78,414 research outputs found

    Development and Validation of an In‐Line API Quantification Method Using AQbD Principles Based on UV‐Vis Spectroscopy to Monitor and Optimise Continuous Hot Melt Extrusion Process

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    open access journalA key principle of developing a new medicine is that quality should be built in, with a thorough understanding of the product and the manufacturing process supported by appropriate process controls. Quality by design principles that have been established for the development of drug products/substances can equally be applied to the development of analytical procedures. This paper presents the development and validation of a quantitative method to predict the concentration of piroxicam in KollidonÂź VA 64 during hot melt extrusion using analytical quality by design principles. An analytical target profile was established for the piroxicam content and a novel in‐line analytical procedure was developed using predictive models based on UV‐Vis absorbance spectra collected during hot melt extrusion. Risks that impact the ability of the analytical procedure to measure piroxicam consistently were assessed using failure mode and effect analysis. The critical analytical attributes measured were colour (L* lightness, b* yellow to blue colour parameters—in‐process critical quality attributes) that are linked to the ability to measure the API content and transmittance. The method validation was based on the accuracy profile strategy and ICH Q2(R1) validation criteria. The accuracy profile obtained with two validation sets showed that the 95% ÎČ‐expectation tolerance limits for all piroxicam concentration levels analysed were within the combined trueness and precision acceptance limits set at ±5%. The method robustness was tested by evaluating the effects of screw speed (150–250 rpm) and feed rate (5–9 g/min) on piroxicam content around 15% w/w. In‐line UV‐Vis spectroscopy was shown to be a robust and practical PAT tool for monitoring the piroxicam content, a critical quality attribute in a pharmaceutical HME process

    Optimal receptor-cluster size determined by intrinsic and extrinsic noise

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    Biological cells sense external chemical stimuli in their environment using cell-surface receptors. To increase the sensitivity of sensing, receptors often cluster, most noticeably in bacterial chemotaxis, a paradigm for signaling and sensing in general. While amplification of weak stimuli is useful in absence of noise, its usefulness is less clear in presence of extrinsic input noise and intrinsic signaling noise. Here, exemplified on bacterial chemotaxis, we combine the allosteric Monod-Wyman- Changeux model for signal amplification by receptor complexes with calculations of noise to study their interconnectedness. Importantly, we calculate the signal-to-noise ratio, describing the balance of beneficial and detrimental effects of clustering for the cell. Interestingly, we find that there is no advantage for the cell to build receptor complexes for noisy input stimuli in absence of intrinsic signaling noise. However, with intrinsic noise, an optimal complex size arises in line with estimates of the sizes of chemoreceptor complexes in bacteria and protein aggregates in lipid rafts of eukaryotic cells.Comment: 15 pages, 12 figures,accepted for publication on Physical Review

    Noise control and utility: From regulatory network to spatial patterning

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    Stochasticity (or noise) at cellular and molecular levels has been observed extensively as a universal feature for living systems. However, how living systems deal with noise while performing desirable biological functions remains a major mystery. Regulatory network configurations, such as their topology and timescale, are shown to be critical in attenuating noise, and noise is also found to facilitate cell fate decision. Here we review major recent findings on noise attenuation through regulatory control, the benefit of noise via noise-induced cellular plasticity during developmental patterning, and summarize key principles underlying noise control

    Krypton assay in xenon at the ppq level using a gas chromatographic system and mass spectrometer

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    We have developed a new method to measure krypton traces in xenon at unprecedented low concentrations. This is a mandatory task for many near-future low-background particle physics detectors. Our system separates krypton from xenon using cryogenic gas chromatography. The amount of krypton is then quantified using a mass spectrometer. We demonstrate that the system has achieved a detection limit of 8 ppq (parts per quadrillion) and present results of distilled xenon with krypton concentrations below 1 ppt.Comment: 7 pages, 4 figure

    Signals on Graphs: Uncertainty Principle and Sampling

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    In many applications, the observations can be represented as a signal defined over the vertices of a graph. The analysis of such signals requires the extension of standard signal processing tools. In this work, first, we provide a class of graph signals that are maximally concentrated on the graph domain and on its dual. Then, building on this framework, we derive an uncertainty principle for graph signals and illustrate the conditions for the recovery of band-limited signals from a subset of samples. We show an interesting link between uncertainty principle and sampling and propose alternative signal recovery algorithms, including a generalization to frame-based reconstruction methods. After showing that the performance of signal recovery algorithms is significantly affected by the location of samples, we suggest and compare a few alternative sampling strategies. Finally, we provide the conditions for perfect recovery of a useful signal corrupted by sparse noise, showing that this problem is also intrinsically related to vertex-frequency localization properties.Comment: This article is the revised version submitted to the IEEE Transactions on Signal Processing on May, 2016; first revision was submitted on January, 2016; original manuscript was submitted on July, 2015. The work includes 16 pages, 8 figure
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