LABRAD : Vol 41, Issue 2 - July 2015

An Overview of Immunoglobulin G4-Related Disease Plasma Neutrophil Gelatinase Associated Lipocalin (NGAL) a Marker of Acute Kidney Injury Celiac Disease: Biomarkers for Diagnosis and Monitoring Pathophysiology of Paroxysmal Nocturnal Haemoglobinuria and Diagnosis by Flowcytommetry Pathological Changes in Renal Transplant Biopsies not Related to Allo-Immune Mechanisms Myelodysplastic Syndromes Fluorescent Optical Method for Platelet Estimation: An Advanced Clinical Parameter in Laboratory Hematology Introduction of Beta-D-Glucan and Galactomannan - Testing for Diagnosis of Invasive Fungal Infections Basic Concepts in Hematopoietic Stem Cell Transplantationhttps://ecommons.aku.edu/labrad/1001/thumbnail.jp

A Rule Based Classification Model to Predict Colon Cancer Survival

Introduction: Colon cancer is the second most common cancer in the world and fourth most common cancer in both sexes in Iran, whose % 8.12 of all cancers in the covers. Predict the outcome of cancer and basic clinical data about it is very important. Data mining techniques can be used to predict cancer outcome. In our country, data mining studies on colon cancer, not covered as lung or breast cancers. It seems can be with identify factors influencing on survival and modify them, increased survival of colon cancer patients. Then according to high rates of colon cancer and the benefits of data mining to predict survival, in this study examined factors influencing on the survival of these patients. Materials and Methods: We use a dataset with four attributes that include the records of 570 patients in which 327 Patients (57.4%) and 243 (42.6%) patients were males and females respectively. Trees Random Forest (TRF), AdaBoost (AD), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of colon cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Results: Out of 570 patients, 338 patients and 232 patients were alive and dead respectively. In this Study, at first sight it seems that among this techniques, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (AD, RBFN and MLP). The accuracy, sensitivity, specificity and the area under ROC curve of TRF are 0.76, 0.808, 0.70 and 0.83, respectively. Conclusions: In this study seems that Trees Random Forest model (TRF) which is a rule based classification model was the best model with the highest level of accuracy. Therefore, this model is recommended as a useful tool for colon cancer survival prediction as well as medical decision making

Urinary NGAL measured after the first year post kidney transplantation predicts changes in glomerular filtration over one-year follow-Up

Currently, serum creatinine and estimated glomerular filtration rate (eGFR) together with albuminuria or proteinuria are laboratory markers used in long-term monitoring of kidney transplant recipients. There is a need for more sensitive markers that could serve as early warning signs of graft dysfunction. Our aim was to assess the urinary concentrations of neutrophil gelatinase-associated lipocalin (NGAL) as a predictor of changes in kidney transplant function after the first year post-transplantation. We prospectively recruited 109 patients with functioning graft at least one year after the transplantation, with no acute conditions over the past three months, during their control visits in kidney transplant ambulatory. Urinary NGAL measured on recruitment was twice higher in patients with at least 10% decrease in eGFR over 1-year follow-up compared to those with stable or improving transplant function. Baseline NGAL significantly predicted the relative and absolute changes in eGFR and the mean eGFR during the follow-up independently of baseline eGFR and albuminuria. Moreover, baseline NGAL significantly predicted urinary tract infections during the follow-up, although the infections were not associated with decreasing eGFR. Additionally, we assessed urinary concentrations of matrix metalloproteinase 9—NGAL complex in a subgroup of 77 patients and found higher levels in patients who developed urinary tract infections during the follow-up but not in those with decreasing eGFR. High urinary NGAL in clinically stable kidney transplant recipients beyond the first year after transplantation may be interpreted as a warning and trigger the search for transient or chronic causes of graft dysfunction, or urinary tract infection

Kidney histopathology in lethal human sepsis

PURPOSE: The histopathology of sepsis-associated acute kidney injury (AKI) in critically ill patients remains an understudied area. Previous studies have identified that acute tubular necrosis (ATN) is not the only driver of sepsis-AKI. The focus of this study was to identify additional candidate processes that may drive sepsis-AKI. To do this we immunohistochemically characterized the histopathological and cellular features in various compartments of human septic kidneys. METHODS: We studied the following histopathological features: leukocyte subsets, fibroblast activation, cellular proliferation, apoptosis, and fibrin deposition in the glomerulus and the tubulointerstitium in human post-mortem kidney biopsy tissue. Biopsy tissue samples from 27 patients with sepsis-AKI were collected 33 min (range 24-150) after death in the ICU. The unaffected part of the kidneys from 12 patients undergoing total nephrectomy as a result of renal carcinoma served as controls. RESULTS: Immunohistochemical analysis revealed the presence of more neutrophils and macrophages in the glomeruli and more neutrophils in the tubulointerstitium of renal tissue from patients with sepsis compared to control renal tissue. Type II macrophages were predominant, with some macrophages expressing both type I and type II markers. In contrast, there were almost no macrophages found in control kidneys. The number of activated (myo)fibroblasts was low in the glomeruli of sepsis-AKI kidneys, yet this was not observed in the tubulointerstitium. Cell proliferation and fibrin deposition were more pronounced in the glomeruli and tubulointerstitium of sepsis-AKI than in control kidneys. CONCLUSIONS: The extensive heterogeneity of observations among and within patients emphasizes the need to thoroughly characterize patients with sepsis-AKI in a large sample of renal biopsy tissue from patients with sepsis

Abstracts of the South African Renal Congress 2024, held in Johannesburg, South Africa, 18-20 October 2024

Abstracts of the South African Renal Congress 2024, held in Johannesburg, South Africa, 18-20 October 2024. Abstracts published as received

Henoch–schonlein purpura following exposure to SARS-CoV2 vaccine or infection: a systematic review and a case report

Background: Henoch–Schonlein purpura (HSP) is an IgA-mediated systemic small-vessel vasculitis (IgAV) that typically presents with a variable tetrad of symptoms. HSP if often preceded by respiratory tract infections, vaccinations, drugs or malignancies. During the recent COVID-19 pandemic multiples cases of HSP have been described after both infection and vaccination for SARS-CoV2. This study aims to perform a systematic review of literature and describe an additional complicated case of de-novo HSP appeared after the administration of the third dose of a mRNA-SARS-CoV2 vaccination. Methods: Electronic bibliographic research was performed to identify all the original reports describing cases of de-novo HSP or IgAV appeared after respiratory infection or vaccine administration for SARS-CoV2. We included all case series or case reports of patients who respected our inclusion and exclusion criteria. Results: Thirty-eight publications met our pre-defined inclusion criteria, for an overall number of 44 patients. All patients presented with palpable purpura variable associated with arthralgia, abdominal pain or renal involvement. Increased levels of inflammation markers, mild leukocytosis and elevated D-dimer were the most common laboratory findings. Up to 50% of patients presented proteinuria and/or hematuria. Almost all skin biopsies showed leukocytoclastic vasculitis, with IgA deposits at direct immunofluorescence in more than 50% of cases. Conclusions: Our results suggest that the immune response elicited by SARS-CoV2 vaccine or infection could play a role in the development of HSP. Current research suggests a possible role of IgA in immune hyperactivation, highlighted by early seroconversion to IgA found in some COVID-19 patients who develop IgA vasculitis