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BACKGROUND: SELDI-TOF mass spectrometry (MS) is a high-throughput proteomic approach with potential for identifying novel forms of serum biomarkers of arthritis.

Objective. To identify serum protein biomarkers specific for rheumatoid arthritis (RA), using surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) technology. Conclusion. SELDI-TOF-MS technology allows rapid analysis of many serum samples, and use of decision tree boosting analysis as the main statistical method allowed us to propose a pattern of protein peaks specific for RA.

Objectives: Infliximab is the first anti-TNFα accepted by the Food and Drug Administration for use in inflammatory bowel disease treatment. Few clinical, biological and genetic factors tend to predict response in Crohn's disease (CD) patient subcategories, none widely predicting response to infliximab. Design and methods: Twenty CD patients showing clinical response or non response to infliximab were used for serum proteomic profiling on Surface Enhanced Lazer Desorption Ionisation-Time of Flight-Mass Spectrometry (SELDI-TOF-MS), each before and after treatment. Univariate and multivariate data analysis were performed for prediction and characterization of response to infliximab. Results: We obtained a model of classification predicting response to treatment and selected relevant potential biomarkers, among which platelet aggregation factor 4 (PF4). We quantified PF4, sCD40L and IL-6 by ELISA for correlation studies. Conclusions: This first proteomic pilot study on response to infliximab in CD suggests association between platelet metabolism and response to infliximab and requires validation studies on a larger cohort of patients.

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Background Proteinuria has been commonly reported in patients with COVID-19. However, only dipstick tests have been frequently used thus far. Here, the quantification and characterization of proteinuria were investigated and their association with mortality was assessed. Methods This retrospective, observational, single center study included 153 patients, hospitalized with COVID-19 between March 28th and April 30th, 2020, in whom total proteinuria and urinary α1-microglobulin (a marker of tubular injury) were measured. Association with mortality was evaluated, with a follow-up until May 7th, 2020. Results According to the Kidney Disease Improving Global Outcomes staging, 14% (n = 21) of the patients had category 1 proteinuria (< 150 mg/g of urine creatinine), 42% (n = 64) had category 2 (between 150 and 500 mg/g) and 44% (n = 68) had category 3 proteinuria (over 500 mg/g). Urine α1-microglobulin concentration was higher than 15 mg/g in 89% of patients. After a median follow-up of 27 [14;30] days, the mortality rate reached 18%. Total proteinuria and urinary α1-microglobulin were associated with mortality in unadjusted and adjusted models. This association was stronger in subgroups of patients with normal renal function and without a urinary catheter. Conclusions Proteinuria is frequent in patients with COVID-19. Its characterization suggests a tubular origin, with increased urinary α1-microglobulin. Tubular proteinuria was associated with mortality in COVID-19 in our restropective, observational study.

Background: Cystatin C-based equations are used to estimate GFR. However, three cystatin C immunoassays are on the market. Difference in cystatin C assays could have strong consequences on the accuracy and precision of cystatin C-based equations. We have performed an analytical study of these three assays and studied potential differences between assays on the precision of cystatin C-based equations. Methods:We have studied imprecision, recovery, linearity and interferences of the three immunoassays (nephelometric assay from Siemens and turbidimetric assays from Dako and Gentian). The impact of differences in cystatin C assays has been studied for the equations published by Levey (Siemens assay) and Grubb (Dako assay). Results Conclusion:The Siemens and Gentian assays seem analytically more valid than the Dako assay for cystatin C determination. Differences in cystatin C assays can lead to significant differences in cystatin C-based equations. However, these differences seem less important than the differences observed with creatinine and creatininebased equations.