Spectral lines

Dicarbonyl didact – NMR spectroscopy has been used to investigate dicarbonyl sugars formed inside the human body from the natural breakdown of the simple sugar, glucose. The implications for understanding the link with diabetes are discussed.

Biochemist Anthony Serianni and postdoctoral research associate, Wenhui Zhang,of the University of Notre Dame in Indiana, USA, are providing important new clues as to the nature of diabetes that one day might lead to novel treatments. Serianni explains that the biological compounds known as dicarbonyl sugars are produced inside the human body from the natural breakdown of the basic sugar compound, glucose. The formation of these sugars occurs to a greater extent in people with diabetes because glucose concentrations in the blood and plasma can be much higher than normal. More on Sweet complexity….

Brainy structure – Structural changes in the brain revealed by magnetic resonance imaging are tied to common gene variants linked to disorders such as Alzheimer’s disease, schizophrenia, and autism and can be observed in brain scans of newborn infants.

In research that was funded by the US National Institutes of Health, Rebecca Knickmeyer of the University of North Carolina School of Medicine and colleagues John Gilmore, Jiaping Wang, Hongtu Zhu, Xiujuan Geng, Sandra Woolson, Robert Hamer, Thomas Konneker, Weili Lin and Martin Styner, show how certain changes in the brain found in adults are associated with common gene variants present at birth. More on brain scanning and genetics….

Wall to wall antioxidants – Amino acid functionalised nanotubes scavenge free radicals faster than conventional synthetic antioxidants. Multi-walled carbon nanotubes functionalized by sonication with various amino acids can act as synthetic antioxidants. IR spectroscopy and other techniques have been used to study their effects and reveal these entities to be more potent than other synthetic agents in scavenging free radicals.

Ahm Amiri of the Department of Engineering at the Islamic Azad University, in Marvdasht, Iran, and colleagues Mina Memarpoor-Yazdi, Mehdi Shanbedi, Hossein Eshghi, writing in the Journal of Biomedical Materials Research A explain how they are keen to develop potent antioxidants able to scavenge free radicals. Free radicals are implicated in oxidative reactions involved in diabetes mellitus, certain forms of cancer and cardiovascular disease. More on antioxidant nanotubes.

Musical emotion detector

Music recommendation systems have been around for a while, last.fm, Pandora, Spotify, Peter Gabriel’s “The Filter” and more recently they have been extended into the social domain, just like it was in the days before mp3s and Napster when we used to make mix tapes for each other and recommend bands…by word-of-mouth…in the school playground! But, one thing that all of the various systems have in common is that the software doesn’t understand the emotion inherent in the songs (other than in general genre terms).

Now, informatics expert Angelina Tzacheva and her colleagues at the University of South Carolina Upstate, Spartanburg, hope to remedy the situation by developing an algorithm that can extract the emotional qualities of a song from an audio file. Writing in the International Journal of Social Network Mining this month, they explain how they have trained their algorithm to recognize different timbres, types of instrumental sounds, commonly associated with specific emotions in a piece of music. In so doing they hope to bridge the gap between earlier attempts to detect emotions in music and the actual human perception of the feelings evoked in a specific musical work.

The team explains that, “We believe emotions are not something that is embedded within a digital signal, but is a feeling experienced by a human being.” They then ask “Is it possible for an emotion to be searched for and detected within a signal?” They find the answer that indeed it is. “Certain information is present within the signal, which can be linked to the emotion that is invoked within a human while listening to the music.” The team focuses on timbre as the bridge between the information and the emotion. Timbre being the characteristics other than the pitch or loudness of a musical sound.

The team suggests that their approach could be successfully applied in music recommendation systems allowing users to retrieve music and create playlists based on the types of emotion different music might invoke. Additionally, it might also be used commercially in radio and TV programming as well as in music therapy.

Research Blogging IconTzacheva A.A., Schlingmann D. & Bell K.J. (2012). Automatic detection of emotions with music files, International Journal of Social Network Mining, 1 (2) 129. DOI: 10.1504/IJSNM.2012.051054