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PubMedDate not supplied

Technical aspects of internet-based knowledge presentation in radiotherapy.

Three-dimensional radiotherapy planning is a complex and time-consuming optimization process which requires much experience. To simplify and to speed up the process of treatment planning as well as to exchange experience and therapeutic knowledge, the department of Medical Physics at the German Cancer Research Centre (DKFZ) in Heidelberg is developing an Internet-based 3D Radiotherapy planning and Information System (IRIS). IRIS designed internet-based client-server application, implemented using Java, CORBA and PVM. The concept of IRIS combines the functionality of an interactive tutorial with a discussion forum, teleconferencing tool and an atlas of dose distributions. Furthermore an integral knowledge-based system provides automatically generated, preoptimized treatment plans. This paper explains the technical design of the system and gives an overview of experiences gained by the technical realization of a first prototype using currently available internet technology. The prototype is currently running for testing in the intranet of DKFZ.

Artificial Intelligence↗

PubMed1999

Effects of cellulose derivatives and additives in the spray-drying preparation of acetaminophen delivery systems.

Microcrystalline cellulose (MCC), sodium carboxymethylcellulose (NaCMC), hydroxypropylmethylcellulose (HPMC), hydroxyethylcellulose (HEC), hydroxypropylcellulose (HPC), and ethylcellulose (EC) were used for the production of time-controlled acetaminophen delivery systems using a spray-drying technique. The influence of factors such as polymer concentration, inlet temperature, and drug/polymer ratio were investigated. The product yields were a function of the type and concentration of the polymer, with the highest values being reached from feeds containing 1% MCC and EC. Parameters of 1% polymer concentration and an inlet temperature of 140 degrees C gave rise to optimal processing conditions. Using these parameters, the influence of some adjuncts, such as polyethylene glycol 6000 (PEG 6000), dibutyl sebacate (DBS), polyvinylpyrrolidone (PVP), and carboxylic acids such as citric acid (CA), phthalic acid (PA), succinic acid (SA), tartaric acid (TA), and oxalic acid (OA), on the spray-drying process was evaluated. Of the additives tested, PVP (with MCC), DBS (with EC), and PEG 6000 (with NaCMC) induced yield decreases from 70% to 49%, 66% to 39%, and 37% to 17%, respectively. As for carboxylic acids (with NaCMC), similar or better performances of 43%, 45%, 47%, and 49% were obtained with SA, OA, PA, and TA, respectively. Dissolution studies in pH 1 dilute HCl and pH 6.8 phosphate buffer dissolution media showed that formulations consisting of 1% polymer with a drug/polymer ratio of 1/1 exhibited the slowest drug release, with the spheroids coated with NaCMC and HEC showing the longest T50% values (with 45 and 53 min at pH 1 and 49 and 55 min at pH 6.8, respectively). Slightly better sustained drug release in pH 6.8 dissolution medium was reached, showing the following trend: HEC > NaCMC > MCC > EC > HPMC. Concerning the additives, the trends in dissolution T50% of drug revealed TA > SA > CA > OA > PVP > PA > DBS in acidic pH 1 dissolution medium and PVP > OA > TA > SA > PA > CA > DBS in phosphate buffer at pH 6.8.

Acetaminophen↗

PubMed2005

Reconstruction of air contaminant concentration distribution in a two-dimensional plane by computed tomography and remote sensing FTIR spectroscopy.

This research combined open path FTIR (OP-FTIR) technique and computed tomography (CT) to reconstruct air contaminant concentration distribution in a two-dimensional plane. Remote sensing FTIR instrument was used to scan radial beam geometry and obtain path integrated concentration (PIC) data of acetone gas in the measuring plane. Smooth basis function minimization (SBFM) algorithm was adopted to reconstruct gaseous concentration distribution. For the purpose of finding out the preferable number of Gaussians used in SBFM algorithm, single-Gaussian, double-Gaussian, and three-Gaussian models were used respectively. Experimental results showed that the reconstruction result of acetone concentration distribution by SBFM algorithm with double-Gaussian model agreed with real distribution more qualitatively and quantitatively than single-Gaussian and three-Gaussian. Also, it has been proved that simulated annealing algorithm used in the optimization process of SBFM reconstruction was feasible and effective. Although computed tomography and remote sensing FTIR technique (CT-RS-FTIR) is still at the laboratory study stage, with further improvement of SBFM algorithm and beam geometry, it promises to be used in air pollution monitoring widely.

Acetone↗

PubMed2002

Generation of gelatin aerosol particles from nebulized solutions as model drug carrier systems.

PURPOSE: Aerodynamically stable, nebulized aerosols are desirable to achieve optimum asthma therapy. Stabilizing droplet size using gel-forming polymers may assist in achieving this goal. Semisolid particles may be generated through aerosolization of a polymer solution. Gelatin was employed as a model polymer in a process optimization study using the marker, disodium fluorescein, and the drug, budesonide delivered from two commercially available air-jet nebulizers. METHODS: The aerosol delivery system consisted of either of the air-jet nebulizers attached to a 30 cm drying column. The nebulizers employed were the Aerotech II and Salter SL8900. Two gelatin solutions (0.1 and 0.7% w/v) were evaluated following initial density and viscosity measurements. Particle characterization was conducted by scanning electron microscopy, eight-stage cascade impaction (CI), and phase-Doppler analysis. Disodium fluorescein (NaF, 5 and 7% w/v) and budesonide (B, 0.05% w/v) were added to the gelatin solutions in a 2(4)-factorial design study and the follow-up drug formulation study, respectively. The factorial design experiment evaluated the influence of device, operating pressure, marker, and gelatin concentrations on mass median aerodynamic diameter (MMAD) and fine particle fraction (FPF). Spectrophotometry of the CI samples was performed at wavelengths of 486 (NaF) and 254 (B) nm. RESULTS: The factorial design experiment utilizing NaF showed that MMADs were not influenced significantly be the device, operating pressure, marker, or gelatin concentrations (p > 0.05). However, FPFs were significantly influenced by marker concentration and device (p < 0.05). In the presence of budesonide, the MMADs and FPFs for Aerotech and Salter, respectively, were: MMAD = 1.39 +/- 0.30 microns and 1.75 +/- 0.63 microns, FPF = 93.5 +/- 4% and 68.5 +/- 5%, (n = 3). These values were consistent with those predicted in the designed experiment. CONCLUSIONS: A range of semisolid particle sizes were produced (1.3 < MMAD < 1.8 microns) for the 0.7% w/v gelatin formulation using different nebulizers. The budesonide formulation produced FPFs of 69-93%.

Aerosols↗

PubMed2005

Response surface methodology for the development of self-nanoemulsified drug delivery system (SNEDDS) of all-trans-retinol acetate.

UNLABELLED: The purpose was to prepare, characterize, and optimize a self-nanoemulsified drug delivery system (SNEDDS) of a model lipophilic compound, all-trans-retinol acetate. As part of the optimization process, the main effects, interaction effects, and quadratic effects of the formulation ingredients were investigated. METHOD: A three-factor, three-level Box-Behnken design was used to explore the quadratic response surfaces and construct a second-order polynomial model in the form: Y = A + A1X1 + A2X2+ A3X3 + A4X1X2 + A5X2X3 + A6X1X3+ A7X1(2) + A8X2(2) + A9X3(2) + E. Amount of added oil (X1), surfactant (X2), and cosurfactant (X3) were selected as the factors. Particle size (Y1), turbidity (Y2), and cumulative amount of the active ingredient emulsified after 10 (Y3) and 30 (Y4) min were the observed variables. Response surface plots were used to demonstrate the effect of factors (X1), (X2), and (X3) on the response (Y4). Amount of added soybean oil (X1), Cremophor EL (X2), and Capmul MCM-C8 (X3) showed a significant effect on the emulsification rates, as well as on the physical properties of the resultant emulsion (particle size and turbidity). Observed and predicted values of Y4 obtained from the constructed equations were in close agreement. Response surface methodology was then used to predict the levels of factors X1, X2, and X3 under the constrained variables for an optimum response. Applied constraints were 0 < Y1 < 0.5, 1 < Y2 < 20, 60 < Y3 < 80, and 90 < Y4 < 100. The predicted values were 0.0704 microm for particle size (Y1), 18.95 NTU for turbidity (Y2), 88.88% for drug release after 10 min (Y3), and 110.7% drug release after 30 min (Y4). Two new formulations were prepared according to the predicted levels. The observed and predicted values were in close agreement.

Chemistry, Pharmaceutical↗

PubMed2002

A unified model for the speed of sound in cranial bone based on genetic algorithm optimization.

The density and structure of bone is highly heterogeneous, causing wide variations in the reported speed of sound for ultrasound propagation. Current research on the propagation of high intensity focused ultrasound through an intact human skull for non-invasive therapeutic action on brain tissue requires a detailed model for the acoustic velocity in cranial bone. Such models have been difficult to derive empirically due to the aforementioned heterogeneity of bone itself. We propose a single unified model for the speed of sound in cranial bone based upon the apparent density of bone by CT scan. This model is based upon the coupling of empirical measurement, theoretical acoustic simulation and genetic algorithm optimization. The phase distortion caused by the presence of skull in an acoustic path is empirically measured. The ability of a theoretical acoustic simulation coupled with a particular speed-of-sound model to predict this phase distortion is compared against the empirical data, thus providing the fitness function needed to perform genetic algorithm optimization. By performing genetic algorithm optimization over an initial population of candidate speed-of-sound models, an ultimate single unified model for the speed of sound in both the cortical and trabecular regions of cranial bone is produced. The final model produced by genetic algorithm optimization has a nonlinear dependency of speed of sound upon local bone density. This model is shown by statistical significance to be a suitable model of the speed of sound in bone. Furthermore, using a skull that was not part of the optimization process, this model is also tested against a published homogeneous speed-of-sound model and shown to return an improved prediction of transcranial ultrasound propagation.

Algorithms↗

PubMed2005

Incorporating organ movements in inverse planning: assessing dose uncertainties by Bayesian inference.

We present a method to calculate dose uncertainties due to inter-fraction organ movements in fractionated radiotherapy, i.e. in addition to the expectation value of the dose distribution a variance distribution is calculated. To calculate the expectation value of the dose distribution in the presence of organ movements, one estimates a probability distribution of possible patient geometries. The respective variance of the expected dose distribution arises for two reasons: first, the patient is irradiated with a finite number of fractions only and second, the probability distribution of patient geometries has to be estimated from a small number of images and is therefore not exactly known. To quantify the total dose variance, we propose a method that is based on the principle of Bayesian inference. The method is of particular interest when organ motion is incorporated in inverse IMRT planning by means of inverse planning performed on a probability distribution of patient geometries. In order to make this a robust approach, it turns out that the dose variance should be considered (and minimized) in the optimization process. As an application of the presented concept of Bayesian inference, we compare three approaches to inverse planning based on probability distributions that account for an increasing degree of uncertainty. The Bayes theorem further provides a concept to interpolate between patient specific data and population-based knowledge on organ motion which is relevant since the number of CT images of a patient is typically small.

Algorithms↗

PubMed2006

Real-time analysis of enzyme kinetics via micro parallel liquid chromatography.

A generic method for real-time monitoring of enzyme kinetics is described in this paper. This approach enables rapid development of assays for high-throughput screening or reaction monitoring in the linear range of the enzyme kinetic curve. In this paper, we used protein kinase A and kemptide (a well-studied assay system) to demonstrate assay optimization by using micro parallel liquid chromatography. The optimal substrate and enzyme concentrations were determined rapidly and conveniently compared with the traditional methods for determining these parameters. Additionally, the data collected from the same experiment permitted calculations of K (m) for the substrate, V (max), and time-course study. In general, this approach provides two advantages. First, the broad ranges of detectable product conversions facilitate selection and implementation of assay conditions for high-throughput screening. Second, the system permits determination of 50% inhibitory concentration values at less than 1% conversion of substrate to product, thereby validating screening hits in the linear range of the enzyme kinetic curve. Overall, this optimization process can be done in less than 8 h. To demonstrate the ability to monitor a wide range of assay conditions, we varied initial concentrations over eight orders of magnitude within a single experiment. Compared with a classical enzyme kinetics study, this method significantly speeds the target validation process and reduces time associated with assay development and high-throughput screening implementation.

Chromatography, Liquid↗

PubMed2006

Manualized communication interventions to enhance palliative care research and training: rigorous, testable approaches.

Palliative care practice requires excellent communication between the patient, family, and clinical team. Experts in the field have proposed a variety of communication interventions that can be used in the palliative care setting. However, these interventions are at a high level of generality: the specifics of each intervention are not well codified; the individual steps in each intervention are not easily reproducible and thus not comparable between practitioners; the methods to measure adherence to these communication protocols have not been established; and there is little detail on how to adapt these general interventions to the individual patient and family. Therefore, we lack good evidence for the efficacy of these recommendations. This paper makes the case for development of structured, testable approaches to communication that will inform clinical practice and communication training. To do so, palliative care communication should be conceived as a formal medical and psychosocial intervention-a potential treatment with risks and benefits to be systematically researched and operationalized in the same manner as medication interventions. As we illustrate, psychotherapy research has faced the same challenges in the past and has utilized manualized treatments to meet its goals. Through such approaches, we can begin to address the most basic intervention questions such as protocol efficacy, dose-response, side effects, and the optimal process and content of communication with the patient and family. The advantages of manualized communication approaches; some concepts underlying manual construction; and challenges to extending manualized communication to the palliative care domain are discussed.

Communication↗

PubMed1991

A novel method for optimum biopsy specimen preservation for histochemical and immunohistochemical analysis.

A novel method has been developed for optimally processing biopsy specimens combining freeze-substitution with low-temperature plastic embedding. Immunohistochemistry and conventional histochemical stains were all readily performed on tissue displaying high-quality morphologic preservation. Labile antigens, especially lymphoid cell surface antigens, were well preserved. This new method avoids the need for tissue fixation and combines the superior morphologic preservation of fixed embedded tissue with the reactivity of cryostat sections. This method ensures that diagnostic information from even the smallest biopsy specimen is maximized because a wide range of phenotypic markers can be applied and evaluated in relation to high-quality morphologic preservation of tissue. Biopsy specimens are stored at room temperature without loss of tissue-specific characteristics during storage.

Acetone↗

PubMed1999

Segmentation of yeast DNA using hidden Markov models.

MOTIVATION: Compositionally homogeneous segments of genomic DNA often correspond to meaningful biological units. Simple sliding window analysis is usually insufficient for compositional segmentation of natural sequences. Hidden Markov models (HMM) with a small number of states are a natural language for description of compositional properties of chromosome-size DNA sequences. RESULTS: The algorithms were applied to yeast Saccharomyces cerevisiae chromosomes (YC) I, III, IV, VI and IX. The optimal number of HMM states is found to be four. The optimal four-state HMMs for all chromosomes are very similar, as well as the reconstructed segmentations. In most cases the models with k + 1 states are obtained by 'splitting' one of the states in the model with k states, and the corresponding increase of the level of detail in segmentation. The high AT states usually correspond to intergenic regions. We also explore the model's likelihood landscape and analyze the dynamics of the optimization process, thus addressing the problem of reliability of the obtained optima and efficiency of the algorithms.

Algorithms↗

PubMed1989

TEFOOL/2: a program for theoretical drug design on microcomputers.

TEFOOL/2, a program written in BASIC, is presented in this paper. The purpose of TEFOOL/2 is to provide people interested in drug design with an easy-to-handle program where some of the most important techniques in QSAR are included. The program permits the selection of the training series, performs regression calculations and searches for optimum substituents. The latter is achieved by using either a Hansch's strategy or geometrical procedures. The program is interactive and can be implemented on an IBM-PC or compatible microcomputer. Although TEFOOL/2 has been developed for its application in drug design studies, its great flexibility makes it suitable for application to any experimental design or optimization process.

Algorithms↗

PubMed2025

Unicorn: enhancing single-cell Hi-C data with blind super-resolution for 3D genome structure reconstruction.

MOTIVATION: Single-cell Hi-C (scHi-C) data provide critical insights into chromatin interactions at individual cell levels, uncovering unique genomic 3D structures. However, scHi-C datasets are characterized by sparsity and noise, complicating efforts to accurately reconstruct high-resolution chromosomal structures. In this study, we present ScUnicorn, a novel blind super-resolution framework for scHi-C data enhancement. ScUnicorn uses an iterative degradation kernel optimization process, unlike traditional super-resolution approaches, which rely on downsampling, predefined degradation ratios, or constant assumptions about the input data to reconstruct high-resolution interaction matrices. Hence, our approach more reliably preserves critical biological patterns and minimizes noise. Additionally, we propose 3DUnicorn, a maximum likelihood algorithm that leverages the enhanced scHi-C data to infer precise 3D chromosomal structures. RESULTS: Our evaluation demonstrates that ScUnicorn achieves superior performance over the state-of-the-art methods in terms of Peak Signal-to-Noise Ratio, Structural Similarity Index Measure, and GenomeDisco scores. Moreover, 3DUnicorn's reconstructed structures align closely with experimental 3D-FISH data, underscoring its biological relevance. Together, ScUnicorn and 3DUnicorn provide a robust framework for advancing genomic research by enhancing scHi-C data fidelity and enabling accurate 3D genome structure reconstruction. AVAILABILITY AND IMPLEMENTATION: Unicorn implementation is publicly accessible at https://github.com/OluwadareLab/Unicorn.

Single-Cell Analysis↗

PubMed2004

Missing value estimation for DNA microarray gene expression data: local least squares imputation.

MOTIVATION: Gene expression data often contain missing expression values. Effective missing value estimation methods are needed since many algorithms for gene expression data analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares formulation are proposed to estimate missing values in the gene expression data, which exploit local similarity structures in the data as well as least squares optimization process. RESULTS: The proposed local least squares imputation method (LLSimpute) represents a target gene that has missing values as a linear combination of similar genes. The similar genes are chosen by k-nearest neighbors or k coherent genes that have large absolute values of Pearson correlation coefficients. Non-parametric missing values estimation method of LLSimpute are designed by introducing an automatic k-value estimator. In our experiments, the proposed LLSimpute method shows competitive results when compared with other imputation methods for missing value estimation on various datasets and percentages of missing values in the data. AVAILABILITY: The software is available at http://www.cs.umn.edu/~hskim/tools.html CONTACT: hpark@cs.umn.edu

Algorithms↗

PubMed2005

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates.

MOTIVATION: To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process. RESULTS: We present an overview of the most important databases with 2-dimensional and 3-dimensional structural information about drugs and drug candidates, and of databases with relevant properties. Access to experimental data and numerical methods for selecting and utilizing these data is crucial for developing accurate predictive in silico models. Many interesting predictive methods for classifying the suitability of chemical compounds as potential drugs, as well as for predicting their physico-chemical and ADMET properties have been proposed in recent years. These methods are discussed, and some possible future directions in this rapidly developing field are described.

Chemistry, Pharmaceutical↗

PubMed2005

Modulation of the C1 visual event-related component by conditioned stimuli: evidence for sensory plasticity in early affective perception.

Previous research has demonstrated optimized processing of motivationally significant stimuli early in perception. In the present study, the time course and underlying mechanisms for such fast differentiation are of interest. We investigated the involvement of the primary visual cortex in affective evaluation of conditioned stimuli (CSs). In order to elicit learning within the visual system we chose affective pictures as unconditioned stimuli and used laterally presented gratings as CSs. Using high-density electroencephalography, we demonstrated modulation of the C1 visual event-related component for threat-related stimuli versus neutral stimuli, which increased with continuing acquisition of affective meaning. The differentiation between aversive and neutral visual stimuli occurred as early as 65-90 ms after stimulus onset and suggested involvement of the primary visual areas in affective evaluation. As an underlying mechanism, we discuss short-term reorganization in visual cortex, enabling sensory amplification of specific visual features that are related to motivationally relevant information.

Adult↗

PubMedDate not supplied

Planar chromatographic method development using the PRISMA optimization system and flow charts.

This study presents a modern planar chromatographic method-development procedure, based on the "PRISMA" optimization system, in which the optimum separation is achieved systematically and the structures and properties of the substances to be separated are not known. The procedure consists of three stages. In the first of these the basic conditions the stationary phase, vapor phase, and individual solvents are selected with a TLC procedure (generally in nonsaturated chromatographic chambers). In the second stage, the optimum combination of the selected solvents is determined with the PRISMA model. The third part of the procedure includes the selection of the development mode (circular, linear, or anticircular); the selection of an appropriate forced-flow chromatographic technique (over-pressured layer chromatography or rotation planar chromatography) with high-performance thin-layer chromatographic plates; the transfer of the optimized mobile phase to the various analytical, planar, or column preparative liquid chromatographic techniques; and the selection of the operating conditions. For practical reasons, the optimization process is presented with the help of flow charts.

Journal Article↗

PubMed2004

DNA chip technology in brain banks: confronting a degrading world.

DNA microarray technology is based on the principle of hybridization between 2 complementary strands of nucleic acids, one being fixed into a solid membrane, the other being the sample to analyze. This has resulted in a very powerful method to examine differential gene expression between samples, and has been widely used in the study of tumors. The application of DNA microarray technology to the study of the nervous system has to consider several properties of the nervous tissue: composition of various neuronal types, as well as astrocytes, oligodendrocytes, and microglia; regional and area differences; developmental and age-dependent variations; and functional and pathological status. Moreover, human samples are usually obtained postmortem following variable agonal periods and postmortem delays between death and tissue preservation, which are accompanied by variable RNA degradation. Yet human postmortem nervous tissue stored in brain banks offers a unique opportunity to facilitate material for the study of diseases of the nervous system and to gain direct understanding on the mechanisms of disease. This review analyzes the application of DNA microarray technology to current practice using brain-banked tissues in order to recognize and minimize sub-optimal processing of brain samples and to correct pitfalls due to inadequate procedures. Also discussed are RNA preservation and RNA degradation effects on expression pattern assessments, analysis of individual versus pooled samples, array normalization, types of DNA chip platforms, whole genomic analysis versus specialized chips, and microgenomics. Minimizing RNA degradation and improving detection of resistant RNA in postmortem brain has been considered in detail in order to improve the efficiency and reliability of DNA microarray technology employed in the study of human postmortem nervous tissue.

Animals↗