LSD1/KDM1A is essential for neural stem cell differentiation in mice

The proper regulation of neural stem cell differentiation is required for the proper specification of the central nervous system. Here we investigated the function of the H3K4me1/2 demethylase LSD1/KDM1A during neural stem differentiation in mice. Conditional deletion of LSD1 in nestin- positive neural stem cells results in 100% perinatal lethality after birth with severe motor coordination deficits, retarded growth and defects in brain morphology. Despite these severe defects, motor neuron progenitors and the initial motor neuron population are specified normally and motor neurons with normal morphology can be cultured from these mice in vitro. However, motor neurons cultured from mice lacking LSD1 in neural stem cells continue to inappropriately maintain critical neural stem cell proteins. Taken together these results suggest that, as in other mouse stem cell populations, LSD1 is required to deactivate the stem cell program to enable normal neural stem cell differentiation. However, unlike in other mouse stem cell populations, the inappropriate maintenance of the stem cell program during neural stem cell differentiation may compromise neuronal function rather than neuronal specification.

Recurrence Quantification Analysis of Crowd Sound Dynamics

When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions.

Resampling to address inequities in predictive modeling of suicide deaths

Objective

Improve methodology for equitable suicide death prediction when using sensitive predictors, such as race/ethnicity, for machine learning and statistical methods.

Methods

Train predictive models, logistic regression, naive Bayes, gradient boosting (XGBoost) and random forests, using three resampling techniques (Blind, Separate, Equity) on emergency department (ED) administrative patient records. The Blind method resamples without considering racial/ethnic group. Comparatively, the Separate method trains disjoint models for each group and the Equity method builds a training set that is balanced both by racial/ethnic group and by class.

Results

Using the Blind method, performance range of the models’ sensitivity for predicting suicide death between racial/ethnic groups (a measure of prediction inequity) was 0.47 for logistic regression, 0.37 for naive Bayes, 0.56 for XGBoost and 0.58 for random forest. By building separate models for different racial/ethnic groups or using the equity method on the training set, we decreased the range in performance to 0.16, 0.13, 0.19, 0.20 with Separate method, and 0.14, 0.12, 0.24, 0.13 for Equity method, respectively. XGBoost had the highest overall area under the curve (AUC), ranging from 0.69 to 0.79.

Discussion

We increased performance equity between different racial/ethnic groups and show that imbalanced training sets lead to models with poor predictive equity. These methods have comparable AUC scores to other work in the field, using only single ED administrative record data.

Conclusion

We propose two methods to improve equity of suicide death prediction among different racial/ethnic groups. These methods may be applied to other sensitive characteristics to improve equity in machine learning with healthcare applications.

Coordination dynamics of multi-agent interaction in a musical ensemble

Humans interact with other humans at a variety of timescales and in a variety of social contexts. We exhibit patterns of coordination that may differ depending on whether we are genuinely interacting as part of a coordinated group of individuals vs merely co-existing within the same physical space. Moreover, the local coordination dynamics of an interacting pair of individuals in an otherwise non-interacting group may spread, propagating change in the global coordination dynamics and interaction of an entire crowd. Dynamical systems analyses, such as Recurrence Quantification Analysis (RQA), can shed light on some of the underlying coordination dynamics of multi-agent human interaction. We used RQA to examine the coordination dynamics of a performance of "Welcome to the Imagination World", composed for wind orchestra. This performance enacts a real-life simulation of the transition from uncoordinated, non-interacting individuals to a coordinated, interacting multi-agent group. Unlike previous studies of social interaction in musical performance which rely on different aspects of video and/or acoustic data recorded from each individual, this project analyzes group-level coordination patterns solely from the group-level acoustic data of an audio recording of the performance. Recurrence and stability measures extracted from the audio recording increased when musicians coordinated as an interacting group. Variability in these measures also increased, indicating that the interacting ensemble of musicians were able to explore a greater variety of behavior than when they performed as non-interacting individuals. As an orchestrated (non-emergent) example of coordination, we believe these analyses provide an indication of approximate expected distributions for recurrence patterns that may be measurable before and after truly emergent coordination.

How much can we influence the rate of innovation?

Innovation is how organizations drive technological change, but the rate of innovation can vary considerably from one technological domain to another. To understand why some domains flourish more rapidly than others, we studied a model of innovation in which products are built out of components. We derived a conservation law for the average size of the product space as more components are acquired and tested our insights using historical data from language, gastronomy, mixed drinks, and technology. We find that the innovation rate is partly influenceable and partly predetermined, similar to how traits are partly set by nurture and partly set by nature. The predetermined aspect is fixed solely by the distribution of the complexity of products in each domain. Different distributions can produce markedly different innovation rates. This helps explain why some domains show faster innovation than others, despite similar efforts to accelerate them. Our insights also give a quantitative perspective on lean methodology, frugal innovation, and mechanisms to encourage tinkering.

Particle-size effects in the formation of bicontinuous Pickering emulsions

We demonstrate that the formation of bicontinuous emulsions stabilized by interfacial particles (bijels) is more robust when nanoparticles rather than microparticles are used. Emulsification via spinodal demixing in the presence of nearly neutrally wetting particles is induced by rapid heating. Using confocal microscopy, we show that nanospheres allow successful bijel formation at heating rates two orders of magnitude slower than is possible with microspheres. In order to explain our results, we introduce the concept of mechanical leeway, i.e., nanoparticles benefit from a smaller driving force towards disruptive curvature. Finally, we suggest that leeway mechanisms may benefit any formulation in which challenges arise due to tight restrictions on a pivotal parameter, but where the restrictions can be relaxed by rationally changing the value of a more accessible parameter.

Measurement of the inclusive electron neutrino charged current cross section on carbon with the T2K near detector

The T2K off-axis near detector ND280 is used to make the first differential cross-section measurements of electron neutrino charged current interactions at energies ∼1  GeV as a function of electron momentum, electron scattering angle, and four-momentum transfer of the interaction. The total flux-averaged ν(e) charged current cross section on carbon is measured to be ⟨σ⟩(ϕ)=1.11±0.10(stat)±0.18(syst)×10⁻³⁸ cm²/nucleon. The differential and total cross-section measurements agree with the predictions of two leading neutrino interaction generators, NEUT and GENIE. The NEUT prediction is 1.23×10⁻³⁸ cm²/nucleon and the GENIE prediction is 1.08×10⁻³⁸ cm²/nucleon. The total ν(e) charged current cross-section result is also in agreement with data from the Gargamelle experiment.

Precise measurement of the neutrino mixing parameter θ23 from muon neutrino disappearance in an off-axis beam

New data from the T2K neutrino oscillation experiment produce the most precise measurement of the neutrino mixing parameter θ23. Using an off-axis neutrino beam with a peak energy of 0.6 GeV and a data set corresponding to 6.57×10(20) protons on target, T2K has fit the energy-dependent νμ oscillation probability to determine oscillation parameters. The 68% confidence limit on sin(2)(θ23) is 0.514(-0.056)(+0.055) (0.511±0.055), assuming normal (inverted) mass hierarchy. The best-fit mass-squared splitting for normal hierarchy is Δm32(2)=(2.51±0.10)×10(-3)  eV(2)/c(4) (inverted hierarchy: Δm13(2)=(2.48±0.10)×10(-3)  eV(2)/c(4)). Adding a model of multinucleon interactions that affect neutrino energy reconstruction is found to produce only small biases in neutrino oscillation parameter extraction at current levels of statistical uncertainty.

Observation of electron neutrino appearance in a muon neutrino beam

The T2K experiment has observed electron neutrino appearance in a muon neutrino beam produced 295 km from the Super-Kamiokande detector with a peak energy of 0.6 GeV. A total of 28 electron neutrino events were detected with an energy distribution consistent with an appearance signal, corresponding to a significance of 7.3σ when compared to 4.92±0.55 expected background events. In the Pontecorvo-Maki-Nakagawa-Sakata mixing model, the electron neutrino appearance signal depends on several parameters including three mixing angles θ12, θ23, θ13, a mass difference Δm(32)(2) and a CP violating phase δ(CP). In this neutrino oscillation scenario, assuming |Δm(32)(2)|=2.4×10(-3)  eV(2), sin(2)θ(23)=0.5, and Δm322>0 (Δm(32)(2)<0), a best-fit value of sin(2)2θ(13)=0.140(-0.032)(+0.038) (0.170(-0.037)(+0.045)) is obtained at δ(CP)=0. When combining the result with the current best knowledge of oscillation parameters including the world average value of θ(13) from reactor experiments, some values of δ(CP) are disfavored at the 90% C.L.

Measurement of neutrino oscillation parameters from muon neutrino disappearance with an off-axis beam

The T2K Collaboration reports a precision measurement of muon neutrino disappearance with an off-axis neutrino beam with a peak energy of 0.6 GeV. Near detector measurements are used to constrain the neutrino flux and cross section parameters. The Super-Kamiokande far detector, which is 295 km downstream of the neutrino production target, collected data corresponding to 3.01×10(20) protons on target. In the absence of neutrino oscillations, 205±17 (syst) events are expected to be detected while only 58 muon neutrino event candidates are observed. A fit to the neutrino rate and energy spectrum, assuming three neutrino flavors and normal mass hierarchy yields a best-fit mixing angle sin2(θ23)=0.514±0.082 and mass splitting |Δm(32)(2)|=2.44(-0.15)(+0.17)×10(-3) eV2/c4. Our result corresponds to the maximal oscillation disappearance probability.

Continuous Intra-articular Infusion of Ropivacaine after Unilateral Total Knee Arthroplasty

Intra-articular infusion of local anaesthetic after joint arthroplasty is attractive in that it is simple and will not cause motor block. However, the efficacy of the technique has yet to be established. We enrolled 66 patients scheduled for unilateral total knee arthroplasty under general anaesthesia and single-shot femoral and sciatic nerve blocks. All patients had an intra-articular Painbuster® device sited at the end of the procedure. Patients were then randomised to control or one of two treatment arms – low-dose and high-dose ropivacaine. In the control group the balloon was filled with saline, in the low-dose group with 0.2% ropivacaine and in the high-dose group 0.375% ropivacaine. The catheters were infused continuously for 48 hours and then removed. Patients were followed up daily for three days to determine pain scores, opioid consumption and subjective assessment of the analgesic efficacy of the catheter. Data were analysed for 30 controls and 31 in the treatment arms. Both groups were similar. There were no significant differences between the control and treatment groups at all time points after adjustment for age. Patients in the high-dose group had higher pain scores and higher opioid consumption than the control groups from 24 to 48 hours. There were two cases of infection, both in the treatment groups.

No positive benefit of intra-articular infusion of local anaesthetic after total knee arthroplasty could be identified. On the contrary there may be negative effects in terms of expense, pain and possibly infection risks.