Enhancing the Performance of Propagation Model-Based Positioning Algorithms

Object localization in wireless networks through Received Signal Strength (RSS) measurements requires a precise estimation of the signal attenuation model in order to produce meaningful results. The popular lognormal channel model, widely adopted to describe the signal strength attenuation as a function of the distance between nodes, turns out to be too simplistic when applied to a real scenario. In this paper, we analyze two possible improvements to this model: on one hand, we build a different channel model for each reference node in the network, with the aim of tackling the anisotropy of the environment. On the other hand, we explicitly append to the lognormal model a term to account for walls attenuation. A thorough experimental testbed demonstrates the potentials of the two approaches, with the second one being especially useful to counteract the effect of the limited sensitivity of practical wireless receivers

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information

Additive Role of Immune System Infiltration and Angiogenesis in Uveal Melanoma Progression

Uveal melanoma (UM) is a malignant tumor that arises in the melanocytes of the uveal tract. It is the most frequent eye cancer, and despite new therapeutic approaches, prognosis is still poor, with up to 50% of patients developing metastasis with no efficient treatment options available. In contrast to cutaneous melanoma, UM is considered an "immune-cold" tumor due to the low mutational burden and the unique immunosuppressive microenvironment. To gain insight into the role of the UM microenvironment in regard to prognosis and metastatic progression, we have performed a pool analysis characterizing the UM microenvironment by using a bioinformatic approach. A variety of scores based on gene expression measuring stromal infiltration were calculated and used to assess association with prognosis. As a result, the highest immune and stromal scores were associated with poor prognosis. Specifically, stromal cells (fibroblasts and endothelial cells), T cells CD8+, natural killer (NK) cells, and macrophages M1 and M2 infiltration were associated with poor prognosis. Contrary to other tumors, lymphocytic infiltration is related to poor prognosis. Only B cells were associated with more favorable prognosis. UM samples scoring high in both angiogenesis (Angio) and antigen presentation (AP) pathways showed a poor prognosis suggesting an additive role of both functions. Almost all these tumors exhibited a chromosome 3 monosomy. Finally, an enrichment analysis showed that tumors classified as high Angio-high AP also activated metabolic pathways such as glycolysis or PI3K-AKT-MTOR. In summary, our pool analysis identified a cluster of samples with angiogenic and inflammatory phenotypes exhibiting poor prognosis and metabolic activation. Our analysis showed robust results replicated in a pool analysis merging different datasets from different analytic platforms

Lung metastases share common immune features regardless of primary tumor origin

Background: Only certain disseminated cells are able to grow in secondary organs to create a metastatic tumor. Under the hypothesis that the immune microenvironment of the host tissue may play an important role in this process, we have categorized metastatic samples based on their immune features. Methods: Gene expression data of metastatic samples (n=374) from four secondary sites (brain, bone, liver and lung) were used to characterize samples based on their immune and stromal infiltration using gene signatures and cell quantification tools. A clustering analysis was done that separated metastatic samples into three different immune categories: high, medium and low. Results: Significant differences were found between the immune profiles of samples metastasizing in distinct organs. Metastases in lung showed a higher immunogenic score than metastases in brain, liver or bone, regardless of their primary site of origin. Also, they preferentially clustered in the high immune group. Samples in this cluster exhibited a clear inflammatory phenotype, higher levels of immune infiltrate, overexpression of programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) pathways and upregulation of genes predicting clinical response to programmed cell death protein 1 (PD-1) blockade (T-cell inflammatory signature). A decision tree algorithm was used to select CD74 as a biomarker that identify samples belonging to this high-immune subtype of metastases, having specificity of 0.96 and sensitivity of 1. Conclusions: We have found a group of lung-enriched metastases showing an inflammatory phenotype susceptible to be treated with immunotherapy

NTHL1 biallelic mutations seldom cause colorectal cancer, serrated polyposis or a multi-tumor phenotype, in absence of colorectal adenomas

In 2015 Weren et al. described a hereditary cancer syndrome caused by biallelic mutations in the DNA base excision repair gene NTHL1, characterized by attenuated adenomatous polyposis and increased colorectal cancer (CRC) risk, largely resembling the recessive syndrome caused by MUTYH mutations1. To date, 33 homozygous or compound heterozygous NTHL1 mutation carriers have been reported (21 families)1,2,3,4,5,6,7,8. More than 5 colonic adenomas (range: 6 to >50) were identified in 24 of the 28 (85%) mutation carriers who underwent colonoscopy screening, and CRC was diagnosed in 19 (68%) of them. Noteworthy, 17 carriers (57%) were diagnosed with multiple primary malignant tumors in extracolonic locations, being the most recurrently found breast and endometrial tumors, head neck squamous cell carcimomas, meningiomas, and bladder and basal cell carcinomas, suggesting that the NTHL1-associated syndrome is a multi-tumor disease rather than a solely CRC syndrome. On the other hand, the fact that at least ¼ (7/28) of the reported biallelic mutation carriers who underwent colonoscopy screening had ≤10 adenomas, and that ≥5 hyperplastic polyps were detected in five carriers (polyp number range: 5->30), lead us to suspect a possible association of NTHL1 mutations with nonpolyposis CRC and serrated/hyperplastic polyposis. Based on previous evidence and with the aim of refining the phenotypic characteristics of the NTHL1-associated syndrome, here we evaluated the implication of NTHL1 biallelic mutations in the predisposition to personal or familial history of multiple tumor types, familial/early-onset nonpolyposis CRC, and serrated/hyperplastic polyposis

Crambescin C1 Acts as A Possible Substrate of iNOS and eNOS Increasing Nitric Oxide Production and Inducing In Vivo Hypotensive Effect

Crambescins are guanidine alkaloids from the sponge Crambe crambe. Crambescin C1 (CC) induces metallothionein genes and nitric oxide (NO) is one of the triggers. We studied and compared the in vitro, in vivo, and in silico effects of some crambescine A and C analogs. HepG2 gene expression was analyzed using microarrays. Vasodilation was studied in rat aortic rings. In vivo hypotensive effect was directly measured in anesthetized rats. The targets of crambescines were studied in silico. CC and homo-crambescine C1 (HCC), but not crambescine A1 (CA), induced metallothioneins transcripts. CC increased NO production in HepG2 cells. In isolated rat aortic rings, CC and HCC induced an endothelium-dependent relaxation related to eNOS activation and an endothelium-independent relaxation related to iNOS activation, hence both compounds increase NO and reduce vascular tone. In silico analysis also points to eNOS and iNOS as targets of Crambescin C1 and source of NO increment. CC effect is mediated through crambescin binding to the active site of eNOS and iNOS. CC docking studies in iNOS and eNOS active site revealed hydrogen bonding of the hydroxylated chain with residues Glu377 and Glu361, involved in the substrate recognition, and explains its higher binding affinity than CA. The later interaction and the extra polar contacts with its pyrimidine moiety, absent in the endogenous substrate, explain its role as exogenous substrate of NOSs and NO production. Our results suggest that CC serve as a basis to develop new useful drugs when bioavailability of NO is perturbed.Fil: Rubiolo, Juan Andrés. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas; Argentina. Ministerio de Ciencia, Tecnologia E Innovacion Productiva (santa Fe). - Gobierno de la Provincia de Santa Fe. Ministerio de Ciencia, Tecnologia E Innovacion Productiva (santa Fe).; Argentina. Universidad de Santiago de Compostela; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Lence, Emilio. Universidad de Santiago de Compostela; EspañaFil: González Bello, Concepción. Universidad de Santiago de Compostela; EspañaFil: Roel, María. Universidad de Santiago de Compostela; EspañaFil: Gil Longo, José. Universidad de Santiago de Compostela; EspañaFil: Campos Toimil, Manuel. Universidad de Santiago de Compostela; EspañaFil: Ternon, Eva. Université Nice Sophia Antipolis. Laboratoire Jean-alexandre Dieudonné.; FranciaFil: Thomas, Olivier P.. National University of Ireland Galway; IrlandaFil: González Cantalapiedra, Antonio. Universidad de Santiago de Compostela; EspañaFil: López Alonso, Henar. Universidad de Santiago de Compostela; EspañaFil: Vieytes, Mercedes R.. Universidad de Santiago de Compostela; EspañaFil: Botana, Luis M.. Universidad de Santiago de Compostela; Españ

Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance

Use of non-steroidal anti-inflammatory drugs and risk of breast cancer: The Spanish Multi-Case-control (MCC) study

Background: The relationship between non-steroidal anti-inflammatory drug (NSAID) consumption and breast cancer has been repeatedly studied, although the results remain controversial. Most case-control studies reported that NSAID consumption protected against breast cancer, while most cohort studies did not find this effect. Most studies have dealt with NSAIDs as a whole group or with specific drugs, such aspirin, ibuprofen, or others, but not with NSAID subgroups according to the Anatomical Therapeutic Chemical Classification System; moreover, scarce attention has been paid to their effect on different tumor categories (i.e.: ductal/non-ductal, stage at diagnosis or presence of hormonal receptors). Methods: In this case-control study, we report the NSAID – breast cancer relationship in 1736 breast cancer cases and 1895 healthy controls; results are reported stratifying by the women’s characteristics (i.e.: menopausal status or body mass index category) and by tumor characteristics. Results: In our study, NSAID use was associated with a 24 % reduction in breast cancer risk (Odds ratio [OR] = 0.76; 95 % Confidence Interval [CI]: 0.64–0.89), and similar results were found for acetic acid derivatives, propionic acid derivatives and COXIBs, but not for aspirin. Similar results were found in postmenopausal and premenopausal women. NSAID consumption also protected against hormone + or HER2+ cancers, but not against triple negative breast cancers. The COX-2 selectivity showed an inverse association with breast cancer (i.e. OR < 1), except in advanced clinical stage and triple negative cancers. Conclusion: Most NSAIDs, but not aspirin, showed an inverse association against breast cancer; this effect seems to be restricted to hormone + or HER2+ cancers. Keywords: Breast cancer, Non-steroidal anti-inflammatory drug, Hormone receptor positive breast cancer, HER2 positive breast cancer, Triple negative breast cance

Novel Common Genetic Susceptibility Loci for Colorectal Cancer

BACKGROUND: Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. METHODS: We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. RESULTS: The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. CONCLUSIONS: This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screenin