Objective
To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.
Materials and Methods
This prospective study consisted of 144 patients with chronic ...hepatitis B. Ultrasomics—high-throughput quantitative data from ultrasound imaging of liver fibrosis—were generated using conventional radiomics, original radiofrequency (ORF) and contrast-enhanced micro-flow (CEMF) features. Three categories of features were explored using pairwise correlation and hierarchical clustering. Features were selected using diagnostic tests for fibrosis, activity and steatosis stage, with the histopathological results as the reference. The fibrosis staging performance of ultrasomics models with combinations of the selected features was evaluated with machine-learning algorithms by calculating the area under the receiver-operator characteristic curve (AUC).
Results
ORF and CEMF features had better predictive power than conventional radiomics for liver fibrosis stage (both
p
< 0.01). CEMF features exhibited the highest diagnostic value for activity stage (both
p
< 0.05), and ORF had the best diagnostic value for steatosis stage (both
p
< 0.01). The machine-learning classifiers of adaptive boosting, random forest and support vector machine were found to be optimal algorithms with better (all mean AUCs = 0.85) and more stable performance (coefficient of variation = 0.01–0.02) for fibrosis staging than decision tree, logistic regression and neural network (mean AUC = 0.61–0.72, CV = 0.07–0.08). The multiparametric ultrasomics model achieved much better performance (mean AUC values of 0.78–0.85) than the features from a single modality in discriminating significant fibrosis (≥ F2).
Conclusion
Machine-learning-based analysis of multiparametric ultrasomics can help improve the discrimination of significant fibrosis compared with mono or dual modalities.
Key Points
• Multiparametric ultrasomics has achieved much better performance in the discrimination of significant fibrosis (≥ F2) than the single modality of conventional radiomics, original radiofrequency and contrast-enhanced micro-flow.
• Adaptive boosting, random forest and support vector machine are the optimal algorithms for machine learning.
NMR-Based Protein Potentials Li, Da-Wei; Brüschweiler, Rafael
Angewandte Chemie (International ed.),
September 10, 2010, Volume:
49, Issue:
38
Journal Article
Peer reviewed
Speed training: A highly efficient screening of new potentials against the parent molecular dynamics (MD) trajectories of trial proteins provides a greater than 105‐fold increase in the speed of the ...analysis by using a re‐weighting scheme guided by experimental NMR data for proteins, thereby improving the accuracy of computer simulations of proteins.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
As quality requirements play a crucial role in supply chain management (SCM), enterprises require appropriate information architecture to address evolving supply chain needs. Information architecture ...for supply chain quality management has drawn much attention from the research community and the industry in recent years. Recent research explores the role of service-oriented architecture (SOA), RFID, agent, workflow management, and the Internet of Things (IoT) as an enabler of real-time quality management and control in the supply chain. This paper attempts to analyse the current state of the art in information management for supply chain quality management, reviewing the current research and development in information architecture for supply chain quality management, and highlighting some of the key technologies that have the potential to significantly improve the performance of supply chain quality management. It is our hope that this paper will motivate the supply chain quality management community in deploying the technologies along with their breakthroughs with the objective of realising automated supply chain quality management.
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BFBNIB, GIS, IJS, IZUM, KILJ, KISLJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Manipulating a quantum state via electrostatic gating has been of great importance for many model systems in nanoelectronics. Until now, however, controlling the electron spins or, more specifically, ...the magnetism of a system by electric-field tuning has proven challenging
. Recently, atomically thin magnetic semiconductors have attracted significant attention due to their emerging new physical phenomena
. However, many issues are yet to be resolved to convincingly demonstrate gate-controllable magnetism in these two-dimensional materials. Here, we show that, via electrostatic gating, a strong field effect can be observed in devices based on few-layered ferromagnetic semiconducting Cr
Ge
Te
. At different gate doping, micro-area Kerr measurements in the studied devices demonstrate bipolar tunable magnetization loops below the Curie temperature, which is tentatively attributed to the moment rebalance in the spin-polarized band structure. Our findings of electric-field-controlled magnetism in van der Waals magnets show possibilities for potential applications in new-generation magnetic memory storage, sensors and spintronics.
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IJS, NUK, SBMB, UL, UM, UPUK
Deficiency in decidualization has been widely regarded as an important cause of spontaneous abortion. Generalized decidualization also includes massive infiltration and enrichment of NK cells. ...However, the underlying mechanism of decidual NK (dNK) cell residence remains largely unknown. Here, we observe that the increased macroautophagy/autophagy of decidual stromal cells (DSCs) during decidualization, facilitates the adhesion and retention of dNK cells during normal pregnancy. Mechanistically, this process is mediated through activation of the MITF-TNFRSF14/HVEM signaling, and further upregulation of multiple adhesion adhesions (e.g. Selectins and ICAMs) in a MMP9-dependent manner. Patients with unexplained spontaneous abortion display insufficient DSC autophagy and dNK cell residence. In addition, poor vascular remodeling of placenta, low implantation number and high ratio of embryo loss are observed in NK cell depletion mice. In therapeutic studies, low doses of rapamycin, a known autophagy inducer that significantly promotes endometrium autophagy and NK cell residence, and improves embryo absorption in spontaneous abortion mice models, which should be dependent on the activation of MITF-TNFRSF14/HVEM-MMP9-adhension molecules axis. This observation reveals novel molecular mechanisms underlying DSCs autophagy-driven dNK cell residence, and provides a potential therapeutic strategy to prevent spontaneous abortion.
Abbreviations: ACTA2/αSMA: actin alpha 2, smooth muscle; ATG: autophagy-related; ATG5
over
ESC: ATG5-overexpressed ESCs; BTLA: B and T lymphocyte associated; CDH1: cadherin 1; CDH5: cadherin 5; CXCL12: C-X-C motif chemokine ligand 12; dNK: decidual NK; DIC: decidual immune cell; DSC: decidual stromal cell; EOMES: eomesodermin; ESC: endometrial stromal cell; FCGR3A/CD16: Fc fragment of IgG receptor IIIa; HUVEC: human umbilical vein endothelial cell; ICAM: intercellular cell adhesion molecule; ILC: innate lymphoid cell; ITGB1: integrin subunit beta 1; ITGA2: integrin subunit alpha 2; IPA: Ingenuity Pathway Analysis; KIR2DL1: killer cell immunoglobulin like receptor, two Ig domains and long cytoplasmic tail 1; KLRD1/CD94: killer cell lectin like receptor D1; KLRK1/NKG2D: killer cell lectin like receptor K1; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; 3-MA: 3-methyladenine; MITF: melanocyte inducing transcription factor; MiT-TFE: microphthalmia family of bHLH-LZ transcription factors; MMP9: matrix metalloproteinase 9; MTOR: mechanistic target of rapamycin kinase; NCAM1/CD56: neural cell adhesion molecule 1; NCR2/NKp44: natural cytotoxicity triggering receptor 2; NK: natural killer; KLRB1/NK1.1: killer cell lectin like receptor B1; NP: normal pregnancy; PBMC: peripheral blood mononuclear cell; PECAM1/CD31: platelet and endothelial cell adhesion molecule 1; pNK: peripheral blood NK; PRF1/Perforin: Perforin 1; PTPRC/CD45: protein tyrosine phosphatase receptor type C; Rapa: rapamycin; rh-TNFSF14/LIGHT: recombinant human TNFSF14/LIGHT; SA: spontaneous abortion; SELE: selectin E; SELP: selectin P; SELL: selectin L; siATG5 DSCs: ATG5-silenced DSCs; siTNFRSF14/HVEM DSCs: TNFRSF14/HVEM-silenced DSCs; TBX21/T-bet: T-box transcription factor 21; SQSTM1/p62: sequestosome 1; TNFRSF14/HVEM: TNF receptor superfamily member 14; TNFSF14/LIGHT: TNF superfamily member 14; uNK: uterine NK; UIC: uterine immune cell; USC: uterine stromal cell; VCAM1: vascular cell adhesion molecule 1; VIM: vimentin.
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BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK
This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges ...which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.
The configuration designs and printing materials of screen-printed electrodes (SPEs) are developed over the past decades and the applications of SPEs in environmental analysis are reviewed in this ...article. Display omitted
► Screen-printed electrodes (SPEs) are economical substrates that attract interests. ► SPEs have been utilised for the rapid in situ analysis of environmental pollutants. ► The configuration designs and printing materials of SPEs are developed a lot. ► Some pretreatment techniques of surfaces are especially addressed.
Screen-printed electrodes (SPEs), which are used as economical electrochemical substrates, have gone through significant improvements over the past few decades with respect to both their format and their printing materials. Because of their advantageous material properties, such as disposability, simplicity, and rapid responses, SPEs have been successfully utilised for the rapid in situ analysis of environmental pollutants. This critical review describes the basic fabrication principles, the configuration designs of SPEs and the hybrid analytical techniques based on SPEs. We mainly overview the electrochemical applications of SPEs in environmental analysis over the past 3 years, including the determination of organic compounds, heavy metals and gas pollutants.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Lithium–sulfur (Li–S) batteries are one of promising candidates for the emerging applications that demand of high-energy and low-cost power sources. The pouch cell configuration is an essential ...platform to truly evaluate the advantages, challenges and opportunities of Li–S batteries. Herein, a critical link of specific energy and cost to pouch cell parameters is established to figure out importance of individual components in cells and hopefully direct future meaningful investigations. The specific energy analysis of a pouch cell indicates that realizing a projected specific energy of more than 500 Wh kg−1 requires to push critical cell parameters to their limits and that the electrolyte volume dominantly determines specific energy and cost of a Li–S pouch cell. Therefore, low-cost and high-energy Li–S batteries principally relies on stable operations of batteries under electrolyte-lean conditions. Especially, the cost of lithium salts used in Li–S batteries has a large room to fall down, by which Li–S batteries are expected to be more sustainable and affordable in the emerging applications. This Perspective article affords an alternative view to call for practical approaches to promote Li–S batteries toward markets.
Display omitted
•Li–S batteries are quantitatively analyzed based on pouch cell configurations.•A link of specific energy and cost to pouch cell parameters is established.•Electrolytes take a large portion of weight and cost in a pouch cell.•Achieving a 500 Wh kg−1 in cells pushes cell parameters to their limits.•Low cost lithium salts promise an affordable Li–S batteries.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The problem of domain generalization is to learn from multiple training domains, and extract a domain-agnostic model that can then be applied to an unseen domain. Domain generalization (DG) has a ...clear motivation in contexts where there are target domains with distinct characteristics, yet sparse data for training. For example recognition in sketch images, which are distinctly more abstract and rarer than photos. Nevertheless, DG methods have primarily been evaluated on photo-only benchmarks focusing on alleviating the dataset bias where both problems of domain distinctiveness and data sparsity can be minimal. We argue that these benchmarks are overly straightforward, and show that simple deep learning baselines perform surprisingly well on them. In this paper, we make two main contributions: Firstly, we build upon the favorable domain shift-robust properties of deep learning methods, and develop a low-rank parameterized CNN model for end-to-end DG learning. Secondly, we develop a DG benchmark dataset covering photo, sketch, cartoon and painting domains. This is both more practically relevant, and harder (bigger domain shift) than existing benchmarks. The results show that our method outperforms existing DG alternatives, and our dataset provides a more significant DG challenge to drive future research.
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