Photoconductivity analyzed in the frequency domain - an introductory case study of strontium titanate

Strontium titanate (STO, SrTiO3) has been used for many applications in solid state electrochemistry and is considered a standard and model material. Its characteristics, and those of its derivatives such as STF (SrTi0.65Fe0.35O3-x), have been characterized by many groups on various aspects, such as electronic/ionic conductivity, oxygen exchange kinetics and the impact of doping. Recently, the interaction of light with STO/STF has been of increased interest. A persistent photoconductivity has been observed [1] and enhanced oxygen exchange kinetics have been detected, opening up new fields of application, such as a light-driven fuel cell [2]. The reasons behind these effects remain subject to discussion or even speculation as the relation to the relatively large bandgap and the photoresponse at long wavelengths remains unclear. What makes the analysis of these effects difficult is the interplay of many electrochemical and photoelectrochemical processes that contribute to the photoresponse including the electronic and ionic conductivity, the number and nature of charge carriers, charge traps, phonon related effects, and surface reactions. With electrochemical impedance spectroscopy (EIS), one can distinguish diverse processes on the basis of their time constants and how they evolve as a function of operating conditions, such as temperature, atmosphere (leading to stoichiometry changes) and illumination. However, the impact of light can only be characterized implicitly as a change in other processes that also prevail in the dark. Intensity modulated photocurrent/-voltage spectroscopy (IMPS/IMVS) have been shown to reveal valuable information about charge carrier dynamics for photoelectrodes and photovoltaic cells [3]. To the best of our knowledge, these techniques have never been applied to devices or materials that are not photoactive, or in other words, that do not show a photovoltage, such as a symmetrical model cells based on STO or STF. However, with the small signal light perturbation that is the key element of IMPS and IMVS, we can trigger the light effect directly and analyze the system response by its current and voltage signals. In this contribution, we will begin with a brief introduction into IMPS and IMVS and show how these techniques can be applied to model electrodes consisting of STO and STF. The results are compared to EIS under different illumination and we will show how to extract the relevant information about the photoresponse. By evaluating the activation energies of the different electrochemical and photoelectrochemical processes, we can attribute those to physical effects and clarify some of the previously unknown processes that lead to anomalies observed in STO/STF under illumination. The capacity of IMPS and IMVS have been underestimated so far and in this contribution, we will conclude with an outlook for their potential to other fields of application, such as ionic motion in perovskite solar cells that are thought to be responsible for their accelerated degradation under illumination. This work was supported by JSPS Core-to-Core Program, A. Advanced Research Networks: “Solid Oxide Interfaces for Faster Ion Transport”. References [1] M. C. Tarun et al., Phys. Rev. Lett. 111, 187403, 2013. [2] G. C. Bunauer, Adv. Funct. Mater. 26, 120, 2016. [3] D. Klotz et al., Phys. Chem. Chem. Phys. 18, 23438, 2016

Effect of Algorithm-Based Therapy vs Usual Care on Clinical Success and Serious Adverse Events in Patients with Staphylococcal Bacteremia: A Randomized Clinical Trial

Importance: The appropriate duration of antibiotics for staphylococcal bacteremia is unknown. Objective: To test whether an algorithm that defines treatment duration for staphylococcal bacteremia vs standard of care provides noninferior efficacy without increasing severe adverse events. Design, Setting, and Participants: A randomized trial involving adults with staphylococcal bacteremia was conducted at 16 academic medical centers in the United States (n = 15) and Spain (n = 1) from April 2011 to March 2017. Patients were followed up for 42 days beyond end of therapy for those with Staphylococcus aureus and 28 days for those with coagulase-negative staphylococcal bacteremia. Eligible patients were 18 years or older and had 1 or more blood cultures positive for S aureus or coagulase-negative staphylococci. Patients were excluded if they had known or suspected complicated infection at the time of randomization. Interventions: Patients were randomized to algorithm-based therapy (n = 255) or usual practice (n = 254). Diagnostic evaluation, antibiotic selection, and duration of therapy were predefined for the algorithm group, whereas clinicians caring for patients in the usual practice group had unrestricted choice of antibiotics, duration, and other aspects of clinical care. Main Outcomes and Measures: Coprimary outcomes were (1) clinical success, as determined by a blinded adjudication committee and tested for noninferiority within a 15% margin; and (2) serious adverse event rates in the intention-to-treat population, tested for superiority. The prespecified secondary outcome measure, tested for superiority, was antibiotic days among per-protocol patients with simple or uncomplicated bacteremia. Results: Among the 509 patients randomized (mean age, 56.6 [SD, 16.8] years; 226 [44.4%] women), 480 (94.3%) completed the trial. Clinical success was documented in 209 of 255 patients assigned to algorithm-based therapy and 207 of 254 randomized to usual practice (82.0% vs 81.5%; difference, 0.5% [1-sided 97.5% CI, -6.2% to ∞]). Serious adverse events were reported in 32.5% of algorithm-based therapy patients and 28.3% of usual practice patients (difference, 4.2% [95% CI, -3.8% to 12.2%]). Among per-protocol patients with simple or uncomplicated bacteremia, mean duration of therapy was 4.4 days for algorithm-based therapy vs 6.2 days for usual practice (difference, -1.8 days [95% CI, -3.1 to -0.6]). Conclusions and Relevance: Among patients with staphylococcal bacteremia, the use of an algorithm to guide testing and treatment compared with usual care resulted in a noninferior rate of clinical success. Rates of serious adverse events were not significantly different, but interpretation is limited by wide confidence intervals. Further research is needed to assess the utility of the algorithm. Trial Registration: ClinicalTrials.gov Identifier: NCT01191840

α7-Nicotinic Acetylcholine Receptor: Role in Early Odor Learning Preference in Mice

Recently, we have shown that mice with decreased expression of α7-nicotinic acetylcholine receptors (α7) in the olfactory bulb were associated with a deficit in odor discrimination compared to wild-type mice. However, it is unknown if mice with decreased α7-receptor expression also show a deficit in early odor learning preference (ELP), an enhanced behavioral response to odors with attractive value observed in rats. In this study, we modified ELP methods performed in rats and implemented similar conditions in mice. From post-natal days 5–18, wild-type mice were stroked simultaneously with an odor presentation (conditioned odor) for 90 s daily. Control mice were only stroked, exposed to odor, or neither. On the day of testing (P21), mice that were stroked in concert with a conditioned odor significantly investigated the conditioned odor compared to a novel odor, as observed similarly in rats. However, mice with a decrease in α7-receptor expression that were stroked during a conditioned odor did not show a behavioral response to that odorant. These results suggest that decreased α7-receptor expression has a role in associative learning, olfactory preference, and/or sensory processing deficits

Micro-solid oxide fuel cells as power supply for small portable electronic equipment

Micro-solid oxide fuel cell (SOFC) systems are anticipated for powering small, portable electronic devices, such as laptop, personal digital assistant (PDA), medical and industrial accessories. It is predicted that micro-SOFC systems have a 2-4 higher energy density than Li-ion batteries [1]. However, literature mainly focuses on the fabrication and characterization of thin films and membranes for micro-SOFC systems [2-12]; the entire system approach is not yet studied in detail. We will therefore discuss in this paper the entire approach from the fabrication of thin films and membranes up to the complete system, including fuel processing, thermal management and integration

Is (poly-) substance use associated with impaired inhibitory control? A mega-analysis controlling for confounders.

Many studies have reported that heavy substance use is associated with impaired response inhibition. Studies typically focused on associations with a single substance, while polysubstance use is common. Further, most studies compared heavy users with light/non-users, though substance use occurs along a continuum. The current mega-analysis accounted for these issues by aggregating individual data from 43 studies (3610 adult participants) that used the Go/No-Go (GNG) or Stop-signal task (SST) to assess inhibition among mostly "recreational" substance users (i.e., the rate of substance use disorders was low). Main and interaction effects of substance use, demographics, and task-characteristics were entered in a linear mixed model. Contrary to many studies and reviews in the field, we found that only lifetime cannabis use was associated with impaired response inhibition in the SST. An interaction effect was also observed: the relationship between tobacco use and response inhibition (in the SST) differed between cannabis users and non-users, with a negative association between tobacco use and inhibition in the cannabis non-users. In addition, participants' age, education level, and some task characteristics influenced inhibition outcomes. Overall, we found limited support for impaired inhibition among substance users when controlling for demographics and task-characteristics

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)