RESUMEN
In this proof-of-principle study, we systematically studied the potential of Raman spectroscopy for detecting pre-analytical delays in blood serum samples. Spectra from 330 samples from a liver cirrhosis cohort were acquired over the course of eight days, stored one day at room temperature, and stored subsequently at 4 °C. The spectra were then used to train Convolutional Neural Networks (CNN) to predict the delay to sample examination. We achieved 90% accuracy for binary classification of the serum samples in the groups "without delay" versus "delayed". Spectra recorded on the first day could be distinguished clearly from all subsequent measurements. Distinguishing between spectra taken in the range from the second to the last day seems to be possible as well, but currently, with an accuracy of approximately 70% only. Importantly, filtering out the fluorescent background significantly reduces the precision of detection.
Asunto(s)
Redes Neurales de la Computación , Espectrometría Raman , Humanos , Espectrometría Raman/métodos , Cirrosis HepáticaRESUMEN
Background: Metabolites, especially lipids, have been shown to be promising therapeutic targets. In conjugation with genes and proteins they can be used to identify phenotypes of disease and support the development of targeted treatments. The majority of clinically collected tissue samples are stored in formalin-fixed and paraffin embedded (FFPE) blocks due to their tissue conservation ability and indefinite storage capacity. For metabolic analysis, however, fresh frozen (FF) samples are currently preferred over FFPE samples due to concerns of metabolic information being lost when preparing the samples. With little or no sample preparation, desorption electrospray ionisation mass spectrometry imaging (DESI-MSI) allows for the study of spatial as well as spectral information. Methods: DESI-MSI analysis was performed on FFPE breast cancer tissue microarray samples from 213 patients collected between the years 1935-2013. Logistic regression (LR) models were built to classify samples based on age and FF samples were used for feature validation. Results: LR models developed on the FFPE samples achieved an average classification accuracy of 96% when predicting their age with a 10-year grouping. Closer examination of the metabolic change over time revealed that the mean signal intensities for the lower mass range (100 - 500 m/z) linearly decrease over time, while the mean intensities for the higher mass range (500 - 900 m/z), remained relatively constant. Conclusions: In our samples, which span over 70 years, sample age has a weak yet quantifiable impact on metabolite content in FFPE samples, while the higher mass range is seemingly unaffected. FFPE samples thus provide an alternative avenue for metabolic analysis of lipids.
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In recent years, nonhuman ancient DNA studies have begun to focus on larger sample sizes and whole genomes, offering the potential to reveal exciting and hitherto unknown answers to ongoing biological and archaeological questions. However, one major limitation to such studies is the substantial financial and time investments still required during sample screening, due to uncertainty regarding successful sample selection. This study investigates the effect of a wide range of sample properties including latitude, sample age, skeletal element, collagen preservation, and context on endogenous content and DNA damage profiles for 317 ancient and historic pinniped samples collected from across the North Atlantic and surrounding regions. Using generalised linear and mixed-effect models, we found that a range of factors affected DNA preservation within each of the species under consideration. The most important findings were that endogenous content varied significantly within species according to context, the type of skeletal element, the collagen content and collection year. There also appears to be an effect of the sample's geographic origin, with samples from the Arctic generally showing higher endogenous content and lower damage rates. Both latitude and sample age were found to have significant relationships with damage levels, but only for walrus samples. Sex, ontogenetic age and extraction material preparation were not found to have any significant relationship with DNA preservation. Overall, skeletal element and sample context were found to be the most influential factors and should therefore be considered when selecting samples for large-scale ancient genome studies.
Asunto(s)
Organismos Acuáticos/genética , Caniformia/genética , ADN Antiguo , Animales , Arqueología , Regiones ÁrticasRESUMEN
OBJECTIVE: Determination of color and evaluating its variation form the basis for a broad range of research questions. For studies on taxonomy, systematics, etc., resorting to mammal specimens in museum collections has a number of advantages over using field specimens. However, if museum specimens are to be for studying color, they should accurately represent the color of live animals, or we should understand how they differ. Basically, this study addresses this question: How does coat color vary when dealing with specimens of Akodon budini (Budin's grass mouse, Thomas 1918), stored in one museum collection for different periods of time? RESULTS: We measured color values through a spectroradiometer and a diffuse illumination cabin and used the reflectance values in the form of CIELab tri-stimulus values, considering CIE standard illuminant A. We observed that there is a relationship between specimen storage antiquity and pelage color and it seems that it is general for at least a number of small mammals and this could indicate a universal phenomenon across several mammal species and across several storage conditions. Our results, as others, emphasize the importance of considering storage time, among other circumstances, in research studies using mammal skins and where color is of importance.