A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere

Background and Aims Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Methods Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1–9 years per site from 1998 to 2011. Key Results The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. Conclusions The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.

Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

Altered directed functional connectivity in temporal lobe epilepsy in the absence of interictal spikes: A high density EEG study.

OBJECTIVE In patients with epilepsy, seizure relapse and behavioral impairments can be observed despite the absence of interictal epileptiform discharges (IEDs). Therefore, the characterization of pathologic networks when IEDs are not present could have an important clinical value. Using Granger-causal modeling, we investigated whether directed functional connectivity was altered in electroencephalography (EEG) epochs free of IED in left and right temporal lobe epilepsy (LTLE and RTLE) compared to healthy controls. METHODS Twenty LTLE, 20 RTLE, and 20 healthy controls underwent a resting-state high-density EEG recording. Source activity was obtained for 82 regions of interest (ROIs) using an individual head model and a distributed linear inverse solution. Granger-causal modeling was applied to the source signals of all ROIs. The directed functional connectivity results were compared between groups and correlated with clinical parameters (duration of the disease, age of onset, age, and learning and mood impairments). RESULTS We found that: (1) patients had significantly reduced connectivity from regions concordant with the default-mode network; (2) there was a different network pattern in patients versus controls: the strongest connections arose from the ipsilateral hippocampus in patients and from the posterior cingulate cortex in controls; (3) longer disease duration was associated with lower driving from contralateral and ipsilateral mediolimbic regions in RTLE; (4) aging was associated with a lower driving from regions in or close to the piriform cortex only in patients; and (5) outflow from the anterior cingulate cortex was lower in patients with learning deficits or depression compared to patients without impairments and to controls. SIGNIFICANCE Resting-state network reorganization in the absence of IEDs strengthens the view of chronic and progressive network changes in TLE. These resting-state connectivity alterations could constitute an important biomarker of TLE, and hold promise for using EEG recordings without IEDs for diagnosis or prognosis of this disorder.

M-AARE - Coupling atmospheric, hydrological, hydrodynamic and damage models in the Aare river basin, Switzerland

The triggering mechanism and the temporal evolution of large flood events, especially of worst-case scenarios, are not yet fully understood. Consequently, the cumulative losses of extreme floods are unknown. To study the link between weather conditions, discharges and flood losses it is necessary to couple atmospheric, hydrological, hydrodynamic and damage models. The objective of the M-AARE project is to test the potentials and opportunities of a model chain that relates atmospheric conditions to flood losses or risks. The M-AARE model chain is a set of coupled models consisting of four main components: the precipitation module, the hydrology module, the hydrodynamic module, and the damage module. The models are coupled in a cascading framework with harmonized time-steps. First exploratory applications show that the one way coupling of the WRF-PREVAH-BASEMENT models has been achieved and provides promising new insights for a better understanding of key aspects in flood risk analysis.

Methodology and models in erosion research: discussion and conclusions

This paper summarises the discussions which took place at the Workshop on Methodology in Erosion Research in Zürich, 2010, and aims, where possible, to offer guidance for the development and application of both in vitro and in situ models for erosion research. The prospects for clinical trials are also discussed. All models in erosion research require a number of choices regarding experimental conditions, study design and measurement techniques, and these general aspects are discussed first. Among in vitro models, simple (single- or multiple-exposure) models can be used for screening products regarding their erosive potential, while more elaborate pH cycling models can be used to simulate erosion in vivo. However, in vitro models provide limited information on intra-oral erosion. In situ models allow the effect of an erosive challenge to be evaluated under intra-oral conditions and are currently the method of choice for short-term testing of low-erosive products or preventive therapeutic products. In the future, clinical trials will allow longer-term testing. Possible methodologies for such trials are discussed.

Irradiation with water-filtered infrared A plus visible light improves cutaneous scleroderma lesions in a series of cases

Cutaneous scleroderma is a chronic inflammatory disease of the dermal and subcutaneous connective tissue leading to sclerosis. Sclerosis of the skin can lead to dysmorphism, contractures and restrictions of movement.

LFA-1 expression in a series of colorectal adenocarcinomas

LFA-1 is an adhesion molecule which belongs to the β2-integrin family. Overexpression of LFA-1 in hepatic natural killer cells has been associated with increased apoptosis of neoplastic cells in colorectal cancer (CRC); moreover, studies in CRC have linked LFA-1 overexpression in neoplastic cells with vascular intrusion through adhesion to endothelial cells, thus implying a possible role in creation of metastases.

Differences between RNA and DNA due to RNA editing in temporal lobe epilepsy

To investigate whether alterations in RNA editing (an enzymatic base-specific change to the RNA sequence during primary transcript formation from DNA) of neurotransmitter receptor genes and of transmembrane ion channel genes play a role in human temporal lobe epilepsy (TLE), this exploratory study analyzed 14 known cerebral editing sites in RNA extracted from the brain tissue of 41 patients who underwent surgery for mesial TLE, 23 with hippocampal sclerosis (MTLE+HS). Because intraoperatively sampled RNA cannot be obtained from healthy controls and the best feasible control is identically sampled RNA from patients with a clinically shorter history of epilepsy, the primary aim of the study was to assess the correlation between epilepsy duration and RNA editing in the homogenous group of MTLE+HS. At the functionally relevant I/V site of the voltage-gated potassium channel Kv1.1, an inverse correlation of RNA editing was found with epilepsy duration (r=-0.52, p=0.01) but not with patient age at surgery, suggesting a specific association with either the epileptic process itself or its antiepileptic medication history. No significant correlations were found between RNA editing and clinical parameters at other sites within glutamate receptor or serotonin 2C receptor gene transcripts. An "all-or-none" (≥95% or ≤5%) editing pattern at most or all sites was discovered in 2 patients. As a secondary part of the study, RNA editing was also analyzed as in the previous literature where up to now, few single editing sites were compared with differently obtained RNA from inhomogenous patient groups and autopsies, and by measuring editing changes in our mouse model. The present screening study is first to identify an editing site correlating with a clinical parameter, and to also provide an estimate of the possible effect size at other sites, which is a prerequisite for power analysis needed in planning future studies.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Sleep-wake habits and disorders in a series of 100 adult epilepsy patients--a prospective study

The aim of the study was to assess sleep-wake habits and disorders and excessive daytime sleepiness (EDS) in an unselected outpatient epilepsy population. Sleep-wake habits and presence of sleep disorders were assessed by means of a clinical interview and a standard questionnaire in 100 consecutive patients with epilepsy and 90 controls. The questionnaire includes three validated instruments: the Epworth Sleepiness Scale (ESS) for EDS, SA-SDQ for sleep apnea (SA), and the Ullanlinna Narcolepsy Scale (UNS) for narcolepsy. Sleep complaints were reported by 30% of epilepsy patients compared to 10% of controls (p=0.001). The average total sleep time was similar in both groups. Insufficient sleep times were suspected in 24% of patients and 33% of controls. Sleep maintenance insomnia was more frequent in epilepsy patients (52% vs. 38%, p=0.06), whereas nightmares (6% vs. 16%, p=0.04) and bruxism (10% vs. 19%, p=0.07) were more frequent in controls. Sleep onset insomnia (34% vs. 28%), EDS (ESS >or=10, 19% vs. 14%), SA (9% vs. 3%), restless legs symptoms (RL-symptoms, 18% vs. 12%) and most parasomnias were similarly frequent in both groups. In a stepwise logistic regression model loud snoring and RL-symptoms were found to be the only independent predictors of EDS in epilepsy patients. In conclusion, sleep-wake habits and the frequency of most sleep disorders are similar in non-selected epilepsy patients as compared to controls. In epilepsy patients, EDS was predicted by a history of loud snoring and RL-symptoms but not by SA or epilepsy-related variables (including type of epilepsy, frequency of seizures, and number of antiepileptic drugs).