1,621 research outputs found

    Novel critical point drying (CPD) based preparation and transmission electron microscopy (TEM) imaging of protein specific molecularly imprinted polymers (HydroMIPs)

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    We report the transmission electron microscopy (TEM) imaging of a hydrogel-based molecularly imprinted polymer (HydroMIP) specific to the template molecule bovine haemoglobin (BHb). A novel critical point drying based sample preparation technique was employed to prepare the molecularly imprinted polymer (MIP) samples in a manner that would facilitate the use of TEM to image the imprinted cavities, and provide an appropriate degree of both magnification and resolution to image polymer architecture in the <10 nm range. For the first time, polymer structure has been detailed that clearly displays molecularly imprinted cavities, ranging from 5-50 nm in size, that correlate (in terms of size) with the protein molecule employed as the imprinting template. The modified critical point drying sample preparation technique used may potentially play a key role in the imaging of all molecularly imprinted polymers, particularly those prepared in the aqueous phase

    Oral tolerance to cancer can be abrogated by T regulatory cell inhibition

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    Oral administration of tumour cells induces an immune hypo-responsiveness known as oral tolerance. We have previously shown that oral tolerance to a cancer is tumour antigen specific, non-cross-reactive and confers a tumour growth advantage. We investigated the utilisation of regulatory T cell (Treg) depletion on oral tolerance to a cancer and its ability to control tumour growth. Balb/C mice were gavage fed homogenised tumour tissue – JBS fibrosarcoma (to induce oral tolerance to a cancer), or PBS as control. Growth of subcutaneous JBS tumours were measured; splenic tissue excised and flow cytometry used to quantify and compare systemic Tregs and T effector (Teff) cell populations. Prior to and/or following tumour feeding, mice were intraperitoneally administered anti-CD25, to inactivate systemic Tregs, or given isotype antibody as a control. Mice which were orally tolerised prior to subcutaneous tumour induction, displayed significantly higher systemic Treg levels (14% vs 6%) and faster tumour growth rates than controls (p<0.05). Complete regression of tumours were only seen after Treg inactivation and occurred in all groups - this was not inhibited by tumour feeding. The cure rates for Treg inactivation were 60% during tolerisation, 75% during tumour growth and 100% during inactivation for both tolerisation and tumour growth. Depletion of Tregs gave rise to an increased number of Teff cells. Treg depletion post-tolerisation and post-tumour induction led to the complete regression of all tumours on tumour bearing mice. Oral administration of tumour tissue, confers a tumour growth advantage and is accompanied by an increase in systemic Treg levels. The administration of anti-CD25 Ab decreased Treg numbers and caused an increase in Teffs. Most notably Treg cell inhibition overcame established oral tolerance with consequent tumor regression, especially relevant to foregut cancers where oral tolerance is likely to be induced by the shedding of tumour tissue into the gut

    Different Renal Function Equations and Dosing of Direct Oral Anticoagulants in Atrial Fibrillation

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    BACKGROUND: Randomized trials of direct oral anticoagulants (DOACs) adopted the Cockcroft-Gault (CG) formula to calculate estimated glomerular filtration rate (eGFR) to determine the dosages of DOACs. OBJECTIVES: The authors aimed to investigate the agreements/disagreements of eGFRs calculated using different equations (CG, Modified Diet in Renal Disease [MDRD], and Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI] formulas), and their impacts on the dosages of DOACs and clinical outcomes. METHODS: Medical data from a multicenter health care provider in Taiwan including 39,239 patients with atrial fibrillation were used. Among these patients, there were 11,185 and 2,323 patients treated with DOACs and warfarin, respectively. RESULTS: At the cutoff values of eGFR of 50 mL/min, the agreements were 78% between MDRD and CG and 81% between CKD-EPI and CG. The disagreements among the different equations were largely due to overestimations, especially for patients aged >75 years and with a body weight of <50 kg (58.8% for MDRD and 50.9% for CKD-EPI). Among patients receiving DOACs whose dosages were defined as “on label” based on MDRD or CKD-EPI, only those whose dosages were “truly on label” based on CG were associated with a lower risk of major bleeding (adjusted HR: 0.34; 95% CI: 0.26-0.45) compared to warfarin. CONCLUSIONS: The adoptions of MDRD or CKD-EPI rather than CG would result in inappropriate dosing of DOACs (mainly overdosing), which would attenuate the advantages of DOACs compared to warfarin. The CG equation should be used as the gold standard to calculate eGFRs and guide the DOAC dosages

    Geometry, thermodynamics, and finite-size corrections in the critical Potts model

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    We establish an intriguing connection between geometry and thermodynamics in the critical q-state Potts model on two-dimensional lattices, using the q-state bond-correlated percolation model (QBCPM) representation. We find that the number of clusters of the QBCPM has an energy-like singularity for q different from 1, which is reached and supported by exact results, numerical simulation, and scaling arguments. We also establish that the finite-size correction to the number of bonds, has no constant term and explains the divergence of related quantities as q --> 4, the multicritical point. Similar analyses are applicable to a variety of other systems.Comment: 12 pages, 6 figure

    Faster and more accurate classification of time series by exploiting a novel dynamic time warping averaging algorithm

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    A concerted research effort over the past two decades has heralded significant improvements in both the efficiency and effectiveness of time series classification. The consensus that has emerged in the community is that the best solution is a surprisingly simple one. In virtually all domains, the most accurate classifier is the nearest neighbor algorithm with dynamic time warping as the distance measure. The time complexity of dynamic time warping means that successful deployments on resource-constrained devices remain elusive. Moreover, the recent explosion of interest in wearable computing devices, which typically have limited computational resources, has greatly increased the need for very efficient classification algorithms. A classic technique to obtain the benefits of the nearest neighbor algorithm, without inheriting its undesirable time and space complexity, is to use the nearest centroid algorithm. Unfortunately, the unique properties of (most) time series data mean that the centroid typically does not resemble any of the instances, an unintuitive and underappreciated fact. In this paper we demonstrate that we can exploit a recent result by Petitjean et al. to allow meaningful averaging of “warped” time series, which then allows us to create super-efficient nearest “centroid” classifiers that are at least as accurate as their more computationally challenged nearest neighbor relatives. We demonstrate empirically the utility of our approach by comparing it to all the appropriate strawmen algorithms on the ubiquitous UCR Benchmarks and with a case study in supporting insect classification on resource-constrained sensors
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