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Additional file 1. Pain Diary.

Additional file 1.

Additional file 5. Study Information and Informed Consent Form.

Additional file 4. WHO trial registration data set.

Additional file 3. Study information and consent form.

Additional file 4. Lab Guidelines.

Additional file 6. World Health Organization Trial Registration Dataset.

Combined_supplemental_materials-Edmondson_et_al for Naturally Acquired Mouse Kidney Parvovirus Infection Produces a Persistent Interstitial Nephritis in Immunocompetent Laboratory Mice by Elijah F. Edmondson, Wang-Ting Hsieh, Josh A. Kramer, Matthew W. Breed, Melody E. Roelke-Parker, Julie Stephens-Devalle, Nathan M. Pate, Laura L. Bassel, Melinda G. Hollingshead, Baktiar O. Karim, Donna O. Butcher, Andrew C. Warner, Kunio Nagashima and Jatinder Gulani in Veterinary Pathology

Additional file 2. Follow-up evaluation schedule.

Additional file 1. Treatment Planning Guidelines.

Additional file 1. Dose constraints, OAR definitions, planning priorities.

Additional file 2. Surgical Credentialling Form.

Additional file 3. Schedule of Enrolment, Interventions and Assessments.

Dose Constraints. Dose Constraints for Treatment Planning. (DOC 123 kb)

Sample Consent Form. Sample Consent Form. (DOC 129 kb)

World Health Organization Trial Registration Dataset. List of Fields in Trial Registration Database. (DOC 76 kb)

Table S1. Target Dose and Volume Data by Individual Patient. CTV- clinical target volume; PTV-I – initial planning target volume; PTF-F – final planning target volume; NR – not reported. Table S2. Organ at Risk (OAR) Constraints and Doses (cGy). D1–99% of the contoured volume receives this dose or less; D33–67% of the contoured volume receives this dose or less; *Small bowel dose constraints were exceeded in Patients 2 & 6. Patient 2 reported no toxicity whatsoever and Patient 6 reported only grade 1 emesis. Table S3. Summary of Quality of Life (QoL) Data at Baseline and Last Available Follow-Up (N = 12*). (DOCX 28 kb)

Appendix C: Proportion of All Disease Sites Mentioned on Proton Therapy Centre Websites. (DOCX 21 kb)

Appendix A: Data collection form. (DOCX 17 kb)

Appendix B: Included and Excluded Proton Therapy Centers, sorted by country, state and city. (DOCX 19 kb)

GDP accounts are customarily compiled in several alternative ways, each aggregating transactions in different ways, but all (at least in theory) adding to the same total. Two of the most common aggregations are that focused on expenditures (based on the standard national income accounting identity of C + I + G + X - M) and that based on revenues, or incomes. The two methods should, of course, add to the same number since they measure different sides of the same activity: what money people receive on the one side, and what they do with it on the other. However, Bulgarian GDP statistics using the revenue approach give growth rates 2 percentage points lower than the expenditure approach for 1998 and 1999. In other words, data based on what people actually spend show growth rates of 5.4% (1998) and 4.4% (1999), while official figures based on revenues are 3.5% and 2.4%, respectively. This can be interpreted as evidence that there are underreported incomes. It is of interest not only for statistical but also for economic policy purposes to have more detailed information about the discrepancies between official statistics and activities not covered by the official statistical system. It is particularly interesting to know the size and structure of unreported, hidden economic activities, or what has come to be called the “shadow economy.” Currently published estimates of the size of the shadow economy vary from 20 to 25% of officially measured GDP, implying that this is a far larger issue than that implied by the differential growth rates cited above. The objective of this study is to estimate the size of the informal sector, its structure, and the dynamics of its development since Bulgaria ended its long standing centrally directed command economy. Different methods were used to get results that are compatible for international comparisons; also, alternative calculations allow a range of estimates which can help to balance the methodological weaknesses of the individual approaches. The basic rationale of Physical Input Approaches to measuring the size of the shadow economy is that energy consumption (electricity, plus other sources) in a given country is proportional to total economic activity and any change in energy consumption which does not correspond to changes in the measured total activity level of the country indicates a change in the size of the shadow economy. These results provide useful indicators of changes in the shadow economy over time, but cannot be used to quantify its absolute size since this depends on an initial estimate of its size in the base year. This estimate is necessarily arbitrary to some degree in the absence of specific micro-level data allowing definition of an explicit relationship between energy use and economic activity. Results show that the Bulgarian shadow economy in 1998 declined below the estimated base year (1989) share of 30%. According to our calculations the share of the shadow economy in 1998 GDP in Bulgaria was 22%. The largest shares were observed in 1990 (32.2%) and 1996 (34.4%), declining thereafter. This study has shown that though the size of the shadow economy has declined from its peaks in the mid 1990’s, it remains a sizable portion of the Bulgarian economy. While in many ways shadow activities have the potential to be dynamic growth sectors, bringing them into official economy would help spread the burden of social programs more broadly. Our results show that a substantial portion of the response to policy initiatives is effectively hidden from official view. Thus, an ability to correctly estimate the size and structure of the shadow economy will not only provide more accurate statistics but can help improve growth policies as well.

The preeminent economic challenge for Central European economies in transition is to grow rapidly for a sustained period of time. On current policies, the Central European economies can expect to grow at moderate rates, faster than Western Europe, but far short of the rapid growth rates achieved in the very fast growing economies (VFGEs) in Asia and elsewhere. This paper discusses the sources of rapid growth in the VFGEs, and the ways in which Central Europe could emulate key aspects of the economic policies of the VFGEs in order to raise the growth rates of the Central European economies.

The authors investigate the impact on economic growth and development of long-run movements in the external terms of trade, with special reference to the experience of 18 oil-exporting countries between 1973 and 1989. They argue that this sample approximates a controlled experiment for examining the impact of unanticipated -- but permanent -- shocks to the terms of trade. They analyze the sample econometrically using panel data techniques. They find that permanent terms-of-trade shocks have a strongly significant positive effect on investment, which they justify theoretically on the grounds that countries in the sample import much of their capital equipment. The shocks also have a significant positive effect on consumption. Government consumption responds almost twice as strongly as private consumption. The shocks have no effect on savings and adversely affect the trade and current account balances. There is a significant positive effect on the output of all main categories of nontradables. But Dutch disease effects are strikingly absent. Agriculture and manufacturing do not contract in reaction to an oil price increase. Dutch disease effects may be absent in part because of policy-induced output restraints in the oil sector, or because of the"enclave"nature of the oil sector, which does not participate in domestic factor markets.

Can developing countries affect the variance of real imports solely by altering the way debt service is paid? The answer, says the author, is a qualified yes. The presumption that fixed rate debt is less risky than flexible rate debt is historically inaccurate as a general proposition. Using annual data for 1970-90, the author shows that for many developing countries, flexible rate borrowing actually reduced net risk - whether debt service payments were indexed to nominal interest rates or to inflation in industrial countries. The covariance terms are larger and more often positive with inflation than with nominal interest rates. The author presents a macro model of the industrial countries to organize thoughts about the comovements of these variables in response to shocks. The terms of trade of developing countries are linked to this model by the assumption that the level of demand in industrial countries positively affects the terms of trade in developing countries. The worst case scenarios for developing countries is flexible interest rate borrowing combined with monetary contraction in the industrial world, which raises nominal interest rates, reduces inflation, and worsens the terms of trade of developing countries. To the extent that developing countries want to avoid this scenario, borrowing at either fixed interest rates or inflation indexed rates would be preferable to borrowing at flexible nominal interest rate. To reduce risk, countries should seek debt contracts in which debt service payments vary positively with their terms of trade. Results indicate that inflation indexed debt is most desirable on this score. The author examines only extreme options, with all debt of one type. The optimal strategy would probably entail all three kinds of borrowing. And the paper does not examine options for efficient international risk sharing.

The author proposes and estimates a microeconomic investment model to determine the relative importance of three explanations for Mexico's investment decline in the early 1980s: the decline in oil prices; the termination of capital inflows; and the effects of debt overhang and uncertainty. He uses investment data for private industries between 1981 and 1985, which have yet to be used in addressing the question under discussion. The data indicate that the main microeconomic mechanism driving the decline in investment was a rise in the relative price of investment goods - especially the relative price of machinery (a traded good in Mexico). Moreover, the decline in trade (driven by falling world oil prices) explains much of the increase in this relative price. The decline in Mexico's international terms of trade was probably the most important ultimate cause of the increased relative cost of machinery, but the reversal in net capital inflows to Mexico probably also played a role in increasing this relative price. On this point, the evidence is not as clear. After controlling for these effects, the author finds little evidence that the effects of debt overhang and uncertainty had much to do with the investment decline. The author points out that investment in Texas and Louisiana (which were also riding the oil boom of 1973-81) also fell in 1981-86, and adverse commodity price shocks also affected many other heavily indebted countries. At the very least, commodity price shocks (such as Mexico's decline in oil prices) as a direct cause of declining investment levels in the 1980s have been insufficiently emphasized in the literature on the effects of the international debt crisis.

Additional file 6: Table S3. Univariate Analysis for Disease-free Survival.

Additional file 5: Table S2. Univariate Analysis for Overall Survival.

Additional file 1 Appendix 1. World Health Organization Trial Registration Dataset. Appendix 2. Dose constraints for SABR arm

Additional file 1 Appendix 1. World Health Organization Trial Registration Dataset. Appendix 2. Dose constraints for SABR arm

Supplemental Methods. Table S1. Predicted binding of KK-LC-152-60 to MHC-I molecules. Table S2. Peptides identified by an in silico search and tested for cross-reactivity. Figure S1. Determination of HLA-A*01:01 expression in transduced cell lines by flow cytometry. Figure S2. CT83 expression levels differed in the cell lines used for in vivo experiments. Figure S3. Sample gating strategy for flow cytometry. (DOCX 15400 kb)

Additional file 4: Table S1. Summary of TP53 mutations.

Additional file 4: Table S1. Summary of TP53 mutations.

Supplemental Methods. Table S1. Predicted binding of KK-LC-152-60 to MHC-I molecules. Table S2. Peptides identified by an in silico search and tested for cross-reactivity. Figure S1. Determination of HLA-A*01:01 expression in transduced cell lines by flow cytometry. Figure S2. CT83 expression levels differed in the cell lines used for in vivo experiments. Figure S3. Sample gating strategy for flow cytometry. (DOCX 15400 kb)

Additional file 5: Table S2. Univariate Analysis for Overall Survival.

Additional file 6: Table S3. Univariate Analysis for Disease-free Survival.