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

Nephropathic Cystinosis: Pathogenic Roles of Inflammation and Potential for New Therapies

The activation of several inflammatory pathways has recently been documented in patients and different cellular and animal models of nephropathic cystinosis. Upregulated inflammatory signals interact with many pathogenic aspects of the disease, such as enhanced oxidative stress, abnormal autophagy, inflammatory cell recruitment, enhanced cell death, and tissue fibrosis. Cysteamine, the only approved specific therapy for cystinosis, ameliorates many but not all pathogenic aspects of the disease. In the current review, we summarize the inflammatory mechanisms involved in cystinosis and their potential impact on the disease pathogenesis and progression. We further elaborate on the crosstalk between inflammation, autophagy, and apoptosis, and discuss the potential of experimental drugs for suppressing the inflammatory signals in cystinosis

Urine-Derived Epithelial Cells as Models for Genetic Kidney Diseases

Epithelial cells exfoliated in human urine can include cells anywhere from the urinary tract and kidneys; however, podocytes and proximal tubular epithelial cells (PTECs) are by far the most relevant cell types for the study of genetic kidney diseases. When maintained in vitro, they have been proven extremely valuable for discovering disease mechanisms and for the development of new therapies. Furthermore, cultured patient cells can individually represent their human sources and their specific variants for personalized medicine studies, which are recently gaining much interest. In this review, we summarize the methodology for establishing human podocyte and PTEC cell lines from urine and highlight their importance as kidney disease cell models. We explore the well-established and recent techniques of cell isolation, quantification, immortalization and characterization, and we describe their current and future applications

Cysteamine–bicalutamide combination therapy corrects proximal tubule phenotype in cystinosis

Nephropathic cystinosis is a severe monogenic kidney disorder caused by mutations in CTNS, encoding the lysosomal transporter cystinosin, resulting in lysosomal cystine accumulation. The sole treatment, cysteamine, slows down the disease progression, but does not correct the established renal proximal tubulopathy. Here, we developed a new therapeutic strategy by applying omics to expand our knowledge on the complexity of the disease and prioritize drug targets in cystinosis. We identified alpha-ketoglutarate as a potential metabolite to bridge cystinosin loss to autophagy, apoptosis and kidney proximal tubule impairment in cystinosis. This insight combined with a drug screen revealed a bicalutamide–cysteamine combination treatment as a novel dual-target pharmacological approach for the phenotypical correction of cystinotic kidney proximal tubule cells, patient-derived kidney tubuloids and cystinotic zebrafish