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5. Multiscale simulations of growth-dominated Sb$_2$Te phase-change material for non-volatile photonic applications

Author

Wang, Xu-Dong, Zhou, Wen, Zhang, Hangming, Ahmed, Shehzad, Huang, Tiankuo, Mazzarello, Riccardo, Ma, En, and Zhang, Wei

Subjects
Condensed Matter - Materials Science
Abstract

Chalcogenide phase-change materials (PCMs) are widely applied in electronic and photonic applications, such as non-volatile memory and neuro-inspired computing. Doped Sb$_2$Te alloys are now gaining increasing attention for on-chip photonic applications, due to their growth-driven crystallization features. However, it remains unknown whether Sb$_2$Te also forms a metastable crystalline phase upon nanoseconds crystallization in devices, similar to the case of nucleation-driven Ge-Sb-Te alloys. Here, we carry out ab initio simulations to understand the changes in optical properties of amorphous Sb$_2$Te upon crystallization and post annealing. During the continuous transformation process, changes in the dielectric function are highly wavelength-dependent from the visible-light range towards the telecommunication band. Our finite-difference time-domain simulations based on the ab initio input reveal key differences in device output for color display and photonic memory applications upon tellurium ordering. Our work serves as an example of how multiscale simulations of materials can guide practical photonic phase-change applications., Comment: 16 pages,8 figures

Published
2023
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6. Spin glass behavior in amorphous Cr2Ge2Te6 phase-change alloy

Author

Wang, Xiaozhe, Sun, Suyang, Wang, Jiang-Jing, Li, Shuang, Zhou, Jian, Aktas, Oktay, Xu, Ming, Deringer, Volker L., Mazzarello, Riccardo, Ma, En, and Zhang, Wei

Subjects
Condensed Matter - Materials Science
Abstract

The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two-dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, we demonstrate that Cr2Ge2Te6 preserves the spin-polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum-mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the Cr-Te-Cr bonds, connecting chromium-centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 could be exploited for multifunctional, magnetic phase-change devices that switch between crystalline and amorphous states.

Published
2023

7. Unlocking device-scale atomistic modelling of phase-change memory materials

Author

Zhou, Yuxing, Zhang, Wei, Ma, En, and Deringer, Volker L.

Subjects
Condensed Matter - Materials Science
Abstract

Quantum-accurate computer simulations play a central role in understanding phase-change materials (PCMs) for advanced memory technologies. However, direct quantum-mechanical simulations are necessarily limited to simplified models, containing no more than a few hundred or a thousand atoms. Machine learning (ML) based potential models that are "trained" on quantum-mechanical data are an emerging alternative approach, currently evolving from highly specialised to more widely applied simulation tools. Here we show that a universal, compositionally flexible ML model can describe a wide range of flagship Ge-Sb-Te PCMs under real device conditions, including non-isothermal heating and chemical disorder which are relevant for memory applications. The speed of the ML model enables atomistic simulations of multiple thermal cycles and delicate operations for neuro-inspired computing, namely, cumulative SET and iterative RESET. A device-scale capability demonstration (40 x 20 x 20 nm3) shows that the new ML potential can directly describe technologically relevant processes in PCM-based memory products. In a wider context, our work demonstrates how ML-driven materials simulations are now entering a stage where they can guide architecture design for high-performance electronic devices.

Published
2022

8. Designing inorganic semiconductors with cold-rolling processability

Author

Wang, Xu-Dong, Tan, Jieling, Ouyang, Jian, Zhang, Hangming, Wang, Jiang-Jing, Wang, Yuecun, Deringer, Volker L., Zhou, Jian, Zhang, Wei, and Ma, En

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

While metals can be readily processed and reshaped by cold rolling, most bulk inorganic semiconductors are brittle materials that tend to fracture when plastically deformed. Manufacturing thin sheets and foils of inorganic semiconductors is therefore a bottleneck problem, severely restricting their use in flexible electronics applications. It was recently reported that a few single-crystalline two-dimensional van der Waals (vdW) semiconductors, such as InSe, are deformable under compressive stress. Here we demonstrate that intralayer fracture toughness can be tailored via compositional design to make inorganic semiconductors processable by cold rolling. We report systematic ab initio calculations covering a range of van der Waals semiconductors homologous to InSe, leading to material-property maps that forecast trends in both the susceptibility to interlayer slip and the intralayer fracture toughness against cracking. GaSe has been predicted, and experimentally confirmed, to be practically amenable to being rolled to large (three quarters) thickness reduction and length extension by a factor of three. Our findings open a new realm of possibility for alloy selection and design towards processing-friendly group-III chalcogenides for flexible electronic and thermoelectric applications.

Published
2022

9. Large scale proteomic studies create novel privacy considerations

Author

Hill, Andrew C, Guo, Claire, Litkowski, Elizabeth M, Manichaikul, Ani W, Yu, Bing, Konigsberg, Iain R, Gorbet, Betty A, Lange, Leslie A, Pratte, Katherine A, Kechris, Katerina J, DeCamp, Matthew, Coors, Marilyn, Ortega, Victor E, Rich, Stephen S, Rotter, Jerome I, Gerzsten, Robert E, Clish, Clary B, Curtis, Jeffrey L, Hu, Xiaowei, Obeidat, Ma-en, Morris, Melody, Loureiro, Joseph, Ngo, Debby, O’Neal, Wanda K, Meyers, Deborah A, Bleecker, Eugene R, Hobbs, Brian D, Cho, Michael H, Banaei-Kashani, Farnoush, and Bowler, Russell P

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Cardiovascular, Minority Health, Biotechnology, Atherosclerosis, Health Disparities, Human Genome, Generic health relevance, Humans, Proteome, Bayes Theorem, Privacy, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract

Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90-95% of proteomes to their correct genome and for 95-99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Published
2023

10. In situ characterization of vacancy ordering in Ge-Sb-Te phase-change memory alloys

Author

Jiang, Ting-Ting, Wang, Xu-Dong, Wang, Jiang-Jing, Zhang, Han-Yi, Lu, Lu, Jia, Chunlin, Wuttig, Matthias, Mazzarello, Riccardo, Zhang, Wei, and Ma, En

Subjects
Condensed Matter - Materials Science
Abstract

Tailoring the degree of structural disorder in Ge-Sb-Te alloys is important for the development of non-volatile phase-change memory and neuro-inspired computing. Upon crystallization from the amorphous phase, these alloys form a cubic rocksalt-like structure with a high content of intrinsic vacancies. Further thermal annealing results in a gradual structural transition towards a layered structure and an insulator-to-metal transition. In this work, we elucidate the atomic-level details of the structural transition in crystalline GeSb2Te4 by in situ high-resolution transmission electron microscopy (HRTEM) experiments and ab initio density functional theory (DFT) calculations, providing a comprehensive real-time and real-space view of the vacancy ordering process. We also discuss the impact of vacancy ordering on altering the electronic and optical properties of GeSb2Te4, which is relevant to multilevel storage applications. The phase evolution paths in Ge-Sb-Te alloys are illustrated using a summary diagram, which serves as a guide for designing phase-change memory devices.

Published
2022

11. Custom-designed heat treatment simultaneously resolves multiple challenges facing 3D-printed single-crystal superalloys

Author

Lin, Sicong, Chen, Kai, He, Weifeng, Tamura, Nobumichi, and Ma, En

Subjects
Manufacturing Engineering, Engineering, Ni-based superalloy single crystals, Heat treatment, Recovery, Recrystallization, Stray grain growth, Chemical homogenization, Materials Engineering, Mechanical Engineering, Materials, Materials engineering, Mechanical engineering
Abstract

Single-crystal Ni-based superalloys are currently the material of choice for turbine blade applications, especially with the emerging additive manufacturing (AM) that facilitates the manufacture/repair of these single crystals. This promising AM route, however, comes with a dilemma: in the fusion and heat affected zones after e-beam or laser induced melting, one needs a solutionizing annealing to relieve the residual stresses and homogenize the chemical/microstructure. The super-solvus solutionizing temperature is usually adopted from the protocol for the cast superalloys, which almost always causes recrystallization and stray grain growth, resulting in a polycrystalline microstructure and degrading the high-temperature mechanical performance. Here we demonstrate a custom-designed post-printing heat treatment to replace the conventional super-solvus one. The recovery and relatively low temperature diminish the driving force for recrystallization and the movement of stray grain boundaries, without suffocating the chemical/microstructural homogenization thanks to the narrow dendrite width and short element segregation distance. The optimal duration of the heat treatment is proposed to achieve atomic-diffusion mediated chemical homogenization while limiting γ′-particle coarsening in the interdendritic regions. Our strategy makes it practically feasible to resolve several bottleneck problems with one processing/treatment, removing a seemingly formidable obstacle to effective additive manufacturing of superalloy single crystal products.

Published
2022

15. Molecular-scale Integration of Multi-modal Sensing and Neuromorphic Computing with Organic Electrochemical Transistors

Author

Wang, Shijie, Chen, Xi, Zhao, Chao, Kong, Yuxin, Lin, Baojun, Wu, Yongyi, Bi, Zhaozhao, Xuan, Ziyi, Li, Tao, Li, Yuxiang, Zhang, Wei, Ma, En, Wang, Zhongrui, and Ma, Wei

Subjects
Computer Science - Emerging Technologies, Condensed Matter - Materials Science, Condensed Matter - Soft Condensed Matter
Abstract

Abstract: Bionic learning with fused sensing, memory and processing functions outperforms artificial neural networks running on silicon chips in terms of efficiency and footprint. However, digital hardware implementation of bionic learning suffers from device heterogeneity in sensors and processing cores, which incurs large hardware, energy and time overheads. Here, we present a universal solution to simultaneously perform multi-modal sensing, memory and processing using organic electrochemical transistors with designed architecture and tailored channel morphology, selective ion injection into the crystalline/amorphous regions. The resultant device work as either a volatile receptor that shows multi-modal sensing, or a non-volatile synapse that features record-high 10-bit analog states, low switching stochasticity and good retention without the integration of any extra devices. Homogeneous integration of such devices enables bionic learning functions such as conditioned reflex and real-time cardiac disease diagnose via reservoir computing, illustrating the promise for future smart edge health informatics., Comment: 17 pages, 4 figures

Published
2022

20. Thrombosis risk in single- and double-heterozygous carriers of factor V Leiden and prothrombin G20210A in FinnGen and the UK Biobank

Author

Palotie, Aarno, Daly, Mark, Riley-Gills, Bridget, Jacob, Howard, Viollet, Coralie, Petrovski, Slavé, Chen, Chia-Yen, John, Sally, Okafo, George, Plenge, Robert, Maranville, Joseph, McCarthy, Mark, Pendergrass, Rion, Ehm, Margaret G., Auro, Kirsi, Longerich, Simonne, Mälarstig, Anders, Vlahiotis, Anna, Klinger, Katherine, Chatelain, Clement, Gossel, Matthias, Estrada, Karol, Graham, Robert, Waterworth, Dawn, O´Donnell, Chris, Renaud, Nicole, Mäkelä, Tomi P., Kaprio, Jaakko, Ruddock, Minna, Virolainen, Petri, Hakanen, Antti, Kilpi, Terhi, Perola, Markus, Partanen, Jukka, Raivio, Taneli, Tikkanen, Jani, Serpi, Raisa, Kristiansson, Kati, Kosma, Veli-Matti, Laukkanen, Jari, Hautalahti, Marco, Tuovila, Outi, Waring, Jeffrey, Riley-Gillis, Bridget, Rahimov, Fedik, Tachmazidou, Ioanna, Ding, Zhihao, Jung, Marc, Tuoken, Hanati, Biswas, Shameek, Pulford, David, Raghavan, Neha, Huertas-Vazquez, Adriana, Sul, Jae-Hoon, Hu, Xinli, Hedman, Åsa, Obeidat, Ma´en, Chung, Jonathan, Zierer, Jonas, Niemi, Mari, Ripatti, Samuli, Schleutker, Johanna, Arvas, Mikko, Carpén, Olli, Hinttala, Reetta, Kettunen, Johannes, Mannermaa, Arto, Aalto-Setälä, Katriina, Kähönen, Mika, Mäkelä, Johanna, Kälviäinen, Reetta, Julkunen, Valtteri, Soininen, Hilkka, Remes, Anne, Hiltunen, Mikko, Peltola, Jukka, Raivio, Minna, Tienari, Pentti, Rinne, Juha, Kallionpää, Roosa, Partanen, Juulia, Ziemann, Adam, Smaoui, Nizar, Lehtonen, Anne, Eaton, Susan, Runz, Heiko, Lahdenperä, Sanni, Bowers, Natalie, Teng, Edmond, Xu, Fanli, Addis, Laura, Eicher, John, Li, Qingqin S., He, Karen, Khramtsova, Ekaterina, Färkkilä, Martti, Koskela, Jukka, Pikkarainen, Sampsa, Jussila, Airi, Kaukinen, Katri, Blomster, Timo, Kiviniemi, Mikko, Voutilainen, Markku, Lu, Tim, McCarthy, Linda, Hart, Amy, Guan, Meijian, Miller, Jason, Kalpala, Kirsi, Miller, Melissa, Eklund, Kari, Palomäki, Antti, Isomäki, Pia, Pirilä, Laura, Kaipiainen-Seppänen, Oili, Huhtakangas, Johanna, Mars, Nina, Lertratanakul, Apinya, Hochfeld, Marla, Gordillo, Jorge Esparza, Farias, Fabiana, Bing, Nan, Laitinen, Tarja, Pelkonen, Margit, Kauppi, Paula, Kankaanranta, Hannu, Harju, Terttu, Lahesmaa, Riitta, Chen, Hubert, Betts, Joanna, Mishra, Rajashree, Mouded, Majd, Ngo, Debby, Niiranen, Teemu, Vaura, Felix, Salomaa, Veikko, Metsärinne, Kaj, Aittokallio, Jenni, Hernesniemi, Jussi, Gordin, Daniel, Sinisalo, Juha, Taskinen, Marja-Riitta, Tuomi, Tiinamaija, Hiltunen, Timo, Elliott, Amanda, Reeve, Mary Pat, Ruotsalainen, Sanni, Paul, Dirk, Chu, Audrey, Reilly, Dermot, Mendelson, Mike, Parkkinen, Jaakko, Meretoja, Tuomo, Joensuu, Heikki, Mattson, Johanna, Salminen, Eveliina, Auranen, Annika, Karihtala, Peeter, Auvinen, Päivi, Elenius, Klaus, Pitkänen, Esa, Popovic, Relja, Fabre, Margarete, Schutzman, Jennifer, Kulkarni, Diptee, Porello, Alessandro, Loboda, Andrey, Lehtonen, Heli, McDonough, Stefan, Vuoti, Sauli, Kaarniranta, Kai, Turunen, Joni A., Ollila, Terhi, Uusitalo, Hannu, Karjalainen, Juha, Liu, Mengzhen, Loomis, Stephanie, Strauss, Erich, Chen, Hao, Tasanen, Kaisa, Huilaja, Laura, Hannula-Jouppi, Katariina, Salmi, Teea, Peltonen, Sirkku, Koulu, Leena, Choy, David, Wu, Ying, Pussinen, Pirkko, Salminen, Aino, Salo, Tuula, Rice, David, Nieminen, Pekka, Palotie, Ulla, Siponen, Maria, Suominen, Liisa, Mäntylä, Päivi, Gursoy, Ulvi, Anttonen, Vuokko, Sipilä, Kirsi, Laivuori, Hannele, Kurra, Venla, Kotaniemi-Talonen, Laura, Heikinheimo, Oskari, Kalliala, Ilkka, Aaltonen, Lauri, Jokimaa, Varpu, Vääräsmäki, Marja, Uimari, Outi, Morin-Papunen, Laure, Niinimäki, Maarit, Piltonen, Terhi, Kivinen, Katja, Widen, Elisabeth, Tukiainen, Taru, Välimäki, Niko, Laakkonen, Eija, Tyrmi, Jaakko, Silven, Heidi, Sliz, Eeva, Arffman, Riikka, Savukoski, Susanna, Laisk, Triin, Pujol, Natalia, Kumar, Janet, Hovatta, Iiris, Isometsä, Erkki, Ollila, Hanna, Suvisaari, Jaana, Mäkitie, Antti, Bizaki-Vallaskangas, Argyro, Toppila-Salmi, Sanna, Willberg, Tytti, Saarentaus, Elmo, Aarnisalo, Antti, Rahikkala, Elisa, Aittomäki, Kristiina, Åberg, Fredrik, Kurki, Mitja, Havulinna, Aki, Mehtonen, Juha, Palta, Priit, Hassan, Shabbeer, Della Briotta Parolo, Pietro, Zhou, Wei, Maasha, Mutaamba, Lemmelä, Susanna, Rivas, Manuel, Liu, Aoxing, Lehisto, Arto, Ganna, Andrea, Llorens, Vincent, Heyne, Henrike, Rämö, Joel, Rodosthenous, Rodos, Strausz, Satu, Palotie, Tuula, Palin, Kimmo, Garcia-Tabuenca, Javier, Siirtola, Harri, Kiiskinen, Tuomo, Lee, Jiwoo, Tsuo, Kristin, Hyvärinen, Kati, Ritari, Jarmo, Pylkäs, Katri, Karjalainen, Minna, Mantere, Tuomo, Kangasniemi, Eeva, Heikkinen, Sami, Pitkänen, Nina, Lessard, Samuel, Chatelain, Clément, Kallio, Lila, Wahlfors, Tiina, Punkka, Eero, Siltanen, Sanna, Kuopio, Teijo, Jalanko, Anu, Shen, Huei-Yi, Kajanne, Risto, Aavikko, Mervi, Cooper, Helen, Öller, Denise, Leinonen, Rasko, Palin, Henna, Linna, Malla-Maria, Kanai, Masahiro, Zheng, Zhili, Lahtela, L. Elisa, Kaunisto, Mari, Kilpeläinen, Elina, Sipilä, Timo P., Dada, Oluwaseun Alexander, Ghazal, Awaisa, Kytölä, Anastasia, Weldatsadik, Rigbe, Donner, Kati, Loukola, Anu, Laiho, Päivi, Sistonen, Tuuli, Kaiharju, Essi, Laukkanen, Markku, Järvensivu, Elina, Lähteenmäki, Sini, Männikkö, Lotta, Wong, Regis, Toivola, Auli, Brunfeldt, Minna, Mattsson, Hannele, Koskelainen, Sami, Hiekkalinna, Tero, Paajanen, Teemu, Luo, Shuang, Padmanabhuni, Shanmukha Sampath, Niemi, Marianna, Gracia-Tabuenca, Javier, Helminen, Mika, Luukkaala, Tiina, Vähätalo, Iida, Tammerluoto, Jyrki, Smith, Sarah, Southerington, Tom, Lehto, Petri, Ryu, Justine, Rämö, Joel T., Jurgens, Sean J., Sanna-Cherchi, Simone, Bauer, Kenneth A., Haj, Amelia, Choi, Seung Hoan, Ellinor, Patrick T., and Bendapudi, Pavan K.

Published
2024
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24. Radiation-tolerant high-entropy alloys via interstitial-solute-induced chemical heterogeneities

Author

Su, Zhengxiong, Ding, Jun, Song, Miao, Jiang, Li, Shi, Tan, Li, Zhiming, Wang, Sheng, Gao, Fei, Yun, Di, Lu, Chenyang, and Ma, En

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

High-entropy alloys (HEAs) composed of multiple principal elements have been shown to offer improved radiation resistance over their elemental or dilute-solution counterparts. Using NiCoFeCrMn HEA as a model, here we introduce carbon and nitrogen interstitial alloying elements to impart chemical heterogeneities in the form of the local chemical order (LCO) and associated compositional variations. Density functional theory simulations predict chemical short-range order (CSRO) (nearest neighbors and the next couple of atomic shells) surrounding C and N, due to the chemical affinity of C with (Co, Fe) and N with (Cr, Mn). Atomic-resolution chemical mapping of the elemental distribution confirms marked compositional variations well beyond statistical fluctuations. Ni+ irradiation experiments at elevated temperatures demonstrate a remarkable reduction in void swelling by at least one order of magnitude compared to the base HEA without C and N alloying. The underlying mechanism is that the interstitial-solute-induced chemical heterogeneities roughen the lattice as well as the energy landscape, impeding the movements of, and constraining the path lanes for, the normally fast-moving self-interstitials and their clusters. The irradiation-produced interstitials and vacancies therefore recombine more readily, delaying void formation. Our findings thus open a promising avenue towards highly radiation-tolerant alloys., Comment: 24 pages, 10 figures

Published
2021
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27. Dynamic modulation of multicolor upconversion luminescence of Er3+ via excitation pulse width.

Author

Ma, En, Yu, Shiqi, You, Wenwu, Tu, Datao, Wen, Fei, Xing, Yun, Lu, Shan, and Chen, Xueyuan

Subjects
*LUMINESCENCE, *LASER pulses, *SEMICONDUCTOR lasers, *PHOTON upconversion, *ENERGY transfer
Abstract

Lanthanide-doped upconversion (UC) luminescent materials display multicolor emissions, making them ideal for a variety of applications, such as multi-channel biological imaging, fluorescence encryption, anti-counterfeiting, and 3D display. Manipulating the UC emissions of the luminescent materials with a fixed composition is crucial for their applications. Herein, we propose a facile strategy to achieve pulse-width-dependent multicolor UC emissions in NaYF4:Yb/Er/Tm nanocrystals. Upon excitation with a 980 nm continuous-wave laser diode, Er3+ ions in NaYF4:20%Yb,15%Er,1%Tm nanocrystals exhibited UC emissions with a red-to-green (R/G) ratio of 11.3. Nevertheless, by employing a 980 nm pulse laser with pulse widths from 0.1 to 10 ms, the UC R/G ratio can be easily adjusted from 0.9 to 11.3, resulting in continuous and remarkable color transformation from green, yellow, orange, to red. By virtue of the dynamic luminescence color variation of these NaYF4:20%Yb,15%Er,1%Tm nanocrystals, we demonstrated their potential applications in the areas of anti-counterfeiting and information encryption. These findings provide deep insights into the excited-state dynamics and energy transfer of Er3+ in NaYF4:Yb/Er/Tm nanocrystals upon 980 nm pulse excitation, which may pave the way for designing multicolor UC materials toward versatile applications. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Berberine Promotes Mouse Breast Cancer Metastasis to Lung via Inducing Epithelial–mesenchymal Transition

Author

YUAN Zhiying, MA En, WO Da, PENG Jun, ZHU Weidong, and REN Danni

Subjects
berberine, breast cancer, 4t1 cells, metastasis, emt, vimentin, snail, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Objective To study the effect and mechanism of berberine (BBR) on the lung metastasis of mouse breast cancer via epithelial-mesenchymal transition (EMT). Methods CCK-8 and Transwell migration assays were utilized to investigate the proliferation and migration properties of breast cancer 4T1 cells after BBR treatment.Mouse 4T1-Luc cells were injected into mice under the fourth mammary fat pad, and the mice were then randomly divided into the control and BBR groups.The mice in the BBR group received daily intraperitoneal injections of BBR working solution and those in the control group were continuously intraperitoneally injected with the same volume of the solvent used to dissolve BBR powder.Tumor metastasis in the lungs of living mice was detected by using an in vivo imaging system.After 42 days of administration, lung metastasis was measured via microscopy and HE staining.Western blot analysis was used to examine the effects of BBR on the expression of EMT-related proteins (Vimentin and Snail) as well as the activation of the Akt and ERK signaling pathways. Results BBR significantly promoted 4T1 cell migration (P < 0.05).In vivo experiments showed that the number of lung metastases in the BBR group had significantly increased compared with that in control group (P < 0.05) as observed under microcopy and histological staining.Compared with the control group, BBR upregulated the expression levels of Vimentin and Snail as well as the phosphorylated levels of p-Akt and p-ERK (P < 0.05). Conclusion BBR may promote EMT and lung metastasis of breast cancer 4T1 cells by activating the expression of proteins in the p-Akt and p-ERK pathways.

Published
2023
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30. Large scale proteomic studies create novel privacy considerations

Author

Andrew C. Hill, Claire Guo, Elizabeth M. Litkowski, Ani W. Manichaikul, Bing Yu, Iain R. Konigsberg, Betty A. Gorbet, Leslie A. Lange, Katherine A. Pratte, Katerina J. Kechris, Matthew DeCamp, Marilyn Coors, Victor E. Ortega, Stephen S. Rich, Jerome I. Rotter, Robert E. Gerzsten, Clary B. Clish, Jeffrey L. Curtis, Xiaowei Hu, Ma-en Obeidat, Melody Morris, Joseph Loureiro, Debby Ngo, Wanda K. O’Neal, Deborah A. Meyers, Eugene R. Bleecker, Brian D. Hobbs, Michael H. Cho, Farnoush Banaei-Kashani, and Russell P. Bowler

Subjects
Medicine, Science
Abstract

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to link SomaScan 1.3K proteomes to genomes for 2812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We correctly linked 90–95% of proteomes to their correct genome and for 95–99% we identify the 1% most likely links. The linking accuracy in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. We also linked proteomes-to-proteomes and used the proteome only to determine features such as sex, ancestry, and first-degree relatives. When serial proteomes are available, the linking algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Published
2023
Full Text
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33. FinnGen provides genetic insights from a well-phenotyped isolated population

Author

Kurki, Mitja I., Karjalainen, Juha, Palta, Priit, Sipilä, Timo P., Kristiansson, Kati, Donner, Kati M., Reeve, Mary P., Laivuori, Hannele, Aavikko, Mervi, Kaunisto, Mari A., Loukola, Anu, Lahtela, Elisa, Mattsson, Hannele, Laiho, Päivi, Della Briotta Parolo, Pietro, Lehisto, Arto A., Kanai, Masahiro, Mars, Nina, Rämö, Joel, Kiiskinen, Tuomo, Heyne, Henrike O., Veerapen, Kumar, Rüeger, Sina, Lemmelä, Susanna, Zhou, Wei, Ruotsalainen, Sanni, Pärn, Kalle, Hiekkalinna, Tero, Koskelainen, Sami, Paajanen, Teemu, Llorens, Vincent, Gracia-Tabuenca, Javier, Siirtola, Harri, Reis, Kadri, Elnahas, Abdelrahman G., Sun, Benjamin, Foley, Christopher N., Aalto-Setälä, Katriina, Alasoo, Kaur, Arvas, Mikko, Auro, Kirsi, Biswas, Shameek, Bizaki-Vallaskangas, Argyro, Carpen, Olli, Chen, Chia-Yen, Dada, Oluwaseun A., Ding, Zhihao, Ehm, Margaret G., Eklund, Kari, Färkkilä, Martti, Finucane, Hilary, Ganna, Andrea, Ghazal, Awaisa, Graham, Robert R., Green, Eric M., Hakanen, Antti, Hautalahti, Marco, Hedman, Åsa K., Hiltunen, Mikko, Hinttala, Reetta, Hovatta, Iiris, Hu, Xinli, Huertas-Vazquez, Adriana, Huilaja, Laura, Hunkapiller, Julie, Jacob, Howard, Jensen, Jan-Nygaard, Joensuu, Heikki, John, Sally, Julkunen, Valtteri, Jung, Marc, Junttila, Juhani, Kaarniranta, Kai, Kähönen, Mika, Kajanne, Risto, Kallio, Lila, Kälviäinen, Reetta, Kaprio, Jaakko, Kerimov, Nurlan, Kettunen, Johannes, Kilpeläinen, Elina, Kilpi, Terhi, Klinger, Katherine, Kosma, Veli-Matti, Kuopio, Teijo, Kurra, Venla, Laisk, Triin, Laukkanen, Jari, Lawless, Nathan, Liu, Aoxing, Longerich, Simonne, Mägi, Reedik, Mäkelä, Johanna, Mäkitie, Antti, Malarstig, Anders, Mannermaa, Arto, Maranville, Joseph, Matakidou, Athena, Meretoja, Tuomo, Mozaffari, Sahar V., Niemi, Mari E. K., Niemi, Marianna, Niiranen, Teemu, O´Donnell, Christopher J., Obeidat, Ma´en, Okafo, George, Ollila, Hanna M., Palomäki, Antti, Palotie, Tuula, Partanen, Jukka, Paul, Dirk S., Pelkonen, Margit, Pendergrass, Rion K., Petrovski, Slavé, Pitkäranta, Anne, Platt, Adam, Pulford, David, Punkka, Eero, Pussinen, Pirkko, Raghavan, Neha, Rahimov, Fedik, Rajpal, Deepak, Renaud, Nicole A., Riley-Gillis, Bridget, Rodosthenous, Rodosthenis, Saarentaus, Elmo, Salminen, Aino, Salminen, Eveliina, Salomaa, Veikko, Schleutker, Johanna, Serpi, Raisa, Shen, Huei-yi, Siegel, Richard, Silander, Kaisa, Siltanen, Sanna, Soini, Sirpa, Soininen, Hilkka, Sul, Jae Hoon, Tachmazidou, Ioanna, Tasanen, Kaisa, Tienari, Pentti, Toppila-Salmi, Sanna, Tukiainen, Taru, Tuomi, Tiinamaija, Turunen, Joni A., Ulirsch, Jacob C., Vaura, Felix, Virolainen, Petri, Waring, Jeffrey, Waterworth, Dawn, Yang, Robert, Nelis, Mari, Reigo, Anu, Metspalu, Andres, Milani, Lili, Esko, Tõnu, Fox, Caroline, Havulinna, Aki S., Perola, Markus, Ripatti, Samuli, Jalanko, Anu, Laitinen, Tarja, Mäkelä, Tomi P., Plenge, Robert, McCarthy, Mark, Runz, Heiko, Daly, Mark J., and Palotie, Aarno

Published
2023
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36. The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections

Author

Palotie, Aarno, Daly, Mark, Riley-Gills, Bridget, Jacob, Howard, Paul, Dirk, Petrovski, Slavé, Runz, Heiko, John, Sally, Okafo, George, Lawless, Nathan, Salminen-Mankonen, Heli, Plenge, Robert, Maranville, Joseph, McCarthy, Mark, Ehm, Margaret G., Auro, Kirsi, Longerich, Simonne, Mälarstig, Anders, Klinger, Katherine, Chatelain, Clement, Gossel, Matthias, Estrada, Karol, Graham, Robert, Yang, Robert, O´Donnell, Chris, Mäkelä, Tomi P., Kaprio, Jaakko, Virolainen, Petri, Hakanen, Antti, Kilpi, Terhi, Perola, Markus, Partanen, Jukka, Pitkäranta, Anne, Raivio, Taneli, Tikkanen, Jani, Serpi, Raisa, Laitinen, Tarja, Kosma, Veli-Matti, Laukkanen, Jari, Hautalahti, Marco, Tuovila, Outi, Pakkanen, Raimo, Waring, Jeffrey, Riley-Gillis, Bridget, Rahimov, Fedik, Tachmazidou, Ioanna, Chen, Chia-Yen, Ding, Zhihao, Jung, Marc, Biswas, Shameek, Pendergrass, Rion, Pulford, David, Raghavan, Neha, Huertas-Vazquez, Adriana, Sul, Jae-Hoon, Hu, Xinli, Hedman, Åsa, Rivas, Manuel, Waterworth, Dawn, Renaud, Nicole, Obeidat, Ma´en, Ripatti, Samuli, Schleutker, Johanna, Arvas, Mikko, Carpén, Olli, Hinttala, Reetta, Kettunen, Johannes, Mannermaa, Arto, Aalto-Setälä, Katriina, Kähönen, Mika, Mäkelä, Johanna, Kälviäinen, Reetta, Julkunen, Valtteri, Soininen, Hilkka, Remes, Anne, Hiltunen, Mikko, Peltola, Jukka, Raivio, Minna, Tienari, Pentti, Rinne, Juha, Kallionpää, Roosa, Partanen, Juulia, Abbasi, Ali, Ziemann, Adam, Smaoui, Nizar, Lehtonen, Anne, Eaton, Susan, Lahdenperä, Sanni, Bowers, Natalie, Teng, Edmond, Xu, Fanli, Addis, Laura, Eicher, John, Li, Qingqin S., He, Karen, Khramtsova, Ekaterina, Färkkilä, Martti, Koskela, Jukka, Pikkarainen, Sampsa, Jussila, Airi, Kaukinen, Katri, Blomster, Timo, Kiviniemi, Mikko, Voutilainen, Markku, Lu, Tim, McCarthy, Linda, Hart, Amy, Guan, Meijian, Miller, Jason, Kalpala, Kirsi, Miller, Melissa, Eklund, Kari, Palomäki, Antti, Isomäki, Pia, Pirilä, Laura, Kaipiainen-Seppänen, Oili, Huhtakangas, Johanna, Mars, Nina, Lertratanakul, Apinya, Viollet, Coralie, Hochfeld, Marla, Gordillo, Jorge Esparza, Farias, Fabiana, Bing, Nan, Pelkonen, Margit, Kauppi, Paula, Kankaanranta, Hannu, Harju, Terttu, Lahesmaa, Riitta, Chen, Hubert, Betts, Joanna, Mishra, Rajashree, Mouded, Majd, Ngo, Debby, Niiranen, Teemu, Vaura, Felix, Salomaa, Veikko, Metsärinne, Kaj, Aittokallio, Jenni, Hernesniemi, Jussi, Gordin, Daniel, Sinisalo, Juha, Taskinen, Marja-Riitta, Tuomi, Tiinamaija, Hiltunen, Timo, Elliott, Amanda, Reeve, Mary Pat, Ruotsalainen, Sanni, Chu, Audrey, Reilly, Dermot, Mendelson, Mike, Parkkinen, Jaakko, Meretoja, Tuomo, Joensuu, Heikki, Mattson, Johanna, Salminen, Eveliina, Auranen, Annika, Karihtala, Peeter, Auvinen, Päivi, Elenius, Klaus, Pitkänen, Esa, Popovic, Relja, Fabre, Margarete, Schutzman, Jennifer, Kulkarni, Diptee, Porello, Alessandro, Loboda, Andrey, Lehtonen, Heli, McDonough, Stefan, Vuoti, Sauli, Kaarniranta, Kai, Turunen, Joni A., Ollila, Terhi, Uusitalo, Hannu, Karjalainen, Juha, Liu, Mengzhen, Loomis, Stephanie, Strauss, Erich, Chen, Hao, Tasanen, Kaisa, Huilaja, Laura, Hannula-Jouppi, Katariina, Salmi, Teea, Peltonen, Sirkku, Koulu, Leena, Choy, David, Wu, Ying, Pussinen, Pirkko, Salminen, Aino, Salo, Tuula, Rice, David, Nieminen, Pekka, Palotie, Ulla, Siponen, Maria, Suominen, Liisa, Mäntylä, Päivi, Gursoy, Ulvi, Anttonen, Vuokko, Sipilä, Kirsi, Laivuori, Hannele, Kurra, Venla, Kotaniemi-Talonen, Laura, Heikinheimo, Oskari, Kalliala, Ilkka, Aaltonen, Lauri, Jokimaa, Varpu, Vääräsmäki, Marja, Uimari, Outi, Morin-Papunen, Laure, Niinimäki, Maarit, Piltonen, Terhi, Kivinen, Katja, Widen, Elisabeth, Tukiainen, Taru, Välimäki, Niko, Laakkonen, Eija, Tyrmi, Jaakko, Silven, Heidi, Sliz, Eeva, Arffman, Riikka, Savukoski, Susanna, Laisk, Triin, Pujol, Natalia, Kumar, Janet, Hovatta, Iiris, Isometsä, Erkki, Ollila, Hanna, Suvisaari, Jaana, Als, Thomas Damm, Mäkitie, Antti, Bizaki-Vallaskangas, Argyro, Toppila-Salmi, Sanna, Willberg, Tytti, Saarentaus, Elmo, Aarnisalo, Antti, Rahikkala, Elisa, Aittomäki, Kristiina, Åberg, Fredrik, Kurki, Mitja, Havulinna, Aki, Mehtonen, Juha, Palta, Priit, Hassan, Shabbeer, Della Briotta Parolo, Pietro, Zhou, Wei, Maasha, Mutaamba, Lemmelä, Susanna, Liu, Aoxing, Lehisto, Arto, Ganna, Andrea, Llorens, Vincent, Heyne, Henrike, Rämö, Joel, Rodosthenous, Rodos, Strausz, Satu, Palotie, Tuula, Palin, Kimmo, Garcia-Tabuenca, Javier, Siirtola, Harri, Kiiskinen, Tuomo, Lee, Jiwoo, Tsuo, Kristin, Kristiansson, Kati, Hyvärinen, Kati, Ritari, Jarmo, Pylkäs, Katri, Karjalainen, Minna, Mantere, Tuomo, Kangasniemi, Eeva, Heikkinen, Sami, Pitkänen, Nina, Lessard, Samuel, Chatelain, Clément, Kallio, Lila, Wahlfors, Tiina, Punkka, Eero, Siltanen, Sanna, Kuopio, Teijo, Jalanko, Anu, Shen, Huei-Yi, Kajanne, Risto, Aavikko, Mervi, Leinonen, Rasko, Palin, Henna, Linna, Malla-Maria, Kanai, Masahiro, Zheng, Zhili, Lahtela, L. Elisa, Kaunisto, Mari, Kilpeläinen, Elina, Sipilä, Timo P., Dada, Oluwaseun Alexander, Ghazal, Awaisa, Kytölä, Anastasia, Weldatsadik, Rigbe, Donner, Kati, Loukola, Anu, Laiho, Päivi, Sistonen, Tuuli, Kaiharju, Essi, Laukkanen, Markku, Järvensivu, Elina, Lähteenmäki, Sini, Männikkö, Lotta, Wong, Regis, Toivola, Auli, Brunfeldt, Minna, Mattsson, Hannele, Koskelainen, Sami, Hiekkalinna, Tero, Paajanen, Teemu, Pärn, Kalle, Kals, Mart, Luo, Shuang, Padmanabhuni, Shanmukha Sampath, Niemi, Marianna, Gracia-Tabuenca, Javier, Helminen, Mika, Luukkaala, Tiina, Vähätalo, Iida, Tammerluoto, Jyrki, Smith, Sarah, Southerington, Tom, Lehto, Petri, Jones, Samuel E., Maisha, Fahrisa I., Strausz, Satu J., Lammi, Vilma, Cade, Brian E., Tervi, Anniina, Helaakoski, Viola, Broberg, Martin E., Lane, Jacqueline M., Redline, Susan, Saxena, Richa, and Ollila, Hanna M.

Published
2023
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49. Risk of Midlife Stroke After Adverse Pregnancy Outcomes: The FinnGen Study

Author

Miller, Eliza C., Kauko, Anni, Tom, Sarah E., Laivuori, Hannele, Niiranen, Teemu, Bello, Natalie A., Palotie, Aarno, Daly, Mark, Riley-Gills, Bridget, Jacob, Howard, Paul, Dirk, Matakidou, Athena, Platt, Adam, Runz, Heiko, John, Sally, Okafo, George, Lawless, Nathan, Salminen-Mankonen, Heli, Plenge, Robert, Maranville, Joseph, McCarthy, Mark, Hunkapiller, Julie, Ehm, Margaret G., Auro, Kirsi, Longerich, Simonne, Fox, Caroline, Mälarstig, Anders, Klinger, Katherine, Raipal, Deepak, Green, Eric, Graham, Robert, Yang, Robert, Donnell, Chris O´, Mäkelä, Tomi P., Kaprio, Jaakko, Virolainen, Petri, Hakanen, Antti, Kilpi, Terhi, Perola, Markus, Partanen, Jukka, Pitkäranta, Anne, Raivio, Taneli, Serpi, Raisa, Laitinen, Tarja, Kosma, Veli-Matti, Laukkanen, Jari, Hautalahti, Marco, Tuovila, Outi, Pakkanen, Raimo, Waring, Jeffrey, Riley-Gillis, Bridget, Rahimov, Fedik, Tachmazidou, Ioanna, Chen, Chia-Yen, Runz, Heiko, Ding, Zhihao, Jung, Marc, Biswas, Shameek, Pendergrass, Rion, Hunkapiller, Julie, Ehm, Margaret G., Pulford, David, Raghavan, Neha, Huertas-Vazquez, Adriana, Sul, Jae-Hoon, Mälarstig, Anders, Hu, Xinli, Klinger, Katherine, Graham, Robert, Green, Eric, Mozaffari, Sahar, Waterworth, Dawn, Renaud, Nicole, Obeidat, Ma´en, Ripatti, Samuli, Schleutker, Johanna, Perola, Markus, Arvas, Mikko, Carpén, Olli, Hinttala, Reetta, Kettunen, Johannes, Mannermaa, Arto, Aalto-Setälä, Katriina, Kähönen, Mika, Laukkanen, Jari, Mäkelä, Johanna, Kälviäinen, Reetta, Julkunen, Valtteri, Soininen, Hilkka, Remes, Anne, Hiltunen, Mikko, Peltola, Jukka, Raivio, Minna, Tienari, Pentti, Rinne, Juha, Kallionpää, Roosa, Partanen, Juulia, Abbasi, Ali, Ziemann, Adam, Smaoui, Nizar, Lehtonen, Anne, Eaton, Susan, Runz, Heiko, Lahdenperä, Sanni, Biswas, Shameek, Hunkapiller, Julie, Bowers, Natalie, Teng, Edmond, Pendergrass, Rion, Xu, Fanli, Pulford, David, Auro, Kirsi, Addis, Laura, Eicher, John, Li, Qingqin S, He, Karen, Khramtsova, Ekaterina, Raghavan, Neha, Färkkilä, Martti, Koskela, Jukka, Pikkarainen, Sampsa, Jussila, Airi, Kaukinen, Katri, Blomster, Timo, Kiviniemi, Mikko, Voutilainen, Markku, Daly, Mark, Abbasi, Ali, Waring, Jeffrey, Smaoui, Nizar, Rahimov, Fedik, Lehtonen, Anne, Lu, Tim, Bowers, Natalie, Pendergrass, Rion, McCarthy, Linda, Hart, Amy, Guan, Meijian, Miller, Jason, Kalpala, Kirsi, Miller, Melissa, Hu, Xinli, Eklund, Kari, Palomäki, Antti, Isomäki, Pia, Pirilä, Laura, Kaipiainen-Seppänen, Oili, Huhtakangas, Johanna, Mars, Nina, Abbasi, Ali, Waring, Jeffrey, Rahimov, Fedik, Lertratanakul, Apinya, Smaoui, Nizar, Lehtonen, Anne, Hochfeld, Marla, Bowers, Natalie, Pendergrass, Rion, Esparza Gordillo, Jorge, Auro, Kirsi, Waterworth, Dawn, Farias, Fabiana, Kalpala, Kirsi, Bing, Nan, Hu, Xinli, Laitinen, Tarja, Pelkonen, Margit, Kauppi, Paula, Kankaanranta, Hannu, Harju, Terttu, Lahesmaa, Riitta, Smaoui, Nizar, Lassi, Glenda, Eaton, Susan, Chen, Hubert, Pendergrass, Rion, Bowers, Natalie, Betts, Joanna, Auro, Kirsi, Mishra, Rajashree, Mouded, Majd, Ngo, Debby, Vaura, Felix, Salomaa, Veikko, Metsärinne, Kaj, Aittokallio, Jenni, Kähönen, Mika, Hernesniemi, Jussi, Gordin, Daniel, Sinisalo, Juha, Taskinen, Marja-Riitta, Tuomi, Tiinamaija, Hiltunen, Timo, Laukkanen, Jari, Elliott, Amanda, Pat Reeve, Mary, Ruotsalainen, Sanni, Challis, Benjamin, Paul, Dirk, Hunkapiller, Julie, Bowers, Natalie, Pendergrass, Rion, Chu, Audrey, Auro, Kirsi, Reilly, Dermot, Mendelson, Mike, Parkkinen, Jaakko, Miller, Melissa, Meretoja, Tuomo, Joensuu, Heikki, Carpén, Olli, Mattson, Johanna, Salminen, Eveliina, Auranen, Annika, Karihtala, Peeter, Elenius, Päivi Auvinen Klaus, Schleutker, Johanna, Pitkänen, Esa, Mars, Nina, Daly, Mark, Popovic, Relja, Waring, Jeffrey, Riley-Gillis, Bridget, Lehtonen, Anne, Schutzman, Jennifer, Hunkapiller, Julie, Bowers, Natalie, Pendergrass, Rion, Kulkarni, Diptee, Auro, Kirsi, Porello, Alessandro, Loboda, Andrey, Lehtonen, Heli, McDonough, Stefan, Vuoti, Sauli, Kaarniranta, Kai, Turunen, Joni A, Ollila, Terhi, Uusitalo, Hannu, Karjalainen, Juha, Pitkänen, Esa, Liu, Mengzhen, Runz, Heiko, Loomis, Stephanie, Strauss, Erich, Bowers, Natalie, Chen, Hao, Pendergrass, Rion, Tasanen, Kaisa, Huilaja, Laura, Hannula-Jouppi, Katariina, Salmi, Teea, Peltonen, Sirkku, Koulu, Leena, Smaoui, Nizar, Rahimov, Fedik, Lehtonen, Anne, Choy, David, Pendergrass, Rion, Waterworth, Dawn, Kalpala, Kirsi, Wu, Ying, Pussinen, Pirkko, Salminen, Aino, Salo, Tuula, Rice, David, Nieminen, Pekka, Palotie, Ulla, Siponen, Maria, Suominen, Liisa, Mäntylä, Päivi, Gursoy, Ulvi, Anttonen, Vuokko, Sipilä, Kirsi, Pendergrass, Rion, Kurra, Venla, Kotaniemi-Talonen, Laura, Heikinheimo, Oskari, Kalliala, Ilkka, Aaltonen, Lauri, Jokimaa, Varpu, Kettunen, Johannes, Vääräsmäki, Marja, Uimari, Outi, Morin-Papunen, Laure, Niinimäki, Maarit, Piltonen, Terhi, Kivinen, Katja, Widen, Elisabeth, Tukiainen, Taru, Pat Reeve, Mary, Daly, Mark, Välimäki, Niko, Laakkonen, Eija, Tyrmi, Jaakko, Silven, Heidi, Sliz, Eeva, Arffman, Riikka, Savukoski, Susanna, Laisk, Triin, Pujol, Natalia, Liu, Mengzhen, Riley-Gillis, Bridget, Pendergrass, Rion, Kumar, Janet, Auro, Kirsi, Hovatta, Iiris, Chen, Chia-Yen, Isometsä, Erkki, Ollila, Hanna, Suvisaari, Jaana, Damm Als, Thomas, Mäkitie, Antti, Bizaki-Vallaskangas, Argyro, Toppila-Salmi, Sanna, Willberg, Tytti, Saarentaus, Elmo, Aarnisalo, Antti, Salminen, Eveliina, Rahikkala, Elisa, Kettunen, Johannes, Aittomäki, Kristiina, Åberg, Fredrik, Kurki, Mitja, Ripatti, Samuli, Daly, Mark, Karjalainen, Juha, Havulinna, Aki, Mehtonen, Juha, Palta, Priit, Hassan, Shabbeer, Della, Pietro, Parolo, Briotta, Zhou, Wei, Maasha, Mutaamba, Hassan, Shabbeer, Lemmelä, Susanna, Rivas, Manuel, Niemi, Mari E., Palotie, Aarno, Liu, Aoxing, Lehisto, Arto, Ganna, Andrea, Llorens, Vincent, Tukiainen, Taru, Pat Reeve, Mary, Heyne, Henrike, Mars, Nina, Rämö, Joel, Saarentaus, Elmo, Ollila, Hanna, Rodosthenous, Rodos, Strausz, Satu, Palotie, Tuula, Palin, Kimmo, Garcia-Tabuenca, Javier, Siirtola, Harri, Kiiskinen, Tuomo, Lee, Jiwoo, Tsuo, Kristin, Elliott, Amanda, Kristiansson, Kati, Arvas, Mikko, Hyvärinen, Kati, Ritari, Jarmo, Carpén, Olli, Kettunen, Johannes, Pylkäs, Katri, Sliz, Eeva, Karjalainen, Minna, Mantere, Tuomo, Kangasniemi, Eeva, Heikkinen, Sami, Mannermaa, Arto, Laakkonen, Eija, Pitkänen, Nina, Lessard, Samuel, Chatelain, Clément, Terho, Perttu, Soini, Sirpa, Partanen, Jukka, Punkka, Eero, Serpi, Raisa, Siltanen, Sanna, Kosma, Veli-Matti, Kuopio, Teijo, Jalanko, Anu, Shen, Huei-Yi, Kajanne, Risto, Aavikko, Mervi, Palin, Henna, Linna, Malla-Maria, Kurki, Mitja, Karjalainen, Juha, Della, Pietro, Parolo, Briotta, Lehisto, Arto, Mehtonen, Juha, Zhou, Wei, Kanai, Masahiro, Maasha, Mutaamba, Havulinna, Aki, Lemmelä, Susanna, Kiiskinen, Tuomo, Elisa Lahtela, L., Kaunisto, Mari, Kilpeläinen, Elina, Sipilä, Timo P., Alexander Dada, Oluwaseun, Ghazal, Awaisa, Kytölä, Anastasia, Weldatsadik, Rigbe, Ruotsalainen, Sanni, Donner, Kati, Sipilä, Timo P., Loukola, Anu, Laiho, Päivi, Sistonen, Tuuli, Kaiharju, Essi, Laukkanen, Markku, Järvensivu, Elina, Lähteenmäki, Sini, Männikkö, Lotta, Wong, Regis, Toivola, Auli, Brunfeldt, Minna, Mattsson, Hannele, Kristiansson, Kati, Lemmelä, Susanna, Koskelainen, Sami, Hiekkalinna, Tero, Paajanen, Teemu, Palta, Priit, Pärn, Kalle, Kals, Mart, Luo, Shuang, Laitinen, Tarja, Pat Reeve, Mary, Sampath Padmanabhuni, Shanmukha, Niemi, Marianna, Siirtola, Harri, Gracia-Tabuenca, Javier, Helminen, Mika, Luukkaala, Tiina, Vähätalo, Iida, Pitkänen, Jyrki, Hautalahti, Marco, Mäkelä, Johanna, Smith, Sarah, and Southerington, Tom

Published
2023
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