NKT cell-dependent glycolipid–peptide vaccines with potent anti-tumour activity

It is known that T cells can eliminate tumour cells through recognition of unique or aberrantly expressed antigens presented as peptide epitopes by major histocompatibility complex (MHC) molecules on the tumour cell surface. With recent advances in defining tumour-associated antigens, it should now be possible to devise therapeutic vaccines that expand specific populations of anti-tumour T cells. However there remains a need to develop simpler efficacious synthetic vaccines that possess clinical utility. We present here the synthesis and analysis of vaccines based on conjugation of MHC-binding peptide epitopes to α-galactosylceramide, a glycolipid presented by the nonpolymorphic antigen-presenting molecule CD1d to provoke the stimulatory activity of type I natural killer T (NKT) cells. The chemical design incorporates an enzymatically cleavable linker that effects controlled release of the active components in vivo. Chemical and biological analysis of different linkages with different enzymatic targets enabled selection of a synthetic vaccine construct with potent therapeutic anti-tumour activity in mice, and marked in vitro activity in human blood.     

Vibration Spectroscopy Stability Investigation of 12-Tungstosilicic Acid Solution

Heteropoly acids (HPA) attract the attention of large variety of scientists, due to HPA’s extraordinary interesting properties and possible application fields. 12-tungstosilicic acid (WSiA), the Keggin type HPA, has some promising characteristic to be used in catalytic processes, but with not well-defined stability. Raman spectroscopy was used for in situ analysis of WSiA hydrolysis in detail in a wide pH range of 1–12. Raman spectroscopy is able to give an almost immediate response/spectrum as a representation of the exact profile/composition of the solution. This method and FTIR spectroscopy, as a complementary technique, enabled recording of the solid and liquid phases of the same sample under different conditions. Our results confirm that the decomposition pathways of WSiA in solution proceed via the formation of the lacunary monovacant anion at pH > 6.4. This anion is a major constituent in pH range up to 9.5. With further increases in pH this species convert to the trivacant lacunary anion. The total decomposition of the Keggin anion to silicate and tungstate occurs at pH > 11.0. The results of the performed study contribute to understand the behavior of WSiA in the water–methanol solution, as the model system of aqueous-organic system. It is concluded that addition of methanol in aqueous solution of WSiA leads to expansion of the pH region where Keggin anion is stable up to 8.1 and above this pH value, precipitation occurs. The obtained data clarify the stability range of WSiA in both water and water–methanol solutions, as well.     

Mechanistic investigations reveal that dibromobimane extrudes sulfur from biological sulfhydryl sources other than hydrogen sulfide

Hydrogen sulfide (H₂S) has emerged as an important biological signaling molecule in the last decade. During the growth of this field, significant controversy has arisen centered on the physiological concentrations of H₂S. Recently, a monobromobimane (mBB) method has been developed for the quantification of different biologically-relevant sulfide pools. Based on the prevalence of the mBB method for sulfide quantification, we expand on this method to report the use of dibromobimane (dBB) for sulfide quantification. Reaction of H₂S with dBB results in formation of highly-fluorescent bimane thioether (BTE), which is readily quantifiable by HPLC. Additionally, the reaction of sulfide with dBB to form BTE is significantly faster than the reaction of sulfide with mBB to form sulfide dibimane. Using the dBB method, BTE levels as low as 0.6 pM can be detected. Upon use of the dBB method in wild-type and CSE^–/– mice, however, dBB reports significantly higher sulfide levels than those measured using mBB. Further investigation revealed that dBB is able to extract sulfur from other sulfhydryl sources including thiols. Based on mechanistic studies, we demonstrate that dBB extracts sulfur from thiols with α- or β-hydrogens, thus leading to higher BTE formation than from sulfide alone. Taken together, the dBB method is a highly sensitive method for H₂S but is not compatible for use in studies in which other thiols are present.     

Insights into the structure–photoreactivity relationships in well-defined perovskite ferroelectric KNbO3 nanowires

Structure–function correlations are a central theme in heterogeneous (photo)catalysis. In this study, the geometric and electronic structure of perovskite ferroelectric KNbO₃ nanowires with respective orthorhombic and monoclinic polymorphs have been systematically addressed. By virtue of aberration-corrected scanning transmission electron microscopy, we directly visualize surface photocatalytic active sites, measure local atomic displacements at an accuracy of several picometers, and quantify ferroelectric polarization combined with first-principles calculations. The photoreactivity of the as-prepared KNbO₃ nanowires is assessed toward aqueous rhodamine B degradation under UV light. A synergy between the ferroelectric polarization and electronic structure in photoreactivity enhancement is uncovered, which accounts for the prominent reactivity order: orthorhombic > monoclinic. Additionally, by identifying new photocatalytic products, rhodamine B degradation pathways involving N-deethylation and conjugated structure cleavage are proposed. Our findings not only provide new insights into the structure–photoreactivity relationships in perovskite ferroelectric photocatalysts, but also have broad implications in perovskite-based water splitting and photovoltaics, among others.     

Advanced Developments in Cyclic Polymers: Synthesis,Applications, and Perspectives

Due to the topological effect, cyclic polymers demonstrate different and unique physical and biological properties in comparison with linear counterparts having the same molecular-weight range. With advanced synthetic and analytic technologies, cyclic polymers with different topologies, e.g. multicyclic polymers, have been reported and well characterized. For example, various cyclic DNA and related structures, such as cyclic duplexes, have been prepared conveniently by click chemistry. These types of DNA have increased resistance to enzymatic degradation and have high thermodynamic stability, and thus, have potential therapeutic applications. In addition, cyclic polymers have also been used to prepare organic–inorganic hybrids for applications in catalysis, e.g. catalyst supports. Due to developments in synthetic technology, highly pure cyclic polymers could now be produced in large scale. Therefore, we anticipate discovering more applications in the near future. Despite their promise, cyclic polymers are still less explored than linear polymers like polyolefins and polycarbonates, which are widely used in daily life. Some critical issues, including controlling the molecular weight and finding suitable applications, remain big challenges in the cyclic-polymer field. This review briefly summarizes the commonly used synthetic methodologies and focuses more on the attractive functional materials and their biological properties and potential applications.     

Sorting out the value of spectroscopic tools to assess the Colletotrichum acutatum impact in olive cultivars with different susceptibilities

The olive tree (Olea europaea L.) can be affected by Colletotrichum acutatum, causing a loss of yield and quality of the final products, whilst the incidence of this fungal infection depends on several factors, including cultivar susceptibility. Thus, the effect of C. acutatum infection in cultivars displaying different susceptibilities to this fungal disease (‘Galega Vulgar’ ‐ susceptible, ‘Cobrançosa’ ‐ moderately susceptible, ‘Picual’ ‐ tolerant) has been assessed through spectrophotometric methods and HPLC, while the FTIR spectra of the cuticles have been concomitantly registered, resorting to the ATR accessory. With the support of multivariate analysis, these spectra allowed to discriminate olives with distinct infection times, besides retrieving evidences concerning the different susceptibility of each cultivar, while these observations were reinforced by the spectrophotometric and chromatographic methods. Furthermore, the assessment of the phenolic profile evidenced individual compounds in the distinct cultivars, so as their variations in response to the fungal infection.     

Wavelength selection framework for classifying food and pharmaceutical samples into multiple classes

Near infrared (NIR) spectroscopy is an efficient, low‐cost analytical technique widely applied to identify the origin of food and pharmaceutical products. NIR spectra‐based classification strategies typically use thousands of equally spaced wavelengths as input information, some of which may not carry relevant information for product classification. When that is the case, the performance of predictive and exploratory multivariate techniques may be undermined by such noisy information. In this paper, we propose an iterative framework for selecting subsets of NIR wavelengths aimed at classifying samples into categories. For that matter, we integrate Principal Components Analysis (PCA) and three classification techniques: k‐Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Linear Discriminant Analysis (LDA). PCA is first applied to NIR data, and a wavelength importance index is derived based on the PCA loadings. Samples are then categorized using the wavelength with the highest index and the classification accuracy is calculated; next, the wavelength with the second highest index is inserted into the dataset and a new classification is performed. This forward‐based iterative procedure is carried out until all original wavelengths are inserted into the dataset used for classification. The subset of wavelengths leading to the maximum accuracy is chosen as the recommended subset. Our propositions performed remarkably well when applied to four datasets related to food and pharmaceutical products. Copyright © 2016 John Wiley & Sons, Ltd.