Human FGβ(Fibrinogen Beta) ELISA Kit

Renal cell carcinoma (RCC) is one of the common lethal urologic tumors. Recent studies revealed that SIRT1 might function as a tumor suppressor during the progression of RCC. In addition, studies showed that FGB expression was abnormally upregulated in RCC and related to the progress of RCC. This study aimed to define the function of SIRT1 and underlying mechanism in the RCC progression. The expression of SIRT1 and FGB in RCC specimens and cells were detected by immunoblotting and immunostaining. Luciferase reporter assay was performed to confirm FGB as the target gene of STAT3. Other methods including stable transfection, co-immunoprecipitation, Western blot, and in vitro and in vivo proliferation assays were also performed. Our results showed that SIRT1 expression was downregulated in RCC tissues compared to adjacent normal tissues and relatively high expression of SIRT1 conferred a better prognosis for patients. Next, we showed that SIRT1 overexpression inhibited RCC tumorigenesis both in vitro and in vivo. In addition, FGB expression was upregulated in RCC tissues and overexpressing SIRT1 reduced FGB expression levels. Furthermore, inhibition of RCC proliferation by SIRT1 overexpression was rescued by FGB overexpression, indicating that SIRT1 inhibited RCC proliferation by repressing FGB expression. Mechanistically, we confirmed that FGB was the target gene of STAT3, and SIRT1 repressed the expression of FGB by deacetylation of STAT3, leading to STAT3 destabilization and degradation. SIRT1 inhibited RCC tumorigenesis by downregulating FGB expression, and this novel SIRT1STAT3-FGB axis provided a potential target for RCC therapy.

Fiber Bragg grating (FGB) sensors offer a significant advantage for structural health monitoring due to their ability to simultaneously monitor both static and dynamic strain while being durable, lightweight, capable of multiplexing, and immune to electromagnetic interference. Drawing upon the benefits of FBG sensors, this research explores ways to use a series of long-gage fiber optic sensors for damage detection. Typically, structural identification relies upon determining the frequency and modal shapes of the system. However, relying purely on these parameters has proven challenging for damage detection as they are not sensitive enough. Long gage FBG sensors offer a promising alternative as the same sensors can be used for both frequency and modal analysis and overcome some of the disadvantages associated with traditional dynamic measurement methods through the strain and curvature analysis. Small scale experimental testing was performed using an aluminum beam instrumented with a series of FBG optical fiber sensors. Dynamic strain measurements were obtained as the beam was subjected to various support and loading conditions and damage was simulated by creating imperfect support constraints for the aluminum beam. From the dynamic strain measurements, the curvature as well as the natural frequencies of the structure can be determined. Additionally, a normalized parameter based on the strain and curvature from the dynamic strain measurements has been developed as a potential means of damage detection. Theoretical predictions and experimental data were compared and conclusions carried out. The preliminary results demonstrated potential of FBG longgage sensors to facilitate dynamic monitoring at both the local and global scale, thus allowing assessment of the structures health.