33 research outputs found
Stable (C, O, S) isotopes and whole-rock geochemistry of carbonatites from Alto ParanaÃba Igneous Province, SE Brazil
Levels And Patterns Of Expression Of Hypoxia-inducible Factor-1α, Vascular Endothelial Growth Factor, Glucose Transporter-1 And Cd105 In Adenoid Cystic Carcinomas With High-grade Transformation
Aims: To compare the expression of proteins regulated by hypoxia between adenoid cystic carcinoma (ACC) with and without high-grade transformation (HGT). Methods and results: In eight ACC-HGT and 18 ACC without HGT, expression of hypoxia-inducible factor-1 (HIF-1α), vascular endothelial growth factor (VEGF), glucose transporter-1 (GLUT-1) and microvascular density (MVD) by CD105 (a hypoxia-inducible protein expressed in angiogenic endothelial cells) was determined. Expression levels of HIF-1α and VEGF as well as CD105-MVD did not differ significantly between: (i) transformed and conventional areas (TA and CA, respectively) of ACC-HGT, (ii) CA and ordinary ACC. HIF-1α was detected in 100% of cases and presented a diffuse expression pattern. No significant association was found between levels of HIF-1α expression and tumour size, metastasis and recurrence. GLUT-1 showed a prostromal expression pattern and was observed exclusively in TA (three of six cases) and in only three of 14 ACC. Conclusions: Both the absence of significant alterations in levels of expression of HIF-1α, VEGF and CD105 and the patterns of expression of HIF-1α and GLUT-1 suggest that hypoxia may not play a key role in the process of high-grade transformation of ACC. Although HIF-1α expression is a common finding in ACC, it cannot be used as a marker of tumour aggressiveness. © 2012 Blackwell Publishing Limited.605816825El-Naggar, A.K., Huvos, A.G., Adenoid cystic carcinoma (2005) World Health Organization classification of tumour. Pathology and genetics. Head and neck tumours, pp. 223-224. , Barnes L, Eveson JW, Reichart P, Sidransky D eds. Lyon: IARC PressSimpson, R.H., Pereira, E.M., Ribeiro, A.C., Abdulkadir, A., Reis-Filho, J.S., Polymorphous low-grade adenocarcinoma of the salivary glands with transformation to high-grade carcinoma (2002) Histopathology, 41, pp. 250-259Nagao, T., Gaffey, T.A., Serizawa, H., Dedifferentiated adenoid cystic carcinoma: a clinicopathologic study of 6 cases (2003) Mod. Pathol., 16, pp. 1265-1272Seethala, R.R., Hunt, J.L., Baloch, Z.W., Livolsi, V.A., Leon Barnes, E., Adenoid cystic carcinoma with high-grade transformation: a report of 11 cases and a review of the literature (2007) Am. J. Surg. Pathol., 31, pp. 1683-1694Skalová, A., Sima, R., Vanecek, T., Acinic cell carcinoma with high-grade transformation: a report of 9 cases with immunohistochemical study and analysis of TP53 and HER-2/neu genes (2009) Am. J. Surg. Pathol., 33, pp. 1137-1145Roy, P., Bullock, M.J., Perez-Ordoñez, B., Dardick, I., Weinreb, I., Epithelial-myoepithelial carcinoma with high-grade transformation (2010) Am. J. Surg. Pathol., 34, pp. 1258-1265Costa, A.F., Altemani, A., Vékony, H., Genetic profile of adenoid cystic carcinomas (ACC) with high-grade transformation versus solid type (2011) Cell. Oncol., 34, pp. 369-379Costa, A.F., Altemani, A., Hermsen, M., Current concepts on dedifferentiation/high-grade transformation in salivary gland tumors (2011) Patholog. Res. Int., 2011, p. 325965Cheuk, W., Chan, J.K., Ngan, R.K., Dedifferentiation in adenoid cystic carcinoma of salivary gland. An uncommon complication associated with an accelerated clinical course (1999) Am. J. Surg. Pathol., 23, pp. 465-472Harris, A.L., Hypoxia - a key regulatory factor in tumour growth (2002) Nat. Rev. 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Invited perspectives: How machine learning will change flood risk and impact assessment
Increasing amounts of data, together with more computing power and better machine learning algorithms to analyse the data, are causing changes in almost every aspect of our lives. This trend is expected to continue as more data keep becoming available, computing power keeps improving and machine learning algorithms keep improving as well. Flood risk and impact assessments are also being influenced by this trend, particularly in areas such as the development of mitigation measures, emergency response preparation and flood recovery planning. Machine learning methods have the potential to improve accuracy as well as reduce calculating time and model development cost. It is expected that in the future more applications will become feasible and many process models and traditional observation methods will be replaced by machine learning. Examples of this include the use of machine learning on remote sensing data to estimate exposure and on social media data to improve flood response. Some improvements may require new data collection efforts, such as for the modelling of flood damages or defence failures. In other components, machine learning may not always be suitable or should be applied complementary to process models, for example in hydrodynamic applications. Overall, machine learning is likely to drastically improve future flood risk and impact assessments, but issues such as applicability, bias and ethics must be considered carefully to avoid misuse. This paper presents some of the current developments on the application of machine learning in this field and highlights some key needs and challenges..Hydraulic Structures and Flood RiskWater Resource
Evolution of chemical composition of pyrochlore group minerals from phoscorites and carbonatites of the Khibina alkaline massif
Rare earth element enrichment in Palaeoproterozoic Fengzhen carbonatite from the North China block
Electron impact ionization and fragmentation of biofuels
We present in this article, a review of our recent experimental and theoretical studies published in the literature on electron impact ionization and fragmentation of the primary alcohols methanol, ethanol, 1-propanol and 1-butanol (C1–C4). We discuss the mass spectra (MS) of these alcohols, measured for the electron impact energy of 70 eV and also, total (TICS) and partial (PICS) ionization cross sections in the energy range from 10 to 100 eV, which revealed the probability of forming different cations, by either direct or dissociative ionization. These experimental TICS are summarized together with theoretical values, calculated using the Binary-encounter Bethe (BEB) and the independent atom model with the screening corrected additivity rule (IAM-SCAR) methods. Additionally, we compared data of appearance energies – AE and discussed the application of the extended Wannier theory to PICS in order to produce the ionization and ionic fragmentation thresholds for the electron impact of these alcohols