The role of network science in glioblastoma

Network science has long been recognized as a well-established discipline across many biological domains. In the particular case of cancer genomics, network discovery is challenged by the multitude of available high-dimensional heterogeneous views of data. Glioblastoma (GBM) is an example of such a complex and heterogeneous disease that can be tackled by network science. Identifying the architecture of molecular GBM networks is essential to understanding the information flow and better informing drug development and pre-clinical studies. Here, we review network-based strategies that have been used in the study of GBM, along with the available software implementations for reproducibility and further testing on newly coming datasets. Promising results have been obtained from both bulk and single-cell GBM data, placing network discovery at the forefront of developing a molecularly-informed-based personalized medicine.This work was partially supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with references CEECINST/00102/2018, CEECIND/00072/2018 and PD/BDE/143154/2019, UIDB/04516/2020, UIDB/00297/2020, UIDB/50021/2020, UIDB/50022/2020, UIDB/50026/2020, UIDP/50026/2020, NORTE-01-0145-FEDER-000013, and NORTE-01-0145-FEDER000023 and projects PTDC/CCI-BIO/4180/2020 and DSAIPA/DS/0026/2019. This project has received funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No. 951970 (OLISSIPO project)

Tcox: Correlation-based regularization applied to colorectal cancer survival data

This work was partially supported by national funds through Fundacao para a Ciencia e a Tecnologia (FCT) with references PD/BD/139146/2018, IF/00409/2014, UIDB/50021/2020 (INESC-ID), UIDB/50022/2020 (IDMEC), UIDB/04516/2020 (NOVA LINCS), and UIDB/00297/2020 (CMA) and projects PREDICT (PTDC/CCI-CIF/29877/2017) and MATISSE (DSAIPA/DS/0026/2019).Colorectal cancer (CRC) is one of the leading causes of mortality and morbidity in the world. Being a heterogeneous disease, cancer therapy and prognosis represent a significant challenge to medical care. The molecular information improves the accuracy with which patients are classified and treated since similar pathologies may show different clinical outcomes and other responses to treatment. However, the high dimensionality of gene expression data makes the selection of novel genes a problematic task. We propose TCox, a novel penalization function for Cox models, which promotes the selection of genes that have distinct correlation patterns in normal vs. tumor tissues. We compare TCox to other regularized survival models, Elastic Net, HubCox, and OrphanCox. Gene expression and clinical data of CRC and normal (TCGA) patients are used for model evaluation. Each model is tested 100 times. Within a specific run, eighteen of the features selected by TCox are also selected by the other survival regression models tested, therefore undoubtedly being crucial players in the survival of colorectal cancer patients. Moreover, the TCox model exclusively selects genes able to categorize patients into significant risk groups. Our work demonstrates the ability of the proposed weighted regularizer TCox to disclose novel molecular drivers in CRC survival by accounting for correlation-based network information from both tumor and normal tissue. The results presented support the relevance of network information for biomarker identification in high-dimensional gene expression data and foster new directions for the development of network-based feature selection methods in precision oncology.publishersversionpublishe

Sugarcane bagasse delignification with potassium hydroxide for enhanced enzymatic hydrolysis

The optimization of an alkaline pretreatment process for the delignification of sugarcane bagasse (SCB) to enhance the subsequent enzymatic hydrolysis was performed according to the Doehlert uniform shell design. In this experimental design, the effect of two factors—potassium hydroxide (KOH) concentration and autoclaving time at 121 C (1 atm)—on cellulose, hemicellulose, or the total polysaccharide and lignin content in SCB was evaluated. This response surface methodology revealed that KOH concentration is the factor that most influences the chemical characteristics of treated SCB (SCBt), with optimal conditions for the highest delignification being KOH in the range 5–10% (w/v) and an autoclaving time of 35 min, which provides an average of 97% total polysaccharides without inhibitor accumulation (furfural, 5-hydroxymethyl furfural) and #5% lignin. SCBt samples from two pretreatment conditions (KOH 3.25% – 13 min; KOH 10% – 35 min) were selected, based on the greatest delignification (70–74%) and polysaccharide availability (95–97%) after pretreatment, and further hydrolysed for fermentable sugar production. High sugar yields were obtained from both the pretreated samples (866 to 880 mg sugar per g biomass, respectively) in contrast with the 129 mg sugar per g raw biomass obtained from untreated SCB. These results demonstrate the effectiveness of KOH alkali pretreatments, which improves the overall digestibility of raw SCB polysaccharides from about 18% up to 91%. However, harsh alkali treatment (KOH 10%) is the most effective if the highest glucose/xylose ratio in the final sugar-rich hydrolysate is the aim. Hence, the use of sugar-rich hydrolysates obtained from SCBt as the carbon source for industrial purposes may provide a sustainable and economic solution for the production of bio-based added-value products, such as second generation (2G) bioethanol

Time-Lagged Correlation Analysis of Shellfish Toxicity Reveals Predictive Links to Adjacent Areas, Species, and Environmental Conditions

This work was funded by the project “MATISSE: A machine learning-based forecasting system for shellfish safety” (DSAIPA/DS/0026/2019). The work was also supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with references CEECINST/00102/2018, CEECIND/01399/2017, UIDB/04326/2020, UIDP/04326/2020 and LA/P/0101/2020 (CCMAR), UIDB/04516/2020 (NOVA LINCS), UIDB/00297/2020 (NovaMath), and UIDB/50021/2020 (INESC-ID). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951970 (OLISSIPO project).Diarrhetic Shellfish Poisoning (DSP) is an acute intoxication caused by the consumption of contaminated shellfish, which is common in many regions of the world. To safeguard human health, most countries implement programs focused on the surveillance of toxic phytoplankton abundance and shellfish toxicity levels, an effort that can be complemented by a deeper understanding of the underlying phenomena. In this work, we identify patterns of seasonality in shellfish toxicity across the Portuguese coast and analyse time-lagged correlations between this toxicity and various potential risk factors. We extend the understanding of these relations through the introduction of temporal lags, allowing the analysis of time series at different points in time and the study of the predictive power of the tested variables. This study confirms previous findings about toxicity seasonality patterns on the Portuguese coast and provides further quantitative data about the relations between shellfish toxicity and geographical location, shellfish species, toxic phytoplankton abundances, and environmental conditions. Furthermore, multiple pairs of areas and shellfish species are identified as having correlations high enough to allow for a predictive analysis. These results represent the first step towards understanding the dynamics of DSP toxicity in Portuguese shellfish producing areas, such as temporal and spatial variability, and towards the development of a shellfish safety forecasting system.publishersversionpublishe

Ergonomics applied to the development and evaluation of insoles for protective footwear

Knowledge of ergonomics/human factors plays an important role in the creation and design of safety shoes and insoles, contributing to worker protection, comfort, and stability. The purpose of this study is to compare previous insole designs and analyze the plantar pressure and gait pattern kinematics using the Oxford foot model protocol. The tests were performed comparing the environments on the three rockers of the gait, represented by the heel, midfoot, and forefoot, according to the classification of foot type. The analysis of plantar pressure, regarding its total and maximum distribution, showed that the innovative insole presents a better load distribution in terms of the maximum plantar pressure exerted in the hindfoot and forefoot regions. In the biomechanical analysis of gait, the five variables studied did not show variation in the normal mechanics of the foot in any of the three environments considered. The hallux joint was the one that presented the greatest divergences with the barefoot in terms of amplitude and variability, as expected.SHOE@FUTURE: Technological Solutions for Professional Footwear, POCI-01-0247-FEDER-033835, co-financed by the European Regional Development Fund (FEDER) through the Competitiveness and Internationalization Operational Program under the “Portugal 2020” Program. This work has been supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

Cymoxanil inhibits respiration through inhibition of mitochondrial complex IV

Cymoxanil is a synthetic acetamide fungicide, used against oomycetes. It was first introduced in 1977 and can be used against downy mildew diseases induced by Plasmopara viticola in grapevine cultures and late blight diseases caused by Phytophthora infestans, in tomatoes and potatoes cultures. This fungicide is used in mixed formulations and its higher solubility enables a relatively widespread occurrence in toxic concentrations in aquatic environments. Although it has been used over the years, its biochemical mode of action is not yet known. Some studies reported that cymoxanil affects growth, respiration, DNA, RNA and protein synthesis and RNA polymerase activity of Phytophthora infestans, and it was reported to inhibit cell growth and biomass production and decrease the respiration rate of S. cerevisiae. Using yeast S. cerevisiae as model, we further characterized its effect on mitochondria. We found that whole cells treated with cymoxanil present a higher inhibition of oxygen consumption after 3 h of treatment that remains over time. Using isolated mitochondria, we observe that cymoxanil inhibits respiratory rate of yeast cells by inhibiting oxidative phosphorylation, through inhibition of complex IV activity. Although other targets cannot be excluded, our data provide new information about mode of action of cymoxanil that can be instrumental to drive informed management regarding the use of this fungicide.info:eu-repo/semantics/publishedVersio

Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe

Influence of muscle fitness test performance on metabolic risk factors among adolescent girls

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to examine the association between muscular fitness (MF), assessed by 2 components of Fitnessgram test battery, the Curl-Up and Push-Ups tests and the metabolic risk score among adolescent girls.</p> <p>Methods</p> <p>A total of 229 girls (aged 12-15 years old) comprised the sample of this study. Anthropometric data (height, body mass, waist circumference) were collected. Body mass index (BMI) was also calculated. Muscular strength was assessed taking into account the tests that comprised the FITNESSGRAM test battery, i.e. the curl-up and the push-up. Participants were then categorized in one of 3 categories according the number of tests in which they accomplished the scores that allow them to be classified in health or above health zone. The blood pressure [BP], fasting total cholesterol [TC], low density lipoprotein-cholesterol [LDL-C], high density lipoprotein-cholesterol [HDL-C], triglycerides [TG], glucose, and a metabolic risk score (MRS) were also examined. Physical Activity Index (PAI) was obtained by questionnaire.</p> <p>Results</p> <p>Higher compliance with health-zone criteria (good in the 2 tests), adjusted for age and maturation, were positive and significantly (p ≤ 0.05) associated with height (r = 0.19) and PAI (r = 0.21), while a significant but negative association was found for BMI (r = -0.12); WC (r = -0.19); TC (r = -0.16); TG (r = -0.16); LDL (r = -0.16) and MRS (r = -0.16). Logistic regression showed that who were assigned to MF fittest group were less likely (OR = 0.27; p = 0.003) to be classified overweight/obese and less likely (OR = 0.26; p = 0.03) to be classified as having MRS. This last association was also found for those whom only performed 1 test under the health zone (OR = 0.23; p = 0.02).</p> <p>Conclusions</p> <p>Our data showed that low strength test performance was associated with increased risk for obesity and metabolic risk in adolescent girls even after adjustment for age and maturation.</p