Unravelling the specific site preference in doping of calcium hydroxyapatite with strontium from ab initio investigations and Rietveld analyses

Strontium can be substituted into the calcium sublattice of hydroxyapatite without a solubility limit. However, recent ab initio simulations carried out at 0 K report endothermic nature of this process. There is also striking discrepancy between experimentally observed preference of Sr doping at Ca-II sites and the first principles calculations, which indicate that a Ca-I site is preferred energetically for the Sr substitution. In this paper we combine insights from Density Functional Theory simulations and regular configurational entropy calculations to determine the site preference of Sr doping in the range of 0-100 at% at finite temperatures. In addition, samples of Sr-HA are synthesized and refinement of the relevant structural information provides benchmark information on the experimental unit cell parameters of Sr-HA. We find that the contribution of the entropy of mixing can efficiently overcome the endothermic excess energy at a temperature typical of the calcining step in the synthesis route of hydroxyapatite (700-950 degrees C). We observe that the most preferential substitution pattern is mixed substitution of Sr regardless of the concentration. For a wet chemical method, carried out at a moderate temperature (90 degrees C), the mixed doping is still slightly favourable at higher Sr-concentrations, except the range at 20% Sr, where Site II substitution is not restricted energetically and equally possible as the mixed doping. We observe a close correspondence between our theoretical results and available experimental data. Hence it should be possible to apply this theory to other divalent dopants in HA, such as Zn2+, Mg2+, Pb2+, Cu2+, Ba2+, Cd2+ etc

Evaluating the effectiveness of rosuvastatin in preventing the progression of diastolic dysfunction in aortic stenosis: A substudy of the aortic stenosis progression observation measuring effects of rosuvastatin (ASTRONOMER) study

<p>Abstract</p> <p>Background</p> <p>Tissue Doppler imaging (TDI) is a noninvasive echocardiographic method for the diagnosis of diastolic dysfunction in patients with varying degrees of aortic stenosis (AS). Little is known however, on the utility of TDI in the serial assessment of diastolic abnormalities in AS.</p> <p>Objective</p> <p>The aim of the current proposal was to examine whether treatment with rosuvastatin was successful in improving diastolic abnormalities in patients enrolled in the Aortic Stenosis Progression Observation Measuring Effects of Rosuvastatin (ASTRONOMER) study.</p> <p>Methods</p> <p>Conventional Doppler indices including peak early (E) and late (A) transmitral velocities, and E/A ratio were measured from spectral Doppler. Tissue Doppler measurements including early (E') and late (A') velocities of the lateral annulus were determined, and E/E' was calculated.</p> <p>Results</p> <p>The study population included 168 patients (56 ± 13 years), whose AS severity was categorized based on peak velocity at baseline (Group I: 2.5-3.0 m/s; Group II: 3.1-3.5 m/s; Group III: 3.6-4.0 m/s). Baseline and follow-up hemodynamics, LV dimensions and diastolic functional parameters were evaluated in all three groups. There was increased diastolic dysfunction from baseline to follow-up in each of the placebo and rosuvastatin groups. In patients with increasing severity of AS in Groups I and II, the lateral E' was lower and the E/E' (as an estimate of increased left ventricular end-diastolic pressure) was higher at baseline (p < 0.05). However, treatment with rosuvastatin did not affect the progression of diastolic dysfunction from baseline to 3.5 year follow-up between patients in any of the three predefined groups.</p> <p>Conclusion</p> <p>In patients with mild to moderate asymptomatic AS, rosuvastatin did not attenuate the progression of diastolic dysfunction.</p

Increased Prevalence of Chronic Disease in Back Pain Patients Living in Car-dependent Neighbourhoods in Canada: A Cross-sectional Analysis

Objectives Chronic diseases, including back pain, result in significant patient morbidity and societal burden. Overall improvement in physical fitness is recommended for prevention and treatment. Walking is a convenient modality for achieving initial gains. Our objective was to determine whether neighbourhood walkability, acting as a surrogate measure of physical fitness, was associated with the presence of chronic disease. Methods We conducted a cross-sectional study of prospectively collected data from a prior randomized cohort study of 227 patients referred for tertiary assessment of chronic back pain in Ottawa, ON, Canada. The Charlson Comorbidity Index (CCI) was calculated from patient-completed questionnaires and medical record review. Using patients’ postal codes, neighbourhood walkability was determined using the Walk Score, which awards points based on the distance to the closest amenities, yielding a score from 0 to 100 (0-50: car-dependent; 50-100: walkable). Results Based on the Walk Score, 134 patients lived in car-dependent neighborhoods and 93 lived in walkable neighborhoods. A multivariate logistic regression model, adjusted for age, gender, rural postal code, body mass index, smoking, median household income, percent employment, pain, and disability, demonstrated an adjusted odds ratio of 2.75 (95% confidence interval, 1.16 to 6.53) times higher prevalence for having a chronic disease for patients living in a car-dependent neighborhood. There was also a significant dose-related association (p=0.01; Mantel-Haenszel chi-square=6.4) between living in car-dependent neighbourhoods and more severe CCI scores. Conclusions Our findings suggest that advocating for improved neighbourhood planning to permit greater walkability may help offset the burden of chronic disease

A guide to creating design matrices for gene expression experiments.

Differential expression analysis of genomic data types, such as RNA-sequencing experiments, use linear models to determine the size and direction of the changes in gene expression. For RNA-sequencing, there are several established software packages for this purpose accompanied with analysis pipelines that are well described. However, there are two crucial steps in the analysis process that can be a stumbling block for many -- the set up an appropriate model via design matrices and the set up of comparisons of interest via contrast matrices. These steps are particularly troublesome because an extensive catalogue for design and contrast matrices does not currently exist. One would usually search for example case studies across different platforms and mix and match the advice from those sources to suit the dataset they have at hand. This article guides the reader through the basics of how to set up design and contrast matrices. We take a practical approach by providing code and graphical representation of each case study, starting with simpler examples (e.g. models with a single explanatory variable) and move onto more complex ones (e.g. interaction models, mixed effects models, higher order time series and cyclical models). Although our work has been written specifically with a limma-style pipeline in mind, most of it is also applicable to other software packages for differential expression analysis, and the ideas covered can be adapted to data analysis of other high-throughput technologies. Where appropriate, we explain the interpretation and differences between models to aid readers in their own model choices. Unnecessary jargon and theory is omitted where possible so that our work is accessible to a wide audience of readers, from beginners to those with experience in genomics data analysis

Unravelling the link between solvent-mediated proton transfer and the salt formation of saccharin and sulfamethazine

Molecular tautomerism has been reported to play an important role in the crystallization of active pharmaceutical ingredients, particularly in the formation of pharmaceutical cocrystals and salts. In this work, by combining molecular modeling, crystallization experiments, and spectroscopic techniques, we investigate possible molecular mechanisms by which solvent can mediate proton transfer in a tautomerization process. We found that the salt formation of sulfamethazine-saccharin takes place in the presence of protic solvent (ethanol, water), but is prohibited in aprotic solvent such as toluene. Our density functional theory calculations reveal that protic (polar) solvents such as ethanol and water facilitate proton transfer, serving as catalysts of the transformation of saccharin into its tautomerized (enol) form, being a prerequisite to the formation of the salt. In line with these predictions, our FTIR results confirm that the proton transfer and the resulting transformation from the keto to enol form of saccharin does not take place in aprotic chloroform, but is clearly observed in protic ethanol solution. We believe that the mechanistic insight provided by our study will aid rational solvent selection for the crystallization processes involving molecules with propensity for tautomerization

An insight into the role of additives in controlling polymorphic outcome: a CO2-antisolvent crystallization process of carbamazepine

Controlling pharmaceutical polymorphism in crystallization processes represents a major challenge in pharmaceutical science and engineering. For instance, CO2-antisolvent crystallization typically favors the formation of metastable forms of carbamazepine (CBZ), a highly polymorphic drug, with impurities of other forms. This work demonstrates for the first time that a supercritical CO2- antisolvent crystallization process in combination with certain molecular additives allows control of the polymorphic outcome of carbamazepine. We show herein that in the presence of sodium stearate and Eudragit L-100, needle-shaped crystals of CBZ form II are obtained, while blocky-shaped crystals of CBZ form III are obtained in the presence of Kollidon VA64, sodium dodecyl sulfate, ethyl cellulose and maltitol. This selectivity for pure forms in this supercritical set up contrasts to the results when the same set of additives where used in a solvent evaporation method that yielded mixtures of form I, II and III. The type of additive used in the CO2-antisolvent crystallization process impacted both the product crystals polymorphic form and size. A detailed molecular-level analysis along with DFT calculations allowed us to give a mechanistic insight into the role of sodium stearate and Eudragit L-100 in facilitating nucleation of the metastable form II

Insight into the Role of Additives in Controlling Polymorphic Outcome: A CO₂‑Antisolvent Crystallization Process of Carbamazepine

Controlling pharmaceutical polymorphism in crystallization processes represents a major challenge in pharmaceutical science and engineering. For instance, CO₂-antisolvent crystallization typically favors the formation of metastable forms of carbamazepine (CBZ), a highly polymorphic drug, with impurities of other forms. This work demonstrates for the first time that a supercritical CO₂-antisolvent crystallization process in combination with certain molecular additives allows control of the polymorphic outcome of CBZ. We show herein that in the presence of sodium stearate and Eudragit L-100, needle-shaped crystals of CBZ form II are obtained, while blocky-shaped crystals of CBZ form III are obtained in the presence of Kollidon VA64, sodium dodecyl sulfate, ethyl cellulose, and maltitol. This selectivity for pure forms in this supercritical set up contrasts to the results when the same set of additives where used in a solvent evaporation method that yielded mixtures of form I, II, and III. The type of additive used in the CO₂-antisolvent crystallization process impacted both the product crystal polymorphic form and size. A detailed molecular-level analysis along with density functional theory calculations allowed us to give a mechanistic insight into the role of sodium stearate and Eudragit L-100 in facilitating nucleation of the metastable form II

Unravelling the specific site preference in doping of calcium hydroxyapatite with strontium from ab initio investigations and Rietveld analyses

Strontium can be substituted into the calcium sublattice of hydroxyapatite without a solubility limit. However, recent ab initio simulations carried out at 0 K report endothermic nature of this process. There is also striking discrepancy between experimentally observed preference of Sr doping at Ca-II sites and the first principles calculations, which indicate that a Ca-I site is preferred energetically for the Sr substitution. In this paper we combine insights from Density Functional Theory simulations and regular configurational entropy calculations to determine the site preference of Sr doping in the range of 0-100 at% at finite temperatures. In addition, samples of Sr-HA are synthesized and refinement of the relevant structural information provides benchmark information on the experimental unit cell parameters of Sr-HA. We find that the contribution of the entropy of mixing can efficiently overcome the endothermic excess energy at a temperature typical of the calcining step in the synthesis route of hydroxyapatite (700-950 degrees C). We observe that the most preferential substitution pattern is mixed substitution of Sr regardless of the concentration. For a wet chemical method, carried out at a moderate temperature (90 degrees C), the mixed doping is still slightly favourable at higher Sr-concentrations, except the range at 20% Sr, where Site II substitution is not restricted energetically and equally possible as the mixed doping. We observe a close correspondence between our theoretical results and available experimental data. Hence it should be possible to apply this theory to other divalent dopants in HA, such as Zn2+, Mg2+, Pb2+, Cu2+, Ba2+, Cd2+ etc