The JWST Galactic Center Survey -- A White Paper

The inner hundred parsecs of the Milky Way hosts the nearest supermassive black hole, largest reservoir of dense gas, greatest stellar density, hundreds of massive main and post main sequence stars, and the highest volume density of supernovae in the Galaxy. As the nearest environment in which it is possible to simultaneously observe many of the extreme processes shaping the Universe, it is one of the most well-studied regions in astrophysics. Due to its proximity, we can study the center of our Galaxy on scales down to a few hundred AU, a hundred times better than in similar Local Group galaxies and thousands of times better than in the nearest active galaxies. The Galactic Center (GC) is therefore of outstanding astrophysical interest. However, in spite of intense observational work over the past decades, there are still fundamental things unknown about the GC. JWST has the unique capability to provide us with the necessary, game-changing data. In this White Paper, we advocate for a JWST NIRCam survey that aims at solving central questions, that we have identified as a community: i) the 3D structure and kinematics of gas and stars; ii) ancient star formation and its relation with the overall history of the Milky Way, as well as recent star formation and its implications for the overall energetics of our galaxy's nucleus; and iii) the (non-)universality of star formation and the stellar initial mass function. We advocate for a large-area, multi-epoch, multi-wavelength NIRCam survey of the inner 100\,pc of the Galaxy in the form of a Treasury GO JWST Large Program that is open to the community. We describe how this survey will derive the physical and kinematic properties of ~10,000,000 stars, how this will solve the key unknowns and provide a valuable resource for the community with long-lasting legacy value.Comment: This White Paper will be updated when required (e.g. new authors joining, editing of content). Most recent update: 24 Oct 202

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

pyPOCQuant — A tool to automatically quantify Point-Of-Care Tests from images

Lateral flow Point-Of-Care Tests (POCTs) are a valuable tool for rapidly detecting pathogens and the associated immune response in humans and animals. In the context of the SARS-CoV-2 pandemic, they offer rapid on-site diagnostics and can relieve centralized laboratory testing sites, thus freeing resources that can be focused on especially vulnerable groups. However, visual interpretation of the POCT test lines is subjective, error prone and only qualitative. Here we present pyPOCQuant, an open-source tool implemented in Python 3 that can robustly and reproducibly analyze POCTs from digital images and return an unbiased and quantitative measurement of the POCT test lines

pyPOCQuant — A tool to automatically quantify Point-Of-Care Tests from images

Lateral flow Point-Of-Care Tests (POCTs) are a valuable tool for rapidly detecting pathogens and the associated immune response in humans and animals. In the context of the SARS-CoV-2 pandemic, they offer rapid on-site diagnostics and can relieve centralized laboratory testing sites, thus freeing resources that can be focused on especially vulnerable groups. However, visual interpretation of the POCT test lines is subjective, error prone and only qualitative. Here we present pyPOCQuant, an open-source tool implemented in Python 3 that can robustly and reproducibly analyze POCTs from digital images and return an unbiased and quantitative measurement of the POCT test lines

SpectraSorter: Ocean Insight spectrometer software application for high-throughput full-spectrum UV–VIS analysis and triggered sorting

We present SpectraSorter, a C#-based software application for high-speed Ocean Insight spectrometers with an intuitive GUI. It performs rapid full-spectrum UV–VIS detection followed by real-time data processing, customizable visualization, precise triggering on any spectral features, and external communication via an Arduino microcontroller all in approximately one millisecond. We designed it for high-throughput analytical chemistry applications that require real-time analysis of optical spectra to inform subsequent sample sorting. Hence its name, the “SpectraSorter.” The software was used for the label-free enzymatic screening of bacterial microcolonies contained in microfluidic droplets, but is broadly applicable to other spectrometer screening applications.ISSN:2352-711

Deconvolution of Very Large Data Sets

The Huygens Remote Manager (HRM) is an open-source, multi-user, web-based batch processor for large scale restoration of microscopy images. By enabling mass deconvolution, HRM aims at maximizing the volume of data suitable for segmentation, quantification and analysis. Recent deconvolution runs of large spinning disk and SPIM images show that while these images present a true challenge for current desktop computers, they can be easily processed on a small HRM server automatically

Determination of the source of SHG verniers in zebrafish skeletal muscle

SHG microscopy is an emerging microscopic technique for medically relevant imaging because certain endogenous proteins, such as muscle myosin lattices within muscle cells, are sufficiently spatially ordered to generate detectable SHG without the use of any fluorescent dye. Given that SHG signal is sensitive to the structural state of muscle sarcomeres, SHG functional imaging can give insight into the integrity of muscle cells in vivo. Here, we report a thorough theoretical and experimental characterization of myosin-derived SHG intensity profiles within intact zebrafish skeletal muscle. We determined that “SHG vernier” patterns, regions of bifurcated SHG intensity, are illusory when sarcomeres are staggered with respect to one another. These optical artifacts arise due to the phase coherence of SHG signal generation and the Guoy phase shift of the laser at the focus. In contrast, two-photon excited fluorescence images obtained from fluorescently labeled sarcomeric components do not contain such illusory structures, regardless of the orientation of adjacent myofibers. Based on our results, we assert that complex optical artifacts such as SHG verniers should be taken into account when applying functional SHG imaging as a diagnostic readout for pathological muscle conditions.ISSN:2045-232