Inspiratory muscle training reduces blood lactate concentration during volitional hyperpnoea

Although reduced blood lactate concentrations ([lac−]B) have been observed during whole-body exercise following inspiratory muscle training (IMT), it remains unknown whether the inspiratory muscles are the source of at least part of this reduction. To investigate this, we tested the hypothesis that IMT would attenuate the increase in [lac−]B caused by mimicking, at rest, the breathing pattern observed during high-intensity exercise. Twenty-two physically active males were matched for 85% maximal exercise minute ventilation (V˙Emax) and divided equally into an IMT or a control group. Prior to and following a 6 week intervention, participants performed 10 min of volitional hyperpnoea at the breathing pattern commensurate with 85% V˙Emax

Iron, silicate, and light co-limitation of three Southern Ocean diatom species

The effect of combined iron, silicate, and light co-limitation was investigated in the three diatom species Actinocyclus sp. Ehrenberg, Chaetoceros dichaeta Ehrenberg, and Chaetoceros debilis Cleve, isolated from the Southern Ocean (SO). Growth of all species was co-limited by iron and silicate, reflected in a significant increase in the number of cell divisions compared to the control. Lowest relative Si uptake and drastic frustule malformation was found under iron and silicate co-limitation in C. dichaeta, while Si limitation in general caused cell elongation in both Chaetoceros species. Higher light intensities similar to SO surface conditions showed a negative impact on growth of C. dichaeta and Actinocyclus sp. and no effect on C. debilis. This is in contrast to the assumed light limitation of SO diatoms due to deep wind driven mixing. Our results suggest that growth and species composition of Southern Ocean diatoms is influenced by a sensitive interaction of the abiotic factors, iron, silicate, and light

Impaired perceptual learning in a mouse model of Fragile X syndrome is mediated by parvalbumin neuron dysfunction and is reversible.

To uncover the circuit-level alterations that underlie atypical sensory processing associated with autism, we adopted a symptom-to-circuit approach in the Fmr1-knockout (Fmr1-/-) mouse model of Fragile X syndrome. Using a go/no-go task and in vivo two-photon calcium imaging, we find that impaired visual discrimination in Fmr1-/- mice correlates with marked deficits in orientation tuning of principal neurons and with a decrease in the activity of parvalbumin interneurons in primary visual cortex. Restoring visually evoked activity in parvalbumin cells in Fmr1-/- mice with a chemogenetic strategy using designer receptors exclusively activated by designer drugs was sufficient to rescue their behavioral performance. Strikingly, human subjects with Fragile X syndrome exhibit impairments in visual discrimination similar to those in Fmr1-/- mice. These results suggest that manipulating inhibition may help sensory processing in Fragile X syndrome

A distributed beam loss monitor for the Australian Synchrotron

© 2018 Elsevier B.V. A distributed beam loss monitoring system, named the optical fibre Beam Loss Monitor, has been installed at the Australian Synchrotron. Relativistic charged particles produced in beam loss events generate photons via the Cherenkov mechanism in four silica fibres that run parallel to the beam pipe and cover the majority of the accelerator's length. These photons are then guided by the fibres to detectors located outside of the accelerator tunnel. By measuring the time of flight of these photons, the locations of beam losses can be reconstructed. Based on this method a calibration was produced, mapping the time of flight to a position along the accelerator. This calibration was applied to loss signals collected on the first pass of the beam through the accelerator and the locations of prominent losses were determined. Using this system it was possible to investigate the effect, on the location and intensity of losses, in response to changes in the lattice parameters on a shot-by-shot basis. This system is now used in routine operations and has resulted in a 40 % increase in the capture efficiency of the booster ring

Modeling repeated ordinal responses using a family of power transformations: application to neonatal hypothermia data

BACKGROUND: For analyzing a repeated ordinal response, it is common to use a multivariate cumulative logit model. This model may fit poorly, especially when a nonsymmetric response is available. In these cases, alternative strategies should be utilized. METHODS: In this paper, we present a family of power transformations for the cumulative probabilities to model asymmetric departures from the random-intercept cumulative logit model. To illustrate this method, we analyze the data from an epidemiologic study to identify risk factors of hypothermia among newly born infants in some referral university hospitals in Tehran, Iran. RESULTS: For hypothermia data, using this family of transformations and comparing the goodness-of-fit statistics showed that a model with the cumulative complementary log-log link gives us a better fit compared to a model with the cumulative logit link. CONCLUSION: In some areas, using the ordinary cumulative logit link function does not lead to the best fit. So, other link functions should be evaluated to discover the best transformation for the cumulative probabilities

Oblique decision trees for spatial pattern detection: optimal algorithm and application to malaria risk

BACKGROUND: In order to detect potential disease clusters where a putative source cannot be specified, classical procedures scan the geographical area with circular windows through a specified grid imposed to the map. However, the choice of the windows' shapes, sizes and centers is critical and different choices may not provide exactly the same results. The aim of our work was to use an Oblique Decision Tree model (ODT) which provides potential clusters without pre-specifying shapes, sizes or centers. For this purpose, we have developed an ODT-algorithm to find an oblique partition of the space defined by the geographic coordinates. METHODS: ODT is based on the classification and regression tree (CART). As CART finds out rectangular partitions of the covariate space, ODT provides oblique partitions maximizing the interclass variance of the independent variable. Since it is a NP-Hard problem in R(N), classical ODT-algorithms use evolutionary procedures or heuristics. We have developed an optimal ODT-algorithm in R(2), based on the directions defined by each couple of point locations. This partition provided potential clusters which can be tested with Monte-Carlo inference. We applied the ODT-model to a dataset in order to identify potential high risk clusters of malaria in a village in Western Africa during the dry season. The ODT results were compared with those of the Kulldorff' s SaTScan™. RESULTS: The ODT procedure provided four classes of risk of infection. In the first high risk class 60%, 95% confidence interval (CI95%) [52.22–67.55], of the children was infected. Monte-Carlo inference showed that the spatial pattern issued from the ODT-model was significant (p < 0.0001). Satscan results yielded one significant cluster where the risk of disease was high with an infectious rate of 54.21%, CI95% [47.51–60.75]. Obviously, his center was located within the first high risk ODT class. Both procedures provided similar results identifying a high risk cluster in the western part of the village where a mosquito breeding point was located. CONCLUSION: ODT-models improve the classical scanning procedures by detecting potential disease clusters independently of any specification of the shapes, sizes or centers of the clusters