Citations

Introduction Social media platforms, particularly X (formerly Twitter), play an influential role in professional networking and information dissemination. This study aimed to examine X usage trends among faculty in a single department of surgery at a large academic institution. Methods Faculty X accounts were analyzed from January to June 2022. Metrics such as follower count, number of accounts followed, and post (formerly: tweets) types (original/quoted reposts) were studied. Themes of posts were categorized as personal, promotional, educational, or related to academic events/conferences. Associations between faculty rank, division, gender, and post metrics were explored using Mann-Whitney U and Kruskal-Wallis tests. Results Of 133 faculty members, 53 (39.85%) had X accounts, with 3 excluded due to privacy settings. A total of 3476 posts were analyzed, averaging 0-34 posts/month per faculty. Categories included professional (63%, n = 2174), educational (19%, n = 653), and personal (13%, n = 436). No significant associations were found between faculty gender/division and posting rates. However, faculty rank correlated significantly with primary post categories ( P < 0.01). Associate professors, and professors posted more about academic events (2% and 1%) than instructors or assistant professors (1%). The most followed faculty actively promoted colleagues’ work through reposting. Conclusion Less than half the faculty in a single department of surgery engaged with X. Those active predominantly used it for promotion, followed by education and personal use. Adoption remains limited, highlighting opportunities for growth in utilizing X for academic dissemination.

Abstract The sections in this article are: Effects of Anesthesia on the Chest Wall Anesthesia With Spontaneous Breathing Anesthesia‐Paralysis With Mechanical Ventilation of the Lungs Effects of Anesthesia on FRC Effects of Anesthesia on Pressure‐Volume Relationships Total Respiratory System Lungs Chest Wall Mechanisms for Changes in Pressure‐ Volume Relationships Effects of Anesthesia on Pressure‐Flow Relationships Effects of Anesthesia on Intrapulmonary Inspired‐Gas Distribution Anesthesia With Spontaneous Breathing Anesthesia‐Paralysis With Mechanical Ventilation of the Lungs Conclusions

INTRODUCTION: We conducted a retrospective cohort study comparing the safety of advanced therapies in patients with ulcerative colitis (UC). METHODS: Using an administrative claims database (OptumLabs Data Warehouse), we identified patients with UC who initiated treatment with tumor necrosis factor-α (TNF) antagonists, anti-integrin agents, anti-interleukin, Janus kinase inhibitors (JAK), or sphingosine-1 phosphate receptor modulators between 2016 and 2022 and had followed up for at least 1 year before and after treatment initiation. We compared the risk of serious infections, venous thromboembolism, and major adverse cardiovascular events through multinomial propensity score-based inverse probability weighting, with propensity scores estimated through generalized boosted models that accounted for disease characteristics, healthcare utilization, comorbidities, and previous and concomitant medications, and the competing risk of mortality. We calculated cause-specific hazard ratios (HR) and 95% confidence intervals for multiple treatment comparisons. RESULTS: We included 9,430 patients with UC treated with TNF antagonists (n = 4,111), anti-integrins (n = 3,165), anti-ILs (n = 1,342), JAK inhibitors (n = 701), or sphingosine-1 phosphate receptor modulators (n = 111), followed over median 27 months. After adjusting for confounding variables, anti-ILs were associated with a lower risk of serious infections compared with TNF antagonists (HR, 0.66 [95% confidence interval, 0.51–0.87]) and anti-integrins (HR, 0.75 [0.57–0.98]). JAK inhibitors were associated with a lower risk of serious infections compared with TNF antagonists (HR, 0.66 [0.46–0.94]). The incidence of venous thromboembolism (incidence rate, 1.4–2.0 per 100 py) and major adverse cardiovascular event (0.5–1.0 per 100 py) was very low, without any significant differences across agents. DISCUSSION: In a real-world cohort of patients with UC, anti-ILs and JAK inhibitors were associated with a lower risk of serious infections and may offer net benefit, especially in patients with previous TNF antagonist exposure.

Abstract Aberrant DNA methylation and copy-number alterations (CNA) drive Barrett’s esophagus progression to esophageal adenocarcinoma; however, their combined utility for early detection is unclear. We aimed to identify and validate methylated DNA markers (MDM) and CNAs to distinguish esophageal adenocarcinoma/high-grade dysplasia (HGD) from nondysplastic Barrett’s esophagus (NDBE). In this multiphase, multicenter study, we discovered and validated MDMs and quantified CNAs utilizing whole-genome methylation sequencing of esophageal brushings. DNA biomarkers identified from discovery were further validated in independent patients with paired esophageal brushing and swallowed capsule sponge samples. MDMs were filtered against a reduced representation bisulfite sequencing dataset obtained from independent tissue samples to advance only concordant candidates. CNA burden was quantified using ichorCNA-derived aneuploidy scores (AS). Two hundred MDMs discovered in HGD (N = 18) and esophageal adenocarcinoma (N = 18) versus NDBE brushing samples (N = 18) were tested in independent samples (N = 146). A 52-MDM panel achieved a cross-validated AUC of 0.88 [95% confidence interval (CI), 0.82–0.95]; the addition of AS improved discrimination of HGD/esophageal adenocarcinoma from NDBE to 0.91 (95% CI, 0.86–0.97) AUC. At 80% specificity, the combined model detected 93% of esophageal adenocarcinoma and 88% of HGD cases. In paired capsule sponge samples, a 58-MDM panel achieved a cross-validated AUC of 0.77 (95% CI, 0.66–0.88); a combined 58-MDM and AS model achieved AUC 0.80 (95% CI, 0.7–0.9). MDMs and AS discerned HGD/esophageal adenocarcinoma from normal esophagus/NDBE in endoscopic brushing and capsule sponge samples. This approach may improve Barrett’s esophagus surveillance. Prevention Relevance: This study demonstrates that combining epigenetic and genomic biomarkers across minimally invasive sampling methods can accurately distinguish HGD/esophageal adenocarcinoma from nondysplastic Barrett’s esophagus, offering promising, less invasive strategies to improve BE surveillance and enable endoscopic therapy for esophageal adenocarcinoma prevention and treatment.

Abstract Purpose: Isocitrate dehydrogenase (IDH) 1/2–isoform inhibitors have clinical efficacy in IDH1/IDH2-mutated neoplasms. However, primary resistance and secondary resistance limit their therapeutic potential. LY3410738, an oral, brain-penetrant, dual IDH1/IDH2-mutated isoform-selective inhibitor, was designed to overcome resistance. Patients and Methods: This global, multicenter, open-label, phase I study of patients with IDH-mutant solid tumors evaluated LY3410738 as monotherapy (dose escalation) for advanced solid tumors in combination with cisplatin–gemcitabine (CISGEM) for newly diagnosed cholangiocarcinoma or with durvalumab for relapsed/refractory cholangiocarcinoma (dose expansion; NCT04521686). Primary objectives were the maximum tolerated dose, recommended phase II dose, and preliminary antitumor activity. Safety, pharmacokinetics, inhibition of D-2-hydroxyglutarate, and ctDNA were assessed. Results: Overall, 119 patients received LY3410738 alone (N = 94) or in combination with CISGEM (N = 19) or durvalumab (N = 6). No dose-limiting toxicities were observed; the maximum tolerated dose was not determined. Common adverse events included nausea, vomiting, and decreased appetite. Overall response rates of 5.2% and 11.1% and disease control rates of 56.9% and 63.0% were observed for patients with relapsed/refractory IDH1- or IDH2-mutant cholangiocarcinoma or IDH1-mutant glioma, respectively. D-2-hydroxyglutarate normalization was rapid and durable. In dose-expansion cohorts, combination treatments were tolerable, with one dose-limiting toxicity in the durvalumab cohort. LY3410738 plus CISGEM demonstrated a response rate of 42.1%, a median duration of response of 8.1 months, and a median progression-free survival of 10.2 months for patients with newly diagnosed IDH-mutant cholangiocarcinoma. Conclusions: LY3410738 demonstrated largely cytostatic antitumor activity in IDH1- or IDH2-mutated cholangiocarcinoma and IDH1-mutated gliomas. LY3410738 plus CISGEM exhibited favorable antitumor activity in patients with treatment-naïve IDH-mutated cholangiocarcinoma, warranting further exploration as a treatment strategy.

Objectives: The number of medial ulnar collateral ligament (MUCL) reconstructions are increasing. The epidemiology surrounding revision MUCL reconstructions in professional baseball players has not been well defined. The purpose of this study was to report the epidemiology of revision MUCL reconstruction in professional baseball players. The authors hypothesized that the number of revision MUCL reconstructions would increase over time and that the return to sport rate at the same level of play would be less than 70%. Methods: All professional baseball pitchers who underwent revision MUCL reconstruction between 2010-2023 were identified using the MLB Health and Injury Tracking System (HITS). Rate of return and time to return to play (RTP) and return to same level of play (RTSL) was recorded and analyzed for pitchers with a minimum follow up of 2 years. Surgical variables including technique and graft choice were also recorded. Results: Overall, 191 pitchers (avg age 26.0 years), underwent revision MUCL reconstruction. The average time between primary and revision surgery was 1,381 days (45 months). 130 (68%) of these players were MLB pitchers and the other 61 (32%) were MiLB pitchers. 59% of pitchers were able to RTSL at an average of 604 ± 250 days after surgery. 2023 was the year with most revision MUCL reconstructions (n = 27) and the fewest reconstructions were performed in 2010 and 2011 (n = 4). Monthly distribution demonstrates the highest surgery months to be May (17%), June (20%), and July (17%). Hamstring tendon autograft was found to be the most commonly used graft source (n = 90, 47%), compared to palmaris longus autograft (n = 67, 35%). No significant differences were found in the types of grafts used over time ( P = .238 for palmaris and P = .133 for hamstring). In terms of tunnel configuration, both the Modified Jobe and Docking techniques were used in equal occurrence (n = 70, 37%) Conclusions: Following revision MUCL reconstruction, only 72% of professional baseball pitchers were able to return to play at any level at an average of 556 days (18 months), and only 59% were able to return to the same level of play at an average of 604 days (20 months). The average time between primary and revision MUCL reconstruction was 45 months (3.75 years). Pitchers should be counseled on the relatively low RTSL rate and the prolonged time to RTSL.

Abstract Glioblastoma is the most common type of malignant primary brain tumor and a major cause of morbidity and mortality. In 2021, the World Health Organization updated the classification of Central Nervous System (CNS) tumors to restrict glioblastomas to isocitrate dehydrogenase-wildtype (IDHwt) tumors, improving understanding of the prognosis and optimal therapy for these tumors. This revision also enables more homogeneous populations of patients to be enrolled in clinical trials, facilitating the evaluation of novel therapies. In this updated consensus review from the Society for Neuro-Oncology (SNO) and the European Association of Neuro-Oncology (EANO), the current management of patients with glioblastoma is discussed. In addition, novel therapies such as immunotherapies, viral therapies, targeted molecular therapies, theranostics, and antibody–drug conjugates will be reviewed, as well as the current challenges and future directions for research.

Abstract In this work, we seek to characterize the learned feature space of cancer drug response prediction models in a drug-blind setting and quantify the limits of their generalizability. Drug-blind prediction failure describes the inability of models to predict cell line response to drugs in the test set that are not present during training. The experiments performed in this study utilize a two-arm multilayer perceptron model where embeddings for drugs and cell-lines are calculated separately and then concatenated to predict response. Drug structure is represented by Morgan fingerprint while cell lines utilize gene expression values. We first examine the connection between learned drug features and cell lines by permuting responses within both cell lines and drugs during model training. When permuting response values within cell lines, model performance was entirely depleted, but permutation of responses within drugs resulted in only a 10-15% decrease in performance. This displays the bulk of model performance is due to learned distributions of response for each drug. We also determine the impact of dataset size on drug-blind performance. Increasing the cell line examples per drug did not improve performance, but drug-blind performance exhibited higher variance than mixed set testing. From these experiments, we hypothesized that drug-blind performance was a function of the set of drugs in the training set. We trained a set of 208 models with varying training set and constant test set and fit an elastic net model using drugs in the training set as features and performance of each model as the target. We were able to accurately predict the drug-blind performance of a model, measured in Pearson correlation, based on the drugs in the training set with a mean absolute error of 0.049. We then trained a set of 1641 models where all drugs in the dataset were present in the test set but only 50% of unique drugs were present during training. Hierarchical clustering on the coefficients of an elastic net model fit to each unique drug’s performance across all models shows drugs cluster into groups that correspond to specific mechanisms of action. By examining the relationship between drug embeddings during model training, we see that decreasing validation loss corresponds to reinforcement of mechanistic relationships of drugs not captured by raw Morgan fingerprints. Finally, we show that training on a dataset confined to a single mechanism of action significantly improves overall mixed set performance on those drugs against training on the entire set of drugs. In this study, we identify that drug-blind performance in current large pharmacogenomic datasets is limited to generalization within drug mechanism of action classes. Therefore, global drug-blind prediction benchmarking is a poor indicator of model generalization as the data itself creates these limits, not model architecture. As more data is collected on novel anti-cancer compounds, we hope that the results presented here create a foundation on which to measure progress in cancer drug generalization. Citation Format: William G. Herbert, Paul A. Jensen, Nicholas Chia, Marina RS. Walther-Antonio. Monotherapy cancer drug-blind response prediction is limited to intraclass generalization [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Artificial Intelligence and Machine Learning; 2025 Jul 10-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(13_Suppl):Abstract nr A005.