Search

Background: Minimally invasive lung resections can be particularly challenging in obese patients. We hypothesized robotic surgery (RTS) is associated with less conversion to thoracotomy than video-assisted thoracoscopic surgery (VATS) in obese populations., Methods: The Society of Thoracic Surgeons General Thoracic Surgery Database, Epithor French National Database, and McMaster University Thoracic Surgical Database were queried for obese (body mass index ≥30 kg/m 2 ) patients who underwent VATS or RTS lobectomy or segmentectomy for clinical T1-2, N0-1 non-small cell lung cancer between 2015 and 2019. Propensity score adjusted logistic regression analysis was used to compare the rate of conversion to thoracotomy between the VATS and RTS cohorts., Results: Overall, 8108 patients (The Society of Thoracic Surgeons General Thoracic Surgery Database: n = 7473; Epithor: n = 572; McMaster: n = 63) met inclusion criteria with a mean (SD) age of 66.6 (9) years and body mass index of 34.7 (4.5) kg/m 2 . After propensity score adjusted multivariable analysis, patients who underwent VATS were >5-times more likely to experience conversion to thoracotomy than those who underwent RTS (odds ratio, 5.33; 95% CI, 4.14-6.81; P < .001). There was a linear association between the degree of obesity and odds ratio of VATS conversion to thoracotomy compared with RTS. VATS patients had a longer mean length of stay (5.0 vs 4.3 days, P < .001), higher rate of respiratory failure (2.8% [168 of 5975] vs 1.8% [39 of 2133], P = .026), and were less likely to be discharged to their home (92.5% [5525 of 5975] vs 94.3% [2012 of 2133]; P = .013) compared with RTS patients., Conclusions: In obese patients, RTS anatomic lung resection is associated with a lower rate of conversion to thoracotomy than VATS., (Copyright © 2022 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: Endobronchial ultrasound (EBUS) has features that allow a high accuracy for predicting lymph node (LN) malignancy. However their clinical application remains limited because of high operator dependency. We hypothesized that an artificial intelligence algorithm (NeuralSeg; NeuralSeg Ltd, Hamilton, Ontario, Canada) is capable of accurately identifying and predicting LN malignancy based on EBUS images., Methods: In the derivation phase EBUS images were segmented twice by an endosonographer and used as controls in 5-fold cross-validation training of NeuralSeg. In the validation phase the algorithm was tested on new images it had not seen before. Logistic regression and receiver operator characteristic curves were used to determine NeuralSeg's capability of discrimination between benign and malignant LNs, using pathologic specimens as the gold standard., Results: Two hundred ninety-eight LNs from 140 patients were used for derivation and 108 LNs from 47 patients for validation. In the derivation cohort NeuralSeg was able to predict malignant LNs with an accuracy of 73.8% (95% confidence interval [CI], 68.4%-78.7%). In the validation cohort NeuralSeg had an accuracy of 72.9% (95% CI, 63.5%-81.0%), specificity of 90.8% (95% CI, 81.9%-96.2%), and negative predictive value of 75.9% (95% CI, 71.5%-79.9%). NeuralSeg showed higher diagnostic discrimination during validation compared with derivation (c-statistic = 0.75 [95% CI, 0.65-0.85] vs 0.63 [95% CI, 0.54-0.72], respectively)., Conclusions: NeuralSeg is able to accurately rule out nodal metastasis and can possibly be used as an adjunct to EBUS when nodal biopsy is not possible or inconclusive. Future work to evaluate the algorithm in a clinical trial is required., (Copyright © 2022 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Background: Academic surgeons are encouraged to promote their work on social media. We hypothesized that thoracic surgeons who are active on Twitter have a higher research citation index (Hirsch index [h-index]) than their counterparts who are not., Methods: Thoracic surgeons on CTSNet.org in Canada and the United States were queried for profiles with an h-index on Google Scholar and/or Research Gate in July 2018. Surgeons were categorized by whether they possessed a Twitter account (T+) or not (T-), and h-index values were compared. Within the T+ cohort a multivariate regression model was used to identify independent predictors of increased h-index among variables related to Twitter activity., Results: Of 3741 surgeons queried, 19.3% (722) had a known h-index. The mean h-index for the entire cohort was 14.54 (SD, 15.73). The median h-index was 10 (range, 0-121), and the 75th percentile h-index was 20. T+ surgeons had a median h-index of 10 (range, 0-66), and T- surgeons had a median h-index of 10 (range, 0-72; P = .25). The 75th percentile h-index for T+ surgeons was 23 compared with 20 for T- surgeons (P = .24). For T+ surgeons the regression model identified the number of followers (P = .029), the number of people followed (P = .048), and the frequency of tweeting (P = .046) as independent predictors of a higher h-index., Conclusions: The median h-index for an academic thoracic surgeon in Canada and the United States is 10. Surgeons who engage in Twitter activity are more likely to have their research cited by others., (Copyright © 2020 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Hsp70s are important cancer chaperones that act upstream of Hsp90 and exhibit independent anti-apoptotic activities. To develop chemical tools for the study of human Hsp70, we developed a homology model that unveils a previously unknown allosteric site located in the nucleotide binding domain of Hsp70. Combining structure-based design and phenotypic testing, we discovered a previously unknown inhibitor of this site, YK5. In cancer cells, this compound is a potent and selective binder of the cytosolic but not the organellar human Hsp70s and has biological activity partly by interfering with the formation of active oncogenic Hsp70/Hsp90/client protein complexes. YK5 is a small molecule inhibitor rationally designed to interact with an allosteric pocket of Hsp70 and represents a previously unknown chemical tool to investigate cellular mechanisms associated with Hsp70., (Copyright © 2013 Elsevier Ltd. All rights reserved.)