Synthesis and protease-catalyzed hydrolysis of a novel hydrazinopeptide

In order to explore the potentiality of hydrazinopeptides as protease inhibitors, the resistance of the hydrazinopeptidic bond toward proteolysis was investigated. To this end, the novel hydrazinohexapeptide Z-Ala2-Pro-Val-hIle-Leu-OMe (1), where hIle represents hydrazinoisoleucine, was designed and synthesized together with the parent peptide Z-Ala2-Pro-Val-Ile-Leu-OMe (2). The interactions of 1 and 2 with human leukocyte elastase (HLE) and porcine pancreatic elastase (PPE) were analyzed comparatively. We observed that 1 behaved as a substrate for both elastases, without the formation of a stable acyl-enzyme as in the case of azapeptides. Compounds 1 and 2 were cleaved at the same site (-Val-parallel-NH-) with a slight delay of hydrolysis for 1 compared to 2 (kcat/KM for 1 vs. 2 decreased by a factor of 2.7 for the HLE-catalyzed hydrolysis at pH 8.0 and 25 degrees C). The presence of the hydrazinopeptide bond (-CONHNH-) in 1 reduced by a factor of 4.7 the apparent enzyme affinity without abolishing it. These results indicate that suitably designed hydrazinopeptides may represent interesting targets in the search for protease resisting pseudopeptides.     

Enhanced Osteoblast Adhesion to Epoxide‐Functionalized Surfaces

As an alternative to expensive extracellular matrix (ECM) proteins generally applied as coatings in Petri dishes used for cell binding, an innovative system based on epoxide‐functionalized monolayers capable of protein binding is proposed. Since cells bind to material surfaces through proteins, protein‐binding surfaces should also promote cell binding. Here we investigate how the cell‐binding properties of an epoxide‐functionalized surface compares with ECM protein gel coated surfaces and tissue culture polystyrene control surfaces. Glass surfaces are functionalized with glycidoxypropyltriethoxysilane (GOPS), which results in an epoxide‐functionalized surface capable of binding proteins through an epoxide–amine reaction. Advancing contact angle measurements and atomic force microscopy measurements confirm the formation of a homogeneous GOPS monolayer. This monolayer is micropatterned with fluorescein‐labeled ECM protein gel by microcontact printing (µCP). Confocal laser scanning microscopy (CLSM) shows accurately transferred ECM protein gel micropatterns. Osteoblasts that are seeded on these micropatterned substrates show a clear preference for adhering to the epoxide‐functionalized areas. The morphology of these cultured osteoblasts is needle‐like with high aspect ratios. As controls, osteoblasts are cultured on GOPS‐functionalized surfaces, unstructured ECM protein gel surfaces, and tissue culture polystyrene (TCPS). The GOPS surfaces demonstrate a drastic increase in cell adhesion after 2 h, whilst the other tests show no adverse effects of this surface on the osteoblasts as compared to ECM and TCPS. CLSM shows healthy cell morphologies on each surface. It is demonstrated for the first time that epoxide groups outperform ECM protein gel in cell adhesion, thereby providing new routes for cost‐effective coatings that improve biocompatibility as well as exciting, new methodologies to control and direct cell adhesion.     

Q2ABR: QoE‐aware adaptive video bit rate solution

In this paper, we propose a new adaptive bit rate (ABR) streaming method. This method is based on estimating and monitoring users' video streaming experience, their quality of experience (QoE). This ensures a good user QoE and optimises bandwidth utilisation by monitoring video buffer fill rate to ensure minimal data traffic. First, we achieve a QoE evaluation model based on network bandwidth, video segment representation, and dropped video frame rate parameters. Second, following our QoE evaluation model, we formulate an ABR method using the reinforcement learning (RL) paradigm to select video representations and using a breakpoint detection mechanism to monitor end‐user QoE variation. The proposed ABR method is called “QoE‐aware adaptive bit rate (Q2ABR)” and is composed of three individual modules, one for QoE estimation using machine learning methods, one for QoE variation monitoring using the breakpoint detection mechanism, and one for video representation selection using reinforcement learning. The design objective of Q2ABR is to ensure the overall QoE of these users while maintaining a minimum variation in the standard deviation of the users' QoE values. Third, the performance of the Q2ABR method is evaluated and compared with several existing ABR approaches in the literature using real traces that we collect on different transport scenarios (such as bus and train, among others). Since this method considers the user's perception of video quality as a regulator for optimising the overall video distribution network, good results are ensured in terms of the user's experience and buffer fill rate.     

Sputtering of graphite in pulsed and continuous arc and spark discharges

The environment that leads to the sputtering of graphite electrodes and formation of carbonaceous discharge has been studied with emission spectroscopy. Population level densities, excitation & vibrational temperatures and electron densities have been obtained from a set of three ion sources. The sources operate in continuous and pulsed discharge modes. The sputtered species include monatomic, diatomic and higher carbon clusters. The main sputtered species are excited and ionized C₁ (CI, CII, respectively) and C₂. In the continuous arc discharge the vibrational temperature derived from the Swan band of C₂ is ∼10,000 K, whereas, in the pulsed arc the excitation temperature of Neon is ∼11,000 K. The spark discharge yields an average excitation temperature of CI and NI ∼ 5500 K.     

Roll assortment optimization in a paper mill: An integer programming approach

Fine paper mills produce a variety of paper grades to satisfy demand for a large number of sheeted products. Huge reels of different paper grades are produced on a cyclical basis on paper machines. These reels are then cut into rolls of smaller size which are then either sold as such, or sheeted into finished products in converting plants. A huge number of roll sizes would be required to cut all finished products without trim loss and they cannot all be inventoried. An assortment of rolls is inventoried with the implication that the sheeting operations may yield trim loss. The selection of the assortment of roll sizes to stock and the assignment of these roll sizes to finished products have a significant impact on performances. This paper presents a model to decide the parent roll assortment and assignments to finished products based on these products demand processes, desired service levels, trim loss and inventory holding costs. Risk pooling economies made by assigning several finished products to a given roll size is a fundamental aspect of the problem. The overall model is a binary non-linear program. Two solution methods are developed: a branch and price algorithm based on column generation and a fast pricing heuristic, and a marginal cost heuristic. The two methods are tested on real data and also on randomly generated problem instances. The approach proposed was implemented by a large pulp and paper company.