Clustering of Patients’ Trajectories with an Auto-Stopped Bisecting K-Medoids Algorithm

Nowadays, long wait, cancellations and resource overload frequently occur in healthcare, especially in those sectors related to the patients passing through the operating theatre in both United States and the European Union. Since more and more hospitals seek to develop the overall patient pathways instead of the effectiveness of “isolated” departments, the most important work has been defining suitable patient groups for employing process management and simulation tools developed in the recent decades. In this study, we proposed a data mining method, an auto-stopped Bisecting K-Medoids clustering algorithm, to classify patients into groups with homogenous trajectories. This method classifies the patient trajectories with two stages. At the first stage, patients are classified by the complexity of outpatient visits; afterwards, the groups obtained at the first stage are further classified by the original information of the trajectories where all medical appointments including outpatient ones are taken into account. By using a real data set collected from a medium-size Belgian hospital, we demonstrate how the proposed approach works and examine which kinds of trajectories are grouped into the same clusters. According to the experimental results, the proposed method can be used to classify patients into manageable groups with homogenous trajectories, which can be used as a base for the process modelling techniques and simulation tools.     

Solutions of the Equation of a Spinorial Yamabe-type Problem on Manifolds of Bounded Geometry

We consider a spinorial Yamabe-type problem on open manifolds of bounded geometry. The aim is to study the existence of solutions to the associated Euler–Lagrange-equation. We show that under suitable assumptions such a solution exists. As an application, we prove that existence of a solution implies the conformal Hijazi inequality for the underlying spin manifold.     

Design and Use of de novo Cascades for the Biosynthesis of New Benzylisoquinoline Alkaloids

The benzylisoquinoline alkaloids (BIAs) are an important group of secondary metabolites from higher plants and have been reported to show significant biological activities. The production of BIAs through synthetic biology approaches provides a higher‐yielding strategy than traditional synthetic methods or isolation from plant material. However, the reconstruction of BIA pathways in microorganisms by combining heterologous enzymes can also give access to BIAs through cascade reactions. Most importantly, non‐natural BIAs can be generated through such artificial pathways. In the current study, we describe the use of tyrosinases and decarboxylases and combine these with a transaminase enzyme and norcoclaurine synthase for the efficient synthesis of several BIAs, including six non‐natural alkaloids, in cascades from l ‐tyrosine and analogues.     

Correction to: Quantitative analysis of PET microplastics in environmental model samples using quantitative 1H-NMR spectroscopy: validation of an optimized and consistent sample clean-up method

Analytical and Bioanalytical Chemistry - The original version of this article contained a mistake.     

Mechanical properties of silk: interplay of deformation on macroscopic and molecular length scales

Using an in situ combination of tensile tests and x-ray diffraction, we have determined the mechanical properties of both the crystalline and the disordered phase of the biological nanocomposite silk by adapting a model from linear viscoelastic theory to the semicrystalline morphology of silk. We observe a strong interplay between morphology and mechanical properties. Silk's high extensibility results principally from the disordered phase; however, the crystals are also elastically deformed.     

Elucidating the Anomalous Binding Enhancement of Isoquinoline Boronic Acid for Sialic Acid Under Acidic Conditions: Expanding Biorecognition Beyond Vicinal Diols

A zwitterionic heterocyclic boronic acid based on 4-isoquinolineboronic acid (IQBA) exhibits the highest reported binding affinity for sialic acid or N-acetylneuraminic acid (Neu5Ac, K=5390±190 m ⁻¹) through the formation of a cyclic boronate ester complex under acidic conditions (pH 3). This anomalous pH-dependent binding enhancement does not occur with common neutral saccharides (e.g., glucose, fructose, sorbitiol), because it is mediated via selective complexation to a α-hydroxycarboxylate moiety forming a stable ion pair and ternary complex with Neu5Ac in phosphate buffer. IQBA expands biorecognition beyond classical vicinal diols under neutral or alkaline buffer conditions, which enables the direct analysis of Neu5Ac by native fluorescence with sub-micromolar detection limits.     

Controlled pinewood fractionation with supercritical ethanol: A prerequisite toward pinewood conversion into chemicals and biofuels

The objective of this work was to investigate the ability of supercritical (SC) ethanol conditions to attack preferentially the lignin fraction against the carbohydrate fraction and their effects on the product distribution among gases, light products, bio-oils, and chars. In this study, the conversion of each pinewood component was determined by the analysis of solid residues to quantify cellulose, hemicellulose, lignin, and char contents. It is shown that, by tuning the temperature, hemicellulose and lignin are already transformed in subcritical ethanol conditions, lignin being more reactive than hemicellulose. In contrast, native wood cellulose is recalcitrant to liquefaction in SC ethanol near the critical point (T_c = 241 °C and P_c = 61 bar), but 20% of native wood cellulose is converted in SC ethanol at 280 °C. Besides, the severity of the conditions, in terms of temperature and treatment time, does not significantly influence the yields of gases, light products, and bio-oils but strongly enhances char formation. Interestingly, the increase in SC ethanol density does not change the conversion of biomass components but has a marked effect on bio-oil yield and prevents char formation. The optimum fractionation conditions to convert the lignin component, while keeping unattacked the cellulose fraction with a minimum formation of char, are dense SC ethanol, at 250 °C for 1 h, in batch conditions. However, although lignin is more reactive than hemicellulose under these conditions, these fractions are converted, in a parallel way, to around 50% and 60%, respectively.     

Cu-Doped ZnO Nanoparticles for Non-Enzymatic Glucose Sensing

Copper-doped zinc oxide nanoparticles (NPs) Cu_xZn_1−xO (x = 0, 0.01, 0.02, 0.03, and 0.04) were synthesized via a sol-gel process and used as an active electrode material to fabricate a non-enzymatic electrochemical sensor for the detection of glucose. Their structure, composition, and chemical properties were characterized using X-ray diffraction (XRD), transmission electron microscopy (TEM), Fourier-transform infrared (FTIR) and Raman spectroscopies, and zeta potential measurements. The electrochemical characterization of the sensors was studied using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and differential pulse voltammetry (DPV). Cu doping was shown to improve the electrocatalytic activity for the oxidation of glucose, which resulted from the accelerated electron transfer and greatly improved electrochemical conductivity. The experimental conditions for the detection of glucose were optimized: a linear dependence between the glucose concentration and current intensity was established in the range from 1 nM to 100 μM with a limit of detection of 0.7 nM. The proposed sensor exhibited high selectivity for glucose in the presence of various interfering species. The developed sensor was also successfully tested for the detection of glucose in human serum samples.