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

Hydrogel-Induced Cell Membrane Disruptions Enable Direct Cytosolic Delivery of Membrane-Impermeable Cargo

Intracellular delivery of membrane-impermeable cargo offers unique opportunities for biological research and the development of cell-based therapies. Despite the breadth of available intracellular delivery tools, existing protocols are often suboptimal and alternative approaches that merge delivery efficiency with both biocompatibility, as well as applicability, remain highly sought after. Here, a comprehensive platform is presented that exploits the unique property of cationic hydrogel nanoparticles to transiently disrupt the plasma membrane of cells, allowing direct cytosolic delivery of uncomplexed membrane-impermeable cargo. Using this platform, which is termed Hydrogel-enabled nanoPoration or HyPore, the delivery of fluorescein isothiocyanate (FITC)-dextran macromolecules in various cancer cell lines and primary bovine corneal epithelial cells is convincingly demonstrated. Of note, HyPore demonstrates efficient FITC-dextran delivery in primary human T cells, outperforming state-of-the-art electroporation-mediated delivery. Moreover, the HyPore platform enables cytosolic delivery of functional proteins, including a histone-binding nanobody as well as the enzymes granzyme A and Cre-recombinase. Finally, HyPore-mediated delivery of the MRI contrast agent gadobutrol in primary human T cells significantly improves their T1 -weighted MRI signal intensities compared to electroporation. Taken together, HyPore is proposed as a straightforward, highly versatile, and cost-effective technique for high-throughput, ex vivo manipulation of primary cells and cell lines

Hydrogel‐induced cell membrane disruptions enable direct cytosolic delivery of membrane‐impermeable cargo

Intracellular delivery of membrane-impermeable cargo offers unique opportunities for biological research and the development of cell-based therapies. Despite the breadth of available intracellular delivery tools, existing protocols are often suboptimal and alternative approaches that merge delivery efficiency with both biocompatibility, as well as applicability, remain highly sought after. Here, a comprehensive platform is presented that exploits the unique property of cationic hydrogel nanoparticles to transiently disrupt the plasma membrane of cells, allowing direct cytosolic delivery of uncomplexed membrane-impermeable cargo. Using this platform, which is termed Hydrogel-enabled nanoPoration or HyPore, the delivery of fluorescein isothiocyanate (FITC)-dextran macromolecules in various cancer cell lines and primary bovine corneal epithelial cells is convincingly demonstrated. Of note, HyPore demonstrates efficient FITC-dextran delivery in primary human T cells, outperforming state-of-the-art electroporation-mediated delivery. Moreover, the HyPore platform enables cytosolic delivery of functional proteins, including a histone-binding nanobody as well as the enzymes granzyme A and Cre-recombinase. Finally, HyPore-mediated delivery of the MRI contrast agent gadobutrol in primary human T cells significantly improves their T-1-weighted MRI signal intensities compared to electroporation. Taken together, HyPore is proposed as a straightforward, highly versatile, and cost-effective technique for high-throughput, ex vivo manipulation of primary cells and 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 science. © The Author(s) 2019. Published by Oxford University Press

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