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1. Treatment of patients hospitalized for COVID-19 with remdesivir is associated with lower likelihood of 30-day readmission: a retrospective observational study.

Author

Mozaffari, Essy, Chandak, Aastha, Gottlieb, Robert, Chima-Melton, Chidinma, Kalil, Andre, Sarda, Vishnudas, Der-Torossian, Celine, Oppelt, Thomas, Berry, Mark, and Amin, Alpesh

Subjects
COVID-19, post-discharge outcomes, readmission, remdesivir, Adult, Humans, COVID-19, Patient Readmission, COVID-19 Drug Treatment, Hospitalization, Retrospective Studies, Adenosine Monophosphate, Alanine
Abstract

Aim: This observational study investigated the association between remdesivir treatment during hospitalization for COVID-19 and 30-day COVID-19-related and all-cause readmission across different variants time periods. Patients & methods: Hospitalization records for adult patients discharged from a COVID-19 hospitalization between 1 May 2020 to 30 April 2022 were extracted from the US PINC AI Healthcare Database. Likelihood of 30-day readmission was compared among remdesivir-treated and nonremdesivir-treated patients using multivariable logistic regression models adjusted for age, corticosteroid treatment, Charlson comorbidity index and intensive care unit stay during the COVID-19 hospitalization. Analyses were stratified by maximum supplemental oxygen requirement and variant time period (pre-Delta, Delta and Omicron). Results: Of the 440,601 patients discharged alive after a COVID-19 hospitalization, 248,785 (56.5%) patients received remdesivir. Overall, remdesivir patients had a 30-day COVID-19-related readmission rate of 3.0% and all-cause readmission rate of 6.3% compared with 5.4% and 9.1%, respectively, for patients who did not receive remdesivir during their COVID-19 hospitalization. After adjusting for demographics and clinical characteristics, remdesivir treatment was associated with significantly lower odds of 30-day COVID-19-related readmission (odds ratio 0.60 [95% confidence interval: 0.58-0.62]), and all-cause readmission (0.73 [0.72-0.75]). Significantly lower odds of 30-day readmission in remdesivir-treated patients was observed across all variant time periods. Conclusion: Treating patients hospitalized for COVID-19 with remdesivir is associated with a statistically significant reduction in 30-day COVID-19-related and all-cause readmission across variant time periods. These findings indicate that the clinical benefit of remdesivir may extend beyond the COVID-19 hospitalization.

Published
2024

2. Remdesivir Reduced Mortality in Immunocompromised Patients Hospitalized for COVID-19 Across Variant Waves: Findings From Routine Clinical Practice.

Author

Mozaffari, Essy, Chandak, Aastha, Gottlieb, Robert, Read, Stephanie, Jiang, Heng, Chiang, Mel, Lee, EunYoung, Gupta, Rikisha, Berry, Mark, Kalil, Andre, and Chima-Melton, Chidinma

Subjects
COVID-19, comparative effectiveness research, immunocompromised, mortality, remdesivir, Humans, COVID-19, COVID-19 Drug Treatment, Immunocompromised Host, Inpatients, Antiviral Agents
Abstract

BACKGROUND: Immunocompromised patients are at high risk of severe coronavirus disease 2019 (COVID-19) and death, yet treatment strategies for immunocompromised patients hospitalized for COVID-19 reflect variations in clinical practice. In this comparative effectiveness study, we investigated the effect of remdesivir treatment on inpatient mortality among immunocompromised patients hospitalized for COVID-19 across all variants of concern (VOC) periods. METHODS: Data for immunocompromised patients hospitalized for COVID-19 between December 2020 and April 2022 were extracted from the US PINC AITM Healthcare Database. Patients who received remdesivir within 2 days of hospitalization were matched 1:1 using propensity score matching to patients who did not receive remdesivir. Additional matching criteria included admission month, age group, and hospital. Cox proportional hazards models were used to examine the effect of remdesivir on risk of 14- and 28-day mortality during VOC periods. RESULTS: A total of 19 184 remdesivir patients were matched to 11 213 non-remdesivir patients. Overall, 11.1% and 17.7% of remdesivir patients died within 14 and 28 days, respectively, compared with 15.4% and 22.4% of non-remdesivir patients. Remdesivir was associated with a reduction in mortality at 14 (hazard ratio [HR], 0.70; 95% confidence interval, .62-.78) and 28 days (HR, 0.75; 95% CI, .68-.83). The survival benefit remained significant during the pre-Delta, Delta, and Omicron periods. CONCLUSIONS: Prompt initiation of remdesivir in immunocompromised patients hospitalized for COVID-19 is associated with significant survival benefit across all variant waves. These findings provide much-needed evidence relating to the effectiveness of a foundational treatment for hospitalized COVID-19 patients among a high-risk population.

Published
2023

4. Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users

Author

Diehl, Peter Udo, Zilly, Hannes, Sattler, Felix, Singer, Yosef, Kepp, Kevin, Berry, Mark, Hasemann, Henning, Zippel, Marlene, Kaya, Müge, Meyer-Rachner, Paul, Pudszuhn, Annett, Hofmann, Veit M., Vormann, Matthias, and Sprengel, Elias

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

The hearing loss of almost half a billion people is commonly treated with hearing aids. However, current hearing aids often do not work well in real-world noisy environments. We present a deep learning based denoising system that runs in real time on iPhone 7 and Samsung Galaxy S10 (25ms algorithmic latency). The denoised audio is streamed to the hearing aid, resulting in a total delay of around 75ms. In tests with hearing aid users having moderate to severe hearing loss, our denoising system improves audio across three tests: 1) listening for subjective audio ratings, 2) listening for objective speech intelligibility, and 3) live conversations in a noisy environment for subjective ratings. Subjective ratings increase by more than 40%, for both the listening test and the live conversation compared to a fitted hearing aid as a baseline. Speech reception thresholds, measuring speech understanding in noise, improve by 1.6 dB SRT. Ours is the first denoising system that is implemented on a mobile device, streamed directly to users' hearing aids using only a single channel as audio input while improving user satisfaction on all tested aspects, including speech intelligibility. This includes overall preference of the denoised and streamed signal over the hearing aid, thereby accepting the higher latency for the significant improvement in speech understanding.

Published
2023

5. Remdesivir Is Associated With Reduced Mortality in COVID-19 Patients Requiring Supplemental Oxygen Including Invasive Mechanical Ventilation Across SARS-CoV-2 Variants.

Author

Mozaffari, Essy, Chandak, Aastha, Gottlieb, Robert, Chima-Melton, Chidinma, Read, Stephanie, Lee, EunYoung, Der-Torossian, Celine, Gupta, Rikisha, Berry, Mark, Hollemeersch, Stijn, and Kalil, Andre

Subjects
COVID-19, comparative effectiveness research, hospitalization, mortality, remdesivir
Abstract

BACKGROUND: This comparative effectiveness study investigated the effect of remdesivir on in-hospital mortality among patients hospitalized for coronavirus disease 2019 (COVID-19) requiring supplemental oxygen including low-flow oxygen (LFO), high-flow oxygen/noninvasive ventilation (HFO/NIV), or invasive mechanical ventilation/extracorporeal membrane oxygenation (IMV/ECMO) across variant of concern (VOC) periods. METHODS: Patients hospitalized for COVID-19 between December 2020 and April 2022 and administered remdesivir upon admission were 1:1 propensity score matched to patients not administered remdesivir during their COVID-19 hospitalization. Analyses were stratified by supplemental oxygen requirement upon admission and VOC period. Cox proportional hazards models were used to derive adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) for 14- and 28-day mortality. RESULTS: Patients treated with remdesivir (67 582 LFO, 34 857 HFO/NIV, and 4164 IMV/ECMO) were matched to non-remdesivir patients. Unadjusted mortality rates were significantly lower for remdesivir-treated patients at 14 days (LFO: 6.4% vs. 8.8%; HFO/NIV: 16.8% vs. 19.4%; IMV/ECMO: 27.8% vs. 35.3%) and 28 days (LFO: 9.8% vs. 12.3%; HFO/NIV: 25.8% vs. 28.3%; IMV/ECMO: 41.4% vs. 50.6%). After adjustment, remdesivir treatment was associated with a statistically significant reduction in in-hospital mortality at 14 days (LFO: aHR, 0.72; 95% CI, 0.66-0.79; HFO/NIV: aHR, 0.83; 95% CI, 0.77-0.89; IMV/ECMO: aHR, 0.73; 95% CI, 0.65-0.82) and 28 days (LFO: aHR, 0.79; 95% CI, 0.73-0.85; HFO/NIV: aHR, 0.88; 95% CI, 0.82-0.93; IMV/ECMO: aHR, 0.74; 95% CI, 0.67-0.82) compared with non-remdesivir treatment. Lower risk of mortality among remdesivir-treated patients was observed across VOC periods. CONCLUSIONS: Remdesivir treatment is associated with significantly reduced mortality among patients hospitalized for COVID-19 requiring supplemental oxygen upon admission, including those requiring HFO/NIV or IMV/ECMO with severe or critical disease, across VOC periods.

Published
2023

9. Restoring speech intelligibility for hearing aid users with deep learning

Author

Diehl, Peter Udo, Singer, Yosef, Zilly, Hannes, Schönfeld, Uwe, Meyer-Rachner, Paul, Berry, Mark, Sprekeler, Henning, Sprengel, Elias, Pudszuhn, Annett, and Hofmann, Veit M.

Subjects
Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, Quantitative Biology - Neurons and Cognition
Abstract

Almost half a billion people world-wide suffer from disabling hearing loss. While hearing aids can partially compensate for this, a large proportion of users struggle to understand speech in situations with background noise. Here, we present a deep learning-based algorithm that selectively suppresses noise while maintaining speech signals. The algorithm restores speech intelligibility for hearing aid users to the level of control subjects with normal hearing. It consists of a deep network that is trained on a large custom database of noisy speech signals and is further optimized by a neural architecture search, using a novel deep learning-based metric for speech intelligibility. The network achieves state-of-the-art denoising on a range of human-graded assessments, generalizes across different noise categories and - in contrast to classic beamforming approaches - operates on a single microphone. The system runs in real time on a laptop, suggesting that large-scale deployment on hearing aid chips could be achieved within a few years. Deep learning-based denoising therefore holds the potential to improve the quality of life of millions of hearing impaired people soon.

Published
2022

25. KEAP1/NFE2L2 Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition

Author

Binkley, Michael S, Jeon, Young-Jun, Nesselbush, Monica, Moding, Everett J, Nabet, Barzin Y, Almanza, Diego, Kunder, Christian, Stehr, Henning, Yoo, Christopher H, Rhee, Siyeon, Xiang, Michael, Chabon, Jacob J, Hamilton, Emily, Kurtz, David M, Gojenola, Linda, Owen, Susie Grant, Ko, Ryan B, Shin, June Ho, Maxim, Peter G, Lui, Natalie S, Backhus, Leah M, Berry, Mark F, Shrager, Joseph B, Ramchandran, Kavitha J, Padda, Sukhmani K, Das, Millie, Neal, Joel W, Wakelee, Heather A, Alizadeh, Ash A, Loo, Billy W, and Diehn, Maximilian

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Lung, Cancer, Clinical Research, Lung Cancer, Biomarkers, Glutaminase, Humans, Kelch-Like ECH-Associated Protein 1, Lung Neoplasms, Mutation, NF-E2-Related Factor 2, Radiation Tolerance, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with KEAP1/NFE2L2 mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1-mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in KEAP1 and NFE2L2 predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of KEAP1/NFE2L2-mutant tumors.This article is highlighted in the In This Issue feature, p. 1775.

Published
2020

28. Organised crime in Red City : an ethnographic study of drugs, vice and violence

Author

Berry, Mark

Subjects
364.1, H Social Sciences (General)
Abstract

Illegal drug trafficking and retail drug sales constitute the most common activity of organised crime groups in the UK and draw the largest share of resources from the police and prison services, whilst also generating considerable social costs. There are few contemporary studies in the UK on the supply of drugs, its organisation, culture and risk management practices, and even fewer on active dealers themselves. There remains limited ethnographic research into the drug trade, missing important insights that can be gained from observing distributors in a natural setting. A key absence in criminological literature is the voice of offenders who commit serious crimes and how they perceive and mitigate problems related to their activities. This research aims to fill gaps in the knowledge base by investigating the nature of the drug market, the crime risk management practices of drug dealers, and possible reasons for their involvement and patterns of activity. The study examines the criminal careers of offenders who operate in one of Britain’s largest cities, termed here anonymously as Red City. The participants in this study distribute and manufacture a range of illicit substances, both offline and online. They distribute drugs on local, national and international levels (retail, wholesale, import and export). To complement the fieldwork, interviews were conducted with official actors from the criminal justice system, the private sector and the third sector. The thesis seeks to provide a more nuanced and grounded picture of illicit drug dealing and ‘organised crime’, that provides an account that corrects popular stereotypes. The chapters proceed as follows: Outline of the thesis: Chapter one provides the introduction to the thesis. It identifies the research problem, sets the contexts of the study and explains how the thesis contributes to the field. Chapter two outlines the theoretical framework for the thesis; it combines life course criminology with perspectives taken from research on organised crime. It examines organised crime in terms of markets, networks, and organisations. Chapter three describes the methodological approach employed in this study and considers the ethical and practical challenges of researching illegal activity. Chapter four addresses the ‘start’ of the criminal career when actors first become drug dealers. It follows the lives of the ‘lads’, who make up a core of the participants in the study. Chapter five examines how drug dealing is conducted in the city streets. It draws upon ethnographic data from two parallel drug markets that sit at opposite ends of the spectrum in terms of their harms and ‘legitimacy’. Chapter six provides a sociohistorical analysis of organised crime in the nightclub scene to the present day. It draws upon insights from bouncers and drug dealers working in the field. Chapter seven addresses the effects of emergent technology in the drug trade. It examines how offenders employ digital technologies, both offline and online. Chapter eight addresses the desistance phase in the life-course. It discusses the factors that facilitate and inhibit desistance for individuals and groups of offenders. Chapter nine outlines and evaluates the key findings in the thesis. It makes policy recommendations to mitigate problems related to drugs and organised crime in the future. Throughout all chapters of the analysis, comparisons are made between offenders working in different drug markets and settings, to assess the relationship between their activities and the characteristics of the marketplace in question. The study finds that drug markets that are closest to ‘legitimacy’, in terms of their legal status and the public perception of the drugs, can have less risks for distributors. In light of this, they may be sold more openly and accrue lower levels of exploitation in the trade. Overall, this thesis demonstrates how serious offenders operate in rapidly evolving criminal markets, providing a significant contribution to the knowledge base.

Published
2020

31. Greater ipsilateral rectus muscle atrophy after robotic thoracic surgery compared to open and Video-assisted thoracoscopic surgery approaches

Author

Wang, Yoyo, primary, Randle, Ryan J., additional, Bhandari, Prasha, additional, He, Hao, additional, Trope, Winston L., additional, Guenthart, Brandon A., additional, Guo, Haiwei H., additional, Liou, Douglas Z., additional, Backhus, Leah M., additional, Berry, Mark F., additional, Shrager, Joseph B., additional, and Lui, Natalie S., additional

Published
2024
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35. Population-Based Analysis of Local Therapies for Large (>7 cm) Non-Small Cell Lung Cancer Tumors.

Author

Patel, Deven C., Hao He, Liou, Douglas Z., Speicher, Paul J., and Berry, Mark F.

Subjects
PUBLIC health surveillance, PEARSON correlation (Statistics), SECONDARY analysis, T-test (Statistics), LOGISTIC regression analysis, FISHER exact test, RETROSPECTIVE studies, DESCRIPTIVE statistics, MULTIVARIATE analysis, KAPLAN-Meier estimator, STATISTICS, LUNG cancer, SURVIVAL analysis (Biometry), DATA analysis software, PROPORTIONAL hazards models
Abstract

OBJECTIVE: This study evaluated the impact of local treatment modalities in the management of large non-small cell lung cancer (NSCLC) tumors using a nationwide population-based dataset. MATERIAL AND METHODS: Patients with NSCLC tumors >7 cm that were cN0-1M0 in the Surveillance, Epidemiology, and End Results (SEER) registry from 2010 to 2015 were stratified by local management strategy (surgery, radiation therapy, no local treatment) and evaluated using Kaplan–Meier survival analyses, Cox proportional-hazard methods, and propensity-matched analysis. RESULTS: A total of 3156 patients were identified, of which 1580 (50.1%) underwent surgical resection, 920 (29.2%) received radiation only, 655 (20.7%) received no local treatment. Overall, the 5-year survival of patients undergoing surgical resection was 40.7%, compared to 14.7% and 5.3% for the radiation only and no local treatment groups, respectively (P < .001). Surgery with or without radiation continued to have an independent association with improved survival in multivariable analysis (HR 0.23, P < .0001). Other factors associated with improved survival included younger age, negative nodal disease, and chemotherapy use. In propensity-matched sub-analyses, 5-year survival remained significantly better after surgery alone compared to radiation alone (38.5% vs. 13.6%, P < .001), while survival after radiation alone was better than no local treatment, though both were largely poor (12.4% vs. 7.5%, P < .001). CONCLUSIONS: Survival of patients with large NSCLC managed non-surgically is very poor. Despite the significant long-term survival benefit with surgical intervention, nearly half of the study cohort did not undergo surgery. Patients and clinicians can use these results to estimate specific potential benefits when considering possible treatment strategies for large NSCLC tumors. [ABSTRACT FROM AUTHOR]

Published
2024
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39. Progression of Tricuspid Regurgitation After Surgery for Ischemic Mitral Regurgitation

Author

Miller, Marissa A., Taddei-Peters, Wendy C., Buxton, Dennis, Caulder, Ron, Geller, Nancy L., Gordon, David, Jeffries, Neal O., Lee, Albert, Moy, Claudia S., Gombos, Ilana Kogan, Ralph, Jennifer, Weisel, Richard D., Gardner, Timothy J., O’Gara, Patrick T., Rose, Eric A., Gelijns, Annetine C., Parides, Michael K., Ascheim, Deborah D., Moskowitz, Alan J., Bagiella, Emilia, Moquete, Ellen, Chang, Helena, Chase, Melissa, Foo, James, Chen, Yingchun, Goldfarb, Seth, Gupta, Lopa, Kirkwood, Katherine, Dobrev, Edlira, Levitan, Ron, O’Sullivan, Karen, Overbey, Jessica, Santos, Milerva, Williams, Deborah, Weglinski, Michael, Williams, Paula, Wood, Carrie, Ye, Xia, Nielsen, Sten Lyager, Wiggers, Henrik, Malgaard, Henning, Mack, Michael, Adame, Tracine, Settele, Natalie, Adams, Jenny, Ryan, William, Smith, Robert L., Grayburn, Paul, Chen, Frederick Y., Nohria, Anju, Cohn, Lawrence, Shekar, Prem, Aranki, Sary, Couper, Gregory, Davidson, Michael, Bolman, R. Morton, III, Burgess, Anne, Conboy, Debra, Lawrence, Rita, Noiseux, Nicolas, Stevens, Louis-Mathieu, Prieto, Ignacio, Basile, Fadi, Dionne, Joannie, Fecteau, Julie, Blackstone, Eugene H., Gillinov, A. Marc, Lackner, Pamela, Berroteran, Leoma, Dolney, Diana, Fleming, Suzanne, Palumbo, Roberta, Whitman, Christine, Sankovic, Kathy, Sweeney, Denise Kosty, Geither, Carrie, Doud, Kristen, Pattakos, Gregory, Clarke, Pamela A., Argenziano, Michael, Williams, Mathew, Goldsmith, Lyn, Smith, Craig R., Naka, Yoshifumi, Stewart, Allan, Schwartz, Allan, Bell, Daniel, Van Patten, Danielle, Sreekanth, Sowmya, Smith, Peter K., Alexander, John H., Milano, Carmelo A., Glower, Donald D., Mathew, Joseph P., Harrison, J. Kevin, Welsh, Stacey, Berry, Mark F., Parsa, Cyrus J., Tong, Betty C., Williams, Judson B., Ferguson, T. Bruce, Kypson, Alan P., Rodriguez, Evelio, Harris, Malissa, Akers, Brenda, O'Neal, Allison, Puskas, John D., Thourani, Vinod H., Guyton, Robert, Baer, Jefferson, Baio, Kim, Neill, Alexis A., Voisine, Pierre, Senechal, Mario, Dagenais, François, O’Connor, Kim, Dussault, Gladys, Ballivian, Tatiana, Keilani, Suzanne, Speir, Alan M., Magee, Patrick, Ad, Niv, Keyte, Sally, Dang, Minh, Slaughter, Mark, Headlee, Marsha, Moody, Heather, Solankhi, Naresh, Birks, Emma, Groh, Mark A., Shell, Leslie E., Shepard, Stephanie A., Trichon, Benjamin H., Nanney, Tracy, Hampton, Lynne C., Mangusan, Ralph, Michler, Robert E., D'Alessandro, David A., DeRose, Joseph J., Jr., Goldstein, Daniel J., Bello, Ricardo, Jakobleff, William, Garcia, Mario, Taub, Cynthia, Spevak, Daniel, Swayze, Roger, Sookraj, Nadia, Perrault, Louis P., Basmadjian, Arsène-Joseph, Bouchard, Denis, Carrier, Michel, Cartier, Raymond, Pellerin, Michel, Tanguay, Jean François, El-Hamamsy, Ismail, Denault, André, Demers, Philippe, Jonathan Lacharité, Sophie Robichaud, Horvath, Keith A., Corcoran, Philip C., Siegenthaler, Michael P., Murphy, Mandy, Iraola, Margaret, Greenberg, Ann, Sai-Sudhakar, Chittoor, Hasan, Ayseha, McDavid, Asia, Kinn, Bradley, Pagé, Pierre, Sirois, Carole, Latter, David, Leong-Poi, Howard, Bonneau, Daniel, Errett, Lee, Peterson, Mark D., Verma, Subodh, Feder-Elituv, Randi, Cohen, Gideon, Joyner, Campbell, Fremes, Stephen E., Moussa, Fuad, Christakis, George, Karkhanis, Reena, Yau, Terry, Farkouh, Michael, Woo, Anna, Cusimano, Robert James, David, Tirone, Feindel, Christopher, Garrard, Lisa, Fredericks, Suzanne, Mociornita, Amelia, Mullen, John C., Choy, Jonathan, Meyer, Steven, Kuurstra, Emily, Gammie, James S., Young, Cindi A., Beach, Dana, Villanueva, Robert, Acker, Michael A., Atluri, Pavan, Woo, Y. Joseph, Mayer, Mary Lou, Bowdish, Michael, Starnes, Vaughn A., Shavalle, David, Matthews, Ray, Javadifar, Shadi, Romar, Linda, Kron, Irving L., Ailawadi, Gorav, Johnston, Karen, Dent, John M., Kern, John, Keim, Jessica, Burks, Sandra, Gahring, Kim, Bull, David A., Desvigne-Nickens, Patrice, Dixon, Dennis O., Haigney, Mark, Holubkov, Richard, Jacobs, Alice, Miller, Frank, Murkin, John M., Spertus, John, Wechsler, Andrew S., Sellke, Frank, McDonald, Cheryl L., Byington, Robert, Dickert, Neal, Ikonomidis, John S., Williams, David O., Yancy, Clyde W., Fang, James C., Giannetti, Nadia, Richenbacher, Wayne, Rao, Vivek, Furie, Karen L., Miller, Rachel, Pinney, Sean, Roberts, William C., Walsh, Mary N., Hung, Judy, Zeng, Xin, Kilcullen, Niamh, Hung, David, Keteyian, Stephen J., Brawner, Clinton A., Aldred, Heather, Browndyke, Jeffrey, Toulgoat-Dubois, Yanne, Bertrand, Philippe B., Overbey, Jessica R., Levine, Robert A., Mack, Michael J., Giustino, Gennaro, and Bowdish, Michael E.

Published
2021
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40. Cost-effectiveness of coronary artery bypass grafting plus mitral valve repair versus coronary artery bypass grafting alone for moderate ischemic mitral regurgitation

Author

Miller, Marissa A., Taddei-Peters, Wendy C., Buxton, Dennis, Caulder, Ron, Geller, Nancy L., Gordon, David, Jeffries, Neal O., Lee, Albert, Moy, Claudia S., Gombos, Ilana Kogan, Ralph, Jennifer, Weisel, Richard, Gardner, Timothy J., O'Gara, Patrick T., Rose, Eric A., Gelijns, Annetine C., Parides, Michael K., Ascheim, Deborah D., Moskowitz, Alan J., Bagiella, Emilia, Moquete, Ellen, Chang, Helena, Chase, Melissa, Chen, Yingchun, Goldfarb, Seth, Gupta, Lopa, Kirkwood, Katherine, Dobrev, Edlira, Levitan, Ron, O'Sullivan, Karen, Overbey, Jessica, Santos, Milerva, Weglinski, Michael, Williams, Paula, Wood, Carrie, Ye, Xia, Nielsen, Sten Lyager, Wiggers, Henrik, Malgaard, Henning, Mack, Michael, Adame, Tracine, Settele, Natalie, Adams, Jenny, Ryan, William, Smith, Robert L., Grayburn, Paul, Chen, Frederick Y., Nohria, Anju, Cohn, Lawrence, Shekar, Prem, Aranki, Sary, Couper, Gregory, Davidson, Michael, Bolman, R. Morton, III, Burgess, Anne, Conboy, Debra, Noiseux, Nicolas, Stevens, Louis-Mathieu, Prieto, Ignacio, Basile, Fadi, Dionne, Joannie, Fecteau, Julie, Blackstone, Eugene H., Gillinov, A. Marc, Lackner, Pamela, Berroteran, Leoma, Dolney, Diana, Fleming, Suzanne, Palumbo, Roberta, Whitman, Christine, Sankovic, Kathy, Sweeney, Denise Kosty, Pattakos, Gregory, Clarke, Pamela A., Argenziano, Michael, Williams, Mathew, Goldsmith, Lyn, Smith, Craig R., Naka, Yoshifumi, Stewart, Allan, Schwartz, Allan, Bell, Daniel, Van Patten, Danielle, Sreekanth, Sowmya, Smith, Peter K., Alexander, John H., Milano, Carmelo A., Glower, Donald D., Mathew, Joseph P., Harrison, J. Kevin, Welsh, Stacey, Berry, Mark F., Parsa, Cyrus J., Tong, Betty C., Williams, Judson B., Ferguson, T. Bruce, Kypson, Alan P., Rodriguez, Evelio, Harris, Malissa, Akers, Brenda, O'Neal, Allison, Puskas, John D., Thourani, Vinod H., Guyton, Robert, Baer, Jefferson, Baio, Kim, Neill, Alexis A., Voisine, Pierre, Senechal, Mario, Dagenais, François, O'Connor, Kim, Dussault, Gladys, Ballivian, Tatiana, Keilani, Suzanne, Speir, Alan M., Magee, Patrick, Ad, Niv, Keyte, Sally, Dang, Minh, Slaughter, Mark, Headlee, Marsha, Moody, Heather, Solankhi, Naresh, Birks, Emma, Groh, Mark A., Shell, Leslie E., Shepard, Stephanie A., Trichon, Benjamin H., Nanney, Tracy, Hampton, Lynne C., Michler, Robert E., D'Alessandro, David A., DeRose, Joseph J., Jr., Goldstein, Daniel J., Bello, Ricardo, Jakobleff, William, Garcia, Mario, Taub, Cynthia, Spevak, Daniel, Swayze, Roger, Perrault, Louis P., Basmadjian, Arsène-Joseph, Bouchard, Denis, Carrier, Michel, Cartier, Raymond, Pellerin, Michel, Tanguay, Jean François, El-Hamamsy, Ismail, Denault, André, Demers, Philippe, Robichaud, Sophie, Horvath, Keith A., Corcoran, Philip C., Siegenthaler, Michael P., Murphy, Mandy, Iraola, Margaret, Greenberg, Ann, Sai-Sudhakar, Chittoor, Hasan, Ayseha, McDavid, Asia, Kinn, Bradley, Pagé, Pierre, Sirois, Carole, Latter, David, Leong-Poi, Howard, Bonneau, Daniel, Errett, Lee, Peterson, Mark D., Verma, Subodh, Feder-Elituv, Randi, Cohen, Gideon, Joyner, Campbell, Fremes, Stephen E., Moussa, Fuad, Christakis, George, Karkhanis, Reena, Yau, Terry, Farkouh, Michael, Woo, Anna, Cusimano, Robert James, David, Tirone, Feindel, Christopher, Garrard, Lisa, Fredericks, Suzanne, Mociornita, Amelia, Mullen, John C., Choy, Jonathan, Meyer, Steven, Kuurstra, Emily, Gammie, James S., Young, Cindi A., Beach, Dana, Acker, Michael A., Atluri, Pavan, Woo, Y. Joseph, Mayer, Mary Lou, Bowdish, Michael, Starnes, Vaughn A., Shavalle, David, Matthews, Ray, Javadifar, Shadi, Romar, Linda, Kron, Irving L., Ailawadi, Gorav, Johnston, Karen, Dent, John M., Kern, John, Keim, Jessica, Burks, Sandra, Gahring, Kim, Bull, David A., Desvigne-Nickens, Patrice, Dixon, Dennis O., Haigney, Mark, Holubkov, Richard, Jacobs, Alice, Miller, Frank, Murkin, John M., Spertus, John, Wechsler, Andrew S., Sellke, Frank, McDonald, Cheryl L., Byington, Robert, Dickert, Neal, Ikonomidis, John S., Williams, David O., Yancy, Clyde W., Fang, James C., Giannetti, Nadia, Richenbacher, Wayne, Rao, Vivek, Furie, Karen L., Miller, Rachel, Pinney, Sean, Roberts, William C., Walsh, Mary N., Keteyian, Stephen J., Brawner, Clinton A., Aldred, Heather, Hung, Judy, Zeng, Xin, Browndyke, Jeffrey, Toulgoat-Dubois, Yanne, Ferket, Bart S., Hohmann, Samuel F., Chang, Helena L., Mick, Stephanie L., Hung, Judy W., Overbey, Jessica R., and Lala, Anuradha

Published
2020
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43. Deep learning-based denoising streamed from mobile phones improves speech-in-noise understanding for hearing aid users

Author

Diehl, Peter Udo, primary, Zilly, Hannes, additional, Sattler, Felix, additional, Singer, Yosef, additional, Kepp, Kevin, additional, Berry, Mark, additional, Hasemann, Henning, additional, Zippel, Marlene, additional, Kaya, Müge, additional, Meyer-Rachner, Paul, additional, Pudszuhn, Annett, additional, Hofmann, Veit M., additional, Vormann, Matthias, additional, and Sprengel, Elias, additional

Published
2023
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45. Integrating genomic features for non-invasive early lung cancer detection

Author

Chabon, Jacob J., Hamilton, Emily G., Kurtz, David M., Esfahani, Mohammad S., Moding, Everett J., Stehr, Henning, Schroers-Martin, Joseph, Nabet, Barzin Y., Chen, Binbin, Chaudhuri, Aadel A., Liu, Chih Long, Hui, Angela B., Jin, Michael C., Azad, Tej D., Almanza, Diego, Jeon, Young-Jun, Nesselbush, Monica C., Co Ting Keh, Lyron, Bonilla, Rene F., Yoo, Christopher H., Ko, Ryan B., Chen, Emily L., Merriott, David J., Massion, Pierre P., Mansfield, Aaron S., Jen, Jin, Ren, Hong Z., Lin, Steven H., Costantino, Christina L., Burr, Risa, Tibshirani, Robert, Gambhir, Sanjiv S., Berry, Gerald J., Jensen, Kristin C., West, Robert B., Neal, Joel W., Wakelee, Heather A., Loo, Jr, Billy W., Kunder, Christian A., Leung, Ann N., Lui, Natalie S., Berry, Mark F., Shrager, Joseph B., Nair, Viswam S., Haber, Daniel A., Sequist, Lecia V., Alizadeh, Ash A., and Diehn, Maximilian

Published
2020
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47. Parental Intentions and Perceptions Toward COVID-19 Vaccination Among Children Aged 4 Months to 4 Years--PROTECT Cohort, Four States, July 2021-May 2022

Author

Lutrick, Karen, Fowlkes, Ashley, Rivers, Patrick, Herder, Katherine, Santibanez, Tammy A., LeClair, Lindsay, Groover, Kimberly, Lamberte, Julie Mayo, Grant, Lauren, Odame-Bamfo, Leah, Ferraris, Maria V., Phillips, Andrew L., Sokol, Brian, Lowe, Ashley A., Mathenge, Clare, Pubillones, Felipe A., Cottam, Brianna, McLeland-Wieser, Hilary, Jovel, Krystal S., Ochoa, Jezahel S., Mckell, Jacob, Berry, Mark, Khan, Sana, Solle, Natasha Schaefer, Rai, Ramona P., Nakayima, Flavia Miiro, Newes-Adeyi, Gabriella, Porter, Cynthia, Baccam, Zoe, Ellingson, Katherine D., Burgess, Jeffery L., Gaglani, Manjusha, Gwynn, Lisa, Caban-Martinez, Alberto, and Yoon, Sarang

Subjects
Children's furniture, Vaccination, Parenting, Health
Abstract

Approximately 12 million children and adolescents aged [less than or equal to]18 years in the United States have been infected with SARS-CoV-2, the virus that causes COVID-19, since December 2019,* [...]

Published
2022

48. High-Resolution Magic Angle Spinning (HRMAS) NMR Identifies Oxidative Stress and Impairment of Energy Metabolism by Zearalenone in Embryonic Stages of Zebrafish (Danio rerio), Olive Flounder (Paralichthys olivaceus) and Yellowtail Snapper (Ocyurus chrysurus)

Author

Berry, Mark Annunziato, Narmin Bashirova, Muhamed N. H. Eeza, Ariel Lawson, Daniel Benetti, John D. Stieglitz, Jörg Matysik, A. Alia, and John P.

Subjects
nuclear magnetic resonance (NMR), metabolomics, fish, zebrafish, mycotoxins, zearalenone
Abstract

Zearalenone (ZEA) is a mycotoxin, commonly found in agricultural products, linked to adverse health impacts in humans and livestock. However, less is known regarding effects on fish as both ecological receptors and economically relevant “receptors” through contamination of aquaculture feeds. In the present study, a metabolomics approach utilizing high-resolution magic angle spinning nuclear magnetic resonance (HRMAS NMR) was applied to intact embryos of zebrafish (Danio rerio), and two marine fish species, olive flounder (Paralichthys olivaceus) and yellowtail snapper (Ocyurus chrysurus), to investigate the biochemical pathways altered by ZEA exposure. Following the assessment of embryotoxicity, metabolic profiling of embryos exposed to sub-lethal concentrations showed significant overlap between the three species and, specifically, identified metabolites linked to hepatocytes, oxidative stress, membrane disruption, mitochondrial dysfunction, and impaired energy metabolism. These findings were further supported by analyses of tissue-specific production of reactive oxygen species (ROS) and lipidomics profiling and enabled an integrated model of ZEA toxicity in the early life stages of marine and freshwater fish species. The metabolic pathways and targets identified may, furthermore, serve as potential biomarkers for monitoring ZEA exposure and effects in fish in relation to ecotoxicology and aquaculture.

Published
2023
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