Changes in vegetation spring dates in the second half of the twentieth century

This study aims at estimating trends in spring phenology from vegetation index and air temperature at 2?m height. To this end, we have developed a methodology to infer spring phenological dates from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) time-series, which are then extrapolated to the period 1948–2006 with the help of Reanalysis data, using its 2?m height air temperature parameter. First, yearly NDVI is fitted to a double-logistic function for the whole extent of the GIMMS database (1981–2003). This fitting procedure allows us to describe, on a yearly basis, the NDVI evolution for each pixel through the estimation of six parameters which include the spring date. Retrieved spring date time-series are then upscaled to Reanalysis database resolution and compared to degree-day amounts. Those degree-day amounts are estimated for various thresholds in order to determine the best thresholds for their calculations on a pixel-by-pixel basis. Once the correct thresholds are identified by correlation with corresponding GIMMS spring date time-series, spring dates are estimated for the whole extent of the Reanalysis database (1948–2006). Finally, Mann–Kendall trend tests are conducted on degree-day-retrieved spring date time-series and trends are estimated only for those pixels that show statistically significant trends. These trends in spring occurrence have an average value of –0.03 days per year, but range between –0.9 and?+0.9 days per year, depending on the considered areas. Since the approach is based only on air temperature, retrieved spring dates for vegetation whose growth is limited by water are unreliable, as correlation analysis confirms. The obtained spring date trends show good coherence with previous studies and could be used for climate change impact studies, especially in polar and temperate areas, where the model is more reliable.     

Increased expression of cyclin D1 and the Rb tumor suppressor gene in c-K-ras transformed rat enterocytes

Activating mutations in the c-K-ras gene occur in about 40% of human colorectal carcinomas, yet the role of this oncogene in tumorigenesis is not known. We have developed a model cell culture system to study this problem, utilizing the immortalized but non-tumorigenic epithelial cell line IEC18, originally derived from normal rat intestine epithelium. These cells were cotransfected with the drug resistance selectable marker tk-neo and the plasmid pMIKcys, which encodes a mini human c-K-ras gene (15 kb) containing a cysteine mutation at codon 12. Drug resistant clones were isolated. Clones which also expressed the activated c-K-ras gene displayed a transformed morphology, decreased doubling time, increased level of diacylglycerol, anchorage independent growth in soft agar and an aneuploid karyotype and they were also tumorigenic when injected into nude mice. These clones also displayed increased expression, at both the mRNA and protein levels, of cyclin D1 and Rb. These findings may be of clinical relevance since human colorectal tumors also frequently display increased expression of both cyclin D1 and Rb. This model system may be useful for understanding the role and interrelationship between activation of the c-K-ras oncogene and increased expression of cyclin D1 and Rb in colorectal tumorigenesis.     

Designing a system to extract and interpret timed causal sentences in medical reports

Causal sentences are a main part of the medical explanations, providing the causes of diseases or showing the effects of medical treatments. In medicine, causal association is frequently related to time restrictions. So, some drugs must be taken before or after meals, being ‘after’ and ‘before’ temporary constraints. Thus, we conjecture that medical papers include a lot of time causal sentences. Causality involves a transfer of qualities from the cause to the effect, denoted by a directed arrow. An arrow connecting the node cause with the node effect is a causal graph. Causal graphs are an imagery way to show the causal dependencies that a sentence shows using plain text. In this article, we provide several programs to extract time causal sentences from medical Internet resources and to convert the obtained sentences in their equivalent causal graphs, providing an enlightening image of the relations that a text describes, showing the cause-effect links and the temporary constraints affecting their interpretation.     

Immunomodulatory Effect of Human Lactoferrin on Toll-like Receptors 2 Expression as Therapeutic Approach for Keratoconus

Keratoconus (KC) is a corneal disorder whose etiology shares a close relationship with Lactoferrin (LTF) dysregulation and Toll-like Receptors 2 (TLR2) overexpression. This study shows how these two important biomarkers are clinically and molecularly interrelated, increasing knowledge about KC pathophysiology, and opening the door to future therapies. In this prospective clinical study, serum and tear LTF concentrations were quantified in 90 KC patients and 60 controls. A correlation analysis with multiple blood and tear immunoinflammatory mediators, and KC-associated tomographic parameters, was performed. An in vitro study using HEK-Blue^TMhTLR2 cell cultures was also conducted to determine the expression and functionality of TLR2 under the influence of LTF treatment. As a result, a LTF decreased was observed in KC patients compared to controls (p < 0.0001), evidencing the strong correlation with TLR2 overexpression at systemic and ocular surface level, with inflammatory mediator upregulation and with KC severity. In stimulated cell cultures, TLR2 expression was decreased using 2 mg/mL of LTF. The levels of secreted embryonic alkaline phosphatase (SEAP) and interleukin-8 (IL-8) were also reduced in supernatants after LTF treatment. As conclusions, the dysregulation of LTF and TLR2 in the ocular surface of KC patients contributes to KC severity by maintaining a detrimental chronic immune–inflammatory state. The immunomodulatory properties of LTF on TLR2 expression suggest its potential as a therapeutic approach for KC.     

Global trends in NDVI-derived parameters obtained from GIMMS data

The Normalized Difference Vegetation Index (NDVI) has been proven to be useful to assess vegetation changes around the world, in spite of limitations such as sensitivity to cloud or snow contamination. In order to map vegetation changes at global scale, this study uses NDVI time series provided by the GIMMS (Global Inventory Modeling and Mapping Studies) group, which were fitted annually to a double logistic function. This fitting procedure allowed for retrieval of NDVI-derived parameters which were tested for trends using Mann–Kendall statistics. These trends were validated by comparison at 73 ground control points documented as change hotspots. The obtained trends for NDVI-derived parameters provide information to the remote sensing community on the regions more susceptible to having suffered changes, to complement other traditional methods such as national inventories and field work. Additionally, the validation procedure can be applied to any results obtained from a global dataset.     

A simplified method for estimating the total water vapor contentover sea surfaces using NOAA-AVHRR channels 4 and 5

A simplified method for estimating the total amount of atmospheric water vapor, W, over sea surfaces using NOAA-AVHRR Channels 4 and 5 is presented. This study has been carried out using simulated AVHRR data at 11 and 12 μm (with MODTRAN 3.5 code and the TIGR database) and AVHRR, PODAAC, and AVISO databases provided by the Louis Pasteur University (Strasbourg-France), NASA-NOAA, and Meteo France, respectively. The method is named linear atmosphere-surface temperature relationship (LASTR). It is based on a linear relationship between the effective atmospheric temperature in AVHRR Channel 4 and sea surface temperature. The LASTR method was compared with the linear split-window relationship (LSWR), which is based on a linear regression between W and the difference of brightness temperature measured in the same channels (ΔT=T4-TS). The results demonstrate the advantage of the LASTR method, which is capable of estimating W from NOAA-14 afternoon passes with a bias accuracy of 0.5 g cm^-2 and a standard deviation of 0.3 g cm^-2, compared with the W obtained by the AVISO database. In turn, a global bias accuracy of 0.1 g cm^-2 and a standard deviation within 0.6 g cm^-2 have been obtained in comparison with the W included in the PODAAC database derived from the special sensor microwave/imager (SSM/I) instrument     

Inhibition of Listeria monocytogenes by Lactobacillus sake strains of meat origin

The ability of two Lactobacillus sake strains of meat origin to inhibit the growth of Listeria monocytogenes at 4, 8, 15, 24 and 32°C in a conventional liquid media was investigated. Growth of L. monocytogenes was affected by Lac. sake strains at all temperatures. The inhibition was higher at 15, 24 and 32°C than at refrigeration temperatures. The inhibitory activity of both lactobacilli was similar perhaps due to the fact that Lac. sake 148 produces a bacteriocin inhibitory to L. monocytogenes, while Lac. sake 23 is a strong lactic acid producer. The antagonism exhibited by the lactobacilli on the L. monocytogenes strains seems to display a bacteriostatic rather than a bacteriocidal effect.     

In-scene atmospheric correction of hyperspectral thermal infrared images with nadir,horizontal, and oblique view angles

Atmospheric corrections for hyperspectral thermal images acquired with nadir, horizontal, and oblique views have typically relied on atmospheric modelling software, such as Moderate Resolution Atmospheric Transmission (MODTRAN), to estimate atmospheric parameters. Data-only corrections, which require only information from the scene, are more versatile and less labour intensive, but do not yet seem to have been applied to horizontal and oblique views. Here, we apply, and modify where necessary, one published data-only algorithm (in-scene atmospheric correction (ISAC)) to nadir, horizontal, and slanted views (The Aerospace Corporation's Spatially Enhanced Broadband Array Spectrograph System (SEBASS) and Telops Inc.'s Hyper-Cam data sets) to assess the applicability for different viewing geometries. We find that it successfully retrieves characteristic mineralogical emissivity spectra in scenes taken from all geometries. We also discuss additional corrections to the Hyper-Cam data set to correct for instrumental artefacts.     

Global land surface phenology trends from GIMMS database

A double logistic function has been used to describe global inventory mapping and monitoring studies (GIMMS) normalized difference vegetation index (NDVI) yearly evolution for the 1981 to 2003 period, in order to estimate land surface phenology parameter. A principal component analysis on the resulting time series indicates that the first components explain 36, 53 and 37% of the variance for the start, end and length of growing season, respectively, and shows generally good spatial homogeneity. Mann–Kendall trend tests have been carried out, and trends were estimated by linear regression. Maps of these trends show a global advance in spring dates of 0.38 days per year, a global delay in autumn dates of 0.45 days per year and a global increase of 0.8 days per year in the growing seasons validated by comparison with previous works. Correlations between retrieved phenological parameters and climate indices generally showed a good spatial coherence.     

First results towards building up a reliable in situ measurements database for LST algorithm validations using modular WSN: Northern Morocco campaigns case study

Climate has changed throughout the 4.5 million year history of the globe. At the same time, natural and human activities are affected directly by the global change of Earth system attributes, such as increase in temperature. Land surface temperature (LST) is an important but highly variable climate parameter. Its spatial distribution and the characteristic of its diurnal change over wide areas can only be determined with remote-sensing methods. The power of wireless sensor network (WSN) technology has provided the capability of developing large-scale systems for remote-sensing algorithm and sensor validation.

This article presents a new method (sensitivity ～0.1°C) for in situ LST measurements. The results of wide in situ LST campaigns carried out during 2009 in four distant and different sites located in northern Morocco are shown: (1) Kasr-Seghir, (2) Targha, (3) Tangier, and (4) Chefchaouen. For this purpose, we used two calibrated radiometers with thermal infrared bands, OSM101 and TESTO845. Finally, during these campaigns, a total of 28,531 measurements were made with the proposed wireless-LST (Wi-LST) system. The preliminary results show a wide variability of the measurements, which is in total accordance with the heterogeneity of the targets' nature. This is encouraging for we are interested in building up a reliable and consistent standard in situ LST measurements database for LST algorithm validations.