Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness.

The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.

Plant functional and phylogenetic turnover correlate with climate and land use in the Western Swiss Alps

Understanding the relative importance of historical and environmental processes in the structure and composition of communities is one of the longest quests in ecological research. Increasingly, researchers are relying on the functional and phylogenetic β-diversity of natural communities to provide concise explanations on the mechanistic basis of community assembly and the drivers of trait variation among species. The present study investigated how plant functional and phylogenetic β-diversity change along key environmental and spatial gradients in the Western Swiss Alps. Methods Using the quadratic diversity measure based on six functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height (H), leaf carbon content (C), leaf nitrogen content (N), and leaf carbon to nitrogen content (C/N) alongside a species-resolved phylogenetic tree, we relate variations in climate, spatial geographic, land use and soil gradients to plant functional and phylogenetic turnover in mountain communities of the Western Swiss Alps. Important findings Our study highlights two main points. First, climate and land use factors play an important role in mountain plant community turnover. Second, the overlap between plant functional and phylogenetic turnover along these gradients correlates with the low phylogenetic signal in traits, suggesting that in mountain landscapes, trait lability is likely an important factor in driving plant community assembly. Overall, we demonstrate the importance of climate and land use factors in plant functional and phylogenetic community turnover, and provide valuable complementary insights into understanding patterns of β-diversity along several ecological gradients.

Functional glycosylation of dystroglycan is crucial for thymocyte development in the mouse.

BACKGROUND: Alpha-dystroglycan (alpha-DG) is a cell surface receptor providing a molecular link between the extracellular matrix (ECM) and the actin-based cytoskeleton. During its biosynthesis, alpha-DG undergoes specific and unusual O-glycosylation crucial for its function as a high-affinity cellular receptor for ECM proteins. METHODOLOGY/PRINCIPAL FINDINGS: We report that expression of functionally glycosylated alpha-DG during thymic development is tightly regulated in developing T cells and largely confined to CD4(-)CD8(-) double negative (DN) thymocytes. Ablation of DG in T cells had no effect on proliferation, migration or effector function but did reduce the size of the thymus due to a significant loss in absolute numbers of thymocytes. While numbers of DN thymocytes appeared normal, a marked reduction in CD4(+)CD8(+) double positive (DP) thymocytes occurred. In the periphery mature naïve T cells deficient in DG showed both normal proliferation in response to allogeneic cells and normal migration, effector and memory T cell function when tested in acute infection of mice with either lymphocytic choriomeningitis virus (LCMV) or influenza virus. CONCLUSIONS/SIGNIFICANCE: Our study demonstrates that DG function is modulated by glycosylation during T cell development in vivo and that DG is essential for normal development and differentiation of T cells.

The malaria circumsporozoite protein has two functional domains, each with distinct roles as sporozoites journey from mosquito to mammalian host.

Plasmodium sporozoites make a remarkable journey from the mosquito midgut to the mammalian liver. The sporozoite's major surface protein, circumsporozoite protein (CSP), is a multifunctional protein required for sporozoite development and likely mediates several steps of this journey. In this study, we show that CSP has two conformational states, an adhesive conformation in which the C-terminal cell-adhesive domain is exposed and a nonadhesive conformation in which the N terminus masks this domain. We demonstrate that the cell-adhesive domain functions in sporozoite development and hepatocyte invasion. Between these two events, the sporozoite must travel from the mosquito midgut to the mammalian liver, and N-terminal masking of the cell-adhesive domain maintains the sporozoite in a migratory state. In the mammalian host, proteolytic cleavage of CSP regulates the switch to an adhesive conformation, and the highly conserved region I plays a critical role in this process. If the CSP domain architecture is altered such that the cell-adhesive domain is constitutively exposed, the majority of sporozoites do not reach their target organs, and in the mammalian host, they initiate a blood stage infection directly from the inoculation site. These data provide structure-function information relevant to malaria vaccine development.

Validation of a clinical prediction score for ruling out coronary heart disease in primary care patients with chest pain.

Background: A patient's chest pain raises concern for the possibility of coronary heart disease (CHD). An easy to use clinical prediction rule has been derived from the TOPIC study in Lausanne. Our objective is to validate this clinical score for ruling out CHD in primary care patients with chest pain. Methods: This secondary analysis used data collected from a oneyear follow-up cohort study attending 76 GPs in Germany. Patients attending their GP with chest pain were questioned on their age, gender, duration of chest pain (1-60 min), sternal pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the curve (ROC), sensitivity and specificity of the Lausanne CHD score were calculated for patients with full data. Results: 1190 patients were included. Full data was available for 509 patients (42.8%). Missing data was not related to having CHD (p = 0.397) or having a cardiovascular risk factor (p = 0.275). 76 (14.9%) were diagnosed with a CHD. Prevalence of CHD were respectively of 68/344 (19.8%), 2/62 (3.2%), 6/103 (5.8%) in the high, intermediate and low risk category. ROC was of 72.9 (CI95% 66.8; 78.9). Ruling out patients with low risk has a sensitivity of 92.1% (CI95% 83.0; 96.7) and a specificity of 22.4% (CI95% 18.6%; 26.7%). Conclusion: The Lausanne CHD score shows reasonably good sensitivity and can be used to rule out coronary events in patients with chest pain. Patients at risk of CHD for other rarer reasons should nevertheless also be investigated.

Ruling out coronary artery disease in primary care: development and validation of a simple prediction rule.

BACKGROUND: Chest pain can be caused by various conditions, with life-threatening cardiac disease being of greatest concern. Prediction scores to rule out coronary artery disease have been developed for use in emergency settings. We developed and validated a simple prediction rule for use in primary care. METHODS: We conducted a cross-sectional diagnostic study in 74 primary care practices in Germany. Primary care physicians recruited all consecutive patients who presented with chest pain (n = 1249) and recorded symptoms and findings for each patient (derivation cohort). An independent expert panel reviewed follow-up data obtained at six weeks and six months on symptoms, investigations, hospital admissions and medications to determine the presence or absence of coronary artery disease. Adjusted odds ratios of relevant variables were used to develop a prediction rule. We calculated measures of diagnostic accuracy for different cut-off values for the prediction scores using data derived from another prospective primary care study (validation cohort). RESULTS: The prediction rule contained five determinants (age/sex, known vascular disease, patient assumes pain is of cardiac origin, pain is worse during exercise, and pain is not reproducible by palpation), with the score ranging from 0 to 5 points. The area under the curve (receiver operating characteristic curve) was 0.87 (95% confidence interval [CI] 0.83-0.91) for the derivation cohort and 0.90 (95% CI 0.87-0.93) for the validation cohort. The best overall discrimination was with a cut-off value of 3 (positive result 3-5 points; negative result <or= 2 points), which had a sensitivity of 87.1% (95% CI 79.9%-94.2%) and a specificity of 80.8% (77.6%-83.9%). INTERPRETATION: The prediction rule for coronary artery disease in primary care proved to be robust in the validation cohort. It can help to rule out coronary artery disease in patients presenting with chest pain in primary care.

Reproductive allocation and size constraints in the cladoceran Simocephalus vetulus (Müller)

Like many organisms, the cladoceran Simocephalus vetulus (Müller) continues to grow when reproducing, whereas the optimal strategy is to stop growing at maturity, and to invest all available production into reproduction thereafter. It has been proposed that a size constraint is responsible for the observed strategy (Perrin, Ruedi & Saiah, 1987), by preventing organisms from investing more than a given amount of energy into reproduction. This hypothesis is developed here and the two folowing prediction are derived: (1) the onset of reproduction should be independent of age and (2) the reproductive investement should be size-specific, thus independent of the productin rate. Both predictions are tested by rearing a clone of S.vetulus in a gradient of productivity. The results support the first prediction, but not the second one, so that the size-constraint hypothesis is disproved.

Activated B cells express functional Fas ligand.

Fas ligand (FasL, Apo-1L) is a member of the tumor necrosis factor protein family and binding to its receptor (Fas, Apo-1, CD95) triggers cell death through apoptosis. Ligand expression is restricted to cells with known cytolytic activity and found on hematopoietic cells of the T cell and natural killer lineage. Here we provide evidence that B lymphocytes can express FasL. Flow cytometric analysis revealed that FasL is expressed on the surface of B cells upon stimulation with either lipopolysaccharide or phorbol 12-myristate 13-acetate/ionomycin. FasL expression on activated B cells was confirmed by western blot and reverse transcriptase polymerase chain reaction analysis. FasL on B cells is functional since lipopolysaccharide-activated B lymphocytes derived from wild type, but not from gld mutant mice, were able to kill Fas-sensitive target cells. Our data suggest that the Fas system may contribute to the control of B cell homeostasis.

Persistent hyperglycemia at 24-48 h in acute hyperglycemic stroke patients is not associated with a worse functional outcome.

BACKGROUND: Recently, it was shown that the relation between admission glucose and functional outcome after ischemic stroke is described by a J-shaped curve, with a glucose range of 3.7-7.3 mmol/l associated with a favorable outcome. We tested the hypothesis that persistence of hyperglycemia above this threshold at 24-48 h after stroke onset impairs 3-month functional outcome. METHODS: We analyzed all patients with glucose >7.3 mmol/l on admission from the Acute STroke Registry and Analysis of Lausanne (ASTRAL). Patients were divided into two groups according to their subacute glucose level at 24-48 h after last well-being time (group 1: ≤7.3 mmol/l, group 2: >7.3 mmol/l). A favorable functional outcome was defined as a modified Rankin Score (mRS) ≤2 at 3 months. A multiple logistic regression analysis of multiple demographic, clinical, laboratory and neuroimaging covariates was performed to assess predictors of an unfavorable outcome. RESULTS: A total of 1,984 patients with ischemic stroke were admitted between January 1, 2003 and October 20, 2009, within 24 h after last well-being time. In the 421 patients (21.2%) with admission glucose >7.3 mmol/l, the proportion of patients with a favorable outcome was not statistically significantly different between the two groups (59.2 vs. 48.7%, respectively). In multiple logistic regression analysis, unfavorable outcome was significantly associated with age (odds ratio, OR: 1.06, 95% confidence interval, 95% CI: 1.03-1.08 for every 10-year increase), National Institute of Health Stroke Score, NIHSS score, on admission (OR: 1.16, 95% CI: 1.11-1.21), prehospital mRS (OR: 12.63, 95% CI: 2.61-61.10 for patients with score >0), antidiabetic drug usage (OR: 0.36, 95% CI: 0.15-0.86) and glucose on admission (OR: 1.16, 95% CI: 1.02-1.31 for every 1 mmol/l increase). No association was found between persistent hyperglycemia at 24-28 h and outcome in either diabetics or nondiabetics. CONCLUSIONS: In ischemic stroke patients with acute hyperglycemia, persistent hyperglycemia (>7.3 mmol/l) at 24-48 h after stroke onset is not associated with a worse functional outcome at 3 months whether the patient was previously diabetic or not.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Comparing the artificial neural network with parcial least squares for prediction of soil organic carbon and pH at different moisture content levels using visible and near-infrared spectroscopy

Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.