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The early evolution of a supernova (SN) can reveal information about the environment and the progenitor star. When a star explodes in vacuum, the first photons to escape from its surface appear as a brief, hours-long shock-breakout flare1,2, followed by a cooling phase of emission. However, for stars exploding within a distribution of dense, optically thick circumstellar material (CSM), the first photons escape from the material beyond the stellar edge and the duration of the initial flare can extend to several days, during which the escaping emission indicates photospheric heating3. Early serendipitous observations2,4 that lacked ultraviolet (UV) data were unable to determine whether the early emission is heating or cooling and hence the nature of the early explosion event. Here we report UV spectra of the nearby SN 2023ixf in the galaxy Messier 101 (M101). Using the UV data as well as a comprehensive set of further multiwavelength observations, we temporally resolve the emergence of the explosion shock from a thick medium heated by the SN emission. We derive a reliable bolometric light curve that indicates that the shock breaks out from a dense layer with a radius substantially larger than typical supergiants.

Abstract Background Implementation strategies are essential to deliver evidence-based programs that align with local context, resources, priorities, and preferences. However, it is not always clear how specific strategies are selected (vs. others) and strategies are not always operationalized clearly, distinctly, and dynamically. Implementation logic models provide one useful way to conceptualize the role and selection of implementation strategies, plan evaluation of their intended impacts on implementation and effectiveness outcomes, and to communicate key aspects of a project. Methods This paper describes our initial plans, experiences, and lessons learned from applying implementation logic models in the Quadruple Aim Quality Enhancement Research Initiative (QUERI) a large multi-study program funded by the Veterans Health Administration (VA). We began with two primary implementation strategies based on our earlier work (i.e., Iterative RE-AIM and Relational Facilitation) that were applied across three different health outcomes studies. Results Our implementation strategies evolved over time, and new strategies were added. This evolution and reasons for changes are summarized and illustrated with the resulting logic models, both for the overall Quadruple Aim QUERI and the three specific projects. We found that implementation strategies are often not discrete, and their delivery and adaptation is dynamic and should be guided by emerging data and evolving context. Review of logic models across projects was an efficient and useful approach for understanding similarities and differences across projects. Conclusions Implementation logic models are helpful for clarifying key objectives and issues for both study teams and implementation partners. There are challenges in logic model construction and presentation when multiple strategies are employed, and when strategies change over time. We recommend presentation of both original and periodically updated project models and provide recommendations for future use of implementation logic models.

The Centers for Disease Control and Prevention defines SARS-CoV-2 reinfection as a positive COVID-19 test result >90 days after the collection date for the initial positive test or if sequencing confirms a different lineage is causing the reinfection. Reinfection dynamics have been examined by using PCR or antigen surveillance data. We identified patients in the US Military Health System who had >1 positive SARS-CoV-2 test during March 2020–July 2022 by using whole-genome sequencing data to identify reinfection cases, then compared those data with patient demographics, symptoms, and vaccination status. We identified 267 reinfections, of which 90% were caused by the SARS-CoV-2 Omicron variant. Reinfection symptom severity correlated with initial symptom severity and time since first infection. Furthermore, we found intrahost mutation rates varied greatly in 72 cases of continuing infections with the same variant. Continued investigations of reinfections caused by emerging SARS-CoV-2 variants of concern is needed to maintain US military readiness.

Objectives. This study aimed to determine the clinical profile of non-thyroidal cancer patients with thyroid dysfunction associated with tyrosine kinase inhibitor (TKI) therapy at the University of Santo Tomas Hospital (USTH), Philippines. Methodology. This is a retrospective observational study of TKI-initiated adult non-thyroidal cancer patients with thyroid function testing from 2013 to 2018. Results. Forty percent (95% CI: 26.2% - 58.61%) of the sixty individuals who had thyroid function tests (TFT) had incident thyroid dysfunction. Thirty percent had hypothyroidism (i.e., 25% overt [mean TSH 16.64 uIU/mL]; 5% subclinical [mean TSH 6.62 uIU/mL]). The median time at risk was 8 and 16 months for overt and subclinical hypothyroidism, respectively. Fifty-six percent had persistent hypothyroidism (median TSH 16.75, p = 0.009). The average time to recovery of transient hypothyroidism was 39 months. Ten percent had hyperthyroidism with a median time at risk of 1.5 months. Non-small cell lung cancer and renal cell carcinoma were possible associated risk factors of thyroid dysfunction. Conclusion. TKI-induced thyroid dysfunctions are common. Screening and monitoring for thyroid abnormalities during TKI therapy is important.

Background: Surgical education lacks a standardized, proficiency-based approach to evaluation and feedback. Objective: To assess the implementation and reception (ie, feasibility) of an automated, standardized, longitudinal surgical skill assessment and feedback system, and identify baseline trainee (resident and fellow) characteristics associated with achieving proficiency in robotic surgery while learning robotic-assisted laparoscopic prostatectomy. Design, setting, and participants: A quality improvement study assessing a pilot of a surgical experience tracking program was conducted over 1 yr. Participants were six fellows, eight residents, and nine attending surgeons at a tertiary cancer center. Intervention: Trainees underwent baseline self-assessment. After each surgery, an evaluation was completed independently by the trainee and attending surgeons. Performance was rated on a five-point anchored Likert scale (trainees were considered “proficient” when attending surgeons’ rating was ≥4). Technical skills were assessed using the Global Evaluative Assessment of Robotic Skills (GEARS) and Prostatectomy Assessment and Competency Evaluation (PACE). Outcome measurements and statistical analysis: Program success and utility were assessed by evaluating completion rates, evaluation completion times, and concordance rates between attending and trainee surgeons, and exit surveys. Baseline characteristics were assessed to determine associations with achieving proficiency. Results and limitations: Completion rates for trainees and attending surgeons were 72% and 77%, respectively. Fellows performed more steps/cases than residents (median [interquartile range]: 5 [3–7] and 3 [2–4], respectively; p < 0.01). Prior completion of robotics or laparoscopic skill courses and surgical experience measures were associated with achieving proficiency in multiple surgical steps and GEARS domains. Interclass correlation coefficients on individual components were 0.27–0.47 on GEARS domains. Conclusions: An automated surgical experience tracker with structured, longitudinal evaluation and feedback can be implemented with good participation and minimal participant time commitment, and can guide curricular development in a proficiency-based education program by identifying modifiable factors associated with proficiency, individualizing education, and identifying improvement areas within the education program. Patient summary: An automated, standardized, longitudinal surgical skill assessment and feedback system can be implemented successfully in surgical education settings and used to inform education plans and predict trainee proficiency.

BackgroundMen with grade group 2 or 3 prostate cancer are often considered ineligible for active surveillance; some patients with grade group 2 prostate cancer who are managed with active surveillance will have early disease progression requiring radical therapy. This study aimed to investigate whether MRI-guided focused ultrasound focal therapy can safely reduce treatment burden for patients with localised grade group 2 or 3 intermediate-risk prostate cancer.MethodsIn this single-arm, multicentre, phase 2b study conducted at eight health-care centres in the USA, we recruited men aged 50 years and older with unilateral, MRI-visible, primary, intermediate-risk, previously untreated prostate adenocarcinoma (prostate-specific antigen ≤20 ng/mL, grade group 2 or 3; tumour classification ≤T2) confirmed on combined biopsy (combining MRI-targeted and systematic biopsies). MRI-guided focused ultrasound energy, sequentially titrated to temperatures sufficient for tissue ablation (about 60-70°C), was delivered to the index lesion and a planned margin of 5 mm or more of normal tissue, using real-time magnetic resonance thermometry for intraoperative monitoring. Co-primary outcomes were oncological outcomes (absence of grade group 2 and higher cancer in the treated area at 6-month and 24-month combined biopsy; when 24-month biopsy data were not available and grade group 2 or higher cancer had occurred in the treated area at 6 months, the 6-month biopsy results were included in the final analysis) and safety (adverse events up to 24 months) in all patients enrolled in the study. This study is registered with ClinicalTrials.gov, NCT01657942, and is no longer recruiting.FindingsBetween May 4, 2017, and Dec 21, 2018, we assessed 194 patients for eligibility and treated 101 patients with MRI-guided focused ultrasound. Median age was 63 years (IQR 58-67) and median concentration of prostate-specific antigen was 5·7 ng/mL (IQR 4·2-7·5). Most cancers were grade group 2 (79 [78%] of 101). At 24 months, 78 (88% [95% CI 79-94]) of 89 men had no evidence of grade group 2 or higher prostate cancer in the treated area. No grade 4 or grade 5 treatment-related adverse events were reported, and only one grade 3 adverse event (urinary tract infection) was reported. There were no treatment-related deaths.Interpretation24-month biopsy outcomes show that MRI-guided focused ultrasound focal therapy is safe and effectively treats grade group 2 or 3 prostate cancer. These results support focal therapy for select patients and its use in comparative trials to determine if a tissue-preserving approach is effective in delaying or eliminating the need for radical whole-gland treatment in the long term.FundingInsightec and the National Cancer Institute.

This research presents a comparative analysis of single-sided surface-mounted axial flux permanent magnet (SMAFPM) and consequent-pole axial flux permanent magnet (CPAFPM) machines by evaluating various key electromagnetic parameters. A straightforward replacement of permanent magnets (PMs) with soft magnetic composites (SMCs) is proposed for a conversion of surface-mounted (SM) topology to consequent pole (CP) topology, which maximizes manufacturing ease while sharing the same components. Detailed three-dimensional (3D) finite element analysis (FEA) is performed to assess parameters such as back-EMF, flux-linkage, inductance, torque, and losses. The investigation highlights that despite utilizing 50% less rare-earth permanent magnet (PM) material, the CPAFPM machine produces only 30% less rated torque compared to the SMAFPM machine. However, the CPAFPM machine suffers from reduced magnetic loading and higher armature reaction, leading to 36% lower torque density and reduced efficiency at low speeds and heavy loads. Prototypes of both machines were fabricated, and experimental validation showed a good correlation with the simulation studies. The findings provide insight into the simple conversion to the CPAFPM machine as a viable option for high-speed drives requiring fewer rare-earth PM materials.

A collaborative centralized model predictive controller solving the problem of autonomous vehicles safely crossing an intersection is presented. The solution gives optimal speed trajectories for each vehicle while considering collision avoidance constraints between vehicles traveling on the same path before, after and/or within the intersection. This extends earlier results, where collision avoidance was only considered for vehicles with intersecting paths, with the possibility of vehicles on the same path and by this, the controller is not only one step closer to handling complex traffic intersections but can now be used for merging and splitting of roads, roundabouts and intersection networks. The proficiency of the extended controller is demonstrated by applying it to a four-way intersection. It is shown that the controller provides smooth, collision free trajectories in scenarios with and without vehicles traveling in the same lane. Further, it is evaluated how the solutions differ when using various cost functions and how the controller handles disturbances in the form of a sudden lane blockage. Lastly, it is discussed how the presented controller could also be extended to handle mixed-traffic scenarios and how soft constraints can be used to avoid infeasibility in the case of missing or noisy traffic data.

Open-source software has been highly influential on software development in many fields, and also has a history within computational electromagnetics. With large amounts of open-source code available, both from within computational electromagnetics and from other fields, new combinations can be made by using already existing code packages. This can be especially beneficial to developers who do not otherwise have access to a substantial codebase. In this article we describe how a finite element-boundary integral code using the adaptive cross approximation was developed by combining different existing open-source software packages with new code in Python. We provide a brief overview of the numerical methods used, but our focus is on the implementation and insights that might be useful to others who could benefit from using open-source software in their work. Three numerical examples are also presented to demonstrate accuracy, performance and use of complex materials. Our code is provided at github.com/nwingren/fe2ms both to demonstrate how the open-source packages were combined in practice, but also for those who wish to test the code themselves.

ObjectivesTo prospectively evaluate the performance of a pre-specified statistical model based on four kallikrein markers in blood (total prostate-specific antigen [PSA], free PSA, intact PSA, and human kallikrein-related peptidase 2), commercially available as the 4Kscore, in predicting Gleason Grade Group (GG) ≥2 prostate cancer at biopsy in an international multicentre study at three academic medical centres, and whether microseminoprotein-β (MSP) adds predictive value.Patients and methodsA total of 984 men were prospectively enrolled at three academic centres. The primary outcome was GG ≥2 on prostate biopsy. Three pre-specified statistical models were used: a base model including PSA, age, digital rectal examination and prior negative biopsy; a model that added free PSA to the base model; and the 4Kscore.ResultsA total of 947 men were included in the final analysis and 273 (29%) had GG ≥2 on prostate biopsy. The base model area under the receiver operating characteristic curve of 0.775 increased to 0.802 with the addition of free PSA, and to 0.824 for the 4Kscore. Adding MSP to the 4Kscore model yielded an increase (0.014-0.019) in discrimination. In decision-curve analysis of clinical utility, the 4Kscore showed a benefit starting at a 7.5% threshold.ConclusionA prospective multicentre evaluation of a pre-specified model based on four kallikrein markers (4Kscore) with the addition of MSP improves the predictive discrimination for GG ≥2 prostate cancer on biopsy and could be used to inform biopsy decision-making.

One of the major challenges in educational reform is supporting teachers and the profession in the continual improvement of instruction. Research-practice partnerships and particularly networked improvement communities are well-suited for such knowledge-building work. This article examines how a networked improvement community with eight school-based professional learning communities--comprised of secondary science teachers, science and emergent bilingual coaches, and researchers--launched into improvement work within schools and across the district. We used data from professional learning communities to analyze pathways into improvement work and reflective data to understand practitioners' perspectives. We describe three improvement launch patterns: (1) Local Practice Development, (2) Spread and Local Adaptation, and (3) Integrating New Practices. We raise questions about what is lost and gained in the transfer of tools and practices across schools and theorize about how research-practice partnerships find footholds into joint improvement work.