Single and binary protein electroultrafiltration using poly(vinyl-alcohol)-carbon nanotube (PVA-CNT) composite membranes.

Electrically conductive composite ultrafiltration membranes composed of carbon nanotubes have exhibited efficient fouling inhibition in wastewater treatment applications. In the current study, poly(vinyl-alcohol)-carbon nanotube membranes were applied to fed batch crossflow electroultrafiltration of dilute (0.1 g/L of each species) single and binary protein solutions of α-lactalbumin and hen egg-white lysozyme at pH 7.4, 4 mM ionic strength, and 1 psi. Electroultrafiltration using the poly(vinyl-alcohol)-carbon nanotube composite membranes yielded temporary enhancements in sieving for single protein filtration and in selectivity for binary protein separation compared to ultrafiltration using the unmodified PS-35 membranes. Assessment of membrane fouling based on permeate flux, zeta potential measurements, and scanning electron microscopy visualization of the conditioned membranes indicated significant resulting protein adsorption and aggregation which limited the duration of improvement during electroultrafiltration with an applied cathodic potential of -4.6 V (vs. Ag/AgCl). These results imply that appropriate optimization of electroultrafiltration using carbon nanotube-deposited polymeric membranes may provide substantial short-term improvements in binary protein separations

Systemic therapies for intrahepatic cholangiocarcinoma

Intrahepatic cholangiocarcinoma (iCCA) is a highly lethal hepatobiliary neoplasm whose incidence is increasing. Largely neglected for decades as a rare malignancy and frequently misdiagnosed as carcinoma of unknown primary, considerable clinical and investigative attention has recently been focused on iCCA worldwide. The established standard of care includes first-line (gemcitabine and cisplatin), second-line (FOLFOX) and adjuvant (capecitabine) systemic chemotherapy. Compared to hepatocellular carcinoma, iCCA is genetically distinct with several targetable genetic aberrations identified to date. Indeed, FGFR2 and NTRK fusions, and IDH1 and BRAF targetable mutations have been comprehensively characterised and clinical data is emerging on targeting these oncogenic drivers pharmacologically. Also, the role of immunotherapy has been examined and is an area of intense investigation. Herein, in a timely and topical manner, we will review these advances and highlight future directions of research

Kv2 dysfunction after peripheral axotomy enhances sensory neuron responsiveness to sustained input

AbstractPeripheral nerve injuries caused by trauma are associated with increased sensory neuron excitability and debilitating chronic pain symptoms. Axotomy-induced alterations in the function of ion channels are thought to largely underlie the pathophysiology of these phenotypes. Here, we characterise the mRNA distribution of Kv2 family members in rat dorsal root ganglia (DRG) and describe a link between Kv2 function and modulation of sensory neuron excitability. Kv2.1 and Kv2.2 were amply expressed in cells of all sizes, being particularly abundant in medium-large neurons also immunoreactive for neurofilament-200. Peripheral axotomy led to a rapid, robust and long-lasting transcriptional Kv2 downregulation in the DRG, correlated with the onset of mechanical and thermal hypersensitivity. The consequences of Kv2 loss-of-function were subsequently investigated in myelinated neurons using intracellular recordings on ex vivo DRG preparations. In naïve neurons, pharmacological Kv2.1/Kv2.2 inhibition by stromatoxin-1 (ScTx) resulted in shortening of action potential (AP) after-hyperpolarization (AHP). In contrast, ScTx application on axotomized neurons did not alter AHP duration, consistent with the injury-induced Kv2 downregulation. In accordance with a shortened AHP, ScTx treatment also reduced the refractory period and improved AP conduction to the cell soma during high frequency stimulation. These results suggest that Kv2 downregulation following traumatic nerve lesion facilitates greater fidelity of repetitive firing during prolonged input and thus normal Kv2 function is postulated to limit neuronal excitability. In summary, we have profiled Kv2 expression in sensory neurons and provide evidence for the contribution of Kv2 dysfunction in the generation of hyperexcitable phenotypes encountered in chronic pain states

First-principles calculations and experimental studies of: XYZ 2 thermoelectric compounds: Detailed analysis of van der Waals interactions

First-principles calculations can accelerate the search for novel high-performance thermoelectric materials. However, the prediction of the thermoelectric properties is strongly dependent on the approximations used for the calculations. Here, thermoelectric properties were calculated with different computational approximations (i.e., PBE-GGA, HSE06, spin-orbit coupling and DFT-D3) for three layered XYZ2 compounds (TmAgTe2, YAgTe2, and YCuTe2). In addition to the computations, the structural, electrical and thermal properties of these compounds were measured experimentally and compared to the computations. An enhanced prediction of the crystal structure and heat capacity was achieved with the inclusion of van der Waals interactions due to more accurate modeling of the interatomic forces. In particular, a large shift of the acoustic phonons and low-frequency optical phonons to lower frequencies was observed from the dispersion-optimized structure. From the phonon dispersion curves of these compounds, the ultralow thermal conductivity in the investigated XYZ2 compounds could be described by a recent developed minimum thermal conductivity model. For the prediction of the electrical conductivity, a temperature-dependent relaxation time was used, and it was limited by acoustic phonons. While HSE06 has only a small influence on the electrical properties due to a computed band gap energy of >0.25 eV, the inclusion of both van der Waals interactions and spin-orbit coupling leads to a more accurate band structure, resulting in better prediction of electrical properties. Furthermore, the experimental thermoelectric properties of YAgTe2, TmAg0.95Zn0.05Te2 and TmAg0.95Mg0.05Te2 were measured, showing an increase in zT of TmAg0.95Zn0.05Te2 by more than 35% (zT = 0.47 ± 0.12) compared to TmAgTe2

Penetration Enhancement Effect of Turpentine Oil on Transdermal Film of Ketorolac

Purpose: To prepare transdermal films of ketorolac tromethamine (KT) and study the effect of turpentine oil as a penetration enhancer for the drug.Methods: Transdermal films of KT were prepared with Carbopol-934 and ethyl cellulose, with turpentine oil as the penetration enhancer, using solvent evaporation method. The films were characterized for physicochemical properties, ex vivo permeation, as well as in vivo anti-inflammatory and analgesic activities in Wistar rats. Results: The transdermal films were uniform in weight and thickness, flat, with high drug content (93.9 to 98.5 %) and of high folding endurance (134.0 to 180.0). Drug permeation through excised rat abdominal skin was prolonged, with the total drug release ranging from 58.88 to 88.98 % in 24 h. The films containing penetration enhancer showed higher drug permeation than the one without the enhancer; furthermore, drug permeation increased with increase in the concentration of the enhancer. The films were non-irritant to the skin. The transdermal films prepared with permeation enhancers showed greater anti-inflammatory activity (87.55 ± 2.50 and 83.24 ± 2.29 % inhibition of rat paw edema at the end of 12 h for formulations F2 and F3, respectively, compared to that of the formulation without enhancer with 69.99 %) as well as greater analgesic activity (quicker onset of analgesia in 1.5 h with longer duration of 10 to 12 h).Conclusion: Transdermal films of ketorolac have a potential for use in the treatment of pain andinflammation. Incorporation of turpentine oil in the films enhances not only drug flux but also analgesic and anti-inflammatory activities in rats

A Unique Automation Platform for Measuring Low Level Radioactivity in Metabolite Identification Studies

Generation and interpretation of biotransformation data on drugs, i.e. identification of physiologically relevant metabolites, defining metabolic pathways and elucidation of metabolite structures, have become increasingly important to the drug development process. Profiling using 14C or 3H radiolabel is defined as the chromatographic separation and quantification of drug-related material in a given biological sample derived from an in vitro, preclinical in vivo or clinical study. Metabolite profiling is a very time intensive activity, particularly for preclinical in vivo or clinical studies which have defined limitations on radiation burden and exposure levels. A clear gap exists for certain studies which do not require specialized high volume automation technologies, yet these studies would still clearly benefit from automation. Use of radiolabeled compounds in preclinical and clinical ADME studies, specifically for metabolite profiling and identification are a very good example. The current lack of automation for measuring low level radioactivity in metabolite profiling requires substantial capacity, personal attention and resources from laboratory scientists. To help address these challenges and improve efficiency, we have innovated, developed and implemented a novel and flexible automation platform that integrates a robotic plate handling platform, HPLC or UPLC system, mass spectrometer and an automated fraction collector

Implicitly Constrained Semi-Supervised Least Squares Classification

We introduce a novel semi-supervised version of the least squares classifier. This implicitly constrained least squares (ICLS) classifier minimizes the squared loss on the labeled data among the set of parameters implied by all possible labelings of the unlabeled data. Unlike other discriminative semi-supervised methods, our approach does not introduce explicit additional assumptions into the objective function, but leverages implicit assumptions already present in the choice of the supervised least squares classifier. We show this approach can be formulated as a quadratic programming problem and its solution can be found using a simple gradient descent procedure. We prove that, in a certain way, our method never leads to performance worse than the supervised classifier. Experimental results corroborate this theoretical result in the multidimensional case on benchmark datasets, also in terms of the error rate.Comment: 12 pages, 2 figures, 1 table. The Fourteenth International Symposium on Intelligent Data Analysis (2015), Saint-Etienne, Franc

Study on Supply Chain Disruption Risk Management Strategies and Model

In this paper, the reasons that make a supply chain vulnerable to disruption risks are analyzed; the necessity and significance of developing supply chain disruption risk management strategies that have direct impacts on the effectiveness of supply chain disruption risk management is discussed, combined with the practice of China. Considering the characteristics of disruption risks, the supply chain disruption risk management strategies with the properties of efficiency and resilience are developed and analyzed, and related with actual practice, which include supply management strategies, supply management strategies, product management strategies and information management strategies. And then, in order to offer decision-making support for adopting reasonable strategies, a mathematical model is developed

Functional characterisation of substrate-binding proteins to address nutrient uptake in marine picocyanobacteria.

Marine cyanobacteria are key primary producers, contributing significantly to the microbial food web and biogeochemical cycles by releasing and importing many essential nutrients cycled through the environment. A subgroup of these, the picocyanobacteria (Synechococcus and Prochlorococcus), have colonised almost all marine ecosystems, covering a range of distinct light and temperature conditions, and nutrient profiles. The intra-clade diversities displayed by this monophyletic branch of cyanobacteria is indicative of their success across a broad range of environments. Part of this diversity is due to nutrient acquisition mechanisms, such as the use of high-affinity ATP-binding cassette (ABC) transporters to competitively acquire nutrients, particularly in oligotrophic (nutrient scarce) marine environments. The specificity of nutrient uptake in ABC transporters is primarily determined by the peripheral substrate-binding protein (SBP), a receptor protein that mediates ligand recognition and initiates translocation into the cell. The recent availability of large numbers of sequenced picocyanobacterial genomes indicates both Synechococcus and Prochlorococcus apportion >50% of their transport capacity to ABC transport systems. However, the low degree of sequence homology among the SBP family limits the reliability of functional assignments using sequence annotation and prediction tools. This review highlights the use of known SBP structural representatives for the uptake of key nutrient classes by cyanobacteria to compare with predicted SBP functionalities within sequenced marine picocyanobacteria genomes. This review shows the broad range of conserved biochemical functions of picocyanobacteria and the range of novel and hypothetical ABC transport systems that require further functional characterisation