Improved continuous-flow print head for micro-array deposition

Limitations in depositing ligands using conventional micro-array pin spotting have hindered the application of surface plasmon resonance imaging (SPRi) technology. To address these challenges we introduce a modification to our continuous-flow micro-spotting technology that improves ligand deposition. Using Flexchip™ protein A/G and neutravidin capturing surfaces, we demonstrate that our new microfluidic spotter requires 1000 times less concentrated antibodies and biotinylated ligands than is required for pin spotting. By varying the deposition flow rate, we show that the design of our tip overlay flow cell is efficient at delivering sample to the substrate surface. Finally, contact time studies show that it is possible to capture antibodies and biotinylated ligands at concentrations of less than 0.1 ug/ml and 100 pM, respectively. These improvements in spotting technology will help to expand the applications of SPRi systems in areas such as antibody screening, carbohydrate arrays, and biomarker detection.     

Enzyme microgels in packed-bed bioreactors with downstream amperometric detection using microfabricated interdigitated microsensor electrode arrays.

In this article, we describe the use of pH- responsive hydrogels as matrices for the immobilization of two enzymes, glucose oxidase (GOx) and glutamate oxidase (GlutOx). Spherical hydrogel beads were prepared by inverse suspension polymerization and the enzymes were immobilized by either physical entrapment or covalent immobilization within or on the hydrogel surface. Packed-bed bioreactors were prepared containing the bioactive hydrogels and these incorporated into flow injection (FI) systems for the quantitation of glucose and monosodium glutamate (MSG) respectively. The FI amperometric detector comprised a microfabricated interdigitated array within a thin-layer flow cell. For the FI manifold incorporating immobilized GOx, glucose response curves were found to be linear over the concentration range 1.8-280 mg dL(-1) (0.1-15.5 mM) with a detection limit of 1.4 mg dL(-1) (0.08 mM). Up to 20 samples can be manually analyzed per hour, with the hydrogel-GOx bioreactor exhibiting good within-day (0.19%) precision. The optimized FI manifold for MSG quantitation yielded a linear response range of up to 135 mg dL(-1) (8 mM) with a detection limit of 3.38 mg dL(-1) (0.2 mM) and a throughput of 30 samples h(-1). Analysis of commercially produced soup samples gave a within-day precision of 3.6%. Bioreactors containing these two physically entrapped enzymes retained > 60% of their initial activities after a storage period of up to 1 year.     

Challenges in calculation of the gamma index in radiotherapy – Towards good practice

The gamma index (γ) is one of the most commonly used metrics for the verification of complex modulated radiotherapy. The mathematical definition of the γ is computationally expensive and various techniques have been reported to speed up the calculation either by mathematically refining the γ or employing various computational techniques. These techniques can cause variation in output with different software implementations. The γ has traditionally been used to compare a 2D measured plane against a 2D or 3D dose distribution. Recently, software algorithm and hardware improvements have led to the possibility of using measured 2D data from commercial detector arrays to reconstruct a 3D-dose distribution and perform a volumetric comparison against the treatment planning system (TPS). A limitation in this approach is that commercial detector arrays have so far been limited by their spatial resolution which may affect the accuracy of the reconstructed 3D volume and subsequently the γ calculation. Additionally, 3D versus 3D γ comparison adds a layer of complication in the calculation of the γ given the increase in the number of calculation points and the result cannot be as easily interpreted in the same way as 2D comparison. This review summarises and highlights the computational challenges of the γ calculation and sheds light on some of these issues by means of a bespoke MATLAB software to demonstrate the impact of interpolation, γ search distance, resolution and 2D and 3D calculations. Finally, a recommendation is made on the minimum information that should be reported when publishing γ results.     

An Oscillating MinD Protein Determines the Cellular Positioning of the Motility Machinery in Archaea

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The problem of bone lamellation: An attempt to explain different proposed models

Collagen texture and osteocyte distribution were analyzed in human woven‐ and lamellar‐bone using scanning and transmission electron microscopy. We provide data substantiating the concept that lamellar bone is made up of an alternation of dense‐acellular lamellae and loose‐cellular lamellae, all exhibiting an interwoven texture of collagen fibers. An attempt is also made to explain how the present findings might conform to those of authors whose models propose orderly, geometric arrangements of collagen fibers inside bony lamellae. Such a comparison is possible because the present investigation analyzes split loose lamellae and tangentially‐sectioned dense lamellae. It emerged that only loose lamellae can be dissected, revealing a loose interwoven collagen texture and halved osteocyte lacunae. Dense lamellae cannot be split because of their compactness. The analysis of tangentially sectioned dense lamellae demonstrates that they consist of a network of interwoven collagen fiber bundles. Inside each bundle, collagen fibers run parallel to each other but change direction where they enter adjacent bundles, at angles as described by other authors whose TEM investigations were performed at a much higher magnification than those of the present study. Consequently, what these authors consider to be a lamella are, instead, bundles of collagen fibers inside a lamella. There is discussion of the role played by the manner of osteocyte‐recruitment in the deposition of lamellar‐ and woven‐bone and how the presence of these cells is crucial for collagen spatial arrangement in bone tissues. J. Morphol., 2013. © 2013 Wiley Periodicals, Inc.     

横斑腹小鸮一新亚种—杂斑腹小鸮(鸮形目:鸱鸮科)

在横断山区鸟类考察过程中,发现采自四川宝兴县硗碛和雅江县八角楼的两号小鴞属标本与原记录的种类有显著差异,经研究认为是横斑腹小鴞(Athene brama)的一新亚种,命名为: 横斑腹小鴞 新亚种—杂斑腹小鴞Athene brama poikila Subsp.nov. 正模标本 雄性成鸟(采集号6079),1964年12月6日,采自四川省宝兴县的硗碛,海拔高度2,200米。标本保存在四川农业大学。     

Unusual Formation of CoO@C “Dandelions” Derived from 2D Kagóme MOLs for Efficient Lithium Storage

Despite great breakthroughs, the search for anode materials with high performance for lithium‐ion batteries (LIBs) remains challenging. Hence, engineering advantageous structures via effective routes can bring new possibilities to the development of the LIB field. Herein, the precise synthesis of three‐dimensional (3D) hybrids of ultrathin carbon‐wrapped CoO (CoO@C) dandelions is reported by the pyrolysis of two‐dimensional (2D) Kagóme metal–organic layers (MOLs) at 400 °C under an Ar atmosphere. Due to the special coordination structure of the paternal MOLs, the resulting CoO nanowires show a small diameter of 5–10 nm and are uniformly confined within the ultrathin carbon layer. Based on the time‐dependent pyrolysis experiments, a crystal transformation mechanism of in situ self‐templated‐recrystallization‐self‐assembly accompanied by phase and morphology changes is first presented to reveal the formation of the 3D dandelion‐like spheres with assembly of nanowire arrays from a 2D Kagóme MOL. By virtue of structural and compositional features, including a 3D array structure, the small size of the primary ultrathin nanowires, and a uniform ultrathin graphitic carbon layer, these unique CoO@C dandelions display high specific capacity, good rate capability, and excellent cycling stability. Importantly, this approach can be extended to accurately synthesize other desired composite structures.     

Spillover of Drosophila suzukii between noncrop and crop areas: implications for pest management

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Mixture modeling for genome-wide localization of transcription factors

Chromatin immunoprecipitation followed by DNA microarray analysis (ChIP-chip methodology) is an efficient way of mapping genome-wide protein-DNA interactions. Data from tiling arrays encompass DNA-protein interaction measurements on thousands or millions of short oligonucleotides (probes) tiling a whole chromosome or genome. We propose a new model-based method for analyzing ChIP-chip data. The proposed model is motivated by the widely used two-component multinomial mixture model of de novo motif finding. It utilizes a hierarchical gamma mixture model of binding intensities while incorporating inherent spatial structure of the data. In this model, genomic regions belong to either one of the following two general groups: regions with a local protein-DNA interaction (peak) and regions lacking this interaction. Individual probes within a genomic region are allowed to have different localization rates accommodating different binding affinities. A novel feature of this model is the incorporation of a distribution for the peak size derived from the experimental design and parameters. This leads to the relaxation of the fixed peak size assumption that is commonly employed when computing a test statistic for these types of spatial data. Simulation studies and a real data application demonstrate good operating characteristics of the method including high sensitivity with small sample sizes when compared to available alternative methods.