Thick primary melanoma has a heterogeneous tumor biology: an institutional series

<p>Abstract</p> <p>Background</p> <p>Thick melanomas (TM) ≥4 mm have a high risk for nodal and distant metastases. Optimal surgical management, prognostic significance of sentinel node biopsy (SLNB), and benefits of interferon (IFN) for these patients are unclear. As a continuum of increasing tumor thickness is placed into a single TM group, differences in biologic and clinical behavior may be lost. The purpose of this study was to better characterize the diverse biology in TM, including the value of increasing thickness and nodal status information, potentially identifying high risk TM subgroups that may warrant more aggressive treatment/follow up.</p> <p>Methods</p> <p>155 consecutive TM patients treated at a single institution between 1971 and 2007 were retrospectively reviewed. Patient, disease and treatment features were analyzed with respect to disease-free (DFS) and overall survival (OS).</p> <p>Results</p> <p>Median patient age was 66 years and 68% of patients were men. The trunk was the most common TM location (35%), followed by the head and neck (29%) and lower extremities (20%). Median thickness was 6 mm and 61% were ulcerated. 6% patients had stage IV disease, 12% had clinical nodal metastases. Clinically negative lymph node basins were treated by observation (22 patients - 15.4%), elective lymph node dissection (ELND) (24 patients - 17.6%) or SLNB (91 patients - 67%). 75% of ELND's and 53% of SLNB's were positive. Completion node dissection was performed in 38 SLNB+ patients and 22% had additional positive nodes. 17% of the study patients received IFN. At median follow up of 26 months, 5 year DFS and OS were 42% and 43.6%. For SLNB positive vs negative, median DFS were 22 vs 111 months (p = 0.006) and median OS were 41 vs 111 months (p = 0.006). When stratified by tumor thickness ≤ vs > 6 mm, 5 year DFS was 58.3% vs 20% (p < 0.0001) and OS was 62% vs 20% (P < 0.0001). IFN had no impact on DFS or OS (p = 0.98 and 0.8 respectively).</p> <p>Conclusion</p> <p>Within the high risk group of patients with TM, cases with tumor thickness > 6 mm or a positive SLNB had a significantly worse DFS and OS (p < .0001, <.0001 and .006, .006).</p

Community‐wide validation of geospace model ground magnetic field perturbation predictions to support model transition to operations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98787/1/swe20056.pd

Community‐wide validation of geospace model local K‐index predictions to support model transition to operations

We present the latest result of a community‐wide space weather model validation effort coordinated among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), model developers, and the broader science community. Validation of geospace models is a critical activity for both building confidence in the science results produced by the models and in assessing the suitability of the models for transition to operations. Indeed, a primary motivation of this work is supporting NOAA/SWPC’s effort to select a model or models to be transitioned into operations. Our validation efforts focus on the ability of the models to reproduce a regional index of geomagnetic disturbance, the local K‐index. Our analysis includes six events representing a range of geomagnetic activity conditions and six geomagnetic observatories representing midlatitude and high‐latitude locations. Contingency tables, skill scores, and distribution metrics are used for the quantitative analysis of model performance. We consider model performance on an event‐by‐event basis, aggregated over events, at specific station locations, and separated into high‐latitude and midlatitude domains. A summary of results is presented in this report, and an online tool for detailed analysis is available at the CCMC.Key PointsReport community‐wide model validation resultsEvaluate ability of models to predict a local index of magnetic perturbationAnalysis directly led to selection of models to transition to operations at NOAA/SWPCPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134170/1/swe20333-sup-0001-supplementary.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134170/2/swe20333_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/134170/3/swe20333.pd

Correction: Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey

Correction: Surgeons' perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international surve

Surgeons’ perspectives on artificial intelligence to support clinical decision-making in trauma and emergency contexts: results from an international survey

Background: Artificial intelligence (AI) is gaining traction in medicine and surgery. AI-based applications can offer tools to examine high-volume data to inform predictive analytics that supports complex decision-making processes. Time-sensitive trauma and emergency contexts are often challenging. The study aims to investigate trauma and emergency surgeons’ knowledge and perception of using AI-based tools in clinical decision-making processes. Methods: An online survey grounded on literature regarding AI-enabled surgical decision-making aids was created by a multidisciplinary committee and endorsed by the World Society of Emergency Surgery (WSES). The survey was advertised to 917 WSES members through the society’s website and Twitter profile. Results: 650 surgeons from 71 countries in five continents participated in the survey. Results depict the presence of technology enthusiasts and skeptics and surgeons’ preference toward more classical decision-making aids like clinical guidelines, traditional training, and the support of their multidisciplinary colleagues. A lack of knowledge about several AI-related aspects emerges and is associated with mistrust. Discussion: The trauma and emergency surgical community is divided into those who firmly believe in the potential of AI and those who do not understand or trust AI-enabled surgical decision-making aids. Academic societies and surgical training programs should promote a foundational, working knowledge of clinical AI

Factors regulating the Great Calcite Belt in the Southern Ocean and its biogeochemical significance

The Great Calcite Belt (GCB) is a region of elevated surface reflectance in the Southern Ocean (SO) covering ~16% of the global ocean and is thought to result from elevated, seasonal concentrations of coccolithophores. Here we describe field observations and experiments from two cruises that crossed the GCB in the Atlantic and Indian sectors of the SO. We confirm the presence of coccolithophores, their coccoliths, and associated optical scattering, located primarily in the region of the subtropical, Agulhas, and Subantarctic frontal regions. Coccolithophore-rich regions were typically associated with high-velocity frontal regions with higher seawater partial pressures of CO2 (pCO2) than the atmosphere, sufficient to reverse the direction of gas exchange to a CO2 source. There was no calcium carbonate (CaCO3) enhancement of particulate organic carbon (POC) export, but there were increased POC transfer efficiencies in high-flux particulate inorganic carbon regions. Contemporaneous observations are synthesized with results of trace-metal incubation experiments, 234Th-based flux estimates, and remotely sensed observations to generate a mandala that summarizes our understanding about the factors that regulate the location of the GCB