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 Origins of Intergenerational Associations: Lessons from Swedish Adoption Data

Abstract: We use unique Swedish data with information on adopted children's biological and adoptive parents to estimate intergenerational mobility associations in earnings and education. We argue that the impact from biological parents captures broad prebirth factors, including genes and prenatal environment, and the impact from adoptive parents represents broad postbirth factors, such as childhood environment. We find that both pre- and postbirth factors contribute to intergenerational earnings and education transmissions, and that prebirth factors are more important for mother's education and less important for father's income. We also find some evidence for a positive interaction effect between postbirth environment and prebirth factors.

Cell Therapy in Parkinson's Disease

Abstract: The clinical studies with intrastriatal transplants of fetal mesencephalic tissue in Parkinson’s disease (PD) patients have provided proof-of-principle for the cell replacement strategy in this disorder. The grafted dopaminergic neurons can reinnervate the denervated striatum, restore regulated dopamine (DA) release and movement-related frontal cortical activation, and give rise to significant symptomatic relief. In the most successful cases, patients have been able to withdrawl-dopa treatment after transplantation and resume an independent life. However, there are currently several problems linked to the use of fetal tissue: 1) lack of sufficient amounts of tissue for transplantation in a large number of patients, 2) variability of functional outcome with some patients showing major improvement and others modest if any clinical benefit, and 3) occurrence of troublesome dyskinesias in a significant proportion of patients after transplantation. Thus, neural transplantation is still at an experimental stage in PD. For the development of a clinically useful cell therapy, we need to define better criteria for patient selection and how graft placement should be optimized in each patient. We also need to explore in more detail the importance for functional outcome of the dissection and cellular composition of the graft tissue as well as of immunological mechanisms. Strategies to prevent the development of dyskinesias after grafting have to be developed. Finally, we need to generate large numbers of viable DA neurons in preparations that are standardized and quality controlled. The stem cell technology may provide a virtually unlimited source of DA neurons, but several scientific issues need to be addressed before stem cell-based therapies can be tested in PD patients.

Function recovery following neural transplantation of embryonic septal nuclei in adult rats with septohippocampal lesions

Abstract: The remarkable capacity of transplanted embryonic neurones to innervate the hippocampal formation of mature recipients has been well documented, with the pattern of innervation being shown to be anatomically specific and to resemble normal connectivity1–3. Although transplants are known to have functional consequences in other systems4–9, information has yet to be obtained regarding the functional nature of embryonic septal transplants and the behavioural consequences of transplant innervation of the host hippocampal formation. We provide here evidence that a reinnervation of the hippocampal formation from cholinergic-rich septal transplants is functional in terms of the physiology of neural connectivity and that the newly formed connections can interact with an intrinsic afferent system, the perforant path. Moreover, we demonstrate that the reinnervation can aid in the partial recovery of the performance of a radial maze task that is thought to depend on the integrity of septohippocampal connections10. The behavioural performance of animals with transplants improved significantly compared with those without transplants when both groups were systemically injected with the acetylcholinesterase (AChE) inhibitor, physostigmine. These results suggest that neural transplants from embryonic tissue that reinnervate the hippocampal formation can form functional synaptic connections that can lead to the partial restoration of maze performance.

The adrenergic innervation of the rat thalamus as revealed by the glyoxylic acid fluorescence method

Abstract: The adrenergic innervation of the thalamus, epithalamus, metathalamus, and subthalamus in the rat has been investigated by means of the recently introduced glyoxylic acid fluorescence method. Many areas of the thalamus and adjoining regions, that appear sparsely innervated by catecholamine (CA) fibers in specimens processed according to the standard Falck-Hillarp formaldehyde method, were found to be richly supplied with such fibres in the glyoxylic acid-treated specimens. Moreover, the glyoxylic acid method allows the tracing of the CA axons from the cell bodies up to the terminals, and in combination with stereotaxic lesions the following CA systems to the thalamus could be established: 1 The locus coeruleus system. Most of these axons ascend in the so-called dorsal tegmental bundle through the mesencephalon and the zona incerta into the medial forebrain bundle. From this bundle branches were traced along several routes, giving rise to extensive terminal systems in many thalamic, metathalamic and pretectal areas, most notably the anterior, ventral and lateral nuclear complexes, and the medial and lateral geniculate bodies. 2 The dorsal periventricular bundle, which constitutes a previously not described adrenergic component of the dorsal longitudinal fasciculus. This system originates in cell bodies (defined as the A11 cell group) in the dorsal raphe region, the central gray of the mesencephalon, and in the periventricular gray of the caudal thalamus. The axons ascend within the dorsal longitudinal fasciculus and give rise to a thalamic and hypothalamic periventricular system, projecting to medial and midline thalamic, epithalamic and pretectal regions. 3 Part of the terminals in the paraventricular thalamic nucleus was identified with a non-locus projection from cell bodies in the pontine or medullary reticular formation. 4 A system of delicate, probably dopamine-containing axons was revealed in the caudal thalamus, the zona incerta and the dorsal and anterior hypothalamus. This system probably originates in the dopamine cell bodies of the diencephalic A11 and A13 cell groups, forming a hitherto unknown intradiencephalic dopaminergic system. The adrenergic afferent systems to the thalamus can, to a large extent, be regarded as adrenergic components of known ascending reticular projections. The information on the adrenergic systems obtained with the glyoxylic acid method revealed new features of the organization of the thalamic projections from the brain stem reticular formation.

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.