Housekeeping genes for quantitative expression studies in the three-spined stickleback Gasterosteus aculeatus

Background During the last years the quantification of immune response under immunological challenges, e.g. parasitation, has been a major focus of research. In this context, the expression of immune response genes in teleost fish has been surveyed for scientific and commercial purposes. Despite the fact that it was shown in teleostei and other taxa that the gene for beta-actin is not the most stably expressed housekeeping gene (HKG), depending on the tissue and experimental treatment, the gene has been us Results To establish a reliable method for the measurement of immune gene expression in Gasterosteus aculeatus, sequences from the now available genome database and an EST library of the same species were used to select oligonucleotide primers for HKG, in order to perform quantitative reverse-transcription (RT) PCR. The expression stability of ten candidate reference genes was evaluated in three different tissues, and in five parasite treatment groups, using the three algorithms BestKeeper, geNorm and N Conclusion As they were the most stably expressed genes in all tissues examined, we suggest using the genes for the L13a ribosomal binding protein and ubiquitin as alternative or additional reference genes in expression analysis in Gasterosteus aculeatus.

Dyrk1A Influences Neuronal Morphogenesis Through Regulation of Cytoskeletal Dynamics in Mammalian Cortical Neurons

Down syndrome (DS) is the most frequent genetic cause of mental retardation. Cognitive dysfunction in these patients is correlated with reduced dendritic branching and complexity, along with fewer spines of abnormal shape that characterize the cortical neuronal profile of DS. DS phenotypes are caused by the disruptive effect of specific trisomic genes. Here, we report that overexpression of dual-specificity tyrosine phosphorylation-regulated kinase 1A, DYRK1A, is sufficient to produce the dendritic alterations observed in DS patients. Engineered changes in Dyrk1A gene dosage in vivo strongly alter the postnatal dendritic arborization processes with a similar progression than in humans. In cultured mammalian cortical neurons, we determined a reduction of neurite outgrowth and synaptogenesis. The mechanism underlying neurite dysgenesia involves changes in the dynamic reorganization of the cytoskeleton

Combinations of Service Use Types of People With Early Cognitive Disorders

Objectives Understanding which persons most likely use particular combinations of service types is important as this could lead to a better understanding of care pathways. The aim of this study is to identify combinations of service use within a sample of community-dwelling people with mild cognitive impairment (MCI) and dementia and identify factors related to these service use combinations. Methods A latent class analysis performed at baseline on a merged dataset (n = 530) was used to classify care recipients based on following service use types: general practitioner visits, physiotherapist visits, hospital outpatient specialist visits, emergency room visits, hospital inpatient visits with stay over, day care visits, use of domestic homecare, use of personal homecare, and informal care on (instrumental) activities of daily living. Multinomial logistic regression was performed to identify factors associated with service use combinations using clinical characteristics of the care recipient and demographic characteristics of the care recipient and caregiver. Results Three service use classes were identified; a formal homecare class (10% of participants), an informal care class (46% of participants), and a low user class (44% of participants). Factors increasing the likelihood of being in the formal homecare class compared with the low service use class included a diagnosis of MCI or dementia, activities of daily living impairment, older age of the care recipient, and care recipient not living together with the caregiver. Conclusions Besides a diagnosis of MCI or dementia, other factors (activities of daily living impairment, age, and living situation) were associated with service use. We recommend using these factors alongside the diagnostic label for care indication

Plasma proteome profiling identifies changes associated to AD but not to FTD

Background Frontotemporal dementia (FTD) is caused by frontotemporal lobar degeneration (FTLD), characterized mainly by inclusions of Tau (FTLD-Tau) or TAR DNA binding43 (FTLD-TDP) proteins. Plasma biomarkers are strongly needed for specific diagnosis and potential treatment monitoring of FTD. We aimed to identify specific FTD plasma biomarker profiles discriminating FTD from AD and controls, and between FTD pathological subtypes. In addition, we compared plasma results with results in post-mortem frontal cortex of FTD cases to understand the underlying process. Methods Plasma proteins (n = 1303) from pathologically and/or genetically confirmed FTD patients (n = 56; FTLD-Tau n = 16; age = 58.2 +/- 6.2; 44% female, FTLD-TDP n = 40; age = 59.8 +/- 7.9; 45% female), AD patients (n = 57; age = 65.5 +/- 8.0; 39% female), and non-demented controls (n = 148; 61.3 +/- 7.9; 41% female) were measured using an aptamer-based proteomic technology (SomaScan). In addition, exploratory analysis in post-mortem frontal brain cortex of FTD (n = 10; FTLD-Tau n = 5; age = 56.2 +/- 6.9, 60% female, and FTLD-TDP n = 5; age = 64.0 +/- 7.7, 60% female) and non-demented controls (n = 4; age = 61.3 +/- 8.1; 75% female) were also performed. Differentially regulated plasma and tissue proteins were identified by global testing adjusting for demographic variables and multiple testing. Logistic lasso regression was used to identify plasma protein panels discriminating FTD from non-demented controls and AD, or FTLD-Tau from FTLD-TDP. Performance of the discriminatory plasma protein panels was based on predictions obtained from bootstrapping with 1000 resampled analysis. Results Overall plasma protein expression profiles differed between FTD, AD and controls (6 proteins; p = 0.005), but none of the plasma proteins was specifically associated to FTD. The overall tissue protein expression profile differed between FTD and controls (7-proteins; p = 0.003). There was no difference in overall plasma or tissue expression profile between FTD subtypes. Regression analysis revealed a panel of 12-plasma proteins discriminating FTD from AD with high accuracy (AUC: 0.99). No plasma protein panels discriminating FTD from controls or FTD pathological subtypes were identified. Conclusions We identified a promising plasma protein panel as a minimally-invasive tool to aid in the differential diagnosis of FTD from AD, which was primarily associated to AD pathophysiology. The lack of plasma profiles specifically associated to FTD or its pathological subtypes might be explained by FTD heterogeneity, calling for FTD studies using large and well-characterize cohorts

Chemokine expression in renal ischemia/reperfusion injury is most profound during the reparative phase

Chemokines are important players in the migration of leukocytes to sites of injury and are also involved in angiogenesis, development and wound healing. In this study, we performed microarray analyses to identify chemokines that play a role during the inflammatory and repair phase after renal ischemia/reperfusion (I/R) injury and investigated the temporal relationship between chemokine expression, leukocyte accumulation and renal damage/repair. C57Bl/6 mice were subjected to unilateral ischemia for 45 min and sacrificed 3 h, 1 day and 7 days after reperfusion. From ischemic and contralateral kidney, RNA was isolated and hybridized to a microarray. Microarray results were validated with quantitative real-time reverse transcription–PCR (QRT–PCR) on RNA from an independent experiment. (Immuno)histochemical analyses were performed to determine renal damage/repair and influx of leukocytes. Twenty out of 114 genes were up-regulated at one or more reperfusion periods. All these genes were up-regulated 7 days after I/R. Up-regulated genes included CC chemokines MCP-1 and TARC, CXC chemokines KC and MIP-2α, chemokine receptors Ccr1 and Cx3cr1 and related genes like matrix metalloproteinases. Microarray data of 1 and 7 days were confirmed for 17 up-regulated genes by QRT–PCR. (Immuno)histochemical analysis showed that the inflammatory and repair phase after renal I/R injury take place after, respectively, 1 and 7 days. Interestingly, chemokine expression was highest during the repair phase. In addition, expression profiles showed a biphasic expression of all up-regulated CXC chemokines coinciding with the early inflammatory and late repair phase. In conclusion, we propose that temporal expression of chemokines is a crucial factor in the regulation of renal I/R injury and repair

GCN2-dependent phosphorylation of eukaryotic translation initiation factor-2α in Arabidopsis

The yeast regulatory protein kinase, general control non-derepressible-2 (GCN2) plays a key role in general amino acid control. GCN2 phosphorylates the α subunit of the trimeric eukaryotic translation initiation factor-2 (eIF2), bringing about a decrease in the general rate of protein synthesis but an increase in the synthesis of GCN4, a transcription factor that promotes the expression of genes encoding enzymes for amino acid biosynthesis. The present study concerned the phosphorylation of Arabidopsis eIF2α (AteIF2α) by the Arabidopsis homologue of GCN2, AtGCN2, and the role of AtGCN2 in regulating genes encoding enzymes of amino acid biosynthesis and responding to virus infection. A null mutant for AtGCN2 called GT8359 was obtained and western analysis confirmed that it lacked AtGCN2 protein. GT8359 was more sensitive than wild-type Arabidopsis to herbicides that affect amino acid biosynthesis. Phosphorylation of AteIF2α occurred in response to herbicide treatment but only in wild-type Arabidopsis, not GT8359, showing it to be AtGCN2-dependent. Expression analysis of genes encoding key enzymes for amino acid biosynthesis and nitrate assimilation revealed little effect of loss of AtGCN2 function in GT8359 except that expression of a nitrate reductase gene, NIA1, was decreased. Analysis of wild-type and GT8359 plants infected with Turnip yellow mosaic virus or Turnip crinkle virus showed that AteIF2α was not phosphorylated

Model based analysis of real-time PCR data from DNA binding dye protocols

BACKGROUND: Reverse transcription followed by real-time PCR is widely used for quantification of specific mRNA, and with the use of double-stranded DNA binding dyes it is becoming a standard for microarray data validation. Despite the kinetic information generated by real-time PCR, most popular analysis methods assume constant amplification efficiency among samples, introducing strong biases when amplification efficiencies are not the same. RESULTS: We present here a new mathematical model based on the classic exponential description of the PCR, but modeling amplification efficiency as a sigmoidal function of the product yield. The model was validated with experimental results and used for the development of a new method for real-time PCR data analysis. This model based method for real-time PCR data analysis showed the best accuracy and precision compared with previous methods when used for quantification of in-silico generated and experimental real-time PCR results. Moreover, the method is suitable for the analyses of samples with similar or dissimilar amplification efficiency. CONCLUSION: The presented method showed the best accuracy and precision. Moreover, it does not depend on calibration curves, making it ideal for fully automated high-throughput applications

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

This work validates the generalizability of MRI-based classification of Alzheimer’s disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI).We used a conventional support vector machine (SVM) and a deep convolutional neural network (CNN) approach based on structural MRI scans that underwent either minimal pre-processing or more extensive pre-processing into modulated gray matter (GM) maps. Classifiers were optimized and evaluated using cross-validation in the Alzheimer’s Disease Neuroimaging Initiative (ADNI; 334 AD, 520 CN). Trained classifiers were subsequently applied to predict conversion to AD in ADNI MCI patients (231 converters, 628 non-converters) and in the independent Health-RI Parelsnoer Neurodegenerative Diseases Biobank data set. From this multi-center study representing a tertiary memory clinic population, we included 199 AD patients, 139 participants with subjective cognitive decline, 48 MCI patients converting to dementia, and 91 MCI patients who did not convert to dementia.AD-CN classification based on modulated GM maps resulted in a similar area-under-the-curve (AUC) for SVM (0.940; 95%CI: 0.924–0.955) and CNN (0.933; 95%CI: 0.918–0.948). Application to conversion prediction in MCI yielded significantly higher performance for SVM (AUC = 0.756; 95%CI: 0.720-0.788) than for CNN (AUC = 0.742; 95%CI: 0.709-0.776) (p<0.01 for McNemar’s test). In external validation, performance was slightly decreased. For AD-CN, it again gave similar AUCs for SVM (0.896; 95%CI: 0.855–0.932) and CNN (0.876; 95%CI: 0.836–0.913). For prediction in MCI, performances decreased for both SVM (AUC = 0.665; 95%CI: 0.576-0.760) and CNN (AUC = 0.702; 95%CI: 0.624-0.786). Both with SVM and CNN, classification based on modulated GM maps significantly outperformed classification based on minimally processed images (p=0.01).Deep and conventional classifiers performed equally well for AD classification and their performance decreased only slightly when applied to the external cohort. We expect that this work on external validation contributes towards translation of machine learning to clinical practice