A DIC based technique to measure the contraction of a skeletal muscle engineered tissue

Tissue engineering is a multidisciplinary science based on the application of engineering approaches to biologic tissue formation. Engineered tissue internal organization represents a key aspect to increase biofunctionality before transplant and, as regarding skeletal muscles, the potential of generating contractile forces is dependent on the internal fiber organization and is reflected by some macroscopic parameters, such as the spontaneous contraction. Here we propose the application of digital image correlation (DIC) as an independent tool for an accurate and noninvasive measurement of engineered muscle tissue spontaneous contraction. To validate the proposed technique we referred to the X-MET, a promising 3-dimensional model of skeletal muscle. The images acquired through a high speed camera were correlated with a custom-made algorithm and the longitudinal strain predictions were employed for measuring the spontaneous contraction. The spontaneous contraction reference values were obtained by studying the force response.The relative error between the spontaneous contraction frequencies computed in both ways was always lower than 0.15%. In conclusion, the use of a DIC based systemallows for an accurate and noninvasive measurement of biological tissues’ spontaneous contraction, in addition to the measurement of tissue strain field on any desired region of interest during electrical stimulation

Study of the preanalytical variables affecting the measurement of clinically relevant free-circulating microRNAs: focus on sample matrix, platelet depletion, and storage conditions

Introduction: Circulating microRNAs (miRNAs) are emerging as potential biomarkers. However, the lack of preanalytical and analytical standardization limits their use. The aim of this study was to determine the expression of different miRNAs in plasma according to different collection and storage conditions. Materials and methods: Venous blood from 10 volunteers was collected in tubes spray-coated with dipotassium salt of ethylendiaminetetraacetic acid, either with (plasma-preparation tube, PPT) or without (K2EDTA) gel separator. Platelet-poor plasma (PPP) was also obtained from K2EDTA plasma. After storage under different conditions, miRNA-enriched total RNA was isolated from plasma and reverse transcribed. A panel of 179 miRNAs was assayed by quantitative polymerase chain reaction and the results were analysed by GenEx software. Detectability and stability of miRNAs were determined. Results: The number of undetected miRNAs was: 18, 24, and 22 in PPT; 83, 43, and 20 in K2EDTA; and 76, 106, and 104 in PPP samples, for plasma immediately frozen at - 80°C and plasma stored for 24h at room temperature or 4°C, respectively. Circulating miRNA expression in PPT samples was not affected by storage delay or temperature, while the percentage of up- and down-regulated miRNA in K2EDTA and PPP samples ranged from 2%, and 1% to 7%, and 5%, respectively. Conclusions: Sample matrix, temperature and delay in storage strongly influence the expression level of plasma miRNAs. Our results indicate PPT tubes as the most suitable matrix to improve total miRNA detectability and stability, independently of temperature

A DIC Based Technique to Measure the Contraction of a Skeletal Muscle Engineered Tissue

Tissue engineering is a multidisciplinary science based on the application of engineering approaches to biologic tissue formation. Engineered tissue internal organization represents a key aspect to increase biofunctionality before transplant and, as regarding skeletal muscles, the potential of generating contractile forces is dependent on the internal fiber organization and is reflected by some macroscopic parameters, such as the spontaneous contraction. Here we propose the application of digital image correlation (DIC) as an independent tool for an accurate and noninvasive measurement of engineered muscle tissue spontaneous contraction. To validate the proposed technique we referred to the X-MET, a promising 3-dimensional model of skeletal muscle. The images acquired through a high speed camera were correlated with a custom-made algorithm and the longitudinal strain predictions were employed for measuring the spontaneous contraction. The spontaneous contraction reference values were obtained by studying the force response. The relative error between the spontaneous contraction frequencies computed in both ways was always lower than 0.15%. In conclusion, the use of a DIC based system allows for an accurate and noninvasive measurement of biological tissues' spontaneous contraction, in addition to the measurement of tissue strain field on any desired region of interest during electrical stimulation

A novel methodological approach to simultaneously extract high-quality total RNA and proteins from cortical and trabecular bone

Molecular differences between cortical and trabecular bone, of relevance to understanding the pathophysiological basis of bone diseases, can be determined only through effective isolation methods for RNA and proteins. Here we present a TRIzol-based method, which combines bone pulverization and homogenization to extract simultaneously total RNA and proteins from human cortical and trabecular bone from the same carrot. RNA integrity and purity were determined as the 260/280 nm and 260/230 nm absorbance ratios and the 28S/18S rRNA ratio. Protein integrity and quality were evaluated by Coomassie blue staining. Reverse transcription quantitative polymerase chain reaction and immunoblotting for bone-specific genes and proteins were performed to verify the suitability of the isolated material in downstream applications. The 260/280 nm and 260/230 nm absorbance ratios were, on average, less than or equal to 1.8. Bands on agarose gel were consistent with intact RNA, with mean 28S/18S ratios of 1.68 ± 0.35 and 1.88 ± 0.10 for cortical and trabecular bone, respectively. Band patterns after Coomassie blue staining confirmed protein integrity. Successful gene and protein expression analysis, with relevant differences between the two compartments, highlighted the suitability of the material in downstream applications. The method presented here is appropriate and effective for the study of human bone

Serum calprotectin as a marker of clinical and ultrasound-detected synovitis in early psoriatic and rheumatoid arthritis: results from a cross-sectional retrospective study

OBJECTIVES: We aimed to evaluate the correlation between serum calprotectin and clinical and ultrasonographic (US) variables in early-onset psoriatic arthritis (PsA) and controls with rheumatoid arthritis (RA). METHODS: In a retrospective cross-sectional study, including PsA and matched RA patients, 44 joint counts (TJC, SJC), calprotectin, ESR and CRP were measured. US of wrists and MCPs 1-5 was performed, with grey-scale (GS) and power Doppler (PD) scored 0-3 at each site, summed in a total score. The correlation between calprotectin, clinical and US variables was evaluated by Spearman's coefficient, the predictivity by calprotectin of US by regression. Secondary analyses separating polyarticular PsA and using different US definitions (GS>1, PD>1) were performed. RESULTS: 78 PsA and 78 RA were included (PsA male 32%; mean age 51.7 (13.5)). Calprotectin did not significantly differ in PsA and RA. In PsA, calprotectin correlated with GS score (ρ=0.340, p=0.008), PD score (ρ=0.292, p=0.023) and the presence of PD (ρ=0.263, p=0.042); in RA there were no significant correlations. In polyarticular PsA, a significant correlation between calprotectin and GS (ρ=0.369, p=0.019) and PD scores (ρ=0.363, p=0.021) was confirmed. In both PsA and RA, calprotectin and CRP significantly correlated, while SJC and TJC did not. In the regression analysis, calprotectin did not predict US variables in PsA. Similar results were achieved in RA. CONCLUSIONS: In early PsA, serum calprotectin correlates with US measures of disease activity. Our results provide preliminary evidence for the application of this biomarker in early PsA

Differences in Osteoimmunological Biomarkers Predictive of Psoriatic Arthritis among a Large Italian Cohort of Psoriatic Patients

(1) Background: In literature it is reported that 20–30% of psoriatic patients evolve to psoriatic arthritis over time. Currently, no specific biochemical markers can either predict progression to psoriatic arthritis or response to therapies. This study aimed to identify osteoimmunological markers applicable to clinical practice, giving a quantitative tool for evaluating pathological status and, eventually, to provide prognostic support in diagnosis. (2) Methods: Soluble (serum) bone and cartilage markers were quantified in 50 patients with only psoriasis, 50 psoriatic patients with psoriatic arthritis, and 20 healthy controls by means of multiplex and enzyme-linked immunoassays. (3) Results: Differences in the concentrations of matrix metalloproteases (MMPs), tissue inhibitors of metalloproteinases (TIMPs), receptor activator of nuclear factor kappa-B- ligand (RANK-L), procollagen type I N propeptide (PINP), C-terminal telopeptide of type I collagen (CTx-I), dickkopf-related protein 1 (DKK1), and sclerostin (SOST) distinguished healthy controls from psoriasis and psoriatic arthritis patients. We found that MMP2, MMP12, MMP13, TIMP2, and TIMP4 distinguished psoriasis from psoriatic arthritis patients undergoing a systemic treatment, with a good diagnostic accuracy (Area under the ROC Curve (AUC) > 0.7). Then, chitinase-3-like protein 1 (CHI3L1) and MMP10 distinguished psoriasis from psoriatic arthritis not undergoing systemic therapy and, in the presence of onychopathy, MMP8 levels were higher in psoriasis than in psoriatic arthritis. However, in these latter cases, the diagnostic accuracy of the identified biomarkers was low (0.5 < AUC < 0.7). (4) Conclusions. By highlighting never exploited differences, the wide osteoimmunological biomarkers panel provides a novel clue to the development of diagnostic paths in psoriasis and psoriasis-associated arthropathic disease

Additional file 1 of Enhanced molecular release from elderly bone samples using collagenase I: insights into fatty acid metabolism alterations

Additional file 1: Fig. S1. The SANIST AI-QC pipeline. Fig. S2. Fellowchart presentation of metabolite extraction in different experimental groups. Internal controls were added before the addition of first solvent for each group. Fig. S3. Data validation examples with locally constructed library in NIST software platform. The query molecules are in red, and the best match found in the library is in blue. Table S1. Functional Enrichment analysis for the modified metabolic pathways according to the identified metabolites according to similarity with HDMB. Table S2. Enrichment analysis for the pool of identified molecules’ chemical types. Table S3. Statistical comparison of cortical and trabecular bone metabolites extracted with different methods