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Objective: This study aimed to explore the efficacy and optimal delivery time of human umbilical cord mesenchymal stem cells (hUC-MSCs) in treating collagenase-induced Achilles tendinopathy. Methods: Achilles tendinopathy in rats at early or advanced stages was induced by injecting collagenase I into bilateral Achilles tendons. A total of 28 injured rats were injected with a hUC-MSC solution or normal saline into bilateral tendons twice and sampled after 4 weeks for histological staining, gene expression analysis, transmission electron microscope assay and biomechanical testing analysis. Results: The results revealed better histological performance and a larger collagen fiber diameter in the MSC group. mRNA expression of TNF-α, IL-1β and MMP-3 was lower after MSC transplantation. Early MSC delivery promoted collagen I and TIMP-3 synthesis, and strengthened tendon toughness. Conclusion: hUC-MSCs demonstrated a therapeutic effect in treating collagenase-induced Achilles tendinopathy, particularly in the early stage of tendinopathy. [ABSTRACT FROM AUTHOR]

Nonlinear analysis has become an indispensable means for structural performance evaluation, but is still an expensive process especially for large and complex structures. Although the computer technology has largely improve the performance of nonlinear analysis, more efficient and accurate methods still attract the attention of the researchers. The Woodbury nonlinear method which uses the Woodbury formula to solve the incremental displacement response is an efficient kind of method for local nonlinear analysis, but it is no longer applicable for problems with large part of nonlinearity. Although some approximate methods have been proposed to improve the solution of linear equations in Woodbury nonlinear method, the induced error cannot be effectively controlled which leads to decreasing the convergence rate of the iterative computation and offsetting the improved computational efficiency. To address this problem, this paper proposes the Inexact Newton Woodbury (INW) method for efficient nonlinear analysis, which comprehensively considers the efficiency of both the solution of the linear equations and iterative computation. In terms of the linear equations, the improved Woodbury method is presented, where the approximation method is combined with the Woodbury formula, considerably enhancing the solution efficiency of the linear equations and largely extending the application range of the Woodbury formula. Moreover, to ensure the convergence rate which is another important influence factor of the overall nonlinear analysis efficiency, the inexact Newton condition with a new proposed forcing term applicable for the INW method is employed to make the iterative computation with superlinear convergence rate. Then, the time complexity analysis is conducted to make a comprehensive evaluation of the proposed INW method and the traditional Finite Element Method (FEM) from the aspects of the linear equations solution and iterative computation. The results show that the INW method is more efficient than the FEM especially for problems with large part of nonlinearity. Finally, a simulation example is presented to validate the efficiency and accuracy of the INW method. The results demonstrate that the INW method has higher efficiency under comparable accuracy with the Woodbury nonlinear method so that it has significantly potential for large part of nonlinearity problems. CE Database Subject Headings: Engineering structures; finite element method; material nonlinearity; time complexity [ABSTRACT FROM AUTHOR]

The development of ocean remote sensing makes it possible to obtain valuable information from a large amount of data. Deep learning is a powerful tool that is beneficial for obtaining ocean information from remote sensing data. Oceanic internal waves play an essential role in ocean activities. To obtain information on irregular stripes from Synthetic Aperture Radar (SAR) images, a stripe segmentation algorithm for oceanic internal waves is proposed based on SegNet. The research results show that the proposed method can identify whether the SAR images contain oceanic internal waves and obtain the respective locations of the light and dark stripes of the oceanic internal waves from SAR images. Furthermore, because this method can accurately determine the relative locations of the light and dark stripes, it can distinguish the moment when oceanic internal waves undergo polarity conversion. [ABSTRACT FROM AUTHOR]

This network meta-analysis aimed to compare the efficacy and safety of intravenous (IV) hydralazine, oral nifedipine, and IV labetalol with different dosage regimens in the treatment of severe hypertension during pregnancy. A comprehensive literature search was performed on PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov for randomized controlled trials (RCTs) exploring the effects of hydralazine, nifedipine, and labetalol in the treatment of severe hypertension during pregnancy. A total of 21 RCTs with 2183 patients comparing 7 regimens (oral nifedipine 50,60,90 mg; hydralazine 15,25 mg; and labetalol 220,300 mg) were identified. Compared with IV labetalol 300 mg, nifedipine 50,60, and 90 mg significantly improved the successful treatment rate of severe hypertension during pregnancy, nifedipine 50 and 90 mg and IV hydralazine 25 mg required significantly fewer doses to achieve target blood pressure (BP), and nifedipine 50 mg took significantly shorter time to achieve target BP. Subgroup analysis showed that only nifedipine 50 mg tablets, not capsules, required a significantly shorter time and fewer doses to achieve target BP than IV labetalol 300 mg. Moreover, nifedipine 60,90 mg showed superior effectiveness than IV hydralazine 15,25 mg in the successful treatment rate of severe hypertension during pregnancy. SUCRA analysis suggested that nifedipine 50,60,90 mg as the better regimens with the lower rates of overall ADR and neonatal complications. These findings demonstrated the superiority of oral nifedipine 50,60,90 mg, especially oral nifedipine 50 mg tablets, in the treatment of severe hypertension during pregnancy than IV labetalol 300 mg, while oral nifedipine 60,90 mg also showed superiority in the successful treatment rate of severe hypertension during pregnancy than IV hydralazine 15,25 mg. However, the limitations of the underlying data indicate that future large-scale and rigorous RCTs are needed to confirm such findings. [ABSTRACT FROM AUTHOR]

Purpose: To assess the absorption rate and factors related to the development of benign thyroid nodules (BTNs) following image-guided microwave ablation (MWA). Materials and methods: This retrospective study reviewed nodule efficacy in patients who underwent MWA of BTNs between January 2016 and January 2018. The endpoint was a third-year follow-up. Nodules were categorized into those showing complete absorption (volumes with less than 100% volume reduction ratio (VRR) and those showing partial absorption (100% VRR)). Univariable and multivariable regression analyses were carried out to identify variables that were associated with nodule absorption rates. Results: A total of 173 BTNs (median volume = 4.23 ml; 25–75 percentiles = 2.27–9.00 ml) from 173 patients were evaluated. 49.7% (86/173) of patients had nodules that became completely absorbed. The mean VRRs of all BTNs were 18.0%, 78.7%, 89.0%, 94.5%, and 97.1% at the 1-, 6-,12-, 24- and 36- month follow-ups. At the 3-year follow-up time point, nodule characteristics related to nodule VRR included nodule volume (adjusted odds ratio [AOR], 1.1 [95% CI: 1.0, 1.2]; p = 0.03) and nodule margin (AOR, 5.3 [95% CI: 1.8, 16.0]; p < 0.01). Treatment-related characteristics included energy per ml in nodular volume (AOR, 1.0 [95% CI: 1.0, 1.0]; p < 0.01) and blockage of peripheral flow (AOR, 3.3 [95% CI: 1.3 8.3]; p = 0.01). Conclusions: US-guided image-guided MWA results in satisfactory long-term outcomes for the patients with BTNs. Factors related to nodule absorption rate were the volume and margin of the nodule, energy per ml in nodular volume and blockage of peripheral flow. [ABSTRACT FROM AUTHOR]

A review of the methods of signal enhancement in laser-induced breakdown spectroscopy (LIBS) is presented. Conventional LIBS suffers from disadvantages of low sensitivity and high limits of detection compared with other analytical techniques, such as inductively coupled plasma mass spectrometry. During the last two decades, various methods have been applied to LIBS in order to realize highly quantitative and qualitative analysis. Current approaches include double-pulse excitation, spatial or magnetic confinement, spark discharge, etc. Different configurations of experimental setups and conditions are suggested for the realization of these improved techniques, while various parameters influence significantly on the enhancement effect. With the aim to study the laser ablation process and characterize the effectiveness of each method, several parameters such as plasma volume and emission intensity are reviewed. Several suggestions are proposed to explain the mechanism of each enhancement method. These modified techniques have been applied on various materials and fields. [ABSTRACT FROM AUTHOR]

As increasing numbers of people worldwide are using traditional Chinese medicines, their characterization has become increasingly critical. This study describes the development of a facile and reproducible high-performance liquid chromatography-based method to obtain the fingerprint of the traditional Chinese medicine Yuhuanglian. First, similarity analysis and Principal Component Analysis (PCA) were investigated to interpret differences in the chromatograms of samples from different groups. Seven fingerprint peaks were identified by electrospray ionization tandem mass spectrometry (ESI-MS/MS), including magnolforine, coptisine, berberin, epiberberin, dehydroevodiamine, 12α-hydroxylimonin, and 12α-hydroxyevodol. The established fingerprint method was then applied to the analysis of Evodiae Fructus, Coptis Rhizoma, Yuhuanglian, and analogs of Yuhuanglian, which reflected their chemical constituent properties. The proposed method provides a technical platform for the characterization of Yuhuanglian, which will ensure the safe and effective use of this traditional Chinese medicine. [ABSTRACT FROM PUBLISHER]

In robust statistics, the concept of breakdown point was introduced to quantify the robustness of an estimator in a linear regression model. Computing the breakdown point is useful in tuning some robust regression estimators (e.g., the least trimmed squares estimator). Computing the breakdown point for a structured linear model (i.e., one with dependencies among some prows of then x p design matrix X) can be very demanding. This article presents an algorithm for calculating the maximum breakdown point for sparse linear models, which are a special type of structured linear model whose design matrix has many zero entries. The algorithm decomposes a sparse design matrix into smaller submatrixes on which the computation is performed, thereby leading to substantial savings in computation. An assembly process, along with a few numerical examples, illustrate the application of the algorithm and demonstrate its computational benefits. [ABSTRACT FROM AUTHOR]

Inspired by the recently developed projection chart, such as the U² chart for monitoring a shift in the multivariate mean, this article proposes a multivariate projection chart for monitoring process variability. In engineering practice, people often build a linear process model to connect the multivariate quality measurements with a set of fixed assignable causes. The column space of the process model naturally provides a subspace for projection and subsequent monitoring and was indeed used as the projection subspace in the recently developed projection control charts for monitoring a shift the mean. For the purpose of monitoring variability, however, we will show that such a projection may not be advantageous. We propose an alternative projecting statistic, labeled as VS, to be used for constructing a multivariate variability monitoring chart. We show, through extensive numerical studies, that the VS chart entertains several advantages over other competing methods, such as its less restrictive requirements on the process model and generally improved detection performance. [ABSTRACT FROM AUTHOR]

The article discusses developments in different plant bioreactor expression systems. A summary of different factors that can potentially affect the application of various plant bioreactor systems in producing pharmaceuticals economically is provided. Case-by-case and proof of concept remains a must in utilizing plant bioreactors in order to produce recombinant proteins or pharmaceuticals successfully in plant biotechnology.

Phase I analysis of nonlinear profiles aims at identifying the data from an in-control process as accurately as possible so that quality engineers can have a good reference to establish the control charts for a future process. Unlike linear profiles, which can be represented by a linear regression model with its model parameters used for monitoring and detection, nonlinear profiles are often sampled into high-dimensional data vectors and analyzed by nonparametric methods. Meanwhile, automatic in-process data-collection devices generate huge historical data sets, which must be analyzed for the presence of observations from out-of-control process conditions. The high dimensionality and data contamination present a challenge to the Phase I analysis of nonlinear profiles. This paper presents a strategy that consists of two major components: a data-reduction component that projects the original data into a lower dimension subspace while preserving the data-clustering structure and a data-separation technique that can detect single and multiple shifts as well as outliers in the data. Simulated data sets as well as nonlinear profile signals from a forging process are used to illustrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

Ran, which functions in nucleocytoplasmic transport and mitosis, binds to and is regulated in part by Ran binding protein (RanBP). A RanBP cDNA (TaRanBP1) was isolated from a wheat cDNA library using RT-PCR product as a probe. The predicted amino acid sequence of TaRanBP1 is over 60% identity to AtRanBP1 from Arabidopsis and also with considerable similarity to human and fungi RanBPs. TaRanBP1 gene was expressed ubiquitously in roots, leaves and stems, with a similar abundance in these tissues. Phylogenetic reconstruction of TaRanBP1 with 32 other RanBPs from 26 species of organisms revealed that RanBPs from plants, animals and fungi clustered as the distinct groups, intraspecies isoforms were not developed for RanBPs, contrast with most other ancestral genes. Structural analysis revealed that all RanBPs were highly conserved in the middle region of their amino acid sequence, which included Ran binding domain and the three conserved motifs that have the essential roles in binding with Ran protein and promotion of GTP hydrolysis by the Ran/RanGAP/RanBP complex. However, N-terminus and C-terminus exhibited very low similarity between the different RanBPs. The different structures in N-terminus and C-terminus of RanBPs are likely to direct the Ran into the specific physiological processes and subsequently exhibit the different roles in different organisms. [ABSTRACT FROM AUTHOR]

An optimal engineering design problem is challenging because nonlinear objective functions usually need to be evaluated in a high-dimensional design space. This article presents a data-mining-aided optimal design method, that is able to find a competitive design solution with a relatively low computational cost. The method consists of four components: (1) a uniform-coverage selection method, that chooses design representatives from among a large number of original design alternatives for a nonrectangular design space; (2) feature functions, of which evaluation is computationally economical as the surrogate for the design objective function; (3) a clustering method, that generates a design library based on the evaluation of feature functions instead of an objective function; and (4) a classification method to create the design selection rules, eventually leading us to a competitive design. Those components are implemented to facilitate the optimal fixture layout design in a multistation panel assembly process. The benefit of the data-mining-aided optimal design is clearly demonstrated by comparison with both local optimization methods (e.g., simplex search) and random search-based optimizations (e.g., simulated annealing). [ABSTRACT FROM AUTHOR]

Automatic in-process data collection techniques have been widely Used in complicated manufacturing processes in recent years. The huge amounts of product measurement data have created great opportunities for process monitoring and diagnosis. Given such product quality measurements, this article examines the dignosability of the process faults in a multistage manufacturing process using a linear mixed-effects model. Fault diagnosability is defined in a general way that does not depend on specific diagnosis algorithms. The concept of minimal diagnosable class is proposed to expose the "aliasing" structure among process faults in a partially diagnosable system. The algorithms and procedures needed to obtain the minimal diagnosable class and to evaluate the system-level diagnosability are presented. The methodology, which can he used for any general linear input-output system, is illustrated using a panel assembly process and an engine head machining process. [ABSTRACT FROM AUTHOR]