Linc-ROR and its spliced variants 2 and 4 are significantly up-regulated in esophageal squamous cell carcinoma

Objective(s): Similar characteristics of molecular pathways between cellular reprogramming events and tumorigenesis have been accentuated in recent years. Reprogramming-related transcription factors, also known as Yamanaka factors (OCT4, SOX2, KLF4, and c-MYC), are also well-known oncogenes promoting cancer initiation, progression, and cellular transformation into cancer stem cells. Long non-coding RNAs (lncRNAs) are a major class of RNA molecules with emerging roles in stem cell pluripotency, cellular reprogramming, cellular transformation, and tumorigenesis. The long intergenic non-coding RNA ROR (lincRNA-ROR, linc-ROR) acts as a regulator of cellular reprograming through sponging miR-145 that normally negatively regulates the expression of the stemness factors NANOG, OCT4, and SOX2. Materials and Methods: Here, we employed a real-time PCR approach to determine the expression patterns of linc-ROR and its two novel spliced variants (variants 2 and 4) in esophageal squamous cell carcinoma (ESCC). Results: The quantitative real-time RT-PCR results revealed a significant up-regulation of linc-ROR (P=0.0098) and its variants 2 (P=0.0250) and 4 (P=0.0002) in tumor samples of ESCC, compared to their matched non-tumor tissues obtained from the margin of same tumors. Our data also demonstrated a significant up-regulation of variant 4 in high-grade tumor samples, in comparison to the low-grade ones (P=0.04). Moreover, the ROC curve analysis demonstrated that the variant 4 of ROR has a potential to discriminate between tumor and non-tumor samples (AUC=0.66, P<0.05). Conclusion: Our data suggest a significant up-regulation of linc-ROR and its variants 2 and 4 in ESCC tissue samples. � 2016, Mashhad University of Medical Sciences. All rights reserved

Distribución espacial de la rugosidad en parcelas agrícolas en Provincia de Buenos Aires - Argentina Roughness spatial distribution in agricultural parcels in Buenos Aires Province, Argentina

<abstract language="por">O uso de imagens SAR para estimar e monitorar a umidade superficial do solo requer que se considere outros fatores que influenciam na retrodifusão do sinal-radar, entre os quais a rugosidade da cobertura da superfície à escala de centímetro é muito importante. Há diversos métodos para determinar a rugosidade, mas muitos são caros ou de operação de campo complexa. Neste trabalho, é apresentado um método versátil e econômico que usa máquina fotográfica e tela quadrada. Cada fotografia é processada numericamente obtendo a altura RMS, como parâmetro da rugosidade da cobertura. Por meio de técnicas geoestatísticas de krigagem é estimada a distribuição espacial da rugosidade. São mostradas experiências em áreas com cobertura de trigo, localizadas na área agrícola serrana da Província o Buenos Aires, Argentina. Os valores de RMS encontrados (29 mm < RMS < 48 mm) foram analisados com quatro critérios de rugosidade. É expressa sua utilidade para estimar o estado hídrico superficial de solos em áreas agrícolas mediante sua aplicação como entrada (input) nos modelos de retrodispersão de imagens SAR.<br>Use of SAR images for soil surface moisture estimation requires taking into account the other factors that influence the radar backscattering signal, among which the surface cover roughness at centimeter scale is very important. There are several methods to determine the roughness, but many are expensive or complex field operation. A versatile and economic method that uses a photographic camera and a girded screen is presented. Each picture is numerically processed obtaining the RMS height, as parameter of the crop-soil complex roughness. By means of krigging geostatistics techniques the spatial distribution of roughness is estimated. Experiences in parcels with wheat cover, located in the hill agricultural area of Buenos Aires Province, Argentina are shown. The found RMS values (29 mm < RMS < 48 mm) are analyzed with four roughness approaches. Their utility in order to estimate soil surface moisture status in agricultural parcels by means of their application like input into the SAR images backscattering models is stated