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PubMedDate not supplied

The effectiveness of a specialized trauma course in the knowledge base and level of job satisfaction in emergency nurses.

The purpose of this study is to evaluate the level of job satisfaction of the emergency department nurses that care for trauma patients. The hospital is a Level I trauma center and tertiary care center that provides multiple services to more than 1.2 million people in 29 counties. The Trauma Service and the Emergency Department (ED) must define and maintain the same expectations. The level of job satisfaction of the emergency department nurses will define the success of safe and effective patient care in a Level I Trauma Center.

Curriculum↗
PubMedDate not supplied

Motivation and organizational principles for anatomical knowledge representation: the digital anatomist symbolic knowledge base.

OBJECTIVE: Conceptualization of the physical objects and spaces that constitute the human body at the macroscopic level of organization, specified as a machine-parseable ontology that, in its human-readable form, is comprehensible to both expert and novice users of anatomical information. DESIGN: Conceived as an anatomical enhancement of the UMLS Semantic Network and Metathesaurus, the anatomical ontology was formulated by specifying defining attributes and differentia for classes and subclasses of physical anatomical entities based on their partitive and spatial relationships. The validity of the classification was assessed by instantiating the ontology for the thorax. Several transitive relationships were used for symbolically modeling aspects of the physical organization of the thorax. RESULTS: By declaring Organ as the macroscopic organizational unit of the body, and defining the entities that constitute organs and higher level entities constituted by organs, all anatomical entities could be assigned to one of three top level classes (Anatomical structure, Anatomical spatial entity and Body substance). The ontology accommodates both the systemic and regional (topographical) views of anatomy, as well as diverse clinical naming conventions of anatomical entities. CONCLUSIONS: The ontology formulated for the thorax is extendible to microscopic and cellular levels, as well as to other body parts, in that its classes subsume essentially all anatomical entities that constitute the body. Explicit definitions of these entities and their relationships provide the first requirement for standards in anatomical concept representation. Conceived from an anatomical viewpoint, the ontology can be generalized and mapped to other biomedical domains and problem solving tasks that require anatomical knowledge.

Anatomy↗
PubMed2002

Conflict resolution and peer mediation in middle schools: extending the process and outcome knowledge base.

Many professional educators are implementing school-based prevention focused on conflict resolution (CR) and peer mediation (PM). The authors conducted research on CR-PM in 3 middle schools. Specifically, they surveyed teachers and students, tracked disciplinary incidents across school years, collected mediation data, and compared mediators with a matched sample to determine attitudinal change as a result of PM training and experience. The authors also surveyed peer mediators and disputants about program satisfaction, as well as peer mediators and their parents about the generalization of PM skills. The authors conclude with implications for developing future CR programs, including a focus on mediation-process evaluation as well as schoolwide outcome measures and the use of peer mediation training as an intervention for students at risk.

Adolescent↗
PubMed2001

Risk factors of child maltreatment within the family: towards a knowledgeable base of family nursing.

The purpose of this study was to compare family dynamics in child maltreating families (n=42) with that in ordinary families with children (n=77), and to ascertain risk factors of child maltreatment within the family. Child maltreatment was defined as physical, psychological or sexual abuse or neglect of a child by a parent. Data were collected using questionnaires (Family Dynamics Measure 2, FMD 2) (N=119) basing on Barnhill's conceptual framework of healthy family systems and analysed by forming sum variables and logistic regression. The study results indicate that family functioning in child maltreating families is lower on all dimensions of family dynamics (individuation, mutuality, flexibility, stability, communication and roles) than that in ordinary families with children. Furthermore, it seems that specific risk factors, detected with logistic regression analysis, are related to whether child maltreatment occurs in the family or not. These include the parent's low educational background, many children in the family, unemployment of a parent, low individuation of the family members, and poor stability and security within the family. The results of this study provide guidelines for detecting and preventing child maltreatment as well as for recognising its existence, although no generalizations can be made due to the small sample size and complexity of the phenomenon under study.

Adult↗
PubMed1999

Reducing risks associated with drinking among young adults: promoting knowledge-based perspectives and harm reduction strategies.

The situation with regard to drinking is particularly complex for young adults: they are typically faced with pressures on one hand to abstain or drink small quantities, and on the other hand there may be expectations to drink heroic amounts and engage in risk-taking while drinking. Furthermore, in some cultures a very short transition period time is evident between condoned occasional experimentation with alcohol and the expectations of being able to manage alcohol use in a wide range of settings. Also, the perceived invincibility among youth stands in sharp contrast to their high rates of traumatic events involving alcohol. The paper by Barbara Leigh examines the nature and dimensions of risk-taking particularly among young adults. For example, her analysis encourages us to look beyond preliminary associations about the proportion of certain events where drinking was involved, and consider whether drinking was a correlate or a contributing cause. The paper by James Mosher points to the importance of obtaining information about the population, situation and drinker as a basis for population-level interventions, involving environmental changes in the promotion and distribution of alcoholic beverages. The papers point to a search for interventions that are distinguished by their effectiveness in reducing harm, and not necessarily by their faddish value. An essential step is drawing the younger drinker into an accurate documentation of risk-taking experiences, and also in collaborating in developing humane, reasonable and effective approaches in reducing drinking-related harm.

Adolescent↗
PubMed2002

Autism, an extreme challenge to integrative medicine. Part: 1: The knowledge base.

Autism, archetype of the autistic spectrum disorders (ASD), is a neurodevelopmental disorder characterized by socially aloof behavior and impairment of language and social interaction. Its prevalence has surged in recent years. Advanced functional brain imaging has confirmed pervasive neurologic involvement. Parent involvement in autism management has accelerated understanding and treatment. Often accompanied by epilepsy, cognitive deficits, or other neurologic impairment, autism manifests in the first three years of life and persists into adulthood. Its etiopathology is poorly defined but likely multifactorial with heritability playing a major role. Prenatal toxic exposures (teratogens) are consistent with autism spectrum symptomatology. Frequent vaccinations with live virus and toxic mercurial content (thimerosal) are a plausible etiologic factor. Autistic children frequently have abnormalities of sulfoxidation and sulfation that compromise liver detoxification, which may contribute to the high body burden of xenobiotics frequently found. Frequent copper-zinc imbalance implies metallothionein impairment that could compound the negative impact of sulfur metabolism impairments on detoxification and on intestinal lining integrity. Intestinal hyperpermeability manifests in autistic children as dysbiosis, food intolerances, and exorphin (opioid) intoxication, most frequently from casein and gluten. Immune system abnormalities encompass derangement of antibody production, skewing of T cell subsets, aberrant cytokine profiles, and other impairments consistent with chronic inflammation and autoimmunity. Coagulation abnormalities have been reported. Part 2 of this review will attempt to consolidate progress in integrative management of autism, aimed at improving independence and lifespan for people with the disorder.

Autistic Disorder↗
PubMed1997

Knowledge-based modeling of a bacterial dichloromethane dehalogenase.

A three-dimensional structural model of the dichloromethane dehalogenase (DCMD) from Methylophilus sp. DM11 is constructed based on sequence similarities to the glutathione S-transferases (GSTs). To maximize sequence identity and minimize gaps in the alignment, a hybrid approach is used that takes advantage of the increased homology found between DM11 and domain I of the sheep blowfly theta class GST (residues 1-79) and domain II of the human alpha class GST (residues 81-222). The resulting structure has C alpha root mean square deviations of 1.16 A in domain I and 1.83 A in domain II from the template GSTs, which compare well to those seen in other GST inter-class comparisons. The model is further applied to explore the structural basis for substrate binding and catalysis. A conserved network of hydrogen bonds is described that binds glutathione to the G site, placing the thiol group in a suitable location for nucleophilic attack of dichloromethane. A mechanism is proposed that involves activation through a hydrogen bond interaction between Ser12 and glutathione, similar to that found in the theta-GSTs. The model also demonstrates how aromatic residues in the hydrophobic site (H site) could play a role in promoting catalysis: His116 and Trp117 are ideally situated to accept a growing negative charge on a chlorine of dichloromethane, stabilizing displacement. This scheme is consistent with experimental results of single-point mutations and comparisons with other GST structures and mechanisms.

Amino Acid Sequence↗
PubMed1999

Knowledge-based interaction potentials for proteins.

We discuss the derivation of atomic-level potentials of mean force from the known protein structures and their applicability for structural evaluation applications. In the derivation process, rigorous density estimation methodology is used to estimate the probability density functions (PDFs) for the distributions of interatomic distances in the protein structures. Potentials of mean force are then derived from these density functions using simple Boltzmann's relation. We also test the potentials against pairs of current and superseded protein structures in the Protein Data Bank. Using PDF potentials to evaluate each structure pair, we are able to identify, with high accuracy, which of the two structures is of higher resolution or better quality. This result shows that the PDF potentials are sensitive to details in protein structures as the current and superseded atomic coordinates generally do not differ by more than 1 A in root-mean-square deviation, and that the PDF potentials could potentially be used for X-ray structure refinement and protein structure prediction.

Databases, Factual↗
PubMed1993

Knowledge-based model building of proteins: concepts and examples.

We describe how to build protein models from structural templates. Methods to identify structural similarities between proteins in cases of significant, moderate to low, or virtually absent sequence similarity are discussed. The detection and evaluation of structural relationships is emphasized as a central aspect of protein modeling, distinct from the more technical aspects of model building. Computational techniques to generate and complement comparative protein models are also reviewed. Two examples, P-selectin and gp39, are presented to illustrate the derivation of protein model structures and their use in experimental studies.

Amino Acid Sequence↗
PubMed2003

Data mining crystallization databases: knowledge-based approaches to optimize protein crystal screens.

Protein crystallization is a major bottleneck in protein X-ray crystallography, the workhorse of most structural proteomics projects. Because the principles that govern protein crystallization are too poorly understood to allow them to be used in a strongly predictive sense, the most common crystallization strategy entails screening a wide variety of solution conditions to identify the small subset that will support crystal nucleation and growth. We tested the hypothesis that more efficient crystallization strategies could be formulated by extracting useful patterns and correlations from the large data sets of crystallization trials created in structural proteomics projects. A database of crystallization conditions was constructed for 755 different proteins purified and crystallized under uniform conditions. Forty-five percent of the proteins formed crystals. Data mining identified the conditions that crystallize the most proteins, revealed that many conditions are highly correlated in their behavior, and showed that the crystallization success rate is markedly dependent on the organism from which proteins derive. Of the proteins that crystallized in a 48-condition experiment, 60% could be crystallized in as few as 6 conditions and 94% in 24 conditions. Consideration of the full range of information coming from crystal screening trials allows one to design screens that are maximally productive while consuming minimal resources, and also suggests further useful conditions for extending existing screens.

Archaeal Proteins↗
PubMed1995

Knowledge-based protein secondary structure assignment.

We have developed an automatic algorithm STRIDE for protein secondary structure assignment from atomic coordinates based on the combined use of hydrogen bond energy and statistically derived backbone torsional angle information. Parameters of the pattern recognition procedure were optimized using designations provided by the crystallographers as a standard-of-truth. Comparison to the currently most widely used technique DSSP by Kabsch and Sander (Biopolymers 22:2577-2637, 1983) shows that STRIDE and DSSP assign secondary structural states in 58 and 31% of 226 protein chains in our data sample, respectively, in greater agreement with the specific residue-by-residue definitions provided by the discoverers of the structures while in 11% of the chains, the assignments are the same. STRIDE delineates every 11th helix and every 32nd strand more in accord with published assignments.

Algorithms↗
PubMed1994

Factors influencing the ability of knowledge-based potentials to identify native sequence-structure matches.

Several types of potentials are derived from a dataset of known protein structures by computing statistical relations between amino acid sequence and different descriptions of the protein conformation. These potentials formulate in different ways backbone dihedral angle preferences, pairwise distance-dependent interactions between amino acid residues, and solvation effects based on accessible surface area calculations. Parameters affecting the characteristics and the performance of the potentials are critically assessed by monitoring recognition of the native fold in a strict screening test, where each sequence in the dataset is threaded through a repertoire of motifs, generated from all corresponding structures. Sequence gaps are not allowed, to avoid additional approximations. Results show that residue interaction potentials computed from distances between average side-chain centroids perform significantly better on this test than those computed considering inter-C alpha or inter-C beta distances. Combining potentials that are based on different structural descriptions and different interactions is also beneficial. The performance of some of these potentials is in fact so good that they recognize the correct fold for all the tested proteins, including subunits known to be unstable in the absence of quaternary interactions. Most strikingly, potentials representing backbone dihedral angle preferences recognize as many as 68 protein chains out of a total of 74, even though they consider solely local interactions along the chain, which, being the same as those considered in secondary structure prediction methods, are well known to be incapable of determining the full three-dimensional fold. This leads us to question the ability of procedures that screen a limited repertoire of structures to act as a stringent test for the potentials. We concede, however, that they are useful and fast tests, capable of revealing gross shortcomings of the potentials, or possible biases towards native recognition due, for example, to effects of sequence memory.

Algorithms↗
PubMed1999

SuperStar: a knowledge-based approach for identifying interaction sites in proteins.

An empirical method for identifying interaction sites in proteins is described and validated. The method is based entirely on experimental information about non-bonded interactions occurring in small-molecule crystal structures. These data are used in the form of scatterplots that show the experimentally observed distribution of one functional group (the "contact group" or "probe") around another. A template molecule (e.g. a protein binding site) is broken down into structure fragments and the scatterplots, showing the distribution of a chosen probe around these structure fragments, are superimposed on the corresponding parts of the template. The scatterplots are then translated into a three-dimensional map that shows the propensity of the probe at different positions around the template molecule. The method is illustrated for l -arabinose-binding protein, complexed with l -arabinose and with d -fucose, and for dihydrofolate reductase complexed with methotrexate. The method is validated on 122 X-ray structures of protein-ligand complexes. For all the binding sites of these proteins, propensity maps are generated for four different probes: a charged NH+3nitrogen, a carbonyl oxygen, a hydroxyl oxygen and a methyl carbon atom. Next, the maps are compared with the experimentally observed positions of ligand atoms of these types. For 74% of these ligand atoms (84% of the solvent-inaccessible ones) the calculated propensity of the matching probe at the experimental positions is higher than expected by chance. For 68% of the atoms (82% of the solvent-inaccessible ones) the propensity of the matching probe is higher than that of the other three probes. These results indicate that the approach generally gives good predictions for protein-ligand interactions. The potential applications of the propensity maps range from an aid in manual docking and structure-based drug design to their use in pharmacophore development.

Artificial Intelligence↗
PubMed1999

Ab initio fold prediction of small helical proteins using distance geometry and knowledge-based scoring functions.

The problem of protein tertiary structure prediction from primary sequence can be separated into two subproblems: generation of a library of possible folds and specification of a best fold given the library. A distance geometry procedure based on random pairwise metrization with good sampling properties was used to generate a library of 500 possible structures for each of 11 small helical proteins. The input to distance geometry consisted of sets of restraints to enforce predicted helical secondary structure and a generic range of 5 to 11 A between predicted contact residues on all pairs of helices. For each of the 11 targets, the resulting library contained structures with low RMSD versus the native structure. Near-native sampling was enhanced by at least three orders of magnitude compared to a random sampling of compact folds. All library members were scored with a combination of an all-atom distance-dependent function, a residue pair-potential, and a hydrophobicity function. In six of the 11 cases, the best-ranking fold was considered to be near native. Each library was also reduced to a final ab initio prediction via consensus distance geometry performed over the 50 best-ranking structures from the full set of 500. The consensus results were of generally higher quality, yielding six predictions within 6.5 A of the native fold. These favorable predictions corresponded to those for which the correlation between the RMSD and the scoring function were highest. The advantage of the reported methodology is its extreme simplicity and potential for including other types of structural restraints.

Protein Folding↗
PubMed2001

SuperStar: improved knowledge-based interaction fields for protein binding sites.

SuperStar is an empirical method for identifying interaction sites in proteins, based entirely on experimental information about non-bonded interactions occurring in small-molecule crystal structures, taken from the IsoStar database. We describe recent modifications and additions to SuperStar, validating the results on a test set of 122 X-ray structures of protein-ligand complexes. In this validation, propensity maps are generated for all the binding sites of these proteins, using four different probes: a charged NH(+)(3) nitrogen atom, a carbonyl oxygen atom, a hydroxyl oxygen atom and a methyl carbon atom. Next, the maps are compared with the experimentally observed positions of ligand atoms of these types. A peak-searching algorithm is introduced that highlights potential interaction hot spots. For the three hydrogen-bonding probes - NH(+)(3) nitrogen atom, carbonyl oxygen atom and hydroxyl oxygen atom - the average distance from the ligand atom to the nearest SuperStar peak is 1.0-1.2 A (0.8-1.0 A for solvent-inaccessible ligand atoms). For the methyl carbon atom probe, this distance is about 1.5 A, probably because interactions to methyl groups are much less directional. The most important addition to SuperStar is the enabling of propensity maps around metal centres - Ca(2+), Mg(2+) and Zn(2+) - in protein binding sites. The results are validated on a test set of 24 protein-ligand complexes that have a metal ion in their binding site. Coordination geometries are derived automatically, using only the protein atoms that coordinate to the metal ion. The correct coordination geometry is derived in approximately 75 % of the cases. If the derived geometry is assumed during the SuperStar calculation, the average distance from a ligand atom coordinating to the metal ion to the nearest peak in the propensity map for an oxygen probe is 0.87(7) A. If the correct coordination geometry is imposed, this distance reduces to 0.59(7)A. This indicates that the SuperStar predictions around metal-binding sites are at least as good as those around other protein groups. Using clustering techniques, a non-redundant set of probes is selected from the set of probes available in the IsoStar database. The performance in SuperStar of all these probes is tested on the test set of protein-ligand complexes. With the exception of the "ether oxygen" probe and the "any NH(+)" probe, all new probes perform as well as the four probes introduced first.

Algorithms↗
PubMed1982

Knowledge-based acquisition of rules for medical diagnosis.

Medical consultation systems in the EXPERT framework contain rules written under the guidance of expert physicians. We present a methodology and preliminary implementation of a system that learns compiled rule chains from positive case examples of a diagnostic class and negative examples of alternative diagnostic classes. Rule acquisition is guided by the constraints of physiological process models represented in the system. Evaluation of the system is proceeding in the area of glaucoma diagnosis, and an example of an experiment in this domain is included.

Diagnosis, Computer-Assisted↗