Changes in circulating microRNA levels associated with prostate cancer

BACKGROUND: The aim of this study was to investigate the hypothesis that changes in circulating microRNAs (miRs) represent potentially useful biomarkers for the diagnosis, staging and prediction of outcome in prostate cancer. METHODS: Real-time polymerase chain reaction analysis of 742 miRs was performed using plasma-derived circulating microvesicles of 78 prostate cancer patients and 28 normal control individuals to identify differentially quantified miRs. RESULTS: A total of 12 miRs were differentially quantified in prostate cancer patients compared with controls, including 9 in patients without metastases. In all, 11 miRs were present in significantly greater amounts in prostate cancer patients with metastases compared with those without metastases. The association of miR-141 and miR-375 with metastatic prostate cancer was confirmed using serum-derived exosomes and microvesicles in a separate cohort of patients with recurrent or non-recurrent disease following radical prostatectomy. An analysis of five selected miRs in urine samples found that miR-107 and miR-574-3p were quantified at significantly higher concentrations in the urine of men with prostate cancer compared with controls. CONCLUSION: These observations suggest that changes in miR concentration in prostate cancer patients may be identified by analysing various body fluids. Moreover, circulating miRs may be used to diagnose and stage prostate cance

EMA - A R package for Easy Microarray data analysis

<p>Abstract</p> <p>Background</p> <p>The increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users.</p> <p>Findings</p> <p>Based on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package (EMA) devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results.</p> <p>Conclusions</p> <p>Strategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at <url>http://bioinfo.curie.fr/projects/ema/</url>.</p

Surgical treatment for acromioclavicular joint osteoarthritis: patient selection, surgical options, complications, and outcome

Osteoarthritis is one of the most common causes of pain originating from the acromioclavicular (AC) joint. An awareness of appropriate diagnostic techniques is necessary in order to localize clinical symptoms to the AC joint. Initial treatments for AC joint osteoarthritis, which include non-steroidal anti-inflammatory drugs (NSAIDS) and corticosteroids, are recommended prior to surgical interventions. Distal clavicle excision, the main surgical treatment option, can be performed by various surgical approaches, such as open procedures, direct arthroscopic, and indirect arthroscopic techniques. When choosing the best surgical option, factors such as avoidance of AC ligament damage, clavicular instability, and post-operative pain must be considered. This article examines patient selection, complications, and outcomes of surgical treatment options for AC joint osteoarthritis

Regulation of the HIF switch in human endothelial and cancer cells

Hypoxia-inducible factors (HIFs) are transcription factors that reprogram the transcriptome for cells to survive hypoxic insults and oxidative stress. They are important during embryonic development and reprogram the cells to utilize glycolysis when the oxygen levels are extremely low. This metabolic change facilitates normal cell survival as well as cancer cell survival. The key feature in survival is the transition between acute hypoxia and chronic hypoxia, and this is regulated by the transition between HIF-1 expression and HIF-2/HIF-3 expression. This transition is observed in many human cancers and endothelial cells and referred to as the HIF Switch. Here we discuss the mechanisms involved in the HIF Switch in human endothelial and cancer cells which include mRNA and protein levels of the alpha chains of the HIFs. A major continuing effort in this field is directed towards determining the differences between normal and tumor cell utilization of this important pathway, and how this could lead to potential therapeutic approaches

Exploring county-level spatio-temporal patterns in opioid overdose related emergency department visits.

Opioid overdoses within the United States continue to rise and have been negatively impacting the social and economic status of the country. In order to effectively allocate resources and identify policy solutions to reduce the number of overdoses, it is important to understand the geographical differences in opioid overdose rates and their causes. In this study, we utilized data on emergency department opioid overdose (EDOOD) visits to explore the county-level spatio-temporal distribution of opioid overdose rates within the state of Virginia and their association with aggregate socio-ecological factors. The analyses were performed using a combination of techniques including Moran's I and multilevel modeling. Using data from 2016-2021, we found that Virginia counties had notable differences in their EDOOD visit rates with significant neighborhood-level associations: many counties in the southwestern region were consistently identified as the hotspots (areas with a higher concentration of EDOOD visits) whereas many counties in the northern region were consistently identified as the coldspots (areas with a lower concentration of EDOOD visits). In most Virginia counties, EDOOD visit rates declined from 2017 to 2018. In more recent years (since 2019), the visit rates showed an increasing trend. The multilevel modeling revealed that the change in clinical care factors (i.e., access to care and quality of care) and socio-economic factors (i.e., levels of education, employment, income, family and social support, and community safety) were significantly associated with the change in the EDOOD visit rates. The findings from this study have the potential to assist policymakers in proper resource planning thereby improving health outcomes