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4,087 results on '"K Oh"'

1. Adaptation of the socioecological model to address disparities in engagement of Black men in prostate cancer genetic testing

Author

Amy E. Leader, Timothy R. Rebbeck, William K. Oh, Alpa V. Patel, Eric P. Winer, LeeAnn O. Bailey, Leonard G. Gomella, Crystal Y. Lumpkins, Isla P. Garraway, Lisa B. Aiello, Monica L. Baskin, Heather H. Cheng, Kathleen A. Cooney, Amanda Ganzak, Daniel J. George, Susan Halabi, Feighanne Hathaway, Claire Healy, Joseph W. Kim, Michael S. Leapman, Stacy Loeb, Kara N. Maxwell, Christopher McNair, Todd M. Morgan, Breanne Prindeville, Howard R. Soule, Whitney L. Steward, Sakinah C. Suttiratana, Mary-Ellen Taplin, Kosj Yamoah, Thierry Fortune, Kris Bennett, Joshua Blanding-Godbolt, Laura Gross, and Veda N. Giri

Subjects
Prostate cancer, Genetic testing, Disparities, Health equity, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Black men consistently have higher rates of prostate cancer (PCA)- related mortality. Advances in PCA treatment, screening, and hereditary cancer assessment center around germline testing (GT). Of concern is the significant under-engagement of Black males in PCA GT, limiting the benefit of precision therapy and tailored cancer screening despite longstanding awareness of these disparities. To address these critical disparities, the Socioecological Model (SEM) was employed to develop comprehensive recommendations to overcome barriers and implement equitable strategies to engage Black males in PCA GT. Methods Clinical/research experts, national organization leaders, and community stakeholders spanning multiple regions in US and Africa participated in developing a framework for equity in PCA GT grounded in the SEM. A novel mixed-methods approach was employed to generate key areas to be addressed and informed statements for consensus consideration utilizing the modified Delphi model. Statements achieving strong consensus (> =75% agreement) were included in final equity frameworks addressing clinical/community engagement and research engagement. Results All societal levels of the SEM (interpersonal, institutional, community, and policy/advocacy) must deliver information about PCA GT to Black males that address benefits/limitations, clinical impact, hereditary cancer implications, with acknowledgment of mistrust (mean scores [MS] 4.57-5.00). Interpersonal strategies for information delivery included engagement of family/friends/peers/Black role models to improve education/awareness and overcome mistrust (MS 4.65-5.00). Institutional strategies included diversifying clinical, research, and educational programs and integrating community liaisons into healthcare institutions (MS 4.57-5.00). Community strategies included partnerships with healthcare institutions and visibility of healthcare providers/researchers at community events (MS 4.65–4.91). Policy/advocacy included improving partnerships between advocacy and healthcare/community organizations while protecting patient benefits (MS 4.57-5.00). Media strategies were endorsed for the first time at every level (MS 4.56-5.00). Conclusion The SEM-based equity frameworks proposed provide the first multidisciplinary strategies dedicated to increase engagement of Black males in PCA GT, which are critical to reduce disparities in PCA-mortality through informing tailored screening, targeted therapy, and cascade testing in families.

Published
2024
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2. Echocardiographic Diagnosis of Hypertrophic Cardiomyopathy by Machine Learning

Author

Nasibeh Zanjirani Farahani, PhD, Mateo Alzate Aguirre, MD, Vanessa Karlinski Vizentin, MD, Moein Enayati, PhD, J. Martijn Bos, MD, PhD, Andredi Pumarejo Medina, MD, Kathryn F. Larson, MD, Kalyan S. Pasupathy, PhD, Christopher G. Scott, MS, April L. Zacher, MS, Eduard Schlechtinger, MS, Bruce K. Daniels, RDCS, Vinod C. Kaggal, MS, Jeffrey B. Geske, MD, Patricia A. Pellikka, MD, Jae K. Oh, MD, Steve R. Ommen, MD, Garvan C. Kane, MD, Michael J. Ackerman, MD, PhD, and Adelaide M. Arruda-Olson, MD, PhD

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Objective: To develop machine learning tools for automated hypertrophic cardiomyopathy (HCM) case recognition from echocardiographic metrics, aiming to identify HCM from standard echocardiographic data with high performance. Patients and Methods: Four different random forest machine learning models were developed using a case-control cohort composed of 5548 patients with HCM and 16,973 controls without HCM, from January 1, 2004, to March 15, 2019. Each patient with HCM was matched to 3 controls by sex, age, and year of echocardiography. Ten-fold crossvalidation was used to train the models to identify HCM. Variables included in the models were demographic characteristics (age, sex, and body surface area) and 16 standard echocardiographic metrics. Results: The models were differentiated by global, average, individual, or no strain measurements. Area under the receiver operating characteristic curves (area under the curve) ranged from 0.92 to 0.98 for the 4 separate models. Area under the curves of model 2 (using left ventricular global longitudinal strain; 0.97; 95% CI, 0.95-0.98), 3 (using averaged strain; 0.96; 95% CI, 0.94-0.97), and 4 (using 17 individual strains per patient; 0.98; 95% CI, 0.97-0.99) had comparable performance. By comparison, model 1 (no strain data; 0.92; 95% CI, 0.90-0.94) had an inferior area under the curve. Conclusion: Machine learning tools that analyze echocardiographic metrics identified HCM cases with high performance. Detection of HCM cases improved when strain data was combined with standard echocardiographic metrics.

Published
2024
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4. Single-cell transcriptomic-informed deconvolution of bulk data identifies immune checkpoint blockade resistance in urothelial cancer

Author

Li Wang, Sudeh Izadmehr, John P. Sfakianos, Michelle Tran, Kristin G. Beaumont, Rachel Brody, Carlos Cordon-Cardo, Amir Horowitz, Robert Sebra, William K. Oh, Nina Bhardwaj, Matthew D. Galsky, and Jun Zhu

Subjects
Microenvironment, Biocomputational method, Cancer systems biology, Cancer, Transcriptomics, Science
Abstract

Summary: Interactions within the tumor microenvironment (TME) significantly influence tumor progression and treatment responses. While single-cell RNA sequencing (scRNA-seq) and spatial genomics facilitate TME exploration, many clinical cohorts are assessed at the bulk tissue level. Integrating scRNA-seq and bulk tissue RNA-seq data through computational deconvolution is essential for obtaining clinically relevant insights. Our method, ProM, enables the examination of major and minor cell types. Through evaluation against existing methods using paired single-cell and bulk RNA sequencing of human urothelial cancer (UC) samples, ProM demonstrates superiority. Application to UC cohorts treated with immune checkpoint inhibitors reveals pre-treatment cellular features associated with poor outcomes, such as elevated SPP1 expression in macrophage/monocytes (MM). Our deconvolution method and paired single-cell and bulk tissue RNA-seq dataset contribute novel insights into TME heterogeneity and resistance to immune checkpoint blockade.

Published
2024
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5. MicroRNA‐30d and ‐483‐3p for bi‐ventricular remodelling and miR‐126‐3p for pulmonary hypertension in advanced heart failure

Author

Alessia Gallo, Valentina Agnese, Sergio Sciacca, Cesare Scardulla, Manlio Cipriani, Michele Pilato, Jae K. Oh, Salvatore Pasta, Joseph Maalouf, Pier Giulio Conaldi, and Diego Bellavia

Subjects
Biomarkers, Cardiomyopathy, Diagnosis, Heart failure, MicroRNAs, Prognosis, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Aims MicroRNAs play a role in pathogenic mechanisms leading to heart failure. We measured a panel of 754 miRNAs in the myocardial tissue and in the serum of patients with heart failure with reduced ejection fraction due to dilatative idiopathic cardiomyopathy (DCM, N = 10) or ischaemic cardiomyopathy (N = 3), referred to left ventricular assist device implant. We aim to identify circulating miRNAs with high tissue co‐expression, significantly associated to echocardiographic and haemodynamic measures. Methods and results We have measured a panel of 754 miRNAs in the myocardial tissue [left ventricular (LV) apex] and in the serum obtained at the same time in a well selected study population of end‐stage heart failure with reduced ejection fraction due to either DCM or ischaemic cardiomyopathy, referred to continuous flow left ventricular assist device implant. We observed moderate agreement for miR‐30d, miR‐126‐3p, and miR‐483‐3p. MiR‐30d was correlated to LV systolic as well as diastolic volumes (r = 0.78, P = 0.001 and r = 0.80, P = 0.005, respectively), while miR‐126‐3p was associated to mPAP and PCWP (r = −0.79, P = 0.007 and r = −0.80, P = 0.005, respectively). Finally, serum miR‐483‐3p had an association with right ventricular end diastolic diameter (r = −0.73, P = 0.02) and central venous pressure (CVP) (r − 0.68 p 0.03). Conclusions In patients with DCM, few miRNAs are co‐expressed in serum and tissue: They are related to LV remodelling (miR‐30d), post‐capillary pulmonary artery pressure (miR‐126‐3p), and right ventricular remodelling/filling pressures (miR‐483‐3p). Further studies are needed to confirm their role in diagnosis, prognosis or as therapeutic targets in heart failure with reduced ejection fraction.

Published
2024
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6. Artificial intelligence-enabled ECG for left ventricular diastolic function and filling pressure

Author

Eunjung Lee, Saki Ito, William R. Miranda, Francisco Lopez-Jimenez, Garvan C. Kane, Samuel J. Asirvatham, Peter A. Noseworthy, Paul A. Friedman, Rickey E. Carter, Barry A. Borlaug, Zachi I. Attia, and Jae K. Oh

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Assessment of left ventricular diastolic function plays a major role in the diagnosis and prognosis of cardiac diseases, including heart failure with preserved ejection fraction. We aimed to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify echocardiographically determined diastolic dysfunction and increased filling pressure. We trained, validated, and tested an AI-enabled ECG in 98,736, 21,963, and 98,763 patients, respectively, who had an ECG and echocardiographic diastolic function assessment within 14 days with no exclusion criteria. It was also tested in 55,248 patients with indeterminate diastolic function by echocardiography. The model was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, and its prognostic performance was compared to echocardiography. The AUC for detecting increased filling pressure was 0.911. The AUCs to identify diastolic dysfunction grades ≥1, ≥2, and 3 were 0.847, 0.911, and 0.943, respectively. During a median follow-up of 5.9 years, 20,223 (20.5%) died. Patients with increased filling pressure predicted by AI-ECG had higher mortality than those with normal filling pressure, after adjusting for age, sex, and comorbidities in the test group (hazard ratio (HR) 1.7, 95% CI 1.645–1.757) similar to echocardiography and in the indeterminate group (HR 1.34, 95% CI 1.298–1.383). An AI-enabled ECG identifies increased filling pressure and diastolic function grades with a good prognostic value similar to echocardiography. AI-ECG is a simple and promising tool to enhance the detection of diseases associated with diastolic dysfunction and increased diastolic filling pressure.

Published
2024
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7. BASS XXIX: The near-infrared view of the BLR: the effects of obscuration in BLR characterisation

Author

F., Ricci, E., Treister, E., Bauer F., E., Mejía-Restrepo J., M., Koss, S., den Brok, M., Baloković, R., Bär, P., Bessiere, T., Caglar, F., Harrison, K., Ichikawa, D., Kakkad, I., Lamperti, R., Mushotzky, K., Oh, C., Powell M., C., Privon G., C., Ricci, R., Riffel, F., Rojas A., E., Sani, L., Smith K., D., Stern, B., Trakhtenbrot, M., Urry C., and S., Veilleux

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Virial black hole mass ($M_{BH}$) determination directly involves knowing the broad line region (BLR) clouds velocity distribution, their distance from the central supermassive black hole ($R_{BLR}$) and the virial factor ($f$). Understanding whether biases arise in $M_{BH}$ estimation with increasing obscuration is possible only by studying a large (N$>$100) statistical sample of obscuration unbiased (hard) X-ray selected active galactic nuclei (AGN) in the rest-frame near-infrared (0.8-2.5$\mu$m) since it penetrates deeper into the BLR than the optical. We present a detailed analysis of 65 local BAT-selected Seyfert galaxies observed with Magellan/FIRE. Adding these to the near-infrared BAT AGN spectroscopic survey (BASS) database, we study a total of 314 unique near-infrared spectra. While the FWHMs of H$\alpha$ and near-infrared broad lines (He\textsc{i}, Pa$\beta$, Pa$\alpha$) remain unbiased to either BLR extinction or X-ray obscuration, the H$\alpha$ broad line luminosity is suppressed when $N_H\gtrsim10^{21}$ cm$^{-2}$, systematically underestimating $M_{BH}$ by $0.23-0.46$ dex. Near-infrared line luminosities should be preferred to H$\alpha$ until $N_H<10^{22}$ cm$^{-2}$, while at higher obscuration a less biased $R_{BLR}$ proxy should be adopted. We estimate $f$ for Seyfert 1 and 2 using two obscuration-unbiased $M_{BH}$ measurements, i.e. the stellar velocity dispersion and a BH mass prescription based on near-infrared and X-ray, and find that the virial factors do not depend on redshift or obscuration, but for some broad lines show a mild anti-correlation with $M_{BH}$. Our results show the critical impact obscuration can have on BLR characterization and the importance of the near-infrared and X-rays for a less biased view of the BLR., Comment: 28 pages (excluding appendices), 14 figures, pre-proof version accepted for publication on ApJ (to appear on the BASS DR2 ApJ Special Issue)

Published
2021
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8. Topological Data Analysis Identified Prognostically-Distinct Phenotypes in Transcatheter Edge-to-Edge Repair Patients

Author

Chieh-Ju Chao, MD, Timothy Barry, MB, BCh, BAO, Amith Seri, MBBS, Ahmed El Shaer, MBBS, Nadia Chavez Ponce, MD, Soham Chakraborty, BS, Sean Smith, MD, Mohamad Alkhouli, MD, Jeremy Thaden, MD, David Fortuin, MD, John P. Sweeney, MD, Mackram Eleid, MD, Charanjit S. Rihal, MD, David R. Holmes, MD, Peter M. Pollak, MD, Abdallah El Sabbagh, MD, Steven J. Lester, MD, Jae K. Oh, MD, Win-Kuang Shen, MD, Imon Banerjee, PhD, and Reza Arsanjani, MD

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Objective: To identify prognostically distinct phenotype clusters in transcatheter edge-to-edge repair (TEER) patients based on topological data analysis (TDA), which was never used to assess the heterogeneous TEER population. Patients and Methods: Patients who underwent TEER (June 2014-September 2020) at Mayo Clinic sites were identified from the institutional database. Thirteen variables were used for TDA. The topological network graph was created using the Python Scikit-TDA Kepler-Mapper package (v. 2.0.1), and clustering was performed at the graph level with Louvain’s modularity method. Kaplan-Meier survival analysis was used to assess the all-cause mortality of each cluster. Result: A total of 389 consecutive patients were included in the final analysis, and 2 major clusters were identified. The mean age was 80.3 ± 8.7 years; 256 (65.8%) were male. Fifty-five (14.5%) patients died during the mean follow-up duration (185 days). Kaplan-Meier analysis showed significant survival differences among the 2 clusters (hazard ratio, 2.70; 95% CI, 1.50-4.87; P=.0005). Cluster 1 (n=227) had moderate or increased residual mitral regurgitation (cluster 0 vs cluster 1: 19.4% vs 41.9%; P

Published
2023
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9. A Retrospective Review of Patient-reported Outcomes after Postaxial Polydactyly Ligation and Surgical Excision

Author

Nakul Ganju, BS, Esperanza Mantilla-Rivas, MD, Paul F. Martinez, BS, Monica Manrique, MD, Joseph M. Escandón, MD, Samay Shah, BS, Ashley E. Rogers, MD, Michael J. Boyajian, MD, Albert K. Oh, MD, and Gary F. Rogers, MD, JD, LLM, MBA, MPH

Subjects
Surgery, RD1-811
Abstract

Background:. Interventions for type B postaxial polydactyly include suture ligation and surgical excision, yet there is a paucity of literature comparing the outcomes of these procedures. This study sought to compare patient-reported long-term outcomes of postaxial digit excision. Methods:. A six-question survey was distributed from January 2021 to March 2022 to patients who underwent treatment for type B postaxial polydactyly at a single pediatric institution from 2010 to 2016. Patients were queried about the incidence of pain sensitivity, keloid healing, and/or persistent presence of bump (“nubbin”) at the treatment site. Results:. A total of 158 responses accounting for 258 digits were attained for a 53% response rate. The majority of digits (67.4%, n = 174) were surgically excised. Median age at procedure was 49 days: 13.0 days for ligation, 63.0 days for surgical excision. Median age at survey was 8 [IQR 5.4–10.2] years. Short-term (

Published
2024
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10. A Rare Case of Dermatofibrosarcoma in a Pediatric Patient

Author

Paul F. Martinez, BS, Skyler Richardson, BS, Melanie Bakovic, BS, Monica Manrique, MD, Esperanza Mantilla-Rivas, MD, Albert K. Oh, MD, and Gary F. Rogers, MD, JD, LLM, MBA, MPH

Subjects
Surgery, RD1-811
Abstract

Summary:. Dermatofibrosarcoma protuberans (DFSP) is a rare malignant fibroblastic tumor. DFSP has an insidious onset, slow growth, and heterogeneous presentation that can create a delay in diagnosis and increase morbidity. In this case report, we present a child with DFSP that presented as a large, slow-growing mass over the dorsum of the left foot. She underwent successful surgical excision with no functional sequelae.

Published
2024
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11. GWTC-3: Compact Binary Coalescences Observed by LIGO and Virgo during the Second Part of the Third Observing Run

Author

R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, N. Adhikari, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, M. Agathos, K. Agatsuma, N. Aggarwal, O. D. Aguiar, L. Aiello, A. Ain, P. Ajith, S. Akcay, T. Akutsu, S. Albanesi, A. Allocca, P. A. Altin, A. Amato, C. Anand, S. Anand, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Ando, T. Andrade, N. Andres, T. Andrić, S. V. Angelova, S. Ansoldi, J. M. Antelis, S. Antier, S. Appert, Koji Arai, Koya Arai, Y. Arai, S. Araki, A. Araya, M. C. Araya, J. S. Areeda, M. Arène, N. Aritomi, N. Arnaud, M. Arogeti, S. M. Aronson, K. G. Arun, H. Asada, Y. Asali, G. Ashton, Y. Aso, M. Assiduo, S. M. Aston, P. Astone, F. Aubin, C. Austin, S. Babak, F. Badaracco, M. K. M. Bader, C. Badger, S. Bae, Y. Bae, A. M. Baer, S. Bagnasco, Y. Bai, L. Baiotti, J. Baird, R. Bajpai, M. Ball, G. Ballardin, S. W. Ballmer, A. Balsamo, G. Baltus, S. Banagiri, D. Bankar, J. C. Barayoga, C. Barbieri, B. C. Barish, D. Barker, P. Barneo, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, J. Bartlett, M. A. Barton, I. Bartos, R. Bassiri, A. Basti, M. Bawaj, J. C. Bayley, A. C. Baylor, M. Bazzan, B. Bécsy, V. M. Bedakihale, M. Bejger, I. Belahcene, V. Benedetto, D. Beniwal, T. F. Bennett, J. D. Bentley, M. BenYaala, F. Bergamin, B. K. Berger, S. Bernuzzi, C. P. L. Berry, D. Bersanetti, A. Bertolini, J. Betzwieser, D. Beveridge, R. Bhandare, U. Bhardwaj, D. Bhattacharjee, S. Bhaumik, I. A. Bilenko, G. Billingsley, S. Bini, R. Birney, O. Birnholtz, S. Biscans, M. Bischi, S. Biscoveanu, A. Bisht, B. Biswas, M. Bitossi, M.-A. Bizouard, J. K. Blackburn, C. D. Blair, D. G. Blair, R. M. Blair, F. Bobba, N. Bode, M. Boer, G. Bogaert, M. Boldrini, L. D. Bonavena, F. Bondu, E. Bonilla, R. Bonnand, P. Booker, B. A. Boom, R. Bork, V. Boschi, N. Bose, S. Bose, V. Bossilkov, V. Boudart, Y. Bouffanais, A. Bozzi, C. Bradaschia, P. R. Brady, A. Bramley, A. Branch, M. Branchesi, J. Brandt, J. E. Brau, M. Breschi, T. Briant, J. H. Briggs, A. Brillet, M. Brinkmann, P. Brockill, A. F. Brooks, J. Brooks, D. D. Brown, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, T. Bulik, H. J. Bulten, A. Buonanno, R. Buscicchio, D. Buskulic, C. Buy, R. L. Byer, G. S. Cabourn Davies, L. Cadonati, G. Cagnoli, C. Cahillane, J. Calderón Bustillo, J. D. Callaghan, T. A. Callister, E. Calloni, J. Cameron, J. B. Camp, M. Canepa, S. Canevarolo, M. Cannavacciuolo, K. C. Cannon, H. Cao, Z. Cao, E. Capocasa, E. Capote, G. Carapella, F. Carbognani, J. B. Carlin, M. F. Carney, M. Carpinelli, G. Carrillo, G. Carullo, T. L. Carver, J. Casanueva Diaz, C. Casentini, G. Castaldi, S. Caudill, M. Cavaglià, F. Cavalier, R. Cavalieri, M. Ceasar, G. Cella, P. Cerdá-Durán, E. Cesarini, W. Chaibi, K. Chakravarti, S. Chalathadka Subrahmanya, E. Champion, C.-H. Chan, C. Chan, C. L. Chan, K. Chan, M. Chan, K. Chandra, P. Chanial, S. Chao, C. E. A. Chapman-Bird, P. Charlton, E. A. Chase, E. Chassande-Mottin, C. Chatterjee, Debarati Chatterjee, Deep Chatterjee, M. Chaturvedi, S. Chaty, K. Chatziioannou, C. Chen, H. Y. Chen, J. Chen, K. Chen, X. Chen, Y.-B. Chen, Y.-R. Chen, Z. Chen, H. Cheng, C. K. Cheong, H. Y. Cheung, H. Y. Chia, F. Chiadini, C-Y. Chiang, G. Chiarini, R. Chierici, A. Chincarini, M. L. Chiofalo, A. Chiummo, G. Cho, H. S. Cho, R. K. Choudhary, S. Choudhary, N. Christensen, H. Chu, Q. Chu, Y-K. Chu, S. Chua, K. W. Chung, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, A. A. Ciobanu, R. Ciolfi, F. Cipriano, A. Cirone, F. Clara, E. N. Clark, J. A. Clark, L. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, E. Codazzo, P.-F. Cohadon, D. E. Cohen, L. Cohen, M. Colleoni, C. G. Collette, A. Colombo, M. Colpi, C. M. Compton, M. Constancio, Jr., L. Conti, S. J. Cooper, P. Corban, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, K. R. Corley, N. Cornish, D. Corre, A. Corsi, S. Cortese, C. A. Costa, R. Cotesta, M. W. Coughlin, J.-P. Coulon, S. T. Countryman, B. Cousins, P. Couvares, D. M. Coward, M. J. Cowart, D. C. Coyne, R. Coyne, J. D. E. Creighton, T. D. Creighton, A. W. Criswell, M. Croquette, S. G. Crowder, J. R. Cudell, T. J. Cullen, A. Cumming, R. Cummings, L. Cunningham, E. Cuoco, M. Curyło, P. Dabadie, T. Dal Canton, S. Dall’Osso, G. Dálya, A. Dana, L. M. DaneshgaranBajastani, B. D’Angelo, B. Danila, S. Danilishin, S. D’Antonio, K. Danzmann, C. Darsow-Fromm, A. Dasgupta, L. E. H. Datrier, V. Dattilo, I. Dave, M. Davier, D. Davis, M. C. Davis, E. J. Daw, P. F. de Alarcón, R. Dean, D. DeBra, M. Deenadayalan, J. Degallaix, M. De Laurentis, S. Deléglise, V. Del Favero, F. De Lillo, N. De Lillo, W. Del Pozzo, L. M. DeMarchi, F. De Matteis, V. D’Emilio, N. Demos, T. Dent, A. Depasse, R. De Pietri, R. De Rosa, C. De Rossi, R. DeSalvo, R. De Simone, S. Dhurandhar, M. C. Díaz, M. Diaz-Ortiz, Jr., N. A. Didio, T. Dietrich, L. Di Fiore, C. Di Fronzo, C. Di Giorgio, F. Di Giovanni, M. Di Giovanni, T. Di Girolamo, A. Di Lieto, B. Ding, S. Di Pace, I. Di Palma, F. Di Renzo, A. K. Divakarla, A. Dmitriev, Z. Doctor, L. D’Onofrio, F. Donovan, K. L. Dooley, S. Doravari, I. Dorrington, M. Drago, J. C. Driggers, Y. Drori, J.-G. Ducoin, P. Dupej, O. Durante, D. D’Urso, P.-A. Duverne, S. E. Dwyer, C. Eassa, P. J. Easter, M. Ebersold, T. Eckhardt, G. Eddolls, B. Edelman, T. B. Edo, O. Edy, A. Effler, S. Eguchi, J. Eichholz, S. S. Eikenberry, M. Eisenmann, R. A. Eisenstein, A. Ejlli, E. Engelby, Y. Enomoto, L. Errico, R. C. Essick, H. Estellés, D. Estevez, Z. Etienne, T. Etzel, M. Evans, T. M. Evans, B. E. Ewing, V. Fafone, H. Fair, S. Fairhurst, A. M. Farah, S. Farinon, B. Farr, W. M. Farr, N. W. Farrow, E. J. Fauchon-Jones, G. Favaro, M. Favata, M. Fays, M. Fazio, J. Feicht, M. M. Fejer, E. Fenyvesi, D. L. Ferguson, A. Fernandez-Galiana, I. Ferrante, T. A. Ferreira, F. Fidecaro, P. Figura, I. Fiori, M. Fishbach, R. P. Fisher, R. Fittipaldi, V. Fiumara, R. Flaminio, E. Floden, H. Fong, J. A. Font, B. Fornal, P. W. F. Forsyth, A. Franke, S. Frasca, F. Frasconi, C. Frederick, J. P. Freed, Z. Frei, A. Freise, R. Frey, P. Fritschel, V. V. Frolov, G. G. Fronzé, Y. Fujii, Y. Fujikawa, M. Fukunaga, M. Fukushima, P. Fulda, M. Fyffe, H. A. Gabbard, W. E. Gabella, B. U. Gadre, J. R. Gair, J. Gais, S. Galaudage, R. Gamba, D. Ganapathy, A. Ganguly, D. Gao, S. G. Gaonkar, B. Garaventa, F. García, C. García-Núñez, C. García-Quirós, F. Garufi, B. Gateley, S. Gaudio, V. Gayathri, G.-G. Ge, G. Gemme, A. Gennai, J. George, R. N. George, O. Gerberding, L. Gergely, P. Gewecke, S. Ghonge, Abhirup Ghosh, Archisman Ghosh, Shaon Ghosh, Shrobana Ghosh, B. Giacomazzo, L. Giacoppo, J. A. Giaime, K. D. Giardina, D. R. Gibson, C. Gier, M. Giesler, P. Giri, F. Gissi, J. Glanzer, A. E. Gleckl, P. Godwin, E. Goetz, R. Goetz, N. Gohlke, J. Golomb, B. Goncharov, G. González, A. Gopakumar, M. Gosselin, R. Gouaty, D. W. Gould, B. Grace, A. Grado, M. Granata, V. Granata, A. Grant, S. Gras, P. Grassia, C. Gray, R. Gray, G. Greco, A. C. Green, R. Green, A. M. Gretarsson, E. M. Gretarsson, D. Griffith, W. 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Zhu, A. B. Zimmerman, Y. Zlochower, M. E. Zucker, and J. Zweizig

Subjects
Physics, QC1-999
Abstract

The third Gravitational-Wave Transient Catalog (GWTC-3) describes signals detected with Advanced LIGO and Advanced Virgo up to the end of their third observing run. Updating the previous GWTC-2.1, we present candidate gravitational waves from compact binary coalescences during the second half of the third observing run (O3b) between 1 November 2019, 15∶00 Coordinated Universal Time (UTC) and 27 March 2020, 17∶00 UTC. There are 35 compact binary coalescence candidates identified by at least one of our search algorithms with a probability of astrophysical origin p_{astro}>0.5. Of these, 18 were previously reported as low-latency public alerts, and 17 are reported here for the first time. Based upon estimates for the component masses, our O3b candidates with p_{astro}>0.5 are consistent with gravitational-wave signals from binary black holes or neutron-star–black-hole binaries, and we identify none from binary neutron stars. However, from the gravitational-wave data alone, we are not able to measure matter effects that distinguish whether the binary components are neutron stars or black holes. The range of inferred component masses is similar to that found with previous catalogs, but the O3b candidates include the first confident observations of neutron-star–black-hole binaries. Including the 35 candidates from O3b in addition to those from GWTC-2.1, GWTC-3 contains 90 candidates found by our analysis with p_{astro}>0.5 across the first three observing runs. These observations of compact binary coalescences present an unprecedented view of the properties of black holes and neutron stars.

Published
2023
Full Text
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13. BASS. XLII. The Relation between the Covering Factor of Dusty Gas and the Eddington Ratio in Nearby Active Galactic Nuclei

Author

C. Ricci, K. Ichikawa, M. Stalevski, T. Kawamuro, S. Yamada, Y. Ueda, R. Mushotzky, G. C. Privon, M. J. Koss, B. Trakhtenbrot, A. C. Fabian, L. C. Ho, D. Asmus, F. E. Bauer, C. S. Chang, K. K. Gupta, K. Oh, M. Powell, R. W. Pfeifle, A. Rojas, F. Ricci, M. J. Temple, Y. Toba, A. Tortosa, E. Treister, F. Harrison, D. Stern, and C. M. Urry

Subjects
Active galaxies, Seyfert galaxies, Infrared photometry, X-ray astronomy, Quasars, Astrophysics, QB460-466
Abstract

Accreting supermassive black holes (SMBHs) located at the centers of galaxies are typically surrounded by large quantities of gas and dust. The structure and evolution of this circumnuclear material can be studied at different wavelengths, from the submillimeter to the X-ray. Recent X-ray studies have shown that the covering factor of the obscuring material tends to decrease with increasing Eddington ratio, likely due to radiative feedback on dusty gas. Here we study a sample of 549 nearby ( z ≲ 0.1) hard X-ray (14–195 keV) selected nonblazar active galactic nuclei (AGN) and use the ratio between the AGN infrared and bolometric luminosity as a proxy of the covering factor. We find that, in agreement with what has been found by X-ray studies of the same sample, the covering factor decreases with increasing Eddington ratio. We also confirm previous findings that showed that obscured AGN typically have larger covering factors than unobscured sources. Finally, we find that the median covering factors of AGN located in different regions of the column density–Eddington ratio diagram are in good agreement with what would be expected from a radiation-regulated growth of SMBHs.

Published
2023
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14. Oncology

Author

William K. Oh, Ajai Chari, William K. Oh, Ajai Chari

Published
2019

17. 3-Year Outcomes After Transcatheter or Surgical Aortic Valve Replacement in Low-Risk Patients With Aortic Stenosis

Author

John K. Forrest, G. Michael Deeb, Steven J. Yakubov, Hemal Gada, Mubashir A. Mumtaz, Basel Ramlawi, Tanvir Bajwa, Paul S. Teirstein, Michael DeFrain, Murali Muppala, Bruce J. Rutkin, Atul Chawla, Bart Jenson, Stanley J. Chetcuti, Robert C. Stoler, Marie-France Poulin, Kamal Khabbaz, Melissa Levack, Kashish Goel, Didier Tchétché, Ka Yan Lam, Pim A.L. Tonino, Saki Ito, Jae K. Oh, Jian Huang, Jeffrey J. Popma, Neal Kleiman, Michael J. Reardon, Paul Sorajja, Timothy Byrne, Merick Kirshner, John Crouch, Joseph Coselli, Guilherme Silva, Robert Hebeler, Robert Stoler, Ashequl Islam, Anthony Rousou, Mark Bladergroen, Peter Fail, Donald Netherland, W.A.L. Tonino, Arnaud Sudre, Pierre Berthoumieu, Houman Khalili, G. Chad Hughes, J Kevin Harrison, Ajanta De, Pei Tsau, Nicolas M. van Mieghem, Robert Larbalestier, Gerald Yong, Shikhar Agarwal, William Martin, Steven Park, Michael Reardon, Siamak Mohammadi, Josep Rodes-Cabau, Jeffrey Sparling, C. Craig Elkins, Brian Ganzel, Ray V. Matthews, Vaughn A. Starnes, Kenji Ando, Bernard Chevalier, Arnaud Farge, William Combs, Rodrigo Bagur, Michael Chu, Gregory Fontana, Visha Dev, Ferdinand Leya, J. Michael Tuchek, Ignacio Inglessis, Arminder Jassar, Nicolo Piazza, Kevin Lacappelle, Daniel Steinberg, Marc Katz, John Wang, Joseph Kozina, Frank Slachman, Robert Merritt, Bart Jensen, Jorge Alvarez, Robert Gooley, Julian Smith, Reda Ibrahim, Raymond Cartier, Joshua Rovin, Tomoyuki Fujita, Bruce Rutkin, Steven Yakubov, Howard Song, Firas Zahr, Shigeru Miyagawa, Vivek Rajagopal, James Kauten, Mubashir Mumtaz, Ravinay Bhindi, Peter Brady, Sanjay Batra, Thomas Davis, Ayman Iskander, David Heimansohn, James Hermiller, Itaru Takamisawa, Thomas Haldis, Seiji Yamazaki, Paul Teirstein, Norio Tada, Shigeru Saito, William Merhi, Stephane Leung, David Muller, Robin Heijmen, George Petrossian, Newell Robinson, Peter Knight, Frederick Ling, Sam Radhakrishnan, Stephen Fremes, Eric Lehr, Sameer Gafoor, Thomas Noel, Antony Walton, Jon Resar, David Adams, Samin Sharma, Scott Lilly, Peter Tadros, George Zorn, Harold Dauerman, Frank Ittleman, Erik Horlick, Chris Feindel, Frederick Welt, Vikas Sharma, Alan Markowitz, John Carroll, David Fullerton, Bartley Griffith, Anuj Gupta, Eduardo de Marchena, Tomas Salerno, Stanley Chetcuti, Ibrahim Sultan, Sanjeevan Pasupati, Neal Kon, David Zhao, and John Forrest

Subjects
Cardiology and Cardiovascular Medicine
Published
2023

19. Observation of Gravitational Waves from Two Neutron Star–Black Hole Coalescences

Author

R. Abbott, T. D. Abbott, S. Abraham, F. Acernese, K. Ackley, A. Adams, C. Adams, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, M. Agathos, K. Agatsuma, N. Aggarwal, O. D. Aguiar, L. Aiello, A. Ain, P. Ajith, T. Akutsu, K. M. Aleman, G. Allen, A. Allocca, P. A. Altin, A. Amato, S. Anand, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Ando, S. V. Angelova, S. Ansoldi, J. M. Antelis, S. Antier, S. Appert, Koya Arai, Koji Arai, Y. Arai, S. Araki, A. Araya, M. C. Araya, J. S. Areeda, M. Arène, N. Aritomi, N. Arnaud, S. M. Aronson, K. G. Arun, H. Asada, Y. Asali, G. Ashton, Y. Aso, S. M. Aston, P. Astone, F. Aubin, P. Aufmuth, K. AultONeal, C. Austin, S. Babak, F. Badaracco, M. K. M. Bader, S. Bae, Y. Bae, A. M. Baer, S. Bagnasco, Y. Bai, L. Baiotti, J. Baird, R. Bajpai, M. Ball, G. Ballardin, S. W. Ballmer, M. Bals, A. Balsamo, G. Baltus, S. Banagiri, D. Bankar, R. S. Bankar, J. C. Barayoga, C. Barbieri, B. C. Barish, D. Barker, P. Barneo, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, J. Bartlett, M. A. Barton, I. Bartos, R. Bassiri, A. Basti, M. Bawaj, J. C. Bayley, A. C. Baylor, M. Bazzan, B. Bécsy, V. M. Bedakihale, M. Bejger, I. Belahcene, V. Benedetto, D. Beniwal, M. G. Benjamin, R. Benkel, T. F. Bennett, J. D. Bentley, M. BenYaala, F. Bergamin, B. K. Berger, S. Bernuzzi, C. P. L. Berry, D. Bersanetti, A. Bertolini, J. Betzwieser, R. Bhandare, A. V. Bhandari, D. Bhattacharjee, S. Bhaumik, J. Bidler, I. A. Bilenko, G. Billingsley, I. A. Birney, O. Birnholtz, S. Biscans, M. Bischi, S. Biscoveanu, A. Bisht, B. Biswas, M. Bitossi, M.-A. Bizouard, J. K. Blackburn, J. Blackman, C. D. Blair, D. G. Blair, R. M. Blair, F. Bobba, N. Bode, M. Boer, G. Bogaert, M. Boldrini, F. Bondu, E. Bonilla, R. Bonnand, P. Booker, B. A. Boom, R. Bork, V. Boschi, N. Bose, S. Bose, V. Bossilkov, V. Boudart, Y. Bouffanais, A. Bozzi, C. Bradaschia, P. R. Brady, A. Bramley, A. Branch, M. Branchesi, J. E. Brau, M. Breschi, T. Briant, J. H. Briggs, A. Brillet, M. Brinkmann, P. Brockill, A. F. Brooks, J. Brooks, D. D. Brown, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, A. Buikema, T. Bulik, H. J. Bulten, A. Buonanno, R. Buscicchio, D. Buskulic, R. L. Byer, L. Cadonati, M. Caesar, G. Cagnoli, C. Cahillane, H. W. Cain III, J. Calderón Bustillo, J. D. Callaghan, T. A. Callister, E. Calloni, J. B. Camp, M. Canepa, M. Cannavacciuolo, K. C. Cannon, H. Cao, J. Cao, Z. Cao, E. Capocasa, E. Capote, G. Carapella, F. Carbognani, J. B. Carlin, M. F. Carney, M. Carpinelli, G. Carullo, T. L. Carver, J. Casanueva Diaz, C. Casentini, G. Castaldi, S. Caudill, M. Cavaglià, F. Cavalier, R. Cavalieri, G. Cella, P. Cerdá-Durán, E. Cesarini, W. Chaibi, K. Chakravarti, B. Champion, C.-H. Chan, C. Chan, C. L. Chan, M. Chan, K. Chandra, P. Chanial, S. Chao, P. Charlton, E. A. Chase, E. Chassande-Mottin, D. Chatterjee, M. Chaturvedi, K. Chatziioannou, A. Chen, C. Chen, H. Y. Chen, J. Chen, K. Chen, X. Chen, Y.-B. Chen, Y.-R. Chen, Z. Chen, H. Cheng, C. K. Cheong, H. Y. Cheung, H. Y. Chia, F. Chiadini, C-Y. Chiang, R. Chierici, A. Chincarini, M. L. Chiofalo, A. Chiummo, G. Cho, H. S. Cho, S. Choate, R. K. Choudhary, S. Choudhary, N. Christensen, H. Chu, Q. Chu, Y-K. Chu, S. Chua, K. W. Chung, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, A. A. Ciobanu, R. Ciolfi, F. Cipriano, A. Cirone, F. Clara, E. N. Clark, J. A. Clark, L. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, P.-F. Cohadon, D. E. Cohen, L. Cohen, M. Colleoni, C. G. Collette, M. Colpi, C. M. Compton, M. Constancio Jr., L. Conti, S. J. Cooper, P. Corban, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, K. R. Corley, N. Cornish, D. Corre, A. Corsi, S. Cortese, C. A. Costa, R. Cotesta, M. W. Coughlin, S. B. Coughlin, J.-P. Coulon, S. T. Countryman, B. Cousins, P. Couvares, P. B. Covas, D. M. Coward, M. J. Cowart, D. C. Coyne, R. Coyne, J. D. E. Creighton, T. D. Creighton, A. W. Criswell, M. Croquette, S. G. Crowder, J. R. Cudell, T. J. Cullen, A. Cumming, R. Cummings, E. Cuoco, M. Curyło, T. Dal Canton, G. Dálya, A. Dana, L. M. DaneshgaranBajastani, B. D’Angelo, S. L. Danilishin, S. D’Antonio, K. Danzmann, C. Darsow-Fromm, A. Dasgupta, L. E. H. Datrier, V. Dattilo, I. Dave, M. Davier, G. S. Davies, D. Davis, E. J. Daw, R. Dean, D. DeBra, M. Deenadayalan, J. Degallaix, M. De Laurentis, S. Deléglise, V. Del Favero, F. De Lillo, N. De Lillo, W. Del Pozzo, L. M. DeMarchi, F. De Matteis, V. D’Emilio, N. Demos, T. Dent, A. Depasse, R. De Pietri, R. De Rosa, C. De Rossi, R. DeSalvo, R. De Simone, S. Dhurandhar, M. C. Díaz, M. Diaz-Ortiz Jr., N. A. Didio, T. Dietrich, L. Di Fiore, C. Di Fronzo, C. Di Giorgio, F. Di Giovanni, T. Di Girolamo, A. Di Lieto, B. Ding, S. Di Pace, I. Di Palma, F. Di Renzo, A. K. Divakarla, A. Dmitriev, Z. Doctor, L. D’Onofrio, F. Donovan, K. L. Dooley, S. Doravari, I. Dorrington, M. Drago, J. C. Driggers, Y. Drori, Z. Du, J.-G. Ducoin, P. Dupej, O. Durante, D. D’Urso, P.-A. Duverne, S. E. Dwyer, P. J. Easter, M. Ebersold, G. Eddolls, B. Edelman, T. B. Edo, O. Edy, A. Effler, S. Eguchi, J. Eichholz, S. S. Eikenberry, M. Eisenmann, R. A. Eisenstein, A. Ejlli, Y. Enomoto, L. Errico, R. C. Essick, H. Estellés, D. Estevez, Z. Etienne, T. Etzel, M. Evans, T. M. Evans, B. E. Ewing, V. Fafone, H. Fair, S. Fairhurst, X. Fan, A. M. Farah, S. Farinon, B. Farr, W. M. Farr, N. W. Farrow, E. J. Fauchon-Jones, M. Favata, M. Fays, M. Fazio, J. Feicht, M. M. Fejer, F. Feng, E. Fenyvesi, D. L. Ferguson, A. Fernandez-Galiana, I. Ferrante, T. A. Ferreira, F. Fidecaro, P. Figura, I. Fiori, M. Fishbach, R. P. Fisher, R. Fittipaldi, V. Fiumara, R. Flaminio, E. Floden, E. Flynn, H. Fong, J. A. Font, B. Fornal, P. W. F. Forsyth, A. Franke, S. Frasca, F. Frasconi, C. Frederick, Z. Frei, A. Freise, R. Frey, P. Fritschel, V. V. Frolov, G. G. Fronzé, Y. Fujii, Y. Fujikawa, M. Fukunaga, M. Fukushima, P. Fulda, M. Fyffe, H. A. Gabbard, B. U. Gadre, S. M. Gaebel, J. R. Gair, J. Gais, S. Galaudage, R. Gamba, D. Ganapathy, A. Ganguly, D. Gao, S. G. Gaonkar, B. Garaventa, C. García-Núñez, C. García-Quirós, F. Garufi, B. Gateley, S. Gaudio, V. Gayathri, G. Ge, G. Gemme, A. Gennai, J. George, L. Gergely, P. Gewecke, S. Ghonge, Abhirup. Ghosh, Archisman Ghosh, Shaon Ghosh, Shrobana Ghosh, Sourath Ghosh, B. Giacomazzo, L. Giacoppo, J. A. Giaime, K. D. Giardina, D. R. Gibson, C. Gier, M. Giesler, P. Giri, F. Gissi, J. Glanzer, A. E. Gleckl, P. Godwin, E. Goetz, R. Goetz, N. Gohlke, B. Goncharov, G. González, A. Gopakumar, M. Gosselin, R. Gouaty, B. Grace, A. Grado, M. Granata, V. Granata, A. Grant, S. Gras, P. Grassia, C. Gray, R. Gray, G. Greco, A. C. Green, R. Green, A. M. Gretarsson, E. M. Gretarsson, D. Griffith, W. Griffiths, H. L. Griggs, G. Grignani, A. Grimaldi, E. Grimes, S. J. Grimm, H. Grote, S. Grunewald, P. Gruning, J. G. Guerrero, G. M. Guidi, A. R. Guimaraes, G. Guixé, H. K. Gulati, H.-K. Guo, Y. Guo, Anchal Gupta, Anuradha Gupta, P. Gupta, E. K. Gustafson, R. Gustafson, F. Guzman, S. Ha, L. Haegel, A. Hagiwara, S. Haino, O. Halim, E. D. Hall, E. Z. Hamilton, G. Hammond, W.-B. Han, M. Haney, J. Hanks, C. Hanna, M. D. Hannam, O. A. Hannuksela, H. Hansen, T. J. Hansen, J. Hanson, T. Harder, T. Hardwick, K. Haris, J. Harms, G. M. Harry, I. W. Harry, D. Hartwig, K. Hasegawa, B. Haskell, R. K. Hasskew, C.-J. Haster, K. Hattori, K. Haughian, H. Hayakawa, K. Hayama, F. J. Hayes, J. Healy, A. Heidmann, M. C. Heintze, J. Heinze, J. Heinzel, H. Heitmann, F. Hellman, P. Hello, A. F. Helmling-Cornell, G. Hemming, M. Hendry, I. S. Heng, E. Hennes, J. Hennig, M. H. Hennig, F. Hernandez Vivanco, M. Heurs, S. Hild, P. Hill, Y. Himemoto, T. Hinderer, A. S. Hines, Y. Hiranuma, N. Hirata, E. Hirose, W. C. G. Ho, S. Hochheim, D. Hofman, J. N. Hohmann, A. M. Holgado, N. A. Holland, I. J. Hollows, Z. J. Holmes, K. Holt, D. E. Holz, Z. Hong, P. Hopkins, J. Hough, E. J. Howell, C. G. Hoy, D. Hoyland, A. Hreibi, B-H. Hsieh, Y. Hsu, G-Z. Huang, H-Y. Huang, P. Huang, Y-C. Huang, Y.-J. Huang, Y.-W. Huang, M. T. Hübner, A. D. Huddart, E. A. Huerta, B. Hughey, D. C. Y. Hui, V. Hui, S. Husa, S. H. Huttner, R. Huxford, T. Huynh-Dinh, S. Ide, B. Idzkowski, A. Iess, B. Ikenoue, S. Imam, K. Inayoshi, H. Inchauspe, C. Ingram, Y. Inoue, G. Intini, K. Ioka, M. Isi, K. Isleif, K. Ito, Y. Itoh, B. R. Iyer, K. Izumi, V. JaberianHamedan, T. Jacqmin, S. J. Jadhav, S. P. Jadhav, A. L. James, A. Z. Jan, K. Jani, K. Janssens, N. N. Janthalur, P. Jaranowski, D. Jariwala, R. Jaume, A. C. Jenkins, C. Jeon, M. Jeunon, W. Jia, J. Jiang, H.-B. Jin, G. R. Johns, A. W. Jones, D. I. Jones, J. D. Jones, P. Jones, R. Jones, R. J. G. Jonker, L. Ju, K. Jung, P. Jung, J. Junker, K. Kaihotsu, T. Kajita, M. Kakizaki, C. V. Kalaghatgi, V. Kalogera, B. Kamai, M. Kamiizumi, N. Kanda, S. Kandhasamy, G. Kang, J. B. Kanner, Y. Kao, S. J. Kapadia, D. P. Kapasi, S. Karat, C. Karathanasis, S. Karki, R. Kashyap, M. Kasprzack, W. Kastaun, S. Katsanevas, E. Katsavounidis, W. Katzman, T. Kaur, K. Kawabe, K. Kawaguchi, N. Kawai, T. Kawasaki, F. Kéfélian, D. Keitel, J. S. Key, S. Khadka, F. Y. Khalili, I. Khan, S. Khan, E. A. Khazanov, N. Khetan, M. Khursheed, N. Kijbunchoo, C. Kim, J. C. Kim, J. Kim, K. Kim, W. S. Kim, Y.-M. Kim, C. Kimball, N. Kimura, P. J. King, M. Kinley-Hanlon, R. Kirchhoff, J. S. Kissel, N. Kita, H. Kitazawa, L. Kleybolte, S. Klimenko, A. M. Knee, T. D. Knowles, E. Knyazev, P. Koch, G. Koekoek, Y. Kojima, K. Kokeyama, S. Koley, P. Kolitsidou, M. Kolstein, K. Komori, V. Kondrashov, A. K. H. Kong, A. Kontos, N. Koper, M. Korobko, K. Kotake, M. Kovalam, D. B. Kozak, C. Kozakai, R. Kozu, V. Kringel, N. V. Krishnendu, A. Królak, G. Kuehn, F. Kuei, A. Kumar, P. Kumar, Rahul Kumar, Rakesh Kumar, J. Kume, K. Kuns, C. Kuo, H-S. Kuo, Y. Kuromiya, S. Kuroyanagi, K. Kusayanagi, K. Kwak, S. Kwang, D. Laghi, E. Lalande, T. L. Lam, A. Lamberts, M. Landry, P. Landry, B. B. Lane, R. N. Lang, J. Lange, B. Lantz, I. La Rosa, A. Lartaux-Vollard, P. D. Lasky, M. Laxen, A. Lazzarini, C. Lazzaro, P. Leaci, S. Leavey, Y. K. 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Markosyan, A. Markowitz, E. Maros, A. Marquina, S. Marsat, F. Martelli, I. W. Martin, R. M. Martin, M. Martinez, V. Martinez, K. Martinovic, D. V. Martynov, E. J. Marx, H. Masalehdan, K. Mason, E. Massera, A. Masserot, T. J. Massinger, M. Masso-Reid, S. Mastrogiovanni, A. Matas, M. Mateu-Lucena, F. Matichard, M. Matiushechkina, N. Mavalvala, J. J. McCann, R. McCarthy, D. E. McClelland, P. McClincy, S. McCormick, L. McCuller, G. I. McGhee, S. C. McGuire, C. McIsaac, J. McIver, D. J. McManus, T. McRae, S. T. McWilliams, D. Meacher, M. Mehmet, A. K. Mehta, A. Melatos, D. A. Melchor, G. Mendell, A. Menendez-Vazquez, C. S. Menoni, R. A. Mercer, L. Mereni, K. Merfeld, E. L. Merilh, J. D. Merritt, M. Merzougui, S. Meshkov, C. Messenger, C. Messick, P. M. Meyers, F. Meylahn, A. Mhaske, A. Miani, H. Miao, I. Michaloliakos, C. Michel, Y. Michimura, H. Middleton, L. Milano, A. L. Miller, M. Millhouse, J. C. Mills, E. Milotti, M. C. Milovich-Goff, O. Minazzoli, Y. Minenkov, N. Mio, Ll. M. Mir, A. Mishkin, C. Mishra, T. Mishra, T. Mistry, S. Mitra, V. P. Mitrofanov, G. Mitselmakher, R. Mittleman, O. Miyakawa, A. Miyamoto, Y. Miyazaki, K. Miyo, S. Miyoki, Geoffrey Mo, K. Mogushi, S. R. P. Mohapatra, S. R. Mohite, I. Molina, M. Molina-Ruiz, M. Mondin, M. Montani, C. J. Moore, D. Moraru, F. Morawski, A. More, C. Moreno, G. Moreno, Y. Mori, S. Morisaki, Y. Moriwaki, B. Mours, C. M. Mow-Lowry, S. Mozzon, F. Muciaccia, Arunava Mukherjee, D. Mukherjee, Soma Mukherjee, Subroto Mukherjee, N. Mukund, A. Mullavey, J. Munch, E. A. Muñiz, P. G. Murray, R. Musenich, S. L. Nadji, K. Nagano, S. Nagano, A. Nagar, K. Nakamura, H. Nakano, M. Nakano, R. Nakashima, Y. Nakayama, I. Nardecchia, T. Narikawa, L. Naticchioni, B. Nayak, R. K. Nayak, R. Negishi, B. F. Neil, J. Neilson, G. Nelemans, T. J. N. Nelson, M. Nery, A. Neunzert, K. Y. Ng, S. W. S. Ng, C. Nguyen, P. Nguyen, T. Nguyen, L. Nguyen Quynh, W.-T. Ni, S. A. Nichols, A. Nishizawa, S. Nissanke, F. Nocera, M. Noh, M. Norman, C. North, S. Nozaki, L. K. Nuttall, J. Oberling, B. D. O’Brien, Y. Obuchi, J. O’Dell, W. Ogaki, G. Oganesyan, J. J. Oh, K. Oh, S. H. Oh, M. Ohashi, N. Ohishi, M. Ohkawa, F. Ohme, H. Ohta, M. A. Okada, Y. Okutani, K. Okutomi, C. Olivetto, K. Oohara, C. Ooi, R. Oram, B. O’Reilly, R. G. Ormiston, N. D. Ormsby, L. F. Ortega, R. O’Shaughnessy, E. O’Shea, S. Oshino, S. Ossokine, C. Osthelder, S. Otabe, D. J. Ottaway, H. Overmier, A. E. Pace, G. Pagano, M. A. Page, G. Pagliaroli, A. Pai, S. A. Pai, J. R. Palamos, O. Palashov, C. Palomba, K. Pan, P. K. Panda, H. Pang, P. T. H. Pang, C. Pankow, F. Pannarale, B. C. Pant, F. Paoletti, A. Paoli, A. Paolone, A. Parisi, J. Park, W. Parker, D. Pascucci, A. Pasqualetti, R. Passaquieti, D. Passuello, M. Patel, B. Patricelli, E. Payne, T. C. Pechsiri, M. Pedraza, M. Pegoraro, A. Pele, F. E. Peña Arellano, S. Penn, A. Perego, A. Pereira, T. Pereira, C. J. Perez, C. Périgois, A. Perreca, S. Perriès, J. Petermann, D. Petterson, H. P. Pfeiffer, K. A. Pham, K. S. Phukon, O. J. Piccinni, M. Pichot, M. Piendibene, F. Piergiovanni, L. Pierini, V. Pierro, G. Pillant, F. Pilo, L. Pinard, I. M. Pinto, B. J. Piotrzkowski, K. Piotrzkowski, M. Pirello, M. Pitkin, E. Placidi, W. Plastino, C. Pluchar, R. Poggiani, E. Polini, D. Y. T. Pong, S. Ponrathnam, P. Popolizio, E. K. Porter, J. Powell, M. Pracchia, T. Pradier, A. K. Prajapati, K. Prasai, R. Prasanna, G. Pratten, T. Prestegard, M. Principe, G. A. Prodi, L. Prokhorov, P. Prosposito, L. Prudenzi, A. Puecher, M. Punturo, F. Puosi, P. Puppo, M. Pürrer, H. Qi, V. Quetschke, P. J. Quinonez, R. Quitzow-James, F. J. Raab, G. Raaijmakers, H. Radkins, N. Radulesco, P. Raffai, S. X. Rail, S. Raja, C. Rajan, K. E. Ramirez, T. D. Ramirez, A. Ramos-Buades, J. Rana, P. Rapagnani, U. D. Rapol, B. Ratto, A. Ray, V. Raymond, N. Raza, M. Razzano, J. Read, L. A. Rees, T. Regimbau, L. Rei, S. Reid, D. H. Reitze, P. Relton, P. Rettegno, F. Ricci, C. J. Richardson, J. W. Richardson, L. Richardson, P. M. Ricker, G. Riemenschneider, K. Riles, M. Rizzo, N. A. Robertson, R. Robie, F. Robinet, A. Rocchi, J. A. Rocha, S. Rodriguez, R. D. Rodriguez-Soto, L. Rolland, J. G. Rollins, V. J. Roma, M. Romanelli, R. Romano, C. L. Romel, A. Romero, I. M. Romero-Shaw, J. H. Romie, C. A. Rose, D. Rosińska, S. G. Rosofsky, M. P. Ross, S. Rowan, S. J. Rowlinson, Santosh Roy, Soumen Roy, D. Rozza, P. Ruggi, K. Ryan, S. Sachdev, T. Sadecki, J. Sadiq, N. Sago, S. Saito, Y. Saito, K. Sakai, Y. Sakai, M. Sakellariadou, Y. Sakuno, O. S. Salafia, L. Salconi, M. Saleem, F. Salemi, A. Samajdar, E. J. Sanchez, J. H. Sanchez, L. E. Sanchez, N. Sanchis-Gual, J. R. Sanders, A. Sanuy, T. R. Saravanan, N. Sarin, B. Sassolas, H. Satari, B. S. Sathyaprakash, S. Sato, T. Sato, O. Sauter, R. L. Savage, V. Savant, T. Sawada, D. Sawant, H. L. Sawant, S. Sayah, D. Schaetzl, M. Scheel, J. Scheuer, A. Schindler-Tyka, P. Schmidt, R. Schnabel, M. Schneewind, R. M. S. Schofield, A. Schönbeck, B. W. Schulte, B. F. Schutz, E. Schwartz, J. Scott, S. M. Scott, M. Seglar-Arroyo, E. Seidel, T. Sekiguchi, Y. Sekiguchi, D. Sellers, A. S. Sengupta, N. Sennett, D. Sentenac, E. G. Seo, V. Sequino, A. Sergeev, Y. Setyawati, T. Shaffer, M. S. Shahriar, B. Shams, L. Shao, S. Sharifi, A. Sharma, P. Sharma, P. Shawhan, N. S. Shcheblanov, H. Shen, S. Shibagaki, M. Shikauchi, R. Shimizu, T. Shimoda, K. Shimode, R. Shink, H. Shinkai, T. Shishido, A. Shoda, D. H. Shoemaker, D. M. Shoemaker, K. Shukla, S. ShyamSundar, M. Sieniawska, D. Sigg, L. P. Singer, D. Singh, N. Singh, A. Singha, A. M. Sintes, V. Sipala, V. Skliris, B. J. J. Slagmolen, T. J. Slaven-Blair, J. Smetana, J. R. Smith, R. J. E. Smith, S. N. Somala, K. Somiya, E. J. Son, K. Soni, S. Soni, B. Sorazu, V. Sordini, F. Sorrentino, N. Sorrentino, H. Sotani, R. Soulard, T. Souradeep, E. Sowell, V. Spagnuolo, A. P. Spencer, M. Spera, A. K. Srivastava, V. Srivastava, K. Staats, C. Stachie, D. A. Steer, J. Steinlechner, S. Steinlechner, D. J. Stops, S. Stevenson, M. Stover, K. A. Strain, L. C. Strang, G. Stratta, A. Strunk, R. Sturani, A. L. Stuver, J. Südbeck, S. Sudhagar, V. Sudhir, R. Sugimoto, H. G. Suh, T. Z. Summerscales, H. Sun, L. Sun, S. Sunil, A. Sur, J. Suresh, P. J. Sutton, Takamasa Suzuki, Toshikazu Suzuki, B. L. Swinkels, M. J. Szczepańczyk, P. Szewczyk, M. Tacca, H. Tagoshi, S. C. Tait, H. Takahashi, R. Takahashi, A. Takamori, S. Takano, H. Takeda, M. Takeda, C. Talbot, H. Tanaka, Kazuyuki Tanaka, Kenta Tanaka, Taiki Tanaka, Takahiro Tanaka, A. J. Tanasijczuk, S. Tanioka, D. B. Tanner, D. Tao, A. Tapia, E. N. Tapia San Martin, J. D. Tasson, S. Telada, R. Tenorio, L. Terkowski, M. Test, M. P. Thirugnanasambandam, M. Thomas, P. Thomas, J. E. Thompson, S. R. Thondapu, K. A. Thorne, E. Thrane, Shubhanshu Tiwari, Srishti Tiwari, V. Tiwari, K. Toland, A. E. Tolley, T. Tomaru, Y. Tomigami, T. Tomura, M. Tonelli, A. Torres-Forné, C. I. Torrie, I. Tosta e Melo, D. Töyrä, A. Trapananti, F. Travasso, G. Traylor, M. C. Tringali, A. Tripathee, L. Troiano, A. Trovato, L. Trozzo, R. J. Trudeau, D. S. Tsai, D. Tsai, K. W. Tsang, T. Tsang, J-S. Tsao, M. Tse, R. Tso, K. Tsubono, S. Tsuchida, L. Tsukada, D. Tsuna, T. Tsutsui, T. Tsuzuki, M. Turconi, D. Tuyenbayev, A. S. Ubhi, N. Uchikata, T. Uchiyama, R. P. Udall, A. Ueda, T. Uehara, K. Ueno, G. Ueshima, D. Ugolini, C. S. Unnikrishnan, F. Uraguchi, A. L. Urban, T. Ushiba, S. A. Usman, A. C. Utina, H. Vahlbruch, G. Vajente, A. Vajpeyi, G. Valdes, M. Valentini, V. Valsan, N. van Bakel, M. van Beuzekom, J. F. J. van den Brand, C. Van Den Broeck, D. C. Vander-Hyde, L. van der Schaaf, J. V. van Heijningen, J. Vanosky, M. H. P. M. van Putten, M. Vardaro, A. F. Vargas, V. Varma, M. Vasúth, A. Vecchio, G. Vedovato, J. Veitch, P. J. Veitch, K. Venkateswara, J. Venneberg, G. Venugopalan, D. Verkindt, Y. Verma, D. Veske, F. Vetrano, A. Viceré, A. D. Viets, V. Villa-Ortega, J.-Y. Vinet, S. Vitale, T. Vo, H. Vocca, E. R. G. von Reis, J. von Wrangel, C. Vorvick, S. P. Vyatchanin, L. E. Wade, M. Wade, K. J. Wagner, R. C. Walet, M. Walker, G. S. Wallace, L. Wallace, S. Walsh, J. Wang, J. Z. Wang, W. H. Wang, R. L. Ward, J. Warner, M. Was, T. Washimi, N. Y. Washington, J. Watchi, B. Weaver, L. Wei, M. Weinert, A. J. Weinstein, R. Weiss, C. M. Weller, F. Wellmann, L. Wen, P. Weßels, J. W. Westhouse, K. Wette, J. T. Whelan, D. D. White, B. F. Whiting, C. Whittle, D. Wilken, D. Williams, M. J. Williams, A. R. Williamson, J. L. Willis, B. Willke, D. J. Wilson, W. Winkler, C. C. Wipf, T. Wlodarczyk, G. Woan, J. Woehler, J. K. Wofford, I. C. F. Wong, C. Wu, D. S. Wu, H. Wu, S. Wu, D. M. Wysocki, L. Xiao, W-R. Xu, T. Yamada, H. Yamamoto, Kazuhiro Yamamoto, Kohei Yamamoto, T. Yamamoto, K. Yamashita, R. Yamazaki, F. W. Yang, L. Yang, Yang Yang, Yi Yang, Z. Yang, M. J. Yap, D. W. Yeeles, A. B. Yelikar, M. Ying, K. Yokogawa, J. Yokoyama, T. Yokozawa, A. Yoon, T. Yoshioka, Hang Yu, Haocun Yu, H. Yuzurihara, A. Zadrożny, M. Zanolin, F. Zappa, S. Zeidler, T. Zelenova, J.-P. Zendri, M. Zevin, M. Zhan, H. Zhang, J. Zhang, L. Zhang, R. Zhang, T. Zhang, C. Zhao, G. Zhao, Yue Zhao, Yuhang Zhao, Z. Zhou, X. J. Zhu, Z.-H. Zhu, A. B. Zimmerman, Y. Zlochower, M. E. Zucker, J. Zweizig, and the LIGO Scientific Collaboration, the Virgo Collaboration, and the KAGRA Collaboration

Subjects
Astrophysics, QB460-466
Abstract

We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses $8.{9}_{-1.5}^{+1.2}$ and $1.{9}_{-0.2}^{+0.3}\,{M}_{\odot }$ , whereas the source of GW200115 has component masses $5.{7}_{-2.1}^{+1.8}$ and $1.{5}_{-0.3}^{+0.7}\,{M}_{\odot }$ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are ${280}_{-110}^{+110}$ and ${300}_{-100}^{+150}\,\mathrm{Mpc}$ , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of ${45}_{-33}^{+75}\,{\mathrm{Gpc}}^{-3}\,{\mathrm{yr}}^{-1}$ when assuming that GW200105 and GW200115 are representative of the NSBH population or ${130}_{-69}^{+112}\,{\mathrm{Gpc}}^{-3}\,{\mathrm{yr}}^{-1}$ under the assumption of a broader distribution of component masses.

Published
2021
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20. A Plastic Surgeons Guide to the Temporomandibular Joint: Part III, Treatment

Author

Esperanza Mantilla-Rivas, Hannah R. Crowder, Jacob S. Nasser, Monica Manrique, Taylor J. Ibelli, Mitchell Buller, Albert K. Oh, S. Alex Rottgers, Peter J. Taub, Erik M. Wolfswinkel, Jason M. Marrazzo, and Gary F. Rogers

Subjects
Cardiology and Cardiovascular Medicine
Abstract

The temporomandibular joint (TMJ) has a complex and unique anatomy. When disarranged, it may produce a constellation of symptoms and dysfunction, leading to morbidity. The causes of TMJ dysfunction are numerous but often present with similar clinical signs and symptoms. In this series, we included a review of normal anatomy and a review of the pathophysiology with assessment of the most common TMJ dysfunctions, including myofascial pain, internal derangements of the articular disk, osteoarthrosis, among others. The authors present the last of a 3-part educational series on the TMJ, addressing treatment strategies for these disorders.

Published
2023

21. Bilateral Digital Extensor Hypoplasia Correction: A Case Report and Systematic Review

Author

Marudeen Aivaz, Esperanza Mantilla-Rivas, Ashleigh Brennan, John Thomas, Elizabeth L. Malphrus, Monica Manrique, Albert K. Oh, and Gary F. Rogers

Subjects
Surgery
Abstract

Digital extensor hypoplasia (DEH) is a rare malformation that presents with loss of active finger extension at the metacarpophalangeal (MCP) joints. Descriptions of optimal treatment and outcomes in this population are sparse. We describe successful operative treatment of a child with DEH involving the extensor digitorum communis, extensor digiti minimi, and the extensor indicis proprius tendons. The 5-year-old male patient was referred for severe limitation on bilateral finger extension since birth. He had been previously diagnosed with arthrogryposis and managed conservatively. Due to lack of improvement, magnetic resonance imaging was done evidencing hypoplasia/aplasia of the extensor tendons. The patient underwent successful tendon transfers using extensor carpi radialis longus to the common extensor tendons, and one hand required an additional tenolysis procedure. 2 years postoperatively, his MCP position and finger extension are markedly improved, and he is able to grip objects without limitation or difficulty. The patient returned to full activity without restriction.

Published
2023

22. Left atrial reservoir strain as a novel predictor of new-onset atrial fibrillation in light-chain-type cardiac amyloidosis

Author

You-Jung Choi, Darae Kim, Tea-Min Rhee, Hyun-Jung Lee, Jun-Bean Park, Seung-Pyo Lee, Sung-A Chang, Yong-Jin Kim, Eun-Seok Jeon, Jae K Oh, Jin-Oh Choi, and Hyung-Kwan Kim

Subjects
Radiology, Nuclear Medicine and imaging, General Medicine, Cardiology and Cardiovascular Medicine
Abstract

Aims To investigate whether left arterial reservoir strain (LASr) could predict new-onset atrial fibrillation (NOAF) in patients with light-chain-type cardiac amyloidosis (ALCA). Methods and results This study enrolled 427 patients with CA from two tertiary centres between 2005 and 2019. LASr was measured using a vendor-independent analysis programme. The primary outcome was NOAF. A total of 287 patients with ALCA were included [median age 63.0 (56.0–70.0) years, 53.3% male]. The median LASr was 13.9% (10.5–20.8%). During the median follow-up of 0.85 years, AF occurred in 34 patients (11.8%). In the receiver operating characteristics curve analysis, the optimal cut-off of LASr for predicting NOAF was 14.4%. Patients with LASr ≤14.4% had a higher risk of NOAF than those with LASr >14.4% (18.1% vs. 5.1%, P < 0.010). In the multivariate analysis adjusting for confounding factors, including left arterial volume index and left ventricular global longitudinal strain (LV-GLS), higher LASr (%) was independently associated with lower risk for NOAF [adjusted hazard ratio (aHR): 0.936, 95% confidence interval (95% CI): 0.879–0.997, P = 0.039]. Furthermore, LASr ≤14.4% was an independent predictor for NOAF (aHR: 3.370, 95% CI: 1.337–8.492, P = 0.010). This remained true after accounting for all-cause death as a competing risk. Compared with Model 1 (LV-GLS) and Model 2 (LV-GLS plus LAVI), Model 3, including LASr showed a better reclassification ability for predicting NOAF (net reclassification index = 0.735, P < 0.001 compared with Model 1; net reclassification index = 0.514, P = 0.003 compared with Model 2). Conclusion LASr was an independent predictor of NOAF in patients with ALCA.

Published
2023

24. 2-Year Outcomes of Transcatheter Mitral Valve Replacement in Patients With Annular Calcification, Rings, and Bioprostheses

Author

Mackram F. Eleid, Dee Dee Wang, Amit Pursnani, Susheel K. Kodali, Issac George, Igor Palacios, Hyde Russell, Raj R. Makkar, Saibal Kar, Lowell F. Satler, Vivek Rajagopal, George Dangas, Gilbert H.L. Tang, James M. McCabe, Brian K. Whisenant, Kenith Fang, Tatiana Kaptzan, Bradley Lewis, Pamela Douglas, Rebecca Hahn, Jeremy Thaden, Jae K. Oh, Martin Leon, William O'Neill, Charanjit S. Rihal, and Mayra E. Guerrero

Subjects
Bioprosthesis, Quality of Life, Humans, Mitral Valve, Calcinosis, Prospective Studies, Cardiology and Cardiovascular Medicine
Abstract

The MITRAL (Mitral Implantation of Transcatheter Valves) trial is the first prospective study for valve-in-mitral annular calcification (ViMAC), mitral valve-in-ring (MViR), and mitral valve-in-valve (MViV) using balloon-expandable aortic transcatheter heart valves. Procedural outcomes beyond 1 year are not well described.This study evaluated 2-year outcomes in ViMAC, MViR, and MViV in the MITRAL trial.This multicenter prospective study enrolled patients with severe MAC, prior failed mitral annuloplasty ring repair, or prior failed bioprosthetic MV replacement who were at high surgical risk at 13 U.S. sites.Between February 1, 2015, and December 31, 2017, 91 patients were enrolled (31 with ViMAC, 30 with MViR, and 30 with MViV). In the ViMAC group, 2-year all-cause mortality was 39.3%, 66.7% were New York Heart Association (NYHA) functional class I-II, and mean MV gradient was 5.6 ± 2.0 mm Hg. In the MViR group, 2-year all-cause mortality was 50%, 65% were NYHA functional class I-II, and mean MV gradient was 6.5 ± 2.7 mm Hg. In the MViV group, 2-year all-cause mortality was 6.7%, 85% were NYHA functional class I-II, and mean MV gradient was 6.9 ± 2.4 mm Hg. At 2 years, all patients had ≤mild mitral regurgitation and survivors in all 3 arms showed sustained improvement in Kansas City Cardiomyopathy Questionnaire scores compared to baseline.Use of balloon-expandable aortic transcatheter heart valves in selected patients with severe MAC, failed annuloplasty ring, and bioprosthetic MV dysfunction is associated with improvements in symptoms, quality of life, and stable prosthesis function at 2-year follow-up. Between 1 and 2 years, the MViR group experienced higher mortality rates than the MViV and ViMAC groups.

Published
2022

25. Narrowband Searches for Continuous and Long-duration Transient Gravitational Waves from Known Pulsars in the LIGO-Virgo Third Observing Run

Author

R. Abbott, T. D. Abbott, F. Acernese, K. Ackley, C. Adams, N. Adhikari, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, M. Agathos, K. Agatsuma, N. Aggarwal, O. D. Aguiar, L. Aiello, A. Ain, P. Ajith, T. Akutsu, S. Albanesi, A. Allocca, P. A. Altin, A. Amato, C. Anand, S. Anand, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Ando, T. Andrade, N. Andres, T. Andrić, S. V. Angelova, S. Ansoldi, J. M. Antelis, S. Antier, S. Appert, Koji Arai, Koya Arai, Y. Arai, S. Araki, A. Araya, M. C. Araya, J. S. Areeda, M. Arène, N. Aritomi, N. Arnaud, S. M. Aronson, K. G. Arun, H. Asada, Y. Asali, G. Ashton, Y. Aso, M. Assiduo, S. M. Aston, P. Astone, F. Aubin, C. Austin, S. Babak, F. Badaracco, M. K. M. Bader, C. Badger, S. Bae, Y. Bae, A. M. Baer, S. Bagnasco, Y. Bai, M. Bailes, L. Baiotti, J. Baird, R. Bajpai, M. Ball, G. Ballardin, S. W. Ballmer, A. Balsamo, G. Baltus, S. Banagiri, D. Bankar, J. C. Barayoga, C. Barbieri, B. C. Barish, D. Barker, P. Barneo, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, J. Bartlett, M. A. Barton, I. Bartos, R. Bassiri, A. Basti, M. Bawaj, J. C. Bayley, A. C. Baylor, M. Bazzan, B. Bécsy, V. M. Bedakihale, M. Bejger, I. Belahcene, V. Benedetto, D. Beniwal, T. F. Bennett, J. D. Bentley, M. BenYaala, F. Bergamin, B. K. Berger, S. Bernuzzi, D. Bersanetti, A. Bertolini, J. Betzwieser, D. Beveridge, R. Bhandare, U. Bhardwaj, D. Bhattacharjee, S. Bhaumik, I. A. Bilenko, G. Billingsley, S. Bini, I. A. Birney, O. Birnholtz, S. Biscans, M. Bischi, S. Biscoveanu, A. Bisht, B. Biswas, M. Bitossi, M.-A. Bizouard, J. K. Blackburn, C. D. Blair, D. G. Blair, R. M. Blair, F. Bobba, N. Bode, M. Boer, G. Bogaert, M. Boldrini, L. D. Bonavena, F. Bondu, E. Bonilla, R. Bonnand, P. Booker, B. A. Boom, R. Bork, V. Boschi, N. Bose, S. Bose, V. Bossilkov, V. Boudart, Y. Bouffanais, A. Bozzi, C. Bradaschia, P. R. Brady, A. Bramley, A. Branch, M. Branchesi, J. E. Brau, M. Breschi, T. Briant, J. H. Briggs, A. Brillet, M. Brinkmann, P. Brockill, A. F. Brooks, J. Brooks, D. D. Brown, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, T. Bulik, H. J. Bulten, A. Buonanno, R. Buscicchio, D. Buskulic, C. Buy, R. L. Byer, L. Cadonati, G. Cagnoli, C. Cahillane, J. Calderón Bustillo, J. D. Callaghan, T. A. Callister, E. Calloni, J. Cameron, J. B. Camp, M. Canepa, S. Canevarolo, M. Cannavacciuolo, K. C. Cannon, H. Cao, Z. Cao, E. Capocasa, E. Capote, G. Carapella, F. Carbognani, J. B. Carlin, M. F. Carney, M. Carpinelli, G. Carrillo, G. Carullo, T. L. Carver, J. Casanueva Diaz, C. Casentini, G. Castaldi, S. Caudill, M. Cavaglià, F. Cavalier, R. Cavalieri, M. Ceasar, G. Cella, P. Cerdá-Durán, E. Cesarini, W. Chaibi, K. Chakravarti, S. Chalathadka Subrahmanya, E. Champion, C.-H. Chan, C. Chan, C. L. Chan, K. Chan, M. Chan, K. Chandra, P. Chanial, S. Chao, P. Charlton, E. A. Chase, E. Chassande-Mottin, C. Chatterjee, Debarati Chatterjee, Deep Chatterjee, M. Chaturvedi, S. Chaty, C. Chen, H. Y. Chen, J. Chen, K. Chen, X. Chen, Y.-B. Chen, Y.-R. Chen, Z. Chen, H. Cheng, C. K. Cheong, H. Y. Cheung, H. Y. Chia, F. Chiadini, C-Y. Chiang, G. Chiarini, R. Chierici, A. Chincarini, M. L. Chiofalo, A. Chiummo, G. Cho, H. S. Cho, R. K. Choudhary, S. Choudhary, N. Christensen, H. Chu, Q. Chu, Y-K. Chu, S. Chua, K. W. Chung, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, A. A. Ciobanu, R. Ciolfi, F. Cipriano, A. Cirone, F. Clara, E. N. Clark, J. A. Clark, L. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, E. Codazzo, P.-F. Cohadon, D. E. Cohen, L. Cohen, M. Colleoni, C. G. Collette, A. Colombo, M. Colpi, C. M. Compton, M. Constancio Jr., L. Conti, S. J. Cooper, P. Corban, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, K. R. Corley, N. Cornish, D. Corre, A. Corsi, S. Cortese, C. A. Costa, R. Cotesta, M. W. Coughlin, J.-P. Coulon, S. T. Countryman, B. Cousins, P. Couvares, D. M. Coward, M. J. Cowart, D. C. Coyne, R. Coyne, J. D. E. Creighton, T. D. Creighton, A. W. Criswell, M. Croquette, S. G. Crowder, J. R. 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J. E. Smith, J. Soldateschi, S. N. Somala, K. Somiya, E. J. Son, K. Soni, S. Soni, V. Sordini, F. Sorrentino, N. Sorrentino, H. Sotani, R. Soulard, T. Souradeep, E. Sowell, V. Spagnuolo, A. P. Spencer, M. Spera, R. Srinivasan, A. K. Srivastava, V. Srivastava, K. Staats, C. Stachie, D. A. Steer, J. Steinlechner, S. Steinlechner, D. J. Stops, M. Stover, K. A. Strain, L. C. Strang, G. Stratta, A. Strunk, R. Sturani, A. L. Stuver, S. Sudhagar, V. Sudhir, R. Sugimoto, H. G. Suh, T. Z. Summerscales, H. Sun, L. Sun, S. Sunil, A. Sur, J. Suresh, P. J. Sutton, Takamasa Suzuki, Toshikazu Suzuki, B. L. Swinkels, M. J. Szczepańczyk, P. Szewczyk, M. Tacca, H. Tagoshi, S. C. Tait, H. Takahashi, R. Takahashi, A. Takamori, S. Takano, H. Takeda, M. Takeda, C. J. Talbot, C. Talbot, H. Tanaka, Kazuyuki Tanaka, Kenta Tanaka, Taiki Tanaka, Takahiro Tanaka, A. J. Tanasijczuk, S. Tanioka, D. B. Tanner, D. Tao, L. Tao, E. N. Tapia San Martín, C. Taranto, J. D. Tasson, S. Telada, R. Tenorio, J. E. Terhune, L. Terkowski, M. P. Thirugnanasambandam, M. Thomas, P. Thomas, J. E. Thompson, S. R. Thondapu, K. A. Thorne, E. Thrane, Shubhanshu Tiwari, Srishti Tiwari, V. Tiwari, A. M. Toivonen, K. Toland, A. E. Tolley, T. Tomaru, Y. Tomigami, T. Tomura, M. Tonelli, A. Torres-Forné, C. I. Torrie, I. Tosta e Melo, D. Töyrä, A. Trapananti, F. Travasso, G. Traylor, M. Trevor, M. C. Tringali, A. Tripathee, L. Troiano, A. Trovato, L. Trozzo, R. J. Trudeau, D. S. Tsai, D. Tsai, K. W. Tsang, T. Tsang, J-S. Tsao, M. Tse, R. Tso, K. Tsubono, S. Tsuchida, L. Tsukada, D. Tsuna, T. Tsutsui, T. Tsuzuki, K. Turbang, M. Turconi, D. Tuyenbayev, A. S. Ubhi, N. Uchikata, T. Uchiyama, R. P. Udall, A. Ueda, T. Uehara, K. Ueno, G. Ueshima, C. S. Unnikrishnan, F. Uraguchi, A. L. Urban, T. Ushiba, A. Utina, H. Vahlbruch, G. Vajente, A. Vajpeyi, G. Valdes, M. Valentini, V. Valsan, N. van Bakel, M. van Beuzekom, J. F. J. van den Brand, C. Van Den Broeck, D. C. Vander-Hyde, L. van der Schaaf, J. V. van Heijningen, J. Vanosky, M. H. P. M. van Putten, N. van Remortel, M. Vardaro, A. F. Vargas, V. Varma, M. Vasúth, A. Vecchio, G. Vedovato, J. Veitch, P. J. Veitch, J. Venneberg, G. Venugopalan, D. Verkindt, P. Verma, Y. Verma, D. Veske, F. Vetrano, A. Viceré, S. Vidyant, A. D. Viets, A. Vijaykumar, V. Villa-Ortega, J.-Y. Vinet, A. Virtuoso, S. Vitale, T. Vo, H. Vocca, E. R. G. von Reis, J. S. A. von Wrangel, C. Vorvick, S. P. Vyatchanin, L. E. Wade, M. Wade, K. J. Wagner, R. C. Walet, M. Walker, G. S. Wallace, L. Wallace, S. Walsh, J. Wang, J. Z. Wang, W. H. Wang, R. L. Ward, J. Warner, M. Was, T. Washimi, N. Y. Washington, J. Watchi, B. Weaver, S. A. Webster, M. Weinert, A. J. Weinstein, R. Weiss, C. M. Weller, F. Wellmann, L. Wen, P. Weßels, K. Wette, J. T. Whelan, D. D. White, B. F. Whiting, C. Whittle, D. Wilken, D. Williams, M. J. Williams, A. R. Williamson, J. L. Willis, B. Willke, D. J. Wilson, W. Winkler, C. C. Wipf, T. Wlodarczyk, G. Woan, J. Woehler, J. K. Wofford, I. C. F. Wong, C. Wu, D. S. Wu, H. Wu, S. Wu, D. M. Wysocki, L. Xiao, W-R. Xu, T. Yamada, H. Yamamoto, Kazuhiro Yamamoto, Kohei Yamamoto, T. Yamamoto, K. Yamashita, R. Yamazaki, F. W. Yang, L. Yang, Y. Yang, Yang Yang, Z. Yang, M. J. Yap, D. W. Yeeles, A. B. Yelikar, M. Ying, K. Yokogawa, J. Yokoyama, T. Yokozawa, J. Yoo, T. Yoshioka, Hang Yu, Haocun Yu, H. Yuzurihara, A. Zadrożny, M. Zanolin, S. Zeidler, T. Zelenova, J.-P. Zendri, M. Zevin, M. Zhan, H. Zhang, J. Zhang, L. Zhang, T. Zhang, Y. Zhang, C. Zhao, G. Zhao, Y. Zhao, Yue Zhao, R. Zhou, Z. Zhou, X. J. Zhu, Z.-H. Zhu, M. E. Zucker, J. Zweizig, The LIGO Scientific Collaboration, the Virgo Collaboration, and the KAGRA Collaboration, D. Antonopoulou, Z. Arzoumanian, A. Basu, S. Bogdanov, I. Cognard, K. Crowter, T. Enoto, C. M. Espinoza, C. M. L. Flynn, E. Fonseca, D. C. Good, L. Guillemot, S. Guillot, A. K. Harding, M. J. Keith, L. Kuiper, M. E. Lower, A. G. Lyne, J. W. McKee, B. W. Meyers, C. Ng, J. L. Palfreyman, R. M. Shannon, B. Shaw, I. H. Stairs, B. W. Stappers, C. M. Tan, G. Theureau, and P. Weltevrede

Subjects
Gravitational wave astronomy, Neutron stars, Pulsars, Astrophysics, QB460-466
Abstract

Isolated neutron stars that are asymmetric with respect to their spin axis are possible sources of detectable continuous gravitational waves. This paper presents a fully coherent search for such signals from eighteen pulsars in data from LIGO and Virgo’s third observing run (O3). For known pulsars, efficient and sensitive matched-filter searches can be carried out if one assumes the gravitational radiation is phase-locked to the electromagnetic emission. In the search presented here, we relax this assumption and allow both the frequency and the time derivative of the frequency of the gravitational waves to vary in a small range around those inferred from electromagnetic observations. We find no evidence for continuous gravitational waves, and set upper limits on the strain amplitude for each target. These limits are more constraining for seven of the targets than the spin-down limit defined by ascribing all rotational energy loss to gravitational radiation. In an additional search, we look in O3 data for long-duration (hours–months) transient gravitational waves in the aftermath of pulsar glitches for six targets with a total of nine glitches. We report two marginal outliers from this search, but find no clear evidence for such emission either. The resulting duration-dependent strain upper limits do not surpass indirect energy constraints for any of these targets.

Published
2022
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27. A Tale of Two Hierarchies: Interactive Effects of Power Differentiation and Status Differentiation on Team Performance

Author

Nicholas A. Hays, Huisi (Jessica) Li, Xue Yang, Jo K. Oh, Andrew Yu, Ya-Ru Chen, John R. Hollenbeck, and Bradley B. Jamieson

Subjects
Organizational Behavior and Human Resource Management, Management of Technology and Innovation, Strategy and Management, education
Abstract

Scholars have long wrestled with whether hierarchical differentiation is functional or dysfunctional for teams. Building on emerging research that emphasizes the distinction between power (i.e., control over resources) and status (i.e., respect from others), we aim to help reconcile the functional and dysfunctional accounts of hierarchy by examining the effects of power differentiation on team performance, contingent on status differentiation. We theorize that power differentiation is dysfunctional for teams with high status differentiation by increasing knowledge hiding, which undermines team performance. In contrast, we predict that power differentiation is functional for teams with low status differentiation by decreasing knowledge hiding, which improves team performance. In a field study, we found that power differentiation harmed team performance via knowledge hiding in teams with high status differentiation, but power differentiation had no effect on knowledge hiding or performance in teams with low status differentiation. In an experiment, we again found that power differentiation harmed team performance by increasing knowledge hiding in teams with high status differentiation. However, power differentiation improved team performance by decreasing knowledge hiding in teams with status equality. Finally, in a third study, we confirm the role of status differentiation in making team climates more competitive and examine the effect of power-status alignment within teams, finding that misalignment exacerbates the dysfunctional effects of power differentiation in teams with high status differentiation. By examining how power and status hierarchies operate in tandem, this work underscores the need to take a more nuanced approach to studying hierarchy in teams. Funding: This research is partially supported by the National Natural Science Foundation of China [Grants 71572079 and 71872086]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1540 .

Published
2022

28. Self-expanding Transcatheter vs Surgical Aortic Valve Replacement in Intermediate-Risk Patients: 5-Year Outcomes of the SURTAVI Randomized Clinical Trial

Author

Nicolas M, Van Mieghem, G Michael, Deeb, Lars, Søndergaard, Eberhard, Grube, Stephan, Windecker, Hemal, Gada, Mubashir, Mumtaz, Peter S, Olsen, John C, Heiser, William, Merhi, Neal S, Kleiman, Stanley J, Chetcuti, Thomas G, Gleason, Joon Sup, Lee, Wen, Cheng, Raj R, Makkar, Juan, Crestanello, Barry, George, Isaac, George, Susheel, Kodali, Steven J, Yakubov, Patrick W, Serruys, Rüdiger, Lange, Nicolo, Piazza, Mathew R, Williams, Jae K, Oh, David H, Adams, Shuzhen, Li, Michael J, Reardon, and James, Yun

Subjects
Male, Stroke, Aortic Valve, Heart Valve Prosthesis, Humans, Female, Aortic Valve Stenosis, Prospective Studies, Cardiology and Cardiovascular Medicine, Aged
Abstract

Importance: In patients with severe aortic valve stenosis at intermediate surgical risk, transcatheter aortic valve replacement (TAVR) with a self-expanding supra-annular valve was noninferior to surgery for all-cause mortality or disabling stroke at 2 years. Comparisons of longer-term clinical and hemodynamic outcomes in these patients are limited.Objective: To report prespecified secondary 5-year outcomes from the Symptomatic Aortic Stenosis in Intermediate Risk Subjects Who Need Aortic Valve Replacement (SURTAVI) randomized clinical trial.Design, setting, and participants: SURTAVI is a prospective randomized, unblinded clinical trial. Randomization was stratified by investigational site and need for revascularization determined by the local heart teams. Patients with severe aortic valve stenosis deemed to be at intermediate risk of 30-day surgical mortality were enrolled at 87 centers from June 19, 2012, to June 30, 2016, in Europe and North America. Analysis took place between August and October 2021.Intervention: Patients were randomized to TAVR with a self-expanding, supra-annular transcatheter or a surgical bioprosthesis.Main outcomes and measures: The prespecified secondary end points of death or disabling stroke and other adverse events and hemodynamic findings at 5 years. An independent clinical event committee adjudicated all serious adverse events and an independent echocardiographic core laboratory evaluated all echocardiograms at 5 years.Results: A total of 1660 individuals underwent an attempted TAVR (n = 864) or surgical (n = 796) procedure. The mean (SD) age was 79.8 (6.2) years, 724 (43.6%) were female, and the mean (SD) Society of Thoracic Surgery Predicted Risk of Mortality score was 4.5% (1.6%). At 5 years, the rates of death or disabling stroke were similar (TAVR, 31.3% vs surgery, 30.8%; hazard ratio, 1.02 [95% CI, 0.85-1.22]; P = .85). Transprosthetic gradients remained lower (mean [SD], 8.6 [5.5] mm Hg vs 11.2 [6.0] mm Hg; P < .001) and aortic valve areas were higher (mean [SD], 2.2 [0.7] cm2 vs 1.8 [0.6] cm2; P < .001) with TAVR vs surgery. More patients had moderate/severe paravalvular leak with TAVR than surgery (11 [3.0%] vs 2 [0.7%]; risk difference, 2.37% [95% CI, 0.17%- 4.85%]; P = .05). New pacemaker implantation rates were higher for TAVR than surgery at 5 years (289 [39.1%] vs 94 [15.1%]; hazard ratio, 3.30 [95% CI, 2.61-4.17]; log-rank P < .001), as were valve reintervention rates (27 [3.5%] vs 11 [1.9%]; hazard ratio, 2.21 [95% CI, 1.10-4.45]; log-rank P = .02), although between 2 and 5 years only 6 patients who underwent TAVR and 7 who underwent surgery required a reintervention.Conclusions and relevance: Among intermediate-risk patients with symptomatic severe aortic stenosis, major clinical outcomes at 5 years were similar for TAVR and surgery. TAVR was associated with superior hemodynamic valve performance but also with more paravalvular leak and valve reinterventions.

Published
2023

29. Extraction of Treatment Information From Electronic Health Records and Evaluation of Testosterone Recovery in Patients With Prostate Cancer

Author

Sunny Guin, Tomi Jun, Vaibhav G. Patel, Kristin L. Ayers, Matthew Deitz, Yuqin Cai, Xiang Zhou, Che-Kai Tsao, William K. Oh, Rong Chen, and Bobby C. Liaw

Subjects
Male, Electronic Health Records, Humans, Prostatic Neoplasms, Androgen Antagonists, Testosterone, General Medicine, ORIGINAL REPORTS, Prostate-Specific Antigen
Abstract

PURPOSE Data quality and standardization remain a challenge when analyzing real-world clinical data. We built a clinical research database, using machine learning and natural learning processing, and investigated factors influencing testosterone recovery (T-recovery) in patients with localized prostate cancer (LPC) after initial androgen deprivation therapy (ADT). METHODS Medication and treatment-associated dates missing in structured tables were extracted from patient notes using ConceptMapper, an automated data extraction tool, standardized and curated in Sema4 clinical research database. ADT usage duration was evaluated, and T-recovery in patients with LPC was analyzed by the Kaplan-Meier method and multivariable Cox proportional hazards models. We assessed the prognostic value of post-ADT T-recovery with prostate-specific antigen progression-free survival and failure-free survival. RESULTS In total, 4,125 of 30,832 (13.4%) patients with prostate cancer had medication exclusively from notes with high precision and recall, F1 score ≥ 0.95. Association of dates with medication usage had a F1 score of 0.76. ADT duration estimation had higher accuracy combining information from notes to tables from electronic medical record (70% v 45%). Baseline testosterone was the strongest predictor of T-recovery in these patients. Patients with a baseline testosterone ≥ 300 ng/dL recovered in 9.79 versus 38 months for patients with baseline testosterone < 300 ng/dL ( P < .0001). Shorter prostate-specific antigen progression-free interval was observed for patients with T-recovery (≥ 300 ng/dL) at 6 months after ADT cessation compared with patients without T-recovery (< 300 ng/dL; 13.7 v 25.1 months; P = .055). CONCLUSION We augmented structured electronic medical record data with data extracted from notes and improved the accuracy of medication information for patients. ADT exposure and T-recovery in patients with LPC produced results consistent with the literature and clinical experience and illustrates the power of applying machine learning methods to enhance the quality of real-world evidence in answering clinically relevant questions.

Published
2023

31. Echo-Doppler and strain assessment of filling pressures in adults with congenitally corrected transposition and systemic right ventricles

Author

C Charles Jain, Alexander C Egbe, Jae K Oh, Heidi M Connolly, and William R Miranda

Subjects
Radiology, Nuclear Medicine and imaging, General Medicine, Cardiology and Cardiovascular Medicine
Abstract

Aims Systolic dysfunction of the systemic right ventricle (sRV) is common in adults with transposition of the great arteries and sRV. In acquired disease, diastology analysis for assessment of filling pressures (FP) is paramount in patient care. Methods and results Retrospective analysis of 47 adults with sRV without prior systemic tricuspid valve surgery undergoing catheterization and echocardiography within 7 days (median −2 [−1, −3]) from January 2000 to February 2021 at our institution. Median age was 48 (31, 55) years, and 16 (34.0%) patients were female. FPs were normal in 21 patients (44.7%). Left atrial size was enlarged in most patients (83.0%) with mean indexed value 58.3 ± 23.4 mL/m2. Tissue Doppler e′ was not significantly different between those with high FPs vs. normal (medial 0.07 ± 0.03 vs. 0.08 ± 0.03 m/s, P = 0.63; lateral 0.08 ± 0.04 vs. 0.08 ± 0.04 m/s, P = 0.88). E velocity and subpulmonic mitral regurgitant velocity were higher in those with high FPs (0.9 ± 0.3 vs. 0.6 ± 0.2 m/s, P = 0.005; 3.8 ± 1.1 vs. 2.8 ± 0.9 m/s, P = 0.004). Left atrial reservoir strain, sRV global longitudinal strain, and subpulmonic left ventricular strain were worse in those with high FP (18.0 ± 7.6 vs. 27.9 ± 10.2%, P = 0.0009; −13.0 ± 4.4 vs. −17.9 ± 5.0%, P = 0.002; −16.8 ± 5.7 vs. −23.0 ± 3.8%, P = 0.001). Conclusion Despite the complex anatomy, FPs can be assessed non-invasively in adults with sRV without prior systemic tricuspid valve surgery. The current guideline algorithm for diastolic dysfunction in acquired heart disease has limited applicability in this population. Given the limitations of Doppler in this heterogeneous population, strain analysis can be a helpful adjunct for estimation of FPs.

Published
2022

34. Left common trunkus pulmonary veins have genetic background and poor rhythm outcome after atrial fibrillation catheter ablation

Author

S Choi, S Y Yang, J K Oh, D Kim, J W Park, H T Yu, J S Uhm, B Joung, M H Lee, C Hwang, and H N Pak

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Funding Acknowledgements Type of funding sources: None. Background There is a genetic background in pulmonary vein (PV) development and atrial fibrillation (AF). However, the genetic trait of PV variations and their rhythm outcome after AF catheter ablation (AFCA) is unclear. Objective We explored the genetic and clinical characteristics and long-term rhythm outcomes of AF patients with PV variation or left common trunkus (LCT)-PV. Methods We included 2,897 AF patients (74.0% male, age 59.0 ± 10.7 years, 66.3% paroxysmal AF) with available genome-wide association study results, cardiac computed tomogram data, and protocol-based regular rhythm follow-up from the Yonsei AF ablation cohort database. We defined LCT-PV when the upper and lower PV separate at >10 mm distal to the left PV antrum margin. PV variations included both LCT-PV and accessory PVs. We analyzed the polygenic risk score (PRS) of 12 AF-associated genes (DSP, GJA1, HCN4, KCNQ1, NPPA, PITX2, RYR2, SCN5a, SHOX2, ATP2A2, TBX3, and TBX5) and long-term rhythm outcomes after AFCA. Results We found PV variation in 296 (10.2%) and LCT-PV in 102 (3.5%). PRS of 1,227 single nucleotid polymorphisms (SNPs) was significantly higher in PV variation patients (p=4.93e-08) and LCT-PV patients (p=1.95e-20). The patients with LCT-PV had higher CHA2DS2VASc scores (p=0.024) and lower atrial epicardial adipose tissue volume (p=0.034). During 39.7 ± 34.8 months follow-up period, LCT-PV patients had a significantly higher recurrence rate than their counter part in the paroxysmal AF sub-group (Log-rank p=0.036), but not in overall PV variations. LCT-PV with the highest 10% PRS was independently associated with AF recurrence after AFCA (HR 2.10, 95% CI 1.21-3.63, p=0.008). Conclusions Among the patients who underwent AFCA, PV variation, including LCT-PV, has a significant genetic background. The post-AFCA recurrence rate was significantly higher in patients with LCT-PV and high PRS, especially in paroxysmal AF.

Published
2023

36. Incidence, relevant patient factors, and clinical outcomes of the misdiagnosis of ST-elevation myocardial infarction: Results from the Korea Acute Myocardial Infraction Registry

Author

K Cho, M H Shin, M C Kim, D S Sim, Y J Hong, J H Kim, Y Ahn, H S Kim, S H Hur, S R Lee, J Y Hwang, S K Oh, K S Cha, and M H Jeong

Subjects
General Medicine, Cardiology and Cardiovascular Medicine, Critical Care and Intensive Care Medicine
Abstract

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Korea Centre for Disease Control and Prevention. Background/Introduction Data regarding the incidence, relevant patient factors, and clinical outcomes of the misdiagnosis of ST-elevation myocardial infarction (STEMI) in the modern era of percutaneous coronary intervention are limited. Purpose We investigated the incidence, relevant patient factors, and clinical outcomes of the misdiagnosis of STEMI from a nationwide, prospective Korean registry of acute myocardial infarction. Methods Out of 28,470 patients with acute myocardial infarction between November 2011 and June 2020, 11,796 were eventually diagnosed with STEMI following a coronary angiogram. They were classified into two groups: patients with an initial working diagnosis of STEMI before starting the initial treatment and patients with an initial working diagnosis of non-STEMI (misdiagnosed group). Results Out of 11,796 patients with a final diagnosis of STEMI, 165 (1.4%) were misdiagnosed. The door-to-angiography time in the misdiagnosed group was five times longer than that in the timely diagnosed group (median 220 [interquartile range 66–1177] vs. 43 [31–58] minutes, P Conclusion Misdiagnosis of STEMI is not uncommon and is associated with a significant delay in coronary angiography, resulting in an increased one-year mortality for patients with culprit lesions in the left anterior descending artery.

Published
2023

38. Supplementary Table S1 from Association of Prostate Cancer Risk Loci with Disease Aggressiveness and Prostate Cancer–Specific Mortality

Author

Matthew L. Freedman, Philip W. Kantoff, William K. Oh, Mari Nakabayashi, Gillian Petrozziello, Carolyn Evan, Tong Sun, Gwo-Shu Mary Lee, Meredith M. Regan, Wanling Xie, Lillian Werner, and Mark M. Pomerantz

Abstract

Supplementary Table S1 from Association of Prostate Cancer Risk Loci with Disease Aggressiveness and Prostate Cancer–Specific Mortality

Published
2023

39. Supplementary Data 1 from Prostate Cancer in World Trade Center Responders Demonstrates Evidence of an Inflammatory Cascade

Author

William K. Oh, Emanuela Taioli, Jun Zhu, Matthew Galsky, Stuart A. Aaronson, Michael J. Donovan, Mayte Suarez-Farinas, Dana Hashim, Lung-Chi Chen, Judith Zelikoff, Hyun-Wook Lee, Sung-Hyun Park, Maureen Sisco, Lori Horton, Colette Prophete, Mitchell D. Cohen, Naomi Alpert, Haocheng Yu, Li Wang, and Yixuan Gong

Abstract

Difference in gene expression between archived WTC and non WTC cases

Published
2023

40. Supplementary Data 3 from Prostate Cancer in World Trade Center Responders Demonstrates Evidence of an Inflammatory Cascade

Author

William K. Oh, Emanuela Taioli, Jun Zhu, Matthew Galsky, Stuart A. Aaronson, Michael J. Donovan, Mayte Suarez-Farinas, Dana Hashim, Lung-Chi Chen, Judith Zelikoff, Hyun-Wook Lee, Sung-Hyun Park, Maureen Sisco, Lori Horton, Colette Prophete, Mitchell D. Cohen, Naomi Alpert, Haocheng Yu, Li Wang, and Yixuan Gong

Abstract

Differentially expressed genes in rat prostates exposed to WTC dusts

Published
2023

41. STR DNA Profiling for Cell Line Authentication from Small-Molecule Activators of Protein Phosphatase 2A for the Treatment of Castration-Resistant Prostate Cancer

Author

Matthew D. Galsky, Goutham Narla, Michael Ohlmeyer, Yiannis Ioannou, Analisa DiFeo, Rosalie Sears, John P. Sfakianos, Alexander Kirschenbaum, Alice C. Levine, William K. Oh, Cynthia C.T. Sprenger, Stephen R. Plymate, David L. Brautigan, Yixuan Gong, Nilesh Zaware, Daniel McQuaid, Divya Hoon, Shen Yao, Agnes Stachnik, Janna Kiselar, Maxwell Cooper, Daniela Schlatzer, David B. Kastrinsky, Jaya Sangodkar, Abbey Perl, Danica Wiredja, Sudeh Izadmehr, David Callejas, Rita A. Avelar, and Kimberly McClinch

Abstract

STR DNA Profiling for Cell Line Authentication

Published
2023

42. Data from Evaluation of 8q24 and 17q Risk Loci and Prostate Cancer Mortality

Author

Matthew L. Freedman, Meir J. Stampfer, David J. Hunter, Philip W. Kantoff, Janet L. Stanford, Lorelei Mucci, Jing Ma, Tobias Kurth, Elaine A. Ostrander, Oliver Sartor, William K. Oh, Gwo-Shu Lee, Christine A. Beckwith, Fredrick R. Schumacher, Mark Pomerantz, Claudia A. Salinas, and Kathryn L. Penney

Abstract

Purpose: Variants at chromosomal loci 8q24 and 17q are established risk factors for prostate cancer. Many studies have confirmed the findings for risk, but few have examined aggressiveness and other clinical variables in detail. Additionally, Gleason score is typically used as a surrogate for the primary end point of prostate cancer mortality. We investigated whether the 8q24 and 17q risk variants are associated with clinical variables as well as prostate cancer mortality.Experimental Design: In the Physicians' Health Study (1,347 cases and 1,462 controls), the Dana-Farber Harvard Cancer Center Specialized Program of Research Excellence (Gelb Center; 3,714 cases), and the Fred Hutchinson Cancer Research Center King County Case-Control Studies (1,308 cases and 1,266 controls), we examined eight previously identified 8q24 and 17q risk variants for association with prostate cancer mortality in men of European ancestry. We considered associations with other surrogate markers of prostate cancer aggressiveness, such as Gleason score, pathologic stage, prostate-specific antigen at diagnosis, and age at diagnosis.Results: Six of the eight variants were confirmed as prostate cancer risk factors. Several variants were nominally associated with age at diagnosis; when totaling all alleles for single nucleotide polymorphisms significantly associated with risk, each additional allele decreased age at diagnosis by an average of 6 months in the Physicians' Health Study (P = 0.0005) and 4 months in the Dana-Farber Harvard Cancer Center Specialized Program of Research Excellence (Gelb Center) cohort (P = 0.0016). However, there were no statistically significant associations with prostate cancer mortality.Conclusions: Our results suggest that the 8q24 and 17q prostate cancer risk variants may influence age at diagnosis but not disease aggressiveness.

Published
2023

43. Data from Genome-wide Association Study of Prostate Cancer Mortality

Author

Matthew L. Freedman, David J. Hunter, Meir J. Stampfer, Edward L. Giovannucci, Philip W. Kantoff, Tobias Kurth, William K. Oh, Jing Ma, Peter L. Kraft, Lorelei A. Mucci, Jennifer A. Sinnott, Fredrick R. Schumacher, Saumyadipta Pyne, and Kathryn L. Penney

Abstract

Background: A pressing clinical issue in prostate cancer is to distinguish which men will have an indolent or aggressive course of disease. Clinical variables such as Gleason grade and stage are useful predictors of lethal cancer; however, the low predictive values of the common Gleason scores, changes in grading over time, and earlier diagnosis of patients due to screening limits their clinical utility. Identifying genetic variants associated with lethal prostate cancer could inform clinical decision making.Methods: We conducted a genome-wide association study, comparing lethal prostate cancer cases to cases surviving at least 10 years beyond their initial diagnosis. Genotyping was done with the Affymetrix 5.0 chip [∼500,000 single nucleotide polymorphisms (SNP) and 1,483 copy number variants (CNV)] on DNA from participants in the Physicians' Health Study and Health Professionals Follow-up Study (196 lethal cases, 368 long-term survivors). After excluding SNPs and individuals based on quality control criteria, logistic regression assuming an additive model was done using the PLINK software.Results: No SNP reached genome-wide significance (P ≤ 1 × 10−7); however, three independent SNPs had P < 1 × 10−5. One top-ranked SNP replicated (P = 0.05) in an independent follow-up study. Although no CNV had genome-wide significance, 14 CNVs showed nominal association with prostate cancer mortality (P < 0.05).Conclusions: No variants were significantly associated at a genome-wide level with prostate cancer mortality. Common genetic determinants of lethal prostate cancer are likely to have odds ratios Impact: Genetic markers identified could provide biological insight to improve therapy for men with potentially fatal cancer. Larger studies are necessary to detect the genetic causes of prostate cancer mortality. Cancer Epidemiol Biomarkers Prev; 19(11); 2869–76. ©2010 AACR.

Published
2023

44. Supplementary Tables and Figures from Genome-wide Association Study of Prostate Cancer Mortality

Author

Matthew L. Freedman, David J. Hunter, Meir J. Stampfer, Edward L. Giovannucci, Philip W. Kantoff, Tobias Kurth, William K. Oh, Jing Ma, Peter L. Kraft, Lorelei A. Mucci, Jennifer A. Sinnott, Fredrick R. Schumacher, Saumyadipta Pyne, and Kathryn L. Penney

Abstract

Supplementary Tables and Figures from Genome-wide Association Study of Prostate Cancer Mortality

Published
2023

46. Supplementary Data from Evaluation of 8q24 and 17q Risk Loci and Prostate Cancer Mortality

Author

Matthew L. Freedman, Meir J. Stampfer, David J. Hunter, Philip W. Kantoff, Janet L. Stanford, Lorelei Mucci, Jing Ma, Tobias Kurth, Elaine A. Ostrander, Oliver Sartor, William K. Oh, Gwo-Shu Lee, Christine A. Beckwith, Fredrick R. Schumacher, Mark Pomerantz, Claudia A. Salinas, and Kathryn L. Penney

Abstract

Supplementary Data from Evaluation of 8q24 and 17q Risk Loci and Prostate Cancer Mortality

Published
2023

47. Data from Application of Oligonucleotide Microarrays to Assess the Biological Effects of Neoadjuvant Imatinib Mesylate Treatment for Localized Prostate Cancer

Author

Daniel George, Todd Golub, William K. Oh, Philip W. Kantoff, Massimo Loda, Mark A. Rubin, Aaron Thorner, and Phillip G. Febbo

Abstract

Purpose: Neoadjuvant administration of antineoplastic therapies is used to rapidly assess the clinical and biological activity of novel systemic treatments. To assess the feasibility of using microarrays to assess molecular end points following targeted treatment in a heterogeneous tumor, we measured global gene expression in localized prostate cancer before and following neoadjuvant treatment with imatinib mesylate.Patients and Methods: Patients with intermediate-risk to high-risk prostate cancer were treated for 6 weeks with 200 to 300 mg of oral imatinib mesylate. Frozen tissue was obtained from pretreatment ultrasound-guided biopsies and posttreatment radical prostatectomy specimens. Oligonucleotide microarray analysis following laser capture microdissection (LCM) and RNA amplification was used to assess gene expression changes associated with imatinib mesylate therapy. Immunohistochemistry was used to measure protein expression of MKP1 and CD31 and to assess cellular apoptosis.Results: Of the 11 patients enrolled, high-quality microarray data was obtained from both biopsies (n = 7) and radical prostatectomy specimens (n = 9). Technically introduced intrasample gene expression variability was found to be significantly less than intertumor biological variability. Large gene expression differences were observed, and the gene with the most consistent differential expression (MKP1) was validated by immunohistochemistry. Gene set enrichment analysis suggests that imatinib mesylate therapy results in apoptosis of microvascular endothelial cells, an observation anecdotally supported by immunohistochemistry.Conclusions: This study shows that high-quality microarray data can be generated using LCM and RNA amplification to discover potential mechanisms of targeted therapy in cancer.

Published
2023

48. Data from Blood mRNA Expression Profiling Predicts Survival in Patients Treated with Tremelimumab

Author

Philip Friedlander, William K. Oh, John Kirkwood, David Fisher, Karl Wassmann, Yichun Fu, Sara Harcharik, Ellen de Moll, Bobby Liaw, Jay Magidson, and Yvonne Saenger

Abstract

Purpose: Tremelimumab (ticilimumab, Pfizer), is a monoclonal antibody (mAb) targeting cytotoxic T lymphocyte–associated antigen-4 (CTLA-4). Ipilimumab (Yervoy, BMS), another anti-CTLA-4 antibody, is approved by the U.S. Federal Drug Administration (FDA). Biomarkers are needed to identify the subset of patients who will achieve tumor control with CTLA-4 blockade.Experimental Design: Pretreatment peripheral blood samples from 218 patients with melanoma who were refractory to prior therapy and receiving tremelimumab in a multicenter phase II study were measured for 169 mRNA transcripts using reverse transcription polymerase chain reaction (RT-PCR). A two-class latent model yielded a risk score based on four genes that were highly predictive of survival (P < 0.001). This signature was validated in an independent population of 260 treatment-naïve patients with melanoma enrolled in a multicenter phase III study of tremelimumab.Results: Median follow-up was 297 days for the training population and 386 days for the test population. Expression levels of the 169 genes were closely correlated across the two populations (r = 0.9939). A four-gene model, including cathepsin D (CTSD), phopholipase A2 group VII (PLA2G7), thioredoxin reductase 1 (TXNRD1), and interleukin 1 receptor–associated kinase 3 (IRAK3), predicted survival in the test population (P = 0.001 by log-rank test). This four-gene model added to the predictive value of clinical predictors (P < 0.0001).Conclusions: Expression levels of CTSD, PLA2G7, TXNRD1, and IRAK3 in peripheral blood are predictive of survival in patients with melanoma treated with tremelimumab. Blood mRNA signatures should be further explored to define patient subsets likely to benefit from immunotherapy. Clin Cancer Res; 20(12); 3310–8. ©2014 AACR.

Published
2023

49. Supplementary Materials and Methods from Small-Molecule Activators of Protein Phosphatase 2A for the Treatment of Castration-Resistant Prostate Cancer

Author

Matthew D. Galsky, Goutham Narla, Michael Ohlmeyer, Yiannis Ioannou, Analisa DiFeo, Rosalie Sears, John P. Sfakianos, Alexander Kirschenbaum, Alice C. Levine, William K. Oh, Cynthia C.T. Sprenger, Stephen R. Plymate, David L. Brautigan, Yixuan Gong, Nilesh Zaware, Daniel McQuaid, Divya Hoon, Shen Yao, Agnes Stachnik, Janna Kiselar, Maxwell Cooper, Daniela Schlatzer, David B. Kastrinsky, Jaya Sangodkar, Abbey Perl, Danica Wiredja, Sudeh Izadmehr, David Callejas, Rita A. Avelar, and Kimberly McClinch

Abstract

Antibody information and primer sequences.

Published
2023

50. Data from Myeloid Cell–associated Resistance to PD-1/PD-L1 Blockade in Urothelial Cancer Revealed Through Bulk and Single-cell RNA Sequencing

Author

Matthew D. Galsky, Jun Zhu, Nina Bhardwaj, Padmanee Sharma, Eric Schadt, Xin Yao, Keziban Unsal-Kacmaz, Megan Wind-Rotolo, Peter M. Szabo, William K. Oh, Peter Wiklund, Sudeh Izadmehr, Austin Hake, Sacha Gnjatic, Adam M. Farkas, Robert P. Sebra, Amir Horowitz, Guray Akturk, Kristin G. Beaumont, John P. Sfakianos, and Li Wang

Abstract

Purpose:To define dominant molecular and cellular features associated with PD-1/PD-L1 blockade resistance in metastatic urothelial cancer.Experimental Design:We pursued an unbiased approach using bulk RNA sequencing data from two clinical trials to discover (IMvigor 210) and validate (CheckMate 275) pretreatment molecular features associated with resistance to PD-1/PD-L1 blockade in metastatic urothelial cancer. We then generated single-cell RNA sequencing (scRNA-seq) data from muscle-invasive bladder cancer specimens to dissect the cellular composition underlying the identified gene signatures.Results:We identified an adaptive immune response gene signature associated with response and a protumorigenic inflammation gene signature associated with resistance to PD-1/PD-L1 blockade. The adaptive immune response:protumorigenic inflammation signature expression ratio, coined the 2IR score, best correlated with clinical outcomes, and was externally validated. Mapping these bulk gene signatures onto scRNA-seq data uncovered their underlying cellular diversity, with prominent expression of the protumorigenic inflammation signature by myeloid phagocytic cells. However, heterogeneity in expression of adaptive immune and protumorigenic inflammation genes was observed among single myeloid phagocytic cells, quantified as the myeloid single cell immune:protumorigenic inflammation ratio (Msc2IR) score. Single myeloid phagocytic cells with low Msc2IR scores demonstrated upregulation of proinflammatory cytokines/chemokines and downregulation of antigen presentation genes, were unrelated to M1 versus M2 polarization, and were enriched in pretreatment blood samples from patients with PD-L1 blockade–resistant metastatic urothelial cancer.Conclusions:The balance of adaptive immunity and protumorigenic inflammation in individual tumor microenvironments is associated with PD-1/PD-L1 resistance in urothelial cancer with the latter linked to a proinflammatory cellular state of myeloid phagocytic cells detectable in tumor and blood.See related commentary by Drake, p. 4139

Published
2023

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