Experimental elucidation of templated crystallization and secondary processing of peptides

The crystallization of peptides offers a sustainable and inexpensive alternative to the purification process. In this study, diglycine was crystallised in porous silica, showing the porous templates' positive yet discriminating effect. The diglycine induction time was reduced by five-fold and three-fold upon crystallising in the presence of silica with pore sizes of 6 nm and 10 nm, respectively. The diglycine induction time had a direct relationship with the silica pore size. The stable form (α-form) of diglycine was crystallised in the presence of porous silica, with the diglycine crystals obtained associated with the silica particles. Further, we studied the mechanical properties of diglycine tablets for their tabletability, compactability, and compressibility. The mechanical properties of the diglycine tablets were similar to those of pure MCC, even with the presence of diglycine crystals in the tablets. The diffusion studies of the tablets using the dialysis membrane presented an extended release of diglycine through the dialysis membrane, confirming that the peptide crystal can be used for oral formulation. Hence, the crystallization of peptides preserved their mechanical and pharmacological properties. More data on different peptides can help us produce oral formulation peptides faster than usual

Critical evaluation of a simple retention time predictor based on LogKow as a complementary tool in the identification of emerging contaminants in water

There has been great interest in environmental analytical chemistry in developing screening methods based on liquid chromatography–high resolution mass spectrometry (LC–HRMS) for emerging contaminants. Using HRMS, compound identification relies on the high mass resolving power and mass accuracy attainable by these analyzers. When dealing with wide-scope screening, retention time prediction can be a complementary tool for the identification of compounds, and can also reduce tedious data processing when several peaks appear in the extracted ion chromatograms. There are many in silico, Quantitative Structure–Retention Relationship methods available for the prediction of retention time for LC. However, most of these methods use commercial software to predict retention time based on various molecular descriptors. This paper explores the applicability and makes a critical discussion on a far simpler and cheaper approach to predict retention times by using LogKow. The predictor was based on a database of 595 compounds, their respective LogKow values and a chromatographic run time of 18 min. Approximately 95% of the compounds were found within 4.0 min of their actual retention times, and 70% within 2.0 min. A predictor based purely on pesticides was also made, enabling 80% of these compounds to be found within 2.0 min of their actual retention times. To demonstrate the utility of the predictors, they were successfully used as an additional tool in the identification of 30 commonly found emerging contaminants in water. Furthermore, a comparison was made by using different mass extraction windows to minimize the number of false positives obtained.Ministerio de Economia y Competitividad, CTQ2012-36189. Generalitat Valenciana, 2009/054, 2014/023, ISIC/2012/016. European Union, 317205

On the evolutionary behaviour of BL Lac objects

We present a new well defined sample of BL Lac objects selected from the ROSAT All-Sky Survey (RASS). The sample consists of 39 objects with 35 forming a flux limited sample down to f_X = 8 x 10^{-13} cgs, redshifts are known for 33 objects (and 31 of the complete sample). X-ray spectral properties were determined for each object individually with the RASS data. The luminosity function of RASS selected BL Lac objects is compatible with results provided by objects selected with the Einstein observatory, but the RASS selected sample contains objects with luminosities at least tenfold higher. Our analysis confirms the negative evolution for X-ray selected BL Lac objects found in a sample by the Einstein observatory, the parameterization provides similar results. A subdivision of the sample into halves according to the X-ray to optical flux ratio yielded unexpected results. The extremely X-ray dominated objects have higher redshifts and X-ray luminosities and only this subgroup shows clear signs of strong negative evolution. The evolutionary behaviour of objects with an intermediate spectral energy distribution between X-ray and radio dominated is compatible with no evolution at all. Consequences for unified schemes of X-ray and radio selected BL Lac objects are discussed.We suggest that the intermediate BL Lac objects are the basic BL Lac population. The distinction between the two subgroups can be explained if extreme X-ray dominated BL Lac objects are observed in a state of enhanced X-ray activity.Comment: 14 pages incl. 8 figures, accepted by A&

Prediction of Retention Time and Collision Cross Section (CCSH+, CCSH–, and CCSNa+) of Emerging Contaminants Using Multiple Adaptive Regression Splines

Ultra-high performance liquid chromatography coupled to ion mobility separation and high-resolution mass spectrometry instruments have proven very valuable for screening of emerging contaminants in the aquatic environment. However, when applying suspect or nontarget approaches (i.e., when no reference standards are available), there is no information on retention time (RT) and collision cross-section (CCS) values to facilitate identification. In silico prediction tools of RT and CCS can therefore be of great utility to decrease the number of candidates to investigate. In this work, Multiple Adaptive Regression Splines (MARS) were evaluated for the prediction of both RT and CCS. MARS prediction models were developed and validated using a database of 477 protonated molecules, 169 deprotonated molecules, and 249 sodium adducts. Multivariate and univariate models were evaluated showing a better fit for univariate models to the experimental data. The RT model (R2 = 0.855) showed a deviation between predicted and experimental data of ±2.32 min (95% confidence intervals). The deviation observed for CCS data of protonated molecules using the CCSH model (R2 = 0.966) was ±4.05% with 95% confidence intervals. The CCSH model was also tested for the prediction of deprotonated molecules, resulting in deviations below ±5.86% for the 95% of the cases. Finally, a third model was developed for sodium adducts (CCSNa, R2 = 0.954) with deviation below ±5.25% for 95% of the cases. The developed models have been incorporated in an open-access and user-friendly online platform which represents a great advantage for third-party research laboratories for predicting both RT and CCS data.Funding for open access charge: CRUE-Universitat Jaume

Monitoring a large number of pesticides and transformation products in water samples from Spain and Italy

Assessing the presence of pesticides in environmental waters is particularly challenging because of the huge number of substances used which may end up in the environment. Furthermore, the occurrence of pesticide transformation products (TPs) and/or metabolites makes this task even harder. Most studies dealing with the determination of pesticides in water include only a small number of analytes and in many cases no TPs. The present study applied a screening method for the determination of a large number of pesticides and TPs in wastewater (WW) and surface water (SW) from Spain and Italy. Liquid chromatography coupled to high-resolution mass spectrometry (HRMS) was used to screen a database of 450 pesticides and TPs. Detection and identification were based on specific criteria, i.e. mass accuracy, fragmentation, and comparison of retention times when reference standards were available, or a retention time prediction model when standards were not available. Seventeen pesticides and TPs from different classes (fungicides, herbicides and insecticides) were found in WW in Italy and Spain, and twelve in SW. Generally, in both countries more compounds were detected in effluent WW than in influent WW, and in SW than WW. This might be due to the analytical sensitivity in the different matrices, but also to the presence of multiple sources of pollution. HRMS proved a good screening tool to determine a large number of substances in water and identify some priority compounds for further quantitative analysis.N. I. Rousis and R. Bade acknowledge the European Union’s International Training Network SEWPROF (Marie Curie-FP7-PEOPLE Grant no. 317205) for their Early Stage Researcher contracts. The authors of University Jaume I acknowledge the financial support of Generalitat Valenciana (Prometeo II 2014/023) and of the Spanish Ministry of Economy and Competitiveness (Project ref. CTQ2015-65603). The authors are grateful to J. D. Baggott for English editing

Facilitating high resolution mass spectrometry data processing for screening of environmental water samples: An evaluation of two deconvolution tools

A screening approach was applied to influent and effluent wastewater samples. After injection in a LC-LTQ-Orbitrap, data analysis was performed using two deconvolution tools, MsXelerator (modules MPeaks and MS Compare) and Sieve 2.1. The outputs were searched incorporating an in-house database of more than 200 pharmaceuticals and illicit drugs or ChemSpider. This hidden target screening approach led to the detection of numerous compounds including the illicit drug cocaine and its metabolite benzoylecgonine and the pharmaceuticals carbamazepine, gemfibrozil and losartan. The compounds found using both approaches were combined, and isotopic pattern and retention time prediction were used to filter out false positives. The remaining potential positives were reanalysed in MS/MS mode and their product ions were compared with literature and/or mass spectral libraries. The inclusion of the chemical database ChemSpider led to the tentative identification of several metabolites, including paraxanthine, theobromine, theophylline and carboxylosartan, as well as the pharmaceutical phenazone. The first three of these compounds are isomers and they were subsequently distinguished based on their product ions and predicted retention times. This work has shown that the use deconvolution tools facilitates non-target screening and enables the identification of a higher number of compoundsRichard Bade and Ana Causanilles acknowledge the European Union for their Early Stage Researcher (ESR) contracts as part of the EU-International Training Network SEWPROF (Marie Curie- PEOPLE Grant #317205) Part of this work was supported by the COST Action ES1307 “SCORE - Sewage biomarker analysis for community health assessment”. The financial support of Generalitat Valenciana (Prometeo II 2014/023) and of the Spanish Ministry of Economy and Competitiveness (Project ref CTQ2015-65603) is also acknowledged by the authors of University Jaume I

Fatigue and Structural Analysis of Azimuth Thruster Assembly

Composite is stated as constituent of two or more materials which retain their own physical and chemical property during the time of application, but produce a component which inherent the properties of its constituent materials and makes it better for the real time USAge. There are varieties of processing techniques for fabricating composite parts or structures such as: (1) Resin Transfer Moulding, (2) Pultrusion, (3) Filament Winding, (4) Autoclave Moulding. Among all these technique of exercising composite materials, the filament winding technique is the most appropriate because it avails the user with the ease of USAge, as well as gives wide range of degree of freedom for fabricating or manufacturing objects. In the paper we basically reveal the maximum approach made to study basic theory related to the filament winding technique or method, which provides initial platform for the new learner

A cross sectional study on prescription pattern of drugs in upper respiratory tract infections in a tertiary care hospital

Background: Upper respiratory tract infections are one of the leading causes of hospital visits worldwide. Judicious use of antibiotics is challenging for upper respiratory tract infections (URTIs) in developing countries like India. This leads to inappropriate use of antibiotics causing many dreaded conditions like antibacterial resistance among other things. Hence rational use of drugs, mainly antibacterial, is a priority to reduce the burden of treatment failure. The objective of this study is to study the prescribing patterns and rationality of drugs prescribed in the management of URTIs.Methods: This was a cross-sectional study. Data was collected from records of 300 outpatients clinically diagnosed as URTIs from SSIMS and RC Hospital, Davangere between January 2015 and June 2016. The prescribing patterns, approval status and listing of drugs in World Health Organization (WHO) essential medicines list/ National List of Essential Medicines (NLEM) were analysed. The data was presented as percentages, mean and standard deviations.Results: A total of 300 cases were studied. Among these, acute pharyngitis (29%) and acute sinusitis (26%) are the most common infections. Of the 300 cases studied, 283 (94.3%) were prescribed antimicrobials. Of the total 740 medications prescribed, 393 (53.1%) were fixed-dose combinations (FDCs). A total of 724 medications (97.8%) were approved by Drugs Controller General of India and 248 (33.5%) by Food and Drug Administration. Only 5.8% of the prescribed drugs have been listed in WHO’s and NLEM. The most common class of antibacterials prescribed was Beta-lactams.Conclusions: Oral formulations were preferred over parenteral formulations and FDCs were preferred over single drug formulations. Beta-lactams comprised the major class of antibacterial prescribed