Dual Stimuli-Responsive Self-Assembly Behavior of a Tailor-Made ABC-Type Amphiphilic Tri-Block Copolymer

This investigation describes the synthesis of a dual stimuli-responsive, amphiphilic ABC tri-block copolymer (BCP) based on the functional monomers via RAFT polymerization. In this case, ABC-type BCP was prepared based on N-isopropylacrylamide, n-butyl acrylate, and 4-vinylpyridine in DMF solvent using cyanomethyl dodecyl trithiocarbonate as the RAFT agent and azobisisobutyronitrile as a thermal initiator in a subsequent macro-RAFT approach, respectively. The BCPs were characterized by SEC, 1H-NMR, FTIR spectroscopy, and DSC analyses. Temperature and pH-dependent properties of the smart BCP micelles in aqueous medium were investigated using dynamic light scattering. Transmission electron microscopic images were taken at cryogenic and dry conditions to study the morphology of molecular assemblies of block copolymers in an aqueous medium. The phase and topographical images were captured by atomic force microscopy to understand the assembly of block copolymers in solvents of different polarities. The morphology of BCP micelles was transformed from flower-like to spherical in the presence of solvents with different polarities (H2O or CHCl3). © 2020 The Authors. Journal of Polymer Science published by Wiley Periodicals, Inc

Enabling the measurement of particle sizes in stirred colloidal suspensions by embedding dynamic light scattering into an automated probe head

A novel probe head design is introduced, which enables in-line monitoring of particle sizes in undiluted stirred fluids using dynamic light scattering. The novel probe head separates a small sample volume of 0.65 ml from the bulk liquid by means of an impeller. In this sample volume, particle sizing is performed using a commercially available fiber-optical backscatter probe. While conventional light scattering measurements in stirred media fail due to the superposition of Brownian’ motion and forced convection, undistorted measurements are possible with the proposed probe head. One measurement takes approximately 30 s used for liquid exchange by rotation of the impeller and for collection of scattered light. The probe head is applied for in-line monitoring of the particle growth during microgel synthesis by precipitation polymerization in a one liter laboratory reactor. The in-line measurements are compared to off-line measurements and show a good agreement

Enabling the measurement of particle sizes in stirred colloidal suspensions by embedding dynamic light scattering into an automated probe head

A novel probe head design is introduced, which enables in-line monitoring of particle sizes in undiluted stirred fluids using dynamic light scattering. The novel probe head separates a small sample volume of 0.65 ml from the bulk liquid by means of an impeller. In this sample volume, particle sizing is performed using a commercially available fiber-optical backscatter probe. While conventional light scattering measurements in stirred media fail due to the superposition of Brownian’ motion and forced convection, undistorted measurements are possible with the proposed probe head. One measurement takes approximately 30 s used for liquid exchange by rotation of the impeller and for collection of scattered light. The probe head is applied for in-line monitoring of the particle growth during microgel synthesis by precipitation polymerization in a one liter laboratory reactor. The in-line measurements are compared to off-line measurements and show a good agreement

Synthesis of Polyampholyte Janus-like Microgels by Coacervation of Reactive Precursors in Precipitation Polymerization

Controlling the distribution of ionizable groups of opposite charge in microgels is an extremely challenging task, which could open new pathways to design a new generation of stimuli-responsive colloids. Herein, we report a straightforward approach for the synthesis of polyampholyte Janus-like microgels, where ionizable groups of opposite charge are located on different sides of the colloidal network. This synthesis approach is based on the controlled self-assembly of growing polyelectrolyte microgel precursors during the precipitation polymerization process. We confirmed the morphology of polyampholyte Janus-like microgels and demonstrate that they are capable of responding quickly to changes in both pH and temperature in aqueous solutions. © 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA

Synthesis of Polyampholyte Janus-like Microgels by Coacervation of Reactive Precursors in Precipitation Polymerization

Controlling the distribution of ionizable groups of opposite charge in microgels is an extremely challenging task, which could open new pathways to design a new generation of stimuli-responsive colloids. Herein, we report a straightforward approach for the synthesis of polyampholyte Janus-like microgels, where ionizable groups of opposite charge are located on different sides of the colloidal network. This synthesis approach is based on the controlled self-assembly of growing polyelectrolyte microgel precursors during the precipitation polymerization process. We confirmed the morphology of polyampholyte Janus-like microgels and demonstrate that they are capable of responding quickly to changes in both pH and temperature in aqueous solutions. © 2019 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA

Triterpene Acids from Frankincense and Semi-Synthetic Derivatives That Inhibit 5-Lipoxygenase and Cathepsin G

Age-related diseases, such as osteoarthritis, Alzheimer’s disease, diabetes, and cardiovascular disease, are often associated with chronic unresolved inflammation. Neutrophils play central roles in this process by releasing tissue-degenerative proteases, such as cathepsin G, as well as pro-inflammatory leukotrienes produced by the 5-lipoxygenase (5-LO) pathway. Boswellic acids (BAs) are pentacyclic triterpene acids contained in the gum resin of the anti-inflammatory remedy frankincense that target cathepsin G and 5-LO in neutrophils, and might thus represent suitable leads for intervention with age-associated diseases that have a chronic inflammatory component. Here, we investigated whether, in addition to BAs, other triterpene acids from frankincense interfere with 5-LO and cathepsin G. We provide a comprehensive analysis of 17 natural tetra- or pentacyclic triterpene acids for suppression of 5-LO product synthesis in human neutrophils. These triterpene acids were also investigated for their direct interference with 5-LO and cathepsin G in cell-free assays. Furthermore, our studies were expanded to 10 semi-synthetic BA derivatives. Our data reveal that besides BAs, several tetra- and pentacyclic triterpene acids are effective or even superior inhibitors of 5-LO product formation in human neutrophils, and in parallel, inhibit cathepsin G. Their beneficial target profile may qualify triterpene acids as anti-inflammatory natural products and pharmacological leads for intervention with diseases related to aging

Ensayo aleatorizado del cierre de orejuela izquierda vs varfarina para la prevención de accidentes cerebrovasculares tromboembólicos en pacientes con fibrilación auricular no relacionada con valvulopatía. Estudio PREVAIL

The successful application of poly­(<i>N</i>-vinylcaprolactam)-based microgels requires a profound understanding of their synthesis. For this purpose, a validated process model for the microgels synthesis by precipitation copolymerization with the cross-linker <i>N</i>,<i>N</i>′-methylenebis­(acrylamide) is formulated. Unknown reaction rate constants, reaction enthalpies, and partition coefficients are obtained by quantum mechanical calculations. The remaining parameter values are estimated from reaction calorimetry and Raman spectroscopy measurements of experiments with different monomer/cross-linker compositions. Because of high cross-propagation reaction rate constants, simulations predict a fast incorporation of the cross-linker. This agrees with reaction calorimetry measurements. Furthermore, the gel phase is predicted as the major reaction locus. The model is utilized for a prediction of the internal particle structure regarding its cross-link distribution. The highly cross-linked core reported in the literature corresponds to the predictions of the model

The range and level of impurities in CO2 streams from different carbon capture sources

For CO2 capture and storage deployment, the impact of impurities in the gas or dense phase CO2 stream arising from fossil fuel power plants, or large scale industrial emitters, is of fundamental importance to the safe and economic transportation and storage of the captured CO2. This paper reviews the range and level of impurities expected from the main capture technologies used with fossil-fuelled power plants in addition to other CO2 emission-intensive industries. Analysis is presented with respect to the range of impurities present in CO2 streams captured using pre-combustion, post-combustion and oxy-fuel technologies, in addition to an assessment of the different parameters affecting the CO2 mixture composition. This includes modes of operation of the power plant, and different technologies for the reduction and removal of problematic components such as water and acid gases (SOx/NOx). A literature review of data demonstrates that the purity of CO2 product gases from carbon capture sources is highly dependent upon the type of technology used. This paper also addresses the CO2 purification technologies available for the removal of CO2 impurities from raw oxy-fuel flue gas, such as Hg and non-condensable compounds. CO2 purities of over 99% are achievable using post-combustion capture technologies with low levels of the main impurities of N2, Ar and O2. However, CO2 capture from oxy-fuel combustion and integrated gasification combined cycle power plants will need to take into consideration the removal of non-condensables, acid gas species, and other contaminants. The actual level of CO2 purity required will be dictated by a combination of transport and storage requirements, and process economics

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study

Aim Gastric cancer (GC) is a tumor entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesized that GC primary tissue contains information that is predictive of lymph node status and patient prognosis and that this information can be extracted using Deep Learning (DL). Methods Using three patient cohorts comprising 1146 patients, we trained and validated a DL system to predict lymph node status directly from hematoxylin-and-eosin stained GC tissue sections. We investigated the concordance between the DL-based prediction from the primary tumor slides (aiN score) and the histopathological lymph node status (pN). Furthermore, we assessed the prognostic value of the aiN score alone and when combined with the pN status. Results The aiN score predicted the pN status reaching Area Under the Receiver Operating Characteristic curves (AUROCs) of 0.71 in the training cohort and 0.69 and 0.65 in the two test cohorts. In a multivariate Cox analysis, the aiN score was an independent predictor of patient survival with Hazard Ratios (HR) of 1.5 in the training cohort and of 1.3 and 2.2 in the two test cohorts. A combination of the aiN score and the pN status prognostically stratified patients by survival with p-values <0.05 in log-rank tests. Conclusion GC primary tumor tissue contains additional prognostic information that is accessible using the aiN score. In combination with the pN status, this can be used for personalized management of gastric cancer patients after prospective validation

Clinical-grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning

Background and Aims: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and cheaper than molecular assays. But clinical application of this technology requires high performance and multisite validation, which have not yet been performed. Methods: We collected hematoxylin and eosin-stained slides, and findings from molecular analyses for MSI and dMMR, from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning detector to identify samples with MSI from these slides; performance was assessed by cross-validation (n=6406 specimens) and validated in an external cohort (n=771 specimens). Prespecified endpoints were area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC). Results: The deep-learning detector identified specimens with dMMR or MSI with a mean AUROC curve of 0.92 (lower bound 0.91, upper bound 0.93) and an AUPRC of 0.63 (range, 0.59–0.65), or 67% specificity and 95% sensitivity, in the cross-validation development cohort. In the validation cohort, the classifier identified samples with dMMR with an AUROC curve of 0.95 (range, 0.92–0.96) without image-preprocessing and an AUROC curve of 0.96 (range, 0.93–0.98) after color normalization. Conclusions: We developed a deep-learning system that detects colorectal cancer specimens with dMMR or MSI using hematoxylin and eosin-stained slides; it detected tissues with dMMR with an AUROC of 0.96 in a large, international validation cohort. This system might be used for high-throughput, low-cost evaluation of colorectal tissue specimens