BACKGROUND: High-throughput time-lapse imaging is a fundamental tool for efficient living cell profiling at single-cell resolution. Label-free phase-contrast video microscopy enables noninvasive, nontoxic, and long-term imaging. The tradeoff between speed and throughput, however, implies that despite the state-of-the-art autofocusing algorithms, out-of-focus cells are unavoidable due to the migratory nature of immune cells (velocities >10 μm/min). Here, we propose PostFocus to (i) identify out-of-focus images within time-lapse sequences with a classifier, and (ii) deploy a de-noising diffusion probabilistic model to yield reliable in-focus images.
RESULTS: De-noising diffusion probabilistic model outperformed deep discriminative models with a superior performance on the whole image and around cell boundaries. In addition, PostFocus improves the accuracy of image analysis (cell and contact detection) and the yield of usable videos.
METHODS: Open-source code and sample data are available at: https://github.com/kwu14victor/PostFocus.

Video-microscopy is a technology widely used to follow, in a single cell manner, cell behavior. A number of new studies are searching a way to track these behaviors by artificial intelligence; unfortunately some real-time events still have to be track manually. For that reason, we developed a software that helps the experimenter to analyze collected data. Toto-cell is very simple to use and it can be adapted at different type of analyses or treatments. It allows a wide new range of parameters that were nearly impossible to calculate only by hand. We thus developed this new software using HEC-1-A endometrial cell line to track different cellular parameters such as: the number of normal/abnormal mitosis, the ratio per day of death, mitosis, cell fusions or finally the length between two mitosis cycles. We treated our cells with cisplatin, doxorubicin or AZD5363 (an Akt inhibitor) to obtain different cellular events. What emerged is a huge heterogeneity for these analyzed parameters between the cells in a single treatment which is clearly demonstrated by the results provided by Toto-Cell. In conclusion, our software is an important tool to facilitate the analysis of video-microscopy, in a quantifying and qualifying manner. It enables a higher accuracy when compared to manual calculations.

Flagellum-mediated motility is essential to Pseudomonas aeruginosa (P. aeruginosa) virulence. Antibody against flagellin reduces motility and inhibits the spread of the bacteria from the infection site. The standard soft-agar assay to demonstrate anti-flagella motility inhibition requires long incubation times, is difficult to interpret, and requires large amounts of antibody. We have developed a time-lapse video microscopy method to analyze anti-flagellin P. aeruginosa motility inhibition that has several advantages over the soft agar assay. Antisera from mice immunized with flagellin type A or B were incubated with Green Fluorescent Protein (GFP)-expressing P. aeruginosa strain PAO1 (FlaB+) and GFP-expressing P. aeruginosa strain PAK (FlaA+). We analyzed the motion of the bacteria in video taken in ten second time intervals. An easily measurable decrease in bacterial locomotion was observed microscopically within minutes after the addition of small volumes of flagellin antiserum. From data analysis, we were able to quantify the efficacy of anti-flagellin antibodies in the test serum that decreased P. aeruginosa motility. This new video microscopy method to assess functional activity of anti-flagellin antibodies required less serum, less time, and had more robust and reproducible endpoints than the standard soft agar motility inhibition assay.

Optical microscopy videos enable experts to analyze the motion of several biological elements. Particularly in blood samples infected with Trypanosoma cruzi (T. cruzi), microscopy videos reveal a dynamic scenario where the parasites\' motions are conspicuous. While parasites have self-motion, cells are inert and may assume some displacement under dynamic events, such as fluids and microscope focus adjustments. This paper analyzes the trajectory of T. cruzi and blood cells to discriminate between these elements by identifying the following motion patterns: collateral, fluctuating, and pan-tilt-zoom (PTZ). We consider two approaches: i) classification experiments for discrimination between parasites and cells; and ii) clustering experiments to identify the cell motion. We propose the trajectory step dispersion (TSD) descriptor based on standard deviation to characterize these elements, outperforming state-of-the-art descriptors. Our results confirm motion is valuable in discriminating T. cruzi of the cells. Since the parasites perform the collateral motion, their trajectory steps tend to randomness. The cells may assume fluctuating motion following a homogeneous and directional path or PTZ motion with trajectory steps in a restricted area. Thus, our findings may contribute to developing new computational tools focused on trajectory analysis, which can advance the study and medical diagnosis of Chagas disease.

Primary ciliary dyskinesia (PCD) is an inherited disorder that impairs motile cilia, essential for respiratory health, with a reported prevalence of 1 in 16,309 within Hispanic populations. Despite 70% of Puerto Rican patients having the RSPH4A [c.921+3_921+6del (intronic)] founder mutation, the characterization of the ciliary dysfunction remains unidentified due to the unavailability of advanced diagnostic modalities like High-Speed Video Microscopy Analysis (HSVA). Our study implemented HSVA for the first time on the island as a tool to better diagnose and characterize the RSPH4A [c.921+3_921+6del (intronic)] founder mutation in Puerto Rican patients. By applying HSVA, we analyzed the ciliary beat frequency (CBF) and pattern (CBP) in native Puerto Rican patients with PCD. Our results showed decreased CBF and a rotational CBP linked to the RSPH4A founder mutation in Puerto Ricans, presenting a novel diagnostic marker that could be implemented as an axillary test into the PCD diagnosis algorithm in Puerto Rico. The integration of HSVA technology in Puerto Rico substantially enhances the PCD evaluation and diagnosis framework, facilitating prompt detection and early intervention for improved disease management. This initiative, demonstrating the potential of HSVA as an adjunctive test within the PCD diagnostic algorithm, could serve as a blueprint for analogous developments throughout Latin America.

Senescence is a state of irreversible cell cycle arrest accompanied by the acquisition of the senescence-associated secretory phenotype (SASP), which is activated in response to a variety of damaging stimuli, including genotoxic therapy. Accumulating evidence indicates that mitotic stress also promotes entry into senescence. This occurs via a mechanism involving defective mitoses and mitotic arrest, followed by abortion of cell division and slippage in the G1 phase. In this process, mitotic slippage leads to the generation of senescent cells characterized by a large cell body and a multinucleated and/or enlarged nuclear size. Here, we provide a detailed protocol for the assessment of cell proliferation and mitotic slippage in colorectal cancer cells upon pharmacological inhibition of the mitotic kinesin KIF11, best known as EG5. This approach can be used for preliminary characterization of senescence induction by therapeutics, but requires validation with standard senescence assays.

BACKGROUND: International guidelines disagree on how best to diagnose primary ciliary dyskinesia (PCD), not least because many tests rely on pattern recognition. We hypothesized that quantitative distribution of ciliary ultrastructural and motion abnormalities would detect most frequent PCD-causing groups of genes by soft computing analysis.
METHODS: Archived data on transmission electron microscopy and high-speed video analysis from 212 PCD patients were re-examined to quantitate distribution of ultrastructural (10 parameters) and functional ciliary features (4 beat pattern and 2 frequency parameters). The correlation between ultrastructural and motion features was evaluated by blinded clustering analysis of the first two principal components, obtained from ultrastructural variables for each patient. Soft computing was applied to ultrastructure to predict ciliary beat frequency (CBF) and motion patterns by a regression model. Another model classified the patients into the five most frequent PCD-causing gene groups, from their ultrastructure, CBF and beat patterns.
RESULTS: The patients were subdivided into six clusters with similar values to homologous ultrastructural phenotype, motion patterns, and CBF, except for clusters 1 and 4, attributable to normal ultrastructure. The regression model confirmed the ability to predict functional ciliary features from ultrastructural parameters. The genetic classification model identified most of the different groups of genes, starting from all quantitative parameters.
CONCLUSIONS: Applying soft computing methodologies to PCD diagnostic tests optimizes their value by moving from pattern recognition to quantification. The approach may also be useful to evaluate atypical PCD, and novel genetic abnormalities of unclear disease-producing potential in the future.

Autonomous migration is essential for the function of immune cells such as neutrophils and plays an important role in numerous diseases. The ability to routinely measure or target it would offer a wealth of clinical applications. Video microscopy of live cells is ideal for migration analysis, but cannot be performed at sufficiently high-throughput (HT). Here we introduce ComplexEye, an array microscope with 16 independent aberration-corrected glass lenses spaced at the pitch of a 96-well plate to produce high-resolution movies of migrating cells. With the system, we enable HT migration analysis of immune cells in 96- and 384-well plates with very energy-efficient performance. We demonstrate that the system can measure multiple clinical samples simultaneously. Furthermore, we screen 1000 compounds and identify 17 modifiers of migration in human neutrophils in just 4 days, a task that requires 60-times longer with a conventional video microscope. ComplexEye thus opens the field of phenotypic HT migration screens and enables routine migration analysis for the clinical setting.

The wall of the ventricular system within the neuraxis is lined almost entirely by E1 ependymal cells, each of which projects multiple motile cilia from their apical surface into the cerebrospinal fluid (CSF). This specialized layer of E1 cells constitutes the border between the CSF and the brain interstitial fluid (BIF), and by controlling influx and efflux across the CSF to BIF interface, it is increasingly recognized to play an integral role in modulating and maintaining the brain microenvironment. The motile cilia have been shown to be responsive to changes in the CSF microenvironment, and while the physiological role of this mechanism remains incompletely understood, manipulating this control mechanism may influence the brain microenvironment potentially opening a new frontier in therapeutic intervention.In this paper, we describe our techniques for preparing organotypic slices from the murine brain parenchyma and establishing cell cultures of multiciliated ependymal cells from mouse and rat neonatal brain tissue. Our methodology generates a functional readout of ciliary function, specifically high-speed video microscopy (HSVM) enables the quantification of ciliary beat frequency (CBF), and characterization of ciliary beat pattern.

Reliable label-free methods are needed for detecting and profiling apoptotic events in time-lapse cell-cell interaction assays. Prior studies relied on fluorescent markers of apoptosis, e.g. Annexin-V, that provide an inconsistent and late indication of apoptotic onset for human melanoma cells. Our motivation is to improve the detection of apoptosis by directly detecting apoptotic bodies in a label-free manner.
Our trained ResNet50 network identified nanowells containing apoptotic bodies with 92% accuracy and predicted the onset of apoptosis with an error of one frame (5 min/frame). Our apoptotic body segmentation yielded an IoU accuracy of 75%, allowing associative identification of apoptotic cells. Our method detected apoptosis events, 70% of which were not detected by Annexin-V staining.
Open-source code and sample data provided at https://github.com/kwu14victor/ApoBDproject.