Bone loss and aggravated autoimmune arthritis in HLA-DRβ1-bearing humanized mice following oral challenge with Porphyromonas gingivalis

BACKGROUND: The linkage between periodontal disease and rheumatoid arthritis is well established. Commonalities among the two are that both are chronic inflammatory diseases characterized by bone loss, an association with the shared epitope susceptibility allele, and anti-citrullinated protein antibodies. METHODS: To explore immune mechanisms that may connect the two seemingly disparate disorders, we measured host immune responses including T-cell phenotype and anti-citrullinated protein antibody production in human leukocyte antigen (HLA)-DR1 humanized C57BL/6 mice following exposure to the Gram-negative anaerobic periodontal disease pathogen Porphyromonas gingivalis. We measured autoimmune arthritis disease expression in mice exposed to P. gingivalis, and also in arthritis-resistant mice by flow cytometry and multiplex cytokine-linked and enzyme-linked immunosorbent assays. We also measured femoral bone density by microcomputed tomography and systemic cytokine production. RESULTS: Exposure of the gingiva of DR1 mice to P. gingivalis results in a transient increase in the percentage of Th17 cells, both in peripheral blood and cervical lymph nodes, a burst of systemic cytokine activity, a loss in femoral bone density, and the generation of anti-citrullinated protein antibodies. Importantly, these antibodies are not produced in response to P. gingivalis treatment of wild-type C57BL/6 mice, and P. gingivalis exposure triggered expression of arthritis in arthritis-resistant mice. CONCLUSIONS: Exposure of gingival tissues to P. gingivalis has systemic effects that can result in disease pathology in tissues that are spatially removed from the initial site of infection, providing evidence for systemic effects of this periodontal pathogen. The elicitation of anti-citrullinated protein antibodies in an HLA-DR1-restricted fashion by mice exposed to P. gingivalis provides support for the role of the shared epitope in both periodontal disease and rheumatoid arthritis. The ability of P. gingivalis to induce disease expression in arthritis-resistant mice provides support for the idea that periodontal infection may be able to trigger autoimmunity if other disease-eliciting factors are already present

Molecular classification and biomarkers of clinical outcome in breast ductal carcinoma in situ: Analysis of TBCRC 038 and RAHBT cohorts

Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome

Digital Storytelling An Innovative Technological Approach to Nursing Education

This study investigated the impact of using digital stories in promoting deeper understanding in nursing students about palliative care concepts. Students (N = 134) created a 5-minute narrated digital story utilizing VoiceThread technology that synthesized and applied knowledge that had been presented in class and course readings. Postsurvey and focus group evaluation data revealed that through the writing and sharing of digital stories, students embraced the personal and complex nature of palliative care.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110783/1/Digital_Storytelling__An_Innovative_Technological.pdfDescription of Digital_Storytelling__An_Innovative_Technological.pdf : Articl

A predictive model for creep deformation following vertebral compression fractures

Many vertebral compression fractures continue to collapse over time, resulting in spinal deformity and chronic back pain. Currently, there is no adequate screening strategy to identify patients at risk of progressive vertebral collapse. This study developed a mathematical model to describe the quantitative relationship between initial bone damage and progressive (“creep”) deformation in human vertebrae. The model uses creep rate before damage, and the degree of vertebral bone damage, to predict creep rate of a fractured vertebra following bone damage. Mechanical testing data were obtained from 27 vertebral trabeculae samples, and 38 motion segments, from 26 human spines. These were analysed to evaluate bone damage intensity, and creep rates before and after damage, in order to estimate the model parameter, p, which represents how bone damage affects the change of creep rate after damage. Results of the model showed that p was 1.38 (R2 = 0.72, p 0.05). Further analyses revealed that p was not significantly influenced by cortical bone damage, endplate damage, disc degeneration, vertebral size, or vertebral areal bone mineral density (aBMD) (P > 0.05). The key determinant of creep deformation following vertebral compression fracture was the degree of trabecular bone damage. The proposed model could be used to identify the measures of bone damage on routine MR images that are associated with creep deformation so that a screening tool can be developed to predict progressive vertebral collapse following compression fracture

Global Oceanic Diazotroph Database Version 2 and Elevated Estimate of Global N\u3csub\u3e2\u3c/sub\u3e Fixation

Marine diazotrophs convert dinitrogen (N2) gas into bioavailable nitrogen (N), supporting life in the global ocean. In 2012, the first version of the global oceanic diazotroph database (version 1) was published. Here, we present an updated version of the database (version 2), significantly increasing the number of in situ diazotrophic measurements from 13 565 to 55 286. Data points for N2 fixation rates, diazotrophic cell abundance, and nifH gene copy abundance have increased by 184 %, 86 %, and 809 %, respectively. Version 2 includes two new data sheets for the nifH gene copy abundance of non-cyanobacterial diazotrophs and cell-specific N2 fixation rates. The measurements of N2 fixation rates approximately follow a log-normal distribution in both version 1 and version 2. However, version 2 considerably extends both the left and right tails of the distribution. Consequently, when estimating global oceanic N2 fixation rates using the geometric means of different ocean basins, version 1 and version 2 yield similar rates (43–57 versus 45–63 Tg N yr−1; ranges based on one geometric standard error). In contrast, when using arithmetic means, version 2 suggests a significantly higher rate of 223±30 Tg N yr−1 (mean ± standard error; same hereafter) compared to version 1 (74±7 Tg N yr−1). Specifically, substantial rate increases are estimated for the South Pacific Ocean (88±23 versus 20±2 Tg N yr−1), primarily driven by measurements in the southwestern subtropics, and for the North Atlantic Ocean (40±9 versus 10±2 Tg N yr−1). Moreover, version 2 estimates the N2 fixation rate in the Indian Ocean to be 35±14 Tg N yr−1, which could not be estimated using version 1 due to limited data availability. Furthermore, a comparison of N2 fixation rates obtained through different measurement methods at the same months, locations, and depths reveals that the conventional 15N2 bubble method yields lower rates in 69 % cases compared to the new 15N2 dissolution method. This updated version of the database can facilitate future studies in marine ecology and biogeochemistry. The database is stored at the Figshare repository (https://doi.org/10.6084/m9.figshare.21677687; Shao et al., 2022)

GREAT3 results I: systematic errors in shear estimation and the impact of real galaxy morphology

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically-varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially-varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by $\sim 1$ per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the S\'{e}rsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods' results support the simple model in which additive shear biases depend linearly on PSF ellipticity.Comment: 32 pages + 15 pages of technical appendices; 28 figures; submitted to MNRAS; latest version has minor updates in presentation of 4 figures, no changes in content or conclusion

Multi-Messenger Gravitational Wave Searches with Pulsar Timing Arrays: Application to 3C66B Using the NANOGrav 11-year Data Set

When galaxies merge, the supermassive black holes in their centers may form binaries and, during the process of merger, emit low-frequency gravitational radiation in the process. In this paper we consider the galaxy 3C66B, which was used as the target of the first multi-messenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C66B to less than $(1.65\pm0.02) \times 10^9~{M_\odot}$ using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits, and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data to `blind' pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences.Comment: 14 pages, 6 figures. Accepted by Ap

Chitosan-zein nano-in-microparticles Capable of Mediating in vivo Transgene Expression Following Oral Delivery

The oral route is an attractive delivery route for the administration of DNA-based therapeutics, specifically for applications in gene therapy and DNA vaccination. However, oral DNA delivery is complicated by the harsh and variable conditions encountered throughout gastrointestinal (GI) transit, leading to degradation of the delivery vector and DNA cargo, and subsequent inefficient delivery to target cells. In this work, we demonstrate the development and optimization of a hybrid-dual particulate delivery system consisting of two natural biomaterials, zein (ZN) and chitosan (CS), to mediate oral DNA delivery. Chitosan-Zein Nano-in-Microparticles (CS-ZN-NIMs), consisting of core Chitosan/DNA nanoparticles (CS/DNA NPs) prepared by ionic gelation with sodium tripolyphosphate (TPP), further encapsulated in ZN microparticles, were formulated using a water-in-oil emulsion (W/O). The resulting particles exhibited high CS/DNA NP loading and encapsulation within ZN microparticles. DNA release profiles in simulated gastric fluid (SGF) were improved compared to un-encapsulated CS/ DNA NPs. Further, site-specific degradation of the outer ZN matrix and release of transfection competent CS/ DNA NPs occurred in simulated intestinal conditions with CS/DNA NP cores successfully mediating transfection in vitro. Finally, CS-ZN-NIMs encoding GFP delivered by oral gavage in vivo induced the production of anti-GFP IgA antibodies, demonstrating in vivo transfection and expression. Together, these results demonstrate the successful formulation of CS-ZN-NIMs and their potential to improve oral gene delivery through improved protection and controlled release of DNA cargo