Refine
Has Fulltext
- yes (4)
Is part of the Bibliography
- yes (4)
Document Type
- Journal article (4)
Language
- English (4)
Keywords
- Adult (1)
- Case-Control Studies (1)
- Central Asia (1)
- Cognitive Therapy (1)
- DNA (1)
- DNA Methylation (1)
- Epigenesis (1)
- Female (1)
- Genetic (1)
- Humans (1)
- LiDAR (1)
- Monoamine Oxidase/genetics (1)
- Panic Disorder/genetics (1)
- Panic Disorder/therapy (1)
- REMO-iMOVE (1)
- Sequence Analysis (1)
- arthropods (1)
- attention‐deficit (1)
- bats (1)
- biodiversity (1)
- birds (1)
- brain asymmetry (1)
- brain laterality (1)
- elevation (1)
- evaluation (1)
- hyperactivity disorder (1)
- interactive vegetation (1)
- large‐scale data (1)
- partial least square regression (1)
- predictive modeling (1)
- regional climate model (RCM) (1)
- species richness (1)
- structural MRI (1)
Epigenetic signatures such as methylation of the monoamine oxidase A (MAOA) gene have been found to be altered in panic disorder (PD). Hypothesizing temporal plasticity of epigenetic processes as a mechanism of successful fear extinction, the present psychotherapy-epigenetic study for we believe the first time investigated MAOA methylation changes during the course of exposure-based cognitive behavioral therapy (CBT) in PD. MAOA methylation was compared between N=28 female Caucasian PD patients (discovery sample) and N=28 age- and sex-matched healthy controls via direct sequencing of sodium bisulfite-treated DNA extracted from blood cells. MAOA methylation was furthermore analyzed at baseline (T0) and after a 6-week CBT (T1) in the discovery sample parallelized by a waiting time in healthy controls, as well as in an independent sample of female PD patients (N=20). Patients exhibited lower MAOA methylation than healthy controls (P<0.001), and baseline PD severity correlated negatively with MAOA methylation (P=0.01). In the discovery sample, MAOA methylation increased up to the level of healthy controls along with CBT response (number of panic attacks; T0-T1: +3.37±2.17%), while non-responders further decreased in methylation (-2.00±1.28%; P=0.001). In the replication sample, increases in MAOA methylation correlated with agoraphobic symptom reduction after CBT (P=0.02-0.03). The present results support previous evidence for MAOA hypomethylation as a PD risk marker and suggest reversibility of MAOA hypomethylation as a potential epigenetic correlate of response to CBT. The emerging notion of epigenetic signatures as a mechanism of action of psychotherapeutic interventions may promote epigenetic patterns as biomarkers of lasting extinction effects.
Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia
(2022)
The current study evaluates the regional climate model REMO (v2015) and its new version REMO-iMOVE, including interactive vegetation and plant functional types (PFTs), over two Central Asian domains for the period of 2000–2015 at two different horizontal resolutions (0.44° and 0.11°). Various statistical metrices along with mean bias patterns for precipitation, temperature, and leaf area index have been used for the model evaluation. A better representation of the spatial pattern of precipitation is found at 0.11° resolution over most of Central Asia. Regarding the mean temperature, both model versions show a high level of agreement with the validation data, especially at the higher resolution. This also reduces the biases in maximum and minimum temperature. Generally, REMO-iMOVE shows an improvement regarding the temperature bias but produces a larger precipitation bias compared to the REMO conventional version with interannually static vegetation. Since the coupled version is capable to simulate the mean climate of Central Asia like its parent version, both can be used for impact studies and future projections. However, regarding the new vegetation scheme and its spatiotemporal representation exemplified by the leaf area index, REMO-iMOVE shows a clear advantage over REMO. This better simulation is caused by the implementation of more realistic and interactive vegetation and related atmospheric processes which consequently add value to the regional climate model.
Analysis of structural brain asymmetries in attention‐deficit/hyperactivity disorder in 39 datasets
(2021)
Objective
Some studies have suggested alterations of structural brain asymmetry in attention‐deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left‐right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.
Methods
We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.
Results
There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from −0.18 to 0.18) and would not survive study‐wide correction for multiple testing.
Conclusion
Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
The monitoring of species and functional diversity is of increasing relevance for the development of strategies for the conservation and management of biodiversity. Therefore, reliable estimates of the performance of monitoring techniques across taxa become important. Using a unique dataset, this study investigates the potential of airborne LiDAR-derived variables characterizing vegetation structure as predictors for animal species richness at the southern slopes of Mount Kilimanjaro. To disentangle the structural LiDAR information from co-factors related to elevational vegetation zones, LiDAR-based models were compared to the predictive power of elevation models. 17 taxa and 4 feeding guilds were modeled and the standardized study design allowed for a comparison across the assemblages. Results show that most taxa (14) and feeding guilds (3) can be predicted best by elevation with normalized RMSE values but only for three of those taxa and two of those feeding guilds the difference to other models is significant. Generally, modeling performances between different models vary only slightly for each assemblage. For the remaining, structural information at most showed little additional contribution to the performance. In summary, LiDAR observations can be used for animal species prediction. However, the effort and cost of aerial surveys are not always in proportion with the prediction quality, especially when the species distribution follows zonal patterns, and elevation information yields similar results.