87 results on '"Kaiyang Zhang"'
Search Results
2. Stable hydrogen evolution reaction at high current densities via designing the Ni single atoms and Ru nanoparticles linked by carbon bridges
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Rui Yao, Kaian Sun, Kaiyang Zhang, Yun Wu, Yujie Du, Qiang Zhao, Guang Liu, Chen Chen, Yuhan Sun, and Jinping Li
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Science - Abstract
Abstract Continuous and effective hydrogen evolution under high current densities remains a challenge for water electrolysis owing to the rapid performance degradation under continuous large-current operation. In this study, theoretical calculations, operando Raman spectroscopy, and CO stripping experiments confirm that Ru nanocrystals have a high resistance against deactivation because of the synergistic adsorption of OH intermediates (OHad) on the Ru and single atoms. Based on this conceptual model, we design the Ni single atoms modifying ultra-small Ru nanoparticle with defect carbon bridging structure (UP-RuNiSAs/C) via a unique unipolar pulse electrodeposition (UPED) strategy. As a result, the UP-RuNiSAs/C is found capable of running steadily for 100 h at 3 A cm−2, and shows a low overpotential of 9 mV at a current density of 10 mA cm−2 under alkaline conditions. Moreover, the UP-RuNiSAs/C allows an anion exchange membrane (AEM) electrolyzer to operate stably at 1.95 Vcell for 250 h at 1 A cm−2.
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- 2024
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3. ROR1-STAT3 signaling contributes to ovarian cancer intra-tumor heterogeneity
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Emilia Piki, Alice Dini, Juuli Raivola, Kari Salokas, Kaiyang Zhang, Markku Varjosalo, Teijo Pellinen, Katja Välimäki, Kristina Tabor Veskimäe, Synnöve Staff, Sampsa Hautaniemi, Astrid Murumägi, and Daniela Ungureanu
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Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 ,Cytology ,QH573-671 - Abstract
Abstract Wnt pathway dysregulation through genetic and non-genetic alterations occurs in multiple cancers, including ovarian cancer (OC). The aberrant expression of the non-canonical Wnt signaling receptor ROR1 is thought to contribute to OC progression and drug resistance. However, the key molecular events mediated by ROR1 that are involved in OC tumorigenesis are not fully understood. Here, we show that ROR1 expression is enhanced by neoadjuvant chemotherapy, and Wnt5a binding to ROR1 can induce oncogenic signaling via AKT/ERK/STAT3 activation in OC cells. Proteomics analysis of isogenic ROR1-knockdown OC cells identified STAT3 as a downstream effector of ROR1 signaling. Transcriptomics analysis of clinical samples (n = 125) revealed that ROR1 and STAT3 are expressed at higher levels in stromal cells than in epithelial cancer cells of OC tumors, and these findings were corroborated by multiplex immunohistochemistry (mIHC) analysis of an independent OC cohort (n = 11). Our results show that ROR1 and its downstream STAT3 are co-expressed in epithelial as well as stromal cells of OC tumors, including cancer-associated fibroblasts or CAFs. Our data provides the framework to expand the clinical utility of ROR1 as a therapeutic target to overcome OC progression.
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- 2023
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4. Robust iterative learning model predictive control for repetitive motion of maglev planar motor
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Kaiyang Zhang, Fengqiu Xu, and Xianze Xu
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Applications of electric power ,TK4001-4102 - Abstract
Abstract This paper presents a robust iterative learning model predictive control (RILMPC) scheme for repetitive trajectory tracking of a magnetically levitated (maglev) planar motor. The motivation lies in the improvement of tracking performance and disturbance rejection ability for the maglev system. Relying on the past error in the repetitive motion, the model discrepancy is persistently compensated with iterations to improve the prediction accuracy. The cost function that serves as the upper bound of the tracking error is then derived from the past control trajectory based on the Lipschitz property of disturbances. In the proposed RILMPC scheme, a minimal robust positive invariant set is introduced into the MPC optimisation to cope with unmodeled dynamics and disturbances. Furthermore, it is theoretically shown that the perturbed closed‐loop system is stable, and the proposed RILMPC scheme is recursively feasible with perfect tracking performance under some conditions. Finally, comparative experiments carried out on a maglev planar motor demonstrate that the proposed control strategy possesses satisfactory transient/steady‐state tracking performance and robustness against disturbances.
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- 2022
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5. Multiomics characterization implicates PTK7 in ovarian cancer EMT and cell plasticity and offers strategies for therapeutic intervention
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Juuli Raivola, Alice Dini, Hanna Karvonen, Emilia Piki, Kari Salokas, Wilhelmiina Niininen, Laura Kaleva, Kaiyang Zhang, Mariliina Arjama, Greta Gudoityte, Brinton Seashore-Ludlow, Markku Varjosalo, Olli Kallioniemi, Sampsa Hautaniemi, Astrid Murumägi, and Daniela Ungureanu
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Cytology ,QH573-671 - Abstract
Abstract Most patients with ovarian cancer (OC) are diagnosed at a late stage when there are very few therapeutic options and a poor prognosis. This is due to the lack of clearly defined underlying mechanisms or an oncogenic addiction that can be targeted pharmacologically, unlike other types of cancer. Here, we identified protein tyrosine kinase 7 (PTK7) as a potential new therapeutic target in OC following a multiomics approach using genetic and pharmacological interventions. We performed proteomics analyses upon PTK7 knockdown in OC cells and identified novel downstream effectors such as synuclein-γ (SNCG), SALL2, and PP1γ, and these findings were corroborated in ex vivo primary samples using PTK7 monoclonal antibody cofetuzumab. Our phosphoproteomics analyses demonstrated that PTK7 modulates cell adhesion and Rho-GTPase signaling to sustain epithelial-mesenchymal transition (EMT) and cell plasticity, which was confirmed by high-content image analysis of 3D models. Furthermore, using high-throughput drug sensitivity testing (525 drugs) we show that targeting PTK7 exhibited synergistic activity with chemotherapeutic agent paclitaxel, CHK1/2 inhibitor prexasertib, and PLK1 inhibitor GSK461364, among others, in OC cells and ex vivo primary samples. Taken together, our study provides unique insight into the function of PTK7, which helps to define its role in mediating aberrant Wnt signaling in ovarian cancer.
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- 2022
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6. Co-evolution of matrisome and adaptive adhesion dynamics drives ovarian cancer chemoresistance
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Elina A. Pietilä, Jordi Gonzalez-Molina, Lidia Moyano-Galceran, Sanaz Jamalzadeh, Kaiyang Zhang, Laura Lehtinen, S. Pauliina Turunen, Tomás A. Martins, Okan Gultekin, Tarja Lamminen, Katja Kaipio, Ulrika Joneborg, Johanna Hynninen, Sakari Hietanen, Seija Grénman, Rainer Lehtonen, Sampsa Hautaniemi, Olli Carpén, Joseph W. Carlson, and Kaisa Lehti
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Science - Abstract
Platinum chemotherapy is standard of care in ovarian cancers but treatment resistance commonly develops. Here, the authors show that the extracellular microenvironment is modulated following chemotherapy and the changes in matrix proteins and stiffness alter the cell death response of tumour cells.
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- 2021
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7. miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data.
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Ariel A Hippen, Matias M Falco, Lukas M Weber, Erdogan Pekcan Erkan, Kaiyang Zhang, Jennifer Anne Doherty, Anna Vähärautio, Casey S Greene, and Stephanie C Hicks
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Biology (General) ,QH301-705.5 - Abstract
Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a 'low-quality' cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC.
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- 2021
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8. Development of Magnetically Levitated Rotary Table for Repetitive Trajectory Tracking
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Fengqiu Xu, Kaiyang Zhang, and Xianze Xu
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magnetic levitation system ,rotary table ,disturbance compensation ,iterative learning control ,trajectory tracking ,Chemical technology ,TP1-1185 - Abstract
The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area.
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- 2022
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9. Characterization of a Pyrethroid-Degrading Pseudomonas fulva Strain P31 and Biochemical Degradation Pathway of D-Phenothrin
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Jingjing Yang, Yanmei Feng, Hui Zhan, Jie Liu, Fang Yang, Kaiyang Zhang, Lianhui Zhang, and Shaohua Chen
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bioremediation ,D-phenothrin ,Pseudomonas fulva ,metabolites ,degradation pathway ,Microbiology ,QR1-502 - Abstract
D-phenothrin is one of the most popular pyrethroid insecticides for its broad spectrum and high insecticidal activity. However, continuous use of D-phenothrin has resulted in serious environmental contamination and raised public concern about its impact on human health. Biodegradation of D-phenothrin has never been investigated and its metabolic behaviors remain unknown. Here, a novel bacterial strain P31 was isolated from active sludge, which completely degraded (100%) D-phenothrin at 50 mg⋅L-1 in 72 h. Based on the morphology, 16S rRNA gene and Biolog tests, the strain was identified as Pseudomonas fulva. Biodegradation conditions were optimized as 29.5°C and pH 7.3 by utilizing response surface methodology. Strain P31 depicted high tolerance and strong D-phenothrin degradation ability through hydrolysis pathway. Strain P31 degraded D-phenothrin at inhibition constant (Ki) of 482.1673 mg⋅L-1 and maximum specific degradation constant (qmax) of 0.0455 h-1 whereas critical inhibitor concentration remained as 41.1189 mg⋅L-1. The 3-Phenoxybenzaldehyde and 1,2-benzenedicarboxylic butyl dacyl ester were identified as the major intermediate metabolites of D-phenothrin degradation pathway through high-performance liquid chromatography and gas chromatography-mass spectrometry. Bioaugmentation of D-phenothrin-contaminated soils with strain P31 dramatically enhanced its degradation, and over 75% of D-phenothrin was removed from soils within 10 days. Moreover, the strain illustrated a remarkable capacity to degrade other synthetic pyrethroids, including permethrin, cyhalothrin, β-cypermethrin, deltamethrin, fenpropathrin, and bifenthrin, exhibiting great potential in bioremediation of pyrethroid-contaminated environment.
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- 2018
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10. The Ink4a/Arf locus operates as a regulator of the circadian clock modulating RAS activity.
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Rukeia El-Athman, Nikolai N Genov, Jeannine Mazuch, Kaiyang Zhang, Yong Yu, Luise Fuhr, Mónica Abreu, Yin Li, Thomas Wallach, Achim Kramer, Clemens A Schmitt, and Angela Relógio
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Biology (General) ,QH301-705.5 - Abstract
The mammalian circadian clock and the cell cycle are two major biological oscillators whose coupling influences cell fate decisions. In the present study, we use a model-driven experimental approach to investigate the interplay between clock and cell cycle components and the dysregulatory effects of RAS on this coupled system. In particular, we focus on the Ink4a/Arf locus as one of the bridging clock-cell cycle elements. Upon perturbations by the rat sarcoma viral oncogene (RAS), differential effects on the circadian phenotype were observed in wild-type and Ink4a/Arf knock-out mouse embryonic fibroblasts (MEFs), which could be reproduced by our modelling simulations and correlated with opposing cell cycle fate decisions. Interestingly, the observed changes can be attributed to in silico phase shifts in the expression of core-clock elements. A genome-wide analysis revealed a set of differentially expressed genes that form an intricate network with the circadian system with enriched pathways involved in opposing cell cycle phenotypes. In addition, a machine learning approach complemented by cell cycle analysis classified the observed cell cycle fate decisions as dependent on Ink4a/Arf and the oncogene RAS and highlighted a putative fine-tuning role of Bmal1 as an elicitor of such processes, ultimately resulting in increased cell proliferation in the Ink4a/Arf knock-out scenario. This indicates that the dysregulation of the core-clock might work as an enhancer of RAS-mediated regulation of the cell cycle. Our combined in silico and in vitro approach highlights the important role of the circadian clock as an Ink4a/Arf-dependent modulator of oncogene-induced cell fate decisions, reinforcing its function as a tumour-suppressor and the close interplay between the clock and the cell cycle network.
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- 2017
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11. Error-Bounded Tracking of Maglev Planar Motor Based on Robust Model Predictive Control
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Kaiyang Zhang, Fengqiu Xu, and Xianze Xu
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Control and Systems Engineering ,Electrical and Electronic Engineering - Published
- 2023
12. Real-Time Application of Robust Offset-Free MPC in Maglev Planar Machine
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Fengqiu Xu, Yang Shi, Kaiyang Zhang, and Xianze Xu
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Control and Systems Engineering ,Electrical and Electronic Engineering - Published
- 2023
13. Organic ligand-assisted synthesis of Ir0.3Cr0.7O2 solid solution oxides for efficient oxygen evolution in acidic media
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Kaiyang Zhang, Yujie Du, Yun Wu, Rui Yao, Qiang Zhao, Jinping Li, and Guang Liu
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Fuel Technology ,Renewable Energy, Sustainability and the Environment ,Energy Engineering and Power Technology ,Condensed Matter Physics - Published
- 2023
14. 6-DoF Magnetically Levitated Rotary Table With Dynamic Numerical Force and Torque Regulator
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Fengqiu Xu, Kaiyang Zhang, Xianze Xu, and Ruotong Peng
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Physics ,Control and Systems Engineering ,Control theory ,Regulator ,Table (database) ,Torque ,Electrical and Electronic Engineering ,Computer Science Applications - Published
- 2022
15. Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high grade serous carcinoma
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Alexandra Lahtinen, Kari Lavikka, Anni Virtanen, Yilin Li, Sanaz Jamalzadeh, Aikaterini Skorda, Anna Røssberg Lauridsen, Kaiyang Zhang, Giovanni Marchi, Veli-Matti Isoviita, Valeria Ariotta, Oskari Lehtonen, Taru A. Muranen, Kaisa Huhtinen, Olli Carpén, Sakari Hietanen, Wojciech Senkowski, Tuula Kallunki, Antti Häkkinen, Johanna Hynninen, Jaana Oikkonen, and Sampsa Hautaniemi
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Cancer Research ,Oncology - Published
- 2023
16. A novel Energy Landscape method incorporating the Latent Dirichlet Allocation topic model and the pairwise Maximum Entropy model, revealing the significant contribution of Bactericides to the development of Inflammatory Bowel Disease
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Kaiyang Zhang and Shinji Nakaoka
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1AbstractThe dysbiosis of microbiota has been reported to be associated with numerous human pathophysiological processes, including Inflammatory Bowel Disease (IBD). With advancements in highthroughput sequencing, various methods have been developed to study the alteration of microbiota in the development and progression of diseases. However, a suitable approach to assess the global stability of the microbiota in disease states through time-series microbiome data is yet to be established. In this study, we introduce a novel Energy Landscape construction method, which incorporates the Latent Dirichlet Allocation (LDA) model and the pairwise Maximum Entropy (MaxEnt) model, and demonstrate its utility by applying it to an IBD time-series dataset. Through this method, we obtained the “energy” profile for the potential patterns of microbiota to occur under disease, indicating their stability and prevalence. The results suggest the potential contribution of several microbial genera, includingBacteroides, Alistipes, andFaecalibacterium, as well as their interactions, to the development of IBD. Our proposed method provides a novel and insightful tool for understanding the alteration and stability of the microbiota under disease states and offers a more holistic view of its complex dynamics at play in microbiota-mediated disease.
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- 2023
17. Adjusting the viscosity of silver nanowire ink for promoting the uniformity and conductivity of transparent electrode
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Shanyong Chen, Kaiyang Zhang, Kai Yang, and Wei Xiao
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Electrical and Electronic Engineering ,Condensed Matter Physics ,Atomic and Molecular Physics, and Optics ,Electronic, Optical and Magnetic Materials - Published
- 2023
18. Ultra-small RuO2/NHC nanocrystal electrocatalysts with efficient water oxidation activities in acidic media
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Yujie Du, Kaiyang Zhang, Rui Yao, Yun Wu, Qiang Zhao, Jinping Li, and Guang Liu
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Inorganic Chemistry - Abstract
RuO2/NHC3 with ultra-small and abundant electrochemically active sites requires a low overpotential of 186 mV at 10 mA cm−2 for acidic OER and maintains wonderful long-term stability within 27 h in 0.5 M H2SO4.
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- 2022
19. picoCTF 2013 - Toaster Wars: When interactive storytelling game meets the largest computer security competition.
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Kaiyang Zhang, Shihao Dong, Guoliang Zhu, Danielle Corporon, Tim McMullan, and Salvador Barrera
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- 2013
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20. Enriching redox active sites by interconnected nanowalls-like nickel cobalt phospho-sulfide nanosheets for high performance supercapacitors
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Mengke Peng, Yushuai Xiong, Yingchun Lin, Li Wang, Yazhou Xu, Kaiyang Zhang, Jun Huang, Kai Yuan, Yiwang Chen, and Ting Hu
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Supercapacitor ,Materials science ,chemistry.chemical_element ,02 engineering and technology ,General Chemistry ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Electrochemistry ,01 natural sciences ,Capacitance ,0104 chemical sciences ,Nickel ,chemistry ,Transition metal ,Chemical engineering ,Electrode ,0210 nano-technology ,Cobalt ,Carbon - Abstract
Although transition metal phospho-sulfides deliver outstanding electrochemical performance, complex preparation methods hindered their further development. Herein, we report a facile one-step electrodeposition approach to deposit interconnected nanowalls-like nickel cobalt phospho-sulfide (Ni-Co-P-S) nanosheets onto the surface of carbon cloth. The thin Ni-Co-P-S nanosheets with multi-components and synergetic effects delivered rich active sites, further enhancing reversible capacitance. Therefore, the as-prepared Ni-Co-P-S electrode materials exhibit excellent electrochemical performance in a three-electrode system, showcasing a high specific capacitance of 2744 F/g at 4 A/g. The full supercapacitors based on Ni-Co-P-S as positive electrode and active carbon as negative electrode showcase a high specific capacitance of 110.9 F/g at 1 A/g, impressive energy density of 39.4 Wh/kg at a power density of 797.5 W/kg in terms of excellent cycling stability (91.87% retention after 10,000 cycles). This simple electrodeposition strategy for synthesizing Ni-Co-P-S can be extended to prepare electrode materials for various sustainable electrochemical energy storage/conversion technologies.
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- 2021
21. Efficient Skeleton-Based Human Assembly Action Recognition Optimized by Data Augmentation
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Yaqian Zhang, Jizhuang Hui, Tao Zhou, Kaiyang Zhang, Kai Ding, and Weiwei Wang
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- 2022
22. Direct conversion of human fibroblasts to pancreatic epithelial cells through transient progenitor states is controlled by temporal activation of defined factors
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Liangru Fei, Kaiyang Zhang, Nikita Poddar, Sampsa Hautaniemi, and Biswajyoti Sahu
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Cell fate can be reprogrammed by ectopic expression of lineage-specific transcription factors (TF). For example, few specialized cell types like neurons, hepatocytes and cardiomyocytes have been generated from fibroblasts by defined factors (Wanget al, 2021). However, the exact cell state transitions and their control mechanisms during cell fate conversion are still poorly understood. Moreover, the defined TFs for generating vast majority of the human cell types are still elusive. Here, we report a novel protocol for reprogramming human fibroblasts to pancreatic exocrine cells with phenotypic and functional characteristics of ductal epithelial cells using a minimal set of six TFs. We mapped the molecular determinants of lineage dynamics at single-cell resolution using a novel factor-indexing method based on single-nuclei multiome sequencing (FI-snMultiome-seq) that enables dissecting the role of each individual TF and pool of TFs in cell fate conversion. We show that transdifferentiation – although being considered a direct cell fate conversion method – occurs through transient progenitor states orchestrated by stepwise activation of distinct TFs. Specifically, transition from mesenchymal fibroblast identity to epithelial pancreatic exocrine fate involves two deterministic steps: first, an endodermal progenitor state defined by activation of HHEX concurrently with FOXA2 and SOX17, and second, temporal GATA4 activation essential for maintenance of pancreatic cell fate program. Collectively, our data provide a high-resolution temporal map of the epigenome and transcriptome remodeling events that facilitate cell fate conversion, suggesting that direct transdifferentiation process occurs through transient dedifferentiation to progenitor cell states controlled by defined TFs.
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- 2022
23. Ultra-small RuO
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Yujie, Du, Kaiyang, Zhang, Rui, Yao, Yun, Wu, Qiang, Zhao, Jinping, Li, and Guang, Liu
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Designing highly active and durable oxygen evolution reaction (OER) electrocatalysts is indispensable for promoting the sluggish reaction kinetics of OER to achieve low overpotential. RuO
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- 2022
24. L1 retrotransposition is regulated post-transcriptionally In High-Grade Serous Ovarian Cancer
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Barun Pradhan, Kaiyang Zhang, Yilin Li, Kari Lavikka, Taru Muranen, Kaisa Huhtinen, Richard Badge, Kathleen H. Burns, Johanna Hynninen, Sakari Hietanen, Jaana Oikkonen, Sampsa Hautaniemi, and Liisa Kauppi
- Abstract
L1 retrotransposons are the only protein-coding active transposable elements in the human genome. Although silenced during normal conditions, they are highly expressed in human epithelial cancers including high-grade serous ovarian cancer (HGSC), where they transcribe to form L1 mRNA and subsequently integrate into the genome by a process called retrotransposition. Despite of high L1 protein expression in the earliest phases of HGSC, these tumors do not accrue many somatic L1 insertions. To understand this unexplained disconnect, we monitored the transcription and retrotransposition activity of two frequently expressed retrotransposition-competent (RC)-L1 (RC-L1) in 64 clinical tumor specimens from 34 HGSC patients and found that despite the presence of RC-L1 mRNA, a third of samples did not acquire somatic L1 insertions. In addition to high inter-patient variability in retrotransposition frequency, there was remarkable intra-patient heterogeneity in L1 insertion patterns between tumor sites, indicating that L1 retrotransposition is highly dynamic in vivo. Comparison of genomic and transcriptomic features of L1-null tumors with L1-high tumors (those with ≥5 somatic L1 insertions) showed that retrotransposition was favored by increased rate of cell proliferation.
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- 2022
25. Co-evolution of matrisome and adaptive adhesion dynamics drives ovarian cancer chemoresistance
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Kaiyang Zhang, Okan Gultekin, Elina A Pietilä, Jordi Gonzalez-Molina, Lidia Moyano-Galceran, Kaisa Lehti, Laura Lehtinen, Ulrika Joneborg, Tarja Lamminen, Sanaz Jamalzadeh, Johanna Hynninen, Tomás A Martins, Rainer Lehtonen, Sakari Hietanen, Sampsa Hautaniemi, Joseph W. Carlson, S. Pauliina Turunen, Seija Grénman, Olli Carpén, Katja Kaipio, Research Program in Systems Oncology, Kaisa Irene Lehti / Principal Investigator, INDIVIDRUG - Individualized Drug Therapy, Sampsa Hautaniemi / Principal Investigator, Research Programs Unit, HUSLAB, Biosciences, Faculty Common Matters (Faculty of Medicine), Bioinformatics, Department of Biochemistry and Developmental Biology, Precision Cancer Pathology, Department of Pathology, and Olli Mikael Carpen / Principal Investigator
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0301 basic medicine ,endocrine system diseases ,INVASION ,Cell ,General Physics and Astronomy ,Apoptosis ,Kaplan-Meier Estimate ,Metastasis ,Transcriptome ,Extracellular matrix ,0302 clinical medicine ,3123 Gynaecology and paediatrics ,Tumor Microenvironment ,Ovarian Neoplasms ,Multidisciplinary ,Extracellular Matrix ,3. Good health ,Gene Expression Regulation, Neoplastic ,Crosstalk (biology) ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Female ,Collagen ,Signal Transduction ,Cancer microenvironment ,Stromal cell ,STROMA ,Science ,3122 Cancers ,Antineoplastic Agents ,Biology ,Article ,General Biochemistry, Genetics and Molecular Biology ,ACTIN ,Evolution, Molecular ,03 medical and health sciences ,Ovarian cancer ,Cell Line, Tumor ,EXTRACELLULAR-MATRIX ,Cell Adhesion ,medicine ,Humans ,Gene Expression Profiling ,Cancer ,General Chemistry ,medicine.disease ,COLLAGEN-VI ,Cystadenocarcinoma, Serous ,030104 developmental biology ,Drug Resistance, Neoplasm ,METASTASIS ,CELLS ,Cancer research ,Cisplatin ,Neoplasm Recurrence, Local ,RESISTANCE - Abstract
Due to its dynamic nature, the evolution of cancer cell-extracellular matrix (ECM) crosstalk, critically affecting metastasis and treatment resistance, remains elusive. Our results show that platinum-chemotherapy itself enhances resistance by progressively changing the cancer cell-intrinsic adhesion signaling and cell-surrounding ECM. Examining ovarian high-grade serous carcinoma (HGSC) transcriptome and histology, we describe the fibrotic ECM heterogeneity at primary tumors and distinct metastatic sites, prior and after chemotherapy. Using cell models from systematic ECM screen to collagen-based 2D and 3D cultures, we demonstrate that both specific ECM substrates and stiffness increase resistance to platinum-mediated, apoptosis-inducing DNA damage via FAK and β1 integrin-pMLC-YAP signaling. Among such substrates around metastatic HGSCs, COL6 was upregulated by chemotherapy and enhanced the resistance of relapse, but not treatment-naïve, HGSC organoids. These results identify matrix adhesion as an adaptive response, driving HGSC aggressiveness via co-evolving ECM composition and sensing, suggesting stromal and tumor strategies for ECM pathway targeting., Platinum chemotherapy is standard of care in ovarian cancers but treatment resistance commonly develops. Here, the authors show that the extracellular microenvironment is modulated following chemotherapy and the changes in matrix proteins and stiffness alter the cell death response of tumour cells.
- Published
- 2021
26. Enabling 2.4-V aqueous supercapacitors through the rational design of an integrated electrode of hollow vanadium trioxide/carbon nanospheres
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Li Wang, Kai Yuan, Yiwang Chen, Yingchun Lin, Jun Huang, Xiannong Tang, Mengke Peng, Kaiyang Zhang, Lingfang Chen, and Ting Hu
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Supercapacitor ,Aqueous solution ,Materials science ,business.industry ,chemistry.chemical_element ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Capacitance ,Energy storage ,0104 chemical sciences ,chemistry ,Electrode ,Optoelectronics ,General Materials Science ,0210 nano-technology ,business ,Carbon ,Power density ,Voltage - Abstract
Aqueous supercapacitors (SCs) exhibit several advantages, including high-power density, cycling durability, and safety; however, the shortage of low energy density inhibits their further application. Acquiring an excellent performance upon using simple strategies would be beneficial, but remains challenging. Here, an integrated electrode of hollow V2O3/carbon nanospheres (H-V2O3/C) was designed and synthesized for SCs. The introduction of carbon can increase the conductivity and stability, whereas the hollow structure endows H-V2O3/C with a high specific surface area and rapid transport of ions. Moreover, the H-V2O3/C integrated electrode can simultaneously work in both negative and positive potential windows. Benefiting from these advantages, the H-V2O3/C integrated electrode exhibits a specific capacitance as high as 708.6 F g−1 in a wide voltage window of −1.1–1.3 V. Furthermore, stemming from the multiple energy storage mechanisms, the aqueous integrated full SC device exhibits a wider potential window and higher energy density than the traditional (a)symmetric ones. Therefore, the proposed device delivers a wide voltage window of 2.4 V with an energy density of 96.8 W h kg−1 at a power density of 1204.6 W kg−1, as well as superior cycling stability. This study enlightens the design and preparation of electrode materials, opening up a possible approach for developing wide voltage aqueous SCs.
- Published
- 2021
27. PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples
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Olli Carpén, Katja Kaipio, Kaisa Huhtinen, Antti Häkkinen, Erdogan Pekcan Erkan, Noora Andersson, Naziha Mansuri, Sampsa Hautaniemi, Anna Vähärautio, Johanna Hynninen, Tarja Lamminen, Amjad Alkodsi, Rainer Lehtonen, Kaiyang Zhang, Jun Dai, Sakari Hietanen, Sampsa Hautaniemi / Principal Investigator, Research Program in Systems Oncology, Research Programs Unit, HUSLAB, Department of Pathology, Precision Cancer Pathology, Olli Mikael Carpen / Principal Investigator, Biosciences, Faculty Common Matters (Faculty of Medicine), Bioinformatics, and Department of Biochemistry and Developmental Biology
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Statistics and Probability ,AcademicSubjects/SCI01060 ,Cell type specific ,Gene Expression ,RNA-Seq ,In situ hybridization ,Computational biology ,Biology ,Patient response ,Biochemistry ,PATHWAY ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,medicine ,Molecular Biology ,SIGNATURES ,GENE-EXPRESSION ,030304 developmental biology ,0303 health sciences ,318 Medical biotechnology ,RNA ,Cancer ,medicine.disease ,CANCER ,Original Papers ,3. Good health ,Computer Science Applications ,Computational Mathematics ,Computational Theory and Mathematics ,030220 oncology & carcinogenesis ,1182 Biochemistry, cell and molecular biology ,3111 Biomedicine ,Prism - Abstract
Motivation A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples. Results To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell-type-specific expression through whole-genome sequencing and RNA in situ hybridization experiments. Availabilityand implementation https://bitbucket.org/anthakki/prism. Supplementary information Supplementary data are available at Bioinformatics online.
- Published
- 2021
28. Abstract 2135: Multi-omics characterization of chemo-refractory HGSC patients
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Taru A. Muranen, Anna Rajavuori, Daria Afenteva, Kaisa Huhtinen, Veli-Matti Isoviita, Sanaz Jamalzadeh, Alexandra Lahtinen, Kari Lavikka, Yilin Li, Giovanni Marchi, Jaana Oikkonen, Kaiyang Zhang, Anni Virtanen, Johanna Hynninen, and Sampsa Hautaniemi
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Cancer Research ,Oncology - Abstract
Neoadjuvant chemotherapy (NACT) is the preferred treatment strategy for high-grade serous (ovarian) cancer (HGSC) patients, if optimal cytoreduction is estimated unachievable at the time of the diagnosis. In such cases, intrinsic sensitivity to standard-of-care (platinum and taxane combination therapy) is a major determinant of the disease progression. The DECIDER project is an international effort to overcome the mechanisms of chemo-resistance by integration of clinical, imaging and multi-omics data layers from a prospective cohort of >300 HGSC patients. In the DECIDER cohort, NACT was chosen as the treatment for 46% of the patients, of whom 31 had intrinsically chemo-refractory disease, defined as progressive or stable disease (SD/PD) at the end of the primary therapy and progression-free interval (PFI) shorter than 45 days. A reference group comprised 60 patients with partial or complete response (PR/CR) after primary therapy and PFI longer than six months. The rest of the NACT-treated patients had at least partial relapse but PFI between one to six months. Herein, we tested the enrichment of clinicopathological and molecular features in the refractory and reference groups. Furthermore, we studied all NACT-treated patients, using a three-state survival model with primary progression and death as events of interest, and characterized survival associations with Cox regression. RNA sequencing data were used to identify cellular states and pathway activities, with the goal of revealing molecular level differences that drive early resistance to chemotherapy. Whole genome sequencing data were integrated to the gene expression-based results, to identify causal genetic aberrations. Additionally, the molecular features were tested against clinicopathological features and known HGSC driver mutations. Our results suggest that the resistance to primary therapy predicts decreased survival, so that the mean time to death was 13.6 months for patients with SD/PD and about 5 months longer for patients with at least partial response. As expected, a higher pathological chemotherapy response score (CRS) predicted increased time to progression and a longer time from primary progression to death. However, there was only marginal difference in the distribution of the CRS between the chemo-refractory and responsive groups. In a multivariable model, mutation signature-based homologous recombination (HR) deficiency was associated with a longer time to primary progression, whereas the time from progression to death was associated only with loss-of-function mutations in HR genes. Interestingly, tumor mutation burden, whole genome duplication, or the level of tumor cell proliferation were not associated with chemo-resistance or patient survival. Immune cell infiltration in solid tissue samples was very low, except for one responsive patient, and was not associated with chemo-response. Citation Format: Taru A. Muranen, Anna Rajavuori, Daria Afenteva, Kaisa Huhtinen, Veli-Matti Isoviita, Sanaz Jamalzadeh, Alexandra Lahtinen, Kari Lavikka, Yilin Li, Giovanni Marchi, Jaana Oikkonen, Kaiyang Zhang, Anni Virtanen, Johanna Hynninen, Sampsa Hautaniemi. Multi-omics characterization of chemo-refractory HGSC patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2135.
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- 2023
29. Quaternary ammonium salts modification preparing charged Janus nanofiltration membrane for the simultaneous separation of divalent anions and cations
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Zhixiao Liu, Zhiming Mi, Lingjun Meng, Yangyang Huang, Dexing Zhang, Junman Wang, Kaiyang Zhang, Jingling Xiao, Pingli Liu, Zhi Rao, Hongru He, and Shuai Wang
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Filtration and Separation ,General Materials Science ,Physical and Theoretical Chemistry ,Biochemistry - Published
- 2023
30. A new magnetic modeling method for magnetic levitation rotary table
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Xianze Xu, Kaiyang Zhang, Gong Yongxing, and Fengqiu Xu
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Physics ,0209 industrial biotechnology ,Mechanical Engineering ,020208 electrical & electronic engineering ,Magnetic modeling ,Mechanical engineering ,02 engineering and technology ,Condensed Matter Physics ,Electronic, Optical and Magnetic Materials ,020901 industrial engineering & automation ,Mechanics of Materials ,0202 electrical engineering, electronic engineering, information engineering ,Table (database) ,Electrical and Electronic Engineering ,Magnetic levitation - Abstract
Precision machining fields require the worktable to have a large-scale multi-degree-of-freedom motion capability. In order to provide a more accurate magnetic model for the control strategy decoupling process and the size parameter optimization design process of the maglev rotary table. This paper proposes a new magnetic modeling method based on the Two-Dimensional Harmonic method. Different from the existing harmonic method, this method simultaneously considers the tangential and radial magnetic field changes of circumferential magnetic array. And it eliminates the edge effect of the magnetic flux density distribution in the radial aperiodic direction. The magnetic force and torque are solved by the Lorenz integral formula and the Gaussian quadrature method. In order to verify the accuracy of the TDH method, the boundary element software RadiaTM is used for simulation, and a prototype is made for measurement. The experimental results shown that this method reduced the maximum error of the radial edge magnetic field from 104.19% to 3.29%. And it improved the calculation accuracy of magnetic force and torque by 60.74% and 84.39% respectively. This method does not rely on special example, and is beneficial to cross-platform applications. It is more suitable for realizing the magnetic modeling of the maglev rotary table with both rotational motion and large-stroke translational motion.
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- 2021
31. Fast assembly of MXene hydrogels by interfacial electrostatic interaction for supercapacitors
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Yiwang Chen, Weizu Yang, Mengke Peng, Li Wang, Ting Hu, Kai Yuan, Longbin Li, and Kaiyang Zhang
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Supercapacitor ,Electrode material ,Materials science ,Metals and Alloys ,General Chemistry ,Capacitance ,Catalysis ,Thionine ,Surfaces, Coatings and Films ,Electronic, Optical and Magnetic Materials ,chemistry.chemical_compound ,chemistry ,Chemical engineering ,Self-healing hydrogels ,Materials Chemistry ,Ceramics and Composites ,Molecule ,Dispersion (chemistry) ,Electrostatic interaction - Abstract
A simple and fast method for preparing MXene hydrogels is proposed by introducing protonated thionine molecules into a MXene dispersion through electrostatic interaction. Such a 3D hydrogel effectively suppressed restacking and oxidation, and enlarged the surface utilization of the MXene, producing an improved specific capacitance of 163 F g−1 at 1 A g−1 and excellent stability when used as an electrode material for supercapacitors.
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- 2021
32. Coupling of EDLC and the reversible redox reaction: oxygen functionalized porous carbon nanosheets for zinc-ion hybrid supercapacitors
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Mingtao Huang, Ting Hu, Longbin Li, Li Wang, Xiannong Tang, Kai Yuan, Mengke Peng, Yiwang Chen, Kaiyang Zhang, and Jun Huang
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Supercapacitor ,Materials science ,Renewable Energy, Sustainability and the Environment ,chemistry.chemical_element ,02 engineering and technology ,General Chemistry ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Oxygen ,Capacitance ,Redox ,Energy storage ,Pseudocapacitance ,0104 chemical sciences ,chemistry ,Chemical engineering ,General Materials Science ,0210 nano-technology ,Carbon ,Power density - Abstract
Zinc-ion hybrid supercapacitors (ZHSCs) are promising next-generation energy storage devices owing to their merits of inexpensiveness, high energy density, high safety, and a long cycle lifespan. However, ZHSC device performance is still unsatisfactory because the carbon cathodes fail to match the high theoretical capacity of Zn electrodes. Herein, oxygen functionalized hierarchical porous carbon (HPC) materials are constructed by an in situ self-activation strategy for enhancing the performance of ZHSCs. Remarkable capacity and energy density are obtained benefitting from the synergistic effect of the electric double-layer capacitance of porous carbon and attractive pseudocapacitance from reversible transformation of oxygen functional groups during charge/discharge processes. Consequently, the as-fabricated ZHSCs demonstrate a high specific capacity of 169.4 mA h g−1, a maximum energy density of 125.1 W h kg−1 at 0.1 A g−1, and an ultrahigh power density of 16.1 kW kg−1. Furthermore, the ZHSCs exhibit an ultralong cycle lifespan of 60 000 cycles at 10 A g−1 and a high-capacity retention of 93.1%. Meanwhile, the corresponding quasi-solid ZHSC device also shows remarkable rate performance and cycling stability. This work provides novel design tactics to enhance the zinc ion storage properties of porous carbon by combining fast ion adsorption and the reversible redox reaction of oxygen functional groups.
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- 2021
33. A generalized one-step in situ formation of metal sulfide/reduced graphene oxide nanosheets toward high-performance supercapacitors
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Jun Huang, Yuanhao Wei, Ting Hu, Kai Yuan, Kaiyang Zhang, Yingbo Xiao, Yiwang Chen, and Weizu Yang
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chemistry.chemical_classification ,Supercapacitor ,Materials science ,Sulfide ,Graphene ,Oxide ,chemistry.chemical_element ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Electrochemistry ,01 natural sciences ,Capacitance ,0104 chemical sciences ,law.invention ,chemistry.chemical_compound ,Chemical engineering ,chemistry ,law ,Electrode ,General Materials Science ,0210 nano-technology ,Carbon - Abstract
Metal sulfides are promising candidates for supercapacitors, but their slow reaction kinetics hinders their electrochemical performance. Large electrochemical surface area and combination with conductive carbon are potential methods to improve their capacitive performance. However, seeking for a generalized and simple approach to prepare two-dimensional composites of metal sulfide and conductive carbon for supercapacitors is challengeable. Herein, a generalized and facile one-step pyrolysis method was designed for in situ growth of cobalt nickel sulfides (CoNi2S4) on reduced graphene oxide (rGO) nanosheets (CoNi2S4/rGO) under mild conditions. The as-prepared CoNi2S4/rGO materials possess the nanoparticles-on-nanosheets structure, which is effective to provide a myriad of active sites and optimized electron/ion diffusion pathway. Benefiting from those advantages, the resultant CoNi2S4/rGO electrodes exhibit impressed specific capacitances of 1526 and 988 F g−1 at 2 and 20 A g−1, respectively. The supercapacitors based on CoNi2S4/rGO showcase an operation potential window of 1.6 V, and energy density of 54.8 W h kg−1 at the power density of 798 W kg−1. The capacitance retention of the supercapacitor is about 93.7% after 8000 cycles at 3 A g−1. Moreover, a series of metal sulfide/rGO hybrids are obtained by this generalized strategy, which could be extended to construct electrode materials for various energy devices.
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- 2020
34. Coaxial electrospun free-standing and mechanically stable hierarchical porous carbon nanofiber membranes for flexible supercapacitors
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Yazhou Xu, Yiwang Chen, Jun Huang, Kai Yuan, Xiannong Tang, Kaiyang Zhang, and Yingbo Xiao
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Supercapacitor ,Materials science ,Fabrication ,Carbon nanofiber ,Nanotechnology ,02 engineering and technology ,General Chemistry ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Capacitance ,0104 chemical sciences ,Membrane ,General Materials Science ,Coaxial ,0210 nano-technology ,Porosity ,Template method pattern - Abstract
The preparation of electrode materials with superior electrochemical performance and excellent mechanical properties are essential for the fabrication of flexible supercapacitors. However, the compatibility of the porosity and flexibility for the electrode materials remains challenging. Herein, free-standing porous coaxial carbon nanofiber (PCCNF) membranes with large specific surface area (648 m2 g−1) and suitable pore size distribution were fabricated by a facile coaxial electrospinning technique and template method. PCCNF possesses superb capacitance of 261 and 48 F g−1 (1 A g−1) in three-electrode and two-electrode system, respectively, result in remarkable energy density (48.6 ± 3 Wh kg−1) and power density (67.5 ± 1 Wh kg−1). Moreover, supercapacitor devices based on PCCNF show superb flexibility as well as excellent electrochemical and mechanical stability. PCCNF-based high performance supercapacitors may be suitable for flexible electronic energy storage devices.
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- 2020
35. TiO2-DNA Nanosensor In Situ for Quick Detection of Nasal Flora in Allergic Rhinitis Patients
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Weihua Chen, Kaiyang Zhang, and Zewei Zhong
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General Immunology and Microbiology ,Applied Mathematics ,Modeling and Simulation ,General Medicine ,General Biochemistry, Genetics and Molecular Biology - Abstract
Background. A relevant study found that allergic rhinitis (AR) may be related to the imbalance of nasal flora. Therefore, if the nasal flora of AR patients can be detected quickly, it is of great significance to study the distribution law of nasal flora in AR patients and explore its correlation with AR. Objective. To design a new and convenient nano-DNA sensor for quick screening of nasal flora in allergic rhinitis (AR) patients, so as to provide experimental basis for the prevention and treatment of AR. Methods. We create a synthesized nanostructured DNA biosensor called Nano-TiO2-DNA sensor which can be combined with samples from nasal mucosa or secretion with high efficiency and detect certain flora in situ without DNA extraction or RNA sequencing. In a physical property test, firstly, we tested the permeability, solubility, and storage temperature of nano-TiO2, so as to provide experimental basis for the synthesis of Nano-TiO2-DNA sensor. Subsequently, the permeability of Nano-TiO2-DNA sensor in Staphylococcus aureus was further tested. In a clinical experiment, we selected 60 AR patients treated in our hospital from September 2020 to September 2021 as the AR group and 60 healthy people who underwent physical examination at the same time as the control group. The Nano-TiO2-DNA sensor was used to detect typical nasal flora in AR patients, and Pearson’s correlation analysis was used to explore the correlation between nasal flora with serum IgE and eosinophils. Results. As for physicochemical characteristics, this sensor can permeate into certain bacteria directly and specifically. It has high affinity ability with a target, and the combination can be detected by evaluating the released fluorescence qualitatively and quantitatively. It can be stored at −20°C in ethyl alcohol stably. By this sensor, we have successfully detected Staphylococcus aureus, Klebsiella pneumoniae, and viridans streptococci in AR patients compared with healthy people, which will help these patients in the prevention of acute sinusitis and acute or subacute pneumonia. Furthermore, we found Proteus had the strongest positive correlation with AR while Actinomyces had the biggest negative correlation. Conclusion. The Nano-TiO2-DNA sensor will help an outpatient doctor more for quick screening certain nasal flora in AR patients and improve the prevention of AR-related complications.
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- 2022
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36. Quaternary Ammonium Salts Modification Preparing Charged Janus Nanofiltration Membrane for the Simultaneous Separation of Divalent Anions and Cations
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Zhiming Mi, Zhixiao Liu, Lingjun Meng, Yangyang Huang, Dexing Zhang, Junman Wang, Kaiyang Zhang, Jingling Xiao, Yue Sun, Jialing Liu, Luowen Xu, Hongru He, and Shuai Wang
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History ,Polymers and Plastics ,Business and International Management ,Industrial and Manufacturing Engineering - Published
- 2022
37. Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer
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Kaiyang Zhang, Erdogan Pekcan Erkan, Sanaz Jamalzadeh, Jun Dai, Noora Andersson, Katja Kaipio, Tarja Lamminen, Naziha Mansuri, Kaisa Huhtinen, Olli Carpén, Sakari Hietanen, Jaana Oikkonen, Johanna Hynninen, Anni Virtanen, Antti Häkkinen, Sampsa Hautaniemi, Anna Vähärautio, Research Program in Systems Oncology, Sampsa Hautaniemi / Principal Investigator, Genome-Scale Biology (GSB) Research Program, HUSLAB, HUS Children and Adolescents, Precision Cancer Pathology, Department of Pathology, Olli Mikael Carpen / Principal Investigator, Faculty Common Matters (Faculty of Medicine), and Bioinformatics
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Ovarian Neoplasms ,EXPRESSION ,Multidisciplinary ,Drug Resistance, Neoplasm ,Sequence Analysis, RNA ,MUTATIONS ,Exome Sequencing ,3122 Cancers ,Humans ,Female ,HETEROGENEITY ,Transcriptome ,EVOLUTION - Abstract
Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer–associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.
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- 2022
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38. Zn-Ion Batteries With Zn Anodes and MnO2 Cathodes: Design and Practice of a Comprehensive Chemistry Experiment
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Xinglong Wu, Hongyan Lü, Miao Du, Size Wang, Xiaotong Wang, Kaiyang Zhang, and Weichen Li
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General Medicine - Published
- 2023
39. Prospective Longitudinal ctDNA Workflow Reveals Clinically Actionable Alterations in Ovarian Cancer
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Seija Grénman, Anniina Färkkilä, Ingrid Schulman, Noora Andersson, Johanna Hynninen, Sampsa Hautaniemi, Olli Carpén, Kaisa Huhtinen, Kari Lavikka, Kaiyang Zhang, Rainer Lehtonen, Liina Salminen, Sakari Hietanen, Erika Ojanperä, Jaana Oikkonen, Research Program in Systems Oncology, Sampsa Hautaniemi / Principal Investigator, Research Programs Unit, University of Helsinki, HUSLAB, and Clinicum
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0301 basic medicine ,Oncology ,Cancer Research ,medicine.medical_specialty ,business.industry ,3122 Cancers ,Cancer ,medicine.disease ,3. Good health ,03 medical and health sciences ,030104 developmental biology ,0302 clinical medicine ,Workflow ,030220 oncology & carcinogenesis ,Internal medicine ,Original Report ,Medicine ,business ,Ovarian cancer - Abstract
PURPOSE Circulating tumor DNA (ctDNA) detection is a minimally invasive technique that offers dynamic molecular snapshots of genomic alterations in cancer. Although ctDNA markers can be used for early detection of cancers or for monitoring treatment efficacy, the value of ctDNA in guiding treatment decisions in solid cancers is controversial. Here, we monitored ctDNA to detect clinically actionable alterations during treatment of high-grade serous ovarian cancer, the most common and aggressive form of epithelial ovarian cancer with a 5-year survival rate of 43%. PATIENTS AND METHODS We implemented a clinical ctDNA workflow to detect clinically actionable alterations in more than 500 cancer-related genes. We applied the workflow to a prospective cohort consisting of 78 ctDNA samples from 12 patients with high-grade serous ovarian cancer before, during, and after treatment. These longitudinal data sets were analyzed using our open-access ctDNA-tailored bioinformatics analysis pipeline and in-house Translational Oncology Knowledgebase to detect clinically actionable genomic alterations. The alterations were ranked according to the European Society for Medical Oncology scale for clinical actionability of molecular targets. RESULTS Our results show good concordance of mutations and copy number alterations in ctDNA and tumor samples, and alterations associated with clinically available drugs were detected in seven patients (58%). Treatment of one chemoresistant patient was changed on the basis of detection of ERBB2 amplification, and this ctDNA-guided decision was followed by significant tumor shrinkage and complete normalization of the cancer antigen 125 tumor marker. CONCLUSION Our results demonstrate a proof of concept for using ctDNA to guide clinical decisions. Furthermore, our results show that longitudinal ctDNA samples can be used to identify poor-responding patients after first cycles of chemotherapy. We provide what we believe to be the first comprehensive, open-source ctDNA workflow for detecting clinically actionable alterations in solid cancers.
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- 2019
40. Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer
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Krister Wennerberg, Anna Vähärautio, Liye He, Jaana Oikkonen, Antti Häkkinen, Sampsa Hautaniemi, Shuyu Zheng, Olli Carpén, Daria Bulanova, Erdogan Pekcan Erkan, Tero Aittokallio, Wenyu Wang, Titta Joutsiniemi, Kaiyang Zhang, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, Jing Tang, Institute for Molecular Medicine Finland, Research Program in Systems Oncology, Sampsa Hautaniemi / Principal Investigator, Genome-Scale Biology (GSB) Research Program, Department of Pathology, Olli Mikael Carpen / Principal Investigator, Precision Cancer Pathology, HUSLAB, Faculty Common Matters (Faculty of Medicine), Department of Biochemistry and Developmental Biology, Bioinformatics, Medicum, Department of Mathematics and Statistics, Krister Wennerberg / Principal Investigator, Helsinki Institute for Information Technology, and Tero Aittokallio / Principal Investigator
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Drug ,drug combinations ,AcademicSubjects/SCI01060 ,media_common.quotation_subject ,3122 Cancers ,MODELS ,Computational biology ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Tumor Cells, Cultured ,medicine ,Humans ,DRUG ,combination synergy ,Molecular Biology ,030304 developmental biology ,media_common ,Ovarian Neoplasms ,0303 health sciences ,Case Study ,business.industry ,network visualization ,Cancer ,medicine.disease ,Combined Modality Therapy ,Ensemble learning ,3. Good health ,Regimen ,machine learning ,ovarian cancer ,toxic effects ,precision oncology ,Cancer cell ,Female ,Ovarian cancer ,business ,Cytometry ,Algorithms ,030217 neurology & neurosurgery ,Information Systems - Abstract
Each patient’s cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.
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- 2021
41. miQC : An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data
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Jennifer A. Doherty, Casey S. Greene, Lukas M. Weber, Erdogan Pekcan Erkan, Anna Vähärautio, Ariel A. Hippen, Stephanie C. Hicks, Matias M. Falco, Kaiyang Zhang, Research Program in Systems Oncology, Research Programs Unit, Faculty of Medicine, and Sampsa Hautaniemi / Principal Investigator
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Downstream (software development) ,Computer science ,computer.software_genre ,Biochemistry ,Bioconductor ,Software ,0302 clinical medicine ,Basic Cancer Research ,Gene expression ,Medicine and Health Sciences ,Preprocessor ,Biology (General) ,MAXIMUM-LIKELIHOOD ,Energy-Producing Organelles ,media_common ,0303 health sciences ,Ecology ,Small number ,High-Throughput Nucleotide Sequencing ,Genomics ,Mitochondrial DNA ,Mitochondria ,Ovarian Cancer ,Nucleic acids ,Oncology ,Computational Theory and Mathematics ,Modeling and Simulation ,Metric (mathematics) ,Probability distribution ,Data mining ,Cellular Structures and Organelles ,Single-Cell Analysis ,Research Article ,Quality Control ,QH301-705.5 ,Forms of DNA ,media_common.quotation_subject ,Computational biology ,Bioenergetics ,Research and Analysis Methods ,DNA, Mitochondrial ,Human Genomics ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Cancer Genomics ,Genomic Medicine ,Fish Genomics ,Code (cryptography) ,Genetics ,Humans ,Quality (business) ,Molecular Biology Techniques ,Molecular Biology ,Gene ,Ecology, Evolution, Behavior and Systematics ,Probability ,030304 developmental biology ,Sequence Analysis, RNA ,business.industry ,Gene Mapping ,Biology and Life Sciences ,Cancers and Neoplasms ,RNA ,Cell Biology ,DNA ,Mixture model ,Animal Genomics ,1182 Biochemistry, cell and molecular biology ,business ,Gynecological Tumors ,computer ,030217 neurology & neurosurgery - Abstract
Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a ‘low-quality’ cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA (mtDNA) encoded genes and (ii) if a small number of genes are detected. Current best practices use these QC metrics independently with either arbitrary, uniform thresholds (e.g. 5%) or biological context-dependent (e.g. species) thresholds, and fail to jointly model these metrics in a data-driven manner. Current practices are often overly stringent and especially untenable on certain types of tissues, such as archived tumor tissues, or tissues associated with mitochondrial function, such as kidney tissue [1]. We propose a data-driven QC metric (miQC) that jointly models both the proportion of reads mapping to mtDNA genes and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses. Our software package is available at https://bioconductor.org/packages/miQC., Author summary We developed the miQC package to predict the low-quality cells in a given scRNA-seq dataset by jointly modeling both the proportion of reads mapping to mitochondrial DNA (mtDNA) genes and the number of detected genes using mixture models in a probabilistic framework. We demonstrate how our QC metric easily adapts to different types of single-cell datasets to remove low-quality cells while preserving high-quality cells that can be used for downstream analyses.
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- 2021
42. Toward Understanding the Differences of PM2.5 Characteristics Among Five China Urban Cities
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Yue Sun, Yikun Yang, Chuanfeng Zhao, Hao Fan, and Kaiyang Zhang
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Pollution ,Atmospheric Science ,education.field_of_study ,010504 meteorology & atmospheric sciences ,media_common.quotation_subject ,Population ,Diurnal temperature variation ,0207 environmental engineering ,Air pollution ,02 engineering and technology ,Structural basin ,Seasonality ,medicine.disease_cause ,medicine.disease ,01 natural sciences ,Geography ,Beijing ,medicine ,Physical geography ,020701 environmental engineering ,education ,China ,0105 earth and related environmental sciences ,media_common - Abstract
Characteristics of PM2.5 are investigated and compared based on observations from 2008 to 2017 in Beijing, Shenyang, Shanghai, Chengdu, and Guangzhou, which cover five different climate regions of China. Significant seasonal variations of PM2.5 are found for all five cities, with the largest values in winter and the smallest in summer. The differences of PM2.5 among the five cities are most likely associated with the emission sources, meteorology and topography. The strong emissions with surrounded mountains in Beijing make PM2.5 high, particularly in winter. The basin topography surrounding by mountains in Chengdu makes the pollution hard to disperse and then causes high PM2.5. By contrast, the sea-land breeze helps disperse the air pollution in coastal cities such as Guangzhou and Shanghai by mixing and transport and makes PM2.5 in those cites relatively low. Moreover, the population shows high values in Beijing and Shanghai, and the vehicle amount shows high values in Beijing and Chengdu, contributing to their high PM2.5. Similar monthly variations of PM2.5 are found for the five cities, while the magnitude of variations are different. The five cities demonstrate more different diurnal variations of PM2.5. Associated with the sea-land breeze, there are very weak diurnal variations of PM2.5 in Shanghai and Guangzhou. Differently, significant diurnal variations exist for Beijing, Shengyang and Chengu, with the minimum values in the afternoon and high values at night.
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- 2019
43. Ultimate optimization of interface thermal resistance by utilizing interfacial nonlinear interaction
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Lei Xu, Tingting Wang, Kaiyang Zhang, Dengke Ma, and Lifa Zhang
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General Physics and Astronomy - Abstract
Decreasing interface thermal resistance (ITR or Kapitza resistance) is the key to solve the problem of heat dissipation in integrated circuits, which are the core elements for electronics. In this paper, interfacial nonlinear interaction is introduced to optimize ITR. Interestingly, it is found that the optimized ITR by introducing interfacial nonlinear interaction can be greatly decreased compared to the case optimized solely with interfacial linear interaction. A 51.2% reduction in ITR is achieved in a weak anharmonic system. The mechanism behind this is attributed to the expansion of inelastic channels and the decrease of mismatch for nonlinear coefficients which are verified by spectral analysis. The relationship of optimized interfacial nonlinear coefficient and interfacial linear coefficient k 12 can be approximately predicted by the self-consistent phonon theory. The studies here emphasize the importance of mutual controlling interfacial linear and nonlinear interactions for further decreasing ITR.
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- 2022
44. Abstract 2707: Factoring expression data of high-grade serous ovarian cancer tumors for unbiased longitudinal analysis
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Antti Häkkinen, Kaiyang Zhang, Susanna Holmström, Sanaz Jamaldazeh, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, and Sampsa Hautaniemi
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Cancer Research ,Oncology - Abstract
We address challenges in longitudinal RNA-seq analysis of patient tumors, which can reveal powerful insights on cancer evolution at personalized level, proposing methods for unbiased analysis and integration Experimental procedures: 214 whole-genome bulk RNA-seq samples from 61 high-grade serous ovarian cancer (HGSC) patients were collected before and after chemotherapy, along with single-cell RNA-seq data from >93,000 cells in 11 patients. 308 TCGA treatment-naive bulk RNA-seq samples from HGSC, 474 from melanoma (SKCM), and 581 from endometrial carcinoma (UCEC) were used for validation. Results: We show that in a longitudinal analysis, cancer progression and chemotherapy exert both microenvironmental and phenotypic changes. We developed PRISM [1] to factor the expression data at individual bulk level, and show the adjustment improves the association between expression profiles and patient survival. Our findings extend to pathway and expression-derived tumor subtype levels in HGSC and SKCM. Technical batch effects pose challenges for multi-institute or long-running sample collections. Unbiased correction requires replicates, which are typically unavailable for patient data. We developed POIBM [submitted] to simultaneously infer a suitable reference and factor out the batch effects. We show that POIBM effectively discovers true replicates, batch effects plague many cancer types in TCGA data, and batch correction allows more meaningful expression subtyping in UCEC. Distinct genomic backgrounds of the patients hinders stratification and discovering shared functional states. We developed PRIMUS [submitted] to simultaneously factor the patient background (or other confounders) and a sample clustering, which is necessary when the underlying stratification is uneven or shared by patient subsets. Among the commonly aberrant cell states, such as EMT, PRIMUS analysis on HGSC scRNA identified a novel stress signature, enriched by chemotherapy and indicating poor survival, which were validated in PRISM-factored TCGA bulk ovarian data. Conclusions: Our methodology facilitates unbiased longitudinal expression analysis and integration. The more accurate phenotypic changes at gene, pathway, and expression subtype level may confer sensitivity/resistance chemotherapy, and, as shown, allow enhance patient survival prediction and discovery of novel chemotherapy related subtypes. Consequently, our work aids ranking putative intervention strategies for overcoming ovarian cancer chemoresistance for future validation experiments. [1]: Hakkinen et al., Bioinformatics 37: 2882 (2021) Citation Format: Antti Häkkinen, Kaiyang Zhang, Susanna Holmström, Sanaz Jamaldazeh, Johanna Hynninen, Sakari Hietanen, Kaisa Huhtinen, Sampsa Hautaniemi. Factoring expression data of high-grade serous ovarian cancer tumors for unbiased longitudinal analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2707.
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- 2022
45. Development of Magnetically Levitated Rotary Table for Repetitive Trajectory Tracking
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Xianze Xu, Fengqiu Xu, and Kaiyang Zhang
- Subjects
Magnetics ,magnetic levitation system ,rotary table ,disturbance compensation ,iterative learning control ,trajectory tracking ,Heart-Assist Devices ,Electrical and Electronic Engineering ,Biochemistry ,Instrumentation ,Atomic and Molecular Physics, and Optics ,Analytical Chemistry - Abstract
The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area.
- Published
- 2022
46. Human cell transformation by combined lineage conversion and oncogene expression
- Author
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Lauri A. Aaltonen, Kaiyang Zhang, Alejandra Cervera, Jussi Taipale, Päivi Pihlajamaa, Ari Ristimäki, Kimmo Palin, Biswajyoti Sahu, Saija Ahonen, Sampsa Hautaniemi, Sahu, Biswajyoti [0000-0001-6576-5440], Pihlajamaa, Päivi [0000-0001-9725-6907], Zhang, Kaiyang [0000-0002-0470-9581], Palin, Kimmo [0000-0002-4621-6128], Cervera, Alejandra [0000-0002-6274-1168], Aaltonen, Lauri A [0000-0001-6839-4286], Hautaniemi, Sampsa [0000-0002-7749-2694], Taipale, Jussi [0000-0003-4204-0951], Apollo - University of Cambridge Repository, Department of Biochemistry and Developmental Biology, Digital Precision Cancer Medicine (iCAN), ATG - Applied Tumor Genomics, Faculty of Medicine, University of Helsinki, Research Program in Systems Oncology, Sampsa Hautaniemi / Principal Investigator, Lauri Antti Aaltonen / Principal Investigator, Department of Medical and Clinical Genetics, Research Programs Unit, Department of Pathology, HUSLAB, Medicum, HUS Diagnostic Center, Helsinki University Hospital Area, Faculty Common Matters (Faculty of Medicine), Bioinformatics, and Jussi Taipale / Principal Investigator
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0301 basic medicine ,Cancer Research ,GENES ,Lineage (genetic) ,3122 Cancers ,MYC ,Biology ,medicine.disease_cause ,Translocation, Genetic ,Article ,03 medical and health sciences ,Mice ,0302 clinical medicine ,TUMOR ,HEPATOCELLULAR-CARCINOMA ,HUMAN FIBROBLASTS ,Gene expression ,Proto-Oncogenes ,RAS ONCOGENES ,TUMORIGENESIS ,Genetics ,medicine ,Animals ,Humans ,Cancer models ,Molecular Biology ,Gene ,Progenitor ,Oncogene ,INDUCTION ,METHYLATION ,Cancer ,Cell Differentiation ,Oncogenes ,medicine.disease ,CANCER ,humanities ,3. Good health ,Cell biology ,030104 developmental biology ,Cell Transformation, Neoplastic ,030220 oncology & carcinogenesis ,Carcinogenesis ,Reprogramming - Abstract
Cancer is the most complex genetic disease known, with mutations implicated in more than 250 genes. However, it is still elusive which specific mutations found in human patients lead to tumorigenesis. Here we show that a combination of oncogenes that is characteristic of liver cancer (CTNNB1, TERT, MYC) induces senescence in human fibroblasts and primary hepatocytes. However, reprogramming fibroblasts to a liver progenitor fate, induced hepatocytes (iHeps), makes them sensitive to transformation by the same oncogenes. The transformed iHeps are highly proliferative, tumorigenic in nude mice, and bear gene expression signatures of liver cancer. These results show that tumorigenesis is triggered by a combination of three elements: the set of driver mutations, the cellular lineage, and the state of differentiation of the cells along the lineage. Our results provide direct support for the role of cell identity as a key determinant in transformation and establish a paradigm for studying the dynamic role of oncogenic drivers in human tumorigenesis.
- Published
- 2021
47. Analysis of single-cell RNA-seq data from ovarian cancer samples before and after chemotherapy links stress-related transcriptional profile with chemotherapy resistance
- Author
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Jun Dai, Kaisa Huhtinen, Antti Häkkinen, Johanna Hynninen, Anna Vähärautio, Kaiyang Zhang, Olli Carpén, Katja Kaipio, Sampsa Hautaniemi, Sakari Hietanen, Jaana Oikkonen, Naziha Mansuri, Erdogan Pekcan Erkan, Tarja Lamminen, and Noora Andersson
- Subjects
0303 health sciences ,Chemotherapy ,Stromal cell ,business.industry ,medicine.medical_treatment ,Cell ,RNA-Seq ,medicine.disease ,3. Good health ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,medicine.anatomical_structure ,Cell culture ,030220 oncology & carcinogenesis ,medicine ,Cancer research ,Ovarian cancer ,business ,Gene ,030304 developmental biology - Abstract
Chemotherapy resistance is the greatest contributor to cancer mortality and the most urgent unmet challenge in oncology. In order to reveal transcriptomics changes due to platinum-based chemotherapy we analyzed single-cell RNA-seq data from fresh tissue samples taken at the time of diagnosis and after neoadjuvant chemotherapy from 11 high-grade serous ovarian cancer (HGSOC) patients. With a novel clustering method accounting for patient-specific variability and technical confounders, we identified 12 clusters. Of these, a stress-related transcriptional profile was enriched during chemotherapy and associated significantly to poor progression-free survival (PFS) and disease-free interval (DFI) in deconvoluted bulk RNA-seq data analysis of treatment-naive samples in TCGA cohort. Pan-cancer cell line analysis suggests that patients with high stress-related transcriptional profile may benefit from MEK1/2 inhibitors instead of platinum. Further, high proportion of stromal components and high interaction score between tumor and stromal suggest the tumor cells with high-stress profile actively interact with and potentially recruit stromal cells to their microenvironment already prior to chemotherapy, potentially facilitating protection from chemotherapeutic treatments. In summary, we have identified a stress-related transcriptional profile, which is present at the time of diagnosis, enriched during platinum treatment, independent predictor for poor PFS and DFI, and, based on in vitro data, targetable with MEK1/2 inhibitors.Translational relevanceWe discovered a stress-related transcriptional profile that is significantly enriched in fresh tissue samples after chemotherapy and is significantly associated with poor progression-free survival in an independent patient cohort. The survival association is independent of age, tumor purity or BRCAness. Therefore, this chemotherapy resistance associated profile is intrinsic and could thus be targeted already in treatment-naive patients. The translation potential of the stress-related transcriptomics profile was further supported by pan-cancer cell line analysis that showed that cell lines with high stress-related transcriptional profile are not affected by platinum, corroborating our results, whereas they were more sensitive to MEK1/2 inhibitors. Taken together, the stress-related transcriptional profile, quantifiable with a set of 35 marker genes, provides a basis for improved prediction of platinum response as well as novel avenues to treat this patient group more effectively.
- Published
- 2020
48. Asymmetric response of different functional insect groups to low-grazing pressure in Eurasian steppe in Ningxia
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Jing Wei, Xubin Pan, Kaiyang Zhang, Shuhua Wei, Zihua Zhao, Rong Zhang, Mengmeng Zhu, Hao Li, and Huang Wenguang
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0106 biological sciences ,predator ,Steppe ,Biodiversity ,Biology ,010603 evolutionary biology ,01 natural sciences ,Grazing pressure ,Grassland ,diversity ,Predation ,Ecosystem ,population density ,Ecology, Evolution, Behavior and Systematics ,Original Research ,Nature and Landscape Conservation ,Herbivore ,geography ,Functional ecology ,geography.geographical_feature_category ,Ecology ,04 agricultural and veterinary sciences ,ecological function ,040103 agronomy & agriculture ,community ,0401 agriculture, forestry, and fisheries - Abstract
In recent years, the continued loss and fragmentation of steppe has caused decreased ecosystem functions and species losses in insect diversity. In the 2000s, the Chinese government developed a series of national projects, such as the construction of enclosures, to conserve natural ecosystems, including steppe. However, the effects of these enclosures on steppe arthropod community are largely unknown. In the present study, we selected enclosed and low‐grazing regions at eight National Grassland Fixed Monitoring Stations to examine the compositional differences in four insect functional groups and their associated ecological functions. The results showed that diversity significantly differed between the enclosed and low‐grazing regions, with the number of insect families being significantly higher in enclosed regions than in regions with low‐grazing pressure. The responses of the insect community to steppe management also varied among the four groups (herbivores, predators, parasitoids, and pollinators). The abundances of herbivores, predators, and parasitoids were higher in enclosed regions than in low‐grazing regions, while there was no significant difference in pollinators. Additionally, there were no significant differences in the predator/prey ratio between enclosed regions and low‐grazing regions in any of the steppe types. The parasitic wasp/prey ratio was higher in enclosed regions than in low‐grazing regions in meadow steppe and typical steppe, while there were no significant differences between the enclosed and low‐grazing regions in desert steppe and steppe desert. Herbivores were observed to benefit much more from enclosures than predators, parasitoids, and pollinators. Therefore, we recommend low‐grazing should be considered in steppe conservation, which could conserve biodiversity and achieve biocontrol functions of arthropod community.
- Published
- 2018
49. Spatial and temporal distribution of NO2 and SO2 in Inner Mongolia urban agglomeration obtained from satellite remote sensing and ground observations
- Author
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Chuanfeng Zhao, Xiaolin Wu, Yuanzhe Ren, Gao Jing, Li Yanping, Qi Qiao, Chai Fahe, Kaiyang Zhang, Xin Zhang, and Caiwang Zheng
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Pollution ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,media_common.quotation_subject ,Diurnal temperature variation ,Climate change ,010501 environmental sciences ,Atmospheric sciences ,Spatial distribution ,01 natural sciences ,Troposphere ,chemistry.chemical_compound ,chemistry ,Common spatial pattern ,Environmental science ,Nitrogen dioxide ,Air quality index ,0105 earth and related environmental sciences ,General Environmental Science ,media_common - Abstract
Nitrogen dioxide (NO_2) and sulfur dioxide (SO_2) are important pollution gases which can affect air quality, human health and even climate change. Based on the combination of tropospheric NO_2 and SO_2 column density products derived from OMI satellite with the ground station observations, this study analyzed the spatial-temporal distribution of NO_2 and SO_2 amount in Inner Mongolia urban agglomerations. It shows that NO_2 increased continually from 2005 to 2011 at a rate of 14.3% per year and then decreased from 2011 to 2016 at a rate of −8.1% per year. SO_2 increased from 2005 to 2007 with a rate 9.7% per year. While with a peak value in 2011, SO_2 generally showed a decreasing trend of −1.6% per year from 2007 to 2016. With regard to the spatial pattern, the highest levels of NO_2 occur in Hohhot and Baotou, followed by Wuhai and Ordos, the least in Bayannur. Compared with NO_2, the spatial distribution of SO_2 is slightly different. The pollution of SO_2 is the most serious in Wuhai, followed by Hohhot and Baotou, and the lightest in Ordos and Bayannur. The diurnal variations of NO_2 and SO_2 are basically the same, which decrease from 0:00 to 6:00, then increase to a peak value at 8:00, and decrease from 8:00 to 15:00. The diurnal variation of NO_2 and SO_2 is highly related to the diurnal variation of both anthropogenic emission and boundary layer height. Differently, the long-term spatial-temporal distribution of NO_2 and SO_2 are more closely related to human activities.
- Published
- 2018
50. Plant cover associated with aboveground net primary productivity (ANPP) mediates insect community composition in steppes of Northwest China
- Author
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Qi Jiang, Shuhua Wei, Mengmeng Zhu, Zhanjun Wang, Rong Zhang, Yu Hongqian, Kaiyang Zhang, Zihua Zhao, and Gadi V. P. Reddy
- Subjects
0106 biological sciences ,0301 basic medicine ,geography ,geography.geographical_feature_category ,Steppe ,Ecology ,Biome ,Biodiversity ,Community structure ,Primary production ,Plant community ,Biology ,010603 evolutionary biology ,01 natural sciences ,03 medical and health sciences ,030104 developmental biology ,Habitat ,Insect Science ,Plant cover - Abstract
Temperate steppe is one of the most important natural habitats for the conservation of arthropod and bird biodiversity across the Eurasian Tectonic Plate. Since 1950, fragmentation of the steppe habitat has caused a loss of biodiversity and degradation of the species communities found in natural steppe. Therefore, in this study, both plants and insects were sampled at 56 sites in the steppe biome of northwestern China to explore the effects of plant community on insect community composition and diversity. The insect community structure varied in the four different steppe types (meadow steppe, typical steppe, desert steppe, and steppe desert). Plant cover (diversity) was an important driving force, which could enhance number of families and abundance of an insect community. Aboveground net primary productivity and water content of plants had no significant effects on insect community, although the plant community as a whole did mediate insect composition and community structure. Future research should explore the ecological role of particular functional groups in plant and insect communities. Supplemental sowing to improve plant diversity in steppe habitat may be another strategy to enhance biodiversity and achieve sustainable management.
- Published
- 2018
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