Synthesis and Evaluation of Novel Bio-Based Solvents and Solubilizers

The field of green chemistry rapidly gained interest in recent years due to the increasing visibility of present environmental problems. In particular, the replacement of conventional organic solvents is considered urgently important in view of the fact that they are often volatile compounds, obtained from petroleum resource and highly abundant in chemical processes and industry. The idea of this thesis was to develop new approaches towards the development of green, alternative solvents and solubilization concepts. Several substance classes accessed by means of different strategies were studied to reach this aim. Firstly, the naturally originating L-carnitine was found to be a valuable starting material for the development of ionic liquids, cationic hydrotropes and surfactants. Starting from the zwitterionic natural molecule, cationic carnitine ester species were synthesized and the greenness of the employed reaction pathways was evaluated. The properties of the resulting pure substances and aqueous solutions were determined next to their applicability in terms of solubilization. In a second approach, the rather new solvent class of deep eutectic solvents was studied by extending the so far investigated range of members of this class. Mixtures consisting of betaine or carnitine in combination with carboxylic acids were found to exhibit a certain ionic liquid character. Furthermore, the suitability of biologically relevant substances, such as antioxidants was assessed for the formation of functional deep eutectic solvents. Natural hormones, in particular sodium salts of dehydroepiandrosterone sulphate, indole-3-acetic acid and indole-3-butyric acid were found to feature hydrotropic character. This allowed for the consideration of hormones being relevant for mechanisms in the organism beyond their primary function as hormones. The presented work has shown that numerous approaches relying on the utilization of well-known natural substances or modified derivatives thereof hold promise for their use as solvents or solubilizers in green chemistry

Potential Dependence of Surfactant Adsorption at the Graphite Electrode / Deep Eutectic Solvent Interface

Atomic force microscope (AFM) and cyclic voltammetry (CV) are used to probe how ionic surfactant adsorbed layer structure affects redox processes at deep eutectic solvent (DES)/graphite interfaces. Unlike its behaviour in water, sodium dodecyl sulphate (SDS) in DESs only adsorbs as a complete layer of hemicylindrical hemimicelles far above its critical micelle concentration (CMC). Near the CMC it forms a tail-to-tail monolayer at OCP and positive potentials, and which desorbs at negative potentials. In contrast, cetyltrimethylammonium bromide (CTAB) adsorbs as hemimicelles at low concentrations, and remains adsorbed at both positive and negative potentials. The SDS horizontal monolayer has little overall effect on redox processes at the graphite interface, but hemimicelles form an effective and stable barrier. The stronger solvophobic interactions between the C16 versus C12 alkyl chains in the DES allow CTAB to self-assemble into a robust coating at low concentrations, and illustrate how the structure of the DES/electrode interface and electrochemical response can be engineered by controlling surfactant structure

Validation Study for Non-Invasive Prediction of IDH Mutation Status in Patients with Glioma Using In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

The isocitrate dehydrogenase (IDH) mutation status is an indispensable prerequisite for diagnosis of glioma (astrocytoma and oligodendroglioma) according to the WHO classification of brain tumors 2021 and is a potential therapeutic target. Usually, immunohistochemistry followed by sequencing of tumor tissue is performed for this purpose. In clinical routine, however, non-invasive determination of IDH mutation status is desirable in cases where tumor biopsy is not possible and for monitoring neuro-oncological therapies. In a previous publication, we presented reliable prediction of IDH mutation status employing proton magnetic resonance spectroscopy (1H-MRS) on a 3.0 Tesla (T) scanner and machine learning in a prospective cohort of 34 glioma patients. Here, we validated this approach in an independent cohort of 67 patients, for which 1H-MR spectra were acquired at 1.5 T between 2002 and 2007, using the same data analysis approach. Despite different technical conditions, a sensitivity of 82.6% (95% CI, 61.2-95.1%) and a specificity of 72.7% (95% CI, 57.2-85.0%) could be achieved. We concluded that our 1H-MRS based approach can be established in a routine clinical setting with affordable effort and time, independent of technical conditions employed. Therefore, the method provides a non-invasive tool for determining IDH status that is well-applicable in an everyday clinical setting

The hype with ionic liquids as solvents

In this mini review, we give our personal opinion about the present state of the art concerning Ionic Liquids, proposed as alternative solvents. In particular, we consider their different drawbacks and disadvantages and discuss the critical aspects of the research of Ionic Liquids as solvents. Finally, we point out some aspects on potentially promising Ionic Liquid solvents. (C) 2016 Elsevier B.V. All rights reserved

Some aspects of green solvents

Chemical solvents constitute around 80% of the total volume of chemicals used in many important chemical processes, especially fine chemical manufacturing. Unfortunately, these solvents are often volatile organic compounds from petroleum resource bearing several health and environmental risks. Numerous researchers take these two aspects as a reason to search for novel green solvents to replace the conventional ones. As a consequence, there are an increasing number of publications dealing with green solvents. In this review, we discuss the definition and accuracy of the term "green solvent". We explain our urgent request for application-oriented research in this field. Finally, we point out some promising and interesting kinds of solvents, solvent systems and solubilization concepts for a successful research towards "greener solvents". (C) 2018 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved

Carnitine Alkyl Ester Bromides as Novel Biosourced Ionic Liquids, Cationic Hydrotropes and Surfactants

Hypothesis: In contrast to anionic and nonionic amphiphilic substances, bio-based cationic ones are very rare. Cationic amphiphiles are mostly based on quaternary ammonium, pyridinium or imidazolium groups that are either badly biodegradable or have toxic residues even after degradation. In the search for green alternatives to cationic hydrotropes and amphiphiles, natural L-carnitine could be a promising candidate for a cationic headgroup. Experiments: By esterification of carnitine in one step and with low cost, cationic molecules with alkyl chain length of n = 2-14 could be obtained. Their thermal properties, aggregation behaviour and cytotoxicity were determined. Hydrophobic compounds were solubilized in their aqueous solutions and the PIT slope method was applied to determine a relative hydrophilicity. Findings: It was found that some pure carnitine ester bromides were liquid at room temperature and thus can be classified as ionic liquids. They are highly water-soluble, and in aqueous solutions, they showed hydrotrope or surfactant behaviour depending on their alkyl chain length. Their high hydrotropic efficiency was demonstrated by solubilizing Disperse Red 13, while also biomolecules, like vanillin, could be dissolved in reasonable amounts. In all tests, they performed at least as good as the tested reference substances, while showing similar cytotoxicity towards human skin keratinocytes, thus demonstrating their potential as green functional amphiphilic molecules of positive charge. (C) 2017 Elsevier Inc. All rights reserved

Epidemiology and Risk Factors of Clostridioides difficile Infections in Germany: A Health Claims Data Analysis

Abstract Introduction Clostridioides difficile infection (CDI) is increasingly recognized as a public health threat at the community level in addition to being one of the most common causes of healthcare-associated infections. In Germany, the epidemiology of CDI is primarily informed by national hospital-based CDI surveillance. We used health claims data from Germany to obtain valuable insights on population-level disease burden and risk factors for CDI. Methods This was a retrospective cohort study using a representative sample from the InGef research database. Overall and age- and sex-stratified CDI incidence rates were estimated for German adults from 2013 to 2017 using different case definitions (i.e., main, broad, strict), and further stratified by setting (inpatient versus outpatient). Risk factors for CDI were assessed for the 2013–2016 period. Results The CDI incidence rate was high but declined by 15.3% from 2013 [141 (95% confidence interval, CI 137–145) cases/100,000 person-years] to 2017 [120 (95% CI 116–123)]. Annual CDI incidence rates were higher in female patients and the elderly. The most important risk factors for CDI were chronic inflammatory bowel disease [odds ratio (OR) 4.7, 95% CI 4.0–5.5], chemotherapy (OR 4.7, 95% CI 4.1–5.2), chronic kidney disease (OR 2.9, 95% CI 2.6–3.3), and ciprofloxacin receipt (OR 2.6, 95% CI 2.4–2.8). Conclusions Despite prevention strategies leading to declining incidence, CDI remains an important public health threat in Germany, with a high burden in the hospital setting and an outpatient epidemiology that is poorly understood. These findings, which are relevant both regionally and globally, can be used as a basis for further research on the full burden of CDI in Germany

Non-Invasive Prediction of IDH Mutation in Patients with Glioma WHO II/III/IV Based on F-18-FET PET-Guided In Vivo 1H-Magnetic Resonance Spectroscopy and Machine Learning

Simple Summary Approximately 75-80% of according to the classification of world health organization (WHO) grade II and III gliomas are characterized by a mutation of the isocitrate dehydrogenase (IDH) enzymes, which are very important in glioma cell metabolism. Patients with IDH mutated glioma have a significantly better prognosis than patients with IDH wildtype status, typically seen in glioblastoma WHO grade IV. Here we used a prospective O-(2-F-18-fluoroethyl)-L-tyrosine (F-18-FET) positron emission tomography guided single-voxel H-1-magnetic resonance spectroscopy approach to predict the IDH status before surgery. Finally, 34 patients were included in this neuroimaging study, of whom eight had additionally tissue analysis. Using a machine learning technique, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% and a specificity of 75.0%. It was newly recognized, that two metabolites (myo-inositol and glycine) have a particularly important role in the determination of the IDH status. Isocitrate dehydrogenase (IDH)-1 mutation is an important prognostic factor and a potential therapeutic target in glioma. Immunohistological and molecular diagnosis of IDH mutation status is invasive. To avoid tumor biopsy, dedicated spectroscopic techniques have been proposed to detect D-2-hydroxyglutarate (2-HG), the main metabolite of IDH, directly in vivo. However, these methods are technically challenging and not broadly available. Therefore, we explored the use of machine learning for the non-invasive, inexpensive and fast diagnosis of IDH status in standard H-1-magnetic resonance spectroscopy (H-1-MRS). To this end, 30 of 34 consecutive patients with known or suspected glioma WHO grade II-IV were subjected to metabolic positron emission tomography (PET) imaging with O-(2-F-18-fluoroethyl)-L-tyrosine (F-18-FET) for optimized voxel placement in H-1-MRS. Routine H-1-magnetic resonance (H-1-MR) spectra of tumor and contralateral healthy brain regions were acquired on a 3 Tesla magnetic resonance (3T-MR) scanner, prior to surgical tumor resection and molecular analysis of IDH status. Since 2-HG spectral signals were too overlapped for reliable discrimination of IDH mutated (IDHmut) and IDH wild-type (IDHwt) glioma, we used a nested cross-validation approach, whereby we trained a linear support vector machine (SVM) on the complete spectral information of the H-1-MRS data to predict IDH status. Using this approach, we predicted IDH status with an accuracy of 88.2%, a sensitivity of 95.5% (95% CI, 77.2-99.9%) and a specificity of 75.0% (95% CI, 42.9-94.5%), respectively. The area under the curve (AUC) amounted to 0.83. Subsequent ex vivo H-1-nuclear magnetic resonance (H-1-NMR) measurements performed on metabolite extracts of resected tumor material (eight specimens) revealed myo-inositol (M-ins) and glycine (Gly) to be the major discriminators of IDH status. We conclude that our approach allows a reliable, non-invasive, fast and cost-effective prediction of IDH status in a standard clinical setting