Potential for pancreatic maturation of differentiating human embryonic stem cells is sensitive to the specific pathway of definitive endoderm commitment

This study provides a detailed experimental and mathematical analysis of the impact of the initial pathway of definitive endoderm (DE) induction on later stages of pancreatic maturation. Human embryonic stem cells (hESCs) were induced to insulin-producing cells following a directed-differentiation approach. DE was induced following four alternative pathway modulations. DE derivatives obtained from these alternate pathways were subjected to pancreatic progenitor (PP) induction and maturation and analyzed at each stage. Results indicate that late stage maturation is influenced by the initial pathway of DE commitment. Detailed quantitative analysis revealed WNT3A and FGF2 induced DE cells showed highest expression of insulin, are closely aligned in gene expression patterning and have a closer resemblance to pancreatic organogenesis. Conversely, BMP4 at DE induction gave most divergent differentiation dynamics with lowest insulin upregulation, but highest glucagon upregulation. Additionally, we have concluded that early analysis of PP markers is indicative of its potential for pancreatic maturation. © 2014 Jaramillo et al

Cloning and characterization of miRNAs from maize seedling roots under low phosphorus stress

MicroRNAs (miRNAs) are a class of small, non-coding regulatory RNAs that regulate gene expression by guiding target mRNA cleavage or translational inhibition in plants and animals. In this study, a small RNA library was constructed to identify conserved miRNAs as well as novel miRNAs in maize seedling roots under low level phosphorus stress. Twelve miRNAs were identified by high throughput sequencing of the library and subsequent analysis, two belong to conserved miRNA families (miRNA399b and miRNA156), and the remaining ten are novel and one of latter is conserved in gramineous species. Based on sequence homology, we predicted 125 potential target genes of these miRNAs and then expression patterns of 7 miRNAs were validated by semi-RT-PCR analysis. MiRNA399b, Zma-miR3, and their target genes (Zmpt1 and Zmpt2) were analyzed by real-time PCR. It is shown that both miRNA399b and Zma-miR3 are induced by low phosphorus stress and regulated by their target genes (Zmpt1 and Zmpt2). Moreover, Zma-miR3, regulated by two maize inorganic phosphate transporters as a newly identified miRNAs, would likely be directly involved in phosphate homeostasis, so was miRNA399b in Arabidopsis and rice. These results indicate that both conserved and maize-specific miRNAs play important roles in stress responses and other physiological processes correlated with phosphate starvation, regulated by their target genes. Identification of these differentially expressed miRNAs will facilitate us to uncover the molecular mechanisms underlying the progression of maize seedling roots development under low level phosphorus stress

A Novel Hybrid Error Criterion-Based Active Control Method for on-Line Milling Vibration Suppression with Piezoelectric Actuators and Sensors

Milling vibration is one of the most serious factors affecting machining quality and precision. In this paper a novel hybrid error criterion-based frequency-domain LMS active control method is constructed and used for vibration suppression of milling processes by piezoelectric actuators and sensors, in which only one Fast Fourier Transform (FFT) is used and no Inverse Fast Fourier Transform (IFFT) is involved. The correction formulas are derived by a steepest descent procedure and the control parameters are analyzed and optimized. Then, a novel hybrid error criterion is constructed to improve the adaptability, reliability and anti-interference ability of the constructed control algorithm. Finally, based on piezoelectric actuators and acceleration sensors, a simulation of a spindle and a milling process experiment are presented to verify the proposed method. Besides, a protection program is added in the control flow to enhance the reliability of the control method in applications. The simulation and experiment results indicate that the proposed method is an effective and reliable way for on-line vibration suppression, and the machining quality can be obviously improved

Fundamentally mode-locked 3 ghz femtosecond erbium fiber laser

Proceedings of the 16th International Conference, Palazzo dei Congressi Stresa, Italy, June 9--13, 2008Low jitter 500-fs pulse trains at a fundamental repetition rate of 3.2 GHz, from an Erfiber laser with a saturable Bragg reflector. An increase in repetition rate of femtosecond fiberlasers by one order of magnitude

Subclass representation‐based face‐recognition algorithm derived from the structure scatter of training samples

Representation‐based face‐recognition techniques have received attention in the field of pattern recognition in recent years; however, the well‐known works focus mainly on constraint conditions and dictionary learning. Few researchers study, which sample data features determine the performance of representation‐based classification algorithms. To address this problem, the authors define the structure‐scatter degree, which represents the structural features of training sample sets, to determine whether a set is suitable for the representation‐based classification algorithm. Experimental results show that sets with a higher structure scatter more likely allows a classification algorithm to obtain a higher recognition rate. Further, the block contribution degree (DBC) of a training sample set is defined to evaluate whether a sample set is suitable for block‐based sparse‐representation classification algorithms. Experimental results indicate that if the DBC approaches zero, the block technique is unlikely to improve the performance of a representation‐based classification algorithm. Thus, they devise a self‐adaptive optimisation method to generate an optimal block size, an overlapping degree, and a block‐weighting scheme. Finally, they propose the structure scatter‐based subclass representation classification. Experimental results demonstrate that the proposed algorithm not only improves the recognition accuracy of the representation‐based classification algorithm, but also greatly reduces its time complexity