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Precise and quick monitoring of key cytometric features such as cell count, size, morphology, and DNA content is crucial in life science applications. Traditionally, image cytometry relies on visual inspection of hemocytometers. This approach is error-prone due to operator subjectivity. Recently, deep learning approaches have emerged as powerful tools enabling quick and accurate image cytometry applicable to different cell types. Leading to simpler, compact, and affordable solutions, these approaches revealed image cytometry as a viable alternative to flow cytometry or Coulter counting. In this study, we demonstrate a modular deep learning system, DeepCAN, providing a complete solution for automated cell counting and viability analysis. DeepCAN employs three different neural network blocks called Parallel Segmenter, Cluster CNN, and Viability CNN that are trained for initial segmentation, cluster separation, and viability analysis. Parallel Segmenter and Cluster CNN blocks achieve accurate segmentation of individual cells while Viability CNN block performs viability classification. A modified U-Net network, a well-known deep neural network model for bioimage analysis, is used in Parallel Segmenter while LeNet-5 architecture and its modified version Opto-Net are used for Cluster CNN and Viability CNN, respectively. We train the Parallel Segmenter using 15 images of A2780 cells and 5 images of yeasts cells, containing, in total, 14742 individual cell images. Similarly, 6101 and 5900 A2780 cell images are employed for training Cluster CNN and Viability CNN models, respectively. 2514 individual A2780 cell images are used to test the overall segmentation performance of Parallel Segmenter combined with Cluster CNN, revealing high Precision/Recall/F1-Score values of 96.52%/96.45%/98.06%, respectively. Cell counting/viability performance of DeepCAN is tested with A2780 (2514 cells), A549 (601 cells), Colo (356 cells), and MDA-MB-231 (887 cells) cell images revealing high analysis accuracies of 96.76%/99.02%, 93.82%/95.93%, and 92.18%/97.90%, 85.32%/97.40%, respectively. [ABSTRACT FROM AUTHOR]

Fluorescence microscopy is one of the workhorses of biomedical research and laboratory diagnosis; however, their cost, size, maintenance, and fragility has prevented their adoption in developing countries or low-resource settings. Although significant advances have decreased their size, cost and accessibility, their designs and assembly remain rather complex. Here, inspired on the simple mechanism from a nut and a bolt, we report the construction of a portable fluorescence microscope that operates in bright-field mode and in three fluorescence channels: UV, green, and red. It is assembled in under 10 min from only six 3D printed parts, basic electronic components, a microcomputer (Raspberry Pi) and a camera, all of which can be readily purchased in most locations or online for US $122. The microcomputer was programmed in Python language to capture time-lapse images and videos. Resolution and illumination conditions of the microscope were characterized, and its performance was compared with a high-end fluorescence microscope in bright-field and fluorescence mode. We demonstrate that our miniature microscope can resolve and track single cells in both modes. The instructions on how to assemble the microscope are shown in a video, and the software to control it and the design files of the 3D-printed parts are freely available online. Our portable microscope is ideal in applications where space is at a premium, such as lab-on-a-chips or space missions, and can find applications in basic and clinical research, diagnostics, telemedicine and in educational settings. [ABSTRACT FROM AUTHOR]

In breast cancer, tumor hypoxia has been linked to poor prognosis and increased metastasis. Hypoxia activates transcriptional programs in cancer cells that lead to increased motility and invasion, as well as various metabolic changes. One of these metabolic changes, an increase in glycogen metabolism, has been further associated with protection from reactive oxygen species damage that may lead to premature senescence. Here we report that breast cancer cells significantly increase glycogen stores in response to hypoxia. We found that knockdown of the brain isoform of an enzyme that catalyzes glycogen breakdown, glycogen phosphorylase B (PYGB), but not the liver isoform, PYGL, inhibited glycogen utilization in estrogen receptor negative and positive breast cancer cells; whereas both independently inhibited glycogen utilization in the normal-like breast epithelial cell line MCF-10A. Functionally, PYGB knockdown and the resulting inhibition of glycogen utilization resulted in significantly decreased wound-healing capability in MCF-7 cells and a decrease in invasive potential of MDA-MB-231 cells. Thus, we identify PYGB as a novel metabolic target with potential applications in the management and/or prevention of metastasis in breast cancer. [ABSTRACT FROM AUTHOR]

Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotypes alone. In contrast to current single-cell analysis techniques that rely solely on slow and costly genetic/epigenetic analysis, these image-based analyses allow morphological profiling and screening of thousands or even millions of single cells at a fraction of the cost, and have been proven to demonstrate the statistical significance required for understanding the role of cell heterogeneity in diverse biological applications, ranging from cancer screening to drug candidate identification/validation processes. This paper examines the efficacies and opportunities presented by machine learning algorithms in processing large scale datasets with millions of label-free cell images. An automatic single-cell classification framework using convolutional neural network (CNN) has been developed. A comparative analysis of its efficiency in classifying large datasets against conventional k-nearest neighbors (kNN) and support vector machine (SVM) based methods are also presented. Experiments have shown that our proposed framework can efficiently identify multiple types cells with over $99\%$ accuracy based on the phenotypic label-free bright-field images; and CNN-based models perform well and relatively stable against data volume compared with kNN and SVM. [ABSTRACT FROM AUTHOR]

Live cell time-lapse microscopy, a widely-used technique to study gene expression and protein dynamics in single cells, relies on segmentation and tracking of individual cells for data generation. The potential of the data that can be extracted from this technique is limited by the inability to accurately segment a large number of cells from such microscopy images and track them over long periods of time. Existing segmentation and tracking algorithms either require additional dyes or markers specific to segmentation or they are highly specific to one imaging condition and cell morphology and/or necessitate manual correction. Here we introduce a fully automated, fast and robust segmentation and tracking algorithm for budding yeast that overcomes these limitations. Full automatization is achieved through a novel automated seeding method, which first generates coarse seeds, then automatically fine-tunes cell boundaries using these seeds and automatically corrects segmentation mistakes. Our algorithm can accurately segment and track individual yeast cells without any specific dye or biomarker. Moreover, we show how existing channels devoted to a biological process of interest can be used to improve the segmentation. The algorithm is versatile in that it accurately segments not only cycling cells with smooth elliptical shapes, but also cells with arbitrary morphologies (e.g. sporulating and pheromone treated cells). In addition, the algorithm is independent of the specific imaging method (bright-field/phase) and objective used (40X/63X/100X). We validate our algorithm’s performance on 9 cases each entailing a different imaging condition, objective magnification and/or cell morphology. Taken together, our algorithm presents a powerful segmentation and tracking tool that can be adapted to numerous budding yeast single-cell studies. [ABSTRACT FROM AUTHOR]

Multiplexed bioassays, in which multiple analytes of interest are probed in parallel within a single small volume, have greatly accelerated the pace of biological discovery. Bead-based multiplexed bioassays have many technical advantages, including near solution-phase kinetics, small sample volume requirements, many within-assay replicates to reduce measurement error, and, for some bead materials, the ability to synthesize analytes directly on beads via solid-phase synthesis. To allow bead-based multiplexing, analytes can be synthesized on spectrally encoded beads with a 1:1 linkage between analyte identity and embedded codes. Bead-bound analyte libraries can then be pooled and incubated with a fluorescently-labeled macromolecule of interest, allowing downstream quantification of interactions between the macromolecule and all analytes simultaneously via imaging alone. Extracting quantitative binding data from these images poses several computational image processing challenges, requiring the ability to identify all beads in each image, quantify bound fluorescent material associated with each bead, and determine their embedded spectral code to reveal analyte identities. Here, we present a novel open-source Python software package (the mrbles analysis package) that provides the necessary tools to: (1) find encoded beads in a bright-field microscopy image; (2) quantify bound fluorescent material associated with bead perimeters; (3) identify embedded ratiometric spectral codes within beads; and (4) return data aggregated by embedded code and for each individual bead. We demonstrate the utility of this package by applying it towards analyzing data generated via multiplexed measurement of calcineurin protein binding to MRBLEs (icrospheres with atiometric arcode anthanide ncoding) containing known and mutant binding peptide motifs. We anticipate that this flexible package should be applicable to a wide variety of assays, including simple bead or droplet finding analysis, quantification of binding to non-encoded beads, and analysis of multiplexed assays that use ratiometric, spectrally encoded beads. [ABSTRACT FROM AUTHOR]

To date, few optical imaging systems are available in clinical practice to perform noninvasive measurements transcutaneously. Instead, functional imaging is performed using ionizing radiation or intense magnetic fields in most cases. The applicability of fluorescence imaging (e.g., for the detection of fluorescently labeled objects, such as tumors) is limited due to the restricted tissue penetration of light and the required long exposure time. Thus, the development of highly sensitive and easily manageable instruments is necessary to broaden the utility of optical imaging. To advance these developments, an improved fluorescence imaging system was designed in this study that operates on the principle of noncontact laser-induced fluorescence and enables the detection of fluorescence from deeper tissue layers as well as real-time imaging. The high performance of the developed optical laser scanner results from the combination of specific point illumination, an intensified charge-coupled device (ICCD) detector with a novel light trap, and a filtering strategy. The suitability of the laser scanner was demonstrated in two representative applications and an in vivo evaluation. In addition, a comparison with a planar imaging system was performed. The results show that the exposure time with the developed laser scanner can be reduced to a few milliseconds during measurements with a penetration depth of up to 32 mm. Due to these short exposure times, real-time fluorescence imaging can be easily achieved. The ability to measure fluorescence from deep tissue layers enables clinically relevant applications, such as the detection of fluorescently labeled malignant tumors. [ABSTRACT FROM AUTHOR]

Organismal fitness is relevant in many contexts in biology. The most meaningful experimental measure of fitness is competitive fitness, when two or more entities (e.g., genotypes) are allowed to compete directly. In theory, competitive fitness is simple to measure: an experimental population is initiated with the different types in known proportions and allowed to evolve under experimental conditions to a predefined endpoint. In practice, there are several obstacles to obtaining robust estimates of competitive fitness in multicellular organisms, the most pervasive of which is simply the time it takes to count many individuals of different types from many replicate populations. Methods by which counting can be automated in high throughput are desirable, but for automated methods to be useful, the bias and technical variance associated with the method must be (a) known, and (b) sufficiently small relative to other sources of bias and variance to make the effort worthwhile. The nematode Caenorhabditis elegans is an important model organism, and the fitness effects of genotype and environmental conditions are often of interest. We report a comparison of three experimental methods of quantifying competitive fitness, in which wild-type strains are competed against GFP-marked competitors under standard laboratory conditions. Population samples were split into three replicates and counted (1) "by eye" from a saved image, (2) from the same image using CellProfiler image analysis software, and (3) with a large particle flow cytometer (a "worm sorter"). From 720 replicate samples, neither the frequency of wild-type worms nor the among-sample variance differed significantly between the three methods. CellProfiler and the worm sorter provide a tenfold increase in sample handling speed with little (if any) bias or increase in variance. [ABSTRACT FROM AUTHOR]

Cell-substrate adhesions are essential for various physiological processes, including embryonic development and maintenance of organ functions. Hemidesmosomes (HDs) are multiprotein complexes that attach epithelial cells to the basement membrane. Formation and remodeling of HDs are dependent on the surrounding mechanical environment; however, the upstream signaling mechanisms are not well understood. We recently reported that Solo (also known as ARHGEF40), a guanine nucleotide exchange factor targeting RhoA, binds to keratin8/18 (K8/K18) intermediate filaments, and that their interaction is important for force-induced actin and keratin cytoskeletal reorganization. In this study, we show that Solo co-precipitates with an HD protein, β4-integrin. Co-precipitation assays revealed that the central region (amino acids 330–1057) of Solo binds to the C-terminal region (1451–1752) of β4-integrin. Knockdown of Solo significantly suppressed HD formation in MCF10A mammary epithelial cells. Similarly, knockdown of K18 or treatment with Y-27632, a specific inhibitor of Rho-associated kinase (ROCK), suppressed HD formation. As Solo knockdown or Y-27632 treatment is known to disorganize K8/K18 filaments, these results suggest that Solo is involved in HD formation by regulating K8/K18 filament organization via the RhoA-ROCK signaling pathway. We also showed that knockdown of Solo impairs acinar formation in MCF10A cells cultured in 3D Matrigel. In addition, Solo accumulated at the site of traction force generation in 2D-cultured MCF10A cells. Taken together, these results suggest that Solo plays a crucial role in HD formation and acinar development in epithelial cells by regulating mechanical force-induced RhoA activation and keratin filament organization. [ABSTRACT FROM AUTHOR]

Continuous monitoring of physiological parameters inside a living cell will lead to major advances in our understanding of biology and complex diseases, such as cancer. It also enables the development of new medical diagnostics and therapeutics. Progress in nanofabrication and wireless communication has opened up the potential of making a wireless chip small enough that it can be wholly inserted into a living cell. To investigate how such chips could be internalized into various types of living single cells and how this process might affect cells’ physiology, we designed and fabricated a series of multilayered micron-scale tag structures with different sizes as potential RFID (adio requency entification) cell trackers. While the present structures are test structures that do not resonate, the tags that do resonate have similar structure from device fabrication, material properties, and device size point of view. The structures are in four different sizes, the largest with the lateral dimension of 9 μm × 21 μm. The thickness for these structures is kept constant at 1.5 μm. We demonstrate successful delivery of our fabricated chips into various types of living cells, such as melanoma skin cancer, breast cancer, colon cancer and healthy/normal fibroblast skin cells. To our surprise, we observed a remarkable internalization rate difference between each cell type; the uptake rate was faster for more aggressive cancer cells than the normal/healthy cells. Cell viability before and after tag cellular internalization and persistence of the internalized tags have also been recorded over the course of five days of incubation. These results establish the foundations of the possibility of long term, wireless, intracellular physiological signal monitoring. [ABSTRACT FROM AUTHOR]

In this paper we report the development of a cost-effective, modular, open source, and fully automated slide-scanning microscope, composed entirely of easily available off-the-shelf parts, and capable of bright field and fluorescence modes. The automated X-Y stage is composed of two low-cost micrometer stages coupled to stepper motors operated in open-loop mode. The microscope is composed of a low-cost CMOS sensor and low-cost board lenses placed in a 4f configuration. The system has approximately 1 micron resolution, limited by the f/# of available board lenses. The microscope is compact, measuring just 25×25×30 cm, and has an absolute positioning accuracy of ±1 μm in the X and Y directions. A Z-stage enables autofocusing and imaging over large fields of view even on non-planar samples, and custom software enables automatic determination of sample boundaries and image mosaicking. We demonstrate the utility of our device through imaging of fluorescent- and transmission-dye stained blood and fecal smears containing human and animal parasites, as well as several prepared tissue samples. These results demonstrate image quality comparable to high-end commercial microscopes at a cost of less than US$400 for a bright-field system, with an extra US$100 needed for the fluorescence module. [ABSTRACT FROM AUTHOR]

Background: Conventional gold standard characterization of chigger mites involves chemical preparation procedures (i.e. specimen clearing) for visualization of morphological features, which however contributes to destruction of the arthropod host DNA and any endosymbiont or pathogen DNA harbored within the specimen. Methodology/Principal findings: In this study, a novel work flow based on autofluorescence microscopy was developed to enable identification of trombiculid mites to the species level on the basis of morphological traits without any special preparation, while preserving the mite DNA for subsequent genotyping. A panel of 16 specifically selected fluorescence microscopy images of mite features from available identification keys served for complete chigger morphological identification to the species level, and was paired with corresponding genotype data. We evaluated and validated this method for paired chigger morphological and genotypic ID using the mitochondrial cytochrome c oxidase subunit I gene (coi) in 113 chigger specimens representing 12 species and 7 genera (Leptotrombidium, Ascoschoengastia, Gahrliepia, Walchia, Blankaartia, Schoengastia and Schoutedenichia) from the Lao People’s Democratic Republic (Lao PDR) to the species level (complete characterization), and 153 chiggers from 5 genera (Leptotrombidium, Ascoschoengastia, Helenicula, Schoengastiella and Walchia) from Thailand, Cambodia and Lao PDR to the genus level. A phylogenetic tree constructed from 77 coi gene sequences (approximately 640 bp length, n = 52 new coi sequences and n = 25 downloaded from GenBank), demonstrated clear grouping of assigned morphotypes at the genus levels, although evidence of both genetic polymorphism and morphological plasticity was found. Conclusions/Significance: With this new methodology, we provided the largest collection of characterized coi gene sequences for trombiculid mites to date, and almost doubled the number of available characterized coi gene sequences with a single study. The ability to provide paired phenotypic-genotypic data is of central importance for future characterization of mites and dissecting the molecular epidemiology of mites transmitting diseases like scrub typhus. [ABSTRACT FROM AUTHOR]

In Escherichia coli, damage to the chromosomal DNA induces the SOS response, setting in motion a series of different DNA repair and damage tolerance pathways. DNA polymerase IV (pol IV) is one of three specialised DNA polymerases called into action during the SOS response to help cells tolerate certain types of DNA damage. The canonical view in the field is that pol IV primarily acts at replisomes that have stalled on the damaged DNA template. However, the results of several studies indicate that pol IV also acts on other substrates, including single-stranded DNA gaps left behind replisomes that re-initiate replication downstream of a lesion, stalled transcription complexes and recombination intermediates. In this study, we use single-molecule time-lapse microscopy to directly visualize fluorescently labelled pol IV in live cells. We treat cells with the DNA-damaging antibiotic ciprofloxacin, Methylmethane sulfonate (MMS) or ultraviolet light and measure changes in pol IV concentrations and cellular locations through time. We observe that only 5–10% of foci induced by DNA damage form close to replisomes, suggesting that pol IV predominantly carries out non-replisomal functions. The minority of foci that do form close to replisomes exhibit a broad distribution of colocalisation distances, consistent with a significant proportion of pol IV molecules carrying out postreplicative TLS in gaps behind the replisome. Interestingly, the proportion of pol IV foci that form close to replisomes drops dramatically in the period 90–180 min after treatment, despite pol IV concentrations remaining relatively constant. In an SOS-constitutive mutant that expresses high levels of pol IV, few foci are observed in the absence of damage, indicating that within cells access of pol IV to DNA is dependent on the presence of damage, as opposed to concentration-driven competition for binding sites. [ABSTRACT FROM AUTHOR]

Automated optical tweezers-based robotic manipulation of microscale objects requires real-time visual perception for estimating the states, i.e., positions and orientations, of the objects. Such visual perception is particularly challenging in heterogeneous environments comprising mixtures of biological and colloidal objects, such as cells and microspheres, when the popular imaging modality of low contrast bright field microscopy is used. In this paper, we present an accurate method to address this challenge. Our method combines many well-established image processing techniques such as blob detection, histogram equalization, erosion, and dilation with a convolutional neural network in a novel manner. We demonstrate the effectiveness of our processing pipeline in perceiving objects of both regular and irregular shapes in heterogeneous microenvironments of varying compositions. The neural network, in particular, helps in distinguishing the individual microspheres present in dense clusters. [ABSTRACT FROM AUTHOR]

In sea urchin development, structures derived from neurogenic territory control the swimming and feeding responses of the pluteus as well as the process of metamorphosis. We have previously isolated an alpha tubulin family member of Paracentrotus lividus (Pl-Tuba1a, formerly known as Pl-Talpha2) that is specifically expressed in the ciliary band and animal pole neurogenic domains of the sea urchin embryo. In order to identify cis-regulatory elements controlling its spatio-temporal expression, we conducted gene transfer experiments, transgene deletions and site specific mutagenesis. Thus, a genomic region of about 2.6 Kb of Pl-Tuba1a, containing four Interspecifically Conserved Regions (ICRs), was identified as responsible for proper gene expression. An enhancer role was ascribed to ICR1 and ICR2, while ICR3 exerted a pivotal role in basal expression, restricting Tuba1a expression to the proper territories of the embryo. Additionally, the mutation of the forkhead box consensus sequence binding site in ICR3 prevented Pl-Tuba1a expression. [ABSTRACT FROM AUTHOR]

Large benthic foraminifera are unicellular calcifying reef organisms that can form symbiotic relationships with a range of different microalgae. However, the cellular functions, such as symbiosis and calcification, and other aspects of cellular physiology in large benthic foraminifera are not fully understood. Amphisorus kudakajimensis was used as a model to determine the detailed cellular characteristics of large benthic foraminifera. We used calcein acetoxymethyl ester (calcein AM) as a fluorescent indicator for live confocal imaging. We demonstrated that calcein AM is a useful fluorescent indicator to stain the fine network of reticulopodia and the cytoplasm in living A. kudakajimensis. We showed that at least two types of reticulopodia exist in A. kudakajimensis: the straight bundle of reticulopodia that spreads from the aperture and the fine reticulopodia along the surface of the aperture and chamber walls. The cytoplasm in outer chambers was highly branched and contained a few dinoflagellates. In contrast, the inner chamberlets contained condensed cytoplasm and many dinoflagellates, suggesting that the cytoplasm of A. kudakajimensis performs different functions based on its location within the large test. Our confocal detailed image analysis provides real-time cellular morphology and cell physiology of living foraminifera. [ABSTRACT FROM AUTHOR]

The mechanical properties of tumors and the tumor environment provide important information for the progression and characterization of cancer. Tumors are surrounded by an extracellular matrix (ECM) dominated by collagen I. The geometrical and mechanical properties of the ECM play an important role for the initial step in the formation of metastasis, presented by the migration of malignant cells towards new settlements as well as the vascular and lymphatic system. The extent of this cell invasion into the ECM is a key medical marker for cancer prognosis. In vivo studies reveal an increased stiffness and different architecture of tumor tissue when compared to its healthy counterparts. The observed parallel collagen organization on the tumor border and radial arrangement at the invasion zone has raised the question about the mechanisms organizing these structures. Here we study the effect of contractile forces originated from model tumor spheroids embedded in a biomimetic collagen I matrix. We show that contractile forces act immediately after seeding and deform the ECM, thus leading to tensile radial forces within the matrix. Relaxation of this tension via cutting the collagen does reduce invasion, showing a mechanical relation between the tensile state of the ECM and invasion. In turn, these results suggest that tensile forces in the ECM facilitate invasion. Furthermore, simultaneous contraction of the ECM and tumor growth leads to the condensation and reorientation of the collagen at the spheroid’s surface. We propose a tension-based model to explain the collagen organization and the onset of invasion by forces originating from the tumor. [ABSTRACT FROM AUTHOR]

Despite the strength of the Cre/loxP recombination system in animal models, its application in rats trails that in mice because of the lack of relevant reporter strains. Here, we generated a floxed STOP tdTomato rat that conditionally expresses a red fluorescent protein variant (tdTomato) in the presence of exogenous Cre recombinase. The tdTomato signal vividly visualizes neurons including their projection fibers and spines without any histological enhancement. In addition, a transgenic rat line (FLAME) that ubiquitously expresses tdTomato was successfully established by injecting intracytoplasmic Cre mRNA into fertilized ova. Our rat reporter system will facilitate connectome studies as well as the visualization of the fine structures of genetically identified cells for long periods both in vivo and ex vivo. Furthermore, FLAME is an ideal model for organ transplantation research owing to improved traceability of cells/tissues. [ABSTRACT FROM AUTHOR]

Toxigenic cyanobacteria are one of the main health risks associated with water resources worldwide, as their toxins can affect humans and fauna exposed via drinking water, aquaculture and recreation. Microscopy monitoring of cyanobacteria in water bodies and massive growth systems is a routine operation for cell abundance and growth estimation. Here we present ACQUA (Automated Cyanobacterial Quantification Algorithm), a new fully automated image analysis method designed for filamentous genera in Bright field microscopy. A pre-processing algorithm has been developed to highlight filaments of interest from background signals due to other phytoplankton and dust. A spline-fitting algorithm has been designed to recombine interrupted and crossing filaments in order to perform accurate morphometric analysis and to extract the surface pattern information of highlighted objects. In addition, 17 specific pattern indicators have been developed and used as input data for a machine-learning algorithm dedicated to the recognition between five widespread toxic or potentially toxic filamentous genera in freshwater: Aphanizomenon , Cylindrospermopsis , Dolichospermum , Limnothrix and Planktothrix. The method was validated using freshwater samples from three Italian volcanic lakes comparing automated vs. manual results. ACQUA proved to be a fast and accurate tool to rapidly assess freshwater quality and to characterize cyanobacterial assemblages in aquatic environments. [ABSTRACT FROM AUTHOR]

A novel design of gold-coated iron oxide nanoparticles was fabricated as a potential delivery system to improve the efficiency and stability of d, l-sulforaphane as an anticancer drug. To this purpose, the surface of gold-coated iron oxide nanoparticles was modified for sulforaphane delivery via furnishing its surface with thiolated polyethylene glycol-folic acid and thiolated polyethylene glycol-FITC. The synthesized nanoparticles were characterized by different techniques such as FTIR, energy dispersive X-ray spectroscopy, UV-visible spectroscopy, scanning and transmission electron microscopy. The average diameters of the synthesized nanoparticles before and after sulforaphane loading were obtained ∼ 33 nm and ∼ 38 nm, respectively, when ∼ 2.8 mmol/g of sulforaphane was loaded. The result of cell viability assay which was confirmed by apoptosis assay on the human breast cancer cells (MCF-7 line) as a model of in vitro-cancerous cells, proved that the bare nanoparticles showed little inherent cytotoxicity, whereas the sulforaphane-loaded nanoparticles were cytotoxic. The expression rate of the anti-apoptotic genes (bcl-2 and bcl-xL), and the pro-apoptotic genes (bax and bak) were quantified, and it was found that the expression rate of bcl-2 and bcl-xL genes significantly were decreased when MCF-7 cells were incubated by sulforaphane-loaded nanoparticles. The sulforaphane-loaded into the designed gold-coated iron oxide nanoparticles, acceptably induced apoptosis in MCF-7 cells. [ABSTRACT FROM AUTHOR]

Introduction: Long-term drug delivery to the inner ear may be achieved by functionalizing cochlear implant (CI) electrodes with cells providing neuroprotective factors. However, effective strategies in order to coat implant surfaces with cells need to be developed. Our vision is to make benefit of electromagnetic field attracting forces generated by CI electrodes to bind BDNF-secreting cells that are labelled with magnetic beads (MB) onto the electrode surfaces. Thus, the effect of MB-labelling on cell viability and BDNF production were investigated. Materials and Methods: Murine NIH 3T3 fibroblasts—genetically modified to produce BDNF—were labelled with MB. Results: Atomic force and bright field microscopy illustrated the internalization of MB by fibroblasts after 24 h of cultivation. Labelling cells with MB did not expose cytotoxic effects on fibroblasts and allowed adhesion on magnetic surfaces with sufficient BDNF release. Discussion: Our data demonstrate a novel approach for mediating enhanced long-term adhesion of BDNF-secreting fibroblasts on model electrode surfaces for cell-based drug delivery applications in vitro and in vivo. This therapeutic strategy, once transferred to cells suitable for clinical application, may allow the biological modifications of CI surfaces with cells releasing neurotrophic or other factors of interest. [ABSTRACT FROM AUTHOR]

Automated optical tweezers-based robotic manipulation of microscale objects requires real-time visual perception for estimating the states, i.e., positions and orientations, of the objects. Such visual perception is particularly challenging in heterogeneous environments comprising mixtures of biological and colloidal objects, such as cells and microspheres, when the popular imaging modality of low contrast bright field microscopy is used. In this paper, we present an accurate method to address this challenge. Our method combines many well-established image processing techniques such as blob detection, histogram equalization, erosion, and dilation with a convolutional neural network in a novel manner. We demonstrate the effectiveness of our processing pipeline in perceiving objects of both regular and irregular shapes in heterogeneous microenvironments of varying compositions. The neural network, in particular, helps in distinguishing the individual microspheres present in dense clusters.

A compact mathematical model of the STEM imaging process including bright field (BF) and dark field (DF) is derived. This description is valid for thin samples, does not rely on the weak phase approximation and does not require time-consuming simulation of the scanning process. It is well-known that STEM imaging is a nonlinear technique and therefore cannot be described in terms of a sample-independent linear contrast transfer function (CTF). In this work we derive a nonlinear description showing that a STEM image can in fact be described with two terms. Both terms are cross-correlations between a function that is independent of the sample and a function that depends only on the sample. The latter two can be seen as two different objects. These objects directly correspond to two specific cases: the weak phase approximation (WPA) and annular dark field (ADF) imaging, which are known from the literature. We clarify the need for recognizing and understanding what the object is of any particular STEM technique. The model was validated using simulated STEM images and an excellent agreement as well as a reduction in computation time of 3 orders of magnitude was found. [ABSTRACT FROM AUTHOR]

A high sensitivity, infrared (IR) microscope operating in the wavelength range 800 to 2500 nm has been applied to a variety of packaging related issues. Applications can be divided into three categories. 1) For flip chip devices the advantage of the IR microscope is that most silicon is effectively transparent at wavelengths greater than 1100 nm. This enable defects such as voids, delamination cracks and corrosion to be investigated while the chip is mounted on the substrate. 2) The IR microscope enables thermal images of devices to be obtained with a temperature resolution of approximately 1 K and spatial resolution of 2-3 μm. 3) The transparency of silicon to IR radiation has proved particularly valuable for characterising micro-electro-mechanical systems (MEMS) devices such as microphones, at various stages of packaging, e.g., after die bonding and wire bonding. [ABSTRACT FROM PUBLISHER]