for the CT binding to eukaryotic cells), TcpA (enhances bacterial attachment to enterocytes) and OmpW were produced, in single, coupled or combined forms, to evaluate and compare their protectivity potency. Immunoreactivity of IgYs were examined through protein and whole cell ELISA, their specificity was confirmed by western blotting, and their neutralizing effects on CT was evaluated in Y1 cell culture.