Cholinergic-related pupil activity reflects level of emotionality during motor performance.

Pupil size covaries with the diffusion rate of the cholinergic and noradrenergic neurons throughout the brain, which are essential to arousal. Recent findings suggest that slow pupil fluctuations during locomotion are an index of sustained activity in cholinergic axons, whereas phasic dilations are related to the activity of noradrenergic axons. Here, we investigated movement induced arousal (i.e., by singing and swaying to music), hypothesising that actively engaging in musical behaviour will provoke stronger emotional engagement in participants and lead to different qualitative patterns of tonic and phasic pupil activity. A challenge in the analysis of pupil data is the turbulent behaviour of pupil diameter due to exogenous ocular activity commonly encountered during motor tasks and the high variability typically found between individuals. To address this, we developed an algorithm that adaptively estimates and removes pupil responses to ocular events, as well as a functional data methodology, derived from Pfaffs' generalised arousal, that provides a new statistical dimension on how pupil data can be interpreted according to putative neuromodulatory signalling. We found that actively engaging in singing enhanced slow cholinergic-related pupil dilations and having the opportunity to move your body while performing amplified the effect of singing on pupil activity. Phasic pupil oscillations during motor execution attenuated in time, which is often interpreted as a measure of sense of agency over movement.

More on functional data analysis and other aspects in OODA.

This is a discussion of the paper "Overview of object oriented data analysis" by J. Steve Marron and Andrés M. Alonso.

Calorimetric studies of ligands binding to glutathione S-transferase from the malarial parasite Plasmodium falciparum.

Glutathione S-transferase, from the malarial parasite Plasmodium falciparum (PfGST), exerts a protective role in the organism and is thus considered an interesting target for antimalarial drug development. In contrast to other GSTs, it is present in solution as a tetramer and a dimer in equilibrium, which is induced by glutathione (GSH). These properties prevent a calorimetric titration from being conducted upon binding of ligands to this protein's G-site. Thermodynamic characterization can be an optimal strategy for antimalarial drug development, and isothermal titration calorimetry (ITC) is the only technique that allows the separation of the binding energy into both enthalpic and entropic contributions. This information facilitates an understanding of the changes in the drugs' substituents, improving their affinity and specificity. In this study, we have applied a nontypical ITC procedure, based on the dissociation of the ligand-protein complex, to calorimetrically study the binding of the GSH substrate, and the glutathione sulfonate competitive inhibitor, to dimeric PfGST over a temperature range of 15-37 °C. The optimal experimental conditions for applying this procedure have been optimized by studying the dimer to tetramer conversion using size exclusion chromatography. The binding of these ligands to dimeric PfGST is noncooperative, the affinity of glutathione sulfonate being approximately 2 orders of magnitude higher than that of its natural substrate GSH. The binding of both ligands is enthalpically favorable and entropically unfavorable at all the studied temperatures. These results demonstrate that, although PfGST presents differences when compared to other known GSTs, these ligands bind to its dimeric form with a similar affinity and energetic balance. However, in contrast to that of other GSTs, the binding of GSH to protein, in the absence of the ligand, is slow.

Basis expansion approaches for functional analysis of variance with repeated measures.

The methodological contribution in this paper is motivated by biomechanical studies where data characterizing human movement are waveform curves representing joint measures such as flexion angles, velocity, acceleration, and so on. In many cases the aim consists of detecting differences in gait patterns when several independent samples of subjects walk or run under different conditions (repeated measures). Classic kinematic studies often analyse discrete summaries of the sample curves discarding important information and providing biased results. As the sample data are obviously curves, a Functional Data Analysis approach is proposed to solve the problem of testing the equality of the mean curves of a functional variable observed on several independent groups under different treatments or time periods. A novel approach for Functional Analysis of Variance (FANOVA) for repeated measures that takes into account the complete curves is introduced. By assuming a basis expansion for each sample curve, two-way FANOVA problem is reduced to Multivariate ANOVA for the multivariate response of basis coefficients. Then, two different approaches for MANOVA with repeated measures are considered. Besides, an extensive simulation study is developed to check their performance. Finally, two applications with gait data are developed.

Knee flexion of saxophone players anticipates tonal context of music.

Music performance requires high levels of motor control. Professional musicians use body movements not only to accomplish and help technical efficiency, but to shape expressive interpretation. Here, we recorded motion and audio data of twenty participants performing four musical fragments varying in the degree of technical difficulty to analyze how knee flexion is employed by expert saxophone players. Using a computational model of the auditory periphery, we extracted emergent acoustical properties of sound to inference critical cognitive patterns of music processing and relate them to motion data. Results showed that knee flexion is causally linked to tone expectations and correlated to rhythmical density, suggesting that this gesture is associated with expressive and facilitative purposes. Furthermore, when instructed to play immobile, participants tended to microflex (>1 Hz) more frequently compared to when playing expressively, possibly indicating a natural urge to move to the music. These results underline the robustness of body movement in musical performance, providing valuable insights for the understanding of communicative processes, and development of motor learning cues.

Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient.

We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I-V) plots, such as switching voltages or state resistances, we take into account the whole I-V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I-V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memories.

Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic.

Faced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of NO 2 , PM 10 , PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

Diuretic drug binding to human glutathione transferase P1-1: potential role of Cys-101 revealed in the double mutant C47S/Y108V.

The diuretic drug ethacrynic acid (EA), both an inhibitor and substrate of pi class glutathione S-transferase (GST P1-1), has been tested in clinical trials as an adjuvant in chemotherapy. We recently studied the role of the active site residue Tyr-108 in binding EA to the enzyme and found that the analysis was complicated by covalent binding of this drug to the highly reactive Cys-47. Previous attempts to eliminate this binding by chemical modification yielded ambiguous results and therefore we decided here to produce a double mutant C47S/Y108V by site directed mutagenesis and further expression in Escherichia coli and the interaction of EA and its GSH conjugate (EASG) examined by calorimetric studies and X-ray diffraction. Surprisingly, in the absence of Cys-47, Cys-101 (located at the dimer interface) becomes a target for modification by EA, albeit at a lower conjugation rate than Cys-47. The Cys-47 → Ser mutation in the double mutant enzyme induces a positive cooperativity between the two subunits when ligands with affinity to G-site bind to enzyme. However, this mutation does not seem to affect the thermodynamic properties of ligand binding to the electrophilic binding site (H-site) and the thermal or chemical stability of this double mutant does not significantly affect the unfolding mechanism in either the absence or presence of ligand. Crystal structures of apo and an EASG complex are essentially identical with a few exceptions in the H-site and in the water network at the dimer interface.

Forecasting pollen concentration by a two-step functional model.

A functional regression model to forecast the cypress pollen concentration during a given time interval, considering the air temperature in a previous interval as the input, is derived by means of a two-step procedure. This estimation is carried out by functional principal component (FPC) analysis and the residual noise is also modeled by FPC regression, taking as the explicative process the pollen concentration during the earlier interval. The prediction performance is then tested on pollen data series recorded in Granada (Spain) over a period of 10 years.

Calorimetric and structural studies of the nitric oxide carrier S-nitrosoglutathione bound to human glutathione transferase P1-1.

The nitric oxide molecule (NO) is involved in many important physiological processes and seems to be stabilized by reduced thiol species, such as S-nitrosoglutathione (GSNO). GSNO binds strongly to glutathione transferases, a major superfamily of detoxifying enzymes. We have determined the crystal structure of GSNO bound to dimeric human glutathione transferase P1-1 (hGSTP1-1) at 1.4 A resolution. The GSNO ligand binds in the active site with the nitrosyl moiety involved in multiple interactions with the protein. Isothermal titration calorimetry and differential scanning calorimetry (DSC) have been used to characterize the interaction of GSNO with the enzyme. The binding of GSNO to wild-type hGSTP1-1 induces a negative cooperativity with a kinetic process concomitant to the binding process occurring at more physiological temperatures. GSNO inhibits wild-type enzyme competitively at lower temperatures but covalently at higher temperatures, presumably by S-nitrosylation of a sulfhydryl group. The C47S mutation removes the covalent modification potential of the enzyme by GSNO. These results are consistent with a model in which the flexible helix alpha2 of hGST P1-1 must move sufficiently to allow chemical modification of Cys47. In contrast to wild-type enzyme, the C47S mutation induces a positive cooperativity toward GSNO binding. The DSC results show that the thermal stability of the mutant is slightly higher than wild type, consistent with helix alpha2 forming new interactions with the other subunit. All these results suggest that Cys47 plays a key role in intersubunit cooperativity and that under certain pathological conditions S-nitrosylation of Cys47 by GSNO is a likely physiological scenario.