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1,307 results on '"Hong, Jing"'

1. A Convolutional Neural Network-based Ensemble Post-processing with Data Augmentation for Tropical Cyclone Precipitation Forecasts

Author

Chen, Sing-Wen, Juang, Joyce, Wang, Charlotte, Chang, Hui-Ling, Hong, Jing-Shan, and Hsiao, Chuhsing Kate

Subjects
Statistics - Applications, Physics - Geophysics, 86A05 (Primary) 62-08 (Secondary)
Abstract

Heavy precipitation from tropical cyclones (TCs) may result in disasters, such as floods and landslides, leading to substantial economic damage and loss of life. Prediction of TC precipitation based on ensemble post-processing procedures using machine learning (ML) approaches has received considerable attention for its flexibility in modeling and its computational power in managing complex models. However, when applying ML techniques to TC precipitation for a specific area, the available observation data are typically insufficient for comprehensive training, validation, and testing of the ML model, primarily due to the rapid movement of TCs. We propose to use the convolutional neural network (CNN) as a deep ML model to leverage the spatial information of precipitation. The proposed model has three distinct features that differentiate it from traditional CNNs applied in meteorology. First, it utilizes data augmentation to alleviate challenges posed by the small sample size. Second, it contains geographical and dynamic variables to account for area-specific features and the relative distance between the study area and the moving TC. Third, it applies unequal weights to accommodate the temporal structure in the training data when calculating the objective function. The proposed CNN-all model is then illustrated with the TC Soudelor's impact on Taiwan. Soudelor was the strongest TC of the 2015 Pacific typhoon season. The results show that the inclusion of augmented data and dynamic variables improves the prediction of heavy precipitation. The proposed CNN-all outperforms traditional CNN models, based on the continuous probability skill score (CRPSS), probability plots, and reliability diagram. The proposed model has the potential to be utilized in a wide range of meteorological studies., Comment: 21 pages, 6 figures, 2 tables, 2 supplementary figures

Published
2024

2. Automated Contrastive Learning Strategy Search for Time Series

Author

Jing, Baoyu, Wang, Yansen, Sui, Guoxin, Hong, Jing, He, Jingrui, Yang, Yuqing, Li, Dongsheng, and Ren, Kan

Subjects
Computer Science - Machine Learning
Abstract

In recent years, Contrastive Learning (CL) has become a predominant representation learning paradigm for time series. Most existing methods manually build specific CL Strategies (CLS) by human heuristics for certain datasets and tasks. However, manually developing CLS usually requires excessive prior knowledge about the data, and massive experiments to determine the detailed CL configurations. In this paper, we present an Automated Machine Learning (AutoML) practice at Microsoft, which automatically learns CLS for time series datasets and tasks, namely Automated Contrastive Learning (AutoCL). We first construct a principled search space of size over $3\times10^{12}$, covering data augmentation, embedding transformation, contrastive pair construction, and contrastive losses. Further, we introduce an efficient reinforcement learning algorithm, which optimizes CLS from the performance on the validation tasks, to obtain effective CLS within the space. Experimental results on various real-world datasets demonstrate that AutoCL could automatically find the suitable CLS for the given dataset and task. From the candidate CLS found by AutoCL on several public datasets/tasks, we compose a transferable Generally Good Strategy (GGS), which has a strong performance for other datasets. We also provide empirical analysis as a guide for the future design of CLS., Comment: Accepted by CIKM'2024. Fixed typos

Published
2024
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8. Comprehensive molecular characterization of collecting duct carcinoma for therapeutic vulnerability

Author

Guan, Peiyong, Chen, Jianfeng, Mo, Chengqiang, Fukawa, Tomoya, Zhang, Chao, Cai, Xiuyu, Li, Mei, Hong, Jing Han, Chan, Jason Yongsheng, Ng, Cedric Chuan Young, Lee, Jing Yi, Wong, Suet Far, Liu, Wei, Zeng, Xian, Wang, Peili, Xiao, Rong, Rajasegaran, Vikneswari, Myint, Swe Swe, Lim, Abner Ming Sun, Yeong, Joe Poh Sheng, Tan, Puay Hoon, Ong, Choon Kiat, Xu, Tao, Du, Yiqing, Bai, Fan, Yao, Xin, Teh, Bin Tean, and Tan, Jing

Published
2024
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12. All-electrical skyrmionic magnetic tunnel junction

Author

Chen, Shaohai, Lourembam, James, Ho, Pin, Toh, Alexander K. J., Huang, Jifei, Chen, Xiaoye, Tan, Hang Khume, Yap, Sherry L. K., Lim, Royston J. J., Tan, Hui Ru, Suraj, T. S., Sim, May Inn, Toh, Yeow Teck, Lim, Idayu, Lim, Nelson C. B., Zhou, Jing, Chung, Hong Jing, Lim, Sze Ter, and Soumyanarayanan, Anjan

Published
2024
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16. The complete chloroplast genomes of Polygonatum hunanense, P. verticillatum, and P. caulialatum and their phylogenetic positions

Author

Qing-Dong Ma, Hong-Jing Zhang, Yan-Ran Qi, Zheng-You Yin, Dong-Yang Yi, and Si-Rong Yi

Subjects
Chloroplast genome, Polygonatum hunanense, Polygonatum kingianum var. grandifolium, Polygonatum verticillatum, Polygonatum caulialatum, Genetics, QH426-470
Abstract

Polygonatum hunanense H.H. Liu & B.Z. Wang (2021) and P. verticillatum (L.) All. (1875) have been widely used as foods and as folk medicines in China and India, and P. caulialatum S. R. Yi (2021) has recently been described as a new medical plant in China. There is at present a lack of genome information regarding the species. Hence, this study reports the complete chloroplast genomes of the three species. The genomes of P. hunanense, P. verticillatum, and P. caulialatum were 155,583 bp, 155,650 bp, and 155,352 bp in length, respectively. They contained large single-copy (LSC) regions of 84,412 bp, 84,404 bp, and 84,285 bp, small single-copy (SSC) regions of 18,427 bp, 18,416 bp, and 18,463 bp, and a pair of inverted repeats of 26,372 bp, 26,415 bp, and 26,302 bp, respectively. The chloroplast genomes of P. hunanense, P. verticillatum, and P. caulialatum had 133 (103 unique) genes, consisting of 87 protein-coding genes, 38 ribosomal ribonucleic acid (RNA) genes, and eight transfer RNA genes, respectively. A maximum-likelihood phylogenetic tree showed that P. kingianum Coll. et Hemsl. var. grandifolium D.M. Liu & W.Z. Zeng (1991) was closer to P. cyrtonema Hua (1892) rather than to P. kingianum Coll. et Hemsl. (1890), further supporting its status as a unique species of the genus. Moreover, P. verticillatum was separated from the easily confused herb P. cirrhifolium (Wall.) Royle (1839), while P. caulialatum was closest to P. humile Fisch. ex Maxim. (1859). This research provides a foundation for further study of these herbs.

Published
2024
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17. All-Electrical Skyrmionic Bits in a Chiral Magnetic Tunnel Junction

Author

Chen, Shaohai, Ho, Pin, Lourembam, James, Toh, Alexander K. J., Huang, Jifei, Chen, Xiaoye, Tan, Hang Khume, Yap, Sherry K. L., Lim, Royston J. J., Tan, Hui Ru, Suraj, T. S., Toh, Yeow Teck, Lim, Idayu, Zhou, Jing, Chung, Hong Jing, Ter Lim, Sze, and Soumyanarayanan, Anjan

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

Topological spin textures such as magnetic skyrmions hold considerable promise as robust, nanometre-scale, mobile bits for sustainable computing. A longstanding roadblock to unleashing their potential is the absence of a device enabling deterministic electrical readout of individual spin textures. Here we present the wafer-scale realization of a nanoscale chiral magnetic tunnel junction (MTJ) hosting a single, ambient skyrmion. Using a suite of electrical and multi-modal imaging techniques, we show that the MTJ nucleates skyrmions of fixed polarity, whose large readout signal - 20-70% relative to uniform states - corresponds directly to skyrmion size. Further, the MTJ exploits complementary mechanisms to stabilize distinctly sized skyrmions at zero field, thereby realizing three nonvolatile electrical states. Crucially, it can write and delete skyrmions using current densities 1,000 times lower than state-of-the-art. These results provide a platform to incorporate readout and manipulation of skyrmionic bits across myriad device architectures, and a springboard to harness chiral spin textures for multi-bit memory and unconventional computing., Comment: 8 pages, 5 figures

Published
2023
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18. Emulation of Neuron and Synaptic Functions in Spin-Orbit Torque Domain Wall Devices

Author

Kumar, Durgesh, Maddu, Ramu, Chung, Hong Jing, Rahaman, Hasibur, Jin, Tianli, Bhatti, Sabpreet, Ter Lim, Sze, Sbiaa, Rachid, and Piramanayagam, S. N.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Neuromorphic computing (NC) architecture has shown its suitability for energy-efficient computation. Amongst several systems, spin-orbit torque (SOT) based domain wall (DW) devices are one of the most energy-efficient contenders for NC. To realize spin-based NC architecture, the computing elements such as synthetic neurons and synapses need to be developed. However, there are very few experimental investigations on DW neurons and synapses. The present study demonstrates the energy-efficient operations of neurons and synapses by using novel reading and writing strategies. We have used a W/CoFeB-based energy-efficient SOT mechanism to drive the DWs at low current densities. We have used the concept of meander devices for achieving synaptic functions. By doing this, we have achieved 9 different resistive states in experiments. We have experimentally demonstrated the functional spike and step neurons. Additionally, we have engineered the anomalous Hall bars by incorporating several pairs, in comparison to conventional Hall crosses, to increase the sensitivity as well as signal-to-noise ratio (SNR). We performed micromagnetic simulations and transport measurements to demonstrate the above-mentioned functionalities.

Published
2022

19. Terlipressin versus placebo or noradrenalin in the treatment of hepatorenal syndrome: a systematic review and meta-analysis

Author

Yue-Meng Wan, Song-Quan Huang, Hua-Mei Wu, Yu-Hua Li, Hong-Jing Yin, and Ying Xu

Subjects
hepatorenal syndrome, vasoactive drugs, terlipressin, noradrenaline, treatment response, survival, Therapeutics. Pharmacology, RM1-950
Abstract

BackgroundHepatorenal syndrome (HRS) bears a very poor prognosis with unmet need for safe and effective therapies. This systematic review and meta-analysis aimed to re-assess safety and efficacy of terlipressin versus placebo or noradrenaline for HRS, based on previous randomized controlled trials (RCTs).MethodsPubMed, EMBASE, MEDLINE (OvidSP) and Cochrane registers were searched for trials reporting HRS treatment by terlipressin or noradrenaline. Search terms included: “hepatorenal syndrome”, “terlipressin”, “noradrenaline”, and corresponding synonyms. Comparisons between terlipressin, noradreanaline, placebo and albumin were included. Meta-analysis was conducted for treatment response (both HRS reversal and complete response), mortality and adverse events.Results15 RCTs were included, enrolling 1236 HRS patients (type 1: 1166, type 2: 70). Treatment with terlipressin+albumin resulted in significantly higher treatment response than placebo+albumin or albumin alone (risk ratio [RR]:2.75, 95% confidence interval [CI]:1.96 to 3.84; I2 = 28%, p = 0.23; n = 6). Noradrenaline was equally effective in treatment response compared to terlipressin (RR:1.19, 95% CI:0.96 to 1.46; I2 = 16%, p = 0.31; n = 7), but trials were limited by its non-blind design and small size. Sensitivity analysis showed no survival benefit with terlipressin compared to either placebo (RR:1.03, 95% CI:0.83 to 1.28; I2 = 0%, p = 0.72; n = 3) or noradreanline (RR:0.83, 95% CI:0.69 to 1.00; I2 = 4%, p = 0.39; n = 7) at 30 days of follow-up. Terlipressin carried higher risk of treatment-related adverse events compared to either placebo (RR:2.92, 95% CI:1.48 to 5.77; I2 = 0%, p = 0.75; n = 3) or noradrenaline (RR:2.45, 95% CI:1.37 to 4.37; I2 = 0%, p = 0.92; n = 5).ConclusionTerlipressin is superior to placebo, and comparable to noradreanline in treatment response, but survival benefit is lacking. Noradrenaline, with low certainty, may be a better alternative for HRS.

Published
2024
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28. Carrageenan maintains the contractile phenotype of vascular smooth muscle cells by increasing macromolecular crowding in vitro

Author

Qing Liu, Hong-Jing Jiang, Yin-Di Wu, Jian-Dong Li, Xu-Heng Sun, Cong Xiao, Jian-Yi Xu, and Zhan-Yi Lin

Subjects
Carrageenan, Macromolecular crowding, Vascular smooth muscle cells, Contractile phenotype, Transcriptomics, Medicine
Abstract

Abstract Background The contractile phenotype of vascular smooth muscle cells (VSMCs) results in good diastolic and contractile capacities, and its altered function is the main pathophysiological basis for diseases such as hypertension. VSMCs exist as a synthetic phenotype in vitro, making it challenging to maintain a contractile phenotype for research. It is widely recognized that the common medium in vitro is significantly less crowded than in the in vivo environment. Additionally, VSMCs have a heightened sense for detecting changes in medium crowding. However, it is unclear whether macromolecular crowding (MMC) helps maintain the VSMCs contractile phenotype. Purpose This study aimed to explore the phenotypic, behavioral and gene expression changes of VSMCs after increasing the crowding degree by adding carrageenan (CR). Methods The degree of medium crowding was examined by a dynamic light scattering assay; VSMCs survival and activity were examined by calcein/PI cell activity and toxicity and CCK-8 assays; VSMCs phenotypes and migration were examined by WB and wound healing assays; and gene expression was examined by transcriptomic analysis and RT-qPCR. Results Notably, 225 μg/mL CR significantly increased the crowding degree of the medium and did not affect cell survival. Simultaneously, CR significantly promoted the contraction phenotypic marker expression in VSMCs, shortened cell length, decreased cell proliferation, and inhibited cell migration. CR significantly altered gene expression in VSMCs. Specifically, 856 genes were upregulated and 1207 genes were downregulated. These alterations primarily affect the cellular ion channel transport, microtubule movement, respiratory metabolism, amino acid transport, and extracellular matrix synthesis. The upregulated genes were primarily involved in the cytoskeleton and contraction processes of VSMCs, whereas the downregulated genes were mainly involved in extracellular matrix synthesis. Conclusions The in vitro study showed that VSMCs can maintain the contractile phenotype by sensing changes in the crowding of the culture environment, which can be maintained by adding CR. Graphical Abstract

Published
2024
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29. Humoral and cellular immune responses following Omicron BA.2.2 breakthrough infection and Omicron BA.5 reinfection

Author

Xin-Jing Zhao, Bin Ji, Chao Shang, De-Yu Li, Sheng Zhang, Hong-Jing Gu, Hong-Hong Peng, Cheng Qian, Cui-Ling Zhang, Chao Shi, Yuan Shen, Jin-Jin Chen, Qiang Xu, Chen-Long Lv, Bao-Gui Jiang, Hui Wang, Xiao Li, Guo-Lin Wang, and Li-Qun Fang

Subjects
health sciences, immunity, virology, Science
Abstract

Summary: The emergence of novel Omicron subvariants has raised concerns regarding the efficacy of immunity induced by prior Omicron subvariants breakthrough infection (BTI) or reinfection against current circulating Omicron subvariants. Here, we prospectively investigated the durability of antibody and T cell responses in individuals post Omicron BA.2.2 BTI, with or without subsequent Omicron BA.5 reinfection. Our findings reveal that the emerging Omicron subvariants, including CH.1.1, XBB, and JN.1, exhibit extensive immune evasion induced by previous infections. Notably, the level of IgG and neutralizing antibodies were found to correlate with subsequent Omicron BA.5 reinfection. Fortunately, T cell responses recognizing both Omicron BA.2 and CH.1.1 peptides were observed. Furthermore, Omicron BA.5 reinfection may alleviate immune imprinting induced by WT-vaccination, bolster virus-specific ICS+ T cell responses, and promote the phenotypic differentiation of virus-specific memory CD8+ T cells. Antigen-updated or T cell-conserved vaccines are needed to control the transmission of diverse emerging SARS-CoV-2 variants.

Published
2024
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30. Association of BMI, lipid-lowering medication, and age with prevalence of type 2 diabetes in adults with heterozygous familial hypercholesterolaemia: a worldwide cross-sectional study

Author

Elshorbagy, Amany, Lyons, Alexander R.M., Vallejo-Vaz, Antonio J., Stevens, Christophe A.T., Dharmayat, Kanika I., Brandts, Julia, Catapano, Alberico L., Freiberger, Tomas, Hovingh, G. Kees, Mata, Pedro, Raal, Frederick J., Santos, Raul D., Soran, Handrean, Watts, Gerald F., Abifadel, Marianne, Aguilar-Salinas, Carlos A., Alhabib, Khalid F., Alkhnifsawi, Mutaz, Almahmeed, Wael, Alonso, Rodrigo, Al-Rasadi, Khalid, Al-Sarraf, Ahmad, Ashavaid, Tester F., Banach, Maciej, Binder, Christoph J., Bourbon, Mafalda, Brunham, Liam R., Chlebus, Krzysztof, Corral, Pablo, Cruz, Diogo, Davletov, Kairat, Descamps, Olivier S., Ezhov, Marat, Gaita, Dan, Groselj, Urh, Harada-Shiba, Mariko, Holven, Kirsten B., Kayikcioglu, Meral, Khovidhunkit, Weerapan, Lalic, Katarina, Latkovskis, Gustavs, Laufs, Ulrich, Liberopoulos, Evangelos, Lima-Martinez, Marcos M., Lin, Jie, Maher, Vincent, Marais, A. David, März, Winfried, Mirrakhimov, Erkin, Miserez, André R., Mitchenko, Olena, Nawawi, Hapizah, Nordestgaard, Børge G., Panayiotou, Andrie G., Paragh, György, Petrulioniene, Zaneta, Pojskic, Belma, Postadzhiyan, Arman, Reda, Ashraf, Reiner, Željko, Reyes, Ximena, Sadiq, Fouzia, Sadoh, Wilson E., Schunkert, Heribert, Shek, Aleksandr B., Stroes, Erik, Su, Ta-Chen, Subramaniam, Tavintharan, Susekov, Andrey V., Tilney, Myra, Tomlinson, Brian, Truong, Thanh-Huong, Tselepis, Alexandros D., Tybjærg-Hansen, Anne, Vázquez, Alejandra C., Viigimaa, Margus, Vohnout, Branislav, Wang, Luya, Yamashita, Shizuya, Arca, Marcello, Averna, Maurizio, Schreier, Laura, Pang, Jing, Ebenbichler, Christoph, Dieplinger, Hans, Innerhofer, Reinhold, Winhofer-Stöckl, Yvonne, Greber-Platzer, Susanne, Krychtiuk, Konstantin, Speidl, Walter, Toplak, Hermann, Widhalm, Kurt, Stulnig, Thomas, Huber, Kurt, Höllerl, Florian, Rega-Kaun, Gersina, Kleemann, Lucas, Mäser, Martin, Scholl-Bürgi, Sabine, Säly, Christoph, Mayer, Florian J., Sperone, Alexandra, Tanghe, Chloé, Gérard, Anne-Catherine, Pojskic, Lamija, Sisic, Ibrahim, Durak Nalbantic, Azra, Ejubovic, Malik, Jannes, Cinthia E., Pereira, Alexandre C., Krieger, Jose E., Petrov, Ivo, Goudev, Assen, Nikolov, Fedya, Tisheva, Snejana, Yotov, Yoto, Tzvetkov, Ivajlo, Baass, Alexis, Bergeron, Jean, Bernard, Sophie, Brisson, Diane, Cermakova, Lubomira, Couture, Patrick, Francis, Gordon A., Gaudet, Daniel, Hegele, Robert A., Khoury, Etienne, Mancini, G.B. John, McCrindle, Brian W., Paquette, Martine, Ruel, Isabelle, Iatan, Iulia, Cuevas, Ada, Wang, Xumin, Meng, Kang, Song, Xiantao, Yong, Qiang, Jiang, Tao, Liu, Ziyou, Duan, Yanyu, Hong, Jing, Ye, Pucong, Chen, Yan, Qi, Jianguang, Liu, Zesen, Li, Yuntao, Zhang, Chaoyi, Peng, Jie, Yang, Ya, Yu, Wei, Wang, Qian, Yuan, Hui, Cheng, Shitong, Jiang, Long, Chong, Mei, Jiao, Jian, Wu, Yue, Wen, Wenhui, Xu, Liyuan, Zhang, Ruiying, Qu, Yichen, He, Jianxun, Fan, Xuesong, Wang, Zhenjia, Chow, Elaine, Pećin, Ivan, Perica, Dražen, Symeonides, Phivos, Vrablik, Michal, Ceska, Richard, Soska, Vladimir, Tichy, Lukas, Adamkova, Vera, Franekova, Jana, Cifkova, Renata, Kraml, Pavel, Vonaskova, Katerina, Cepova, Jana, Dusejovska, Magdalena, Pavlickova, Lenka, Blaha, Vladimir, Rosolova, Hana, Nussbaumerova, Barbora, Cibulka, Roman, Vaverkova, Helena, Cibickova, Lubica, Krejsova, Zdenka, Rehouskova, Katerina, Malina, Pavel, Budikova, Milena, Palanova, Vaclava, Solcova, Lucie, Lubasova, Alena, Podzimkova, Helena, Bujdak, Juraj, Vesely, Jiri, Jordanova, Marta, Salek, Tomas, Urbanek, Robin, Zemek, Stanislav, Lacko, Jan, Halamkova, Hana, Machacova, Sona, Mala, Sarka, Cubova, Eva, Valoskova, Katerina, Burda, Lukas, Benn, Marianne, Bendary, Ahmed, Daoud, Ihab, Emil, Sameh, Elbahry, Atef, Rafla, Samir, Sanad, Osama, Kazamel, Ghada, Ashraf, Dr Mohamed, Sobhy, Mohamed, El-Hadidy, Amro, Shafy, Mohamed Abdoul, Kamal, Saif, Bendary, Mohamed, Talviste, Grete, Christmann, Jutta, Dressel, Alexander, Fath, Felix, Ferraro, Chiara, Frenzke, Lydia, Gopon, Alica, Klein, Isabel, Pienkowska, Dominika, Sietmann, Tobias, Sonntag, Antonia, Adjan, Omar, Bahrmann, Philipp, Baessler, Andrea, Barkowski, Rasmus, Beckerdjian, Raffi, Berr, Christina, Birkenfeld, Andreas, Böll, Gereon, Carstensen, Avisha, Demuth, Ilya, Finkernagel, Holger, Gouni-Berthold, Ioanna, Hahmann, Harry, Hamerle, Michael, Halder, Julian, Heide, Maria, Julius, Ulrich, Kassner, Ursula, Katzmann, Julius L, Kirschbaum, Anja, Klose, Gerald, Könemann, Stephanie, König, Christel, König, Wolfgang, Krämer, Bernhard, Kuprat, Gerrit, Koschker, Ann-Cathrin, Kilic, Özlem, Lindenmeier, Gerd, Van de Loo, Iris, Lorenz, Babette, Lorenz, Elke, Löhr, Birgit, McChord, Johanna, Maslarska, Mariya, Methe, Heiko, Merkel, Martin, Moussaoui, Zineb, Müller-Kozarez, Irina, Olivier, Christoph B, Ong, Peter, Otte, Britta, Parhofer, Klaus, Partsch, Carl-Joachim, Paulus, Michael, Pehlivanli, Sinan, Pflederer, Tobias, Pusl, Thomas, Richter, Veronika, Rosner, Stefanie, Sanin, Veronika, Schäfer, Sebastian, Schäfer, Christoph, Schatz, Ulrike, Schirmer, Stephan, Schmidt, Christine, Seeger, Wolfgang, Sisovic, Snezna, Spens, Antje, Jablonski, Ksenija Stach, Stadelmann, Alexander, Steinhagen-Thiessen, Elisabeth, Stürzebecher, Paulina, Tafelmeier, Maria, Tillack, Dörthe, Tselmin, Sergey, Tünnemann-Tarr, Adrienn, Vogt, Anja, Beckerath, Jens von, Wilke, Andreas, Wolf, Ulrich, Zemmrich, Claudia, Rizos, Christos V., Skoumas, Ioannis, Tziomalos, Konstantinos, Rallidis, Loukianos, Kotsis, Vasileios, Doumas, Michalis, Athyros, Vasileios, Skalidis, Emmanouil, Kolovou, Genovefa, Kolovou, Vana, Garoufi, Anastasia, Bilianou, Eleni, Koutagiar, Iosif, Kiouri, Estela, Antza, Christina, Zacharis, Evangelos, Attilakos, Achilleas, Sfikas, George, Koumaras, Charalambos, Anagnostis, Panagiotis, Anastasiou, Georgia, Liamis, George, Koutsogianni, Amalia-Despoina, Petkou, Ermioni, Milionis, Haralambos, Koulouri, Anastasia, Prodromiadou, Elisavet, Karányi, Zsolt, Harangi, Mariann, Bajnok, László, Audikovszky, Mária, Márk, László, Benczúr, Béla, Reiber, István, Nagy, Gergely, Nagy, András, Reddy, Lakshmi Lavanya, Shah, Swarup A. V, Ponde, Chandrashekhar K., Dalal, Jamshed J., Sawhney, Jitendra P.S., Verma, Ishwar C., Altaey, Mays, Al-Jumaily, Khalid, Rasul, Dilshad, Abdalsahib, Ali Fawzi, Jabbar, Amer Abdl, Al-ageedi, Mohanad, Dhamin, Mohammed, AlFil, Sarmad, Khadhim, Foad, Miahy, Sabah, Agar, Ruth, Catapano, Alberico Luigi, Calandra, Sebastiano, Tarugi, Patrizia, Casula, Manuela, Galimberti, Federica, Olmastroni, Elena, Sarzani, Riccardo, Ferri, Claudio, Repetti, Elena, Piro, Salvatore, Suppressa, Patrizia, Meregalli, Giancarla, Borghi, Claudio, Muntoni, Sandro, Calabrò, Paolo, Cipollone, Francesco, Purrello, Francesco, Pujia, Arturo, Passaro, Angelina, Marcucci, Rossella, Pecchioli, Valerio, Pisciotta, Livia, Mandraffino, Giuseppe, Pellegatta, Fabio, Mombelli, Giuliana, Branchi, Adriana, Fiorenza, Anna Maria, Pederiva, Cristina, Werba, Josè Pablo, Parati, Gianfranco, Carubbi, Francesca, Iughetti, Lorenzo, Fortunato, Giuliana, Iannuzzi, Arcangelo, Iannuzzo, Gabriella, Cefalù, Angelo Baldassare, Biasucci, Giacomo, Zambon, Sabina, Pirro, Matteo, Sbrana, Francesco, Trenti, Chiara, D'Erasmo, Laura, Federici, Massimo, Ben, Maria Del, Bartuli, Andrea, Giaccari, Andrea, Pipolo, Antonio, Citroni, Nadia, Guardamagna, Ornella, Lia, Salvatore, Benso, Andrea, Biolo, Gianni, Maroni, Lorenzo, Lupi, Alessandro, Bonanni, Luca, Rinaldi, Elisabetta, Zenti, Maria Grazia, Matsuki, Kota, Hori, Mika, Ogura, Masatsune, Masuda, Daisaku, Kobayashi, Takuya, Nagahama, Kumiko, Al-Jarallah, Mohammed, Radovic, Mirjana, Lunegova, Olga, Bektasheva, Erkayim, Abilova, Saamay, Erglis, Andrejs, Gilis, Dainus, Nesterovics, Georgijs, Saripo, Vita, Meiere, Ruta, Skudrina, Gunda, Terauda, Elizabete, Jambart, Selim, Ayoub, Carine, Ghaleb, Youmna, Aliosaitiene, Urte, Kutkiene, Sandra, Abdul Kadir, Siti Hamimah Sheikh, Kasim, Noor Alicezah Mohd, Nor, Noor Shafina Mohd, Abdul Hamid, Hasidah, Abdul Razak, Suraya, Al-Khateeb, Alyaa, Abd Muid, Suhaila, Abdul Rahman, Thuhairah, Kasim, Sazzli Shahlan, Radzi, Ahmad Bakhtiar Md, Ibrahim, Khairul Shafiq, Rosli, Marshima Mohd, Razali, Rafezah, Chua, Yung An, Razman, Aimi Zafira, Nazli, Sukma Azureen, Aziz, Nazirul, Rosman, Azhari, Abdul Murad, NorAzian, Jalaludin, Mohd Amin, Abdul Latif, Ahmad Zubaidi, Azzopardi, C., Mehta, Roopa, Martagon, Alexandro J., Ramirez, Gabriela A. Galan, Villa, Neftali E Antonio, Vazquez, Arsenio Vargas, Elias-Lopez, Daniel, Retana, Gustavo Gonzalez, Rodriguez, Betsabel, Macías, Jose J. Ceballos, Zazueta, Alejandro Romero, Alvarado, Rocio Martinez, Portano, Julieta D. Morales, Lopez, Humberto Alvares, Sauque-Reyna, Leobardo, Herrera, Laura G. Gomez, Mendia, Luis E. Simental, Aguilar, Humberto Garcia, Cooremans, Elizabeth Ramirez, Aparicio, Berenice Peña, Zubieta, Victoria Mendoza, Gonzalez, Perla A. Carrillo, Ferreira-Hermosillo, Aldo, Portilla, Nacu Caracas, Dominguez, Guadalupe Jimenez, Garcia, Alinna Y. Ruiz, Cazares, Hector E. Arriaga, Gonzalez, Jesus R., Valencia, Carla V. Mendez, Padilla, Francisco G., Prado, Ramon Madriz, Ibarra, Manuel O. De los Rios, Villicaña, Ruy D. Arjona, Rivera, Karina J. Acevedo, Carrera, Ricardo Allende, Alvarez, Jose A., Martinez, Jose C. Amezcua, Bustillo, Manuel de los Reyes Barrera, Vargas, Gonzalo Carazo, Chacon, Roberto Contreras, Andrade, Mario H. Figueroa, Ortega, Ashanty Flores, Alcala, Hector Garcia, de Leon, Laura E. Garcia, Guzman, Berenice Garcia, Garcia, Jose J. Garduño, Cuellar, Juan C. Garnica, Cruz, Jose R. Gomez, Garcia, Anell Hernandez, Almada, Jesus R. Holguin, Herrera, Ursulo Juarez, Sobrevilla, Fabiola Lugo, Rodriguez, Eduardo Marquez, Sibaja, Cristina Martinez, Rodriguez, Alma B. Medrano, Oyervides, Jose C. Morales, Vazquez, Daniel I. Perez, Rodriguez, Eduardo A. Reyes, Osorio, Ma. Ludivina Robles, Saucedo, Juan Rosas, Tamayo, Margarita Torres, Talavera, Luis A. Valdez, Arroyo, Luis E. Vera, Carrillo, Eloy A. Zepeda, Stroes, Erik S, Defesche, J, Zuurbier, L, Reeskamp, L, Ibrahim, S, Roeters van Lennep, Jeanine, Wiegman, Albert, Isara, Alphonsus, Obaseki, Darlington E., Al-Waili, Khalid, Al-Zadjali, Fahad, Al-Zakwani, Ibrahim, Al-Kindi, Mohammed, Al-Mukhaini, Suad, Al-Barwani, Hamida, Rana, Asim, Shah, Lahore Saeed Ullah, Al-Nouri, Fahad, Starostecka, Ewa, Konopka, Agnieszka, Bielecka-Dabrowa, Agata, Lewek, Joanna, Sosnowska, Bozena, Gąsior, Mariusz, Dyrbuś, Krzysztof, Jóźwiak, Jacek, Pajkowski, Marcin, Romanowska-Kocejko, Marzena, Żarczyńska-Buchowiecka, Marta, Chmara, Magdalena, Wasąg, Bartosz, Stróżyk, Aneta, Michalska-Grzonkowska, Aleksandra, Medeiros, Ana Margarida, Alves, Ana Catarina, Silva, Francisco, Lobarinhas, Goreti, Palma, Isabel, de Moura, Jose Pereira, Rico, Miguel Toscano, Rato, Quitéria, Pais, Patrícia, Correia, Susana, Moldovan, Oana, Virtuoso, Maria João, Araujo, Francisco, Salgado, Jose Miguel, Colaço, Ines, Dumitrescu, Andreea, Lengher, Calin, Mosteoru, Svetlana, Meshkov, Alexey, Ershova, Alexandra, Rozhkova, Tatiana, Korneva, Victoria, Yu, Kuznetsova T., Zafiraki, Vitaliy, Voevoda, Mikhail, Gurevich, Victor, Duplyakov, Dmitry, Ragino, Yulia, Chubykina, Uliana, Shaposhnik, Igor, Alkaf, Fahmi, Khudari, Alia, Rwaili, Nawal, Al-Allaf, Faisal, Alghamdi, Mohammad, Batais, Mohammed A, Almigbal, Turky H, Kinsara, Abdulhalim, AlQudaimi, Ashraf Hammouda Ahmed, Awan, Zuhier, Elamin, Omer A, Altaradi, Hani, Popovic, Ljiljana, Singh, Sandra, Rasulic, Iva, Petakov, Ana, Lalic, Nebojsa M., Lam, Carolyn, Le, Tan Ju, Siang, Eric Lim Tien, Dissanayake, Sanjaya, I-Shing, Justin Tang, Shyong, Tai E, Jin, Terrance Chua Siang, Ting, Sharon Pek Li, Ming, Jeremy Hoe Kian, Drum, Chester Lee, Nastar, Fathima Ashna, Jia, Loh Wann, Ya, Natalie Koh Si, Jie, Marvin Chua Wei, Dalan, Rinkoo, Wei, Yong Quek, sian, Tiong Yee, Keong, Yeo Khung, Rong, Siau Kai, Jin, Darren Seah Ee, Ming, Ian Koh Jan, Chang, Tan Hong, Peng, Fabian Yap Kok, Vasanwala, Rashida Farhad, Raslova, Katarina, Balinth, Karin, Buganova, Ingrid, Fabryova, Lubomira, Kadurova, Michaela, Klabnik, Alexander, Kozárová, Miriam, Sirotiakova, Jana, Battelino, Tadej, Cevc, Matija, Debeljak, Marusa, Torkar, Ana Drole, Fras, Zlatko, Jug, Borut, Cugalj, Barbara Kern, Kovac, Jernej, Mlinaric, Matej, Sikonja, Jaka, Pilcher, Gillian Joan, Blom, D J, Wolmarans, K H, Brice, B C, Muñiz-Grijalvo, Ovidio, Díaz-Díaz, Jose Luis, de Isla, Leopoldo Pérez, Fuentes, Francisco, Badimon, Lina, Martin, François, Miserez, Eleonore B., Shipton, Janine L., Ganokroj, Poranee, Chattranukulchai, Pairoj, Jiamjarasrungsi, Wiroj, Thongtang, Nuntakorn, Krittayaphong, Rungroj, Vathesatogkit, Prin, Sriphrapradang, Chutintorn, Phimphilai, Mattabhorn, Leelawattana, Rattana, Anthanont, Pimjai, Suraamornkul, Swangjit, Deerochanawong, Chaicharn, Senthong, Vichai, Torpongpun, Artit, Suteerayongprasert, Panuwat, Pengpong, Nawarat, Sathavarodom, Nattapol, Sunanta, Usanee, Porntharukchareon, Thachanun, Kiatpanabhikul, Phatharaporn, Kaewkrasaesin, Chatchon, Kongkit, Jaruwan, Umphonsathien, Mongkontida, Akbulut, Mehmet, Alici, Gökhan, Bayram, Fahri, Can, Levent Hürkan, Celik, Ahmet, Ceyhan, Ceyhun, Coskun, Fatma Yilmaz, Demir, Mesut, Demircan, Sabri, Dogan, Volkan, Durakoglugil, Emre, Dural, İbrahim Etem, Gedikli, Omer, Hacioglu, Aysa, Ildizli, Muge, Kilic, Salih, Kirilmaz, Bahadir, Kutlu, Merih, Oguz, Aytekin, Ozdogan, Oner, Onrat, Ersel, Ozer, Savas, Sabuncu, Tevfik, Sahin, Tayfun, Sivri, Fatih, Sonmez, Alper, Temizhan, Ahmet, Topcu, Selim, Tokgozoglu, Lale, Tuncez, Abdullah, Vural, Mirac, Yenercag, Mustafa, Yesilbursa, Dilek, Yigit, Zerrin, Yildirim, Aytul Belgi, Yildirir, Aylin, Yilmaz, Mehmet Birhan, Atallah, Bassam, Traina, Mahmoud, Sabbour, Hani, Abdul Hay, Dana, Luqman, Neama, Elfatih, Abubaker, Abdulrasheed, Arshad, Manla, Yosef, Kwok, See, DellOca, Nicolas, Alieva, Rano B., Fozilov, Khurshid G., Hoshimov, Shavkat U., Nizamov, Ulugbek I., Kan, Liliya E., Kim, Andrey R., Abdullaeva, Guzal J., Abdullaev, Alisher A., Do, Doan Loi, Nguyen, Mai Ngoc Thi, Kim, Ngoc Thanh, Le, Thanh Tung, Le, Hong An, and Ray, Kausik K.

Published
2024
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37. Oxygen-tolerant CO2 electroreduction over covalent organic frameworks via photoswitching control oxygen passivation strategy

Author

Hong-Jing Zhu, Duan-Hui Si, Hui Guo, Ziao Chen, Rong Cao, and Yuan-Biao Huang

Subjects
Science
Abstract

Abstract The direct use of flue gas for the electrochemical CO2 reduction reaction is desirable but severely limited by the thermodynamically favorable oxygen reduction reaction. Herein, a photonicswitching unit 1,2-Bis(5’-formyl-2’-methylthien-3’-yl)cyclopentene (DAE) is integrated into a cobalt porphyrin-based covalent organic framework for highly efficient CO2 electrocatalysis under aerobic environment. The DAE moiety in the material can reversibly modulate the O2 activation capacity and electronic conductivity by the framework ring-closing/opening reactions under UV/Vis irradiation. The DAE-based covalent organic framework with ring-closing type shows a high CO Faradaic efficiency of 90.5% with CO partial current density of −20.1 mA cm−2 at −1.0 V vs. reversible hydrogen electrode by co-feeding CO2 and 5% O2. This work presents an oxygen passivation strategy to realize efficient CO2 electroreduction performance by co-feeding of CO2 and O2, which would inspire to design electrocatalysts for the practical CO2 source such as flue gas from power plants or air.

Published
2024
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38. Lactylation-driven FTO targets CDK2 to aggravate microvascular anomalies in diabetic retinopathy

Author

Xue Chen, Ying Wang, Jia-Nan Wang, Yi-Chen Zhang, Ye-Ran Zhang, Ru-Xu Sun, Bing Qin, Yuan-Xin Dai, Hong-Jing Zhu, Jin-Xiang Zhao, Wei-Wei Zhang, Jiang-Dong Ji, Song-Tao Yuan, Qun-Dong Shen, and Qing-Huai Liu

Subjects
Diabetic Retinopathy (DR), FTO, N6-Methyladenosine (m6A), Vascular Endothelial Cells, Pericyte, Medicine (General), R5-920, Genetics, QH426-470
Abstract

Abstract Diabetic retinopathy (DR) is a leading cause of irreversible vision loss in working-age populations. Fat mass and obesity-associated protein (FTO) is an N6-methyladenosine (m6A) demethylase that demethylates RNAs involved in energy homeostasis, though its influence on DR is not well studied. Herein, we detected elevated FTO expression in vitreous fibrovascular membranes of patients with proliferative DR. FTO promoted cell cycle progression and tip cell formation of endothelial cells (ECs) to facilitate angiogenesis in vitro, in mice, and in zebrafish. FTO also regulated EC-pericyte crosstalk to trigger diabetic microvascular leakage, and mediated EC–microglia interactions to induce retinal inflammation and neurodegeneration in vivo and in vitro. Mechanistically, FTO affected EC features via modulating CDK2 mRNA stability in an m6A-YTHDF2-dependent manner. FTO up-regulation under diabetic conditions was driven by lactate-mediated histone lactylation. FB23-2, an inhibitor to FTO’s m6A demethylase activity, suppressed angiogenic phenotypes in vitro. To allow for systemic administration, we developed a nanoplatform encapsulating FB23-2 and confirmed its targeting and therapeutic efficiency in mice. Collectively, our study demonstrates that FTO is important for EC function and retinal homeostasis in DR, and warrants further investigation as a therapeutic target for DR patients.

Published
2024
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39. Deep learning on nuclear mass and $\alpha$ decay half-lives

Author

Li, Chen-Qi, Tong, Chao-Nan, Du, Hong-Jing, and Pang, Long-Gang

Subjects
Nuclear Theory
Abstract

Ab-initio calculations of nuclear masses, the binding energy and the $\alpha$ decay half-lives are intractable for heavy nucleus, because of the curse of dimensionality in many body quantum simulations as proton number($\mathrm{N}$) and neutron number($\mathrm{Z}$) grow. We take advantage of the powerful non-linear transformation and feature representation ability of deep neural network(DNN) to predict the nuclear masses and $\alpha$ decay half-lives. For nuclear binding energy prediction problem we achieve standard deviation $\sigma=0.263$ MeV on 10-fold cross validation on 2149 nuclei. Word-vectors which are high dimensional representation of nuclei from the hidden layers of mass-regression DNN help us to calculate $\alpha$ decay half-lives. For this task, we get $\sigma=0.797$ on 100 times 10-fold cross validation on 350 nuclei on $log_{10}T_{1/2}$ and $\sigma=0.731 $ on 486 nuclei. We also find physical a priori such as shell structure, magic numbers and augmented inputs inspired by Finite Range Droplet Model are important for this small data regression task., Comment: 17 pages

Published
2022
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41. Analyse de la construction comme ça et de ses fonctions intra- ou extra-prédicatives dans le genre de l’entretien culturel

Author

Hong Jing

Subjects
discourse marker, comme ça, intra-predicative function, extra-predicative function, cultural interview, discourse phraseology, Philology. Linguistics, P1-1091
Abstract

The article analyses the polyfunctionality of comme ça in spoken French, on the basis of an interview between the producer Agnès Varda and the journalist Antoine Guillot (for the realisation of a masterclass on France Culture). The interview lasts more than an hour and the frequency of the appearance of comme ça goes hand in hand with the diversity of its uses. Therefore, in accordance with existing analyses (Cappeau & Savelli 2001, Corminboeuf 2017), we proceeded to a description of the two units – comme and ça – that make up the expression and then to a sorting of the occurrences of comme ça, intra- or extra-predicative. In this way, we can identify a first dichotomy between the marker of syntactic scope, governed by a verb or a noun, and the discourse marker. We will examine some problematic cases that will help us to rule on the non-verbal or suprasegmental material (mimicry, intonation) that accompanies the production of comme ça. The article concludes with a discussion of the phenomena of discourse phraseology as they are reflected in the use of comme ça. We will then be able to re-examine the semantic approximation basis of comme ça (Corminboeuf 2017), which could justify the frequency of the expression in dialogical and narrative contexts (in the manner of a competing marker, voilà).

Published
2023

42. PRP significantly promotes the adhesion and migration of vascular smooth muscle cells on stent material

Author

Yin-Di Wu, Hong-Jing Jiang, Hao-Hao Zhou, Jian-Yi Xu, Qing Liu, Xu-Heng Sun, Yue-Heng Wu, and Zhan-Yi Lin

Subjects
Platelet-rich plasma (PRP), Smooth muscle cell (SMC), Cell migration assays, Decellularized extracellular matrix (ECM), Medicine
Abstract

Abstract Background The adhesion and survival state of cells on scaffold material is a major problem in tissue-engineered blood vessel (TEBV) culture. Platelet-rich plasma (PRP) contains a large amount of biologically active factors and fibrin, which is expected to play an important role in TEBV culture. Purpose To combine PRP with cells and scaffold material to promote cell adhesion and biological activity on the scaffold material. Methods The adhesion status and migration of SMCs under the optimal concentration suitable for SMC growth and the optimal concentration of PRP were examined by scanning electron microscopy, HE staining, CCK-8 assays, qPCR, WB, and other experimental methods and compared with those under the conventional culture (20% FBS); finally, the effect of PRP on the deposition of ECM in vascular tissue engineering culture was verified by three-dimensional culture. Results PRP at 20% is a suitable concentration for SMCs. Compared with the control group, the 20% PRP group had better migration, and the number of SMC adhesions was significantly higher than that of the control group. In addition, collagen deposition in the experimental group was significantly higher than that in the control group. Conclusion PRP (20%) can promote SMC adhesion, migration, and collagen deposition on the scaffold material.

Published
2023
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43. Improving Deep Neural Network Classification Confidence using Heatmap-based eXplainable AI

Author

Tjoa, Erico, Khok, Hong Jing, Chouhan, Tushar, and Cuntai, Guan

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

This paper quantifies the quality of heatmap-based eXplainable AI (XAI) methods w.r.t image classification problem. Here, a heatmap is considered desirable if it improves the probability of predicting the correct classes. Different XAI heatmap-based methods are empirically shown to improve classification confidence to different extents depending on the datasets, e.g. Saliency works best on ImageNet and Deconvolution on Chest X-Ray Pneumonia dataset. The novelty includes a new gap distribution that shows a stark difference between correct and wrong predictions. Finally, the generative augmentative explanation is introduced, a method to generate heatmaps capable of improving predictive confidence to a high level.

Published
2021

44. The Immunosuppressive Receptor CD32b Regulation of Macrophage Polarization and Its Implications in Tumor Progression

Author

Hong-Jing Chuang, Ying-Yin Chen, Yi-Da Chung, Evelyn Huang, Cadence Yoshang Huang, Jrhau Lung, Chung-Yu Chen, and Hui-Fen Liao

Subjects
FC gamma receptor CD32b, macrophage polarization, classically activated macrophage (M1), alternatively activated macrophage (M2), tumor stage, Biology (General), QH301-705.5, Chemistry, QD1-999
Abstract

Macrophages, pivotal components of the immune system, orchestrate host defense mechanisms in humans and mammals. Their polarization into classically activated macrophages (CAMs or M1) and alternatively activated macrophages (AAMs or M2) dictates distinct functional roles in immunity and tissue homeostasis. While the negative regulatory role of CD32b within the FC gamma receptor (FCγR) family is recognized across various immune cell types, its influence on macrophage polarization remains elusive. This study aimed to elucidate the regulatory role of CD32b in macrophage polarization and discern the differential expression markers between the M1 and M2 phenotypes following CD32b siRNA transfection. The results revealed a decrease in the CD32b levels in lipopolysaccharide (LPS)-treated M1 and an increase in interleukin-4 (IL-4)-treated M2 macrophages, as observed in macrophage Raw264.7 cells. Furthermore, CD32b siRNA transfection significantly downregulated the M2 markers (IL-10, VEGF, Arg-1, and STAT6), while upregulating the M1 markers (IL-6, NF-κB, NOS2, and STAT1) in the Raw264.7 cells. Similar findings were recapitulated in macrophage-rich adherent cells isolated from mouse spleens. Additionally, the cytopathological analysis of pleural effusions and ascitic fluids from patients with cancer revealed a positive correlation between advanced tumor stages, metastasis, and elevated CD32b levels. In conclusion, this study highlights the regulatory influence of CD32b in suppressing M1 expression and promoting M2 polarization. Moreover, heightened M2 activation and CD32b levels appear to correlate with tumor progression. A targeted CD32b blockade may serve as a novel therapeutic strategy to inhibit M2 macrophage polarization and is promising for anti-tumor intervention.

Published
2024
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45. CDK4/6 inhibition augments anti-tumor efficacy of XPO1 inhibitor selinexor in natural killer/T-cell lymphoma

Author

Wang, Yali, Chen, Jianfeng, Gao, Yan, Chai, Kelila Xin Ye, Hong, Jing Han, Wang, Peili, Chen, Jinghong, Yu, Zhaoliang, Liu, Lizhen, Huang, Cheng, Taib, Nur Ayuni Muhammad, Lim, Kerry May Huifen, Guan, Peiyong, Chan, Jason Yongsheng, Huang, Dachuan, Teh, Bin Tean, Li, Wenyu, Lim, Soon Thye, Yu, Qiang, Ong, Choon Kiat, Huang, Huiqiang, and Tan, Jing

Published
2024
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