The social construction of cooperation: exchange, identification and collective intentions within the organization

My aim is to develop a theory of cooperation within the organization and empirically test it. Drawing upon social exchange theory, social identity theory, the idea of collective intentions, and social constructivism, the main assumption of my work implies that both cooperation and the organization itself are continually shaped and restructured by actions, judgments, and symbolic interpretations of the parties involved. Therefore, I propose that the decision to cooperate, expressed say as an intention to cooperate, reflects and depends on a three step social process shaped by the interpretations of the actors involved. The first step entails an instrumental evaluation of cooperation in terms of social exchange. In the second step, this “social calculus” is translated into cognitive, emotional and evaluative reactions directed toward the organization. Finally, once the identification process is completed and membership awareness is established, I propose that individuals will start to think largely in terms of “We” instead of “I”. Self-goals are redefined at the collective level, and the outcomes for self, others, and the organization become practically interchangeable. I decided to apply my theory to an important cooperative problem in management research: knowledge exchange within organizations. Hence, I conducted a quantitative survey among the members of the virtual community, “www.borse.it” (n=108). Within this community, members freely decide to exchange their knowledge about the stock market among themselves. Because of the confirmatory requirements and the structural complexity of the theory proposed (i.e., the proposal that instrumental evaluations will induce social identity and this in turn will causes collective intentions), I use Structural Equation Modeling to test all hypotheses in this dissertation. The empirical survey-based study found support for the theory of cooperation proposed in this dissertation. The findings suggest that an appropriate conceptualization of the decision to exchange knowledge is one where collective intentions depend proximally on social identity (i.e., cognitive identification, affective commitment, and evaluative engagement) with the organization, and this identity depends on instrumental evaluations of cooperators (i.e., perceived value of the knowledge received, assessment of past reciprocity, expected reciprocity, and expected social outcomes of the exchange). Furthermore, I find that social identity fully mediates the effects of instrumental motives on collective intentions.

Structural patterns for document engineering: from an empirical bottom-up analysis to an ontological theory

This thesis aims at investigating a new approach to document analysis based on the idea of structural patterns in XML vocabularies. My work is founded on the belief that authors do naturally converge to a reasonable use of markup languages and that extreme, yet valid instances are rare and limited. Actual documents, therefore, may be used to derive classes of elements (patterns) persisting across documents and distilling the conceptualization of the documents and their components, and may give ground for automatic tools and services that rely on no background information (such as schemas) at all. The central part of my work consists in introducing from the ground up a formal theory of eight structural patterns (with three sub-patterns) that are able to express the logical organization of any XML document, and verifying their identifiability in a number of different vocabularies. This model is characterized by and validated against three main dimensions: terseness (i.e. the ability to represent the structure of a document with a small number of objects and composition rules), coverage (i.e. the ability to capture any possible situation in any document) and expressiveness (i.e. the ability to make explicit the semantics of structures, relations and dependencies). An algorithm for the automatic recognition of structural patterns is then presented, together with an evaluation of the results of a test performed on a set of more than 1100 documents from eight very different vocabularies. This language-independent analysis confirms the ability of patterns to capture and summarize the guidelines used by the authors in their everyday practice. Finally, I present some systems that work directly on the pattern-based representation of documents. The ability of these tools to cover very different situations and contexts confirms the effectiveness of the model.

Frog oocytes to unveil the structure and supramolecular organization of human transport proteins

Structural analyses of heterologously expressed mammalian membrane proteins remain a great challenge given that microgram to milligram amounts of correctly folded and highly purified proteins are required. Here, we present a novel method for the expression and affinity purification of recombinant mammalian and in particular human transport proteins in Xenopus laevis frog oocytes. The method was validated for four human and one murine transporter. Negative stain transmission electron microscopy (TEM) and single particle analysis (SPA) of two of these transporters, i.e., the potassium-chloride cotransporter 4 (KCC4) and the aquaporin-1 (AQP1) water channel, revealed the expected quaternary structures within homogeneous preparations, and thus correct protein folding and assembly. This is the first time a cation-chloride cotransporter (SLC12) family member is isolated, and its shape, dimensions, low-resolution structure and oligomeric state determined by TEM, i.e., by a direct method. Finally, we were able to grow 2D crystals of human AQP1. The ability of AQP1 to crystallize was a strong indicator for the structural integrity of the purified recombinant protein. This approach will open the way for the structure determination of many human membrane transporters taking full advantage of the Xenopus laevis oocyte expression system that generally yields robust functional expression.

Reconstitution of mitochondrial ATP synthase into lipid bilayers for structural analysis

Mitochondrial F(1)F(o)-ATP synthase is a molecular motor that couples the energy generated by oxidative metabolism to the synthesis of ATP. Direct visualization of the rotary action of the bacterial ATP synthase has been well characterized. However, direct observation of rotation of the mitochondrial enzyme has not been reported yet. Here, we describe two methods to reconstitute mitochondrial F(1)F(o)-ATP synthase into lipid bilayers suitable for structure analysis by electron and atomic force microscopy (AFM). Proteoliposomes densely packed with bovine heart mitochondria F(1)F(o)-ATP synthase were obtained upon detergent removal from ternary mixtures (lipid, detergent and protein). Two-dimensional crystals of recombinant hexahistidine-tagged yeast F(1)F(o)-ATP synthase were grown using the supported monolayer technique. Because the hexahistidine-tag is located at the F(1) catalytic subcomplex, ATP synthases were oriented unidirectionally in such two-dimensional crystals, exposing F(1) to the lipid monolayer and the F(o) membrane region to the bulk solution. This configuration opens a new avenue for the determination of the c-ring stoichiometry of unknown hexahistidine-tagged ATP synthases and the organization of the membrane intrinsic subunits within F(o) by electron microscopy and AFM.

Purchasing Organization and Design: A Literature Review

This paper presents the results of a comprehensive literature review of the organization of purchasing covering the period from 1967 to 2009. The review provides a structured overview of prior research topics and findings and identifies gaps in the existing literature that may be addressed in future research. The intention of the review is to a) synthesize prior research, b) provide researchers with a structural framework on which future research on the organization of purchasing may be oriented, and c) suggest promising areas for future research.

Supramolecular Organization of Heptapyrenotide Oligomers—An in Depth Investigation by Molecular Dynamics Simulations

We present a molecular modeling study based on ab initio and classical molecular dynamics calculations, for the investigation of the tridimensional structure and supramolecular assembly formation of heptapyrenotide oligomers in water solution. Our calculations show that free oligomers self-assemble in helical structures characterized by an inner core formed by π- stacked pyrene units, and external grooves formed by the linker moieties. The coiling of the linkers has high ordering, dominated by hydrogen-bond interactions among the phosphate and amide groups. Our models support a mechanism of longitudinal supramolecular oligomerization based on interstrand pyrene intercalation. Only a minimal number of pyrene units intercalate at one end, favoring formation of very extended longitudinal chains, as also detected by AFM experiment. Our results provide a structural explanation of the mechanism of chirality amplification in 1:1 mixtures of standard heptapyrenotides and modified oligomers with covalently linked deoxycytidine, based on selective molecular recognition and binding of the nucleotide to the groove of the left-wound helix.

The structural substrate of brain function: analysis of brain structural networks based on diffusion-weighted imaging

The brain is a complex neural network with a hierarchical organization and the mapping of its elements and connections is an important step towards the understanding of its function. Recent developments in diffusion-weighted imaging have provided the opportunity to reconstruct the whole-brain structural network in-vivo at a large scale level and to study the brain structural substrate in a framework that is close to the current understanding of brain function. However, methods to construct the connectome are still under development and they should be carefully evaluated. To this end, the first two studies included in my thesis aimed at improving the analytical tools specific to the methodology of brain structural networks. The first of these papers assessed the repeatability of the most common global and local network metrics used in literature to characterize the connectome, while in the second paper the validity of further metrics based on the concept of communicability was evaluated. Communicability is a broader measure of connectivity which accounts also for parallel and indirect connections. These additional paths may be important for reorganizational mechanisms in the presence of lesions as well as to enhance integration in the network. These studies showed good to excellent repeatability of global network metrics when the same methodological pipeline was applied, but more variability was detected when considering local network metrics or when using different thresholding strategies. In addition, communicability metrics have been found to add some insight into the integration properties of the network by detecting subsets of nodes that were highly interconnected or vulnerable to lesions. The other two studies used methods based on diffusion-weighted imaging to obtain knowledge concerning the relationship between functional and structural connectivity and about the etiology of schizophrenia. The third study integrated functional oscillations measured using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) as well as diffusion-weighted imaging data. The multimodal approach that was applied revealed a positive relationship between individual fluctuations of the EEG alpha-frequency and diffusion properties of specific connections of two resting-state networks. Finally, in the fourth study diffusion-weighted imaging was used to probe for a relationship between the underlying white matter tissue structure and season of birth in schizophrenia patients. The results are in line with the neurodevelopmental hypothesis of early pathological mechanisms as the origin of schizophrenia. The different analytical approaches selected in these studies also provide arguments for discussion of the current limitations in the analysis of brain structural networks. To sum up, the first studies presented in this thesis illustrated the potential of brain structural network analysis to provide useful information on features of brain functional segregation and integration using reliable network metrics. In the other two studies alternative approaches were presented. The common discussion of the four studies enabled us to highlight the benefits and possibilities for the analysis of the connectome as well as some current limitations.

From Ribbons to Networks: Hierarchical Organization of DNA-Grafted Supramolecular Polymers

DNA-grafted supramolecular polymers (SPs) allow the programmed organization of DNA in a highly regular, one-dimensional array. Oligonucleotides are arranged along the edges of pyrene-based helical polymers. Addition of complementary oligonucleotides triggers the assembly of individual nanoribbons resulting in the development of extended supramolecular networks. Network formation is enabled by cooperative coaxial stacking interactions of terminal GC base pairs. The process is accompanied by structural changes in the pyrene polymer core that can be followed spectroscopically. Network formation is reversible, and disassembly into individual ribbons is realized either via thermal denaturation or by addition of a DNA separator strand.

Anatomo-functional organization in brain networks

There are several studies focused on comparing rsFC networks with their structural substrate \cite{hagmann2008, honey2010}. However an accurate description of how anatomo-­functional connections are organized, both at physical and topological levels, is still to be defined. Here we present an approach to quantify the anatomo-functional organization and discuss its consistency.

Plant β-diversity i in human-altered forest ecosystems: the importance of the structural, spatial, and topographical characteristics of stands in patterning plant species assemblages

An understanding of spatial patterns of plant species diversity and the factors that drive those patterns is critical for the development of appropriate biodiversity management in forest ecosystems. We studied the spatial organization of plants species in human- modified and managed oak forests (primarily, Quercus faginea) in the Central Pre- Pyrenees, Spain. To test whether plant community assemblages varied non-randomly across the spatial scales, we used multiplicative diversity partitioning based on a nested hierarchical design of three increasingly coarser spatial scales (transect, stand, region). To quantify the importance of the structural, spatial, and topographical characteristics of stands in patterning plant species assemblages and identify the determinants of plant diversity patterns, we used canonical ordination. We observed a high contribution of ˟-diversity to total -diversity and found ˟-diversity to be higher and ˞-diversity to be lower than expected by random distributions of individuals at different spatial scales. Results, however, partly depended on the weighting of rare and abundant species. Variables expressing the historical management intensities of the stand such as mean stand age, the abundance of the dominant tree species (Q. faginea), age structure of the stand, and stand size were the main factors that explained the compositional variation in plant communities. The results indicate that (1) the structural, spatial, and topographical characteristics of the forest stands have the greatest effect on diversity patterns, (2) forests in landscapes that have different land use histories are environmentally heterogeneous and, therefore, can experience high levels of compositional differentiation, even at local scales (e.g., within the same stand). Maintaining habitat heterogeneity at multiple spatial scales should be considered in the development of management plans for enhancing plant diversity and related functions in human-altered forests

Automated detection and classification of brain injury lesions on structural magnetic resonance imaging

El daño cerebral adquirido (DCA) es un problema social y sanitario grave, de magnitud creciente y de una gran complejidad diagnóstica y terapéutica. Su elevada incidencia, junto con el aumento de la supervivencia de los pacientes, una vez superada la fase aguda, lo convierten también en un problema de alta prevalencia. En concreto, según la Organización Mundial de la Salud (OMS) el DCA estará entre las 10 causas más comunes de discapacidad en el año 2020. La neurorrehabilitación permite mejorar el déficit tanto cognitivo como funcional y aumentar la autonomía de las personas con DCA. Con la incorporación de nuevas soluciones tecnológicas al proceso de neurorrehabilitación se pretende alcanzar un nuevo paradigma donde se puedan diseñar tratamientos que sean intensivos, personalizados, monitorizados y basados en la evidencia. Ya que son estas cuatro características las que aseguran que los tratamientos son eficaces. A diferencia de la mayor parte de las disciplinas médicas, no existen asociaciones de síntomas y signos de la alteración cognitiva que faciliten la orientación terapéutica. Actualmente, los tratamientos de neurorrehabilitación se diseñan en base a los resultados obtenidos en una batería de evaluación neuropsicológica que evalúa el nivel de afectación de cada una de las funciones cognitivas (memoria, atención, funciones ejecutivas, etc.). La línea de investigación en la que se enmarca este trabajo de investigación pretende diseñar y desarrollar un perfil cognitivo basado no sólo en el resultado obtenido en esa batería de test, sino también en información teórica que engloba tanto estructuras anatómicas como relaciones funcionales e información anatómica obtenida de los estudios de imagen. De esta forma, el perfil cognitivo utilizado para diseñar los tratamientos integra información personalizada y basada en la evidencia. Las técnicas de neuroimagen representan una herramienta fundamental en la identificación de lesiones para la generación de estos perfiles cognitivos. La aproximación clásica utilizada en la identificación de lesiones consiste en delinear manualmente regiones anatómicas cerebrales. Esta aproximación presenta diversos problemas relacionados con inconsistencias de criterio entre distintos clínicos, reproducibilidad y tiempo. Por tanto, la automatización de este procedimiento es fundamental para asegurar una extracción objetiva de información. La delineación automática de regiones anatómicas se realiza mediante el registro tanto contra atlas como contra otros estudios de imagen de distintos sujetos. Sin embargo, los cambios patológicos asociados al DCA están siempre asociados a anormalidades de intensidad y/o cambios en la localización de las estructuras. Este hecho provoca que los algoritmos de registro tradicionales basados en intensidad no funcionen correctamente y requieran la intervención del clínico para seleccionar ciertos puntos (que en esta tesis hemos denominado puntos singulares). Además estos algoritmos tampoco permiten que se produzcan deformaciones grandes deslocalizadas. Hecho que también puede ocurrir ante la presencia de lesiones provocadas por un accidente cerebrovascular (ACV) o un traumatismo craneoencefálico (TCE). Esta tesis se centra en el diseño, desarrollo e implementación de una metodología para la detección automática de estructuras lesionadas que integra algoritmos cuyo objetivo principal es generar resultados que puedan ser reproducibles y objetivos. Esta metodología se divide en cuatro etapas: pre-procesado, identificación de puntos singulares, registro y detección de lesiones. Los trabajos y resultados alcanzados en esta tesis son los siguientes: Pre-procesado. En esta primera etapa el objetivo es homogeneizar todos los datos de entrada con el objetivo de poder extraer conclusiones válidas de los resultados obtenidos. Esta etapa, por tanto, tiene un gran impacto en los resultados finales. Se compone de tres operaciones: eliminación del cráneo, normalización en intensidad y normalización espacial. Identificación de puntos singulares. El objetivo de esta etapa es automatizar la identificación de puntos anatómicos (puntos singulares). Esta etapa equivale a la identificación manual de puntos anatómicos por parte del clínico, permitiendo: identificar un mayor número de puntos lo que se traduce en mayor información; eliminar el factor asociado a la variabilidad inter-sujeto, por tanto, los resultados son reproducibles y objetivos; y elimina el tiempo invertido en el marcado manual de puntos. Este trabajo de investigación propone un algoritmo de identificación de puntos singulares (descriptor) basado en una solución multi-detector y que contiene información multi-paramétrica: espacial y asociada a la intensidad. Este algoritmo ha sido contrastado con otros algoritmos similares encontrados en el estado del arte. Registro. En esta etapa se pretenden poner en concordancia espacial dos estudios de imagen de sujetos/pacientes distintos. El algoritmo propuesto en este trabajo de investigación está basado en descriptores y su principal objetivo es el cálculo de un campo vectorial que permita introducir deformaciones deslocalizadas en la imagen (en distintas regiones de la imagen) y tan grandes como indique el vector de deformación asociado. El algoritmo propuesto ha sido comparado con otros algoritmos de registro utilizados en aplicaciones de neuroimagen que se utilizan con estudios de sujetos control. Los resultados obtenidos son prometedores y representan un nuevo contexto para la identificación automática de estructuras. Identificación de lesiones. En esta última etapa se identifican aquellas estructuras cuyas características asociadas a la localización espacial y al área o volumen han sido modificadas con respecto a una situación de normalidad. Para ello se realiza un estudio estadístico del atlas que se vaya a utilizar y se establecen los parámetros estadísticos de normalidad asociados a la localización y al área. En función de las estructuras delineadas en el atlas, se podrán identificar más o menos estructuras anatómicas, siendo nuestra metodología independiente del atlas seleccionado. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la identificación automática de lesiones utilizando estudios de imagen médica estructural, concretamente estudios de resonancia magnética. Basándose en estos cimientos, se han abrir nuevos campos de investigación que contribuyan a la mejora en la detección de lesiones. ABSTRACT Brain injury constitutes a serious social and health problem of increasing magnitude and of great diagnostic and therapeutic complexity. Its high incidence and survival rate, after the initial critical phases, makes it a prevalent problem that needs to be addressed. In particular, according to the World Health Organization (WHO), brain injury will be among the 10 most common causes of disability by 2020. Neurorehabilitation improves both cognitive and functional deficits and increases the autonomy of brain injury patients. The incorporation of new technologies to the neurorehabilitation tries to reach a new paradigm focused on designing intensive, personalized, monitored and evidence-based treatments. Since these four characteristics ensure the effectivity of treatments. Contrary to most medical disciplines, it is not possible to link symptoms and cognitive disorder syndromes, to assist the therapist. Currently, neurorehabilitation treatments are planned considering the results obtained from a neuropsychological assessment battery, which evaluates the functional impairment of each cognitive function (memory, attention, executive functions, etc.). The research line, on which this PhD falls under, aims to design and develop a cognitive profile based not only on the results obtained in the assessment battery, but also on theoretical information that includes both anatomical structures and functional relationships and anatomical information obtained from medical imaging studies, such as magnetic resonance. Therefore, the cognitive profile used to design these treatments integrates information personalized and evidence-based. Neuroimaging techniques represent an essential tool to identify lesions and generate this type of cognitive dysfunctional profiles. Manual delineation of brain anatomical regions is the classical approach to identify brain anatomical regions. Manual approaches present several problems related to inconsistencies across different clinicians, time and repeatability. Automated delineation is done by registering brains to one another or to a template. However, when imaging studies contain lesions, there are several intensity abnormalities and location alterations that reduce the performance of most of the registration algorithms based on intensity parameters. Thus, specialists may have to manually interact with imaging studies to select landmarks (called singular points in this PhD) or identify regions of interest. These two solutions have the same inconvenient than manual approaches, mentioned before. Moreover, these registration algorithms do not allow large and distributed deformations. This type of deformations may also appear when a stroke or a traumatic brain injury (TBI) occur. This PhD is focused on the design, development and implementation of a new methodology to automatically identify lesions in anatomical structures. This methodology integrates algorithms whose main objective is to generate objective and reproducible results. It is divided into four stages: pre-processing, singular points identification, registration and lesion detection. Pre-processing stage. In this first stage, the aim is to standardize all input data in order to be able to draw valid conclusions from the results. Therefore, this stage has a direct impact on the final results. It consists of three steps: skull-stripping, spatial and intensity normalization. Singular points identification. This stage aims to automatize the identification of anatomical points (singular points). It involves the manual identification of anatomical points by the clinician. This automatic identification allows to identify a greater number of points which results in more information; to remove the factor associated to inter-subject variability and thus, the results are reproducible and objective; and to eliminate the time spent on manual marking. This PhD proposed an algorithm to automatically identify singular points (descriptor) based on a multi-detector approach. This algorithm contains multi-parametric (spatial and intensity) information. This algorithm has been compared with other similar algorithms found on the state of the art. Registration. The goal of this stage is to put in spatial correspondence two imaging studies of different subjects/patients. The algorithm proposed in this PhD is based on descriptors. Its main objective is to compute a vector field to introduce distributed deformations (changes in different imaging regions), as large as the deformation vector indicates. The proposed algorithm has been compared with other registration algorithms used on different neuroimaging applications which are used with control subjects. The obtained results are promising and they represent a new context for the automatic identification of anatomical structures. Lesion identification. This final stage aims to identify those anatomical structures whose characteristics associated to spatial location and area or volume has been modified with respect to a normal state. A statistical study of the atlas to be used is performed to establish which are the statistical parameters associated to the normal state. The anatomical structures that may be identified depend on the selected anatomical structures identified on the atlas. The proposed methodology is independent from the selected atlas. Overall, this PhD corroborates the investigated research hypotheses regarding the automatic identification of lesions based on structural medical imaging studies (resonance magnetic studies). Based on these foundations, new research fields to improve the automatic identification of lesions in brain injury can be proposed.

A structural view of evolutionary divergence

Two directed evolution experiments on p-nitrobenzyl esterase yielded one enzyme with a 100-fold increased activity in aqueous-organic solvents and another with a 17°C increase in thermostability. Structures of the wild type and its organophilic and thermophilic counterparts are presented at resolutions of 1.5 Å, 1.6 Å, and 2.0 Å, respectively. These structures identify groups of interacting mutations and demonstrate how directed evolution can traverse complex fitness landscapes. Early-generation mutations stabilize flexible loops not visible in the wild-type structure and set the stage for further beneficial mutations in later generations. The mutations exert their influence on the esterase structure over large distances, in a manner that would be difficult to predict. The loops with the largest structural changes generally are not the sites of mutations. Similarly, none of the seven amino acid substitutions in the organophile are in the active site, even though the enzyme experiences significant changes in the organization of this site. In addition to reduction of surface loop flexibility, thermostability in the evolved esterase results from altered core packing, helix stabilization, and the acquisition of surface salt bridges, in agreement with other comparative studies of mesophilic and thermophilic enzymes. Crystallographic analysis of the wild type and its evolved counterparts reveals networks of mutations that collectively reorganize the active site. Interestingly, the changes that led to diversity within the α/β hydrolase enzyme family and the reorganization seen in this study result from main-chain movements.

Structural protein 4.1 is located in mammalian centrosomes

Structural protein 4.1 was first characterized as an important 80-kDa protein in the mature red cell membrane skeleton. It is now known to be a member of a family of protein isoforms detected at diverse intracellular sites in many nucleated mammalian cells. We recently reported that protein 4.1 isoforms are present at interphase in nuclear matrix and are rearranged during the cell cycle. Here we report that protein 4.1 epitopes are present in centrosomes of human and murine cells and are detected by using affinity-purified antibodies specific for 80-kDa red cell 4.1 and for 4.1 peptides. Immunofluorescence, by both conventional and confocal microscopy, showed that protein 4.1 epitopes localized in the pericentriolar region. Protein 4.1 epitopes remained in centrosomes after extraction of cells with detergent, salt, and DNase. Higher resolution electron microscopy of detergent-extracted cell whole mounts showed centrosomal protein 4.1 epitopes distributed along centriolar cylinders and on pericentriolar fibers, at least some of which constitute the filamentous network surrounding each centriole. Double-label electron microscopy showed that protein 4.1 epitopes were predominately localized in regions also occupied by epitopes for centrosome-specific autoimmune serum 5051 but were not found on microtubules. Our results suggest that protein 4.1 is an integral component of centrosome structure, in which it may play an important role in centrosome function during cell division and organization of cellular architecture.

Nucleosomes, linker DNA, and linker histone form a unique structural motif that directs the higher-order folding and compaction of chromatin

The compaction level of arrays of nucleosomes may be understood in terms of the balance between the self-repulsion of DNA (principally linker DNA) and countering factors including the ionic strength and composition of the medium, the highly basic N termini of the core histones, and linker histones. However, the structural principles that come into play during the transition from a loose chain of nucleosomes to a compact 30-nm chromatin fiber have been difficult to establish, and the arrangement of nucleosomes and linker DNA in condensed chromatin fibers has never been fully resolved. Based on images of the solution conformation of native chromatin and fully defined chromatin arrays obtained by electron cryomicroscopy, we report a linker histone-dependent architectural motif beyond the level of the nucleosome core particle that takes the form of a stem-like organization of the entering and exiting linker DNA segments. DNA completes ≈1.7 turns on the histone octamer in the presence and absence of linker histone. When linker histone is present, the two linker DNA segments become juxtaposed ≈8 nm from the nucleosome center and remain apposed for 3–5 nm before diverging. We propose that this stem motif directs the arrangement of nucleosomes and linker DNA within the chromatin fiber, establishing a unique three-dimensional zigzag folding pattern that is conserved during compaction. Such an arrangement with peripherally arranged nucleosomes and internal linker DNA segments is fully consistent with observations in intact nuclei and also allows dramatic changes in compaction level to occur without a concomitant change in topology.

Drosophila coracle, a Member of the Protein 4.1 Superfamily, Has Essential Structural Functions in the Septate Junctions and Developmental Functions in Embryonic and Adult Epithelial Cells

Although extensively studied biochemically, members of the Protein 4.1 superfamily have not been as well characterized genetically. Studies of coracle, a Drosophila Protein 4.1 homologue, provide an opportunity to examine the genetic functions of this gene family. coracle was originally identified as a dominant suppressor of EgfrElp, a hypermorphic form of the Drosophila Epidermal growth factor receptor gene. In this article, we present a phenotypic analysis of coracle, one of the first for a member of the Protein 4.1 superfamily. Screens for new coracle alleles confirm the null coracle phenotype of embryonic lethality and failure in dorsal closure, and they identify additional defects in the embryonic epidermis and salivary glands. Hypomorphic coracle alleles reveal functions in many imaginal tissues. Analysis of coracle mutant cells indicates that Coracle is a necessary structural component of the septate junction required for the maintenance of the transepithelial barrier but is not necessary for apical–basal polarity, epithelial integrity, or cytoskeletal integrity. In addition, coracle phenotypes suggest a specific role in cell signaling events. Finally, complementation analysis provides information regarding the functional organization of Coracle and possibly other Protein 4.1 superfamily members. These studies provide insights into a range of in vivo functions for coracle in developing embryos and adults.