Solubility determination from clear points upon solvent addition

A method is described for determining the solubility of multicomponent crystalline compounds from clear points upon sample dilution at a constant temperature. Clear points are established by continuously adding a solvent mixture to a suspension of known composition until a clear solution appears. For validation, this solvent addition method is compared to the traditional equilibrium concentration method at constant temperature and the more recent temperature variation method with which clear point temperatures are determined upon increasing the sample temperature. Solubility data of binary systems (1 solute, 1 solvent) measured using the solvent addition method are obtained relatively quickly compared to the equilibrium concentration method. These solubility data are consistent with those of the temperature variation and the equilibrium concentration method. For the temperature variation method, the results are dependent on the heating rate. Likewise, for the solvent addition method, they are dependent on the addition rate. Additionally, for ternary systems involving antisolvent or cocrystals, solubilities are determined at a constant temperature using the solvent addition method. The use of the solvent addition method is especially valuable in the case of solvent mixtures and other complex multicomponent systems, in which the temperature variation method cannot be applied easily

Immobilization of gluten in spherical matrices of food-grade hydrogels

The aim of this paper is to produce spherical encapsulates of wheat gluten in a food-grade biopolymer for preparing sheared meat analogs, to prevent instant fibrilization of the gluten during a pre-mixing step. The hydrogel should release the gluten inside the Couette Cell, as a result of the higher temperature and shear in the process. Both sodium alginate and κ-carrageenan were used as encapsulants. Spherical particles of hydrogel-gluten mixtures were produced by means of a dripping method using an encapsulator. While the particle properties of κ-carrageenan surpassed those of alginate in terms of controlled release of the core, the particle production using the encapsulator was more complicated. With κ-carrageenan, a layer of oil on top of the cross-linking bath fluid, as well as through the outer orifice of a concentric nozzle were required to obtain a good sphericity of the particles. For the alginate particles the use of oil was not necessary. Gluten loadings of 7% w/w were achieved with 1.5% w/w alginate and with 2% w/w κ-carrageenan. The water content of the particles can be easily controlled by a subsequent partial drying step. A mixture of Soy Protein Isolate and particles was sheared in the Couette Cell. Controlled release of the gluten from the alginate particles was not achieved properly by temperature or shear. The controlled release of the gluten was achieved at the processing conditions only with κ-carrageenan. Some fibrilization was observed in the sheared product, but the macrostructure was not yet well developed. However, an optimization of the shearing process for the use of the particles may lead to an improved structure for the meat analogs. Practical applications: This paper investigated the effect of encapsulation in hydrogels on the fibrilization behavior of wheat gluten upon contact with water. A cheap and easily scalable dripping technique was used to create spherical particles in which the gluten did not fibrilize, although the coating material consists of ≥95% of water. Upon reaching the process conditions in the shearing device, the gluten is released and able to form fibers. The results show that hydrogels can mechanically protect the core and act as a delivery structure. The protective and carrier functions of the hydrogel can alternatively be used for cores like food additives (e.g., vitamins) or even to pharmaceutical ingredients, not only for the production of meat analogs, but also in other food applications

Dynamic thoracohumeral kinematics are dependent upon the etiology of the shoulder injury

[EN] Obtaining kinematic patterns that depend on the shoulder injury may be important when planning rehabilitation. The main goal of this study is to explore whether the kinematic patterns of continuous and repetitive shoulder elevation motions are different according to the type of shoulder injury in question, specifically tendinopathy or rotator cuff tear, and to analyze the influence of the load handled during its assessment. For this purpose, 19 individuals with tendinopathy and 9 with rotator cuff tear performed a repetitive scaption movement that was assessed with stereophotogrammetry. Furthermore, static range of motion (ROM) and isometric strength were evaluated with a goniometer and a dynamometer, respectively. Dynamic measurements of maximum elevation (Emax), variablility of the maximum angle (VMA), maximum angular velocity (Velmax), and time to maximum velocity (tmaxvel) were found to be significantly different between the tendinopathy group (TG) and the rotator cuff tear group (RTCG). No differences were found in the ROM assessed with goniometry and the isometric strength. The effect of increasing the load placed in the hand during the scaption movement led to significant differences in Emax, VMA, tmaxvel and repeatability. Therefore, only the dynamic variables showed sufficient capability of detecting differences in functional performance associated with structural shoulder injury. The differences observed in the kinematic variables between patients with tendinopathy and rotator cuff tear seem to be related to alterations in thoracohumeral rhythm and neuromuscular control. Kinematic analysis may contribute to a better understanding of the functional impact of shoulder injuries, which would help in the assessment and treatment of shoulder pain.This work was funded by the Spanish Government, Secretaria de Estado de Investigacion, Desarrollo e Innovacion, and co-financed by EU FEDER funds (Grant DPI2013-44227-R). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Lopez Pascual, J.; Page Del Pozo, AF.; Serra Añó, P. (2017). Dynamic thoracohumeral kinematics are dependent upon the etiology of the shoulder injury. PLoS ONE. 12(8). https://doi.org/10.1371/journal.pone.0183954S12

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

Aims Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients.Methods and results Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 +/- 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P &lt;0.001).Conclusion Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com).</p

Sudden Cardiac Death Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy: A Multinational Collaboration

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. METHODS: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. RESULTS: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism. CONCLUSIO

A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy

AIMS: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. METHODS AND RESULTS: Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P < 0.001). CONCLUSION: Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com)

Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.Publisher PDFPeer reviewe

Role of Hyaluronic Acid on the Nucleation Kinetics of Calcium Oxalate Hydrates in Artificial Urine Quantified with Droplet Microfluidics

The increasing prevalence of urolithiasis in industrialized societies triggered considerable interest in how various species found in urine regulate the nucleation and growth of common kidney stone constituents such as calcium oxalate (CaOx). Yet, the role macromolecules play in kidney stone formation is often overlooked due to their low concentration in urine. In this study, we investigate the nucleation kinetics of CaOx in artificial urine with droplet-based microfluidic induction time measurements at varying concentrations of oxalate and hyaluronic acid (HA), a polysaccharide commonly found in urine. The formation of two pseudo-polymorphic forms of calcium oxalate crystals, calcium oxalate monohydrate (COM) and calcium oxalate dihydrate (COD), are carefully monitored using polarized light microscopy in induction time experiments. COM and COD nucleated concomitantly in artificial urine yet with distinct kinetics. Our results indicate that higher oxalate concentrations favor the formation of COD, the metastable form, over COM, the most stable form. Moreover, COD is also the fastest nucleating form in droplets under studied conditions. Furthermore, increasing the concentration of HA at fixed calcium and oxalate concentrations favored the nucleation of COM. We observed that in droplets where COM nucleated first, COD was not formed within the experimental time scale. However, in the droplets where COD appeared first, COM crystals were also observed later. We hope our findings shed light on the role macromolecules such as HA plays in dictating the pseudo-polymorphic form of CaOx and guide next generation treatments. QC 20220601</p

Rapid and On-Scene Chemical Identification of Intact Explosives with Portable Near-Infrared Spectroscopy and Multivariate Data Analysis

There is an ongoing forensic and security need for rapid, on-scene, easy-to-use, non-invasive chemical identification of intact energetic materials at pre-explosion crime scenes. Recent technological advances in instrument miniaturization, wireless transfer and cloud storage of digital data, and multivariate data analysis have created new and very promising options for the use of near-infrared (NIR) spectroscopy in forensic science. This study shows that in addition to drugs of abuse, portable NIR spectroscopy with multivariate data analysis also offers excellent opportunities to identify intact energetic materials and mixtures. NIR is able to characterize a broad range of chemicals of interest in forensic explosive investigations, covering both organic and inorganic compounds. NIR characterization of actual forensic casework samples convincingly shows that this technique can handle the chemical diversity encountered in forensic explosive investigations. The detailed chemical information contained in the 1350–2550 nm NIR reflectance spectrum allows for correct compound identification within a given class of energetic materials, including nitro-aromatics, nitro-amines, nitrate esters, and peroxides. In addition, the detailed characterization of mixtures of energetic materials, such as plastic formulations containing PETN (pentaerythritol tetranitrate) and RDX (trinitro triazinane), is feasible. The results presented illustrate that the NIR spectra of energetic compounds and mixtures are sufficiently selective to prevent false-positive results for a broad range of food-related products, household chemicals, raw materials used for the production of home-made explosives, drugs of abuse, and products that are sometimes used to create hoax improvised explosive devices. However, for frequently encountered pyrotechnic mixtures, such as black powder, flash powder, and smokeless powder, and some basic inorganic raw materials, the application of NIR spectroscopy remains challenging. Another challenge is presented by casework samples of contaminated, aged, and degraded energetic materials or poor-quality HMEs (home-made explosives), for which the spectral signature deviates significantly from the reference spectra, potentially leading to false-negative outcomes