Analysis of the relationship between land surface temperature and wildfire severity in a series of landsat images

The paper assesses spatio-temporal patterns of land surface temperature (LST) and fire severity in the Las Hurdes wildfire of Pinus pinaster forest, which occurred in July 2009, in Extremadura (Spain), from a time series of fifteen Landsat 5 TM images corresponding to 27 post-fire months. The differenced Normalized Burn Ratio (dNBR) was used to evaluate burn severity. The mono-window algorithm was applied to estimate LST from the Landsat thermal band. The burned zones underwent a significant increase in LST after fire. Statistically significant differences have been detected between the LST within regions of burn severity categories. More substantial changes in LST are observed in zones of greater fire severity, which can be explained by the lower emissivity of combustion products found in the burned area and changes in the energy balance related to vegetation removal. As time progresses over the 27 months after fire, LST differences decrease due to vegetation regeneration. The differences in LST and Normalized Difference Vegetation Index (NDVI) values between burn severity categories in each image are highly correlated (r = 0.84). Spatial patterns of severity and post-fire LST obtained from Landsat time series enable an evaluation of the relationship between these variables to predict the natural dynamics of burned areas

The N-Terminal Domain of the Drosophila Retinoblastoma Protein Rbf1 Interacts with ORC and Associates with Chromatin in an E2F Independent Manner

The retinoblastoma (Rb) tumor suppressor protein can function as a DNA replication inhibitor as well as a transcription factor. Regulation of DNA replication may occur through interaction of Rb with the origin recognition complex (ORC).We characterized the interaction of Drosophila Rb, Rbf1, with ORC. Using expression of proteins in Drosophila S2 cells, we found that an N-terminal Rbf1 fragment (amino acids 1-345) is sufficient for Rbf1 association with ORC but does not bind to dE2F1. We also found that the C-terminal half of Rbf1 (amino acids 345-845) interacts with ORC. We observed that the amino-terminal domain of Rbf1 localizes to chromatin in vivo and associates with chromosomal regions implicated in replication initiation, including colocalization with Orc2 and acetylated histone H4.Our results suggest that Rbf1 can associate with ORC and chromatin through domains independent of the E2F binding site. We infer that Rbf1 may play a role in regulating replication directly through its association with ORC and/or chromatin factors other than E2F. Our data suggest an important role for retinoblastoma family proteins in cell proliferation and tumor suppression through interaction with the replication initiation machinery

Soil organic matter and texture estimation from visible–near infrared–shortwave infrared spectra in areas of land cover changes using correlated component regression

Land use changes due to natural and human-related factors, which include wildfires and crop abandonment, are among the most important drivers of soil degradation and demand regular monitoring. Proximal soil sensing in visible–near infrared–shortwave infrared spectral regions could offer a solution. However, to become operational, optimal combination of data and technique has to be defined. Thus, the purpose of this study was (a) to predict the soil organic matter (SOM) content and soil texture in areas of wildfire burns and crop abandonment in Aragón Province, Northern Spain, from their laboratory reflectance spectra using novel correlated components regression with a step-down variable selection algorithm (CCR-SD) and (b) to compare the CCR-SD and the partial least squares regression (PLSR) methods. The results obtained by the tested methods were similar. CCR-SD models showed high predictive capacity with coefficients of determination (R2) in the range of 0.80–0.86 and 0.70–0.87 for calibration and validation data sets, respectively, and the highest R2 value was attained in the SOM estimation. Moreover, the CCR-SD models stand out for the superior accuracy–parsimony relationship: the number of predictors varied from 16 (silt models) to 49 (SOM models). On average, the CCR-SD calibrations needed less than a half of the predictors employed in PLSR models. This research confirmed that CCR-SD can be used for monitoring SOM content and texture of soils from visible–near infrared–shortwave infrared spectra in the study area and, probably, in other areas of land use/land cover change and that CCR-SD can create highly parsimonious models that achieve results comparable with the commonly used PLSR method

Relationship between gene co-expression and sharing of transcription factor binding sites in Drosophila melanogaster

Motivation: In functional genomics, it is frequently useful to correlate expression levels of genes to identify transcription factor binding sites (TFBS) via the presence of common sequence motifs. The underlying assumption is that co-expressed genes are more likely to contain shared TFBS and, thus, TFBS can be identified computationally. Indeed, gene pairs with a very high expression correlation show a significant excess of shared binding sites in yeast. We have tested this assumption in a more complex organism, Drosophila melanogaster, by using experimentally determined TFBS and microarray expression data. We have also examined the reverse relationship between the expression correlation and the extent of TFBS sharing