Background: Natural language processing models such as ChatGPT can generate text-based content and are poised to become a major information source in medicine and beyond. The accuracy and completeness of ChatGPT for medical queries is not known. Methods: Thirty-three physicians across 17 specialties generated 284 medical questions that they subjectively classified as easy, medium, or hard with either binary (yes/no) or descriptive answers. The physicians then graded ChatGPT-generated answers to these questions for accuracy (6-point Likert scale; range 1 – completely incorrect to 6 – completely correct) and completeness (3-point Likert scale; range 1 – incomplete to 3 - complete plus additional context). Scores were summarized with descriptive statistics and compared using Mann-Whitney U or Kruskal-Wallis testing. Results: Across all questions (n=284), median accuracy score was 5.5 (between almost completely and completely correct) with mean score of 4.8 (between mostly and almost completely correct). Median completeness score was 3 (complete and comprehensive) with mean score of 2.5. For questions rated easy, medium, and hard, median accuracy scores were 6, 5.5, and 5 (mean 5.0, 4.7, and 4.6; p=0.05). Accuracy scores for binary and descriptive questions were similar (median 6 vs. 5; mean 4.9 vs. 4.7; p=0.07). Of 36 questions with scores of 1-2, 34 were re-queried/re-graded 8-17 days later with substantial improvement (median 2 vs. 4; p<0.01). Conclusions: ChatGPT generated largely accurate information to diverse medical queries as judged by academic physician specialists although with important limitations. Further research and model development are needed to correct inaccuracies and for validation.

Tumors continually shed DNA into the blood where it can be detected as circulating tumor DNA (ctDNA). While this phenomenon has been recognized for decades, techniques that are sensitive and specific enough to robustly detect ctDNA have only become available recently. Quantification of ctDNA represents a new approach for cancer detection and disease burden quantification that has the potential to revolutionize response assessment and personalized treatment in radiation oncology. Analysis of ctDNA has many potential applications, including detection of minimal residual disease following radiotherapy, non-invasive tumor genotyping, and early detection of tumor recurrence. Ultimately ctDNA-based assays could lead to personalization of therapy based on identification of somatic alterations present in tumors and changes in ctDNA concentrations before and after treatment. In this review, we will discuss methods of ctDNA detection and clinical applications of ctDNA-based biomarkers in radiation oncology, with a focus on recently developed techniques that employ next generation sequencing for ctDNA quantification.

CDC25A phosphatase activates multiple cyclin-dependent kinases (CDK) during cell cycle progression. Inactivation of CDC25A by ubiquitin-mediated degradation is a major mechanism of DNA damage-induced S-G 2 checkpoint.

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Activation of the anaphase-promoting complex/cyclosome (APC/C) by Cdc20 is critical for the metaphase–anaphase transition. APC/C-Cdc20 is required for polyubiquitination and degradation of securin and cyclin B at anaphase onset. The spindle assembly checkpoint delays APC/C-Cdc20 activation until all kinetochores attach to mitotic spindles. In this study, we demonstrate that a HECT (homologous to the E6-AP carboxyl terminus) ubiquitin ligase, Smurf2, is required for the spindle checkpoint. Smurf2 localizes to the centrosome, mitotic midbody, and centromeres. Smurf2 depletion or the expression of a catalytically inactive Smurf2 results in misaligned and lagging chromosomes, premature anaphase onset, and defective cytokinesis. Smurf2 inactivation prevents nocodazole-treated cells from accumulating cyclin B and securin and prometaphase arrest. The silencing of Cdc20 in Smurf2-depleted cells restores mitotic accumulation of cyclin B and securin. Smurf2 depletion results in enhanced polyubiquitination and degradation of Mad2, a critical checkpoint effector. Mad2 is mislocalized in Smurf2-depleted cells, suggesting that Smurf2 regulates the localization and stability of Mad2. These data indicate that Smurf2 is a novel mitotic regulator.