Looking to the metabolic landscapes for prostate health monitoring.
Ontology highlight
ABSTRACT:
SUBMITTER: Kim WJ
PROVIDER: S-EPMC5551909 | biostudies-other | 2017 Sep
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Metabolic rewiring offers novel therapeutic opportunities in cancer. Until recently, there was scant information regarding soft tissue sarcomas, due to their heterogeneous tissue origin, histological definition and underlying genetic history. Novel large-scale genomic and metabolomics approaches are now helping stratify their physiopathology. In this review, we show how various genetic alterations skew activation pathways and orient metabolic rewiring in sarcomas. We provide an update on the contribution of newly described mechanisms of metabolic regulation. We underscore mechanisms that are relevant to sarcomagenesis or shared with other cancers. We then discuss how diverse metabolic landscapes condition the tumor microenvironment, anti-sarcoma immune responses and prognosis. Finally, we review current attempts to control sarcoma growth using metabolite-targeting drugs.
| S-EPMC8296645 | biostudies-literature
Project description:Confidence in our memories is influenced by many factors, including beliefs about the perceptibility or memorability of certain kinds of objects and events, as well as knowledge about our skill sets, habits, and experiences. Notoriously, our knowledge and beliefs about memory can lead us astray, causing us to be overly confident in eyewitness testimony or to overestimate the frequency of recent experiences. Here, using visual working memory as a case study, we stripped away all these potentially misleading cues, requiring observers to make confidence judgments by directly assessing the quality of their memory representations. We show that individuals can monitor the status of information in working memory as it degrades over time. Our findings suggest that people have access to information reflecting the existence and quality of their working memories, and furthermore, that they can use this information to guide their behavior. (PsycINFO Database Record
| S-EPMC5374054 | biostudies-literature
Project description:Metabolic deregulation is an emergent hallmark of cancer. Altered patterns of metabolic pathways result in exacerbated synthesis of macromolecules, increased proliferation, and resistance to treatment via alteration of drug processing. In addition, molecular heterogeneity creates a barrier to therapeutic options. In breast cancer, this broad variation in molecular metabolism constitutes, simultaneously, a source of prognostic and therapeutic challenges and a doorway to novel interventions. In this work, we investigated the metabolic deregulation landscapes in breast cancer molecular subtypes. Such landscapes are the regulatory signatures behind subtype-specific metabolic features. n = 735 breast cancer samples of the Luminal A, Luminal B, Her2+, and Basal subtypes, as well as n = 113 healthy breast tissue samples were analyzed. By means of a single-sample-based algorithm, deregulation for all metabolic pathways in every sample was determined. Deregulation levels match almost perfectly with the molecular classification, indicating that metabolic anomalies are closely associated with gene-expression signatures. Luminal B tumors are the most deregulated but are also the ones with higher within-subtype variance. We argued that this variation may underlie the fact that Luminal B tumors usually present the worst prognosis, a high rate of recurrence, and the lowest response to treatment in the long term. Finally, we designed a therapeutic scheme to regulate purine metabolism in breast cancer, independently of the molecular subtype. This scheme is founded on a computational tool that provides a set of FDA-approved drugs to target pathway-specific differentially expressed genes. By providing metabolic deregulation patterns at the single-sample level in breast cancer subtypes, we have been able to further characterize tumor behavior. This approach, together with targeted therapy, may open novel avenues for the design of personalized diagnostic, prognostic, and therapeutic strategies.
| S-EPMC7026677 | biostudies-literature
Project description:Marine plankton abundance and dynamics in the open and interior ocean is still an unknown field. The knowledge of gelatinous zooplankton distribution is especially challenging, because this type of plankton has a very fragile structure and cannot be directly sampled using traditional net based techniques. To overcome this shortcoming, Computer Vision techniques can be successfully used for the automatic monitoring of this group.This paper presents the GUARD1 imaging system, a low-cost stand-alone instrument for underwater image acquisition and recognition of gelatinous zooplankton, and discusses the performance of three different methodologies, Tikhonov Regularization, Support Vector Machines and Genetic Programming, that have been compared in order to select the one to be run onboard the system for the automatic recognition of gelatinous zooplankton. The performance comparison results highlight the high accuracy of the three methods in gelatinous zooplankton identification, showing their good capability in robustly selecting relevant features. In particular, Genetic Programming technique achieves the same performances of the other two methods by using a smaller set of features, thus being the most efficient in avoiding computationally consuming preprocessing stages, that is a crucial requirement for running on an autonomous imaging system designed for long lasting deployments, like the GUARD1. The Genetic Programming algorithm has been installed onboard the system, that has been operationally tested in a two-months survey in the Ligurian Sea, providing satisfactory results in terms of monitoring and recognition performances.
| S-EPMC5191104 | biostudies-literature
Project description:GigaScience is now 5 years old, having been launched at the 2012 Intelligent Systems for Molecular Biology conference. Anyone who has attended what is the largest computational biology conference since then has had the opportunity to join us for each birthday celebration-and receive 1 of our fun T-shirts as a party prize. Since launching, we have pushed our agenda of openness, transparency, reproducibility, and reusability. Here, we look back at our first 5 years and what we have done to forward our open science goals in scientific publishing. Our mainstay has been to create a process that allows the availability and publication of as many "research objects" as possible to create a more complete way of communicating how the research process is done.
| S-EPMC5603759 | biostudies-literature
Project description:"Omics" technologies have been developed to understand the whole complex microbial systems; however, most omics studies reported so far were utilized to analyze the living matters of “single-species”. To understand the cell-cell interaction in the gut microbial complex, we selected to examine the interaction of Escherichia coli O157:H7 (O157) and Bifidobacterium longum (BL), known as a pathogenic and a commensal bacteria, as a first step for understanding the whole gut microbial complex. We have developed a novel time-lapse 2D-NMR metabolic profiling system in order to measure the extracellular metabolites, which are considered a key factor to understand the bacterial crosstalk. Furthermore, in combination with transcriptome and proteome analysis, we found that the relationship between BL and O157 could be partially regarded as the producer and the consumer of nutrients, especially in the case of serine and aspartate metabolism. These findings suggest that our novel profiling systems could be a powerful tool toward understanding crosstalk of the whole microbial complex such as the gut, industrial bioreactors or environmental microbial communities. In vitro mono and coculture were performed. All experiments were performed in duplicate.
2011-09-30 | E-GEOD-18474 | biostudies-arrayexpress
Project description:Raw data for our manuscript in prep, titled: "Real time health monitoring through urine analysis: A preliminary observational study."
2019-05-31 | MSV000083880 | MassIVE
Project description:To investigate the impact of metabolic components and body composition indices on prostate volume (PV) in a population of middle-aged men receiving health check-ups.Six hundred and sixteen men receiving health assessments were stratified to large and small prostates based on the cut-off of median PV. Their demographic data, health history, and international prostate symptoms scores (IPSS) were collected. Metabolic components and body composition indices were compared between subjects with large and small prostates. Moreover, the correlations between these parameters and PV were analyzed by multivariate logistic regression.The median PV was 27 mL and mean age was 54.8 years. Subjects with large PV were older (56.5 vs. 52.7 years) and had higher serum prostate specific antigen (PSA) level (1.73 vs. 0.96 ng/mL), higher IPSS score (8.37 vs. 6.16), and higher body fat, body mass, and waist circumference (all p<0.05). In multivariate analysis, age (OR, 2.45; 95%CI, 1.74-3.45), serum PSA (OR, 2.75; 95%CI, 1.96-3.86), waist circumference (OR, 1.45; 95%CI, 1.02-2.07), fatness (OR, 1.47; 95%CI, 1.04-2.09), and body fat mass (OR, 1.43; 95%CI, 1.00-2.03) were significantly correlated with PV of study subjects. In subgroup analysis, raised waist circumference (OR, 1.89; 95%CI, 1.00-3.59) was the independent predictor of PV in subjects with bothersome lower urinary tract symptoms.Several metabolic components and body composition indices are significantly associated with PV of middle-aged men, including raised waist circumference, fatness, and body fat mass. Raised waist circumference is the only independent predictor of PV in middle-aged men with bothersome LUTS.
| S-EPMC4701412 | biostudies-other
Project description:Prostate adenocarcinoma (PRAD) is a leading cause of death among men. Messenger ribonucleic acid (mRNA) vaccine presents an attractive approach to achieve satisfactory outcomes; however, tumor antigen screening and vaccination candidates show a bottleneck in this field. We aimed to investigate the tumor antigens for mRNA vaccine development and immune subtypes for choosing appropriate patients for vaccination. We identified eight overexpressed and mutated tumor antigens with poor prognostic value of PRAD, including KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3. The correlation of those genes with antigen-presenting immune cells were assessed. We further identified three immune subtypes of PRAD (PRAD immune subtype [PIS] 1-3) with distinct clinical, molecular, and cellular characteristics. PIS1 showed better survival and immune cell infiltration, nevertheless, PIS2 and PIS3 showed cold tumor features with poorer prognosis and higher tumor genomic instability. Moreover, these immune subtypes presented distinguished association with immune checkpoints, immunogenic cell death modulators, and prognostic factors of PRAD. Furthermore, immune landscape characterization unraveled the immune heterogeneity among patients with PRAD. To summarize, our study suggests KLHL17, CPT1B, IQGAP3, LIME1, YJEFN3, KIAA1529, MSH5 and CELSR3 are potential antigens for PRAD mRNA vaccine development, and patients in the PIS2 and PIS3 groups are more suitable for vaccination.
| S-EPMC8645679 | biostudies-literature
Project description:"Omics" technologies have been developed to understand the whole complex microbial systems; however, most omics studies reported so far were utilized to analyze the living matters of “single-species”. To understand the cell-cell interaction in the gut microbial complex, we selected to examine the interaction of Escherichia coli O157:H7 (O157) and Bifidobacterium longum (BL), known as a pathogenic and a commensal bacteria, as a first step for understanding the whole gut microbial complex. We have developed a novel time-lapse 2D-NMR metabolic profiling system in order to measure the extracellular metabolites, which are considered a key factor to understand the bacterial crosstalk. Furthermore, in combination with transcriptome and proteome analysis, we found that the relationship between BL and O157 could be partially regarded as the producer and the consumer of nutrients, especially in the case of serine and aspartate metabolism. These findings suggest that our novel profiling systems could be a powerful tool toward understanding crosstalk of the whole microbial complex such as the gut, industrial bioreactors or environmental microbial communities.
2011-10-01 | GSE18474 | GEO