1,945 research outputs found

    Algorithms for the self-optimisation of chemical reactions

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    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

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

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    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

    The price of tumor control: an analysis of rare side effects of anti-CTLA-4 therapy in metastatic melanoma from the ipilimumab network

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    Background: Ipilimumab, a cytotoxic T-lymphocyte antigen-4 (CTLA-4) blocking antibody, has been approved for the treatment of metastatic melanoma and induces adverse events (AE) in up to 64% of patients. Treatment algorithms for the management of common ipilimumab-induced AEs have lead to a reduction of morbidity, e.g. due to bowel perforations. However, the spectrum of less common AEs is expanding as ipilimumab is increasingly applied. Stringent recognition and management of AEs will reduce drug-induced morbidity and costs, and thus, positively impact the cost-benefit ratio of the drug. To facilitate timely identification and adequate management data on rare AEs were analyzed at 19 skin cancer centers. Methods and Findings: Patient files (n = 752) were screened for rare ipilimumab-associated AEs. A total of 120 AEs, some of which were life-threatening or even fatal, were reported and summarized by organ system describing the most instructive cases in detail. Previously unreported AEs like drug rash with eosinophilia and systemic symptoms (DRESS), granulomatous inflammation of the central nervous system, and aseptic meningitis, were documented. Obstacles included patientś delay in reporting symptoms and the differentiation of steroid-induced from ipilimumab-induced AEs under steroid treatment. Importantly, response rate was high in this patient population with tumor regression in 30.9% and a tumor control rate of 61.8% in stage IV melanoma patients despite the fact that some patients received only two of four recommended ipilimumab infusions. This suggests that ipilimumab-induced antitumor responses can have an early onset and that severe autoimmune reactions may reflect overtreatment. Conclusion: The wide spectrum of ipilimumab-induced AEs demands doctor and patient awareness to reduce morbidity and treatment costs and true ipilimumab success is dictated by both objective tumor responses and controlling severe side effects

    High-Resolution Genotyping of the Endemic Salmonella Typhi Population during a Vi (Typhoid) Vaccination Trial in Kolkata

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    Typhoid fever is caused by the bacterium Salmonella enterica serovar Typhi (S. Typhi) and is a major health problem especially in developing countries. Vaccines against typhoid are commonly used by travelers but less so by residents of endemic areas. We used single nucleotide polymorphism (SNP) typing to investigate the population structure of 372 S. Typhi bacteria isolated from typhoid patients during a typhoid disease burden study and Vi anti-typhoid vaccine trial in Kolkata, India. Approximately sixty thousand people were enrolled for fever surveillance for 19 months prior to, and 24 months following, vaccination of one third of the study population against typhoid (May 2003–December 2006, vaccinations given December 2004). We detected a diverse population of S. Typhi, including 21 different genetic forms (haplotypes) of the bacteria. The most common (69%) were of a haplogroup known as H58, which included all multidrug resistant isolates (bacteria resistant to the antibiotics chloramphenicol, ampicillin and co-trimoxazole). Resistance to quinolones, a class of antibiotics commonly used to treat typhoid fever, was particularly high among a subgroup of H58 (H58-G). Vi vaccination did not obviously impact on the haplotype distribution of the S. Typhi circulating during the study period

    Host Factors Required for Modulation of Phagosome Biogenesis and Proliferation of Francisella tularensis within the Cytosol

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    Francisella tularensis is a highly infectious facultative intracellular bacterium that can be transmitted between mammals by arthropod vectors. Similar to many other intracellular bacteria that replicate within the cytosol, such as Listeria, Shigella, Burkholderia, and Rickettsia, the virulence of F. tularensis depends on its ability to modulate biogenesis of its phagosome and to escape into the host cell cytosol where it proliferates. Recent studies have identified the F. tularensis genes required for modulation of phagosome biogenesis and escape into the host cell cytosol within human and arthropod-derived cells. However, the arthropod and mammalian host factors required for intracellular proliferation of F. tularensis are not known. We have utilized a forward genetic approach employing genome-wide RNAi screen in Drosophila melanogaster-derived cells. Screening a library of ∼21,300 RNAi, we have identified at least 186 host factors required for intracellular bacterial proliferation. We silenced twelve mammalian homologues by RNAi in HEK293T cells and identified three conserved factors, the PI4 kinase PI4KCA, the ubiquitin hydrolase USP22, and the ubiquitin ligase CDC27, which are also required for replication in human cells. The PI4KCA and USP22 mammalian factors are not required for modulation of phagosome biogenesis or phagosomal escape but are required for proliferation within the cytosol. In contrast, the CDC27 ubiquitin ligase is required for evading lysosomal fusion and for phagosomal escape into the cytosol. Although F. tularensis interacts with the autophagy pathway during late stages of proliferation in mouse macrophages, this does not occur in human cells. Our data suggest that F. tularensis utilizes host ubiquitin turnover in distinct mechanisms during the phagosomal and cytosolic phases and phosphoinositide metabolism is essential for cytosolic proliferation of F. tularensis. Our data will facilitate deciphering molecular ecology, patho-adaptation of F. tularensis to the arthropod vector and its role in bacterial ecology and patho-evolution to infect mammals

    Artifactual measurement of low serum HDL-cholesterol due to paraproteinemia

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    High levels of serum low density lipoprotein cholesterol (LDL-C) and low levels of high density lipoprotein cholesterol (HDL-C) are well-known risk factors for premature atherosclerotic vascular disease [1, 2]. They are targets for primary and secondary prevention. Interpreting lipid profiles is part of the daily routine for a cardiologist. The most common cause of low HDL-C in western society is metabolic syndrome. More rare are primary lipid disorders (e.g., Tangier syndrome due to an ABCA transporter deficiency or deficiency of apolipoprotein A1) and secondary causes like (ab)use of androgens (Table 1). Extremely low serum HDL levels are associated with an increased risk of death, sepsis and malignancy [3]. A rare but important cause is interference in the biochemical assay by paraproteins, yielding an artifactually low HDL-C measurement result. We present the case of a patient who had his lipid profile repeatedly tested over the course of 4 years and had progressive decline in HDL-C measurements

    Probing the action of a novel anti-leukaemic drug therapy at the single cell level using modern vibrational spectroscopy techniques

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    Acute myeloid leukaemia (AML) is a life threatening cancer for which there is an urgent clinical need for novel therapeutic approaches. A redeployed drug combination of bezafibrate and medroxyprogesterone acetate (BaP) has shown anti-leukaemic activity in vitro and in vivo. Elucidation of the BaP mechanism of action is required in order to understand how to maximise the clinical benefit. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, Synchrotron radiation FTIR (S-FTIR) and Raman microspectroscopy are powerful complementary techniques which were employed to probe the biochemical composition of two AML cell lines in the presence and absence of BaP. Analysis was performed on single living cells along with dehydrated and fixed cells to provide a large and detailed data set. A consideration of the main spectral differences in conjunction with multivariate statistical analysis reveals a significant change to the cellular lipid composition with drug treatment; furthermore, this response is not caused by cell apoptosis. No change to the DNA of either cell line was observed suggesting this combination therapy primarily targets lipid biosynthesis or effects bioactive lipids that activate specific signalling pathways
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