A sinonasal NUT midline carcinoma in an 84‐year‐old man undergoing radiation and proton therapy

Abstract NUT midline carcinomas are rare, aggressive, and poorly differentiated tumors that must be considered in the differential diagnosis of midline head and neck tumors. Despite the scarce data, proton therapy could be an option for some patients

Research Overview of the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE)

CARTHE (http://carthe.org/) is a Gulf of Mexico Research Initiative (GoMRI) consortium established through a competitive peer-reviewed selection process. CARTHE comprises 26 principal investigators from 14 universities and research institutions distributed across four Gulf of Mexico states and other four states. It fuses into one group investigators with unique scientific and technical knowledge and extensive publications related to oil fate/transport processes, oceanic and atmospheric turbulence, air-sea interactions, tropical cyclones and winter storms, and coastal and nearshore modeling and observations. Our primary goal is to accurately predict the fate of hydrocarbons released into the environment. Achieving this goal is particularly challenging since petroleum releases into the environment interact with natural processes across six orders of magnitude of time and space scales. We are developing a multi-scale modeling tool by incorporating state-of-the-art hydrophysical models, each applicable for a restricted range of scales, into a single, interconnected modeling system to predict the physical dispersal of hydrocarbons across scales ranging from the microscale at the wellhead to oceanic and atmospheric mesoscales. CARTHE is also conducting novel in-situ observations and laboratory experiments specifically designed for quantifying submesoscale dispersion as well as for both model validation and parameterization. Finally, we are providing a robust set of uncertainty metrics and analysis tools to assess model performance and quantify predictive uncertainty

Immune-based classification of HPV-associated oropharyngeal cancer with implications for biomarker-driven treatment de-intensification.

BACKGROUND: There is significant interest in treatment de-escalation for human papillomavirus-associated (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) patients given the generally favourable prognosis. However, 15-30% of patients recur after primary treatment, reflecting a need for improved risk-stratification tools. We sought to develop a molecular test to risk stratify HPV+ OPSCC patients. METHODS: We created an immune score (UWO3) associated with survival outcomes in six independent cohorts comprising 906 patients, including blinded retrospective and prospective external validations. Two aggressive radiation de-escalation cohorts were used to assess the ability of UWO3 to identify patients who recur. Multivariate Cox models were used to assess the associations between the UWO3 immune class and outcomes. FINDINGS: A three-gene immune score classified patients into three immune classes (immune rich, mixed, or immune desert) and was strongly associated with disease-free survival in six datasets, including large retrospective and prospective datasets. Pooled analysis demonstrated that the immune rich group had superior disease-free survival compared to the immune desert (HR = 9.0, 95% CI: 3.2-25.5, P = 3.6 × 10-5) and mixed (HR = 6.4, 95% CI: 2.2-18.7, P = 0.006) groups after adjusting for age, sex, smoking status, and AJCC8 clinical stage. Finally, UWO3 was able to identify patients from two small treatment de-escalation cohorts who remain disease-free after aggressive de-escalation to 30 Gy radiation. INTERPRETATION: With additional prospective validation, the UWO3 score could enable biomarker-driven clinical decision-making for patients with HPV+ OPSCC based on robust outcome prediction across six independent cohorts. Prospective de-escalation and intensification clinical trials are currently being planned. FUNDING: CIHR, European Union, and the NIH

Data assimilation considerations for improved ocean predictability during the Gulf of Mexico Grand Lagrangian Deployment (GLAD)

•Extensive drifter observations allow new understanding to data assimilation.•Background error covariance is the point at which assumptions have historically been placed.•Components of background error covariance are tested to determine impact.•Amplitude of background error covariance is a critical factor.•Time correlation in background errors must be considered in 3DVar and 4DVar.Ocean prediction systems rely on an array of assumptions to optimize their data assimilation schemes. Many of these remain untested, especially at smaller scales, because sufficiently dense observations are very rare. A set of 295 drifters deployed in July 2012 in the north-eastern Gulf of Mexico provides a unique opportunity to test these systems down to scales previously unobtainable. In this study, background error covariance assumptions in the 3DVar assimilation process are perturbed to understand the effect on the solution relative to the withheld dense drifter data. Results show that the amplitude of the background error covariance is an important factor as expected, and a proposed new formulation provides added skill. In addition, the background error covariance time correlation is important to allow satellite observations to affect the results over a period longer than one daily assimilation cycle. The results show the new background error covariance formulations provide more accurate placement of frontal positions, directions of currents and velocity magnitudes. These conclusions have implications for the implementation of 3DVar systems as well as the analysis interval of 4DVar systems

Immune-based classification of HPV-associated oropharyngeal cancer with implications for biomarker-driven treatment de-intensification

Background There is significant interest in treatment de-escalation for human papillomavirus-associated (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) patients given the generally favourable prognosis. However, 15-30% of patients recur after primary treatment, reflecting a need for improved risk-stratification tools. We sought to develop a molecular test to risk stratify HPV+ OPSCC patients. Methods We created an immune score (UWO3) associated with survival outcomes in six independent cohorts comprising 906 patients, including blinded retrospective and prospective external validations. Two aggressive radiation de-escalation cohorts were used to assess the ability of UWO3 to identify patients who recur. Multivariate Cox models were used to assess the associations between the UWO3 immune class and outcomes. Findings A three-gene immune score classified patients into three immune classes (immune rich, mixed, or immune desert) and was strongly associated with disease-free survival in six datasets, including large retrospective and prospective datasets. Pooled analysis demonstrated that the immune rich group had superior disease-free survival compared to the immune desert (HR = 9.0, 95% CI: 3.2-25.5, P = 3.6 x 10-5) and mixed (HR = 6.4, 95% CI: 2.2-18.7, P = 0.006) groups after adjusting for age, sex, smoking status, and AJCC8 clinical stage. Finally, UWO3 was able to identify patients from two small treatment de-escalation cohorts who remain disease-free after aggressive de-escalation to 30 Gy radiation. Interpretation With additional prospective validation, the UWO3 score could enable biomarker-driven clinical decision-making for patients with HPV+ OPSCC based on robust outcome prediction across six independent cohorts. Prospective de-escalation and intensification clinical trials are currently being planned. Copyright (C) 2022 The Author(s). Published by Elsevier B.V