Optimum Magnetometer Transect Spacing to Locate Legacy Oil and Gas Wells: Preliminary Results

The purpose of this project was to examine the optimum transect spacing to locate legacy oil and gas wells using an Overhauser magnetometer. Widely known to be a potential environmental hazard, legacy oil and gas wells may act as a conduit for methane and/or deeper subsurface fluids (naturally occurring brines, injected waste fluids, or injected CO2) to the surface or shallow subsurface. Many plugged wells have all surface equipment removed leaving no visible trace at the surface and thus making the environmental assessment of these wells difficult. Using a magnetometer along a set of predefined transects, magnetic anomalies from the metal casing can be detected. In order to assess large numbers of wells, understanding the typical anomaly size is critical to maximize the transect spacing and therefore minimize magnetometer field work time. Here we briefly review the wide range of transect spacings reported in the literature and show the results of five wells with an initial survey grid at two meter spacing. Although there is significant variation in the anomaly size (X, Y, and Z), transect spacing of 20 m was sufficient to identify all buried wells using the method described herein. The anomalies associated with four of the wells ranged from approximately 1000-4000 nanoteslas (nT), while one well anomaly exhibited more than 10,000 nT above background

The science of clinical practice: disease diagnosis or patient prognosis? Evidence about "what is likely to happen" should shape clinical practice.

BACKGROUND: Diagnosis is the traditional basis for decision-making in clinical practice. Evidence is often lacking about future benefits and harms of these decisions for patients diagnosed with and without disease. We propose that a model of clinical practice focused on patient prognosis and predicting the likelihood of future outcomes may be more useful. DISCUSSION: Disease diagnosis can provide crucial information for clinical decisions that influence outcome in serious acute illness. However, the central role of diagnosis in clinical practice is challenged by evidence that it does not always benefit patients and that factors other than disease are important in determining patient outcome. The concept of disease as a dichotomous 'yes' or 'no' is challenged by the frequent use of diagnostic indicators with continuous distributions, such as blood sugar, which are better understood as contributing information about the probability of a patient's future outcome. Moreover, many illnesses, such as chronic fatigue, cannot usefully be labelled from a disease-diagnosis perspective. In such cases, a prognostic model provides an alternative framework for clinical practice that extends beyond disease and diagnosis and incorporates a wide range of information to predict future patient outcomes and to guide decisions to improve them. Such information embraces non-disease factors and genetic and other biomarkers which influence outcome. SUMMARY: Patient prognosis can provide the framework for modern clinical practice to integrate information from the expanding biological, social, and clinical database for more effective and efficient care

The impact of networks on clinical trials in the United Kingdom

The conduct of clinical trials in the UK has been affected by the recent introduction of managed clinical networks, clinical research networks and rigorous governance regulations. This commentary considers the challenges that these changes have posed for clinical triallists in the UK, based on experiences derived in the conduct of a multicentre neonatal clinical trial under the conditions that now prevail. We conclude that the considerable skills and knowledge that are now required to be an effective Principal Investigator should be recognised and that application processes, including issuing honorary contracts, should be simplified and centralised

Prevention and early detection of prostate cancer

This Review was sponsored and funded by the International Society of Cancer Prevention (ISCaP), the European Association of Urology (EAU), the National Cancer Institute, USA (NCI) (grant number 1R13CA171707-01), Prostate Cancer UK, Cancer Research UK (CRUK) (grant number C569/A16477), and the Association for International Cancer Research (AICR

Method for evaluating prediction models that apply the results of randomized trials to individual patients

<p>Abstract</p> <p>Introduction</p> <p>The clinical significance of a treatment effect demonstrated in a randomized trial is typically assessed by reference to differences in event rates at the group level. An alternative is to make individualized predictions for each patient based on a prediction model. This approach is growing in popularity, particularly for cancer. Despite its intuitive advantages, it remains plausible that some prediction models may do more harm than good. Here we present a novel method for determining whether predictions from a model should be used to apply the results of a randomized trial to individual patients, as opposed to using group level results.</p> <p>Methods</p> <p>We propose applying the prediction model to a data set from a randomized trial and examining the results of patients for whom the treatment arm recommended by a prediction model is congruent with allocation. These results are compared with the strategy of treating all patients through use of a net benefit function that incorporates both the number of patients treated and the outcome. We examined models developed using data sets regarding adjuvant chemotherapy for colorectal cancer and Dutasteride for benign prostatic hypertrophy.</p> <p>Results</p> <p>For adjuvant chemotherapy, we found that patients who would opt for chemotherapy even for small risk reductions, and, conversely, those who would require a very large risk reduction, would on average be harmed by using a prediction model; those with intermediate preferences would on average benefit by allowing such information to help their decision making. Use of prediction could, at worst, lead to the equivalent of an additional death or recurrence per 143 patients; at best it could lead to the equivalent of a reduction in the number of treatments of 25% without an increase in event rates. In the Dutasteride case, where the average benefit of treatment is more modest, there is a small benefit of prediction modelling, equivalent to a reduction of one event for every 100 patients given an individualized prediction.</p> <p>Conclusion</p> <p>The size of the benefit associated with appropriate clinical implementation of a good prediction model is sufficient to warrant development of further models. However, care is advised in the implementation of prediction modelling, especially for patients who would opt for treatment even if it was of relatively little benefit.</p

Importance of prostate volume in the European Randomised Study of Screening for Prostate Cancer (ERSPC) risk calculators: results from the prostate biopsy collaborative group

OBJECTIVES: To compare the predictive performance and potential clinical usefulness of risk calculators of the European Randomized Study of Screening for Prostate Cancer (ERSPC RC) with and without information on prostate volume. METHODS: We studied 6 cohorts (5 European and 1 US) with a total of 15,300 men, all biopsied and with pre-biopsy TRUS measurements of prostate volume. Volume was categorized into 3 categories (25, 40, and 60 cc), to reflect use of digital rectal examination (DRE) for volume assessment. Risks of prostate cancer were calculated according to a ERSPC DRE-based RC (including PSA, DRE, prior biopsy, and prostate volume) and a PSA + DRE model (including PSA, DRE, and prior biopsy). Missing data on prostate volume were completed by single imputation. Risk predictions were evaluated with respect to calibration (graphically), discrimination (AUC curve), and clinical usefulness (net benefit, graphically assessed in decision curves). RESULTS: The AUCs of the ERSPC DRE-based RC ranged from 0.61 to 0.77 and were substantially larger than the AUCs of a model based on only PSA + DRE (ranging from 0.56 to 0.72) in each of the 6 cohorts. The ERSPC DRE-based RC provided net benefit over performing a prostate biopsy on the basis of PSA and DRE outcome in five of the six cohorts. CONCLUSIONS: Identifying men at increased risk for having a biopsy detectable prostate cancer should consider multiple factors, including an estimate of prostate volume

MicroRNA-27b is a regulatory hub in lipid metabolism and is altered in dyslipidemia

Cellular and plasma lipid levels are tightly controlled by complex gene regulatory mechanisms. Elevated plasma lipid content, or hyperlipidemia, is a significant risk factor for cardiovascular morbidity and mortality. MicroRNAs (miRNAs) are posttranscriptional regulators of gene expression and have emerged as important modulators of lipid homeostasis, but the extent of their role has not been systematically investigated. In this study, we performed high-throughput small RNA sequencing and detected approximately 150 miRNAs in mouse liver. We then employed an unbiased, in silico strategy to identify miRNA regulatory hubs in lipid metabolism, and miR-27b was identified as the strongest such hub in human and mouse liver. In addition, hepatic miR-27b levels were determined to be sensitive to plasma hyperlipidemia, as evidenced by its ~3-fold up-regulation in the liver of mice on a high-fat diet (42% calories from fat). Further, we showed in a human hepatocyte cell line (Huh7) that miR-27b regulates the expression (mRNA and protein) of several key lipid-metabolism genes, including Angptl3 and Gpam. Finally, we demonstrated that hepatic miR-27b and its target genes are inversely altered in a mouse model of dyslipidemia and atherosclerosis

Determinants for receiving acupuncture for LBP and associated treatments: a prospective cohort study

BACKGROUND: Acupuncture is a frequently used but controversial adjunct to the treatment of chronic low back pain (LBP). Acupuncture is now considered to be effective for chronic LBP and health care systems are pressured to make a decision whether or not acupuncture should be covered. It has been suggested that providing such services might reduce the use of other health care services. Therefore, we explored factors associated with acupuncture treatment for LBP and the relation of acupuncture with other health care services. METHODS: This is a post hoc analysis of a longitudinal prospective cohort study. General practitioners (GPs) recruited consecutive adult patients with LBP. Data on physical function, subjective mood and utilization of health care services was collected at the first consultation and at follow-up telephone interviews for a period of twelve months. RESULTS: A total of 179 (13 %) out of 1,345 patients received acupuncture treatment. The majority of those (59 %) had chronic LBP. Women and elderly patients were more likely to be given acupuncture. Additional determinants of acupuncture therapy were low functional capacity and chronicity of pain. Chronic (vs. acute) back pain OR 1.6 (CL 1.4–2.9) was the only significant disease-related factor associated with the treatment. The strongest predictors for receiving acupuncture were consultation with a GP who offers acupuncture OR 3.5 (CL 2.9–4.1) and consultation with a specialist OR 2.1 (CL 1.9–2.3). After adjustment for patient characteristics, acupuncture remained associated with higher consultation rates and an increased use of other health care services like physiotherapy. CONCLUSION: Receiving acupuncture for LBP depends mostly on the availability of the treatment. It is associated with increased use of other health services even after adjustment for patient characteristics. In our study, we found that receiving acupuncture does not offset the use of other health care resources. A significant proportion of patients who received did not meet the so far only known selection criterion (chonicity). Acupuncture therapy might be a reflection of helplessness in both patients and health care providers

The effects of using the PReDicT Test to guide the antidepressant treatment of depressed patients: study protocol for a randomised controlled trial

Background Antidepressant medication is commonly used to treat depression. However, many patients do not respond to the first medication prescribed and improvements in symptoms are generally only detectable by clinicians 4–6 weeks after the medication has been initiated. As a result, there is often a long delay between the decision to initiate an antidepressant medication and the identification of an effective treatment regimen. Previous work has demonstrated that antidepressant medications alter subtle measures of affective cognition in depressed patients, such as the appraisal of facial expression. Furthermore, these cognitive effects of antidepressants are apparent early in the course of treatment and can also predict later clinical response. This trial will assess whether an electronic test of affective cognition and symptoms (the Predicting Response to Depression Treatment Test; PReDicT Test) can be used to guide antidepressant treatment in depressed patients and, therefore, hasten treatment response compared to a control group of patients treated as usual. Methods/design The study is a randomised, two-arm, multi-centre, open-label, clinical investigation of a medical device, the PReDicT Test. It will be conducted in five European countries (UK, France, Spain, Germany and the Netherlands) in depressed patients who are commencing antidepressant medication. Patients will be randomised to treatment guided by the PReDicT Test (PReDicT arm) or to Treatment as Usual (TaU arm). Patients in the TaU arm will be treated as per current standard guidelines in their particular country. Patients in the PReDicT arm will complete the PReDicT Test after 1 (and if necessary, 2) weeks of treatment. If the test indicates non-response to the treatment, physicians will be advised to immediately alter the patient’s antidepressant therapy by dose escalation or switching to another compound. The primary outcome of the study is the proportion of patients showing a clinical response (defined as 50% or greater decrease in baseline scores of depression measured using the Quick Inventory of Depressive Symptoms – Self-Rated questionnaire) at week 8. Health economic and acceptability data will also be collected and analysed. Discussion This trial will test the clinical efficacy, cost-effectiveness and acceptability of using the novel PReDicT Test to guide antidepressant treatment selection in depressed patients

MicroRNA-223 coordinates cholesterol homeostasis

Results from this study represent a breakthrough in our understanding of posttranscriptional control of cholesterol metabolism and how microRNAs (miRNAs) are at the heart of cholesterol regulatory circuitry and homeostasis. Although cells are adept at maintaining proper cholesterol levels, it was unknown how cells posttranscriptionally coordinate cholesterol uptake, efflux, and synthesis. MicroRNA-223 (miR-223) transcription and expression are maintained by cholesterol, and, as a feedback network, miR-223 inhibits cholesterol biosynthesis and uptake and increases cholesterol efflux. This study clearly demonstrates the extensive role that miRNAs play in coordinating metabolic adaptation to disease and general homeostasis. This work highlights a unique regulatory control point for cholesterol homeostasis and illustrates how important the study of miRNAs is to the greater understanding of dyslipidemia and cardiovascular disease