Rheumatoid nodule of the thyrohyoid membrane: a case report

BACKGROUND: Rheumatoid nodules are common extra-articular findings occurring in 20% of rheumatoid arthritis patients. They develop most commonly subcutaneously in pressure areas (elbows and finger joints) and may occasionally affect internal organs including pleura, lungs, meninges, larynx, and in other connective tissues elsewhere in the body CASE PRESENTATION: We present the case of a 62-year-old male who presented with a midline neck mass. Clinically it moved on swallowing and tongue protrusion-suggesting attachment to the thyrohyoid membrane. Ultrasound examination revealed a cystic lesion in the absence of cervical lymphadenopathy in a non-smoker. The neck was explored and histological examination of the excised lesion which was attached to the thyrohyoid membrane revealed a rheumatoid nodule. CONCLUSION: A rheumatoid nodule of the thyrohyoid membrane is very rare. The triple diagnostic scheme of clinical examination supplemented with ultrasound and guided fine needle aspiration for neck lumps remains valid in most cases. If excision is indicated we feel it should be performed in such a manner that the scar tract could easily be encompassed in a neck dissection excision should definitive histological examination be adverse. We suggest that when dealing with patients with established rheumatoid arthritis one should consider a rheumatoid nodule as a differential diagnosis for any swelling on the patient whether it be subcutaneous or deep

Predicting a small molecule-kinase interaction map: A machine learning approach

<p>Abstract</p> <p>Background</p> <p>We present a machine learning approach to the problem of protein ligand interaction prediction. We focus on a set of binding data obtained from 113 different protein kinases and 20 inhibitors. It was attained through ATP site-dependent binding competition assays and constitutes the first available dataset of this kind. We extract information about the investigated molecules from various data sources to obtain an informative set of features.</p> <p>Results</p> <p>A Support Vector Machine (SVM) as well as a decision tree algorithm (C5/See5) is used to learn models based on the available features which in turn can be used for the classification of new kinase-inhibitor pair test instances. We evaluate our approach using different feature sets and parameter settings for the employed classifiers. Moreover, the paper introduces a new way of evaluating predictions in such a setting, where different amounts of information about the binding partners can be assumed to be available for training. Results on an external test set are also provided.</p> <p>Conclusions</p> <p>In most of the cases, the presented approach clearly outperforms the baseline methods used for comparison. Experimental results indicate that the applied machine learning methods are able to detect a signal in the data and predict binding affinity to some extent. For SVMs, the binding prediction can be improved significantly by using features that describe the active site of a kinase. For C5, besides diversity in the feature set, alignment scores of conserved regions turned out to be very useful.</p

The Distribution of Dust and Gas in Elliptical Galaxies

Results from IRAS and recent optical CCD surveys are examined to discuss the distribution and origin of dust and ionized gas in elliptical galaxies. In strong contrast with the situation among spiral galaxies, masses of dust in elliptical galaxies as derived from optical extinction are an order of magnitude LOWER than those derived from IRAS data. I find that this dilemma can be resolved by assuming the presence of a diffusely distributed component of dust which is not detectable in optical data. The morphology of dust lanes and their association with ionized gas in elliptical galaxies argues for an external origin of BOTH components of the ISM.Comment: Invited talk given at conference on "NEW EXTRAGALACTIC PERSPECTIVES IN THE NEW SOUTH AFRICA: Changing Perceptions of the Morphology, Dust Content and Dust-Gas Ratios in Galaxies", Held in Johannesburg, South Africa, during January 22-26, 1996. Proceedings will be edited by D.L. Block and published by Kluwer, Dordrecht, The Netherlands. uuencoded, gzipped LaTeX file of 8 pages; figures included as PostScript files (enclosed). Uses crckapb.sty (enclosed) and psfig.st

Clusters of galaxies : observational properties of the diffuse radio emission

Clusters of galaxies, as the largest virialized systems in the Universe, are ideal laboratories to study the formation and evolution of cosmic structures...(abridged)... Most of the detailed knowledge of galaxy clusters has been obtained in recent years from the study of ICM through X-ray Astronomy. At the same time, radio observations have proved that the ICM is mixed with non-thermal components, i.e. highly relativistic particles and large-scale magnetic fields, detected through their synchrotron emission. The knowledge of the properties of these non-thermal ICM components has increased significantly, owing to sensitive radio images and to the development of theoretical models. Diffuse synchrotron radio emission in the central and peripheral cluster regions has been found in many clusters. Moreover large-scale magnetic fields appear to be present in all galaxy clusters, as derived from Rotation Measure (RM) studies. Non-thermal components are linked to the cluster X-ray properties, and to the cluster evolutionary stage, and are crucial for a comprehensive physical description of the intracluster medium. They play an important role in the cluster formation and evolution. We review here the observational properties of diffuse non-thermal sources detected in galaxy clusters: halos, relics and mini-halos. We discuss their classification and properties. We report published results up to date and obtain and discuss statistical properties. We present the properties of large-scale magnetic fields in clusters and in even larger structures: filaments connecting galaxy clusters. We summarize the current models of the origin of these cluster components, and outline the improvements that are expected in this area from future developments thanks to the new generation of radio telescopes.Comment: Accepted for the publication in The Astronomy and Astrophysics Review. 58 pages, 26 figure

Genotype of metabolic enzymes and the benefit of tamoxifen in postmenopausal breast cancer patients

BACKGROUND: Tamoxifen is widely used as endocrine therapy for oestrogen-receptor-positive breast cancer. However, many of these patients experience recurrence despite tamoxifen therapy by incompletely understood mechanisms. In the present report we propose that tamoxifen resistance may be due to differences in activity of metabolic enzymes as a result of genetic polymorphism. Cytochrome P450 2D6 (CYP2D6) and sulfotransferase 1A1 (SULT1A1) are polymorphic and are involved in the metabolism of tamoxifen. The CYP2D6*4 and SULT1A1*2 genotypes result in decreased enzyme activity. We therefore investigated the genotypes of CYP2D6 and SULT1A1 in 226 breast cancer patients participating in a trial of adjuvant tamoxifen treatment in order to validate the benefit from the therapy. METHODS: The patients were genotyped using PCR followed by cleavage with restriction enzymes. RESULTS: Carriers of the CYP2D6*4 allele demonstrated a decreased risk of recurrence when treated with tamoxifen (relative risk = 0.28, 95% confidence interval = 0.11–0.74, P = 0.0089). A similar pattern was seen among the SULT1A1*1 homozygotes (relative risk = 0.48, 95% confidence interval = 0.21–1.12, P = 0.074). The combination of CYP2D6*4 and/or SULT1A1*1/*1 genotypes comprised 60% of the patients and showed a 62% decreased risk of distant recurrence with tamoxifen (relative risk = 0.38, 95% confidence interval = 0.19–0.74, P = 0.0041). CONCLUSION: The present study suggests that genotype of metabolic enzymes might be useful as a guide for adjuvant endocrine treatment of postmenopausal breast cancer patients. However, results are in contradiction to prior hypotheses and the present sample size is relatively small. Findings therefore need to be confirmed in a larger cohort

Prediction of specificity-determining residues for small-molecule kinase inhibitors

<p>Abstract</p> <p>Background</p> <p>Designing small-molecule kinase inhibitors with desirable selectivity profiles is a major challenge in drug discovery. A high-throughput screen for inhibitors of a given kinase will typically yield many compounds that inhibit more than one kinase. A series of chemical modifications are usually required before a compound exhibits an acceptable selectivity profile. Rationalizing the selectivity profile for a small-molecule inhibitor in terms of the specificity-determining kinase residues for that molecule can be an important step toward the goal of developing selective kinase inhibitors.</p> <p>Results</p> <p>Here we describe S-Filter, a method that combines sequence and structural information to predict specificity-determining residues for a small molecule and its kinase selectivity profile. Analysis was performed on seven selective kinase inhibitors where a structural basis for selectivity is known. S-Filter correctly predicts specificity determinants that were described by independent groups. S-Filter also predicts a number of novel specificity determinants that can often be justified by further structural comparison.</p> <p>Conclusion</p> <p>S-Filter is a valuable tool for analyzing kinase selectivity profiles. The method identifies potential specificity determinants that are not readily apparent, and provokes further investigation at the structural level.</p

The effects of breastfeeding on retinoblastoma development: Results from an international multicenter retinoblastoma survey

The protective effects of breastfeeding on various childhood malignancies have been established but an association has not yet been determined for retinoblastoma (RB). We aimed to further investigate the role of breastfeeding in the severity of nonhereditary RB development, assessing relationship to (1) age at diagnosis, (2) ocular prognosis, measured by International Intraocular RB Classification (IIRC) or Intraocular Classification of RB (ICRB) group and success of eye salvage, and (3) extraocular involvement. Analyses were performed on a global dataset subgroup of 344 RB patients whose legal guardian(s) consented to answer a neonatal questionnaire. Patients with undetermined or mixed feeding history, family history of RB, or sporadic bilateral RB were excluded. There was no statistically significant difference between breastfed and formula-fed groups in (1) age at diagnosis (p = 0.20), (2) ocular prognosis measures of IIRC/ICRB group (p = 0.62) and success of eye salvage (p = 0.16), or (3) extraocular involvement shown by International Retinoblastoma Staging System (IRSS) at presentation (p = 0.74), lymph node involvement (p = 0.20), and distant metastases (p = 0.37). This study suggests that breastfeeding neither impacts the sporadic development nor is associated with a decrease in the severity of nonhereditary RB as measured by age at diagnosis, stage of disease, ocular prognosis, and extraocular spread. A further exploration into the impact of diet on children who develop RB is warranted

Genetic variants of CYP3A5, CYP2D6, SULT1A1, UGT2B15 and tamoxifen response in postmenopausal patients with breast cancer

INTRODUCTION: Tamoxifen therapy reduces the risk of recurrence and prolongs the survival of oestrogen-receptor-positive patients with breast cancer. Even if most patients benefit from tamoxifen, many breast tumours either fail to respond or become resistant. Because tamoxifen is extensively metabolised by polymorphic enzymes, one proposed mechanism underlying the resistance is altered metabolism. In the present study we investigated the prognostic and/or predictive value of functional polymorphisms in cytochrome P450 3A5 CYP3A5 (*3), CYP2D6 (*4), sulphotransferase 1A1 (SULT1A1; *2) and UDP-glucuronosyltransferase 2B15 (UGT2B15; *2) in tamoxifen-treated patients with breast cancer. METHODS: In all, 677 tamoxifen-treated postmenopausal patients with breast cancer, of whom 238 were randomised to either 2 or 5 years of tamoxifen, were genotyped by using PCR with restriction fragment length polymorphism or PCR with denaturing high-performance liquid chromatography. RESULTS: The prognostic evaluation performed in the total population revealed a significantly better disease-free survival in patients homozygous for CYP2D6*4. For CYP3A5, SULT1A1 and UGT2B15 no prognostic significance was observed. In the randomised group we found that for CYP3A5, homozygous carriers of the *3 allele tended to have an increased risk of recurrence when treated for 2 years with tamoxifen, although this was not statistically significant (hazard ratio (HR) = 2.84, 95% confidence interval (CI) = 0.68 to 11.99, P = 0.15). In the group randomised to 5 years' tamoxifen the survival pattern shifted towards a significantly improved recurrence-free survival (RFS) among CYP3A5*3-homozygous patients (HR = 0.20, 95% CI = 0.07 to 0.55, P = 0.002). No reliable differences could be seen between treatment duration and the genotypes of CYP2D6, SULT1A1 or UGT2B15. The significantly improved RFS with prolonged tamoxifen treatment in CYP3A5*3 homozygotes was also seen in a multivariate Cox model (HR = 0.13, CI = 0.02 to 0.86, P = 0.03), whereas no differences could be seen for CYP2D6, SULT1A1 and UGT2B15. CONCLUSION: The metabolism of tamoxifen is complex and the mechanisms responsible for the resistance are unlikely to be explained by a single polymorphism; instead it is a combination of several mechanisms. However, the present data suggest that genetic variation in CYP3A5 may predict response to tamoxifen therapy

A Computational Approach to Finding Novel Targets for Existing Drugs

Repositioning existing drugs for new therapeutic uses is an efficient approach to drug discovery. We have developed a computational drug repositioning pipeline to perform large-scale molecular docking of small molecule drugs against protein drug targets, in order to map the drug-target interaction space and find novel interactions. Our method emphasizes removing false positive interaction predictions using criteria from known interaction docking, consensus scoring, and specificity. In all, our database contains 252 human protein drug targets that we classify as reliable-for-docking as well as 4621 approved and experimental small molecule drugs from DrugBank. These were cross-docked, then filtered through stringent scoring criteria to select top drug-target interactions. In particular, we used MAPK14 and the kinase inhibitor BIM-8 as examples where our stringent thresholds enriched the predicted drug-target interactions with known interactions up to 20 times compared to standard score thresholds. We validated nilotinib as a potent MAPK14 inhibitor in vitro (IC50 40 nM), suggesting a potential use for this drug in treating inflammatory diseases. The published literature indicated experimental evidence for 31 of the top predicted interactions, highlighting the promising nature of our approach. Novel interactions discovered may lead to the drug being repositioned as a therapeutic treatment for its off-target's associated disease, added insight into the drug's mechanism of action, and added insight into the drug's side effects

Generation of ribosome imprinted polymers for sensitive detection of translational responses

Whilst the profiling of the transcriptome and proteome even of single-cells becomes feasible, the analysis of the translatome, which refers to all messenger RNAs (mRNAs) engaged with ribosomes for protein synthesis, is still an elaborate procedure requiring millions of cells. Herein, we report the generation and use of “smart materials”, namely molecularly imprinted polymers (MIPs) to facilitate the isolation of ribosomes and translated mRNAs from merely 1,000 cells. In particular, we show that a hydrogel-based ribosome imprinted polymer could recover ribosomes and associated mRNAs from human, simian and mice cellular extracts, but did not selectively enrich yeast ribosomes, thereby demonstrating selectivity. Furthermore, ribosome imprinted polymers enabled the sensitive measurement of an mRNA translational regulatory event, requiring 1,000-fold less cells than current methodologies. These results provide first evidence for the suitability of MIPs to selectively recover ribonucleoprotein complexes such as ribosomes, founding a novel means for sensitive detection of gene regulation