An EZH2-dependent transcriptional complex promotes aberrant epithelial remodelling after injury.

Unveiling the molecular mechanisms of tissue remodelling following injury is imperative to elucidate its regenerative capacity and aberrant repair in disease. Using different omics approaches, we identified enhancer of zester homolog 2 (EZH2) as a key regulator of fibrosis in injured lung epithelium. Epithelial injury drives an enrichment of nuclear transforming growth factor-ß-activated kinase 1 (TAK1) that mediates EZH2 phosphorylation to facilitate its liberation from polycomb repressive complex 2 (PRC2). This process results in the establishment of a transcriptional complex of EZH2, RNA-polymerase II (POL2) and nuclear actin, which orchestrates aberrant epithelial repair programmes. The liberation of EZH2 from PRC2 is accompanied by an EZH2-EZH1 switch to preserve H3K27me3 deposition at non-target genes. Loss of epithelial TAK1, EZH2 or blocking nuclear actin influx attenuates the fibrotic cascade and restores respiratory homeostasis. Accordingly, EZH2 inhibition significantly improves outcomes in a pulmonary fibrosis mouse model. Our results reveal an important non-canonical function of EZH2, paving the way for new therapeutic interventions in fibrotic lung diseases.

Recapitulating idiopathic pulmonary fibrosis related alveolar epithelial dysfunction in a human iPSC-derived air-liquid interface model.

Idiopathic pulmonary fibrosis (IPF) is a fatal disease of unknown cause that is characterized by progressive fibrotic lung remodeling. An abnormal emergence of airway epithelial-like cells within the alveolar compartments of the lung, herein termed bronchiolization, is often observed in IPF. However, the origin of this dysfunctional distal lung epithelium remains unknown due to a lack of suitable human model systems. In this study, we established a human induced pluripotent stem cell (iPSC)-derived air-liquid interface (ALI) model of alveolar epithelial type II (ATII)-like cell differentiation that allows us to investigate alveolar epithelial progenitor cell differentiation in vitro. We treated this system with an IPF-relevant cocktail (IPF-RC) to mimic the pro-fibrotic cytokine milieu present in IPF lungs. Stimulation with IPF-RC during differentiation increases secretion of IPF biomarkers and RNA sequencing (RNA-seq) of these cultures reveals significant overlap with human IPF patient data. IPF-RC treatment further impairs ATII differentiation by driving a shift toward an airway epithelial-like expression signature, providing evidence that a pro-fibrotic cytokine environment can influence the proximo-distal differentiation pattern of human lung epithelial cells. In conclusion, we show for the first time, the establishment of a human model system that recapitulates aspects of IPF-associated bronchiolization of the lung epithelium in vitro.

Segmentation and quantification of materials with energy discriminating computed tomography: a phantom study.

PURPOSE: To experimentally investigate whether a computed tomography (CT) system based on CdZnTe (CZT) detectors in conjunction with a least-squares parameter estimation technique can be used to decompose four different materials. METHODS: The material decomposition process was divided into a segmentation task and a quantification task. A least-squares minimization algorithm was used to decompose materials with five measurements of the energy dependent linear attenuation coefficients. A small field-of-view energy discriminating CT system was built. The CT system consisted of an x-ray tube, a rotational stage, and an array of CZT detectors. The CZT array was composed of 64 pixels, each of which is 0.8 x 0.8 x 3 mm. Images were acquired at 80 kVp in fluoroscopic mode at 50 ms per frame. The detector resolved the x-ray spectrum into energy bins of 22-32, 33-39, 40-46, 47-56, and 57-80 keV. Four phantoms were constructed from polymethylmethacrylate (PMMA), polyethylene, polyoxymethylene, hydroxyapatite, and iodine. Three phantoms were composed of three materials with embedded hydroxyapatite (50, 150, 250, and 350 mg/ml) and iodine (4, 8, 12, and 16 mg/ml) contrast elements. One phantom was composed of four materials with embedded hydroxyapatite (150 and 350 mg/ml) and iodine (8 and 16 mg/ml). Calibrations consisted of PMMA phantoms with either hydroxyapatite (100, 200, 300, 400, and 500 mg/ml) or iodine (5, 15, 25, 35, and 45 mg/ml) embedded. Filtered backprojection and a ramp filter were used to reconstruct images from each energy bin. Material segmentation and quantification were performed and compared between different phantoms. RESULTS: All phantoms were decomposed accurately, but some voxels in the base material regions were incorrectly identified. Average quantification errors of hydroxyapatite/iodine were 9.26/7.13%, 7.73/5.58%, and 12.93/8.23% for the three-material PMMA, polyethylene, and polyoxymethylene phantoms, respectively. The average errors for the four-material phantom were 15.62% and 2.76% for hydroxyapatite and iodine, respectively. CONCLUSIONS: The calibrated least-squares minimization technique of decomposition performed well in breast imaging tasks with an energy resolving detector. This method can provide material basis images containing concentrations of the relevant materials that can potentially be valuable in the diagnostic process.

Least squares parameter estimation methods for material decomposition with energy discriminating detectors.

PURPOSE: Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. METHODS: Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg/ml) and iodine (4, 12, 20, 28, 36, and 44 mg/ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30/70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg/ml) and iodine (5, 15, 25, 35, and 45 mg/ml). The x-ray transport process was simulated where the Beer-Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. RESULTS: The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. CONCLUSIONS: The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine.

Radiation dose reduction using a CdZnTe-based computed tomography system: comparison to flat-panel detectors.

PURPOSE: Although x-ray projection mammography has been very effective in early detection of breast cancer, its utility is reduced in the detection of small lesions that are occult or in dense breasts. One drawback is that the inherent superposition of parenchymal structures makes visualization of small lesions difficult. Breast computed tomography using flat-panel detectors has been developed to address this limitation by producing three-dimensional data while at the same time providing more comfort to the patients by eliminating breast compression. Flat panels are charge integrating detectors and therefore lack energy resolution capability. Recent advances in solid state semiconductor x-ray detector materials and associated electronics allow the investigation of x-ray imaging systems that use a photon counting and energy discriminating detector, which is the subject of this article. METHODS: A small field-of-view computed tomography (CT) system that uses CdZnTe (CZT) photon counting detector was compared to one that uses a flat-panel detector for different imaging tasks in breast imaging. The benefits afforded by the CZT detector in the energy weighting modes were investigated. Two types of energy weighting methods were studied: Projection based and image based. Simulation and phantom studies were performed with a 2.5 cm polymethyl methacrylate (PMMA) cylinder filled with iodine and calcium contrast objects. Simulation was also performed on a 10 cm breast specimen. RESULTS: The contrast-to-noise ratio improvements as compared to flat-panel detectors were 1.30 and 1.28 (projection based) and 1.35 and 1.25 (image based) for iodine over PMMA and hydroxylapatite over PMMA, respectively. Corresponding simulation values were 1.81 and 1.48 (projection based) and 1.85 and 1.48 (image based). Dose reductions using the CZT detector were 52.05% and 49.45% for iodine and hydroxyapatite imaging, respectively. Image-based weighting was also found to have the least beam hardening effect. CONCLUSIONS: The results showed that a CT system using an energy resolving detector reduces the dose to the patient while maintaining image quality for various breast imaging tasks.

CO2-Activated Adsorption: A New Approach to Dye Removal by Chitosan Hydrogel.

This study focuses on development of a new adsorption technique by CO2-activated chitosan. Carbon dioxide was utilized to form the functional chemical groups of chitosan on the adsorptions of anionic dyes, Brilliant Blue FCF and Congo Red, in the aqueous solution. CO2-activated chitosan results in the dye adsorption significantly faster than that of chitosan in pure water. The adsorption capacities and removal efficiencies of the dye are increased by CO2-activated chitosan. Furthermore, the dye adsorptions on CO2-activated chitosan were investigated at various temperatures and initial dye concentrations in the aqueous solution. Interestingly, the high temperature adsorption provides the enhancement of adsorption capacities and removal efficiencies of the dye by the carbamate cross-linking of chitosan with CO2. CO2-activated chitosan was further characterized by Fourier transform infrared spectra, amino group ratio, zeta potential, and thermal gravimetric analysis. These characterizations can be used for understanding the unique adsorption of the dye on CO2-activated chitosan. Carbon dioxide-activated chitosan in this work will provide an effective operation and a clean process of dye adsorption in wastewater treatment.

Adhesion forces and cortical tension couple cell proliferation and differentiation to drive epidermal stratification.

To establish and maintain organ structure and function, tissues need to balance stem cell proliferation and differentiation rates and coordinate cell fate with position. By quantifying and modelling tissue stress and deformation in the mammalian epidermis, we find that this balance is coordinated through local mechanical forces generated by cell division and delamination. Proliferation within the basal stem/progenitor layer, which displays features of a jammed, solid-like state, leads to crowding, thereby locally distorting cell shape and stress distribution. The resulting decrease in cortical tension and increased cell-cell adhesion trigger differentiation and subsequent delamination, reinstating basal cell layer density. After delamination, cells establish a high-tension state as they increase myosin II activity and convert to E-cadherin-dominated adhesion, thereby reinforcing the boundary between basal and suprabasal layers. Our results uncover how biomechanical signalling integrates single-cell behaviours to couple proliferation, cell fate and positioning to generate a multilayered tissue.

Optimization of K-edge imaging for vulnerable plaques using gold nanoparticles and energy resolved photon counting detectors: a simulation study.

We investigated the effect of different imaging parameters, such as dose, beam energy, energy resolution and the number of energy bins, on the image quality of K-edge spectral computed tomography (CT) of gold nanoparticles (GNP) accumulated in an atherosclerotic plaque. A maximum likelihood technique was employed to estimate the concentration of GNP, which served as a targeted intravenous contrast material intended to detect the degree of the plaque's inflammation. The simulation studies used a single-slice parallel beam CT geometry with an x-ray beam energy ranging between 50 and 140 kVp. The synthetic phantoms included small (3 cm in diameter) cylinder and chest (33 × 24 cm(2)) phantoms, where both phantoms contained tissue, calcium and gold. In the simulation studies, GNP quantification and background (calcium and tissue) suppression tasks were pursued. The x-ray detection sensor was represented by an energy resolved photon counting detector (e.g., CdZnTe) with adjustable energy bins. Both ideal and more realistic (12% full width at half maximum (FWHM) energy resolution) implementations of the photon counting detector were simulated. The simulations were performed for the CdZnTe detector with a pixel pitch of 0.5-1 mm, which corresponds to a performance without significant charge sharing and cross-talk effects. The Rose model was employed to estimate the minimum detectable concentration of GNPs. A figure of merit (FOM) was used to optimize the x-ray beam energy (kVp) to achieve the highest signal-to-noise ratio with respect to the patient dose. As a result, the successful identification of gold and background suppression was demonstrated. The highest FOM was observed at the 125 kVp x-ray beam energy. The minimum detectable GNP concentration was determined to be approximately 1.06 µmol mL(-1) (0.21 mg mL(-1)) for an ideal detector and about 2.5 µmol mL(-1) (0.49 mg mL(-1)) for a more realistic (12% FWHM) detector. The studies show the optimal imaging parameters at the lowest patient dose using an energy resolved photon counting detector to image GNP in an atherosclerotic plaque.

Breast density quantification with cone-beam CT: a post-mortem study.

Forty post-mortem breasts were imaged with a flat-panel based cone-beam x-ray CT system at 50 kVp. The feasibility of breast density quantification has been investigated using standard histogram thresholding and an automatic segmentation method based on the fuzzy c-means algorithm (FCM). The breasts were chemically decomposed into water, lipid, and protein immediately after image acquisition was completed. The per cent fibroglandular volume (%FGV) from chemical analysis was used as the gold standard for breast density comparison. Both image-based segmentation techniques showed good precision in breast density quantification with high linear coefficients between the right and left breast of each pair. When comparing with the gold standard using %FGV from chemical analysis, Pearson's r-values were estimated to be 0.983 and 0.968 for the FCM clustering and the histogram thresholding techniques, respectively. The standard error of the estimate was also reduced from 3.92% to 2.45% by applying the automatic clustering technique. The results of the postmortem study suggested that breast tissue can be characterized in terms of water, lipid and protein contents with high accuracy by using chemical analysis, which offers a gold standard for breast density studies comparing different techniques. In the investigated image segmentation techniques, the FCM algorithm had high precision and accuracy in breast density quantification. In comparison to conventional histogram thresholding, it was more efficient and reduced inter-observer variation.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PURPOSE: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. METHODS: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. RESULTS: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. CONCLUSIONS: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

Controlled release of dry reagents in porous media for tunable temporal and spatial distribution upon rehydration.

Novel methods are demonstrated that enable controlled spatial and temporal rehydration of dried reagents in a porous matrix. These methods can be used in paper-based microfluidic assays to define reagent concentrations over time at zones downstream for improved performance, and can reduce costs by simplifying the manufacturing process with the use of a single porous substrate. First, the creation of uniform reagent pulses from patterned arrays of dried reagent is demonstrated. Second, reagents are stored dry in separate regions of the porous matrix so that they can be combined upon rehydration for immediate use in the device. Third, reagents are reconstituted sequentially from dry storage depots with tunable delivery times. Fourth, the total time for dissolution is varied to achieve a range of reagent delivery times to a downstream region. Finally, the utility of these control methods is demonstrated in the context of real-time reagent rehydration and mixing on a porous device.

Allometric scaling in the coronary arterial system.

Biological variables such as basal metabolic rate scale with body mass through a power law relationship. The coronary arterial system also exhibits power law relations between morphological parameters such as total distal arterial length and lumen volume. The current study validated this power law and extended the relations to include the regional myocardial mass. The coronary arteries of 10 swine hearts were casted with a radio-opaque polymer solution and were imaged with cone-beam computed tomography. The CT images were analyzed by segmenting the vessels and myocardium. The vessels were tracked in 3D and the branch diameter, length, and lumen volume were computed. Regional myocardial mass were then computed for each branch. The perfusion beds of the three main coronary arterial trees were also colored differently to validate the measured mass and CT computed mass. The power laws for the morphological characteristics were then analyzed and the exponents were found to be 3/4 for the length-mass and length-volume relationships, and 1.0 for the volume-mass relationship. The CT computed myocardial mass (MCT) and the actual measured mass (MA) were related by MCT = 1.002 MA + 2.033 g. The relationship of the morphological parameters of the coronary arterial tree can potentially be used for quantification of diffuse coronary artery disease and anatomic area at risk.