СВЧ плазмохимическое осаждение структур для высокоапертурных планарных оптических волноводов

Представлены результаты разработки технологии и исследования оптических характеристик высокоапертурных ПОВ на основе SiO₂-F | SiO₂ | SiO₂-F-структур, формируемых в плазме СВЧ-разряда

Characterization of the Fungal Microbiota (Mycobiome) in Healthy and Dandruff-Afflicted Human Scalps

The human scalp harbors a vast community of microbial mutualists, the composition of which is difficult to elucidate as many of the microorganisms are not culturable using current culture techniques. Dandruff, a common scalp disorder, is known as a causative factor of a mild seborrheic dermatitis as well as pityriasis versicolor, seborrheic dermatitis, and atopic dermatitis. Lipophilic yeast Malassezia is widely accepted to play a role in dandruff, but relatively few comprehensive studies have been reported. In order to investigate fungal biota and genetic resources of dandruff, we amplified the 26S rRNA gene from samples of healthy scalps and dandruff-afflicted scalps. The sequences were analyzed by a high throughput method using a GS-FLX 454 pyrosequencer. Of the 74,811 total sequence reads, Basidiomycota (Filobasidium spp.) was the most common phylum associated with dandruff. In contrast, Ascomycota (Acremonium spp.) was common in the healthy scalps. Our results elucidate the distribution of fungal communities associated with dandruff and provide new avenues for the potential prevention and treatment of dandruff

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

Differential Attraction of Malaria Mosquitoes to Volatile Blends Produced by Human Skin Bacteria

The malaria mosquito Anopheles gambiae sensu stricto is mainly guided by human odour components to find its blood host. Skin bacteria play an important role in the production of human body odour and when grown in vitro, skin bacteria produce volatiles that are attractive to A. gambiae. The role of single skin bacterial species in the production of volatiles that mediate the host-seeking behaviour of mosquitoes has remained largely unknown and is the subject of the present study. Headspace samples were taken to identify volatiles that mediate this behaviour. These volatiles could be used as mosquito attractants or repellents. Five commonly occurring species of skin bacteria were tested in an olfactometer for the production of volatiles that attract A. gambiae. Odour blends produced by some bacterial species were more attractive than blends produced by other species. In contrast to odours from the other bacterial species tested, odours produced by Pseudomonas aeruginosa were not attractive to A. gambiae. Headspace analysis of bacterial volatiles in combination with behavioural assays led to the identification of six compounds that elicited a behavioural effect in A. gambiae. Our results provide, to our knowledge, the first evidence for a role of selected bacterial species, common on the human skin, in determining the attractiveness of humans to malaria mosquitoes. This information will be used in the further development of a blend of semiochemicals for the manipulation of mosquito behaviour

Investigating large-scale brain dynamics using field potential recordings: Analysis and interpretation

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (EEG, MEG, ECoG and LFP) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide best-practice recommendations for the analyses and interpretations using a forward model and an inverse model. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems