The analysis of burned human remains has been of great interest among forensic anthropologists largely due to the difficulty that their recovery, classification, reconstruction, and identification present. The main purpose of this analysis is to present histological methodology for the interpretation of bones altered by thermal processes. We include analyses of the microscopic changes among bones exposed to different temperatures, with the goal of establishing categories of histological morphology in relation to fire temperature. Samples of bone (ilium) were exposed systematically to controlled temperatures. Analysis of the resulting histological changes has allowed the formation of a clear four-stage classification of the alterations observed. This classification should prove useful in assessing bone changes in relation to temperature of exposure, particularly in cases where this temperature was previously not known.

<b><i>Introduction:</i></b> Mayo clinic classification (MCC) has been proposed in patients with autosomal dominant polycystic kidney disease (ADPKD) to identify who may experience a rapid decline of renal function. Our aim was to validate this predictive model in a population from southern Spain. <b><i>Methods:</i></b> ADPKD patients with measurements of height-adjusted total kidney volume (HtTKV) and baseline estimated glomerular filtration rate (eGFR) &#x3e;30 mL/min/1.73 m² were selected. Last eGFR was estimated with Mayo Clinic (MC) equation and bias and accuracy were studied. We also analyzed predictive capacity of MCC classes using survival analysis and Cox regression models. <b><i>Results:</i></b> We included 134 patients with a mean follow-up of 82 months. While baseline eGFR was not different between classes, last eGFR decreased significantly with them. eGFR variation rate was different according to the MCC class with a more rapid decline in 1C, 1D, and 1E classes. Final eGFR predicted was not significantly different from the real one, with an absolute bias of 0.6 ± 17.0 mL/min/1.73 m². P10 accuracy was low ranging from 37.5 to 59.5% in classes 1C, 1D, and 1E. Using MC equation, the rate of eGFR decline was underestimated in 1C, 1D, and 1E classes. Cox regression analysis showed that MCC class is a predictor of renal survival after adjusting with baseline eGFR, age, sex, and HtTKV, with 1D and 1E classes having the worst prognosis. <b><i>Conclusion:</i></b> MCC classification is able to identify patients who will undergo a more rapid decline of renal function in a Spanish population. Prediction of future eGFR with MC equation is acceptable as a group, although it shows a loss of accuracy considering individual values. The rate of eGFR decline calculated using MC equation can underestimate the real rate presented by patients of 1C, 1D, and 1E classes.

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Background and Aims. There is growing evidence of the effects of immunosuppressive agents on "immune targets" in renal transplantation. Immunological monitoring could indirectly measure the suppressive effect of these drugs and guide early preventive interventions in transplant recipients. Due to the selective antiproliferative effect of mycophenolate mofetil (MMF) on lymphocytes, our goal was to determine whether MMF modulates peripheral blood lymphocyte subsets (PBLS) in kidney allograft patients.

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