B‐cell receptors of EBV‐negative Burkitt lymphoma bind modified isoforms of autoantigens

Burkitt lymphoma (BL) represents the most aggressive B‐cell‐lymphoma. Beside the hallmark of IG‐MYC‐translocation, surface B‐cell receptor (BCR) is expressed, and mutations in the BCR pathway are frequent. Coincidental infections in endemic BL, and specific extra‐nodal sites suggest antigenic triggers. To explore this hypothesis, BCRs of BL cell lines and cases were screened for reactivities against a panel of bacterial lysates, lysates of Plasmodium falciparum, a custom‐made virome array and against self‐antigens, including post‐translationally modified antigens. An atypically modified, SUMOylated isoform of Bystin, that is, SUMO1‐BYSL was identified as the antigen of the BCR of cell line CA46. SUMO1‐BYSL was exclusively expressed in CA46 cells with K139 as site of the SUMOylation. Secondly, an atypically acetylated isoform of HSP40 was identified as the antigen of the BCR of cell line BL41. K104 and K179 were the sites of immunogenic acetylation, and the acetylated HSP40 isoform was solely present in BL41 cells. Functionally, addition of SUMO1‐BYSL and acetylated HSP40 induced BCR pathway activation in CA46 and BL41 cells, respectively. Accordingly, SUMO1‐BYSL‐ETA’ immunotoxin, produced by a two‐step intein‐based conjugation, led to the specific killing of CA46 cells. Autoantibodies directed against SUMO1‐BYSL were found in 3 of 14 (21.4%), and autoantibodies against acetylated HSP40 in 1/14(7.1%) patients with sporadic Burkitt‐lymphoma. No reactivities against antigens of the infectious agent spectrum could be observed. These results indicate a pathogenic role of autoreactivity evoked by immunogenic post‐translational modifications in a subgroup of sporadic BL including two EBV‐negative BL cell lines

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

Antimicrobial Strategies and Economic Considerations for Polymeric Medical Implants.

Healthcare acquired infections (HAI's) are a worldwide problem that can be exacerbated by surgery and the implantation of polymeric medical devices. The use of polymer based medical devices which incorporate antimicrobial strategies are now becoming an increasingly routine way of trying to prevent the potential for reduce chronic infection and device failure. There are a wide range of potential antimicrobial agents currently being incorporated into such polymers. However, it is difficult to determine which antimicrobial agent provides the greatest infection control. The economics of replacing current methods with impregnated polymer materials further complicates matters. It has been suggested that the use of a holistic system wide approach should to be developed around the implantation of medical devices which minimises the potential risk of infection. However, the use of such different approaches is still being developed. The control of such infections is important for individual patient health and the economic implications for healthcare services

Leveraging Ligand Affinity and Properties: Discovery of Novel Benzamide-Type Cereblon Binders for the Design of PROTACs

Immunomodulatory imide drugs (IMiDs) such as thalidomide, pomalidomide, and lenalidomide represent the most typical cereblon (CRBN) recruiters that are frequently utilized in proteolysis-targeting chimera (PROTAC) design. These CRBN binders, however, cause degradation of IMiD neosubstrates and are innately unstable as they undergo hydrolytic degradation under mild conditions. Here we present the systematic approach towards novel non-phthalimide CRBN binders that were obtained via the simultaneous optimization of their physiochemical properties, stability, on-target affinity, and off-target neosubstrate modulation features. Our efforts led to the discovery of conformationally-locked benzamide-type derivatives that mimic the interactions of the natural CRBN degron, displayed improved chemical stability, and showed a favorable selectivity profile with respect to the recruitment of neosubstrates. The usefulness of the most potent ligands was demonstrated by their conversion into potent degraders of BRD4 and HDAC6 that displayed superiority compared to previously described benchmark PROTACs. We show that our diversified CRBN ligands offer opportunities to design chemically inert proximity-inducing compounds with reduced neomorphic E3 ligase activity of CRBN

A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses

Seibold H, Czerny S, Decke S, et al. A computational reproducibility study of PLOS ONE articles featuring longitudinal data analyses. PLoS ONE . 2021;16(6): e0251194.Computational reproducibility is a corner stone for sound and credible research. Especially in complex statistical analyses-such as the analysis of longitudinal data-reproducing results is far from simple, especially if no source code is available. In this work we aimed to reproduce analyses of longitudinal data of 11 articles published in PLOS ONE. Inclusion criteria were the availability of data and author consent. We investigated the types of methods and software used and whether we were able to reproduce the data analysis using open source software. Most articles provided overview tables and simple visualisations. Generalised Estimating Equations (GEEs) were the most popular statistical models among the selected articles. Only one article used open source software and only one published part of the analysis code. Replication was difficult in most cases and required reverse engineering of results or contacting the authors. For three articles we were not able to reproduce the results, for another two only parts of them. For all but two articles we had to contact the authors to be able to reproduce the results. Our main learning is that reproducing papers is difficult if no code is supplied and leads to a high burden for those conducting the reproductions. Open data policies in journals are good, but to truly boost reproducibility we suggest adding open code policies

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 science. © The Author(s) 2019. Published by Oxford University Press