Evaluation of antigen-induced synovitis in a porcine model: Immunological, arthroscopic and kinetic studies.

BACKGROUND: Synovitis is an inflammation-related disease linked to rheumatoid arthritis, osteoarthritis, infections and trauma. This inflammation is accompanied by immune cells infiltration which initiates an inflammatory response causing pain, discomfort and affecting the normal joint function. The treatment of synovitis is based on the administration of anti-inflammatory drugs or biological agents such as platelet rich plasma and mesenchymal stem cells. However, the evaluation and validation of more effective therapies of synovitis requires the establishment of clinically relevant animal models. RESULTS: In this study, Large White pigs were pre-immunized to evaluate an antigen-induced synovitis. The immune monitoring of synovial fluids in this model allowed us the identification of IL-12p40 and T cell subsets as immune biomarkers. Moreover, the evolution of synovitis was performed by arthroscopic procedures and kinetic analysis. In summary, this paper describes an animal model of antigen-induced synovitis to be used in the evaluation of anti-inflammatory therapies. CONCLUSIONS: The novelty of this paper lies in the development of a clinically relevant model of synovitis which permits the simultaneous evaluation of synovitis from an immunological, surgical and kinetic point of view.

Diffused Matrix Format: a new storage and processing format for airborne hyperspectral sensor images.

At present, hyperspectral images are mainly obtained with airborne sensors that are subject to turbulences while the spectrometer is acquiring the data. Therefore, geometric corrections are required to produce spatially correct images for visual interpretation and change detection analysis. This paper analyzes the data acquisition process of airborne sensors. The main objective is to propose a new data format called Diffused Matrix Format (DMF) adapted to the sensor's characteristics including its spectral and spatial information. The second objective is to compare the accuracy of the quantitative maps derived by using the DMF data structure with those obtained from raster images based on traditional data structures. Results show that DMF processing is more accurate and straightforward than conventional image processing of remotely sensed data with the advantage that the DMF file structure requires less storage space than other data formats. In addition the data processing time does not increase when DMF is used.

IFDOTMETER: A New Software Application for Automated Immunofluorescence Analysis.

Most laboratories interested in autophagy use different imaging software for managing and analyzing heterogeneous parameters in immunofluorescence experiments (e.g., LC3-puncta quantification and determination of the number and size of lysosomes). One solution would be software that works on a user's laptop or workstation that can access all image settings and provide quick and easy-to-use analysis of data. Thus, we have designed and implemented an application called IFDOTMETER, which can run on all major operating systems because it has been programmed using JAVA (Sun Microsystems). Briefly, IFDOTMETER software has been created to quantify a variety of biological hallmarks, including mitochondrial morphology and nuclear condensation. The program interface is intuitive and user-friendly, making it useful for users not familiar with computer handling. By setting previously defined parameters, the software can automatically analyze a large number of images without the supervision of the researcher. Once analysis is complete, the results are stored in a spreadsheet. Using software for high-throughput cell image analysis offers researchers the possibility of performing comprehensive and precise analysis of a high number of images in an automated manner, making this routine task easier.