Immunocytochemical characterisation of cultures of human bladder mucosal cells

<p>Abstract</p> <p>Background</p> <p>The functional role of the bladder urothelium has been the focus of much recent research. The bladder mucosa contains two significant cell types: urothelial cells that line the bladder lumen and suburothelial interstitial cells or myofibroblasts. The aims of this study were to culture these cell populations from human bladder biopsies and to perform immunocytochemical characterisation.</p> <p>Methods</p> <p>Primary cell cultures were established from human bladder biopsies (n = 10). Individual populations of urothelial and myofibroblast-like cells were isolated using magnetic activated cell separation (MACS). Cells were slow growing, needing 3 to 5 weeks to attain confluence.</p> <p>Results</p> <p>Cytokeratin 20 positive cells (umbrella cells) were isolated at primary culture and also from patients' bladder washings but these did not proliferate. In primary culture, proliferating cells demonstrated positive immunocytochemical staining to cytokeratin markers (AE1/AE3 and A0575) as well fibroblasts (5B5) and smooth muscle (αSMA) markers. An unexpected finding was that populations of presumptive urothelial and myofibroblast-like cells, isolated using the MACS beads, stained for similar markers. In contrast, staining for cytokeratins and fibroblast or smooth muscle markers was not co-localised in full thickness bladder sections.</p> <p>Conclusions</p> <p>Our results suggest that, in culture, bladder mucosal cells may undergo differentiation into a myoepithelial cell phenotype indicating that urothelial cells have the capacity to respond to environmental changes. This may be important pathologically but also suggests that studies of the physiological function of these cells in culture may not give a reliable indicator of human physiology.</p

Probing the Connection between IceCube Neutrinos and MOJAVE AGN

Active galactic nuclei (AGN) are prime candidate sources of the high-energy, astrophysical neutrinos detected by IceCube. This is demonstrated by the real-time multimessenger detection of the blazar TXS 0506+056 and the recent evidence of neutrino emission from NGC 1068 from a separate time-averaged study. However, the production mechanism of the astrophysical neutrinos in AGN is not well established, which can be resolved via correlation studies with photon observations. For neutrinos produced due to photohadronic interactions in AGN, in addition to a correlation of neutrinos with high-energy photons, there would also be a correlation of neutrinos with photons emitted at radio wavelengths. In this work, we perform an in-depth stacking study of the correlation between 15 GHz radio observations of AGN reported in the MOJAVE XV catalog, and 10 yr of neutrino data from IceCube. We also use a time-dependent approach, which improves the statistical power of the stacking analysis. No significant correlation was found for both analyses, and upper limits are reported. When compared to the IceCube diffuse flux, at 100 TeV and for a spectral index of 2.5, the upper limits derived are ∼3% and ∼9% for the time-averaged and time-dependent cases, respectively

Search for Continuous and Transient Neutrino Emission Associated with IceCube's Highest-Energy Tracks: An 11-Year Analysis

IceCube alert events are neutrinos with a moderate-to-high probability of having astrophysical origin. In this study, we analyze 11 years of IceCube data and investigate 122 alert events and a selection of high-energy tracks detected between 2009 and the end of 2021. This high-energy event selection (alert events + high-energy tracks) has an average probability of $\geq 0.5$ to be of astrophysical origin. We search for additional continuous and transient neutrino emission within the high-energy events' error regions. We find no evidence for significant continuous neutrino emission from any of the alert event directions. The only locally significant neutrino emission is the transient emission associated with the blazar TXS~0506+056, with a local significance of $3 \sigma$, which confirms previous IceCube studies. When correcting for 122 test positions, the global p-value is $0.156$ and is compatible with the background hypothesis. We constrain the total continuous flux emitted from all 122 test positions at 100~TeV to be below $1.2 \times 10^{-15}$~(TeV cm$^2$ s)$^{-1}$ at 90% confidence assuming an $E^{-2}$ spectrum. This corresponds to 4.5% of IceCube's astrophysical diffuse flux. Overall, we find no indication that alert events, in general, are linked to lower-energetic continuous or transient neutrino emission.Comment: Accepted by Ap

Acceptance Tests of more than 10 000 Photomultiplier Tubes for the multi-PMT Digital Optical Modules of the IceCube Upgrade

More than 10 000 photomultiplier tubes (PMTs) with a diameter of 80 mm will be installed in multi-PMT Digital Optical Modules (mDOMs) of the IceCube Upgrade. These have been tested and pre-calibrated at two sites. A throughput of more than 1000 PMTs per week with both sites was achieved with a modular design of the testing facilities and highly automated testing procedures. The testing facilities can easily be adapted to other PMTs, such that they can, e.g., be re-used for testing the PMTs for IceCube-Gen2. Single photoelectron response, high voltage dependence, time resolution, prepulse, late pulse, afterpulse probabilities, and dark rates were measured for each PMT. We describe the design of the testing facilities, the testing procedures, and the results of the acceptance tests

Citizen science for IceCube: Name that Neutrino

Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions. Name that Neutrino obtained more than 128,000 classifications by over 1800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for both Name that Neutrino and the deep neural network are discussed

Citizen science for IceCube: Name that Neutrino

Name that Neutrino is a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions. Name that Neutrino obtained more than 128,000 classifications by over 1,800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for both Name that Neutrino and the deep neural network are discussed

Search for joint multimessenger signals from potential Galactic PeVatrons with HAWC and IceCube

Galactic PeVatrons are sources that can accelerate cosmic rays to PeV energies. The high-energy cosmic rays are expected to interact with the surrounding ambient material or radiation, resulting in the production of gamma rays and neutrinos. To optimize for the detection of such associated production of gamma rays and neutrinos for a given source morphology and spectrum, a multi-messenger analysis that combines gamma rays and neutrinos is required. In this study, we use the Multi-Mission Maximum Likelihood framework (3ML) with IceCube Maximum Likelihood Analysis software (i3mla) and HAWC Accelerated Likelihood (HAL) to search for a correlation between 22 known gamma-ray sources from the third HAWC gamma-ray catalog and 14 years of IceCube track-like data. No significant neutrino emission from the direction of the HAWC sources was found. We report the best-fit gamma-ray model and 90% CL neutrino flux limit from the 22 sources. From the neutrino flux limit, we conclude that the gamma-ray emission from five of the sources can not be produced purely from hadronic interactions. We report the limit for the fraction of gamma rays produced by hadronic interactions for these five sources

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

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