Quantification Of Morphology Research Articles

Automated Cardiac Evaluation From Chest CT: Potential Role in COVID-19

Un-gated chest CT can be used as the basis of detailed segmentation of cardiac chamber sizes. Atlas-based machine learning tools allow automatic quantification of cardiac morphology and may allow early detection of abnormalities in conditions such as COVID-19 where dedicated cardiac imaging may be hazardous or unavailable.

Mitoxantrone Inhibits FMLP-Induced Degenerative Changes in Human Neutrophils

Neutrophils fight with invading pathogens through various mechanisms including degranulation, phagocytosis, and the release of neutrophil extracellular traps (NETs). This study aimed to determine the impact of a synthetic formyl-peptide (FMLP) on human neutrophils in vitro, and to determine the role of mitoxantrone (MTX), a pharmacological blocker of mitochondrial Ca^(2+) Uniporter (MCU), on FMLP-induced alterations. Isolated neutrophils and a whole-blood preparation of neutrophils were pre-treated with MTX and then stimulated with FMLP. Field's-stained smears and brightfield microscopy were employed for morphological characterization and quantification of neutrophils. The release of cell-free DNA (cfDNA) was also measured for determining neutrophil damage. Our data demonstrated degenerative changes in neutrophils and a greater cfDNA release upon stimulation with FMLP which was negatively associated with the presence of resting platelets in whole blood preparation. Interestingly, MTX pre-treatment significantly reduced FMLP-triggered neutrophil damage and cfDNA release. Metformin, a known inhibitor of NETs formation, also decreased the FMLP-induced changes in neutrophils. In addition to confirming the degenerative potential of FMLP, this study reveals a novel contribution of MCU in regulating FMLP-induced morphological alterations in human neutrophils.

Quantification of true lumen helical morphology and chirality in type B aortic dissections

A novel definition of helical propagation of type B aortic dissections reveals a distinct bimodality, with the true lumen being either achiral (nonhelical) or exclusively right-handed. This right-handed chirality is consistent with anatomic and physiological phenomena such as right-handed twist during left ventricle contraction, helical blood flow, and tissue fiber direction. The helical character of aortic dissections may be useful for pathology research, diagnostics, treatment selection, therapeutic durability prediction, and aortic device design.

Machine Learning-Supported Analyses Improve Quantitative Histological Assessments of Amyloid-β Deposits and Activated Microglia.

Background:Detailed pathology analysis and morphological quantification is tedious and prone to errors. Automatic image analysis can help to increase objectivity and reduce time. Here, we present the evaluation of the DeePathology STUDIO™ for automatic analysis of histological whole-slide images using machine learning/artificial intelligence.Objective:To evaluate and validate the use of DeePathology STUDIO for the analysis of histological slides at high resolution.Methods:We compared the DeePathology STUDIO and our current standard method using macros in AxioVision for the analysis of amyloid-β (Aβ) plaques and microglia in APP-transgenic mice at different ages. We analyzed density variables and total time invested with each approach. In addition, we correlated Aβ concentration in brain tissue measured by ELISA with the results of Aβ staining analysis.Results:DeePathology STUDIO showed a significant decrease of the time for establishing new analyses and the total analysis time by up to 90%. On the other hand, both approaches showed similar quantitative results in plaque and activated microglia density in the different experimental groups. DeePathology STUDIO showed higher sensitivity and accuracy for small-sized plaques. In addition, DeePathology STUDIO allowed the classification of plaques in diffuse- and dense-packed, which was not possible with our traditional analysis.Conclusion:DeePathology STUDIO substantially reduced the effort needed for a new analysis showing comparable quantitative results to the traditional approach. In addition, it allowed including different objects (categories) or cell types in a single analysis, which is not possible with conventional methods.

Quantification of microplastics by count, size and morphology in beverage containers using Nile Red and ImageJ

Abstract Abundant evidence of microplastics (MP) found in the environment, and its toxicity effect in animals calls for human-related research. However, well-established quantitative controlled studies on the potential route of human exposure to MP are still sparse. MP count, size and morphology in 15 polylactic acid (PLA)-lined plastic cups and 15 PLA-lined paper cups were examined using Nile Red fluorescence tagging, microscopic photography, and morphology assessment and quantification based on ImageJ. In the plastic cups, the count and area of MP fibers were found to be significantly higher compared with blanks (p < 0.05), but not MP particles or total MP. In paper cups, count or area was not significantly different in terms of MP particle, MP fibers or total MP. No interesting trend was observed in the distribution regarding the size of MP particles or fibers. These results indicate that selected paper cups and plastic cups could be considered as safe beverage containers, but further research on the toxicological effects of MPs in different morphologies released from plastic cups on human health is needed.

Corrected Super-Resolution Microscopy Enables Nanoscale Imaging of Autofluorescent Lung Macrophages

Observing the cell surface and underlying cytoskeleton at nanoscale resolution using super-resolution microscopy has enabled many insights into cell signaling and function. However, the nanoscale dynamics of tissue-specific immune cells have been relatively little studied. Tissue macrophages, for example, are highly autofluorescent, severely limiting the utility of light microscopy. Here, we report a correction technique to remove autofluorescent noise from stochastic optical reconstruction microscopy (STORM) data sets. Simulations and analysis of experimental data identified a moving median filter as an accurate and robust correction technique, which is widely applicable across challenging biological samples. Here, we used this method to visualize lung macrophages activated through Fc receptors by antibody-coated glass slides. Accurate, nanoscale quantification of macrophage morphology revealed that activation induced the formation of cellular protrusions tipped with MHC class I protein. These data are consistent with a role for lung macrophage protrusions in antigen presentation. Moreover, the tetraspanin protein CD81, known to mark extracellular vesicles, appeared in ring-shaped structures (mean diameter 93 ± 50 nm) at the surface of activated lung macrophages. Thus, a moving median filter correction technique allowed us to quantitatively analyze extracellular secretions and membrane structure in tissue-derived immune cells.

Quantification of plant morphology and leaf thickness with optical coherence tomography

Optical coherence tomography (OCT) can be a valuable imaging tool for in vivo and label-free digital plant phenotyping. However, for imaging leaves, air-filled cavities limit the penetration depth and reduce the image quality. Moreover, up to now quantification of leaf morphology with OCT has been done in one-dimensional or two-dimensional images only, and has often been limited to relative measurements. In this paper, we demonstrate a significant increase in OCT imaging depth and image quality by infiltrating the leaf air spaces with water. In the obtained high-quality OCT images the top and bottom surface of the leaf are digitally segmented. Moreover, high-quality en face images of the leaf are obtained from numerically flattened leaves. Segmentation in three-dimensional OCT images is used to quantify the spatially resolved leaf thickness. Based on a segmented leaf image, the refractive index of an infiltrated leaf is measured to be 1.345±0.004, deviating only 1.2% from that of pure water. Using the refractive index and a correction for refraction effects at the air-leaf interface, we quantitatively mapped the leaf thickness. The results show that OCT is an efficient and promising technique for quantitative phenotyping on leaf and tissue level.

Independent components of human brain morphology

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.

A Prognostic Model Incorporating Tumor Lesion Morphology and Texture Features Identifies High-Risk Patient Subpopulations in De Novo DLBCL and FL

Background: Despite effective first-line (1L) treatment options for patients with NHL almost 40% of patients with diffuse large B cell lymphoma (DLBCL) will have a poor response or disease progression after 1L treatment. In follicular lymphoma (FL) 15-20% of patients experience early relapse, and almost 8% may develop transformation to more aggressive forms of the disease (such as DLBCL) after 1L treatment. More accurate identification of patients at high-risk for a poor prognosis with the standard of care could lead to improved outcomes. Although the International Prognostic Index (IPI) and its FL extension (FLIPI) are often used to stratify patients by prognosis, they have relatively modest sensitivity and specificity for predicting individualized risk. Radiomics is a promising approach to improve upon existing prognostic models because it provides a comprehensive quantification of tumor lesion morphology and texture derived from FDG-PET scans and may provide new and important information about disease biology and progression risk on an individual level. Methods: A collection of 107 radiomics features [pyradiomics v2.20] that describe shape, size or volume and texture of tumor lesions, including complex features that are believed to reflect the underlying biological tumor phenotype and microenvironment, were derived for n=1093 de novo DLBCL patients with available baseline FDG-PET scans from the Phase III GOYA study (NCT01287741) evaluating obinutuzumab plus CHOP chemotherapy (G-CHOP) versus rituximab plus CHOP chemotherapy (R-CHOP) (Vitolo, et al. J Clin Oncol 2017). The same set of features were also extracted from n=451 de novo FL patients with available baseline FDG-PET scans from the Phase III GALLIUM study (NCT01332968) comparing obinutuzumab plus chemotherapy with rituximab plus chemotherapy [Marcus, et al. N Engl J Med 2017]. To investigate the association between the derived radiomics features along with baseline clinical variables and progression-free survival (PFS), a Cox proportional hazard model with L1 regularization was trained and internally validated using the GOYA study. We used a nested Monte Carlo Cross Validation (nMCCV) strategy to train our model and provide high- and low-risk group predictions on held-out samples of data. This modeling strategy allows us to make a group prediction on all GOYA patients while reducing overfitting. To evaluate prognostic performance, we ported the final model trained using the GOYA study (called the Li prognostic model) to the fully independent GALLIUM study. Results: Using our nMCCV approach we identified 11 factors, with an inclusion probability of >50%, that are associated with PFS of DLBCL patients (Figure A). Included within the top features are several image-derived morphometric (i.e. metabolic tumor volume, surface area) and radiomics features (i.e. tumor elongation, NGTDM contrast, GLCM inverse variance). When stratifying patients on the predicted (via majority vote) low-risk vs high-risk groupings we found that our high-risk group had significantly worse prognosis vs the low-risk group (Figure B). In comparison, the high-risk group from the IPI model (defined as IPI > 2) had significantly worse prognosis vs the low-risk group, but the performance was slightly worse than our model (Figure C). PFS probability estimates at 2 and 5 years for predicted high-risk patients was 72.7% [70.0-76.6] and 59.8% [54.8-65.2] (vs 74% [70.0-78.2] and 60.4% [55.1-66.2] for the IPI model). After training and testing in the DLBCL population, we evaluated the prognostic performance of our model in an independent set of FL patients. We found that high-risk FL patients had a significantly worse prognosis than the low-risk group (Figure D). PFS probability estimates at 2 and 5 years for predicted high-risk patients was 77.4% [69.8-85.8] and 48.9% [39.5-60.5] (vs. 80% [0.748-0.856] and 58.3% [51.6-65.9] in the full group). Conclusions: Radiomics features are prognostic in DLBCL and provide a modest improvement in prognostic performance when combined with traditional IPI scores, clinical features, and lab values (vs IPI alone). Our prognostic signature, developed in DLBCL, has significant prognostic performance in an independent dataset of patients with FL. While these results are promising, our FL validation dataset was relatively small and further evidence is required to confirm our findings. Disclosures Li: Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Jemaa:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Carano:F. Hoffmann-La Roche: Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Bengtsson:Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company. Paulson:F. Hoffmann-La Roche: Current equity holder in private company, Current equity holder in publicly-traded company; Genentech, Inc.: Current Employment. Jansen:F. Hoffmann-La Roche: Current Employment; Molecular Health GmbH: Ended employment in the past 24 months; F. Hoffmann-La Roche, Abbvie, Alphabet, other (non-healthcare), indexed funds and ETFs: Current equity holder in publicly-traded company. Nielsen:F. Hoffmann-La Roche: Current Employment, Current equity holder in publicly-traded company. Hibar:Genentech, Inc.: Current Employment; F. Hoffmann-La Roche: Current equity holder in publicly-traded company.

In-Depth Investigation of Copper Surface Chemistry Modification by Ultrashort Pulsed Direct Laser Interference Patterning.

Surface patterning in the micro- and nanometer-range by means of pulsed laser interference has repeatedly proven to be a versatile tool for surface functionalization. With these techniques, however, the surface is often changed not only in terms of morphology but also in terms of surface chemistry. In this study, we present an in-depth investigation of the chemical surface modification occurring during surface patterning of copper by ultrashort pulsed direct laser interference patterning (USP-DLIP). A multimethod approach of parallel analysis using visualizing, topography-sensitive, and spectroscopic techniques allowed a detailed quantification of surface morphology as well as composition and distribution of surface chemistry related to both processing and atmospheric aging. The investigations revealed a heterogeneous surface composition separated in peak and valley regions predominantly consisting of Cu2O, as well as superficial agglomerations of CuO and carbon species. The evaluation was supported by a modeling approach for the quantification of XPS results in relation to heterogeneous surface composition, which was observed by means of a combination of different spectroscopic techniques. The overall results provide a detailed understanding of the chemical and topographical surface modification during USP-DLIP, which allows a more targeted use of this technology for surface functionalization.

Cardiac changes after cardiac resynchronization therapy assessed using cardiac magnetic resonance imaging during biventricular pacing

Abstract Cardiac magnetic resonance (CMR) is a valuable tool in the assessment of left and right ventricular volumes and functions therefore establishing the effect of cardiac resynchronization therapy (CRT), but in majority of the devices MR safe mode does not include biventricular pacing as an option. We aimed to assess the effect of cardiac resynchronization using CMR with resynchronization on. NYHA class II-III patients with LVEF≤35% despite optimal medical therapy and complete LBBB with broad QRS (>150 ms) were prospectively recruited (n=16, 65±7 years, 56% male, 69% nonischaemic). CMR examination was performed at baseline and at 6-month follow-up, applying both biventricular and AOO pacing. The following data were measured: conventional CMR parameters including left and right ventricular ejection fraction (LVEF), end-diastolic index (LVEDVi) and end-systolic volume index (LVESVi), stroke volume and mass, remodelling indices such as 3D sphericity and relative wall thickness (RWT: 2x end-diastolic wall thickness /end-diastolic long-axis diameter). Using feature tracking analysis global longitudinal, circumferential, radial strain, global dyssynchrony (mechanical dispersion (MD)) and regional dyssynchrony was measured. Comparing the baseline and follow-up CMR parameters measured during biventricular pacing, we found a significant increase in LVEF (27±7 vs 45±9%; p<0.001) and decrease in LVEDVi and LVESVi (LVEDVi: 149±28 vs 91±20ml/m2; LVESVi: 108±31 vs 51±17ml/m2; p<0.001). Based on decrease in LVESVi 14 patients were classified as super-responder (>30%), one responder (>15%) and one non-responder (<15%). ProBNP levels significantly decreased (1186±83 vs 323±271 pg/ml, p<0.05). LV remodelling indices (3D sphericity: 0.46±0.13 vs 0.61±0.11, RWT: 0.33±0.07 vs 0.43±0.10), global longitudinal, circumferential and radial strain values showed significant improvement. Circumferential MD decreased (18.3±6.7 vs 13.3±3.4, p<0.01), while longitudinal MD did not change. Regional dyssynchrony drastically improved (358±108 vs 98±61ms, p<0.001). Applying AOO pacing resulted in an immediate deterioration in LVEF (45±9 vs 38±9%), LVESVi (51±17 vs 58±19 ml/m2), global circumferential and radial strain and regional dyssynchrony. In conclusion CMR imaging during biventricular pacing is feasible and enables a more precise quantification of LV function, morphology and mechanics. As a result, it may contribute to a better understanding of the effects of resynchronization therapy and might improve responder rate in the future. Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): National Research, Development and Innovation Office of Hungary (NKFIA)

Analysis of calcareous sand particle shape using fourier descriptor analysis

Soil particle shape analysis was conducted on two calcareous sands from Dissa and Matmata in Tunisia and one silica sand from Jumunjin in Korea using an image analysis method. This technique uses complex Fourier shape descriptors and image analysis of sand grains SEM photographs to provide accurate quantification of particle morphology and texture. The Fourier descriptors, denoted “Signature Descriptors”, provide measures of Elongation, Triangularity, Squareness, and Asymmetry and identify the overall shape of soil particles. A summary of higher-order descriptors provides textural information linked up to local roughness and texture characteristics. After analyzing the Fourier descriptors, elongation was found to be the major characteristics of the three sands, mainly for the Dissa and Matmata carbonate sands. In addition, the elongation signature descriptors for the Dissa and Matmata sands have very high values compared to those of Ras Alkhair (Saudi Arabia) and Dog’s bay (Ireland) sands. Therefore, the Dissa and Matmata carbonate sands have higher angles of friction and higher critical state angle of friction than Ras Alkhair and Dog’s bay sands. Furthermore, the Dissa and Matmata carbonate sands show higher roughness than Jumunjin’s silica sand.

Heteromorphosis associated to host-exploitation in an atypical parasitoid, Mallophora ruficauda (Diptera: Asilidae)

In this work, we provide morphological illustration and descriptions of the immature stages of the ectoparasitoid robber fly Mallophora ruficauda. Additionally, we studied the ecological aspects of its life cycle through the correlation between the morphology and function performed in each phase of the consumption of their host, the white grub Cyclocephala signaticollis. For the morphological description and quantification of length and width of the egg and larval instars I–II, images were used through optical and scanning electron microscopy. Individuals from larval instars III–V were weighed and measured with digital calibre directly. Finally, images were taken of the cephalic structures of the larval instars and through the use of image processing software we measured in each instar the size of cephalic structures. In addition, the changes in the width of cephalic capsule and the relative size of the maxillary palps and labrum with respect to the width of cephalic capsule were studied for each larval instar through GLMs, to relate the morphology of the cephalic structures with the function they perform. We found that the cephalic structures of the larva undergo changes when moulting to the next instar, according to their relationship with the host, matching with the stage of development where the processes of orientation to the host and attachment to its cuticle take place. These observations reveal, for the first time in a parasitoid asilid larva, the correlation between cephalic morphology and ecological function during the parasitism process and host use.

MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology.

SummaryWhile the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis.

Non-Destructive Tumor Aggregate Morphology and Viability Quantification at Cellular Resolution, During Development and in Response to Drug

Three-dimensional (3D) tissue-engineered in vitro models, particularly multicellular spheroids and organoids, have become important tools to explore disease progression and guide the development of novel therapeutic strategies. These avascular constructs are particularly powerful in oncological research due to their ability to mimic several key aspects of in vivo tumors, such as 3D structure and pathophysiologic gradients. Advancement of spheroid models requires characterization of critical features (i.e., size, shape, cellular density, and viability) during model development, and in response to treatment. However, evaluation of these characteristics longitudinally, quantitatively and non-invasively remains a challenge. Herein, Optical Coherence Tomography (OCT) is used as a label-free tool to assess 3D morphologies and cellular densities of tumor spheroids generated via the liquid overlay technique. We utilize this quantitative tool to assess Matrigel's influence on spheroid morphologic development, finding that the absence of Matrigel produces flattened, disk-like aggregates rather than 3D spheroids with physiologically-relevant features. Furthermore, this technology is adapted to quantify cell number within tumor spheroids, and to discern between live and dead cells, to non-destructively provide valuable information on tissue/construct viability, as well as a proof-of-concept for longitudinal drug efficacy studies. Together, these findings demonstrate OCT as a promising noninvasive, quantitative, label-free, longitudinal and cell-based method that can assess development and drug response in 3D cellular aggregates at a mesoscopic scale.

Exploring the relationship between spatial morphology characteristics and scenic beauty preference of landscape open space unit by using point cloud data

To explore the relationship between the objective morphological features and subjective scenic beauty preference of landscape open space units, this study improves the research method for morphology quantification, scenic beauty preference survey and relationship analysis. Fourteen morphology factors representing the features of boundary, domain and enclosure are quantified based on the point cloud data of 35 open space units. Scenic beauty evaluation is conducted online with dynamic panoramic photos. Principal component analysis is implemented to convert 14 correlated form factors into five principal components representing morphological principle. The multiple linear regression model explains the contribution of each principal component to scenic beauty preference values, showing a significance sequence of penetration, scale, naturalness, complexity and rhythm. The first three principal components have positive impacts on scenic beauty preference, while the last two principal components are negative. This work aims to reveal the regularity of public’s scenic beauty preference for open space morphology.

Construction of a hierarchical multiscale conducting network for enhanced thermoelectric response in organic PEDOT:PSS based nanocomposites

Thermoelectric technology, which is characterized by the interconversion between heat and electricity, is demonstrated as an efficient and environmentally friendly route for thermal energy harvesting and solid-state cooling devices. The pursuit for high-performance room temperature thermoelectric materials is of significant interest. Here, we proposed a design strategy to dramatically improve the thermoelectric response by constructing a hierarchical multiscale conductor network (AgNWs/CNT) in polymer matrix (PEDOT:PSS). At the optimized composition, the highest Seebeck coefficient and electrical conductivity of base treated ternary PEDOT:PSS/AgNWs/CNT composite are optimized to be 58.6 μV K−1 and ∼1950 S cm−1. Correspondingly, the power factor is thus calculated to be on the order of 670 μW m−1 K−2, which is among one of the highest values compared with previous reports. The underlying mechanism is illustrated based on detailed structure, morphology and electron transport quantification. This work affords a novel strategy for the future development of high-performance room temperature nanocomposite thermoelectrics.

Defective migration and dysmorphology of neutrophil granulocytes in atypical chronic myeloid leukemia treated with ruxolitinib

BackgroundThe identification of pathologically altered neutrophil granulocyte migration patterns bears strong potential for surveillance and prognostic scoring of diseases. We recently identified a strong correlation between impaired neutrophil motility and the disease stage of myelodysplastic syndrome (MDS). Here, we apply this assay to study quantitively increased neutrophils of a patient suffering from a rare leukemia subtype, atypical chronic myeloid leukemia (aCML).MethodsA 69-year-old male was analyzed in this study. Besides routine analyses, we purified the patient’s neutrophils from peripheral whole blood and studied their migration behavior using time-lapse video microscopy in a standardized assay. These live cell migration analyses also allowed for the quantification of cell morphology. Furthermore, the cells were stained for the markers CD15, CD16, fMLPR, CXCR1 and CXCR2.ResultsDespite cytoreductive therapy with hydroxyurea, the patient’s WBC and ANC were poorly controlled and severe dysgranulopoiesis with hypogranularity was observed. Neutrophils displayed strongly impaired migration when compared to healthy controls and migrating cells exhibited a more flattened-out morphology than control neutrophils. Because of a detected CSF3R (p.T618I) mutation and constitutional symptoms treatment with ruxolitinib was initiated. Within 1 week of ruxolitinib treatment, the cell shape normalized and remained indistinguishable from healthy control neutrophils. However, neutrophil migration did not improve over the course of ruxolitinib therapy but was strikingly altered shortly before a sinusitis with fever and bleeding from a gastric ulcer. Molecular work-up revealed that under ruxolitinib treatment, the CSF3R clone was depleted, yet the expansion of a NRAS mutated subclone was promoted.ConclusionThese results demonstrate the usefulness of neutrophil migration analyses to uncover corresponding alterations of neutrophil migration in rare myeloid neoplasms. Furthermore, in addition to monitoring migration the determination of morphological features of live neutrophils might represent a useful tool to monitor the effectiveness of therapeutic approaches.

SCAU-Net: Spatial-Channel Attention U-Net for Gland Segmentation.

With the development of medical technology, image semantic segmentation is of great significance for morphological analysis, quantification, and diagnosis of human tissues. However, manual detection and segmentation is a time-consuming task. Especially for biomedical image, only experts are able to identify tissues and mark their contours. In recent years, the development of deep learning has greatly improved the accuracy of computer automatic segmentation. This paper proposes a deep learning image semantic segmentation network named Spatial-Channel Attention U-Net (SCAU-Net) based on current research status of medical image. SCAU-Net has an encoder-decoder-style symmetrical structure integrated with spatial and channel attention as plug-and-play modules. The main idea is to enhance local related features and restrain irrelevant features at the spatial and channel levels. Experiments on the gland dataset GlaS and CRAG show that the proposed SCAU-Net model is superior to the classic U-Net model in image segmentation task, with 1% improvement on Dice score and 1.5% improvement on Jaccard score.

Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice.

The 3×Tg-AD mouse is one of the most studied animal models of Alzheimer's disease (AD), and develops both amyloid beta deposits and neurofibrillary tangles in a temporal and spatial pattern that is similar to human AD pathology. Additionally, abnormal myelination patterns with changes in oligodendrocyte and myelin marker expression are reported to be an early pathological feature in this model. Only few diffusion MRI (dMRI) studies have investigated white matter abnormalities in 3×Tg-AD mice, with inconsistent results. Thus, the goal of this study was to investigate the sensitivity of dMRI to capture brain microstructural alterations in 2-month-old 3×Tg-AD mice. In the fimbria, the fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), and radial kurtosis (K┴ ) were found to be significantly lower in 3×Tg-AD mice than in controls, while the mean diffusivity (MD) and radial diffusivity (D┴ ) were found to be elevated. In the fornix, K┴ was lower for 3×Tg-AD mice; in the dorsal hippocampus MD and D┴ were elevated, as were FA, MD, and D┴ in the ventral hippocampus. These results indicate, for the first time, dMRI changes associated with myelin abnormalities in young 3×Tg-AD mice, before they develop AD pathology. Morphological quantification of myelin basic protein immunoreactivity in the fimbria was significantly lower in the 3×Tg-AD mice compared with the age-matched controls. Our results demonstrate that dMRI is able to detect widespread, significant early brain morphological abnormalities in 2-month-old 3×Tg-AD mice.