Optimization of pixel size and propagation distance in X-ray phase-contrast virtual histology

X-ray phase-contrast coupled to high-spatial resolution imaging systems provides a high sensitivity for distinguishing soft tissue structures in small samples, thus being suited for X-ray virtual histology. Propagation-based phase-contrast tomography can deliver a considerable gain in signal-to-noise ratio (SNR) at small pixel sizes when it is combined to a suitable phase retrieval filter. We optimized acquisition parameters, namely the propagation distance and the pixel size, with the aim of providing adequate spatial resolution and sensitivity for virtual histology of breast surgery specimens, scanned with a phase-contrast microtomography (mu CT) system employing a commercial sCMOS detector at the SYRMEP beamline of the Italian synchrotron facility Elettra (Trieste, Italy). A pathological breast tissue sample was embedded in paraffin and imaged using a polychromatic synchrotron beam at an average energy of 24 keV. The high numerical optical aperture of the imaging system enabled to adjust the pixel size to 1, 2.5 and 4 mu m. The scans were acquired at five sample-to-detector distances: 4.5, 150, 250, 500 and 1000 mm. SNR was measured in an homogeneous region portion of the mu CT image for each combination of pixel size and propagation distance. Experimental results were compared to a theoretical model taking into account the actual point spread function of the employed imaging system. The measured gain of SNR associated with the application of the phase-retrieval matched the predictions for large Fresnel numbers (N-F > 2). For each pixel size, an optimal range of propagation distances was found. Optimal mu CT reconstructions were then compared with their respective histopatological images, showing an excellent visibility of relevant structures. The optimization performed in this study will allow to select the most appropriate geometrical configurations for future acquisitions of virtual histology images of different specimens via phase-contrast microtomography

Demographic History of Indigenous Populations in Mesoamerica Based on mtDNA Sequence Data

The genetic characterization of Native American groups provides insights into their history and demographic events. We sequenced the mitochondrial D-loop region (control region) of 520 samples from eight Mexican indigenous groups. In addition to an analysis of the genetic diversity, structure and genetic relationship between 28 Native American populations, we applied Bayesian skyline methodology for a deeper insight into the history of Mesoamerica. AMOVA tests applying cultural, linguistic and geographic criteria were performed. MDS plots showed a central cluster of Oaxaca and Maya populations, whereas those from the North and West were located on the periphery. Demographic reconstruction indicates higher values of the effective number of breeding females (Nef) in Central Mesoamerica during the Preclassic period, whereas this pattern moves toward the Classic period for groups in the North and West. Conversely, Nef minimum values are distributed either in the Lithic period (i.e. founder effects) or in recent periods (i.e. population declines). The Mesomerican regions showed differences in population fluctuation as indicated by the maximum Inter-Generational Rate (IGRmax): i) Center-South from the lithic period until the Preclassic; ii) West from the beginning of the Preclassic period until early Classic; iii) North characterized by a wide range of temporal variation from the Lithic to the Preclassic. Our findings are consistent with the genetic variations observed between central, South and Southeast Mesoamerica and the North-West region that are related to differences in genetic drift, structure, and temporal survival strategies (agriculture versus hunter-gathering, respectively). Interestingly, although the European contact had a major negative demographic impact, we detect a previous decline in Mesoamerica that had begun a few hundred years before

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Reuse of lipase from pseudomonas fluorescens via its step-by-step coimmobilization on glyoxyl-octyl agarose beads with least stable lipases

Coimmobilization of lipases may be interesting in many uses, but this means that the stability of the least stable enzyme determines the stability of the full combilipase. Here, we propose a strategy that permits the reuse the most stable enzyme. Lecitase Ultra (LU) (a phospholipase) and the lipases from Rhizomucor miehei (RML) and from Pseudomonas fluorescens (PFL) were immobilized on octyl agarose, and their stabilities were studied under a broad range of conditions. Immobilized PFL was found to be the most stable enzyme under all condition ranges studied. Furthermore, in many cases it maintained full activity, while the other enzymes lost more than 50% of their initial activity. To coimmobilize these enzymes without discarding fully active PFL when LU or RML had been inactivated, PFL was covalently immobilized on glyoxyl-agarose beads. After biocatalysts reduction, the other enzyme was coimmobilized just by interfacial activation. After checking that glyoxyl-octyl-PFL was stable in 4% Triton X-100, the biocatalysts of PFL coimmobilized with LU or RML were submitted to inactivation under different conditions. Then, the inactivated least stable coimmobilized enzyme was desorbed (using 4% detergent) and a new enzyme reloading (using in some instances RML and in some others employing LU) was performed. The initial activity of immobilized PFL was maintained intact for several of these cycles. This shows the great potential of this lipase coimmobilization strategy.This research was funded by MICIU, grant number CTQ2017-86170-R and Colciencias grant number FP 44842-076-2016). N.S.R. thanks to CNPq for a predoctoral fellowship (CNPq scholarship—Brazil).Peer reviewe

OL19 - A method for the quantitative discrimination of breast tissue chemical composition based on the spectral decomposition of x-ray tomographic breast images

Purpose: Breast cancer is one of the leading causes of death for women worldwide. Early and accurate detection of malignancies is essential for improving the outcome of cancer treatments. Conventional X-ray imaging is based purely on contrasts of attenuation and, since no contrast difference between cancerous and glandular tissues is evident, the diagnosis is mainly based on the morphological characteristics of cancer. On the other hand, advanced imaging techniques allow the extraction of quantitative information. We aim to exploit a technique of spectral decomposition to quantify the difference in chemical composition between healthy and malignant dense tissues. Materials and Method: The study was carried out using a custom-made phantom, filled with water and containing inserts of plastic materials (polyethylene, nylon, polymethyl methacrylate, polyoxymethylene, polytetrafluoroethylene) that mimic the attenuation properties of breast tissues. An attempt to quantitatively describe breast mastectomy samples was also made. Imaging was performed at Elettra, the Italian synchrotron facility, using monochromatic beams of several energies in the breast CT imaging energy range (25-35 keV). 3D tomographic maps of attenuation coefficients were obtained by acquiring projections in a free space propagation phase-contrast setup and further processing them utilizing a phase retrieval filter, a procedure resulting in a significant noise reduction without loss of spatial resolution. Images were processed by a spectral decomposition algorithm, resulting in composition maps in terms of a selected pair of basis materials. Material choice matched the tissue range of interest inside the breast. Using a dedicated mathematical procedure, we managed to decouple the information about the material density and its chemical composition. Finally, a calibration allowed us to retrieve the effective atomic number associated with each reconstructed voxel. Results: The procedure allowed accurate discrimination of the chemical composition of considered inserts. The range of effective atomic numbers among the plastics matched the slight differences among tissues in the breast. Compared to previous studies, the present approach exhibits a much higher sensitivity in material discrimination, which was necessary for the quantitative characterization of breast mastectomy samples. Conclusions: The decoupling of the information about the chemical composition allows very accurate discrimination of similar tissues composing the breast. The proposed technique of spectral decomposition and decoupling allows a quantitative description of imaged sample composition, opening the possibility of significant contributions to a breast cancer diagnosis

Modulating the properties of the lipase from Thermomyces lanuginosus immobilized on octyl agarose beads by altering the immobilization conditions

The lipase from Thermomyces lanuginosus (TLL) has been immobilized on octyl-agarose beads via interfacial activation under 16 different conditions (changing the immobilization pH, the ionic strength, the presence of additives like calcium, phosphate or glycerol) and using a low loading (1 mg/g support). Then, the properties of the different biocatalysts have been evaluated: stability at pH 7.0 and 70 °C and activity versus p-nitro phenyl propionate, triacetin and R- and S- methyl mandelate. Results clearly indicate that the immobilization conditions determine the final enzyme properties, altering enzyme stability (by 10 folds), activity (by 8 folds using R- methyl mandelate) and specificity (VR/VS changed from 0.7 to 2.3 using mandelate esters). For instance, the enzymes immobilized at pH 7.0 using 5 mM buffer were the most stable preparations, while the presence of 250 mM sodium phosphate greatly decreased the final enzyme stability. The biocatalyst stability of TLL increased with increasing NaCl in the immobilization buffer at pH 5. Fluorescence studies confirmed that the conformation of the different immobilized enzymes were different, despite being a physical and reversible immobilization method. Thus, the immobilization of TLL on octyl agarose beads under different conditions produced biocatalysts with different properties, the optimal condition depends on the studied reaction and condition.We gratefully recognize the support from the MICIU from Spanish Government, (project number CTQ2017-86170-R). FLG thanks ARAID for granting his permanent position at the University of Zaragoza. NSR thanks to CNPq for a predoctoral fellowship (CNPq scholarship – Brazil).Peer reviewe

Increasing the enzyme loading capacity of porous supports by a layer-by-layer immobilization strategy using PEI as glue

© The Author(s).A new strategy to increase the enzyme-loading capacity of porous supports was investigated. Lipase from Pseudomonas fluorescens (PFL) was immobilized on octyl-agarose (OA) beads and treated with polyethyleneimine (PEI). Then, PFL was immobilized on the previous PFL layer. Next, the biocatalyst was coated with PEI and a third layer of PFL was added. Sodium dodecyl sulfate polyacrylamide electrophoresis showed that the amount of PFL proportionally increased with each enzyme layer; however, the effects on biocatalyst activity were not as clear. Hydrolyzing 50 mM of triacetin at 25 °C, the activity of the three-layer biocatalyst was even lower than that of the bi-layer one; on the contrary its activity was higher when the activity was measured at 4 °C in the presence of 30% acetonitrile (that reduced the activity and thus the relevance of the substrate diffusion limitations). That is, the advantage of the multilayer formation depends on the specific activity of the enzyme and on the diffusion limitations of the substrate. When octyl agarose (OA)-PFL-PEI-PFL preparation was treated with glutaraldehyde, the activity was reduced, although the enzyme stability increased and the immobilization of the last PFL layer offered results similar to the one obtained using the three-layer preparation without glutaraldehyde modification (90%).This research was funded by MICIU grant number CTQ2017-86170-R (Spain). N. S. R. thanks to CNPq for a predoctoral fellowship (CNPq scholarship–Brazil).Peer reviewe