The feasibility of daily monitoring in adolescents and young adults with mild intellectual disability or borderline intellectual functioning

BACKGROUND: It is unclear whether the limitations of young persons with a mild intellectual disability or borderline intellectual functioning preclude feasibility of the daily diary method.METHOD: For 60 consecutive days, 50 participants (M age  = 21.4, 56% male) who receive care in an ambulatory, residential, or juvenile detention setting, self-rated both standardised and personalised diary questions through an app. Diary entries were used for feedback in treatment. Interviews were used to explore acceptability. RESULTS: Average compliance was 70.4%, while 26% of participants dropped out. Compliance was good in ambulatory (88.9%) and residential care (75.6%), but not in the juvenile detention setting (19.4%). The content of self-selected diary items varied widely. Participants deemed the method acceptable.CONCLUSIONS: Daily monitoring is feasible for individuals with a mild intellectual disability or borderline intellectual functioning receiving ambulatory or residential care, and can provide scientists and practitioners with important insights into day-to-day behavioural patterns.</p

A Bayesian Approach to Risk Management in a World of High-Frequency Data

A Realised Volatility GARCH model using high-frequency data is developed within a Bayesian framework for the purpose of forecasting Value at Risk and Conditional Value at Risk. A Skewed Student-t return distribution is combined with a Student-t distribution in the measurement equation in a GARCH framework. Realised Volatility GARCH models show a marked improvement compared to ordinary GARCH. A Skewed Student-t Realised DCC copula model using Realised Volatility GARCH marginal functions is developed within a Bayesian framework for the purpose of forecasting portfolio tail risk. The use of copulas is implemented so that the marginal distributions can be separated from the dependence structure to produce tail forecasts. This is compared to using traditional GARCH-copula models, and GARCH on an aggregated portfolio. Copula models implementing a Realised Volatility GARCH framework show an improvement over traditional GARCH models. A Bayesian detection of regime changes utilizing high-frequency data is developed, once again for the purpose of forecasting portfolio tail risk. The use of high-frequency data improves the accuracy of regime change detection compared to daily data. Monte Carlo sampling schemes are employed for the estimation of these models

Thermography and thermoregulation of the face

BACKGROUND: Although clinical diagnosis of thermoregulation is gaining in importance there is no consistent evidence on the value of thermography of the facial region. In particular there are no reference values established with standardised methods. METHODS: Skin temperatures were measured in the facial area at 32 fixed measuring sites in 26 health subjects (7–72 years) with the aid of a contact thermograph (Eidatherm). A total of 6 measurements were performed separately for the two sides of the face at intervals of equal lengths (4 hours) over a period of 24 hours. Thermoregulation was triggered by application of a cold stimulus in the region of the ipsilateral ear lobe. RESULTS: Comparison of the sides revealed significant asymmetry of face temperature. The left side of the face showed a temperature that was on the average 0.1°C lower than on the right. No increase in temperature was found following application of the cold stimulus. However, a significant circadian rhythm with mean temperature differences of 0.7°C was observed. CONCLUSION: The results obtained should be seen as an initial basis for compiling an exact thermoprofile of the surface temperature of the facial region that takes into account the circadian rhythm, thus closing gaps in studies on physiological changes in the temperature of the skin of the face

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

cGMP-Dependent Protein Kinase Type I Is Implicated in the Regulation of the Timing and Quality of Sleep and Wakefulness

Many effects of nitric oxide (NO) are mediated by the activation of guanylyl cyclases and subsequent production of the second messenger cyclic guanosine-3′,5′-monophosphate (cGMP). cGMP activates cGMP-dependent protein kinases (PRKGs), which can therefore be considered downstream effectors of NO signaling. Since NO is thought to be involved in the regulation of both sleep and circadian rhythms, we analyzed these two processes in mice deficient for cGMP-dependent protein kinase type I (PRKG1) in the brain. Prkg1 mutant mice showed a strikingly altered distribution of sleep and wakefulness over the 24 hours of a day as well as reductions in rapid-eye-movement sleep (REMS) duration and in non-REM sleep (NREMS) consolidation, and their ability to sustain waking episodes was compromised. Furthermore, they displayed a drastic decrease in electroencephalogram (EEG) power in the delta frequency range (1–4 Hz) under baseline conditions, which could be normalized after sleep deprivation. In line with the re-distribution of sleep and wakefulness, the analysis of wheel-running and drinking activity revealed more rest bouts during the activity phase and a higher percentage of daytime activity in mutant animals. No changes were observed in internal period length and phase-shifting properties of the circadian clock while chi-squared periodogram amplitude was significantly reduced, hinting at a less robust oscillator. These results indicate that PRKG1 might be involved in the stabilization and output strength of the circadian oscillator in mice. Moreover, PRKG1 deficiency results in an aberrant pattern, and consequently a reduced quality, of sleep and wakefulness, possibly due to a decreased wake-promoting output of the circadian system impinging upon sleep

Terrestrial laser scanning for plot-scale forest measurement

Plot-scale measurements have been the foundation for forest surveys and reporting for over 200 years. Through recent integration with airborne and satellite remote sensing, manual measurements of vegetation structure at the plot scale are now the basis for landscape, continental and international mapping of our forest resources. The use of terrestrial laser scanning (TLS) for plot-scale measurement was first demonstrated over a decade ago, with the intimation that these instruments could replace manual measurement methods. This has not yet been the case, despite the unparalleled structural information that TLS can capture. For TLS to reach its full potential, these instruments cannot be viewed as a logical progression of existing plot-based measurement. TLS must be viewed as a disruptive technology that requires a rethink of vegetation surveys and their application across a wide range of disciplines. We review the development of TLS as a plotscale measurement tool, including the evolution of both instrument hardware and key data processing methodologies. We highlight two broad data modelling approaches of gap probability and geometrical modelling and the basic theory that underpins these. Finally, we discuss the future prospects for increasing the utilisation of TLS for plot-scale forest assessment and forest monitoring