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305. Differential distribution and prognostic value of CD4+ T cell subsets before and after radioactive iodine therapy in differentiated thyroid cancer with varied curative outcomes

Author

Shi, Zhi-Yong, primary, Zhang, Sheng-Xiao, additional, Li, Cai-Hong, additional, Fan, Di, additional, Xue, Yan, additional, Cheng, Zhe-Hao, additional, Wu, Li-Xiang, additional, Lu, Ke-Yi, additional, Wu, Zhi-Fang, additional, Li, Xiao-Feng, additional, Liu, Hai-Yan, additional, and Li, Si-Jin, additional

Published
2022
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312. Mediation effect of perceived social support and psychological distress between psychological resilience and sleep quality among Chinese medical staff

Author

Nannan Wu, Fan Ding, Bo Ai, Ronghua Zhang, and Yaoyao Cai

Subjects
Medicine, Science
Abstract

Abstract Sleep quality is crucial for the personal well-being of healthcare professionals and the health outcomes of their patients. This study aims to explore the relationship between psychological resilience (PR), perceived social support (PSS), psychological distress (comprising anxiety,depression,and stress), and sleep quality. It also examines whether PSS and psychological distress function as chain mediators between PR and sleep quality. A cross-sectional online survey was conducted using a convenient sampling method, with 454 participants included. The survey instruments included the Connor and Davidson Resilience Scale, the Perceived Social Support Scale, the 21-item Depression Anxiety Stress Scale, and the Pittsburgh Sleep Quality Index. Structural equation modeling revealed that PR significantly predicted sleep quality of Chinese medical staff. Psychological distress was identified as a mediating factor between PR and sleep quality. However, PSS did not directly mediate the relationship between PR and sleep quality. Instead, PSS and psychological distress were found to play a chain mediating role in the relationship between PR and sleep quality. This study provides new insights into the impact of PR on sleep quality, highlights the importance of PSS and psychological distress, and suggests practical implications for enhancing sleep quality among medical staff.

Published
2024
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318. Integration of Dual Targeting and Dual Therapeutic Modules Endows Self-Assembled Nanoparticles with Anti-Tumor Growth and Metastasis Functions

Author

Xiaoding Lou, Jun Jun Wu, Quan Wang, Wenwen Wang, Xiyuan Dong, Shixuan Wang, Xiaoqi Dong, Biao Chen, Jun Dai, Meng Huang Wu, and Fan Di Xia

Subjects
Polymers, Nanofibers, Pharmaceutical Science, Peptide, 02 engineering and technology, 01 natural sciences, HeLa, Neoplasms, Drug Discovery, Tumor Microenvironment, modular peptide, Neoplasm Metastasis, Cytotoxicity, Original Research, chemistry.chemical_classification, Mice, Inbred BALB C, Principal Component Analysis, biology, Chemistry, General Medicine, 021001 nanoscience & nanotechnology, Cell biology, Matrix Metalloproteinase 2, Nanomedicine, Female, 0210 nano-technology, Intracellular, anti-metastasis, Cell Survival, Biophysics, Mice, Nude, Antineoplastic Agents, Bioengineering, transcriptome sequencing, 010402 general chemistry, Biomaterials, In vivo, Cell Line, Tumor, Animals, Humans, Neoplasm Invasiveness, nanofiber, anti-tumor, Cell Proliferation, Tumor microenvironment, Organic Chemistry, biology.organism_classification, In vitro, 0104 chemical sciences, Nanoparticles, Peptides, Reactive Oxygen Species, Transcriptome, HeLa Cells
Abstract

Object High targeting and efficient cytotoxicity toward tumor cells endow NPs excellent anti-tumor activity. Herein, a peptide polymer possessing dual-targeting ability and double therapeutic activity was developed and named TGMF, which can form NPs through self-assembly. It is composed of four functional modules: 1) Active targeting peptide TMTP1 (T) deliver NPs to tumors specifically; 2) Therapeutic peptide GO-203 (G), which can significantly inhibit tumor growth by disrupting the redox balance in cells; 3) A passively targeted enzyme-responsive peptide PLGLGA (M), which can be cleaved specifically by metalloproteinase-2 (MMP-2) highly expressed in the tumor microenvironment (TME); and 4) Hexadecyl (F), which has strong hydrophobicity, can promote the self-assembly of TGMF NPs. Methods Five modular peptide probes, namely, TGF, TMF, TGM, GMF, and TGMF were synthesized and self-assembled into NPs in solution. The characterization, enzyme reactivity, and cytotoxicity of NPs were evaluated in vitro, and the pharmacokinetics, bio-distribution, anti-tumor activity of NPs were investigated in vivo. In addition, transcriptome sequencing identified the intracellular signaling pathway-related genes involved in the anti-tumor effect of TGMF. Results Upon enzyme cleavage, two types of nanostructure, NPs and nanofibers (NFs), were detected under TEM. Moreover, the cytotoxicity and anti-invasion activity of TGMF against tumor cells used were strongest among the five modular probes examined in vitro. TGMF increased reactive oxygen species (ROS) levels in cytoplasm and produced numerous NFs in extracellular interval and intracellular space. Transcriptome sequencing revealed that TGMF caused 446 genes' down-regulation and 270 genes' up-regulation in HeLa cells. In vivo, TGMF has a good anti-tumor effect, effectively prolonging the survival time of HeLa-tumor-bearing mice without systemic side effects. Conclusion Integration of multiple functional modules into NPs could be a promising strategy for the future of nanomedicine design towards tumor treatment.

Published
2021
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320. Advancing literature review methodology through rigour, generativity, scope and transparency

Author

Fan, Di, Breslin, Dermot, Callahan, Jamie, Iszatt-White, Marian, Fan, Di, Breslin, Dermot, Callahan, Jamie, and Iszatt-White, Marian

Abstract

The International Journal of Management Reviews (IJMR) is proud to offer a special section for articles that address methods and methodologies associated with undertaking literature reviews. In this editorial, we share our goals and aspirations for this special section. Drawing upon the motivations and objectives set out in 2020 and 2021 IJMR editorials, this editorial first discusses what potential benefits such an ongoing special section can bring to management and organization research in the longer term. In the next two sections, we detail what editors expect to see in the submissions we receive, and we also elaborate on some general and specific publication criteria as to how editors and reviewers will assess submissions related to methodology discussion. We hope this editorial will help authors avoid the disappointment of a rejection and encourage them to develop rigorous, innovative and impactful methodological advances and discussion.

Published
2022

321. Research on the Design of Financial Management Model Based on SOM-PNN Driven by Digital Economy

Author

Fan, Di and Fan, Di

Abstract

This study proposes a novel financial risk prediction methodology by harnessing the power of self-organizing mapping (SOM) neural network and probabilistic neural network (PNN). The amalgamation of SOM and PNN's advantageous characteristics is seamlessly integrated into the algorithm posited within this paper. In order to collate and prognosticate data, the SOM network employs a two-dimensional topological framework comprising of two layers of neurons. Subsequently, the PNN model expeditiously furnishes the final classification outcomes by processing the output results obtained from the SOM model. The technique developed atop this composite model offers accelerated computation, effectively mitigates the impact of noisy samples, and significantly augments model accuracy. Finally, the effectiveness of the proposed method was demonstrated through a comprehensive financial risk analysis of listed companies from 2016 to 2020. The experimental results show that the SOM-PNN method has achieved high accuracy in predicting the financial difficulties experienced by traditional companies in the selected company samples, exceeding 85%. Especially when the sample data is insufficient, its accuracy reaches 80%, surpassing other algorithms. Statement: In the modern era, financial institutions use big data to perform background analysis and review, continuously optimize, and adjust, in order to introduce quantitative analysis methods into every link of risk management as far as possible. This allows financial institutions to quickly achieve balance in the game process of risk and income, and achieve Profit maximization in local or even more space.

Published
2022

322. Biomedical image analysis competitions: The state of current participation practice

Author

Eisenmann, Matthias, Reinke, Annika, Weru, Vivienn, Tizabi, Minu Dietlinde, Isensee, Fabian, Adler, Tim J., Godau, Patrick, Cheplygina, Veronika, Kozubek, Michal, Ali, Sharib, Gupta, Anubha, Kybic, Jan, Noble, Alison, de Solórzano, Carlos Ortiz, Pachade, Samiksha, Petitjean, Caroline, Sage, Daniel, Wei, Donglai, Wilden, Elizabeth, Alapatt, Deepak, Andrearczyk, Vincent, Baid, Ujjwal, Bakas, Spyridon, Balu, Niranjan, Bano, Sophia, Bawa, Vivek Singh, Bernal, Jorge, Bodenstedt, Sebastian, Casella, Alessandro, Choi, Jinwook, Commowick, Olivier, Daum, Marie, Depeursinge, Adrien, Dorent, Reuben, Egger, Jan, Eichhorn, Hannah, Engelhardt, Sandy, Ganz, Melanie, Girard, Gabriel, Hansen, Lasse, Heinrich, Mattias, Heller, Nicholas, Hering, Alessa, Huaulmé, Arnaud, Kim, Hyunjeong, Landman, Bennett, Li, Hongwei Bran, Li, Jianning, Ma, Jun, Martel, Anne, Martín-Isla, Carlos, Menze, Bjoern, Nwoye, Chinedu Innocent, Oreiller, Valentin, Padoy, Nicolas, Pati, Sarthak, Payette, Kelly, Sudre, Carole, van Wijnen, Kimberlin, Vardazaryan, Armine, Vercauteren, Tom, Wagner, Martin, Wang, Chuanbo, Yap, Moi Hoon, Yu, Zeyun, Yuan, Chun, Zenk, Maximilian, Zia, Aneeq, Zimmerer, David, Bao, Rina, Choi, Chanyeol, Cohen, Andrew, Dzyubachyk, Oleh, Galdran, Adrian, Gan, Tianyuan, Guo, Tianqi, Gupta, Pradyumna, Haithami, Mahmood, Ho, Edward, Jang, Ikbeom, Li, Zhili, Luo, Zhengbo, Lux, Filip, Makrogiannis, Sokratis, Müller, Dominik, Oh, Young-tack, Pang, Subeen, Pape, Constantin, Polat, Gorkem, Reed, Charlotte Rosalie, Ryu, Kanghyun, Scherr, Tim, Thambawita, Vajira, Wang, Haoyu, Wang, Xinliang, Xu, Kele, Yeh, Hung, Yeo, Doyeob, Yuan, Yixuan, Zeng, Yan, Zhao, Xin, Abbing, Julian, Adam, Jannes, Adluru, Nagesh, Agethen, Niklas, Ahmed, Salman, Khalil, Yasmina Al, Alenyà, Mireia, Alhoniemi, Esa, An, Chengyang, Anwar, Talha, Arega, Tewodros Weldebirhan, Avisdris, Netanell, Aydogan, Dogu Baran, Bai, Yingbin, Calisto, Maria Baldeon, Basaran, Berke Doga, Beetz, Marcel, Bian, Cheng, Bian, Hao, Blansit, Kevin, Bloch, Louise, Bohnsack, Robert, Bosticardo, Sara, Breen, Jack, Brudfors, Mikael, Brüngel, Raphael, Cabezas, Mariano, Cacciola, Alberto, Chen, Zhiwei, Chen, Yucong, Chen, Daniel Tianming, Cho, Minjeong, Choi, Min-Kook, Xie, Chuantao Xie Chuantao, Cobzas, Dana, Cohen-Adad, Julien, Acero, Jorge Corral, Das, Sujit Kumar, de Oliveira, Marcela, Deng, Hanqiu, Dong, Guiming, Doorenbos, Lars, Efird, Cory, Escalera, Sergio, Fan, Di, Serj, Mehdi Fatan, Fenneteau, Alexandre, Fidon, Lucas, Filipiak, Patryk, Finzel, René, Freitas, Nuno R., Friedrich, Christoph M., Fulton, Mitchell, Gaida, Finn, Galati, Francesco, Galazis, Christoforos, Gan, Chang Hee, Gao, Zheyao, Gao, Shengbo, Gazda, Matej, Gerats, Beerend, Getty, Neil, Gibicar, Adam, Gifford, Ryan, Gohil, Sajan, Grammatikopoulou, Maria, Grzech, Daniel, Güley, Orhun, Günnemann, Timo, Guo, Chunxu, Guy, Sylvain, Ha, Heonjin, Han, Luyi, Han, Il Song, Hatamizadeh, Ali, He, Tian, Heo, Jimin, Hitziger, Sebastian, Hong, SeulGi, Hong, SeungBum, Huang, Rian, Huang, Ziyan, Huellebrand, Markus, Huschauer, Stephan, Hussain, Mustaffa, Inubushi, Tomoo, Polat, Ece Isik, Jafaritadi, Mojtaba, Jeong, SeongHun, Jian, Bailiang, Jiang, Yuanhong, Jiang, Zhifan, Jin, Yueming, Joshi, Smriti, Kadkhodamohammadi, Abdolrahim, Kamraoui, Reda Abdellah, Kang, Inha, Kang, Junghwa, Karimi, Davood, Khademi, April, Khan, Muhammad Irfan, Khan, Suleiman A., Khantwal, Rishab, Kim, Kwang-Ju, Kline, Timothy, Kondo, Satoshi, Kontio, Elina, Krenzer, Adrian, Kroviakov, Artem, Kuijf, Hugo, Kumar, Satyadwyoom, La Rosa, Francesco, Lad, Abhi, Lee, Doohee, Lee, Minho, Lena, Chiara, Li, Hao, Li, Ling, Li, Xingyu, Liao, Fuyuan, Liao, KuanLun, Oliveira, Arlindo Limede, Lin, Chaonan, Lin, Shan, Linardos, Akis, Linguraru, Marius George, Liu, Han, Liu, Tao, Liu, Di, Liu, Yanling, Lourenço-Silva, João, Lu, Jingpei, Lu, Jiangshan, Luengo, Imanol, Lund, Christina B., Luu, Huan Minh, Lv, Yi, Macar, Uzay, Maechler, Leon, L., Sina Mansour, Marshall, Kenji, Mazher, Moona, McKinley, Richard, Medela, Alfonso, Meissen, Felix, Meng, Mingyuan, Miller, Dylan, Mirjahanmardi, Seyed Hossein, Mishra, Arnab, Mitha, Samir, Mohy-ud-Din, Hassan, Mok, Tony Chi Wing, Murugesan, Gowtham Krishnan, Karthik, Enamundram Naga, Nalawade, Sahil, Nalepa, Jakub, Naser, Mohamed, Nateghi, Ramin, Naveed, Hammad, Nguyen, Quang-Minh, Quoc, Cuong Nguyen, Nichyporuk, Brennan, Oliveira, Bruno, Owen, David, Pal, Jimut Bahan, Pan, Junwen, Pan, Wentao, Pang, Winnie, Park, Bogyu, Pawar, Vivek, Pawar, Kamlesh, Peven, Michael, Philipp, Lena, Pieciak, Tomasz, Plotka, Szymon, Plutat, Marcel, Pourakpour, Fattaneh, Preložnik, Domen, Punithakumar, Kumaradevan, Qayyum, Abdul, Queirós, Sandro, Rahmim, Arman, Razavi, Salar, Ren, Jintao, Rezaei, Mina, Rico, Jonathan Adam, Rieu, ZunHyan, Rink, Markus, Roth, Johannes, Ruiz-Gonzalez, Yusely, Saeed, Numan, Saha, Anindo, Salem, Mostafa, Sanchez-Matilla, Ricardo, Schilling, Kurt, Shao, Wei, Shen, Zhiqiang, Shi, Ruize, Shi, Pengcheng, Sobotka, Daniel, Soulier, Théodore, Fadida, Bella Specktor, Stoyanov, Danail, Mun, Timothy Sum Hon, Sun, Xiaowu, Tao, Rong, Thaler, Franz, Théberge, Antoine, Thielke, Felix, Torres, Helena, Wahid, Kareem A., Wang, Jiacheng, Wang, YiFei, Wang, Wei, Wang, Xiong, Wen, Jianhui, Wen, Ning, Wodzinski, Marek, Wu, Ye, Xia, Fangfang, Xiang, Tianqi, Xiaofei, Chen, Xu, Lizhan, Xue, Tingting, Yang, Yuxuan, Yang, Lin, Yao, Kai, Yao, Huifeng, Yazdani, Amirsaeed, Yip, Michael, Yoo, Hwanseung, Yousefirizi, Fereshteh, Yu, Shunkai, Yu, Lei, Zamora, Jonathan, Zeineldin, Ramy Ashraf, Zeng, Dewen, Zhang, Jianpeng, Zhang, Bokai, Zhang, Jiapeng, Zhang, Fan, Zhang, Huahong, Zhao, Zhongchen, Zhao, Zixuan, Zhao, Jiachen, Zhao, Can, Zheng, Qingshuo, Zhi, Yuheng, Zhou, Ziqi, Zou, Baosheng, Maier-Hein, Klaus, Jäger, Paul F., Kopp-Schneider, Annette, Maier-Hein, Lena, Eisenmann, Matthias, Reinke, Annika, Weru, Vivienn, Tizabi, Minu Dietlinde, Isensee, Fabian, Adler, Tim J., Godau, Patrick, Cheplygina, Veronika, Kozubek, Michal, Ali, Sharib, Gupta, Anubha, Kybic, Jan, Noble, Alison, de Solórzano, Carlos Ortiz, Pachade, Samiksha, Petitjean, Caroline, Sage, Daniel, Wei, Donglai, Wilden, Elizabeth, Alapatt, Deepak, Andrearczyk, Vincent, Baid, Ujjwal, Bakas, Spyridon, Balu, Niranjan, Bano, Sophia, Bawa, Vivek Singh, Bernal, Jorge, Bodenstedt, Sebastian, Casella, Alessandro, Choi, Jinwook, Commowick, Olivier, Daum, Marie, Depeursinge, Adrien, Dorent, Reuben, Egger, Jan, Eichhorn, Hannah, Engelhardt, Sandy, Ganz, Melanie, Girard, Gabriel, Hansen, Lasse, Heinrich, Mattias, Heller, Nicholas, Hering, Alessa, Huaulmé, Arnaud, Kim, Hyunjeong, Landman, Bennett, Li, Hongwei Bran, Li, Jianning, Ma, Jun, Martel, Anne, Martín-Isla, Carlos, Menze, Bjoern, Nwoye, Chinedu Innocent, Oreiller, Valentin, Padoy, Nicolas, Pati, Sarthak, Payette, Kelly, Sudre, Carole, van Wijnen, Kimberlin, Vardazaryan, Armine, Vercauteren, Tom, Wagner, Martin, Wang, Chuanbo, Yap, Moi Hoon, Yu, Zeyun, Yuan, Chun, Zenk, Maximilian, Zia, Aneeq, Zimmerer, David, Bao, Rina, Choi, Chanyeol, Cohen, Andrew, Dzyubachyk, Oleh, Galdran, Adrian, Gan, Tianyuan, Guo, Tianqi, Gupta, Pradyumna, Haithami, Mahmood, Ho, Edward, Jang, Ikbeom, Li, Zhili, Luo, Zhengbo, Lux, Filip, Makrogiannis, Sokratis, Müller, Dominik, Oh, Young-tack, Pang, Subeen, Pape, Constantin, Polat, Gorkem, Reed, Charlotte Rosalie, Ryu, Kanghyun, Scherr, Tim, Thambawita, Vajira, Wang, Haoyu, Wang, Xinliang, Xu, Kele, Yeh, Hung, Yeo, Doyeob, Yuan, Yixuan, Zeng, Yan, Zhao, Xin, Abbing, Julian, Adam, Jannes, Adluru, Nagesh, Agethen, Niklas, Ahmed, Salman, Khalil, Yasmina Al, Alenyà, Mireia, Alhoniemi, Esa, An, Chengyang, Anwar, Talha, Arega, Tewodros Weldebirhan, Avisdris, Netanell, Aydogan, Dogu Baran, Bai, Yingbin, Calisto, Maria Baldeon, Basaran, Berke Doga, Beetz, Marcel, Bian, Cheng, Bian, Hao, Blansit, Kevin, Bloch, Louise, Bohnsack, Robert, Bosticardo, Sara, Breen, Jack, Brudfors, Mikael, Brüngel, Raphael, Cabezas, Mariano, Cacciola, Alberto, Chen, Zhiwei, Chen, Yucong, Chen, Daniel Tianming, Cho, Minjeong, Choi, Min-Kook, Xie, Chuantao Xie Chuantao, Cobzas, Dana, Cohen-Adad, Julien, Acero, Jorge Corral, Das, Sujit Kumar, de Oliveira, Marcela, Deng, Hanqiu, Dong, Guiming, Doorenbos, Lars, Efird, Cory, Escalera, Sergio, Fan, Di, Serj, Mehdi Fatan, Fenneteau, Alexandre, Fidon, Lucas, Filipiak, Patryk, Finzel, René, Freitas, Nuno R., Friedrich, Christoph M., Fulton, Mitchell, Gaida, Finn, Galati, Francesco, Galazis, Christoforos, Gan, Chang Hee, Gao, Zheyao, Gao, Shengbo, Gazda, Matej, Gerats, Beerend, Getty, Neil, Gibicar, Adam, Gifford, Ryan, Gohil, Sajan, Grammatikopoulou, Maria, Grzech, Daniel, Güley, Orhun, Günnemann, Timo, Guo, Chunxu, Guy, Sylvain, Ha, Heonjin, Han, Luyi, Han, Il Song, Hatamizadeh, Ali, He, Tian, Heo, Jimin, Hitziger, Sebastian, Hong, SeulGi, Hong, SeungBum, Huang, Rian, Huang, Ziyan, Huellebrand, Markus, Huschauer, Stephan, Hussain, Mustaffa, Inubushi, Tomoo, Polat, Ece Isik, Jafaritadi, Mojtaba, Jeong, SeongHun, Jian, Bailiang, Jiang, Yuanhong, Jiang, Zhifan, Jin, Yueming, Joshi, Smriti, Kadkhodamohammadi, Abdolrahim, Kamraoui, Reda Abdellah, Kang, Inha, Kang, Junghwa, Karimi, Davood, Khademi, April, Khan, Muhammad Irfan, Khan, Suleiman A., Khantwal, Rishab, Kim, Kwang-Ju, Kline, Timothy, Kondo, Satoshi, Kontio, Elina, Krenzer, Adrian, Kroviakov, Artem, Kuijf, Hugo, Kumar, Satyadwyoom, La Rosa, Francesco, Lad, Abhi, Lee, Doohee, Lee, Minho, Lena, Chiara, Li, Hao, Li, Ling, Li, Xingyu, Liao, Fuyuan, Liao, KuanLun, Oliveira, Arlindo Limede, Lin, Chaonan, Lin, Shan, Linardos, Akis, Linguraru, Marius George, Liu, Han, Liu, Tao, Liu, Di, Liu, Yanling, Lourenço-Silva, João, Lu, Jingpei, Lu, Jiangshan, Luengo, Imanol, Lund, Christina B., Luu, Huan Minh, Lv, Yi, Macar, Uzay, Maechler, Leon, L., Sina Mansour, Marshall, Kenji, Mazher, Moona, McKinley, Richard, Medela, Alfonso, Meissen, Felix, Meng, Mingyuan, Miller, Dylan, Mirjahanmardi, Seyed Hossein, Mishra, Arnab, Mitha, Samir, Mohy-ud-Din, Hassan, Mok, Tony Chi Wing, Murugesan, Gowtham Krishnan, Karthik, Enamundram Naga, Nalawade, Sahil, Nalepa, Jakub, Naser, Mohamed, Nateghi, Ramin, Naveed, Hammad, Nguyen, Quang-Minh, Quoc, Cuong Nguyen, Nichyporuk, Brennan, Oliveira, Bruno, Owen, David, Pal, Jimut Bahan, Pan, Junwen, Pan, Wentao, Pang, Winnie, Park, Bogyu, Pawar, Vivek, Pawar, Kamlesh, Peven, Michael, Philipp, Lena, Pieciak, Tomasz, Plotka, Szymon, Plutat, Marcel, Pourakpour, Fattaneh, Preložnik, Domen, Punithakumar, Kumaradevan, Qayyum, Abdul, Queirós, Sandro, Rahmim, Arman, Razavi, Salar, Ren, Jintao, Rezaei, Mina, Rico, Jonathan Adam, Rieu, ZunHyan, Rink, Markus, Roth, Johannes, Ruiz-Gonzalez, Yusely, Saeed, Numan, Saha, Anindo, Salem, Mostafa, Sanchez-Matilla, Ricardo, Schilling, Kurt, Shao, Wei, Shen, Zhiqiang, Shi, Ruize, Shi, Pengcheng, Sobotka, Daniel, Soulier, Théodore, Fadida, Bella Specktor, Stoyanov, Danail, Mun, Timothy Sum Hon, Sun, Xiaowu, Tao, Rong, Thaler, Franz, Théberge, Antoine, Thielke, Felix, Torres, Helena, Wahid, Kareem A., Wang, Jiacheng, Wang, YiFei, Wang, Wei, Wang, Xiong, Wen, Jianhui, Wen, Ning, Wodzinski, Marek, Wu, Ye, Xia, Fangfang, Xiang, Tianqi, Xiaofei, Chen, Xu, Lizhan, Xue, Tingting, Yang, Yuxuan, Yang, Lin, Yao, Kai, Yao, Huifeng, Yazdani, Amirsaeed, Yip, Michael, Yoo, Hwanseung, Yousefirizi, Fereshteh, Yu, Shunkai, Yu, Lei, Zamora, Jonathan, Zeineldin, Ramy Ashraf, Zeng, Dewen, Zhang, Jianpeng, Zhang, Bokai, Zhang, Jiapeng, Zhang, Fan, Zhang, Huahong, Zhao, Zhongchen, Zhao, Zixuan, Zhao, Jiachen, Zhao, Can, Zheng, Qingshuo, Zhi, Yuheng, Zhou, Ziqi, Zou, Baosheng, Maier-Hein, Klaus, Jäger, Paul F., Kopp-Schneider, Annette, and Maier-Hein, Lena

Abstract

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps.

Published
2022

323. GPU-Net: Lightweight U-Net with more diverse features

Author

Yu, Heng, Fan, Di, Song, Weihu, Yu, Heng, Fan, Di, and Song, Weihu

Abstract

Image segmentation is an important task in the medical image field and many convolutional neural networks (CNNs) based methods have been proposed, among which U-Net and its variants show promising performance. In this paper, we propose GP-module and GPU-Net based on U-Net, which can learn more diverse features by introducing Ghost module and atrous spatial pyramid pooling (ASPP). Our method achieves better performance with more than 4 times fewer parameters and 2 times fewer FLOPs, which provides a new potential direction for future research. Our plug-and-play module can also be applied to existing segmentation methods to further improve their performance.

Published
2022

324. FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

Author

He, Chaoyang, Shah, Alay Dilipbhai, Tang, Zhenheng, Fan, Di, Sivashunmugam, Adarshan Naiynar, Bhogaraju, Keerti, Shimpi, Mita, Shen, Li, Chu, Xiaowen, Soltanolkotabi, Mahdi, Avestimehr, Salman, He, Chaoyang, Shah, Alay Dilipbhai, Tang, Zhenheng, Fan, Di, Sivashunmugam, Adarshan Naiynar, Bhogaraju, Keerti, Shimpi, Mita, Shen, Li, Chu, Xiaowen, Soltanolkotabi, Mahdi, and Avestimehr, Salman

Abstract

Federated Learning (FL) is a distributed learning paradigm that can learn a global or personalized model from decentralized datasets on edge devices. However, in the computer vision domain, model performance in FL is far behind centralized training due to the lack of exploration in diverse tasks with a unified FL framework. FL has rarely been demonstrated effectively in advanced computer vision tasks such as object detection and image segmentation. To bridge the gap and facilitate the development of FL for computer vision tasks, in this work, we propose a federated learning library and benchmarking framework, named FedCV, to evaluate FL on the three most representative computer vision tasks: image classification, image segmentation, and object detection. We provide non-I.I.D. benchmarking datasets, models, and various reference FL algorithms. Our benchmark study suggests that there are multiple challenges that deserve future exploration: centralized training tricks may not be directly applied to FL; the non-I.I.D. dataset actually downgrades the model accuracy to some degree in different tasks; improving the system efficiency of federated training is challenging given the huge number of parameters and the per-client memory cost. We believe that such a library and benchmark, along with comparable evaluation settings, is necessary to make meaningful progress in FL on computer vision tasks.

Published
2022

328. Activation of HIF-1[alpha] and LL-37 by commensal bacteria inhibits Candida albicans colonization

Author

Fan, Di, Coughlin, Laura A., Neubauer, Megan M., Kim, Jiwoong, Kim, Min Soo, Zhan, Xiaowei, Simms-Waldrip, Tiffany R., Xie, Yang, Hooper, Lora V., and Koh, Andrew Y.

Subjects
Microbiota (Symbiotic organisms) -- Physiological aspects -- Genetic aspects -- Research, DNA binding proteins -- Physiological aspects -- Research, Candida albicans -- Physiological aspects -- Genetic aspects -- Research, Biological sciences, Health
Abstract

Candida albicans colonization is required for invasive disease (1-3). Unlike humans, adult mice with mature intact gut microbiota are resistant to C. albicans gastrointestinal (GI) colonization (2, 4), but the factors that promote C. albicans colonization resistance are unknown. Here we demonstrate that commensal anaerobic bacteria--specifically clostridial Firmicutes (clusters IV and XIVa) and Bacteroidetes--are critical for maintaining C. albicans colonization resistance in mice. Using Bacteroides thetaiotamicron as a model organism, we find that hypoxia-inducible factor-1[alpha] (HIF-1[alpha]), a transcription factor important for activating innate immune effectors, and the antimicrobial peptide LL-37 (CRAMP in mice) are key determinants of C. albicans colonization resistance. Although antibiotic treatment enables C. albicans colonization, pharmacologic activation of colonic Hif1a induces CRAMP expression and results in a significant reduction of C. albicans GI colonization and a 50% decrease in mortality from invasive disease. In the setting of antibiotics, Hif1a and Camp (which encodes CRAMP) are required for B. thetaiotamicron-induced protection against C. albicans colonization of the gut. Thus, modulating C. albicans GI colonization by activation of gut mucosal immune effectors may represent a novel therapeutic approach for preventing invasive fungal disease in humans., Commensal fungi, mostly Candida spp., have been detected in the GI tracts of various mammals (5). Although reportedly 40-60% of humans are colonized with C. albicans (CA) in the GI [...]

Published
2015

329. Firm-specific political risk: a systematic investigation of its antecedents and implications for vertical integration and diversification strategies.

Author

Fan, Di and Xiao, Chengyong

Subjects
VERTICAL integration, SUPPLY chain management, ECONOMIC uncertainty, DIVERSIFICATION in industry, DATA libraries, REVERSE logistics
Abstract

Purpose: Uncertainties caused by political risks can drastically affect global supply chains. However, the supply chain management literature has thus far developed rather limited knowledge on firms' perception of and reactions to increased political risks. This study has two main purposes: to explore the relationship between extant risk exposure and perceived firm-specific political risk and to understand the impact of firm-specific political risk on firms' vertical integration and diversification strategies. Design/methodology/approach: The authors developed a unique dataset for testing our hypotheses. Specifically, the authors sampled manufacturers (SIC20-39) listed in the United States from 2002 to 2019. The authors collected financial and diversification data from Compustat, vertical integration data from the Frésard-Hoberg-Phillips Vertical Relatedness Data Library and political risk data from the Economic Policy Uncertainty database. This data collection process yielded 1,287 firms (8,329 observations) with available data for analysis. Findings: A two-way fixed-effect regression analysis of panel data revealed that firms tend to be more sensitive to political risk when faced with income stream uncertainty or strategic risk. By contrast, exposure to stock returns uncertainty does not significantly influence firms' sensitivity toward political risk. Moreover, firm-specific political risk is positively associated with vertical integration and product diversification. However, firm-specific political risk does not result in higher levels of geographical diversification. Originality/value: This study joins the literature that systematically explores the antecedents and implications of firm-specific political risk, thus broadening the scope of supply chain risk management. [ABSTRACT FROM AUTHOR]

Published
2023
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330. The role of business locations in international patenting.

Author

Fan, Di and Zhao, Long

Subjects
INDUSTRIAL location, INTERNATIONAL business enterprises, PATENTS, TECHNOLOGY transfer
Abstract

Despite the importance of international patenting in understanding technology diffusion across countries, it is unclear how business locations affect firms' international patenting behavior. This paper investigates the impact of business locations on international patenting using data from the Management, Organization and Innovation survey 2009 with a representative sample of 1508 firms from twelve countries. Several findings emerge from our analyses. First, firms outsourcing abroad tend to patent abroad but not at home. Second, firms are more likely to patent at home when facing foreign competitors. Third, when facing domestic competitors, firms are less likely to apply for patents. These findings imply that firms use patents to compete against foreign competitors. [ABSTRACT FROM AUTHOR]

Published
2023
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331. Smart cities and sustainable development.

Author

Su, Yiyi and Fan, Di

Subjects
SMART cities, GREEN technology, SUSTAINABLE development, FUZZY sets, ECOLOGICAL modernization
Abstract

The last two decades have witnessed a surge in interest in the smart–sustainable city, but it remains unclear how smart cities can achieve the multifaceted goals of sustainable development, such as ecological performance, human development and sustainability efficiency. This study performs a fuzzy-set qualitative comparative analysis (fsQCA) of 35 Chinese large smart cities through configurational theorizing of the smart–sustainable city nexus. The findings not only reveal the causal complexity of constructing smart cities to achieve urban sustainability, but also develop a taxonomy of smart city configurations leading to ecological performance or human development, namely, duplex-centric, eco-centric, human-centric and double-bind modes. [ABSTRACT FROM AUTHOR]

Published
2023
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335. The significance of pressure injuries and purpura in COVID-19 patients hospitalized at a large urban academic medical center: A retrospective cohort study

Author

Connie R. Shi, Kevin J. Moore, Zachary E. Holcomb, Fan Di Xia, Daniela Kroshinsky, Hannah Song, Daniel A. Yanes, Jennifer A. Lo, Colleen K. Gabel, Virginia A. Triant, Christopher Iriarte, Rajesh T. Gandhi, Renajd Rrapi, Sarah Song, and Sidharth Chand

Subjects
Adult, Male, medicine.medical_specialty, 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), novel coronavirus, Dermatology, pressure injury, Article, skin manifestation, Hospitals, Urban, Intubation, Intratracheal, Prone Position, medicine, Humans, Purpura, Aged, Retrospective Studies, Pressure Ulcer, Academic Medical Centers, Pressure injury, SARS-CoV-2, business.industry, pandemic, Incidence, Incidence (epidemiology), COVID-19, Retrospective cohort study, Length of Stay, Middle Aged, Emergency medicine, Female, medicine.symptom, business
Published
2021
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338. Dynamic Immune Function Changes Before and After the First Radioactive Iodine Therapy After Total Resection of Differentiated Thyroid Carcinoma

Author

Shi, Zhi-Yong, primary, Zhang, Sheng-Xiao, additional, Fan, Di, additional, Li, Cai-Hong, additional, Cheng, Zhe-Hao, additional, Xue, Yan, additional, Wu, Li-Xiang, additional, Lu, Ke-Yi, additional, Yang, Su-Yun, additional, Cheng, Yan, additional, Wu, Zhi-Fang, additional, Gao, Chong, additional, Li, Xiao-Feng, additional, Liu, Hai-Yan, additional, and Li, Si-Jin, additional

Published
2022
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