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.

In utero gene transfer reveals survival effects of nerve growth factor on rat brain cholinergic neurones during development

Abstract: Nerve growth factor (NGF) is a maintenance factor for cholinergic neurones in the brain, but its properties as a developmental survival factor are largely unknown. The low accessibility of the developing mammalian brain to experimental manipulation makes it difficult to increase NGF levels during the early phases of brain development. In the present study we have used an in utero, ex-vivo gene transfer approach to explore NGF actions during development of the cholinergic system in the rat brain. Significantly increased numbers of cholinergic neurones were found only in the mesopontine complex in animals receiving NGF-secreting transplants, whereas the cholinergic neurones in the basal forebrain and striatum were not clearly affected. The present results suggest that overexpression of NGF during development may promote the survival of distinct populations of central cholinergic neurones into adulthood.

Release of acetylcholine and its dopaminergic control in slices from striatal grafts in the ibotenic acid-lesioned rat striatum.

Abstract: Tritium accumulation during incubation with 3-H-choline, and the efflux as well as the electrically evoked overflow of tritium during subsequent superfusion, were investigated in slices from unilateral striatal suspension grafts 16 to 20 weeks after implantation into the previously ibotenic acid-lesioned rat striatum Slices from non-operated animals, from striata contralateral to grafts, and from animals with acute ibotenic acid lesions of the striatum were studied in parallel The accumulation of tritium and the overflow of tritium in response to electrical stimulation (2 min, 3 Hz) were markedly impaired in acutely lesioned striata In graft slices, tritium accumulation and the subsequent electrically evoked overflow were greater than in slices obtained after acute lesions, but were still smaller than in non-operated animals or in the contralateral striata The dopamine D2-receptor agonist quinpirole inhibited the electrically evoked overflow of tritium in grafts, but only to a small extent The D2-receptor antagonist sulpiride increased, whereas the dopamine uptake inhibitor nomifensine and the dopamine releasing drug amphetamine decreased the evoked overflow in slices from non-operated rats and from striata contralateral to grafts, but had no significant effect in grafts As in graft slices, the release of acetylcholine in striata from animals in which the mesostriatal dopamine pathway had been lesioned by 6-hydroxy-dopamine was not changed by sulpiride and amphetamine, and was only minimally decreased by nomifensine Our data show that striato-striatal grafts can partly restore the impaired choline accumulation and acetylcholine release in excitotoxinlesioned striata Functional D2-receptors are present on graft cholinergic cells, but are not activated by endogenous dopamine under the present in vitro conditions

Transgenic reporter mice as tools for studies of transplantability and connectivity of dopamine neuron precursors in fetal tissue grafts.

Abstract: Cell therapy for Parkinson's disease (PD) is based on the idea that new midbrain dopamine (mDA) neurons, implanted directly into the brain of the patient, can structurally and functionally replace those lost to the disease. Clinical trials have provided proof-of-principle that the grafted mDA neurons can survive and function after implantation in order to provide sustained improvement in motor function for some patients. Nonetheless, there are a number of issues limiting the application of this approach as mainstream therapy, including: the use of human fetal tissue as the only safe and reliable source of transplantable mDA neurons, and variability in the therapeutic outcome. Here we review recent progress in this area from investigations using rodent models of PD, paying particular attention to the use of transgenic reporter mice as tools for neural transplantation studies. Cell type-specific expression of reporter genes, such as green fluorescent protein, affords valuable technical advantages in transplantation experiments, such as the ability to selectively isolate specific cell fractions from mixed populations prior to grafting, and the unambiguous visualization of graft-derived dopamine neuron fiber patterns after transplantation. The results from these investigations have given new insights into the transplantability of mDA precursors as well as their connectivity after grafting and have interesting implications for the development of stem cell based approaches for the treatment of PD.

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.