The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses.

Background Proton Magnetic Resonance (MR) Spectroscopy (MRS) is a widely available technique for those clinical centres equipped with MR scanners. Unlike the rest of MR-based techniques, MRS yields not images but spectra of metabolites in the tissues. In pathological situations, the MRS profile changes and this has been particularly described for brain tumours. However, radiologists are frequently not familiar to the interpretation of MRS data and for this reason, the usefulness of decision-support systems (DSS) in MRS data analysis has been explored. Results This work presents the INTERPRET DSS version 3.0, analysing the improvements made from its first release in 2002. Version 3.0 is aimed to be a program that 1st, can be easily used with any new case from any MR scanner manufacturer and 2nd, improves the initial analysis capabilities of the first version. The main improvements are an embedded database, user accounts, more diagnostic discrimination capabilities and the possibility to analyse data acquired under additional data acquisition conditions. Other improvements include a customisable graphical user interface (GUI). Most diagnostic problems included have been addressed through a pattern-recognition based approach, in which classifiers based on linear discriminant analysis (LDA) were trained and tested. Conclusions The INTERPRET DSS 3.0 allows radiologists, medical physicists, biochemists or, generally speaking, any person with a minimum knowledge of what an MR spectrum is, to enter their own SV raw data, acquired at 1.5 T, and to analyse them. The system is expected to help in the categorisation of MR Spectra from abnormal brain masses

Automatic relevance source determination in human brain tumors using Bayesian NMF.

The clinical management of brain tumors is very sensitive; thus, their non-invasive characterization is often preferred. Non-negative Matrix Factorization techniques have been successfully applied in the context of neuro-oncology to extract the underlying source signals that explain different tissue tumor types, for which knowing the number of sources to calculate was always required. In the current study we estimate the number of relevant sources for a set of discrimination problems involving brain tumors and normal brain. For this, we propose to start by calculating a high number of sources using Bayesian NMF and automatically discarding the irrelevant ones during the iterative process of matrices decomposition, hence obtaining a reduced range of interpretable solutions. The real data used in this study come from a widely tested human brain tumor database. Simulated data that resembled the real data was also generated to validate the hypothesis against ground truth. The results obtained suggest that the proposed approach is able to provide a small range of meaningful solutions to the problem of source extraction in human brain tumors

Semi-supervised source extraction methodology for the nosological imaging of glioblastoma response to therapy.

Glioblastomas are one the most aggressive brain tumors. Their usual bad prognosis is due to the heterogeneity of their response to treatment and the lack of early and robust biomarkers to decide whether the tumor is responding to therapy. In this work, we propose the use of a semi-supervised methodology for source extraction to identify the sources representing tumor response to therapy, untreated/unresponsive tumor, and normal brain; and create nosological images of the response to therapy based on those sources. Fourteen mice were used to calculate the sources, and an independent test set of eight mice was used to further evaluate the proposed approach. The preliminary results obtained indicate that was possible to discriminate response and untreated/unresponsive areas of the tumor, and that the color-coded images allowed convenient tracking of response, especially throughout the course of therapy

Real-world data of fulvestrant as first-line treatment of postmenopausal women with estrogen receptor-positive metastatic breast cancer

Goals of endocrine therapy for advanced breast cancer (ABC) include prolonging survival rates, maintaining the quality of life, and delaying the initiation of chemotherapy. We evaluated the effectiveness of fulvestrant as first-line in patients with estrogen receptor (ER)-positive ABC with relapse during or after adjuvant anti-estrogenic therapy in real-world settings. Retrospective, observational study involving 171 postmenopausal women with ER-positive ABC who received fulvestrant as first-line between January 2011 and May 2018 in Spanish hospitals. With a median follow-up of 31.4 months, the progression-free survival (PFS) with fulvestrant was 14.6 months. No differences were seen in the visceral metastatic (14.3 months) versus non-visceral (14.6 months) metastatic subgroup for PFS. Overall response rate and clinical benefit rate were 35.2% and 82.8%. Overall survival was 43.1 months. The duration of the clinical benefit was 19.2 months. Patients with ECOG performance status 0 at the start of treatment showed a significant greater clinical benefit rate and overall survival than with ECOG 1-2. Results in real-world settings are in concordance with randomized clinical trials. Fulvestrant continues to demonstrate clinical benefits in real-world settings and appears be well tolerated as first-line for the treatment of postmenopausal women with ER-positive ABC

Développement d'un outil informatique opérationnel d'aide à la décision et de modélisation des pollutions en Méditerranée

National audienc

The pregnane X receptor drives sexually dimorphic hepatic changes in lipid and xenobiotic metabolism in response to gut microbiota in mice.

The gut microbiota-intestine-liver relationship is emerging as an important factor in multiple hepatic pathologies, but the hepatic sensors and effectors of microbial signals are not well defined. By comparing publicly available liver transcriptomics data from conventional vs. germ-free mice, we identified pregnane X receptor (PXR, NR1I2) transcriptional activity as strongly affected by the absence of gut microbes. Microbiota depletion using antibiotics in Pxr <sup>+/+</sup> vs Pxr <sup>-/-</sup> C57BL/6J littermate mice followed by hepatic transcriptomics revealed that most microbiota-sensitive genes were PXR-dependent in the liver in males, but not in females. Pathway enrichment analysis suggested that microbiota-PXR interaction controlled fatty acid and xenobiotic metabolism. We confirmed that antibiotic treatment reduced liver triglyceride content and hampered xenobiotic metabolism in the liver from Pxr <sup>+/+</sup> but not Pxr <sup>-/-</sup> male mice. These findings identify PXR as a hepatic effector of microbiota-derived signals that regulate the host's sexually dimorphic lipid and xenobiotic metabolisms in the liver. Thus, our results reveal a potential new mechanism for unexpected drug-drug or food-drug interactions. Video abstract

Pathogenic Bacillus anthracis in the progressive gene losses and gains in adaptive evolution

Background: Sequence mutations represent a driving force of adaptive evolution in bacterial pathogens. It is especially evident in reductive genome evolution where bacteria underwent lifestyles shifting from a free-living to a strictly intracellular or host-depending life. It resulted in loss of function mutations and/or the acquisition of virulence gene clusters. Bacillus anthracis shares a common soil bacterial ancestor with its closely related bacillus species but is the only obligate, causative agent of inhalation anthrax within the genus Bacillus. The anthrax-causing Bacillus anthracis experienced the similar lifestyle changes. We thus hypothesized that the bacterial pathogen would follow a compatible evolution path. Results: In this study, a cluster-based evolution scheme was devised to analyze genes that are gained by or lost from B. anthracis. The study detected gene losses/gains at two separate evolutionary stages. The stage I is when B. anthracis and its sister species within the Bacillus cereus group diverged from other species in genus Bacillus. The stage II is when B. anthracis differentiated from its two closest relatives: B. cereus and B. thuringiensis. Many genes gained at these stages are homologues of known pathogenic factors such those for internalin, B. anthracis-specific toxins and large groups of surface proteins and lipoproteins. Conclusion: The analysis presented here allowed us to portray a progressive evolutionary process during the lifestyle shift of B. anthracis, thus providing new insights into how B. anthracis had evolved and bore a promise of finding drug and vaccine targets for this strategically important pathogen

Multi-task learning with a natural metric for quantitative structure activity relationship learning

The goal of Quantitative Structure Activity Relationship (QSAR) Learning is to learn a function that, given the structure of a small molecule (a potential drug), outputs the predicted activity of the compound. We employed multi-task learning (MTL) to exploit commonalities in drug targets and assays. We used datasets containing curated records about the activity of speci c compounds on drug targets provided by ChEMBL. Totally, 1091 assays have been analysed. As a baseline, a single task learning approach that trains random forest to predict drug activity for each drug target individually was considered. We then carried out feature-based and instance-based MTL to predict drug activities. We introduced a natural metric of evolutionary distance between drug targets as a measure of tasks relatedness. Instance-based MTL signi cantly outperformed both, feature-based MTL and the base learner, on 741 drug targets out of 1091. Feature-based MTL won on 179 occasions and the base learner performed best on 171 drug targets. We conclude that MTL QSAR is improved by incorporating the evolutionary distance between targets. These results indicate that QSAR learning can be performed effectively, even if little data is available for speci c drug targets, by leveraging what is known about similar drug targets

Randomized crossover pharmacokinetic evaluation of subcutaneous versus intravenous granisetron in cancer patients treated with platinum-based chemotherapy

BACKGROUND: 5-HT3-receptor antagonists are one of the mainstays of antiemetic treatment, and they are administered either i.v. or orally. Nevertheless, sometimes neither administration route is feasible, such as in patients unable to admit oral intake managed in an outpatient setting. Our objective was to evaluate the bioavailability of s.c. granisetron. PATIENTS AND METHODS: Patients receiving platinum-based chemotherapy were randomized to receive 3 mg of granisetron either s.c. or i.v. in a crossover manner during two cycles. Blood and urine samples were collected after each cycle. Pharmacokinetic parameters observed with each administration route were compared by analysis of variance. RESULTS: From May to November 2005, 31 patients were included and 25 were evaluable. Subcutaneous granisetron resulted in a 27% higher area under the concentration-time curve for 0-12 hours (AUC(0-12h)) and higher levels at 12 hours, with similar values for AUC(0-24h). The maximum concentration was lower with the s.c. than with the i.v. route and was observed 30 minutes following s.c. administration. CONCLUSION: Granisetron administered s.c. achieves complete bioavailability. This is the first study that shows that s.c. granisetron might be a valid alternative to i.v. delivery. Further trials to confirm clinical equivalence are warranted. This new route of administration might be especially relevant for outpatient management of emesis in cancer patients

Tratamiento hormonal del cáncer de mama

Hormonal therapy has been the first systemic treatment against breast cancer. Up to now Tamoxifen and ovarian supression/ablation were the best optionts we had to treat early breast cancer as advancer disease. The advent of aromatase inhibitors, new SERMS and antistrogen Fulvestrant have supoused a great advance in the treatment of this disease and at the same time have complicated the election of the optimal drug for each patient. This article tries to review the aviable treatment options insiting on its indications