Your class is online now: Now What? How Online Creative Writing Can Offer a More Democratic Space and a Few Specific Examples

Five accomplished, diverse writers who teach creative writing online confront the challenges of remote courses and programs, offering experiences, assignments, and best practices that meet the specific needs of online writing students and help these learners to succeed and soar. Panelists provide valuable takeaways for writers considering remote education, for curriculum designers, and for the growing number of faculty who will choose or need (for the same reasons as students) to teach online

From the CMD of Omega Centauri and (super-)AGB stellar models to a Galactic plane passage gas purging chemical evolution scenario

[Abbreviated] We have investigated the color-magnitude diagram of Omega Centauri and find that the blue main sequence (bMS) can be reproduced only by models that have a of helium abundance in the range Y=0.35-$0.40. To explain the faint subgiant branch of the reddest stars ("MS-a/RG-a" sequence), isochrones for the observed metallicity ([Fe/H]\approx0.7) appear to require both a high age (~13Gyr) and enhanced CNO abundances ([CNO/Fe]\approx0.9$). Y~0.35 must also be assumed in order to counteract the effects of high CNO on turnoff colors, and thereby to obtain a good fit to the relatively blue turnoff of this stellar population. This suggest a short chemical evolution period of time (<1Gyr) for Omega Cen. Our intermediate-mass (super-)AGB models are able to reproduce the high helium abundances, along with [N/Fe]~2 and substantial O depletions if uncertainties in the treatment of convection are fully taken into account. These abundance features distinguish the bMS stars from the dominant [Fe/H] $\approx1.7$ population. The most massive super-AGB stellar models (M_zams>=6.8M_sun, M_He,core>=1.245M_sun) predict too large N-enhancements, which limits their role in contributing to the extreme populations. We show quantitatively that highly He- and N-enriched AGB ejecta have particularly efficient cooling properties. Based on these results and on the reconstruction of the orbit of Omega Cen with respect to the Milky Way we propose the galactic plane passage gas purging scenario for the chemical evolution of this cluster. Our model addresses the formation and properties of the bMS population (including their central location in the cluster). We follow our model descriptively through four passage events, which could explain not only some key properties of the bMS, but also of the MS-a/RGB-a and the s-enriched stars.Comment: Accepted for publication in ApJ. 10 figures, 5 tables, 21 page

DOK3 Negatively Regulates LPS Responses and Endotoxin Tolerance

Innate immune activation via Toll-like receptors (TLRs), although critical for host defense against infection, must be regulated to prevent sustained cell activation that can lead to cell death. Cells repeatedly stimulated with lipopolysaccharide (LPS) develop endotoxin tolerance making the cells hypo-responsive to additional TLR stimulation. We show here that DOK3 is a negative regulator of TLR signaling by limiting LPS-induced ERK activation and cytokine responses in macrophages. LPS induces ubiquitin-mediated degradation of DOK3 leading to SOS1 degradation and inhibition of ERK activation. DOK3 mice are hypersensitive to sublethal doses of LPS and have altered cytokine responses in vivo. During endotoxin tolerance, DOK3 expression remains stable, and it negatively regulates the expression of SHIP1, IRAK-M, SOCS1, and SOS1. As such, DOK3-deficient macrophages are more sensitive to LPS-induced tolerance becoming tolerant at lower levels of LPS than wild type cells. Taken together, the absence of DOK3 increases LPS signaling, contributing to LPS-induced tolerance. Thus, DOK3 plays a role in TLR signaling during both naïve and endotoxin-induced tolerant conditions

Psymberin, a marine-derived natural product, induces cancer cell growth arrest and protein translation inhibition

Colorectal cancer (CRC) is the third most prevalent form of cancer in the United States and results in over 50,000 deaths per year. Treatments for metastatic CRC are limited, and therefore there is an unmet clinical need for more effective therapies. In our prior work, we coupled high-throughput chemical screens with patient-derived models of cancer to identify new potential therapeutic targets for CRC. However, this pipeline is limited by (1) the use of cell lines that do not appropriately recapitulate the tumor microenvironment, and (2) the use of patient-derived xenografts (PDXs), which are time-consuming and costly for validation of drug efficacy. To overcome these limitations, we have turned to patient-derived organoids. Organoids are increasingly being accepted as a “standard” preclinical model that recapitulates tumor microenvironment cross-talk in a rapid, cost-effective platform. In the present work, we employed a library of natural products, intermediates, and drug-like compounds for which full synthesis has been demonstrated. Using this compound library, we performed a high-throughput screen on multiple low-passage cancer cell lines to identify potential treatments. The top candidate, psymberin, was further validated, with a focus on CRC cell lines and organoids. Mechanistic and genomics analyses pinpointed protein translation inhibition as a mechanism of action of psymberin. These findings suggest the potential of psymberin as a novel therapy for the treatment of CRC

Care management for Type 2 diabetes in the United States: a systematic review and meta-analysis

<p>Abstract</p> <p>Background</p> <p>This systematic review and meta-analysis aims at assessing the composition and performance of care management models evaluated in the last decade and their impact on patient important outcomes.</p> <p>Methods</p> <p>A comprehensive literature search of electronic bibliographic databases was performed to identify care management trials in type 2 diabetes. Random effects meta-analysis was used when feasible to pool outcome measures.</p> <p>Results</p> <p>Fifty-two studies were eligible. Most commonly reported were surrogate outcomes (such as HbA1c and LDL), followed by process measures (clinic visit or testing frequency). Less frequently reported were quality of life, patient satisfaction, self-care, and healthcare utilization. Most care management modalities were carved out from primary care. Meta-analysis demonstrated a statistically significant but trivial reduction of HbA1c (weighted difference in means -0.21%, 95% confidence interval -0.40 to -0.03, p < .03) and LDL-cholesterol (weighted difference in means -3.38 mg/dL, 95% confidence interval -6.27 to -0.49, p < .02).</p> <p>Conclusions</p> <p>Most care management programs for patients with type 2 diabetes are 'carved-out', accomplish limited effects on metabolic outcomes, and have unknown effects on patient important outcomes. Comparative effectiveness research of different models of care management is needed to inform the design of medical homes for patients with chronic conditions.</p

Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events

Funder: School of Clinical Medicine, University of Cambridge; doi: http://dx.doi.org/10.13039/501100007552Funder: Frank Edward Elmore FundFunder: National Institute for Health Research (NIHR) Imperial Biomedical Research CentreFunder: British Heart Foundation Cambridge Centre of Research ExcellenceFunder: Royal College of Surgeons of England; doi: http://dx.doi.org/10.13039/501100000297Funder: Cancer Research UK; doi: http://dx.doi.org/10.13039/501100000289Funder: AstraZeneca Oncology RFunder: National Institute for Health Research; doi: http://dx.doi.org/10.13039/501100000272Funder: Leverhulme Trust; doi: http://dx.doi.org/10.13039/501100000275Funder: Cantab Capital Institute for the Mathematics of InformationFunder: Alan Turing Institute; doi: http://dx.doi.org/10.13039/100012338Funder: NIHR Cambridge Biomedical Research CentreFunder: Higher Education Funding Council for England; doi: http://dx.doi.org/10.13039/501100000384Abstract: Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into predictive models, for good generalisability. We extracted 93 radiomic features from carotid artery computed tomography angiograms of 41 patients with cerebrovascular events. We tested feature robustness to region-of-interest perturbations, image pre-processing settings and quantisation methods using both single- and multi-slice approaches. We assessed the ability of the most robust features to identify culprit and non-culprit arteries using several machine learning algorithms and report the average area under the curve (AUC) from five-fold cross validation. Multi-slice features were superior to single for producing robust radiomic features (67 vs. 61). The optimal image quantisation method used bin widths of 25 or 30. Incorporating our top 10 non-redundant robust radiomics features into ElasticNet achieved an AUC of 0.73 and accuracy of 69% (compared to carotid calcification alone [AUC: 0.44, accuracy: 46%]). Our results provide key information for introducing carotid CT radiomics into clinical practice. If validated prospectively, our robust carotid radiomic set could improve stroke prediction and target therapies to those at highest risk