Drugs, Devices, and Desires: A Problem-based Learning Course in the History of Medicine

Problem-based learning (PBL) is well suited for courses in the history of medicine, where multiple perspectives exist and information has to be gleaned from different sources. A student, an archivist, and a teacher offer three perspectives about a senior level course where students explored the antecedents and consequences of medical technology. Two active learning strategies were used: (a) PBL to explore the historical basis of procedures used to diagnose, prevent and treat a single disease, tuberculosis, and (b) a concurrent inquiry-based component that permitted individual exploration of other medical technologies and demonstration of learning through diverse options (book reviews, conversations, essays, archival research, oral exams). This course was highly rated by students with an overall rating of 9.5 ± 0.7 (36 students from 2008–2012)

An Improved Algorithm for Neural Network Classification of Imbalanced Training Sets

In this paper, we analyze the reason for the slow rate of convergence of net output error when using the backpropagation algorithm to train neural networks for a two-class problems in which the numbers of exemplars for the two classes differ greatly. This occurs because the negative gradient vector computed by backpropagation for an imbalanced training set does not point initially in a downhill direction for the class with the smaller number of exemplars. Consequently, in the initial iteration, the net error for the exemplars in this class increases significantly. The subsequent rate of convergence of the net error is very low. We suggest a modified technique for calculating a direction in weight-space which is downhill for both classes. Using this algorithm, we have been able to accelerate the rate of learning for two-class classification problems by an order of magnitude

An Efficient Neural Algorithm for the Multiclass Problem

One connectionist approach to the classification problem, which has gained popularity in recent years, is the use of backpropagation-trained feed-forward neural networks. In practice, however, we find that the rate of convergence of net output error is especially low when training networks for multi-class problems. In this paper, we show that while backpropagation will reduce the Euclidean distance between the actual and desired output vectors, the difference between some of the components of these vectors will actually increase in the first iteration. Furthermore, the magnitudes of subsequent weight changes in each iteration are very small, so that many iterations are required to compensate for the increased error in some components in the initial iterations. We describe a modular network architecture to improve the rate of learning for such classification problems. Our basic approach is to reduce a K-class problem to set of K two-class problems with a separately trained network for each of the K problems. We also present the results from several experiments comparing our new algorithm and approach with standard backpropagation, and find that speedups of about one order of magnitude can be obtained

Protein phosphatase beta, a putative type-2A protein phosphatase from the human malaria parasite Plasmodium falciparum.

Protein phosphatases play a critical role in the regulation of the eukaryotic cell cycle and signal transduction. A putative protein serine/threonine phosphatase gene has been isolated from the human malaria parasite Plasmodium falciparum. The gene has an unusual intron that contains four repeats of 32 nucleotides and displays a high degree of size polymorphism among different strains of P. falciparum. The open reading frame reconstituted by removal of the intron encodes a protein of 466 amino acids with a predicted molecular mass of approximately 53.7 kDa. The encoded protein, termed protein phosphatase beta (PP-beta), is composed of two distinct domains. The C-terminal domain comprises 315 amino acids and exhibits a striking similarity to the catalytic subunits of the type-2A protein phosphatases. Database searches revealed that the catalytic domain has the highest similarity to Schizosaccharomyces pombe Ppa1 (58% identity and 73% similarity). However, it contains a hydrophilic insert consisting of five amino acids. The N-terminal domain comprises 151 amino acid residues and exhibits several striking features, including high levels of charged amino acids and asparagine, and multiple consensus phosphorylation sites for a number of protein kinases. An overall structural comparison of PP-beta with other members of the protein phosphatase 2A group revealed that PP-beta is more closely related to Saccharomyces cerevisiae PPH22. Southern blots of genomic DNA digests and chromosomal separations showed that PP-beta is a single-copy gene and is located on chromosome 9. A 2800-nucleotide transcript of this gene is expressed specifically in the sexual erythrocytic stage (gametocytes). The results indicate that PP-beta may be involved in sexual stage development

Do coder characteristics influence validity of ICD-10 hospital discharge data?

<p>Abstract</p> <p>Background</p> <p>Administrative data are widely used to study health systems and make important health policy decisions. Yet little is known about the influence of coder characteristics on administrative data validity in these studies. Our goal was to describe the relationship between several measures of validity in coded hospital discharge data and 1) coders' volume of coding (≥13,000 vs. <13,000 records), 2) coders' employment status (full- vs. part-time), and 3) hospital type.</p> <p>Methods</p> <p>This descriptive study examined 6 indicators of face validity in ICD-10 coded discharge records from 4 hospitals in Calgary, Canada between April 2002 and March 2007. Specifically, mean number of coded diagnoses, procedures, complications, Z-codes, and codes ending in 8 or 9 were compared by coding volume and employment status, as well as hospital type. The mean number of diagnoses was also compared across coder characteristics for 6 major conditions of varying complexity. Next, kappa statistics were computed to assess agreement between discharge data and linked chart data reabstracted by nursing chart reviewers. Kappas were compared across coder characteristics.</p> <p>Results</p> <p>422,618 discharge records were coded by 59 coders during the study period. The mean number of diagnoses per record decreased from 5.2 in 2002/2003 to 3.9 in 2006/2007, while the number of records coded annually increased from 69,613 to 102,842. Coders at the tertiary hospital coded the most diagnoses (5.0 compared with 3.9 and 3.8 at other sites). There was no variation by coder or site characteristics for any other face validity indicator. The mean number of diagnoses increased from 1.5 to 7.9 with increasing complexity of the major diagnosis, but did not vary with coder characteristics. Agreement (kappa) between coded data and chart review did not show any consistent pattern with respect to coder characteristics.</p> <p>Conclusions</p> <p>This large study suggests that coder characteristics do not influence the validity of hospital discharge data. Other jurisdictions might benefit from implementing similar employment programs to ours, e.g.: a requirement for a 2-year college training program, a single management structure across sites, and rotation of coders between sites. Limitations include few coder characteristics available for study due to privacy concerns.</p

Aging diminishes the resistance of AO rats to EAE: putative role of enhanced generation of GM-CSF Expressing CD4+T cells in aged rats

Background: Aging influences immune response and susceptibility to EAE in a strain specific manner. The study was designed to examine influence of aging on EAE induction in Albino Oxford (AO) rats. Results: Differently from 3-month-old (young) rats, which were resistant to EAE induction, the majority of aged (24-26-month-old) rats developed mild chronic form of EAE. On 16th day post-immunization, when in aged rats the neurological deficit reached plateau, more mononuclear cells, including CD4+ T lymphocytes was retrieved from spinal cord of aged than young rats. The frequencies of IL-17+ and GM-CSF+ cells within spinal cord infiltrating CD4+ lymphocytes were greater in aged rats. To their increased frequency contributed the expansion of GM-CSF + IL-17 + IFN-gamma+ cells, which are highly pathogenic in mice. The expression of the cytokines (IL-1 beta and IL-23/p19) driving GM-CSF + IL-17 + IFN-gamma + cell differentiation in mice was also augmented in aged rat spinal cord mononuclear cells. Additionally, in aged rat spinal cord the expansion of GM-CSF + IL-17-IFN-gamma- CD4+ T lymphocytes was found. Consistently, the expression of mRNAs for IL-3, the cytokine exhibiting the same expression pattern as GM-CSF, and IL-7, the cytokine driving differentiation of GM-CSF + IL-17-IFN-gamma- CD4 + lymphocytes in mice, was upregulated in aged rat spinal cord mononuclear cells, and the tissue, respectively. This was in accordance with the enhanced generation of the brain antigen-specific GM-CSF+ CD4+ lymphocytes in aged rat draining lymph nodes, as suggested by (i) the higher frequency of GM-CSF+ cells (reflecting the expansion of IL-17-IFN-gamma- cells) within their CD4+ lymphocytes and (ii) the upregulated GM-CSF and IL-3 mRNA expression in fresh CD4+ lymphocytes and MBP-stimulated draining lymph node cells and IL-7 mRNA in lymph node tissue from aged rats. In agreement with the upregulated GM-CSF expression in aged rats, strikingly more CD11b + CD45(int) (activated microglia) and CD45(hi) (mainly proinflammatory dendritic cells and macrophages) cells was retrieved from aged than young rat spinal cord. Besides, expression of mRNA for SOCS1, a negative regulator of proinflammatory cytokine expression in innate immunity cells, was downregulated in aged rat spinal cord mononuclear cells. Conclusions: The study revealed that aging may overcome genetic resistance to EAE, and indicated the cellular and molecular mechanisms contributing to this phenomenon in AO rats

T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection.

The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence. Here we show that a transcriptional signature reflecting CD8 T-cell exhaustion is associated with poor clearance of chronic viral infection, but conversely predicts better prognosis in multiple autoimmune diseases. The development of CD8 T-cell exhaustion during chronic infection is driven both by persistence of antigen and by a lack of accessory 'help' signals. In autoimmunity, we find that where evidence of CD4 T-cell co-stimulation is pronounced, that of CD8 T-cell exhaustion is reduced. We can reproduce the exhaustion signature by modifying the balance of persistent stimulation of T-cell antigen receptors and specific CD2-induced co-stimulation provided to human CD8 T cells in vitro, suggesting that each process plays a role in dictating outcome in autoimmune disease. The 'non-exhausted' T-cell state driven by CD2-induced co-stimulation is reduced by signals through the exhaustion-associated inhibitory receptor PD-1, suggesting that induction of exhaustion may be a therapeutic strategy in autoimmune and inflammatory disease. Using expression of optimal surrogate markers of co-stimulation/exhaustion signatures in independent data sets, we confirm an association with good clinical outcome or response to therapy in infection (hepatitis C virus) and vaccination (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (type 1 diabetes, anti-neutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, idiopathic pulmonary fibrosis and dengue haemorrhagic fever). Thus, T-cell exhaustion plays a central role in determining outcome in autoimmune disease and targeted manipulation of this process could lead to new therapeutic opportunities