Drug-sensitivity and passive immunity mathematical epidemiological model for tuberculosis

Regardless of many decades of research, the widespread availability of a vaccine and more recently highly visible WHO efforts to promote a unified global control strategy, Tuberculosis remains a leading cause of infectious mortality. In this paper, a Mathematical Model for Tuberculosis Epidemic with Passive Immunity and Drug-Sensitivity is presented. We carried out analytical studies of the model where the population comprises of eight compartments: passively immune infants, susceptible, latently infected with DS-TB. The Disease Free Equilibrium (DFE) and the Endemic Equilibrium (EE) points were established. The next generation matrix method was used to obtain the reproduction number for drug sensitive () Tuberculosis. We obtained the disease-free equilibrium for drug sensitive TB which is locally asymptotically stable when < 1 indicating that tuberculosis eradication is possible within the population. We also obtained the global stability of the disease-free equilibrium and results showed that the disease-free equilibrium point is globally asymptotically stable when ≤ 1 which indicates that tuberculosis naturally dies out

Effect of early tranexamic acid administration on mortality, hysterectomy, and other morbidities in women with post-partum haemorrhage (WOMAN): an international, randomised, double-blind, placebo-controlled trial

Background Post-partum haemorrhage is the leading cause of maternal death worldwide. Early administration of tranexamic acid reduces deaths due to bleeding in trauma patients. We aimed to assess the effects of early administration of tranexamic acid on death, hysterectomy, and other relevant outcomes in women with post-partum haemorrhage. Methods In this randomised, double-blind, placebo-controlled trial, we recruited women aged 16 years and older with a clinical diagnosis of post-partum haemorrhage after a vaginal birth or caesarean section from 193 hospitals in 21 countries. We randomly assigned women to receive either 1 g intravenous tranexamic acid or matching placebo in addition to usual care. If bleeding continued after 30 min, or stopped and restarted within 24 h of the first dose, a second dose of 1 g of tranexamic acid or placebo could be given. Patients were assigned by selection of a numbered treatment pack from a box containing eight numbered packs that were identical apart from the pack number. Participants, care givers, and those assessing outcomes were masked to allocation. We originally planned to enrol 15 000 women with a composite primary endpoint of death from all-causes or hysterectomy within 42 days of giving birth. However, during the trial it became apparent that the decision to conduct a hysterectomy was often made at the same time as randomisation. Although tranexamic acid could influence the risk of death in these cases, it could not affect the risk of hysterectomy. We therefore increased the sample size from 15 000 to 20 000 women in order to estimate the effect of tranexamic acid on the risk of death from post-partum haemorrhage. All analyses were done on an intention-to-treat basis. This trial is registered with ISRCTN76912190 (Dec 8, 2008); ClinicalTrials.gov, number NCT00872469; and PACTR201007000192283. Findings Between March, 2010, and April, 2016, 20 060 women were enrolled and randomly assigned to receive tranexamic acid (n=10 051) or placebo (n=10 009), of whom 10 036 and 9985, respectively, were included in the analysis. Death due to bleeding was significantly reduced in women given tranexamic acid (155 [1·5%] of 10 036 patients vs 191 [1·9%] of 9985 in the placebo group, risk ratio [RR] 0·81, 95% CI 0·65–1·00; p=0·045), especially in women given treatment within 3 h of giving birth (89 [1·2%] in the tranexamic acid group vs 127 [1·7%] in the placebo group, RR 0·69, 95% CI 0·52–0·91; p=0·008). All other causes of death did not differ significantly by group. Hysterectomy was not reduced with tranexamic acid (358 [3·6%] patients in the tranexamic acid group vs 351 [3·5%] in the placebo group, RR 1·02, 95% CI 0·88–1·07; p=0·84). The composite primary endpoint of death from all causes or hysterectomy was not reduced with tranexamic acid (534 [5·3%] deaths or hysterectomies in the tranexamic acid group vs 546 [5·5%] in the placebo group, RR 0·97, 95% CI 0·87-1·09; p=0·65). Adverse events (including thromboembolic events) did not differ significantly in the tranexamic acid versus placebo group. Interpretation Tranexamic acid reduces death due to bleeding in women with post-partum haemorrhage with no adverse effects. When used as a treatment for postpartum haemorrhage, tranexamic acid should be given as soon as possible after bleeding onset. Funding London School of Hygiene & Tropical Medicine, Pfizer, UK Department of Health, Wellcome Trust, and Bill & Melinda Gates Foundation

Fully Unsupervised Machine Translation Using Context-Aware Word Translation and Denoising Autoencoder

Learning machine translation by using only monolingual data sets is a complex task as there are many possible ways to connect or associate target sentences with source sentences. The monolingual word embeddings are linearly mapped on a common shared space through robust learning or adversarial training in an unsupervised way, but these learning techniques have fundamental limitations in translating sentences. In this paper, a simple yet effective method has been proposed for fully unsupervised machine translation that is based on cross-lingual sense to word embedding instead of cross-lingual word embedding and language model. We have utilized word sense disambiguation to incorporate the source language context in order to select the sense of a word more appropriately. A language model for considering target language context in lexical choices and denoising autoencoder for language insertion, deletion, and reordering are integrated. The proposed approach eliminates the problem of noisy target language context due to erroneous word translations. This work takes into account the challenge of homonyms and polysemous words in the case of morphologically rich languages. The experiments performed on English-Hindi and Hindi-English using different evaluation metrics show an improvement of +3 points in BLEU and METEOR-Hindi over the baseline system

Synthesis of Novel Conjugated Linoleic Acid (CLA)-Coated Superparamagnetic Iron Oxide Nanoparticles (SPIONs) for the Delivery of Paclitaxel with Enhanced In Vitro Anti-Proliferative Activity on A549 Lung Cancer Cells

The application of Superparamagnetic Iron Oxide Nanoparticles (SPIONs) as a nanomedicine for Non-Small Cell Lung Carcinoma (NSCLC) can provide effective delivery of anticancer drugs with minimal side-effects. SPIONs have the flexibility to be modified to achieve enhanced oading of hydrophobic anticancer drugs such as paclitaxel (PTX). The purpose of this study was to synthesize novel trans-10, cis-12 conjugated linoleic acid (CLA)-coated SPIONs loaded with PTX to enhance the anti-proliferative activity of PTX. CLA-coated PTX-SPIONs with a particle size and zeta potential of 96.5 ± 0.6 nm and −27.3 ± 1.9 mV, respectively, were synthesized. The superparamagnetism of the CLA-coated PTX-SPIONs was confirmed, with saturation magnetization of 60 emu/g and 29 Oe coercivity. CLA-coated PTX-SPIONs had a drug loading efficiency of 98.5% and demonstrated sustained site-specific in vitro release of PTX over 24 h (i.e., 94% at pH 6.8 mimicking the tumor microenvironment). Enhanced anti-proliferative activity was also observed with the CLA-coated PTX-SPIONs against a lung adenocarcinoma (A549) cell line after 72 h, with a recorded cell viability of 17.1%. The CLA-coated PTX-SPIONs demonstrated enhanced suppression of A549 cell proliferation compared to pristine PTX, thus suggesting potential application of the nanomedicine as an effective site-specific delivery system for enhanced therapeutic activity in NSCLC therapy

Universal Dependencies 2.8.1

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008). Version 2.8.1 fixes a bug in 2.8 where a portion of the Dutch Alpino treebank was accidentally omitted

Universal Dependencies 2.7

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008)

Universal Dependencies 2.10

Universal Dependencies is a project that seeks to develop cross-linguistically consistent treebank annotation for many languages, with the goal of facilitating multilingual parser development, cross-lingual learning, and parsing research from a language typology perspective. The annotation scheme is based on (universal) Stanford dependencies (de Marneffe et al., 2006, 2008, 2014), Google universal part-of-speech tags (Petrov et al., 2012), and the Interset interlingua for morphosyntactic tagsets (Zeman, 2008)