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Black sea bass (Centropristis striata; BSB) are a commercially managed species with an increasing population in the Northwest Atlantic Ocean. Understanding their movement ecology can be difficult due to their wide distribution and ability to inhabit both inshore and offshore reef habitats. BSB have been studied using a range of tagging techniques, and here we present the results of the first deployments of pop‐up satellite archival tags (PSAT) on this species. During 2019 and 2021, we conducted four fishing trips within the southern Mid‐Atlantic Bight region of the NW Atlantic and tagged a total of 30 fish with T‐bar tags and external data loggers, of which 4 received a PSAT and the rest received a Star‐Oddi conductivity–temperature–depth (CTD) archival tag. All PSATs transmitted some data, with short attachment durations (8–32 days) relative to the programmed release of 250 days, and we did not recover a Star‐Oddi tag. External tag attachment techniques need to be examined and improved before continued deployment of larger data loggers on BSB. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer patients, especially long-distance patients, often struggle to receive timely and precise medical information and support for their symptom management and survivorship care. ChatGPT-4's responses to queries concerning head and neck (HN) cancer remain questionable. The purpose of this study was to develop and validate a retrained large language model (LLM) for HN cancer patients. In this cross-sectional study, the presented LLM was retrained with a high-quality user-defined knowledge base. The responses from the LLM to patients' questions were validated against human responses, and the model showed a superior performance, with average scores of 4.25 for accuracy, 4.35 for clarity, 4.22 for completeness, and 4.32 for relevance, on a 5-point scale. The confined-trained LLM with a high-quality user-defined knowledge base demonstrates high accuracy, clarity, completeness, and relevance in offering evidence-based information and guidance on the symptom management and survivorship care for head and neck cancer patients. Purpose: This study aimed to develop a retrained large language model (LLM) tailored to the needs of HN cancer patients treated with radiotherapy, with emphasis on symptom management and survivorship care. Methods: A comprehensive external database was curated for training ChatGPT-4, integrating expert-identified consensus guidelines on supportive care for HN patients and correspondences from physicians and nurses within our institution's electronic medical records for 90 HN patients. The performance of our model was evaluated using 20 patient post-treatment inquiries that were then assessed by three Board certified radiation oncologists (RadOncs). The rating of the model was assessed on a scale of 1 (strongly disagree) to 5 (strongly agree) based on accuracy, clarity of response, completeness s, and relevance. Results: The average scores for the 20 tested questions were 4.25 for accuracy, 4.35 for clarity, 4.22 for completeness, and 4.32 for relevance, on a 5-point scale. Overall, 91.67% (220 out of 240) of assessments received scores of 3 or higher, and 83.33% (200 out of 240) received scores of 4 or higher. Conclusion: The custom-trained model demonstrates high accuracy in providing support to HN patients offering evidence-based information and guidance on their symptom management and survivorship care. [ABSTRACT FROM AUTHOR]

Background: Communication and interpersonal skills are essential medical components of oncology patient care. Patients and families rely on physicians for treatment, expertise, guidance, hope, meaning, and compassion throughout a life-threatening illness. A provider's inability to empathize with patients is linked to physician-related fatigue and burnout. Because oncology training programs focus on teaching evidence-based medicine and clinical acumen, little time may be dedicated to professional development and acquisition of interactive skills. Traditional communication courses typically include two components: formal, knowledge-based learning skills, which are gained from didactic lectures, and role-playing, which usually occurs in small groups. We report the implementation of a novel longitudinal communication curriculum for trainees in Oncology. Materials and Methods: At a single-center institution, an innovative communication curriculum titled "REFLECT" (Respect, Empathy, Facilitate Effective Communication, Listen, Elicit Information, Compassion, and Teach Others) was implemented for radiation oncology residents and medical oncology fellows to improve and refine physician/patient interactions. All oncology specialty residents and fellows were eligible to participate in this communication curriculum. The curriculum emphasized a reflective process to guide trainees through challenging scenarios. Results: Since October 2018, this comprehensive course consisted of quarterly (four hour) workshops comprising assigned reading, knowledge assessments, didactic lectures, expert guest lecturers, standardized patient simulations, role-playing, patient/expert panels, coaching, reflective writing, and debriefing/feedback sessions. The curriculum provided longitudinal communication training integrated with the learners' daily physician/patient encounters rather than occasional isolated experiences. Fifteen workshops have been completed. Each focused on navigating challenging situations with patients, loved ones, or colleagues. Conclusions: Future directions of the curriculum will entail improving the communication skills of oncology trainees and gathering communication improvement data to assess the program's success formally. [ABSTRACT FROM AUTHOR]

Background: The optimal approach for partial breast irradiation (PBI) is unknown. We investigated a novel de-intensified 3-fraction PBI regimen for photons, protons, and brachytherapy., Methods: A multicenter nonrandomized controlled trial with primary outcome of adverse cosmesis at 3 years versus pre-PBI. Eligibility criteria were ≥ age 50 years treated with breast-conserving surgery for node-negative estrogen receptor positive (ER+) invasive breast cancer or any ductal carcinoma in-situ (DCIS) measuring ≤ 2.5 cm. Photon and proton PBI were prescribed 21.9 Gy (RBE) and brachytherapy 21 Gy in 3 fractions. Radiotherapy technique and use of adjuvant endocrine therapy was selected at physician and patient discretion., Results: Between June 17, 2015 and July 13, 2017, 161 eligible patients were treated with photons (56), protons (49), or brachytherapy (56). Median patient age was 66.8 years. 126 (78.3%) had invasive breast cancer (all ER+) and 35 (21.7%) had DCIS (88.6% ER+). 54.0% of patients with invasive breast cancer and 25.8% of patients with ER+ DCIS initiated and adhered to prescribed endocrine therapy. The proportion of patients with adverse cosmesis (by trained nurse assessment) was 14.5% at baseline, 2.3% at 3 years (difference -12.2%, 95% CI (-100%, -6.4%)). Adverse cosmesis at last-follow-up, with median follow-up 5 years, was 5.7% by nurse assessment, 5.6% by panel assessment of digital photographs, and 5.2% by patient self-report. There were no observed clinically meaningful changes in other patient reported outcomes, and just two grade 2 or higher adverse events, both grade 2, in the brachytherapy cohort. 5-year local recurrence-free and progression-free survival were 98.0% and 95.5%, respectively. There were no local recurrences amongst 60 patients with invasive breast cancer and Ki67 ≤ 13.25%., Conclusions: De-intensified 3-day PBI provided favorable disease control, tolerability, and cosmetic outcomes, meeting the pre-specified criteria for acceptability. This approach is an attractive option for small node-negative ER+ BC and DCIS patients., Trial Registration: ClinicalTrials.gov identifier NCT02453737., Competing Interests: Conflicts of interest There are no conflicts of interest to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Background: Bolus materials have been used for decades in radiotherapy. Most frequently, these materials are utilized to bring dose closer to the skin surface to cover superficial targets optimally. While cavity filling, such as nasal cavities, is desirable, traditional commercial bolus is lacking, requiring other solutions. Recently, investigators have worked on utilizing 3D printing technology, including commercially available solutions, which can overcome some challenges with traditional bolus., Purpose: To utilize failure modes and effects analysis (FMEA) to successfully implement a comprehensive 3D printed bolus solution to replace commercial bolus in our clinic using a series of open-source (or free) software products., Methods: 3D printed molds for bespoke bolus were created by exporting the DICOM structures of the bolus designed in the treatment planning system and manipulated to create a multipart mold for 3D printing. A silicone (Ecoflex 00-30) mixture is poured into the mold and cured to form the bolus. Molds for sheet bolus of five thicknesses were also created. A comprehensive FMEA was performed to guide workflow adjustments and QA steps., Results: The process map identified 39 and 30 distinct steps for the bespoke and flat sheet bolus workflows, respectively. The corresponding FMEA highlighted 119 and 86 failure modes, with 69 shared between the processes. Misunderstanding of plan intent was a potential cause for most of the highest-scoring failure modes, indicating that physics and dosimetry involvement early in the process is paramount., Conclusion: FMEA informed the design and implementation of QA steps to guarantee a safe and high-quality comprehensive implementation of silicone bolus from 3D printed molds. This approach allows for greater adaptability not afforded by traditional bolus, as well as potential dissemination to other clinics due to the open-source nature of the workflow., (© 2024 The Author(s). Journal of Applied Clinical Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)