Counting unstained, confluent cells by modified bright-field microscopy

Automated cell counting for Trypan blue-stained cell cultures using machine learning

Cell counting is a vital practice in the maintenance and manipulation of cell cultures. It is a crucial aspect of assessing cell viability and determining proliferation rates, which are integral to maintaining the health and functionality of a culture. Additionally, it is critical for establishing the time of infection in bioreactors and monitoring cell culture response to targeted infection over time. However, when cell counting is performed manually, the time involved can become substantial, particularly when multiple cultures need to be handled in parallel. Automated cell counters, which enable significant time reduction, are commercially available but remain relatively expensive. Here, we present a machine learning (ML) model based on YOLOv4 that is able to perform cell counts with a high accuracy (>95%) for Trypan blue-stained insect cells. Images of two distinctly different cell lines, Trichoplusia ni (High FiveTM; Hi5 cells) and Spodoptera frugiperda (Sf9), were used for training, validation, and testing of the model. The ML model yielded F1 scores of 0.97 and 0.96 for alive and dead cells, respectively, which represents a substantially improved performance over that of other cell counters. Furthermore, the ML model is versatile, as an F1 score of 0.96 was also obtained on images of Trypan blue-stained human embryonic kidney (HEK) cells that the model had not been trained on. Our implementation of the ML model comes with a straightforward user interface and can image in batches, which makes it highly suitable for the evaluation of multiple parallel cultures (e.g. in Design of Experiments). Overall, this approach for accurate classification of cells provides a fast, bias-free alternative to manual counting.

Disposable Polymeric Nanostructured Plasmonic Biosensors for Cell Culture Adhesion Monitoring

Over the last years, optical biosensors based on plasmonic nanomaterials have gained great scientific interest due to their unquestionable advantages compared to other biosensing technologies. They can achieve sensitive, direct, and label-free analysis with exceptional potential for multiplexing and miniaturization. Recently, it has been demonstrated the potential of using optical discs as high throughput nanotemplates for the development of plasmonic biosensors in a cost-effective way. This work is a pilot study focused on the development of an integrated plasmonic biosensor for the monitoring of cell adhesion and growth of human retinal pigmented cell line (ARPE-19) under different media conditions (0 and 2% of FBS). We observed an increase of the plasmonic band displacement under 2% FBS compared to 0% conditions over time (1, 3, and 5 h). These preliminary results show that the proposed plasmonic biosensing approach is a direct, non-destructive, and real-time tool that could be employed in the study of living cells behavior and culture conditions. Furthermore, this setup could assess the viability of the cells and their growth over time with low variability between the technical replicates improving the experimental replicability.

Quantitative Subcellular Analysis of Cyclic Cell-Penetrating Peptide EJP18 in Nonadherent Cells

Cyclization of cell-penetrating peptides (CPPs) often results in improved capacity for intracellular delivery of a range of cargoes but quantitating the distinct subcellular localization of them, and their linear counterparts, remains a challenge. Here we describe an optimized method for recombinant generation and purification of eGFP attached to the cyclic form of the newly discovered CPP EJP18 in E. coli. We also demonstrate a novel microscopy method for quantifying its subcellular distribution in leukemia cells.

Automated Raman Micro-Spectroscopy of Epithelial Cell Nuclei for High-Throughput Classification

Simple Summary

We demonstrate an automated Raman cytology system designed for high-throughput and reproducibility. The system uses a Raman spectroscopy system integrated into a conventional microscope, all controlled electronically via and open source software, Micro-Manager. The system can automatically identify and probe epithelial cell nuclei for Raman spectroscopy. 6426 HT1197 (high-grade bladder cancer) cell spectra, and 7499 RT112 (low-grade bladdercancer) cell spectra were recorded. The data was subsequently culled and processed for denoising and artifact removal. We demonstrate, using multivariate statistical analysis, that the cells can be distinguished, using a variety of approaches with accuracy, sensitivity and specificity in excess of 95%.

Abstract

Raman micro-spectroscopy is a powerful technique for the identification and classification of cancer cells and tissues. In recent years, the application of Raman spectroscopy to detect bladder, cervical, and oral cytological samples has been reported to have an accuracy greater than that of standard pathology. However, despite being entirely non-invasive and relatively inexpensive, the slow recording time, and lack of reproducibility have prevented the clinical adoption of the technology. Here, we present an automated Raman cytology system that can facilitate high-throughput screening and improve reproducibility. The proposed system is designed to be integrated directly into the standard pathology clinic, taking into account their methodologies and consumables. The system employs image processing algorithms and integrated hardware/software architectures in order to achieve automation and is tested using the ThinPrep standard, including the use of glass slides, and a number of bladder cancer cell lines. The entire automation process is implemented, using the open source Micro-Manager platform and is made freely available. We believe that this code can be readily integrated into existing commercial Raman micro-spectrometers.

Automatic cell counting for phase-contrast microscopic images based on a combination of Otsu and watershed segmentation method

Cell counting plays a vital role in biomedical researches. However, manual cell counting is time-consuming, laborious, and low efficiency and has a high counting error rate problem. An automatic counting approach for Hela cells of phase-contrast microscopic images is proposed based on the combination of Otsu and watershed segmentation methods to solve the mentioned issues. Firstly, image preprocessing is performed. Secondly, the Otsu method was used to obtain an automatic global optimal threshold for segmentation to achieve batch counting of images. Thirdly, the marker watershed was performed to separate adherent cells and to avoid over-segmentation simultaneously. Finally, cells in phase-contrast microscopic images were counted by detecting the numbers of connected domains in the binary image. Taking the manual counting result as the counting standard and MIS, INC, and ACC are used as evaluation indicators. The experimental results showed that the average values of MIS, INC, and ACC of the proposed method are only 3.31%, 3.49%, and 96.69%, respectively. Additionally, each cell image was counted only takes 0.65 s on averagely. To further test the performance of the proposed method, a comparative experiment was carried out by Image J, and the result shows that the proposed method has a better counting performance with a higher average accuracy of 96.55% to Image J with 93.39%.The proposed method for cell counting is simple, feasible, fast and high accurate, and it can be used as an effective method for cell counting of the phase-contrast microscopic images.

Engineering Microneedle Patches for Improved Penetration: Analysis, Skin Models and Factors Affecting Needle Insertion

Transdermal microneedle (MN) patches are a promising tool used to transport a wide variety of active compounds into the skin. To serve as a substitute for common hypodermic needles, MNs must pierce the human stratum corneum (~ 10 to 20 µm), without rupturing or bending during penetration. This ensures that the cargo is released at the predetermined place and time. Therefore, the ability of MN patches to sufficiently pierce the skin is a crucial requirement. In the current review, the pain signal and its management during application of MNs and typical hypodermic needles are presented and compared. This is followed by a discussion on mechanical analysis and skin models used for insertion tests before application to clinical practice. Factors that affect insertion (e.g., geometry, material composition and cross-linking of MNs), along with recent advancements in developed strategies (e.g., insertion responsive patches and 3D printed biomimetic MNs using two-photon lithography) to improve the skin penetration are highlighted to provide a backdrop for future research.

A novel method combining aptamer-Ag10NPs based microfluidic biochip with bright field imaging for detection of KPC-2-expressing bacteria

The β-lactam drugs resistance poses a serious threat to human health throughout the world. Klebsiella pneumoniae carbapenemase 2 (KPC-2) is a carbapenemase that produced in bacteria can hydrolyze carbapenems, which typically considered as the antibiotics of last resort. Therefore, there is an urgent need to quickly and accurately detect whether bacteria express KPC-2. In this paper, a PDMS/glass microfluidic biochip integrated with aptamer-modified Ag₁₀NPs nano-biosensors was developed for rapid, simple and specific pathogenic bacteria detection, more importantly, the biochip was combined with bright field imaging, then the captured bacteria could be observed and counted directly without using extra chemical labeling. KPC-2-expressing Escherichia coli (KPC-2 E.coli) was used as the target bacterium with a detected limit of 10² CFU and capture efficiency exceeded 90%. This method is remarkably specific towards KPC-2 E.coli over other non-resistant bacteria, and pathogen assay only takes ∼1 h to complete in a ready-to-use microfluidic biochip. Furthermore, the effective capture and fast counting of microfluidic biochip system demonstrates its potential for the rapid detection of antibiotic-resistant bacteria.

The promyelocytic leukemia protein isoform PML1 is an oncoprotein and a direct target of the antioxidant sulforaphane (SFN)

The gene encoding promyelocytic leukemia protein (PML) generates several spliced isoforms. Ectopic expression of PML1 promotes the proliferation of ERα-positive MCF-7 breast cancer (BC) cells, while a loss of PML by knockdown or overexpression of PML4 does the opposite. PML is an essential constituent of highly dynamic particles called PML nuclear bodies (NBs). PML NBs are heterogenous multiprotein subnuclear structures that are part of cellular stress sensing machinery. The antioxidant sulforaphane (SFN) inhibits the proliferation of BC cells and causes a redistribution of the subcellular localization of PML, a disruption of disulfide-bond linkages in nuclear PML-containing complexes, and a reduction in the number and size of PML NBs. Mechanistically, SFN modifies several cysteine residues, including C204, located in the RBCC domain of PML. PML is sumoylated and contains a Sumo-interacting motif, and a significant fraction of Sumo1 and Sumo2/3 co-localizes with PML NBs. Ectopic expression of the mutant C204A selectively inhibits the biogenesis of endogenous PML NBs but not PML-less Sumo1-, Sumo2/3, or Daxx-containing nuclear speckles. Importantly, PML1 (C204A) functions as a dominant-negative mutant over endogenous PML protein and promotes anti-proliferation activity. Together, we conclude that SFN elicits its cytotoxic activity in part by inactivating PML1's pro-tumorigenic activity.

Optimized High-Contrast Brightfield Microscopy Application for Noninvasive Proliferation Assays of Human Cell Cultures

High-contrast brightfield (HCBF) microscopy has emerged as a strong tool for noninvasive counting of cells in culture. HCBF imaging delivers precise cell growth data and is completely label free rendering it an attractive alternative to common cell counting procedures that often adversely affect cell growth. With computational image analysis, HCBF achieves efficient high-throughput automated workflows, extremely relevant for drug and chemical screens in pharmaceutical, toxicological, and biomedical research. We demonstrate the applicability of HCBF microscopy to count three common cell types (HEK293, Huh7, and primary human dermal fibroblasts) with diverse morphology challenging the method. The three cell types required different analysis settings, and we identified two parameters of the computational image analysis, which after cell-specific optimization significantly improved the cell counting accuracy, namely the lower size limit and the intensity threshold. Three-dimensional (3D) imaging approaches, which have obtained great attention in recent years, were an interesting prospect to combine with HCBF microscopy. We optimized the analysis of two 3D outputs but found 3D HCBF imaging to be inferior to the optimized single-layer HCBF imaging for cell counting. HCBF cell counts were highly linearly correlated with (R² > 0.99) and highly similar (<15% difference) to cell counts obtained through Hoechst staining, over a broad range of densities allowing at least this level of accuracy for two to three cell generations in Huh7 cells and fibroblasts. Counts of HEK293 cells correlated somewhat less. In conclusion, the HCBF cell counting method is excellently suited for cell proliferation assays and cytotoxicity assays.

Infrared spectroscopy of live cells from a flowing solution using electrically-biased plasmonic metasurfaces

Spectral cytopathology (SCP) is a promising label-free technique for diagnosing diseases and monitoring therapeutic outcomes using FTIR spectroscopy. In most cases, cells must be immobilized on a substrate prior to spectroscopic interrogation. This creates significant limitations for high throughput phenotypic whole-cell analysis, especially for the non-adherent cells. Here we demonstrate how metasurface-enhanced infrared reflection spectroscopy (MEIRS) can be applied to a continuous flow of live cell solution by applying AC voltage to metallic metasurfaces. By integrating metasurfaces with microfluidic delivery channels and attracting the cells to the metasurface via dielectrophoretic (DEP) force, we collect the infrared spectra of cells in real time within a minute, and correlate the spectra with simultaneously acquired images of the attracted cells. The resulting DEP-MEIRS technique paves the way for rapid SCP of complex cell-containing body fluids with low cell concentrations, and for the development of a wide range of label-free liquid biopsies.

Optical microscopic study of surface morphology and filtering efficiency of face masks

Background

Low-cost face masks made from different cloth materials are very common in developing countries. The cloth masks (CM) are usually double layered with stretchable ear loops. It is common practice to use such masks for months after multiple washing and drying cycles. If a CM is used for long time, the ear loops become stretched. The loop needs to be knotted to make the mask loop fit better on the face. It is not clear how washing and drying and stretching practices change the quality of a CM. The particulate matter (PM) filtering efficiency of a mask depends on multiple parameters, such as pore size, shape, clearance, and pore number density. It is important to understand the effect of these parameters on the filtering efficiency.

Methods

We characterized the surface of twenty different types of CMs using optical image analysis method. The filtering efficiency of selected cloth face masks was measured using the particle counting method. We also studied the effects of washing and drying and stretching on the quality of a mask.

Results

The pore size of masks ranged from 80 to 500 μm, which was much bigger than particular matter having diameter of 2.5 μm or less (PM_2.5) and 10 μm or less (PM₁₀) size. The PM₁₀ filtering efficiency of four of the selected masks ranged from 63% to 84%. The poor filtering efficiency may have arisen from larger and open pores present in the masks. Interestingly, we found that efficiency dropped by 20% after the 4th washing and drying cycle. We observed a change in pore size and shape and a decrease in microfibers within the pores after washing. Stretching of CM surface also altered the pore size and potentially decreased the filtering efficiency. As compared to CMs, the less frequently used surgical/paper masks had complicated networks of fibers and much smaller pores in multiple layers in comparison to CMs, and therefore had better filtering efficiency. This study showed that the filtering efficiency of cloth face masks were relatively lower, and washing and drying practices deteriorated the efficiency. We believe that the findings of this study will be very helpful for increasing public awareness and help governmental agencies to make proper guidelines and policies for use of face mask.

Integrated use of LC/MS/MS and LC/Q-TOF/MS targeted metabolomics with automated label-free microscopy for quantification of purine metabolites in cultured mammalian cells

Purine metabolites have been implicated as clinically relevant biomarkers of worsening or improving Parkinson's disease (PD) progression. However, the identification of purine molecules as biomarkers in PD has largely been determined using non-targeted metabolomics analysis. The primary goal of this study was to develop an economical targeted metabolomics approach for the routine detection of purine molecules in biological samples. Specifically, this project utilized LC/MS/MS and LC/QTOF/MS to accurately quantify levels of six purine molecules in samples from cultured N2a murine neuroblastoma cells. The targeted metabolomics workflow was integrated with automated label-free digital microscopy, which enabled normalization of purine concentration per unit cell in the absence of fluorescent dyes. The established method offered significantly enhanced selectivity compared to previously published procedures. In addition, this study demonstrates that a simple, quantitative targeted metabolomics approach can be developed to identify and quantify purine metabolites in biological samples. We envision that this method could be broadly applicable to quantification of purine metabolites from other complex biological samples, such as cerebrospinal fluid or blood.

Iterative unsupervised domain adaptation for generalized cell detection from brightfield z-stacks

BACKGROUND

Cell counting from cell cultures is required in multiple biological and biomedical research applications. Especially, accurate brightfield-based cell counting methods are needed for cell growth analysis. With deep learning, cells can be detected with high accuracy, but manually annotated training data is required. We propose a method for cell detection that requires annotated training data for one cell line only, and generalizes to other, unseen cell lines.

RESULTS

Training a deep learning model with one cell line only can provide accurate detections for similar unseen cell lines (domains). However, if the new domain is very dissimilar from training domain, high precision but lower recall is achieved. Generalization capabilities of the model can be improved with training data transformations, but only to a certain degree. To further improve the detection accuracy of unseen domains, we propose iterative unsupervised domain adaptation method. Predictions of unseen cell lines with high precision enable automatic generation of training data, which is used to train the model together with parts of the previously used annotated training data. We used U-Net-based model, and three consecutive focal planes from brightfield image z-stacks. We trained the model initially with PC-3 cell line, and used LNCaP, BT-474 and 22Rv1 cell lines as target domains for domain adaptation. Highest improvement in accuracy was achieved for 22Rv1 cells. F1-score after supervised training was only 0.65, but after unsupervised domain adaptation we achieved a score of 0.84. Mean accuracy for target domains was 0.87, with mean improvement of 16 percent.

CONCLUSIONS

With our method for generalized cell detection, we can train a model that accurately detects different cell lines from brightfield images. A new cell line can be introduced to the model without a single manual annotation, and after iterative domain adaptation the model is ready to detect these cells with high accuracy.

Improved contrast microscopy: modification of bright field for urine sediment visualisation

BACKGROUND

Phase contrast microscopy is the recommended technique for urine sediment examination. Bright field microscopy does not differentiate objects with slight changes in the refractive index and hence phase contrast is a superior alternative.

METHODS

In this article, we describe a novel method to improve contrast in bright field microscopy. A strategically placed disc of specific dimensions enhances the diffraction of rays by Fresnel principle causing a shift in wavelength in the rays which are perceived as differences in contrast by the eye due to constructive and destructive interference.

RESULTS

Epithelial cells, red blood cells (RBCs), dysmorphic red blood cells, casts, bacteria and crystals are easily seen and differentiated by this technique.

CONCLUSIONS

The images obtained are similar to those obtained by phase contrast microscopy.

Identification and validation of COX-2 as a co-target for overcoming cetuximab resistance in colorectal cancer cells

Cetuximab, an epidermal growth factor receptor (EGFR)-blocking antibody, was approved for treatment of metastatic colorectal cancer over a decade ago; however, patients' responses to cetuximab vary substantially due to intrinsic and acquired resistance to cetuximab. Here, we report our findings using Affymetrix HG-U133A array to examine changes in global gene expression between DiFi, a human colorectal cancer cell line that is highly sensitive to cetuximab, and two other cell lines: DiFi5, a DiFi subline with acquired resistance to cetuximab, and DiFi-AG, a DiFi subline with acquired resistance to the EGFR tyrosine kinase inhibitor AG1478 but sensitivity to cetuximab. We identified prostaglandin-endoperoxide synthase 2 (PTGS2), which encodes cyclooxygenase-2 (COX-2), as the gene with the greatest difference between the cetuximab-resistant DiFi5 cells and the cetuximab-sensitive DiFi cells and DiFi-AG cells. Reverse transcription polymerase chain reaction and Western blotting validated upregulation of COX-2 in DiFi5 but not in DiFi or DiFi-AG cells. We developed COX-2 knockdown stable clones from DiFi5 cells and demonstrated that genetic knockdown of COX-2 partially re-sensitized DiFi5 cells to cetuximab. We further confirmed that cetuximab in combination with a COX-2 inhibitor led to cell death via apoptosis or autophagy not only in DiFi5 cells but also in another colorectal cancer cell line naturally resistant to cetuximab. Our findings support further evaluation of the strategy of combining cetuximab and a COX-2 inhibitor for treatment of metastatic colorectal cancer.

Human-level blood cell counting on lens-free shadow images exploiting deep neural networks

In-line holographic microscopes paved the way for realizing portable cell counting systems using deep neural networks.

A feed-forward regulation of endothelin receptors by c-Jun in human non-pigmented ciliary epithelial cells and retinal ganglion cells

c-Jun, c-Jun N-terminal kinase(JNK) and endothelin B (ET_B) receptor have been shown to contribute to the pathogenesis of glaucoma. Previously, we reported that an increase of c-Jun and CCAAT/enhancer binding protein β (C/EBPβ) immunohistostaining is associated with upregulation of the ET_B receptor within the ganglion cell layer of rats with elevated intraocular pressure (IOP). In addition, both transcription factors regulate the expression of the ET_B receptor in human non-pigmented ciliary epithelial cells (HNPE). The current study addressed the mechanisms by which ET-1 produced upregulation of ET receptors in primary rat retinal ganglion cells (RGCs) and HNPE cells. Treatment of ET-1 and ET-3 increased the immunocytochemical staining of c-Jun and C/EBPβ in primary rat RGCs and co-localization of both transcription factors was observed. A marked increase in DNA binding activity of AP-1 and C/EBPβ as well as elevated protein levels of c-Jun and c-Jun-N-terminal kinase (JNK) were detected following ET-1 treatment in HNPE cells. Overexpression of ET_A or ET_B receptor promoted the upregulation of c-Jun and also elevated its promoter activity. In addition, upregulation of C/EBPβ augmented DNA binding and mRNA expression of c-Jun, and furthermore, the interaction of c-Jun and C/EBPβ was confirmed using co-immunoprecipitation. Apoptosis of HNPE cells was identified following ET-1 treatment, and overexpression of the ET_A or ET_B receptor produced enhanced apoptosis. ET-1 mediated upregulation of c-Jun and C/EBPβ and their interaction may represent a novel mechanism contributing to the regulation of endothelin receptor expression. Reciprocally, c-Jun was also found to regulate the ET receptors and C/EBPβ appeared to play a regulatory role in promoting expression of c-Jun. Taken together, the data suggests that ET-1 triggers the upregulation of c-Jun through both ET_A and ET_B receptors, and conversely c-Jun also upregulates endothelin receptor expression, thereby generating a positive feed-forward loop of endothelin receptor activation and expression. This feed-forward regulation may contribute to RGC death and astrocyte proliferation following ET-1 treatment.

AP1G1 is involved in cetuximab-mediated downregulation of ASCT2-EGFR complex and sensitization of human head and neck squamous cell carcinoma cells to ROS-induced apoptosis

In this study, we expanded our recent work showing that ASCT2, a Na⁺-dependent neutral amino acid transporter that plays a major role in glutamine uptake in cancer cells, is physically associated with EGFR in human head and neck squamous cell carcinoma cells and in several other types of cancer cells. We found in our current study that ASCT2 can be downregulated by cetuximab, an approved anti-EGFR therapeutic antibody, via cetuximab-induced EGFR endocytosis independently of cetuximab-mediated inhibition of EGFR tyrosine kinase. We further found that ASCT2-EGFR association involves the adaptor-related protein complex 1 gamma 1 subunit (AP1G1), a subunit of clathrin-associated adaptor protein complex 1, which plays a role in membrane protein sorting in endosomes after receptor-mediated endocytosis. We found that AP1G1 is physically associated with both ASCT2 and EGFR and, together with those molecules, forms a heterotrimeric molecular complex. Knockdown of AP1G1 lowered the level of ASCT2-EGFR association, inhibited cetuximab-mediated internalization of ASCT2-EGFR complex, and decreased intracellular glutamine uptake and glutathione biosynthesis. These findings suggest a new therapeutic strategy to overcome cetuximab resistance in cancer cells through combination of cetuximab, which co-targets ASCT2 along with EGFR, with an ROS-inducing agent.

Robust microbial cell segmentation by optical-phase thresholding with minimal processing requirements

High-throughput imaging with single-cell resolution has enabled remarkable discoveries in cell physiology and Systems Biology investigations. A common, and often the most challenging step in all such imaging implementations, is the ability to segment multiple images to regions that correspond to individual cells. Here, a robust segmentation strategy for microbial cells using Quantitative Phase Imaging is reported. The proposed method enables a greater than 99% yeast cell segmentation success rate, without any computationally-intensive, post-acquisition processing. We also detail how the method can be expanded to bacterial cell segmentation with 98% success rates with substantially reduced processing requirements in comparison to existing methods. We attribute this improved performance to the remarkably uniform background, elimination of cell-to-cell and intracellular optical artifacts, and enhanced signal-to-background ratio-all innate properties of imaging in the optical-phase domain. © 2017 International Society for Advancement of Cytometry.

Quantification of Calcified Particles in Human Valve Tissue Reveals Asymmetry of Calcific Aortic Valve Disease Development

Recent studies indicated that small calcified particles observable by scanning electron microscopy (SEM) may initiate calcification in cardiovascular tissues. We hypothesized that if the calcified particles precede gross calcification observed in calcific aortic valve disease (CAVD), they would exhibit a regional asymmetric distribution associated with CAVD development, which always initiates at the base of aortic valve leaflets adjacent to the aortic outflow in a region known as the fibrosa. Testing this hypothesis required counting the calcified particles in histological sections of aortic valve leaflets. SEM images, however, do not provide high contrast between components within images, making the identification and quantification of particles buried within tissue extracellular matrix difficult. We designed a new unique pattern-matching based technique to allow for flexibility in recognizing particles by creating a gap zone in the detection criteria that decreased the influence of non-particle image clutter in determining whether a particle was identified. We developed this flexible pattern particle-labeling (FpPL) technique using synthetic test images and human carotid artery tissue sections. A conventional image particle counting method (preinstalled in ImageJ) did not properly recognize small calcified particles located in noisy images that include complex extracellular matrix structures and other commonly used pattern-matching methods failed to detect the wide variation in size, shape, and brightness exhibited by the particles. Comparative experiments with the ImageJ particle counting method demonstrated that our method detected significantly more (p < 2 × 10^-7) particles than the conventional method with significantly fewer (p < 0.0003) false positives and false negatives (p < 0.0003). We then applied the FpPL technique to CAVD leaflets and showed a significant increase in detected particles in the fibrosa at the base of the leaflets (p < 0.0001), supporting our hypothesis. The outcomes of this study are twofold: (1) development of a new image analysis technique that can be adapted to a wide range of applications and (2) acquisition of new insight on potential early mediators of calcification in CAVD.

Understanding Polymer-Cell Attachment

The development of polymeric materials with cell adhesion abilities requires an understanding of cell-surface interactions which vary with cell type. To investigate the correlation between cell attachment and the nature of the polymer, a series of random and block copolymers composed of 2-(dimethylamino)ethyl acrylate and ethyl acrylate are synthesized through single electron transfer living radical polymerization. The polymers are synthesized with highly defined and controlled monomer compositions and exhibited narrow polydispersity indices. These polymers are examined for their performance in the attachment and growth of HeLa and HEK cells, with attachment successfully modeled on monomer composition and polymer chain length, with both cell lines found to preferentially attach to moderately hydrophobic functional materials. The understanding of the biological-material interactions assessed in this study will underpin further investigations of engineered polymer scaffolds with predictable cell binding performance.

Acetyl-CoA carboxylase rewires cancer metabolism to allow cancer cells to survive inhibition of the Warburg effect by cetuximab

Cetuximab inhibits HIF-1-regulated glycolysis in cancer cells, thereby reversing the Warburg effect and leading to inhibition of cancer cell metabolism. AMP-activated protein kinase (AMPK) is activated after cetuximab treatment, and a sustained AMPK activity is a mechanism contributing to cetuximab resistance. Here, we investigated how acetyl-CoA carboxylase (ACC), a downstream target of AMPK, rewires cancer metabolism in response to cetuximab treatment. We found that introduction of experimental ACC mutants lacking the AMPK phosphorylation sites (ACC1_S79A and ACC2_S212A) into head and neck squamous cell carcinoma (HNSCC) cells protected HNSCC cells from cetuximab-induced growth inhibition. HNSCC cells with acquired cetuximab resistance contained not only high levels of T172-phosphorylated AMPK and S79-phosphorylated ACC1 but also an increased level of total ACC. These findings were corroborated in tumor specimens of HNSCC patients treated with cetuximab. Cetuximab plus TOFA (an allosteric inhibitor of ACC) achieved remarkable growth inhibition of cetuximab-resistant HNSCC xenografts. Our data suggest a novel paradigm in which cetuximab-mediated activation of AMPK and subsequent phosphorylation and inhibition of ACC is followed by a compensatory increase in total ACC, which rewires cancer metabolism from glycolysis-dependent to lipogenesis-dependent.

Technique to ‘Map' Chromosomal Mosaicism at the Blastocyst Stage

The purpose of this study was to identify a technique that allows for comprehensive chromosome screening (CCS) of individual cells within human blastocysts along with the approximation of their location in the trophectoderm relative to the inner cell mass (ICM). This proof-of-concept study will allow for a greater understanding of chromosomal mosaicism at the blastocyst stage and the mechanisms by which mosaicism arises. One blastocyst was held by a holding pipette and the ICM was removed. While still being held, the blastocyst was further biopsied into quadrants. To separate the individual cells from the biopsied sections, the sections were placed in calcium/magnesium-free medium with serum for 20 min. A holding pipette was used to aspirate the sections until individual cells were isolated. Individual cells from each section were placed into PCR tubes and prepped for aCGH. A total of 18 cells were used for analysis, of which 15 (83.3%) amplified and provided a result and 3 (16.7%) did not. Fifteen cells were isolated from the trophectoderm; 13 (86.7%) provided an aCGH result, while 2 (13.3%) did not amplify. Twelve cells were euploid (46,XY), while 1 was complex abnormal (44,XY), presenting with monosomy 7, 10, 11, 13, and 19, and trisomy 14, 15, and 21. A total of 3 cells were isolated from the ICM; 2 were euploid (46,XY) and 1 did not amplify. Here, we expand on a previously published technique which disassociates biopsied sections of the blastocyst into individual cells. Since the blastocyst sections were biopsied in regard to the position of the ICM, it was possible to reconstruct a virtual image of the blastocyst while presenting each cell's individual CCS results.

Non-invasive and non-destructive measurements of confluence in cultured adherent cell lines

Many protocols used for measuring the growth of adherent monolayer cells in vitro are invasive, destructive and do not allow for the continued, undisturbed growth of cells within flasks. Protocols often use indirect methods for measuring proliferation. Microscopy techniques can analyse cell proliferation in a non-invasive or non-destructive manner but often use expensive equipment and software algorithms. In this method images of cells within flasks are captured by photographing under a standard inverted phase contract light microscope using a digital camera with a camera lens adaptor. Images are analysed for confluence using ImageJ freeware resulting in a measure of confluence known as an Area Fraction (AF) output. An example of the AF method in use on OVCAR8 and UPN251 cell lines is included.

•

Measurements of confluence from growing adherent cell lines in cell culture flasks is obtained in a non-invasive, non-destructive, label-free manner.

•

The technique is quick, affordable and eliminates sample manipulation.

•

The technique provides an objective, consistent measure of when cells reach confluence and is highly correlated to manual counting with a haemocytometer. The average correlation co-efficient from a Spearman correlation (n = 3) was 0.99 ± 0.008 for OVCAR8 (p = 0.01) and 0.99 ± 0.01 for UPN251 (p = 0.01) cell lines.

Semi-quantitative monitoring of confluence of adherent mesenchymal stromal cells on calcium-phosphate granules by using widefield microscopy images

The analysis of cell confluence and proliferation is essential to design biomaterials and scaffolds to use as bone substitutes in clinical applications. Accordingly, several approaches have been proposed in the literature to estimate the area of the scaffold covered by cells. Nevertheless, most of the approaches rely on sophisticated equipment not employed for routine analyses, while the rest of them usually do not provide significant statistics about the cell distribution. This research aims at studying confluence and proliferation of mesenchymal stromal cells (MSC) adherent on OSPROLIFE(®), a commercial biomaterial in the form of granules. In particular, we propose a Computer Vision approach that can routinely be employed to monitor the surface of the single granules covered by cells because only a standard widefield fluorescent microscope is required. In order to acquire significant statistics data, we analyse wide-area images built by using MicroMos v2.0, an updated version of a previously published software specific for stitching brightfield and phase-contrast images manually acquired via a widefield microscope. In particular, MicroMos v2.0 permits to build accurate "mosaics" of fluorescent images, after correcting vignetting and photo-bleaching effects, providing a consistent representation of a sample region containing numerous granules. Then, our method allows to make automatically a statistically significant estimate of the percentage of the area of the single granules covered by cells. Finally, by analysing hundreds of granules at different time intervals we also obtained reliable data regarding cell proliferation, confirming that not only MSC adhere onto the OSPROLIFE(®) granules, but even proliferate over time.