Computational Simulation of LAVA Treatment of Thyroid Eye Disease Predicts Soft Tissue Outcome Comparable to Two-Wall Resection.

Thyroid eye disease (TED) is a common extrathyroidal manifestation of hyperthyroidism, typically associated with Graves' disease (GD). This condition can cause severe functional limitations as well as significant aesthetic concerns. Treatment for TED patients aims to restore functionality and address aesthetic concerns.

Linel2D-Net: A deep learning approach to solving 2D linear elastic boundary value problems on image domains.

Efficient solution of physical boundary value problems (BVPs) remains a challenging task demanded in many applications. Conventional numerical methods require time-consuming domain discretization and solving techniques that have limited throughput capabilities. Here, we present an efficient data-driven DNN approach to non-iterative solving arbitrary 2D linear elastic BVPs.

High-Throughput Spike Detection in Greenhouse Cultivated Grain Crops with Attention Mechanisms-Based Deep Learning Models.

Detection of spikes is the first important step toward image-based quantitative assessment of crop yield. However, spikes of grain plants occupy only a tiny fraction of the image area and often emerge in the middle of the mass of plant leaves that exhibit similar colors to spike regions. Consequently, accurate detection of grain spikes renders, in general, a non-trivial task even for advanced, state-of-the-art deep neural networks (DNNs).

Awn Image Analysis and Phenotyping Using BarbNet.

Consideration of the properties of awns is important for the phenotypic description of grain crops. Awns have a number of important functions in grasses, including assimilation, mechanical protection, and seed dispersal and burial. An important feature of the awn is the presence or absence of barbs-tiny hook-like single-celled trichomes on the outer awn surface that can be visualized using microscopic imaging.

FDM data driven U-Net as a 2D Laplace PINN solver.

Efficient solution of partial differential equations (PDEs) of physical laws is of interest for manifold applications in computer science and image analysis. However, conventional domain discretization techniques for numerical solving PDEs such as Finite Difference (FDM), Finite Element (FEM) methods are unsuitable for real-time applications and are also quite laborious in adaptation to new applications, especially for non-experts in numerical mathematics and computational modeling. More recently, alternative approaches to solving PDEs using the so-called Physically Informed Neural Networks (PINNs) received increasing attention because of their straightforward application to new data and potentially more efficient performance.

Effect of the lateral wall valgisation in the treatment of patients with endocrine orbitopathy.

Orbital decompression is an established procedure used to correct exophthalmos that results from excess orbital soft tissue. This study aimed to explore a new minimally-invasive technique that features three-dimensional planning and patient-specific implants for lateral valgisation (LAVA) of the orbital wall. We analysed the outcomes of this procedure in nine endocrine orbitopathy (EO) patients (32-65 years of age with a mean clinical activity score of 4.

Deep Learning Based Greenhouse Image Segmentation and Shoot Phenotyping (DeepShoot).

Background: Automated analysis of large image data is highly demanded in high-throughput plant phenotyping. Due to large variability in optical plant appearance and experimental setups, advanced machine and deep learning techniques are required for automated detection and segmentation of plant structures in complex optical scenes.

Methods: Here, we present a GUI-based software tool (DeepShoot) for efficient, fully automated segmentation and quantitative analysis of greenhouse-grown shoots which is based on pre-trained U-net deep learning models of arabidopsis, maize, and wheat plant appearance in different rotational side- and top-views.

Consideration of specific key points improves outcome of decompression treatment in patients with endocrine orbitopathy: pre-/post-OP comparison and biomechanical simulation.

Endocrine orbitopathy is typically treated by resecting orbital walls. This procedure reduces intraorbital pressure by releasing intraorbital tissue, effectively alleviating the symptoms. However, selection of an appropriate surgical plan for treatment of endocrine orbitopathy requires careful consideration because predicting the effects of one-, two-, or three-wall resections on the release of orbital tissues is difficult.

Towards Automated Analysis of Grain Spikes in Greenhouse Images Using Neural Network Approaches: A Comparative Investigation of Six Methods.

Automated analysis of small and optically variable plant organs, such as grain spikes, is highly demanded in quantitative plant science and breeding. Previous works primarily focused on the detection of prominently visible spikes emerging on the top of the grain plants growing in field conditions. However, accurate and automated analysis of all fully and partially visible spikes in greenhouse images renders a more challenging task, which was rarely addressed in the past.

Fully-automated root image analysis (faRIA).

High-throughput root phenotyping in the soil became an indispensable quantitative tool for the assessment of effects of climatic factors and molecular perturbation on plant root morphology, development and function. To efficiently analyse a large amount of structurally complex soil-root images advanced methods for automated image segmentation are required. Due to often unavoidable overlap between the intensity of fore- and background regions simple thresholding methods are, generally, not suitable for the segmentation of root regions.

Transcriptome profiling reveals Silibinin dose-dependent response network in non-small lung cancer cells.

Silibinin (SIL), a natural flavonolignan from the milk thistle (Silybum marianum), is known to exhibit remarkable hepatoprotective, antineoplastic and EMT inhibiting effects in different cancer cells by targeting multiple molecular targets and pathways. However, the predominant majority of previous studies investigated effects of this phytocompound in a one particular cell line. Here, we carry out a systematic analysis of dose-dependent viability response to SIL in five non-small cell lung cancer (NSCLC) lines that gradually differ with respect to their intrinsic EMT stage.

Application of Aptamers Improves CRISPR-Based Live Imaging of Plant Telomeres.

Development of live imaging techniques for providing information how chromatin is organized in living cells is pivotal to decipher the regulation of biological processes. Here, we demonstrate the improvement of a live imaging technique based on CRISPR/Cas9. In this approach, the sgRNA scaffold is fused to RNA aptamers including MS2 and PP7.

A two-step registration-classification approach to automated segmentation of multimodal images for high-throughput greenhouse plant phenotyping.

Background: Automated segmentation of large amount of image data is one of the major bottlenecks in high-throughput plant phenotyping. Dynamic optical appearance of developing plants, inhomogeneous scene illumination, shadows and reflections in plant and background regions complicate automated segmentation of unimodal plant images. To overcome the problem of ambiguous color information in unimodal data, images of different modalities can be combined to a virtual multispectral cube.

Automated Spike Detection in Diverse European Wheat Plants Using Textural Features and the Frangi Filter in 2D Greenhouse Images.

Spike is one of the crop yield organs in wheat plants. Determination of the phenological stages, including heading time point (HTP), and area of spike from non-invasive phenotyping images provides the necessary information for the inference of growth-related traits. The algorithm previously developed by Qiongyan et al.

Gene Expression Profiling of Different Huh7 Variants Reveals Novel Hepatitis C Virus Host Factors.

Chronic Hepatitis C virus (HCV) infection still constitutes a major global health problem with almost half a million deaths per year. To date, the human hepatoma cell line Huh7 and its derivatives is the only cell line that robustly replicates HCV. However, even different subclones and passages of this single cell line exhibit tremendous differences in HCV replication efficiency.

Semi-automated Root Image Analysis (saRIA).

Quantitative characterization of root system architecture and its development is important for the assessment of a complete plant phenotype. To enable high-throughput phenotyping of plant roots efficient solutions for automated image analysis are required. Since plants naturally grow in an opaque soil environment, automated analysis of optically heterogeneous and noisy soil-root images represents a challenging task.

Retrospective cohort study of three-wall orbital resection for treatment of endocrine orbitopathy using 3D tomographic data and biomechanical modeling.

Background: Surgical treatment of endocrine orbitopathy can be performed by way of resecting orbital walls, which effectively releases superfluous tissue from the surgically enlarged orbital space allowing the eyeballs to move back. Existing approaches aim to select an optimal surgical strategy based on statistical correlations between the extent of the surgical procedure and the resulting bulbus displacement but do not provide an individual surgery plan or predict surgery outcome.

Methods: In this retrospective study, we performed a quantitative analysis of pre- and post-surgery 3D tomographic data of six patients and applied explorative biomechanical modeling of orbital mechanics to dissect factors influencing patient-specific outcome.

Comparison of feature point detectors for multimodal image registration in plant phenotyping.

With the introduction of multi-camera systems in modern plant phenotyping new opportunities for combined multimodal image analysis emerge. Visible light (VIS), fluorescence (FLU) and near-infrared images enable scientists to study different plant traits based on optical appearance, biochemical composition and nutrition status. A straightforward analysis of high-throughput image data is hampered by a number of natural and technical factors including large variability of plant appearance, inhomogeneous illumination, shadows and reflections in the background regions.

Comparison and extension of three methods for automated registration of multimodal plant images.

With the introduction of high-throughput multisensory imaging platforms, the automatization of multimodal image analysis has become the focus of quantitative plant research. Due to a number of natural and technical reasons (e.g.

Automated Alignment of Multi-Modal Plant Images Using Integrative Phase Correlation Approach.

Modern facilities for high-throughput phenotyping provide plant scientists with a large amount of multi-modal image data. Combination of different image modalities is advantageous for image segmentation, quantitative trait derivation, and assessment of a more accurate and extended plant phenotype. However, visible light (VIS), fluorescence (FLU), and near-infrared (NIR) images taken with different cameras from different view points in different spatial resolutions exhibit not only relative geometrical transformations but also considerable structural differences that hamper a straightforward alignment and combined analysis of multi-modal image data.

A combined planning approach for improved functional and esthetic outcome of bimaxillary rotation advancement for treatment of obstructive sleep apnea using 3D biomechanical modeling.

In recent years, bimaxillary rotation advancement (BRA) has become the method of choice for surgical treatment of obstructive sleep apnea (OSA). As dislocation of the jaw bones affects both, airways and facial contours, surgeons are facing the challenge of finding an optimal jaw position that allows for the reestablishment of normal airway ventilation and esthetic surgical outcome. Owing to the complexity of the facial anatomy and its mechanical behavior, individual planning of surgical OSA treatment under consideration of functional and esthetic aspects presents a challenge that surgeons typically approach in a non-quantitative manner using subjective evaluation and clinical experience.

The role of Vimentin in Regulating Cell Invasive Migration in Dense Cultures of Breast Carcinoma Cells.

Cell migration and mechanics are tightly regulated by the integrated activities of the various cytoskeletal networks. In cancer cells, cytoskeletal modulations have been implicated in the loss of tissue integrity and acquisition of an invasive phenotype. In epithelial cancers, for example, increased expression of the cytoskeletal filament protein vimentin correlates with metastatic potential.

Live-cell CRISPR imaging in plants reveals dynamic telomere movements.

Elucidating the spatiotemporal organization of the genome inside the nucleus is imperative to our understanding of the regulation of genes and non-coding sequences during development and environmental changes. Emerging techniques of chromatin imaging promise to bridge the long-standing gap between sequencing studies, which reveal genomic information, and imaging studies that provide spatial and temporal information of defined genomic regions. Here, we demonstrate such an imaging technique based on two orthologues of the bacterial clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 (Cas9).

Graph-theoretical model of global human interactome reveals enhanced long-range communicability in cancer networks.

Malignant transformation is known to involve substantial rearrangement of the molecular genetic landscape of the cell. A common approach to analysis of these alterations is a reductionist one and consists of finding a compact set of differentially expressed genes or associated signaling pathways. However, due to intrinsic tumor heterogeneity and tissue specificity, biomarkers defined by a small number of genes/pathways exhibit substantial variability.