Vasculitis is a systemic disease characterized by immune-mediated injury of blood vessels. Current treatments for vasculitis, such as glucocorticoids and alkylating agents, are associated with significant side effects. Furthermore, the management of both small and large vessel vasculitis is challenging because of a lack of robust markers of disease activity. Recent research has advanced our understanding of the pathogenesis of both small and large vessel vasculitis, and this has led to the development of novel biologic therapies capable of targeting key cytokine and cellular effectors of the inflammatory cascade. In parallel, a diverse range of imaging modalities with the potential to monitor vessel inflammation are emerging. Continued expansion of combined structural and molecular imaging using positron emission tomography with computed tomography or magnetic resonance imaging may soon provide reliable longitudinal tracking of vascular inflammation. In addition, the emergence of radiotracers able to assess macrophage activation and immune checkpoint activity represents an exciting new frontier in imaging vascular inflammation. In the near future, these advances will allow more precise imaging of disease activity enabling clinicians to offer more targeted and individualized patient management.
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http://dx.doi.org/10.1161/ATVBAHA.118.310957 | DOI Listing |
Eur Thyroid J
January 2025
D Yabe, Department of Diabetes, Endocrinology and Nutrition, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan.
Immune checkpoint inhibitors (ICIs) frequently cause immune-related adverse events (irAEs), with thyroid irAEs being the most common endocrine-related irAEs. The incidence of overt thyroid irAEs ranged 8.9-22.
View Article and Find Full Text PDFPLoS Genet
January 2025
Department of Human Genetics, The University of Chicago, Chicago, Illinois, United States of America.
Understanding the genetic regulatory mechanisms of gene expression is an ongoing challenge. Genetic variants that are associated with expression levels are readily identified when they are proximal to the gene (i.e.
View Article and Find Full Text PDFPLoS One
January 2025
School of Economics and Management, Jiangxi Agricultural University, Nanchang, Jiangxi, China.
The utilization of manure resources is an important measure to promote the development of agricultural green low-carbon cycle and solve the challenges associated with the current large-scale development of the livestock and poultry breeding industry. Based on the survey data of pig farmers in Qingdao, Shandong Province, China, this paper constructs a theoretical analysis framework of pig breeding scale and technical cognition on the utilization behavior of livestock and poultry manure resources of pig farmers. The binary Logit model and the moderating effect model are used to deeply explore the scale effect of breeding scale on the utilization behavior of pig farmers' manure resources, and the moderating effect of technical cognition on the influence of breeding scale on the utilization behavior of manure resources.
View Article and Find Full Text PDFChem Biol Drug Des
January 2025
Department of Molecular Biology and Biochemistry, University of California, Irvine, California, USA.
A new series of 13 ritonavir-like inhibitors of human drug-metabolizing CYP3A4 was rationally designed to study the R side-group and R end-group interplay when the R side-group is represented by phenyl. Spectral, functional, and structural characterization showed no improvement in the binding affinity and inhibitory potency of R/R-phenyl inhibitors upon elongation and/or fluorination of R-Boc (tert-butyloxycarbonyl) or its replacement with benzenesulfonyl. When R is pyridine, the impact of R-phenyl-to-indole/naphthalene substitution was multidirectional and highly dependent on side-group stereo configuration.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway.
Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.
Purpose: This work tests the viability of semi-supervision for brain metastases segmentation.
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