16 research outputs found
Identification of a target antigen in human anti-tubular basement membrane nephritis
Identification of a target antigen in human anti-tubular basement membrane nephritis. Sera from two patients with primary anti-tubular–basement–membrane–mediated tubulointerstitial nephritis, one a renal allograft recipient and the other with spontaneous anti-tubular–basement–membrane disease, were analyzed for the specificity of their autoantibodies. Both sera had circulating antibodies that reacted by ELISA with extracts of tubular basement membrane from several species, but failed to react significantly with extracts of glomerular basement membrane. Reactive antigen was solubilized with 6 M guanidine-HCl, 6 M urea, with reduction and alkylation, and with sodium dodecylsulfate. Digestion of the basement membrane with collagenase released relatively small quantities of antigen from the membrane, and trypsin and pepsin destroyed its antigenicity. The antigenic activity was characterized with respect to its size distribution by gel filtration and by immuno-overlay analysis of protein blots. Collectively, the results indicate that the major reactivity of both sera is directed towards a Mr 58,000 component that is unique to the tubular basement membrane. Minor reactivities toward high molecular weight components common to both glomerular and tubular basement membranes were detected by immuno-overlay analysis. This study identifies an antigen that is involved in human anti-tubular–basement–membrane–mediated tubulointerstitial nephritis, and demonstrates an advantage of the use of denaturing extraction over proteolytic methods to prepare the antigen
Glomerular distribution of type IV collagen in diabetes by high resolution quantitative immunochemistry
Glomerular distribution of type IV collagen in diabetes by high resolution quantitative immunochemistry. We examined type IV collagen distribution and density in human diabetic kidneys by quantitative immunogold electron microscopy. We studied normal kidney transplant donors and “slow-track” and “fast-track” insulin dependent diabetic (IDDM) patients. The “slow-track” patients had IDDM for ≥ 20 years and mesangial volume fraction (VvMes/glom) of ≤ 0.32. The “fast-track” patients had IDDM for ≤ 20 years and VvMes/glom ≥ 0.37. Renal biopsies were embedded in Lowicryl, reacted with polyclonal anti-type IV collagen (in the distribution of the classical α1(IV) and α2(IV) collagen chains) and monoclonal anti-α4(IV) collagen chain antibody followed by gold conjugated secondary antibody. We found, by morphometric techniques, a decrease in the immunogold densities of anti-type IV collagen in the subendothelial zone of the GBM in the “fast-track” IDDM patients. There was a trend towards a decrease in mesangial matrix (MM) particle density in the “fast-track” (P = 0.07) but not in the “slow-track” patients. However, because of the marked increase in MM in the “fast-track” patients, the per glomerulus estimated quantity of these antigens in MM was increased. In contrast, the density of α4(IV) collagen chain was increased in the epithelial zone of the GBM in the “fast-track” IDDM patients. It is not known whether these changes in glomerular type IV collagen represent markers of advanced diabetic lesions or whether these changes might be detected earlier in diabetic patients destined for the later development of serious lesions
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe