Association of NTRK3 and its interaction with NGF suggest an altered cross-regulation of the neurotrophin signaling pathway in eating disorders

Eating disorders (EDs) are complex psychiatric diseases that include anorexia nervosa and bulimia nervosa, and have higher than 50% heritability. Previous studies have found association of BDNF and NTRK2 to ED, while animal models suggest that other neurotrophin genes might also be involved in eating behavior. We have performed a family-based association study with 151 TagSNPs covering 10 neurotrophin signaling genes: NGFB, BDNF, NTRK1, NGFR/p75, NTF4/5, NTRK2, NTF3, NTRK3, CNTF and CNTFR in 371 ED trios of Spanish, French and German origin. Besides several nominal associations, we found a strong significant association after correcting for multiple testing (P = 1.04 × 10−4) between ED and rs7180942, located in the NTRK3 gene, which followed an overdominant model of inheritance. Interestingly, HapMap unrelated individuals carrying the rs7180942 risk genotypes for ED showed higher levels of expression of NTRK3 in lymphoblastoid cell lines. Furthermore, higher expression of the orthologous murine Ntrk3 gene was also detected in the hypothalamus of the anx/anx mouse model of anorexia. Finally, variants in NGFB gene appear to modify the risk conferred by the NTRK3 rs7180942 risk genotypes (P = 4.0 × 10−5) showing a synergistic epistatic interaction. The reported data, in addition to the previous reported findings for BDNF and NTRK2, point neurotrophin signaling genes as key regulators of eating behavior and their altered cross-regulation as susceptibility factors for EDs.

Hedgehog signaling governs the development of otic sensory epithelium and its associated innervation in zebrafish

The inner ear is responsible for the perception of motion and sound in vertebrates. Its functional unit, the sensory patch, contains mechanosensory hair cells innervated by sensory neurons from the statoacoustic ganglion (SAG) that project to the corresponding nuclei in the brainstem. How hair cells develop at specific positions, and how otic neurons are sorted to specifically innervate each endorgan and to convey the extracted information to the hindbrain is not completely understood. In this work, we study the generation of macular sensory patches and investigate the role of Hedgehog (Hh) signaling in the production of their neurosensory elements. Using zebrafish transgenic lines to visualize the dynamics of hair cell and neuron production, we show that the development of the anterior and posterior maculae is asynchronic, suggesting they are independently regulated. Tracing experiments demonstrate the SAG is topologically organized in two different neuronal subpopulations, which are spatially segregated and innervate specifically each macula. Functional experiments identify the Hh pathway as crucial in coordinating the production of hair cells in the posterior macula, and the formation of its specific innervation. Finally, gene expression analyses suggest that Hh influences the balance between different SAG neuronal subpopulations. These results lead to a model in which Hh orients functionally the development of inner ear towards an auditory fate in all vertebrate species.

Predictability of music descriptor time series and its application to cover song detection

Intuitively, music has both predictable and unpredictable components. In this work we assess this qualitative statement in a quantitative way using common time series models fitted to state-of-the-art music descriptors. These descriptors cover different musical facets and are extracted from a large collection of real audio recordings comprising a variety of musical genres. Our findings show that music descriptor time series exhibit a certain predictability not only for short time intervals, but also for mid-term and relatively long intervals. This fact is observed independently of the descriptor, musical facet and time series model we consider. Moreover, we show that our findings are not only of theoretical relevance but can also have practical impact. To this end we demonstrate that music predictability at relatively long time intervals can be exploited in a real-world application, namely the automatic identification of cover songs (i.e. different renditions or versions of the same musical piece). Importantly, this prediction strategy yields a parameter-free approach for cover song identification that is substantially faster, allows for reduced computational storage and still maintains highly competitive accuracies when compared to state-of-the-art systems.

Applause identification and its relevance to archival of Carnatic music

A Carnatic music concert is made up of a sequence of pieces, where each piece corresponds to a particular genre and ra¯aga (melody). Unlike a western music concert, the artist may be applauded intra-performance inter-performance. Most Carnatic music that is archived today correspond to a single audio recordings of entire concerts.The purpose of this paper is to segment single audio recordings into a sequence of pieces using thecharacteristic features of applause and music. Spectral flux, spectral entropy change quite significantly from music to applause and vice-versa. The characteristics of these features for a subset of concerts was studied. A threshold based approach was used to segment the pieces into music fragments and applauses. Preliminary resultson recordings 19 concerts from matched microphones show that the EER is about 17% for a resolution of 0.25 seconds. Further, a parameter called CUSUM is estimatedfor the applause regions. The CUSUM values determine the strength of the applause. The CUSUM is used to characterise the highlights of a concert.