A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder

Importance

Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified.

Objective

To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD.

Design, Setting, and Participants

This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023.

Exposure

Patients with MDD and healthy controls.

Main Outcome and Measure

Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression.

Results

Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups.

Conclusion and Relevance

Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.

Trail using ants follow idiosyncratic routes in complex landscapes

A large volume of research on individually navigating ants has shown how path integration and visually guided navigation form a major part of the ant navigation toolkit for many species and are sufficient mechanisms for successful navigation. One of the behavioural markers of the interaction of these mechanisms is that experienced foragers develop idiosyncratic routes that require that individual ants have personal and unique visual memories that they use to guide habitual routes between the nest and feeding sites. The majority of ants, however, inhabit complex cluttered environments and social pheromone trails are often part of the collective recruitment, organisation and navigation of these foragers. We do not know how individual navigation interacts with collective behaviour along shared trails in complex natural environments. We thus asked here if wood ants that forage through densely cluttered woodlands where they travel along shared trails repeatedly follow the same routes or if they choose a spread of paths within the shared trail. We recorded three long homing trajectories of 20 individual wood ants in their natural woodland habitat. We found that wood ants follow idiosyncratic routes when navigating along shared trails through highly complex visual landscapes. This shows that ants rely on individual memories for habitual route guidance even in cluttered environments when chemical trail information is available. We argue that visual cues are likely to be the dominant sensory modality for the idiosyncratic routes. These experiments shed new light on how ants, or insects in general, navigate through complex multimodal environments.

Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction

Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising therapeutic approach. Yet, fundamental questions concerning anti-angiogenic therapy remain unanswered, partly due to the scale and resolution gap between microscopy and clinical imaging and a lack of quantitative data readouts. To what extend does treatment lead to vessel regression or vessel normalization and does it ameliorate or aggravate hypoxia? Clearly, a better understanding of the underlying mechanisms would greatly benefit the development of desperately needed improved treatment regimens. Here, using orthotopic transplantation of Gli36 cells, a widely used murine glioma model, we present a mesoscopic approach based on light sheet fluorescence microscopic imaging of wholemount stained tumors. Deep learning-based segmentation followed by automated feature extraction allowed quantitative analyses of the entire tumor vasculature and oxygenation statuses. Unexpectedly in this model, the response to both cytotoxic and anti-angiogenic therapy was dominated by vessel normalization with little evidence for vessel regression. Equally surprising, only cytotoxic therapy resulted in a significant alleviation of hypoxia. Taken together, we provide and evaluate a quantitative workflow that addresses some of the most urgent mechanistic questions in anti-angiogenic therapy.

Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears

ABSTRACT

The detection of genetic aberrations is crucial for early therapy decisions in acute myeloid leukemia (AML) and recommended for all patients. Because genetic testing is expensive and time consuming, a need remains for cost-effective, fast, and broadly accessible tests to predict these aberrations in this aggressive malignancy. Here, we developed a novel fully automated end-to-end deep learning pipeline to predict genetic aberrations directly from single-cell images from scans of conventionally stained bone marrow smears already on the day of diagnosis. We used this pipeline to compile a multiterabyte data set of >2 000 000 single-cell images from diagnostic samples of 408 patients with AML. These images were then used to train convolutional neural networks for the prediction of various therapy-relevant genetic alterations. Moreover, we created a temporal test cohort data set of >444 000 single-cell images from further 71 patients with AML. We show that the models from our pipeline can significantly predict these subgroups with high areas under the curve of the receiver operating characteristic. Potential genotype-phenotype links were visualized with 2 different strategies. Our pipeline holds the potential to be used as a fast and inexpensive automated tool to screen patients with AML for therapy-relevant genetic aberrations directly from routine, conventionally stained bone marrow smears already on the day of diagnosis. It also creates a foundation to develop similar approaches for other bone marrow disorders in the future.

Human fertilization in vivo and in vitro requires the CatSper channel to initiate sperm hyperactivation

The infertility of many couples rests on an enigmatic dysfunction of the man's sperm. To gain insight into the underlying pathomechanisms, we assessed the function of the sperm-specific multisubunit CatSper-channel complex in the sperm of almost 2,300 men undergoing a fertility workup, using a simple motility-based test. We identified a group of men with normal semen parameters but defective CatSper function. These men or couples failed to conceive naturally and upon medically assisted reproduction via intrauterine insemination and in vitro fertilization. Intracytoplasmic sperm injection (ICSI) was, ultimately, required to conceive a child. We revealed that the defective CatSper function was caused by variations in CATSPER genes. Moreover, we unveiled that CatSper-deficient human sperm were unable to undergo hyperactive motility and, therefore, failed to penetrate the egg coat. Thus, our study provides the experimental evidence that sperm hyperactivation is required for human fertilization, explaining the infertility of CatSper-deficient men and the need of ICSI for medically assisted reproduction. Finally, our study also revealed that defective CatSper function and ensuing failure to hyperactivate represents the most common cause of unexplained male infertility known thus far and that this sperm channelopathy can readily be diagnosed, enabling future evidence-based treatment of affected couples.

Event-driven adaptive optical neural network

We present an adaptive optical neural network based on a large-scale event-driven architecture. In addition to changing the synaptic weights (synaptic plasticity), the optical neural network's structure can also be reconfigured enabling various functionalities (structural plasticity). Key building blocks are wavelength-addressable artificial neurons with embedded phase-change materials that implement nonlinear activation functions and nonvolatile memory. Using multimode focusing, the activation function features both excitatory and inhibitory responses and shows a reversible switching contrast of 3.2 decibels. We train the neural network to distinguish between English and German text samples via an evolutionary algorithm. We investigate both the synaptic and structural plasticity during the training process. On the basis of this concept, we realize a large-scale network consisting of 736 subnetworks with 16 phase-change material neurons each. Overall, 8398 neurons are functional, highlighting the scalability of the photonic architecture.

An overview and a roadmap for artificial intelligence in hematology and oncology

BACKGROUND

Artificial intelligence (AI) is influencing our society on many levels and has broad implications for the future practice of hematology and oncology. However, for many medical professionals and researchers, it often remains unclear what AI can and cannot do, and what are promising areas for a sensible application of AI in hematology and oncology. Finally, the limits and perils of using AI in oncology are not obvious to many healthcare professionals.

METHODS

In this article, we provide an expert-based consensus statement by the joint Working Group on "Artificial Intelligence in Hematology and Oncology" by the German Society of Hematology and Oncology (DGHO), the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), and the Special Interest Group Digital Health of the German Informatics Society (GI). We provide a conceptual framework for AI in hematology and oncology.

RESULTS

First, we propose a technological definition, which we deliberately set in a narrow frame to mainly include the technical developments of the last ten years. Second, we present a taxonomy of clinically relevant AI systems, structured according to the type of clinical data they are used to analyze. Third, we show an overview of potential applications, including clinical, research, and educational environments with a focus on hematology and oncology.

CONCLUSION

Thus, this article provides a point of reference for hematologists and oncologists, and at the same time sets forth a framework for the further development and clinical deployment of AI in hematology and oncology in the future.

Inverse design of nanophotonic devices using dynamic binarization

The complexity of applications addressed with photonic integrated circuits is steadily rising and poses increasingly challenging demands on individual component functionality, performance and footprint. Inverse design methods have recently shown great promise to address these demands using fully automated design procedures that enable access to non-intuitive device layouts beyond conventional nanophotonic design concepts. Here we present a dynamic binarization method for the objective-first algorithm that lies at the core of the currently most successful inverse design algorithms. Our results demonstrate significant performance advantages over previous implementations of objective first algorithms, which we show for a fundamental TE₀₀ to TE₂₀ waveguide mode converter both in simulation and in experiments with fabricated devices.

CATER: Combined Animal Tracking & Environment Reconstruction

Quantifying the behavior of small animals traversing long distances in complex environments is one of the most difficult tracking scenarios for computer vision. Tiny and low-contrast foreground objects have to be localized in cluttered and dynamic scenes as well as trajectories compensated for camera motion and drift in multiple lengthy recordings. We introduce CATER, a novel methodology combining an unsupervised probabilistic detection mechanism with a globally optimized environment reconstruction pipeline enabling precision behavioral quantification in natural environments. Implemented as an easy to use and highly parallelized tool, we show its application to recover fine-scale motion trajectories, registered to a high-resolution image mosaic reconstruction, of naturally foraging desert ants from unconstrained field recordings. By bridging the gap between laboratory and field experiments, we gain previously unknown insights into ant navigation with respect to motivational states, previous experience, and current environments and provide an appearance-agnostic method applicable to study the behavior of a wide range of terrestrial species under realistic conditions.

Immersive training of clinical decision making with AI driven virtual patients - a new VR platform called medical tr.AI.ning

Background

Medical students need to be prepared for various situations in clinical decision-making that cannot be systematically trained with real patients without risking their health or integrity. To target system-related limitations of actor-based training, digital learning methods are increasingly used in medical education, with virtual reality (VR)- training seeming to have high potential. Virtually generated training scenarios allow repetitive training of highly relevant clinical skills within a protected, realistic learning environment. Thanks to Artificial Intelligence (AI), face-to-face interaction with virtual agents is feasible. Combining this technology with VR-simulations offers a new way of situated context-based, first-person training for medical students.

Project goal and method

The authors' aim is to develop a modular digital training platform for medical education with virtual, interactable agents and to integrate this platform into the medical curriculum. The medical tr.AI.ning platform will provide veridical simulation of clinical scenarios with virtual patients, augmented with highly realistic medical pathologies within a customizable, realistic situational context. Medical tr.AI.ning is scaled to four complementary developmental steps with different scenarios that can be used separately and so each outcome can successively be integrated early within the project. Every step has its own focus (visual, movement, communication, combination) and extends an author toolbox through its modularity. The modules of each step will be specified and designed together with medical didactics experts.

Perspective

To ensure constant improvement of user experience, realism, and medical validity, the authors will perform regular iterative evaluation rounds.Furthermore, integration of medical tr.AI.ning into the medical curriculum will enable long-term and large-scale detection of benefits and limitations of this approach, providing enhanced alternative teaching paradigms for VR technology.

Volumetric imaging reveals VEGF-C-dependent formation of hepatic lymph vessels in mice

The liver is a major biosynthetic and detoxifying organ in vertebrates, but also generates 25%–50% of the lymph passing through the thoracic duct and is thereby the organ with the highest contribution to lymph flow. In contrast to its metabolic function, the role of the liver for lymph generation and composition is presently severely understudied. We took a rigorous, volume imaging-based approach to describe the microarchitecture and spatial composition of the hepatic lymphatic vasculature with cellular resolution in whole mount immune stained specimen ranging from thick sections up to entire mouse liver lobes. Here, we describe that in healthy adult livers, lymphatic vessels were exclusively located within the portal tracts, where they formed a unique, highly ramified tree. Ragged, spiky initials enmeshed the portal veins along their entire length and communicated with long lymphatic vessels that followed the path of the portal vein in close association with bile ducts. Together these lymphatic vessels formed a uniquely shaped vascular bed with a delicate architecture highly adapted to the histological structure of the liver. Unexpectedly, with the exception of short collector stretches at the porta hepatis, which we identified as exit point of the liver lymph vessels, the entire hepatic lymph vessel system was comprised of capillary lymphatic endothelial cells only. Functional experiments confirmed the space of Disse as the origin of the hepatic lymph and flow via the space of Mall to the portal lymph capillaries. After entry into the lymphatic initials, the lymph drained retrograde to the portal blood flow towards the exit at the liver hilum. Perinatally, the liver undergoes complex changes transforming from the main hematopoietic to the largest metabolic organ. We investigated the time course of lymphatic vessel development and identified the hepatic lymphatics to emerge postnatally in a process that relies on input from the VEGF-C/VERGFR-3 growth factor—receptor pair for formation of the fully articulate hepatic lymph vessel bed.

Perspectives in machine learning for wildlife conservation

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into relevant information. We argue that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could improve inputs for ecological models and lead to integrated hybrid modeling tools. This approach will require close interdisciplinary collaboration to ensure the quality of novel approaches and train a new generation of data scientists in ecology and conservation.

An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling

The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk marker of cross-disorder brain changes, growing into a cornerstone of biological age research. However, machine learning models underlying the field do not consider uncertainty, thereby confounding results with training data density and variability. Also, existing models are commonly based on homogeneous training sets, often not independently validated, and cannot be shared because of data protection issues. Here, we introduce an uncertainty-aware, shareable, and transparent Monte Carlo dropout composite quantile regression (MCCQR) Neural Network trained on N = 10,691 datasets from the German National Cohort. The MCCQR model provides robust, distribution-free uncertainty quantification in high-dimensional neuroimaging data, achieving lower error rates compared with existing models. In two examples, we demonstrate that it prevents spurious associations and increases power to detect deviant brain aging. We make the pretrained model and code publicly available.

Resolving Colliding Larvae by Fitting ASM to Random Walker-Based Pre-Segmentations

Drosophila melanogaster is an important model organism for research in neuro- and behavioral biology. Automated studies of their locomotion are crucial to link sensory input and neural processing to motor output which has led to numerous vision-based tracking systems. However, most of these approaches share the inability to segment the contours of colliding animals causing identity losses, appearing and disappearing animals, and the absence of posture and motion related measurements during the time of the collision. We present a novel collision resolution algorithm enabling an accurate contour segmentation of multiple touching Drosophila larvae. Our algorithm utilizes an adapted active shape model (ASM) to learn a low dimensional posture space which is fitted to random-walker generated pre-segmentations. We evaluate our collision resolution algorithm using three publicly available datasets and compare it with the current state-of-the-art methods. In addition, we introduce a refined dataset enabling a segmentation evaluation on the level of pixel accuracy. The results demonstrate that our approach outperforms the state-of-the-art approaches in both accuracy and computational time. We will incorporate this algorithm into our widely used tracking program to improve the statistical strength of the behavioral quantification and allow marker-free studies of interacting Drosophila larvae.

Towards image-based animal tracking in natural environments using a freely moving camera

BACKGROUND

Image-based tracking of individual animals can provide rich data to underpin breakthroughs in biological and medical research, but few if any existing methods extend to tracking unconstrained natural behaviour in the field.

NEW METHOD

We have developed a visual tracking system for animals filmed with a freely moving hand-held or drone-operated camera in their natural environment. This exploits a global inference method for detecting motion of an animal against a cluttered background. Trajectories are then generated by a novel video key-frame selection scheme in combination with a geometrically constrained image stitching algorithm, resulting in a two-dimensional panorama image of the environment on which the dense animal path is displayed.

RESULTS

By introducing a minimal and plausible set of constraints regarding the camera orientation and movement, we demonstrate that both per-frame animal positions and overall trajectories can be extracted with reasonable accuracy, for a range of different animals, environments and imaging modalities.

COMPARISON

Our method requires only a single uncalibrated camera, does not require marking or training data to detect the animal, and makes no prior assumptions about appearance of the target or background. In particular it can detect targets occupying fewer than 20 pixels in the image, and deal with poor contrast, highly dynamic lighting and frequent occlusion.

CONCLUSION

Our algorithm produces highly informative qualitative trajectories embedded in a panorama of the environment. The results are still subject to rotational drift and additional scaling routines would be needed to obtain absolute real-world coordinates. It nevertheless provides a flexible and easy-to-use system to obtain rich data on natural animal behaviour in the field.

From skylight input to behavioural output: A computational model of the insect polarised light compass

Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to 'true north' during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.

The Drosophila NCAM homolog Fas2 signals independent of adhesion

The development of tissues and organs requires close interaction of cells. To do so, cells express adhesion proteins such as the neural cell adhesion molecule (NCAM) or its Drosophila orthologue Fasciclin 2 (Fas2). Both are members of the Ig-domain superfamily of proteins that mediate homophilic adhesion. These proteins are expressed as different isoforms differing in their membrane anchorage and their cytoplasmic domains. To study the function of single isoforms we have conducted a comprehensive genetic analysis of fas2. We reveal the expression pattern of all major Fas2 isoforms, two of which are GPI-anchored. The remaining five isoforms carry transmembrane domains with variable cytoplasmic tails. We generated fas2 mutants expressing only single isoforms. In contrast to the null mutation which causes embryonic lethality, these mutants are viable, indicating redundancy among the different isoforms. Cell type specific rescue experiments showed that glial secreted Fas2 can rescue the fas2 mutant phenotype to viability. This demonstrates cytoplasmic Fas2 domains have no apparent essential functions and indicate that Fas2 has function(s) other than homophilic adhesion. In conclusion, our data propose novel mechanistic aspects of a long studied adhesion protein.

The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae

Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva – because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour–taste associative learning, as well as light/dark–electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages.

FIMTrack: An open source tracking and locomotion analysis software for small animals

Imaging and analyzing the locomotion behavior of small animals such as Drosophila larvae or C. elegans worms has become an integral subject of biological research. In the past we have introduced FIM, a novel imaging system feasible to extract high contrast images. This system in combination with the associated tracking software FIMTrack is already used by many groups all over the world. However, so far there has not been an in-depth discussion of the technical aspects. Here we elaborate on the implementation details of FIMTrack and give an in-depth explanation of the used algorithms. Among others, the software offers several tracking strategies to cover a wide range of different model organisms, locomotion types, and camera properties. Furthermore, the software facilitates stimuli-based analysis in combination with built-in manual tracking and correction functionalities. All features are integrated in an easy-to-use graphical user interface. To demonstrate the potential of FIMTrack we provide an evaluation of its accuracy using manually labeled data. The source code is available under the GNU GPLv3 at https://github.com/i-git/FIMTrack and pre-compiled binaries for Windows and Mac are available at http://fim.uni-muenster.de.

An FIM-Based Long-Term In-Vial Monitoring System for Drosophila Larvae

Drosophila larvae are an insightful model and the automated analysis of their behavior is an integral readout in behavioral biology. Current tracking systems, however, entail a disturbance of the animals, are labor-intensive, and cannot be easily used for long-term monitoring purposes. Here, we present a novel monitoring system for Drosophila larvae, which allows us to analyze the animals in cylindrical culture vials. By utilizing the frustrated total internal reflection in combination with a multi-camera/microcomputer setup, we image the complete housing vial surface and, thus, the larvae for days. We introduce a calibration scheme to stitch the images from the multi-camera system and unfold arbitrary cylindrical surfaces to support different vials. As a result, imaging and analysis of a whole population can be done implicitly. For the first time, this allows us to extract long-term activity quantities of larvae without disturbing the animals. We demonstrate the capabilities of this new setup by automatically quantifying the activity of multiple larvae moving in a vial. The accuracy of the system and the spatio-temporal resolution are sufficient to obtain motion trajectories and higher level features, such as body bending. This new setup can be used for in-vial activity monitoring and behavioral analysis and is capable of gathering millions of data points without both disturbing the animals and increasing labor time. In total, we have analyzed 107 671 frames resulting in 8650 trajectories, which are longer than 30 s, and obtained more than 4.2 × 10⁶ measurements.

FIM$^{2c\;}$: Multicolor, Multipurpose Imaging System to Manipulate and Analyze Animal Behavior

In vivo whole-body imaging of small animals plays an important role for biomedical studies. In particular, animals like the fruit fly Drosophila melanogaster or the nematode Caenorhabditis elegans are popular model organisms for preclinical research since they offer sophisticated genetic tool-kits. Recording these translucent animals with high contrast in a large arena is however not trivial. Furthermore, fluorescent proteins are widely used to mark cells in vivo and report their functions. This paper introduces a novel optical imaging technique called FIM^2c enabling simultaneous detection of the animals posture and movement as well as fluorescent markers like green fluorescent protein (GFP). FIM^2c utilizes frustrated total internal reflection of two distinct wavelengths and captures both, reflected and emitted light. The resultant two-color high-contrast images are superb compared to other imaging systems for larvae or worms. This multipurpose method enables a large variety of different experimental approaches. For example, FIM^2c can be used to image GFP positive cells/tissues/animals and supports the integration of fluorescent tracers into multitarget tracking paradigms. Moreover, optogenetic tools can be applied in large-scale behavioral analysis to manipulate and study neuronal functions. To demonstrate the benefit of our system, we use FIM^2c to resolve colliding larvae in a high-throughput approach, which was impossible given the existing tools. Finally, we present a comprehensive database including images and locomotion features of more than 1300 resolved collisions available for the community. In conclusion, FIM^2c is a versatile tool for advanced imaging and locomotion analysis for a variety of different model organisms.

FIM imaging and FIMtrack: two new tools allowing high-throughput and cost effective locomotion analysis

The analysis of neuronal network function requires a reliable measurement of behavioral traits. Since the behavior of freely moving animals is variable to a certain degree, many animals have to be analyzed, to obtain statistically significant data. This in turn requires a computer assisted automated quantification of locomotion patterns. To obtain high contrast images of almost translucent and small moving objects, a novel imaging technique based on frustrated total internal reflection called FIM was developed. In this setup, animals are only illuminated with infrared light at the very specific position of contact with the underlying crawling surface. This methodology results in very high contrast images. Subsequently, these high contrast images are processed using established contour tracking algorithms. Based on this, we developed the FIMTrack software, which serves to extract a number of features needed to quantitatively describe a large variety of locomotion characteristics. During the development of this software package, we focused our efforts on an open source architecture allowing the easy addition of further modules. The program operates platform independent and is accompanied by an intuitive GUI guiding the user through data analysis. All locomotion parameter values are given in form of csv files allowing further data analyses. In addition, a Results Viewer integrated into the tracking software provides the opportunity to interactively review and adjust the output, as might be needed during stimulus integration. The power of FIM and FIMTrack is demonstrated by studying the locomotion of Drosophila larvae.

Quantifying subtle locomotion phenotypes of Drosophila larvae using internal structures based on FIM images

Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.

The Drosophila FHOD1-like formin Knittrig acts through Rok to promote stress fiber formation and directed macrophage migration during the cellular immune response

A tight spatiotemporal control of actin polymerization is important for many cellular processes that shape cells into a multicellular organism. The formation of unbranched F-actin is induced by several members of the formin family. Drosophila encodes six formin genes, representing six of the seven known mammalian subclasses. Knittrig, the Drosophila homolog of mammalian FHOD1, is specifically expressed in the developing central nervous system midline glia, the trachea, the wing and in macrophages. knittrig mutants exhibit mild tracheal defects but survive until late pupal stages and mainly die as pharate adult flies. knittrig mutant macrophages are smaller and show reduced cell spreading and cell migration in in vivo wounding experiments. Rescue experiments further demonstrate a cell-autonomous function of Knittrig in regulating actin dynamics and cell migration. Knittrig localizes at the rear of migrating macrophages in vivo, suggesting a cellular requirement of Knittrig in the retraction of the trailing edge. Supporting this notion, we found that Knittrig is a target of the Rho-dependent kinase Rok. Co-expression with Rok or expression of an activated form of Knittrig induces actin stress fibers in macrophages and in epithelial tissues. Thus, we propose a model in which Rok-induced phosphorylation of residues within the basic region mediates the activation of Knittrig in controlling macrophage migration.

Drosophila pupal macrophages--a versatile tool for combined ex vivo and in vivo imaging of actin dynamics at high resolution

Molecular understanding of actin dynamics requires a genetically traceable model system that allows live cell imaging together with high-resolution microscopy techniques. Here, we used Drosophila pupal macrophages that combine many advantages of cultured cells with a genetic in vivo model system. Using structured illumination microscopy together with advanced spinning disk confocal microscopy we show that these cells provide a powerful system for single gene analysis. It allows forward genetic screens to characterize the regulatory network controlling cell shape and directed cell migration in a physiological context. We knocked down components regulating lamellipodia formation, including WAVE, single subunits of Arp2/3 complex and CPA, one of the two capping protein subunits and demonstrate the advantages of this model system by imaging mutant macrophages ex vivo as well as in vivo upon laser-induced wounding.

FIM, a novel FTIR-based imaging method for high throughput locomotion analysis

We designed a novel imaging technique based on frustrated total internal reflection (FTIR) to obtain high resolution and high contrast movies. This FTIR-based Imaging Method (FIM) is suitable for a wide range of biological applications and a wide range of organisms. It operates at all wavelengths permitting the in vivo detection of fluorescent proteins. To demonstrate the benefits of FIM, we analyzed large groups of crawling Drosophila larvae. The number of analyzable locomotion tracks was increased by implementing a new software module capable of preserving larval identity during most collision events. This module is integrated in our new tracking program named FIMTrack which subsequently extracts a number of features required for the analysis of complex locomotion phenotypes. FIM enables high throughput screening for even subtle behavioral phenotypes. We tested this newly developed setup by analyzing locomotion deficits caused by the glial knockdown of several genes. Suppression of kinesin heavy chain (khc) or rab30 function led to contraction pattern or head sweeping defects, which escaped in previous analysis. Thus, FIM permits forward genetic screens aimed to unravel the neural basis of behavior.

Biochemical and immunohistochemical detection of the epidermal growth-factor receptor (EGF-R) in breast-tumor specimens

Analyses of the level of expression of the epidermal growth factor receptor (EGF-R) of breast cancer tumors may add independent information about the prognosis of individual patients. Furthermore, the use of monoclonal antibodies directed against EGF-R as therapeutic tools (e.g., Mab 425) requires a reliable evaluation of the individual EGF-R content. Various analytical methods have been published, including (Scarff RW and Torloni H: World Health Organization, Geneva, 1968), biochemical detection of EGF-R by a radiolabeled physiologic ligand [I-125]EGF, (Early Breast Cancer Trialists' Collaborative Group: Lancet 329: 1-15, 1992) biochemical analyses of EGF-R content with a monoclonal antibody, and (McGuire WL and Clark GM: N Engl J Med 326: 1756-1761, 1992) immunohistochemical EGF-R detection. We measured the EGF-R content in membrane pellets derived from routine processing for evaluation of estrogen (ER, ER-EIA) and progesterone receptor (PgR; PgR-EIA) in 185 breast cancers and 18 benign breast samples, using a single-point saturation assay (RBA). Simultaneously, ER (ER-ICA), PgR (PgR-ICA), and EGF-R immunohistochemistry was performed on frozen sections of the same tumors. Various cell lines and normal skin tissue samples served as EGF-R positive or negative controls. The results of the two different EGF-R analyzing methods were compared with other biological characteristics of the tumors. 37% of the tumors were EGF-R positive. There was an inverse correlation between the ER or PgR and the EGF-R content. EGF-R overexpression correlated with high tumor grade. Analyses of EGF-R content in membrane pellets of breast cancer samples by single point saturation assay as well as the evaluation of tumor sections by immunohistochemistry can be performed routinely. The results obtained with both analytical methods did not differ significantly. but the immunohistochemistry proved to be more difficult to perform and to interpret. Thus, we prefer to perform both analytical methods simultaneously to provide information potentially useful for clinical management of individual cancer patients.

Serpins in the human hair follicle

Proteinases and their inhibitors are very likely to function as mediators or regulators of the hair growth cycle. Very little information is currently available, however, regarding the specific inhibitors present in human hair follicles at defined stages of their growth cycle. In this study we have analyzed two proteinase inhibitors, plasminogen activator inhibitor type 2 and protease nexin 1, in human hair follicles using in situ hybridization and/or immunohistochemistry. Protease nexin 1 mRNA was found only in the mesenchymal population of the hair follicle, i.e., the follicular papilla cells, during the anagen but not the catagen phase. In contrast, plasminogen activator inhibitor type 2 was localized to several epithelial populations in the follicle: the more differentiated cells of the infundibulum; the companion layer in anagen follicles; and the single layer of outer root sheath cells directly abutting the club hair in telogen follicles. At least some of the plasminogen activator inhibitor type 2 in human follicles appears to be in the relaxed form, as evidenced by strong staining with an antibody that is specific for this form of the inhibitor. This suggests that plasminogen activator inhibitor type 2 interacts with and is cleaved by an endogenous follicular proteinase and supports a constitutive role for this inhibitor in human follicular epithelia.

Plasminogen activator inhibitor type 2 in human corneal epithelium

PURPOSE

To examine normal human corneal epithelium in vivo and in vitro for expression and status of plasniinogcn activ:ltor inhibitor type 2 (PAI-2).

METHODS

Normal hiuman corneas were prepared for frozen sections and for culture of corneal keratinocytes. PAI-2 was analyzed by immunohistochemistry and western blot analysis uising antibodies that recognize all forms of PAI-2.

RESULTS

In vivo and in vitro, PAI-2 was immunohistochemically localized to the superficial corneal keratinocytes. Immunostaining also revealed the presence of PAI-2 in its relaxed (i.e., cleaved) conformation. In vivo, the staining pattern of the relaxed form was identical with that of total PAI-2, but in vitro the relaxed form was detected in a smaller subpopulation of superficial cells. In vitro, the staining pattern indicated a cytoplasmic localization for PAI-2. Western blot analysis revealed that most of the PAI-2 was cell associated and functionally active.

CONCLUSIONS

The present results are the first to show that PAI-2 is found in normal human corneal epithelium in vivo and in vitro, where it can be considered as a differentiation product. At least in vitro, all detectable PAI-2 is cell associated, with a cytoplasmic distribution. A subpopulation of keratinocytes also contains PAI-2 in its relaxed (i.e., cleaved) conformation. Cleavage by an as yet unidentified cytoplasmic proteinase may constitute a crucial aspect of the function of corneal epithelial PAI-2, which may be relevant to terminal differentiation and death of the corneal keratinocyte.

Seroprevalence study of herpes simplex virus type 2 among pregnant women in Germany using a type-specific enzyme immunoassay

In a German seroepidemiological study to determine the proportion of pregnant women infected with herpes simplex virus type 2 (HSV-2) and at risk of transmitting the infection to the newborn during delivery, IgG antibodies to HSV-2 in 1999 sera collected from pregnant women in 1996-1997 were measured using an automated type-specific enzyme immunoassay (Cobas Core HSV-2 IgG EIA; Roche Diagnostics, Switzerland). The seroprevalence of HSV-2 was 8.9%, and control studies with a type-common HSV assay measuring antibodies to HSV-1 and HSV-2 revealed that 20.7% of pregnant women were seronegative for HSV antibodies and are therefore at risk of acquiring primary genital HSV infection of either type.

Protective effect of vaccination with a combination of recombinant surface antigen 1 and interleukin-12 against toxoplasmosis in mice

We studied the immune response induced in mice by recombinant Toxoplasma gondii surface antigen 1 (rSAG1) protein, alone or combined with interleukin-12 (IL-12) as an adjuvant, and the protective effect against toxoplasmosis. Immunization with rSAG1 alone induced a specific humoral type 2 immunity and did not protect the animals from infection. In contrast, immunization with rSAG1 plus IL-12 redirected humoral and cellular immunity toward a type 1 pattern and reduced the brain parasite load by 40%.

Localization of plasminogen activator inhibitor type 2 (PAI-2) in hair and nail: implications for terminal differentiation

Plasminogen activator inhibitor type 2 (PAI-2) is an unusual serine proteinase inhibitor in that it is largely retained within the cell and is found in high concentrations in the upper viable layers of human epidermis. Studies using transfected cell lines that express high levels of PAI-2 have suggested that this inhibitor may confer protection against programmed cell death. To test the hypothesis that PAI-2 may protect epithelial cells in vivo from premature programmed cell death, we determined expression patterns of PAI-2 in murine hair and nail. These epidermal derivatives are comprised of numerous epithelial cell types with distinct differentiation pathways. Furthermore, the cyclic nature of the follicular epithelium makes it ideal for studying sequential stages of cell differentiation and death. PAI-2 mRNA and protein were detected in the differentiating cells of the outer root sheath and medulla of the follicle during the anagen phase of the hair growth cycle. PAI-2 was also detected in the permanent portion of the catagen follicle. In the telogen phase of the hair growth cycle, PAI-2 was limited to the postmitotic cells of the outer root sheath directly abutting the club hair. In the nail, PAI-2 was detected in the differentiating cells of the matrix and nail bed. This consistent, selective distribution of PAI-2 in the postmitotic, maturing cells prior to terminal keratinization and death suggests that (i) PAI-2 may be considered as a differentiation marker for many epithelial cell types, and (ii) PAI-2 is appropriately positioned to protect epithelial cells from premature demise.

Regulation of Bcl-xL expression in human keratinocytes by cell-substratum adhesion and the epidermal growth factor receptor

Cell-substratum adhesion is an essential requirement for survival of human neonatal keratinocytes in vitro. Similarly, activation of the epidermal growth factor receptor (EGF-R) has recently been implicated not only in cell cycle progression but also in survival of normal keratinocytes. The mechanisms by which either cell-substratum adhesion or EGF-R activation protect keratinocytes from programmed cell death are poorly understood. Here we describe that blockade of the EGF-R and inhibition of substratum adhesion share a common downstream event, the down-regulation of the cell death protector Bcl-xL. Expression of Bcl-xL protein was down-regulated during forced suspension culture of keratinocytes, concurrent with large-scale apoptosis. Similarly, EGF-R blockade was accompanied by down-regulation of Bcl-xL steady-state mRNA and protein levels to an extent comparable to that observed in forced suspension culture. However, down-regulation of Bcl-xL expression by EGF-R blockade was not accompanied by apoptosis; in this case, a second signal, generated by passaging, was required to induce rapid and large-scale apoptosis. These findings are consistent with the conclusions that (i) Bcl-xL represents a shared molecular target for signaling through cell-substrate adhesion receptors and the EGF-R, and (ii) reduced levels of Bcl-xL expression through EGF-R blockade lower the tolerance of keratinocytes for cell death signals generated by cellular stress.

Identification of differentially expressed messenger RNAs in human melanocytes and melanoma cells

The phenotype of malignant lesions is a reflection of genetic events altering the RNA and protein expression patterns of normal cells. We have investigated RNA expression patterns distinguishing normal melanocytes (FM 902), a primary melanoma cell line (WM 793), and its variant cell line (1205-LU), selected for metastatic phenotype in athymic mice. Using mRNA differential display, we identified 42 different cDNA PCR products with cell line-specific expression patterns. Direct sequence analysis matched approximately 50% of the cDNA PCR products with gene sequences accessible in DNA databases. Among the known genes, two functionally distinct groups were recognized: (a) genes encoding ribosomal and mitochondrial proteins that were predominantly up-regulated in the malignant cells; and (b) genes encoding modulators of the immune response. Among the immunomodulators, the T-cell antigen MART-1 and the protease inhibitor alpha2-macroglobulin were detected in the melanocyte cell line but not in the tumor cells. By contrast, mRNAs for the complement inhibitor CD59 and the cytokine IL-1beta were found to be overexpressed in the malignant melanoma cells. RNA slot blot hybridization on a larger panel of melanocyte and melanoma cell lines confirmed differential expression of 15 of 42 genes including MART-1, alpha2-macroglobulin, and CD59. This molecular screening approach identified also three partially characterized and three novel sequences with differential expression patterns in normal and malignant melanocytes.

A yeast DnaJ homologue, Scj1p, can function in the endoplasmic reticulum with BiP/Kar2p via a conserved domain that specifies interactions with Hsp70s

Eukaryotic cells contain multiple Hsp70 proteins and DnaJ homologues. The partnership between a given Hsp70 and its interacting DnaJ could, in principle, be determined by their cellular colocalization or by specific protein-protein interactions. The yeast SCJ1 gene encodes one of several homologues of the bacterial chaperone DnaJ. We show that Scj1p is located in the lumen of the endoplasmic reticulum (ER), where it can function with Kar2p (the ER-lumenal BiP/Hsp70 of yeast). The region common to all DnaJ homologues (termed the J domain) from Scj1p can be swapped for a similar region in Sec63p, which is known to interact with Kar2p in the ER lumen, to form a functional transmembrane protein component of the secretory machinery. Thus, Kar2p can interact with two different DnaJ proteins. On the other hand, J domains from two other non-ER DnaJs, Sis1p and Mdj1p, do not function when swapped into Sec63p. However, only three amino acid changes in the Sis1p J domain render the Sec63 fusion protein fully functional in the ER lumen. These results indicate that the choice of an Hsp70 partner by a given DnaJ homologue is specified by the J domain.

Use of a serum-free epidermal culture model to show deleterious effects of epidermal growth factor on morphogenesis and differentiation

The presence of serum has limited the utility of many culture models for the study of cytokine effects because its complexity and variability can confound the interpretation of data. In the present study, a serum-free skin co-culture model was used to investigate the effect of exogenous epidermal growth factor (EGF) on epidermal proliferation and differentiation. Human keratinocytes cultured on collagen rafts at the air-liquid interface produced a well-differentiated epithelium that resembled normal epidermis. Keratin filaments, membrane-coating granules, and keratohyalin granules were all observed. Epidermal differentiation markers keratin K1/K10, involucrin, and transglutaminase were localized in most of the suprabasal layers, whereas profilaggrin/filaggrin was confined to the granular layers and stratum corneum. In the continual presence of 10-20 ng/mL EGF, the epidermis was less organized, thinner, and less proliferative. EGF also depressed several indicators of differentiation: The number of keratohyalin granules and membrane-coating granules was greatly decreased; antigen expression of profilaggrin/filaggrin appeared diminished by immunocytochemical staining; frequent nuclear retention was noted in the relatively thickened stratum corneum-like layers. As detected by immunohistochemical staining, the expression of EGF receptor in the epidermis was reduced by exogenous EGF. These data illustrate that EGF cannot be considered a simple mitogen. Our findings also underscore the importance of using sophisticated culture models to assess complex cytokine effects that may be dependent on the architecture of a differentiating epidermis.

Characterization of the stabilizing effect of point mutations of pyruvate oxidase from Lactobacillus plantarum: protection of the native state by modulating coenzyme binding and subunit interaction

Point mutations in the gene of pyruvate oxidase from Lactobacillus plantarum, with proline residue 178 changed to serine, serine 188 to asparagine, and alanine 458 to valine, as well as a combination of the three single point mutations, lead to a significant functional stabilization of the protein. The enzyme is a tetrameric flavoprotein with tightly bound cofactors, FAD, TPP, and divalent metal ions. Thus, stabilization may be achieved either at the level of tertiary or quaternary interactions, or by enhanced cofactor binding. In order to discriminate between these alternatives, unfolding, dissociation, and cofactor binding of the mutant proteins were analyzed. The point mutations do not affect the secondary and tertiary structure, as determined by circular dichroism and protein fluorescence. Similarly, the amino acid substitutions neither modulate the enzymatic properties of the mutant proteins nor do they stabilize the structural stability of the apoenzymes. This holds true for both the local and the global structure with unfolding transitions around 2.5 M and 5 M urea, respectively. On the other hand, deactivation of the holoenzyme (by urea or temperature) is significantly decreased. The most important stabilizing effect is caused by the Ala-Val exchange in the C-terminal domain of the molecule. Its contribution is close to the value observed for the triple mutant, which exhibits maximum stability, with a shift in the thermal transition of ca. 10 degrees C. The effects of the point mutations on FAD binding and subunit association are interconnected. Because FAD binding is linked to oligomerization, the stability of the mutant apoenzyme-FAD complexes is increased. Accordingly, mutants with maximum apparent FAD binding exhibit maximum stability. Analysis of the quaternary structure of the mutant enzymes in the absence and in the presence of coenzymes gives clear evidence that both improved ligand binding and subunit interactions contribute to the observed thermal stabilization.

Stability and reconstitution of pyruvate oxidase from Lactobacillus plantarum: dissection of the stabilizing effects of coenzyme binding and subunit interaction

Pyruvate oxidase from Lactobacillus plantarum is a homotetrameric flavoprotein with strong binding sites for FAD, TPP, and a divalent cation. Treatment with acid ammonium sulfate in the presence of 1.5 M KBr leads to the release of the cofactors, yielding the stable apoenzyme. In the present study, the effects of FAD, TPP, and Mn2+ on the structural properties of the apoenzyme and the reconstitution of the active holoenzyme from its constituents have been investigated. As shown by circular dichroism and fluorescence emission, as well as by Nile red binding, the secondary and tertiary structures of the apoenzyme and the holoenzyme do not exhibit marked differences. The quaternary structure is stabilized significantly in the presence of the cofactors. Size-exclusion high-performance liquid chromatography and analytical ultracentrifugation demonstrate that the holoenzyme retains its tetrameric state down to 20 micrograms/mL, whereas the apoenzyme shows stepwise tetramer-dimer-monomer dissociation, with the monomer as the major component, at a protein concentration of < 20 micrograms/mL. In the presence of divalent cations, the coenzymes FAD and TPP bind to the apoenzyme, forming the inactive binary FAD or TPP complexes. Both FAD and TPP affect the quaternary structure by shifting the equilibrium of association toward the dimer or tetramer. High FAD concentrations exert significant stabilization against urea and heat denaturation, whereas excess TPP has no effect. Reconstitution of the holoenzyme from its components yields full reactivation. The kinetic analysis reveals a compulsory sequential mechanism of cofactor binding and quaternary structure formation, with TPP binding as the first step. The binary TPP complex (in the presence of 1 mM Mn2+/TPP) is characterized by a dimer-tetramer equilibrium transition with an association constant of Ka = 2 x 10(7) M-1. The apoenzyme TPP complex dimer associates with the tetrameric holoenzyme in the presence of 10 microM FAD. This association step obeys second-order kinetics with an association rate constant k = 7.4 x 10(3) M-1 s-1 at 20 degrees C. FAD binding to the tetrameric binary TPP complex is too fast to be resolved by manual mixing.

Characterization of Recombinant Factor XIIIa Produced in Saccharomyces cerevisiae

Recombinant factor XIIIa (FXIIIa), produced in Saccharomyces cerevisiae, was recovered as a fully active cytosolic component and rigorously compared to natural F XIIIa from human placenta with respect to physicochemical and functional properties. Identical parameters were found in SDS polyacrylamide gel electrophoresis, analytical ultracentrifugation and HPLC gel filtration, and all spectral characteristics including derivative UV absorbance, fluorescence and circular dichroism were identical. Similarly, the interaction of both proteins with polyclonal antibodies directed against the entire FXIIIa or its N-terminal 4 kD activation peptide were identical. Furthermore, thrombin cleavage and fibrin cross-linking showed indistinguishable patterns. The only difference we observed was with respect to endgroup analysis. The recombinant protein is homogeneous, whereas placental FXIIIa shows multiple electrophoretic bands caused by microheterogeneity in the C-terminal part of the protein.

Denaturation-renaturation of the fibrin-stabilizing factor XIII a-chain isolated from human placenta. Properties of the native and reconstituted protein

The denaturation-renaturation transition between the native and unfolded states of the dimeric blood coagulation factor XIIIa has been examined by far-UV circular dichroism, fluorescence spectroscopy, activity measurements, sedimentation equilibrium analysis, and size exclusion high performance liquid chromatography. Guanidine hydrochloride and urea-dependent denaturation in the absence and in the presence of 5mM dithioerythritol or glutathione (5mM GSH) exhibit biphasic transitions. The first stage represents a sharp transition characterized by a change in secondary structure without subunit dissociation. This step is accompanied by the irreversible loss of biological activity. The second transition reflects the dissociation and complete unfolding of the protein to a random coil. After loss of biological activity no reactivation can be accomplished under any of the following conditions: (i) denaturation and renaturation under reducing or non-reducing conditions, (ii) variation of the protein concentration and temperature, (iii) addition of specific ligands (Ca2+, substrate), (iv) presence of stabilizing and/or destabilizing agents. Attempts to renature the protein under standard conditions (0.1 M Tris/HCl pH 7.5-9.0, 5mM DTE, 5mM EDTA) lead to refolding intermediates which exhibit a strong tendency to aggregate. A soluble product of reconstitution can be obtained by refolding at low protein concentration, low temperature, and in the presence of small amounts of destabilizing agents such as arginine or urea in the renaturation buffer at pH 7.5 to 9. The spectroscopic and hydrodynamic characterization of the partially reconstituted (non-native inactive) protein shows that partially reconstituted factor XIIIa exhibits the fluorescence properties and the dimeric structure of the native protein.(ABSTRACT TRUNCATED AT 250 WORDS)