Psychogenic Elaboration of Simple Partial Seizures

Seizures that cause loss of consciousness (LOC) can be classified as epileptic or nonepileptic based on evaluation of ictal semiology and analysis of changes in EEG events, recorded with continuous scalp EEG and video monitoring. We report 3 patients who had hippocampal electrographic seizures documented with intracranial EEG recording with no accompanying scalp EEG change immediately preceding psychogenic unresponsiveness. Each patient also had complex partial seizures (CPS) originating in the hippocampus. Some individuals can have complex interactions of epileptic and nonepileptic seizures.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66184/1/j.1528-1157.1995.tb00471.x.pd

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

Neoadjuvant chemoradiotherapy with or without panitumumab in patients with wild-type KRAS, locally advanced rectal cancer (LARC): a randomized, multicenter, phase II trial SAKK 41/07

Background We conducted a randomized, phase II, multicenter study to evaluate the anti-epidermal growth factor receptor (EGFR) mAb panitumumab (P) in combination with chemoradiotherapy (CRT) with standard-dose capecitabine as neoadjuvant treatment for wild-type KRAS locally advanced rectal cancer (LARC). Patients and methods Patients with wild-type KRAS, T3-4 and/or N+ LARC were randomly assigned to receive CRT with or without P (6 mg/kg). The primary end-point was pathological near-complete or complete tumor response (pNC/CR), defined as grade 3 (pNCR) or 4 (pCR) histological regression by Dworak classification (DC). Results Forty of 68 patients were randomly assigned to P + CRT and 28 to CRT. pNC/CR was achieved in 21 patients (53%) treated with P + CRT [95% confidence interval (CI) 36%-69%] versus 9 patients (32%) treated with CRT alone (95% CI: 16%-52%). pCR was achieved in 4 (10%) and 5 (18%) patients, and pNCR in 17 (43%) and 4 (14%) patients. In immunohistochemical analysis, most DC 3 cells were not apoptotic. The most common grade ≥3 toxic effects in the P + CRT/CRT arm were diarrhea (10%/6%) and anastomotic leakage (15%/4%). Conclusions The addition of panitumumab to neoadjuvant CRT in patients with KRAS wild-type LARC resulted in a high pNC/CR rate, mostly grade 3 DC. The results of both treatment arms exceeded prespecified thresholds. The addition of panitumumab increased toxicit

Variable Incidence of Spiroplasma Infections in Natural Populations of Drosophila Species

Spiroplasma is widespread as a heritable bacterial symbiont in insects and some other invertebrates, in which it sometimes acts as a male-killer and causes female-biased sex ratios in hosts. Besides Wolbachia, it is the only heritable bacterium known from Drosophila, having been found in 16 of over 200 Drosophila species screened, based on samples of one or few individuals per species. To assess the extent to which Spiroplasma infection varies within and among species of Drosophila, intensive sampling consisting of 50–281 individuals per species was conducted for natural populations of 19 Drosophila species. Infection rates varied among species and among populations of the same species, and 12 of 19 species tested negative for all individuals. Spiroplasma infection never was fixed, and the highest infection rates were 60% in certain populations of D. hydei and 85% in certain populations of D. mojavensis. In infected species, infection rates were similar for males and females, indicating that these Spiroplasma infections do not confer a strong male-killing effect. These findings suggest that Spiroplasma has other effects on hosts that allow it to persist, and that environmental or host variation affects transmission or persistence leading to differences among populations in infection frequencies

Natural disturbance impacts on trade-offs and co-benefits of forest biodiversity and carbon

With accelerating environmental change, understanding forest disturbance impacts on trade-offs between biodiversity and carbon dynamics is of high socio-economic importance. Most studies, however, have assessed immediate or short-term effects of disturbance, while long-term impacts remain poorly understood. Using a tree-ring-based approach, we analysed the effect of 250 years of disturbances on present-day biodiversity indicators and carbon dynamics in primary forests. Disturbance legacies spanning centuries shaped contemporary forest co-benefits and trade-offs, with contrasting, local-scale effects. Disturbances enhanced carbon sequestration, reaching maximum rates within a comparatively narrow post-disturbance window (up to 50 years). Concurrently, disturbance diminished aboveground carbon storage, which gradually returned to peak levels over centuries. Temporal patterns in biodiversity potential were bimodal; the first maximum coincided with the short-term post-disturbance carbon sequestration peak, and the second occurred during periods of maximum carbon storage in complex old-growth forest. Despite fluctuating local-scale trade-offs, forest biodiversity and carbon storage remained stable across the broader study region, and our data support a positive relationship between carbon stocks and biodiversity potential. These findings underscore the interdependencies of forest processes, and highlight the necessity of large-scale conservation programmes to effectively promote both biodiversity and long-term carbon storage, particularly given the accelerating global biodiversity and climate crises

Protein Sequence Alignment Analysis by Local Covariation: Coevolution Statistics Detect Benchmark Alignment Errors

The use of sequence alignments to understand protein families is ubiquitous in molecular biology. High quality alignments are difficult to build and protein alignment remains one of the largest open problems in computational biology. Misalignments can lead to inferential errors about protein structure, folding, function, phylogeny, and residue importance. Identifying alignment errors is difficult because alignments are built and validated on the same primary criteria: sequence conservation. Local covariation identifies systematic misalignments and is independent of conservation. We demonstrate an alignment curation tool, LoCo, that integrates local covariation scores with the Jalview alignment editor. Using LoCo, we illustrate how local covariation is capable of identifying alignment errors due to the reduction of positional independence in the region of misalignment. We highlight three alignments from the benchmark database, BAliBASE 3, that contain regions of high local covariation, and investigate the causes to illustrate these types of scenarios. Two alignments contain sequential and structural shifts that cause elevated local covariation. Realignment of these misaligned segments reduces local covariation; these alternative alignments are supported with structural evidence. We also show that local covariation identifies active site residues in a validated alignment of paralogous structures. Loco is available at https://sourceforge.net/projects/locoprotein/files

Amazonia as a carbon source linked to deforestation and climate change

Amazonia hosts the Earth's largest tropical forests and has been shown to be an important carbon sink over recent decades1-3. This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change1-3. Here we investigate Amazonia's carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 20184. We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends5-9. We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia1,10.</p

Amazonia as a carbon source linked to deforestation and climate change

Amazonia hosts the Earth’s largest tropical forests and has been shown to be an important carbon sink over recent decades1,2,3. This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change1,2,3. Here we investigate Amazonia’s carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 20184. We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends5,6,7,8,9. We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia1,10

Quantifying Canopy Tree Loss and Gap Recovery in Tropical Forests under Low-Intensity Logging Using VHR Satellite Imagery and Airborne LiDAR

Logging, including selective and illegal activities, is widespread, affecting the carbon cycle and the biodiversity of tropical forests. However, automated approaches using very high resolution (VHR) satellite data (≤1 m spatial resolution) to accurately track these small-scale human disturbances over large and remote areas are not readily available. The main constraint for performing this type of analysis is the lack of spatially accurate tree-scale validation data. In this study, we assessed the potential of VHR satellite imagery to detect canopy tree loss related to selective logging in closed-canopy tropical forests. To do this, we compared the tree loss detection capability of WorldView-2 and GeoEye-1 satellites with airborne LiDAR, which acquired pre- and post-logging data at the Jamari National Forest in the Brazilian Amazon. We found that logging drove changes in canopy height ranging from −5.6 to −42.2 m, with a mean reduction of −23.5 m. A simple LiDAR height difference threshold of −10 m was enough to map 97% of the logged trees. Compared to LiDAR, tree losses can be detected using VHR satellite imagery and a random forest (RF) model with an average precision of 64%, while mapping 60% of the total tree loss. Tree losses associated with large gap openings or tall trees were more successfully detected. In general, the most important remote sensing metrics for the RF model were standard deviation statistics, especially those extracted from the reflectance of the visible bands (R, G, B), and the shadow fraction. While most small canopy gaps closed within ~2 years, larger gaps could still be observed over a longer time. Nevertheless, the use of annual imagery is advised to reach acceptable detectability. Our study shows that VHR satellite imagery has the potential for monitoring the logging in tropical forests and detecting hotspots of natural disturbance with a low cost at the regional scale

Correlated Mutations: A Hallmark of Phenotypic Amino Acid Substitutions

Point mutations resulting in the substitution of a single amino acid can cause severe functional consequences, but can also be completely harmless. Understanding what determines the phenotypical impact is important both for planning targeted mutation experiments in the laboratory and for analyzing naturally occurring mutations found in patients. Common wisdom suggests using the extent of evolutionary conservation of a residue or a sequence motif as an indicator of its functional importance and thus vulnerability in case of mutation. In this work, we put forward the hypothesis that in addition to conservation, co-evolution of residues in a protein influences the likelihood of a residue to be functionally important and thus associated with disease. While the basic idea of a relation between co-evolution and functional sites has been explored before, we have conducted the first systematic and comprehensive analysis of point mutations causing disease in humans with respect to correlated mutations. We included 14,211 distinct positions with known disease-causing point mutations in 1,153 human proteins in our analysis. Our data show that (1) correlated positions are significantly more likely to be disease-associated than expected by chance, and that (2) this signal cannot be explained by conservation patterns of individual sequence positions. Although correlated residues have primarily been used to predict contact sites, our data are in agreement with previous observations that (3) many such correlations do not relate to physical contacts between amino acid residues. Access to our analysis results are provided at http://webclu.bio.wzw.tum.de/~pagel/supplements/correlated-positions/