An evaluation of fixation methods: Spatial and compositional cellular changes observed by Raman imaging

AbstractAlthough live cell imaging is desirable, it is not always feasible and in many situations cells are fixed in order to provide a ‘snapshot’ of the nature and distribution of molecules within a cell while minimising changes from cell movement, sample degradation etc. There is a wide range of fixation methods available that act via different mechanisms, and on different cell components. Each method has advantages and disadvantages and a choice of what fixation method to choose for a particular experiment needs to take these factors into consideration. Here we used Raman spectroscopic imaging of live cells, and compared with cells preserved with aldehyde, or organic solvent-based fixation methods to assess the chemical changes induced by each fixative, and their impact on the quality of images that can be obtained from fixed cells. Overall, aldehyde fixation methods performed significantly better than organic solvents with less severe loss of biochemical information. Aldehyde based fixatives show an altered biochemical content of the cells, attributed to adduct formation, but this can be minimised by optimising fixation temperature, or through removal of adduct formation by detergent-based permeabilization treatments as a second step (at the cost of the loss of other biochemical information). The results showed that organic solvents, on the other hand, lead to a severe loss of cell content, attributed to the loss of membrane integrity after the removal of lipids. Additionally, fixation with aldehydes prior to permeabilization with organic solvents does not provide adequate protection of cytoplasmic content. The use of Raman imaging is ideal for comparing groups of cells in terms of their molecular content, and the results show that aldehyde fixations methods are preferable for studies where the overall molecular content of the samples is important. Although there is no universal fixation method for every application, the results here allow us to provide a few general principles: where spectral similarity to live cells is important, fixation with paraformaldehyde at room temperature is preferable, at the cost of some blebbing and vacuole formation. Where preservation of cellular structure or biomolecular distribution is important, a mix of paraformaldehyde and glutaraldehyde would be more appropriate, but at the cost of some changes to spectral profile, particularly in DNA-related bands

The effect of colour vision status on the detection and selection of fruits by tamarins (Saguinus spp.)

The evolution of trichromatic colour vision by the majority of anthropoid primates has been linked to the efficient detection and selection of food, particularly ripe fruits among leaves in dappled light. Modelling of visual signals has shown that trichromats should be more efficient than dichromats at distinguishing both fruits from leaves and ripe from unripe fruits. This prediction is tested in a controlled captive setting using stimuli recreated from those actually encountered by wild tamarins (Saguinus spp.). Dietary data and reflectance spectra of Abuta fluminum fruits eaten by wild saddleback (Saguinus fuscicollis) and moustached (Saguinus mystax) tamarins and their associated leaves were collected in Peru. A. fluminum leaves, and fruits in three stages of ripeness, were reproduced and presented to captive saddleback and red-bellied tamarins (Saguinus labiatus). Trichromats were quicker to learn the task and were more efficient at selecting ripe fruits than were dichromats. This is the first time that a trichromatic foraging advantage has been demonstrated for monkeys using naturalistic stimuli with the same chromatic properties as those encountered by wild animal

Identification of host transcriptional networks showing concentration-dependent regulation by HPV16 E6 and E7 proteins in basal cervical squamous epithelial cells.

Development of cervical squamous cell carcinoma requires increased expression of the major high-risk human-papillomavirus (HPV) oncogenes E6 and E7 in basal cervical epithelial cells. We used a systems biology approach to identify host transcriptional networks in such cells and study the concentration-dependent changes produced by HPV16-E6 and -E7 oncoproteins. We investigated sample sets derived from the W12 model of cervical neoplastic progression, for which high quality phenotype/genotype data were available. We defined a gene co-expression matrix containing a small number of highly-connected hub nodes that controlled large numbers of downstream genes (regulons), indicating the scale-free nature of host gene co-expression in W12. We identified a small number of 'master regulators' for which downstream effector genes were significantly associated with protein levels of HPV16 E6 (n = 7) or HPV16 E7 (n = 5). We validated our data by depleting E6/E7 in relevant cells and by functional analysis of selected genes in vitro. We conclude that the network of transcriptional interactions in HPV16-infected basal-type cervical epithelium is regulated in a concentration-dependent manner by E6/E7, via a limited number of central master-regulators. These effects are likely to be significant in cervical carcinogenesis, where there is competitive selection of cells with elevated expression of virus oncoproteins.Cancer Research UK (Programme Grant A13080)This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/srep2983

Automated bow shock and magnetopause boundary detection with Cassini using threshold and deep learning methods

Two algorithms set for automatic detection of bow shock (BS) and magnetopause (MP) boundaries at Saturn using in situ magnetic field and plasma data acquired by the Cassini spacecraft are presented. Traditional threshold-based and modern deep learning algorithms were investigated for the task of boundary detection. Sections of Cassini’s orbits were pre-selected based on empirical BS and MP boundary models, and from outlier detection in magnetic field data using an autoencoder neural network. The threshold method was applied to pre-selected magnetic field and plasma data independently to compute parameters to which a threshold was applied to determine the presence of a boundary. The deep learning method used a type of convolutional neural network (CNN) called ResNet on images of magnetic field time series data and electron energy-time spectrograms to classify the presence of boundaries. 2012 data were held out of the training data to test and compare the algorithms on unseen data. The comparison showed that the CNN method applied to plasma data outperformed the threshold method. A final multiclass CNN classifier trained on plasma data obtained F1 scores of 92.1% ± 1.4% for BS crossings and 84.7% ± 1.9% for MP crossings on a corrected test dataset (from use of a bootstrap method). Reliable automated detection of boundary crossings could enable future spacecraft experiments like the PEP instrument on the upcoming JUICE spacecraft mission to dynamically adapt the best observing mode based on rapid classification of the boundary crossings as soon as it appears, thus yielding higher quality data and improved potential for scientific discovery

Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus

Every year at the United Nations, member states deliver statements during the General Debate discussing major issues in world politics. These speeches provide invaluable information on governments’ perspectives and preferences on a wide range of issues, but have largely been overlooked in the study of international politics. This paper introduces a new dataset consisting of over 7,300 country statements from 1970-2014. We demonstrate how the UN General Debate Corpus (UNGDC) can be used to derive country positions on different policy dimensions using text analytic methods. The paper provides applications of these estimates, demonstrating the contribution the UNGDC can make to the study of international politics

Blood pressure and mortality:using offspring blood pressure as an instrument for own blood pressure in the HUNT study

Given that observational associations may be inaccurate, we used offspring blood pressure (BP) to provide alternative estimates of the associations between own BP and mortality. Observational associations between BP and mortality, estimated as hazard ratios (HRs) from Cox regression, were compared to HRs obtained using offspring BP as an instrumental variable (IV) for own BP (N = 32,227 mother-offspring and 27,535 father-offspring pairs). Observationally, there were positive associations between own BP and mortality from all-causes, cardiovascular disease (CVD), coronary heart disease (CHD), stroke and diabetes. Point estimates of the associations between BP and mortality from all-causes, CVD and CHD were amplified in magnitude when using offspring BP as an IV. For example, the HR for all-cause mortality per standard deviation (SD) increase in own systolic BP (SBP) obtained in conventional observational analyses increased from 1.10 (95% CI: 1.09–1.12; P < 0.0001) to 1.31 (95% CI: 1.19–1.43; P < 0.0001). Additionally, SBP was positively associated with diabetes and cancer mortality (HRs: 2.00; 95% CI: 1.12–3.35; P = 0.02 and 1.20; 95% CI: 1.02–1.42; P = 0.03, respectively) and diastolic BP (DBP) with stroke mortality (HR: 1.30; 95% CI: 1.02–1.66; P = 0.03). Results support positive associations between BP and mortality from all-causes, CVD and CHD, SBP on cancer mortality and DBP on stroke mortality

Exploring views on satisfaction with life in young children with chronic illness: an innovative approach to the collection of self-report data from children under 11

The objective of this study was to explore young children’s views on the impact of chronic illness on their life in order to inform future development of a patient-based self-report health outcome measure. We describe an approach to facilitating self-report views from young children with chronic illness. A board game was designed in order to obtain qualitative data from 39 children with a range of chronic illness conditions and 38 healthy controls ranging in age from 3 to 11 years. The format was effective in engaging young children in a self-report process of determining satisfaction with life and identified nine domains. The board game enabled children aged 5–11 years with chronic illness to describe the effects of living with illness on home, family, friends, school and life in general. It generated direct, non-interpreted material from children who, because of their age, may have been considered unable or limited their ability to discuss and describe how they feel. Obtaining this information for children aged 4 and under continues to be a challenge