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.

The Amphetamine Induced Rotation Test: A Re-Assessment of Its Use as a Tool to Monitor Motor Impairment and Functional Recovery in Rodent Models of Parkinson's Disease.

Abstract: Rats and mice with unilateral damage to the nigrostriatal dopamine system-induced by neurotoxins, such as 6-hydroxydopamine, overexpression of α-synuclein, or injections of toxic synuclein protofibrils-are widely used as experimental models to mimic the loss of dopamine neurons seen in Parkinson's disease. The amphetamine rotation test is commonly used to monitor the extent of motor impairment induced by the lesion, and this test has also become the standard tool to demonstrate transplant-induced functional recovery or the efficacy of neuroprotective interventions aimed to preserve or restore DA neuron function. Although the amphetamine-induced rotation test is highly useful for this purpose it has some important pitfalls and the interpretation of the data may not always be straightforward. Unless the test is applied properly and the data are displayed and interpreted appropriately the conclusions may be misleading or simply totally wrong. The purpose of this review is to draw attention to the potential problems and pitfalls involved in the use of drug-induced rotation tests, and to provide recommendations and advice on how to avoid them.

The Meso-Telencephalic Dopamine Neuron System: A Review of Its Anatomy

Abstract: The unmyelinated and sparsely myelinated fibre systems probably comprise the vast majority of connections in the central nervous system. Until the staining methods for degenerating fibres were introduced, their anatomy was, however, virtually unknown. The subsequent development of a new arsenal of histochemical and autoradio-graphic tracing techniques has meant a mere revolution in our understanding of the organization of many functional systems in the brain, not least the limbic system.

Dopamine neurons grafted unilaterally to the nucleus accumbens affect drug-induced circling and locomotion.

Abstract: The purpose of the present study was to investigate the amplifying function of the nucleus accumbens septi region (NAS) in 6-hydroxydopamine (6-OHDA)-induced rotational behaviour by implanting fetal dopamine (DA)-rich mesencephalic cell suspensions unilaterally in the NAS of rats previously subjected to combined mesostriatal (MS) and NAS 6-OHDA lesions. First, all the rats received a unilateral 6-OHDA lesion of the ascending MS DA pathway, which produced an amphetamine-induced rotational asymmetry towards the lesioned side. In a second step, the rats received a local bilateral 6-OHDA lesion of the NAS which, as previously shown, caused a significant attenuation of the amphetamine-induced locomotor (1.5 mg/kg) and rotational (5 mg/kg) behaviour. Finally, some of these MS + NAS lesioned rats received a unilateral mesencephalic DA graft into the NAS ipsilateral to the original MS lesion. The unilateral DA-rich grafts in the NAS significantly elevated the amphetamine-induced locomotion and ipsilateral circling (opposite to the direction of rotation produced when a graft is placed in the ipsilateral caudate-putamen), suggesting that the NAS plays only an amplifier role in locomotor behaviour and not a directional role. In addition, these grafts significantly attenuated the supersensitive locomotor response observed in lesioned rats when given apomorphine (0.05 mg/kg). The findings emphasize the amplifying role of the NAS in locomotion and circling behaviour and they extend previous findings demonstrating the functional heterogeneity of the striatal complex as well as the regional specificity of the graft-derived functional effects. Moreover, the results argue against the notion that DA grafts can function through a diffusion of transmitter over large distances since, despite the large size of the grafts, the functional graft effects were well localized to the reinnervated NAS and ventromedial striatal regions. We conclude, therefore, that graft-induced amelioration of postural and locomotor deficits are affected through different parts of the striatal complex, and that multiple graft placements are required to produce more complete recovery of motoric behaviour in the DA-depleted brain.

GDNF and Parkinson’s Disease: Where Next? A Summary from a Recent Workshop

Abstract: The concept of repairing the brain with growth factors has been pursued for many years in a variety of neurodegenerative diseases including primarily Parkinson's disease (PD) using glial cell line-derived neurotrophic factor (GDNF). This neurotrophic factor was discovered in 1993 and shown to have selective effects on promoting survival and regeneration of certain populations of neurons including the dopaminergic nigrostriatal pathway. These observations led to a series of clinical trials in PD patients including using infusions or gene delivery of GDNF or the related growth factor, neurturin (NRTN). Initial studies, some of which were open label, suggested that this approach could be of value in PD when the agent was injected into the putamen rather than the cerebral ventricles. In subsequent double-blind, placebo-controlled trials, the most recent reporting in 2019, treatment with GDNF did not achieve its primary end point. As a result, there has been uncertainty as to whether GDNF (and by extrapolation, related GDNF family neurotrophic factors) has merit in the future treatment of PD. To critically appraise the existing work and its future, a special workshop was held to discuss and debate this issue. This paper is a summary of that meeting with recommendations on whether there is a future for this therapeutic approach and also what any future PD trial involving GDNF and other GDNF family neurotrophic factors should consider in its design.

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.