Quantitative detection of grey and white matter amyloid pathology using a combination of K114 and CRANAD-3 fluorescence

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease that exacts a huge toll on the patient, the healthcare system and society in general. Abundance and morphology of protein aggregates such as amyloid β plaques and tau tangles, along with cortical atrophy and gliosis are used as measures to assess the changes in the brain induced by the disease. Not all of these parameters have a direct correlation with cognitive decline. Studies have shown that only particular protein conformers can be the main drivers of disease progression, and conventional approaches are unable to distinguish different conformations of disease-relevant proteins. METHODS AND RESULTS: Using the fluorescent amyloid probes K114 and CRANAD-3 and spectral confocal microscopy, we examined formalin-fixed paraffin-embedded brain samples from different control and AD cases. Based on the emission spectra of the probes used in this study, we found that certain spectral signatures can be correlated with different aggregates formed by different proteins. The combination of spectral imaging and advanced image analysis tools allowed us to detect variability of protein deposits across the samples. CONCLUSION: Our proposed method offers a quicker and easier neuropathological assessment of tissue samples, as well as introducing an additional parameter by which protein aggregates can be discriminated

Characterization of gene expression on genomic segment 7 of infectious salmon anaemia virus

BACKGROUND: Infectious salmon anaemia (ISA) virus (ISAV), an important pathogen of fish that causes disease accompanied by high mortality in marine-farmed Atlantic salmon, is the only species in the genus Isavirus, one of the five genera of the Orthomyxoviridae family. The Isavirus genome consists of eight single-stranded RNA species, and the virions have two surface glycoproteins; haemagglutinin-esterase (HE) protein encoded on segment 6 and fusion (F) protein encoded on segment 5. Based on the initial demonstration of two 5'-coterminal mRNA transcripts by RT-PCR, ISAV genomic segment 7 was suggested to share a similar coding strategy with segment 7 of influenza A virus, encoding two proteins. However, there appears to be confusion as to the protein sizes predicted from the two open reading frames (ORFs) of ISAV segment 7 which has in turn led to confusion of the predicted protein functions. The primary goal of the present work was to clone and express these two ORFs in order to assess whether the predicted protein sizes match those of the expressed proteins so as to clarify the coding assignments, and thereby identify any additional structural proteins of ISAV. RESULTS: In the present study we show that ISAV segment 7 encodes 3 proteins with estimated molecular masses of 32, 18, and 9.5 kDa. The 18-kDa and 9.5-kDa products are based on removal of an intron each from the primary transcript (7-ORF1) so that the translation continues in the +2 and +3 reading frames, respectively. The segment 7-ORF1/3 product is variably truncated in the sequence of ISAV isolates of the European genotype. All three proteins are recognized by rabbit antiserum against the 32-kDa product of the primary transcript, as they all share the N-terminal 22 amino acids. This antiserum detected a single 35-kDa protein in Western blots of purified virus, and immunoprecipitated a 32-kDa protein in ISAV-infected TO cells. Immunofluorescence staining of infected cells with the same antiserum revealed the protein(s) to be localized in the cytoplasm. Vaccination of farmed Atlantic salmon with the 32-kDa protein resulted in a higher survival rate than what was attainable with the HE protein, albeit a moderate protection against the low ISAV challenge. CONCLUSION: Collectively, our observations suggest that the product of ISAV segment 7 primary transcript (7-ORF1) is a structural protein. The 18-kDa (7-ORF1/2) protein is identified as the putative ISAV nuclear export protein based on the presence of nuclear export signals. The function of the 9.5-kDa (7-ORF1/3) protein is not presently known

Spatiotemporal information transfer pattern differences in motor selection

Analysis of information transfer between variables in brain images is currently a popular topic, e.g. [1]. Such work typically focuses on average information transfer (i.e. transfer entropy [2]), yet the dynamics of transfer from a source to a destination can also be quantified at individual time points using the local transfer entropy (TE) [3]. This local perspective is known to reveal dynamical structure that the average cannot. We present a method to quantify local TE values in time between source and destination regions of variables in brain-imaging data, combining: a. computation of inter-regional transfer between two regions of variables (e.g. voxels) [1], with b. the local perspective of the dynamics of such transfer in time [3]. Transfer is computed over samples from all variables – there is no training in or subset selection of variables to use. We apply this method to a set of fMRI measurements where we could expect to see differences in local information transfer between two conditions at specific time steps. The fMRI data set analyzed (from [4]) contains brain activity recorded from 7 localized regions while 12 subjects (who gave informed written consent) were asked to freely decide whether to pus

Decreased total antioxidant levels and increased oxidative stress in South African type 2 diabetes mellitus patients

Background: Chronic hyperglycaemia in diabetes mellitus leads to increased lipid peroxidation in the body, followed by the development of chronic complications due to oxidative stress. Objective: The aim of this study was to compare total antioxidant (TAO) levels and oxidative stress in type 2 diabetes mellitus (T2DM) patients with that of healthy controls without diabetes.Methods: A total of 98 participants (57 T2DM and 41 healthy people) gave their consent and participated in the study. Routine biochemical methods were used for fasting plasma glucose (FPG), glycosylated haemoglobin (HbA1c) and lipid profile measurements. Serum TAO levels, malondialdehyde (MDA), oxidised low-density lipoprotein (ox-LDL) levels and superoxide dismutase (SOD) activity were analysed using standard commercial reagent kits.Results: A significant rise in FPG, HbA1c, triglycerides, MDA and ox-LDL, and a significant reduction in TAO and high-density lipoprotein cholesterol (HDL-C) was observed in T2DM patients compared with controls. A significant negative relationship was observed between TAO levels and MDA levels in the T2DM group. Increased lipid peroxidation and reduced antioxidant levels were observed in T2DM patients.Conclusion: Early management through an antioxidant-rich diet and lifestyle changes in T2DM patients would help to avert the debilitating complications of diabetes.Keywords: diabetes mellitus, oxidative stress, total antioxidant statu

African forest elephant movements depend on time scale and individual behavior.

The critically endangered African forest elephant (Loxodonta cyclotis) plays a vital role in maintaining the structure and composition of Afrotropical forests, but basic information is lacking regarding the drivers of elephant movement and behavior at landscape scales. We use GPS location data from 96 individuals throughout Gabon to determine how five movement behaviors vary at different scales, how they are influenced by anthropogenic and environmental covariates, and to assess evidence for behavioral syndromes-elephants which share suites of similar movement traits. Elephants show some evidence of behavioral syndromes along an 'idler' to 'explorer' axis-individuals that move more have larger home ranges and engage in more 'exploratory' movements. However, within these groups, forest elephants express remarkable inter-individual variation in movement behaviours. This variation highlights that no two elephants are the same and creates challenges for practitioners aiming to design conservation initiatives

Differential expression analysis with global network adjustment

<p>Background: Large-scale chromosomal deletions or other non-specific perturbations of the transcriptome can alter the expression of hundreds or thousands of genes, and it is of biological interest to understand which genes are most profoundly affected. We present a method for predicting a gene’s expression as a function of other genes thereby accounting for the effect of transcriptional regulation that confounds the identification of genes differentially expressed relative to a regulatory network. The challenge in constructing such models is that the number of possible regulator transcripts within a global network is on the order of thousands, and the number of biological samples is typically on the order of 10. Nevertheless, there are large gene expression databases that can be used to construct networks that could be helpful in modeling transcriptional regulation in smaller experiments.</p> <p>Results: We demonstrate a type of penalized regression model that can be estimated from large gene expression databases, and then applied to smaller experiments. The ridge parameter is selected by minimizing the cross-validation error of the predictions in the independent out-sample. This tends to increase the model stability and leads to a much greater degree of parameter shrinkage, but the resulting biased estimation is mitigated by a second round of regression. Nevertheless, the proposed computationally efficient “over-shrinkage” method outperforms previously used LASSO-based techniques. In two independent datasets, we find that the median proportion of explained variability in expression is approximately 25%, and this results in a substantial increase in the signal-to-noise ratio allowing more powerful inferences on differential gene expression leading to biologically intuitive findings. We also show that a large proportion of gene dependencies are conditional on the biological state, which would be impossible with standard differential expression methods.</p> <p>Conclusions: By adjusting for the effects of the global network on individual genes, both the sensitivity and reliability of differential expression measures are greatly improved.</p&gt

Inactivation of Ppp1r15a minimises weight gain and insulin resistance during caloric excess in female mice.

Phosphorylation of the translation initiation factor eIF2α within the mediobasal hypothalamus is known to suppress food intake, but the role of the eIF2α phosphatases in regulating body weight is poorly understood. Mice deficient in active PPP1R15A, a stress-inducible eIF2α phosphatase, are healthy and more resistant to endoplasmic reticulum stress than wild type controls. We report that when female Ppp1r15a mutant mice are fed a high fat diet they gain less weight than wild type littermates owing to reduced food intake. This results in healthy leaner Ppp1r15a mutant animals with reduced hepatic steatosis and improved insulin sensitivity, albeit with a possible modest defect in insulin secretion. By contrast, no weight differences are observed between wild type and Ppp1r15a deficient mice fed a standard diet. We conclude that female mice lacking the C-terminal PP1-binding domain of PPP1R15A show reduced dietary intake and preserved glucose tolerance. Our data indicate that this results in reduced weight gain and protection from diet-induced obesity.The work was also supported by Diabetes UK and the MRC [G1002610]. VP held an Arthur and Sadie Pethybridge PhD Studentship from Diabetes UK. The CIMR microscopy core facility is supported by a Wellcome Trust Strategic Award [100140] and a Wellcome Trust equipment grant [093026]