Proteoglycans Quantification in Tissue Engineered Cartilage using Sodium MRI at 11.7 T

Musculoskeletal disorders affect nearly 33% Americans annually, with injuries to cartilage due to osteoarthritis and sports injuries, accounting for a large fraction of these afflictions. There are currently no effective long-term treatments and cartilage tissue engineering is expected to play a leading role in cartilage treatment. Cartilage tissue engineering relies on the production of collagen and proteoglycans (PG), the two major extracellular matrix components of cartilage, as biomarkers for success. The current characterization and quantification methods for these biomarkers, such as histology and biochemical analyses, are invasive and cannot be performed in vivo. As sodium is known to bind with negatively charged PG, sodium MRI has potential to be used for PG quantification in tissue engineered cartilage. In this study, we present preliminary results of sodium MRI using a) Phantoms with 150 mM, 300 mM, and 500 mM sodium concentration prepared in 1% agarose gel and b) Scaffold free bovine chondrocyte pellets grown in culture medium for four weeks. Sodium MRI experiments were performed at room temperature on an 11.7 T Bruker Avance spectrometer (23Na freq = 132.30 MHz) using a 5 mm proton-sodium double tuned rf coil. Our preliminary results show that the sodium concentration changes correlate with sodium image intensity, which suggests a potential use of sodium MRI for PG quantification for tissue engineered cartilage

Measures of EID indicators.

Measures of EID indicators.</p

Grouping regression results of corporation size factors.

Grouping regression results of corporation size factors.</p

Regression test results of intra-industry peer group effect in EID.

Regression test results of intra-industry peer group effect in EID.</p

Grouping regression results of corporate governance factors.

Grouping regression results of corporate governance factors.</p

Correlation analysis.

Correlation analysis.</p

Descriptive statistical results of variables.

Descriptive statistical results of variables.</p

Robustness test results.

Robustness test results.</p

Regression test results of intra-industry peer group effect in EID.

Regression test results of intra-industry peer group effect in EID.</p

Image_1_Healthy dietary patterns, foods, and risk of glioma: A systematic review and meta-analysis of observational studies.TIF

BackgroundAccumulating epidemiological evidence has shown the favorable associations between healthy dietary patterns and risk of glioma, although the results remain inconclusive.ObjectiveWe therefore carried out a systematic review and meta-analysis to summarize the evidence from previous published studies, and to clarify the effects of healthy dietary patterns, typical healthy foods on glioma.MethodsPubMed, Web of Science, CNKI, and Wan fang data were searched from inception up to September 2022 for eligible studies. Two authors independently performed the literature search, study selection, data extraction, and quality assessment. Heterogeneity across studies was estimated using the Cochran’s Q test and I2 statistic. According to heterogeneity, the fixed-effects model or random-effects model was selected to obtain the relative risk (RR) of the merger. Subgroup analysis, sensitivity analysis and publication bias were also used for our analysis.ResultsTwenty-four articles that met the selection criteria, involving 7,278 glioma cases and 2,143,528 participants, were included in our analysis. There was a reduced risk of glioma in the highest compared with the lowest categories of healthy dietary patterns (RR = 0.58; 95% CI: 0.44–0.77; P 0.05).ConclusionFindings from this systematic review and meta-analysis indicate that higher intakes of healthy dietary patterns, vegetables, and fruits are significantly associated with the lower risk of glioma. Further studies, particularly with prospective design, are required to confirm our findings.</p