Computerized method for analyzing maximum and partial expiratory flow-volume curves.

Computerized instrumentation and software have been developed to obtain maximum expiratory flow-volume (MEFV) and partial expiratory flow-volume (PEFV) curves. The computerized system calculates and prints out the flow at 25% and 40% of control vital capacity (VC), the expiratory volume, peak expiratory flow rate and expiratory volume at one second (FEV1) divided by VC, the latter expressed as a percent. The flow-volume curves can be displayed on an oscilloscope or plotter and stored on magnetic tape. A pilot study was completed to demonstrate the reliability and validity of the data obtained.     

Acquiring multichannel analyzer spectra with a mini computer

Spectra are produced on a multichannnel analyzer from biological samples with monochromatic fluorescent X-radiation. This mini-computer system is designed (1) to provide spectral data in a form immediately usable for computation, (2) to provide a great number of spectra stored on magnetic tape, (3) to examine the spectra in the laboratory before committing the spectra to tape and (4) facilitate the examining and manipulation of data in the laboratory. The spectra on the tape are used in high-level analyses. The mini-computer can examine parts of a spectrum, plot and print the values, identify and integrate peaks, all at the user's discretion.     

Computerized graphic display of physiological data collected during human stereotactic surgery.

An on-line computerized graphic display has been developed for use during stereotactic operations. This depicts in the form of figurine charts and alph-numeric symbols, appropriately oriented on saggital brain diagrams, the results of serial threshold stimulation of the brain. The display facilitates choice of target sites and the data can be stored in a tape library from which search-and-plot programs can be activated for any type or combination of types of response.     

A computerized plankton counter

A portable computerized plankton counting system is presented, which has the potential to enumerate 255 different species per sample. The software is used to count phytoplankton samples and produce summary data. The hardware allows the results to be reproduced in the form of a hardcopy, stored on a cassette tape, or transferred to a larger computer for analysis.     

A microcomputer-based video vector system for clinical gait analysis

A microcomputer-based video vector system has been developed to display the resultant ground reaction force vector on a television image of the subject in real-time. For each television field the force platform signals are acquired and processed and the resultant force vector superimposed on the video image of the walking subject. The force platform results are stored on disc and the composite video signals recorded on video tape for further analysis. The system is easy to set up and use and the results can be readily interpreted. The external moments produced at the joint centres by the ground reaction forces can be observed visually and, if required, quantification of the external moments can be achieved following data collection. The spatial resolution of the system is 0.342% vertically and 0.156% horizontally. The force vector visualization technique has routine applications in orthotics and prosthetics. It is also a useful technique for the teaching of biomechanics.     

A rapid,flexibel method for biochemical assays using a microtiter plate reader and a microcomputer. Application for assays of protein,Na,K-Atpase and K-p-Nitrophenylphosphatase

A computerized system which greatly accelerates and eases the collection, storage, and analysis of data has been applied to several standard biochemical assays. The system uses a commercially available microtiter plate reader connected to an apple IIe microcomputer via a standard serial port. Data are transmitted automatically from the reader to the microcomputer, where they can be viewed, printed, further analyzed immediately, or stored on a diskette for later retrieval and processing. Some or all of the data may be entered manually. The program calculates a linear least squares best fit to a standard curve after correcting all data for blanks, then determines the quantities of substrate or product contained in each well of a microtiter plate. Data from two plates may be combined, enabling calculation of enzyme specific activities. This system can be adapted to any assay whose final step can be performed by a microtiter plate reader. Its use is described for determination of protein concentration, Na,K-ATPase activity, and K-stimulated p-nitrophenylphosphatase activity.     

Dual transformation of homonuclear solid-state NMR spectra--an option to decrease measuring time

Long measurement times due to low sensitivity are a prime concern in solid-state NMR and limit the application of multidimensional experiments severely. One possibility to address this problem could be post-experimental suppression of noise and a reduction of the number of increments needed for higher dimensional data sets. This can be achieved by a hybrid approach based on the combination of separately Fourier transformed and covariance processed datasets. The method is applied to synthetic sets as well as to experimental two-dimensional homonuclear solid-state NMR spectra of peptide samples. It is demonstrated that a reduction in experiment time by a factor of 4 can be achieved for the case of a 13C-13C correlation spectrum on the nonapeptide bradykinin.     

Nmrglue: an open source Python package for the analysis of multidimensional NMR data

Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.     

The BACTLAB system - a data system for bacteriological routine.

An implemented version of a data system for routine bacteriology is described which uses punch cards to capture all administrative data and OMR (optical mark recognition) documents for the bacteriological findings: diagnosis, antibiotic sensitivity patterns, phage type etc. The output includes reports for the customers and report lists for the laboratory, as well as surveys over findings of pertinent bacteria produced twice each month. In addition bills are produced at regular intervals, both for hospitals and for private patients. All results are stored on magnetic tape in order to make later analysis possible. The system has also been adapted for use in a research project for the study of postoperative infections.     

AURELIA,a program for computer-aided analysis of multidimensional NMR spectra

Summary AURELIA is an advanced program for the computer-aided evaluation of two-, three- and four-dimensional NMR spectra of any type of molecule. It can be used for the analysis of spectra of small molecules as well as for evaluation of complicated spectra of biological macromolecules such as proteins. AURELIA is highly interactive and offers a large number of tools, such as artefact reduction, cluster and multiplet analysis, spin system searches, resonance assignments, automated calculation of volumes in multidimensional spectra, calculation of distances with different approaches, including the full relaxation matrix approach, Bayesian analysis of peak features, correlation of molecular structures with NMR data, comparison of spectra via spectral algebra and pattern match techniques, automated sequential assignments on the basis of triple resonance spectra, and automatic strip calculation. In contrast to most other programs, many tasks are performed automatically.     

A microcomputer system for monitoring and analysing oxyhemoglobin saturation during sleep

A computerized data acquisition and analysis routine was developed to quantitate respiratory disturbances in sleeping patients. Polysomnographic recordings of patients consisted of electroencephalograms, electro-occulograms, submental electromyograms, air flow at the nose and mouth, esophageal pressure, and oxyhemoglobin saturation (SaO2). SaO2, a physiological effect of ventilatory airflow, was sampled every two seconds and stored on disk during the night's study for subsequent analysis. Wild points in the data file can be marked so that they will be skipped during analysis. Patient polysomnographs were scored manually for sleep stage by a sleep technician. A file was then created containing the scored sleep information with time marks corresponding to each change in sleep stage during the study. An analysis routine used this file to develop indices of sleep apnea, severity for combinations or specific stages of sleep. These indices were: (A) number of oxyhemoglobin desaturation episodes per hour; (B) average maximum desaturation per episode; and (C) desaturation index, the product of (A) and (B). A graph was plotted showing cumulative sleep time at given SaO2 values. The degree of sleep apnea can be determined using these indices.     

A color composite technique for detecting root dynamics of barley (Hordeum vulgare L.) from minirhizotron images

Quantification of root dynamics by destructive methods is confounded by high coefficients of variation and loss of fine roots. The minirhizotron technique is non-destructive and allows for sequential root observations to be made at the same depth in situ. Observations can be stored on video tape which facilitates data handling and computer-aided image processing. A color composite technique using digital image analyses was adapted in this study to detect barley root dynamics from sequential minirhizotron images. Plants were grown in the greenhouse in boxes (80 × 80 × 75 cm) containing soil from a surface horizon of a Typic Cryoboroll. A minirhizotron was installed at a 45°C angle in each box. Roots intersecting the minirhizotron were observed and video-recorded at tillering, stem extension, heading, dough and ripening growth stages. The images from a particular depth were digitized from the analog video then registered to each other. Discrimination of roots from the soil matrix gave quantitative estimates of root appearance and disappearance. Changes in root appearance and disappearance were detected by assigning a separate primary color (red, green, blue) to selected growth stages, then overlaying the images to create red-green and red-green-blue color composites. The resulting composites allowed for a visual interpretation and quantification of barley root dynamics in situ.     

Dual transformation of homonuclear solid-state NMR spectra—an option to decrease measuring time

Long measurement times due to low sensitivity are a prime concern in solid-state NMR and limit the application of multidimensional experiments severely. One possibility to address this problem could be post-experimental suppression of noise and a reduction of the number of increments needed for higher dimensional data sets. This can be achieved by a hybrid approach based on the combination of separately Fourier transformed and covariance processed datasets. The method is applied to synthetic sets as well as to experimental two-dimensional homonuclear solid-state NMR spectra of peptide samples. It is demonstrated that a reduction in experiment time by a factor of 4 can be achieved for the case of a ¹³C-¹³C correlation spectrum on the nonapeptide bradykinin.     

Multidimensional protein profiling technology and its application to human plasma proteome

In clinical and diagnostic proteomics, it is essential to develop a comprehensive and robust system for proteome analysis. Although multidimensional liquid chromatography/tandem mass spectrometry (LC/MS/MS) systems have been recently developed as powerful tools especially for identification of protein complexes, these systems still some drawbacks in their application to clinical research that requires an analysis of a large number of human samples. Therefore, in this study, we have constructed a technically simple and high throughput protein profiling system comprising a two-dimensional (2D)-LC/MS/MS system which integrates both a strong cation exchange (SCX) chromatography and a microLC/MS/MS system with micro-flowing reversed-phase chromatography. Using the microLC/MS/MS system as the second dimensional chromatography, SCX separation has been optimized as an off-line first dimensional peptide fractionation. To evaluate the performance of the constructed 2D-LC/MS/MS system, the results of detection and identification of proteins were compared using digests mixtures of 6 authentic proteins with those obtained using one-dimensional microLC/MS/MS system. The number of peptide fragments detected and the coverage of protein sequence were found to be more than double through the use of our newly built 2D-LC/MS/MS system. Furthermore, this multidimensional protein profiling system has been applied to plasma proteome in order to examine its feasibility for clinical proteomics. The experimental results revealed the identification of 174 proteins from one serum sample depleted HSA and IgG which corresponds to only 1 microL of plasma, and the total analysis run time was less than half a day, indicating a fairly high possibility of practicing clinical proteomics in a high throughput manner.     

TSAR: a program for automatic resonance assignment using 2D cross-sections of high dimensionality, high-resolution spectra

While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra (≥4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the δ?subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments.     

Congruent qualitative behavior of complete and reconstructed phase space trajectories from biomolecular dynamics simulation

Central to the study of a complex dynamical system is knowledge of its phase space behavior. Experimentally, it is rarely possible to record a system's (multidimensional) phase space variables. Rather, the system is observed via one (or few) scalar-valued signal(s) of emission or response. In dynamical systems analysis, the multidimensional phase space of a system can be reconstructed by manipulation of a one-dimensional signal. The trick is in the construction of a (higher-dimensional) space through the use of a time lag (or delay) on the signal time series. The trajectory in this embedding space can then be examined using phase portraits generated in selected subspaces. By contrast, in computer simulation, one has an embarrassment of riches: direct access to the complete multidimensional phase space variables, at arbitrary time resolution and precision. Here, the problem is one of reducing the dimensionality to make analysis tractable. This can be achieved through linear or nonlinear projection of the trajectory into subspaces containing high information content. This study considers trajectories of the small protein crambin from molecular dynamics simulations. The phase space behavior is examined using principal component analysis on the Cartesian coordinate covariance matrix of 138 dimensions. In addition, the phase space is reconstructed from a one dimensional signal, representing the radius of gyration of the structure along the trajectory. Comparison of low-dimensional phase portraits obtained from the two methods shows that the complete phase space distribution is well represented by the reconstruction. The study suggests that it may be possible to develop a deeper connection between the experimental and simulated dynamics of biomolecules via phase space reconstruction using data emerging from recent advances in single-molecule time-resolved biophysical techniques.     

Parameterized specification, configuration and execution of data-intensive scientific workflows

Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multidimensional parameter space consisting of input performance parameters to the applications that are known to affect their execution times. While some performance parameters such as grouping of workflow components and their mapping to machines do not affect the accuracy of the analysis, others may dictate trading the output quality of individual components (and of the whole workflow) for performance. This paper describes an integrated framework which is capable of supporting performance optimizations along multiple such parameters. Using two real-world applications in the spatial, multidimensional data analysis domain, we present an experimental evaluation of the proposed framework.     

Interactive computer supported tumor registry in the state of Rhode Island.

A new interactive computerized tumor registry has been established for the state of Rhode Island. The registry is implemented with new data base software which features a pagination scheme with rapid retrieval of non-coded variable data. The types of data stored are discussed as well as the computer system and methods of data entry storage and retrieval.     

U‐CIE [/juː ‘siː/]: Color encoding of high‐dimensional data

Data visualization is essential to discover patterns and anomalies in large high‐dimensional datasets. New dimensionality reduction techniques have thus been developed for visualizing omics data, in particular from single‐cell studies. However, jointly showing several types of data, for example, single‐cell expression and gene networks, remains a challenge. Here, we present ‘U‐CIE, a visualization method that encodes arbitrary high‐dimensional data as colors using a combination of dimensionality reduction and the CIELAB color space to retain the original structure to the extent possible. U‐CIE first uses UMAP to reduce high‐dimensional data to three dimensions, partially preserving distances between entities. Next, it embeds the resulting three‐dimensional representation within the CIELAB color space. This color model was designed to be perceptually uniform, meaning that the Euclidean distance between any two points should correspond to their relative perceptual difference. Therefore, the combination of UMAP and CIELAB thus results in a color encoding that captures much of the structure of the original high‐dimensional data. We illustrate its broad applicability by visualizing single‐cell data on a protein network and metagenomic data on a world map and on scatter plots.