Temporal variability of antibiotics fluxes in wastewater and contribution from hospitals.

Significant quantities of antibiotics are used in all parts of the globe to treat diseases with bacterial origins. After ingestion, antibiotics are excreted by the patient and transmitted in due course to the aquatic environment. This study examined temporal fluctuations (monthly time scale) in antibiotic sources (ambulatory sales and data from a hospital dispensary) for Lausanne, Switzerland. Source variability (i.e., antibiotic consumption, monthly data for 2006-2010) were examined in detail for nine antibiotics--azithromycin, ciprofloxacin, clarithromycin, clindamycin, metronidazole, norfloxacin, ofloxacin, sulfamethoxazole and trimethoprim, from which two main conclusions were reached. First, some substances--azithromycin, clarithromycin, ciprofloxacin--displayed high seasonality in their consumption, with the winter peak being up to three times higher than the summer minimum. This seasonality in consumption resulted in seasonality in Predicted Environmental Concentrations (PECs). In addition, the seasonality in PECs was also influenced by that in the base wastewater flow. Second, the contribution of hospitals to the total load of antibiotics reaching the Lausanne Wastewater Treatment Plant (WTP) fluctuated markedly on a monthly time scale, but with no seasonal pattern detected. That is, there was no connection between fluctuations in ambulatory and hospital consumption for the substances investigated.

Mapping the proteome of Leishmania Viannia parasites using two-dimensional polyacrylamide gel electrophoresis and associated technologies.

In this study we have demonstrated the potential of two-dimensional electrophoresis (2DE)-based technologies as tools for characterization of the Leishmania proteome (the expressed protein complement of the genome). Standardized neutral range (pH 5-7) proteome maps of Leishmania (Viannia) guyanensis and Leishmania (Viannia) panamensis promastigotes were reproducibly generated by 2DE of soluble parasite extracts, which were prepared using lysis buffer containing urea and nonidet P-40 detergent. The Coomassie blue and silver nitrate staining systems both yielded good resolution and representation of protein spots, enabling the detection of approximately 800 and 1,500 distinct proteins, respectively. Several reference protein spots common to the proteomes of all parasite species/strains studied were isolated and identified by peptide mass spectrometry (LC-ES-MS/MS), and bioinformatics approaches as members of the heat shock protein family, ribosomal protein S12, kinetoplast membrane protein 11 and a hypothetical Leishmania-specific 13 kDa protein of unknown function. Immunoblotting of Leishmania protein maps using a monoclonal antibody resulted in the specific detection of the 81.4 kDa and 77.5 kDa subunits of paraflagellar rod proteins 1 and 2, respectively. Moreover, differences in protein expression profiles between distinct parasite clones were reproducibly detected through comparative proteome analyses of paired maps using image analysis software. These data illustrate the resolving power of 2DE-based proteome analysis. The production and basic characterization of good quality Leishmania proteome maps provides an essential first step towards comparative protein expression studies aimed at identifying the molecular determinants of parasite drug resistance and virulence, as well as discovering new drug and vaccine targets.

Do we truly see what we think we see? The role of cognitive bias in pathological interpretation.

In the histomorphological grading of prostate carcinoma, pathologists have regularly assigned comparable scores for the architectural Gleason and the now-obsolete nuclear World Health Organization (WHO) grading systems. Although both systems demonstrate good correspondence between grade and survival, they are based on fundamentally different biological criteria. We tested the hypothesis that this apparent concurrence between the two grading systems originates from an interpretation bias in the minds of diagnostic pathologists, rather than reflecting a biological reality. Three pathologists graded 178 prostatectomy specimens, assigning Gleason and WHO scores on glass slides and on digital images of nuclei isolated out of their architectural context. The results were analysed with respect to interdependencies among the grading systems, to tumour recurrence (PSA relapse > 0.1 ng/ml at 48 months) and robust nuclear morphometry, as assessed by computer-assisted image analysis. WHO and Gleason grades were strongly correlated (r = 0.82) and demonstrated identical prognostic power. However, WHO grades correlated poorly with nuclear morphology (r = 0.19). Grading of nuclei isolated out of their architectural context significantly improved accuracy for nuclear morphology (r = 0.55), but the prognostic power was virtually lost. In conclusion, the architectural organization of a tumour, which the pathologist cannot avoid noticing during initial slide viewing at low magnification, unwittingly influences the subsequent nuclear grade assignment. In our study, the prognostic power of the WHO grading system was dependent on visual assessment of tumour growth pattern. We demonstrate for the first time the influence a cognitive bias can have in the generation of an error in diagnostic pathology and highlight a considerable problem in histopathological tumour grading.

Brain tissue segmentation of fetal MR images

We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).

A New Imaging Software To Evaluate The Centration Of Capsulorhexis And Intraocular Lens (IOL) After Cataract Surgery

Purpose: IOL centration and stability after cataract surgery is of high interest for cataract surgeons and IOL-producing companies. We present a new imaging software to evaluate the centration of the rhexis and the centration of the IOL after cataract surgery.Methods: We developed, in collaboration with the Biomedical Imaging Group (BIG), EPFL, Lausanne, a new working tool in order to assess precisely outcomes after IOL-implantation, such as ideal capsulorhexis and IOL-centration. The software is a plug-in of ImageJ, a general-purpose image processing and image-analysis package. The specifications of this software are: evaluation of the rhexis-centration and evaluation the position of the IOL in the posterior chamber. The end points are to analyze the quality of the centration of a rhexis after cataract surgery, the deformation of the rhexis with capsular bag retraction and the centration of the IOL after implantation.Results: This software delivers tools to interactively measure the distances between limbus, IOL and capsulorhexis and its changes over time. The user is invited to adjust nodes of three radial curves for the limbus, rhexis and the optic of the IOL. The radial distances of the curves are computed to evaluate the IOL implantation. The user is also able to define patterns for ideal capsulorhexis and optimal IOL-centration. We are going to present examples of calculations after cataract surgery.Conclusions: Evaluation of the centration of the rhexis and of the IOL after cataract surgery is an important end point for optimal IOL implantation after cataract surgery. Especially multifocal or accommodative lenses need a precise position in the bag with a good stability over time. This software is able to evaluate these parameters just after the surgery but also its changes over time. The results of these evaluations can lead to an optimizing of surgical procedures and materials.

Glucose and lactate are equally effective in energizing activity-dependent synaptic vesicle turnover in purified cortical neurons.

This study examines the role of glucose and lactate as energy substrates to sustain synaptic vesicle cycling. Synaptic vesicle turnover was assessed in a quantitative manner by fluorescence microscopy in primary cultures of mouse cortical neurons. An electrode-equipped perfusion chamber was used to stimulate cells both by electrical field and potassium depolarization during image acquisition. An image analysis procedure was elaborated to select in an unbiased manner synaptic boutons loaded with the fluorescent dye N-(3-triethylammoniumpropyl)-4-(4-(dibutylamino)styryl)pyridinium dibromide (FM1-43). Whereas a minority of the sites fully released their dye content following electrical stimulation, others needed subsequent K(+) depolarization to achieve full release. This functional heterogeneity was not significantly altered by the nature of metabolic substrates. Repetitive stimulation sequences of FM1-43 uptake and release were then performed in the absence of any metabolic substrate and showed that the number of active sites dramatically decreased after the first cycle of loading/unloading. The presence of 1 mM glucose or lactate was sufficient to sustain synaptic vesicle cycling under these conditions. Moreover, both substrates were equivalent for recovery of function after a phase of decreased metabolic substrate availability. Thus, lactate appears to be equivalent to glucose for sustaining synaptic vesicle turnover in cultured cortical neurons during activity.

Pacing redistributes glycogen within the developing myocardium.

Electrical pacing at physiological rate induces myocardial remodeling associated with regional changes in workload, blood flow and oxygen consumption. However, to what extent energy-producing pathways are also modified within the paced heart remains to be investigated. Pacing could particularly affect glycogen metabolism since hypertrophy stimulates glycolysis and increased workload favors glucose over fat oxidation. In order to test this hypothesis, we used the embryonic chick heart model in which ventricular pacing rapidly resulted in thinning of the ventricle wall and thickening of the atrial wall. Hearts of stage 22HH chick embryos were submitted in ovo to asynchronous and intermittent ventricular pacing delivered at physiological rate during 24 h. The resulting alterations of glycogen content were determined in atrium, ventricle and conotruncus of paced and sham-operated hearts. Hemodynamic parameters of the paced and spontaneously beating hearts were derived from computerized image analysis of video recordings. With respect to sham, paced hearts showed a significant decrease in glycogen content (nmoles glucose units/microg protein; mean+/-S.D.) only in atrium (1.48+/-0.40 v 0.84+/-0.34, n=8) and conotruncus (0.75+/-0.28 v 0.42+/-0.23, n=8). Pacing decreased the end diastolic and stroke volumes by 34 and 44%, respectively. Thus, the rapid glycogen depletion in regions remote from the stimulation site appears to be associated with regional changes in workload and remodeling. These findings underscore the importance of the coupling mechanisms between metabolic pathways and myocardial remodeling in the ectopically paced heart.

Cytotoxic effects of FGF2-saporin on bovine epithelial lens cells in vitro.

PURPOSE: To test the ability of two preparations of FGF2-saporin, either FGF2 chemically conjugated to saporin (FGF2-SAP) or genetically engineered FGF2-saporin (rFGF2-SAP) to inhibit the growth of bovine epithelial lens (BEL) cells in vitro when in solution and when immobilized on heparin surface-modified (HSM) polymethylmethacrylate (PMMA) intraocular lenses (IOLs). METHOD: Bovine epithelial lens cells were incubated with various concentrations FGF2-saporin for as long as 4 days. The number of surviving cells was determined by counting the number of nuclei. Because FGF2 binds to heparin, FGF2-saporin was incubated with HSM PMMA IOLs; excess toxin was washed off, and the BEL cells were grown on the FGF2-saporin-treated IOLs (HSM and non-HSM) for 4 days. Cell density was determined by image analysis. RESULTS: Both FGF2-SAP and rFGF2-SAP were highly cytotoxic (nM range), with rFGF2-SAP 10 times less active than FGF2-SAP. FGF2-saporin bound to the surface of HSM IOLs and eluted by 2M NaCl retained its activity. Toxin bound to HSM IOLs killed more than 90% of the BEL cells placed on the IOL surface within 4 days. The ability of FGF2-saporin to prevent the growth of cells on the IOL surface was strictly dependent on the presence of heparin on the IOL. CONCLUSIONS: FGF2-saporin is bound to HSM PMMA IOLs and prevents the growth of epithelial cells on the surface of the lens.

Quantitative distribution of parvalbumin, calretinin, and calbindin D-28k immunoreactive neurons in the visual cortex of normal and Alzheimer cases.

The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.

Comparative Study of Chemoembolization, Loadable Beads: In vitro Drug Release and Physical Properties of DC Bead and Hepasphere, Loaded with Doxorubicin and Irinotecan

Purpose To characterize in vitro the loadability, physical properties, and release of irinotecan and doxorubicin from two commercially available embolization microspheres. Materials and Methods DC Bead (500-700 μm) and Hepasphere (400-600 μm) microspheres were loaded with either doxorubicin or irinotecan solutions. Drug amount was quantified with spectrophotometry, bead elasticity was measured under compression, and bead size and loading homogeneity were assessed with microscopy image analysis. Drug release was measured over 1-week periods in saline by using a pharmacopeia flow-through method. Results Almost complete drug loading was obtained for both microsphere types and drugs. Doxorubicin-loaded DC Beads maintained their spherical shape throughout the release. In contrast, Hepaspheres showed less homogeneous doxorubicin loading and, after release, some fractured microspheres. Incomplete doxorubicin release was observed in saline over 1 week (27% ± 2 for DC beads and 18% ± 7 for Hepaspheres; P = .013). About 75% of this amount was released within 2.2 hours for both beads. For irinotecan, complete release was obtained for both types of beads, in a sustained manner over 2-3 hours for DC Beads, and in a significantly faster manner as a 7-minute burst for Hepaspheres. Conclusions The two drug-eluting microspheres could be efficiently loaded with both drugs. Incomplete doxorubicin release was attributed to strong drug-bead ionic interactions. Weaker interactions were observed with irinotecan, which led to faster drug release.

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification

This paper presents 3-D brain tissue classificationschemes using three recent promising energy minimizationmethods for Markov random fields: graph cuts, loopybelief propagation and tree-reweighted message passing.The classification is performed using the well knownfinite Gaussian mixture Markov Random Field model.Results from the above methods are compared with widelyused iterative conditional modes algorithm. Theevaluation is performed on a dataset containing simulatedT1-weighted MR brain volumes with varying noise andintensity non-uniformities. The comparisons are performedin terms of energies as well as based on ground truthsegmentations, using various quantitative metrics.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

A rapid and effective vignetting correction for quantitative microscopy

Images acquired using optical microscopes are inherently subject to vignetting effects due to imperfect illumination and image acquisition. However, such vignetting effects hamper accurate extraction of quantitative information from biological images, leading to less effective image segmentation and increased noise in the measurements. Here, we describe a rapid and effective method for vignetting correction, which generates an estimate for a correction function from the background fluorescence without the need to acquire additional calibration images. We validate the usefulness of this algorithm using artificially distorted images as a gold standard for assessing the accuracy of the applied correction and then demonstrate that this correction method enables the reliable detection of biologically relevant variation in cell populations. A simple user interface called FlattifY was developed and integrated into the image analysis platform YeastQuant to facilitate easy application of vignetting correction to a wide range of images.

Cross validation of experts versus registration methods for target localization in deep brain stimulation.

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.