Automatic preparation,calibration, and simulation of deformable objects

Many simulation environments – particularly those intended for medical simulation – require solid objects to deform at interactive rates, with deformation properties that correspond to real materials. Furthermore, new objects may be created frequently (for example, each time a new patient's data is processed), prohibiting manual intervention in the model preparation process. This paper provides a pipeline for rapid preparation of deformable objects with no manual intervention, specifically focusing on mesh generation (preparing solid meshes from surface models), automated calibration of models to finite element reference analyses (including a novel approach to reducing the complexity of calibrating nonhomogeneous objects), and automated skinning of meshes for interactive simulation.     

High-throughput sample preparation procedures for the quantitation of a new bone integrin alpha(nu)beta(3) antagonist in human plasma and urine using liquid chromatography-tandem mass spectrometry

High throughput LC-MS/MS assays to quantitate a new alpha(nu)beta(3) bone integrin antagonist (I) in human plasma and urine have been developed using instruments programmed to automate sample preparation procedures. Packard liquid handling system-MultiPROBE II EX was programmed for preparing calibration standards in control plasma and urine, acidifying all standards, quality control (QC), and clinical samples with necessary dilutions, and adding the internal standard to the acidified samples. TOMTEC Quadra 96 was programmed to perform the solid phase extraction (SPE) process on a 3M 96-well mixed phase cation standard density (MPC-SD) plate to isolate the analytes from the sample matrix. The extract collected from both types of matrices was directly injected into reversed-phase LC-MS/MS system with a Turbo Ion Spray (TIS) interface in the positive ionization mode. The plasma and urine assays have the calibration range of 0.5-1500 and 2-6000 ng/mL, respectively. Validation of the automated and the manual plasma assays showed that application of MultiPROBE II to sample preparation gave comparable accuracy and precision. Overall, the automated approaches with minimum manual intervention enhanced the throughput of sample preparation.     

Automated Identification of Filaments in Cryoelectron Microscopy Images

Since the foundation for the three-dimensional image reconstruction of helical objects from electron micrographs was laid more than 30 years ago, there have been sustained developments in specimen preparation, data acquisition, image analysis, and interpretation of results. However, the boxing of filaments in large numbers of images--one of the critical steps toward the reconstruction at high resolution--is still constrained by manual processing even though interactive interfaces have been built to aid the tedious and sometimes inaccurate boxing process. This article describes an accurate approach for automated detection of filamentous structures in low-contrast images acquired in defocus pairs using cryoelectron microscopy. The performance of the approach has been evaluated across various magnifications and at a series of defocus values using tobacco mosaic virus (TMV) preserved in vitreous ice as a test specimen. By integrating the proposed approach into our automated data acquisition and reconstruction system, we are now able to generate a three-dimensional map of TMV to approximately 10-A resolution within 24 h of inserting the specimen grid into the microscope.     

Strategies for rare-event detection: an approach for automated fetal cell detection in maternal blood.

This article explores the feasibility of the use of automated microscopy and image analysis to detect the presence of rare fetal nucleated red blood cells (NRBCs) circulating in maternal blood. The rationales for enrichment and for automated image analysis for "rare-event" detection are reviewed. We also describe the application of automated image analysis to 42 maternal blood samples, using a protocol consisting of one-step enrichment followed by immunocytochemical staining for fetal hemoglobin (HbF) and FISH for X- and Y-chromosomal sequences. Automated image analysis consisted of multimode microscopy and subsequent visual evaluation of image memories containing the selected objects. The FISH results were compared with the results of conventional karyotyping of the chorionic villi. By use of manual screening, 43% of the slides were found to be positive (>=1 NRBC), with a mean number of 11 NRBCs (range 1-40). By automated microscopy, 52% were positive, with on average 17 NRBCs (range 1-111). There was a good correlation between both manual and automated screening, but the NRBC yield from automated image analysis was found to be superior to that from manual screening (P=.0443), particularly when the NRBC count was >15. Seven (64%) of 11 XY fetuses were correctly diagnosed by FISH analysis of automatically detected cells, and all discrepancies were restricted to the lower cell-count range. We believe that automated microscopy and image analysis reduce the screening workload, are more sensitive than manual evaluation, and can be used to detect rare HbF-containing NRBCs in maternal blood.     

Scalable transcriptome preparation for massive parallel sequencing

Background

The tremendous output of massive parallel sequencing technologies requires automated robust and scalable sample preparation methods to fully exploit the new sequence capacity.

Methodology

In this study, a method for automated library preparation of RNA prior to massively parallel sequencing is presented. The automated protocol uses precipitation onto carboxylic acid paramagnetic beads for purification and size selection of both RNA and DNA. The automated sample preparation was compared to the standard manual sample preparation.

Conclusion/Significance

The automated procedure was used to generate libraries for gene expression profiling on the Illumina HiSeq 2000 platform with the capacity of 12 samples per preparation with a significantly improved throughput compared to the standard manual preparation. The data analysis shows consistent gene expression profiles in terms of sensitivity and quantification of gene expression between the two library preparation methods.     

Automated metaphase finding: an assessment of the efficiency of the METAFER2 system in a routine mutagenicity assay

The efficiency of the automated metaphase finding system METAFER2 is assessed in a routine mutagenicity assay using an aneuploid rat liver cell line treated with various promutagens. Data sets generated by automated and manual selection of metaphases are compared. It is demonstrated that METAFER2 routinely allows an efficient automatic identification of metaphases not only in lymphocyte preparations, but also in preparation from mammalian cell lines with varying chromosome numbers. Although larger slide areas are required for automated compared to manual metaphase scanning, the automatic system is faster by a factor of about 5. The interactive visual elimination of metaphases of insufficient quality is an easy and fast procedure.METAFER2 allows an unbiased selection of metaphases irrespective of their appearance as homogeneously stained first or harlequin-staines second division cells. Random selection of metaphases is neither influenced by various structural chromosome changes nor by increased frequencies of sister-chromatid exchanges.     

Automated screening of neurite outgrowth

Outgrowth of neurites in culture is used for assessing neurotrophic activity. Neurite measurements have been performed very slowly using manual methods or more efficiently with interactive image analysis systems. In contrast, medium-throughput and noninteractive image analysis of neurite screens has not been well described. The authors report the performance of an automated image acquisition and analysis system (IN Cell Analyzer 1000) in the neurite assay. Neuro-2a (N2a) cells were plated in 96-well plates and were exposed to 6 conditions of retinoic acid. Immunofluorescence labeling of the cytoskeleton was used to detect neurites and cell bodies. Acquisition of the images was automatic. The image set was then analyzed by both manual tracing and automated algorithms. On 5 relevant parameters (number of neurites, neurite length, total cell area, number of cells, neurite length per cell), the authors did not observe a difference between the automated analysis and the manual analysis done by tracing. These data suggest that the automated system addresses the same biology as human scorers and with the same measurement precision for treatment effects. However, throughput of the automated system is orders of magnitude higher than with manual methods.     

Statistical shape and appearance models for fast and automated estimation of proximal femur fracture load using 2D finite element models

Estimating the risk of osteoporotic fractures is an important diagnostic step that needs to be taken before medicinal treatment. Densitometry-based criteria are normally used in clinical practice for this purpose. However, densitometry-based techniques could not explain all low-energy fractures. As patient-specific finite element (FE) models allow for consideration of other parameters (e.g. load conditions) that are known to be associated with fracture, they are considered promising candidates for more accurate fracture risk estimation. Nevertheless, they are often time consuming, expensive, and complex to build and may need the type of expertise that is not normally available in clinical settings. In this study, we report the development of an automated platform for estimating proximal femur fracture loads using patient-specific 2D FE models generated using dual-energy x-ray absorptiometry (DXA) scans. First, a statistical shape and appearance model (SSAM) is built using DXA scans of patients screened for osteoporosis following a low energy fracture. SSAM is then used together with Active Appearance Models (AAM) for automated segmentation of the proximal femur from new unseen DXA scans. The mean point-to-curve error of the automated procedure, i.e. 1.2–1.4 mm, is shown to be only slightly larger than the intra-observer variability of manual segmentation, i.e. 1.0 mm. Moreover, the developed platform automatically meshes the segmented shape, assigns density-based mechanical properties, assigns loads and boundary conditions, submits the 2D FE model for solution, and performs post-processing of the 2D FE simulation data to determine fracture loads. The fracture loads predicted using the manually generated and automatically generated 2D FE models are shown to be very close with a mean difference of around 8.8%. Repeated measures ANOVA showed no significant differences between the fracture loads calculated using FE models manually generated by three independent observers and those calculated using the automatically generated FE models (p>0.05).     

A new automated method for isolation of Chlamydia trachomatis from urine eliminates inhibition and increases robustness for NAAT systems

Chlamydia trachomatis is a leading cause of sexually transmitted infection. Diagnostic methods with easy non-invasive sample collection are important to increase testing and hence to reduce the spread of this infection. To enable more use of urine samples in C. trachomatis diagnostics, automation is an absolute requirement since obtaining high-quality DNA from urine specimens involves extensive processing.

Here, we present a study in which a new automated sample preparation method, BUGS'n BEADS™ STI (BnB STI), was used up-front of the BDProbeTec™ ET end point analysis and compared with the full BDProbeTec™ ET method to analyze C. trachomatis in 1002 urine samples.

The BnB STI system represents a new concept within magnetic sample preparation in which bacteria are first isolated from the sample material followed by purification of bacterial nucleic acid using the same magnetic particles. Similar sensitivity and specificity were obtained with both methods. None of the samples processed with BnB STI inhibited the BDProbeTec™ ET test whereas 1.8% showed inhibition when processed according to the manual BDProbeTec™ ET DNA preparation method. Moreover, the average MOTA scores obtained with the BnB STI system were 48% higher for all amplification controls and 57% higher for positive samples, compared to the manual sample preparation. Based on these results and the significant reduction in hands-on-time for urine sample processing, the automated BnB STI sample preparation method was implemented for routine analysis of C. trachomatis from urine samples.     

Manually and automatically produced pellet cultures of human primary chondrocytes: A comparative analysis

Cartilage defects are often associated with restriction of the locomotor system. New methods are required to investigate cartilage tissue and for the repair of cartilage tissue. 3D cultures are promising due to better simulation of in vivo conditions. The aim of this study was to provide a model system for studying cartilage tissue. We solved this problem by automated production of pellet cultures of human primary chondrocytes in media with and without antibiotics using the Biomek® Cell Workstation and consequent automated bioscreening with a high‐throughput screening system, and compared with the regular manual processes. The Biomek® Cell Workstation allows the cultivation of different cell types (suspensions cells and adherent cells) and 3D cell cultures (pellet cultures, alginate beads and spheroid cultures). The proliferation was analyzed by DNA quantification and compared with the EZ4U proliferation assay as a new tool for pellet cultures. The toxicity was evaluated by the detection of ubiquitous adenylate kinases. The proliferation increased from day 14 until day 35 and was associated with a decrease in the cytotoxicity. The comparative analysis showed similar results for manual and automated processes. We concluded that the manual methods can be replaced by automated processes (pellet manufacturing and screening), which would allow large‐scale procedures to support studies on cartilage regeneration.     

Comparison of manual and automated methods for identifying target sounds in audio recordings of Pileated, Pale-billed, and putative Ivory-billed woodpeckers

ABSTRACT.   Although offering many benefits over manual recording and survey techniques for avian field studies, automated sound recording systems produce large datasets that must be carefully examined to locate sounds of interest. We compared two methods for locating target sounds in continuous sound recordings: (1) a manual method using computer software to provide a visual representation of the recording as a sound spectrogram and (2) an automated method using sound analysis software preprogrammed to identify specific target sounds. For both methods, we examined the time required to process a 24-h recording, scanning accuracy, and scanning comprehensiveness using four different target sounds of Pileated Woodpeckers ( Dryocopus pileatus ), Pale-billed Woodpeckers ( Campephilus guatemalensis ), and putative Ivory-billed Woodpeckers ( Campehilus principalis ). We collected recordings from the bottomland forests of Florida and the Neotropical dry forests of Costa Rica, and compared manual versus automated cross-correlation scanning techniques. The automated scanning method required less time to process sound recordings, but made more false positive identifications and was less comprehensive than the manual method, identifying significantly fewer target sounds. Although the automated scanning method offers a fast and economic alternative to traditional manual efforts, our results indicate that manual scanning is best for studies requiring an accurate account of temporal patterns in call frequency and for those involving birds with low vocalization rates.     

An automated phylogenetic tree-based small subunit rRNA taxonomy and alignment pipeline (STAP)

Comparative analysis of small-subunit ribosomal RNA (ss-rRNA) gene sequences forms the basis for much of what we know about the phylogenetic diversity of both cultured and uncultured microorganisms. As sequencing costs continue to decline and throughput increases, sequences of ss-rRNA genes are being obtained at an ever-increasing rate. This increasing flow of data has opened many new windows into microbial diversity and evolution, and at the same time has created significant methodological challenges. Those processes which commonly require time-consuming human intervention, such as the preparation of multiple sequence alignments, simply cannot keep up with the flood of incoming data. Fully automated methods of analysis are needed. Notably, existing automated methods avoid one or more steps that, though computationally costly or difficult, we consider to be important. In particular, we regard both the building of multiple sequence alignments and the performance of high quality phylogenetic analysis to be necessary. We describe here our fully-automated ss-rRNA taxonomy and alignment pipeline (STAP). It generates both high-quality multiple sequence alignments and phylogenetic trees, and thus can be used for multiple purposes including phylogenetically-based taxonomic assignments and analysis of species diversity in environmental samples. The pipeline combines publicly-available packages (PHYML, BLASTN and CLUSTALW) with our automatic alignment, masking, and tree-parsing programs. Most importantly, this automated process yields results comparable to those achievable by manual analysis, yet offers speed and capacity that are unattainable by manual efforts.     

The mesh-matching algorithm: an automatic 3D mesh generator for finite element structures

Several authors have employed finite element analysis for stress and strain analysis in orthopaedic biomechanics. Unfortunately, the definition of three-dimensional models is time consuming (mainly because of the manual 3D meshing process) and consequently the number of analyses to be performed is limited. The authors have investigated a new patient-specific method allowing automatically 3D mesh generation for structures as complex as bone for example. This method, called the mesh-matching (M-M) algorithm, generated automatically customized 3D meshes of anatomical structures from an already existing model. The M-M algorithm has been used to generate FE models of 10 proximal human femora from an initial one which had been experimentally validated. The automatically generated meshes seemed to demonstrate satisfying results.     

Determination of amphetamine and methamphetamine enantiomers by chiral derivatization and gas chromatography–mass spectrometry as a test case for an automated sample preparation system

An automated sample preparation system has been applied to the chiral analysis of amphetamine and methamphetamine using derivatization with trifluoracetyl-L -prolyl chloride (L -TPC) and subsequent separation on a gas chromatography–mass spectrometry (GC-MS) system. Tasks automated were the dilution of standards and the off-line preparation of the diastereoisomer derivatives. Chromatographic performance, sensitivity, and reproducibility of the automated procedure were compared to the equivalent values obtained with two existing assays methods which employ manual derivatiation, either on-column or off-line. Chromatographic performance was unaffected by the derivatization procedure and sensitivity was better for both automated and manual off-line derivatization. Qualitative reproducibility as based on enantiomeric composition was equivalent for all three approaches, while quantitative reproducibility as based on peak areas was best for the automated procedure. Considering the fact that the diastereoisomer derivatives are unstable over time, automated sample preparation with “just-in-time” derivatization can increase the overall precision of the analytical method. The procedures described here are general enough in nature that they could be applied to other chiral or even achiral analytes. © 1994 Wiley-Liss, Inc.     

A new system of chromosome analysis by image treatment: the chromoscan

The authors present a new interactive system for chromosome analysis. All the operations are checked by the biologist with the use of a "mouse". This system avoids the photographic work and the manual classification. Its main interest is to carry out quickly the karyotype after the slide preparation.     

Rapid quantitation of cyanide in whole blood by automated headspace gas chromatography

Cyanide (CN), a chemical asphyxiant, is a rapidly acting and powerful poison. We have developed a sensitive, rapid, simple, and fully automated method for measuring CN in whole blood. The assay is based on the use of gas chromatography (GC) with nitrogen-phosphorus detection and acetonitrile as an internal reference. Following the automated addition of phosphoric acid to the blood sample, the released hydrogen cyanide is analyzed using a fully automated headspace GC system. The assay, validated on human blood samples spiked with potassium cyanide and on clinical samples from fire victims who had smoke inhalation injury, can detect CN at a wide range of concentrations (30-6000 microg/l) in about 17 min (including incubation and GC run time, and <2 min for manual sample preparation). This automated, high-throughput, simple, and sensitive method is suitable for the rapid diagnosis of CN in clinical and forensic specimens.     

Automated analysis of the pyridinium crosslinks of collagen in tissue and urine using solid-phase extraction and reversed-phase high-performance liquid chromatography.

A fully automated method for assaying the collagen crosslinking amino acids, pyridinoline and deoxypyridinoline, in human urine samples or tissue hydrolysates is described. Samples were processed using a Gilson ASPEC system with solid-phase extraction of the crosslinks on columns containing 100 mg of microgranular cellulose. Introduction of an additional solvent step during sample preparation allowed direct analysis by reversed-phase HPLC and elimination of the drying step used previously in a manual method. Use of a synthetic pyridinoline derivative as internal standard enabled accurate quantification of the crosslinks by correcting for recoveries through the whole assay. Samples were analyzed in sequential mode with a total assay time of 30 min. The automated assay showed close correlation with the manual method for both free and total crosslink determinations in human urine (r > 0.97). Reproducibility was improved, as seen from replicate analyses of human urine (CV < 3% for automated pyridinoline measurement compared with 8-12% previously observed for the manual method). Crosslink excretion is the most useful marker of collagen degradation in metabolic bone diseases and arthritic disorders. The automated assay which has been developed is rapid, convenient, and reliable and will greatly facilitate the monitoring of urinary collagen crosslinks and their tissue levels in clinical investigations.     

Automated fluorescence image cytometry. DNA quantification and detection of chlamydial infections

Digitized fluorescence microscopy in conjunction with automated image segmentation is a promising approach for screening clinical specimens quickly and reliably. This paper describes the hardware and software of a prototype image-based cytometer that can identify fluorescent objects, discriminate true objects from artifacts and divide overlapping pairs of objects. The use of this image cytometer is discussed for: (1) the measurement of the DNA ploidy distribution of isolated mature rat liver nuclei labeled with 4',6-diamidine-2-phenylindole; (2) the comparison of the DNA ploidy distributions of the same samples measured by image cytometry (ICM) and flow cytometry (FCM); and (3) the quantification of chlamydial infection by double labeling cells with antichlamydiae antibody and Hoechst 33258 for nuclear DNA analysis. Ploidy distributions measured by the automated image cytometer compared favorably to those obtained by FCM. All pairs of overlapping nuclei were automatically detected by an additional computer algorithm, and those pairs that were clearly more than one nucleus by visual inspection were correctly divided. The irregular morphology of the chlamydiae-infected cells meant that 26% of them were not correctly identified in the fluorescein-stained images (as judged by manual inspection), but all cells were nevertheless detected correctly from the images of the Hoechst-stained samples. Automated fluorescence ICM yielded results similar to those obtained with FCM and had the additional benefit of maintaining cell and tissue architecture while preserving the opportunity for subsequent manual inspection of the specimen.     

An Object-Oriented Modeling and Simulation Environment for Reactive Systems Development

An environment to support the modeling, analysis, simulation, and development of state transition models, SMOOCHES (State Machines for Object-Oriented Concurrent Hierarchical Engineering Specifications), is presented. SMOOCHES allows the hierarchical construction, analysis, and simulation of state transition models in an object-oriented distributed environment. Statecharts (see Harel 1987b), a powerful mechanism for state transition specification, are fundamental to the development of SMOOCHES. To assist in the specification of hierarchical state transition models for distributed and reactive systems, statecharts are extended by introducing the concept of exit-safe states. SMOOCHES allows the specification of objects in the system with hierarchical state transition models and the derivation of new classes of objects through inheritance. A graphical monitoring system has been developed to represent and simulate the object state life cycles and monitor event generations. The example presented illustrates the modeling and simulation of different state life cycles of an assembly robot.     

Liquid ultraviolet matrix-assisted laser desorption/ionization -- mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet -- matrix-assisted laser desorption/ionisation -- mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. The low-femtomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydroxybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and low-mass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.