Evolution of the stellar mass function and infrared luminosity function of galaxies since z = 1.2

© 2019. The American Astronomical Society. All rights reserved. We measured evolution of the K-band luminosity function and stellar mass function (SMF) for red and blue galaxies at z 0.4 luminosity and mass function measurements. Using an evolving relation for K-band mass-to-light ratios as a function of (B-V) color, we found a slowly decreasing rate of growth in red galaxy stellar mass density of ×2.3 from z ∼ 1.1 to z ∼ 0.3, indicating a slowly decreasing rate of migration from the blue cloud to the red sequence. Unlike some studies of the SMF, we find that massive red galaxies grow by a factor of ×1.7 from z ∼ 1.1 to z ∼ 0.3, with the rate of growth due to mergers decreasing with time. These results are comparable with measurements of merger rates and clustering, and they are also consistent with the red galaxy stellar mass growth implied by comparing K-band luminosity evolution with the fading of passive stellar population models

Multi-heme Cytochromes in Shewanella oneidensis MR-1:Structures, functions and opportunities

Multi-heme cytochromes are employed by a range of microorganisms to transport electrons over distances of up to tens of nanometers. Perhaps the most spectacular utilization of these proteins is in the reduction of extracellular solid substrates, including electrodes and insoluble mineral oxides of Fe(III) and Mn(III/IV), by species of Shewanella and Geobacter. However, multi-heme cytochromes are found in numerous and phylogenetically diverse prokaryotes where they participate in electron transfer and redox catalysis that contributes to biogeochemical cycling of N, S and Fe on the global scale. These properties of multi-heme cytochromes have attracted much interest and contributed to advances in bioenergy applications and bioremediation of contaminated soils. Looking forward there are opportunities to engage multi-heme cytochromes for biological photovoltaic cells, microbial electrosynthesis and developing bespoke molecular devices. As a consequence it is timely to review our present understanding of these proteins and we do this here with a focus on the multitude of functionally diverse multi-heme cytochromes in Shewanella oneidensis MR-1. We draw on findings from experimental and computational approaches which ideally complement each other in the study of these systems: computational methods can interpret experimentally determined properties in terms of molecular structure to cast light on the relation between structure and function. We show how this synergy has contributed to our understanding of multi-heme cytochromes and can be expected to continue to do so for greater insight into natural processes and their informed exploitation in biotechnologies

Universally Sloppy Parameter Sensitivities in Systems Biology

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring \emph{in vivo} biochemical parameters is difficult, and collectively fitting them to other data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a `sloppy' spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.Comment: Submitted to PLoS Computational Biology. Supplementary Information available in "Other Formats" bundle. Discussion slightly revised to add historical contex

A state-space model of the burst suppression ratio

Burst suppression is an electroencephalogram pattern observed in states of severely reduced brain activity, such as general anesthesia, hypothermia and anoxic brain injuries. The burst suppression ratio (BSR), defined as the fraction of EEG spent in suppression per epoch, is the standard quantitative measure used to characterize burst suppression. We present a state space model to compute a dynamic estimate of the BSR as the instantaneous probability of suppression. We estimate the model using an approximate EM algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia. Our approach removes the need to artificially average the ratio over long epochs and allows us to make formal statistical comparisons of burst activity at different time points. Our state-space model suggests a more principled way to analyze this key EEG feature that may offer more informative assessments of its associated brain state.Massachusetts General Hospital. Dept. of Anesthesia and Critical CareNational Institutes of Health (U.S.) (Grant DP1 OD003646-01)National Institutes of Health (U.S.) (Grant R01 MH071847)National Institutes of Health (U.S.) (Grant K08 GM094394

Darwin in Mind: New Opportunities for Evolutionary Psychology

Evolutionary Psychology (EP) views the human mind as organized into many modules, each underpinned by psychological adaptations designed to solve problems faced by our Pleistocene ancestors. We argue that the key tenets of the established EP paradigm require modification in the light of recent findings from a number of disciplines, including human genetics, evolutionary biology, cognitive neuroscience, developmental psychology, and paleoecology. For instance, many human genes have been subject to recent selective sweeps; humans play an active, constructive role in co-directing their own development and evolution; and experimental evidence often favours a general process, rather than a modular account, of cognition. A redefined EP could use the theoretical insights of modern evolutionary biology as a rich source of hypotheses concerning the human mind, and could exploit novel methods from a variety of adjacent research fields

Sex differences in confidence influence patterns of conformity

The research was supported in part by an ERC Advanced Grant (EVOCULTURE, Ref.232823) awarded to KNL.Lack of confidence in one's own ability can increase the likelihood of relying on social information. Sex differences in confidence have been extensively investigated in cognitive tasks, but implications for conformity have not been directly tested. Here, we tested the hypothesis that, in a task that shows sex differences in confidence, an indirect effect of sex on social information use will also be evident. Participants (N = 168) were administered a mental rotation (MR) task or a letter transformation (LT) task. After providing an answer, participants reported their confidence before seeing the responses of demonstrators and being allowed to change their initial answer. In the MR, but not the LT, task, women showed lower levels of confidence than men, and confidence mediated an indirect effect of sex on the likelihood of switching answers. These results provide novel, experimental evidence that confidence is a general explanatory mechanism underpinning susceptibility to social influences. Our results have implications for the interpretation of the wider literature on sex differences in conformity.PostprintPeer reviewe

AMCIS 2022 Awards Luncheon

This is a video recording and PDF document with the AMCIS 2022 Awards Ceremony

Correcting for serial dependence in studies of respiratory dynamics

Understanding the physiological impact of drug treatments on patients is important in assessing their performance and determining possible side effects. While this effect might be best determined in individual subjects, conventional methods assess treatment performance by averaging a physiological measure of interest before and after drug administration for n subjects. Summarizing large numbers of time-series observations in two means for each subject in this way results in significant information loss. Treatment effect can instead be analyzed in individual subjects. Because serial dependence of observations from the same animal must then be considered, methods that assume independence of observations, such as the t-test and z-test, cannot be used. We address this issue in the case of respiratory data collected from anesthetized rats that were injected with a dopamine agonist. In order to accurately assess treatment effect in time-series data, we begin by formulating a method of conditional likelihood maximization to estimate the parameters of a first-order autoregressive (AR) process. We show that treatment effect of a dopamine agonist can be determined while incorporating serial effect into the analysis. In addition, while maximum likelihood estimators of a large sample with independent observations may converge to an asymptotically normal distribution, this result of large sample theory may not hold when observations are serially dependent. In this case, a parametric bootstrap comparison can be used to approximate an appropriate measure of uncertainty.National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant K08-GM094394)National Institutes of Health (U.S.) (Grant K08-GM083216

Enhanced balance associated with coordination training with stochastic resonance stimulation in subjects with functional ankle instability: an experimental trial

<p>Abstract</p> <p>Background</p> <p>Ankle sprains are common injuries that often lead to functional ankle instability (FAI), which is a pathology defined by sensations of instability at the ankle and recurrent ankle sprain injury. Poor postural stability has been associated with FAI, and sports medicine clinicians rehabilitate balance deficits to prevent ankle sprains. Subsensory electrical noise known as stochastic resonance (SR) stimulation has been used in conjunction with coordination training to improve dynamic postural instabilities associated with FAI. However, unlike static postural deficits, dynamic impairments have not been indicative of ankle sprain injury. Therefore, the purpose of this study was to examine the effects of coordination training with or without SR stimulation on static postural stability. Improving postural instabilities associated with FAI has implications for increasing ankle joint stability and decreasing recurrent ankle sprains.</p> <p>Methods</p> <p>This study was conducted in a research laboratory. Thirty subjects with FAI were randomly assigned to either a: 1) conventional coordination training group (CCT); 2) SR stimulation coordination training group (SCT); or 3) control group. Training groups performed coordination exercises for six weeks. The SCT group received SR stimulation during training, while the CCT group only performed coordination training. Single leg postural stability was measured after the completion of balance training. Static postural stability was quantified on a force plate using anterior/posterior (A/P) and medial/lateral (M/L) center-of-pressure velocity (COPvel), M/L COP standard deviation (COPsd), M/L COP maximum excursion (COPmax), and COP area (COParea).</p> <p>Results</p> <p>Treatment effects comparing posttest to pretest COP measures were highest for the SCT group. At posttest, the SCT group had reduced A/P COPvel (2.3 ± 0.4 cm/s vs. 2.7 ± 0.6 cm/s), M/L COPvel (2.6 ± 0.5 cm/s vs. 2.9 ± 0.5 cm/s), M/L COPsd (0.63 ± 0.12 cm vs. 0.73 ± 0.11 cm), M/L COPmax (1.76 ± 0.25 cm vs. 1.98 ± 0.25 cm), and COParea (0.13 ± 0.03 cm²vs. 0.16 ± 0.04 cm²) than the pooled means of the CCT and control groups (P < 0.05).</p> <p>Conclusion</p> <p>Reduced values in COP measures indicated postural stability improvements. Thus, six weeks of coordination training with SR stimulation enhanced postural stability. Future research should examine the use of SR stimulation for decreasing recurrent ankle sprain injury in physically active individuals with FAI.</p