Variability of rainfall in Suriname and the relation with ENSO-SST and TA-SST

Spatial correlations in the annual rainfall anomalies are analyzed using principle component analyses (PCA). Cross correlation analysis and composites are used to measure the influence of sea surface temperatures anomalies (SSTAs) in the tropical Atlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. The spatial and time variability in rainfall is mainly determined by the meridional movement of the Inter-tropical Convergence Zone (ITCZ). Rainfall anomalies tend to occur fairly uniformly over the whole country. In December-January (short wet season), there is a lagged correlation with the SSTAs in the Pacific region (<i>c</i>_lag3^Nino1+2=-0.63). The strongest correlation between the March-May rainfall (beginning long wet season) and the Pacific SSTAs is found with a correlation coefficient of <i>c_k</i>^Nino1+2=0.59 at lag 1 month. The June-August rainfall (end part of long wet season) shows the highest correlation with SSTAs in the TSA region and is about <i>c</i>=-0.52 for lag 0. In the September-November long dry season there is also a lagged correlation with the TSA SSTAs of about <i>c</i>_lag3=0.66. The different correlations and predictors can be used for seasonal rainfall predictions

Development of scenarios for future climate change in Suriname

This paper describes one way of developing climate change scenarios fortemperature and precipitation, using results of five atmospheric-ocean globalcirculation models (AO-GCMs). The scenarios are developed using theMAGICC/SCENGEN model and the GCMs, having a spatial resolution of 0.5º x 0.5ºlongitude/latitude. Four global emission scenarios, SRES A1, A2, B1, B2, and threetime horizons, year 2020, 2050 and 2080, are used. The results shows that there is arelative high correlation (0.66 to 0.86) between the monthly observed temperature dataand the modeled baseline data by the GCMs, while weak correlation (0.02 to 0.47) isfound between the monthly observed precipitation and modeled baseline data by theCSI296, GFDL90 and ECH498 model, and a relative high correlation (0.66 to 0.85) bythe HAD300 and CCSR96 model. Most of the GCMs follow the seasonal pattern ofthe temperature and precipitation in Suriname well. The model outputs show that forboth temperature and precipitation, the A1, B1 and B2 scenarios give similar results,which differ significantly from the A2 scenario. The climate change scenarios forSuriname lead to an annual increase in mean temperature up to 2.9ºC in 2080 forSRES A2, and 2.6ºC for SRES A1, B1, B2, reference to 1961-1990. For the annualprecipitation, an increase is expected up to 342.3 mm (16%) in 2080 for SRES A2 anda decrease in annual precipitation up to 102.6 mm (5%) in 2080 for SRES A1, B1, B2,reference to 1981-2000. The outputs of the SRES A1, B1, B2 indicate an increase inmean precipitation up till 2080 during January and April, and a decrease in meanprecipitation during May and December. The SRES A2 output indicates however anincrease in mean precipitation from December till March, and from July till October,and a decrease from April till June, and in November. The future increase in meantemperature will lead to an increase in evaporation/evapotranspiration andcorrespondingly changes in future precipitation. Wet and dry seasons in Suriname willbe affected, resulting in an overall increase or decrease of water resources. There istherefore a need to develop high resolution scenarios (scale of about 25-50 km), usingregional climate models (RCMs) in order to assess the impact of climate change onsmaller scales

Tumor slice culture system to assess drug response of primary breast cancer

Background The high incidence of breast cancer has sparked the development of novel targeted and personalized therapies. Personalization of cancer treatment requires reliable prediction of chemotherapy responses in individual patients. Effective selection can prevent unnecessary treatment that would mainly result in the unwanted side effects of the therapy. This selection can be facilitated by characterization of individual tumors using robust and specific functional assays, which requires development of powerful ex vivo culture systems and procedures to analyze the response to treatment. Methods We optimized culture methods for primary breast tumor samples that allowed propagation of tissue ex vivo. We combined several tissue culture strategies, including defined tissue slicing technology, growth medium optimization and use of a rotating platform to increase nutrient exchange. Results We could maintain tissue cultures for at least 7 days without losing tissue morphology, viability or cell proliferation. We also developed methods to determine the cytotoxic response of individual tumors to the chemotherapeutic treatment FAC (5-FU, Adriamycin [Doxorubicin] and Cyclophosphamide). Using this tool we designated tumors as sensitive or resistant and distinguished a clinically proven resistant tumor from other tumors. Conclusion This method defines conditions that allow ex vivo testing of individual tumor responses to anti-cancer drugs and therefore might improve personalization of breast cancer treatment

Attenuated XPC expression is not associated with impaired DNA repair in bladder cancer

Bladder cancer has a high incidence with significant morbidity and mortality. Attenuated expression of the DNA damage response protein Xeroderma Pigmentosum complementation group C (XPC) has been described in bladder cancer. XPC plays an essential role as the main initiator and damage-detector in global genome nucleotide excision repair (NER) of UV-induced lesions, bulky DNA adducts and intrastrand crosslinks, such as those made by the chemotherapeutic agent Cisplatin. Hence, XPC protein might be an informative biomarker to guide personalized therapy strategies in a subset of bladder cancer cases. Therefore, we measured the XPC protein expression level and functional NER activity of 36 bladder tumors in a standardized manner. We optimized conditions for dissociation and in vitro culture of primary bladder cancer cells and confirmed attenuated XPC expression in approximately 40% of the tumors. However, NER activity was similar to co-cultured wild type cells in all but one of 36 bladder tumors. We conclude, that (i) functional NER deficiency is a relatively rare phenomenon in bladder cancer and (ii) XPC protein levels are not useful as biomarker for NER activity in these tumors

Rainfall variability in Suriname and its relationship with the Tropical Pacific ENSO SST anomalies and the Atlantic SST anomalies

Spatial correlations (r) in the annual rainfall anomalies are analyzed using principlecomponent analyses (PCA). Cross correlation analysis and composites are used tomeasure the influence of sea surface temperatures anomalies (SSTAs) in the tropicalAtlantic and tropical Pacific Ocean with the seasonal rainfall in Suriname. It is shownthat the spatial and time variability in rainfall is mainly determined by the meridionalmovement of the Inter-tropical Convergence Zone (ITCZ). It occurs that the rainfallanomalies are fairly uniformly over the whole country. The strongest correlationbetween the December-January rainfall (short wet season) at station Cultuurtuin isfound with the SSTAs in the Pacific region and is about ckNino 1+2 = 0.59 at lag 1month. In March-May rainfall (beginning long wet season) there is a lagged correlationwith the SSTAs in the Pacific region (clag 3 Nino 1+2 = 0.59). The June-August rainfall(end part of long wet season) shows the highest correlation with SSTAs in the TSAregion and is about c = -0.52 for lag 0. In the September-November long dry seasonthere is also a lagged correlation with the TSA SSTAs of about clag 3 = 0.66. Thedifferent correlations and predictors can be used for seasonal rainfall predictions

Spatial aspects of oncogenic signalling determine the response to combination therapy in slice explants from Kras-driven lung tumours

A key question in precision medicine is how functional heterogeneity in solid tumours informs therapeutic sensitivity. We demonstrate that spatial characteristics of oncogenic signalling and therapy response can be modelled in precision-cut slices from Kras-driven non-small-cell lung cancer with varying histopathologies. Unexpectedly, profiling of in situ tumours demonstrated that signalling stratifies mostly according to histopathology, showing enhanced AKT and SRC activity in adenosquamous carcinoma, and mitogen-activated protein kinase (MAPK) activity in adenocarcinoma. In addition, high intertumour and intratumour variability was detected, particularly of MAPK and mammalian target of rapamycin (mTOR) complex 1 activity. Using short-term treatment of slice explants, we showed that cytotoxic responses to combination MAPK and phosphoinositide 3-kinase-mTOR inhibition correlate with the spatially defined activities of both pathways. Thus, whereas genetic drivers determine histopathology spectra, histopathology-associated and spatially variable signalling activities determine drug sensitivity. Our study is in support of spatial aspects of signalling heterogeneity being considered in clinical diagnostic settings, particularly to guide the selection of drug combinations