A flare in the optical spotted in the changing-look Seyfert NGC 3516

Context. We present observations from the short-term intensive optical campaign (from September 2019 to January 2020) of the changing-look Seyfert NGC 3516. This active galactic nucleus is known to have strong optical variability and has changed its type in the past. It has been in the low-activity state in the optical since 2013, with some rebrightening from the end of 2015 to the beginning of 2016, after which it remained dormant.Aims. We aim to study the photometric and spectral variability of NGC 3516 from the new observations in U- and B-bands and examine the profiles of the optical broad emission lines in order to demonstrate that this object may be entering a new state of activity.Methods. NGC 3516 has been monitored intensively for the past 4 months with an automated telescope in U and B filters, enabling accurate photometry of 0.01 precision. Spectral observations were triggered when an increase in brightness was spotted. We support our analysis of past-episodes of violent variability with the UV and X-ray long-term light curves constructed from the archival Swift/UVOT and Swift/XRT data.Results. An increase of the photometric magnitude is seen in both U and B filters to a maximum amplitude of 0.25 mag and 0.11 mag, respectively. During the flare, we observe stronger forbidden high-ionization iron lines ([FeVII] and [FeX]) than reported before, as well as the complex broad H alpha and H beta lines. This is especially seen in H alpha, which appears to be double-peaked. It seems that a very broad component of similar to 10 000 km s(-1) in width in the Balmer lines is appearing. The trends in the optical, UV, and X-ray light curves are similar, with the amplitudes of variability being significantly larger in the case of UV and X-ray bands.Conclusions. The increase of the continuum emission, the variability of the coronal lines, and the very broad component in the Balmer lines may indicate that the AGN of NGC 3516 is finally leaving the low-activity state in which it has been for the last similar to 3 years.</div

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases