26 research outputs found

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

    Get PDF
    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

    T-cell exhaustion induced by continuous bispecific molecule exposure is ameliorated by treatment-free intervals.

    No full text
    T-cell–recruiting bispecific molecule therapy has yielded promising results in patients with hematologic malignancies; however, resistance and subsequent relapse remains a major challenge. T-cell exhaustion induced by persistent antigen stimulation or tonic receptor signaling has been reported to compromise outcomes of T-cell–based immunotherapies. The impact of continuous exposure to bispecifics on T-cell function, however, remains poorly understood. In relapsed/refractory B-cell precursor acute lymphoblastic leukemia patients, 28-day continuous infusion with the CD19xCD3 bispecific molecule blinatumomab led to declining T-cell function. In an in vitro model system, mimicking 28-day continuous infusion with the half-life–extended CD19xCD3 bispecific AMG 562, we identified hallmark features of exhaustion arising over time. Continuous AMG 562 exposure induced progressive loss of T-cell function (day 7 vs day 28 mean specific lysis: 88.4% vs 8.6%; n = 6; P = .0003). Treatment-free intervals (TFIs), achieved by AMG 562 withdrawal, were identified as a powerful strategy for counteracting exhaustion. TFIs induced strong functional reinvigoration of T cells (continuous vs TFI-specific lysis on day 14: 34.9% vs 93.4%; n = 6; P < .0001) and transcriptional reprogramming. Furthermore, use of a TFI led to improved T-cell expansion and tumor control in vivo. Our data demonstrate the relevance of T-cell exhaustion in bispecific antibody therapy and highlight that T cells can be functionally and transcriptionally rejuvenated with TFIs. In view of the growing number of bispecific molecules being evaluated in clinical trials, our findings emphasize the need to consider and evaluate TFIs in application schedules to improve clinical outcomes
    corecore