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This study employed a critical inquiry paradigm to explore the significance of equity and social justice in teaching qualitative methodologies and methods to graduate students. Graduate students of multiple minoritized identities and a faculty member conducted a two-year inquiry into the research apprenticeship experience, including the stages of student-led conceptualization, data collection, analysis, international conference presentation, and publication. The study investigated the experiences of the faculty and students as well as the responsibilities of the institution against the backdrop of historical and contemporary pandemics. Consequently, we problematized hidden curriculum and unconscious assumptions to suggest research course design sequencing improvements. The findings emphasize the impact of these experiences on qualitative research teaching and learning practices and institutional responsibility to graduate student research apprenticeships. The Graduate Research Apprenticeship Nested Design Pathway is presented as a tool that institutions worldwide can adapt and implement to serve the complex needs of their students.

Real-time collaborative forecast efforts have become the standard to generate and evaluate forecasts for infectious disease outbreaks (1,2). Individual forecasts are aggregated into an ensemble prediction that has historically outperformed [...]

Background: Newly diagnosed breast cancer patients experience symptoms that may affect their quality of life, treatment outcomes, and survival. Preventing and managing breast cancer-related symptoms soon after diagnosis is essential. The purpose of this study was to investigate the associations between health-related fitness (HRF) and patient-reported symptoms in newly diagnosed breast cancer patients. Methods: This study utilized baseline data from the Alberta Moving Beyond Breast Cancer Cohort Study that were collected within 90 days of diagnosis. HRF measures included peak cardiopulmonary fitness (peak volume of oxygen consumption (VO2peak)), maximal muscular strength and endurance, flexibility, and body composition. Symptom measures included depression, sleep quality, and fatigue. Adjusted multivariable logistic regression was performed for analyses. Results: Of 1458 participants, 51.5% reported poor sleep quality, 26.5% reported significant fatigue, and 10.4% reported moderate depression. In multivariable-adjusted models, lower relative VO2peak was independently associated with a greater likelihood of all symptom measures, including moderate depression (p < 0.001), poor sleep quality (p = 0.009), significant fatigue (p = 0.008), any symptom (p < 0.001), and multiple symptoms (p < 0.001). VO2peak demonstrated threshold associations with all symptom measures such that all 3 lower quartiles exhibited similar elevated risk compared to the highest quartile. The strength of the threshold associations varied by the symptom measure with odds ratios ranging from ∼1.5 for poor sleep quality to ∼3.0 for moderate depression and multiple symptoms. Moreover, lower relative upper body muscular endurance was also independently associated with fatigue in a dose-response manner (p = 0.001), and higher body weight was independently associated with poor sleep quality in an inverted U pattern (p = 0.021). Conclusion: Relative VO2peak appears to be a critical HRF component associated with multiple patient-reported symptoms in newly diagnosed breast cancer patients. Other HRF parameters may also be important for specific symptoms. Exercise interventions targeting different HRF components may help newly diagnosed breast cancer patients manage specific symptoms and improve outcomes.

On the basis of historical influenza and COVID-19 forecasts, we found that more than 3 forecast models are needed to ensure robust ensemble accuracy. Additional models can improve ensemble performance, but with diminishing accuracy returns. This understanding will assist with the design of current and future collaborative infectious disease forecasting efforts.

Abstract Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

Abstract Mycobacterial glycolipids are important cell envelope structures that drive host-pathogen interactions. Arguably, the most important are lipoarabinomannan (LAM) and its precursor, lipomannan (LM), which are trafficked from the bacterium to the host via unknown mechanisms. Arabinomannan is thought to be a capsular derivative of these molecules, lacking a lipid anchor. However, the mechanism by which this material is generated has yet to be elucidated. Here, we describe the identification of a glycoside hydrolase family 76 enzyme that we term LamH (Rv0365c in Mycobacterium tuberculosis) which specifically cleaves α−1,6-mannoside linkages within LM and LAM, driving its export to the capsule releasing its phosphatidyl-myo-inositol mannoside lipid anchor. Unexpectedly, we found that the catalytic activity of this enzyme is important for efficient exit from stationary phase cultures, potentially implicating arabinomannan as a signal for growth phase transition. Finally, we demonstrate that LamH is important for M. tuberculosis survival in macrophages.

Background Glioblastoma is a highly infiltrative, currently incurable brain cancer. To date, translation of novel therapies for glioblastoma from the laboratory into clinical trials has relied heavily on in vitro cell culture and murine (subcutaneous and orthotopic) xenograft models using cells derived from the main bulk of patient tumours. However, it is the residual cells left-behind after surgery that are responsible for disease progression and death in the clinic. A lack of substantial improvements in patient survival for decades suggests commonly used murine xenograft models, a key step before clinical trials, do not reflect the biology of residual disease in patients. Methods To address this, we have developed the ‘Sheffield Protocol’ to generate ex vivo models that reflect both resected, and post-surgical residual disease from the same patient. The protocol leverages parallel derivation of inherently treatment-resistant glioblastoma stem cells (GSCs) from ‘core’ and distant ‘edge’ regions through careful macrodissection of a large en bloc specimen, such as from a partial lobectomy for tumour, followed by tissue dissociation and propagation in serum-free media. Opportunistic en bloc specimen use can liberate the most distant infiltrative cells feasibly accessible from living patients. Results We provide an example illustrating that resected and residual disease models represent spatially divergent tumour subpopulations harbouring distinct transcriptomic and cancer stem cell marker expression profiles. We also introduce the ‘Sheffield Living Biobank’ of glioma models (SLB) that incorporates over 150 GSC lines from 60+ patients, including 44+ resected and residual models, which are available for academic use via MTA. Conclusions These models provide a novel tool to reduce animal xenograft usage by improving candidate drug triage in early preclinical studies and directly replacing animal studies for some therapies that are post-Phase 1+ clinical trial for other cancers/conditions to, ultimately, deliver more effective treatments for post-surgical residual disease in glioblastoma.

Teacher educators have been investigating ways to rob the demographic mismatch of this disempowering history. How can white preservice teachers be prepared to do meaningful work with communities of color? Scholars have been skeptical of the ability of white teachers to become fully culturally relevant. Aaron Schutz worries when teachers with privilege in relation to their students seek to "help" their students, they necessarily formulate their students as having deficit knowledge. If this is true, then what are we to make of programs like Teach For America (TFA) that attempt to deal with problems stemming from the above demographic mismatch in education by paradoxically recruiting mostly white graduates from elite universities to teach in under-resourced communities? Does the willingness of these recruits to "help" communities of color necessarily make them oppressive in the way Schutz identifies? In this article, Spencer Smith theorizes an answer to this question as well as necessary components of the theory of emancipatory teacher education. Using interview data from a study of teachers trained by TFA, Smith argues training in culturally relevant teaching does little to prepare teachers to succeed in culturally diverse classrooms unless it includes some engagement with the cultural Other. Smith pairs these data with the work of Herbert Dreyfus and Charles Taylor who argue encounter with the Other can be a Gadamerian "fusion of horizons." Finally, Smith demonstrates how this fusion of horizons allows teachers to escape Schutz's worries and move closer to embodying culturally responsive teaching.

Background: Nearly one-half of patients admitted with acute decompensated heart failure (ADHF) are discharged with unresolved congestion, elevating rehospitalization risk. This may be due to suboptimal intravenous (IV) loop diuretic dosing, which may be influenced by home oral diuretic dose. Objectives: The objective of this study was to determine the association between: 1) home oral loop diuretic dose and optimal initial IV loop diuretic dosing in ADHF; and 2)receiving optimal initial IV loop diuretic dosing and length of stay and 30-day readmission. Methods: Retrospective analysis of adults admitted to a large U.S. hospital for ADHF on home oral loop diuretics from 1 January 2014 to 21 December 2021. Patients were categorized by home dose: low (≤40 mg furosemide equivalents), medium (>40-80 mg furosemide equivalents), and high (>80 mg furosemide equivalents). Optimal initial IV dosing was considered ≥2 times home oral dosing. Poisson regression models estimated prevalence ratios (CIs) for optimal initial IV loop diuretic dosing. Results: Among 3,269 adults admitted for ADHF (mean age 63 years, 62% male), optimal initial IV dosing occurred in 2,218 (67.9%). The prevalence of optimal initial IV dosing among low, medium, and high home dosing was 95.5%, 59.9%, and 4.0%, respectively. Adjusted prevalence ratios for optimal IV dosing with high and medium home dosing, compared to low, were 0.05 (95% CI: 0.03-0.07) and 0.66 (95% CI: 0.62-0.70), respectively. There was no difference in length of stay or 30-day readmission between optimal and suboptimal initial IV diuretic dosing. Conclusions: Among patients with ADHF, higher home loop diuretic dose was strongly associated with a substantially lower likelihood of optimal initial IV diuretic dosing.

During the COVID-19 pandemic, nucleic acid amplification tests (NAATs) and rapid antigen tests (RATs) have been widely used to direct patient care and control transmission (1). NAATs, such as reverse [...]

Abstract Background Local treatment options for locally recurrent pancreatic adenocarcinoma (LR-PAC) are limited, with median survival time (MST) of 9–13 months (mos) following recurrence. MRI-guided stereotactic body radiation therapy (MRgSBRT) provides the ability to dose escalate while sparing normal tissue. Here we report on the early outcomes of MRgSBRT for LR-PAC. Methods Patients with prior resection of pancreatic adenocarcinoma with local recurrence treated with MRgSBRT at a single tertiary referral center from 5-2021 to 2-2023 were identified from our prospective database. MRgSBRT was delivered to 40–50 Gy in 4–5 fractions with target and OAR delineation per institutional standards. Endpoints included local control per RECIST v1.1, distant failure, overall survival (OS), and acute and chronic toxicities per Common Terminology Criteria for Adverse Events, v5. Results Fifteen patients with LR-PAC were identified with median follow-up of 10.6 mos (2.8–26.5 mos) from MRgSBRT. There were 8 females and 7 males, with a median age of 69 years (50–83). One patient underwent neoadjuvant radiation for 50.4 Gy in 28 fractions followed by resection, and one underwent adjuvant radiation for 45 Gy in 25 fractions prior to recurrence. MRgSBRT was delivered a median of 18.8 mos (3.5–52.8 mos) following resection. OS following recurrence at 6 and 12 mos were 87% and 51%, respectively, with a median survival time of 14.1 mos (3.2–27.4 mos). Three patients experienced local failure at 5.9, 7.8, and 16.6 months from MgSBRT with local control of 92.3% and 83.9% at 6 and 12 months. 10 patients experienced distant failure at a median of 2.9 mos (0.3–6.7 mos). Grade 1–2 acute GI toxicity was noted in 47% of patients, and chronic GI toxicity in 31% of patients. No grade > 3 toxicities were noted. Conclusions This is the first report on toxicity and outcomes of MRgSBRT for LR-PAC in the literature. MRgSBRT is a safe, feasible treatment modality with the potential for improved local control in this vulnerable population. Future research is necessary to better identify which patients yield the most benefit from MRgSBRT, which should continue to be used with systemic therapy as tolerated. Trial Registration: Jefferson IRB#20976, approved 2/17/21.

Abstract Myriad policy, ethical and legal considerations underpin the sharing of biological resources, implying the need for standardised and yet flexible ways to digitally represent diverse ‘use conditions’. We report a core lexicon of terms that are atomic, non-directional ‘concepts of use’, called Common Conditions of use Elements. This work engaged biobanks and registries relevant to the European Joint Programme for Rare Diseases and aimed to produce a lexicon that would have generalised utility. Seventy-six concepts were initially identified from diverse real-world settings, and via iterative rounds of deliberation and user-testing these were optimised and condensed down to 20 items. To validate utility, support software and training information was provided to biobanks and registries who were asked to create Sharing Policy Profiles. This succeeded and involved adding standardised directionality and scope annotations to the employed terms. The addition of free-text parameters was also explored. The approach is now being adopted by several real-world projects, enabling this standard to evolve progressively into a universal basis for representing and managing conditions of use.

Abstract Improving patient care and advancing scientific discovery requires responsible sharing of research data, healthcare records, biosamples, and biomedical resources that must also respect applicable use conditions. Defining a standard to structure and manage these use conditions is a complex and challenging task. This is exemplified by a near unlimited range of asset types, a high variability of applicable conditions, and differing applications at the individual or collective level. Furthermore, the specifics and granularity required are likely to vary depending on the ultimate contexts of use. All these factors confound alignment of institutional missions, funding objectives, regulatory and technical requirements to facilitate effective sharing. The presented work highlights the complexity and diversity of the problem, reviews the current state of the art, and emphasises the need for a flexible and adaptable approach. We propose Digital Use Conditions (DUC) as a framework that addresses these needs by leveraging existing standards, striking a balance between expressiveness versus ambiguity, and considering the breadth of applicable information with their context of use.

School reopenings in 2021 and 2022 coincided with the rapid emergence of new SARS-CoV-2 variants in the United States. In-school mitigation efforts varied, depending on local COVID-19 mandates and resources. Using a stochastic age-stratified agent-based model of SARS-CoV-2 transmission, we estimate the impacts of multiple in-school strategies on both infection rates and absenteeism, relative to a baseline scenario in which only symptomatic cases are tested and positive tests trigger a 10-day isolation of the case and 10-day quarantine of their household and classroom. We find that monthly asymptomatic screening coupled with the 10-day isolation and quarantine period is expected to avert 55.4% of infections while increasing absenteeism by 104.3%. Replacing quarantine with test-to-stay would reduce absenteeism by 66.3% (while hardly impacting infection rates), but would require roughly 10-fold more testing resources. Alternatively, vaccination or mask wearing by 50% of the student body is expected to avert 54.1% or 43.1% of infections while decreasing absenteeism by 34.1% or 27.4%, respectively. Separating students into classrooms based on mask usage is expected to reduce infection risks among those who wear masks (by 23.1%), exacerbate risks among those who do not (by 27.8%), but have little impact on overall risk. A combined strategy of monthly screening, household and classroom quarantine, a 50% vaccination rate, and a 50% masking rate (in mixed classrooms) is expected to avert 81.7% of infections while increasing absenteeism by 90.6%. During future public health emergencies, such analyses can inform the rapid design of resource-constrained strategies that mitigate both public health and educational risks.

We devised a model to interpret discordant SARS-CoV-2 test results. We estimate that, during March 2020–May 2022, a patient in the United States who received a positive rapid antigen test result followed by a negative nucleic acid test result had only a 15.4% (95% CI 0.6%–56.7%) chance of being infected.

The Great Barrier Reef (GBR) is under pressure from climate change and other threats, and part of the solution is to raise awareness of the GBR and its threats beyond a local audience (Great Barrier Reef Marine Park Authority, 2019). Reef HQ Aquarium (the national education centre for the Great Barrier Reef Marine Park Authority) implemented a virtual marine education program focussed on the GBR in 1998. The program uses videoconferencing technology to connect real-time marine biology experts to participants around the world. We report on > ten years of participant trends for this program to assess whether the program is a mechanism for increasing community educational outreach. Since 2005, the program increased the Aquarium's community and educational outreach by 4.8% by connecting an additional 83 388 participants from 19 countries worldwide. While the videoconference technology has evolved overtime, the program content remains a unique, interactive virtual experience that has proven to be an effective way for an informal learning institute to increase their outreach on a national and international level, particularly as there has been a transition to online learning and educational programs due the recent global Coronavirus pandemic.

With diminishing returns and high clinical failure rates from traditional preclinical and animal-based drug discovery strategies, more emphasis is being placed on alternative drug discovery platforms. Ex vivo approaches represent a departure from both more traditional preclinical animal-based models and clinical-based strategies and aim to address intra-tumoural and inter-patient variability at an earlier stage of drug discovery. Additionally, these approaches could also offer precise treatment stratification for patients within a week of tumour resection in order to direct tailored therapy. One tumour group that could significantly benefit from such ex vivo approaches are high-grade gliomas, which exhibit extensive heterogeneity, cellular plasticity and therapy-resistant glioma stem cell (GSC) niches. Historic use of murine-based preclinical models for these tumours has largely failed to generate new therapies, resulting in relatively stagnant and unacceptable survival rates of around 12-15 months post-diagnosis over the last 50 years. The near universal use of DNA damaging chemoradiotherapy after surgical resection within standard-of-care (SoC) therapy regimens provides an opportunity to improve current treatments if we can identify efficient drug combinations in preclinical models that better reflect the complex inter-/intra-tumour heterogeneity, GSC plasticity and inherent DNA damage resistance mechanisms. We have therefore developed and optimised a high-throughput ex vivo drug screening platform; GliExP, which maintains GSC populations using immediately dissociated fresh surgical tissue. As a proof-of-concept for GliExP, we have optimised SoC therapy responses and screened 30+ small molecule therapeutics and preclinical compounds against tumours from 18 different patients, including multi-region spatial heterogeneity sampling from several individual tumours. Our data therefore provides a strong basis to build upon GliExP to incorporate combination-based oncology therapeutics in tandem with SoC therapies as an important preclinical alternative to murine models (reduction and replacement) to triage experimental therapeutics for clinical translation and deliver rapid identification of effective treatment strategies for individual gliomas.

BackgroundCoronavirus Disease 2019 (COVID-19) continues to cause significant hospitalizations and deaths in the United States. Its continued burden and the impact of annually reformulated vaccines remain unclear. Here, we present projections of COVID-19 hospitalizations and deaths in the United States for the next 2 years under 2 plausible assumptions about immune escape (20% per year and 50% per year) and 3 possible CDC recommendations for the use of annually reformulated vaccines (no recommendation, vaccination for those aged 65 years and over, vaccination for all eligible age groups based on FDA approval).Methods and findingsThe COVID-19 Scenario Modeling Hub solicited projections of COVID-19 hospitalization and deaths between April 15, 2023 and April 15, 2025 under 6 scenarios representing the intersection of considered levels of immune escape and vaccination. Annually reformulated vaccines are assumed to be 65% effective against symptomatic infection with strains circulating on June 15 of each year and to become available on September 1. Age- and state-specific coverage in recommended groups was assumed to match that seen for the first (fall 2021) COVID-19 booster. State and national projections from 8 modeling teams were ensembled to produce projections for each scenario and expected reductions in disease outcomes due to vaccination over the projection period. From April 15, 2023 to April 15, 2025, COVID-19 is projected to cause annual epidemics peaking November to January. In the most pessimistic scenario (high immune escape, no vaccination recommendation), we project 2.1 million (90% projection interval (PI) [1,438,000, 4,270,000]) hospitalizations and 209,000 (90% PI [139,000, 461,000]) deaths, exceeding pre-pandemic mortality of influenza and pneumonia. In high immune escape scenarios, vaccination of those aged 65+ results in 230,000 (95% confidence interval (CI) [104,000, 355,000]) fewer hospitalizations and 33,000 (95% CI [12,000, 54,000]) fewer deaths, while vaccination of all eligible individuals results in 431,000 (95% CI: 264,000-598,000) fewer hospitalizations and 49,000 (95% CI [29,000, 69,000]) fewer deaths.ConclusionsCOVID-19 is projected to be a significant public health threat over the coming 2 years. Broad vaccination has the potential to substantially reduce the burden of this disease, saving tens of thousands of lives each year.

Throughout the COVID-19 pandemic, changes in policy, shifts in behavior, and the emergence of new SARS-CoV-2 variants spurred multiple waves of transmission. Accurate assessments of the changing risks were vital for ensuring adequate healthcare capacity, designing mitigation strategies, and communicating effectively with the public. Here, we introduce a model of COVID-19 transmission and vaccination that provided rapid and reliable projections as the BA.1, BA.4 and BA.5 variants emerged and spread across the US. For example, our three-week ahead national projection of the early 2021 peak in COVID-19 hospitalizations was only one day later and 11.6–13.3% higher than the actual peak, while our projected peak in mortality was two days earlier and 0.22–4.7% higher than reported. We track population-level immunity from prior infections and vaccination in terms of the percent reduction in overall susceptibility relative to a completely naive population. As of October 1, 2022, we estimate that the US population had a 36.52% reduction in overall susceptibility to the BA.4/BA.5 variants, with 61.8%, 15.06%, and 23.54% of immunity attributable to infections, primary series vaccination, and booster vaccination, respectively. We retrospectively projected the potential impact of expanding booster coverage starting on July 15, 2022, and found that a five-fold increase in weekly boosting rates would have resulted in 70% of people over 65 vaccinated by Oct 10, 2022 and averted 25,000 (95% CI: 14,400–35,700) deaths during the BA.4/BA.5 surge. Our model provides coherent variables for tracking population-level immunity in the increasingly complex landscape of variants and vaccines and enables robust simulations of plausible scenarios for the emergence and mitigation of novel COVID variants.