Vasari Scoring System in Discerning between Different Degrees of Glioma and IDH Status Prediction: A Possible Machine Learning Application?

(1) The aim of our study is to evaluate the capacity of the Visually AcceSAble Rembrandt Images (VASARI) scoring system in discerning between the different degrees of glioma and Isocitrate Dehydrogenase (IDH) status predictions, with a possible application in machine learning. (2) A retrospective study was conducted on 126 patients with gliomas (M/F = 75/51; mean age: 55.30), from which we obtained their histological grade and molecular status. Each patient was analyzed with all 25 features of VASARI, blinded by two residents and three neuroradiologists. The interobserver agreement was assessed. A statistical analysis was conducted to evaluate the distribution of the observations using a box plot and a bar plot. We then performed univariate and multivariate logistic regressions and a Wald test. We also calculated the odds ratios and confidence intervals for each variable and the evaluation matrices with receiver operating characteristic (ROC) curves in order to identify cut-off values that are predictive of a diagnosis. Finally, we did the Pearson correlation test to see if the variables grade and IDH were correlated. (3) An excellent ICC estimate was obtained. For the grade and IDH status prediction, there were statistically significant results by evaluation of the degree of post-contrast impregnation (F4) and the percentage of impregnated area (F5), not impregnated area (F6), and necrotic (F7) tissue. These models showed good performances according to the area under the curve (AUC) values (>70%). (4) Specific MRI features can be used to predict the grade and IDH status of gliomas, with important prognostic implications. The standardization and improvement of these data (aim: AUC > 80%) can be used for programming machine learning software.

Detrimental effects of Bartonella henselae are counteracted by L-arginine and nitric oxide in human endothelial progenitor cells.

The recruitment of circulating endothelial progenitor cells (EPCs) might have a beneficial effect on the clinical course of several diseases. Endothelial damage and detachment of endothelial cells are known to occur in infection, tissue ischemia, and sepsis. These detrimental effects in EPCs are unknown. Here we elucidated whether human EPCs internalize Bartonella henselae constituting a circulating niche of the pathogen. B. henselae invades EPCs as shown by gentamicin protection assays and transmission electron microscopy (TEM). Dil-Ac-LDL/lectin double immunostaining and fluorescence-activated cell sorting (FACS) analysis of EPCs revealed EPC bioactivity after infection with B. henselae. Nitric oxide (NO) and its precursor l-arginine (l-arg) exert a plethora of beneficial effects on vascular function and modulation of immune response. Therefore, we tested also the hypothesis that l-arg (1-30 mM) would affect the infection of B. henselae or tumor necrosis factor (TNF) in EPCs. Our data provide evidence that l-arg counteracts detrimental effects induced by TNF or Bartonella infections via NO (confirmed by DETA-NO and L-NMMA experiments) and by modulation of p38 kinase phosphorylation. Microarray analysis indicated several genes involved in immune response were differentially expressed in Bartonella-infected EPCs, whereas these genes returned in steady state when cells were exposed to sustained doses of l-arg. This mechanism may have broad therapeutic applications in tissue ischemia, angiogenesis, immune response, and sepsis.