Microwave-Assisted Knoevenagel-Doebner Reaction: An Efficient Method for Naturally Occurring Phenolic Acids Synthesis

The common chemical method to synthesize Phenolic Acids (PAs) involves a relatively considerable energy intake. In order to solve this issue, microwave-assisted Knoevenagel-Doebner condensations were developed. Nevertheless, these synthetic procedures prove difficult to reproduce. Herein, we developed and optimized—by using a combination of a Design of Experiment and a standard optimization approach—a reliable procedure that converts naturally occuring p-hydroxybenzaldehydes into the corresponding PAs with conversions of 86–99% and in 85–97% yields

An expeditive and green chemo-enzymatic route to diester sinapoyl- l -malate analogues: sustainable bioinspired and biosourced UV filters and molecular heaters †

Sinapoyl malate, naturally present in plants, has proved to be an exceptional UV filter and molecular heater for plants. Although there are nowadays industrially relevant sustainable synthetic routes to sinapoyl malate, its incorporation into certain cosmetic formulations, as well as its adsorption on plant leaves, is limited by its hydrophilicity. To overcome these obstacles, it is important to find a way to effectively control the hydrophilic–lipophilic balance of sinapoyl malate to make it readily compatible with the cosmetic formulations and stick on the waxy cuticle of leaves. To this end, herein, we describe a highly regioselective chemo-enzymatic synthesis of sinapoyl malate analogues possessing fatty aliphatic chains of variable length, enabling the lipophilicity of the compounds to be modulated. The potential toxicity (i.e., mutagenicity, carcinogenicity, endocrine disruption, acute and repeated-dose toxicity), bioaccumulation, persistence and biodegradability potential of these new analogues were evaluated in silico, along with the study of their transient absorption spectroscopy, their photostability as well as their photodegradation products

Common garden experiments in the genomic era : new perspectives and opportunities

PdV was supported by a doctoral studentship from the French Ministère de la Recherche et de l’Enseignement Supérieur. OEG was supported by the Marine Alliance for Science and Technology for Scotland (MASTS)The study of local adaptation is rendered difficult by many evolutionary confounding phenomena (e.g. genetic drift and demographic history). When complex traits are involved in local adaptation, phenomena such as phenotypic plasticity further hamper evolutionary biologists to study the complex relationships between phenotype, genotype and environment. In this perspective paper, we suggest that the common garden experiment, specifically designed to deal with phenotypic plasticity has a clear role to play in the study of local adaptation, even (if not specifically) in the genomic era. After a quick review of some high-throughput genotyping protocols relevant in the context of a common garden, we explore how to improve common garden analyses with dense marker panel data and recent statistical methods. We then show how combining approaches from population genomics and genome-wide association studies with the settings of a common garden can yield to a very efficient, thorough and integrative study of local adaptation. Especially, evidence from genomic (e.g. genome scan) and phenotypic origins constitute independent insights into the possibility of local adaptation scenarios, and genome-wide association studies in the context of a common garden experiment allow to decipher the genetic bases of adaptive traits.PostprintPeer reviewe

Integration of modeling and simulation into hospital-based decision support systems guiding pediatric pharmacotherapy

<p>Abstract</p> <p>Background</p> <p>Decision analysis in hospital-based settings is becoming more common place. The application of modeling and simulation approaches has likewise become more prevalent in order to support decision analytics. With respect to clinical decision making at the level of the patient, modeling and simulation approaches have been used to study and forecast treatment options, examine and rate caregiver performance and assign resources (staffing, beds, patient throughput). There us a great need to facilitate pharmacotherapeutic decision making in pediatrics given the often limited data available to guide dosing and manage patient response. We have employed nonlinear mixed effect models and Bayesian forecasting algorithms coupled with data summary and visualization tools to create drug-specific decision support systems that utilize individualized patient data from our electronic medical records systems.</p> <p>Methods</p> <p>Pharmacokinetic and pharmacodynamic nonlinear mixed-effect models of specific drugs are generated based on historical data in relevant pediatric populations or from adults when no pediatric data is available. These models are re-executed with individual patient data allowing for patient-specific guidance via a Bayesian forecasting approach. The models are called and executed in an interactive manner through our web-based dashboard environment which interfaces to the hospital's electronic medical records system.</p> <p>Results</p> <p>The methotrexate dashboard utilizes a two-compartment, population-based, PK mixed-effect model to project patient response to specific dosing events. Projected plasma concentrations are viewable against protocol-specific nomograms to provide dosing guidance for potential rescue therapy with leucovorin. These data are also viewable against common biomarkers used to assess patient safety (e.g., vital signs and plasma creatinine levels). As additional data become available via therapeutic drug monitoring, the model is re-executed and projections are revised.</p> <p>Conclusion</p> <p>The management of pediatric pharmacotherapy can be greatly enhanced via the immediate feedback provided by decision analytics which incorporate the current, best-available knowledge pertaining to dose-exposure and exposure-response relationships, especially for narrow therapeutic agents that are difficult to manage.</p