| 1. |
- Yu, Wenjin, et al.
(författare)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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Ingår i: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Tidskriftsartikel (refereegranskat)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 2. |
- Xue, Song, et al.
(författare)
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Phase separation on cell surface facilitates bFGF signal transduction with heparan sulphate
- 2022
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Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- Liquid-liquid phase separation (LLPS) plays important roles in various cellular processes, facilitating membrane-less organelles construction, chromatin condensation, signal transduction on inner membrane and many other processes. Current perception is that LLPS relies on weak multivalent interactions and crowded environments intracellularly. In this study, we demonstrate that heparan sulfate can serve as a platform to induce the phase separation of basic fibroblast growth factor on cell surface. The phase separation model provides an alternative mechanism how bFGF is enriched to its receptors, therefore triggering the signaling transduction. The research provides insights on the mechanism how growth factors can be recruited to cell surface by heparan sulfate and execute their functions, extending people's view on phase separation from intracellular to extracellular proteins at cellular level. Liquid-liquid phase separation (LLPS) is reported to occur in the intracellular environment. Here the authors show that heparan sulphate serves as a platform for basic fibroblast growth factor to undergo LLPS on the cell surface, therefore facilitating downstream signalling
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| 3. |
- Mi, Yushuai, et al.
(författare)
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Down-regulation of Barx2 predicts poor survival in colorectal cancer
- 2016
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Ingår i: Biochemical and Biophysical Research Communications - BBRC. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0006-291X .- 1090-2104. ; 478:1, s. 67-73
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Tidskriftsartikel (refereegranskat)abstract
- Human BarH-like homeobox 2 (Barx2), a homeodomain factor of the Bar family, has an important role in controlling the expression of cell adhesion molecules and has been reported in an increasing array of tumor types except colorectal cancer (CRC). The purpose of the current study was to characterize the expression of Barx2 and assess the clinical significance of Barx2 in CRC. First, we analyzed the expression of Barx2 in two independent public datasets from Oncomine. Subsequently, we evaluated Barx2 mRNA and protein expression by quantitative real-time PCR and western blotting, respectively. It was determined that Barx2 expression was lower in tumor tissues than in adjacent non-tumorous colorectal tissues of CRC patients, consistent with results from the public datasets. Subsequently, a tissue microarray containing 196 CRC specimens was evaluated for Barx2 expression by immunohistochemical staining. It was found that low expression of Barx2 significantly correlated with TNM stage, AJCC stage, differentiation, and relapse in patients with CRC. Patients with lower levels of Barx2 expression showed reduced disease-free survival and overall survival. Furthermore, a trend toward shorter overall survival in the patient group with Barx2-negative tumors independent of advanced AJCC stage and poor differentiation was determined by Kaplan-Meier survival analysis. Based on univariate and multivariate analyses, Barx2 expression was an independent prognostic factor for determining CRC prognosis. Taken together, low Barx2 expression was associated with the progression of CRC and could serve as a potential independent prognostic biomarker for patients with CRC. (C) 2016 The Authors. Published by Elsevier Inc.
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| 4. |
- Mi, Yushuai, et al.
(författare)
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Downregulation of homeobox gene Barx2 increases gastric cancer proliferation and metastasis and predicts poor patient outcomes
- 2016
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Ingår i: Oncotarget. - : IMPACT JOURNALS LLC. - 1949-2553. ; 7:37, s. 60593-60608
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Tidskriftsartikel (refereegranskat)abstract
- Barx2 is a Bar family homeodomain transcription factor shown to play a critical role in cell adhesion and cytoskeleton remodeling, key processes in carcinogenesis and metastasis. Using quantitative real-time PCR, Western blotting, and immunohistochemistry, we found that Barx2 is expressed at lower levels in human gastric cancer (GC) tissues than in adjacent normal mucosa. In a multivariate analysis, Barx2 expression emerged as an independent prognostic factor for disease-free and overall survival. Kaplan-Meier survival analysis showed a trend toward even shorter overall survival in the patient group with Barx2-negative tumors, independent of advanced UICC stage and tumor relapse. Using in vitro and in vivo assays, we demonstrated that under normal conditions Barx2 inhibited GC cell proliferation and invasiveness through inhibition of the Wnt/beta-catenin signaling pathway. These findings indicate that reduction or loss of Barx2 dis-inhibits GC cell proliferation and invasion, and that reduction in Barx2 could serve as an independent prognostic biomarker for poor outcome in GC patients.
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| 5. |
- Xu, Heng, et al.
(författare)
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Editorial: Some Thoughts on Reviewing for Information Systems Research and Other Leading Information Systems Journals
- 2023
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Ingår i: Information Systems Research. - : INFORMS. - 1526-5536 .- 1047-7047. ; 34:4, s. 1321-1338
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Peer review of research before publication is both an essential and an integral part of scientific knowledge production. For reputable journals, the peer review process distinguishes knowledge claims in journal articles from those in sources with unknown or varying veracity. The peer review process assures readers that the published work is credible (i.e., conducted in line with prescribed norms of research) and meets a certain threshold with respect to contributions and potential impact. Leading journals are perceived as such not only because the best research is submitted to them but also because of the efforts of the best reviewers and editors in evaluating and, when applicable, developing the initially submitted manuscripts1 to publishable form. The sustained quality of reviews is critical for journals such as Information Systems Research (ISR). With the number of submissions to ISR growing each year, as well as an explicit policy of encouraging and celebrating inclusive excellence (Sarker 2023), there is a need for more reviewers for the journal (and the discipline, more generally) who have the necessary expertise to evaluate submitted papers, who understand and are attuned to the norms of the different traditions and genres of work submitted, and who know how to craft reviews that ensure the review process supports effective knowledge production. In this editorial, we draw on the expertise of some of the experienced associate editors (AEs) at ISR2 who represent different research traditions to provide guidance on how ISR reviewers can contribute reviews that AEs and authors are likely to find valuable. The primary audience of this editorial is Ph.D. students and early career scholars who occasionally review for, or seek to review for, ISR and similar journals. Although experienced reviewers likely know most of what we will say in the next few pages, we are hopeful that the editorial can provide a useful recapitulation of characteristics of reviews that are appreciated by ISR editors, irrespective of the reviewers’ experience. Finally, revisiting what reviewers look for in manuscripts can prove helpful for authors submitting papers to journals such as ISR. Before proceeding, we would like to acknowledge the efforts of editors and editorial board members from various journals who have organized reviewer development workshops (e.g., Rai 2019, Whitley 2023), and reflections on the review process and effective reviews by notable scholars in our discipline (e.g., Lee 1995; Saunders 2005a, b; Straub 2009; Kohli and Straub 2011; Davison 2015; Rai 2016; Leidner et al. 2022); see Table 1. Our editorial does not seek to supplant this accumulated wisdom but seeks to add nuances to the various guidelines that have been offered in the past. We illustrate key points with examples from various research traditions.
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| 6. |
- Zhang, Huimin, et al.
(författare)
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Modeling and simulation of a micro gas-cooled nuclear reactor using Modelica
- 2023
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Ingår i: Frontiers in Energy Research. - : Frontiers Media SA. - 2296-598X. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Highly compact micro nuclear reactors, which offer extensive energy benefits across ocean, land, space, and sky applications, have recently emerged as a popular research topic within the international nuclear industry. Due to its excellent inherent safety characteristics, the gas-cooled graphite-moderated reactor with TRISO fuel has attained extensive attention. Nonetheless, micro-reactors exhibit a high degree of system integration, characterized by the tight coupling and mutual constraints among various system functions. Conventional discipline-specific decoupled design patterns find it challenging to tackle the complexity arising from multi-disciplinary couplings. In response, this paper investigates the application of Modelica, a multi-domain unified modeling language, to construct models for several subsystems, encompassing the reactor, energy conversion system, and control system. This approach aims to enhance support for cross-disciplinary design. The accuracy of the reactor core model was verified by high-fidelity CFD simulation results, demonstrating a good agreement. Further investigations were then conducted on the safety and operational characteristics of the whole system. Typically, two simulations were conducted on the Gas cooled micro nuclear reactor (GCMR) design: one focused on an anticipated transients without scram accident scenario and the other on load-following operation. The simulation results demonstrated that the reactor possesses excellent inherent safety, even during extreme accidents. In such scenarios, the reactor is able to achieve shutdown solely through the negative reactivity resulting from increased core temperature. Furthermore, considering the heat accommodated in the reactor system and the constantly generated decay heat, a passive air-cooling mechanism has been investigated and successfully demonstrated with the model. The reactor also exhibits good load-following performance, which can be achieved by simply adjusting helium inventory (or pressure) and control drum position, while maintaining constant core temperature and power generation efficiency. These results can be leveraged to provide guidelines for further detailed designs of the GCMR.
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| 7. |
- Zhao, Yadong, 1985-, et al.
(författare)
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Cellulose nanofibrils-stabilized food-grade Pickering emulsions : Clarifying surface charge's contribution and advancing stabilization mechanism understanding
- 2024
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Ingår i: Food Hydrocolloids. - : Elsevier BV. - 0268-005X .- 1873-7137. ; 152
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Tidskriftsartikel (refereegranskat)abstract
- Pickering emulsions stabilized by cellulose nanofibrils (CN) have sparked significant attention, however the fundamental mechanisms underpinning the stabilization process remain insufficiently elucidated. Focusing on an academic debate of surface charge's contribution to stabilization, this study first explored how the varying carboxyl group contents of TEMPO-oxidized CN (TCNs) impacted Pickering emulsions' formation and stability. TCNs with 662 μmol/g carboxyl groups exhibited distinctive attributes, including larger particle sizes (322 nm in length), improved thermal stability (maximum decomposition temperature of 317 °C), and increased viscosity (1.57 Paִִ⋅s) compared to their counterparts with 963–1011 μmol/g charge density. Notably, the former one, with a larger three-phase contact angle (51.5°), higher interfacial tension, and greater detachment energy (21.69 × 10−18 J), resulted in a homogeneous dispersion of spherical oil droplets and super-stable Pickering emulsions with a consistent emulsifying index of 100% over 30 days. These findings clearly clarified that TCNs with a lower charge density exhibit superior emulsifying properties. In addition, for the first time, a distinct oil droplet-decorated fibrillar structure was observed, probably suggesting that TCNs might be able to serve as anchoring matrixes to guide the distribution of oil droplets. These structures seemed to impeded the migration and accumulation of the oil droplets, consequently enhancing the stability of the resulting Pickering emulsions. To sum, this study clearly elucidated the role of surface charge in stabilizing cellulose-based Pickering emulsions and proposed a new model to expound the cellulose-oil interaction mechanisms, thus providing new theoretical and practical insights on utilization of CN as highly effective emulsifier for super-stable food-grade Pickering emulsions.
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