Anders Björklund

Bio: Anders Björklund is an academic researcher from Lund University. The author has contributed to research in topics: Transplantation & Dopamine. The author has an hindex of 165, co-authored 769 publications receiving 84268 citations. Previous affiliations of Anders Björklund include University of Washington & Institute for the Study of Labor.

American exceptionalism in a new light : a comparison of intergenerational earnings mobility in the Nordic countries, the United Kingdom and the United States

Abstract: We develop methods and employ similar sample restrictions to analyse differences in intergenerational earnings mobility across the United States, the United Kingdom, Denmark, Finland, Norway and Sweden. We examine earnings mobility among pairs of fathers and sons as well as fathers and daughters using both mobility matrices and regression and correlation coefficients. Our results suggest that all countries exhibit substantial earnings persistence across generations, but with statistically significant differences across countries. Mobility is lower in the U.S. than in the U.K., where it is lower again compared to the Nordic countries. Persistence is greatest in the tails of the distributions and tends to be particularly high in the upper tails: though in the U.S. this is reversed with a particularly high likelihood that sons of the poorest fathers will remain in the lowest earnings quintile. This is a challenge to the popular notion of ’American exceptionalism’. The U.S. also differs from the Nordic countries in its very low likelihood that sons of the highest earners will show downward ’long-distance’ mobility into the lowest earnings quintile. In this, the U.K. is more similar to the U.S.

Neurturin enhances the survival of intrastriatal fetal dopaminergic transplants.

Abstract: We investigated here the effect of the novel glial cell line-derived neurotrophic factor (GDNF)-family member neurturin (NTN) on transplanted fetal dopamine (DA) neurons. Three groups of rats with complete unilateral 6-hydroxydopamine (6-OHDA) lesions of the nigrostriatal DA system received intrastriatal grafts of embryonic ventral mesencephalic tissue. Following transplantation animals received repeated injections of vehicle or NTN (0.3 microg or 3.0 microg) over three weeks posttransplantation. NTN-treated animals had significantly (1.8-fold) more tyrosine hydroxylase-immunoreactive (TH-IR) neurons. Graft volume, TH-IR cell volume and overall dopaminergic host reinnervation remained unchanged. Amphetamine-induced rotation was rapidly compensated in all grafted rats. We conclude that administration of NTN may be a powerful way to increase survival of transplanted fetal DA neurons.

The use of neural stem cells for gene therapy in the central nervous system.

Abstract: Anders BjoÈrklund is Professor of Histology at the Wallenberg Neuroscience Center at Lund University in Sweden, where he has been active throughout his career. He initially trained as a neuroanatomist, and became interested in brain regeneration and repair in the early seventies. Together with his close collaborators Ulf Stenevi, Olle Lindvall, Fred Gage (now at the Salk institute in La Jolla, USA) and Steve Dunnett (at the Brain Repair Centre in Cambridge, UK) he started to explore the use of fetal neural transplants for neuronal replacement and functional repair in the damaged CNS, which led to the ®rst application of dopamine neuron transplants in patients with advanced Parkinson's disease. Cell transplantation as a tool for in vivo gene therapy has been part of the Lund program since the early nineties.

Intracerebral Grafting of Neuronal Cell Suspensions into the Adult Brain

Abstract: General principles of intracerebral grafting are presented in overview The development and use of the dissociated neuronal cell suspension method are described as a new method for neural transplantation Experiments are described involving fetal dopamine cells transplanted to adult striatum and fetal cholinergic cells transplanted to the hippocampal formation, as primary examples The main focus of this review is related to results of cell survival and axonal elongation

Econometric Analysis of Cross Section and Panel Data

Abstract: The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Econometric Analysis of Panel Data

Abstract: Preface.1. Introduction.1.1 Panel Data: Some Examples.1.2 Why Should We Use Panel Data? Their Benefits and Limitations.Note.2. The One-way Error Component Regression Model.2.1 Introduction.2.2 The Fixed Effects Model.2.3 The Random Effects Model.2.4 Maximum Likelihood Estimation.2.5 Prediction.2.6 Examples.2.7 Selected Applications.2.8 Computational Note.Notes.Problems.3. The Two-way Error Component Regression Model.3.1 Introduction.3.2 The Fixed Effects Model.3.3 The Random Effects Model.3.4 Maximum Likelihood Estimation.3.5 Prediction.3.6 Examples.3.7 Selected Applications.Notes.Problems.4. Test of Hypotheses with Panel Data.4.1 Tests for Poolability of the Data.4.2 Tests for Individual and Time Effects.4.3 Hausman's Specification Test.4.4 Further Reading.Notes.Problems.5. Heteroskedasticity and Serial Correlation in the Error Component Model.5.1 Heteroskedasticity.5.2 Serial Correlation.Notes.Problems.6. Seemingly Unrelated Regressions with Error Components.6.1 The One-way Model.6.2 The Two-way Model.6.3 Applications and Extensions.Problems.7. Simultaneous Equations with Error Components.7.1 Single Equation Estimation.7.2 Empirical Example: Crime in North Carolina.7.3 System Estimation.7.4 The Hausman and Taylor Estimator.7.5 Empirical Example: Earnings Equation Using PSID Data.7.6 Extensions.Notes.Problems.8. Dynamic Panel Data Models.8.1 Introduction.8.2 The Arellano and Bond Estimator.8.3 The Arellano and Bover Estimator.8.4 The Ahn and Schmidt Moment Conditions.8.5 The Blundell and Bond System GMM Estimator.8.6 The Keane and Runkle Estimator.8.7 Further Developments.8.8 Empirical Example: Dynamic Demand for Cigarettes.8.9 Further Reading.Notes.Problems.9. Unbalanced Panel Data Models.9.1 Introduction.9.2 The Unbalanced One-way Error Component Model.9.3 Empirical Example: Hedonic Housing.9.4 The Unbalanced Two-way Error Component Model.9.5 Testing for Individual and Time Effects Using Unbalanced Panel Data.9.6 The Unbalanced Nested Error Component Model.Notes.Problems.10. Special Topics.10.1 Measurement Error and Panel Data.10.2 Rotating Panels.10.3 Pseudo-panels.10.4 Alternative Methods of Pooling Time Series of Cross-section Data.10.5 Spatial Panels.10.6 Short-run vs Long-run Estimates in Pooled Models.10.7 Heterogeneous Panels.Notes.Problems.11. Limited Dependent Variables and Panel Data.11.1 Fixed and Random Logit and Probit Models.11.2 Simulation Estimation of Limited Dependent Variable Models with Panel Data.11.3 Dynamic Panel Data Limited Dependent Variable Models.11.4 Selection Bias in Panel Data.11.5 Censored and Truncated Panel Data Models.11.6 Empirical Applications.11.7 Empirical Example: Nurses' Labor Supply.11.8 Further Reading.Notes.Problems.12. Nonstationary Panels.12.1 Introduction.12.2 Panel Unit Roots Tests Assuming Cross-sectional Independence.12.3 Panel Unit Roots Tests Allowing for Cross-sectional Dependence.12.4 Spurious Regression in Panel Data.12.5 Panel Cointegration Tests.12.6 Estimation and Inference in Panel Cointegration Models.12.7 Empirical Example: Purchasing Power Parity.12.8 Further Reading.Notes.Problems.References.Index.