Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Does Independent Component Analysis Play a Role in Unmixing Hyperspectral Data?

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Selenium role in an human biomonitoring study applied to occupational health

Selenium functions as a co-factor for the reduction of antioxidant enzymes and is an important component of antioxidant enzymes. Dietary selenium significantly inhibits the induction of skin, liver, colon, and mammary tumours in experimental animals by a number of different carcinogens, as well as the induction of mammary tumours by viruses. Selenium shows a “U” shaped curve for functionality, whereby too little is as damaging as too much. At optimal levels, selenium may protect against the formation of DNA adducts, DNA or chromosome breakage, chromosome gain or loss, mitochondrial DNA, and telomere length and function. Aim of study: Investigate the relation between selenium and genotoxic effects in a human biomonitoring study applied to occupational health.

Insulin resistance does not play a major role in lipid and apolipoprotein profile in obese women

Background: Obesity is associated with increased atherogenesis through alterations in lipids, among other potential factors. Some of those abnormalities might be mediated by insulin resistance (IR). Aims: To compare lipid and apolipoprotein profile between lean and obese women; to evaluate the influence of IR on lipid and apolipoprotein profile, in obese women. Methods: We studied 112 obese and 100 normal-weight premenopausal women without known cardiovascular disease. Both groups were characterized for anthropometrics and a fasting blood sample was collected for assessment of glucose, insulin, triglycerides, cholesterol (total, LDL and HDL), and apolipoproteins A-I, A-II, B, C-II, C-III, and E; IR was assessed by the homeostatic model assessment (HOMA-IR). We compared lipids between obese and lean women; we looked for correlation of those levels with anthropometrics and IR (independently from anthropometrics) in obese women. Results: Obese women were characterized by mean age=34.6±8.3 years, BMI=43.6±7.9 kg/m2, waist circumference (Wc)=117.5±15.1 cm, and HOMA-IR=4.28±3.5. Lean women (age=34.2±8.3 years, BMI=21.4±1.7 kg/m2, Wc=71.7±5.8 cm, and HOMA-IR=1.21±0.76) presented with significantly lower levels of total cholesterol (P=0.001), LDL-cholesterol (P<0.001), and triglycerides (P<0.001); they presented higher levels of HDL-cholesterol (P<0.001), Apo A-I (P<0.001) and Apo A-II (P=0.037). HOMA-IR showed no significant association with apolipoproteins. HOMA-IR was inversely associated with HDL-cholesterol (P=0.048; r=−0.187) but that association disappeared when we adjusted for waist circumference. Only triglycerides were directly associated with HOMA-IR (P<0.001; r=0.343) independently from anthropometrics. Conclusion: We confirm that obese women present worst lipid and apolipoprotein profile. However, with the exception for triglycerides, insulin resistance per se does not play a major role in lipid and apolipoprotein abnormalities observed in obese women.

Cellular polarity in aging: role of redox regulation and nutrition

Cellular polarity concerns the spatial asymmetric organization of cellular components and structures. Such organization is important not only for biological behavior at the individual cell level, but also for the 3D organization of tissues and organs in living organisms. Processes like cell migration and motility, asymmetric inheritance, and spatial organization of daughter cells in tissues are all dependent of cell polarity. Many of these processes are compromised during aging and cellular senescence. For example, permeability epithelium barriers are leakier during aging; elderly people have impaired vascular function and increased frequency of cancer, and asymmetrical inheritance is compromised in senescent cells, including stem cells. Here, we review the cellular regulation of polarity, as well as the signaling mechanisms and respective redox regulation of the pathways involved in defining cellular polarity. Emphasis will be put on the role of cytoskeleton and the AMP-activated protein kinase pathway. We also discuss how nutrients can affect polarity-dependent processes, both by direct exposure of the gastrointestinal epithelium to nutrients and by indirect effects elicited by the metabolism of nutrients, such as activation of antioxidant response and phase-II detoxification enzymes through the transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2). In summary, cellular polarity emerges as a key process whose redox deregulation is hypothesized to have a central role in aging and cellular senescence.