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At least 163 records · Page 9Linked to original sources

Visualization and comparison of molecular dynamics simulations of leukotriene C4, leukotriene D4, and leukotriene E4.

Molecular dynamics simulations of leukotriene C4 (LTC4), leukotriene D4 (LTD4), and leukotriene E4 (LTE4) were carried out, and the data were visualized in an animated video format. Three-dimensional ghost images show the positions of the heavy atoms of all three molecules throughout the simulations. The ghost images can be superimposed to give a single three-dimensional image in which the shapes of the most populated conformers of each molecule are apparent and can be compared. Leukotriene D4 was found to occupy mostly T-shaped conformations, while LTC4 occupied mostly cup-shaped conformations, and LTE4 occupied a wide range of conformations spanning the LTD4 and LTC4 types. Digital filtering and graphing of the internal geometries of the molecules as a function of time revealed differences in dynamic behavior. The results are discussed in light of current knowledge about leukotriene receptors.

Computer Graphics↗

In vivo measurements of indwelling tracheo-oesophageal prostheses in alaryngeal speech.

Over the last 5 years, detailed air pressure, flow and voice measurements have been made on indwelling tracheo-oesophageal speaking valves whilst inserted in patients, using specially designed apparatus. This study was set up to investigate the relationship between speech and in vivo parameters. In vivo pressure measurements were generally lower for Groningen low resistance than Groningen high resistance, while flow and voice measurements were higher. A plot of opening pressure against pressure at maximum flow for all valves suggested a straight line relationship. A graph of maximum voice against composite parameter score for all valves showed a cluster of points between the composite score of 0-15. The advances in knowledge about these valves should be of use in the design of improved valves.

Aged↗

Symbolic inference of xenobiotic metabolism.

We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds.

Algorithms↗

New approaches in molecular structure prediction.

In the past years, much effort has been put on the development of new methodologies and algorithms for the prediction of protein secondary and tertiary structures from (sequence) data; this is reviewed in detail. New approaches for these predictions such as neural network methods, genetic algorithms, machine learning, and graph theoretical methods are discussed. Secondary structure prediction algorithms were improved mostly by considering families of related proteins; however, for the reliable tertiary structure modeling of proteins, knowledge-based techniques are still preferred. Methods and examples with more or less successful results are described. Also, programs and parameterizations for energy minimisations, molecular dynamics, and electrostatic interactions have been improved, especially with respect to their former limits of applicability. Other topics discussed in this review include the use of traditional and on-line databases, the docking problem and surface properties of biomolecules, packing of protein cores, de novo design and protein engineering, prediction of membrane protein structures, the verification and reliability of model structures, and progress made with currently available software and computer hardware. In summary, the prediction of the structure, function, and other properties of a protein is still possible only within limits, but these limits continue to be moved.

Chemical Phenomena↗

Quantitative analysis of nucleic acid three-dimensional structures.

A new computer program to annotate DNA and RNA three-dimensional structures, MC-Annotate, is introduced. The goals of annotation are to efficiently extract and manipulate structural information, to simplify further structural analyses and searches, and to objectively represent structural knowledge. The input of MC-Annotate is a PDB formatted DNA or RNA three-dimensional structure. The output of MC-Annotate is composed of a structural graph that contains the annotations, and a series of HTML documents, one for each nucleotide conformation and base-base interaction present in the input structure. The atomic coordinates of all nucleotides and the homogeneous transformation matrices of all base-base interactions are stored in the structural graph. Symbolic classifications of nucleotide conformations, using sugar puckering modes and nitrogen base orientations around the glycosyl bond, and base-base interactions, using stacking and hydrogen bonding information, are introduced. Peculiarity factors of nucleotide conformations and base-base interactions are defined to indicate their marginalities with all other examples. The peculiarity factors allow us to identify irregular regions and possible stereochemical errors in 3-D structures without interactive visualization. The annotations attached to each nucleotide conformation include its class, its torsion angles, a distribution of the root-mean-square deviations with examples of the same class, the list of examples of the same class, and its peculiarity value. The annotations attached to each base-base interaction include its class, a distribution of distances with examples of the same class, the list of examples of the same class, and its peculiarity value. The distance between two homogeneous transformation matrices is evaluated using a new metric that distinguishes between the rotation and the translation of a transformation matrix in the context of nitrogen bases. MC-Annotate was used to build databases of nucleotide conformations and base-base interactions. It was applied to the ribosomal RNA fragment that binds to protein L11, which annotations revealed peculiar nucleotide conformations and base-base interactions in the regions where the RNA contacts the protein. The question of whether the current database of RNA three-dimensional structures is complete is addressed.

Base Pairing↗

Determination of the etching surface of metal frameworks in resin-bonded prostheses.

The aim of electrolytic etching of the metal framework of resin bonded retainers is a microretentive surface. The results of metal etching depend on various factors such as metal alloy, casting conditions, etching solution, and constant electrolytical conditions. Precise knowledge of the inner metal surface is necessary for an exact setting of the current density per time unit. The indirect method of copying the contours from tinfoil to graph paper reduced the error rate to a mean value of +/- 2.3 mm2. This practical method of determining the metal surface before etching can be accomplished without complicated equipment.

Acid Etching, Dental↗

Network methods for diagonal integration of unpaired single-cell multiomics data: a review.

MOTIVATION: Advances in single-cell sequencing have enabled multiomics profiling at unprecedented resolution; however, mass spectrometry-based single-cell proteomics (scMS) remains inherently destructive, precluding simultaneous transcriptomic capture. Unlike antibody-based methods such as CITE-seq, which permit paired profiling but are restricted to targeted protein panels, scMS provides unbiased, genome-scale coverage of the intracellular proteome yet necessitates post hoc integration of unpaired datasets. This diagonal integration challenge, where transcriptomes and proteomes are measured in separate cells lacking shared anchors, remains underserved by existing reviews, which focus predominantly on vertical integration strategies enabled by non-destructive assays. RESULTS: We survey the complete computational pipeline for constructing mechanistic proteogenomic networks from unpaired single-cell data, covering: (i) unimodal network inference such as knowledge-based approaches, probabilistic graphical models, temporal directionality inference, and generative and foundation model strategies that establish the transcriptomic scaffold; (ii) cross-modal integration architectures such as network propagation, graph neural networks (scMRDR, scmFormer, scCotag), and consensus frameworks designed explicitly for the unpaired proteomics setting; and (iii) benchmarking paradigms spanning network reconstruction (BEELINE, GRETA, CausalBench) and multi-task integration evaluation (scMultiBench, SCMMIB), with guidance on metric selection under network sparsity and class imbalance. We identify three principal axes of future development: generative proteomic translation from transcriptomic precursors, inductive prior embedding in next-generation architectures, and perturbation-based causal benchmarking. AVAILABILITY AND IMPLEMENTATION: This is a review article; no novel software is distributed. A curated benchmark resource table, methods starter guide, and per-method bottleneck annotations are provided in the Supplementary Material.

Multiomics↗

Polished, professional presentation: unlocking the design elements.

Using available computer graphics software programs, a novice can develop a presentation. Going beyond the basics, however, requires knowledge of the use of the elements of design: fonts, colors, and graphics. This article describes how to select fonts and colors and provides guidelines for use of pictures and graphs. Guidelines for use of default settings and templates, and considerations related to the use of animation, sound, and projection are included. Examples are provided to demonstrate important points and creating a polished, professional product.

Audiovisual Aids↗

[Radioisotopic examination and diagnosis of dryness of the mouth].

The clinical and sialographic opposition between true xerostomia (with continuous disorders) and paradoxical asialia (with inter-prandial disturbance, but sparing mealtime) led the authors to analyze these patient's scintigraphic scannings. A kinetic study of excretion was carried out with gamma-camera recording of intensity and glandular activity: the information thus obtained was set down in a numerical integration block and dealt with by computer. A graph of activity was plotted for each gland showing: - a phase of ascending concentration followed by a plateau corresponding to excretion at rest; - a phase of excretion provoked by a gustatory stimulus (physiological) with a very rapidly descending graph. It is possible to establish a ratio of glandular activity/blood activity at maximum concentration and maximum excretion. From the graphs thus obtained it is possible to perfectly differentiate true xerostomia (no excretion even with stimulation) from paradoxical asialia (no plateau of excretion at rest, but stimulus effective). A better knowledge of "dryness of the mouth" should enable better adapted therapy.

Diagnosis, Differential↗

SIRPIDs: a case study.

A relatively new EEG variant has been uncovered in the recordings of critically ill patients. This variant is known as stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs). SIRPIDs are elicited from patients when various forms of stimulation are applied. The pathophysiology of SIRPIDs is still unknown, as is the knowledge of how to best treat patients presenting with SIRPID activity. This paper reviews the case of a 50-year-old unresponsive woman with history of coronary artery bypass graph presenting with a question of brain stem infraction or possible embolic event. The first EEG recording of this patient show both periodic and rhythmical discharges consistently elicited via stimulation, SIRPIDs.

Diagnosis, Differential↗

Representations of metabolic knowledge: pathways.

The automatic generation of drawings of metabolic pathways is a challenging problem that depends intimately on exactly what information has been recorded for each pathway, and on how that information is encoded. The chief contributions of the paper are a minimized representation for biochemical pathways called the predecessor list, and inference procedures for converting the predecessor list into a pathway-graph representation that can serve as input to a pathway-drawing algorithm. The predecessor list has several advantages over the pathway graph, including its compactness and its lack of redundancy. The conversion between the two representations can be formulated as both a constraint-satisfaction problem and a logical inference problem, whose goal is to assign directions to reactions, and to determine which are the main chemical compounds in the reaction. We describe a set of production rules that solves this inference problem. We also present heuristics for inferring whether the exterior compounds that are substrates of reactions at the periphery of a pathway are side or main compounds. These techniques were evaluated on 18 metabolic pathways from the EcoCyc knowledge base.

Animals↗

Computer-assisted assignment of peptides with non-standard amino acids.

A comprehensive peptide assignment program and its application to a cyclic peptide, cyclosporin A, are presented in this paper. A group of graph theoretical algorithms using fuzzy logic are discussed with the aid of examples from cyclosporin A. The algorithms deal with heavily overlapped peaks, recover disjointed and distorted spin coupling networks, and include strategies for sequence-specific assignment. A procedure to extend the Protein Knowledge Base for automatically assigning non-standard amino acid residues is also presented. The program is capable of completely automated assignment for small peptides (approximately 20 residues). For such molecules, it is insensitive to whether the peptide chain is cyclic or acyclic, and to whether amide protons are present or absent. For larger peptides/proteins, more user interaction is required and the sequence-specific assignment step usually must proceed through fragments smaller than the full length to avoid problems due to occurrence of a combinatorial explosion. The program can be applied as a rigorous tool to check manual assignments. The fuzzy graph theoretical concepts built in the program are illustrated with 2D proton spectra of a peptide, but may be extended to higher-dimensional spectra, other biopolymers, natural products and other organic structures.

Algorithms↗

Measuring membrane potential and electric field of brainstem neurons in vitro by confocal microscopy.

A method of measuring transmembrane potential and electric field of neural cells cultured in vitro is described in this paper. The high resolution and scanning speed of the method make it considerable to be used to observe the viability of the neurons cultured on opaque substrate. Rhodamine 123 was used to stain the cells in order to display different intensity corresponding to transmembrane potential. The fluorescence data were collected by confocal laser scanning microscopy (CLSM). Then the data were processed to create the graphs of transmembrane potential and electric field. This is the first paper describes a reliable method for three-dimensional visualization of potential voltage of neurons at the best of our knowledge.

Animals↗

Structural interpretation of a topological index. 1. External factor variable connectivity index (EFVCI).

The external factor variable connectivity index (EFVCI) is interpreted by mining out the structural features hidden in the space spanned by the EFVCI indices through projection pursuit combining with number-theory net (NT-net) on the unit sphere U(Us). Projection pursuit is concerned with "interesting" projections of high-dimensional data sets to machine-pick "interesting" low-dimensional projections of a high-dimensional point cloud by numerically maximizing a certain objective function or projection index. At first, the optimal EFVCI index reaches to -0.80 in the correlation with a retention index of 207 hydrocarbons produced by insects. The EFVCI indices, with regression results of R = 0.99998, s = 3.49, RMSECV = 3.90, and F = 7.9560e+005, obtain high regression quality. The model is proven valid by leave-one-out cross validation. Second, the EFVCI index is interpreted by the structure information, that is, size, branch number, graph center, and branching position of topological structures, which is searched out on the unit sphere U(Us) by projection pursuit. Finally, the interpretation information is used to discover some chemical knowledge concerning the variation of the retention index with the change in chemical structures.

Journal Article↗

Information content in organic molecules: reaction pathway analysis via Brownian processing.

Carbon chemistry offers infinite possibilities for molecules as information carriers. Moreover, there is no boundary on the number of ways in which a carrier's information can change via a chemical reaction. Organic reaction pathways thus pose new types of informatic variables which compel characterization using Brownian methods. We apply the tools of the preceding paper to these variable types for select reactions and classes. Along the way, geometric descriptors are formulated which complement the structure graph sequences of chemistry texts and journals. In addition, the statistical structure underpinning carbon transformations is explored more deeply. Overall, this work brings to light several informatic principles of organic reactions. Knowledge of these can assist in synthetic designs on both large- and small-scales. Brownian methods are able to address the pathway structures of all organic reactions: those reported in the literature, explored in the lab, or in the developmental stage.

Journal Article↗

Suicide rates and methods in different age groups: Australian data and perceptions.

OBJECTIVES: The two major aims of this study were (1) to assess senior medical students' knowledge of the age pattern of suicides in Australia, and (2) to note changes in the pattern of suicide in recent years. DESIGN: (1) Two groups of medical students were asked to graph the age distribution of Australian male and female suicides. (2) Suicide statistics (up to 1994) were provided by the Australian Bureau of Statistics. RESULTS: (1) Only 40% of the 75 medical students were aware that suicide in Australia is much more frequent among males. Only two of the 75 drew graphs that were similar to the true pattern. (2) The male rate of suicide at age 20-40 years was almost 35 per 100000 in 1989-94; above 80 years it was nearly 40 per 100000. The female suicide rate of all age groups from 20 years to late old age was about 7 per 100000. The most striking changes in method of suicide in Australia in recent years have been the doubling of male rates of suicide by hanging and car exhaust fumes, increases being greater in younger age groups. Elderly females are more likely than younger females to use hanging as a means of suicide. CONCLUSIONS: Male suicide rates peak in young adulthood and (higher) in late old age. Senior medical students were unaware of the true age and sex patterns of suicide in Australia. Treating depressions and preventing suicides of elderly people (as well as of young people) should be top priorities.

Adolescent↗

Substructural fragments: an universal language to encode reactions, molecular and supramolecular structures.

Substructural fragments are proposed as a simple and safe way to encode molecular structures in a matrix containing the occurrence of fragments of a given type. The knowledge retrieved from QSPR modelling can also be stored in that matrix in addition to the information about fragments. Complex supramolecular systems (using special bond types) and chemical reactions (represented as Condensed Graphs of Reactions, CGR) can be treated similarly. The efficiency of fragments as descriptors has been demonstrated in QSPR studies of aqueous solubility for a diverse set of organic compounds as well as in the analysis of thermodynamic parameters for hydrogen-bonding in some supramolecular complexes. It has also been shown that CGR may be an interesting opportunity to perform similarity searches for chemical reactions. The relationship between the density of information in descriptors/knowledge matrices and the robustness of QSPR models is discussed.

Computer Simulation↗

A temporal extension to the parsimonious covering theory.

In this paper, parsimonious covering theory is extended in such a way that temporal knowledge can be accommodated. In addition to causally associating possible manifestations with disorders, temporal relationships about duration and the time elapsed before a manifestation comes into existence can be represented by a graph. Precise definitions of the solution of a temporal diagnostic problem as well as algorithms to compute the solutions are provided. The medical suitability of the extended parsimonious cover theory is studied in the domain of food-borne disease.

Algorithms↗