Activated sputum eosinophils associated with exacerbations in children on mepolizumab.

BACKGROUND: MUPPITS-2 was a randomized, placebo-controlled clinical trial that demonstrated mepolizumab (anti-IL-5) reduced exacerbations and blood and airway eosinophils in urban children with severe eosinophilic asthma. Despite this reduction in eosinophilia, exacerbation risk persisted in certain patients treated with mepolizumab. This raises the possibility that subpopulations of airway eosinophils exist that contribute to breakthrough exacerbations. OBJECTIVE: We aimed to determine the effect of mepolizumab on airway eosinophils in childhood asthma. METHODS: Sputum samples were obtained from 53 MUPPITS-2 participants. Airway eosinophils were characterized using mass cytometry and grouped into subpopulations using unsupervised clustering analyses of 38 surface and intracellular markers. Differences in frequency and immunophenotype of sputum eosinophil subpopulations were assessed based on treatment arm and frequency of exacerbations. RESULTS: Median sputum eosinophils were significantly lower among participants treated with mepolizumab compared with placebo (58% lower, 0.35% difference [95% CI 0.01, 0.74], P = .04). Clustering analysis identified 3 subpopulations of sputum eosinophils with varied expression of CD62L. CD62Lint and CD62Lhi eosinophils exhibited significantly elevated activation marker and eosinophil peroxidase expression, respectively. In mepolizumab-treated participants, CD62Lint and CD62Lhi eosinophils were more abundant in participants who experienced exacerbations than in those who did not (100% higher for CD62Lint, 0.04% difference [95% CI 0.0, 0.13], P = .04; 93% higher for CD62Lhi, 0.21% difference [95% CI 0.0, 0.77], P = .04). CONCLUSIONS: Children with eosinophilic asthma treated with mepolizumab had significantly lower sputum eosinophils. However, CD62Lint and CD62Lhi eosinophils were significantly elevated in children on mepolizumab who had exacerbations, suggesting that eosinophil subpopulations exist that contribute to exacerbations despite anti-IL-5 treatment.

Use of Single-Dose Dexamethasone in Patients With Diabetes Undergoing Surgery: A Systematic Review and Meta-Analysis.

The purpose of this review was to examine the effect of single-dose dexamethasone on perioperative blood glucose in diabetic patients. We used PubMed, Cochrane Library, MEDLINE, CINAHL, Google Scholar, and grey literature for our search. Only randomized controlled trials were included. Risk ratio (RR) and mean difference (MD) were used to estimate outcomes with suitable effect models. Quality of evidence was assessed using the Risk of Bias and GRADE systems. We analyzed seven trials involving 1,321 patients. Diabetic patients treated with single-dose dexamethasone had statistically significant changes in blood glucose levels from baseline by 33.61 mg/dL (MD, 33.61; 95% CI, 17.59 to 49.63; P < .0001). Dexamethasone increased blood glucose levels 1-4 hours (MD, 29.02; 95% CI, 7.09 to 50.94; P = .010), 8-24 hours (MD, 30.81; 95% CI, 9.21 to 52.41; P = .005) after administration and increased risks of hyperglycemia. However, there was no difference in surgical site infection (SSI) (RR, 0.81; 95% CI, 0.59 to 1.11; P = .19). Effect size imprecision, substantial heterogeneity, and publication bias was the study's limitations. We found that single-dose dexamethasone increased glucose concentration 24 hours after surgery with little to no effect on SSI. Extrapolation of these findings to clinical settings must take into consideration the review's limitations.

Measuring US fertility using administrative data from the Census Bureau.

BACKGROUND: Longitudinal data available for studying fertility in the United States are not representative at the state level, limiting analyses of subnational variation in US fertility. The US Census Bureau makes available restricted data that may be used for measuring fertility, but the data have not previously been described for a scholarly audience or used for fertility research. OBJECTIVE: This paper describes and analyzes restricted-use administrative birth data available through the Census Numident for nearly all US births for more than the last century. Within these data, most births since 1997 are linked to parents through the Census Household Composition Key (CHCK). These analyses are designed to illustrate the scope and limitations of these data for the study of US fertility. METHODS: We describe the creation and content of the Census Numindent and CHCK data sets and compare the data to published US vital statistics. We also analyze the geographic coverage of both data sets and compare the demographic composition of the new data sources to national demographic composition. We further illustrate how these novel data sources may be used by comparing them to survey responses at the individual level. CONTRIBUTION: This paper describes an underutilized source of national US data for studying fertility, shows the quality of these data by performing analyses, and explains how scholars can access these data for research.

Standardized and reproducible measurement of decision-making in mice.

Progress in science requires standardized assays whose results can be readily shared, compared, and reproduced across laboratories. Reproducibility, however, has been a concern in neuroscience, particularly for measurements of mouse behavior. Here, we show that a standardized task to probe decision-making in mice produces reproducible results across multiple laboratories. We adopted a task for head-fixed mice that assays perceptual and value-based decision making, and we standardized training protocol and experimental hardware, software, and procedures. We trained 140 mice across seven laboratories in three countries, and we collected 5 million mouse choices into a publicly available database. Learning speed was variable across mice and laboratories, but once training was complete there were no significant differences in behavior across laboratories. Mice in different laboratories adopted similar reliance on visual stimuli, on past successes and failures, and on estimates of stimulus prior probability to guide their choices. These results reveal that a complex mouse behavior can be reproduced across multiple laboratories. They establish a standard for reproducible rodent behavior, and provide an unprecedented dataset and open-access tools to study decision-making in mice. More generally, they indicate a path toward achieving reproducibility in neuroscience through collaborative open-science approaches.

In science, it is of vital importance that multiple studies corroborate the same result. Researchers therefore need to know all the details of previous experiments in order to implement the procedures as exactly as possible. However, this is becoming a major problem in neuroscience, as animal studies of behavior have proven to be hard to reproduce, and most experiments are never replicated by other laboratories. Mice are increasingly being used to study the neural mechanisms of decision making, taking advantage of the genetic, imaging and physiological tools that are available for mouse brains. Yet, the lack of standardized behavioral assays is leading to inconsistent results between laboratories. This makes it challenging to carry out large-scale collaborations which have led to massive breakthroughs in other fields such as physics and genetics. To help make these studies more reproducible, the International Brain Laboratory (a collaborative research group) et al. developed a standardized approach for investigating decision making in mice that incorporates every step of the process; from the training protocol to the software used to analyze the data. In the experiment, mice were shown images with different contrast and had to indicate, using a steering wheel, whether it appeared on their right or left. The mice then received a drop of sugar water for every correction decision. When the image contrast was high, mice could rely on their vision. However, when the image contrast was very low or zero, they needed to consider the information of previous trials and choose the side that had recently appeared more frequently. This method was used to train 140 mice in seven laboratories from three different countries. The results showed that learning speed was different across mice and laboratories, but once training was complete the mice behaved consistently, relying on visual stimuli or experiences to guide their choices in a similar way. These results show that complex behaviors in mice can be reproduced across multiple laboratories, providing an unprecedented dataset and open-access tools for studying decision making. This work could serve as a foundation for other groups, paving the way to a more collaborative approach in the field of neuroscience that could help to tackle complex research challenges.

Integrating single-molecule FRET and biomolecular simulations to study diverse interactions between nucleic acids and proteins.

The conformations of biological macromolecules are intimately related to their cellular functions. Conveniently, the well-characterized dipole-dipole distance-dependence of Förster resonance energy transfer (FRET) makes it possible to measure and monitor the nanoscale spatial dimensions of these conformations using fluorescence spectroscopy. For this reason, FRET is often used in conjunction with single-molecule detection to study a wide range of conformationally dynamic biochemical processes. Written for those not yet familiar with the subject, this review aims to introduce biochemists to the methodology associated with single-molecule FRET, with a particular emphasis on how it can be combined with biomolecular simulations to study diverse interactions between nucleic acids and proteins. In the first section, we highlight several conceptual and practical considerations related to this integrative approach. In the second section, we review a few recent research efforts wherein various combinations of single-molecule FRET and biomolecular simulations were used to study the structural and dynamic properties of biochemical systems involving different types of nucleic acids (e.g., DNA and RNA) and proteins (e.g., folded and disordered).

Efficient training of mice on the 5-choice serial reaction time task in an automated rodent training system.

Experiments aiming to understand sensory-motor systems, cognition and behavior necessitate training animals to perform complex tasks. Traditional training protocols require lab personnel to move the animals between home cages and training chambers, to start and end training sessions, and in some cases, to hand-control each training trial. Human labor not only limits the amount of training per day, but also introduces several sources of variability and may increase animal stress. Here we present an automated training system for the 5-choice serial reaction time task (5CSRTT), a classic rodent task often used to test sensory detection, sustained attention and impulsivity. We found that full automation without human intervention allowed rapid, cost-efficient training, and decreased stress as measured by corticosterone levels. Training breaks introduced only a transient drop in performance, and mice readily generalized across training systems when transferred from automated to manual protocols. We further validated our automated training system with wireless optogenetics and pharmacology experiments, expanding the breadth of experimental needs our system may fulfill. Our automated 5CSRTT system can serve as a prototype for fully automated behavioral training, with methods and principles transferrable to a range of rodent tasks.

Reward foraging task and model-based analysis reveal how fruit flies learn value of available options.

Foraging animals have to evaluate, compare and select food patches in order to increase their fitness. Understanding what drives foraging decisions requires careful manipulation of the value of alternative options while monitoring animals choices. Value-based decision-making tasks in combination with formal learning models have provided both an experimental and theoretical framework to study foraging decisions in lab settings. While these approaches were successfully used in the past to understand what drives choices in mammals, very little work has been done on fruit flies. This is despite the fact that fruit flies have served as model organism for many complex behavioural paradigms. To fill this gap we developed a single-animal, trial-based decision making task, where freely walking flies experienced optogenetic sugar-receptor neuron stimulation. We controlled the value of available options by manipulating the probabilities of optogenetic stimulation. We show that flies integrate reward history of chosen options and forget value of unchosen options. We further discover that flies assign higher values to rewards experienced early in the behavioural session, consistent with formal reinforcement learning models. Finally, we also show that the probabilistic rewards affect walking trajectories of flies, suggesting that accumulated value is controlling the navigation vector of flies in a graded fashion. These findings establish the fruit fly as a model organism to explore the genetic and circuit basis of reward foraging decisions.

The pheromone darcin drives a circuit for innate and reinforced behaviours.

Organisms have evolved diverse behavioural strategies that enhance the likelihood of encountering and assessing mates1. Many species use pheromones to communicate information about the location, sexual and social status of potential partners2. In mice, the major urinary protein darcin-which is present in the urine of males-provides a component of a scent mark that elicits approach by females and drives learning3,4. Here we show that darcin elicits a complex and variable behavioural repertoire that consists of attraction, ultrasonic vocalization and urinary scent marking, and also serves as a reinforcer in learning paradigms. We identify a genetically determined circuit-extending from the accessory olfactory bulb to the posterior medial amygdala-that is necessary for all behavioural responses to darcin. Moreover, optical activation of darcin-responsive neurons in the medial amygdala induces both the innate and the conditioned behaviours elicited by the pheromone. These neurons define a topographically segregated population that expresses neuronal nitric oxide synthase. We suggest that this darcin-activated neural circuit integrates pheromonal information with internal state to elicit both variable innate behaviours and reinforced behaviours that may promote mate encounters and mate selection.

A Mathematical Framework for Statistical Decision Confidence.

Decision confidence is a forecast about the probability that a decision will be correct. From a statistical perspective, decision confidence can be defined as the Bayesian posterior probability that the chosen option is correct based on the evidence contributing to it. Here, we used this formal definition as a starting point to develop a normative statistical framework for decision confidence. Our goal was to make general predictions that do not depend on the structure of the noise or a specific algorithm for estimating confidence. We analytically proved several interrelations between statistical decision confidence and observable decision measures, such as evidence discriminability, choice, and accuracy. These interrelationships specify necessary signatures of decision confidence in terms of externally quantifiable variables that can be empirically tested. Our results lay the foundations for a mathematically rigorous treatment of decision confidence that can lead to a common framework for understanding confidence across different research domains, from human and animal behavior to neural representations.

Signatures of a Statistical Computation in the Human Sense of Confidence.

Human confidence judgments are thought to originate from metacognitive processes that provide a subjective assessment about one's beliefs. Alternatively, confidence is framed in mathematics as an objective statistical quantity: the probability that a chosen hypothesis is correct. Despite similar terminology, it remains unclear whether the subjective feeling of confidence is related to the objective, statistical computation of confidence. To address this, we collected confidence reports from humans performing perceptual and knowledge-based psychometric decision tasks. We observed two counterintuitive patterns relating confidence to choice and evidence: apparent overconfidence in choices based on uninformative evidence, and decreasing confidence with increasing evidence strength for erroneous choices. We show that these patterns lawfully arise from statistical confidence, and therefore occur even for perfectly calibrated confidence measures. Furthermore, statistical confidence quantitatively accounted for human confidence in our tasks without necessitating heuristic operations. Accordingly, we suggest that the human feeling of confidence originates from a mental computation of statistical confidence.

A low-cost programmable pulse generator for physiology and behavior.

Precisely timed experimental manipulations of the brain and its sensory environment are often employed to reveal principles of brain function. While complex and reliable pulse trains for temporal stimulus control can be generated with commercial instruments, contemporary options remain expensive and proprietary. We have developed Pulse Pal, an open source device that allows users to create and trigger software-defined trains of voltage pulses with high temporal precision. Here we describe Pulse Pal's circuitry and firmware, and characterize its precision and reliability. In addition, we supply online documentation with instructions for assembling, testing and installing Pulse Pal. While the device can be operated as a stand-alone instrument, we also provide application programming interfaces in several programming languages. As an inexpensive, flexible and open solution for temporal control, we anticipate that Pulse Pal will be used to address a wide range of instrumentation timing challenges in neuroscience research.

Cortical interneurons that specialize in disinhibitory control.

In the mammalian cerebral cortex the diversity of interneuronal subtypes underlies a division of labour subserving distinct modes of inhibitory control. A unique mode of inhibitory control may be provided by inhibitory neurons that specifically suppress the firing of other inhibitory neurons. Such disinhibition could lead to the selective amplification of local processing and serve the important computational functions of gating and gain modulation. Although several interneuron populations are known to target other interneurons to varying degrees, little is known about interneurons specializing in disinhibition and their in vivo function. Here we show that a class of interneurons that express vasoactive intestinal polypeptide (VIP) mediates disinhibitory control in multiple areas of neocortex and is recruited by reinforcement signals. By combining optogenetic activation with single-cell recordings, we examined the functional role of VIP interneurons in awake mice, and investigated the underlying circuit mechanisms in vitro in auditory and medial prefrontal cortices. We identified a basic disinhibitory circuit module in which activation of VIP interneurons transiently suppresses primarily somatostatin- and a fraction of parvalbumin-expressing inhibitory interneurons that specialize in the control of the input and output of principal cells, respectively. During the performance of an auditory discrimination task, reinforcement signals (reward and punishment) strongly and uniformly activated VIP neurons in auditory cortex, and in turn VIP recruitment increased the gain of a functional subpopulation of principal neurons. These results reveal a specific cell type and microcircuit underlying disinhibitory control in cortex and demonstrate that it is activated under specific behavioural conditions.

Choice ball: a response interface for two-choice psychometric discrimination in head-fixed mice.

The mouse is an important model system for investigating the neural circuits mediating behavior. Because of advances in imaging and optogenetic methods, head-fixed mouse preparations provide an unparalleled opportunity to observe and control neural circuits. To investigate how neural circuits produce behavior, these methods need to be paired with equally well-controlled and monitored behavioral paradigms. Here, we introduce the choice ball, a response device that enables two-alternative forced-choice (2AFC) tasks in head-fixed mice based on the readout of lateral paw movements. We demonstrate the advantages of the choice ball by training mice in the random-click task, a two-choice auditory discrimination behavior. For each trial, mice listened to binaural streams of Poisson-distributed clicks and were required to roll the choice ball laterally toward the side with the greater click rate. In this assay, mice performed hundreds of trials per session with accuracy ranging from 95% for easy stimuli (large interaural click-rate contrast) to near chance level for low-contrast stimuli. We also show, using the record of individual paw strokes, that mice often reverse decisions they have already initiated and that decision reversals correlate with improved performance. The choice ball enables head-fixed 2AFC paradigms, facilitating the circuit-level analysis of sensory processing, decision making, and motor control in mice.

Hydroxypropyl cellulose as an adsorptive coating sieving matrix for DNA separations: artificial neural network optimization for microchip analysis.

Effective DNA separations in microelectrophoretic systems are complicated by the need to passivate the surface dynamically or covalently. We describe the optimization and utilization of a novel buffer system for fast DNA separations by capillary and microchip electrophoresis without the need for any surface modification or conditioning prior to separation. At concentrations as high as 5%, hydroxypropyl cellulose (HPC) has a relatively low viscosity, allowing for microchip channel filling to be performed with ease. A MES/TRIS buffer system at pH 6.1 eliminates the need for surface preconditioning procedures due to the promotion of hydrogen bonding of HPC with the wall. An additional benefit with this buffer system is the low current observed at high fields when compared to other common DNA separation buffers. An artificial neural network (ANN) was used to model the data and to predict the optimum conditions. Utility of the ANN-optimized system for molecular diagnostic testing was demonstrated by performing microchip separations on DNA samples from patients suspected of having genetic mutations associated with Duchenne muscular dystrophy (DMD). Microchip analysis easily allowed for the patient samples positive for DMD mutations to be distinguished from patient samples negative for the disease.

A microchip-based proteolytic digestion system driven by electroosmotic pumping.

Microchip-based proteomic analysis requires proteolytic digestion of proteins in microdevices. Enzyme reactors in microdevices, fabricated in glass, silicon, and PDMS substrates, have recently been demonstrated for model protein digestions. The common approach used for these enzyme reactors is employment of a syringe pump(s) to generate hydrodynamic flow, driving the proteins through the reactors. Here we present a novel approach, using electroosmotic flow (EOF) to electrokinetically pump proteins through a proteolytic system. The existence of EOF in the proteolytic system packed with immobilized trypsin gel beads was proven by imaging the movement of a neutral fluorescent marker. Digestions of proteins were subsequently carried out for 12 min, and the tryptic peptides were analyzed independently using capillary electrophoresis (CE) and MALDI-TOF mass spectrometry (MS). The results from CE analysis of the tryptic peptides from the EOF-driven proteolytic system and a conventional water bath digestion were comparable. MALDI-TOF MS was used to identify the parent protein and the tryptic peptides using MS-Fit database searching. The potential utility of the EOF-driven proteolytic system was demonstrated by direct electro-elution of proteins from an acrylamide gel into the proteolytic system, with elution and tryptic digestion achieved in a single step. The EOF-driven proteolytic system, thus, provides a simple way to integrate protein digestion into an electrophoretic micro total analysis system for protein analysis and characterization.

Laser-induced fluorescence detection on multichannel electrophoretic microchips using microprocessor-embedded acousto-optic laser beam scanning.

An improved method for fast scanning and fluorescence detection on multimicrochannel microchips is presented using acousto-optic-deflection-driven laser-beam scanning. A microprocessor embedded subsystem used in conjunction with LabView program as the human-machine interface for control of laser-beam scanning and data preprocessing allowed faster scanning and addressing speeds to be attained and improved attenuation calibration and the data sampling speed. This system allows for flexible, high-resolution fluorescence detection for multimicrochannel electrophoresis in a manner that can be applied to a number of high-throughput analysis applications. Incorporating an F-theta focusing lens into the optical set-up allowed for a laser spot as small as 10 microm to accurately be addressed to the center of microchannels. With this spot size, it will be possible to further increase the channel density in the scanning range without encountering crosstalk. Using a six-channel microchip (four separation channels, two alignment channels), the simultaneous separation and fluorescence detection of amino acids and DNA digest samples in four channels is illustrated. User-friendly interpretation of the separation data is facilitated not only by a peak alignment/normalization routine developed within the software, but also through improved signal-to-noise ratios obtained through exploitation of signal processing.

A simple PDMS-based electro-fluidic interface for microchip electrophoretic separations.

High voltage electrodes for electrophoresis have been integrated into a polymer layer that can be reversibly bound to glass microchips for electrophoretic separations. By using the liquid precursor to the polymer polydimethylsiloxane (PDMS), platinum electrodes and reservoirs can be positioned prior to solidification, providing a simple and flexible method for electrode interface construction. Field strengths up to 875 V cm(-1) over an 8 cm separation channel can be applied to the system without any loss in performance of the interface. The interface can function as an electro-fluidic interface between the high voltage power supply and the separation channel and, when reversibly sealed to an etched glass plate, functions as a cover plate establishing a hybrid PDMS-glass microchip in which the electrodes are directly integrated onto the device. The versatility of this approach is not only demonstrated by separating DNA fragments in a novel buffer sieving matrix, but also with the molecular diagnostic analysis of a variety of DNA samples for Duschenne Muscular Dystrophy and cytomegalovirus (CMV) infection, using both microchip interface configurations.