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101. OA14.03 Garsorasib in KRAS G12C-Mutated Non-Small-Cell Lung Cancer: Updated Results from a Phase 2 Study

Author

Li, Z., Lu, S., Dang, X., Huang, D., Jin, S., Li, W., Shi, J., Wang, X., Zhang, Y., Song, Z., Zhang, J., Zhuang, W., Liu, X., Jiang, L., Meng, X., Zhao, M., Zhou, J., Zhang, L., Wang, P., Luo, H., Yang, J., Cang, S., Wang, J., Cui, J., Yu, Y., Zhang, Z., Lu, J., Yang, W., Li, G., Feng, J., Lv, D., Wu, L., Fang, Y., Wang, Y., Zhao, Y., Cao, B., Zhu, W., Zhuang, Z., Li, Q., Wang, M., Zhou, H., Dong, X., Hu, S., Fang, J., Xu, C.-W., Wang, W., Xiang, Z., and Shi, Z.

Published
2024
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106. The TianQin project: Current progress on science and technology

Author

Mei, J, Bai, Y, Bao, J, Barausse, E, Cai, L, Canuto, E, Cao, B, Chen, W, Chen, Y, Ding, Y, Duan, H, Fan, H, Feng, W, Fu, H, Gao, Q, Gao, T, Gong, Y, Gou, X, Gu, C, Gu, D, He, Z, Hendry, M, Hong, W, Hu, X, Hu, Y, Huang, S, Huang, X, Jiang, Q, Jiang, Y, Jiang, Z, Jin, H, Korol, V, Li, H, Li, M, Li, P, Li, R, Li, Y, Li, Z, Liang, Y, Liang, Z, Liao, F, Liu, Q, Liu, S, Liu, Y, Liu, L, Liu, P, Liu, X, Lu, X, Lu, Y, Lu, Z, Luo, Y, Luo, Z, Milyukov, V, Ming, M, Pi, X, Qin, C, Qu, S, Sesana, A, Shao, C, Shi, C, Su, W, Tan, D, Tan, Y, Tan, Z, Tu, L, Wang, B, Wang, C, Wang, F, Wang, G, Wang, H, Wang, J, Wang, L, Wang, P, Wang, X, Wang, Y, Wei, R, Wu, S, Xiao, C, Xu, X, Xue, C, Yang, F, Yang, L, Yang, M, Yang, S, Ye, B, Yeh, H, Yu, S, Zhai, D, Zhang, C, Zhang, H, Zhang, J, Zhang, L, Zhang, X, Zhou, H, Zhou, M, Zhou, Z, Zhu, D, Zi, T, Luo, J, Mei J., Bai Y. -Z., Bao J., Barausse E., Cai L., Canuto E., Cao B., Chen W. -M., Chen Y., DIng Y. -W., Duan H. -Z., Fan H., Feng W. -F., Fu H., Gao Q., Gao T., Gong Y., Gou X., Gu C. -Z., Gu D. -F., He Z. -Q., Hendry M., Hong W., Hu X. -C., Hu Y. -M., Hu Y., Huang S. -J., Huang X. -Q., Jiang Q., Jiang Y. -Z., Jiang Y., Jiang Z., Jin H. -M., Korol V., Li H. -Y., Li M., Li P., Li R., Li Y., Li Z., Li Z. -X., Liang Y. -R., Liang Z. -C., Liao F. -J., Liu Q., Liu S., Liu Y. -C., Liu L., Liu P. -B., Liu X., Liu Y., Lu X. -F., Lu Y., Lu Z. -H., Luo Y., Luo Z. -C., Milyukov V., Ming M., Pi X., Qin C., Qu S. -B., Sesana A., Shao C., Shi C., Su W., Tan D. -Y., Tan Y., Tan Z., Tu L. -C., Wang B., Wang C. -R., Wang F., Wang G. -F., Wang H., Wang J., Wang L., Wang P., Wang X., Wang Y., Wang Y. -F., Wei R., Wu S. -C., Xiao C. -Y., Xu X. -S., Xue C., Yang F. -C., Yang L., Yang M. -L., Yang S. -Q., Ye B., Yeh H. -C., Yu S., Zhai D., Zhang C., Zhang H., Zhang J. -D., Zhang J., Zhang L., Zhang X., Zhou H., Zhou M. -Y., Zhou Z. -B., Zhu D. -D., Zi T. -G., Luo J., Mei, J, Bai, Y, Bao, J, Barausse, E, Cai, L, Canuto, E, Cao, B, Chen, W, Chen, Y, Ding, Y, Duan, H, Fan, H, Feng, W, Fu, H, Gao, Q, Gao, T, Gong, Y, Gou, X, Gu, C, Gu, D, He, Z, Hendry, M, Hong, W, Hu, X, Hu, Y, Huang, S, Huang, X, Jiang, Q, Jiang, Y, Jiang, Z, Jin, H, Korol, V, Li, H, Li, M, Li, P, Li, R, Li, Y, Li, Z, Liang, Y, Liang, Z, Liao, F, Liu, Q, Liu, S, Liu, Y, Liu, L, Liu, P, Liu, X, Lu, X, Lu, Y, Lu, Z, Luo, Y, Luo, Z, Milyukov, V, Ming, M, Pi, X, Qin, C, Qu, S, Sesana, A, Shao, C, Shi, C, Su, W, Tan, D, Tan, Y, Tan, Z, Tu, L, Wang, B, Wang, C, Wang, F, Wang, G, Wang, H, Wang, J, Wang, L, Wang, P, Wang, X, Wang, Y, Wei, R, Wu, S, Xiao, C, Xu, X, Xue, C, Yang, F, Yang, L, Yang, M, Yang, S, Ye, B, Yeh, H, Yu, S, Zhai, D, Zhang, C, Zhang, H, Zhang, J, Zhang, L, Zhang, X, Zhou, H, Zhou, M, Zhou, Z, Zhu, D, Zi, T, Luo, J, Mei J., Bai Y. -Z., Bao J., Barausse E., Cai L., Canuto E., Cao B., Chen W. -M., Chen Y., DIng Y. -W., Duan H. -Z., Fan H., Feng W. -F., Fu H., Gao Q., Gao T., Gong Y., Gou X., Gu C. -Z., Gu D. -F., He Z. -Q., Hendry M., Hong W., Hu X. -C., Hu Y. -M., Hu Y., Huang S. -J., Huang X. -Q., Jiang Q., Jiang Y. -Z., Jiang Y., Jiang Z., Jin H. -M., Korol V., Li H. -Y., Li M., Li P., Li R., Li Y., Li Z., Li Z. -X., Liang Y. -R., Liang Z. -C., Liao F. -J., Liu Q., Liu S., Liu Y. -C., Liu L., Liu P. -B., Liu X., Liu Y., Lu X. -F., Lu Y., Lu Z. -H., Luo Y., Luo Z. -C., Milyukov V., Ming M., Pi X., Qin C., Qu S. -B., Sesana A., Shao C., Shi C., Su W., Tan D. -Y., Tan Y., Tan Z., Tu L. -C., Wang B., Wang C. -R., Wang F., Wang G. -F., Wang H., Wang J., Wang L., Wang P., Wang X., Wang Y., Wang Y. -F., Wei R., Wu S. -C., Xiao C. -Y., Xu X. -S., Xue C., Yang F. -C., Yang L., Yang M. -L., Yang S. -Q., Ye B., Yeh H. -C., Yu S., Zhai D., Zhang C., Zhang H., Zhang J. -D., Zhang J., Zhang L., Zhang X., Zhou H., Zhou M. -Y., Zhou Z. -B., Zhu D. -D., Zi T. -G., and Luo J.

Abstract

TianQin is a planned space-based gravitational wave (GW) observatory consisting of three Earth-orbiting satellites with an orbital radius of about $10^5 , { m km}$. The satellites will form an equilateral triangle constellation the plane of which is nearly perpendicular to the ecliptic plane. TianQin aims to detect GWs between $10^{-4} , { m Hz}$ and $1 , { m Hz}$ that can be generated by a wide variety of important astrophysical and cosmological sources, including the inspiral of Galactic ultra-compact binaries, the inspiral of stellar-mass black hole binaries, extreme mass ratio inspirals, the merger of massive black hole binaries, and possibly the energetic processes in the very early universe and exotic sources such as cosmic strings. In order to start science operations around 2035, a roadmap called the 0123 plan is being used to bring the key technologies of TianQin to maturity, supported by the construction of a series of research facilities on the ground. Two major projects of the 0123 plan are being carried out. In this process, the team has created a new-generation $17 , { m cm}$ single-body hollow corner-cube retro-reflector which was launched with the QueQiao satellite on 21 May 2018; a new laser-ranging station equipped with a $1.2 , { m m}$ telescope has been constructed and the station has successfully ranged to all five retro-reflectors on the Moon; and the TianQin-1 experimental satellite was launched on 20 December 2019 - the first-round result shows that the satellite has exceeded all of its mission requirements.

Published
2021

110. Traditional Chinese Medicine Astragalus Polysaccharide Enhanced Antitumor Effects of the Angiogenesis Inhibitor Apatinib in Pancreatic Cancer Cells on Proliferation, Invasiveness, and Apoptosis [Corrigendum]

Author

Wu J, Wang J, Su Q, Ding W, Li T, Yu J, and Cao B

Subjects
pancreatic cancer, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, apatinib, aps, RC254-282
Abstract

Wu J, Wang J, Su Q, et al. Onco Targets Ther. 2018;11:2685–2698. The authors have advised the incorrect images were inadvertently selected for Figure 2A, on page 2690, due to the dark background and relatively low resolution of photos captured for the wound healing assay. For Figure 3A on page 2691, all Transwell images were captured and saved in one folder labelled by experimental date. Two overlapping images from different visual fields were captured from one well but labelled incorrectly and inadvertently selected for Figure 3A. The correct Figures 2 and 3 are shown in Download Article. The authors apologize for these errors and advise they do not affect the results of the paper. Read the original article

Published
2022

111. Measurement of the charge asymmetry for the KS → πeν decay and test of CPT symmetry with the KLOE detector

Author

The KLOE-2 collaboration, Anastasi, A., Babusci, D., Berlowski, M., Bloise, C., Bossi, F., Branchini, P., Budano, A., Cao, B., Capon, G., Ceradini, F., Ciambrone, P., Curciarello, F., Czerwinski, E., D’Agostini, G., Danè, E., De Leo, V., De Lucia, E., De Santis, A., De Simone, P., Di Cicco, A., Di Domenico, A., Domenici, D., D’Uffizi, A., Fantini, A., Fantini, G., Fermani, P., Fiore, S., Gajos, A., Gauzzi, P., Giovannella, S., Graziani, E., Ivanov, V. L., Johansson, T., Kang, X., Kisielewska-Kaminska, D., Kozyrev, E. A., Krzemien, W., Kupsć, A., Loffredo, S., Lukin, P. A., Mandaglio, G., Martini, M., Messi, R., Miscetti, S., Moricciani, D., Moskal, P., Passeri, A., Patera, V., Perez del Rio, E., Raha, N., Santangelo, P., Schioppa, M., Selce, A., Silarski, M., Sirghi, F., Solodov, E. P., Tortora, L., Venanzoni, G., Wislicki, W., and Wolke, M.

Published
2018
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112. Microencapsulated sodium silicate for self-healing cement-based in-ground barriers

Author

Cao, B, Souza, L, and Al-Tabbaa, A

Abstract

In-ground vertical barriers are one of the most commonly-used contaminated land remediation technologies to prevent the migration of contaminants. Despite the popularity of in-ground barriers, problems related to their durability and mechanical properties impact serviceability, leading to the need for urgent repair. In-ground barrier materials, therefore, need to be more resilient, so that their whole life carbon emissions and whole life costs can be significantly reduced. Self-healing methodologies, including microencapsulated minerals, have been developed over recent years, with the focus on concrete. The mechanism of self-healing microencapsulation system is that when cracks propagate in the matrix, they rupture the capsules, leading to the release of healing agents into the crack volume. In this study, microencapsulated sodium silicate was incorporated in in-ground barrier materials and the mineral reacts with the calcium hydroxide in the cementitious matrix to form the calcium-silicate-hydrate gel. The characterisation of two different microcapsules and their effects on the properties of in-ground barrier materials were presented. Self-healing efficacy of in-ground barrier materials was examined in terms of crack sealing and the recovery of mechanical properties.

Published
2022
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114. Precision measurement of the η → π + π − π 0 Dalitz plot distribution with the KLOE detector

Author

Anastasi, A., Babusci, D., Bencivenni, G., Berlowski, M., Bloise, C., Bossi, F., Branchini, P., Budano, A., Caldeira Balkeståhl, L., Cao, B., Ceradini, F., Ciambrone, P., Curciarello, F., Czerwinski, E., D’Agostini, G., Danè, E., De Leo, V., De Lucia, E., De Santis, A., De Simone, P., Di Cicco, A., Di Domenico, A., Di Salvo, R., Domenici, D., D’Uffizi, A., Fantini, A., Felici, G., Fiore, S., Gajos, A., Gauzzi, P., Giardina, G., Giovannella, S., Graziani, E., Happacher, F., Heijkenskjöld, L., Ikegami Andersson, W., Johansson, T., Kaminska, D., Krzemien, W., Kupsc, A., Loffredo, S., Mandaglio, G., Martini, M., Mascolo, M., Messi, R., Miscetti, S., Morello, G., Moricciani, D., Moskal, P., Papenbrock, M., Passeri, A., Patera, V., Perez del Rio, E., Ranieri, A., Santangelo, P., Sarra, I., Schioppa, M., Silarski, M., Sirghi, F., Tortora, L., Venanzoni, G., Wislicki, W., Wolke, M., and The KLOE-2 collaboration

Published
2016
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115. Acetone Extract of Cornus officinalis Leaves Exerts Anti-Melanoma Effects via Inhibiting STAT3 Signaling

Author

Xu R, Zeng M, Wu Y, Wang S, Zhang B, Zhang J, Kan Y, Li B, Cao B, Zheng X, and Feng W

Subjects
angiogenesis, cornus officinalis, melanoma, apoptosis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, stat3, RC254-282
Abstract

Ruiqi Xu,1,2 Mengnan Zeng,1,2 Yuanyuan Wu,1,2 Shengchao Wang,1,2 Beibei Zhang,1,2 Jingke Zhang,1,2 Yuxuan Kan,1,2 Benke Li,1,2 Bing Cao,1,2 Xiaoke Zheng,1,2 Weisheng Feng1,2 1School of Pharmacy, Henan University of Traditional Chinese Medicine, Zhengzhou, People’s Republic of China; 2The Engineering and Technology Center for Chinese Medicine Development of Henan Province, Zhengzhou, People’s Republic of ChinaCorrespondence: Xiaoke Zheng; Weisheng FengSchool of Pharmacy, Henan University of Traditional Chinese Medicine, 156 Jinshui East Road, Zhengzhou, 450046, People’s Republic of ChinaTel +86-371-6019-0296Email zhengxk.2006@163.com; fwsh@hactcm.edu.cnPurpose: This research aims to investigate the intervention and mechanism of 50% acetone extract of C. officinalis leaves (SZYY) on melanoma xenografts.Patients and Methods: Tumor size and cardiac function were measured via ultrasound. The accumulation of 2-deoxy-D-glucose (2-DG) in tumor tissue was examined with near-infrared in vivo imaging. Flow cytometry was performed to assess apoptosis and reactive oxygen species (ROS) levels in tumor and immune cells in spleen. The levels of inflammatory cytokines in serum were detected by cytometric bead array. The expression of proliferation-, apoptosis-, and angiogenesis-related proteins in tumor cells was measured to evaluate the underlying mechanisms. Subsequently, the effects of four compounds separated from SZYY on the proliferation and migration of A375 cells and STAT3 signaling were examined. The peak identification and contents of the four components were performed via high-performance liquid chromatography (HPLC). Finally, we evaluated the inhibitory effects of STAT3 overexpression on the cytotoxic activity of four constituents in A375 cells.Results: SZYY inhibited the growth and glycolysis of melanoma xenograft in mice, improved cardiac function, increased the percentages of macrophages, neutrophils, and lymphocytes in spleen, reduced the levels of IL-6, IL-17A, TNF-α, and IFN-γ in serum, promoted apoptosis and oxidative stress in tumor tissues, and inhibited STAT3 phosphorylation and expression of angiogenic factors. Chemical analysis showed that SZYY is rich in loganin, rutin, triohimas C, and triohimas D, which all could restrain the proliferation and migration of A375 cells and inhibit the phosphorylation and nuclear translocation of STAT3. Moreover, STAT3 overexpression could diminish the cytotoxic activity of four compounds on A375 cells.Conclusion: SZYY could exert anti-melanoma effects via inhibiting STAT3 signaling to induce apoptosis and inhibit tumor angiogenesis. Its active ingredients might be loganin, rutin, triohimas C, and triohimas D.Keywords: Cornus officinalis, melanoma, STAT3, apoptosis, angiogenesis

Published
2021

118. Raltitrexed Enhances the Antitumor Effect of Apatinib in Human Esophageal Squamous Carcinoma Cells via Akt and Erk Pathways

Author

Zhen H, Li G, Zhao P, Zhang Y, Wang J, Yu J, and Cao B

Subjects
erk, akt, raltitrexed, escc, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, lcsh:RC254-282, apatinib, antitumor
Abstract

Hongchao Zhen,1 Guangxin Li,2 Pengfei Zhao,1 Ying Zhang,1 Jing Wang,1 Junxian Yu,3 Bangwei Cao1 1Cancer Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, People’s Republic of China; 2Radiation Oncology, Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, People’s Republic of China; 3Department of Pharmacy, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, People’s Republic of ChinaCorrespondence: Bangwei CaoCancer Center, Beijing Friendship Hospital, Capital Medical University, #95 Yong an Road, Xicheng District, Beijing 100050, People’s Republic of ChinaTel/Fax +86-10-63139325Email oncology@ccmu.edu.cnObjective: Apatinib has been proved effective in the treatment of advanced gastric cancer and a variety of solid tumors. Raltitrexed is emerging as a promising alternative for treating advanced colorectal cancer in China. This work aims to study the combinatory antitumor effect of apatinib and raltitrexed on human esophageal squamous carcinoma cells (ESCC).Materials and Methods: Two VEGFR-2-positive human ESCC lines, KYSE-30 and TE-1, were treated with apatinib or raltitrexed, or both, then the cell proliferation rate was measured by MTS assay; cell migration and invasion were studied by transwell assays; cell apoptosis rate was determined by flow cytometry; cellular autophagy level affected was analyzed by Western blot analysis; finally, quantitative polymerase chain reaction (qPCR) was used to monitor transcription and Western blot was performed to check phosphorylation of apoptotic proteins after treatment.Results: Both apatinib and raltitrexed significantly inhibited KYSE-30 and TE-1 cell proliferation in a dose-dependent manner. Treatment with both drugs showed enhanced inhibitory effects on cell proliferation, migration, and invasiveness compared with apatinib monotherapy. Apoptosis percentages in both cell lines were also remarkably increased by the combined treatment. Moreover, the combination of apatinib and raltitrexed down-regulated mRNA level of the anti-apoptotic protein Bcl-2, while up-regulated pro-apoptotic protein PARP, Bax, and caspase-3 transcription. Western blot analysis showed that phosphorylation levels of Erk, Akt, and invasiveness-associated protein matrix metalloproteinases-9 (MMP-9) were decreased in the combination group.Conclusion: Taken together, these results indicate that raltitrexed enhances the antitumor effects of apatinib on human ESCC cells by down-regulating phosphorylation of Akt and Erk, implying a combination of raltitrexed and apatinib might be an effective option for treating esophageal squamous cell carcinoma patients.Keywords: raltitrexed, apatinib, antitumor, ESCC, Akt, Erk

Published
2020

119. Erratum to: Precision tests of quantum mechanics and $$ \mathcal{CPT} $$ symmetry with entangled neutral kaons at KLOE

Author

Babusci, D., Berlowski, M., Bloise, C., Bossi, F., Branchini, P., Budano, A., Cao, B., Ceradini, F., Ciambrone, P., Curciarello, F., Czerwiński, E., D’Agostini, G., D’Amico, R., Danè, E., De Leo, V., De Lucia, E., De Santis, A., De Simone, P., Di Cicco, A., Di Domenico, A., Diociaiuti, E., Domenici, D., D’Uffizi, A., Fantini, A., Fantini, G., Fermani, P., Fiore, S., Gajos, A., Gauzzi, P., Giovannella, S., Graziani, E., Ivanov, V., Johansson, T., Kang, X., Kisielewska-Kamińska, D., Kozyrev, E., Krzemien, W., Kupsc, A., Lukin, P., Mandaglio, G., Martini, M., Messi, R., Miscetti, S., Moricciani, D., Moskal, P., Passeri, A., Patera, V., Perez del Rio, E., Santangelo, P., Schioppa, M., Selce, A., Silarski, M., Sirghi, F., Solodov, E., Tortora, L., Venanzoni, G., Wiślicki, W., and Wolke, M.

Subjects
Nuclear and High Energy Physics
Published
2022

120. The RNA-binding protein SRSF3 has an essential role in megakaryocyte maturation and platelet production

Author

Heazlewood, SY, Ahmad, T, Mohenska, M, Guo, BB, Gangatirkar, P, Josefsson, EC, Ellis, SL, Ratnadiwakara, M, Cao, H, Cao, B, Heazlewood, CK, Williams, B, Fulton, M, White, JF, Ramialison, M, Nilsson, SK, Anko, M-L, Heazlewood, SY, Ahmad, T, Mohenska, M, Guo, BB, Gangatirkar, P, Josefsson, EC, Ellis, SL, Ratnadiwakara, M, Cao, H, Cao, B, Heazlewood, CK, Williams, B, Fulton, M, White, JF, Ramialison, M, Nilsson, SK, and Anko, M-L

Abstract

RNA processing is increasingly recognized as a critical control point in the regulation of different hematopoietic lineages including megakaryocytes responsible for the production of platelets. Platelets are anucleate cytoplasts that contain a rich repertoire of RNAs encoding proteins with essential platelet functions derived from the parent megakaryocyte. It is largely unknown how RNA binding proteins contribute to the development and functions of megakaryocytes and platelets. We show that serine-arginine-rich splicing factor 3 (SRSF3) is essential for megakaryocyte maturation and generation of functional platelets. Megakaryocyte-specific deletion of Srsf3 in mice led to macrothrombocytopenia characterized by megakaryocyte maturation arrest, dramatically reduced platelet counts, and abnormally large functionally compromised platelets. SRSF3 deficient megakaryocytes failed to reprogram their transcriptome during maturation and to load platelets with RNAs required for normal platelet function. SRSF3 depletion led to nuclear accumulation of megakaryocyte mRNAs, demonstrating that SRSF3 deploys similar RNA regulatory mechanisms in megakaryocytes as in other cell types. Our study further suggests that SRSF3 plays a role in sorting cytoplasmic megakaryocyte RNAs into platelets and demonstrates how SRSF3-mediated RNA processing forms a central part of megakaryocyte gene regulation. Understanding SRSF3 functions in megakaryocytes and platelets provides key insights into normal thrombopoiesis and platelet pathologies as SRSF3 RNA targets in megakaryocytes are associated with platelet diseases.

Published
2022

121. FreeSurfer-based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for ENIGMA studies and other collaborative efforts

Author

Samann, PG, Iglesias, JE, Gutman, B, Grotegerd, D, Leenings, R, Flint, C, Dannlowski, U, Clarke-Rubright, EK, Morey, RA, van Erp, TGM, Whelan, CD, Han, LKM, van Velzen, LS, Cao, B, Augustinack, JC, Thompson, PM, Jahanshad, N, Schmaal, L, Samann, PG, Iglesias, JE, Gutman, B, Grotegerd, D, Leenings, R, Flint, C, Dannlowski, U, Clarke-Rubright, EK, Morey, RA, van Erp, TGM, Whelan, CD, Han, LKM, van Velzen, LS, Cao, B, Augustinack, JC, Thompson, PM, Jahanshad, N, and Schmaal, L

Abstract

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013-12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi-)genetics. Finally, we highlight points where FreeSurfer-based hippocampal subfield studies may be optimized.

Published
2022

122. Multiobjective Multiple Mobile Sink Scheduling via Evolutionary Fuzzy Rough Neural Network for Wireless Sensor Networks

Author

Zhao, J., Cao, B., Liu, X., Yang, P., Singh, A. K., Lv, Zhihan, Zhao, J., Cao, B., Liu, X., Yang, P., Singh, A. K., and Lv, Zhihan

Abstract

The sensor nodes in wireless sensor networks have the deficiency of limited energy, and the multi-hop transmission of information will lead to premature paralysis of nodes near the sink. The use of the mobile sink can balance the energy consumption and greatly prolong the lifetime. Therefore, this paper studies the scheduling strategy of multiple mobile sinks and proposes a heuristic strategy based on interval type-2 fuzzy rough neural network. The energy and lifetime of sensor nodes, as well as location information of the mobile sink and special nodes are taken as input features. Through neural network learning, the outputs of whether to move, moving direction, moving distance and residence time can complete the scheduling task. The scheduling problem is regarded as a multiobjective optimization problem, and the network lifetime, the moving path length and the network interpretability are optimized at the same time, so as to obtain a lightweight network with good interpretability and performance. Based on the parallel multiobjective evolutionary algorithm, a neural evolutionary framework is constructed. Compared with static sinks, random- moving sinks, sinks with manually designed strategy and gene expression programming-based sinks as well as other state- of-the-art multiobjective evolutionary algorithms, the proposed framework can achieve superior results. IEEE

Published
2022
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123. A Research Domain Criteria (RDoC)-Guided Dashboard to Review Psilocybin Target Domains: A Systematic Review

Author

Pouyan, N, Khankahdani, ZH, Sisi, FY, Lee, Y, Rosenblat, JD, Teopiz, KM, Lui, LMW, Subramaniapillai, M, Lin, K, Nasri, F, Rodrigues, N, Gill, H, Lipsitz, O, Cao, B, Ho, R, Castle, D, McIntyre, RS, Pouyan, N, Khankahdani, ZH, Sisi, FY, Lee, Y, Rosenblat, JD, Teopiz, KM, Lui, LMW, Subramaniapillai, M, Lin, K, Nasri, F, Rodrigues, N, Gill, H, Lipsitz, O, Cao, B, Ho, R, Castle, D, and McIntyre, RS

Abstract

BACKGROUND: Preliminary results from randomized controlled studies as well as identified molecular, cellular, and circuit targets of select psychedelics (e.g., psilocybin) suggest that their effects are transdiagnostic. In this review, we exploit the Research Domain Criteria (RDoC) transdiagnostic framework, to synthesize extant literature on psilocybin. OBJECTIVE: We aimed to identify RDoC-based effects of psilocybin and vistas for future mechanistic and interventional research. METHODS: A systematic search in electronic databases (i.e., PubMed, Scopus, PsycINFO, and Web of Science) performed in January and February 2021 identified English articles published between 1990 and 2020 reporting the effects of psilocybin on mental health measures. Data from included articles were retrieved and organized according to the RDoC bio-behavioral matrix and its constituent six main domains, namely: positive valence systems, negative valence systems, cognitive systems, social processes, sensorimotor systems, and arousal and regulatory systems. RESULTS: The preponderance of research with psilocybin has differentially reported beneficial effects on positive valence systems, negative valence system, and social process domains. The data from the included studies support both short-term (23 assessments) and long-term (15 assessments) beneficial effects of psilocybin on the positive valence systems. While 12 of the extracted outcome measures suggest that psilocybin use is associated with increases in the "fear" construct of the negative valence systems domain, 19 findings show no significant effects on this construct, and seven parameters show lowered levels of the "sustained threat" construct in the long term. Thirty-four outcome measures revealed short-term alterations in the social systems' construct namely, "perception and understanding of self," and "social communications" as well as enhancements in "perception and understanding of others" and "affiliation and attachment". The ma

Published
2022

130. Reactive MgO-based self-healing slag-cement-bentonite slurry walls

Author

Cao, B, Al-Tabbaa, A, Cao, B [0000-0003-1885-7152], and Apollo - University of Cambridge Repository

Subjects
Self-healing, Reactive MgO, Slag-cement-bentonite, General Materials Science, Building and Construction, Slurry wall, Microstructure
Abstract

Despite the common use of slag-cement-bentonite slurry trench walls for geotechnical and geoenvironmental applications, the materials deteriorate under mechanical, chemical and environmental stresses. Providing the slurry wall with the capacity of self-healing cracks, could address the concerns. This study proposes and investigates, for the first time, the self-healing slag-cement-bentonite incorporating reactive MgO pellets. The incorporation of the MgO pellets slightly increased the UCS and stiffness, without any significant adverse effects on the engineering properties of the slurry wall material. The crack closure percentages after hydration and carbonation reached over 50% and 80%, when the MgO pellets were added at a dosage of 5% and 10%. The post-healing permeability was as low as 8.4×10-9 m/s, satisfying the requirement for slurry walls. TGA and SEM-EDX results show that brucite and hydrated magnesium carbonates produced by the hydration and carbonation processes are the main healing products in the MgO-containing specimens. The uniform dispersion of MgO pellets and healing products was confirmed by micro-CT analysis, and it was observed most of the cracks could be at least partly blocked. The results have collectively demonstrated the great potential of reactive MgO pellets as an effective self-healing agent for the development of more reliable and resilient slag-cement-bentonite slurry walls.

Published
2022

131. Physical mechanisms for the transition from type-III to large ELMs induced by impurity injection on EAST

Author

Lin, X., primary, Xu, G.S., additional, Yang, Q.Q., additional, Yan, N., additional, Wang, Y.F., additional, Ye, Y., additional, Zhu, P., additional, Cao, B., additional, Li, K.D., additional, Chen, R., additional, Zhang, L., additional, Zang, Q., additional, Zhang, T., additional, Wang, Y.M., additional, Hu, G.H., additional, Li, Y.Y., additional, Zhou, C., additional, Chen, Y.J., additional, Meng, L.Y., additional, Yang, X.D., additional, Duan, Y.M., additional, Liu, H.Q., additional, Ding, F., additional, Chen, X.H., additional, Xu, J.C., additional, Wu, M.F., additional, and Wang, L., additional

Published
2022
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134. Measurement of the $K_S \to πe ν$ branching fraction with the KLOE experiment

Author

Babusci, D., Berlowski, M., Bloise, C., Bossi, F., Branchini, P., Cao, B., Ceradini, F., Ciambrone, P., Curciarello, F., Czerwiński, E., D'Agostini, G., D'Amico, R., Danè, E., De Leo, V., De Lucia, E., De Santis, A., De Simone, P., Di Cicco, A., Di Domenico, A., Diociaiuti, E., Domenici, D., D'Uffizi, A., Fantini, G., Gajos, A., Gamrat, S., Gauzzi, P., Giovannella, S., Graziani, E., Kang, X., Kupsc, A., Mandaglio, G., Martini, M., Miscetti, S., Moskal, P., Passeri, A., del Rio, E. Perez, Schioppa, M., Selce, A., Silarski, M., Sirghi, F., Solodov, E. P., Wiślicki, W., and Wolke, M.

Subjects
High Energy Physics - Experiment (hep-ex), FOS: Physical sciences
Abstract

The branching fraction for the decay $K_S \to πe ν$ has been measured with a sample of 300 million $K_S$ mesons produced in $ϕ\to K_L K_S$ decays recorded by the KLOE experiment at the DA$Φ$NE $e^+e^-$ collider. Signal decays are selected by a boosted decision tree built with kinematic variables and time-of-flight measurements. Data control samples of $K_L \to πe ν$ decays are used to evaluate signal selection efficiencies. A fit to the reconstructed electron mass distribution finds 49647$\pm$316 signal events. Normalising to the $K_S \to π^+π^-$ decay events the result for the branching fraction is $\mathcal{B}(K_S \to πe ν) = (7.211 \pm 0.046_{\rm stat} \pm 0.052_{\rm syst}) \times10^{-4}$. The combination with our previous measurement gives $\mathcal{B}(K_S \to πe ν) = (7.153 \pm 0.037_{\rm stat} \pm 0.043_{\rm syst}) \times10^{-4}$. From this value we derive $f_+(0)|V_{us}| = 0.2170 \pm 0.009$., arXiv admin note: substantial text overlap with arXiv:1912.05990

Published
2022
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135. Erratum: Precision tests of quantum mechanics and CPT symmetry with entangled neutral kaons at KLOE (vol 04, 059, 2022)

Author

Babusci, D, Berlowski, M, Bloise, C, Bossi, F, Branchini, P, Budano, A, Cao, B, Ceradini, F, Ciambrone, P, Curciarello, F, Czerwinski, E, D'Agostini, G, D'Amico, R, Dane, E, De Leo, V, De Lucia, E, De Santis, A, De Simone, P, Di Cicco, A, Di Domenico, A, Diociaiuti, E, Domenici, D, D'Uffizi, A, Fantini, A, Fantini, G, Fermani, P, Fiore, S, Gajos, A, Gauzzi, P, Giovannella, S, Graziani, E, Ivanov, Vl, Johansson, T, Kang, X, Kisielewska-Kaminska, D, Kozyrev, Ea, Krzemien, W, Kupsc, A, Lukin, Pa, Mandaglio, G, Martini, M, Messi, R, Miscetti, S, Moricciani, D, Moskal, P, Passeri, A, Patera, V, del Rio, Ep, Santangelo, P, Schioppa, M, Selce, A, Silarski, M, Sirghi, F, Solodov, Ep, Tortora, L, Venanzoni, G, Wislicki, W, and Wolke, M

Subjects
Beyond Standard Model, e plus -e- Experiments
Published
2022

139. Worsening of ovarian cancer prognosis with age: an exploration of pharmacokinetics, body composition, and biology

Author

Extermann, M., primary, Walko, C., additional, Mishra, A., additional, Thomas, K., additional, Cao, B., additional, Chon, H.S., additional, Critea, M., additional, Berglund, A., additional, Chem, J.Y., additional, Cubitt, C., additional, Gomes, A.P., additional, Hoffman, M., additional, Kim, J., additional, Marchion, D., additional, Petersson, F., additional, Sansil, S., additional, Sehovic, M., additional, Shahzad, M., additional, Welsh, E., additional, and Zhang, Y., additional

Published
2021
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140. Effective connectivity between resting-state networks in depression

Author

DeMaster, D, Godlewska, BR, Liang, M, Vannucci, M, Bockmann, T, Cao, B, and Selvaraj, S

Subjects
Psychiatry and Mental health, Clinical Psychology, Brain Mapping, Depressive Disorder, Major, Depression, Brain, Humans, Magnetic Resonance Imaging, Antidepressive Agents
Abstract

Rationale: Although depression has been widely researched, findings characterizing how brain regions influence each other remains scarce, yet this is critical for research on antidepressant treatments and individual responses to particular treatments. Objectives: To identify pre-treatment resting state effective connectivity (rsEC) patterns in patients with major depressive disorder (MDD) and explore their relationship with treatment response. Methods: Thirty-four drug-free MDD patients had an MRI scan and were subsequently treated for 6 weeks with an SSRI escitalopram 10 mg daily; the response was defined as ≥50% decrease in Hamilton Depression Rating Scale (HAMD) score. Results: rsEC networks in default mode, central executive, and salience networks were identified for patients with depression. Exploratory analyses indicated higher connectivity strength related to baseline depression severity and response to treatment. Conclusions: Preliminary analyses revealed widespread dysfunction of rsEC in depression. Functional rsEC may be useful as a predictive tool for antidepressant treatment response. A primary limitation of the current study was the small size; however, the group was carefully chosen, well-characterized, and included only medication-free patients. Further research in large samples of placebo-controlled studies would be required to confirm the results.

Published
2021

144. Measurement of the KS→ πeν branching fraction with the KLOE experiment.

Author

Babusci, D., Berlowski, M., Bloise, C., Bossi, F., Branchini, P., Cao, B., Ceradini, F., Ciambrone, P., Curciarello, F., Czerwiński, E., D’Agostini, G., D’Amico, R., Danè, E., De Leo, V., De Lucia, E., De Santis, A., De Simone, P., Di Cicco, A., Di Domenico, A., and Diociaiuti, E.

Abstract

The ratio R = Γ(KS→ πeν)/Γ(KS→ π+π−) has been measured with a sample of 300 million KS mesons produced in ϕ → KLKS decays recorded by the KLOE experiment at the DAΦNE e+e− collider. KS→ πeν events are selected by a boosted decision tree built with kinematic variables and time-of-flight measurements. Data control samples of KL→ πeν decays are used to evaluate signal selection efficiencies. With 49647±316 signal events we measure R = (1.0421 ± 0.0066stat± 0.0075syst) × 10−3. The combination with our previous measurement gives R = (1.0338 ± 0.0054stat± 0.0064syst) × 10−3. From this value we derive the branching fraction B (KS→ πeν) = (7.153 ± 0.037stat± 0.044syst) × 10−4 and f+(0)|Vus| = 0.2170 ± 0.009. [ABSTRACT FROM AUTHOR]

Published
2023
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146. List of contributors

Author

Balzar, D., primary, Bortz, D.M., additional, Cao, B., additional, Casimir, D., additional, Chen, J., additional, Ciobanu, C.V., additional, Cronk, H., additional, De Souza, M.M., additional, DeJoannis, J., additional, Eymery, J., additional, Fitzgerald, G., additional, Garcia-Sanchez, R., additional, Gittleman, B., additional, Harbola, M.K., additional, Hu, L., additional, Hu, M., additional, Joseph, P., additional, Kang, N., additional, Le Si Dang, D., additional, Li, G., additional, Li, J., additional, Luo, J., additional, Mansfield, E., additional, Meunier, M., additional, Misra, P., additional, Mookerjee, A., additional, Pillai, P., additional, Rast, L., additional, Shan, S., additional, Singh, P., additional, Skeete, Z., additional, Smolyanitsky, A., additional, Stowell, M., additional, Tewary, V.K., additional, Wang, K., additional, Wang, Q., additional, Wu, H., additional, Wu, J., additional, Yan, S., additional, Yue, N., additional, Zhang, Y., additional, Zhao, W., additional, Zhao, Y., additional, Zhong, C.-J., additional, Zhou, W., additional, and Zhuiykov, S., additional

Published
2015
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147. Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Author

Brown, P, Zhou, Y, Tan, A, El-Esawi, M, Liehr, T, Blanck, O, Gladue, D, Almeida, G, Cernava, T, Sorzano, C, Yeung, A, Engel, M, Chandrasekaran, A, Muth, T, Staege, M, Daulatabad, S, Widera, D, Zhang, J, Meule, A, Honjo, K, Pourret, O, Yin, C, Zhang, Z, Cascella, M, Flegel, W, Goodyear, C, van Raaij, M, Bukowy-Bieryllo, Z, Campana, L, Kurniawan, N, Lalaouna, D, Huttner, F, Ammerman, B, Ehret, F, Cobine, P, Tan, E, Han, H, Xia, W, Mccrum, C, Dings, R, Marinello, F, Nilsson, H, Nixon, B, Voskarides, K, Yang, L, Costa, V, Bengtsson-Palme, J, Bradshaw, W, Grimm, D, Kumar, N, Martis, E, Prieto, D, Sabnis, S, Amer, S, Liew, A, Perco, P, Rahimi, F, Riva, G, Zhang, C, Devkota, H, Ogami, K, Basharat, Z, Fierz, W, Siebers, R, Tan, K, Boehme, K, Brenneisen, P, Brown, J, Dalrymple, B, Harvey, D, Ng, G, Werten, S, Bleackley, M, Dai, Z, Dhariwal, R, Gelfer, Y, Hartmann, M, Miotla, P, Tamaian, R, Govender, P, Gurney-Champion, O, Kauppila, J, Zhang, X, Echeverria, N, Subhash, S, Sallmon, H, Tofani, M, Bae, T, Bosch, O, Cuiv, P, Danchin, A, Diouf, B, Eerola, T, Evangelou, E, Filipp, F, Klump, H, Kurgan, L, Smith, S, Terrier, O, Tuttle, N, Ascher, D, Janga, S, Schulte, L, Becker, D, Browngardt, C, Bush, S, Gaullier, G, Ide, K, Meseko, C, Werner, G, Zaucha, J, Al-Farha, A, Greenwald, N, Popoola, S, Rahman, S, Xu, J, Yang, S, Hiroi, N, Alper, O, Baker, C, Bitzer, M, Chacko, G, Debrabant, B, Dixon, R, Forano, E, Gilliham, M, Kelly, S, Klempnauer, K, Lidbury, B, Lin, M, Lynch, I, Ma, W, Maibach, E, Mather, D, Nandakumar, K, Ohgami, R, Parchi, P, Tressoldi, P, Xue, Y, Armitage, C, Barraud, P, Chatzitheochari, S, Coelho, L, Diao, J, Doxey, A, Gobet, A, Hu, P, Kaiser, S, Mitchell, K, Salama, M, Shabalin, I, Song, H, Stevanovic, D, Yadollahpour, A, Zeng, E, Zinke, K, Alimba, C, Beyene, T, Cao, Z, Chan, S, Gatchell, M, Kleppe, A, Piotrowski, M, Torga, G, Woldesemayat, A, Cosacak, M, Haston, S, Ross, S, Williams, R, Wong, A, Abramowitz, M, Effiong, A, Lee, S, Abid, M, Agarabi, C, Alaux, C, Albrecht, D, Atkins, G, Beck, C, Bonvin, A, Bourke, E, Brand, T, Braun, R, Bull, J, Cardoso, P, Carter, D, Delahay, R, Ducommun, B, Duijf, P, Epp, T, Eskelinen, E, Fallah, M, Farber, D, Fernandez-Triana, J, Feyerabend, F, Florio, T, Friebe, M, Furuta, S, Gabrielsen, M, Gruber, J, Grybos, M, Han, Q, Heinrich, M, Helantera, H, Huber, M, Jeltsch, A, Jiang, F, Josse, C, Jurman, G, Kamiya, H, de Keersmaecker, K, Kristiansson, E, de Leeuw, F, Li, J, Liang, S, Lopez-Escamez, J, Lopez-Ruiz, F, Marchbank, K, Marschalek, R, Martin, C, Miele, A, Montagutelli, X, Morcillo, E, Nicoletti, R, Niehof, M, O'Toole, R, Ohtomo, T, Oster, H, Palma, J, Paterson, R, Peifer, M, Portilla, M, Portillo, M, Pritchard, A, Pusch, S, Raghava, G, Roberts, N, Ross, K, Schuele, B, Sergeant, K, Shen, J, Stella, A, Sukocheva, O, Uversky, V, Vanneste, S, Villet, M, Viveiros, M, Vorholt, J, Weinstock, C, Yamato, M, Zabetakis, I, Zhao, X, Ziegler, A, Aizat, W, Atlas, L, Bridges, K, Chakraborty, S, Deschodt, M, Domingues, H, Esfahlani, S, Falk, S, Guisado, J, Kane, N, Kueberuwa, G, Lau, C, Liang, D, Liu, E, Luu, A, Ma, C, Ma, L, Moyer, R, Norris, A, Panthee, S, Parsons, J, Peng, Y, Pinto, I, Reschke, C, Sillanpaa, E, Stewart, C, Uhle, F, Yang, H, Zhou, K, Zhu, S, Ashry, M, Bergsland, N, Berthold, M, Chen, C, Colella, V, Cuypers, M, Eskew, E, Fan, X, Gajda, M, Gonzalezlez-Prendes, R, Goodin, A, Graham, E, Groen, E, Gutierrez-Sacristan, A, Habes, M, Heffler, E, Higginbottom, D, Janzen, T, Jayaraman, J, Jibb, L, Jongen, S, Kinyanjui, T, Koleva-Kolarova, R, Li, Z, Liu, Y, Lund, B, Lussier, A, Mier, P, Moore, M, Nagler, K, Orme, M, Pearson, J, Prajapati, A, Saito, Y, Troder, S, Uchendu, F, Verloh, N, Voutchkova, D, Abu-Zaid, A, Bakkach, J, Baumert, P, Dono, M, Hanson, J, Herbelet, S, Hobbs, E, Kulkarni, A, Liu, S, Loft, N, Reddan, T, Senghore, T, Vindin, H, Xu, H, Bannon, R, Chen, B, Cheung, J, Cooper, J, Esnakula, A, Feghali, K, Ghelardi, E, Gnasso, A, Horbar, J, Lai, H, Ma, R, Pan, Z, Peres, M, Pranata, R, Seow, E, Sydes, M, Testoni, I, Westermair, A, Yang, Y, Afnan, M, Albiol, J, Albuquerque, L, Amir, S, Amiya, E, Amorim, R, An, Q, Andersen, S, Aplin, J, Argyropoulos, C, Asmann, Y, Assaeed, A, Atanasov, A, Atchison, D, Avery, S, Avillach, P, Baade, P, Backman, L, Badie, C, Baldi, A, Ball, E, Bardot, O, Barnett, A, Basner, M, Batra, J, Bazanova, O, Beale, A, Beddoe, T, Bell, M, Berezikov, E, Berners-Price, S, Bernhardt, P, Berry, E, Bessa, T, Billington, C, Birch, J, Blakely, R, Blaskovich, M, Blum, R, Boelaert, M, Bogdanos, D, Bosch, C, Bourgoin, T, Bouvard, D, Boykin, L, Bradley, G, Braun, D, Brownlie, J, Bruhl, A, Burt, A, Butler, L, Byrareddy, S, Byrne, H, Cabantous, S, Calatayud, S, Candal, E, Carlson, K, Casillas, S, Castelvetro, V, Caswell, P, Cavalli, G, Cerovsky, V, Chagoyen, M, Chen, D, Chen, H, Chen, J, Chen, Y, Cheng, C, Cheng, J, Chinapaw, M, Chinopoulos, C, Cho, W, Chong, L, Chowdhury, D, Chwalibog, A, Ciresi, A, Cockcroft, S, Conesa, A, Cook, P, Cooper, D, Coqueret, O, Corea, E, Costa, A, Costa, E, Coupland, C, Crawford, S, Cruz, A, Cui, H, Cui, Q, Culver, D, D'Angiulli, A, Dahms, T, Daigle, F, Dalgleish, R, Danielsen, H, Darras, S, Davidson, S, Day, D, Degirmenci, V, Demaison, L, Devriendt, K, Ding, J, Dogan, Y, Dong, X, Donner, C, Dressick, W, Drevon, C, Duan, H, Ducho, C, Dumaz, N, Dwarakanath, B, Ebell, M, Eisenhardt, S, Elkum, N, Engel, N, Erickson, T, Fairhead, M, Faville, M, Fejzo, M, Festa, F, Feteira, A, Flood-Page, P, Forsayeth, J, Fox, S, Franks, S, Frentiu, F, Frilander, M, Fu, X, Fujita, S, Galea, I, Galluzzi, L, Gani, F, Ganpule, A, Garcia-Alix, A, Gedye, K, Giordano, M, Giunta, C, Gleeson, P, Goarant, C, Gong, H, Gora, D, Gough, M, Goyal, R, Graham, K, Grande-Perez, A, Graves, P, Greidanus, H, Grice, D, Grunau, C, Gumulya, Y, Guo, Y, Gurevich, V, Gusev, O, Hacker, E, Hage, S, Hagen, G, Hahn, S, Haller, D, Hammerschmidt, S, Han, J, Han, R, Handfield, M, Hapuarachchi, H, Harder, T, Hardingham, J, Heck, M, Heers, M, Hew, K, Higuchi, Y, Hilaire, C, Hilton, R, Hodzic, E, Hone, A, Hongoh, Y, Hu, G, Huber, H, Hueso, L, Huirne, J, Hurt, L, Idborg, H, Ikeo, K, Ingley, E, Jakeman, P, Jensen, A, Jia, H, Jia, S, Jiang, J, Jiang, X, Jin, Y, Jo, D, Johnson, A, Johnston, M, Jonscher, K, Jorens, P, Jorgensen, J, Joubert, J, Jung, S, Junior, A, Kahan, T, Kamboj, S, Kang, Y, Karamanos, Y, Karp, N, Kelly, R, Kenna, R, Kennedy, J, Kersten, B, Khalaf, R, Khalid, J, Khatlani, T, Khider, T, Kijanka, G, King, S, Kluz, T, Knox, P, Kobayashi, T, Koch, K, Kohonen-Corish, M, Kong, X, Konkle-Parker, D, Korpela, K, Kostrikis, L, Kraiczy, P, Kratz, H, Krause, G, Krebsbach, P, Kristensen, S, Kumari, P, Kunimatsu, A, Kurdak, H, Kwon, Y, Lachat, C, Lagisz, M, Laky, B, Lammerding, J, Lange, M, Larrosa, M, Laslett, A, Laverman, G, Leclair, E, Lee, K, Lee, M, Li, G, Lieb, K, Lim, Y, Lindsey, M, Line, P, Liu, D, Liu, F, Liu, H, Lloyd, V, Lo, T, Locci, E, Loidl, J, Lorenzen, J, Lorkowski, S, Lovell, N, Lu, H, Lu, W, Lu, Z, Luengo, G, Lundh, L, Lysy, P, Mabb, A, Mack, H, Mackey, D, Mahdavi, S, Maher, P, Maher, T, Maity, S, Malgrange, B, Mamoulakis, C, Mangoni, A, Manke, T, Manstead, A, Mantalaris, A, Marsal, J, Marschall, H, Martin, F, Martinez-Raga, J, Martinez-Salas, E, Mathieu, D, Matsui, Y, Maza, E, Mccutcheon, J, Mckay, G, Mcmillan, B, Mcmillan, N, Meads, C, Medina, L, Merrick, B, Metzger, D, Meunier, F, Michaelis, M, Micheau, O, Mihara, H, Mintz, E, Mizukami, T, Moalic, Y, Mohapatra, D, Monteiro, A, Montes, M, Moran, J, Morozov, S, Mort, M, Murai, N, Murphy, D, Murphy, S, Murray, S, Naganawa, S, Nammi, S, Nasios, G, Natoli, R, Nguyen, F, Nicol, C, van Nieuwerburgh, F, Nilsen, E, Nobile, C, O'Mahony, M, Ohlsson, S, Olatunbosun, O, Olofsson, P, Ortiz, A, Ostrikov, K, Otto, S, Outeiro, T, Ouyang, S, Paganoni, S, Page, A, Palm, C, Paradies, Y, Parsons, M, Parsons, N, Pascal, P, Paul, E, Peckham, M, Pedemonte, N, Pellizzon, M, Petrelli, M, Pichugin, A, Pinto, C, Plevris, J, Pollesello, P, Polz, M, Ponti, G, Porcelli, P, Prince, M, Quinn, G, Quinn, T, Ramula, S, Rappsilber, J, Rehfeldt, F, Reiling, J, Remacle, C, Rezaei, M, Riddick, E, Ritter, U, Roach, N, Roberts, D, Robles, G, Rodrigues, T, Rodriguez, C, Roislien, J, Roobol, M, Rowe, A, Ruepp, A, van Ruitenbeek, J, Rust, P, Saad, S, Sack, G, Santos, M, Saudemont, A, Sava, G, Schrading, S, Schramm, A, Schreiber, M, Schuler, S, Schymkowitz, J, Sczyrba, A, Seib, K, Shi, H, Shimada, T, Shin, J, Shortt, C, Silveyra, P, Skinner, D, Small, I, Smeets, P, So, P, Solano, F, Sonenshine, D, Song, J, Southall, T, Speakman, J, Srinivasan, M, Stabile, L, Stasiak, A, Steadman, K, Stein, N, Stephens, A, Stewart, D, Stine, K, Storlazzi, C, Stoynova, N, Strzalka, W, Suarez, O, Sultana, T, Sumant, A, Summers, M, Sun, G, Tacon, P, Tanaka, K, Tang, H, Tanino, Y, Targett-Adams, P, Tayebi, M, Tayyem, R, Tebbe, C, Telfer, E, Tempel, W, Teodorczyk-Injeyan, J, Thijs, G, Thorne, S, Thrift, A, Tiffon, C, Tinnefeld, P, Tjahjono, D, Tolle, F, Toth, E, Del Tredici, A, Tsapas, A, Tsirigotis, 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Abstract

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.

Published
2019

150. Simulation and improvements of a magnetic flux sensor for application in immunomagnetic biosensing platforms

Author

Cheng Y, Cui D, Cao B, Wang K, Xu H, Jin Q, Zheng W, Li T, and Zheng C

Subjects
Materials science, Nanotechnology, Biosensor, Magnetic flux
Abstract

In recent years, point-of-care testing (POCT) has become a topical issue. Lateral flow immunoassay strategies based on magnetic nanoparticles (MNPs) are important POCT elements due to their sensitive quantification of biological materials via MNP magnetic field measurement. In this study, we designed a magnetic flux sensor for use in immunomagnetic biosensing platforms, incorporating a mathematical model and computer simulation strategy. The system used field programmable gate array (FPGA) as the control chip, synthesized excitation signals and excited coils to generate excitation magnetic fields. Also, the stepping motor was controlled to drive the test strip at a uniform speed through the sensor detection area. A differential configuration strategy was used for sensor pick-up coils to assess MNP influence on the magnetic flux, which was insensitive to background magnetic interference and common-mode noise. These factors significantly enhanced the signal-to-noise ratio of the sensor. The magnetic flux sensor structure was optimized, and response magnetic field characteristics of MNP on test strips analyzed using finite element analysis (FEA) simulations. System performance was evaluated by testing human chorionic gonadotropin (HCG), which demonstrated a linear performance, with a limit of detection of 0.0098 mIU/mL. This system may be used to identify other target analytes in different application settings.

Published
2021

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