A paper-based resonance energy transfer nucleic acid hybridization assay using upconversion nanoparticles as donors and quantum dots as acceptors

Monodisperse aqueous upconverting nanoparticles (UCNPs) were covalently immobilized on aldehyde modified cellulose paper via reduction amination to develop a luminescence resonance energy transfer (LRET)-based nucleic acid hybridization assay. This first account of covalent immobilization of UCNPs on paper for a bioassay reports an optically responsive method that is sensitive, reproducible and robust. The immobilized UCNPs were decorated with oligonucleotide probes to capture HPRT1 housekeeping gene fragments, which in turn brought reporter conjugated quantum dots (QDs) in close proximity to the UCNPs for LRET. This sandwich assay could detect unlabeled oligonucleotide target, and had a limit of detection of 13 fmol and a dynamic range spanning nearly 3 orders of magnitude. The use of QDs, which are excellent LRET acceptors, demonstrated improved sensitivity, limit of detection, dynamic range and selectivity compared to similar assays that have used molecular fluorophores as acceptors. The selectivity of the assay was attributed to the decoration of the QDs with polyethylene glycol to eliminate non-specific adsorption. The kinetics of hybridization were determined to be diffusion limited and full signal development occurred within 3 min.     

Electrocatalysis in confined space

The complex interplay of restricted mass transport leading to local accumulation or depletion of educts, intermediates, products, counterions and co-ions influences the reactions at the active sites of electrocatalysts when electrodes are rough, three-dimensionally mesoporous or nanoporous. This influence is important with regard to activity, and even more to selectivity, of electrocatalytic reactions. The underlying principles are discussed based on the growing awareness of these considerations over recent years.     

Effect of the milling process on the thermal behavior and crystallinity of buckwheat starch

Journal of Thermal Analysis and Calorimetry - Buckwheat starch is an alternative source to supply the high global demand for starch. The properties of starch can be modified through chemical and...     

Identifying aspirin polymorphs from combined DFT-based crystal structure prediction and solid-state NMR

A combined experimental and computational approach was used to distinguish between different polymorphs of the pharmaceutical drug aspirin. This method involves the use of ab initio random structure searching (AIRSS), a density functional theory (DFT)-based crystal structure prediction method for the high-accuracy prediction of polymorphic structures, with DFT calculations of nuclear magnetic resonance (NMR) parameters and solid-state NMR experiments at natural abundance. AIRSS was used to predict the crystal structures of form-I and form-II of aspirin. The root-mean-square deviation between experimental and calculated ¹H chemical shifts was used to identify form-I as the polymorph present in the experimental sample, the selection being successful despite the large similarities between the molecular environments in the crystals of the two polymorphs.     

In vivo comprehensive multiphase NMR

Traditionally, due to different hardware requirements, nuclear magnetic resonance (NMR) has developed as two separate fields: one dealing with solids, and one with solutions. Comprehensive multiphase (CMP) NMR combines all electronics and hardware (magic angle spinning [MAS], gradients, high power Radio Frequency (RF) handling, lock, susceptibility matching) into a universal probe that permits a comprehensive study of all phases (i.e., liquid, gel-like, semisolid, and solid), in intact samples. When applied in vivo, it provides unique insight into the wide array of bonds in a living system from the most mobile liquids (blood, fluids) through gels (muscle, tissues) to the most rigid (exoskeleton, shell). In this tutorial, the practical aspects of in vivo CMP NMR are discussed including: handling the organisms, rotor preparation, sample spinning, water suppression, editing experiments, and finishes with a brief look at the potential of other heteronuclei (²H, ¹⁵N, ¹⁹F, ³¹P) for in vivo research. The tutorial is aimed as a general resource for researchers interested in developing and applying MAS-based approaches to living organisms. Although the focus here is CMP NMR, many of the approaches can be adapted (or directly applied) using conventional high-resolution magic angle spinning, and in some cases, even standard solid-state NMR probes.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.     

Lithium Insertion Mechanism in Iron-Based Oxyfluorides with Anionic Vacancies Probed by PDF Analysis

The mechanism of lithium insertion that occurs in an iron oxyfluoride sample with a hexagonal–tungsten–bronze (HTB)-type structure was investigated by the pair distribution function. This study reveals that upon lithiation, the HTB framework collapses to yield disordered rutile and rock salt phases followed by a conversion reaction of the fluoride phase toward lithium fluoride and nanometer-sized metallic iron. The occurrence of anionic vacancies in the pristine framework was shown to strongly impact the electrochemical activity, that is, the reversible capacity scales with the content of anionic vacancies. Similar to FeOF-type electrodes, upon de-lithiation, a disordered rutile phase forms, showing that the anionic chemistry dictates the atomic arrangement of the re-oxidized phase. Finally, it was shown that the nanoscaling and structural rearrangement induced by the conversion reaction allow the in situ formation of new electrode materials with enhanced electrochemical properties.     

Finite‐size corrections at the hard edge for the Laguerre β ensemble

A fundamental question in random matrix theory is to quantify the optimal rate of convergence to universal laws. We take up this problem for the Laguerre β ensemble, characterized by the Dyson parameter β, and the Laguerre weight , in the hard edge limit. The latter relates to the eigenvalues in the vicinity of the origin in the scaled variable . Previous work has established the corresponding functional form of various statistical quantities—for example, the distribution of the smallest eigenvalue, provided that . We show, using the theory of multidimensional hypergeometric functions based on Jack polynomials, that with the modified hard edge scaling , the rate of convergence to the limiting distribution is , which is optimal. In the case , general the explicit functional form of the distribution of the smallest eigenvalue at this order can be computed, as it can for and general . An iterative scheme is presented to numerically approximate the functional form for general .     

Elemental distribution by synchrotron X-ray microfluorescence of prostate 3D cell culture

Prostate cancer is a highly prevalent disease and ranks second among malignant neoplasms that affect men around the world, behind lung cancer alone. Trace elements are very important and are involved in many cellular processes. The X-ray microfluorescence technique is an advanced tool of high spatial resolution, sensitivity, multielemental analysis, and nondestructiveness for trace element study. This study aimed to investigate the elemental distribution in spheroids obtained through the following human prostate cell lines using synchrotron X-ray microfluorescence: tumor cell line androgen independent (DU145), tumor cell line androgen dependent (LNCaP), and normal cell line (RWPE-1). The measurements were performed with a standard geometry of 45° of incidence, excited by a white beam using a pixel of 25 μm and an acquisition time of 300 ms/pixel at the X-ray fluorescence beamline at the Synchrotron Light National Laboratory (Campinas, Brazil). The synchrotron X-ray microfluorescence results showed differences between groups in all elements analyzed and suggested that further studies should be performed to understand the relationship of these trace elements with the progression and development of the disease.