CONSERVATION OF MOLECULAR PREPATTERNS DURING THE EVOLUTION OF CUTICLE MORPHOLOGY IN DROSOPHILA LARVAE

We are using patterns of cuticle specialization in Drosophila larvae as models to investigate the molecular, genetic, and developmental bases of morphological evolution. Members of the virilis species group differ markedly from one another in the distribution of hairs on the dorsal surface of first instar larvae. In particular, characteristic bands of hairs cover about 20% of each trunk segment in some species but about 70% in others. These major types do not correlate with recently proposed phylogenetic relationships, suggesting that similar phenotypes have arisen independently in different lineages. The patterns of expression of several genes that control or reflect intrasegmental patterning are indistinguishable in species with very different cuticle morphologies. We conclude that, in this case, morphology probably has evolved via altered response to a conserved molecular prepattern.     

Isolation and reconstruction of cardiac mitochondria from SBEM images using a deep learning-based method

Mitochondrial morphological defects are a common feature of diseased cardiac myocytes. However, quantitative assessment of mitochondrial morphology is limited by the time-consuming manual segmentation of electron micrograph (EM) images. To advance understanding of the relation between morphological defects and dysfunction, an efficient morphological reconstruction method is desired to enable isolation and reconstruction of mitochondria from EM images. We propose a new method for isolating and reconstructing single mitochondria from serial block-face scanning EM (SBEM) images. CDeep3M, a cloud-based deep learning network for EM images, was used to segment mitochondrial interior volumes and boundaries. Post-processing was performed using both the predicted interior volume and exterior boundary to isolate and reconstruct individual mitochondria. Series of SBEM images from two separate cardiac myocytes were processed. The highest F1-score was 95% using 50 training datasets, greater than that for previously reported automated methods and comparable to manual segmentations. Accuracy of separation of individual mitochondria was 80% on a pixel basis. A total of 2315 mitochondria in the two series of SBEM images were evaluated with a mean volume of 0.78 µm³. The volume distribution was very broad and skewed; the most frequent mitochondria were 0.04–0.06 µm³, but mitochondria larger than 2.0 µm³ accounted for more than 10% of the total number. The average short-axis length was 0.47 µm. Primarily longitudinal mitochondria (0–30 degrees) were dominant (54%). This new automated segmentation and separation method can help quantitate mitochondrial morphology and improve understanding of myocyte structure–function relationships.     

Simple low-cost approaches to semantic segmentation in radiation therapy planning for prostate cancer using deep learning with non-contrast planning CT images

PurposeDeep learning has shown great efficacy for semantic segmentation. However, there are difficulties in the collection, labeling and management of medical imaging data, because of ethical complications and the limited number of imaging studies available at a single facility.This study aimed to find a simple and low-cost method to increase the accuracy of deep learning semantic segmentation for radiation therapy of prostate cancer.MethodsIn total, 556 cases with non-contrast CT images for prostate cancer radiation therapy were examined using a two-dimensional U-Net. Initially, all slices were used for the input data. Then, we removed slices of the cranial portions, which were beyond the margins of the bladder and rectum. Finally, the ground truth labels for the bladder and rectum were added as channels to the input for the prostate training dataset.ResultsThe highest mean dice similarity coefficients (DSCs) for each organ in the test dataset of 56 cases were 0.85 ± 0.05, 0.94 ± 0.04 and 0.85 ± 0.07 for the prostate, bladder and rectum, respectively. Removal of the cranial slices from the original images significantly increased the DSC of the rectum from 0.83 ± 0.09 to 0.85 ± 0.07 (p < 0.05). Adding bladder and rectum information to prostate training without removing the slices significantly increased the DSC of the prostate from 0.79 ± 0.05 to 0.85 ± 0.05 (p < 0.05).ConclusionsThese cost-free approaches may be useful for new applications, which may include updated models and datasets. They may be applicable to other organs at risk (OARs) and clinical targets such as elective nodal irradiation.     

The evolution of arthropod limbs

Limb morphology across the arthropods is reviewed using external morphological and internal anatomical data from both recent and fossil arthropods. Evolutionary trends in limb structure are identified primarily by reference to the more rigorous of the many existing phylogenetic schemes, but no major new phylogenetic inferences are presented. Tagmosis patterns are not considered, although the origins and patterns of heteronomy within the postantennulary limb series are analysed. The phenomenon of annulation is examined and two basic types of annuli are recognised: terminal and intercalary. The annulation of the apical segment of a limb results in the formation of terminal flagella, and is typical of primarily sensory appendages such as insect and malacostracan antennules and maxillary palps of some hexapods. Intercalary annulation, arising by subdivision of existing subterminal segments, is common, particularly in the tarsal region of arthropodan walking limbs. Differentiating between segments and annuli is discussed and is recognised as a limiting factor in the interpretation of fossils, which usually lack information on intrinsic musculature, and in the construction of groundplans. Rare examples of secondary segmentation, where the criteria for distinguishing between segments and annuli fail, are also highlighted. The basic crown-group arthropodan limb is identified as tripartite, comprising protopodite, telopodite and exopodite, and the basic segmentation patterns of each of these parts are hypothesised. Possible criteria are discussed that can be used for establishing the boundary between protopodite and telopodite in limbs that are uniramous through loss of the exopodite. The subdivision of the protopodite, which is typical of the postantennulary limbs of mandibulates, is examined. The difficulties resulting from the partial or complete failure of expression of articulations within the mandibulate protopodite and subsequent incorporation of partial protopodal segments into the body wall, are also discussed. The development and homology between the various exites, including gills, on the postantennulary limbs of arthropods are considered in some detail, and the question of the possible homology between crustacean gills and insect wings is critically addressed. The hypothesis that there are only two basic limb types in arthropods, antennules and postantennulary limbs, is proposed and its apparent contradiction by the transformation of antennules into walking limbs by homeotic mutation is discussed with respect to the appropriate level of serial homology between these limbs.     

Consumer Attitudes Toward Animal Welfare-Friendly Products and Willingness to Pay: Exploration of Mexican Market Segments

The study aim was to identify consumer segmentation based on nonhuman animal welfare (AW) attitudes and their relationship with demographic features and willingness to pay (WTP) for welfare-friendly products (WFP) in Mexico. Personal interviews were conducted with 843 Mexican consumers who stated they purchased most of the animal products in their home. Respondents were selected using a quota sampling method with age, gender, education, and origin as quota control variables. The multivariate analysis suggested there were three clusters or consumer profiles labeled “skeptical,” “concerned,” and “ethical,” which helped explain the association between AW attitudes, some demographic variables, and WTP for WFP. This study is one of the first to address consumer profiling in Latin America, and the findings could have implications for the commercialization of WFP. Hence, customers should receive information to consider welfare innovations when deciding to purchase animal products. The growth of the WFP food market establishes an element of a far more multifaceted phenomenon of sustainable consumption and support of a new paradigm called responsible marketing in emerging markets such as Mexico.     

Automatic lung segmentation in COVID-19 patients: Impact on quantitative computed tomography analysis

PurposeTo assess the impact of lung segmentation accuracy in an automatic pipeline for quantitative analysis of CT images.MethodsFour different platforms for automatic lung segmentation based on convolutional neural network (CNN), region-growing technique and atlas-based algorithm were considered. The platforms were tested using CT images of 55 COVID-19 patients with severe lung impairment. Four radiologists assessed the segmentations using a 5-point qualitative score (QS). For each CT series, a manually revised reference segmentation (RS) was obtained. Histogram-based quantitative metrics (QM) were calculated from CT histogram using lung segmentationsfrom all platforms and RS. Dice index (DI) and differences of QMs (ΔQMs) were calculated between RS and other segmentations.ResultsHighest QS and lower ΔQMs values were associated to the CNN algorithm. However, only 45% CNN segmentations were judged to need no or only minimal corrections, and in only 17 cases (31%), automatic segmentations provided RS without manual corrections. Median values of the DI for the four algorithms ranged from 0.993 to 0.904. Significant differences for all QMs calculated between automatic segmentations and RS were found both when data were pooled together and stratified according to QS, indicating a relationship between qualitative and quantitative measurements. The most unstable QM was the histogram 90th percentile, with median ΔQMs values ranging from 10HU and 158HU between different algorithms.ConclusionsNone of tested algorithms provided fully reliable segmentation. Segmentation accuracy impacts differently on different quantitative metrics, and each of them should be individually evaluated according to the purpose of subsequent analyses.     

A semi-automated method for hexahedral mesh construction of human vertebrae from CT scans

Generation of finite element (FE) meshes of vertebrae from computed tomography (CT) scans is labour intensive due to their geometric complexity. As such, techniques that simplify creation of meshes of vertebrae are needed to make FE analysis feasible for large studies and clinical applications. Techniques to obtain a geometric representation of bone contours from CT scans of vertebrae and construct a hexahedral mesh from the contours were developed. An automated edge detection technique was developed to identify surface contours of the vertebrae, followed by atlas based B-spline curve fitting to construct curves from the edge points. The method was automatic and robust to missing data, with a controllable degree of smoothing and interpolation. Parametric mapping was then used to generate nodes for each CT slice, which were connected between slices to obtain a hexahedral mesh. This method could be adapted for modelling a variety of orthopaedic structures.     

一种基于视网膜主血管方向的视盘定位及提取方法

为分割出眼底图像中的视盘,构建基于眼底图像的计算机辅助诊断系统,提出了一种基于视网膜主血管方向的视盘定位及提取方法。首先,利用Otsu阈值分割眼底图像R通道获取视盘候选区域;然后利用彩色眼底图像的HSV空间的H通道提取视网膜主血管并确定主血管方向;在此基础上,通过在方向图内寻找出对加权匹配滤波器响应值最高的点确定视盘中心位置;最后,利用该位置信息从视盘候选区域中"挑选"出真正的视盘。利用该方法对100幅不同颜色、不同亮度的眼底图像进行视盘分割,得到准确率98%,平均每幅图像处理时间1.3 s。结果表明:该方法稳定可靠,能快速、有效分割出眼底图像中的视盘。     

Interactive graph-cut segmentation for fast creation of finite element models from clinical ct data for hip fracture prediction

In this study, we propose interactive graph cut image segmentation for fast creation of femur finite element (FE) models from clinical computed tomography scans for hip fracture prediction. Using a sample of N = 48 bone scans representing normal, osteopenic and osteoporotic subjects, the proximal femur was segmented using manual (gold standard) and graph cut segmentation. Segmentations were subsequently used to generate FE models to calculate overall stiffness and peak force in a sideways fall simulations. Results show that, comparable FE results can be obtained with the graph cut method, with a reduction from 20 to 2–5 min interaction time. Average differences between segmentation methods of 0.22 mm were not significantly correlated with differences in FE derived stiffness (R² = 0.08, p = 0.05) and weakly correlated to differences in FE derived peak force (R² = 0.16, p = 0.01). We further found that changes in automatically assigned boundary conditions as a consequence of small segmentation differences were significantly correlated with FE derived results. The proposed interactive graph cut segmentation software MITK-GEM is freely available online at https://simtk.org/home/mitk-gem.