Alternating polarity for enhanced electrochemical synthesis

Synthetic electrochemistry has recently become an exciting technology for chemical synthesis. The majority of reported syntheses use either constant current or constant potential, however a few use nonlinear profiles – mostly alternating polarity – to maintain efficiency throughout the process, such as controlling deposits on electrodes or ensuring even use of electrodes. However, even though parameters that are associated with such profiles, such as the frequency, can have a major impact on the reaction outcome, they are often not investigated. Herein, we report the crucial impact that the applied frequency of the alternating polarity has on the observed reaction rate of Cu(I)–NHC complex formation and demonstrate that this can be manipulated to give enhanced yield that is stable over extended reaction times

Algorithms for the self-optimisation of chemical reactions

Self-optimising chemical systems have experienced a growing momentum in recent years, with the evolution of self-optimising platforms leading to their application for reaction screening and chemical synthesis. With the desire for improved process sustainability, self-optimisation provides a cheaper, faster and greener approach to the chemical development process. The use of such platforms aims to enhance the capabilities of the researcher by removing the need for labor-intensive experimentation, allowing them to focus on more challenging tasks. The establishment of these systems have enabled opportunities for self-optimising platforms to become a key element of a laboratory’s repertoire. To enable the wider adoption of self-optimising chemical platforms, this review summarises the history of algorithmic usage in chemical reaction self-optimisation, detailing the functionality of the algorithms and their applications in a way that is accessible for chemists and highlights opportunities for the further exploitation of algorithms in chemical synthesis moving forward

Hypothermia and Fever After Organophosphorus Poisoning in Humans—A Prospective Case Series

There have been many animal studies on the effects of organophosphorus pesticide (OP) poisoning on thermoregulation with inconsistent results. There have been no prospective human studies. Our aim was to document the changes in body temperature with OP poisoning. A prospective study was conducted in a rural hospital in Polonnaruwa, Sri Lanka. We collected data on sequential patients with OP poisoning and analyzed 12 patients selected from 53 presentations who had overt signs and symptoms of OP poisoning and who had not received atropine prior to arrival. All patients subsequently received specific management with atropine and/or pralidoxime and general supportive care. Tympanic temperature, ambient temperature, heart rate, and clinical examination and interventions were recorded prospectively throughout their hospitalization. Initial hypothermia as low as 32°C was observed in untreated patients. Tympanic temperature increased over time from an early hypothermia (<35°C in 6/12 patients) to later fever (7/12 patients >38°C at some later point). While some of the late high temperatures occurred in the setting of marked tachycardia, it was also apparent that in some cases fever was not accompanied by tachycardia, making excessive atropine or severe infection an unlikely explanation for all the fevers. In humans, OP poisoning causes an initial hypothermia, and this is followed by a period of normal to high body temperature. Atropine and respiratory complications may contribute to fever but do not account for all cases

Automated Self-Optimisation of Multi-Step Reaction and Separation Processes Using Machine Learning

There has been an increasing interest in the use of automated self-optimising continuous flow platforms for the development and manufacture in synthesis in recent years. Such processes include multiple reactive and work-up steps, which need to be efficiently optimised. Here, we report the combination of multi-objective optimisation based on machine learning methods (TSEMO algorithm) with self-optimising platforms for the optimisation of multi-step continuous reaction processes. This is demonstrated for a pharmaceutically relevant Sonogashira reaction. We demonstrate how optimum reaction conditions are re-evaluated with the changing downstream work-up specifications in the active learning process. Furthermore, a Claisen-Schmidt condensation reaction with subsequent liquid-liquid separation was optimised with respect to three-objectives. This approach provides the ability to simultaneously optimise multi-step processes with respect to multiple objectives, and thus has the potential to make substantial savings in time and resources

Rapid, Automated Determination of Reaction Models and Kinetic Parameters

We herein report a novel kinetic modelling methodology whereby identification of the correct reaction model and kinetic parameters is conducted by an autonomous framework combined with transient flow measurements to enable comprehensive process understanding with minimal user input. An automated flow chemistry platform was employed to initially conduct linear flow-ramp experiments to rapidly map the reaction profile of three processes using transient flow data. Following experimental data acquisition, a computational approach was utilised to discriminate between all possible reaction models as well as identify the correct kinetic parameters for each process. Species that are known to participate in the process (starting materials, intermediates, products) are initially inputted by the user prior to flow ramp experiments, then all possible model candidates are compiled into a model library based on their potential to occur after mass balance assessment. Parallel computational optimisation then evaluates each model by algorithmically altering the kinetic parameters of the model to allow convergence of a simulated kinetic curve to the experimental data provided. Statistical analysis then determines the most likely reaction model based on model simplicity and agreement with experimental data. This automated approach to gaining full process understanding, whereby a small number of data-rich experiments are conducted, and the kinetics are evaluated autonomously, shows significant improvements on current industrial optimisation techniques in terms of labour, time and overall cost. The computational approach herein described can be employed using data from any set of experiments and the code is open-source

Genome sequencing of the extinct Eurasian wild aurochs, Bos primigenius, illuminates the phylogeography and evolution of cattle

Background Domestication of the now-extinct wild aurochs, Bos primigenius, gave rise to the two major domestic extant cattle taxa, B. taurus and B. indicus. While previous genetic studies have shed some light on the evolutionary relationships between European aurochs and modern cattle, important questions remain unanswered, including the phylogenetic status of aurochs, whether gene flow from aurochs into early domestic populations occurred, and which genomic regions were subject to selection processes during and after domestication. Here, we address these questions using whole-genome sequencing data generated from an approximately 6,750-year-old British aurochs bone and genome sequence data from 81 additional cattle plus genome-wide single nucleotide polymorphism data from a diverse panel of 1,225 modern animals. Results Phylogenomic analyses place the aurochs as a distinct outgroup to the domestic B. taurus lineage, supporting the predominant Near Eastern origin of European cattle. Conversely, traditional British and Irish breeds share more genetic variants with this aurochs specimen than other European populations, supporting localized gene flow from aurochs into the ancestors of modern British and Irish cattle, perhaps through purposeful restocking by early herders in Britain. Finally, the functions of genes showing evidence for positive selection in B. taurus are enriched for neurobiology, growth, metabolism and immunobiology, suggesting that these biological processes have been important in the domestication of cattle. Conclusions This work provides important new information regarding the origins and functional evolution of modern cattle, revealing that the interface between early European domestic populations and wild aurochs was significantly more complex than previously thought

Patient-derived mutations within the N-terminal domains of p85α impact PTEN or Rab5 binding and regulation

The p85α protein regulates flux through the PI3K/PTEN signaling pathway, and also controls receptor trafficking via regulation of Rab-family GTPases. In this report, we determined the impact of several cancer patient-derived p85α mutations located within the N-terminal domains of p85α previously shown to bind PTEN and Rab5, and regulate their respective functions. One p85α mutation, L30F, significantly reduced the steady state binding to PTEN, yet enhanced the stimulation of PTEN lipid phosphatase activity. Three other p85α mutations (E137K, K288Q, E297K) also altered the regulation of PTEN catalytic activity. In contrast, many p85α mutations reduced the binding to Rab5 (L30F, I69L, I82F, I177N, E217K), and several impacted the GAP activity of p85α towards Rab5 (E137K, I177N, E217K, E297K). We determined the crystal structure of several of these p85α BH domain mutants (E137K, E217K, R262T E297K) for bovine p85α BH and found that the mutations did not alter the overall domain structure. Thus, several p85α mutations found in human cancers may deregulate PTEN and/or Rab5 regulated pathways to contribute to oncogenesis. We also engineered several experimental mutations within the p85α BH domain and identified L191 and V263 as important for both binding and regulation of Rab5 activit

Flow chemistry for process optimisation using design of experiments

Implementing statistical training into undergraduate or postgraduate chemistry courses can provide high-impact learning experiences for students. However, the opportunity to reinforce this training with a combined laboratory practical can significantly enhance learning outcomes by providing a practical bolstering of the concepts. This paper outlines a flow chemistry laboratory practical for integrating design of experiments optimisation techniques into an organic chemistry laboratory session in which students construct a simple flow reactor and perform a structured series of experiments followed by computational processing and analysis of the results

Shwachman-Bodian-Diamond syndrome (SBDS) protein is a direct inhibitor of protein phosphatase 2A (PP2A) activity and overexpressed in acute myeloid leukaemia.

Protein phosphatase 2A (PP2A) is a serine/threonine phosphatase inactivated in many cancers including acute myeloid leukaemia (AML). Activation of PP2A is emerging as a therapeutic strategy, however the mechanisms underpinning PP2A inhibition are not well understood. Using myeloid progenitor cells harbouring oncogenic mutant c-KIT and characterised by PP2A inhibition, we have identified the ribosome biogenesis protein SBDS, as a target of the PP2A activating drugs FTY720 and AAL(S). We show SBDS binds to PP2A complexes comprised of the B55α regulatory subunit of PP2A. shRNA mediated knockdown of SBDS increased PP2A activity and induced apoptosis. At diagnosis, AML patients expressed significantly more SBDS mRNA than healthy controls, with relapsed patients expressing significantly more SBDS mRNA than both healthy controls and patients at diagnosis. Together, our data presents a role for SBDS in the dysregulation of PP2A in AML