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The Roman Empire expanded through the Mediterranean shores and brought human mobility and cosmopolitanism across this inland sea to an unprecedented scale. However, if this was also common at the Empire frontiers remains undetermined. The Balkans and Danube River were of strategic importance for the Romans acting as an East-West connection and as a defense line against “barbarian” tribes. We generated genome-wide data from 70 ancient individuals from present-day Serbia dated to the first millennium CE; including Viminacium, capital of Moesia Superior province. Our analyses reveal large scale-movements from Anatolia during Imperial rule, similar to the pattern observed in Rome, and cases of individual mobility from as far as East Africa. Between ∼250-500 CE, we detect gene-flow from Central/Northern Europe harboring admixtures of Iron Age steppe groups. Tenth-century CE individuals harbored North-Eastern European-related ancestry likely associated to Slavic-speakers, which contributed >20% of the ancestry of today’s Balkan people.

High throughput image cytometers analyze individual cells in digital photomicrographs by first assigning pixels within each image to plasma membrane, cytoplasm, nucleus, or other regions. In this study, we report on a novel algorithm that: 1) identifies plasma membrane regions to measure changes in plasma membrane-associated proteins (protein kinase C [PKC] alpha, N-cadherin, E-cadherin, vascular endothelium [VE]-cadherin, and pan-cadherin) that regulate cell division, migration, and adhesion and 2) delineates the cell for generalized three-compartment image cytometry. Validation assays were performed for these proteins on cells cultured in 96-well plates and also for tissue sections obtained from transgenic and chemical carcinogenic models of skin cancer. The algorithm successfully quantified phorbol 12-myristate 13-acetate (PMA)-induced plasma membrane localization of PKCalpha in HeLa cells (Z' of 0.88). Additionally, PMA activated translocation to the plasma membrane at P.01 of N-cadherin (in HeLa cells), E-cadherin (in A431 cells), and VE-cadherin (in human dermal microvascular endothelial cells), suggesting a relationship between PKCalpha activity and cadherin localization. For VE-cadherin, a Z' of 0.52 was obtained between serum-free medium, which increased VE-cadherin, and EGTA, which diminished VE-cadherin at the plasma membrane. For sections obtained from the transgenic skin cancer model, analysis of images with the plasma membrane algorithm revealed that tumor cells exhibited cadherin expression that was just 34% of that expressed by surrounding normal tissue; furthermore, tumor cells expressed elevated DNA content, consistent with development of aneuploidy. In contrast, increased DNA content did not occur for tumor cells produced by chemical carcinogenesis. The results demonstrate that this new algorithm for plasma membrane image cytometry enables statistically significant analyses in a variety of applications in both cultured cells and tissue sections.

This report describes statistical validation methods implemented on assay data for inhibition of subcellular redistribution of nuclear factor kappaB (NF kappaB) in HeLa cells. We quantified cellular inhibition of cytoplasmic-nuclear translocation of NF kappaB in response to a range of concentrations of interleukin-1 (IL-1) receptor antagonist in the presence of IL-1alpha using eight replicate rows in each four 96-well plates scanned five times on each of 2 days. Translocation was measured as the fractional localized intensity of the nucleus (FLIN), an implementation of our more general fractional localized intensity of the compartments (FLIC), which analyzes whole compartments in the context of the entire cell. The NF kappaB antagonist assay (inhibition of IL-1- induced NF kappaB translocation) data were collected on a Q3DM (San Diego, CA) EIDAQtrade mark 100 high throughput microscopy system. [In 2003, Q3DM was purchased by Beckman Coulter Inc. (Fullerton, CA), which released the IC 100 successor to the EIDAQ 100.] The generalized FLIC method is described along with two-point (minimum-maximum) and multiple point titration statistical methods. As a ratio of compartment intensities that tend to change proportionally, FLIN was resistant to photobleaching errors. Two-point minimum-maximum statistical analyses yielded the following: a Z' of 0.174 with the data as n = 320 independent well samples; Z' by row data in a range of 0.393-0.933, with a mean of 0.766; by-plate Z' data of 0.310, 0.443, 0.545, and 0.794; and by-plate means of columns Z' data of 0.879, 0.927, 0.945, and 0.963. The mean 50% inhibitory concentration (IC50) for IL-1 receptor antagonist over all experiments was 213 ng/ml. The combined IC50 coefficients of variation (CVs) were 0.74%, 0.85%, 2.09%, and 2.52% for the four plates. Repeatability IC50 CVs were as follows: day to day 3.0%, row to row 8.0%, plate to plate 2.8%, and day to day 0.6%. The number of cells required for statistically resolvable differences in dose concentrations, plotted in a family of FLIN sigma/deltamicro (SD/range) curves and tabulated, demonstrated cell-by-cell assay precision with our combined sigma/deltamicro = 0.32 that required approximately 10-fold fewer cells than in a previously reported NF kappaB assay with sigma/deltamicro = 1.52. To better understand the relationship between cell-by-cell measurements and IC50 precision, 500 Monte Carlo simulations with varying cell-measurement SDs were used to explore three-, five-, seven-, and 11-point model titrations. The reductions in deltaIC50 90% confidence intervals from 11- to three-point titrations were 10-fold with the previously reported sigma/deltamicro = 1.52 and twofold with our sigma/deltamicro = 0.32. With these normalized parameters, this report provides a common statistical foundation, independent of the assay details, for evaluating the performance of imaging data on any instrument.

We present an integrated system for automatic acquisition of the human body model and motion tracking using input from multiple synchronized video streams. The video frames are segmented and the 3D voxel reconstructions of the human body shape in each frame are computed from the foreground silhouettes. These reconstructions are then used as input to the model acquisition and tracking algorithms. The human body model consists of ellipsoids and cylinders and is described using the twists framework resulting in a non-redundant set of model parameters. Model acquisition starts with a simple body part localization procedure based on template fitting and growing, which uses prior knowledge of average body part shapes and dimensions. The initial model is then refined using a Bayesian network that imposes human body proportions onto the body part size estimates. The tracker is an extended Kalman filter that estimates model parameters based on the measurements made on the labeled voxel data. A voxel labeling procedure that handles large frame-to-frame displacements was designed resulting in very robust tracking performance. Extensive evaluation shows that the system performs very reliably on sequences that include different types of motion such as walking, sitting, dancing, running and jumping and people of very different body sizes, from a nine year old girl to a tall adult male.

This paper presents a method for segmentation and tracking of cardiac structures in ultrasound image sequences. The developed algorithm is based on the active contour framework. This approach requires initial placement of the contour close to the desired position in the image, usually an object outline. Best contour shape and position are then calculated, assuming that at this configuration a global energy function, associated with a contour, attains its minimum. Active contours can be used for tracking by selecting a solution from a previous frame as an initial position in a present frame. Such an approach, however, fails for large displacements of the object of interest. This paper presents a technique that incorporates the information on pixel velocities (optical flow) into the estimate of initial contour to enable tracking of fast-moving objects. The algorithm was tested on several ultrasound image sequences, each covering one complete cardiac cycle. The contour successfully tracked boundaries of mitral valve leaflets, aortic root and endocardial borders of the left ventricle. The algorithm-generated outlines were compared against manual tracings by expert physicians. The automated method resulted in contours that were within the boundaries of intraobserver variability.

Sole reliance on one drug, Praziquantel, for treatment and control of schistosomiasis raises concerns about development of widespread resistance, prompting renewed interest in the discovery of new anthelmintics. To discover new leads we designed an automated label-free, high content-based, high throughput screen (HTS) to assess drug-induced effects on in vitro cultured larvae (schistosomula) using bright-field imaging. Automatic image analysis and Bayesian prediction models define morphological damage, hit/non-hit prediction and larval phenotype characterization. Motility was also assessed from time-lapse images. In screening a 10,041 compound library the HTS correctly detected 99.8% of the hits scored visually. A proportion of these larval hits were also active in an adult worm ex-vivo screen and are the subject of ongoing studies. The method allows, for the first time, screening of large compound collections against schistosomes and the methods are adaptable to other whole organism and cell-based screening by morphology and motility phenotyping., Author Summary Schistosomiasis is a severe helminth infection affecting an estimated 600 million people. The one drug widely available, praziquantel (PZQ), is not ideal. PZQ kills the adult worms but not the developing juveniles so the treated patient may not be cured long-term. In addition, use of repeated mass treatment campaigns with PZQ to control morbidity raises concerns about the development of drug resistance. Our work is aimed at providing starting points for drug discovery programs for schistosomiasis by screening large compound libraries against whole organisms. Praziquantel and several other known anti-schistosomal drugs are also active in vitro against the adult worms and the larval stages, schistosomula. The latter are ideal for novel drug screening as they can be produced in large numbers in vitro, are small and so are amenable to screening in microwell plates. Drug activity can be assessed visually but this is subjective and laborious. We have built an automated system for assessing drug action involving the collection of images of the larvae and the development of computer algorithms to analyze their morphology and motility, defining them as "hits" or "nonhits." The method is reliable, consistent and efficient, making it feasible, for the first time, to screen large compound collections.

Estrogen receptor-α (ER) is an important target both for therapeutic compounds and endocrine disrupting chemicals (EDCs); however, the mechanisms involved in chemical modulation of regulating ER transcriptional activity are inadequately understood. Here, we report the development of a high content analysis-based assay to describe ER activity that uniquely exploits a microscopically visible multi-copy integration of an ER-regulated promoter. Through automated single-cell analyses, we simultaneously quantified promoter occupancy, recruitment of transcriptional cofactors and large-scale chromatin changes in response to a panel of ER ligands and EDCs. Image-derived multi-parametric data was used to classify a panel of ligand responses at high resolution. We propose this system as a novel technology providing new mechanistic insights into EDC activities in a manner useful for both basic mechanistic studies and drug testing.

Intracellular lipid droplets are associated with a myriad of afflictions including obesity, fatty liver disease, coronary artery disease, and infectious diseases (eg, HCV and tuberculosis). To develop high-content analysis (HCA) techniques to analyze lipid droplets and associated proteins, primary human preadipocytes were plated in 96-well dishes in the presence of rosiglitazone (rosi), a PPAR-(c) agonist that promotes adipogenesis. The cells were then labeled for nuclei, lipid droplets, and proteins such as perilipin, protein kinase C (PKC), and hormone-sensitive lipase (HSL). The cells were imaged via automated digital microscopy and algorithms were developed to quantify lipid droplet (Lipid Droplet algorithm) and protein expression and colocalization (Colocalization algorithm). The algorithms, which were incorporated into Vala Science Inc's CyteSeer((R)) image cytometry program, quantified the rosi-induced increases in lipid droplet number, size, and intensity, and the expression of perilipin with exceptional consistency (Z' values of 0.54-0.71). Regarding colocalization with lipid droplets, Pearson's correlation coefficients of 0.38 (highly colocalized), 0.16 (moderate), and -0.0010 (random) were found for perilipin, PKC, and HSL, respectively. For hepatocytes (AML12, HuH-7, and primary cells), the algorithms also quantified the stimulatory and inhibitory effect of oleic acid and triacsin C on lipid droplets (Z's0.50) and ADFP expression/colocalization. Oleic acid-induced lipid droplets in HeLa cells and macrophages (THP-1) were also well quantified. The results suggest that HCA techniques can be utilized to quantify lipid droplets and associated proteins in many cell models relevant to a variety of diseases.

Using manual and automated high throughput microscopy (HTM), ligand-dependent trafficking of green fluorescent protein-androgen receptor (GFP-AR) was analyzed in fixed and living cells to determine its spatial distribution, solubility, mobility, and co-activator interactions. Within minutes, addition of the agonist R1881 resulted translocation of GFP-AR from the cytoplasm to the nucleus, where it displayed a hyperspeckled pattern and extraction resistance in low expressing cells. AR antagonists (Casodex, hydroxyflutamide) also caused nuclear translocation, however, the antagonist-bound GFP-AR had a more diffuse nuclear distribution, distinct from the agonist-bound GFP-AR, and was completely soluble; overexpressed GFP-AR in treated cells was extraction resistant, independent of ligand type. To more dramatically show the different effects of ligand on AR distribution, we utilized an AR with a mutation in the DNA binding domain (ARC619Y) that forms distinct foci upon exposure to agonists but retains a diffuse nuclear distribution in the presence of antagonists. Live-cell imaging of this mutant demonstrated that cytoplasmic foci formation occurs immediately upon agonist but not antagonist addition. Fluorescence recovery after photobleaching (FRAP) revealed that agonist-bound GFP-AR exhibited reduced mobility relative to unliganded or antagonist-bound GFP-AR. Importantly, agonist-bound GFP-AR mobility was strongly affected by protein expression levels in transiently transfected cells, and displayed reduced mobility even in slightly overexpressing cells. Cyan fluorescent protein-AR (CFP-AR) and yellow fluorescent protein-CREB binding protein (YFP-CBP) in the presence of agonists and antagonists were used to demonstrate that CFP-AR specifically co-localizes with YFP-CBP in an agonist dependent manner. Dual FRAP experiments demonstrated that CBP mobility mirrored AR mobility only in the presence of agonist. HTM enabled simultaneous studies of the sub-cellular distribution of GFP-AR and ARC619Y in response to a range of concentrations of agonists and antagonists (ranging from 10−12 to 10−5) in thousands of cells. These results further support the notion that ligand specific interactions rapidly affect receptor and co-factor organization, solubility, and molecular dynamics, and each can be aberrantly affected by mutation and overexpression. J. Cell. Biochem. 98: 770–788, 2006. © 2006 Wiley-Liss, Inc.

The addition of a lipid moiety to a protein increases its hydrophobicity and subsequently its attraction to lipophilic environments like membranes. Indeed most lipid‐modified proteins are localized to membranes where they associate with multiprotein signaling complexes. Acylation and prenylation are the two common categories of lipidation. The enzymology and pharmacology of prenylation are well understood but relatively very little is known about palmitoylation, the most common form of acylation. One distinguishing characteristic of palmitoylation is that it is a dynamic modification. To understand more about how palmitoylation is regulated, we fused palmitoylation substrates to fluorescent proteins and reported their subcellular distribution and trafficking. We used automated high‐throughput fluorescence microscopy and a specialized computer algorithm to image and measure the fraction of palmitoylation reporter on the plasma membrane versus the cytoplasm. Using this system we determined the residence half‐life of palmitate on the dipalmitoyl substrate peptide from GAP43 as well as the EC50 for 2‐bromopalmitate, a common inhibitor of palmitoylation.

Intelligent environments can be viewed as systems where humans and machines (rooms) collaborate. Intelligent (or smart) environments need to extract and maintain an awareness of a wide range of events and human activities occurring in these spaces. This requirement is crucial for supporting efficient and effective interactions among humans as well as humans and intelligent spaces. Visual information plays an important role for developing accurate and useful representation of the static and dynamic states of an intelligent environment. Accurate and efficient capture, analysis, and summarization of the dynamic context requires the vision system to work at multiple levels of semantic abstractions in a robust manner. In this paper, we present details of a long-term and ongoing research project, where indoor intelligent spaces endowed with a range of useful functionalities are designed, built, and systematically evaluated. Some of the key functionalities include: intruder detection; multiple person tracking; body pose and posture analysis; person identification; human body modeling and movement analysis; and for integrated systems for intelligent meeting rooms, teleconferencing, or performance spaces. The paper includes an overall system architecture to support design and development of intelligent environments. Details of panoramic (omnidirectional) video camera arrays, calibration, video stream synchronization, and real-time capture/processing are discussed. Modules for multicamera-based multiperson tracking, event detection and event based servoing for selective attention, voxelization, streaming face recognition, are also discussed. The paper includes experimental studies to systematically evaluate performance of individual video analysis modules as well as to evaluate basic feasibility of an integrated system for dynamic context capture and event based servoing, and semantic information summarization.

Moving shadows need careful consideration in the development of robust dynamic scene analysis systems. Moving shadow detection is critical for accurate object detection in video streams since shadow points are often misclassified as object points, causing errors in segmentation and tracking. Many algorithms have been proposed in the literature that deal with shadows. However, a comparative evaluation of the existing approaches is still lacking. In this paper, we present a comprehensive survey of moving shadow detection approaches. We organize contributions reported in the literature in four classes two of them are statistical and two are deterministic. We also present a comparative empirical evaluation of representative algorithms selected from these four classes. Novel quantitative (detection and discrimination rate) and qualitative metrics (scene and object independence, flexibility to shadow situations, and robustness to noise) are proposed to evaluate these classes of algorithms on a benchmark suite of indoor and outdoor video sequences. These video sequences and associated "ground-truth" data are made available at http://cvrr.ucsd.edu/aton/shadow to allow for others in the community to experiment with new algorithms and metrics.

Knowledge of tricuspid annular shape, size and motion is critical for surgical repair of the tricuspid valve. However these characteristics for the valve are poorly understood. The authors reconstructed the three dimensional shape and motion of the tricuspid annulus in 2 normals and 2 patients who underwent tricuspid valve repair using a flexible annuloplasty ring. The data were acquired with EKG and respiratory gating. The algorithm allows for quantitative analysis of annular area and excursion over a cardiac cycle. The preliminary results show that the shape and motion of tricuspid annulus is preserved by the flexible tricuspid valve annuloplasty ring.

We present an algorithm for segmentation of traffic scenes that distinguishes moving objects from their moving cast shadows. A fading memory estimator calculates mean and variance of all three color components for each background pixel. Given the statistics for a background pixel, simple rules for calculating its statistics when covered by a shadow are used. Then, MAP classification decisions are made for each pixel. In addition to the color features, we examine the use of neighborhood information to produce smoother classification. We also propose the use of temporal information by modifying class a priori probabilities based on predictions from the previous frame.

Intelligent environments provide challenging research problems for natural and efficient interfaces between humans and computers as well as between humans. We present a multimodal sensory intelligent system testbed based on some general requirements for developing intelligent environments. We also present rigorous experimental investigations on the processing and control modules for the active camera networks and the microphone array which are embedded in the intelligent room. An integrated intelligent system is developed utilizing four basic modules for visual and audio processing. The integrated system has the functionality of human tracking, active camera control, face recognition and speaker recognition. This system is demonstrated to be suitable for teleconferencing type of applications.

We describe a novel architecture for developing distributed video networks for incident detection and management. The networks utilize both rectilinear and omnidirectional cameras. It is recognized that robust and reliable segmentation of automobiles and shadows is critical in our application. We describe new segmentation procedure and present experimental results to support the basic feasibility and utility of the algorithms.

Robustness to changes in illumination conditions as well as viewing perspectives is an important requirement for many computer vision applications. One of the key factors in enhancing the robustness of dynamic scene analysis is that of accurate and reliable means for shadow detection. Shadow detection is critical for correct object detection in image sequences. Many algorithms have been proposed in the literature that deal with shadows. However, a comparative evaluation of the existing approaches is still lacking. In this paper, the full range of problems underlying the shadow detection is identified and discussed. We classify the proposed solutions to this problem using a taxonomy of four main classes, deterministic model and non-model based, and statistical parametric and nonparametric. Novel quantitative (detection and discrimination accuracy) and qualitative metrics (scene and object independence, flexibility to shadow situations and robustness to noise) are proposed to evaluate these classes of algorithms on a benchmark suite of indoor and outdoor video sequences.

Shadow detection is critical for robust and reliable vision-based systems for traffic flow analysis. In this paper we discuss various shadow detection approaches and compare two critically. The goal of these algorithms is to prevent moving shadows being misclassified as moving objects (or parts of them), thus avoiding the merging of two or more objects into one and improving the accuracy of object localization. The environment considered is an outdoor highway scene with multiple lanes observed by a single fixed camera. The important features of shadow detection algorithms and the parameter set-up are analyzed and discussed. A critical evaluation of the results both in terms of accuracy and in terms of computational complexity are outlined. Finally, possible integration of the two approaches into a robust shadow detector is presented as future direction of our research.