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.

Reversal of spatial memory impairments in aged rats by nerve growth factor and neurotrophins 3 and 4/5 but not by brain-derived neurotrophic factor

Abstract: Aged rats, displaying impairments in spatial learning and memory associated with marked cellular atrophy of forebrain cholinergic neurons, received intracerebroventricular infusions of one of the four neurotrophins nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF), neurotrophin 3 (NT-3), or neurotrophin 4/5 (NT-4/5), or a combination of NGF and BDNF, or vehicle. During the 4-week infusion period rats receiving NGF, NT-3, or NT-4/5 showed improved acquisition and retention of spatial memory. With NGF and NT-3, but not NT-4/5, this was accompanied by a significant reduction in cholinergic neuron atrophy in septum, nucleus basalis, and striatum. BDNF, in contrast, was without effect either alone or in combination with NGF. These results show that memory deficits associated with aging can be reversed by several members of the neurotrophin family and that this effect may be mediated through activation of multiple neurotrophin receptors associated with cholinergic and possibly noncholinergic systems in the brain.

Hippocampal Noradrenaline and Serotonin Release over 24 Hours as Measured by the Dialysis Technique in Freely Moving Rats: Correlation to Behavioural Activity State, Effect of Handling and Tail-Pinch

Abstract: Hippocampal extracellular levels of noradrenaline (NA), 5-hydroxytryptamine (5-HT), and 5-hydroxyindoleacetic acid (5-HIAA) were monitored with the microdialysis technique in freely moving rats. In one experiment 30 min samples were collected during 24 h of continuous perfusion, and the monoamine output was compared to the behavioural activity state, as arbitrarily classified in three categories: sleep/rest, drowsiness and full alertness associated with complex behaviours. In the individual animal the hippocampal NA and 5-HT output showed pronounced fluctuations during the 24 h period, but the 30 min sampling times did not allow for a clear-cut correlation to behavioural activity state. However, the mean NA and 5-HT output for all animals during the dark period of the day was 43 and 38% higher, respectively, than during the light period, and the average NA and 5-HT levels in samples collected during periods of high behavioural activity was 34 and 45% higher, respectively, than during periods of rest or sleep. In contrast, there were no detectable changes in extracellular 5-HIAA. The selective serotonin uptake blocker indalpine, added to the perfusion fluid at 1 microM, increased the extracellular 5-HT levels 6-fold, with a similar correlation to behavioural activity state as without indalpine. In a second experiment the effect of handling and tail-pinch was studied in 15 min sample fractions. Gentle handling of the animals during the sampling period increased the hippocampal NA and 5-HT output by 32 and 72%, respectively, and a similar increase (63 and 48%) was obtained by application of tail-pinch. Maximum NA output was reached during the handling or tail-pinch period, whereas maximal 5-HT levels were detected in the subsequent 15 min sample fraction. No changes in extracellular 5-HIAA was observed. It is concluded (1) that intracerebral microdialysis provides a useful method for the study of extracellular NA and 5-HT in the hippocampal formation of conscious rats during active behaviour; (2) that there are substantial fluctuations in hippocampal NA and 5-HT output in freely moving rats which correlate with the light - dark cycle as well as with the activity state of the animals; (3) that the spontaneous variations in 5-HT output are maintained during reuptake blockade; and (4) that behavioural activation through gentle handling or tail-pinch elicits NA and 5-HT release. The present data support a role of the forebrain NA and 5-HT systems in behavioural state control and highlights the necessity of experimental designs in which the spontaneous fluctuations in transmitter release are controlled for in studies of, for example, drug effects on NA and 5-HT release in conscious animals.

A comparison between actual distributions of annual and lifetime income: sweden 1951–89

Abstract: This paper uses register data on tax assessed income from 1951 to 1989 for a representative sample of Swedish men in order to compare the distributions of annual income and “lifetime” income. It is found that the dispersion of lifetime income is around 35 to 40 percent lower than typical cross-sections of annual income. It is income up to around 30 years of age that mainly explains this discrepancy in the magnitude of dispersions. From the age of 30 until 65 years the correlations between annual and lifetime income are quite high and the dispersion of annual income is not very much higher than the dispersion of lifetime income. An analysis of the evolution of income mobility shows that there is a slight tendency to rising mobility over time. This finding implies that the common approach to study the development of income distribution by using only annual income can be misleading.

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.