"The truth should not be hidden": Experiences and recommendations of individuals making NPE discoveries through genetic genealogy databases.

PURPOSE: Fueled by direct-to-consumer (DTC) genetic testing and genetic-relative finder services, some participants in genetic genealogy databases are making "not parent expected" (NPE) discoveries. To better understand experiences of this phenomenon, we surveyed a large cohort of users of genetic relative finder (GRF) services concerning their experiences after an NPE discovery. METHODS: Using thematic analysis, we analyzed responses from a cohort of GRF users (n = 646) to open-ended survey items to understand these experiences and their recommendations for DTC genetic testing companies and other GRF users. RESULTS: We found that individuals had both positive and negative emotional experiences related to the NPE discovery. Positive aspects included deeper self-understanding, connecting with new family members, and uncovering answers to questions. Negative aspects included rejection by new genetic relatives, inability to seek answers from relatives who had already died, and impairment of family relationships, especially with mothers. For many participants, the challenges after the discovery nevertheless felt worthwhile because the truth was uncovered. Perhaps notably, some participants suggested enhanced warnings prediscovery and improved support after discovery from companies who provide DTC genetic testing services. CONCLUSION: GRF services are powerful tools for family research and genealogy. Despite some possible positive and worthwhile experiences arising from making an NPE discovery, GRF users risk dealing with this potentially life-altering experience without adequate support. Participants in this study recommended an increase in resources from DTC genetic testing companies that could help users anticipate and navigate an NPE discovery.

Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep-learning tool HEV-finder.

Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor-draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high-throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep-learning model and created a graphical user interface for visualization of the results. The tool, named the HEV-finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV-finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large-scale, fully automated, and user-independent, image-based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Comparison of two rapid automated analysis tools for large FTIR microplastic datasets.

One of the biggest issues in microplastic (MP, plastic items <5 mm) research is the lack of standardisation and harmonisation in all fields, reaching from sampling methodology to sample purification, analytical methods and data analysis. This hampers comparability as well as reproducibility among studies. Concerning chemical analysis of MPs, Fourier-transform infrared (FTIR) spectroscocopy is one of the most powerful tools. Here, focal plane array (FPA) based micro-FTIR (µFTIR) imaging allows for rapid measurement and identification without manual preselection of putative MP and therefore enables large sample throughputs with high spatial resolution. The resulting huge datasets necessitate automated algorithms for data analysis in a reasonable time frame. Although solutions are available, little is known about the comparability or the level of reliability of their output. For the first time, within our study, we compare two well-established and frequently applied data analysis algorithms in regard to results in abundance, polymer composition and size distributions of MP (11-500 µm) derived from selected environmental water samples: (a) the siMPle analysis tool (systematic identification of MicroPlastics in the environment) in combination with MPAPP (MicroPlastic Automated Particle/fibre analysis Pipeline) and (b) the BPF (Bayreuth Particle Finder). The results of our comparison show an overall good accordance but also indicate discrepancies concerning certain polymer types/clusters as well as the smallest MP size classes. Our study further demonstrates that a detailed comparison of MP algorithms is an essential prerequisite for a better comparability of MP data.

Measurement of Trunk Movement during Sit-to-Stand Motion Using Laser Range Finders: A Preliminary Study.

The sit-to-stand (STS) motion evaluates physical functions in frail older adults. Mounting sensors or using a camera is necessary to measure trunk movement during STS motion. Therefore, we developed a simple measurement method by embedding laser range finders in the backrests and seats of chairs that can be used in daily life situations. The objective of this study was to validate the performance of the proposed measurement method in comparison with that of the optical motion capture (MoCap) system during STS motion. The STS motions of three healthy young adults were simultaneously measured under seven conditions using a chair with embedded sensors and the optical MoCap system. We evaluated the waveform similarity, absolute error, and relationship of the trunk joint angular excursions between these measurement methods. The experimental results indicated high waveform similarity in the trunk flexion phase regardless of STS conditions. Furthermore, a strong relationship was observed between the two measurement methods with respect to the angular excursion of the trunk flexion. Although the angular excursion of the trunk extension exhibited a large error, the developed chair with embedded sensors evaluated trunk flexion during the STS motion, which is a characteristic of frail older adults.

A Novel In Silico Method for Molecular Mimicry Detection Finds a Formin with the Potential to Manipulate the Maize Cell Cytoskeleton.

Molecular mimicry is one of the evolutionary strategies that parasites use to manipulate the host metabolism and perform an effective infection. This phenomenon has been observed in several animal and plant pathosystems. Despite the relevance of this mechanism in pathogenesis, little is known about it in fungus-plant interactions. For that reason, we performed an in silico method to select plausible mimicry candidates for the Ustilago maydis-maize interaction. Our methodology used a tripartite sequence comparison between the parasite, the host, and nonparasitic organisms' genomes. Furthermore, we used RNA sequencing information to identify gene coexpression, and we determined subcellular localization to detect potential cases of colocalization in the imitator-imitated pairs. With these approximations, we found a putative extracellular formin in U. maydis with the potential to rearrange the host cell cytoskeleton. In parallel, we detected at least two maize genes involved in the cytoskeleton rearrangement differentially expressed under U. maydis infection; thus, this find increases the expectation for the potential mimicry role of the fungal protein. The use of several sources of data led us to develop a strict and replicable in silico methodology to detect molecular mimicry in pathosystems with enough information available. Furthermore, this is the first time that a genomewide search has been performed to detect molecular mimicry in a U. maydis-maize system. Additionally, to allow the reproducibility of this experiment and the use of this pipeline, we created a Web server called Molecular Mimicry Finder.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

An automatized workflow from molecular dynamic simulation to quantum chemical methods to identify elementary reactions and compute reaction constants.

We present an automatized workflow which, starting from molecular dynamics simulations, identifies reaction events, filters them, and prepares them for accurate quantum chemical calculations using, for example, Density Functional Theory (DFT) or Coupled Cluster methods. The capabilities of the automatized workflow are demonstrated by the example of simulations for the combustion of some polycyclic aromatic hydrocarbons (PAHs). It is shown how key elementary reaction candidates are filtered out of a much larger set of redundant reactions and refined further. The molecular species in question are optimized using DFT and reaction energies, barrier heights, and reaction rates are calculated. The setup is general enough to include at this stage configurational sampling, which can be exploited in the future. Using the introduced machinery, we investigate how the observed reaction types depend on the gas atmosphere used in the molecular dynamics simulation. For the re-optimization on the DFT level, we show how the additional information needed to switch from reactive force-field to electronic structure calculations can be filled in and study how well ReaxFF and DFT agree with each other and shine light on the perspective of using more accurate semi-empirical methods in the MD simulation.

A large-scale metagenomic study for enzyme profiles using the focused identification of the NGS-based definitive enzyme research (FINDER) strategy.

Excavating the molecular details of many diverse enzymes from metagenomes remains challenging in agriculture, food, health, and environmental fields. We present a versatile method that accelerates metabolic enzyme discovery for highly selective gene capture in metagenomes using next-generation sequencing. Culture-independent enzyme mining of environmental DNA is based on a set of short identifying degenerate sequences specific for a wide range of enzyme superfamilies, followed by multiplexed DNA barcode sequencing. A strategy of 'focused identification of next-generation sequencing-based definitive enzyme research' enabled us to generate targeted enzyme datasets from metagenomes, resulting in minimal hands-on obtention of high-throughput biological diversity and potential function profiles, without being time-consuming. This method also provided a targeted inventory of predicted proteins and molecular features of metabolic activities from several metagenomic samples. We suggest that the efficiency and sensitivity of this method will accelerate the decryption of microbial diversity and the signature of proteins and their metabolism from environmental samples.

Changes in flight paths of large-bodied birds after construction of large terrestrial wind turbines.

The proliferation of ever-larger wind turbines poses risks to wildlife, especially from avian collision, yet avoidance behaviour of large-bodied, long-lived bird species in relation to wind turbines remains little studied away from collision "black spots" and offshore marine environments. Here, three-dimensional flight trajectory data are reported from a laser range-finder study of local movements of large-bodied birds (e.g. swans, geese, gulls, cormorants, raptors and cranes, whose populations are relatively more demographically sensitive to collision mortality) in relation to seven terrestrial 150-222 m high (mean 182 m) wind turbines constructed in Denmark in a N-S line. Comparisons of two-dimensional flight passages between turbines pre- (n = 287) and post-construction (n = 1210) showed significant (P < 0.0001) reductions from 48% to 35% within 150 m of each turbine, with corresponding increase 200-300 m from turbines. Results also showed a significant (P < 0.001) 50% reduction in the percentage of avian passages (from 21% to 10%) through the maximum turbine sweep area after construction and that the proportion of birds that passed between turbines at heights below (0-45 m) and above the turbine sweep area (> 182 m) were significantly greater (P < 0.0001) post-construction than prior to construction. These are the first results from tracking large-bodied bird flight trajectories to show the magnitude of their vertical and horizontal adjustments to the presence of turbines, which have implications for assumptions of even flight densities made by collision risk models currently used to predict avian turbine collision rates.

[Screening and validation of RT-qPCR reference genes of Viola yedoensis under different light intensities].

Screening the reference genes that were stably expressed under different light intensities for Viola yedoensis could provide reference for the related molecular research. In this study, 11 candidate reference genes were detected by RT-qPCR for tissues of V. yedoensis treated with different light intensities. Ge Norm, Norm Finder, Best Keeper, and Ref Finder website were used to comprehensively evaluate the reference genes, and verify the stability of the reference gene based on CAT1. Finally, the ideal reference gene was determined. The results showed that CYP, Actin, and SAMDC had small Ct value ranges and stable expression. Ge Norm demonstrated that CYP, SAMDC, and Actin were suitable reference genes. Norm Finder showed that the expression of α-TUB was the most stable. Best Keeper recommended CYP, Actin, and SAMDC as reference genes. Ref Finder assessed that SAMDC, CYP, α-TUB, and Actin had better stability, while GAPDH had the worst stability. The expression trend of CAT1 gene was consistent when calibrated with SAMDC, CYP, and Actin, while it was quite different from that calibrated with GAPDH. In summary, SAMDC, CYP, and Actin can be used as ideal reference genes for the gene expression profiling of V. yedoensis under different light intensities.

Human-like telomeres in Zostera marina reveal a mode of transition from the plant to the human telomeric sequences.

A previous study describing the genome of Zostera marina, the most widespread seagrass in the Northern hemisphere, revealed some genomic signatures of adaptation to the aquatic environment such as the loss of stomatal genes, while other functions such as an algal-like cell wall composition were acquired. Beyond these, the genome structure and organization were comparable with those of the majority of plant genomes sequenced, except for one striking feature that went unnoticed at that time: the presence of human-like instead of the expected plant-type telomeric sequences. By using different experimental approaches including fluorescence in situ hybridization (FISH), genome skimming by next-generation sequencing (NGS), and analysis of non-coding transcriptome, we have confirmed its telomeric location in the chromosomes of Z. marina. We have also identified its telomerase RNA (TR) subunit, confirming the presence of the human-type telomeric sequence in the template region. Remarkably, this region was found to be very variable even in clades with a highly conserved telomeric sequence across their species. Based on this observation, we propose that alternative annealing preferences in the template borders can explain the transition between the plant and human telomeric sequences. The further identification of paralogues of TR in several plant genomes led us to the hypothesis that plants may retain an increased ability to change their telomeric sequence. We discuss the implications of this occurrence in the evolution of telomeres while introducing a mechanistic model for the transition from the plant to the human telomeric sequences.

The role of human in the loop: lessons from D3R challenge 4.

The rapid development of new machine learning techniques led to significant progress in the area of computer-aided drug design. However, despite the enormous predictive power of new methods, they lack explainability and are often used as black boxes. The most important decisions in drug discovery are still made by human experts who rely on intuitions and simplified representation of the field. We used D3R Grand Challenge 4 to model contributions of human experts during the prediction of the structure of protein-ligand complexes, and prediction of binding affinities for series of ligands in the context of absence or abundance of experimental data. We demonstrated that human decisions have a series of biases: a tendency to focus on easily identifiable protein-ligand interactions such as hydrogen bonds, and neglect for a more distributed and complex electrostatic interactions and solvation effects. While these biases still allow human experts to compete with blind algorithms in some areas, the underutilization of the information leads to significantly worse performance in data-rich tasks such as binding affinity prediction.

Two novel truncating variants of the AAAS gene causative of the triple A syndrome.

PURPOSE: The triple A syndrome (AAAS) is an inherited condition associated with mutations in the AAAS gene, which encodes a protein of 546 amino acids known as ALADIN (alacrima achalasia adrenal insufficiency neurologic disorder) whose function is not well understood. This protein belongs to the WD-repeat family of regulatory proteins and is located in the nuclear pore complexes. Only a few cohorts of AAAS patients have been reported and fully characterized. Thus, the objective of the present study was to report on a mini cohort of Italian AAAS patients and to get insights on their predisposing genetic defects. METHODS: Genetic analysis of AAAS gene in triple A syndrome patient and molecular and functional characterization of the novel identified allelic variants. RESULTS: Here we describe three newly diagnosed cases of AAAS, in whom genetic analysis allowed us to identify two novel allelic variants in the AAAS gene: the frameshift substitution c.765 dupT (p.Gly256Trp fsX67) in exon 8 and the splice site mutation in intron 11(c.997-2 A > G, IVS11-2A > G). Both variants result in a truncated non-functional protein, as we demonstrate by transcript analysis and expression studies. CONCLUSIONS: Our findings establish a pathogenic role for both new variants. Moreover, our data highlight the essential role of the C-terminal domain of the protein for its correct targeting and function and underline the importance of sequencing splice sites surrounding the intron-exon junctions to ensure accurate molecular diagnosis and correct genetic counseling in AAAS patients.

Validation of the Clouclip and utility in measuring viewing distance in adults.

PURPOSE: To validate the Clouclip, a continuously measuring objective rangefinder, and examine viewing behaviours during various near tasks in non-myopic and myopic adults. METHODS: In experiment 1, five Clouclip devices were utilised. An infrared camera was used to visualise and measure infrared beam size and angle. Repeatability for distance tracking was assessed from 5 to 120 cm in 5 cm increments. Accuracy of distance tracking was investigated for paper and iPad targets, spatial integration was calculated, effects of target tilt were determined and light measurements were compared to a lux meter. In experiment 2, viewing behaviour was assessed in 41 subjects (21 non-myopic, 20 myopic) during four 15-min near tasks; (1) passive reading of printed material, (2) active writing on printed material, (3) passive viewing on an electronic device and (4) active engagement on an electronic device. Working distance was compared between tasks and refractive error groups. RESULTS: Clouclip distance tracking showed good repeatability, with a mean difference of 0.34 cm and limits of agreement of ±2.0 cm. Clouclip-measured and actual distances were highly correlated for paper and electronic targets from 5 to 120 cm, with mean differences and limits of agreement of 3.96 ± 13.78 cm and 4.48 ± 8.92 cm, respectively; variability increased for distances >100 cm. Tracking ability increased with larger target sizes; tracking was accurate when the target occupied 1.5%-20.3% of tracking beam area, depending on distance and with target tilt up to ±60 degrees. Clouclip- and lux meter-measured ambient illumination were highly correlated for a wide range of intensities (r = 0.96, p < 0.001), but with greater variability for intensities >20 000 lux. The Clouclip infrared beam was measured to have a diameter of 25.6 ± 2.2° and a downward angle of 10.3 ± 0.5°. For subject testing, viewing distance was significantly closer for active and passive printed tasks (29.5 ± 6.7 cm and 33.2 ± 8.8 cm, respectively) than for active and passive electronic tasks (35.4 ± 8.0 cm and 40.8 ± 10.4 cm, respectively), with no differences between refractive error groups (p = 0.88). CONCLUSIONS: The Clouclip performed well in measuring near and intermediate distances and could distinguish between indoor (<1000 lux) and outdoor (>1000 lux) illumination. A closer working distance was observed for printed tasks compared to those on an iPad, with no difference in viewing distance between non-myopic and myopic adults.

Autonomous Road Roundabout Detection and Navigation System for Smart Vehicles and Cities Using Laser Simulator-Fuzzy Logic Algorithms and Sensor Fusion.

A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator-fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. A wheeled mobile robot (WMR) is supposed to navigate autonomously on the road in real-time and reach a predefined goal while discovering and detecting the road roundabout. A complete modeling and path planning of the road's roundabout intersection was derived to enable the WMR to navigate autonomously in indoor and outdoor terrains. A new algorithm, called Laser Simulator, has been introduced to detect various entities in a road roundabout setting, which is later integrated with fuzzy logic algorithm for making the right decision about the existence of the roundabout. The sensor fusion process involving the use of a Wi-Fi camera, laser range finder, and odometry was implemented to generate the robot's path planning and localization within the road environment. The local maps were built using the extracted data from the camera and laser range finder to estimate the road parameters such as road width, side curbs, and roundabout center, all in two-dimensional space. The path generation algorithm was fully derived within the local maps and tested with a WMR platform in real-time.

Balancing contest competition, scramble competition, and social tolerance at feeding sites in wild common marmosets (Callithrix jacchus).

Models of primate sociality focus on the costs and benefits of group living and how factors such as rank, feeding competition, alliance formation, and cooperative behavior shape within-group social relationships. We conducted a series of controlled field experiments designed to investigate how resource distribution (one or three of four reward platforms) and amount of food on a reward platform affected foraging strategies and individual feeding success in four groups of wild common marmosets (Callithrix jacchus) living in the Caatinga of northeastern Brazil. At our field site, common marmoset groups are characterized by a single breeding female who can produce twin litters twice per year, strong social cohesion, and cooperative infant care provided principally by several adult male helpers. We found that except for the dominant breeding female, rank (based on aggression) was not a strong predictor of feeding success. Although the breeding female in each group occupied the highest rank position and obtained the greatest daily feeding success, all other group members, including adults and juveniles experienced relatively equal feeding success across most experimental conditions. This was accomplished using a balance of behavioral strategies related to contest competition, scramble competition (associated with a finder's advantage), and social tolerance (sharing the same feeding platform). Based on these results, the social structure of common marmosets is best described as "single female dominance," with the breeding female maximizing food intake needed to offset the energetic costs associated with reproductive twinning and the ability to produce two litters per year. Cooperative infant caregiving, in which the number of helpers is positively correlated with offspring survivorship, requires a set of behavioral strategies that serve to reduce contest competition and promote prosocial behaviors at feeding sites.

Vein Pattern Locating Technology for Cannulation: A Review of the Low-Cost Vein Finder Prototypes Utilizing near Infrared (NIR) Light to Improve Peripheral Subcutaneous Vein Selection for Phlebotomy.

One of the most common means for diagnosis is through medical laboratory testing, which primarily uses venous blood as a sample. This requires an invasive method by cannulation that needs proper vein selection. The use of a vein finder would help the phlebotomist to easily locate the vein, preventing possible pre-analytical error in the specimen collection and even more discomfort and pain to the patient. This paper is a review of the scientific publications on the different developed low-cost vein finder prototypes utilizing camera assisted near infrared (NIR) light technology. Methods: Electronic databases were searched online, these included PubMed (PMC), MEDLINE, Science Direct, ResearchGate, and Institute of Electrical and Electronics Engineers (IEEE) Xplore digital library. Specifically, publications with the terms vein finder prototype, NIR technology, vein detection, and infrared imaging were screened. In addition, reference lists were used to further review related publications. Results: Cannulation challenges medical practitioners because of the different factors that can be reduced by the utilization of a vein finder. A limited number of publications regarding the assessment of personnel performing cannulation were observed. Moreover, variations in methodology, number of patients, type of patients according to their demographics and materials used in the assessment of the developed prototypes were noted. Some studies were limited with regard to the actual human testing of the prototype. Conclusions: The development of a low-cost effective near infrared (NIR) vein finder remains in the phase of improvement. Since, it is being challenged by different human factors, increasing the number of parameters and participants/human for actual testing of the prototypes must also be taken into consideration for possible commercialization. Finally, it was noted that publications regarding the assessment of the performance of phlebotomists using vein finders were limited.

A Robust Indoor Localization System Integrating Visual Localization Aided by CNN-Based Image Retrieval with Monte Carlo Localization.

This paper proposes a novel multi-sensor-based indoor global localization system integrating visual localization aided by CNN-based image retrieval with a probabilistic localization approach. The global localization system consists of three parts: coarse place recognition, fine localization and re-localization from kidnapping. Coarse place recognition exploits a monocular camera to realize the initial localization based on image retrieval, in which off-the-shelf features extracted from a pre-trained Convolutional Neural Network (CNN) are adopted to determine the candidate locations of the robot. In the fine localization, a laser range finder is equipped to estimate the accurate pose of a mobile robot by means of an adaptive Monte Carlo localization, in which the candidate locations obtained by image retrieval are considered as seeds for initial random sampling. Additionally, to address the problem of robot kidnapping, we present a closed-loop localization mechanism to monitor the state of the robot in real time and make adaptive adjustments when the robot is kidnapped. The closed-loop mechanism effectively exploits the correlation of image sequences to realize the re-localization based on Long-Short Term Memory (LSTM) network. Extensive experiments were conducted and the results indicate that the proposed method not only exhibits great improvement on accuracy and speed, but also can recover from localization failures compared to two conventional localization methods.

Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques.

BAL31-NGS approach for identification of telomeres de novo in large genomes.

This article describes a novel method to identify as yet undiscovered telomere sequences, which combines next generation sequencing (NGS) with BAL31 digestion of high molecular weight DNA. The method was applied to two groups of plants: i) dicots, genus Cestrum, and ii) monocots, Allium species (e.g. A. ursinum and A. cepa). Both groups consist of species with large genomes (tens of Gb) and a low number of chromosomes (2n=14-16), full of repeat elements. Both genera lack typical telomeric repeats and multiple studies have attempted to characterize alternative telomeric sequences. However, despite interesting hypotheses and suggestions of alternative candidate telomeres (retrotransposons, rDNA, satellite repeats) these studies have not resolved the question. In a novel approach based on the two most general features of eukaryotic telomeres, their repetitive character and sensitivity to BAL31 nuclease digestion, we have taken advantage of the capacity and current affordability of NGS in combination with the robustness of classical BAL31 nuclease digestion of chromosomal termini. While representative samples of most repeat elements were ensured by low-coverage (less than 5%) genomic shot-gun NGS, candidate telomeres were identified as under-represented sequences in BAL31-treated samples.

Imaging flow cytometry analysis of intracellular pathogens.

Imaging flow cytometry has been applied to address questions in infection biology, in particular, infections induced by intracellular pathogens. This methodology, which utilizes specialized analytic software makes it possible to analyze hundreds of quantified features for hundreds of thousands of individual cellular or subcellular events in a single experiment. Imaging flow cytometry analysis of host cell-pathogen interaction can thus quantitatively addresses a variety of biological questions related to intracellular infection, including cell counting, internalization score, and subcellular patterns of co-localization. Here, we provide an overview of recent achievements in the use of fluorescently labeled prokaryotic or eukaryotic pathogens in human cellular infections in analysis of host-pathogen interactions. Specifically, we give examples of Imagestream-based analysis of cell lines infected with Toxoplasma gondii or Mycobacterium tuberculosis. Furthermore, we illustrate the capabilities of imaging flow cytometry using a combination of standard IDEAS™ software and the more recently developed Feature Finder algorithm, which is capable of identifying statistically significant differences between researcher-defined image galleries. We argue that the combination of imaging flow cytometry with these software platforms provides a powerful new approach to understanding host control of intracellular pathogens.