Urinary MicroRNAs, Possible Biomarkers for Early Detection of Patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD).

INTRODUCTION: Autosomal dominant polycystic kidney disease (ADPKD) is a prevalent renal disorder that causes abnormal growth of renal epithelial cells. The excessive expansion of renal epithelial cells can lead to cyst formation that is associated with serious renal complications. The early diagnosis of ADPKD makes the control of the disease somehow attainable. Regarding the diagnostic potential of microRNAs (miRs) as robust clinical biomarkers, the present study aimed to examine the potential of urinary miRs in early diagnosis of ADPKD in asymptomatic patients. METHODS: Urine samples were obtained from 20 asymptomatic ADPKD patients and 20 healthy control individuals and the miR content of the samples was extracted and converted to cDNA for the qRT-PCR experiment. The relative expressions of miR-17, miR-21, miR-143, and miR-223 were evaluated in ADPKD cases and healthy individuals. Serum levels of kidney function markers were also evaluated in the study participants. RESULTS: The urine samples of patients with ADPKD demonstrated higher levels of miR-17, miR-21, and miR-143 along with a lower miR-223 level compared to the healthy control group. CONCLUSION: This study revealed the differential expression of the studied miRs in ADPKD patients. Detection of miRs in urinary samples might provide a useful platform for early diagnosis of ADPKD in asymptomatic patients.  DOI: 10.52547/ijkd.7281.

Effect of green GO/Au nanocomposite on in-vitro amplification of human DNA.

Recently nanomaterials have attracted interest for increasing efficiency of polymerase chain reaction (PCR) systems. Here, the authors report on the usefulness of green graphene oxide/gold (GO/Au) nanocomposites for enhancement of PCR reactions. In this study, green GO/Au nanocomposite was prepared with Matricaria chamomilla extract as reducing/capping agent for site-directed nucleation of Auo atoms on surface of GO sheets. The as-prepared green GO/Au nanocomposites were then characterised with UV-VIS spectrophotometer and scanning electron microscopy. Later, the effect of these nanocomposites was studied on end-point and real-time PCR employed for amplification of human glyceraldehyde-3-phosphate dehydrogenase gene. The results indicated that GO/Au nanocomposite can improve both end-point and real-time PCR methods at the optimum concentrations, possibly through interaction between GO/Au nanocomposite and the materials in PCR reaction, and through providing increased thermal convection by the GO surface as well as the Au nanostructures. In conclusion, it can be suggested that green GO/Au nanocomposite is a biocompatible and eco-friendly candidate as enhancer of in-vitro molecular amplification strategies.

Renal structural image processing techniques: a systematic review.

BACKGROUND AND OBJECTIVE: Renal disease, such as nephritis and nephropathy, is very harmful to human health. Accordingly, how to achieve early diagnosis and enhance treatment for kidney disorders would be the important lesion. Nevertheless, the clues from the clinical data, such as biochemistry examination, serological examination, and radiological studies are quite indirect and limited. It is no doubt that pathological examination of kidney will supply the direct evidence. There is a requirement for greater understanding of image processing techniques for renal diagnosis to optimize treatment and patient care. METHODS: This study aims to systematically review the literature on publications that has been used image processing methods on pathological microscopic image for renal diagnosis. RESULTS: Nine included studies revealed image analysis techniques for the diagnosis of renal abnormalities on pathological microscopic image, renal image studies are clustered as follows: Glomeruli Segmentation and analysis of the Glomerular basement membrane (55/55%), Blood vessels and tubules classification and detection (22/22%) and The Grading of renal cell carcinomas (22/22%). CONCLUSIONS: A medical image analysis method should provide an auto-adaptive and no external-human action dependency. In addition, since medical systems should have special characteristics such as high accuracy and reliability then clinical validation is highly recommended. New high-quality studies based on Moore neighborhood contour tracking method for glomeruli segmentation and using powerful texture analysis techniques such as the local binary pattern are recommended.