The impact of climate change on lakes in the Netherlands: a review

Climate change will alter freshwater ecosystems but specific effects will vary among regions and the type of water body. Here, we give an integrative review of the observed and predicted impacts of climate change on shallow lakes in the Netherlands and put these impacts in an international perspective. Most of these lakes are man-made and have preset water levels and poorly developed littoral zones. Relevant climatic factors for these ecosystems are temperature, ice-cover and wind. Secondary factors affected by climate include nutrient loading, residence time and water levels. We reviewed the relevant literature in order to assess the impact of climate change on these lakes. We focussed on six management objectives as bioindicators for the functioning of these ecosystems: target species, nuisance species, invading species, transparency, carrying capacity and biodiversity. We conclude that climate change will likely (i) reduce the numbers of several target species of birds; (ii) favour and stabilize cyanobacterial dominance in phytoplankton communities; (iii) cause more serious incidents of botulism among waterfowl and enhance the spreading of mosquito borne diseases; (iv) benefit invaders originating from the Ponto-Caspian region; (v) stabilize turbid, phytoplankton-dominated systems, thus counteracting restoration measures; (vi) destabilize macrophyte-dominated clear-water lakes; (vii) increase the carrying capacity of primary producers, especially phytoplankton, thus mimicking eutrophication; (viii) affect higher trophic levels as a result of enhanced primary production; (ix) have a negative impact on biodiversity which is linked to the clear water state; (x) affect biodiversity by changing the disturbance regime. Water managers can counteract these developments by reduction of nutrient loading, development of the littoral zone, compartmentalization of lakes and fisheries management.     

Pneumococcal immune evasion: ZmpC inhibits neutrophil influx

Neutrophil recruitment is essential in clearing pneumococcal infections. The first step in neutrophil extravasation involves the interaction between P‐selectin on activated endothelium and P‐Selectin Glycoprotein 1 (PSGL‐1) on neutrophils. Here, we identify pneumococcal Zinc metalloproteinase C as a potent inhibitor of PSGL‐1. ZmpC degrades the N‐terminal domain of PSGL‐1, thereby disrupting the initial rolling of neutrophils on activated human umbilical vein endothelial cells. Furthermore, mice infected with wild‐type strain in the model of pneumococcal pneumonia showed lower lungs neutrophil infiltration compare to animals infected with ZmpC mutant. In addition, we confirmed the association of zmpC with serotype 8 and 11A and found it to be associated with serotype 33F as well. In conclusion, wereport PSGL‐1 as a novel target for ZmpC and show that ZmpC inhibits neutrophil extravasation during pneumococcal pneumonia.     

The flying buttress construct for posterior spinopelvic fixation: a technical note

Background

School screening for adolescent idiopathic scoliosis (AIS) is discussed. The aim of the present study was to describe the point prevalence of AIS and to evaluate the effectiveness of school screening in 12-year- old children.

Methods

Community nurses and physical therapists in the Southern Health region of Norway including about 12000 school children aged 12 years were invited to participate. All participating community nurses and physical therapists fulfilled an educational course to improve their knowledge about AIS and learn the screening procedure including the Adam Forward Bending Test and measurement of gibbus using a scoliometer.

Results

Sub-regions including 4000 school children participated. The prevalence of idiopathic scoliosis defined as a positive Adam Forward Bending Test, gibbus > 7° and primary major curve on radiographs > 10°, was 0.55%. Five children (0.13%) had a major curve > 20°. Bracing was not indicated in any child; all children were post menarche; four had Risser sign of 4, and one with Risser 1 did not have curve progression > 5° at later follow-up. In one of these 5 children however, the major curve progressed to 45° within 7 months after screening and the girl was operated.

Conclusion

The point prevalence of AIS in 12- year old children is in agreement or slightly lower than previous studies. The screening model employed demonstrates acceptable sensitivity and specificity and low referral rates. Screening at the age of 12 years only was not effective for detecting patients with indication for brace treatment.     

Pollen-mediated gene flow in maize in real situations of coexistence

We present the first study on cross-fertilization between Bt and conventional maize in real situations of coexistence in two regions in which Bt and conventional maize were cultivated. A map was designed and the different crops were identified, as were the sowing and flowering dates, in Bt and conventional maize fields. These data were used to choose the non-transgenic fields for sampling and analysis by the real-time quantification system-polymerase chain reaction (RTQ-PCR) technique. In general, the rate of cross-fertilization was higher in the borders and, in most of the fields, decreased towards the centre of the field. Nine fields had values of genetically modified organism DNA to total DNA of much lower than 0.9%, whereas in three the rate was higher. Some differences were found when comparing our results with those of common field trials. In real conditions of coexistence and in cropping areas with smaller fields, the main factors that determined cross-pollination were the synchronicity of flowering and the distances between the donor and receptor fields. By establishing an index based on these two variables, the rate of the adventitious presence of genetically modified maize could be predicted, as well as the influence of other factors. By applying this index, and in the case of a fully synchronous flowering time, a security distance between transgenic and conventional fields of about 20 m should be sufficient to maintain the adventitious presence of genetically modified organisms as a result of pollen flow below the 0.9% threshold in the total yield of the field.     

Identification of a Novel Human Papillomavirus by Metagenomic Analysis of Samples from Patients with Febrile Respiratory Illness

As part of a virus discovery investigation using a metagenomic approach, a highly divergent novel Human papillomavirus type was identified in pooled convenience nasal/oropharyngeal swab samples collected from patients with febrile respiratory illness. Phylogenetic analysis of the whole genome and the L1 gene reveals that the new HPV identified in this study clusters with previously described gamma papillomaviruses, sharing only 61.1% (whole genome) and 63.1% (L1) sequence identity with its closest relative in the Papillomavirus episteme (PAVE) database. This new virus was named HPV_SD2 pending official classification. The complete genome of HPV-SD2 is 7,299 bp long (36.3% G/C) and contains 7 open reading frames (L2, L1, E6, E7, E1, E2 and E4) and a non-coding long control region (LCR) between L1 and E6. The metagenomic procedures, coupled with the bioinformatic methods described herein are well suited to detect small circular genomes such as those of human papillomaviruses.     

Inferring differences in the distribution of reaction rates across conditions

Elucidating changes in the distribution of reaction rates in metabolic pathways under different conditions is a central challenge in systems biology. Here we present a method for inferring regulation mechanisms responsible for changes in the distribution of reaction rates across conditions from correlations in time-resolved data. A reversal of correlations between conditions reveals information about regulation mechanisms. With the use of a small in silico hypothetical network, based on only the topology and directionality of a known pathway, several regulation scenarios can be formulated. Confronting these scenarios with experimental data results in a short list of possible pathway regulation mechanisms associated with the reversal of correlations between conditions. This procedure allows for the formulation of regulation scenarios without detailed prior knowledge of kinetics and for the inference of reaction rate changes without rate information. The method was applied to experimental time-resolved metabolomics data from multiple short-term perturbation-response experiments in S. cerevisiae across aerobic and anaerobic conditions. The method's output was validated against a detailed kinetic model of glycolysis in S. cerevisiae, which showed that the method can indeed infer the correct regulation scenario.     

Unbiased and efficient log-likelihood estimation with inverse binomial sampling

The fate of scientific hypotheses often relies on the ability of a computational model to explain the data, quantified in modern statistical approaches by the likelihood function. The log-likelihood is the key element for parameter estimation and model evaluation. However, the log-likelihood of complex models in fields such as computational biology and neuroscience is often intractable to compute analytically or numerically. In those cases, researchers can often only estimate the log-likelihood by comparing observed data with synthetic observations generated by model simulations. Standard techniques to approximate the likelihood via simulation either use summary statistics of the data or are at risk of producing substantial biases in the estimate. Here, we explore another method, inverse binomial sampling (IBS), which can estimate the log-likelihood of an entire data set efficiently and without bias. For each observation, IBS draws samples from the simulator model until one matches the observation. The log-likelihood estimate is then a function of the number of samples drawn. The variance of this estimator is uniformly bounded, achieves the minimum variance for an unbiased estimator, and we can compute calibrated estimates of the variance. We provide theoretical arguments in favor of IBS and an empirical assessment of the method for maximum-likelihood estimation with simulation-based models. As case studies, we take three model-fitting problems of increasing complexity from computational and cognitive neuroscience. In all problems, IBS generally produces lower error in the estimated parameters and maximum log-likelihood values than alternative sampling methods with the same average number of samples. Our results demonstrate the potential of IBS as a practical, robust, and easy to implement method for log-likelihood evaluation when exact techniques are not available.     

Equilibrium-Phase High Spatial Resolution Contrast-Enhanced MR Angiography at 1.5T in Preoperative Imaging for Perforator Flap Breast Reconstruction

Objectives

The aim was (i) to evaluate the accuracy of equilibrium-phase high spatial resolution (EP) contrast-enhanced magnetic resonance angiography (CE-MRA) at 1.5T using a blood pool contrast agent for the preoperative evaluation of deep inferior epigastric artery perforator branches (DIEP), and (ii) to compare image quality with conventional first-pass CE-MRA.

Methods

Twenty-three consecutive patients were included. All patients underwent preoperative CE-MRA to determine quality and location of DIEP. First-pass imaging after a single bolus injection of 10 mL gadofosveset trisodium was followed by EP imaging. MRA data were compared to intra-operative findings, which served as the reference standard.

Results

There was 100% agreement between EP CE-MRA and surgical findings in identifying the single best perforator branch. All EP acquisitions were of diagnostic quality, whereas in 10 patients the quality of the first-pass acquisition was qualified as non-diagnostic. Both signal- and contrast-to-noise ratios were significantly higher for EP imaging in comparison with first-pass acquisitions (p<0.01).

Conclusions

EP CE-MRA of DIEP in the preoperative evaluation of patients undergoing a breast reconstruction procedure is highly accurate in identifying the single best perforator branch at 1.5Tesla (T). Besides accuracy, image quality of EP imaging proved superior to conventional first-pass CE-MRA.     

FAME, the Flux Analysis and Modeling Environment

Background

The creation and modification of genome-scale metabolic models is a task that requires specialized software tools. While these are available, subsequently running or visualizing a model often relies on disjoint code, which adds additional actions to the analysis routine and, in our experience, renders these applications suboptimal for routine use by (systems) biologists.

Results

The Flux Analysis and Modeling Environment (FAME) is the first web-based modeling tool that combines the tasks of creating, editing, running, and analyzing/visualizing stoichiometric models into a single program. Analysis results can be automatically superimposed on familiar KEGG-like maps. FAME is written in PHP and uses the Python-based PySCeS-CBM for its linear solving capabilities. It comes with a comprehensive manual and a quick-start tutorial, and can be accessed online at http://f-a-m-e.org/.

Conclusions

With FAME, we present the community with an open source, user-friendly, web-based "one stop shop" for stoichiometric modeling. We expect the application will be of substantial use to investigators and educators alike.