Improvement in clinical step and shoot intensity modulated radiation therapy delivery accuracy on an integrated linear accelerator control system

Purpose: The dose delivery accuracy of 30 clinical step and shoot intensity modulated radiation therapy plans was investigated using the single integrated multileaf collimator controller of the Varian Truebeam linear accelerator (linac) (Varian Medical Systems, Palo Alto, CA) and compared with the dose delivery accuracy on a previous generation Varian 2100CD C-Series linac.

Methods and Materials: Ten prostate, 10 prostate and pelvic node, and 10 head-and-neck cases were investigated in this study. Dose delivery accuracy on each linac was assessed using Farmer ionization chamber point dose measurements, 2-dimensional planar ionization chamber array measurements, and the corresponding Varian dynamic log files. Absolute point dose measurements, fluence delivery accuracy, leaf position accuracy, and the overshoot effect were assessed for each plan.

Results: Absolute point dose delivery accuracy increased by 1.5% on the Truebeam compared with the 2100CD linac. No improvement in fluence delivery accuracy between the linacs, at a gamma criterion of 3%/3 mm was measured using the 2-dimensional ionization chamber array, with median (interquartile range) gamma passing rates of 98.99% (97.70%-99.72%) and 99.28% (98.26%-99.75%) for the Truebeam and 2100CD linacs, respectively. Varian log files also showed no improvement in fluence delivery between the linacs at 3%/3 mm, with median gamma passing rates of 99.97% (99.93%-99.99%) and 99.98% (99.94%-100%) for the Truebeam and 2100CD linacs, respectively. However, log files revealed improved leaf position accuracy and fluence delivery at 1%/1 mm criterion on the Truebeam (99.87%; 99.78%-99.94%) compared with the 2100CD linac (97.87%; 91.93%-99.49%). The overshoot effect, characterized on the 2100CD linac, was not observed on the Truebeam.

Conclusions: The integrated multileaf collimator controller on the Varian Truebeam improves clinical treatment delivery accuracy of step and shoot intensity modulated radiation therapy fields compared with delivery on a Varian C-series linac. © 2014.

The prospective effects of workplace violence on physicians' job satisfaction and turnover intentions: the buffering effect of job control

Background: Health care professionals, including physicians, are at high risk of encountering workplace violence. At the same time physician turnover is an increasing problem that threatens the functioning of the health care sector worldwide. The present study examined the prospective associations of work-related physical violence and bullying with physicians’ turnover intentions and job satisfaction. In addition, we tested whether job control would modify these associations.

Methods: The present study was a 4-year longitudinal survey study, with data gathered in 2006 and 2010.The present sample included 1515 (61% women) Finnish physicians aged 25–63 years at baseline. Analyses of covariance (ANCOVA) were conducted while adjusting for gender, age, baseline levels, specialisation status, and employment sector.

Results: The results of covariance analyses showed that physical violence led to increased physician turnover intentions and that both bullying and physical violence led to reduced physician job satisfaction even after adjustments. We also found that opportunities for job control were able to alleviate the increase in turnover intentions resulting from bullying.

Conclusions: Our results suggest that workplace violence is an extensive problem in the health care sector and may lead to increased turnover and job dissatisfaction. Thus, health care organisations should approach this problem through different means, for example, by giving health care employees more opportunities to control their own work.

GABAergic control of arteriolar diameter in the rat retina

Purpose: To investigate the role of γ-aminobutryic acid (GABA) in the regulation of arteriolar diameter in the rat retina.

Methods.: The actions of GABA on arteriolar diameter were examined using ex vivo retinal whole-mount preparations and isolated vessel segments. In most experiments, arterioles were partially preconstricted with endothelin (Et)-1. The expression levels of GABAA and GABAB receptors on isolated rat retinal Müller cells were assessed by immunohistochemistry.

Results.: GABA (0.1–1 mM) evoked vasodilation or vasoconstriction of arterioles in whole-mount preparations. No such effects were observed with isolated vessel segments. In whole mount samples, the GABAA receptor agonist muscimol caused vasomotor responses in only a small proportion of vessels. In contrast, arteriolar responses to the GABAB receptor agonists baclofen and SKF97541 more closely resembled those observed with GABA. No responses were seen with the GABAC receptor agonist 5-methylimidazoleacetic acid. GABA-induced vasodilator responses were, for the most part, repeatable in the presence of the GABAA receptor antagonist bicuculline. These responses, however, were completely blocked in the presence of the GABAB receptor inhibitor 2-hydroxysaclofen. Strong immunolabeling for both GABAA and GABAB receptors was detected in isolated Müller cells. In the absence of Et-1–induced preconstriction, most vessels were unresponsive to bicuculline or 2-hydroxysaclofen.

Conclusions.: GABA exerts complex effects on arteriolar diameter in the rat retina. These actions appear largely dependent upon the activation of GABAB receptors in the retinal neuropile, possibly those located on perivascular Müller cells. Despite these findings, endogenous GABA appears to contribute little to the regulation of basal arteriolar diameter in the rat retina.

Beta-blocker usage after malignant melanoma diagnosis and survival: a population-based nested case-control study

Background: Beta-blockers have potential antiangiogenic and antimigratory activity. Studies have demonstrated a survival benefit in patients with malignant melanoma treated with beta-blockers.

Objectives: To investigate the association between postdiagnostic beta-blocker usage and risk of melanoma-specific mortality in a population-based cohort of patients with malignant melanoma.

Methods: Patients with incident malignant melanoma diagnosed between 1998 and 2010 were identified within the U.K. Clinical Practice Research Datalink and confirmed using cancer registry data. Patients with malignant melanoma with a melanoma-specific death (cases) recorded by the Office of National Statistics were matched on year of diagnosis, age and sex to four malignant melanoma controls (who lived at least as long after diagnosis as their matched case). A nested case–control approach was used to investigate the association between postdiagnostic beta-blocker usage and melanoma-specific death and all-cause mortality. Conditional logistic regression was applied to generate odds ratios (ORs) and 95% confidence intervals (CIs) for beta-blocker use determined from general practitioner prescribing.

Results: Beta-blocker medications were prescribed after malignant melanoma diagnosis to 20·2% of 242 patients who died from malignant melanoma (cases) and 20·3% of 886 matched controls. Consequently, there was no association between beta-blocker use postdiagnosis and cancer-specific death (OR 0·99, 95% CI 0·68–1·42), which did not markedly alter after adjustment for confounders including stage (OR 0·87, 95% CI 0·56–1·34). No significant associations were detected for individual beta-blocker types, by defined daily doses of use or for all-cause mortality.

Conclusions: Contrary to some previous studies, beta-blocker use after malignant melanoma diagnosis was not associated with reduced risk of death from melanoma in this U.K. population-based study.

Beta-blocker usage and breast cancer survival: a nested case-control study within a UK clinical practice research datalink cohort.

Background: To investigate the association between post-diagnostic beta-blocker usage and risk of cancer-specific mortality in a large population-based cohort of female breast cancer patients.

Methods: A nested case-control study was conducted within a cohort of breast cancer patients identified from cancer registries in England(using the National Cancer Data repository) and diagnosed between 1998 and 2007. Patients who had a breast cancer-specific death(ascertained from Office of National Statistics death registration data) were each matched to four alive controls by year and age at diagnosis. Prescription data for these patients were available through the Clinical Practice Research Datalink. Conditional logistic regression models were used to investigate the association between breast cancer-specific death and beta-blocker usage.

Results: Post-diagnostic use of beta-blockers was identified in 18.9% of 1435 breast cancer-specific deaths and 19.4% of their 5697 matched controls,indicating little evidence of association between beta-blocker use and breast cancer-specific mortality [odds ratio (OR) = 0.97,95% confidence interval (CI) 0.83, 1.13]. There was also little evidence of an association when analyses were restricted to cardio non-selective beta-blockers (OR = 0.90, 95% CI 0.69, 1.17). Similar results were observed in analyses of drug dosage frequency and duration, and beta-blocker type.

Conclusions: In this large UK population-based cohort of breast cancer patients,there was little evidence of an association between post-diagnostic beta-blocker usage and breast cancer progression. Further studies which include information on tumour receptor status are warranted to determine whether response to beta-blockers varies by tumour subtypes.

Comparison of methods used to calculate typical threshold values for potentially toxic elements in soil

The environmental quality of land can be assessed by calculating relevant threshold values, which differentiate between concentrations of elements resulting from geogenic and diffuse anthropogenic sources and concentrations generated by point sources of elements. A simple process allowing the calculation of these typical threshold values (TTVs) was applied across a region of highly complex geology (Northern Ireland) to six elements of interest; arsenic, chromium, copper, lead, nickel and vanadium. Three methods for identifying domains (areas where a readily identifiable factor can be shown to control the concentration of an element) were used: k-means cluster analysis, boxplots and empirical cumulative distribution functions (ECDF). The ECDF method was most efficient at determining areas of both elevated and reduced concentrations and was used to identify domains in this investigation. Two statistical methods for calculating normal background concentrations (NBCs) and upper limits of geochemical baseline variation (ULBLs), currently used in conjunction with legislative regimes in the UK and Finland respectively, were applied within each domain. The NBC methodology was constructed to run within a specific legislative framework, and its use on this soil geochemical data set was influenced by the presence of skewed distributions and outliers. In contrast, the ULBL methodology was found to calculate more appropriate TTVs that were generally more conservative than the NBCs. TTVs indicate what a "typical" concentration of an element would be within a defined geographical area and should be considered alongside the risk that each of the elements pose in these areas to determine potential risk to receptors.

Beta-blocker usage and prostate cancer survival:A nested case-control study in the UK Clinical Practice Research Datalink cohort

Background: Recent laboratory and epidemiological evidence suggests that beta-blockers could inhibit prostate cancer progression. Methods: We investigated the effect of beta-blockers on prostate cancer-specific mortality in a cohort of prostate cancer patients. Prostate cancer patients diagnosed between 1998 and 2006 were identified from the UK Clinical Practice Research Database and confirmed by cancer registries. Patients were followed up to 2011 with deaths identified by the Office of National Statistics. A nested case-control analysis compared patients dying from prostate cancer (cases) with up to three controls alive at the time of their death, matched by age and year of diagnosis. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional logistic regression. Results: Post-diagnostic beta-blocker use was identified in 25% of 1184 prostate cancer-specific deaths and 26% of 3531 matched controls. There was little evidence (P=0.40) of a reduction in the risk of cancer-specific death in beta-blocker users compared with non-users (OR=0.94 95% CI 0.81, 1.09). Similar results were observed after adjustments for confounders, in analyses by beta-blocker frequency, duration, type and for all-cause mortality. Conclusions: Beta-blocker usage after diagnosis was not associated with cancer-specific or all-cause mortality in prostate cancer patients in this large UK study.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

Post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific survival: a nested case-control study in a breast cancer cohort from the UK Clinical Practice Research Datalink

INTRODUCTION: Recent observational studies indicate that post-diagnostic use of aspirin in breast cancer patients may protect against cancer progression perhaps by inhibiting cyclooxygenase-2 dependent mechanisms. Evidence also supports a crucial role for interactions between tumour cells and circulating platelets in cancer growth and dissemination, therefore, use of low-dose aspirin may reduce the risk of death from cancer in breast cancer patients.

METHODS: A cohort of newly diagnosed breast cancer patients (1998 to 2006) were identified in the UK Clinical Practice Research Datalink (and confirmed by cancer registry linkage). Cancer-specific deaths were identified up to 2011 from Office for National Statistics mortality data. A nested case-control analysis was conducted using conditional logistic regression to compare post-diagnostic aspirin exposure using General Practice prescription data in 1,435 cases (breast cancer deaths) with 5,697 controls (matched by age and year of diagnosis).

RESULTS: After breast cancer diagnosis, 18.3% of cancer-specific deaths and 18.5% of matched controls received at least one prescription for low-dose aspirin, corresponding to an odds ratio (OR) of 0.98 (95% CI 0.83, 1.15). Adjustment for potential confounders (including stage and grade) had little impact on this estimate. No dose response relationship was observed when the number of tablets was investigated and no associations were seen when analyses were stratified by receipt of prescriptions for aspirin in the pre-diagnostic period, by stage at diagnosis or by receipt of prescriptions for hormone therapy.

CONCLUSIONS: Overall, in this large population-based cohort of breast cancer patients, there was little evidence of an association between receipt of post-diagnostic prescriptions for low-dose aspirin and breast cancer-specific death. However, information was not available on medication compliance or over-the-counter use of aspirin, which may have contributed to the null findings.

Prediction of integral type failures in semiconductor manufacturing through classification methods

Smart management of maintenances has become fundamental in manufacturing environments in order to decrease downtime and costs associated with failures. Predictive Maintenance (PdM) systems based on Machine Learning (ML) techniques have the possibility with low added costs of drastically decrease failures-related expenses; given the increase of availability of data and capabilities of ML tools, PdM systems are becoming really popular, especially in semiconductor manufacturing. A PdM module based on Classification methods is presented here for the prediction of integral type faults that are related to machine usage and stress of equipment parts. The module has been applied to an important class of semiconductor processes, ion-implantation, for the prediction of ion-source tungsten filament breaks. The PdM has been tested on a real production dataset. © 2013 IEEE.

Virtual metrology enabled early stage prediction for enhanced control of multi-stage fabrication processes

Semiconductor fabrication involves several sequential processing steps with the result that critical production variables are often affected by a superposition of affects over multiple steps. In this paper a Virtual Metrology (VM) system for early stage measurement of such variables is presented; the VM system seeks to express the contribution to the output variability that is due to a defined observable part of the production line. The outputs of the processed system may be used for process monitoring and control purposes. A second contribution of this work is the introduction of Elastic Nets, a regularization and variable selection technique for the modelling of highly-correlated datasets, as a technique for the development of VM models. Elastic Nets and the proposed VM system are illustrated using real data from a multi-stage etch process used in the fabrication of disk drive read/write heads. © 2013 IEEE.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.

Test methods for concrete durability indicators

Durability of concrete structures is primarily dependent on the environmental influences, i.e. the penetration of aggressive substances in the structural element from the environment. Penetrability is an important durability indicator of concrete and by specifying different classes of penetrability of concrete it should be possible to design a structure with the required resistance to environmental loads. This chapter covers descriptions of the available and commonly applied in situ and laboratory, non-invasive and semi-invasive test methods for evaluating concrete penetrability properties.

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.