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Introduction Chronic kidney disease (CKD) is common. It may arise from multiple diseases and may lead to end stage kidney disease, necessitating dialysis or renal transplantation. CKD is characterized by interstitial fibrosis, with the extent of scarring predicting renal functional outcome. Although often assumed to be irreversible, fibrosis may resolve in other organs such as the liver. In addition, patients with moderate diabetic nephropathy, who have received a successful pancreas transplant, exhibited a reduction in renal scarring, though this took 5 to 10 years. With a commonly used unilateral ureteric obstruction (UUO) model, novel insights have been generated into the pathogenesis of renal inflammation and fibrosis. However, there is little experimental data regarding the potential reversibility of renal fibrosis. In this study the reversible UUO model (RUUO) was used to study the renal response following the removal of ureteric obstruction, thereby allowing the study of renal fibrosis during the reversal phase. Renal fibrosis is driven by pro-fibrotic cytokines and growth factors such as transforming growth factor β (TGFβ) and platelet derived growth factor (PDGF). Myofibroblasts are the main contributor of extracellular matrix (ECM) in the injured kidney. Recent work suggests that they arise from PDGFRβ+ pericytes, fibroblasts or perivascular mesenchymal cells. Imatinib is a tyrosine kinase inhibitor that targets the PDGFRβ pathway and is clinically licensed for use in humans. Treatment with imatinib before and during UUO inhibits PDGFRβ phosphorylation, suppresses myofibroblast proliferation and limits kidney fibrosis. However, patients with CKD typically present with established renal fibrosis and there is no data as to whether imatinib exerts an anti-fibrotic effect upon established kidney scarring. This is required before potential translational studies in patients. While macrophages are detrimental and pro-fibrotic during the early injury phase, they may adopt an anti-fibrotic reparative phenotype during the later recovery phase. Macrophage depletion studies in models of liver fibrosis demonstrate that macrophages are required for the successful resolution of fibrosis. So far, there is no data indicating whether such fibrolytic macrophages are present or active in the kidney. In this study, the RUUO model was studied in detail and performed a comprehensive analysis of the nature of the cellular and extracellular matrix changes during UUO and following the reversal of UUO. Both transgenic reporter mice and wild-type mice were used to develop a method for PDGFRβ+ cell isolation. In addition, the anti-fibrotic effect of imatinib during RUUO was tested at the dose shown to be effective in UUO, in order to determine whether imatinib could accelerate the degradation of established kidney scarring. Finally, macrophages were depleted with clodronate liposomes during RUUO to determine whether there was a population of fibrolytic macrophages during the RUUO phase. Materials and Methods FVB/N mice or C57BL/6J mice underwent sham surgery, left UUO surgery or UUO + RUUO surgery. The kidney tissue was analyzed for αSMA+ myofibroblasts, PDGFR β + cells, F4/80+ macrophages and extracellular matrix (ECM) deposition including collagen I, III and IV and fibronectin. The expression of kidney injury molecule-1 (KIM-1), growth factors (TGF β , PDGF), metalloproteinases (MMPs) and tissue inhibitor of metalloproteinases 1 (TIMP1) was determined by RT-PCR. Attempts were made to purify PDGFR β + cells using FACS sorting, magnetic beads or Percoll gradients. To confirm the anti-fibrotic efficacy of imatinib, the drug or vehicle was administered during UUO at 2 doses (25mg/kg or 50mg/kg) by either intraperitoneal or subcutaneous injection. Intraperitoneal administration of 50mg/kg imatinib was anti-fibrotic in UUO. This dose and route of administration was used in the RUUO studies. Imatinib was administered to mice from day 7 to 14 of RUUO, when the kidneys exhibited significant fibrosis with upregulation of PDGF and PDGFRβ. Tissue was analyzed at day 14 or day 28 RUUO for αSMA and PDGFRβ immunostaining, ECM gene expression and ECM deposition by immunohistochemistry. Clodronate liposomes (5 doses) were administered by intraperitoneal injection from day 11 to 19 of RUUO to deplete macrophages. Day 21 RUUO tissue was immunostained for macrophages and collagen III to assess macrophage depletion and fibrosis. Results There were subtle differences in the response to UUO and RUUO between FVB/N and C57BL/6J mice, though the patterns of injury and fibrosis remodeling were generally similar. Day 7 UUO kidneys exhibited KIM-1 upregulation, prominent macrophage infiltration, increased αSMA and PDGFβ immunostaining, marked ECM deposition and increased MMP/TIMP1 expression. During RUUO the central area of the kidney showed a progressive reduction in KIM-1, collagen III/IV and fibronectin mRNA expression and reduced immunostaining for αSMA, PDGFRβ, collagen III/IV and fibronectin. In contrast, the renal poles remained scarred. The reduced ECM deposition was accompanied by a fall in TIMP1 gene expression and persistently elevated MMP expression, with in situ zymography indicating increased MMP bioactivity during RUUO. These findings indicate that the RUUO model exhibits significant ECM degradation and can therefore be used to study the underlying cellular and molecular mechanisms. Attempts were made to isolate PDGFRβ+ cells using PDGFRβ-eGFP mice, magnetic beads and Percoll gradients, though cell number and cell viability was problematic. Dose response studies with imatinib in UUO indicated that a dose of 50mg/kg administered by intraperitoneal injections could significantly reduce fibrosis in UUO. Despite this, imatinib treatment administered between day 7 and 14 of RUUO failed to augment the remodeling of kidney fibrosis. Increased gene expression of inducible nitric oxide synthase 2 (Nos2: a M1 macrophage marker) was found in UUO. During RUUO, Nos2 expression decreased gradually while the gene expression of mannose receptor C-type I (Mrc1: a M2 macrophage marker) remained elevated, suggesting a phenotypic switch in macrophages. Clodronate liposomes administered during RUUO efficiently depleted F4/80+ macrophages compared to PBS liposomes. Macrophage depletion resulted in persistent collagen III expression indicative of reduced remodeling of fibrosis. Conclusions The RUUO model exhibits acute injury, inflammation and fibrosis during UUO, with a loss of myofibroblasts and significant degradation of ECM occurring during the reversal phase, indicating the value of the model to study renal modelling. Although imatinib treatment reduced fibrosis in UUO, it failed to augment the removal of ECM when administered during RUUO. Macrophage depletion during RUUO retarded the degradation of kidney fibrosis, suggesting the presence of fibrolytic macrophages.

'Enthusiasm' is claimed to be one of the most important ingredients of effective teaching. It is assumed in the studies that enthusiasm is a well-defined behavioural state which can be recognized and reproduced. However, at closer inspection the term becomes elusive and several ions arise: Is enthusiasm a universally valid category or does it bear cultural and individual differentiation? And does it always lead to good teaching? If not, which aspects are central? This study was designed using a hybrid qualitative method which consisted of a mixture of three different methods: multiple-case studies, in-depth interviews and classroom observations.

This manuscript includes three topics in causal inference, all of which are under the randomization inference framework (Neyman, 1923; Fisher, 1935a; Rubin, 1978). This manuscript contains three self-contained chapters. Chapter 1. Under the potential outcomes framework, causal effects are defined as comparisons between potential outcomes under treatment and control. To infer causal effects from randomized experiments, Neyman proposed to test the null hypothesis of zero average causal effect (Neyman’s null), and Fisher proposed to test the null hypothesis of zero individual causal effect (Fisher’s null). Although the subtle difference between Neyman’s null and Fisher’s null has caused lots of controversies and confusions for both theoretical and practical statisticians, a careful comparison between the two approaches has been lacking in the literature for more than eighty years. I fill in this historical gap by making a theoretical comparison between them and highlighting an intriguing paradox that has not been recognized by previous re- searchers. Logically, Fisher’s null implies Neyman’s null. It is therefore surprising that, in actual completely randomized experiments, rejection of Neyman’s null does not imply rejection of Fisher’s null for many realistic situations, including the case with constant causal effect. Furthermore, I show that this paradox also exists in other commonly-used experiments, such as stratified experiments, matched-pair experiments, and factorial experiments. Asymptotic analyses, numerical examples, and real data examples all support this surprising phenomenon. Besides its historical and theoretical importance, this paradox also leads to useful practical implications for modern researchers. Chapter 2. Causal inference in completely randomized treatment-control studies with binary outcomes is discussed from Fisherian, Neymanian and Bayesian perspectives, using the potential outcomes framework. A randomization-based justification of Fisher’s exact test is provided. Arguing that the crucial assumption of constant causal effect is often unrealistic, and holds only for extreme cases, some new asymptotic and Bayesian inferential procedures are proposed. The proposed procedures exploit the intrinsic non-additivity of unit-level causal effects, can be applied to linear and non- linear estimands, and dominate the existing methods, as verified theoretically and also through simulation studies. Chapter 3. Recent literature has underscored the critical role of treatment effect variation in estimating and understanding causal effects. This approach, however, is in contrast to much of the foundational research on causal inference; Neyman, for example, avoided such variation through his focus on the average treatment effect and his definition of the confidence interval. In this chapter, I extend the Ney- manian framework to explicitly allow both for treatment effect variation explained by covariates, known as the systematic component, and for unexplained treatment effect variation, known as the idiosyncratic component. This perspective enables es- timation and testing of impact variation without imposing a model on the marginal distributions of potential outcomes, with the workhorse approach of regression with interaction terms being a special case. My approach leads to two practical results. First, I combine estimates of systematic impact variation with sharp bounds on over- all treatment variation to obtain bounds on the proportion of total impact variation explained by a given model—this is essentially an R2 for treatment effect variation. Second, by using covariates to partially account for the correlation of potential out- comes problem, I exploit this perspective to sharpen the bounds on the variance of the average treatment effect estimate itself. As long as the treatment effect varies across observed covariates, the resulting bounds are sharper than the current sharp bounds in the literature. I apply these ideas to a large randomized evaluation in educational research, showing that these results are meaningful in practice., Statistics