Building up PtII−Thiosemicarbazone−Lysine−sC18 Conjugates

Three chiral tridentate N^N^S coordinating pyridine-carbaldehyde (S)-N4-(α-methylbenzyl)thiosemicarbazones (HTSCmB) were synthesised along with lysine-modified derivatives. One of them was selected and covalently conjugated to the cell-penetrating peptide sC18 by solid-phase peptide synthesis. The HTSCmB model ligands, the HTSCLp derivatives and the peptide conjugate rapidly and quantitatively form very stable Pt^II chlorido complexes [Pt(TSC)Cl] when treated with K₂PtCl₄ in solution. The Pt(CN) derivatives were obtained from one TSCmB model complex and the peptide conjugate complex through Cl⁻→CN⁻ exchange. Ligands and complexes were characterised by NMR, IR spectroscopy, HR-ESI-MS and single-crystal XRD. Intriguingly, no decrease in cell viability was observed when testing the biological activity of the lysine-tagged HdpyTSCLp, its sC18 conjugate HdpyTSCL-sC18 or the PtCl and Pt(CN) conjugate complexes in three different cell lines. Thus, given the facile and effective preparation of such Pt-TSC-peptide conjugates, these systems might pave the way for future use in late-stage labelling with Pt radionuclides and application in nuclear medicine.     

Loliolide,a New Therapeutic Option for Neurological Diseases? In Vitro Neuroprotective and Anti-Inflammatory Activities of a Monoterpenoid Lactone Isolated from Codium tomentosum

Parkinsons Disease (PD) is the second most common neurodegenerative disease worldwide, and is characterized by a progressive degeneration of dopaminergic neurons. Without an effective treatment, it is crucial to find new therapeutic options to fight the neurodegenerative process, which may arise from marine resources. Accordingly, the goal of the present work was to evaluate the ability of the monoterpenoid lactone Loliolide, isolated from the green seaweed Codium tomentosum, to prevent neurological cell death mediated by the neurotoxin 6-hydroxydopamine (6-OHDA) on SH-SY5Y cells and their anti-inflammatory effects in RAW 264.7 macrophages. Loliolide was obtained from the diethyl ether extract, purified through column chromatography and identified by NMR spectroscopy. The neuroprotective effects were evaluated by the MTT method. Cells’ exposure to 6-OHDA in the presence of Loliolide led to an increase of cells’ viability in 40%, and this effect was mediated by mitochondrial protection, reduction of oxidative stress condition and apoptosis, and inhibition of the NF-kB pathway. Additionally, Loliolide also suppressed nitric oxide production and inhibited the production of TNF-α and IL-6 pro-inflammatory cytokines. The results suggest that Loliolide can inspire the development of new neuroprotective therapeutic agents and thus, more detailed studies should be considered to validate its pharmacological potential.     

Pull-Down of Metalloproteins in Their Native States by Using Desthiobiotin-Based Probes

One-third of all proteins are estimated to require metals for structural stability and/or catalytic activity. Desthiobiotin probes containing metal binding groups can be used to capture metalloproteins with exposed active-site metals under mild conditions so as to prevent changes in metallation state. The proof-of-concept was demonstrated with carbonic anhydrase (CA), an open active site, Zn²⁺-containing protein. CA was targeted by using sulfonamide derivatives. Linkers of various lengths and structures were screened to determine the optimal structure for capture of the native protein. The optimized probes could selectively pull down CA from red blood cell lysate and other protein mixtures. Pull-down of differently metallated CAs was also investigated.     

Uncertainties in the determination of pyrrolizidine alkaloid levels in naturally contaminated honeys and comparison of results obtained by different analytical approaches

The contamination of honey with hepatotoxic pyrrolizidine alkaloids (PAs) is a well-known hazard for food safety. While management strategies and controls of the honey industry aim to reduce the PA levels, uncertainties remain with regard to the safety of regionally produced and marketed honey. In addition, a previous study showed large differences of results obtained after various periods of storage and apparent differences between the analytical results of different laboratories. Therefore, this study aimed at examining these uncertainties by monitoring the impact of storage on the PA and PA N-oxide (PANO) content of two freshly harvested honeys and on possible demixing effects caused by pollen settling. Additionally, three analytical approaches – target analysis with matrix-matched calibration or standard addition and a sum parameter method – were applied for a comparative analysis of 20 honeys harvested in summer 2016. All samples originated from Schleswig-Holstein in Northern Germany where the PA plant Jacobaea vulgaris is currently observed on a massive scale. The results of the time series analyses showed that PANO levels markedly decreased within a few weeks and practically reached the LOD 16 weeks after harvest. Tertiary PAs, by contrast, remained stable and did not increase as a consequence of PANO decrease. The experiments on a putative demixing, which may result in a heterogeneous distribution of PAs/PANOs, revealed that there was no such effect during storage of up to 12 weeks. A comparison of the PA/PANO levels obtained by different analytical approaches showed that in some cases the sum parameter method yielded much higher levels than the target approaches, whereas in other cases, the target analysis with standard addition found higher levels than the other two methods. In summary, the results of this study highlight uncertainties regarding the validity and comparability of analytical results and consequently regarding health risk assessment.     

Modelling and optimization of a flexible poly(vinyl chloride) compound formulation for mine cables

Developments by Labuschagné et al. (Patent, WO 2006/123284 A2, 2006) in the manufacture of Layered Double Hydroxides (LDHs) have led to a patent describing a new effluent free synthesis method. A promising application for the LDH is as an additive for a flexible poly(vinyl chloride) (PVC) compound used for the insulation for cables used in South African underground mines. Consequently, a new formulation is required. Unfortunately formulating a PVC compound is a complex problem. The purpose of the investigation is to develop a method that can be used to find an optimum PVC formulation where the material requirements are met while also allowing for the quantitative analysis of the effect of the ingredients on the material properties. This is achieved by modeling the thermal stability, fire retardancy, and basic mechanical properties of the compound as a function of the relative proportions of the ingredients using 2nd order Scheffé polynomials. The empirical models are determined using statistical experimental design. Each model is interpreted using statistical analysis of the model terms which allows for the quantification of the effects and interactions of all the ingredients on the various response variables. The models are also used as constraints in the optimization of the PVC formulation for minimum cost. Parametric analyses are done to demonstrate how the optimization can be used to analyze the entire system taking into account the cost performance of the ingredients. Finally, it is demonstrated how the above approach requires significantly less time and labor to find an optimum formulation than the traditional approach. J. VINYL ADDIT. TECHNOL., 25:E44–E58, 2019. © 2017 Society of Plastics Engineers     

Ultrathin PECVD epitaxial Si solar cells on glass via low‐temperature transfer process

Fabrication of high‐quality ultrathin monocrystalline silicon layers and their transfer to low‐cost substrates are key steps for flexible electronics and photovoltaics. In this work, we demonstrate a low‐temperature and low‐cost process for ultrathin silicon solar cells. By using standard plasma‐enhanced chemical vapor deposition (PECVD), we grow high‐quality epitaxial silicon layers (epi‐PECVD) from SiH₄/H₂ gas mixtures at 175 °C. Using secondary ion mass spectrometry and transmission electron microscopy, we show that the porosity of the epi‐PECVD/crystalline silicon interface can be tuned by controlling the hydrogen accumulation there. Moreover, we demonstrate that 13–14% porosity is a threshold above which the interface becomes fragile and can easily be cleaved. Taking advantage of the H‐rich interface fragility, we demonstrate the transfer of large areas (∽10 cm²) ultrathin epi‐PECVD layers (0.5–5.5 µm) onto glass substrates by anodic bonding and moderate annealing (275–350 °C). The structural properties of transferred layers are assessed, and the first PECVD epitaxial silicon solar cells transferred on glass are characterized. Copyright © 2016 John Wiley & Sons, Ltd.     

The polynomial discrete Radon transform

This paper presents a new approach called polynomial discrete Radon transform (PDRT), regarded as a generalization of the classical finite discrete Radon transform. Specifically, the PDRT transforms an image into Radon space by summing the pixels according to polynomial curves. The PDRT can be applied on square \(p \times p\) images where \(p\) is assumed to be a prime number. It is based on a simple arithmetic operations and requires no data interpolation. An interesting property of the PDRT is its exact inversion. This means that an image can be transformed and then perfectly reconstructed. Through this study, we show that the new approach can be applied for some pattern recognition applications.     

An improved machine learning technique based on downsized KPCA for Alzheimer's disease classification

Alzheimer's disease (AD), a neurodegenerative disorder, is a very serious illness that cannot be cured, but the early diagnosis allows precautionary measures to be taken. The current used methods to detect Alzheimer's disease are based on tests of cognitive impairment, which does not provide an exact diagnosis before the patient passes a moderate stage of AD. In this article, a novel classifier of brain magnetic resonance images (MRI) based on the new downsized kernel principal component analysis (DKPCA) and multiclass support vector machine (SVM) is proposed. The suggested scheme classifies AD MRIs. First, a multiobjective optimization technique is used to determine the optimal parameter of the kernel function in order to ensure good classification results and to minimize the number of retained principle components simultaneously. The optimal parameter is used to build the optimized DKPCA model. Second, DKPCA is applied to normalized features. Downsized features are then fed to the classifier to output the prediction. To validate the effectiveness of the proposed method, DKPCA was tested using synthetic data to demonstrate its efficiency on dimensionality reduction, then the DKPCA based technique was tested on the OASIS MRI database and the results were satisfactory compared to conventional approaches.     

Carotene Degradation and Isomerization during Thermal Processing: A Review on the Kinetic Aspects

Kinetic models are important tools for process design and optimization to balance desired and undesired reactions taking place in complex food systems during food processing and preservation. This review covers the state of the art on kinetic models available to describe heat-induced conversion of carotenoids, in particular lycopene and β-carotene. First, relevant properties of these carotenoids are discussed. Second, some general aspects of kinetic modeling are introduced, including both empirical single-response modeling and mechanism-based multi-response modeling. The merits of multi-response modeling to simultaneously describe carotene degradation and isomerization are demonstrated. The future challenge in this research field lies in the extension of the current multi-response models to better approach the real reaction pathway and in the integration of kinetic models with mass transfer models in case of reaction in multi-phase food systems.