Diffusion Retardation by Binding of Tobramycin in an Alginate Biofilm Model

Microbial cells embedded in a self-produced extracellular biofilm matrix cause chronic infections, e. g. by Pseudomonas aeruginosa in the lungs of cystic fibrosis patients. The antibiotic killing of bacteria in biofilms is generally known to be reduced by 100–1000 times relative to planktonic bacteria. This makes such infections difficult to treat. We have therefore proposed that biofilms can be regarded as an independent compartment with distinct pharmacokinetics. To elucidate this pharmacokinetics we have measured the penetration of the tobramycin into seaweed alginate beads which serve as a model of the extracellular polysaccharide matrix in P. aeruginosa biofilm. We find that, rather than a normal first order saturation curve, the concentration of tobramycin in the alginate beads follows a power-law as a function of the external concentration. Further, the tobramycin is observed to be uniformly distributed throughout the volume of the alginate bead. The power-law appears to be a consequence of binding to a multitude of different binding sites. In a diffusion model these results are shown to produce pronounced retardation of the penetration of tobramycin into the biofilm. This filtering of the free tobramycin concentration inside biofilm beads is expected to aid in augmenting the survival probability of bacteria residing in the biofilm.     

Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals

Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain–Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classification of multi-channel fNIRS signals using support-vector machines (SVM), so as to determine its feasibility as an online neurofeedback system. Towards this goal, we used left versus right hand movement execution and movement imagery as study paradigms in a series of experiments. In the first two experiments, activations in the motor cortex during movement execution and movement imagery were used to develop subject-dependent models that obtained high classification accuracies thereby indicating the robustness of our classification method. In the third experiment, a generalized classifier-model was developed from the first two experimental data, which was then applied for subject-independent neurofeedback training. Application of this method in new participants showed mean classification accuracy of 63% for movement imagery tasks and 80% for movement execution tasks. These results, and their corresponding offline analysis reported in this study demonstrate that SVM based real-time subject-independent classification of fNIRS signals is feasible. This method has important applications in the field of hemodynamic BCIs, and neuro-rehabilitation where patients can be trained to learn spatio-temporal patterns of healthy brain activity.     

Target Fortification of Breast Milk: Predicting the Final Osmolality of the Feeds

For preterm infants, it is common practice to add human milk fortifiers to native breast milk to enhance protein and calorie supply because the growth rates and nutritional requirements of preterm infants are considerably higher than those of term infants. However, macronutrient intake may still be inadequate because the composition of native breast milk has individual inter- and intra-sample variation. Target fortification (TFO) of breast milk is a new nutritional regime aiming to reduce such variations by individually measuring and adding deficient macronutrients. Added TFO components contribute to the final osmolality of milk feeds. It is important to predict the final osmolality of TFO breast milk to ensure current osmolality recommendations are followed to minimize feeding intolerance and necrotizing enterocolitis. This study aims to develop and validate equations to predict the osmolality of TFO milk batches. To establish prediction models, the osmolalities of either native or supplemented breast milk with known amounts of fat, protein, and carbohydrates were analyzed. To validate prediction models, the osmolalities of each macronutrient and combinations of macronutrients were measured in an independent sample set. Additionally, osmolality was measured in TFO milk samples obtained from a previous clinical study and compared with predicted osmolality using the prediction equations. Following the addition of 1 g of carbohydrates (glucose polymer), 1 g of hydrolyzed protein, or 1 g of whey protein per 100 mL breast milk, the average increase in osmolality was 20, 38, and 4 mOsm/kg respectively. Adding fat decreased osmolality only marginally due to dilution effect. Measured and predicted osmolality of combinations of macronutrients as well as single macronutrient (R² = 0.93) were highly correlated. Using clinical data (n = 696), the average difference between the measured and predicted osmolality was 3 ± 11 mOsm/kg and was not statistically significant. In conclusion, the prediction model can be utilized to estimate osmolality values after fortification.     

Cortical Thickness,Surface Area and Subcortical Volume Differentially Contribute to Cognitive Heterogeneity in Parkinson’s Disease

Parkinson’s disease (PD) is often associated with cognitive deficits, although their severity varies considerably between patients. Recently, we used voxel-based morphometry (VBM) to show that individual differences in gray matter (GM) volume relate to cognitive heterogeneity in PD. VBM does, however, not differentiate between cortical thickness (CTh) and surface area (SA), which might be independently affected in PD. We therefore re-analyzed our cohort using the surface-based method FreeSurfer, and investigated (i) CTh, SA, and (sub)cortical GM volume differences between 93 PD patients and 45 matched controls, and (ii) the relation between these structural measures and cognitive performance on six neuropsychological tasks within the PD group. We found cortical thinning in PD patients in the left pericalcarine gyrus, extending to cuneus, precuneus and lingual areas and left inferior parietal cortex, bilateral rostral middle frontal cortex, and right cuneus, and increased cortical surface area in the left pars triangularis. Within the PD group, we found negative correlations between (i) CTh of occipital areas and performance on a verbal memory task, (ii) SA and volume of the frontal cortex and visuospatial memory performance, and, (iii) volume of the right thalamus and scores on two verbal fluency tasks. Our primary findings illustrate that i) CTh and SA are differentially affected in PD, and ii) VBM and FreeSurfer yield non-overlapping results in an identical dataset. We argue that this discrepancy is due to technical differences and the subtlety of the PD-related structural changes.     

Leaf vein fraction influences the Péclet effect and 18O enrichment in leaf water

The process of evaporation results in the fractionation of water isotopes such that the lighter ¹⁶O isotope preferentially escapes the gas phase leaving the heavier ¹⁸O isotope to accumulate at the sites of evaporation. This applies to transpiration from a leaf with the degree of fractionation dependent on a number of environmental and physiological factors that are well understood. Nevertheless, the ¹⁸O enrichment of bulk leaf water is often less than that predicted for the sites of evaporation. The advection of less enriched water in the transpiration stream has been suggested to limit the back diffusion of enriched evaporative site water (Péclet effect); however, evidence for this effect has been varied. In sampling across a range of species with different vein densities and saturated water contents, we demonstrate the importance of accounting for the relative ‘pool’ sizes of the vascular and mesophyll water for the interpretation of a Péclet effect. Further, we provide strong evidence for a Péclet signal within the xylem that if unaccounted for can lead to confounding of the estimated enrichment within the mesophyll water. This has important implications for understanding variation in the effective path length of the mesophyll and hence potentially the δ¹⁸O of organic matter.     

Muskoxen Modify Plant Abundance,Phenology, and Nitrogen Dynamics in a High Arctic Fen

Ecosystems - Herbivores are key drivers of vegetation dynamics in most ecosystems. However, the effect of high arctic herbivores on vegetation dynamics throughout a growing season is not well...     

Evidence for rapid evolution in a grassland biodiversity experiment

In long‐term grassland experiments, positive biodiversity effects on plant productivity commonly increase with time. Subsequent glasshouse experiments showed that these strengthened positive biodiversity effects persist not only in the local environment but also when plants are transferred into a common environment. Thus, we hypothesized that community diversity had acted as a selective agent, resulting in the emergence of plant monoculture and mixture types with differing genetic composition. To test our hypothesis, we grew offspring from plants that were grown for eleven years in monoculture or mixture environments in a biodiversity experiment (Jena Experiment) under controlled glasshouse conditions in monocultures or two‐species mixtures. We used epiGBS, a genotyping‐by‐sequencing approach combined with bisulphite conversion, to provide integrative genetic and epigenetic (i.e., DNA methylation) data. We observed significant divergence in genetic and DNA methylation data according to selection history in three out of five perennial grassland species, namely Galium mollugo, Prunella vulgaris and Veronica chamaedrys, with DNA methylation differences mostly reflecting the genetic differences. In addition, current diversity levels in the glasshouse had weak effects on epigenetic variation. However, given the limited genome coverage of the reference‐free bisulphite method epiGBS, it remains unclear how much of the differences in DNA methylation was independent of underlying genetic differences. Our results thus suggest that selection of genetic variants, and possibly epigenetic variants, caused the rapid emergence of monoculture and mixture types within plant species in the Jena Experiment.     

The Preprotein Binding Domain of SecA Displays Intrinsic Rotational Dynamics

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