Novel Muscle Imaging in Inflammatory Rheumatic Diseases—A Focus on Ultrasound Shear Wave Elastography and Quantitative MRI

In recent years, imaging has played an increasing role in the clinical management of patients with rheumatic diseases with respect to aiding diagnosis, guiding therapy and monitoring disease progression. These roles have been underpinned by research which has enhanced our understanding of disease pathogenesis and pathophysiology of rheumatology conditions, in addition to their key role in outcome measurement in clinical trials. However, compared to joints, imaging research of muscles is less established, despite the fact that muscle symptoms are very common and debilitating in many rheumatic diseases. Recently, it has been shown that even though patients with rheumatoid arthritis may achieve clinical remission, defined by asymptomatic joints, many remain affected by lingering constitutional systemic symptoms like fatigue, tiredness, weakness and myalgia, which may be attributed to changes in the muscles. Recent improvements in imaging technology, coupled with an increasing clinical interest, has started to ignite new interest in the area. This perspective discusses the rationale for using imaging, particularly ultrasound and MRI, for investigating muscle pathology involved in common inflammatory rheumatic diseases. The muscles associated with rheumatic diseases can be affected in many ways, including myositis—an inflammatory muscle condition, and myopathy secondary to medications, such as glucocorticoids. In addition to non-invasive visual assessment of muscles in these conditions, novel imaging techniques like shear wave elastography and quantitative MRI can provide further useful information regarding the physiological and biomechanical status of the muscle

Quercetin ameliorates methotrexate-induced renal damage, apoptosis and oxidative stress in rats

Background: In the present study, the protective and therapeutic effects of quercetin (QE) on renal injury induced by methotrexate (MTX) have been examined. Materials and methods: A total of 24 male rats were divided into the following three groups: control group, MTX group, and MTX+QE group. Rats in MTX group received 20mg/kg of single dose of MTX, while those in MTX+QE group received 20mg/kg of single dose MTX, in addition to 15mg/kg of QE administered 30min prior to MTX and in the following 5-day period as a single daily dose. At the end of the experimental period, renal tissues were removed for histopathological and biochemical assessments. Results: Light microscopic examination showed a disruption of the renal structure in rats in MTX group in the form of tubular degeneration and dilation, with shedding of the tubular epithelial cells into the lumen. QE treatment was associated with less marked degenerative changes, with a similar histological appearance to that of controls. Furthermore, QE treatment resulted in decreased the number of apoptotic cells. Biochemical assessments showed significantly higher malondialdehyde (MDA) levels in MTX group as compared to control and MTX+QE groups. superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) levels showed a significant decrease in MTX group as compared to controls. However, QE significantly suppressed MDA level, compensated deficits in the anti-oxidant defenses [reduced SOD, GSH-Px, and CAT levels] in kidney tissue resulted from MTX administration. Conclusions: In conclusion, renal toxic effects of MTX may be alleviated by QE

Biomarker identification in breast cancer: beta-adrenergic receptor signaling and pathways to therapeutic response

Recent preclinical studies have associated beta-adrenergic receptor (β-AR) signaling with breast cancer pathways such as progression and metastasis. These findings have been supported by clinical and epidemiological studies which examined the effect of beta-blocker therapy on breast cancer metastasis, recurrence and mortality. Results from these studies have provided initial evidence for the inhibition of cell migration in breast cancer by beta-blockers and have introduced the beta-adrenergic receptor pathways as a target for therapy. This paper analyzes gene expression profiles in breast cancer patients, utilising Artificial Neural Networks (ANNs) to identify molecular signatures corresponding to possible disease management pathways and biomarker treatment strategies associated with beta-2-adrenergic receptor (ADRB2) cell signaling. The adrenergic receptor relationship to cancer is investigated in order to validate the results of recent studies that suggest the use of beta-blockers for breast cancer therapy. A panel of genes is identified which has previously been reported to play an important role in cancer and also to be involved in the beta-adrenergic receptor signaling