Targetin deubiquitinating enzymes in kinetoplastids with small molecules

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Biológicas, leída el 9-05-2017Millones de personas sufren y más de 1000 millones están en riesgo de contraer la tripanosomiasis Africana, el mal de Chagas o la leishmaniasis. Estas enfermedades son causadas por los kinetoplástidos Trypanosoma brucei, T. cruzi y Leishmania spp., respectivamente. Los tratamientos actualmente disponibles para estas enfermedades son viejos y poseen perfiles complejos de administración, baja eficacia y/o serios efectos adversos. Además, los parásitos causantes están desarrollando resistencias a los tratamientos existentes. Por estas razones hay una necesidad urgente de descubrir nuevos tratamientos para estas dolencias. Es por tanto importante enfocarse en nuevas dianas que demuestren ser tratables. La maquinaria de ubiquitina ofrece una oportunidad excitante como diana para el desarrollo de nuevas terapias. Las desubiquitinasas son enzimas responsables de retirar moléculas de ubiquitina de proteínas diana y regulan numerosos procesos celulares. Estas enzimas ya están siendo exploradas como dianas en otras áreas terapéuticas. Recientemente se ha demostrado que algunas desubiquitinasas son esenciales en T. brucei. Los 3 parásitos tienen genomas y biologías similares (El-Sayed et al., 2005). Así, cabe esperar que las moléculas que modulen una diana conservada sean activas frente a los 3 patógenos (Khare et al., 2016)...Millions of people suffer from and more than 1 billion people live at the risk of contracting human African trypanosomiasis (HAT), Chagas disease and leishmaniasis. These diseases are caused by Trypanosoma brucei, T. cruzi and Leishmania spp. respectively - members of the class Kinetoplastida. The current treatments against these diseases are old and have complex administration profiles, low efficacy and/or serious side effects. The causative parasites are also developing resistance against the available treatments. Therefore, there is an urgent need to discover new treatments for these diseases. For this it is important to focus on new targets that have proven to be tractable. The ubiquitin machinery provides an exciting opportunity as the target for development of new therapies. Deubiquitinases are the enzymes responsible for removing ubiquitin from target proteins and regulate a whole lot of cellular processes. They are being pursued as targets in several therapeutic areas. It was shown that some deubiquitinases are essential in T. brucei. The three parasites have similar genomic sequence and biology (El-Sayed et al., 2005). Thus compounds targeting a conserved target could be active against all three parasites (Khare et al., 2016)...Fac. de Ciencias BiológicasTRUEunpu

Spasticity Outcome Tools in Traumatic Complete Spinal Cord Injury

Objective: To evaluate spasticity in patients of complete motor complete spinal cord injury using M.A.S ,SCATS and PSFS tools of spasticity and assessing their correlation. Design:  Observational cross-sectional study. Setting:  In-patient rehabilitation ward. Participants: 50 individuals of chronic (≥ 1 year trauma) motor complete SCI were classified into mild (n=16), moderate (n=11), and severe (n=23) spastic groups; based on their lower limb extensor muscle group spasticity score using a Modified Ashworth Scale (M.A.S), Spinal cord assessment tool for spastic reflexes(SCATS) and Penn spasm frequency scale (PSFS).  Main Outcome Measures: The proportion of cases in mild, moderate, severe spastic groups, mean MAS score, mean SCATS Score and PSFS Score were evaluated and were compared between the groups with different grades of spasticity. Results:  The mean M.A.S score among the study group was 3.71±1.60. The mean SCAT ankle clonus score, flexor spasm score and extensor spasm score were 1.55±1.05, 1.36±0.81 and 1.22±0.76 respectively (P<0.001S).The mean PSFS (frequency) score and mean PSFS (severity) score was 1.78±0.84 and 1.56±0.70 respectively( P<0.001S). All the three spasticity  outcome tools were found to be significantly associated with the type of spasticity (P≤0.001).A significant positive correlation was observed between M.A.S score and the mean PSFS (FREQ; r = 0.856) score and PSFS (SEV; r = 0.818) score and the mean SCAT score(r=0.913).  Conclusion: All three spasticity outcome tools M.A.S, PSFS and SCATS are acceptable as well as feasible, inherit good clinical utility and correlate significantly with the severity of spasticity. Significant correlations were observed between SCATS score and PSFS score with the M.A.S score. No single outcome measure can reflect the multidimensional nature of spasticity; hence a battery of tests should be applied to measure spasticity to plan antispasmodic treatment in such patients. Keywords: Spinal cord injury, Spasticity, Modified Ashworth score, Spinal cord assessment tool for spastic reflexes, Penn spasm frequency scale

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Review spam and reviewer behavior analysis.

Review spam and reviewer behavior analysis

Identifying comparative sentences in text documents

This paper studies the problem of identifying comparative sentences in text documents. The problem is related to but quite different from sentiment/opinion sentence identification or classification. Sentiment classification studies the problem of classifying a document or a sentence based on the subjective opinion of the author. An important application area of sentiment/opinion identification is business intelligence as a product manufacturer always wants to know consumers ’ opinions on its products. Comparisons on the other hand can be subjective or objective. Furthermore, a comparison is not concerned with an object in isolation. Instead, it compares the object with others. An example opinion sentence is “the sound quality of CD player X is poor”. An example comparative sentence is “the sound quality of CD player X is not as good as that of CD player Y”. Clearly, these two sentences give different information. Their language constructs are quite different too. Identifying comparative sentences is also useful in practice because direct comparisons are perhaps one of the most convincing ways of evaluation, which may even be more important than opinions on each individual object. This paper proposes to study the comparative sentence identification problem. It first categorizes comparative sentences into different types, and then presents a novel integrated pattern discovery and supervised learning approach to identifying comparative sentences from text documents. Experiment results using three types of documents, news articles, consumer reviews of products, and Internet forum postings, show a precision of 79% and recall of 81%. More detailed results are given in the paper

Opinion spam and analysis

Evaluative texts on the Web have become a valuable source of opinions on products, services, events, individuals, etc. Recently, many researchers have studied such opinion sources as product reviews, forum posts, and blogs. However, existing research has been focused on classification and summarization of opinions using natural language processing and data mining techniques. An important issue that has been neglected so far is opinion spam or trustworthiness of online opinions. In this paper, we study this issue in the context of product reviews, which are opinion rich and are widely used by consumers and product manufacturers. In the past two years, several startup companies also appeared which aggregate opinions from product reviews. It is thus high time to study spam in reviews. To the best of our knowledge, there is still no published study on this topic, although Web spam and email spam have been investigated extensively. We will see that opinion spam is quite different from Web spam and email spam, and thus requires different detection techniques. Based on the analysis of 5.8 million reviews and 2.14 million reviewers from amazon.com, we show that opinion spam in reviews is widespread. This paper analyzes such spam activities and presents some novel techniques to detect them