A new approach to analysis of intracellular proteins and subcellular localization using cellprofiler and imageJ in combination.

Analytical pipeline, which is used for various analysis application, of CellProfiler, an open-source software for cell imaging analysis, is very important. In the present study, to examine whether intracellular proteins can be discriminated using a combination of CellProfiler and ImageJ, we analyzed neuroblastoma and monocytic cell lines, and disease-specific induced pluripotent stem cell (iPSC)-derived neurons. This revealed that scattered puncta of Rab7 and transferrin in neuroblastoma lines were clearly detectable by created analytical pipelines in CellProfiler. We then constructed pipelines for measuring the distance from the center of the nucleus to allow investigation of the intracellular localization of Rab7 or transferrin. Using CellProfiler and ImageJ in combination, we confirmed that our pipelines were applicable both quantitatively and objectively to analysis of membrane trafficking of proteins such as Rab proteins and transferrin. In addition, when applied to quantitative measurement of phagocytosis, our pipelines clearly detected monocytic cell lines that had engulfed bioparticles. Finally, we developed new pipelines for analysis of disease phenotype using iPSCs from a patient with familial Parkinson's disease (PD), harboring the I2020T LRRK2 mutation (PARK8). These were able to successfully detect Rab5 puncta and Rab7 puncta in PARK8 patient iPSC-derived neurons. Interestingly, in long-term culture, we found that the numbers of Rab7 puncta in a single PARK8 patient iPSC-derived neurons were lower than that of control iPSC-derived neurons. On the other hands, at 14 days in vitro, the numbers of Rab5 puncta in PARK8 patient iPSC-derived neurons were lower than those of isogenic iPSC-derived neurons, but not Rab7 puncta. Furthermore, Rab5 puncta of PARK8 patient iPSC-derived neurons exhibited distinct localization pattern relative to isogenic iPSC-derived neurons. These present results suggest that this new analytical tool can be used as a supporting method for quantification of intracellular protein.

Accuracy of automated intracerebral hemorrhage volume measurement on non-contrast computed tomography: a Swedish Stroke Register cohort study.

PURPOSE: Hematoma volume is the strongest predictor of patient outcome after intracerebral hemorrhage (ICH). The aim of this study was to validate novel fully automated software for quantification of ICH volume on non-contrast computed tomography (CT). METHODS: The population was defined from the Swedish Stroke Register (RS) and included all patients with an ICH diagnosis during 2016-2019 in Region Skåne. Hemorrhage volume on their initial head CT was measured using ABC/2 and manual segmentation (Sectra IDS7 volume measurement tool) and the automated volume quantification tool (qER-NCCT) by Qure.ai. The first 500 were examined by two independent readers. RESULTS: A total of 1649 ICH patients were included. The qER-NCCT had 97% sensitivity in identifying ICH. In total, there was excellent agreement between volumetric measurements of ICH volumes by qER-NCCT and manual segmentation by interclass correlation (ICC = 0.96), and good agreement (ICC = 0.86) between qER-NCCT and ABC/2 method. The qER-NCCT showed volume underestimation, mainly in large (> 30 ml) heterogenous hemorrhages. Interrater agreement by (ICC) was 0.996 (95% CI: 0.99-1.00) for manual segmentation. CONCLUSION: Our study showed excellent agreement in volume quantification between the fully automated software qER-NCCT and manual segmentation of ICH on NCCT. The qER-NCCT would be an important additive tool by aiding in early diagnostics and prognostication for patients with ICH and in provide volumetry on a population-wide level. Further refinement of the software should address the underestimation of ICH volume seen in a portion of large, heterogenous, irregularly shaped ICHs.

CellTool: An Open-Source Software Combining Bio-Image Analysis and Mathematical Modeling for the Study of DNA Repair Dynamics.

Elucidating the dynamics of DNA repair proteins is essential to understanding the mechanisms that preserve genomic stability and prevent carcinogenesis. However, the measurement and modeling of protein dynamics at DNA lesions via currently available image analysis tools is cumbersome. Therefore, we developed CellTool-a stand-alone open-source software with a graphical user interface for the analysis of time-lapse microscopy images. It combines data management, image processing, mathematical modeling, and graphical presentation of data in a single package. Multiple image filters, segmentation, and particle tracking algorithms, combined with direct visualization of the obtained results, make CellTool an ideal application for the comprehensive analysis of DNA repair protein dynamics. This software enables the fitting of obtained kinetic data to predefined or custom mathematical models. Importantly, CellTool provides a platform for easy implementation of custom image analysis packages written in a variety of programing languages. Using CellTool, we demonstrate that the ALKB homolog 2 (ALKBH2) demethylase is excluded from DNA damage sites despite recruitment of its putative interaction partner proliferating cell nuclear antigen (PCNA). Further, CellTool facilitates the straightforward fluorescence recovery after photobleaching (FRAP) analysis of BRCA1 associated RING domain 1 (BARD1) exchange at complex DNA lesions. In summary, the software presented herein enables the time-efficient analysis of a wide range of time-lapse microscopy experiments through a user-friendly interface.

ChromaWizard: An open source image analysis software for multicolor fluorescence in situ hybridization analysis.

Multicolor image analysis finds its applications in a broad range of biological studies. Specifically, multiplex fluorescence in situ hybridization (M-FISH) for chromosome painting facilitates the analysis of individual chromosomes in complex metaphase spreads and is widely used to detect both numerical and structural aberrations. While this is well established for human and mouse karyotypes, for which species sophisticated software and analysis tools are available, other organisms and species are less well served. Commercially available software is proprietary and not easily adaptable to other karyotypes. Therefore, a publically available open source software that combines flexibility and customizable functionalities is needed. Here we present such a tool called "ChromaWizard" which is based on popular scientific image analysis libraries (OpenCV, scikit-image, and NumPy). We demonstrate its functionality on the example of primary Chinese hamster (Cricetulus griseus) fibroblasts metaphase spreads and on Chinese Hamster Ovary cell lines known for the large number of chromosomal rearrangements. The application can be easily adapted to any kind of available labeling kits and is independent of the used organism and instrumentation. It allows direct inspection of the original hybridization signals and enables either manual or automatic assignment of colors, making it a functional and versatile tool that can be used also for other multicolor applications.

Automated classification and characterization of the mitotic spindle following knockdown of a mitosis-related protein.

BACKGROUND: Cell division (mitosis) results in the equal segregation of chromosomes between two daughter cells. The mitotic spindle plays a pivotal role in chromosome alignment and segregation during metaphase and anaphase. Structural or functional errors of this spindle can cause aneuploidy, a hallmark of many cancers. To investigate if a given protein associates with the mitotic spindle and regulates its assembly, stability, or function, fluorescence microscopy can be performed to determine if disruption of that protein induces phenotypes indicative of spindle dysfunction. Importantly, functional disruption of proteins with specific roles during mitosis can lead to cancer cell death by inducing mitotic insult. However, there is a lack of automated computational tools to detect and quantify the effects of such disruption on spindle integrity. RESULTS: We developed the image analysis software tool MatQuantify, which detects both large-scale and subtle structural changes in the spindle or DNA and can be used to statistically compare the effects of different treatments. MatQuantify can quantify various physical properties extracted from fluorescence microscopy images, such as area, lengths of various components, perimeter, eccentricity, fractal dimension, satellite objects and orientation. It can also measure textual properties including entropy, intensities and the standard deviation of intensities. Using MatQuantify, we studied the effect of knocking down the protein clathrin heavy chain (CHC) on the mitotic spindle. We analysed 217 microscopy images of untreated metaphase cells, 172 images of metaphase cells transfected with small interfering RNAs targeting the luciferase gene (as a negative control), and 230 images of metaphase cells depleted of CHC. Using the quantified data, we trained 23 supervised machine learning classification algorithms. The Support Vector Machine learning algorithm was the most accurate method (accuracy: 85.1%; area under the curve: 0.92) for classifying a spindle image. The Kruskal-Wallis and Tukey-Kramer tests demonstrated that solidity, compactness, eccentricity, extent, mean intensity and number of satellite objects (multipolar spindles) significantly differed between CHC-depleted cells and untreated/luciferase-knockdown cells. CONCLUSION: MatQuantify enables automated quantitative analysis of images of mitotic spindles. Using this tool, researchers can unambiguously test if disruption of a protein-of-interest changes metaphase spindle maintenance and thereby affects mitosis.

High-throughput imaging: Focusing in on drug discovery in 3D.

3D organotypic culture models such as organoids and multicellular tumor spheroids (MCTS) are becoming more widely used for drug discovery and toxicology screening. As a result, 3D culture technologies adapted for high-throughput screening formats are prevalent. While a multitude of assays have been reported and validated for high-throughput imaging (HTI) and high-content screening (HCS) for novel drug discovery and toxicology, limited HTI/HCS with large compound libraries have been reported. Nonetheless, 3D HTI instrumentation technology is advancing and this technology is now on the verge of allowing for 3D HCS of thousands of samples. This review focuses on the state-of-the-art high-throughput imaging systems, including hardware and software, and recent literature examples of 3D organotypic culture models employing this technology for drug discovery and toxicology screening.

Precision and Speed at Your Fingertips: An Automated Intracranial Hematoma Volume Calculation.

BACKGROUND: Intracranial hemorrhage (ICH) is a severe condition that requires rapid diagnosis and treatment. Automated methods for calculating ICH volumes can reduce human error and improve clinical decisioPlease provide professional degrees (e.g., PhD, MD) for the corresponding author.n-making. A novel automated method has been developed that is comparable to the ABC/2 method in terms of speed and accuracy while providing more accurate volumetric data. METHODS: We developed a novel automated algorithm for calculating intracranial blood volume from computed tomography (CT) scans. The algorithm consists of a Python script that processes Digital Imaging and Communications in Medicine images and determines the blood volume and ratio. The algorithm was validated against manual calculations performed by neurosurgeons. RESULTS: Our novel automated algorithm for calculating intracranial blood volume from CT scans demonstrated excellent agreement with the ABC/2 method, with a median overall difference of just 1.46 mL. The algorithm was also validated in patient groups with ICH, epidural hematoma (EDH), and SDH, with agreement coefficients of 0.992, 0.983, and 0.997, respectively. CONCLUSIONS: The study introduces a novel automated algorithm for calculating the volumes of various ICHs (EDH, and SDH) within CT scans. The algorithm showed excellent agreement with manual calculations and outperformed the commonly used ABC/2 method, which tends to overestimate ICH volume. The automated algorithm offers a more accurate, efficient, and time-saving approach to quantifying ICH, EDH, and SDH volumes, making it a valuable tool for clinical evaluation and decision-making.

Topographical changes in extracellular matrix during skin fibrosis and recovery can be evaluated using automated image analysis algorithms.

Skin fibrosis is characterized by fibroblast activation and intradermal fat loss, resulting in excess deposition and remodeling of dermal extracellular matrix (ECM). The topography of the dominant ECM proteins, such as collagens, can indicate skin stiffness and remains understudied in evaluating fibrotic skin. Here, we adapted two different unbiased image analysis algorithms to define collagen topography and alignment in a genetically inducible and reversible Wnt activation fibrosis model. We demonstrated that Wnt-activated fibrotic skin has altered collagen fiber characteristics and a loss of collagen alignment, which were restored in the reversible model. This study highlights how unbiased algorithms can be used to analyze ECM topography, providing novel avenues to evaluate fibrotic skin onset, recovery, and treatment.

Localization of EGFR Mutations in Non-small-cell Lung Cancer Tissues Using Mutation-specific PNA-DNA Probes.

BACKGROUND/AIM: Epidermal growth factor receptor (EGFR) signaling inhibitors are potent therapeutic agents for EGFR-mutant non-small-cell lung cancer, but the effects of such inhibitors on the localization of EGFR mutations in tumor tissues remain to be elucidated. Thus, a simple and efficient technology for the detection of mutations in tumor tissue specimens needs to be developed. MATERIALS AND METHODS: Using an EGFR mutation-specific peptide nucleic acid (PNA)-DNA probe, the EGFR mutation-positive part of whole NSCLC tissues was visualized by immunofluorescence. Formalin-fixed paraffin-embedded sections obtained from A549, NCI-H1975, HCC827 and PC-9 tumors transplanted into nude mice were subjected to staining using PNA-DNA probes specific for the mRNA sequences producing the L858R, del E746-A750 and T790M mutations. RESULTS: The probes for the L858R mutation showed intense positive staining in H1975 cells, and the probe for the del E746-A750 mutation exhibited positive staining specifically in HCC827 and PC-9 tumors. On the other hand, A549 tumors without EGFR mutation did not show any significant staining for any PNA-DNA probe. In combination staining, the addition of cytokeratin stain increased the positive staining rate of each PNA-DNA probe. In addition, the positive staining rate of the probes for the L858R mutation was comparable to that of the antibody to EGFR L858R mutated protein. CONCLUSION: PNA-DNA probes specific for EGFR mutations might be useful tools to detect heterogeneous mutant EGFR expression in cancer tissues and efficiently evaluate the effect of EGFR signaling inhibitors on tissues of EGFR-mutant cancer.

Three-dimensional analysis of the morphological changes of the craniofacial jaw and condyle in patients with idiopathic condylar resorption.

In this study we aim to describe the three-dimensional analysis of condylar deformation of the temporomandibular joint (TMJ) and morphological changes of the craniofacial jaw in patients with idiopathic condylar resorption (ICR). We also compare those with a control group that is healthy and matched for age and gender. Cone-beam computed tomography (CBCT) and cephalometric radiograph (X-ray) were conducted and analysis of craniofacial measurement, condylar width, length, height, and condylar axial angle changes were done three-dimensionally using ProPlan CMF™ 3.0 software (Materialise). The craniofacial jaw measurements of the ICR patients were significantly different than the control group and the significant changes in the mandible can be seen in ICR patients according to the results of this study. The results of smaller condylar width and height in the ICR group reflect the smaller size of the condyle compared with an unaffected condyle. Also, both right and left sagittal condylar angles (p = 0.001 and p = 0.003), respectively, and axial condylar angles (p = 0.01 and p = 0.02), respectively, displayed significant differences between the two groups. In conclusion, the vertical development of the condyle decreased along with reduced measurements in the width and height of the condyle in ICR patients, and differences in the morphology of the craniofacial jaw and condylar angles were observed between study groups.

Detection and Quantification of Protein Aggregates in Plants.

Protein quality control is an important aspect of stress recovery. It maintains protein homeostasis through a machinery of regulatory proteins such as chaperones and proteases. When the system recognizes accumulation of misfolded or aggregated proteins, the cell recruits a set of regulatory proteins to initiate protein quality control. To understand the dynamics of stress-mediated aggregate protein formation and recovery in plants, robust methods aimed at detecting and measuring such protein aggregates are needed. This will help us to deepen our understanding of protein quality control mechanisms in plants.

Deep Learning-Based Image Analysis for the Quantification of Tumor-Induced Angiogenesis in the 3D In Vivo Tumor Model-Establishment and Addition to Laser Speckle Contrast Imaging (LSCI).

(1) Background: angiogenesis plays an important role in the growth and metastasis of tumors. We established the CAM assay application, an image analysis software of the IKOSA platform by KML Vision, for the quantification of blood vessels with the in ovo chorioallantoic membrane (CAM) model. We added this proprietary deep learning algorithm to the already established laser speckle contrast imaging (LSCI). (2) Methods: angiosarcoma cell line tumors were grafted onto the CAM. Angiogenesis was measured at the beginning and at the end of tumor growth with both measurement methods. The CAM assay application was trained to enable the recognition of in ovo CAM vessels. Histological stains of the tissue were performed and gluconate, an anti-angiogenic substance, was applied to the tumors. (3) Results: the angiosarcoma cells formed tumors on the CAM that appeared to stay vital and proliferated. An increase in perfusion was observed using both methods. The CAM assay application was successfully established in the in ovo CAM model and anti-angiogenic effects of gluconate were observed. (4) Conclusions: the CAM assay application appears to be a useful method for the quantification of angiogenesis in the CAM model and gluconate could be a potential treatment of angiosarcomas. Both aspects should be evaluated in further research.

Open access tool and microfluidic devices for phenotypic quantification of heart function of intact fruit fly and zebrafish larvae.

In this paper, the heartbeat parameters of small model organisms, i.e. Drosophila melanogaster (fruit fly) and Danio rerio (zebrafish), were quantified in-vivo in intact larvae using microfluidics and a novel MATLAB-based software. Among different developmental stages of flies and zebrafish, the larval stage is privileged due to biological maturity, optical accessibility, and the myogenic nature of the heart. Conventional methods for parametric quantification of heart activities are complex and mostly done on dissected, irreversibly immobilized, or anesthetized larvae. Microfluidics has helped with reversible immobilization without the need for anesthesia, but heart monitoring is still done manually due to challenges associated with the movement of floating organs and cardiac interruptions. In our MATLAB software applied to videos recorded in microfluidic-based whole-organism assays, we have used image segmentation to automatically detect the heart and extract the heartbeat signal based on pixel intensity variations of the most contractile region of the heart tube. The smoothness priors approach (SPA) was applied to remove the undesired low-frequency noises caused by environmental light changes or heart movement. Heart rate and arrhythmicity were automatically measured from the detrended heartbeat signal while other parameters including end-diastolic and end-systolic diameters, shortening distance, shortening time, fractional shortening, and shortening velocity were quantified for the first time in intact larvae, using M-mode images under bright field microscopy. The software was able to detect more than 94% of the heartbeats and the cardiac arrests in intact Drosophila larvae. Our user-friendly software enables in-vivo quantification of D. melanogaster and D. rerio larval heart functions in microfluidic devices, with the potential to be applied to other biological models and used for automatic screening of drugs and alleles that affect their heart.

Comparative Aesthetic Evaluation of Lip Reconstruction Using Abbe's Flap in Secondary Cleft Lip Deformities: A Retrospective Study.

AIM: To objectively evaluate the surgical outcome of deformed cleft lip treated by Abbe's flap using Digimizer image analysis software. METHODS: Fifteen Abbe's flap (AF) reconstruction cases with satisfactory photographic records were acquired in Digimizer image analysis software. Anthropometric landmarks were marked on the lip. Bilateral lip lengths, height and width were measured preoperatively and postoperatively after AF reconstruction for comparison. RESULTS: It was observed that by AF reconstruction, we could increase vermillion lip length and Cupid's bow width, hence providing adequate bulk to the middle of the lip. In addition to it, in some cases we could achieve the acceptable anatomy of the centre of the Cupid's bow with which it was sometimes disturbed during primary cheiloplasty. Lip length and lip height became proportionately equal bilaterally, leading to adequate lip symmetry in all cases. CONCLUSION: Computer-assisted anthropometric analysis of photographs using Digimizer image analysis software (MedCalc Software, Belgium) demonstrates that AF lip reconstruction technique produces aesthetic lip consistently.

A Co-registration Pipeline for Multimodal MALDI and Confocal Imaging Analysis of Stem Cell Colonies.

Multimodal mass spectrometry imaging (MSI) data presents unique big data challenges in handling and analysis. Here, we present a pipeline for co-registering matrix-assisted laser desorption/ionization MSI and confocal immunofluorescence imaging data for extracting single-cell metabolite signatures. We further describe methods and introduce software for the simultaneous analysis of these concatenated data sets, which are designed to establish a connection between cell traits of interest (shape metrics, position within sample) and the cells' own metabolic signatures.

Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods.

Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation. These new features include C++-based code optimization for fast individual fiber tracking, Java-based synthetic fiber generator module for method validation, automatic tumor boundary generation for fiber relative quantification, parallel computing for large-scale batch mode processing, region-of-interest analysis for user-specified quantification, and pre- and post-processing modules for individual fiber visualization. We present a validation of the tracking of individual fibers and fiber orientations by using synthesized fibers generated by the synthetic fiber generator. In addition, we provide a comparison of the fiber orientation calculation on pancreatic tissue images between our tool and three other quantitative approaches. Lastly, we demonstrate the use of our software tool for the automatic tumor boundary creation and the relative alignment quantification of collagen fibers in human breast cancer pathology images, as well as the alignment quantification of in vivo mouse xenograft breast cancer images.

What's the Difference? 2D DIGE Image Analysis by DeCyderTM versus SameSpotsTM.

The efficiency and reproducibility of two-dimensional difference gel electrophoresis (2D DIGE) depends on several crucial steps: (i) adequate number of replicate gels, (ii) accurate image acquisition, and (iii) statistically confident protein abundance analysis. The latter is inherently determined by the image analysis system. Available software solutions apply different strategies for consecutive image alignment and protein spot detection. While DeCyderTM performs spot detection on single gels prior to the alignment of spot maps, SameSpotsTM completes image alignment in advance of spot detection. In this study, the performances of DeCyderTM and SameSpotsTM were compared considering all protein spots detected in 2D DIGE resolved proteomes of three different environmental bacteria with minimal user interference. Proteome map-based analysis by SameSpotsTM allows for fast and reproducible abundance change determination, avoiding time-consuming, manual spot matching. The different raw spot volumes, determined by the two software solutions, did not affect calculated abundance changes. Due to a slight factorial difference, minor abundance changes were very similar, while larger differences in the case of major abundance changes did not impact biological interpretation in the studied cases. Overall, affordable fluorescent dyes in combination with fast CCD camera-based image acquisition and user-friendly image analysis still qualify 2D DIGE as a valuable tool for quantitative proteomics.

Cell-to-cell distances between tumor-infiltrating inflammatory cells have the potential to distinguish functionally active from suppressed inflammatory cells.

Beyond their mere presence, the distribution pattern of inflammatory cells is of special interest. Our hypothesis was that random distribution may be a clear indicator of being non-functional as a consequence of lack of interaction. Here, we have assessed the implication of cell-to-cell distances among inflammatory cells in anal squamous cell carcinoma and a possible association with survival data. Thirty-eight patients suffering from anal carcinoma were studied using tissue microarrays, double staining immunohistochemistry, whole slide scanning and image analysis software. Therapy consisted of concurrent radiochemotherapy. Numbers of stromal and intraepithelial tumor-infiltrating inflammatory cells (TIC) and the distances between cells were quantified. Double-staining of FoxP3(+) cells with either CD8(+), CD1a(+) or CD20(+) cells was performed. Measured cell-to-cell distances were compared to computer simulated cell-to-cell distances leading to the assumption of non-randomly distributed and therefore functional immune cells. Intraepithelial CD1a(+) and CD20(+) cells were randomly distributed and therefore regarded as non-functional. In contrary, stromal CD20(+) cells had a non-random distribution pattern. A non-random distance between CD20(+) and FoxP3(+) cells was associated with a clearly unfavorable outcome. Measured distances between FoxP3(+) cells were distinctly shorter than expected and indicate a functional active state of the regulatory T cells (Treg). Analysis of cell-to-cell distances between TIC has the potential to distinguish between suppressed non-functional and functionally active inflammatory cells. We conclude that in this tumor model most of the CD1a(+) cells are non-functional as are the intraepithelial CD20(+) cells, while stromal CD20(+) cells and FoxP3(+) cells are functional cells.

Development of a viability standard curve for microencapsulated probiotic bacteria using confocal microscopy and image analysis software.

Microencapsulation is proposed to protect probiotic strains from food processing procedures and to maintain probiotic viability. Little research has described the in situ viability of microencapsulated probiotics. This study successfully developed a real-time viability standard curve for microencapsulated bacteria using confocal microscopy, fluorescent dyes and image analysis software.