Novel positioning sensor with real-time feedback for improved postoperative positioning: pilot study in control subjects

Introduction: Repair of retinal detachment frequently requires use of intraocular gas. Patients are instructed to position themselves postoperatively to appose the intraocular bubble to the retinal break(s). We developed a novel wearable wireless positioning sensor, which provides real-time audiovisual feedback on the accuracy of positioning. Methods: Eight healthy volunteers wore the wireless sensor for 3 hours while instructed to maintain their head tilted toward the 2 o’clock meridian with no audiovisual feedback. Positioning accuracy was recorded. The subjects repeated the experiment for 3 hours with the audiovisual feedback enabled. Results: With no audiovisual feedback, the percentage of time greater than 10° out of position varied from 8.9% to 93.9%. With audiovisual feedback enabled, these percentages ranged from 9.4% to 65%. Three subjects showed significant improvement in their time out of position (P<0.01, Fisher’s exact test). Four subjects demonstrated a nonsignificant improvement, and one subject had a significant increase in time out of position with feedback (P<0.01). When pooled, all subjects demonstrated a statistically significant decrease in degrees out of position (P<0.001, Wilcoxon test) and a statistically significant improvement in total time out of position (P<0.001). Conclusion: The novel positioning sensor showed improved positioning compliance in half of the healthy volunteers during our short pilot study. Other subjects derived little benefit from the feedback. The causes for this observation are unclear. However, given the significant improvement as a group, this new technology could be beneficial to patients who struggle with postoperative positioning

Carbon–Carbon Bond Formation at a Neutral Terminal Carbido Ligand: Generation of Cyclopropenylidene and Vinylidene Complexes

No AbstractPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55908/1/7422_ftp.pd

Transition states in protein folding kinetics: Modeling Phi-values of small beta-sheet proteins

Small single-domain proteins often exhibit only a single free-energy barrier, or transition state, between the denatured and the native state. The folding kinetics of these proteins is usually explored via mutational analysis. A central question is which structural information on the transition state can be derived from the mutational data. In this article, we model and structurally interpret mutational Phi-values for two small beta-sheet proteins, the PIN and the FBP WW domain. The native structure of these WW domains comprises two beta-hairpins that form a three-stranded beta-sheet. In our model, we assume that the transition state consists of two conformations in which either one of the hairpins is formed. Such a transition state has been recently observed in Molecular Dynamics folding-unfolding simulations of a small designed three-stranded beta-sheet protein. We obtain good agreement with the experimental data (i) by splitting up the mutation-induced free-energy changes into terms for the two hairpins and for the small hydrophobic core of the proteins, and (ii) by fitting a single parameter, the relative degree to which hairpin 1 and 2 are formed in the transition state. The model helps to understand how mutations affect the folding kinetics of WW domains, and captures also negative Phi-values that have been difficult to interpret.Comment: 27 pages, 6 pages, 3 tables; to appear in Biophys.

A common neural code for social and monetary rewards in the human striatum

Although managing social information and decision making on the basis of reward is critical for survival, it remains uncertain whether differing reward type is processed in a uniform manner. Previously, we demonstrated that monetary reward and the social reward of good reputation activated the same striatal regions including the caudate nucleus and putamen. However, it remains unclear whether overlapping activations reflect activities of identical neuronal populations or two overlapping but functionally independent neuronal populations. Here, we re-analyzed the original data and addressed this question using multivariate-pattern-analysis and found evidence that in the left caudate nucleus and bilateral nucleus accumbens, social vs monetary reward were represented similarly. The findings suggest that social and monetary rewards are processed by the same population of neurons within these regions of the striatum. Additional findings demonstrated similar neural patterns when participants experience high social reward compared to viewing others receiving low social reward (potentially inducing schadenfreude). This is possibly an early indication that the same population of neurons may be responsible for processing two different types of social reward (good reputation and schadenfreude). These findings provide a supplementary perspective to previous research, helping to further elucidate the mechanisms behind social vs non-social reward processing

GP-initiated preconception counselling in a randomised controlled trial does not induce anxiety

BACKGROUND: Preconception counselling (PCC) can reduce adverse pregnancy outcome by addressing risk factors prior to pregnancy. This study explores whether anxiety is induced in women either by the offer of PCC or by participation with GP-initiated PCC. METHODS: Randomised trial of usual care versus GP-initiated PCC for women aged 18–40, in 54 GP practices in the Netherlands. Women completed the six-item Spielberger State Trait Anxiety Inventory (STAI) before PCC (STAI-1) and after (STAI-2). After pregnancy women completed a STAI focusing on the first trimester of pregnancy (STAI-3). RESULTS: The mean STAI-1-score (n = 466) was 36.4 (95% CI 35.4 – 37.3). Following PCC there was an average decrease of 3.6 points in anxiety-levels (95% CI, 2.4 – 4.8). Mean scores of the STAI-3 were 38.5 (95% CI 37.7 – 39.3) in the control group (n = 1090) and 38.7 (95% CI 37.9 – 39.5) in the intervention group (n = 1186). CONCLUSION: PCC from one's own GP reduced anxiety after participation, without leading to an increase in anxiety among the intervention group during pregnancy. We therefore conclude that GPs can offer PCC to the general population without fear of causing anxiety. Trial Registration: ISRCTN5394291

Mathematical Correlations for Describing Solute Transfer into Functionalized Alkane Solvents Containing Hydroxyl, Ether, Ester or Ketone Solvents

This article discusses mathematical correlations for describing solute transfer into functionalized alkane solvents containing hydroxyl, ether, ester or ketone solvents

Cation-specific and anion-specific Abraham model correlations for solute transfer into ionic liquid solvents

Article discussing research on cation-specific and anion-specific Abraham model correlations for solute transfer into ionic liquid solvents

A Recommendation System for Meta-modeling: A Meta-learning Based Approach

Various meta-modeling techniques have been developed to replace computationally expensive simulation models. The performance of these meta-modeling techniques on different models is varied which makes existing model selection/recommendation approaches (e.g., trial-and-error, ensemble) problematic. To address these research gaps, we propose a general meta-modeling recommendation system using meta-learning which can automate the meta-modeling recommendation process by intelligently adapting the learning bias to problem characterizations. The proposed intelligent recommendation system includes four modules: (1) problem module, (2) meta-feature module which includes a comprehensive set of meta-features to characterize the geometrical properties of problems, (3) meta-learner module which compares the performance of instance-based and model-based learning approaches for optimal framework design, and (4) performance evaluation module which introduces two criteria, Spearman\u27s ranking correlation coefficient and hit ratio, to evaluate the system on the accuracy of model ranking prediction and the precision of the best model recommendation, respectively. To further improve the performance of meta-learning for meta-modeling recommendation, different types of feature reduction techniques, including singular value decomposition, stepwise regression and ReliefF, are studied. Experiments show that our proposed framework is able to achieve 94% correlation on model rankings, and a 91% hit ratio on best model recommendation. Moreover, the computational cost of meta-modeling recommendation is significantly reduced from an order of minutes to seconds compared to traditional trial-and-error and ensemble process. The proposed framework can significantly advance the research in meta-modeling recommendation, and can be applied for data-driven system modeling