Heme-induced biomarkers associated with red meat promotion of colon cancer are not modulated by the intake of nitrite

Red and processed meat consumption is associated with the risk of colorectal cancer. Three hypotheses are proposed to explain this association, via heme-induced oxidation of fat, heterocyclic amines, or N-nitroso compounds. Rats have often been used to study these hypotheses, but the lack of enterosalivary cycle of nitrate in rats casts doubt on the relevance of this animal model to predict nitroso- and heme-associated human colon carcinogenesis. The present study was thus designed to clarify whether a nitrite intake that mimics the enterosalivary cycle can modulate hemeinduced nitrosation and fat peroxidation. This study shows that, in contrast with the starting hypothesis, drinking water added with nitrite to mimic the salivary nitrite content did not change the effect of hemoglobin on biochemicalmarkers linked to colon carcinogenesis, notably lipid peroxidation and cytotoxic activity in the colon of rat. However, ingested sodium nitrite increased fecal nitrosocompounds level, but their fecal concentration and their nature (iron-nitrosyl) would probably not be associated with an increased risk of cancer.We thus suggest that the rat model could be relevant for study the effect of red meat on colon carcinogenesis, in spite of the lack of nitrite in the saliva of rats.

Cosmic ray modulation of infra-red radiation in the atmosphere

Cosmic rays produce molecular cluster ions as they pass through the lower atmosphere. Neutral molecular clusters such as dimers and complexes are expected to make a small contribution to the radiative balance, but atmospheric absorption by charged clusters has not hitherto been observed. In an atmospheric experiment, a narrowband thermopile filter radiometer centred on 9.15 {\mu}m, an absorption band previously associated with infra-red absorption of molecular cluster ions, was used to monitor changes following events identified by a cosmic ray telescope sensitive to high-energy (>400 MeV) particles, principally muons. The average change in longwave radiation in this absorption band due to molecular cluster ions is 7 mWm sup{-2}. The integrated atmospheric energy density for each event is 2 Jm sup{-2}, representing an amplification factor of 10 sup{12} compared to the estimated energy density of a typical air shower. This absorption is expected to occur continuously and globally, but calculations suggest that it has only a small effect on climate.

Extended optimal estimation techniques for sea surface temperature from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI)

Sea surface temperature (SST) can be estimated from day and night observations of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) by optimal estimation (OE). We show that exploiting the 8.7 ��m channel, in addition to the ���traditional��� wavelengths of 10.8 and 12.0 ��m, improves OE SST retrieval statistics in validation. However, the main benefit is an improvement in the sensitivity of the SST estimate to variability in true SST. In a fair, single-pixel comparison, the 3-channel OE gives better results than the SST estimation technique presently operational within the Ocean and Sea Ice Satellite Application Facility. This operational technique is to use SST retrieval coefficients, followed by a bias-correction step informed by radiative transfer simulation. However, the operational technique has an additional ���atmospheric correction smoothing���, which improves its noise performance, and hitherto had no analogue within the OE framework. Here, we propose an analogue to atmospheric correction smoothing, based on the expectation that atmospheric total column water vapour has a longer spatial correlation length scale than SST features. The approach extends the observations input to the OE to include the averaged brightness temperatures (BTs) of nearby clear-sky pixels, in addition to the BTs of the pixel for which SST is being retrieved. The retrieved quantities are then the single-pixel SST and the clear-sky total column water vapour averaged over the vicinity of the pixel. This reduces the noise in the retrieved SST significantly. The robust standard deviation of the new OE SST compared to matched drifting buoys becomes 0.39 K for all data. The smoothed OE gives SST sensitivity of 98% on average. This means that diurnal temperature variability and ocean frontal gradients are more faithfully estimated, and that the influence of the prior SST used is minimal (2%). This benefit is not available using traditional atmospheric correction smoothing.

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de M��t��orologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright �� 2005 Royal Meteorological Society.

Infra-red laser ablative micromachining of parylene-C on SiO2substrates for rapid prototyping, high yield, human neuronal cell patterning

Cell patterning commonly employs photolithographic methods for the micro fabrication of structures on silicon chips. These require expensive photo-mask development and complex photolithographic processing. Laser based patterning of cells has been studied in vitro and laser ablation of polymers is an active area of research promising high aspect ratios. This paper disseminates how 800 nm femtosecond infrared (IR) laser radiation can be successfully used to perform laser ablative micromachining of parylene-C on SiO2 substrates for the patterning of human hNT astrocytes (derived from the human teratocarcinoma cell line (hNT)) whilst 248 nm nanosecond ultra-violet laser radiation produces photo-oxidization of the parylene-C and destroys cell patterning. In this work, we report the laser ablation methods used and the ablation characteristics of parylene-C for IR pulse fluences. Results follow that support the validity of using IR laser ablative micromachining for patterning human hNT astrocytes cells. We disseminate the variation in yield of patterned hNT astrocytes on parylene-C with laser pulse spacing, pulse number, pulse fluence and parylene-C strip width. The findings demonstrate how laser ablative micromachining of parylene-C on SiO2 substrates can offer an accessible alternative for rapid prototyping, high yield cell patterning with broad application to multi-electrode arrays, cellular micro-arrays and microfluidics.