TPX2 regulates the localization and activity of Eg5 in the mammalian mitotic spindle

TPX2 promotes mitotic spindle formation by enhancing Eg5 accumulation on microtubules and limiting motor activity

Misregulation of the LOB domain gene DDA1 suggests possible functions in auxin signalling and photomorphogenesis

The LATERAL ORGAN BOUNDARIES DOMAIN (LBD) gene family encodes plant-specific transcription factors. In this report, the LBD gene DOWN IN DARK AND AUXIN1 (DDA1), which is closely related to LATERAL ORGAN BOUNDARIES (LOB) and ASYMMETRIC LEAVES2 (AS2), was characterized. DDA1 is expressed primarily in vascular tissues and its transcript levels were reduced by exposure to exogenous indole-3-acetic acid (IAA or auxin) and in response to dark exposure. Analysis of a T-DNA insertion line, dda1-1, in which the insertion resulted in misregulation of DDA1 transcripts in the presence of IAA and in the dark revealed possible functions in auxin response and photomorphogenesis. dda1-1 plants exhibited reduced sensitivity to auxin, produced fewer lateral roots, and displayed aberrant hypocotyl elongation in the dark. Phenotypes resulting from fusion of a transcriptional repression domain to DDA1 suggest that DDA1 may act as both a transcriptional activator and a transcriptional repressor depending on the context. These results indicate that DDA1 may function in both the auxin signalling and photomorphogenesis pathways

A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort.

Background: REQUITE (validating pREdictive models and biomarkers of radiotherapy toxicity to reduce side effects and improve QUalITy of lifE in cancer survivors) is an international prospective cohort study. The purpose of this project was to analyse a cohort of patients recruited into REQUITE using a deep learning algorithm to identify patient-specific features associated with the development of toxicity, and test the approach by attempting to validate previously published genetic risk factors. Methods: The study involved REQUITE prostate cancer patients treated with external beam radiotherapy who had complete 2-year follow-up. We used five separate late toxicity endpoints: ≥grade 1 late rectal bleeding, ≥grade 2 urinary frequency, ≥grade 1 haematuria, ≥ grade 2 nocturia, ≥ grade 1 decreased urinary stream. Forty-three single nucleotide polymorphisms (SNPs) already reported in the literature to be associated with the toxicity endpoints were included in the analysis. No SNP had been studied before in the REQUITE cohort. Deep Sparse AutoEncoders (DSAE) were trained to recognize features (SNPs) identifying patients with no toxicity and tested on a different independent mixed population including patients without and with toxicity. Results: One thousand, four hundred and one patients were included, and toxicity rates were: rectal bleeding 11.7%, urinary frequency 4%, haematuria 5.5%, nocturia 7.8%, decreased urinary stream 17.1%. Twenty-four of the 43 SNPs that were associated with the toxicity endpoints were validated as identifying patients with toxicity. Twenty of the 24 SNPs were associated with the same toxicity endpoint as reported in the literature: 9 SNPs for urinary symptoms and 11 SNPs for overall toxicity. The other 4 SNPs were associated with a different endpoint. Conclusion: Deep learning algorithms can validate SNPs associated with toxicity after radiotherapy for prostate cancer. The method should be studied further to identify polygenic SNP risk signatures for radiotherapy toxicity. The signatures could then be included in integrated normal tissue complication probability models and tested for their ability to personalize radiotherapy treatment planning

REQUITE: A prospective multicentre cohort study of patients undergoing radiotherapy for breast, lung or prostate cancer

Purpose: REQUITE aimed to establish a resource for multi-national validation of models and biomarkers that predict risk of late toxicity following radiotherapy. The purpose of this article is to provide summary descriptive data. Methods: An international, prospective cohort study recruited cancer patients in 26 hospitals in eight countries between April 2014 and March 2017. Target recruitment was 5300 patients. Eligible patients had breast, prostate or lung cancer and planned potentially curable radiotherapy. Radiotherapy was prescribed according to local regimens, but centres used standardised data collection forms. Pre-treatment blood samples were collected. Patients were followed for a minimum of 12 (lung) or 24 (breast/prostate) months and summary descriptive statistics were generated. Results: The study recruited 2069 breast (99% of target), 1808 prostate (86%) and 561 lung (51%) cancer patients. The centralised, accessible database includes: physician-(47,025 forms) and patient-(54,901) reported outcomes; 11,563 breast photos; 17,107 DICOMs and 12,684 DVHs. Imputed genotype data are available for 4223 patients with European ancestry (1948 breast, 1728 prostate, 547 lung). Radiation-induced lymphocyte apoptosis (RILA) assay data are available for 1319 patients. DNA (n = 4409) and PAXgene tubes (n = 3039) are stored in the centralised biobank. Example prevalences of 2-year (1-year for lung) grade >= 2 CTCAE toxicities are 13% atrophy (breast), 3% rectal bleeding (prostate) and 27% dyspnoea (lung). Conclusion: The comprehensive centralised database and linked biobank is a valuable resource for the radiotherapy community for validating predictive models and biomarkers. Patient summary: Up to half of cancer patients undergo radiation therapy and irradiation of surrounding healthy tissue is unavoidable. Damage to healthy tissue can affect short-and long-term quality-of-life. Not all patients are equally sensitive to radiation "damage" but it is not possible at the moment to identify those who are. REQUITE was established with the aim of trying to understand more about how we could predict radiation sensitivity. The purpose of this paper is to provide an overview and summary of the data and material available. In the REQUITE study 4400 breast, prostate and lung cancer patients filled out questionnaires and donated blood. A large amount of data was collected in the same way. With all these data and samples a database and biobank were created that showed it is possible to collect this kind of information in a standardised way across countries. In the future, our database and linked biobank will be a resource for research and validation of clinical predictors and models of radiation sensitivity. REQUITE will also enable a better understanding of how many people suffer with radiotherapy toxicity

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Brain correlates of subjective freedom of choice

The subjective feeling of free choice is an important feature of human experience. Experimental tasks have typically studied free choice by contrasting free and instructed selection of response alternatives. These tasks have been criticised, and it remains unclear how they relate to the subjective feeling of freely choosing. We replicated previous findings of the fMRI correlates of free choice, defined objectively. We introduced a novel task in which participants could experience and report a graded sense of free choice. BOLD responses for conditions subjectively experienced as free identified a postcentral area distinct from the areas typically considered to be involved in free action. Thus, the brain correlates of subjective feeling of free action were not directly related to any established brain correlates of objectively-defined free action. Our results call into question traditional assumptions about the relation between subjective experience of choosing and activity in the brain's so-called voluntary motor areas

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BSE B223821Y / UCL - Université Catholique de LouvainSIGLEBEBelgiu

Performance of solvent resistant nanofiltration membranes for purification of residual solvent in the pharmaceutical industry: Experiments and simulation

This study explores the possibility of developing a sustainable extraction method for use in pharmaceutical production, based on purification with membrane processes. Two types of commercial polymeric organic solvent nanofiltration membranes (StarMem122 and DuraMem150) were selected and tested for their abilities to recover the solvent from a pharmaceutical/solvent mixture (5, 10, 50 mg L -1). Five different pharmaceutical compounds have been selected in this work, namely: Imatinib mesylate, Riluzole, Donepezil HCl, Atenolol and Alprazolam. Solvents tested in the experiment were those used in the manufacturing process, i.e., methanol, ethanol, iso-propanol and ethyl acetate. An acceptable performance (rejection over 90%) was obtained for DuraMem150 in all tested pharmaceutical and solvent mixtures except for iso-propanol. No flux was observed for iso-propanol over the DuraMem150 due to its high viscosity. No separation was observed by using StarMem122 for Imatinib mesylate in iso-propanol (over 80%). Commercially available solvent resistant nanofiltration (SRNF) membranes (StarMem™122 and DuraMem™150) show promising performances as alternative tools to traditional separation units such as distillation columns for the recovery of solvents. Furthermore, to evaluate the potential of SRNF as a substitution for traditional solvent recovery, a model was developed for nanofiltration membrane units and implemented in a common process simulation software (Aspen Plus). These models were based on the pore flow mechanism and describe a single membrane module. A membrane module is not available in Aspen Plus and in its Model Library. In this study, this shortcoming was overcome through implementation of the NF membrane module within the Aspen Custom Modeler link to Aspen Plus. The model has been tested for two model solutes (Disperse orange 3 and Disperse red 19) since the pharmaceutical physical properties are not included in the Aspen Properties Database. The results presented here confirm the value of the Aspen Custom Modeler as a simulation tool for the use of NF as a novel and sustainable tool in pharmaceutical manufacturing