993 resultados para project grant


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Mode of access: Internet.

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Mode of access: Internet.

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The starting point for this presentation is that applicants provide a large surplus of information when submitting a NHMRC Project Grant proposal for funding. This is costly in their time, attracts high administration costs, makes the task appear daunting for peer reviewers and may reduce the quality of the peer review leading to less than perfect reliability in decision making. We are currently experimenting with alternate models to see whether similar reliability in funding outcomes are achieved at less cost. We will compare traditional NHMRC Grant Review Panels (GRPs) with panels that use less information and journal style panels. By way of background to this experimental work, we will show some results on current levels of reliability for GRPs, the costs incurred by all who participate in Project Grant selection, and the level of reliability acceptable to researchers. By experimenting in this way and building an evidence base for how research funding should be allocated, the NHMRC is showing international leadership in this important field.

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Objective: To estimate the time spent by the researchers for preparing grant proposals, and to examine whether spending more time increase the chances of success. Design: Observational study. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant proposals in March 2012. Main outcome measures: Total researcher time spent preparing proposals; funding success as predicted by the time spent. Results: The NHMRC received 3727 proposals of which 3570 were reviewed and 731 (21%) were funded. Among our 285 participants who submitted 632 proposals, 21% were successful. Preparing a new proposal took an average of 38 working days of researcher time and a resubmitted proposal took 28 working days, an overall average of 34 days per proposal. An estimated 550 working years of researchers' time (95% CI 513 to 589) was spent preparing the 3727 proposals, which translates into annual salary costs of AU$66 million. More time spent preparing a proposal did not increase the chances of success for the lead researcher (prevalence ratio (PR) of success for 10 day increase=0.91, 95% credible interval 0.78 to 1.04) or other researchers (PR=0.89, 95% CI 0.67 to 1.17). Conclusions: Considerable time is spent preparing NHMRC Project Grant proposals. As success rates are historically 20–25%, much of this time has no immediate benefit to either the researcher or society, and there are large opportunity costs in lost research output. The application process could be shortened so that only information relevant for peer review, not administration, is collected. This would have little impact on the quality of peer review and the time saved could be reinvested into research.

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Researchers spend an average of 38 working days preparing an NHMRC Project Grant proposal, but with success rates of just 15% then over 500 years of researcher went into failed applications in 2014. This time would likely have been better spent on actual research. Many applications are non-competitive and could possibly be culled early, saving time for both researchers and funding agencies. Our analysis of the major health and medical scheme in Australia estimated that 61% of applications were never likely to be funded...

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Introduction: The accurate identification of tissue electron densities is of great importance for Monte Carlo (MC) dose calculations. When converting patient CT data into a voxelised format suitable for MC simulations, however, it is common to simplify the assignment of electron densities so that the complex tissues existing in the human body are categorized into a few basic types. This study examines the effects that the assignment of tissue types and the calculation of densities can have on the results of MC simulations, for the particular case of a Siemen’s Sensation 4 CT scanner located in a radiotherapy centre where QA measurements are routinely made using 11 tissue types (plus air). Methods: DOSXYZnrc phantoms are generated from CT data, using the CTCREATE user code, with the relationship between Hounsfield units (HU) and density determined via linear interpolation between a series of specified points on the ‘CT-density ramp’ (see Figure 1(a)). Tissue types are assigned according to HU ranges. Each voxel in the DOSXYZnrc phantom therefore has an electron density (electrons/cm3) defined by the product of the mass density (from the HU conversion) and the intrinsic electron density (electrons /gram) (from the material assignment), in that voxel. In this study, we consider the problems of density conversion and material identification separately: the CT-density ramp is simplified by decreasing the number of points which define it from 12 down to 8, 3 and 2; and the material-type-assignment is varied by defining the materials which comprise our test phantom (a Supertech head) as two tissues and bone, two plastics and bone, water only and (as an extreme case) lead only. The effect of these parameters on radiological thickness maps derived from simulated portal images is investigated. Results & Discussion: Increasing the degree of simplification of the CT-density ramp results in an increasing effect on the resulting radiological thickness calculated for the Supertech head phantom. For instance, defining the CT-density ramp using 8 points, instead of 12, results in a maximum radiological thickness change of 0.2 cm, whereas defining the CT-density ramp using only 2 points results in a maximum radiological thickness change of 11.2 cm. Changing the definition of the materials comprising the phantom between water and plastic and tissue results in millimetre-scale changes to the resulting radiological thickness. When the entire phantom is defined as lead, this alteration changes the calculated radiological thickness by a maximum of 9.7 cm. Evidently, the simplification of the CT-density ramp has a greater effect on the resulting radiological thickness map than does the alteration of the assignment of tissue types. Conclusions: It is possible to alter the definitions of the tissue types comprising the phantom (or patient) without substantially altering the results of simulated portal images. However, these images are very sensitive to the accurate identification of the HU-density relationship. When converting data from a patient’s CT into a MC simulation phantom, therefore, all possible care should be taken to accurately reproduce the conversion between HU and mass density, for the specific CT scanner used. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital (RBWH), Brisbane, Australia. The authors are grateful to the staff of the RBWH, especially Darren Cassidy, for assistance in obtaining the phantom CT data used in this study. The authors also wish to thank Cathy Hargrave, of QUT, for assistance in formatting the CT data, using the Pinnacle TPS. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.

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Introduction: The use of amorphous-silicon electronic portal imaging devices (a-Si EPIDs) for dosimetry is complicated by the effects of scattered radiation. In photon radiotherapy, primary signal at the detector can be accompanied by photons scattered from linear accelerator components, detector materials, intervening air, treatment room surfaces (floor, walls, etc) and from the patient/phantom being irradiated. Consequently, EPID measurements which presume to take scatter into account are highly sensitive to the identification of these contributions. One example of this susceptibility is the process of calibrating an EPID for use as a gauge of (radiological) thickness, where specific allowance must be made for the effect of phantom-scatter on the intensity of radiation measured through different thicknesses of phantom. This is usually done via a theoretical calculation which assumes that phantom scatter is linearly related to thickness and field-size. We have, however, undertaken a more detailed study of the scattering effects of fields of different dimensions when applied to phantoms of various thicknesses in order to derive scattered-primary ratios (SPRs) directly from simulation results. This allows us to make a more-accurate calibration of the EPID, and to qualify the appositeness of the theoretical SPR calculations. Methods: This study uses a full MC model of the entire linac-phantom-detector system simulated using EGSnrc/BEAMnrc codes. The Elekta linac and EPID are modelled according to specifications from the manufacturer and the intervening phantoms are modelled as rectilinear blocks of water or plastic, with their densities set to a range of physically realistic and unrealistic values. Transmissions through these various phantoms are calculated using the dose detected in the model EPID and used in an evaluation of the field-size-dependence of SPR, in different media, applying a method suggested for experimental systems by Swindell and Evans [1]. These results are compared firstly with SPRs calculated using the theoretical, linear relationship between SPR and irradiated volume, and secondly with SPRs evaluated from our own experimental data. An alternate evaluation of the SPR in each simulated system is also made by modifying the BEAMnrc user code READPHSP, to identify and count those particles in a given plane of the system that have undergone a scattering event. In addition to these simulations, which are designed to closely replicate the experimental setup, we also used MC models to examine the effects of varying the setup in experimentally challenging ways (changing the size of the air gap between the phantom and the EPID, changing the longitudinal position of the EPID itself). Experimental measurements used in this study were made using an Elekta Precise linear accelerator, operating at 6MV, with an Elekta iView GT a-Si EPID. Results and Discussion: 1. Comparison with theory: With the Elekta iView EPID fixed at 160 cm from the photon source, the phantoms, when positioned isocentrically, are located 41 to 55 cm from the surface of the panel. At this geometry, a close but imperfect agreement (differing by up to 5%) can be identified between the results of the simulations and the theoretical calculations. However, this agreement can be totally disrupted by shifting the phantom out of the isocentric position. Evidently, the allowance made for source-phantom-detector geometry by the theoretical expression for SPR is inadequate to describe the effect that phantom proximity can have on measurements made using an (infamously low-energy sensitive) a-Si EPID. 2. Comparison with experiment: For various square field sizes and across the range of phantom thicknesses, there is good agreement between simulation data and experimental measurements of the transmissions and the derived values of the primary intensities. However, the values of SPR obtained through these simulations and measurements seem to be much more sensitive to slight differences between the simulated and real systems, leading to difficulties in producing a simulated system which adequately replicates the experimental data. (For instance, small changes to simulated phantom density make large differences to resulting SPR.) 3. Comparison with direct calculation: By developing a method for directly counting the number scattered particles reaching the detector after passing through the various isocentric phantom thicknesses, we show that the experimental method discussed above is providing a good measure of the actual degree of scattering produced by the phantom. This calculation also permits the analysis of the scattering sources/sinks within the linac and EPID, as well as the phantom and intervening air. Conclusions: This work challenges the assumption that scatter to and within an EPID can be accounted for using a simple, linear model. Simulations discussed here are intended to contribute to a fuller understanding of the contribution of scattered radiation to the EPID images that are used in dosimetry calculations. Acknowledgements: This work is funded by the NHMRC, through a project grant, and supported by the Queensland University of Technology (QUT) and the Royal Brisbane and Women's Hospital, Brisbane, Australia. The authors are also grateful to Elekta for the provision of manufacturing specifications which permitted the detailed simulation of their linear accelerators and amorphous-silicon electronic portal imaging devices. Computational resources and services used in this work were provided by the HPC and Research Support Group, QUT, Brisbane, Australia.

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The life course of Australian researchers includes regular funding applications, which incur large personal and time costs. We previously estimated that Australian researchers spent 550 years preparing 3,727 proposals for the 2012 NHMRC Project Grant funding round, at an estimated annual salary cost of AU$66 million. Despite the worldwide importance of funding rounds, there is little evidence on what researchers think of the application process. We conducted a web-based survey of Australian researchers (May–July 2013) asking about their experience with NHMRC Project Grants. Almost all researchers (n=224 at 31 May) supported changes to the application (96%) and peer-review (88%) processes; 73% supported the introduction of shorter initial Expressions of Interest; and half (50%) provided extensive comments on the NHMRC processes. Researchers agreed preparing their proposals always took top priority over other work (97%) and personal (87%) commitments. More than half (57%) provided extensive comments on the ongoing personal impact of concurrent grant-writing and holiday seasons on family, children and other relationships. Researchers with experience on Grant Review Panels (34%) or as External Reviewers (78%) reported many sections of the proposals were rarely or never read, which suggests these sections could be cut with no impact on the quality of peer review. Our findings provide evidence on the experience of Australian researchers as applicants. The process of preparing, submitting and reviewing proposals could be streamlined to minimise the burden on applicants and peer reviewers, giving Australian researchers more time to work on actual research and be with their families.

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Objective To examine the impact of applying for funding on personal workloads, stress and family relationships. Design Qualitative study of researchers preparing grant proposals. Setting Web-based survey on applying for the annual National Health and Medical Research Council (NHMRC) Project Grant scheme. Participants Australian researchers (n=215). Results Almost all agreed that preparing their proposals always took top priority over other work (97%) and personal (87%) commitments. Almost all researchers agreed that they became stressed by the workload (93%) and restricted their holidays during the grant writing season (88%). Most researchers agreed that they submitted proposals because chance is involved in being successful (75%), due to performance requirements at their institution (60%) and pressure from their colleagues to submit proposals (53%). Almost all researchers supported changes to the current processes to submit proposals (95%) and peer review (90%). Most researchers (59%) provided extensive comments on the impact of writing proposals on their work life and home life. Six major work life themes were: (1) top priority; (2) career development; (3) stress at work; (4) benefits at work; (5) time spent at work and (6) pressure from colleagues. Six major home life themes were: (1) restricting family holidays; (2) time spent on work at home; (3) impact on children; (4) stress at home; (5) impact on family and friends and (6) impact on partner. Additional impacts on the mental health and well-being of researchers were identified. Conclusions The process of preparing grant proposals for a single annual deadline is stressful, time consuming and conflicts with family responsibilities. The timing of the funding cycle could be shifted to minimise applicant burden, give Australian researchers more time to work on actual research and to be with their families.

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Caveolin-1 has a complex role in prostate cancer and has been suggested to be a potential biomarker and therapeutic target. As mature caveolin-1 resides in caveolae, invaginated lipid raft domains at the plasma membrane, caveolae have been suggested as a tumor-promoting signaling platform in prostate cancer. However, caveola formation requires both caveolin-1 and cavin-1 (also known as PTRF; polymerase I and transcript release factor). Here, we examined the expression of cavin-1 in prostate epithelia and stroma using tissue microarray including normal, non-malignant and malignant prostate tissues. We found that caveolin-1 was induced without the presence of cavin-1 in advanced prostate carcinoma, an expression pattern mirrored in the PC-3 cell line. In contrast, normal prostate epithelia expressed neither caveolin-1 nor cavin-1, while prostate stroma highly expressed both caveolin-1 and cavin-1. Utilizing PC-3 cells as a suitable model for caveolin-1-positive advanced prostate cancer, we found that cavin-1 expression in PC-3 cells inhibits anchorage-independent growth, and reduces in vivo tumor growth and metastasis in an orthotopic prostate cancer xenograft mouse model. The expression of α-smooth muscle actin in stroma along with interleukin-6 (IL-6) in cancer cells was also decreased in tumors of mice bearing PC-3-cavin-1 tumor cells. To determine whether cavin-1 acts by neutralizing caveolin-1, we expressed cavin-1 in caveolin-1-negative prostate cancer LNCaP and 22Rv1 cells. Caveolin-1 but not cavin-1 expression increased anchorage-independent growth in LNCaP and 22Rv1 cells. Cavin-1 co-expression reversed caveolin-1 effects in caveolin-1-positive LNCaP cells. Taken together, these results suggest that caveolin-1 in advanced prostate cancer is present outside of caveolae, because of the lack of cavin-1 expression. Cavin-1 expression attenuates the effects of non-caveolar caveolin-1 microdomains partly via reduced IL-6 microenvironmental function. With circulating caveolin-1 as a potential biomarker for advanced prostate cancer, identification of the molecular pathways affected by cavin-1 could provide novel therapeutic targets.

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That’s what one researcher told us when we asked them about applying for NHMRC Project Grant funding. Others said that applying for funding had made them ill, lost them friends, ruined Christmas and caused arguments with friends and family. What makes applying for funding so bad? We’ve tried to summarise the problems with the system in the diagram above. This is based on our group’s four years of research into the funding process. Some of the arrows are based on evidence from our surveys (Survey 1, Survey 2), others are based on anecdote or experience and so maybe wrong. Please let me know if I’ve missed an arrow or an issue.

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Objective: To prospectively test two simplified peer review processes, estimate the agreement between the simplified and official processes, and compare the costs of peer review. Design, participants and setting: A prospective parallel study of Project Grant proposals submitted in 2013 to the National Health and Medical Research Council (NHMRC) of Australia. The official funding outcomes were compared with two simplified processes using proposals in Public Health and Basic Science. The two simplified processes were: panels of 7 reviewers who met face-to-face and reviewed only the nine-page research proposal and track record (simplified panel); and 2 reviewers who independently reviewed only the nine-page research proposal (journal panel). The official process used panels of 12 reviewers who met face-to-face and reviewed longer proposals of around 100 pages. We compared the funding outcomes of 72 proposals that were peer reviewed by the simplified and official processes. Main outcome measures: Agreement in funding outcomes; costs of peer review based on reviewers’ time and travel costs. Results: The agreement between the simplified and official panels (72%, 95% CI 61% to 82%), and the journal and official panels (74%, 62% to 83%), was just below the acceptable threshold of 75%. Using the simplified processes would save $A2.1–$A4.9 million per year in peer review costs. Conclusions: Using shorter applications and simpler peer review processes gave reasonable agreement with the more complex official process. Simplified processes save time and money that could be reallocated to actual research. Funding agencies should consider streamlining their application processes.

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Objective: To examine the association between preoperative quality of life (QoL) and postoperative adverse events in women treated for endometrial cancer. Methods: 760 women with apparent Stage I endometrial cancer were randomised into a clinical trial evaluating laparoscopic versus open surgery. This analysis includes women with preoperative QoL measurements, from the Functional Assessment of Cancer Therapy- General (FACT-G) questionnaire, and who were followed up for at least 6 weeks after surgery (n=684). The outcomes for this study were defined as (1) the occurrence of moderate to severe AEs adverse events within 6 months (Common Toxicology Criteria (CTC) grade ≥3); and (2) any Serious Adverse Event (SAE). The association between preoperative QoL and the occurrence of AE was examined, after controlling for baseline comorbidity and other factors. Results: After adjusting for other factors, odds of occurrence of AE of CTC grade ≥3 were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.00-1.03, p=0.030), which was driven by physical well-being (PWB) (OR=1.09, 95% CI 1.04-1.13, p=0.0002) and functional well-being subscales (FWB) (OR=1.04, 95% CI 1.00-1.07, p=0.035). Similarly, odds of SAE occurrence were significantly increased with each unit decrease in baseline FACT-G score (OR=1.02, 95% CI 1.01-1.04, p=0.011), baseline PWB (OR=1.11, 95% CI 1.06-1.16, p<0.0001) or baseline FWB subscales (OR=1.05, 95% CI 1.01-1.10, p=0.0077). Conclusion: Women with early endometrial cancer presenting with lower QoL prior to surgery are at higher risk of developing a serious adverse event following surgery. Funding: Cancer Council Queensland, Cancer Council New South Wales, Cancer Council Victoria, Cancer Council, Western Australia; NHMRC project grant 456110; Cancer Australia project grant 631523; The Women and Infants Research Foundation, Western Australia; Royal Brisbane and Women’s Hospital Foundation; Wesley Research Institute; Gallipoli Research Foundation; Gynetech; TYCO Healthcare, Australia; Johnson and Johnson Medical, Australia; Hunter New England Centre for Gynaecological Cancer; Genesis Oncology Trust; and Smart Health Research Grant QLD Health.

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Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.