In-line cosmetic end-point detection of batch coating processes for colored tablets using multivariate image analysis.

In this study, an in-line Process Analytical Technology (PAT) for cosmetic (non-functional) coating unit operations is developed using images of the tablet bed acquired in real-time by an inexpensive industrial camera and lighting system. The cosmetic end-point of multiple batches, run under different operating conditions, is automatically computed from these images using a Multivariate Image Analysis (MIA) methodology in conjunction with a stability determination strategy. The end-points detected by the algorithm differed, on average, by 3% in terms of total batch time from those identified visually by a trained operator. Since traditional practice typically relies on a coating overage to ensure full batch aspect homogeneity in the face of disturbances, the current in-line method can be used to reduce coating material and processing time (over 40% for the operating policy adopted in this work). Additionally, monitoring of the color features calculated by the algorithm allowed the identification of abnormal process conditions affecting visible coating uniformity. This work also addresses practical challenges related to image acquisition in the harsh environment of a pan coater, bringing this tool closer to a state of maturity for implementation in production units and opening the path for their optimization, monitoring, and automatic control.

Inspection of baked carbon anodes using a combination of multi-spectral acousto-ultrasonic techniques and principal component analysis.

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes.

Dynamics of Endothelial Cell Responses to Laminar Shear Stress on Surfaces Functionalized with Fibronectin-Derived Peptides.

Surface endothelialization could improve the long-term performance of vascular grafts and stents. We previously demonstrated that aerosol-generated fibronectin-derived peptide micropatterns consisting of GRGDS spots over a WQPPRARI background increase endothelial cell yields in static cultures. We developed a novel fluorophore-tagged RGD peptide (RGD-TAMRA) to visualize cell-surface interactions in real-time. Here, we studied the dynamics of endothelial cell response to laminar flow on these peptide-functionalized surfaces. Endothelial cells were exposed to 22 dyn/cm2 wall shear stress while acquiring time-lapse images. Cell surface coverage and cell alignment were quantified by undecimated wavelet transform multivariate image analysis. Similar to gelatin-coated surfaces, surfaces with uniform RGD-TAMRA distribution led to cell retention and rapid cell alignment (∼63% of the final cell alignment was reached within 1.5 h), contrary to the micropatterned surfaces. The RGD-TAMRA peptide is a promising candidate for endothelial cell retention under flow, and the spray-based micropatterned surfaces are more promising for static cultures.

Monitoring of adherent live cells morphology using the undecimated wavelet transform multivariate image analysis (UWT-MIA).

Cell morphology is an important macroscopic indicator of cellular physiology and is increasingly used as a mean of probing culture state in vitro. Phase contrast microscopy (PCM) is a valuable tool for observing live cells morphology over long periods of time with minimal culture artifact. Two general approaches are commonly used to analyze images: individual object segmentation and characterization by pattern recognition. Single-cell segmentation is difficult to achieve in PCM images of adherent cells since their contour is often irregular and blurry, and the cells bundle together when the culture reaches confluence. Alternatively, pattern recognition approaches such as the undecimated wavelet transform multivariate image analysis (UWT-MIA), allow extracting textural features from PCM images that are correlated with cellular morphology. A partial least squares (PLS) regression model built using textural features from a set of 200 ground truth images was shown to predict the distribution of cellular morphological features (major and minor axes length, orientation, and roundness) with good accuracy for most images. The PLS models were then applied on a large dataset of 631,136 images collected from live myoblast cell cultures acquired under different conditions and grown in two different culture media. The method was found sensitive to morphological changes due to cell growth (culture time) and those introduced by the use of different culture media, and was able to distinguish both sources of variations. The proposed approach is promising for application on large datasets of PCM live-cell images to assess cellular morphology and growth kinetics in real-time which could be beneficial for high-throughput screening as well as automated cell culture kinetics assessment and control applications. Biotechnol. Bioeng. 2017;114: 141-153. © 2016 Wiley Periodicals, Inc.

A fluorophore-tagged RGD peptide to control endothelial cell adhesion to micropatterned surfaces.

The long-term patency rates of vascular grafts and stents are limited by the lack of surface endothelialisation of the implanted materials. We have previously reported that GRGDS and WQPPRARI peptide micropatterns increase the endothelialisation of prosthetic materials in vitro. To investigate the mechanisms by which the peptide micropatterns affect endothelial cell adhesion and proliferation, a TAMRA fluorophore-tagged RGD peptide was designed. Live cell imaging revealed that the micropatterned surfaces led to directional cell spreading dependent on the location of the RGD-TAMRA spots. Focal adhesions formed within 3 h on the micropatterned surfaces near RGD-TAMRA spot edges, as expected for cell regions experiencing high tension. Similar levels of focal adhesion kinase phosphorylation were observed after 3 h on the micropatterned surfaces and on surfaces treated with RGD-TAMRA alone, suggesting that partial RGD surface coverage is sufficient to elicit integrin signaling. Lastly, endothelial cell expansion was achieved in serum-free conditions on gelatin-coated, RGD-TAMRA treated or micropatterned surfaces. These results show that these peptide micropatterns mainly impacted cell adhesion kinetics rather than cell proliferation. This insight will be useful for the optimization of micropatterning strategies to improve vascular biomaterials.

Correlation between the plasma characteristics and the surface chemistry of plasma-treated polymers through partial least-squares analysis.

We investigated the effect of various plasma parameters (relative density of atomic N and H, plasma temperature, and vibrational temperature) and process conditions (pressure and H2/(N2 + H2) ratio) on the chemical composition of modified poly(tetrafluoroethylene) (PTFE). The plasma parameters were measured by means of near-infrared (NIR) and UV-visible emission spectroscopy with and without actinometry. The process conditions of the N2-H2 microwave discharges were set at various pressures ranging from 100 to 2000 mTorr and H2/(N2+H2) gas mixture ratios between 0 and 0.4. The surface chemical composition of the modified polymers was determined by X-ray photoelectron spectroscopy (XPS). A mathematical model was constructed using the partial least-squares regression algorithm to correlate the plasma information (process condition and plasma parameters as determined by emission spectroscopy) with the modified surface characteristics. To construct the model, a set of data input variables containing process conditions and plasma parameters were generated, as well as a response matrix containing the surface composition of the polymer. This model was used to predict the composition of PTFE surfaces subjected to N2-H2 plasma treatment. Contrary to what is generally accepted in the literature, the present data demonstrate that hydrogen is not directly involved in the defluorination of the surface but rather produces atomic nitrogen and/or NH radicals that are shown to be at the origin of fluorine atom removal from the polymer surface. The results show that process conditions alone do not suffice in predicting the surface chemical composition and that the plasma characteristics, which cannot be easily correlated with these conditions, should be considered. Process optimization and control would benefit from plasma diagnostics, particularly infrared emission spectroscopy.

Selection and tuning of a fast and simple phase-contrast microscopy image segmentation algorithm for measuring myoblast growth kinetics in an automated manner.

Acquiring and processing phase-contrast microscopy images in wide-field long-term live-cell imaging and high-throughput screening applications is still a challenge as the methodology and algorithms used must be fast, simple to use and tune, and as minimally intrusive as possible. In this paper, we developed a simple and fast algorithm to compute the cell-covered surface (degree of confluence) in phase-contrast microscopy images. This segmentation algorithm is based on a range filter of a specified size, a minimum range threshold, and a minimum object size threshold. These parameters were adjusted in order to maximize the F-measure function on a calibration set of 200 hand-segmented images, and its performance was compared with other algorithms proposed in the literature. A set of one million images from 37 myoblast cell cultures under different conditions were processed to obtain their cell-covered surface against time. The data were used to fit exponential and logistic models, and the analysis showed a linear relationship between the kinetic parameters and passage number and highlighted the effect of culture medium quality on cell growth kinetics. This algorithm could be used for real-time monitoring of cell cultures and for high-throughput screening experiments upon adequate tuning.

Cell culture tracking by multivariate analysis of raw LCMS data.

Liquid chromatography mass spectrometry (LCMS) is a powerful technique that could serve to rapidly characterize cell culture protein expression profile and be used as a process monitoring and control tool. However, this application is often hampered by both the sample proteome and the LCMS signal complexities as well as the variability of this signal. To alleviate this problem, culture samples are usually extensively fractionated and pretreated before being analyzed by top-end instruments. Such an approach precludes LCMS usage for routine on-line or at-line application. In this work, by applying multivariate analysis (MA) directly on raw LCMS signals, we were able to extract relevant information from cell culture samples that were simply lyzed. By using the recombinant adenovirus production process as a model, we were able to follow the accumulation of the three major proteins produced, identified their accumulation dynamics, and draw useful conclusions from these results. The combination of LCMS and MA provides a simple, rapid, and precise means to monitor cell culture.

Single-cell level analysis of megakaryocyte growth and development.

Several fundamental questions regarding cell growth and development can be answered by recording and analyzing the history of cells and their progeny. Herein, long-term and large-field live cell imaging was used to study the process of megakaryopoiesis at the single cell level (n = 9300) from human CD34+ cord blood (CB) in the presence of thrombopoietin (TPO) or the cytokine cocktail BS1 with or without nicotinamide (NIC). Comparative analyses revealed that the cocktail BS1 increased the mitotic and proplatelet rate of diploid and polyploid cells, respectively. Conversely, only NIC treatment increased the endomitotic rate of megakaryocytes (MKs) leading to the formation of CB-MKs with ploidy level frequently observed with BM-MKs. However, NIC failed to enhance platelet production. Rather, a 7- and 31-fold reduction in proplatelet formation was observed in tetraploid and octaploid CB-MKs, respectively, and ex vivo platelet production output was reduced by half due to a reduction in MK output in NIC cultures. Unexpectedly, a significant fraction of di- and polyploid CB-MKs were seen to undergo complete proplatelet regression. Though rare (< 0.6%), proplatelet reversal led to the formation of regular round cells that could at times resume normal development. The cell tracking data was then used to investigate the impact of "developmental fate" and ploidy on cell cycling time, and to identify potential developmental patterns. These analyses revealed that cell fate and ploidy level have major impacts on the cell cycling time of the cells, and that four recurrent cell lineage patterns could be identified for CD34+ cells undergoing MK differentiation.

Polyploid megakaryocytes can complete cytokinesis.

Megakaryocytes (MK) undergo polyploidization through endomitosis, a mitotic process that ends prematurely due to aborted cytokinesis. To better understand this and other events associated with MK differentiation, we performed long-term and large-field live cell imaging of human MKs derived in cord blood (CB) and bone marrow (BM) CD34(+) cell cultures. Polyploid level of imaged cells was evaluated using three complementary approaches; cell history, cell size and ploidy correlation and nuclei staining. This system and strategy enabled the direct observation of the development of a large number of MKs (n=4865) and to quantify their fates. The most significant finding of this study is that a considerable proportion of polyploid MKs could complete cytokinesis. This unexpected process gave rise to polyploid daughter cell(s) with normal fates and contributed significantly to the expansion of polyploid MKs. Further analyses revealed that the proliferation rate amongst polyploid MKs was inversely correlated to their ploidy level, and that this phenomenon was much more frequent in CB- than BM-derived MKs. Accordingly, endomitosis was identified as the dominant fate of polyploid BM-MKs, while this was less accentuated for polyploid CB-MKs. These findings explain partially why CB-derived MKs remain in lower ploidy class. In conclusion, this study demonstrates that the development of polyploid MK results from the failure and/or success of cytokinesis and brings a new paradigm to the field of megakaryopoiesis.

Multivariate analysis of single quadrupole LC-MS spectra for routine characterization and quantification of intact proteins.

Modern high-throughput proteomic platforms allow incomparable protein mixture resolution and identification. However, such sophisticated facilities are expensive and not always accessible for routine analysis of simple mixtures. In this paper, we propose a simple methodology, based on detection of intact, nondigested proteins by LC coupled to single quadrupole MS (sqLC-MS), followed by the analysis of the resulting spectra by multivariate analysis (MA). By doing so, even large molecular weight (MW) proteins, generating complex spectra, can be characterized to a level that allows isoform discrimination, while standard algorithms, such as MS spectrum deconvolution, cannot. To demonstrate the effectiveness of the proposed approach, we have analyzed the spectra of a set of purified, intact albumins from seven different organisms (bovine, human, rabbit, rat, sheep, mouse, and pig) as a model of microheterogenous proteins, using Projection to Latent Structure Discriminant Analysis (PLS-DA). Although these proteins are very similar (less than 1% difference in MW), sqLC-MS/MA allowed their classification, and the identification of unknown source samples. In addition, MA allowed precise protein quantification from the same data (calibration curve R2 = 0.9966). The ability to rapidly characterize and quantify proteins, together with simplicity and affordability, could make of combined sqLC-MS/MA a routine method for the characterization of simple mixture of known proteins.