Validation of a CT-based determination of the glenohumeral index.

The amount of bony support by the glenoid can be determined using the glenohumeral index, i.e. the maximum anteroposterior (AP) diameter of the humeral head divided by the maximum AP dimension of the glenoid. This index has been described theoretically, but has never been validated in practice. In this study we used 20 cadaver shoulders to determine the glenohumeral index in two different ways. One method evaluated the glenohumeral index on a CT scan of the shoulders. The second method determined the anatomical glenohumeral index of the same shoulders by direct measurement of anatomical specimens using a digital caliper. All CT and caliper measurements were repeated by three different investigators. We used the Wilcoxon Signed Rank Test, to calculate the statistical significance of intra-observer and inter-observer differences in measurements on CT and with the caliper. Statistical analysis showed no significant differences between CT scan and caliper measurements for each investigator separately, but we found a statistically significant inter-observer variability concerning the caliper measurements obtained by two different investigators. This study demonstrates that a two-dimensional CT scan of the shoulder is a reliable and very accurate tool to calculate the glenohumeral index, as the values measured for the AP diameter of the humeral head and the AP dimension of the glenoid compare well with those measured in vitro on anatomical specimens.

Functional analysis and classification of phytoplankton based on data from an automated flow cytometer.

Analytical flow cytometry (FCM) is well suited for the analysis of phytoplankton communities in fresh and sea waters. The measurement of light scatter and autofluorescence properties of particles by FCM provides optical fingerprints, which enables different phytoplankton groups to be separated. A submersible version of the CytoSense flow cytometer (the CytoSub) has been designed for in situ autonomous sampling and analysis, making it possible to monitor phytoplankton at a short temporal scale and obtain accurate information about its dynamics. For data analysis, a manual clustering is usually performed a posteriori: data are displayed on histograms and scatterplots, and group discrimination is made by drawing and combining regions (gating). The purpose of this study is to provide greater objectivity in the data analysis by applying a nonmanual and consistent method to automatically discriminate clusters of particles. In other words, we seek for partitioning methods based on the optical fingerprints of each particle. As the CytoSense is able to record the full pulse shape for each variable, it quickly generates a large and complex dataset to analyze. The shape, length, and area of each curve were chosen as descriptors for the analysis. To test the developed method, numerical experiments were performed on simulated curves. Then, the method was applied and validated on phytoplankton cultures data. Promising results have been obtained with a mixture of various species whose optical fingerprints overlapped considerably and could not be accurately separated using manual gating.

Optimizing the setup of a flow cytometric cell sorter for efficient quantitative sorting of long filamentous cyanobacteria.

Heterogeneity within natural phytoplankton communities makes it very difficult to analyze parameters at the single-cell level. Flow cytometric sorting is therefore a useful tool in aquatic sciences, as it provides material for post-sort analysis and culturing. Sorting subpopulations from natural communities, however, often requires handling morphologically diverse and complex particles with various abundances. Long particles, such as filament-forming cyanobacteria (>100-µm long), prove very difficult to handle. These potentially toxic organisms are widespread in eutrophic systems and have important ecological consequences. Being able to sort filamentous cyanobacteria efficiently and as viable cells is therefore highly desirable when studying factors associated with their toxicity and occurrence. This unconventional sorting requires extensive user experience and special instrument setup. We have investigated the effect of hydrodynamic and electromechanical components of a flow cytometer, and sorting protocol on the quantitative sorting efficiency of these long particles using two filamentous cyanobacterial strains with average lengths of ∼100 and ∼300 µm. Sorting efficiency ranged from 9.4 to 96.0% and was significantly affected by filament length, sorting envelope, drop delay (dd), and for the long species also by tip size, but not by cycle time. Filaments survived sorting and were not damaged. The optimal settings found for the modular MoFlo® cell-sorter to sort the filaments were a 100-µm flow tip at 30 psi (207 kPa) with a three-droplet envelope in Enrich mode while using an extended analysis time of 17.6 µs and an intermediate plate charge and deflection percentage combination of 3,000 V/60%, combined with a dd 0 for the cultures with 100-µm filaments and dd +1 for the culture with 300-µm filaments. To the best of our knowledge, the filaments up to 1063.5 µm sorted in this study are the longest ever sorted.

The contribution of phytoplankton degradation to chromophoric dissolved organic matter (CDOM) in eutrophic shallow lakes: field and experimental evidence.

Eight field campaigns in the eutrophic, shallow, Lake Taihu in the summers from 2005 to 2007, and a phytoplankton degradation experiment of 33 days, were carried out to determine the contribution of phytoplankton degradation to CDOM. Significant and positive correlations were found between the CDOM absorption coefficient at 355 nm [a(CDOM)(355)], normalized fluorescence emission (QSU) at 450 nm from excitation at 355 nm [F(n)(355)], and the chlorophyll a (Chla) concentration for all eight field campaigns, which indicates that the decomposition and degradation of phytoplankton is an important source of CDOM. In the degradation experiment, the CDOM absorption coefficient increased as phytoplankton broke down during the first 12 days, showing the production of CDOM from phytoplankton. After 12 days, a(CDOM)(355) had increased from the initial value 0.41+/-0.03 m(-1) to 1.37+/-0.03 m(-1) (a 234% increase), and the Chla concentration decreased from the initial value of 349.1+/-11.2 microg/L to 30.4+/-13.2 microg/L (a 91.3% decrease). The mean daily production rate of CDOM from phytoplankton was 0.08 m(-1) for a(CDOM)(355). Parallel Factor Analysis (PARAFAC) was used to assess CDOM composition from EEM spectra, and four components were identified: a terrestrial-like humic component, two marine-like humic components, and a protein-like component. The rapid increase in marine-like humic fluorophores (C3 and C4) during the degradation experiment suggests that in situ production of CDOM plays an important role in the dynamics of CDOM. The field campaigns and experimental data in the present study show that phytoplankton can be one of the important CDOM producers in eutrophic shallow lakes.

The timescale of phenotypic plasticity and its impact on competition in fluctuating environments.

Although phenotypic plasticity can be advantageous in fluctuating environments, it may come too late if the environment changes fast. Complementary chromatic adaptation is a colorful form of phenotypic plasticity, where cyanobacteria tune their pigmentation to the prevailing light spectrum. Here, we study the timescale of chromatic adaptation and its impact on competition among phytoplankton species exposed to fluctuating light colors. We parameterized a resource competition model using monoculture experiments with green and red picocyanobacteria and the cyanobacterium Pseudanabaena, which can change its color within approximately 7 days by chromatic adaptation. The model predictions were tested in competition experiments, where the incident light color switched between red and green at different frequencies (slow, intermediate, and fast). Pseudanabaena (the flexible phenotype) competitively excluded the green and red picocyanobacteria in all competition experiments. Strikingly, the rate of competitive exclusion was much faster when the flexible phenotype had sufficient time to fully adjust its pigmentation. Thus, the flexible phenotype benefited from its phenotypic plasticity if fluctuations in light color were relatively slow, corresponding to slow mixing processes or infrequent storms in their natural habitat. This shows that the timescale of phenotypic plasticity plays a key role during species interactions in fluctuating environments.

HADDOCK versus HADDOCK: new features and performance of HADDOCK2.0 on the CAPRI targets.

Here we present version 2.0 of HADDOCK, which incorporates considerable improvements and new features. HADDOCK is now able to model not only protein-protein complexes but also other kinds of biomolecular complexes and multi-component (N > 2) systems. In the absence of any experimental and/or predicted information to drive the docking, HADDOCK now offers two additional ab initio docking modes based on either random patch definition or center-of-mass restraints. The docking protocol has been considerably improved, supporting among other solvated docking, automatic definition of semi-flexible regions, and inclusion of a desolvation energy term in the scoring scheme. The performance of HADDOCK2.0 is evaluated on the targets of rounds 4-11, run in a semi-automated mode using the original information we used in our CAPRI submissions. This enables a direct assessment of the progress made since the previous versions. Although HADDOCK performed very well in CAPRI (65% and 71% success rates, overall and for unbound targets only, respectively), a substantial improvement was achieved with HADDOCK2.0.