Modeling of intravenous caspofungin administration using an intestine-on-chip reveals altered Candida albicans microcolonies and pathogenicity.

Candida albicans is a commensal yeast of the human intestinal microbiota that, under predisposing conditions, can become pathogenic and cause life-threatening systemic infections (candidiasis). Fungal-host interactions during candidiasis are commonly studied using conventional 2D in vitro models, which have provided critical insights into the pathogenicity. However, microphysiological models with a higher biological complexity may be more suitable to mimic in vivo-like infection processes and antifungal drug efficacy. Therefore, a 3D intestine-on-chip model was used to investigate fungal-host interactions during the onset of invasive candidiasis and evaluate antifungal treatment under clinically relevant conditions. By combining microbiological and image-based analyses we quantified infection processes such as invasiveness and fungal translocation across the epithelial barrier. Additionally, we obtained novel insights into fungal microcolony morphology and association with the tissue. Our results demonstrate that C. albicans microcolonies induce injury to the epithelial tissue by disrupting apical cell-cell contacts and causing inflammation. Caspofungin treatment effectively reduced the fungal biomass and induced substantial alterations in microcolony morphology during infection with a wild-type strain. However, caspofungin showed limited effects after infection with an echinocandin-resistant clinical isolate. Collectively, this organ-on-chip model can be leveraged for in-depth characterization of pathogen-host interactions and alterations due to antimicrobial treatment.

Plumbago Zeylanica (Chitrak) leaf image dataset: A comprehensive collection for botanical studies, herbal medicine research, and environmental analyses.

The Plumbago Zeylanica (Chitrak) Leaf Image Dataset is a valuable resource for botanical studies, herbal medicine research, and environmental analyses. Comprising a total of 10,660 high-resolution leaf images, the dataset is meticulously categorized into three distinct classes: Unhealthy leaves (3343 images), Healthy leaves (5288 images), and Dried leaves (2029 images). These images were captured from the medicinal plant Chitrak, a species of paramount importance in traditional medicine and environmental contexts. Researchers and practitioners can benefit from this dataset's richness in terms of both quantity and quality, using it to develop and test algorithms for leaf classification and health assessment. The Chitrak leaf image dataset holds the potential to foster innovative investigations and applications within the domains of botany, medicine, and environmental sciences.

An image-based high-content screening for compounds targeting Toxoplasma gondii repurposed inhibitors effective against the malaria parasite Plasmodium falciparum.

Apicomplexa phylum includes numerous obligate intracellular protozoan parasites that are life threatening for humans and animals. In this context, Plasmodium falciparum and Toxoplasma gondii are of particular interest, as they are responsible for malaria and toxoplasmosis, respectively, for which efficient vaccines are presently lacking and therapies need to be improved. Apicomplexan parasites have a highly polarized morphology, with their apical end containing specific secretory organelles named rhoptries and micronemes, which depend on the unique receptor and transporter sortilin TgSORT for their biogenesis. In the present study, we took advantage of the subcellular polarity of the parasite to engineer a clonal transgenic Toxoplasma line that expresses simultaneously the green fluorescent protein TgSORT-GFP in the post-Golgi-endosome-like compartment and the red fluorescent protein rhoptry ROP1-mCherry near the apical end. We utilized this fluorescent transgenic T. gondii to develop a miniaturized image-based phenotype assay coupled to an automated image analysis. By applying this methodology to 1,120 compounds, we identified 12 that are capable of disrupting the T. gondii morphology and inhibiting intracellular replication. Analysis of the selected compounds confirmed that all 12 are kinase inhibitors and intramembrane pumps, with some exhibiting potent activity against Plasmodium falciparum. Our findings highlight the advantage of comparative and targeted phenotypic analysis involving two related parasite species as a means of identifying molecules with a conserved mode of action.

OrBITS: label-free and time-lapse monitoring of patient derived organoids for advanced drug screening.

BACKGROUND: Patient-derived organoids are invaluable for fundamental and translational cancer research and holds great promise for personalized medicine. However, the shortage of available analysis methods, which are often single-time point, severely impede the potential and routine use of organoids for basic research, clinical practise, and pharmaceutical and industrial applications. METHODS: Here, we developed a high-throughput compatible and automated live-cell image analysis software that allows for kinetic monitoring of organoids, named Organoid Brightfield Identification-based Therapy Screening (OrBITS), by combining computer vision with a convolutional network machine learning approach. The OrBITS deep learning analysis approach was validated against current standard assays for kinetic imaging and automated analysis of organoids. A drug screen of standard-of-care lung and pancreatic cancer treatments was also performed with the OrBITS platform and compared to the gold standard, CellTiter-Glo 3D assay. Finally, the optimal parameters and drug response metrics were identified to improve patient stratification. RESULTS: OrBITS allowed for the detection and tracking of organoids in routine extracellular matrix domes, advanced Gri3D®-96 well plates, and high-throughput 384-well microplates, solely based on brightfield imaging. The obtained organoid Count, Mean Area, and Total Area had a strong correlation with the nuclear staining, Hoechst, following pairwise comparison over a broad range of sizes. By incorporating a fluorescent cell death marker, intra-well normalization for organoid death could be achieved, which was tested with a 10-point titration of cisplatin and validated against the current gold standard ATP-assay, CellTiter-Glo 3D. Using this approach with OrBITS, screening of chemotherapeutics and targeted therapies revealed further insight into the mechanistic action of the drugs, a feature not achievable with the CellTiter-Glo 3D assay. Finally, we advise the use of the growth rate-based normalised drug response metric to improve accuracy and consistency of organoid drug response quantification. CONCLUSION: Our findings validate that OrBITS, as a scalable, automated live-cell image analysis software, would facilitate the use of patient-derived organoids for drug development and therapy screening. The developed wet-lab workflow and software also has broad application potential, from providing a launching point for further brightfield-based assay development to be used for fundamental research, to guiding clinical decisions for personalized medicine.

Simulation and Experimental Substantiation of the Thermal Properties of Non-Autoclaved Aerated Concrete with Recycled Concrete Powder.

Non-autoclaved aerated concrete (NAAC) is a two-phase material with a concrete matrix and air, exhibits good thermal insulation performance and shows good potential in the insulating construction industry. In this study, recycled concrete fine powder was used as an auxiliary cementing material, and the NAAC with different porosity and distribution was fabricated by the non-autoclaved method at different curing temperatures. The effect of porosity on the thermal conductivity and mechanical strength of NAAC is analyzed by experimental tests. A prediction method of thermal conductivity combining pore structure reconstruction and numerical simulation was proposed, which is established by two steps. Firstly, the pore size distributions of NAAC with different porosities were characterized by stereology image analyses. Secondly, the thermal conductivity prediction model based on the pore structure information was established by a COMSOL steady-state heat transfer module. The thermal conductivity results of COMSOL simulations were compared with the experiments and other theoretical models to verify the reliability of the model. The model was used to evaluate the effect of porosity, pore size distribution and the concrete matrix's thermal conductivity on the thermal conductivity of NAAC; these are hard to measure when only using laboratory experiments. The results show that with the increase in curing temperature, the porosity of NAAC increases, and the number and volume proportion of macropores increase. The numerical results suggest that the error between the COMSOL simulations and the experiments was less than 10% under different porosities, which is smaller than other models and has strong reliability. The prediction accuracy of this model increases with the increase in NAAC porosity. The steady thermal conductivity of NAAC is less sensitive to the distribution and dispersion of pore size in a given porosity. With the increase in porosity, the thermal conductivity of NAAC is linearly negatively correlated with that of the concrete matrix, and the correlation is close to 1.

Shape Trumps Size: Image-Based Morphological Analysis Reveals That the 3D Shape Discriminates Intracranial Aneurysm Disease Status Better Than Aneurysm Size.

Background: To date, it remains difficult for clinicians to reliably assess the disease status of intracranial aneurysms. As an aneurysm's 3D shape is strongly dependent on the underlying formation processes, it is believed that the presence of certain shape features mirrors the disease status of the aneurysm wall. Currently, clinicians associate irregular shape with wall instability. However, no consensus exists about which shape features reliably predict instability. In this study, we present a benchmark to identify shape features providing the highest predictive power for aneurysm rupture status. Methods: 3D models of aneurysms were extracted from medical imaging data (3D rotational angiographies) using a standardized protocol. For these aneurysm models, we calculated a set of metrics characterizing the 3D shape: Geometry indices (such as undulation, ellipticity and non-sphericity); writhe- and curvature-based metrics; as well as indices based on Zernike moments. Using statistical learning methods, we investigated the association between shape features and aneurysm disease status. This processing was applied to a clinical dataset of 750 aneurysms (261 ruptured, 474 unruptured) registered in the AneuX morphology database. We report here statistical performance metrics [including the area under curve (AUC)] for morphometric models to discriminate between ruptured and unruptured aneurysms. Results: The non-sphericity index NSI (AUC = 0.80), normalized Zernike energies Z N s u r f (AUC = 0.80) and the modified writhe-index W ¯ m e a n L 1 (AUC = 0.78) exhibited the strongest association with rupture status. The combination of predictors further improved the predictive performance (without location: AUC = 0.82, with location AUC = 0.87). The anatomical location was a good predictor for rupture status on its own (AUC = 0.78). Different protocols to isolate the aneurysm dome did not affect the prediction performance. We identified problems regarding generalizability if trained models are applied to datasets with different selection biases. Conclusions: Morphology provided a clear indication of the aneurysm disease status, with parameters measuring shape (especially irregularity) being better predictors than size. Quantitative measurement of shape, alone or in conjunction with information about aneurysm location, has the potential to improve the clinical assessment of intracranial aneurysms.

3D microgels to quantify tumor cell properties and therapy response dynamics.

Tumors contain heterogeneous and dynamic populations of cells that do not all display the fast-proliferating properties that traditional chemotherapies target. There is a need therefore, to develop novel treatment strategies that target diverse tumor cell properties. Identifying therapy combinations is challenging however. Current approaches have relied on cell lines cultured in monolayers with treatment response being assessed using endpoint metabolic assays, which although enable large-scale throughput, do not capture tumor heterogeneity. Here, a 3D in vitro tumor model using micro-molded hydrogels (microgels), the Gels for Live Analysis of Compartmentalized Environments (GLAnCE) platform, is adapted into a 96-well plate format (96-GLAnCE) that integrates patient-derived organoids (PDOs) and is combined with longitudinal automated imaging to address these limitations. Using 96-GLAnCE, two measures of tumor aggressiveness are quantified, tumor cell growth and in situ regrowth after drug treatment, in both cell lines and PDOs. The use of longitudinal image-based readouts enables the identification of tumor cell phenotypes with cell population and subpopulation resolution that cannot be detected by standard bulk-soluble assays. 96-GLAnCE is a versatile and robust platform that combines 3D-ECM based models, PDOs, and real-time assay readouts, to provide an additional tool for pre-clinical anti-cancer drug discovery for the identification of novel targets with translatable clinical significance.

Image-based analysis of skeletal muscle mass predicts cisplatin dose-limiting toxicity in patients with locally advanced head and neck cancer.

PURPOSE: Evidence suggests that patients' skeletal muscle mass (SMM) can predict the patients at risk for cisplatin dose-limiting toxicities (DLT). Cisplatin is currently dosed on body surface area (BSA). The predictive value of SMM for cisplatin DLT in patients with locally advanced head and neck cancer (LA-HNC) is investigated. METHODS: Patients with LA-HNC treated with cisplatin-based chemoradiotherapy (CRT) were included. SMM was measured using pre-treatment scans. Logistic regression analysis was performed to identify the predictive impact of low SMM for DLT. RESULTS: In total, 343 patients were included of which 199 patients (58.0%) had low SMM and 154 patients (44.9%) experienced cisplatin DLT. In multivariate analysis, low SMM at diagnosis was the only predictive factor for DLT (HR 1.8, 95% CI 1.1-2.9). CONCLUSIONS: Low SMM was associated with an increased risk of DLT. Trials are needed to investigate cisplatin dosing with consideration of SMM rather than solely BSA.

Multispectral Assessment of Sweet Pepper (Capsicum annuum L.) Fruit Quality Affected by Calcite Nanoparticles.

Sweet pepper (Capsicum annuum L.) is one of the most important vegetable crops in the world because of the nutritional value of its fruits and its economic importance. Calcium (Ca) improves the quality of sweet pepper fruits, and the application of calcite nanoparticles in agricultural practice has a positive effect on the morphological, physiological, and physicochemical properties of the whole plant. The objectives of this study were to investigate the effect of commercial calcite nanoparticles on yield, chemical, physical, morphological, and multispectral properties of sweet pepper fruits using a combination of conventional and novel image-based nondestructive methods of fruit quality analysis. In the field trial, two sweet pepper cultivars, i.e., Soroksari and Kurtovska kapija, were treated with commercial calcite nanoparticles (at a concentration of 3% and 5%, calcite-based foliar fertilizer (positive control), and water (negative control) three times during vegetation). Sweet pepper fruits were harvested at the time of technological and physiological maturity. Significant differences were observed between pepper cultivars as well as between harvests times. In general, application of calcite nanoparticles reduced yield and increased fruit firmness. However, different effects of calcite nanoparticles were observed on almost all properties depending on the cultivar. In Soroksari, calcite nanoparticles and calcite-based foliar fertilizers significantly increased N, P, K, Mg, Fe, Zn, Mn, and Cu at technological maturity, as well as P, Ca, Mg, Fe, Zn, Mn, Cu, and N at physiological maturity. However, in Kurtovska kapija, the treatments increased only Ca at technological maturity and only P at physiological maturity. The effect of treatments on fruit morphological properties was observed only at the second harvest. In Soroksari, calcite nanoparticles (3% and 5%) increased the fruit length, minimal circle area, and minimal circle radius, and it decreased the fruit width and convex hull compared to the positive and negative controls, respectively. In Kurtovska kapija, calcite nanoparticles increased the fruit width and convex hull compared to the controls. At physiological maturity, lower anthocyanin and chlorophyll indices were found in Kurtovska kapija in both treatments with calcite nanoparticles, while in Soroksari, the opposite effects were observed.

High-Content Analysis Monitoring Intracellular Trafficking and Replication of Mycobacterium tuberculosis Inside Host Cells.

Mycobacterium tuberculosis is able to colonize, persist, and massively replicate in host cells, such as phagocytes and epithelial cells. The intracellular stage of the bacteria is critical to the development of tuberculosis pathogenesis. The detailed mechanisms of intracellular trafficking of the bacillus are not fully understood and require further investigations. Therefore, increasing the knowledge of this process will help to develop therapeutic tools that will lower the burden of tuberculosis. M. tuberculosis is genetically tractable and tolerates the expression of heterologous fluorescent proteins. Thus, the intracellular distribution of the bacteria expressing fluorescent tracers can be easily defined using confocal microscopy. Advances in imaging techniques and images-based analysis allow the rapid quantification of biological objects in complex environments. In this chapter, we detailed high-content / high-throughput imaging methods to track the bacillus within host cell settings.

Patterns, Predictors, and Prognostic Value of Skeletal Muscle Mass Loss in Patients with Locally Advanced Head and Neck Cancer Undergoing Cisplatin-Based Chemoradiotherapy.

Low skeletal muscle mass (SMM) is associated with toxicities and decreased survival in head and neck cancer (HNC). Chemoradiotherapy (CRT) may exaggerate loss of SMM. We investigated the changes in SMM, their predictors, and prognostic impact of SMM in patients treated with CRT between 2012 and 2018. Skeletal muscle area (SMA) segmentation was performed on pre- and post-CRT imaging. Observed changes in SMM were categorized into: (I) Stable, (II) moderate gain (III), moderate loss, (IV) large gain, and (V) large loss. In total, 235 HNC patients were included, of which 39% had stable SMM, 55% moderate loss, 13% moderate gain, 0.4% large loss, and 0.4% large gain of SMM. After CRT, SMA decreased compared to pre-CRT (31.6 cm2 versus 33.3 cm2, p < 0.01). The key predictor was a body mass index (BMI) of ≥30 kg/m2 (OR 3.6, 95% CI 1.4-9.3, p < 0.01). Low SMM at diagnosis (HR 2.1; 95% CI 1.1-4.1, p = 0.03) and an HPV-positive oropharyngeal tumor (HR 0.1; 95% CI 0.01-0.9, p = 0.04) were prognostic for overall survival. Changes in SMM were not prognostic for survival. Loss of SMM is highly prevalent after CRT and a high BMI before treatment may aid in identifying patients at risk.

Influence of software parameters on measurements in automatized image-based analysis of fat tissue histology.

The understanding of fat tissue plays an eminent role in plastic surgery as well as in metabolic research. Histopathological analysis of tissue samples provides insight in free fat graft survival and culture experiments help to better understand fat tissue derived stem cells (ASCs). To facilitate such experiments, modern image-based histology could provide an automatized approach to a large amount of data to gain not only qualitative but also quantitative data. This study was designed to critically evaluate image-based analysis of fat tissue samples in cell culture or in tissue probes and to identify critical parameters to avoid bias in further studies. In the first part of the study, ASCs were harvested and differentiated into adipocytes in cell culture. Histology was performed with the fluorescent dye BODIPY and the obtained digital images were analyzed using Image J software. In the second part of the study, digitalized histology of a previous in vivo study was subjected to automatized fat vacuole quantification using Image J. Both approaches were critically reviewed, and different software parameter settings were tested. Results showed that automatized digital image analysis allows the quantification of fat tissue probes with enough precision giving significant results. But the testing of different software parameters revealed a significant influence of parameters themselves on calculated results. Therefore, we recommend the use of image-based analysis to quantify fat tissue probes to improve the comparability of studies. But we also emphasize to calibrate software using internal controls in every single experimental approach.

AggreCount: an unbiased image analysis tool for identifying and quantifying cellular aggregates in a spatially defined manner.

Protein quality control is maintained by a number of integrated cellular pathways that monitor the folding and functionality of the cellular proteome. Defects in these pathways lead to the accumulation of misfolded or faulty proteins that may become insoluble and aggregate over time. Protein aggregates significantly contribute to the development of a number of human diseases such as amyotrophic lateral sclerosis, Huntington's disease, and Alzheimer's disease. In vitro, imaging-based, cellular studies have defined key biomolecular components that recognize and clear aggregates; however, no unifying method is available to quantify cellular aggregates, limiting our ability to reproducibly and accurately quantify these structures. Here we describe an ImageJ macro called AggreCount to identify and measure protein aggregates in cells. AggreCount is designed to be intuitive, easy to use, and customizable for different types of aggregates observed in cells. Minimal experience in coding is required to utilize the script. Based on a user-defined image, AggreCount will report a number of metrics: (i) total number of cellular aggregates, (ii) percentage of cells with aggregates, (iii) aggregates per cell, (iv) area of aggregates, and (v) localization of aggregates (cytosol, perinuclear, or nuclear). A data table of aggregate information on a per cell basis, as well as a summary table, is provided for further data analysis. We demonstrate the versatility of AggreCount by analyzing a number of different cellular aggregates including aggresomes, stress granules, and inclusion bodies caused by huntingtin polyglutamine expansion.

Small-scale culture of Plasmodium falciparum using µ-Slide Angiogenesis followed by automatic infection rate counting to assess drug effects.

It is very important to reduce the costs involved in malarial drug development by small-scale culture of Plasmodium falciparum, and automation of the assay system for drug efficacy against the parasites for high-throughput screening. In this study, we report that P. falciparum-infected erythrocytes can be stably cultured on µ-Slide Angiogenesis, which is used to investigate angiogenesis in tube formation assays, followed by automatic counting of the infection rate (parasitaemia). After 10 µL of parasite-infected erythrocytes were added to the inner well of µ-Slide Angiogenesis to prevent a multilayer of erythrocytes, 30 µL of silicon oil was overlaid on the culture medium to avoid evaporation of the medium, leading to stable small-scale parasite cultivation. The parasites were stained with a cell-permeant fluorescent nucleic acid stain (SYTO21) followed by cultivation. After taking bright field and fluorescent images using an inverted microscope, the infection rate could be calculated automatically by counting the number of erythrocytes and parasites using MetaMorph Offline software. The effect of anti-malarial drugs on parasite growth could be investigated on µ-Slide Angiogenesis, in which the parasite culture was added to the inner wells containing the drugs followed by their cultivation. Taken together, this method may be useful for image-based screening for anti-malarial drug candidates with automatic counting of parasite infection rates.

Real-Time Digital Bright Field Technology for Rapid Antibiotic Susceptibility Testing.

Optical scanning through bacterial samples and image-based analysis may provide a robust method for bacterial identification, fast estimation of growth rates and their modulation due to the presence of antimicrobial agents. Here, we describe an automated digital, time-lapse, bright field imaging system (oCelloScope, BioSense Solutions ApS, Farum, Denmark) for rapid and higher throughput antibiotic susceptibility testing (AST) of up to 96 bacteria-antibiotic combinations at a time. The imaging system consists of a digital camera, an illumination unit and a lens where the optical axis is tilted 6.25° relative to the horizontal plane of the stage. Such tilting grants more freedom of operation at both high and low concentrations of microorganisms. When considering a bacterial suspension in a microwell, the oCelloScope acquires a sequence of 6.25°-tilted images to form an image Z-stack. The stack contains the best-focus image, as well as the adjacent out-of-focus images (which contain progressively more out-of-focus bacteria, the further the distance from the best-focus position). The acquisition process is repeated over time, so that the time-lapse sequence of best-focus images is used to generate a video. The setting of the experiment, image analysis and generation of time-lapse videos can be performed through a dedicated software (UniExplorer, BioSense Solutions ApS). The acquired images can be processed for online and offline quantification of several morphological parameters, microbial growth, and inhibition over time.

Whole-Plant Manual and Image-Based Phenotyping in Controlled Environments.

Phenotypic measurements and images of crops grown under controlled-environment conditions can be analyzed to compare plant growth and other phenotypes from diverse varieties. Those demonstrating the most favorable phenotypic traits can then be used for crop improvement strategies. This article details a protocol for image-based root and shoot phenotyping of plants grown in the greenhouse to compare traits among different varieties. Diverse maize lines were grown in the greenhouse in large 8-gallon treepots in a clay granule substrate. Replicates of each line were harvested at 4 weeks, 6 weeks, and 8 weeks after planting to capture developmental information. Whole-plant phenotypes include biomass accumulation, ontogeny, architecture, and photosynthetic efficiency of leaves. Image analysis was used to measure leaf surface area and tassel size and to extract shape variance information from complex 3D root architectures. Notably, this framework is extensible to any number of above- or below-ground phenotypes, both morphological and physiological. © 2017 by John Wiley & Sons, Inc.

Cellulose Nanofibril Film as a Piezoelectric Sensor Material.

Self-standing films (45 µm thick) of native cellulose nanofibrils (CNFs) were synthesized and characterized for their piezoelectric response. The surface and the microstructure of the films were evaluated with image-based analysis and scanning electron microscopy (SEM). The measured dielectric properties of the films at 1 kHz and 9.97 GHz indicated a relative permittivity of 3.47 and 3.38 and loss tangent tan Î´ of 0.011 and 0.071, respectively. The films were used as functional sensing layers in piezoelectric sensors with corresponding sensitivities of 4.7-6.4 pC/N in ambient conditions. This piezoelectric response is expected to increase remarkably upon film polarization resulting from the alignment of the cellulose crystalline regions in the film. The CNF sensor characteristics were compared with those of polyvinylidene fluoride (PVDF) as reference piezoelectric polymer. Overall, the results suggest that CNF is a suitable precursor material for disposable piezoelectric sensors, actuators, or energy generators with potential applications in the fields of electronics, sensors, and biomedical diagnostics.

Non-invasive quality evaluation of confluent cells by image-based orientation heterogeneity analysis.

In recent years, cell and tissue therapy in regenerative medicine have advanced rapidly towards commercialization. However, conventional invasive cell quality assessment is incompatible with direct evaluation of the cells produced for such therapies, especially in the case of regenerative medicine products. Our group has demonstrated the potential of quantitative assessment of cell quality, using information obtained from cell images, for non-invasive real-time evaluation of regenerative medicine products. However, image of cells in the confluent state are often difficult to evaluate, because accurate recognition of cells is technically difficult and the morphological features of confluent cells are non-characteristic. To overcome these challenges, we developed a new image-processing algorithm, heterogeneity of orientation (H-Orient) processing, to describe the heterogeneous density of cells in the confluent state. In this algorithm, we introduced a Hessian calculation that converts pixel intensity data to orientation data and a statistical profiling calculation that evaluates the heterogeneity of orientations within an image, generating novel parameters that yield a quantitative profile of an image. Using such parameters, we tested the algorithm's performance in discriminating different qualities of cellular images with three types of clinically important cell quality check (QC) models: remaining lifespan check (QC1), manipulation error check (QC2), and differentiation potential check (QC3). Our results show that our orientation analysis algorithm could predict with high accuracy the outcomes of all types of cellular quality checks (>84% average accuracy with cross-validation).

Comparisons of cell culture medium using distribution of morphological features in microdevice.

As the number of available cell types grows, it becomes necessary to develop more effective ways to optimize the cell-culture medium for each cell line and culture condition. However, because of the vast number of parameters that must be decided, such as the combination of components, optimization is both laborious and costly. Microdevices are a cost-effective way to perform such evaluations because they use only a small volume of media and enable high-throughput analyses. However, assays performed in microdevices are themselves minimized, and each assay unit (well/chamber) commonly contains an insufficient number of cells for comprehensive evaluations such as gene-expression or flow-cytometry analyses. To address this issue, we introduced image-based analysis in conjunction with microdevice assays; this approach allows quantification of every cell in each assay unit. To quantitatively profile differences in cellular behaviors in a microdevice under different culture media conditions, we developed a non-staining image-based analysis method that utilizes cellular morphology. Our approach combines the structural advantages of microdevices, which can increase the stability of images, and the quantitative advantages of an image-based cell evaluation technique that utilizes time-course population change in several morphological features. Our results demonstrate that cellular changes due to small alterations in the concentration of serum in medium or differences in the basal medium can be profiled using only microscopic images.

Fracture healing in mice lacking Pten in osteoblasts: a micro-computed tomography image-based analysis of the mechanical properties of the femur.

In the United States, approximately eight million osseous fractures are reported annually, of which 5-10% fail to create a bony union. Osteoblast-specific deletion of the gene Pten in mice has been found to stimulate bone growth and accelerate fracture healing. Healing rates at four weeks increased in femurs from Pten osteoblast conditional knock-out mice (Pten-CKO) compared to wild-type mice (WT) of the same genetic strain as measured by an increase in mechanical stiffness and failure load in four-point bending tests. Preceding mechanical testing, each femur was imaged using a Skyscan 1172 micro-computed tomography (µCT) scanner (Skyscan, Kontich, Belgium). The present study used µCT image-based analysis to test the hypothesis that the increased femoral fracture force and stiffness in Pten-CKO were due to greater section properties with the same effective material properties as that of the WT. The second moment of area and section modulus were computed in ImageJ 1.46 (National Institutes of Health) and used to predict the effective flexural modulus and the stress at failure for fourteen pairs of intact and callus WT and twelve pairs of intact and callus Pten-CKO femurs. For callus and intact femurs, the failure stress and tissue mineral density of the Pten-CKO and WT were not different; however, the section properties of the Pten-CKO were more than twice as large 28 days post-fracture. It was therefore concluded, when the gene Pten was conditionally knocked-out in osteoblasts, the resulting increased bending stiffness and force to fracture were due to increased section properties.