Music to My Ears: Neural modularity and flexibility differ in response to real-world music stimuli.

Music listening involves many simultaneous neural operations, including auditory processing, working memory, temporal sequencing, pitch tracking, anticipation, reward, and emotion, and thus, a full investigation of music cognition would benefit from whole-brain analyses. Here, we quantify whole-brain activity while participants listen to a variety of music and speech auditory pieces using two network measures that are grounded in complex systems theory: modularity, which measures the degree to which brain regions are interacting in communities, and flexibility, which measures the rate that brain regions switch the communities to which they belong. In a music and brain connectivity study that is part of a larger clinical investigation into music listening and stroke recovery at Houston Methodist Hospital's Center for Performing Arts Medicine, functional magnetic resonance imaging (fMRI) was performed on healthy participants while they listened to self-selected music to which they felt a positive emotional attachment, as well as culturally familiar music (J.S. Bach), culturally unfamiliar music (Gagaku court music of medieval Japan), and several excerpts of speech. There was a marked contrast among the whole-brain networks during the different types of auditory pieces, in particular for the unfamiliar music. During the self-selected and Bach tracks, participants' whole-brain networks exhibited modular organization that was significantly coordinated with the network flexibility. Meanwhile, when the Gagaku music was played, this relationship between brain network modularity and flexibility largely disappeared. In addition, while the auditory cortex's flexibility during the self-selected piece was equivalent to that during Bach, it was more flexible during Gagaku. The results suggest that the modularity and flexibility measures of whole-brain activity have the potential to lead to new insights into the complex neural function that occurs during music perception of real-world songs.

Modular epitope binding predicts influenza quasispecies dominance and vaccine effectiveness: Application to 2018/19 season.

The modular binding sites on the influenza A(H3N2) hemagglutinin protein are under significant pressure to acquire mutations in order to evade human antibody recognition. Analysis of these hemagglutinin epitopes in the strains circulating during 2017/18 and early 2018/19 identified the emergence of a new antigenic cluster that has grown from 4% of circulating strains to 11%. We regressed our module-based antigenic distance, pepitope, with A(H3N2) vaccine effectiveness from recent studies conducted by the US Centers for Disease Control and Prevention (r2 = 0.92), and we used this to estimate that the 2018/19 vaccines will protect against most circulating A(H3N2) strains. The pEpitope model is useful for A(H3N2) influenza vaccine virus selection and development, and it has the potential to aid national or regional regulatory authorities in making geographically localized decisions.

Predicting Influenza H3N2 Vaccine Efficacy From Evolution of the Dominant Epitope.

We predict vaccine efficacy with a measure of antigenic distance between influenza A(H3N2) and vaccine viruses based on amino acid substitutions in the dominant epitope. In 2016-2017, our model predicts 19% efficacy compared with 20% observed. This tool assists candidate vaccine selection by predicting human protection against circulating strains.

The physicist's guide to one of biotechnology's hottest new topics: CRISPR-Cas.

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (Cas) constitute a multi-functional, constantly evolving immune system in bacteria and archaea cells. A heritable, molecular memory is generated of phage, plasmids, or other mobile genetic elements that attempt to attack the cell. This memory is used to recognize and interfere with subsequent invasions from the same genetic elements. This versatile prokaryotic tool has also been used to advance applications in biotechnology. Here we review a large body of CRISPR-Cas research to explore themes of evolution and selection, population dynamics, horizontal gene transfer, specific and cross-reactive interactions, cost and regulation, non-immunological CRISPR functions that boost host cell robustness, as well as applicable mechanisms for efficient and specific genetic engineering. We offer future directions that can be addressed by the physics community. Physical understanding of the CRISPR-Cas system will advance uses in biotechnology, such as developing cell lines and animal models, cell labeling and information storage, combatting antibiotic resistance, and human therapeutics.