The number one Twitter podcaster (see below) with a blue and green icon for an avatar. Substack column newly added. https://t.co/a5Z7Ka0A2l
United States (National)
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John C. primarily covers scientific and healthcare topics, with a significant focus on research findings and data-driven articles. Given this emphasis, he would likely be interested in receiving pitches from experts who can provide insights into the latest developments in cardiology, chemistry, space exploration, genetics, or environmental science.
As John's coverage heavily relies on cited data and press releases, experts looking to reach out should ensure that their pitches are well-supported by credible sources and recent studies within the respective fields. Additionally, given his broad range of article titles covering various scientific disciplines including cardiology, chemistry, space exploration among others; experts offering multidisciplinary perspectives may find success when reaching out to him.
While there is no specific geographic focus mentioned for John's coverage area based on the article titles provided; it appears that he takes an international view of scientific discoveries across different domains.
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By: Rodriguez, John C., Cochrane, Acedo, Vederas, Findlay, Eva M., Lopez, Mercier, Pascal, Jeella Z., Alireza, Stephen A., Brandon
Tridecaptin A1 (TriA1) is a nonribosomal lipopeptide with selective antimicrobial activity against Gram-negative bacteria. Here we show that TriA1 ...
By: Poe, Sungeun, Irimia, Sanjeev, Andrew J., Jiong, Brand, Eric C., Jonathan D., Geoffrey, Foroud, George, Chris, Kewei, Bates, Crawford, Budson, Cairns, Brosch, Anar, Barnes, Colleen S., Kielb, Blank, Smita, Bernard, Carl, Raslau, Gail, Stefanovic, Bonakdarpour, Karen, Lisa, Brockington, Hsiao, Jeffrey M., Mitsis, Brian R., Danowski, Maria T.,, Munic, Carlsson, Khachaturian, Christine M., Faber, Hyungsub, Tatiana M., Quinn, Raj, Shi, Korecka, Goldstein, Liana, Belden, Wong, David A.,, Rudow, Spann, Shulman, Craft, Scherer, Olusegun, Oscar L., Rosen, Lopez, Jacqueline, Leonie, Jr., Allyson, Cleveland, Kelly, Garrett, Mauricio, David, Poki-Walker, Feldman, Garcia, Radford, Juliet, Bartha, Lilly, Trung, Beau, Mathews, Rachel, Richard, Kelly A.,, Allison, Sheikh, Nigel J., Steven E., Kwangsik, Nguyen-Barrera, Alexander, Gustavo, Trojanowki, White, Koeppe, Donna M., Bernick, Ian, Doraiswamy, Risacher, Kittur, Saba, Lamar, Xinghe, Cucchi, Neu, Vanderswag, Pearlson, Michelle, Martin, Richard J., Chet, Helen, Borrie, Erin, Liberty, Mingxi, Pierce, Petersen, Brichko, Onyike, Godfrey, Franklin, Richard E., Payam, Ismail, Horacio, Gloria, Howard J., Grossman, Laura L., Kelly M., Dariella, Ravdin, Sara, Ward, Charles D., Relkin, Bryan M., Nunzio, Norman, Macavoy, Stacy, Clark, Bernhardt, Burns, Nikhil N., Nam, Jaimie, Mccann, Mary L., Rachinsky, Donna, Carole, Cat, Mason, P. Murali, Irina, Fernandez, Megan, Yuliana, Farrington, Anna, Tingus, Tremont, Moore, Lisa C., Shen, Honig, Sperling, William, Li, Phoebe, Jahanshad, Yesavage, Choe, Reyes, Kelley M., Sabbagh, Neylan, Greenberg, Pacini, Steven, James J.,, Pasternak, Nudelman, Wisniewski, Laurel, Amanda, Ntekim, Howard, Chaudhari, Ellen, Koleva, Potter, Brandy R., Douglas W.,, Robson, Dolen, Mark A., Delwyn D., Hernando, Antero, Creech, Raymond Scott, Turner, Thai, Mudge, Ances, Gunter, Denise, Hsiung, Francine, Flashman, Robert B., Chad, Rountree, Thompson, Householder, Nir, Jessica D.,, Kim, Jordan, Anderson, Kowall, Weiner, Miller, Pavlik, John, Gessert, Robin, Teresa, John C., Stephanie, Masterman, Eliezer, Ott, Craig, Flenniken, Kris, Harvey, Zamrini, Toga, Jared, Marissa, Carter, Kaye, Jerome, Bernstein, Matthew, Pawluczyk, Decarli, Keith A., Sheeba, Weintraub, Mia, Nahian F., Susan K., Kaycee M., Marc, Green, Thomas, Sophia I.,, Joanne L., Rawan, Joy L., Ki Won, Ozioma, Shaffer, Maryann, Beatriz, Adam P., Vemuri, Vesna, Chowdhury, Kejal, Brigid, Singleton-Garvin, Swerdlow, Reist, Bret, Lipowski, Jimenez-Maggiora, Kass, Rodriguez, Judith L., Stern, Randall, Lee, Reynolds, Cheng, Lind, Jeffrey A., Robert, Gregory A.,, Truran Sacrey, Sosa, Sara S., Shaw, Fatica, Mintzer, Mintun, Derek, Hajjar, Correia, Burke, Benita, Mark, Earl A.,, Kerwin, Porsteinsson, Anaztasia, Jennifer, Matt, Albers, Landau, Borowski, Gad A., Daniel H.S., Yang, Carroll, Paula, Stephen, Chengshi, Tom, Stobbs, Clanton, Daniel, Teng, Lah, Knopman, Nelson, Reisa A.,, Johnson, Evaristus, Karen M., Aaron, Borna, Mahboubi, Cellar, Jeff D., Kataki, Godfrey D., Tinklenberg, Walter, Becerra, Rottislav, Chenzhong, Hayes, Pradeep, González, Cynthia M., Finger, Marilyn, Griffith, Ron, Schultz, Edward, El Khouli, Bartzokis, Haley, Arvin, Sood, Riham, Silverman, Natelson Love, Oakley, Brendan, Shim, Michele, Rema, Mary, Pomara, Chiadi, Nathaniel, Fockler, Knaack, Ho, Vernice, Khan, Matthews, Clifford R., Williamson, Killiany, Conti, Hart, Roy J., Bickford, Neto, Salvador, Simpson, Wilmes, Hynes, Edmond, Mike, M. Saleem, Schneider, Marie, Andrei, Hristina, Saykin, Aimee, Quiceno, Veitch, Wolk, Lamb, Lu, Tarawneh, Grafman, Adrienne, Asthana, Ryan, Dang, Heyn, Tatsuoka, Dick, Butters, Charles, Olichney, Dana, Robert A.,, Woo, Jin, Mohammed O.,, Po H., Wu, Silverberg, Null, Carson, Balebail Ashok, Santulli, Taylor-Reinwald, Sarah, Potkin, Neuhaus, Jicha, Elizabeth, Winkfield, Carmichael, Neill R., Jared R., Lawrence S., Martin R.,, Samuel, Womack, Coleman, Thomas O.,, Parianne, Zmuda, Scott, Jacobo, Javier, Sadowski, Joseph, Jo, Jason H., Zimmerman, Chertkow, Olga, Karlawish, Brittanie, Maria, Forghanian-Arani, Paul, Assaly, Imms, Sterling, Brewer, Jeffrey R., Kyle, Bruce L.,, Meryl, Crissey, Senjem, Fargher, Shannon, Devon, Joseph S., Raina, Das, Daiello, Pauline, Ranjan, Amgalan, Martinez, Samuels, Kristin, Schwarz, Jesse, Kelly N., Bogdan, Catalinotto, Jamika, Leslie M., Hake, Raj C., Seltzer, Wolday, Boles Ponto, Martha G., Sandra, Christopher M.,, Kristi, Mesulam, Rachelle S.,, Hosein, Diana, Anton P.,, Janet S., Ashley, Norm, Karen Ekstam, Sossi, Neil, Vaishnavi, Albert, Arnold, Prashanthi, Terence Z., Herring, Levey, Shannon L.,, Betty, Farlow, Adegoke, Caileigh, Laura A.,, Rainka, Kormos, Ashford, Drost, Scharre, Obisesan, Grant, Dzintra, Fletcher, Geldmacher, Yanez, Paul M., Coker, Blanchard, Bonnie S., Hergesheimer, Evan, Lon S., Nadarajah, Melanie, Brittany, Gad, Wiliams, Christopher, Rao, Allan I.,, Castro, Carrillo, Apostolova, Okonkwo, Graff, Van Dyck, Jack, Black, Pizzola, Lin, Arthur, Konstantinos, Hector, Jonathan, Muse, Zaven, Villena, Drake, Mintz, Martin A.,, Ong, Maria T, Kremen, Kantarci, Arline, Perry, Magdalena, Lane, Peskind, Owen, Villanueva-Meyer, Taylor, Thomopoulos, Oyonumo E.,, Kathleen, Nosheny, Ogrocki, Patricia, Susan, Mez, Georgia, Tosun-Turgut, Chen, Donohue, Jackson, Nina, Aisen, Ulysse, James, Makino, Cabrera, Foster, Raman, Greig, Capote, Chinthaka, Nguyen, Duara, Debra, Thal, Masliah, Christopher H., Leon, Brooks, Sink, Emily, Stephanie Rossi, Jimenez, Arfanakis, Nancy, Sonia, Rob, Andrew E.,, Paul A., Malloy, Jaila, Nwulia, Lerner, Rosemarie, Varma, Doody, Elaine R., Mathis, Mackin, Dagerman, Angela, Flavius D., O’Connelll, Melissa, Ritter, Akiva, Dallas, Yiu Ho, Shibley, Ajay, Celmins, Michael, Rogalski, Teodoro, Marwan, Alan, Jeff, Michal, Montine, Au, William M., Reid, Sandhitsu, Suzanne, Hillel, Jagust, Marson, Petrie, Masdeu, Fleisher, Lord, Robert C., Shah, Stark, Rossi Chen, Ronald, Ann Marie, Petrella, Malone, Kristine, Liana G., Athena, Salazar, Heidebrink, Yushkevich, Morris, Elise, Shelley, Nick C.,, Eli, Michael W.,, John Q., Adam, Kertesz, Mecca, Marshall, Victoria, Talia M., Parfitt, Laurie, Fox, Neda, Smith, Javed I., Yin, Lindsey, Reiman, Valory, Rafii, Raymundo, Sloan, Maillard, Sanjay, Silbert, Andrew, Mimi, Vaitekunis, Catherine, Miriam, Abigail, Russell H.,, Munir, Kowalski, John K., Sarrael, Beckett, Chao, Bojana, Varon, Lori A., Jessica, Faustin, Connie, Oliver, Keltz, Chuang-Kuo, Gaby, Julia, Jeremy, Finley, Effie, Ziolkowski, Perrin, Curtis, Eric M., Chiang, Kimberly S., Danielle, Angelica, Arthur W.,, Massett, Fleischman, Rogers, Kelley, Nho, Figurski, Newhouse, Sadowsky, Witbracht, Jones, Barton, Duygu, Salloway, Ihab, Yaakov
The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patter...
By: Ivy Tsz-Lo
Oncogene amplification on extrachromosomal DNA is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival.
By: Marcus E., Lee, Morris, Alessandra, Faggionato, Manu S., Metcalf, Nicholas, Vlassenko, John C., John J., Andrei G.
Within the Alzheimer disease (AD) spectrum, metabolic alterations occur in addition to proteinopathies. While hypometabolism is frequently observed in the late symptomatic stages, characterizing the metabolic changes during early AD stages might aid in both understanding its pathophysiology and in patient selection for future treatments. In this study, we conduct an exploratory, data-driven analysis aimed at better understanding the timing and specificity of the metabolic changes in early AD. Using kinetic analysis of [18F]FDG PET brain imaging data coming from 223 individuals, including 33 preclinical individuals and 19 symptomatic individuals, we find new evidence of a more complex spatiotemporal trajectory of glucose metabolism in early AD, which includes a paradoxical regional increase in glucose phosphorylation during preclinical AD. These findings suggest that the pathologic phases of AD parallel changes in brain glucose metabolism, which is readily assessable with [18F]FDG PET imaging. Moreover, they may indicate that metabolic interventions may work differently during preclinical AD as compared to the early symptomatic phase.
Protein dynamism and evolvability are key parameters linking enzyme flexibility to adaptive potential, yet how these concepts apply to nucleic acid enzymes remains largely unexplored.
By: Briana L., Stephanie, Christenson, Payton, Joshua S., Val A., V. Praveen, Nies, Avanelle, Morris, Puukila, Prom, Ronca, Fereshteh, Molika, Choi, Dalouchi, April E., Alwood, Jessica L., Fajardo, Lane K., E. Matthew, Xiaoman, Hockey, Stoltz, Braun, Chakravarthi, Sinha, Sungshin Y., Michael E., Ponte, Hong, John C.
Spaceflight presents unique gravitational, radiation, and isolation hazards for human exploration of the Moon, Mars, and beyond, yet its impact on ...
By: Geoffrey M., Munson, John C., Brittany E., Sam L., Sara J., Aaron R., Sean A.
Background Trialists sometimes find it difficult to determine whether the innovation they are evaluating is a clinical intervention or an implementation strategy. The inaccurate classification of innovations can lead to negative consequences such as the misspecification of the trial’s primary outcome, inappropriate choice of comparators, and suboptimal decisions about site-selection, participant eligibility, masking and fidelity assessment/control. Likewise, inaccurate classification can lead to the mislabeling of the type of hybrid effectiveness-implementation trial, the incorrect choice of reporting frameworks, and/or the inappropriate inclusion or exclusion of trial findings from systematic reviews and meta-analyses. In this paper we propose a systematic process for classifying an innovation as a clinical intervention or an implementation strategy. Main body We propose that logic models be used to provide structure to the classification process. Specifically, causal pathway diagrams can be used to identify the innovation’s mechanisms of action, treatment effect modifiers, proximal outcomes, and distal outcomes that ultimately clarify whether the innovation is a clinical intervention or an implementation strategy. We propose that innovations primarily be classified by determining the type of mechanism(s) of action through which it operates. In cases where it is unclear whether the mechanism of action is clinical or implementation in nature, we propose determining whether its proximal outcome (i.e., the most immediate outcome that is realized because of the mechanism of action) is a clinical outcome as defined by NIH and the FDA or an implementation outcome as defined by the RE-AIM, CFIR, and/or Proctor implementation outcomes frameworks. We also propose that this process may lead to some innovations being classified as having both clinical and implementation components. The proposed classification process has benefits over alternative approaches, including basing the decision on the actor/level targeted by the innovation, who delivers the innovation, whether the innovation itself needs an implementation strategy to promote its successful deployment, or whether the innovation affects clinical outcomes. Conclusions In cases where different trialists using this classification process come to different conclusions, we still believe there is value in justifying the logic of the conclusion.
By: Bowler, John C., Azhar, Dua B.,, Jensen, Lee, Heys, James G., Cambria M.
The authors use recurrent neural networks to predict how structured prior experience shapes neural dynamics as mice learn flexible timing strategies during complex context-dependent behavior.
By: Bastiaan R., Maaike A., Sharon, Robin W., Lieke H., Kaat, Erdag Turgeon, Sillevis Smitt, Verbeek, Nina, Meeter, de Vries, Van Steenhoven, Fransen, Jeroen, Boon, Peter A.E., Bloem, Nagtzaam, Ece, Yvette S., van de Warrenburg, Marcel M., John C., Dopper, Agnita J.W., Esther, Bart P.C., Elise G.P., Harro, Franken, Kerstens, Hoogland, Van Swieten, Juna M., Seelaar, Mariska M.P., Laura Donker, Maarten J., Titulaer, Crijnen, Veenbergen, Suzanne C., De Graaff
Background and ObjectivesPatients with antibody-associated movement disorders sometimes lack specific features of autoimmune diseases and can therefore be misdiagnosed, for example, as neurodegenerative diseases. A well-known example is anti-IgLON5 ...
By: Katarina, Carmen ., Astrid, Pons, Towle, John C., Jiang, Vernon, Collins, Stephan, Philip R., Troyk
Objective To develop and apply a reproducible image-based methodology of the positional stability of the wireless floating microelectrode arrays (WFMAs) of the Intracortical Visual Prosthesis (ICVP) implanted in the visual cortex of two human ...
