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- Codita, Alina
(författare)
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Automated behavioral phenotyping of inbred mouse strains and mouse models of Alzheimer disease
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Behavioral characterization of various mouse strains created as models for human diseases such as Alzheimer disease requires robust phenotyping methods. Previous work on inbred mouse strains has shown that some of the widely used behavioral methods yield inconsistent results across laboratories, in spite of standardization efforts. One approach to minimize experimenter induced variability relies on development of automated methods. The aims of this thesis were to evaluate an automated device - the IntelliCage - which enables behavioral testing of group-housed mice. In a multi-center study, inter- laboratory consistency of behavioral measurements in IntelliCage was evaluated [study I]. Three strains of mice: C57BL/6NCrl (B6), DBA/2NCrl (D2) and (C57BL/6 x DBA/2) F1/NCrl (C6D2F1) were tested simultaneously in four laboratories (n=78/lab). No statistically significant interaction effect of Laboratory x Strain was obtained, indicating that strains were consistently ranked across laboratories. Significant Laboratory effects were obtained for several Activity and Learning variables due to uncontrolled local factors. Phenotypically, the mouse strains were not discriminated during the initial exploratory phase. During the following adaptation phases the B6 mice made more visits to IntelliCage corners than the D2 mice. For unconditioned phases, the visit number for F1 mice was between that of the inbred strains. For conditioned phases F1 mice performed the smallest number of visits. B6 mice discriminated best following place learning and D2 were best at re-learning the task. F1 ranked last on both place learning and reversal measures of learning. Using the same multi-center study design and the same mouse strains, we evaluated the effect of additional components (add-ons) availability on IntelliCage measures [study II]. In the enriched condition (IntelliMaze) access to additional space was made through the “SocialBox” and “AnimalGate” add-on devices. The unconditioned activity during adaptation dark phases was reduced in the presence of add-ons. During the place conditioning paradigms, the overall number of trials needed to reach the learning criterion, was lower in the presence of add-ons. The strain ranks for activity measures were consistent with the results of study I. Dissociation in cognitive abilities of B6 and D2 mice has been proposed as a natural model to study hippocampal (dys)function. Behavioral predictive validity of animal models for Alzheimer disease is implied by impairments in hippocampal dependent tasks. In study III, a double transgenic Amyloid precursor protein model of Alzheiemer disease, (the tg-ArcSwe) was tested longitudinally in the IntelliCage. Lower body weight was found throughout the adult life-span of the tg-APPArcSwe mice. Lower activity counts were seen at 4 month of age, but not at 14 months. A deficit in extinguishing place preference for a previously rewarded corner at 4 month was shown. At 14 months the tg-APPArcSwe mice were impaired in a passive avoidance test in the IntelliCage. During the training phase of the passive avoidance test the behavior (preference for the punished corner) of tg-ArcSwe was found to moderately and inversely correlate with the level of CALB immunoreactivity in the polymorphic layer of the DG. Finally, the effects of IntelliCage exposure as well as relationships between variables obtained during IntelliCage testing and Elevated Plus Maze, Open field, Rotarod, Morris Water Maze and Fear conditioning were explored [study IV]. We found that only a limited amount of variance in the conventional tests could be accounted for by IntelliCage variables. In conclusion we have shown that mouse strains can be discriminated using the IntelliCage. Similarly, the behavior of tg-ArcSwe and non-tg mice was dissociated by this metholodogy. Although some degree of correlation was found between the results of conventional studies and IntelliCage variables, only a small part of the variance in conventional studies was explained by variables obtained in the IntelliCage.
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| 3. |
- Christensen, Jorgen Tornhöj
(författare)
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Komfort IC3
- 1996
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Ingår i: Samverkan fordon - bana. - Linköping : Statens väg- och transportforskningsinstitut. ; , s. 29-51
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)
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| 4. |
- DOrazio, Paul, et al.
(författare)
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Approved IFCC recommendation on reporting results for blood glucose (abbreviated)
- 2005
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Ingår i: Clinical Chemistry. - : Oxford University Press (OUP). - 0009-9147 .- 1530-8561. ; 51:9, s. 1573-1576
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Tidskriftsartikel (refereegranskat)abstract
- In current clinical practice, plasma and blood glucose are used interchangeably with a consequent risk of clinical misinterpretation. In human blood, glucose, like water, is distributed between erythrocytes and plasma. The molality of glucose (amount of glucose per unit of water mass) is the same throughout the sample, but the concentration is higher in plasma because the concentration of water and, therefore, glucose is higher in plasma than in erythrocytes. Different devices for the measurement of glucose may detect and report fundamentally different quantities. Different water concentrations in calibrators, plasma, and erythrocyte fluid can explain some of the differences. Results of glucose measurements depend on sample type and on whether methods require sample dilution or use biosensors in undiluted samples. If the results are mixed up or used indiscriminately, the differences may exceed the maximum allowable error of glucose determinations for diagnosing and monitoring diabetes mellitus, and complicate the treatment. The goal of the IFCC Scientific Division Working Group on Selective Electrodes and Point of Care Testing (IFCC-SD, WG-SEPOCT) is to reach a global consensus on reporting results. The document recommends reporting the concentration of glucose in plasma (with the unit mmol/L), irrespective of sample type or measurement technique. A constant factor of 1.11 is used to convert concentration in whole blood to the equivalent concentration in the pertinent plasma. The conversion will provide harmonized results, facilitating the classification and care of patients and leading to fewer therapeutic misjudgments. © 2005 American Association for Clinical Chemistry.
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