There is a growing body of scientific evidence that the health of the microbiome (the trillions of microbes that inhabit the human host) plays an important role in maintaining the health of the host and that disruptions in the microbiome may play a role in certain disease processes. An increasing number of research studies have provided evidence that the composition of the gut (enteric) microbiome (GM) in at least a subset of individuals with autism spectrum disorder (ASD) deviates from what is usually observed in typically developing individuals. There are several lines of research that suggest that specific changes in the GM could be causative or highly associated with driving core and associated ASD symptoms, pathology, and comorbidities which include gastrointestinal symptoms, although it is also a possibility that these changes, in whole or in part, could be a consequence of underlying pathophysiological features associated with ASD. However, if the GM truly plays a causative role in ASD, then the manipulation of the GM could potentially be leveraged as a therapeutic approach to improve ASD symptoms and/or comorbidities, including gastrointestinal symptoms.

One approach to investigating this possibility in greater detail includes a highly controlled clinical trial in which the GM is systematically manipulated to determine its significance in individuals with ASD. To outline the important issues that would be required to design such a study, a group of clinicians, research scientists, and parents of children with ASD participated in an interdisciplinary daylong workshop as an extension of the 1st International Symposium on the Microbiome in Health and Disease with a Special Focus on Autism (www.microbiome-autism.com). The group considered several aspects of designing clinical studies, including clinical trial design, treatments that could potentially be used in a clinical trial, appropriate ASD participants for the clinical trial, behavioral and cognitive assessments, important biomarkers, safety concerns, and ethical considerations. Overall, the group not only felt that this was a promising area of research for the ASD population and a promising avenue for potential treatment but also felt that further basic and translational research was needed to clarify the clinical utility of such treatments and to elucidate possible mechanisms responsible for a clinical response, so that new treatments and approaches may be discovered and/or fostered in the future.

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80 °C, −20 °C, and room temperature and exposed to multiple freeze-thaw cycles and other adverse conditions in order to assess the possibility that protein oxidation may occur as a result of poor sample storage or handling. Samples from a healthy donor and a participant with poorly controlled type 2 diabetes started at the same low level of protein oxidation and behaved similarly; significant increases in albumin oxidation via S-cysteinylation were found to occur within hours at room temperature and days at −20 °C. Methionine oxidation of apoA-I took place on a longer time scale, setting in after albumin oxidation reached a plateau. Freeze–thaw cycles had a minimal effect on protein oxidation. In matched collections, protein oxidation in serum was the same as that in plasma. Albumin and apoA-I oxidation were not affected by sample headspace or the degree to which vials were sealed. ApoA-I, however, was unexpectedly found to oxidize faster in samples with lower surface-area-to-volume ratios. An initial survey of samples from patients with inflammatory conditions normally associated with elevated oxidative stress-including acute myocardial infarction and prostate cancer—demonstrated a lack of detectable apoA-I oxidation. Albumin S-cysteinylation in these samples was consistent with known but relatively brief exposures to temperatures above −30 °C (the freezing point of blood plasma). Given their properties and ease of analysis, these oxidized proteoforms, once fully validated, may represent the first markers of blood plasma specimen integrity based on direct measurement of oxidative molecular damage that can occur under suboptimal storage conditions.

In recent years, a substantial amount of research has been focused on identifying suitable interfacial layers in organic light-emitting diodes and organic solar cells which has efficient charge transport properties. In this work, a very thin layer of AgOx is deposited on top of the ITO layer along with PEDOT:PSS and is observed that the solar cells having the AgOx interfacial layer showed a 28% increase in power conversion efficiency in comparison to that of the control cell. The enhancement in efficiency has been ascribed to improvements in fill factor as well as the increase in shunt resistance and decrease in the series resistance of the solar cells. An equivalent circuit model is also provided to understand the changes in the series and shunt resistances in the AgOx modified devices.

Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network “mobile” can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.

We develop a completely data-driven approach to reconstructing coupled neuronal networks that contain a small subset of chaotic neurons. Such chaotic elements can be the result of parameter shift in their individual dynamical systems and may lead to abnormal functions of the network. To accurately identify the chaotic neurons may thus be necessary and important, for example, applying appropriate controls to bring the network to a normal state. However, due to couplings among the nodes, the measured time series, even from non-chaotic neurons, would appear random, rendering inapplicable traditional nonlinear time-series analysis, such as the delay-coordinate embedding method, which yields information about the global dynamics of the entire network. Our method is based on compressive sensing. In particular, we demonstrate that identifying chaotic elements can be formulated as a general problem of reconstructing the nodal dynamical systems, network connections and all coupling functions, as well as their weights. The working and efficiency of the method are illustrated by using networks of non-identical FitzHugh–Nagumo neurons with randomly-distributed coupling weights.

Signatures of nonlinear and non-Gaussian dynamics in time-resolved linear and nonlinear (correlation) 2D spectra are analyzed in a model considering a linear plus quadratic dependence of the spectroscopic transition frequency on a Gaussian nuclear coordinate of the thermal bath (quadratic coupling). This new model is contrasted to the commonly assumed linear dependence of the transition frequency on the medium nuclear coordinates (linear coupling). The linear coupling model predicts equality between the Stokes shift and equilibrium correlation functions of the transition frequency and time-independent spectral width. Both predictions are often violated, and we are asking here the question of whether a nonlinear solvent response and/or non-Gaussian dynamics are required to explain these observations. We find that correlation functions of spectroscopic observables calculated in the quadratic coupling model depend on the chromophore’s electronic state and the spectral width gains time dependence, all in violation of the predictions of the linear coupling models. Lineshape functions of 2D spectra are derived assuming Ornstein–Uhlenbeck dynamics of the bath nuclear modes. The model predicts asymmetry of 2D correlation plots and bending of the center line. The latter is often used to extract two-point correlation functions from 2D spectra. The dynamics of the transition frequency are non-Gaussian. However, the effect of non-Gaussian dynamics is limited to the third-order (skewness) time correlation function, without affecting the time correlation functions of higher order. The theory is tested against molecular dynamics simulations of a model polar–polarizable chromophore dissolved in a force field water.

Sliding clamps are ring-shaped oligomeric proteins that are essential for processive deoxyribonucleic acid replication. Although crystallographic structures of several clamps have been determined, much less is known about clamp structure and dynamics in solution. Here, we characterized the intrinsic solution stability and oligomerization dynamics of the homodimeric Escherichia coli β and the homotrimeric Saccharomyces cerevisiae proliferating cell nuclear antigen (PCNA) clamps using single-molecule approaches. We show that E. coli β is stable in solution as a closed ring at concentrations three orders of magnitude lower than PCNA. The trimeric structure of PCNA results in slow subunit association rates and is largely responsible for the lower solution stability. Despite this large difference, the intrinsic lifetimes of the rings differ by only one order of magnitude. Our results show that the longer lifetime of the E. coli β dimer is due to more prominent electrostatic interactions that stabilize the subunit interfaces.

We report the results of an ethnographic study of a natural food cooperative in which we found an inherent tension in its mission between idealism and pragmatism, and we explore the dynamics through which that tension was managed and engaged in day-to-day governance and activities. Insights from participant observation, archival data, semi-structured interviews, and surveys provide a detailed and holistic account of the intergroup and intragroup processes through which the co-op negotiated its dualistic nature, as embodied in its hybrid organizational identity. The findings suggest that the value of each side of the duality was recognized at both the individual and organizational levels. Members’ discomfort with the duality, however, led them to split the mission in two and identify with one part, while projecting their less-favored part on others, creating an identity foil (an antithesis). This splitting resulted in ingroups and outgroups and heated intergroup conflict over realizing cooperative ideals vs. running a viable business. Ingroup members favoring one part of the mission nonetheless identified with the outgroup favoring the other because it embodied a side of themselves they continued to value. Individuals who exemplified their ingroup’s most extreme attributes were seen by the outgroup as prototypical, thus serving as “lightning rods” for intergroup conflict; this dynamic paradoxically enabled other ingroup members to work more effectively with moderate members of the outgroup. The idealist–pragmatist duality was kept continually in play over time through oscillating decisions and actions that shifted power from one group to the other, coupled with ongoing rituals to repair and maintain relationships disrupted by the messiness of the process. Thus ostensible dysfunctionality at the group level fostered functionality at the organizational level.

The dopamine-TiO₂ system shows a specific spectroscopic response, surface enhanced Raman scattering (SERS), whose mechanism is not fully understood. In this study, the goal is to reveal the key role of the molecule–nanoparticle interface in the electronic structure by means of ab initio modeling. The dopamine adsorption energy on anatase surfaces is computed and related to changes in the electronic structure. Two features are observed: the appearance of a state in the material band gap, and charge transfer between molecule and surface upon electronic excitation. The analysis of the energetics of the systems would point to a selective adsorption of dopamine on the (001) and (100) terminations, with much less affinity for the (101) plane.

Two pentacoordinate mononuclear iron carbonyls of the form (bdt)Fe(CO)P₂ [bdt = benzene-1,2-dithiolate; P₂ = 1,1′-diphenylphosphinoferrocene (1) or methyl-2-{bis(diphenylphosphinomethyl)amino}acetate (2)] were prepared as functional, biomimetic models for the distal iron (Fe_d) of the active site of [FeFe]-hydrogenase. X-ray crystal structures of the complexes reveal that, despite similar ν(CO) stretching band frequencies, the two complexes have different coordination geometries. In X-ray crystal structures, the iron center of 1 is in a distorted trigonal bipyramidal arrangement, and that of 2 is in a distorted square pyramidal geometry. Electrochemical investigation shows that both complexes catalyze electrochemical proton reduction from acetic acid at mild overpotential, 0.17 and 0.38 V for 1 and 2, respectively. Although coordinatively unsaturated, the complexes display only weak, reversible binding affinity toward CO (1 bar). However, ligand centered protonation by the strong acid, HBF₄·OEt₂, triggers quantitative CO uptake by 1 to form a dicarbonyl analogue [1(H)-CO]⁺ that can be reversibly converted back to 1 by deprotonation using NEt₃. Both crystallographically determined distances within the bdt ligand and density functional theory calculations suggest that the iron centers in both 1 and 2 are partially reduced at the expense of partial oxidation of the bdt ligand. Ligand protonation interrupts this extensive electronic delocalization between the Fe and bdt making 1(H)⁺ susceptible to external CO binding.