Effects of insurance status on children's access to specialty care: a systematic review of the literature

<p>Abstract</p> <p>Background</p> <p>The current climate of rising health care costs has led many health insurance programs to limit benefits, which may be problematic for children needing specialty care. Findings from pediatric primary care may not transfer to pediatric specialty care because pediatric specialists are often located in academic medical centers where institutional rules determine accepted insurance. Furthermore, coverage for pediatric specialty care may vary more widely due to systematic differences in inclusion on preferred provider lists, lack of availability in staff model HMOs, and requirements for referral. Our objective was to review the literature on the effects of insurance status on children's access to specialty care.</p> <p>Methods</p> <p>We conducted a systematic review of original research published between January 1, 1992 and July 31, 2006. Searches were performed using Pubmed.</p> <p>Results</p> <p>Of 30 articles identified, the majority use number of specialty visits or referrals to measure access. Uninsured children have poorer access to specialty care than insured children. Children with public coverage have better access to specialty care than uninsured children, but poorer access compared to privately insured children. Findings on the effects of managed care are mixed.</p> <p>Conclusion</p> <p>Insurance coverage is clearly an important factor in children's access to specialty care. However, we cannot determine the structure of insurance that leads to the best use of appropriate, quality care by children. Research about specific characteristics of health plans and effects on health outcomes is needed to determine a structure of insurance coverage that provides optimal access to specialty care for children.</p

Isoforms of U1-70k control subunit dynamics in the human spliceosomal U1 snRNP

Most human protein-encoding genes contain multiple exons that are spliced together, frequently in alternative arrangements, by the spliceosome. It is established that U1 snRNP is an essential component of the spliceosome, in human consisting of RNA and ten proteins, several of which are post- translationally modified and exist as multiple isoforms. Unresolved and challenging to investigate are the effects of these post translational modifications on the dynamics, interactions and stability of the particle. Using mass spectrometry we investigate the composition and dynamics of the native human U1 snRNP and compare native and recombinant complexes to isolate the effects of various subunits and isoforms on the overall stability. Our data reveal differential incorporation of four protein isoforms and dynamic interactions of subunits U1-A, U1-C and Sm-B/B’. Results also show that unstructured post- ranslationally modified C-terminal tails are responsible for the dynamics of Sm-B/B’ and U1-C and that their interactions with the Sm core are controlled by binding to different U1-70k isoforms and their phosphorylation status in vivo. These results therefore provide the important functional link between proteomics and structure as well as insight into the dynamic quaternary structure of the native U1 snRNP important for its function.This work was funded by: BBSRC (OVM), BBSRC and EPSRC (HH and NM), EU Prospects (HH), European Science Foundation (NM), the Royal Society (CVR), and fellowship from JSPS and HFSP (YM and DAPK respectively)

In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance

Infections due to parasitic nematodes are common causes of morbidity and fatality around the world especially in developing nations. At present however, there are only three major classes of drugs for treating human nematode infections. Additionally the scientific knowledge on the mechanism of action and the reason for the resistance to these drugs is poorly understood. Commercial incentives to design drugs that are endemic to developing countries are limited therefore, virtual screening in academic settings can play a vital role is discovering novel drugs useful against neglected diseases. In this study we propose to build robust machine learning model to classify and screen compounds active against parasitic nematodes.A set of compounds active against parasitic nematodes were collated from various literature sources including PubChem while the inactive set was derived from DrugBank database. The support vector machine (SVM) algorithm was used for model development, and stratified ten-fold cross validation was used to evaluate the performance of each classifier. The best results were obtained using the radial basis function kernel. The SVM method achieved an accuracy of 81.79% on an independent test set. Using the model developed above, we were able to indentify novel compounds with potential anthelmintic activity.In this study, we successfully present the SVM approach for predicting compounds active against parasitic nematodes which suggests the effectiveness of computational approaches for antiparasitic drug discovery. Although, the accuracy obtained is lower than the previously reported in a similar study but we believe that our model is more robust because we intentionally employed stringent criteria to select inactive dataset thus making it difficult for the model to classify compounds. The method presents an alternative approach to the existing traditional methods and may be useful for predicting hitherto novel anthelmintic compounds.12 page(s

Policy challenges for the pediatric rheumatology workforce: Part I. Education and economics

For children with rheumatic conditions, the available pediatric rheumatology workforce mitigates their access to care. While the subspecialty experiences steady growth, a critical workforce shortage constrains access. This three-part review proposes both national and international interim policy solutions for the multiple causes of the existing unacceptable shortfall. Part I explores the impact of current educational deficits and economic obstacles which constrain appropriate access to care. Proposed policy solutions follow each identified barrier

High-order chromatin architecture determines the landscape of chromosomal alterations in cancer

The rapid growth of cancer genome structural information provides an opportunity for a better understanding of the mutational mechanisms of genomic alterations in cancer and the forces of selection that act upon them. Here we test the evidence for two major forces, spatial chromosome structure and purifying (or negative) selection, that shape the landscape of somatic copy-number alterations (SCNAs) in cancer1. Using a maximum likelihood framework we compare SCNA maps and three-dimensional genome architecture as determined by genome-wide chromosome conformation capture (HiC) and described by the proposed fractal-globule (FG) model2. This analysis provides evidence that the distribution of chromosomal alterations in cancer is spatially related to three-dimensional genomic architecture and additionally suggests that purifying selection as well as positive selection shapes the landscape of SCNAs during somatic evolution of cancer cells

Optimised laser microdissection of the human ocular surface epithelial regions for microarray studies

Background The most important challenge of performing insitu transcriptional profiling of the human ocular surface epithelial regions is obtaining samples in sufficient amounts, without contamination from adjacent tissue, as the region of interest is microscopic and closely apposed to other tissues regions. We have effectively collected ocular surface (OS) epithelial tissue samples from the Limbal Epithelial Crypt (LEC), limbus, cornea and conjunctiva of post-mortem cadaver eyes with laser microdissection (LMD) technique for gene expression studies with spotted oligonucleotide microarrays and Gene 1.0 ST arrays. Methods Human donor eyes (4 pairs for spotted oligonucleotide microarrays, 3 pairs for Gene 1.0 ST arrays) consented for research were included in this study with due ethical approval of the Nottingham Research Ethics Committee. Eye retrieval was performed within 36 hours of post-mortem period. The dissected corneoscleral buttons were immersed in OCT media and frozen in liquid nitrogen and stored at −80°C till further use. Microscopic tissue sections of interest were taken on PALM slides and stained with Toluidine Blue for laser microdissection with PALM microbeam systems. Optimisation of the laser microdissection technique was crucial for efficient and cost effective sample collection. Results The starting concentration of RNA as stipulated by the protocol of microarray platforms was taken as the cut-off concentration of RNA samples in our studies. The area of LMD tissue processed for spotted oligonucleotide microarray study ranged from 86,253 μm2 in LEC to 392,887 μm2 in LEC stroma. The RNA concentration of the LMD samples ranged from 22 to 92 pg/μl. The recommended starting concentration of the RNA samples used for Gene 1.0 ST arrays was 6 ng/5 μl. To achieve the desired RNA concentration the area of ocular surface epithelial tissue sample processed for the Gene 1.0 ST array experiments was approximately 100,0000 μm2 to 130,0000 μm2. RNA concentration of these samples ranged from 10.88 ng/12 μl to 25.8 ng/12 μl, with the RNA integrity numbers (RIN) for these samples from 3.3 to 7.9. RNA samples with RIN values below 2, that had failed to amplify satisfactorily were discarded. Conclusions The optimised protocol for sample collection and laser microdissection improved the RNA yield of the insitu ocular surface epithelial regions for effective microarray studies on spotted oligonucleotide and affymetrix platforms