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6,966 results on '"Yi C"'

104. Softening of a flat phonon mode in the kagome ScV6Sn6

Author

Korshunov, A., primary, Hu, H., additional, Subires, D., additional, Jiang, Y., additional, Călugăru, D., additional, Feng, X., additional, Rajapitamahuni, A., additional, Yi, C., additional, Roychowdhury, S., additional, Vergniory, M. G., additional, Strempfer, J., additional, Shekhar, C., additional, Vescovo, E., additional, Chernyshov, D., additional, Said, A. H., additional, Bosak, A., additional, Felser, C., additional, Bernevig, B. Andrei, additional, and Blanco-Canosa, S., additional

Published
2023
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107. Замечание о неравенстве Харди в версии Дэвиса

Author

Yi C. Huang

Subjects
General Medicine
Abstract

Мы приводим доказательство методом «интегрированием по частям» неравенства Харди в версии Дэвиса. При этом получается усиление со значительно большим весом Харди.

Published
2023

108. Climate control of terrestrial carbon exchange across biomes and continents

Author

Yi, C., Ricciuota, D., and Goulden, M. L.

Abstract

Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate–carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid- and high-latitudes, (2) a strong function of dryness at mid- and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45°N). The sensitivity of NEE to mean annual temperature breaks down at ~ 16 °C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence.

Published
2010

118. An integrated single‐cell RNA‐seq atlas of the mouse hypothalamic paraventricular nucleus links transcriptomic and functional types.

Author

Berkhout, J. B., Poormoghadam, D., Yi, C., Kalsbeek, A., Meijer, O. C., and Mahfouz, A.

Subjects
PARAVENTRICULAR nucleus, AUTONOMIC nervous system, TRANSCRIPTOMES, RNA sequencing, MICE
Abstract

The hypothalamic paraventricular nucleus (PVN) is a highly complex brain region that is crucial for homeostatic regulation through neuroendocrine signaling, outflow of the autonomic nervous system, and projections to other brain areas. In the past years, single‐cell datasets of the hypothalamus have contributed immensely to the current understanding of the diverse hypothalamic cellular composition. While the PVN has been adequately classified functionally, its molecular classification is currently still insufficient. To address this, we created a detailed atlas of PVN transcriptomic cell types by integrating various PVN single‐cell datasets into a recently published hypothalamus single‐cell transcriptome atlas. Furthermore, we functionally profiled transcriptomic cell types, based on relevant literature, existing retrograde tracing data, and existing single‐cell data of a PVN‐projection target region. Finally, we validated our findings with immunofluorescent stainings. In our PVN atlas dataset, we identify the well‐known different neuropeptide types, each composed of multiple novel subtypes. We identify Avp‐Tac1, Avp‐Th, Oxt‐Foxp1, Crh‐Nr3c1, and Trh‐Nfib as the most important neuroendocrine subtypes based on markers described in literature. To characterize the preautonomic functional population, we integrated a single‐cell retrograde tracing study of spinally projecting preautonomic neurons into our PVN atlas. We identify these (presympathetic) neurons to cocluster with the Adarb2+ clusters in our dataset. Further, we identify the expression of receptors for Crh, Oxt, Penk, Sst, and Trh in the dorsal motor nucleus of the vagus, a key region that the pre‐parasympathetic PVN neurons project to. Finally, we identify Trh‐Ucn3 and Brs3‐Adarb2 as some centrally projecting populations. In conclusion, our study presents a detailed overview of the transcriptomic cell types of the murine PVN and provides a first attempt to resolve functionality for the identified populations. [ABSTRACT FROM AUTHOR]

Published
2024
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119. On Galbis' Integration Lemmas.

Author

Huang, Yi C. and Xue, Fei

Abstract

We simplify in this note Galbis' proof of certain norm estimates for self-adjoint Toeplitz operators on the Fock space. This relies on an extension (and a unification) of his integration lemmas, yet with a simpler proof in the same spirit. [ABSTRACT FROM AUTHOR]

Published
2024
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120. On Landau inequality via semigroup orbits

Author

Huang, Yi C., Lian, Yanlu, and Xue, Fei

Subjects
Mathematics - Functional Analysis, Primary 47D06, Secondary 26D10
Abstract

Let $\omega>0$. Given a strongly continuous semigroup $\{e^{tA}\}$ on a Banach space and an element $f\in\mathbf{D}(A^2)$ satisfying the exponential orbital estimates $$\|e^{tA}f\|\leq e^{-\omega t}\|f\| \quad\text{and}\quad \|e^{tA}A^2f\|\leq e^{-\omega t}\|A^2f\|,\quad t\geq0,$$ a dynamical inequality for $\|Af\|$ in terms of $\|f\|$ and $\|A^2f\|$ was derived by Herzog and Kunstmann (Studia Math., 223(1):19-26, 2014). In this note we provide an improvement of their result by relaxing the exponential decay to quadratic, together with a simple and direct way recovering the usual Landau inequality.

Published
2023

121. Early short course of neuromuscular blocking agents in patients with COVID-19 ARDS: a propensity score analysis

Author

Li Bassi, G, Gibbons, K, Suen, J, Dalton, H, White, N, Corley, A, Shrapnel, S, Hinton, S, Forsyth, S, Laffey, J, Fan, E, Fanning, J, Panigada, M, Bartlett, R, Brodie, D, Burrell, A, Chiumello, D, Elhazmi, A, Esperatti, M, Grasselli, G, Hodgson, C, Ichiba, S, Luna, C, Marwali, E, Merson, L, Murthy, S, Nichol, A, Ogino, M, Pelosi, P, Torres, A, Ng, P, Fraser, J, Al-Dabbous, T, Alfoudri, H, Shamsah, M, Elapavaluru, S, Berg, A, Horn, C, Mayasi, Y, Schroll, S, Meyer, D, Velazco, J, Ploskanych, L, Fikes, W, Bagewadi, R, Dao, M, White, H, Ehlers, A, Shalabi-McGuire, M, Witt, T, Grazioli, L, Lorini, L, Grandin, E, Nunez, J, Reyes, T, Obriain, D, Hunter, S, Ramanan, M, Affleck, J, Veerendra, H, Rai, S, Russell-Brown, J, Nourse, M, Joseph, M, Mitchell, B, Tenzer, M, Abe, R, Cho, H, Jeong, I, Rahman, N, Kakar, V, Brozzi, N, Mehkri, O, Krishnan, S, Duggal, A, Houltham, S, Graf, J, Diaz, R, Orrego, R, Delgado, C, Gonzalez, J, Sanchez, M, Piagnerelli, M, Sarrazin, J, Zabert, A, Espinosa, L, Delgado, P, Delgado, V, Rincon, D, Yanten, A, Duque, M, Al-Hudaib, A, Callahan, M, Taufik, M, Wardoyo, E, Gunawan, M, Trisnaningrum, N, Irawany, V, Rayhan, M, Pesenti, A, Zanella, A, Leone, M, Coppola, S, Colombo, S, Antonelli, M, Carelli, S, Grieco, D, Asaki, M, Hoshino, K, Salazar, L, Duarte, L, Mcnicholas, B, Cosgrave, D, Mccaffrey, J, Bone, A, Hakeem, Y, Winearls, J, Tallott, M, Thomson, D, Arnold-Day, C, Cupido, J, Miller, M, Seymore, L, van Straaten, D, Hssain, A, Aliudin, J, Alqahtani, A, Mohamed, K, Mohamed, A, Tan, D, Villanueva, J, Zaqout, A, Kurtzman, E, Ademi, A, Dobrita, A, El Aoudi, K, Segura, J, Giwangkancana, G, Ohshimo, S, Hitoshi, S, Osatnik, J, Joosten, A, Yang, M, Motos, A, Arancibia, F, Williams, V, Noel, A, Luque, N, Trung, T, Yacoub, S, Fantini, M, Garcia, R, Alvarez, E, Greti, A, Ceccato, A, Sanchez, A, Vazquez, A, Roche-Campo, F, Franch-Llasat, D, Tuazon, D, Amato, M, Cassimiro, L, Pola, F, Ribeiro, F, Fonseca, G, Desai, M, Osborn, E, Deeb, H, Arcadipane, A, Martucci, G, Panarello, G, Vitiello, C, Bianco, C, Occhipinti, G, Rossetti, M, Cuffaro, R, Cho, S, Shimizu, H, Moriyama, N, Kim, J, Kitamura, N, Gebauer, J, Yokoyama, T, Al-Fares, A, Buabbas, S, Alamad, E, Alawadhi, F, Alawadi, K, Tanaka, H, Hashimoto, S, Yamazaki, M, Oh, T, Epler, M, Forney, C, Kruse, L, Feister, J, Williamson, J, Grobengieser, K, Gnall, E, Golden, S, Caroline, M, Shapiro, T, Karaj, C, Thome, L, Sher, L, Vanderland, M, Welch, M, Mcdermott, S, Brain, M, Mineall, S, Kimura, D, Brazzi, L, Sales, G, Ogston, T, Nagpal, D, Fischer, K, Lorusso, R, Rangappa, R, Appu, A, Carton, E, Sen, A, Palacios, A, Rainey, D, Samoukoviv, G, Campisi, J, Durham, L, Neumann, E, Seefeldt, C, Falcucci, O, Emmrich, A, Guy, J, Johns, C, Potzner, K, Zimmermann, C, Espinal, A, Buchtele, N, Schwameis, M, Stecher, S, Singh, D, Barnikel, M, Arenz, L, Zaaqoq, A, Galloway, L, Merley, C, Csete, M, Quesada, L, Saba, I, Kasugai, D, Hiraiwa, H, Tanaka, T, Purnama, Y, Dewayanti, S, Ardiyan, Juzar, D, Siagian, D, Chen, Y, Ratsep, I, Oigus, G, Erikson, K, Post, A, Enneveer, L, Sillaots, P, Manetta, F, Mihelis, E, Sarmiento, I, Narasimhan, M, Varrone, M, Komats, M, Garcia-Diaz, J, Harmon, C, Satyapriya, S, Bhatt, A, Mokadam, N, Uribe, A, Gonzalez, A, Shi, H, Mckeown, J, Pasek, J, Fiorda, J, Echeverria, M, Moreno, R, Zakhary, B, Cavana, M, Cucino, A, Foti, G, Giani, M, Russotto, V, Castagna, V, Dellamore, A, Navalesi, P, Shum, H, Vuysteke, A, Usman, A, Acker, A, Smood, B, Mergler, B, Sertic, F, Subramanian, M, Sperry, A, Rizer, N, Burhan, E, Rasmin, M, Akmal, E, Sitompul, F, Lolong, N, Naivedh, B, Erickson, S, Barrett, P, Dean, D, Daugherty, J, Loforte, A, Khan, I, Abraar Quraishi, M, Desantis, O, So, D, Kandamby, D, Mandei, J, Natanael, H, Yudhalantang, E, Lantang, A, Wijaya, S, Jung, A, Ng, G, Ng, W, Fang, S, Tabah, A, Ratcliffe, M, Duroux, M, Adachi, S, Nakao, S, Blanco, P, Prieto, A, Sanchez, J, Nicholson, M, Butt, W, Serratore, A, Delzoppo, C, Janin, P, Yarad, E, Totaro, R, Coles, J, Pujo, B, Balk, R, Vissing, A, Kapania, E, Hays, J, Fox, S, Yantosh, G, Mishin, P, Yuliarto, S, Hari Santoso, K, Djajalaksana, S, Fatoni, A, Fukuda, M, Liu, K, Battaglini, D, Jimenez, J, Bastos, D, Gaiao, S, Rusmawatiningtyas, D, Buchner, J, Cho, Y, Lee, S, Kawasaki, T, Munshi, L, Sakiyalak, P, Nitayavardhana, P, Seitz, T, Arora, R, Kent, D, Marino, D, Parwar, S, Cheng, A, Miller, J, Fujitani, S, Shimizu, N, Madhok, J, Owyang, C, Buscher, H, Reynolds, C, Maasikas, O, Beljantsev, A, Mihnovits, V, Akimoto, T, Aizawa, M, Horibe, K, Onodera, R, Young, M, George, T, Shekar, K, Mcguinness, N, Irvine, L, Flynn, B, Endo, T, Sugiyama, K, Shimizu, K, Exconde, K, Lussier, L, Lotz, G, Malfertheiner, M, Maier, L, Dreier, E, Kusumastuti, N, Mccloskey, C, Dabaliz, A, Elshazly, T, Smith, J, Szuldrzynski, K, Bielanski, P, Wille, K, Parhar, K, Fiest, K, Codan, C, Shahid, A, Fayed, M, Evans, T, Gutierrez, A, Song, T, Rose, R, Bennett, S, Richardson, D, Peek, G, Arora, L, Rappapport, K, Rudolph, K, Sibenaller, Z, Stout, L, Walter, A, Herr, D, Vedadi, N, Thompson, S, Sindt, L, Rajnic, S, Ewald, C, Hoffman, J, Ying, X, Kennedy, R, Griffee, M, Ciullo, A, Kida, Y, Roca, R, Riera, J, Contreras, S, Alegre, C, Kay, C, Fischer, I, Renner, E, Taniguci, H, Bassi, G, Barnett, A, Pearse, I, Abbate, G, Hassan, H, Heinsar, S, Karnik, V, Ki, K, Oneill, H, Obonyo, N, Pimenta, L, Reid, J, Sato, K, Vuorinen, A, Wildi, K, Wood, E, Yerkovich, S, Lee, J, Plotkin, D, Citarella, B, Hartley, E, Lubis, B, Ikeyama, T, Bhaskar, B, Jung, J, Mcguinness, S, Eastwood, G, Marta, S, Guarracino, F, Gerle, S, Coxon, E, Claro, B, Loverde, D, Patil, N, Parrini, V, Mcbride, A, Negaard, K, Ratsch, A, Abdelaziz, A, Uribe, J, Peris, A, Sanders, M, Emerson, D, Kamal, M, Povoa, P, Francis, R, Cherif, A, Joseph, S, Di Nardo, M, Heard, M, Kyle, K, Blackwell, R, Biston, P, Jeong, H, Smith, R, Prawira, Y, Montrucchio, G, Garcia, A, Salterain, N, Meyns, B, Moreno, M, Walia, R, Mehta, A, Schweda, A, Supriatna, M, Kirakli, C, Williams, M, Kim, K, Assad, A, Giraldo, E, Karolak, W, Balik, M, Pocock, E, Gajkowski, E, Masafumi, K, Barrett, N, Takeyama, Y, Park, S, Amin, F, Andriyani, F, Sudakevych, S, Vera, M, Cornejo, R, Schwarz, P, Mardini, A, de Paula, T, Neto, A, Villoldo, A, Colafranceschi, A, Iglesias, A, Granjean, J, Melro, L, Romualdo, G, Gaia, D, Souza, H, Galas, F, Mendiluce, R, Sosa, A, Martinez, I, Kurosawa, H, Salgado, J, Hugi-MayrCharbonneau, B, Barzilai, V, Monteiro, V, de Souza, R, Harper, M, Suzuki, H, Adams, C, Brieva, J, Nyale, G, Eltatar, F, Fatani, J, Baeissa, H, Masri, A, Rabie, A, Hui, M, Yamane, M, Jung, H, Margaret, A, Nacpil, N, Ruck, K, Bakken, R, Jara, C, Felton, T, Berra, L, Shah, B, Chakraborty, A, Cardona, M, Capatos, G, Akkanti, B, Orija, A, Jain, H, Ito, A, Housni, B, Low, S, Iihara, K, Chavez, J, Ramanathan, K, Zabert, G, Naidoo, K, Seppelt, I, Vandyk, M, Macdonald, S, Mcgregor, R, Siebenaler, T, Flynn, H, Lofton, K, Aokage, T, Shigemitsu, K, Moscatelli, A, Fiorentino, G, Baumgaertel, M, Mba, S, Assy, J, Hutahaean, A, Roush, H, Sichting, K, Alessandri, F, Burns, D, Salt, G, Garabedian, C, Millar, J, Sim, M, Mattke, A, Mcauley, D, Tadili, J, Frenzel, T, Bar-Lavie, Y, Ortiz, A, Stone, J, Attokaran, A, Farquharson, M, Patel, B, Gunning, D, Baillie, K, Watson, P, Tamai, K, Sajinadiyasa, G, Kanyawati, D, Salgado, M, Sassine, A, Yudo, B, Mccaul, S, Lee, B, Afek, A, Iwashita, Y, Semedi, B, Metiva, J, Van Belle, N, Martin-Loeches, I, Ivatt, L, Woon, C, Kang, H, Smith, T, James, E, Al-Rawas, N, Iwasaki, Y, King-Chung, K, Gudzenko, V, Hugi-Mayr, B, Taccone, F, Perdhana, F, Lamarche, Y, Ribeiro, J, Bradic, N, Van den Bossche, K, Lansink, O, Singh, G, Debeuckelaere, G, Stelfox, H, Yi, C, Elia, J, Tribble, T, Shankar, S, Padmanabhan, R, Hallinan, B, Paoletti, L, Leyva, Y, Fykuda, T, Badulak, J, Koch, J, Hackman, A, Janowaik, L, Hernandez, D, Osofsky, J, Donadello, K, Lawang, A, Fine, J, Davidson, B, Li Bassi G., Gibbons K., Suen J. Y., Dalton H. J., White N., Corley A., Shrapnel S., Hinton S., Forsyth S., Laffey J. G., Fan E., Fanning J. P., Panigada M., Bartlett R., Brodie D., Burrell A., Chiumello D., Elhazmi A., Esperatti M., Grasselli G., Hodgson C., Ichiba S., Luna C., Marwali E., Merson L., Murthy S., Nichol A., Ogino M., Pelosi P., Torres A., Ng P. Y., Fraser J. F., Al-Dabbous T., Alfoudri H., Shamsah M., Elapavaluru S., Berg A., Horn C., Mayasi Y., Schroll S., Meyer D., Velazco J., Ploskanych L., Fikes W., Bagewadi R., Dao M., White H., Ehlers A., Shalabi-McGuire M., Witt T., Grazioli L., Lorini L., Grandin E. W., Nunez J., Reyes T., OBriain D., Hunter S., Ramanan M., Affleck J., Veerendra H. H., Rai S., Russell-Brown J., Nourse M., Joseph M., Mitchell B., Tenzer M., Abe R., Cho H. J., Jeong I. S., Rahman N., Kakar V., Brozzi N., Mehkri O., Krishnan S., Duggal A., Houltham S., Graf J., Diaz R., Orrego R., Delgado C., Gonzalez J., Sanchez M. S., Piagnerelli M., Sarrazin J. V., Zabert A. /P. G., Espinosa L., Delgado P., Delgado V., Rincon D. F. B., Yanten A. M. M., Duque M. B., Al-Hudaib A., Callahan M., Taufik M. A., Wardoyo E. Y., Gunawan M., Trisnaningrum N. S., Irawany V., Rayhan M., Pesenti A., Zanella A., Leone M., Coppola S., Colombo S., Antonelli M., Carelli S., Grieco D. L., Asaki M., Hoshino K., Salazar L., Duarte L., McNicholas B., Cosgrave D., McCaffrey J., Bone A., Hakeem Y., Winearls J., Tallott M., Thomson D., Arnold-Day C., Cupido J., Miller M., Seymore L., van Straaten D., Hssain A. A., Aliudin J., Alqahtani A. -R., Mohamed K., Mohamed A., Tan D., Villanueva J., Zaqout A., Kurtzman E., Ademi A., Dobrita A., El Aoudi K., Segura J., Giwangkancana G., Ohshimo S., Hitoshi S., Osatnik J., Joosten A., Yang M., Motos A., Arancibia F., Williams V., Noel A., Luque N., Trung T. H., Yacoub S., Fantini M., Garcia R. N. J., Alvarez E. C., Greti A., Ceccato A., Sanchez A., Vazquez A. L., Roche-Campo F., Franch-Llasat D., Tuazon D., Amato M., Cassimiro L., Pola F., Ribeiro F., Fonseca G., Dalton H., Desai M., Osborn E., Deeb H., Arcadipane A., Martucci G., Panarello G., Vitiello C., Bianco C., Occhipinti G., Rossetti M., Cuffaro R., Cho S. -M., Shimizu H., Moriyama N., Kim J. -B., Kitamura N., Gebauer J., Yokoyama T., Al-Fares A., Buabbas S., Alamad E., Alawadhi F., Alawadi K., Tanaka H., Hashimoto S., Yamazaki M., Oh T. -H., Epler M., Forney C., Kruse L., Feister J., Williamson J., Grobengieser K., Gnall E., Golden S., Caroline M., Shapiro T., Karaj C., Thome L., Sher L., Vanderland M., Welch M., McDermott S., Brain M., Mineall S., Kimura D., Brazzi L., Sales G., Ogston T., Nagpal D., Fischer K., Lorusso R., Rangappa R., Appu A., Carton E. G., Sen A., Palacios A., Rainey D., Samoukoviv G., Campisi J., Durham L., Neumann E., Seefeldt C., Falcucci O., Emmrich A., Guy J., Johns C., Potzner K., Zimmermann C., Espinal A., Buchtele N., Schwameis M., Stecher S. -S., Singh D., Barnikel M., Arenz L., Zaaqoq A., Galloway L. A., Merley C., Csete M., Quesada L., Saba I., Kasugai D., Hiraiwa H., Tanaka T., Purnama Y., Dewayanti S. R., Juzar D. A., Siagian D., Chen Y. -S., Ratsep I., Oigus G., Erikson K., Post A. -M., Enneveer L., Sillaots P., Manetta F., Mihelis E., Sarmiento I. C., Narasimhan M., Varrone M., Komats M., Garcia-Diaz J., Harmon C., Satyapriya S. V., Bhatt A., Mokadam N. A., Uribe A., Gonzalez A., Shi H., McKeown J., Pasek J., Fiorda J., Echeverria M., Moreno R., Zakhary B., Cavana M., Cucino A., Foti G., Giani M., Russotto V., Castagna V., DellAmore A., Navalesi P., Shum H. -P., Vuysteke A., Usman A., Acker A., Smood B., Mergler B., Sertic F., Subramanian M., Sperry A., Rizer N., Burhan E., Rasmin M., Akmal E., Sitompul F., Lolong N., Naivedh B., Erickson S., Barrett P., Dean D., Daugherty J., Loforte A., Khan I., Abraar Quraishi M., DeSantis O., So D., Kandamby D., Mandei J. M., Natanael H., YudhaLantang E., Lantang A., Wijaya S. O., Jung A., Ng G., Ng W. Y., Fang S., Tabah A., Ratcliffe M., Duroux M., Adachi S., Nakao S., Blanco P., Prieto A., Sanchez J., Nicholson M., Butt W., Serratore A., Delzoppo C., Janin P., Yarad E., Totaro R., Coles J., Pujo B., Balk R., Vissing A., Kapania E., Hays J., Fox S., Yantosh G., Mishin P., Yuliarto S., Hari Santoso K., Djajalaksana S., Fatoni A. Z., Fukuda M., Liu K., Battaglini D., Jimenez J. F. M., Bastos D., Gaiao S., Rusmawatiningtyas D., Buchner J., Cho Y. -J., Lee S. H., Kawasaki T., Munshi L., Sakiyalak P., Nitayavardhana P., Seitz T., Arora R., Kent D., Marino D., Parwar S., Cheng A., Miller J., Fujitani S., Shimizu N., Madhok J., Owyang C., Buscher H., Reynolds C., Maasikas O., Beljantsev A., Mihnovits V., Akimoto T., Aizawa M., Horibe K., Onodera R., Young M., George T., Shekar K., McGuinness N., Irvine L., Flynn B., Endo T., Sugiyama K., Shimizu K., Exconde K., Lussier L., Lotz G., Malfertheiner M., Maier L., Dreier E., Kusumastuti N. P., McCloskey C., Dabaliz A. -A., Elshazly T. B., Smith J., Szuldrzynski K. S., Bielanski P., Wille K., Parhar K. K. S., Fiest K. M., Codan C., Shahid A., Fayed M., Evans T., Garcia R., Gutierrez A., Song T., Rose R., Bennett S., Richardson D., Peek G., Arora L., Rappapport K., Rudolph K., Sibenaller Z., Stout L., Walter A., Herr D., Vedadi N., Thompson S., Sindt L., Rajnic S., Ewald C., Hoffman J., Ying X., Kennedy R., Griffee M., Ciullo A., Kida Y., Roca R. F., Riera J. I., Contreras S., Alegre C., Kay C., Fischer I., Renner E., Taniguci H., Bassi G. L., Suen J., Barnett A., Pearse I., Abbate G., Hassan H., Heinsar S., Karnik V. A., Ki K., ONeill H. F., Obonyo N., Pimenta L. P., Reid J. D., Sato K., Vuorinen A., Wildi K. S., Wood E. S., Yerkovich S., Lee J., Plotkin D., Citarella B. W., Hartley E., Lubis B., Ikeyama T., Bhaskar B., Jung J. -S., McGuinness S., Eastwood G., Marta S. R., Guarracino F., Gerle S., Coxon E., Claro B., Loverde D., Patil N., Parrini V., McBride A., Negaard K., Ratsch A., Abdelaziz A., Uribe J. D., Peris A., Sanders M., Emerson D., Kamal M., Povoa P., Francis R., Cherif A., Joseph S., Di Nardo M., Heard M., Kyle K., Blackwell R. A., Biston P., Jeong H. W., Smith R., Prawira Y., Montrucchio G., Garcia A. H., Salterain N., Meyns B., Moreno M., Walia R., Mehta A., Schweda A., Supriatna M., Kirakli C., Williams M., Kim K. H., Assad A., Giraldo E., Karolak W., Balik M., Pocock E., Gajkowski E., Masafumi K., Barrett N., Takeyama Y., Park S., Amin F., Andriyani F. M., Sudakevych S., Vera M., Cornejo R., Schwarz P., Mardini A. C., de Paula T., Neto A. S., Villoldo A., Colafranceschi A. S., Iglesias A. U., Granjean J., Melro L. M. G., Romualdo G. F., Gaia D., Souza H., Galas F., Mendiluce R. M., Sosa A., Martinez I., Kurosawa H., Salgado J., Hugi-MayrCharbonneau B. E., Barzilai V. S., Monteiro V., de Souza R. R., Harper M., Suzuki H., Adams C., Brieva J., Nyale G., Eltatar F. S., Fatani J., Baeissa H., Masri A. A., Rabie A., Hui M. Y., Yamane M., Jung H., Margaret A. 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C., Gudzenko V., Hugi-Mayr B., Taccone F., Perdhana F., Lamarche Y., Ribeiro J. M., Bradic N., Van den Bossche K., Lansink O., Singh G., Debeuckelaere G., Stelfox H. T., Yi C., Elia J., Tribble T., Shankar S., Padmanabhan R., Hallinan B., Paoletti L., Leyva Y., Fykuda T., Badulak J., Koch J., Hackman A., Janowaik L., Hernandez D., Osofsky J., Donadello K., Lawang A., Fine J., Davidson B., Vazquez A. O. R., Li Bassi, G, Gibbons, K, Suen, J, Dalton, H, White, N, Corley, A, Shrapnel, S, Hinton, S, Forsyth, S, Laffey, J, Fan, E, Fanning, J, Panigada, M, Bartlett, R, Brodie, D, Burrell, A, Chiumello, D, Elhazmi, A, Esperatti, M, Grasselli, G, Hodgson, C, Ichiba, S, Luna, C, Marwali, E, Merson, L, Murthy, S, Nichol, A, Ogino, M, Pelosi, P, Torres, A, Ng, P, Fraser, J, Al-Dabbous, T, Alfoudri, H, Shamsah, M, Elapavaluru, S, Berg, A, Horn, C, Mayasi, Y, Schroll, S, Meyer, D, Velazco, J, Ploskanych, L, Fikes, W, Bagewadi, R, Dao, M, White, H, Ehlers, A, Shalabi-McGuire, M, Witt, T, Grazioli, L, Lorini, L, Grandin, E, Nunez, J, Reyes, T, Obriain, D, Hunter, S, Ramanan, M, Affleck, J, Veerendra, H, Rai, S, Russell-Brown, J, Nourse, M, Joseph, M, Mitchell, B, Tenzer, M, Abe, R, Cho, H, Jeong, I, Rahman, N, Kakar, V, Brozzi, N, Mehkri, O, Krishnan, S, Duggal, A, Houltham, S, Graf, J, Diaz, R, Orrego, R, Delgado, C, Gonzalez, J, Sanchez, M, Piagnerelli, M, Sarrazin, J, Zabert, A, Espinosa, L, Delgado, P, Delgado, V, Rincon, D, Yanten, A, Duque, M, Al-Hudaib, A, Callahan, M, Taufik, M, Wardoyo, E, Gunawan, M, Trisnaningrum, N, Irawany, V, Rayhan, M, Pesenti, A, Zanella, A, Leone, M, Coppola, S, Colombo, S, Antonelli, M, Carelli, S, Grieco, D, Asaki, M, Hoshino, K, Salazar, L, Duarte, L, Mcnicholas, B, Cosgrave, D, Mccaffrey, J, Bone, A, Hakeem, Y, Winearls, J, Tallott, M, Thomson, D, Arnold-Day, C, Cupido, J, Miller, M, Seymore, L, van Straaten, D, Hssain, A, Aliudin, J, Alqahtani, A, Mohamed, K, Mohamed, A, Tan, D, Villanueva, J, Zaqout, A, Kurtzman, E, Ademi, A, Dobrita, A, El Aoudi, K, Segura, J, Giwangkancana, G, Ohshimo, S, Hitoshi, S, Osatnik, J, Joosten, A, Yang, M, Motos, A, Arancibia, F, Williams, V, Noel, A, Luque, N, Trung, T, Yacoub, S, Fantini, M, Garcia, R, Alvarez, E, Greti, A, Ceccato, A, Sanchez, A, Vazquez, A, Roche-Campo, F, Franch-Llasat, D, Tuazon, D, Amato, M, Cassimiro, L, Pola, F, Ribeiro, F, Fonseca, G, Desai, M, Osborn, E, Deeb, H, Arcadipane, A, Martucci, G, Panarello, G, Vitiello, C, Bianco, C, Occhipinti, G, Rossetti, M, Cuffaro, R, Cho, S, Shimizu, H, Moriyama, N, Kim, J, Kitamura, N, Gebauer, J, Yokoyama, T, Al-Fares, A, Buabbas, S, Alamad, E, Alawadhi, F, Alawadi, K, Tanaka, H, Hashimoto, S, Yamazaki, M, Oh, T, Epler, M, Forney, C, Kruse, L, Feister, J, Williamson, J, Grobengieser, K, Gnall, E, Golden, S, Caroline, M, Shapiro, T, Karaj, C, Thome, L, Sher, L, Vanderland, M, Welch, M, Mcdermott, S, Brain, M, Mineall, S, Kimura, D, Brazzi, L, Sales, G, Ogston, T, Nagpal, D, Fischer, K, Lorusso, R, Rangappa, R, Appu, A, Carton, E, Sen, A, Palacios, A, Rainey, D, Samoukoviv, G, Campisi, J, Durham, L, Neumann, E, Seefeldt, C, Falcucci, O, Emmrich, A, Guy, J, Johns, C, Potzner, K, Zimmermann, C, Espinal, A, Buchtele, N, Schwameis, M, Stecher, S, Singh, D, Barnikel, M, Arenz, L, Zaaqoq, A, Galloway, L, Merley, C, Csete, M, Quesada, L, Saba, I, Kasugai, D, Hiraiwa, H, Tanaka, T, Purnama, Y, Dewayanti, S, Ardiyan, Juzar, D, Siagian, D, Chen, Y, Ratsep, I, Oigus, G, Erikson, K, Post, A, Enneveer, L, Sillaots, P, Manetta, F, Mihelis, E, Sarmiento, I, Narasimhan, M, Varrone, M, Komats, M, Garcia-Diaz, J, Harmon, C, Satyapriya, S, Bhatt, A, Mokadam, N, Uribe, A, Gonzalez, A, Shi, H, Mckeown, J, Pasek, J, Fiorda, J, Echeverria, M, Moreno, R, Zakhary, B, Cavana, M, Cucino, A, Foti, G, Giani, M, Russotto, V, Castagna, V, Dellamore, A, Navalesi, P, Shum, H, Vuysteke, A, Usman, A, Acker, A, Smood, B, Mergler, B, Sertic, F, Subramanian, M, Sperry, A, Rizer, N, Burhan, E, Rasmin, M, Akmal, E, Sitompul, F, Lolong, N, Naivedh, B, Erickson, S, Barrett, P, Dean, D, Daugherty, J, Loforte, A, Khan, I, Abraar Quraishi, M, Desantis, O, So, D, Kandamby, D, Mandei, J, Natanael, H, Yudhalantang, E, Lantang, A, Wijaya, S, Jung, A, Ng, G, Ng, W, Fang, S, Tabah, A, Ratcliffe, M, Duroux, M, Adachi, S, Nakao, S, Blanco, P, Prieto, A, Sanchez, J, Nicholson, M, Butt, W, Serratore, A, Delzoppo, C, Janin, P, Yarad, E, Totaro, R, Coles, 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Sibenaller, Z, Stout, L, Walter, A, Herr, D, Vedadi, N, Thompson, S, Sindt, L, Rajnic, S, Ewald, C, Hoffman, J, Ying, X, Kennedy, R, Griffee, M, Ciullo, A, Kida, Y, Roca, R, Riera, J, Contreras, S, Alegre, C, Kay, C, Fischer, I, Renner, E, Taniguci, H, Bassi, G, Barnett, A, Pearse, I, Abbate, G, Hassan, H, Heinsar, S, Karnik, V, Ki, K, Oneill, H, Obonyo, N, Pimenta, L, Reid, J, Sato, K, Vuorinen, A, Wildi, K, Wood, E, Yerkovich, S, Lee, J, Plotkin, D, Citarella, B, Hartley, E, Lubis, B, Ikeyama, T, Bhaskar, B, Jung, J, Mcguinness, S, Eastwood, G, Marta, S, Guarracino, F, Gerle, S, Coxon, E, Claro, B, Loverde, D, Patil, N, Parrini, V, Mcbride, A, Negaard, K, Ratsch, A, Abdelaziz, A, Uribe, J, Peris, A, Sanders, M, Emerson, D, Kamal, M, Povoa, P, Francis, R, Cherif, A, Joseph, S, Di Nardo, M, Heard, M, Kyle, K, Blackwell, R, Biston, P, Jeong, H, Smith, R, Prawira, Y, Montrucchio, G, Garcia, A, Salterain, N, Meyns, B, Moreno, M, Walia, R, Mehta, A, Schweda, A, Supriatna, M, Kirakli, C, Williams, M, Kim, K, Assad, A, Giraldo, E, Karolak, W, Balik, M, Pocock, E, Gajkowski, E, Masafumi, K, Barrett, N, Takeyama, Y, Park, S, Amin, F, Andriyani, F, Sudakevych, S, Vera, M, Cornejo, R, Schwarz, P, Mardini, A, de Paula, T, Neto, A, Villoldo, A, Colafranceschi, A, Iglesias, A, Granjean, J, Melro, L, Romualdo, G, Gaia, D, Souza, H, Galas, F, Mendiluce, R, Sosa, A, Martinez, I, Kurosawa, H, Salgado, J, Hugi-MayrCharbonneau, B, Barzilai, V, Monteiro, V, de Souza, R, Harper, M, Suzuki, H, Adams, C, Brieva, J, Nyale, G, Eltatar, F, Fatani, J, Baeissa, H, Masri, A, Rabie, A, Hui, M, Yamane, M, Jung, H, Margaret, A, Nacpil, N, Ruck, K, Bakken, R, Jara, C, Felton, T, Berra, L, Shah, B, Chakraborty, A, Cardona, M, Capatos, G, Akkanti, B, Orija, A, Jain, H, Ito, A, Housni, B, Low, S, Iihara, K, Chavez, J, Ramanathan, K, Zabert, G, Naidoo, K, Seppelt, I, Vandyk, M, Macdonald, S, Mcgregor, R, Siebenaler, T, Flynn, H, Lofton, K, Aokage, T, Shigemitsu, K, Moscatelli, A, Fiorentino, G, 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A., Uribe A., Gonzalez A., Shi H., McKeown J., Pasek J., Fiorda J., Echeverria M., Moreno R., Zakhary B., Cavana M., Cucino A., Foti G., Giani M., Russotto V., Castagna V., DellAmore A., Navalesi P., Shum H. -P., Vuysteke A., Usman A., Acker A., Smood B., Mergler B., Sertic F., Subramanian M., Sperry A., Rizer N., Burhan E., Rasmin M., Akmal E., Sitompul F., Lolong N., Naivedh B., Erickson S., Barrett P., Dean D., Daugherty J., Loforte A., Khan I., Abraar Quraishi M., DeSantis O., So D., Kandamby D., Mandei J. M., Natanael H., YudhaLantang E., Lantang A., Wijaya S. O., Jung A., Ng G., Ng W. Y., Fang S., Tabah A., Ratcliffe M., Duroux M., Adachi S., Nakao S., Blanco P., Prieto A., Sanchez J., Nicholson M., Butt W., Serratore A., Delzoppo C., Janin P., Yarad E., Totaro R., Coles J., Pujo B., Balk R., Vissing A., Kapania E., Hays J., Fox S., Yantosh G., Mishin P., Yuliarto S., Hari Santoso K., Djajalaksana S., Fatoni A. Z., Fukuda M., Liu K., Battaglini D., Jimenez J. F. 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M., Codan C., Shahid A., Fayed M., Evans T., Garcia R., Gutierrez A., Song T., Rose R., Bennett S., Richardson D., Peek G., Arora L., Rappapport K., Rudolph K., Sibenaller Z., Stout L., Walter A., Herr D., Vedadi N., Thompson S., Sindt L., Rajnic S., Ewald C., Hoffman J., Ying X., Kennedy R., Griffee M., Ciullo A., Kida Y., Roca R. F., Riera J. I., Contreras S., Alegre C., Kay C., Fischer I., Renner E., Taniguci H., Bassi G. L., Suen J., Barnett A., Pearse I., Abbate G., Hassan H., Heinsar S., Karnik V. A., Ki K., ONeill H. F., Obonyo N., Pimenta L. P., Reid J. D., Sato K., Vuorinen A., Wildi K. S., Wood E. S., Yerkovich S., Lee J., Plotkin D., Citarella B. W., Hartley E., Lubis B., Ikeyama T., Bhaskar B., Jung J. -S., McGuinness S., Eastwood G., Marta S. R., Guarracino F., Gerle S., Coxon E., Claro B., Loverde D., Patil N., Parrini V., McBride A., Negaard K., Ratsch A., Abdelaziz A., Uribe J. D., Peris A., Sanders M., Emerson D., Kamal M., Povoa P., Francis R., Cherif A., Joseph S., Di Nardo M., Heard M., Kyle K., Blackwell R. A., Biston P., Jeong H. W., Smith R., Prawira Y., Montrucchio G., Garcia A. H., Salterain N., Meyns B., Moreno M., Walia R., Mehta A., Schweda A., Supriatna M., Kirakli C., Williams M., Kim K. H., Assad A., Giraldo E., Karolak W., Balik M., Pocock E., Gajkowski E., Masafumi K., Barrett N., Takeyama Y., Park S., Amin F., Andriyani F. M., Sudakevych S., Vera M., Cornejo R., Schwarz P., Mardini A. C., de Paula T., Neto A. S., Villoldo A., Colafranceschi A. S., Iglesias A. U., Granjean J., Melro L. M. G., Romualdo G. F., Gaia D., Souza H., Galas F., Mendiluce R. M., Sosa A., Martinez I., Kurosawa H., Salgado J., Hugi-MayrCharbonneau B. E., Barzilai V. S., Monteiro V., de Souza R. R., Harper M., Suzuki H., Adams C., Brieva J., Nyale G., Eltatar F. S., Fatani J., Baeissa H., Masri A. A., Rabie A., Hui M. Y., Yamane M., Jung H., Margaret A. M., Nacpil N., Ruck K., Bakken R., Jara C., Felton T., Berra L., Shah B., Chakraborty A., Cardona M., Capatos G., Akkanti B., Orija A., Jain H., Ito A., Housni B., Low S., Iihara K., Chavez J., Ramanathan K., Zabert G., Naidoo K., Seppelt I., VanDyk M., MacDonald S., McGregor R., Siebenaler T., Flynn H., Lofton K., Aokage T., Shigemitsu K., Moscatelli A., Fiorentino G., Baumgaertel M., Mba S. E., Assy J., Hutahaean A., Roush H., Sichting K. A., Alessandri F., Burns D., Salt G., Garabedian C. P., Millar J., Sim M., Mattke A., McAuley D., Tadili J., Frenzel T., Bar-Lavie Y., Ortiz A. B., Stone J., Attokaran A., Farquharson M., Patel B., Gunning D., Baillie K., Watson P., Tamai K., Sajinadiyasa G. K., Kanyawati D., Salgado M., Sassine A., Yudo B., McCaul S., Lee B., Lee S. M., Afek A., Iwashita Y., Semedi B. P., Metiva J., Van Belle N., Martin-Loeches I., Ivatt L., Woon C. Y., Kang H. M., Smith T., James E., Al-Rawas N., Iwasaki Y., King-Chung K. C., Gudzenko V., Hugi-Mayr B., Taccone F., Perdhana F., Lamarche Y., Ribeiro J. M., Bradic N., Van den Bossche K., Lansink O., Singh G., Debeuckelaere G., Stelfox H. T., Yi C., Elia J., Tribble T., Shankar S., Padmanabhan R., Hallinan B., Paoletti L., Leyva Y., Fykuda T., Badulak J., Koch J., Hackman A., Janowaik L., Hernandez D., Osofsky J., Donadello K., Lawang A., Fine J., Davidson B., and Vazquez A. O. R.

Abstract

Background: The role of neuromuscular blocking agents (NMBAs) in coronavirus disease 2019 (COVID-19) acute respiratory distress syndrome (ARDS) is not fully elucidated. Therefore, we aimed to investigate in COVID-19 patients with moderate-to-severe ARDS the impact of early use of NMBAs on 90-day mortality, through propensity score (PS) matching analysis. Methods: We analyzed a convenience sample of patients with COVID-19 and moderate-to-severe ARDS, admitted to 244 intensive care units within the COVID-19 Critical Care Consortium, from February 1, 2020, through October 31, 2021. Patients undergoing at least 2 days and up to 3 consecutive days of NMBAs (NMBA treatment), within 48 h from commencement of IMV were compared with subjects who did not receive NMBAs or only upon commencement of IMV (control). The primary objective in the PS-matched cohort was comparison between groups in 90-day in-hospital mortality, assessed through Cox proportional hazard modeling. Secondary objectives were comparisons in the numbers of ventilator-free days (VFD) between day 1 and day 28 and between day 1 and 90 through competing risk regression. Results: Data from 1953 patients were included. After propensity score matching, 210 cases from each group were well matched. In the PS-matched cohort, mean (± SD) age was 60.3 ± 13.2 years and 296 (70.5%) were male and the most common comorbidities were hypertension (56.9%), obesity (41.1%), and diabetes (30.0%). The unadjusted hazard ratio (HR) for death at 90 days in the NMBA treatment vs control group was 1.12 (95% CI 0.79, 1.59, p = 0.534). After adjustment for smoking habit and critical therapeutic covariates, the HR was 1.07 (95% CI 0.72, 1.61, p = 0.729). At 28 days, VFD were 16 (IQR 0–25) and 25 (IQR 7–26) in the NMBA treatment and control groups, respectively (sub-hazard ratio 0.82, 95% CI 0.67, 1.00, p = 0.055). At 90 days, VFD were 77 (IQR 0–87) and 87 (IQR 0–88) (sub-hazard ratio 0.86 (95% CI 0.69, 1.07; p =

Published
2022

122. Isothermal amplification using sequence-specific fluorescence detection of SARS coronavirus 2 and variants in nasal swabs

Author

Les Jones, Hemant K Naikare, Yung-Yi C Mosley, and Ralph A Tripp

Subjects
COVID-19 Testing, Molecular Diagnostic Techniques, SARS-CoV-2, COVID-19, Humans, RNA, Viral, Reverse Transcription, Nucleic Acid Amplification Techniques, Sensitivity and Specificity, General Biochemistry, Genetics and Molecular Biology, Biotechnology
Abstract

Coronavirus disease 2019 is a public health challenge requiring rapid testing for the detection of infections and transmission. Nucleic acid amplification tests targeting SARS coronavirus 2 (CoV2) are used to detect CoV2 in clinical samples. Real-time reverse transcription quantitative PCR is the standard nucleic acid amplification test for CoV2, although reverse transcription loop-mediated isothermal amplification is used in diagnostics. The authors demonstrate a sequence-specific reverse transcription loop-mediated isothermal amplification-based nucleic acid amplification assay that is finished within 30 min using minimally processed clinical nasal swab samples and describe a fluorescence-quenched reverse transcription loop-mediated isothermal amplification assay using labeled primers and a quencher oligonucleotide. This assay can achieve rapid (30 min) and sensitive (1000 plaque-forming units/ml) fluorescence detection of CoV2 (WA1/2020), B.1.1.7 (Alpha) and variants of concern Delta (B.1.617.2) and Omicron (B.1.1.529) in nasal samples.

Published
2022

128. Supplementary Methods, Figures 1 - 8 from Inhibition of Cholinergic Signaling Causes Apoptosis in Human Bronchioalveolar Carcinoma

Author

Lau, Jamie K., primary, Brown, Kathleen C., primary, Thornhill, Brent A., primary, Crabtree, Clayton M., primary, Dom, Aaron M., primary, Witte, Theodore R., primary, Hardman, W. Elaine, primary, McNees, Christopher A., primary, Stover, Cody A., primary, Carpenter, A. Betts, primary, Luo, Haitao, primary, Chen, Yi C., primary, Shiflett, Brandon S., primary, and Dasgupta, Piyali, primary

Published
2023
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130. Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

Author

Ning, X, Liu, R, Wang, N, Xiao, X, Wu, S, Wang, Y, Yi, C, He, Y, Li, D, Chen, H, Ning, X, Liu, R, Wang, N, Xiao, X, Wu, S, Wang, Y, Yi, C, He, Y, Li, D, and Chen, H

Abstract

OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the potential to overcome this hurdle. This study aimed to leverage deep machine learning techniques to establish a precise and efficient diagnostic approach for this cancer type which can also predict the metastatic risk using two software, U-Net and QuPath, which have not been trialled in gastric cancers. METHODS: A U-Net neural network was trained to recognise, and segment differentiated components from 186 pathology images of mixed-type gastric cancer. Undifferentiated components in the same images were annotated using the open-source pathology imaging software QuPath. The outcomes from U-Net and QuPath were used to calculate the ratios of differentiation/undifferentiated components which were correlated to lymph node metastasis. RESULTS: The models established by U-Net recognised ∼91% of the regions of interest, with precision, recall, and F1 values of 90.2%, 90.9% and 94.6%, respectively, indicating a high level of accuracy and reliability. Furthermore, the receiver operating characteristic curve analysis showed an area under the cure of 91%, indicating good performance. A bell-curve correlation between the differentiated/undifferentiated ratio and lymphatic metastasis was found (highest risk between 0.683 and 1.03), which is paradigm-shifting. CONCLUSION: U-Net and QuPath exhibit promising accuracy in the identification of differentiated and undifferentiated components in mixed-type gastric cancer, as well as paradigm-shifting prediction of metastasis. These findings bring us one step closer to their potential clinical application.

Published
2023

131. Can biomarkers be used to diagnose attention deficit hyperactivity disorder?

Author

Chen, H, Yang, Y, Odisho, D, Wu, S, Yi, C, Oliver, BG, Chen, H, Yang, Y, Odisho, D, Wu, S, Yi, C, and Oliver, BG

Abstract

Currently, the diagnosis of attention deficit hyperactivity disorder (ADHD) is solely based on behavioral tests prescribed by the Diagnostic and Statistical Manual of Mental Disorders, 5th Edition (DSM-5). However, biomarkers can be more objective and accurate for diagnosis and evaluating treatment efficacy. Thus, this review aimed to identify potential biomarkers for ADHD. Search terms "ADHD," and "biomarker" combined with one of "protein," "blood/serum," "gene," and "neuro" were used to identify human and animal studies in PubMed, Ovid Medline, and Web of Science. Only papers in English were included. Potential biomarkers were categorized into radiographic, molecular, physiologic, or histologic markers. The radiographic analysis can identify specific activity changes in several brain regions in individuals with ADHD. Several molecular biomarkers in peripheral blood cells and some physiologic biomarkers were found in a small number of participants. There were no published histologic biomarkers for ADHD. Overall, most associations between ADHD and potential biomarkers were properly controlled. In conclusion, a series of biomarkers in the literature are promising as objective parameters to more accurately diagnose ADHD, especially in those with comorbidities that prevent the use of DSM-5. However, more research is needed to confirm the reliability of the biomarkers in larger cohort studies.

Published
2023

132. iPSCs-derived mesenchymal stromal cells mitigate anxiety and neuroinflammation in aging female mice.

Author

Wei, X, Li, R, Li, X, Wang, B, Huang, J, Mu, H, Zhang, Q, Zhang, Z, Ru, Y, Wu, X, Qiu, Y, Ye, Y, Feng, Y, Wang, S, Chen, H, Yi, C, Wang, J, Wei, X, Li, R, Li, X, Wang, B, Huang, J, Mu, H, Zhang, Q, Zhang, Z, Ru, Y, Wu, X, Qiu, Y, Ye, Y, Feng, Y, Wang, S, Chen, H, Yi, C, and Wang, J

Abstract

Perimenopause is a natural transition to menopause, when hormone disturbance can result in both short-term mental disorders, such as anxiety, and long-term neuroinflammation due to blood-brain barrier (BBB) impairment, which may lead to more serious neurological disorders later on, such as dementia. Effective treatments may prevent both short-term and long-term neurological sequela, which formed the aim of this study. In aged female C57BL/6 mice (16-18 months of age), mesenchymal stromal cells (MSCs) differentiated from human-induced pluripotent stem cells (iPSCs), were administered via tail vein injection. Mice showed increased blood estrogen levels, alleviated anxiety and neuroinflammation, and improved BBB integrity. Interestingly, transplanted MSCs were located close to ovarian sympathetic nerves and decreased ovarian norepinephrine levels, which in turn increased ovarian estrogen secretion. Moreover, the administration of anastrozole, an inhibitor of estrogen synthesis, diminished the therapeutic effects of MSCs in vivo, suggesting the effect to be estrogen-dependent. In vitro study confirmed the impact of MSCs on sympathetic nerves via mitochondria exchange. In conclusion, iPSC-derived MSCs may provide a novel option to manage perimenopause-related hormonal dysregulation and neurological disorders during the female aging process.

Published
2023

134. Granger Causal Inference Based on Dual Laplacian Distribution and Its Application to MI-BCI Classification.

Author

Li, P, Gao, X, Li, C, Yi, C, Huang, W, Si, Y, Li, F, Cao, Z, Tian, Y, Xu, P, Li, P, Gao, X, Li, C, Yi, C, Huang, W, Si, Y, Li, F, Cao, Z, Tian, Y, and Xu, P

Abstract

Granger causality-based effective brain connectivity provides a powerful tool to probe the neural mechanism for information processing and the potential features for brain computer interfaces. However, in real applications, traditional Granger causality is prone to the influence of outliers, such as inevitable ocular artifacts, resulting in unreasonable brain linkages and the failure to decipher inherent cognition states. In this work, motivated by constructing the sparse causality brain networks under the strong physiological outlier noise conditions, we proposed a dual Laplacian Granger causality analysis (DLap-GCA) by imposing Laplacian distributions on both model parameters and residuals. In essence, the first Laplacian assumption on residuals will resist the influence of outliers in electroencephalogram (EEG) on causality inference, and the second Laplacian assumption on model parameters will sparsely characterize the intrinsic interactions among multiple brain regions. Through simulation study, we quantitatively verified its effectiveness in suppressing the influence of complex outliers, the stable capacity for model estimation, and sparse network inference. The application to motor-imagery (MI) EEG further reveals that our method can effectively capture the inherent hemispheric lateralization of MI tasks with sparse patterns even under strong noise conditions. The MI classification based on the network features derived from the proposed approach shows higher accuracy than other existing traditional approaches, which is attributed to the discriminative network structures being captured in a timely manner by DLap-GCA even under the single-trial online condition. Basically, these results consistently show its robustness to the influence of complex outliers and the capability of characterizing representative brain networks for cognition information processing, which has the potential to offer reliable network structures for both cognitive studies and future brain

Published
2023

135. Information transmission velocity-based dynamic hierarchical brain networks.

Author

Jiang, L, Li, F, Chen, Z, Zhu, B, Yi, C, Li, Y, Zhang, T, Peng, Y, Si, Y, Cao, Z, Chen, A, Yao, D, Chen, X, Xu, P, Jiang, L, Li, F, Chen, Z, Zhu, B, Yi, C, Li, Y, Zhang, T, Peng, Y, Si, Y, Cao, Z, Chen, A, Yao, D, Chen, X, and Xu, P

Abstract

The brain functions as an accurate circuit that regulates information to be sequentially propagated and processed in a hierarchical manner. However, it is still unknown how the brain is hierarchically organized and how information is dynamically propagated during high-level cognition. In this study, we developed a new scheme for quantifying the information transmission velocity (ITV) by combining electroencephalogram (EEG) and diffusion tensor imaging (DTI), and then mapped the cortical ITV network (ITVN) to explore the information transmission mechanism of the human brain. The application in MRI-EEG data of P300 revealed bottom-up and top-down ITVN interactions subserving P300 generation, which was comprised of four hierarchical modules. Among these four modules, information exchange between visual- and attention-activated regions occurred at a high velocity, related cognitive processes could thus be efficiently accomplished due to the heavy myelination of these regions. Moreover, inter-individual variability in P300 was probed to be attributed to the difference in information transmission efficiency of the brain, which may provide new insight into the cognitive degenerations in clinical neurodegenerative disorders, such as Alzheimer's disease, from the transmission velocity perspective. Together, these findings confirm the capacity of ITV to effectively determine the efficiency of information propagation in the brain.

Published
2023

140. Data from Inhibition of Cholinergic Signaling Causes Apoptosis in Human Bronchioalveolar Carcinoma

Author

Piyali Dasgupta, Brandon S. Shiflett, Yi C. Chen, Haitao Luo, A. Betts Carpenter, Cody A. Stover, Christopher A. McNees, W. Elaine Hardman, Theodore R. Witte, Aaron M. Dom, Clayton M. Crabtree, Brent A. Thornhill, Kathleen C. Brown, and Jamie K. Lau

Abstract

Recent case-controlled clinical studies show that bronchioalveolar carcinomas (BAC) are correlated with smoking. Nicotine, the addictive component of cigarettes, accelerates cell proliferation through nicotinic acetylcholine receptors (nAChR). In this study, we show that human BACs produce acetylcholine (ACh) and contain several cholinergic factors including acetylcholinesterase (AChE), choline acetyltransferase (ChAT), choline transporter 1 (CHT1, SLC5A7), vesicular acetylcholine transporter (VAChT, SLC18A3), and nACh receptors (AChRs, CHRNAs). Nicotine increased the production of ACh in human BACs, and ACh acts as a growth factor for these cells. Nicotine-induced ACh production was mediated by α7-, α3β2-, and β3-nAChRs, ChAT and VAChT pathways. We observed that nicotine upregulated ChAT and VAChT. Therefore, we conjectured that VAChT antagonists, such as vesamicol, may suppress the growth of human BACs. Vesamicol induced potent apoptosis of human BACs in cell culture and nude mice models. Vesamicol did not have any effect on EGF or insulin-like growth factor-II–induced growth of human BACs. siRNA-mediated attenuation of VAChT reversed the apoptotic activity of vesamicol. We also observed that vesamicol inhibited Akt phosphorylation during cell death and that overexpression of constitutively active Akt reversed the apoptotic activity of vesamicol. Taken together, our results suggested that disruption of nicotine-induced cholinergic signaling by agents such as vesamicol may have applications in BAC therapy. Cancer Res; 73(4); 1328–39. ©2012 AACR.

Published
2023

141. Supplementary Methods, Figures 1 - 8 from Inhibition of Cholinergic Signaling Causes Apoptosis in Human Bronchioalveolar Carcinoma

Author

Piyali Dasgupta, Brandon S. Shiflett, Yi C. Chen, Haitao Luo, A. Betts Carpenter, Cody A. Stover, Christopher A. McNees, W. Elaine Hardman, Theodore R. Witte, Aaron M. Dom, Clayton M. Crabtree, Brent A. Thornhill, Kathleen C. Brown, and Jamie K. Lau

Abstract

PDF file - 490K, Figure S1: Cell line authentication data Figure S2: Full screen western blots for ChAT, VAChT, AChE and CHT1 Figure S3: Immunohistochemistry of ChAT and VAChT in normal human lung tissues Figure S4: Nicotine-induced ACh production in human BAC requires nAChRs, VAChT, and CHT1 Figure S5: VAChT and ChAT are expressed on human BACs Figure S6: Transfection of VAChT siRNA and Sigma-R siRNA suppress the expression of these proteins in human BACs Figure S7: Effect of VAChT siRNA on the apoptotic activity of vesamicol in nicotine-treated BACs Figure S8: Overexpression of pcDNA3-HA-Akt-CA in A549 and H358 human BAC cells

Published
2023

142. Phenethyl isothiocyanate inhibits CD133+/CD90+ liver cancer stem cells by modulation of microRNA‐214‐β‐catenin epigenome axis

Author

Chu, Yi C., Lin, Sheng‐Tsai, Setiawan, Syahru A., Hsieh, Ming‐Shou, Yadav, Vijesh K., Huang, Ting‐Yi, Yeh, Chi‐Tai, and Chen, Ming‐Yao

Abstract

Hepatocellular carcinoma (HCC) represents one of the most prevalent and lethal type of malignancies around the globe. Despite the advancement in medical research and therapeutics development, HCC still remains a taunting challenge in clinical settings. Recent studies indicate that the presence of cancer stem cells (CSCs) may be the underlying factor for treatment failure, distant metastasis, and disease recurrence. Elevated stemness gene expression has been correlated to disease stage and poorer prognosis in HCC patients. Initially, we established that β‐catenin is highly expressed in HCC clinical samples. We subsequently re‐validated the idea that CD133+/CD90+ subpopulation cells exhibited CSCs properties including elevated stemness expression (β‐catenin, Nanog, c‐Myc, and Twist1), increased self‐renewal capacity and metastatic potential. Using this cell model, we tested the potential anti‐CSCs effects of phenethyl isothiocynanate (PEITC), a phytochemical isolated from cruciferous vegetables. Treatment of PEITC led to a decreased percentage of CD133+/CD90+ cells in both Huh7 and Sk‐Hep1 cell lines. In addition, PEITC suppressed stemness gene expression, self‐renewal ability, and metastatic potential in HCC CSCs. Mechanistically, PEITC conveyed its anti‐CSCs effects via upregulating microRNA‐214, a negative regulator of β‐catenin. In conclusion, we provided evidence that PEITC could suppress HCC CSCs generation/maintenance. With further clinical testing, PEITC could be used either alone or in combination with currently available chemotherapeutic agents to achieve improved efficacy.

Published
2023
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143. Softening of a flat phonon mode in the kagome ScV6Sn6.

Author

Korshunov, A., Hu, H., Subires, D., Jiang, Y., Călugăru, D., Feng, X., Rajapitamahuni, A., Yi, C., Roychowdhury, S., Vergniory, M. G., Strempfer, J., Shekhar, C., Vescovo, E., Chernyshov, D., Said, A. H., Bosak, A., Felser, C., Bernevig, B. Andrei, and Blanco-Canosa, S.

Subjects
PHONONS, CHARGE density waves, ELECTRON-phonon interactions, SPECIALTY pharmacies
Abstract

Geometrically frustrated kagome lattices are raising as novel platforms to engineer correlated topological electron flat bands that are prominent to electronic instabilities. Here, we demonstrate a phonon softening at the kz = π plane in ScV6Sn6. The low energy longitudinal phonon collapses at ~98 K and q = 1 3 1 3 1 2 due to the electron-phonon interaction, without the emergence of long-range charge order which sets in at a different propagation vector qCDW = 1 3 1 3 1 3 . Theoretical calculations corroborate the experimental finding to indicate that the leading instability is located at 1 3 1 3 1 2 of a rather flat mode. We relate the phonon renormalization to the orbital-resolved susceptibility of the trigonal Sn atoms and explain the approximately flat phonon dispersion. Our data report the first example of the collapse of a kagome bosonic mode and promote the 166 compounds of kagomes as primary candidates to explore correlated flat phonon-topological flat electron physics. The recently discovered charge density wave in ScV6Sn6 kagome metal is under intense debate. By using a combination of experimental and theoretical techniques, the authors point to the role of flat phonon mode softening and momentum-dependent electron-phonon coupling in the formation of the charge density wave. [ABSTRACT FROM AUTHOR]

Published
2023
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144. Evaluation of the influence of pantograph cracks on contact forces in the interaction between pantograph and catenary.

Author

Yi, C., Wang, D., Zhou, L., Lin, J.H., and Zhang, W.H.

Subjects
*CATENARY, *PANTOGRAPH, *CONTACT dermatitis, *INTERMOLECULAR forces
Abstract

Pantograph-catenary (P-C) systems operating under cracks would induce potential risks to railways. Previous relevant research efforts lack consideration of the dynamic characteristics of P-C systems under crack damages. A rigid-flexible P-C coupling model with pantograph cracks for a metro line is developed in this study. The evolution law of P-C contact forces under the condition of cracked propagation is described, and the influence of speed, uplift force, span length, and pullout value arrangement on P-C contact force and the sensitivity of crack influence are explored. Results show that the dispersion of contact force values decreases continuously upon the existence and expansion of cracks on the pantograph. Proper selection of operating conditions is advised because of the sensitivity differences of the five influencing factors indicates. Metro trains should not be operated at 100 km/h for the rail section with an 8 m-span catenary, and further inspections on the pantograph should be scheduled for trains operating over 100 km/h. The uplift force should be adjusted to the 90-100 N range. The 8 m span length is suggested in a metro catenary, and the splayed arrangement of pullout value is recommended as a priority when the situation allows. [ABSTRACT FROM AUTHOR]

Published
2023
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145. Clinical analysis and identification of pediatric patients with colonic ulceration

Author

Yaying You, Yijing Tao, Yanwen Xu, Yi Cao, Haixia Feng, Qingqing Wu, Ying Wang, and Weihui Yan

Subjects
Colonoscopy, Ulcer, Colon, Diagnosis, Inflammatory bowel disease, Pediatrics, RJ1-570
Abstract

Abstract Background A wide variety of diseases mimic inflammatory bowel disease (IBD). This study aimed to reduce the misdiagnosis among children with colonic ulcers. Methods Eighty-six pediatric patients with colonic ulcers detected by colonoscopy were enrolled in the retrospective study. Children were divided into different groups according to the final diagnosis. The clinical characteristics, laboratory examinations, endoscopic findings, and histopathological results were compared. Results IBD (n = 37) was just responsible for 43% of patients with colonic ulceration. Other diagnosis included autoimmune diseases (n = 9), infectious enteritis (n = 13), gastrointestinal allergy (n = 8), and other diseases (n = 19). Comparing IBD and non-IBD groups, children with IBD had a higher frequency of symptoms like weight loss/failure to thrive (P

Published
2024
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146. Autophagy-related protein PlAtg3 participates in vegetative growth, sporangial cleavage, autophagy and pathogenicity of Peronophythora litchii

Author

Chengdong Yang, Manfei Luo, Xue Zhang, Linlin Ye, Ge Yu, Yi Lü, Yi Chen, Taixu Chen, Xuejian Wang, Wanzhen Feng, and Qinghe Chen

Subjects
PlAtg3, sporangial cleavage, autophagy, pathogenicity, Peronophythora litchii, Agriculture (General), S1-972
Abstract

Litchi downy blight, caused by the plant pathogenic oomycete Peronophythora litchii, is one of the most devastating diseases on litchi and resulted in huge economic losses. Autophagy plays an essential role in the development and pathogenicity of the filamentous fungi. However, the function of autophagy in oomycetes remain elusive. Here, an autophagy-related protein Atg3 homolog PlAtg3 was identified and characterized in P. litchii. The absence of PlATG3 through the CRISPR/Cas9 gene replacement strategy compromised vegetative growth and sexual/asexual development. Cytological analyses revealed that the deletion of PlATG3 impaired autophagosome formation with monodansylcadaverine (MDC) staining and significantly disrupted zoospore release due to defects of sporangial cleavage with FM4-64 staining. Atg8 is considered to be an autophagy marker protein in various species. Western blot analysis indicated that PlAtg3 is involved in degradation of PlAtg8-PE. Interestingly, PlAtg3 was unable to interact with PlAtg8 in yeast two hybrid (Y2H) assays, possibly due to the absence of the Atg8 family interacting motif (AIM) in PlAtg3. Furthermore, pathogenicity assays revealed that the deletion of PlATG3 considerably reduced the virulence of P. litchii. Taken together, our data reveal that PlAtg3 plays an important role in radial growth, asexual/sexual development, sporangial cleavage and zoospore release, autophagosome formation, and pathogenicity in P. litchii. This study contributes to a better understanding of the pathogenicity mechanisms of P. litchii and provides insights for the development of more effective strategies to control oomycete diseases.

Published
2024
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147. Source depth estimation based on the higher‐order sound field in the deep ocean

Author

Dajun Sun, Zehua Wang, Junjie Shi, Minshuai Liang, and Yi Chen

Subjects
acoustic signal processing, acoustic wave propagation, sonar target recognition, Telecommunication, TK5101-6720
Abstract

Abstract Lloyd's mirror effect is a spatial interference phenomenon that results from the coherent combination of direct and surface‐reflected propagation paths. The higher‐order vertical sound intensities of the interference sound field contain source depth information, and the relationship between these higher‐order sound intensities can be employed to estimate the source depth. A method for source depth estimation and qualitative binary source depth discrimination using the 0th‐order sound pressure, as well as the 1st‐ and 2nd‐order sound intensities, was proposed. The numerical simulation results confirmed the ability of the proposed method to approximate the source depth and discriminate between surface and submerged sources without requiring long‐term tracking or knowledge of the ocean environment.

Published
2024
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148. SkatingVerse: A large‐scale benchmark for comprehensive evaluation on human action understanding

Author

Ziliang Gan, Lei Jin, Yi Cheng, Yu Cheng, Yinglei Teng, Zun Li, Yawen Li, Wenhan Yang, Zheng Zhu, Junliang Xing, and Jian Zhao

Subjects
computer vision, video signal processing, Computer applications to medicine. Medical informatics, R858-859.7, Computer software, QA76.75-76.765
Abstract

Abstract Human action understanding (HAU) is a broad topic that involves specific tasks, such as action localisation, recognition, and assessment. However, most popular HAU datasets are bound to one task based on particular actions. Combining different but relevant HAU tasks to establish a unified action understanding system is challenging due to the disparate actions across datasets. A large‐scale and comprehensive benchmark, namely SkatingVerse is constructed for action recognition, segmentation, proposal, and assessment. SkatingVerse focus on fine‐grained sport action, hence figure skating is chosen as the task object, which eliminates the biases of the object, scene, and space that exist in most previous datasets. In addition, skating actions have inherent complexity and similarity, which is an enormous challenge for current algorithms. A total of 1687 official figure skating competition videos was collected with a total of 184.4 h, exceeding four times over other datasets with a similar topic. SkatingVerse enables to formulate a unified task to output fine‐grained human action classification and assessment results from a raw figure skating competition video. In addition, SkatingVerse can facilitate the study of HAU foundation model due to its large scale and abundant categories. Moreover, image modality is incorporated for human pose estimation task into SkatingVerse. Extensive experimental results show that (1) SkatingVerse significantly helps the training and evaluation of HAU methods, (2) the performance of existing HAU methods has much room to improve, and SkatingVerse helps to reduce such gaps, and (3) unifying relevant tasks in HAU through a uniform dataset can facilitate more practical applications. SkatingVerse will be publicly available to facilitate further studies on relevant problems.

Published
2024
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149. Super‐evolutionary mechanism and Nelder‐Mead simplex enhanced salp swarm algorithm for photovoltaic model parameter estimation

Author

Huangying Wu, Yi Chen, Zhennao Cai, Ali Asghar Heidari, Huiling Chen, and Yudong Zhang

Subjects
artificial intelligence, learning (artificial intelligence), Renewable energy sources, TJ807-830
Abstract

Abstract In the pursuit of enhancing the efficiency of solar cells, accurate estimation of unspecified parameters in the solar photovoltaic (PV) cell model is imperative. An advanced salp swarm algorithm called the Super‐Evolutionary Nelder‐Mead Salp Swarm Algorithm (SENMSSA) is proposed to achieve this objective. The proposed SENMSSA addresses the limitations of SSA by incorporating a super‐evolutionary mechanism based on a Gaussian‐Cauchy mutation and a vertical and horizontal crossover mechanism. This mechanism enhances both the global optimization capabilities and the local search performance and convergence speed of the algorithm. It enables a secondary refinement of the global optimum, unlocking untapped potential in the solution space near the global optimum and elevating the algorithm's precision and exploitation capabilities to higher levels. The Nelder‐Mead simplex method is further introduced to enhance local search capabilities and convergence accuracy. The Nelder‐Mead simplex method is a versatile optimization algorithm that improves local search by iteratively adjusting a geometric shape (simplex) of points. It operates without needing derivatives, making it suitable for non‐smooth or complex objective functions. To assess the efficacy of SENMSSA, a comparative analysis is conducted against other available algorithms, namely SSA, IWOA, SCADE, LWOA, CBA, and RCBA, using the CEC2014 benchmark function set. Subsequently, the algorithm was employed to determine the unknown PV parameters under fixed conditions for three different diode models. Additionally, SENMSSA is utilized to estimate PV parameters for three commercially available PV models (ST40, SM55, KC200GT) under varying conditions. The experimental results indicate that the SENMSSA proposed in this study displays a remarkably competitive performance in all test cases compared to other algorithms. As such, we consider that the SENMSSA algorithm constitutes a reliable and efficient solution for the challenge of PV parameter estimation.

Published
2024
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150. Fluid activity characteristics of shallow shale veins in the Wufeng–Longmaxi Formation in the Shixi syncline in northern Guizhou and their significance for shale gas preservation

Author

Dandan Wang, Zhenxue Jiang, Wei Du, Dadong Liu, Xindi Shao, Xia Feng, Yi Chen, Wenyi Chen, and Yu Yang

Subjects
Northern Guizhou, Shale gas, Veins, C-O isotopes, Preservation conditions, Gas industry, TP751-762
Abstract

Preservation conditions are key to enriching shallow shale gas. Therefore, the veins of two typical wells in the Shixi syncline in northern Guizhou as research objects. Based on core observation, vein thin-section observation, cathodoluminescence, calcite in situ U-Pb dating, fluid inclusion microthermometry, Raman spectrum shift, single well basin simulation, and C-O isotope geochemical analysis, the researchers clarified the characteristics of the veins and the differences in paleofluid activity, as well as their significance for shale gas preservation. The results showed that: 1) a small number of high-angle fractures had developed mainly in the Shixi syncline in northern Guizhou. The width of viens is small and filled primarily with early calcite-quartz and late calcite. The inclusions were mainly methane and brine. The proportion of brine inclusions in the SD1 well was greater than that in the SX1 well. The SD1 well has experienced more intense second-stage uplift and denudation, and the consequent gas loss is serious. 2) The results of the C-O isotope analysis showed that most of the vein-forming fluids were derived from marine carbonate rocks. The O3b had obvious negative deviations of δ13C and δ18O, which were modified by exogenous or deep hydrothermal fluid. The C-O isotope difference between the vein bodies and the surrounding rock of the SX1 well was small, and the preservation conditions were better. 3) The difference in gas content in the Shixi syncline depends on the degree of damage to gas reservoir preservation conditions caused by burial depth and other factors. Shixi syncline is a wide and gentle syncline with central retention enrichment mode. Therefore, clarifying the development of shale veins, the characteristics of paleofluid activity, and their significance for shale gas preservation can lay a foundation for studying the enrichment mechanism of shallow shale gas and thus guide further exploration and development.

Published
2024
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