Automatic Detection and Extraction of Key Resources from Tables in Biomedical Papers.

Tables are useful information artifacts that allow easy detection of data "missingness" by humans and have been deployed by several publishers to improve the amount of information present for key resources and reagents such as antibodies, cell lines, and other tools that constitute the inputs to a study. The STAR*Methods tables, specifically, have increased the "findability" of these key resources, but they have not been commonly available outside of the Cell Press journal family. To improve the availability of these tables in the broader biomedical literature, we have attempted to automatically process BioRxiv preprints to create tables from text or to recognize tables already created by authors and structure them for later use by publishers and search systems, to improve "findability" of resources in a larger amount of the scientific literature.

Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning.

Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time-consuming, burden patients financially, and sometimes all test results can be negative.

Waterless Dyeing of Polyamide 6.6.

Waterless dyeing of polyamide 6.6 using scCO (supercritical carbon dioxide) was investigated. PA (polyamide) fibers can be dyed with various dyes, including disperse dyes.

Establishing Institutional Scores With the Rigor and Transparency Index: Large-scale Analysis of Scientific Reporting Quality.

Background: Improving rigor and transparency measures should lead to improvements in reproducibility across the scientific literature; however, the assessment of measures of transparency tends to be very difficult if performed manually.

Objective: This study addresses the enhancement of the Rigor and Transparency Index (RTI, version 2.0), which attempts to automatically assess the rigor and transparency of journals, institutions, and countries using manuscripts scored on criteria found in reproducibility guidelines (eg, Materials Design, Analysis, and Reporting checklist criteria).

Antibody Watch: Text mining antibody specificity from the literature.

Antibodies are widely used reagents to test for expression of proteins and other antigens. However, they might not always reliably produce results when they do not specifically bind to the target proteins that their providers designed them for, leading to unreliable research results. While many proposals have been developed to deal with the problem of antibody specificity, it is still challenging to cover the millions of antibodies that are available to researchers.