An examination of Cultural Competence Training in US Medical Education Guided by the Tool for Assessing Cultural Competence Training

In the United States, medical students must demonstrate a standard level of “cultural competence,” upon graduation. Cultural competence is most often defined as a set of congruent behaviors, attitudes, and policies that come together in systems, organizations, and among professionals to enable effective work in cross-cultural situations. The Association of American Medical Colleges developed the Tool for Assessing Cultural Competence Training (TACCT) to assist schools in developing and evaluating cultural competence curricula to meet these requirements. This review uses the TACCT as a guideline to describe and assess pedagogical approaches to cultural competence training in US medical education and identify content gaps and opportunities for curriculum improvement. A total of 18 programs are assessed. Findings support previous research that cultural competence training can improve the knowledge, attitudes, and skills of medical trainees. However, wide variation in the conceptualization, implementation, and evaluation of cultural competence training programs exists, leading to differences in training quality and outcomes. More research is needed to establish optimal approaches to implementing and evaluating cultural competence training that incorporate cultural humility, the social determinants of health, and broader structural competency within the medical system

When Alcoholism Affects Memory Functions: MRI of the Brain.

The development of modern imaging techniques makes it possible to examine directly the relationship between brain abnormalities and memory impairment. Alcoholic amnesics may perform normally on certain tests (priming tasks) that require implicit (unconscious) memory, even though they may not be able consciously to recall the memory. Researchers have therefore postulated the existence of multiple memory mechanisms. Magnetic resonance imaging (MRI) observations suggest that independent memory mechanisms are not necessary to explain the dissociation between explicit and implicit memory. Alcoholic amnesics appear to suffer from damage to structures in two areas of the brain, affecting two separate processing components that are both required in most priming tasks: a stimulus processing component and a memory processing component

Identifying Interaction Sites in "Recalcitrant" Proteins: Predicted Protein and Rna Binding Sites in Rev Proteins of Hiv-1 and Eiav Agree with Experimental Data

Protein-protein and protein nucleic acid interactions are vitally important for a wide range of biological processes, including regulation of gene expression, protein synthesis, and replication and assembly of many viruses. We have developed machine learning approaches for predicting which amino acids of a protein participate in its interactions with other proteins and/or nucleic acids, using only the protein sequence as input. In this paper, we describe an application of classifiers trained on datasets of well-characterized protein-protein and protein-RNA complexes for which experimental structures are available. We apply these classifiers to the problem of predicting protein and RNA binding sites in the sequence of a clinically important protein for which the structure is not known: the regulatory protein Rev, essential for the replication of HIV-1 and other lentiviruses. We compare our predictions with published biochemical, genetic and partial structural information for HIV-1 and EIAV Rev and with our own published experimental mapping of RNA binding sites in EIAV Rev. The predicted and experimentally determined binding sites are in very good agreement. The ability to predict reliably the residues of a protein that directly contribute to specific binding events - without the requirement for structural information regarding either the protein or complexes in which it participates - can potentially generate new disease intervention strategies.Comment: Pacific Symposium on Biocomputing, Hawaii, In press, Accepted, 200

vGNM: a Better Model for Understanding the Dynamics of Proteins in Crystals

The dynamics of proteins are important for understanding their functions. In recent years, the simple coarse-grained Gaussian Network Model (GNM) has been fairly successful in interpreting crystallographic B-factors. However, the model clearly ignores the contribution of the rigid body motions and the effect of crystal packing. The model cannot explain the fact that the same protein may have significantly different B-factors under different crystal packing conditions. In this work, we propose a new Gaussian network model, called vGNM, which takes into account both the contribution of the rigid body motions and the effect of crystal packing, by allowing the amplitude of the internal modes to be variables. It hypothesizes that the effect of crystal packing should cause some modes to be amplified, and others to become less feasible. In doing so, vGNM is able to resolve the apparent discrepancy in experimental B-factors among structures of the same protein but with different crystal packing conditions, which GNM cannot explain. With a small number of parameters, vGNM is able to reproduce experimental B-factors for a large set of proteins with significantly better correlations (having a mean value of 0.81 as compared to 0.59 by GNM). The results of applying vGNM also show that the rigid body motions account for nearly 60% of the total fluctuations, in good agreement with previous findings

Discovery of kHz Fluctuations in Centaurus X-3: Evidence for Photon Bubble Oscillations (PBO) and Turbulence in a High Mass X-ray Binary Pulsar

We report the discovery of kHz fluctuations, including quasi-periodic oscillations (QPO) at ~330 Hz and ~760 Hz and a broadband kHz continuum in the power density spectrum of the high mass X-ray binary pulsar Centaurus X-3. These observations of Cen X-3 were carried out with the Rossi X-ray Timing Explorer (RXTE). The fluctuation spectrum is flat from mHz to a few Hz, then steepens to $f^{-2}$ behavior between a few Hz and ~100 Hz. Above a hundred Hz, the spectrum shows the QPO features, plus a flat continuum extending to ~1200 Hz and then falling out to ~1800 Hz. These results, which required the co-adding three days of observations of Cen X-3, are at least as fast as the fastest known variations in X-ray emission from an accreting compact object (kHz QPO in LMXB sources) and probably faster since extension to ~1800 Hz is indicated by the most likely parameterization of the data. Multi-dimensional radiation hydrodynamics simulations of optically thick plasma flow onto the magnetic poles of an accreting neutron star show that the fluctuations at frequencies above 100 Hz are consistent with photon bubble turbulence and oscillations (PBO) previously predicted to be observable in this source. For a polar cap opening angle of 0.25 radians, we show that the spectral form above 100 Hz is reproduced by the simulations, including the frequencies of the QPO and the relative power in the QPO and the kHz continuum. This has resulted in the first model-dependent measurement of the polar cap size of an X-ray pulsar.Comment: received ApJ: April 1, 1999 accepted ApJ: September 1, 199

Combining Disparate Data Types: Protein Sequences and Protein Structures

With the development of high-throughput, next-generation sequencing and other advanced technologies, a large number of gene expression profiles have been produced. Many of these profiles are available from public databases [1-3]. A challenging research problem that has drawn a lot of attention in the past is to infer gene regulatory networks from the expression data. A gene regulatory network is represented by a directed graph, in which nodes represent transcription factors or mRNA with edges showing transcriptional regulatory relationships between two nodes

Long- and short-range interactions in native protein structures are consistent/minimally frustrated in sequence space

We show that long- and short-range interactions in almost all protein native structures are actually consistent with each other for coarse-grained energy scales; specifically we mean the long-range inter-residue contact energies and the short-range secondary structure energies based on peptide dihedral angles, which are potentials of mean force evaluated from residue distributions observed in protein native structures. This consistency is observed at equilibrium in sequence space rather than in conformational space. Statistical ensembles of sequences are generated by exchanging residues for each of 797 protein native structures with the Metropolis method. It is shown that adding the other category of interaction to either the short- or long-range interactions decreases the means and variances of those energies for essentially all protein native structures, indicating that both interactions consistently work by more-or-less restricting sequence spaces available to one of the interactions. In addition to this consistency, independence by these interaction classes is also indicated by the fact that there are almost no correlations between them when equilibrated using both interactions and significant but small, positive correlations at equilibrium using only one of the interactions. Evidence is provided that protein native sequences can be regarded approximately as samples from the statistical ensembles of sequences with these energy scales and that all proteins have the same effective conformational temperature. Designing protein structures and sequences to be consistent and minimally frustrated among the various interactions is a most effective way to increase protein stability and foldability

Elastic network models capture the motions apparent within ensembles of RNA structures

The role of structure and dynamics in mechanisms for RNA becomes increasingly important. Computational approaches using simple dynamics models have been successful at predicting the motions of proteins and are often applied to ribonucleo-protein complexes but have not been thoroughly tested for well-packed nucleic acid structures. In order to characterize a true set of motions, we investigate the apparent motions from 16 ensembles of experimentally determined RNA structures. These indicate a relatively limited set of motions that are captured by a small set of principal components (PCs). These limited motions closely resemble the motions computed from low frequency normal modes from elastic network models (ENMs), either at atomic or coarse-grained resolution. Various ENM model types, parameters, and structure representations are tested here against the experimental RNA structural ensembles, exposing differences between models for proteins and for folded RNAs. Differences in performance are seen, depending on the structure alignment algorithm used to generate PCs, modulating the apparent utility of ENMs but not significantly impacting their ability to generate functional motions. The loss of dynamical information upon coarse-graining is somewhat larger for RNAs than for globular proteins, indicating, perhaps, the lower cooperativity of the less densely packed RNA. However, the RNA structures show less sensitivity to the elastic network model parameters than do proteins. These findings further demonstrate the utility of ENMs and the appropriateness of their application to well-packed RNA-only structures, justifying their use for studying the dynamics of ribonucleo-proteins, such as the ribosome and regulatory RNAs

SeqStruct : A New Amino Acid Similarity Matrix Based on Sequence Correlations and Structural Contacts Yields Sequence-Structure Congruence

Protein sequence matching does not properly account for some well-known features of protein structures: surface residues being more variable than core residues, the high packing densities in globular proteins, and does not yield good matches of sequences of many proteins known to be close structural relatives. There are now abundant protein sequences and structures to enable major improvements to sequence matching. Here, we utilize structural frameworks to mount the observed correlated sequences to identify the most important correlated parts. The rationale is that protein structures provide the important physical framework for improving sequence matching. Combining the sequence and structure data in this way leads to a simple amino acid substitution matrix that can be readily incorporated into any sequence matching. This enables the incorporation of allosteric information into sequence matching and transforms it effectively from a 1-D to a 3-D procedure. The results from testing in over 3,000 sequence matches demonstrate a 37% gain in sequence similarity and a loss of 26% of the gaps when compared with the use of BLOSUM62. And, importantly there are major gains in the specificity of sequence matching across diverse proteins. Specifically, all known cases where protein structures match but sequences do not match well are resolved