Lack of microsatellite instability in gastrointestinal stromal tumors

The microsatellite instability (MSI) phenotype may constitute an important biomarker for patient response to immunotherapy, particularly to anti-programmed death-1 inhibitors. MSI is a type of genomic instability caused by a defect in DNA mismatch repair (MMR) proteins, which is present mainly in colorectal cancer and its hereditary form, hereditary nonpolyposis colorectal cancer. Gastrointestinal stromal tumor (GIST) development is associated with activating mutations of KIT proto-oncogene receptor tyrosine kinase (KIT) or platelet-derived growth factor receptor alpha (PDGFRA), which are oncogenes that predict the response to imatinib mesylate. In addition to KIT/PDGFRA mutations, other molecular alterations are important in GIST development. In GISTs, the characterization of the MSI phenotype is scarce and the results are not consensual. The present study aimed to assess MSI in a series of 79 GISTs. The evaluation of MSI was performed by pentaplex polymerase chain reaction comprising five markers, followed by capillary electrophoresis. The expression of MMR proteins was evaluated by immunohistochemistry. Regarding the KIT/PDGFRA/B-Raf proto-oncogene, serine/threonine kinase molecular profile of the 79 GISTs, 83.6% of the tumors possessed KIT mutations, 10.1% had PDGFRA mutations and 6.3% were triple wild-type. The mutated-PDGFRA cases were associated with gastric location and a lower mitotic index compared with KIT-mutated and wild-types, and these patients were more likely to be alive and without cancer. MSI analysis identified 4 cases with instability in one marker, however, additional evaluation of normal tissue and immunohistochemical staining of MMR proteins confirmed their microsatellite-stable nature. The results of the present study indicated that MSI is not involved in GIST tumorigenesis and, therefore, cannot serve as a biomarker to immunotherapy response in GIST.The present study was supported by The Brazilian National Council for Scientific and Technological Development (grant no. 476192/2013-7) and the São Paulo Research Foundation Doctoral Fellowship (grant no. 2013/25787-3).info:eu-repo/semantics/publishedVersio

A globally applicable PCR-based detection and discrimination of BK and JC polyomaviruses

BKV and JCV belong to the Polyomaviridae family and are opportunistic agents associated with complications in immunocompromised individuals. Although a single screening assay for both viruses would be convenient, the diversity of BKV and JCV serotypes and genotypes is a methodological challenge. In this paper, we developed a PCR method able to detect and segregate BKV and JCV, despite these genetic discrepancies. A duplex semi-nested PCR (duplex snPCR) was designed to target a conserved region (639nt-1516nt) within the VP2 gene. In the first PCR, a primer set common to all BKV and JCV serotypes/ genotypes was used, followed by a semi-nested PCR with internal primers for BKV and JCV segregation. The limit of detection of the duplex snPCR was as low as 10 copies of BKV or JCV plasmids/µL. Specific products were observed when JCV and BKV plasmids were mixed in the same reaction. In field sample testing, the duplex snPCR detected and distinguished both viruses in different biological samples. Results were confirmed by Sanger’s sequencing. The geographical complexity of BKV and JCV serotypes and genotypes imposes limits to a simple and universal method that could detect each virus. However, we describe here a sensitive and reliable PCR technique for BKV and JCV diagnosis that overcomes these limitations and could be universally applied

Effects of formulations containing dimethylaminoethanol (DMAE) acetoamidobenzoate and pidolate on the skin

The aim of this study was to analyze the effects of formulations containing DMAE pidolate and DMAE acetoamidobenzoate on the skin. Four areas of five swines were submitted to following treatments during 15 days: C (Control), S (Silicone = 80 % DC*LC Blend®), F1 (DMAE acetoamidobenzoate), F2 (DMAE pidolate). Measures of the thickness of epidermis and stratum corneum, and the density population of fibroblasts and leukocytes in papillary dermis were obtained. We also assessed possible variations in birefringence of dermis collagen bundles. Means of the data was compared using ANOVA followed by the Tukey test. The F1 and F2 groups showed a thicker epidermis than the control group (p < 0.01), but did not demonstrate a significant difference in the number of fibroblasts and leukocytes, as well as in the birefringent areas of collagen bundles, in comparison with the control groups. The DMAE-supplemented formulations enhanced viable epidermis thickness, but did not modify structures related with mechanical properties of the skin.Colegio de Farmacéuticos de la Provincia de Buenos Aire

CCQM-K55.b (Aldrin) : Final report: october 2012. CCQM-K55.b key comparison on the characterization of organic substances for chemical purity

Under the auspices of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM K55.b, was coordinated by the Bureau International des Poids et Mesures (BIPM) in 2010/2011. Nineteen national measurement institutes and the BIPM participated. Participants were required to assign the mass fraction of aldrin present as the main component in the comparison sample for CCQM-K55.b which consisted of technical grade aldrin obtained from the National Measurement Institute Australia that had been subject to serial recrystallization and drying prior to sub-division into the units supplied for the comparison. Aldrin was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of organic compounds of medium structural complexity [molar mass range 300 Da to 500 Da] and low polarity (pKOW < −2) for which related structure impurities can be quantified by capillary gas phase chromatography (GC). The key comparison reference value (KCRV) for the aldrin content of the material was 950.8 mg/g with a combined standard uncertainty of 0.85 mg/g. The KCRV was assigned by combination of KCRVs assigned by consensus from participant results for each orthogonal impurity class. The relative expanded uncertainties reported by laboratories having results consistent with the KCRV ranged from 0.3% to 0.6% using a mass balance approach and 0.5% to 1% using a qNMR method. The major analytical challenge posed by the material proved to be the detection and quantification of a significant amount of oligomeric organic material within the sample and most participants relying on a mass balance approach displayed a positive bias relative to the KCRV (overestimation of aldrin content) in excess of 10 mg/g due to not having adequate procedures in place to detect and quantify the non-volatile content—specifically the non-volatile organics content—of the comparison sample. There was in general excellent agreement between participants in the identification and the quantification of the total and individual related structure impurities, water content and the residual solvent content of the sample. The comparison demonstrated the utility of 1H NMR as an independent method for quantitative analysis of high purity compounds. In discussion of the participant results it was noted that while several had access to qNMR estimates for the aldrin content that were inconsistent with their mass balance determination they decided to accept the mass balance result and assumed a hidden bias in their NMR data. By contrast, laboratories that placed greater confidence in their qNMR result were able to resolve the discrepancy through additional studies that provided evidence of the presence of non-volatile organic impurity at the requisite level to bring their mass balance and qNMR estimates into agreement.Fil: Westwood, Steven. Bureau International des Poids et Mesures (BIPM); FranciaFil: Josephs, Ralf. Bureau International des Poids et Mesures (BIPM); FranciaFil: Choteau, Tiphaine. Bureau International des Poids et Mesures (BIPM); FranciaFil: Daireaux, Adeline. Bureau International des Poids et Mesures (BIPM); FranciaFil: Mesquida, Charline. Bureau International des Poids et Mesures (BIPM); FranciaFil: Wielgosz, Robert. Bureau International des Poids et Mesures (BIPM); FranciaFil: Rosso, Adriana. Instituto Nacional de Tecnología Industrial (INTI); ArgentinaFil: Ruiz de Arechavaleta, Mariana. Instituto Nacional de Tecnología Industrial (INTI); ArgentinaFil: Davies, Stephen. National Measurement Institute (NMIA); AustraliaFil: Wang, Hongjie. National Measurement Institute (NMIA); AustraliaFil: Pires do Rego, Eliane Cristina. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Marques Rodrigues, Janaína. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: de Freitas Guimarães, Evelyn. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Barreto Sousa, Marcus Vinicius. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Monteiro, Tânia Maria. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Alves das Neves Valente, Laura. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Marques Violante, Fernando Gustavo. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Rubim, Renato. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Almeida, Ribeiro. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Baptista Quaresma, Maria Cristina. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Nogueira, Raquel. Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMetro); BrasilFil: Windust, Anthony. Institute for National Measurement Standards. National Research Council Canada (NRC-INMS); CanadáFil: Dai, Xinhua. National Institute of Metrology (NIM); ChinaFil: Li, Xiaomin. National Institute of Metrology (NIM); ChinaFil: Zhang, Wei. National Institute of Metrology (NIM); ChinaFil: Li, Ming. National Institute of Metrology (NIM); ChinaFil: Shao, Mingwu. National Institute of Metrology (NIM); ChinaFil: Wei, Chao. National Institute of Metrology (NIM); ChinaFil: Wong, Siu-kay. Government Laboratory of Hong Kong SAR (GLHK); ChinaFil: Cabillic, Julie. Laboratoire National de Métrologie et d’Essais (LNE); FranciaFil: Gantois, Fanny. Laboratoire National de Métrologie et d’Essais (LNE); FranciaFil: Philipp, Rosemarie. Bundesanstalt für Materialforschung (BAM); AlemaniaFil: Pfeifer, Dietmar. Bundesanstalt für Materialforschung (BAM); AlemaniaFil: Hein, Sebastian. Bundesanstalt für Materialforschung (BAM); AlemaniaFil: Klyk-Seitz, Urszula-Anna. Bundesanstalt für Materialforschung (BAM); AlemaniaFil: Ishikawa, Keiichiro. National Metrology Institute of Japan (NMIJ); JapónFil: Castro, Esther. Centro Nacional de Metrología (CENAM); MéxicoFil: Gonzalez, Norma. Centro Nacional de Metrología (CENAM); MéxicoFil: Krylov, Anatoly. D. I. Mendeleev Institute for Metrology (VNIIM); RusiaFil: Lin, Teo Tang. Health Sciences Authority (HSA); SingapurFil: Kooi, Lee Tong. Health Sciences Authority (HSA); SingapurFil: Fernandes-Whaley, M. National Metrology Institute of South Africa (NMISA); SudáfricaFil: Prévoo, D. National Metrology Institute of South Africa (NMISA); SudáfricaFil: Archer, M. National Metrology Institute of South Africa (NMISA); SudáfricaFil: Visser, R. National Metrology Institute of South Africa (NMISA); SudáfricaFil: Nlhapo, N. National Metrology Institute of South Africa (NMISA); SudáfricaFil: de Vos, B. National Metrology Institute of South Africa (NMISA); SudáfricaFil: Ahn, Seonghee. Korea Research Institute of Standards and Science (KRISS); Corea del SurFil: Pookrod, Preeyaporn. National Institute of Metrology of Thailand (NIMT); TailandiaFil: Wiangnon, Kanjana. National Institute of Metrology of Thailand (NIMT); TailandiaFil: Sudsiri, Nittaya. National Institute of Metrology of Thailand (NIMT); TailandiaFil: Muaksang, Kittiya. National Institute of Metrology of Thailand (NIMT); TailandiaFil: Cherdchu, Chainarong. National Institute of Metrology of Thailand (NIMT); TailandiaFil: Gören, Ahmet Ceyhan. National Metrology Institute (TUBITAK UME); TurquíaFil: Bilsel, Mine. National Metrology Institute (TUBITAK UME); TurquíaFil: LeGoff, Thierry. LGC Limited; Reino UnidoFil: Bearden, Dan. National Institute of Standards and Technology (NIST); Estados UnidosFil: Bedner, Mary. National Institute of Standards and Technology (NIST); Estados UnidosFil: Duewer, David. National Institute of Standards and Technology (NIST); Estados UnidosFil: Hancock, Diane. National Institute of Standards and Technology (NIST); Estados UnidosFil: Lang, Brian. National Institute of Standards and Technology (NIST); Estados UnidosFil: Lippa, Katrice. National Institute of Standards and Technology (NIST); Estados UnidosFil: Schantz, Michele. National Institute of Standards and Technology (NIST); Estados UnidosFil: Sieber, John. National Institute of Standards and Technology (NIST); Estados Unido

ATLANTIC-CAMTRAPS: a dataset of medium and large terrestrial mammal communities in the Atlantic Forest of South America

Our understanding of mammal ecology has always been hindered by the difficulties of observing species in closed tropical forests. Camera trapping has become a major advance for monitoring terrestrial mammals in biodiversity rich ecosystems. Here we compiled one of the largest datasets of inventories of terrestrial mammal communities for the Neotropical region based on camera trapping studies. The dataset comprises 170 surveys of medium to large terrestrial mammals using camera traps conducted in 144 areas by 74 studies, covering six vegetation types of tropical and subtropical Atlantic Forest of South America (Brazil and Argentina), and present data on species composition and richness. The complete dataset comprises 53,438 independent records of 83 species of mammals, includes 10 species of marsupials, 15 rodents, 20 carnivores, eight ungulates and six armadillos. Species richness averaged 13 species (±6.07 SD) per site. Only six species occurred in more than 50% of the sites: the domestic dog Canis familiaris, crab-eating fox Cerdocyon thous, tayra Eira barbara, south American coati Nasua nasua, crab-eating raccoon Procyon cancrivorus and the nine-banded armadillo Dasypus novemcinctus. The information contained in this dataset can be used to understand macroecological patterns of biodiversity, community, and population structure, but also to evaluate the ecological consequences of fragmentation, defaunation, and trophic interactions. © 2017 by the Ecological Society of Americ