Bifurcation diagrams for polymer blends with diffuse interfaces in confined and adaptive geometries

Dynamics of binary mixtures such as polymer blends, and fluids near the critical point, is described by the model-H, which couples momentum transport and diffusion of the components [1]. We present an extended version of the model-H that allows to study the combined effect of phase separation in a polymer blend and surface structuring of the film itself [2]. We apply it to analyze the stability of vertically stratified base states on extended films of polymer blends and show that convective transport leads to new mechanisms of instability as compared to the simpler diffusive case described by the Cahn- Hilliard model [3, 4]. We carry out this analysis for realistic parameters of polymer blends used in experimental setups such as PS/PVME. However, geometrically more complicated states involving lateral structuring, strong deflections of the free surface, oblique diffuse interfaces, checkerboard modes, or droplets of a component above of the other are possible at critical composition solving the Cahn Hilliard equation in the static limit for rectangular domains [5, 6] or with deformable free surfaces [6]. We extend these results for off-critical compositions, since balanced overall composition in experiments are unusual. In particular, we study steady nonlinear solutions of the Cahn-Hilliard equation for bidimensional layers with fixed geometry and deformable free surface. Furthermore we distinguished the cases with and without energetic bias at the free surface. We present bifurcation diagrams for off-critical films of polymer blends with free surfaces, showing their free energy, and the L2-norms of surface deflection and the concentration field, as a function of lateral domain size and mean composition. Simultaneously, we look at spatial dependent profiles of the height and concentration. To treat the problem of films with arbitrary surface deflections our calculations are based on minimizing the free energy functional at given composition and geometric constraints using a variational approach based on the Cahn-Hilliard equation. The problem is solved numerically using the finite element method (FEM).

MCT1 T1470A polymorphism influences adherence to strength training in overweight and obese men following a weight loss program

The monocarboxylate transporter (MCT) family member MCT1 transports lactate into and out of myocytes. Oxidative cells import lactate through MCT1 as a substrate, being the role of MCT1 in glycolysis-derived lactate efflux less clear. MCT1 T1470A polymorphism (rs1049434), which has been related with lactate metabolism and sports specialty 1, 2, could be an influencing factor for exercise adherence. Therefore the aim of this study was to relate the adherence to different training modalities with the T1470A MCT1 polymorphism in overweight and obese men following a weight loss program (WLP).

A technological framework based on automatic messaging for improving adherence of diabetic patients

En todo el mundo se ha observado un crecimiento exponencial en la incidencia de enfermedades crónicas como la hipertensión y enfermedades cardiovasculares y respiratorias, así como la diabetes mellitus, que causa un número de muertes cada vez mayor en todo el mundo (Beaglehole et al., 2008). En concreto, la prevalencia de diabetes mellitus (DM) está aumentando de manera considerable en todas las edades y representa un serio problema de salud mundial. La diabetes fue la responsable directa de 1,5 millones de muertes en 2012 y 89 millones de años de vida ajustados por discapacidad (AVAD) (OMS, 2014). Uno de los principales dilemas que suelen asociarse a la gestión de EC es la adherencia de los pacientes a los tratamientos, que representa un aspecto multifactorial que necesita asistencia en lo relativo a: educación, autogestión, interacción entre los pacientes y cuidadores y compromiso de los pacientes. Medir la adherencia del tratamiento es complicado y, aunque se ha hablado ampliamente de ello, aún no hay soluciones “de oro” (Reviews, 2002). El compromiso de los pacientes, a través de la participación, colaboración, negociación y a veces del compromiso firme, aumentan las oportunidades para una terapia óptima en la que los pacientes se responsabilizan de su parte en la ecuación de adherencia. Comprometer e involucrar a los pacientes diabéticos en las decisiones de su tratamiento, junto con expertos profesionales, puede ayudar a favorecer un enfoque centrado en el paciente hacia la atención a la diabetes (Martin et al., 2005). La motivación y atribución de poder de los pacientes son quizás los dos factores interventores más relevantes que afectan directamente a la autogestión de la atención a la diabetes. Se ha demostrado que estos dos factores desempeñan un papel fundamental en la adherencia a la prescripción, así como en el fomento exitoso de un estilo de vida sana y otros cambios de conducta (Heneghan et al., 2013). Un plan de educación personalizada es indispensable para proporcionarle al paciente las herramientas adecuadas que necesita para la autogestión efectiva de la enfermedad (El-Gayar et al. 2013). La comunicación efectiva es fundamental para proporcionar una atención centrada en el paciente puesto que influye en las conductas y actitudes hacia un problema de salud ((Frampton et al. 2008). En este sentido, la interactividad, la frecuencia, la temporalización y la adaptación de los mensajes de texto pueden promover la adherencia a un régimen de medicación. Como consecuencia, adaptar los mensajes de texto a los pacientes puede resultar ser una manera de hacer que las sugerencias y la información sean más relevantes y efectivas (Nundy et al. 2013). En este contexto, las tecnologías móviles en el ámbito de la salud (mHealth) están desempeñando un papel importante al conectar con pacientes para mejorar la adherencia a medicamentos recetados (Krishna et al., 2009). La adaptación de los mensajes de texto específicos de diabetes sigue siendo un área de oportunidad para mejorar la adherencia a la medicación y ofrecer motivación a adultos con diabetes. Sin embargo, se necesita más investigación para entender totalmente su eficacia. Los consejos de texto personalizados han demostrado causar un impacto positivo en la atribución de poder a los pacientes, su autogestión y su adherencia a la prescripción (Gatwood et al., 2014). mHealth se puede utilizar para ofrecer programas de asistencia de autogestión a los pacientes con diabetes y, al mismo tiempo, superar las dificultades técnicas y financieras que supone el tratamiento de la diabetes (Free at al., 2013). El objetivo principal de este trabajo de investigación es demostrar que un marco tecnológico basado en las teorías de cambios de conducta, aplicado al campo de la mHealth, permite una mejora de la adherencia al tratamiento en pacientes diabéticos. Como método de definición de una solución tecnológica, se han adoptado un conjunto de diferentes técnicas de conducta validadas denominado marco de compromiso de retroacción conductual (EBF, por sus siglas en inglés) para formular los mensajes, guiar el contenido y evaluar los resultados. Los estudios incorporan elementos del modelo transteórico (TTM, por sus siglas en inglés), la teoría de la fijación de objetivos (GST, por sus siglas en inglés) y los principios de comunicación sanitaria persuasiva y eficaz. Como concepto general, el modelo TTM ayuda a los pacientes a progresar a su próxima fase de conducta a través de mensajes de texto motivados específicos y permite que el médico identifique la fase actual y adapte sus estrategias individualmente. Además, se adoptan las directrices del TTM para fijar objetivos personalizados a un nivel apropiado a la fase de cambio del paciente. La GST encierra normas que van a ponerse en práctica para promover la intervención educativa y objetivos de pérdida de peso. Finalmente, los principios de comunicación sanitaria persuasiva y eficaz aplicados a la aparición de los mensajes se han puesto en marcha para aumentar la efectividad. El EBF tiene como objetivo ayudar a los pacientes a mejorar su adherencia a la prescripción y encaminarlos a una mejora general en la autogestión de la diabetes mediante mensajes de texto personalizados denominados mensajes de retroacción automáticos (AFM, por sus siglas en inglés). Después de una primera revisión del perfil, consistente en identificar características significativas del paciente basadas en las necesidades de tratamiento, actitudes y conductas de atención sanitaria, el sistema elige los AFM personalizados, los aprueba el médico y al final se transfieren a la interfaz del paciente. Durante el tratamiento, el usuario recopila los datos en dispositivos de monitorización de pacientes (PMD, por sus siglas en inglés) de una serie de dispositivos médicos y registros manuales. Los registros consisten en la toma de medicación, dieta y actividad física y tareas de aprendizaje y control de la medida del metabolismo. El compromiso general del paciente se comprueba al estimar el uso del sistema y la adherencia del tratamiento y el estado de los objetivos del paciente a corto y largo plazo. El módulo de análisis conductual, que consiste en una serie de reglas y ecuaciones, calcula la conducta del paciente. Tras lograr el análisis conductual, el módulo de gestión de AFM actualiza la lista de AFM y la configuración de los envíos. Las actualizaciones incluyen el número, el tipo y la frecuencia de mensajes. Los AFM los revisa periódicamente el médico que también participa en el perfeccionamiento del tratamiento, adaptado a la fase transteórica actual. Los AFM se segmentan en distintas categorías y niveles y los pacientes pueden ajustar la entrega del mensaje de acuerdo con sus necesidades personales. El EBF se ha puesto en marcha integrado dentro del sistema METABO, diseñado para facilitar al paciente diabético que controle sus condiciones relevantes de una manera menos intrusiva. El dispositivo del paciente se vincula en una plataforma móvil, mientras que una interfaz de panel médico permite que los profesionales controlen la evolución del tratamiento. Herramientas específicas posibilitan que los profesionales comprueben la adherencia del paciente y actualicen la gestión de envíos de AFM. El EBF fue probado en un proyecto piloto controlado de manera aleatoria. El principal objetivo era examinar la viabilidad y aceptación del sistema. Los objetivos secundarios eran también la evaluación de la eficacia del sistema en lo referente a la mejora de la adherencia, el control glucémico y la calidad de vida. Se reclutaron participantes de cuatro centros clínicos distintos en Europa. La evaluación del punto de referencia incluía datos demográficos, estado de la diabetes, información del perfil, conocimiento de la diabetes en general, uso de las plataformas TIC, opinión y experiencia con dispositivos electrónicos y adopción de buenas prácticas con la diabetes. La aceptación y eficacia de los criterios de evaluación se aplicaron para valorar el funcionamiento del marco tecnológico. El principal objetivo era la valoración de la eficacia del sistema en lo referente a la mejora de la adherencia. En las pruebas participaron 54 pacientes. 26 fueron asignados al grupo de intervención y equipados con tecnología móvil donde estaba instalado el EBF: 14 pacientes tenían T1DM y 12 tenían T2DM. El grupo de control estaba compuesto por 25 pa cientes que fueron tratados con atención estándar, sin el empleo del EBF. La intervención profesional tanto de los grupos de control como de intervención corrió a cargo de 24 cuidadores, entre los que incluían diabetólogos, nutricionistas y enfermeras. Para evaluar la aceptabilidad del sistema y analizar la satisfacción de los usuarios, a través de LimeSurvey, se creó una encuesta multilingüe tanto para los pacientes como para los profesionales. Los resultados también se recopilaron de los archivos de registro generados en los PMD, el panel médico profesional y las entradas de la base de datos. Los mensajes enviados hacia y desde el EBF y los archivos de registro del sistema y los servicios de comunicación se grabaron durante las cinco semanas del estudio. Se entregaron un total de 2795 mensajes, lo que supuso una media de 107,50 mensajes por paciente. Como se muestra, los mensajes disminuyen con el tiempo, indicando una mejora global de la adherencia al plan de tratamiento. Como se esperaba, los pacientes con T1DM recibieron más consejos a corto plazo, en relación a su estado. Del mismo modo, al ser el centro de T2DM en cambios de estilo de vida sostenible a largo plazo, los pacientes con T2DM recibieron más consejos de recomendación, en cuanto a dietas y actividad física. También se ha llevado a cabo una comparación de la adherencia e índices de uso para pacientes con T1DM y T2DM, entre la primera y la segunda mitad de la prueba. Se han observado resultados favorables para el uso. En lo relativo a la adherencia, los resultados denotaron una mejora general en cada dimensión del plan de tratamiento, como la nutrición y las mediciones de inserción de glucosa en la sangre. Se han llevado a cabo más estudios acerca del cambio a nivel educativo antes y después de la prueba, medidos tanto para grupos de control como de intervención. Los resultados indicaron que el grupo de intervención había mejorado su nivel de conocimientos mientras que el grupo de control mostró una leve disminución. El análisis de correlación entre el nivel de adherencia y las AFM ha mostrado una mejora en la adherencia de uso para los pacientes que recibieron los mensajes de tipo alertas, y unos resultados no significativos aunque positivos relacionados con la adherencia tanto al tratamiento que al uso correlacionado con los recordatorios. Por otra parte, los AFM parecían ayudar a los pacientes que no tomaban suficientemente en serio su tratamiento en el principio y que sí estaban dispuestos a responder a los mensajes recibidos. Aun así, los pacientes que recibieron demasiadas advertencias, comenzaron a considerar el envío de mensajes un poco estresante. El trabajo de investigación llevado a cabo al desarrollar este proyecto ofrece respuestas a las cuatro hipótesis de investigación que fueron la motivación para el trabajo. • Hipótesis 1 : es posible definir una serie de criterios para medir la adherencia en pacientes diabéticos. • Hipótesis 2: es posible diseñar un marco tecnológico basado en los criterios y teorías de cambio de conducta mencionados con anterioridad para hacer que los pacientes diabéticos se comprometan a controlar su enfermedad y adherirse a planes de atención. • Hipótesis 3: es posible poner en marcha el marco tecnológico en el sector de la salud móvil. • Hipótesis 4: es posible utilizar el marco tecnológico como solución de salud móvil en un contexto real y tener efectos positivos en lo referente a indicadores de control de diabetes. La verificación de cada hipótesis permite ofrecer respuesta a la hipótesis principal: La hipótesis principal es: es posible mejorar la adherencia diabética a través de un marco tecnológico mHealth basado en teorías de cambio de conducta. El trabajo llevado a cabo para responder estas preguntas se explica en este trabajo de investigación. El marco fue desarrollado y puesto en práctica en el Proyecto METABO. METABO es un Proyecto I+D, cofinanciado por la Comisión Europea (METABO 2008) que integra infraestructura móvil para ayudar al control, gestión y tratamiento de los pacientes con diabetes mellitus de tipo 1 (T1DM) y los que padecen diabetes mellitus de tipo 2 (T2DM). ABSTRACT Worldwide there is an exponential growth in the incidence of Chronic Diseases (CDs), such as: hypertension, cardiovascular and respiratory diseases, as well as diabetes mellitus, leading to rising numbers of deaths worldwide (Beaglehole et al. 2008). In particular, the prevalence of diabetes mellitus (DM) is largely increasing among all ages and constitutes a major worldwide health problem. Diabetes was directly responsible for 1,5 million deaths in 2012 and 89 million Disability-adjusted life year (DALYs) (WHO 2014). One of the key dilemmas often associated to CD management is the patients’ adherence to treatments, representing a multi-factorial aspect that requires support in terms of: education, self-management, interaction between patients and caregivers, and patients’ engagement. Measuring adherence is complex and, even if widely discussed, there are still no “gold” standards ((Giardini et al. 2015), (Costa et al. 2015). Patient’s engagement, through participation, collaboration, negotiation, and sometimes compromise, enhance opportunities for optimal therapy in which patients take responsibility for their part of the adherence equation. Engaging and involving diabetic patients in treatment decisions, along with professional expertise, can help foster a patient-centered approach to diabetes care (Martin et al. 2005). Patients’ motivation and empowerment are perhaps the two most relevant intervening factors that directly affect self-management of diabetes care. It has been demonstrated that these two factors play an essential role in prescription adherence, as well as for the successful encouragement of a healthy life-style and other behavioural changes (Heneghan et al. 2013). A personalised education plan is indispensable in order to provide the patient with the appropriate tools needed for the effective self-management of the disease (El-Gayar et al. 2013). Effective communication is at the core of providing patient-centred care since it influences behaviours and attitudes towards a health problem (Frampton et al. 2008). In this regard, interactivity, frequency, timing, and tailoring of text messages may promote adherence to a medication regimen. As a consequence, tailoring text messages to patients can constitute a way of making suggestions and information more relevant and effective (Nundy et al. 2013). In this context, mobile health technologies (mHealth) are playing significant roles in improving adherence to prescribed medications (Krishna et al. 2009). The tailoring of diabetes-specific text messages remains an area of opportunity to improve medication adherence and provide motivation to adults with diabetes but further research is needed to fully understand their effectiveness. Personalized text advices have proven to produce a positive impact on patients’ empowerment, self-management, and adherence to prescriptions (Gatwood et al. 2014). mHealth can be used for offering self-management support programs to diabetes patients and at the same time surmounting the technical and financial difficulties involved in diabetes treatment (Free et al. 2013). The main objective of this research work is to demonstrate that a technological framework, based on behavioural change theories, applied to mHealth domain, allows improving adherence treatment in diabetic patients. The framework, named Engagement Behavioural Feedback Framework (EBF), is built on top of validated behavioural techniques to frame messages, guide the definition of contents and assess outcomes: elements from the Transtheoretical Model (TTM), the Goal-Setting Theory (GST), Effective Health Communication (EHC) guidelines and Principles of Persuasive Technology (PPT) were incorporated. The TTM helps patients to progress to a next behavioural stage, through specific motivated text messages, and allow clinician’s identifying the current stage and tailor its strategies individually. Moreover, TTM guidelines are adopted to set customised goals at a level appropriate to the patient’s stage of change. The GST was used to build rules to be applied for enhancing educational intervention and weight loss objectives. Finally, the EHC guidelines and the PPT were applied to increase the effectiveness of messages. The EBF aims to support patients on improving their prescription adherence and persuade them towards a general improvement in diabetes self-management, by means of personalised text messages, named Automatic Feedback Messages (AFM). After a first profile screening, consisting in identifying meaningful patient characteristics based on treatment needs, attitudes and health care behaviours, customised AFMs are selected by the system, approved by the professional, and finally transferred into the patient interface. During the treatment, the user collects the data into a Patient Monitoring Device (PMD) from a set of medical devices and from manual inputs. Inputs consist in medication intake, diet and physical activity, metabolic measurement monitoring and learning tasks. Patient general engagement is checked by estimating the usage of the system and the adherence of treatment and patient goals status in the short and the long term period. The Behavioural Analysis Module, consisting in a set of rules and equations, calculates the patient’s behaviour. After behavioural analysis is accomplished, the AFM library and the dispatch setting are updated by the AFM Manager module. Updates include the number, the type and the frequency of messages. The AFMs are periodically supervised by the professional who also participates to the refinement of the treatment, adapted to the current transtheoretical stage. The AFMs are segmented in different categories and levels and patients can adjust message delivery in accordance with their personal needs. The EBF was integrated to the METABO system, designed to facilitate diabetic patients in managing their disease in a less intrusive approach. Patient device corresponds in a mobile platform, while a medical panel interface allows professionals to monitoring the treatment evolution. Specific tools allow professional to check patient adherence and to update the AFMs dispatch management. The EBF was tested in a randomised controlled pilot. The main objective was to examine the feasibility and acceptance of the system. Secondary objectives were also the assessment of the effectiveness of system in terms of adherence improvement, glycaemic control, and quality of life. Participants were recruited from four different clinical centres in Europe. The baseline assessment included demographics, diabetes status, profile information, knowledge about diabetes in general, usage of ICT platforms, opinion and experience about electronic devices and adoption of good practices with diabetes. Acceptance and the effectiveness evaluation criteria were applied to evaluate the performance of the technological framework. The main objective was the assessment of the effectiveness of system in terms of adherence improvement. Fifty-four patients participated on the trials. Twenty-six patients were assigned in the intervention group and equipped with mobile where the EBF was installed: 14 patients were T1DM and 12 were T2DM. The control group was composed of 25 patients that were treated through a standard care, without the usage of the EBF. Professional’s intervention for both intervention and control groups was carried out by 24 care providers, including endocrinologists, nutritionists, and nurses. In order to evaluate the system acceptability and analyse the users’ satisfaction, an online multi-language survey, using LimeSurvey, was produced for both patients and professionals. Results were also collected from the log-files generated in the PMDs, the professional medical panel and the entries of the data base. The messages sent to and from the EBF and the log-files of the system and communication services were recorded over 5 weeks of the study. A total of 2795 messages were submitted, representing an average of 107,50 messages per patient. As demonstrated, messages decrease over time indicating an overall improvement of the care plan’s adherence. As expected, T1DM patients were more loaded with short-term advices, in accordance with their condition. Similarly, being the focus of T2DM on long-term sustainable lifestyle changes, T2DM received more reminders advices, as for diet and physical activity. Favourable outcomes were observed for treatment and usage adherences of the intervention group: for both the adherence indices, results denoted a general improvement on each care plan’s dimension, such as on nutrition and blood glucose input measurements. Further studies were conducted on the change on educational level before and after the trial, measured for both control and intervention groups. The outcomes indicated the intervention group has improved its level of knowledge, while the control group denoted a low decrease. The correlation analysis between the level of adherences and the AFMs showed an improvement in usage adherence for patients who received warnings message, while non-significantly yet even positive indicators related to both treatment and usage adherence correlated with the Reminders. Moreover, the AFMs seemed to help those patients who did not take their treatment seriously enough in the beginning and who were willing to respond to the messages they received. Even though, patients who received too many Warnings, started to consider the message dispatch to be a bit stressful. The research work carried out in developing this research work provides responses to the four research hypothesis that were the motivation for the work: •Hypothesis 1: It is possible to define a set of criteria to measure adherence in diabetic patients. •Hypothesis 2: It is possible to design a technological framework, based on the aforementioned criteria and behavioural change theories, to engage diabetic patients in managing their disease and adhere to care plans. •Hypothesis 3: It is possible to implement the technological framework in the mobile health domain. •Hypothesis 4: It is possible to use the technological framework as a mobile health solution in a real context and have positive effects in terms of diabetes management indicators. The verification of each hypothesis allowed us to provide a response to the main hypothesis: The Main Hypothesis is: It is possible to improve diabetic adherence through a mHealth technological framework based on behavioural change theories. The work carried out to answer these questions is explained in this research work. The framework was developed and applied in the METABO project. METABO is an R&D project, co-funded by the European Commission (METABO 2008) that integrates mobile infrastructure for supporting the monitoring, management, and treatment of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) patients.

A conserved residue in the tip proteins of CS1 and CFA/I pili of enterotoxigenic Escherichia coli that is essential for adherence

Enterotoxigenic Escherichia coli associated with human diarrheal disease utilize any of a limited group of serologically distinguishable pili for attachment to intestinal cells. These include CS1 and CFA/I pili. We show here that chemical modification of arginyl residues in CS1 pili abolishes CS1-mediated agglutination of bovine erythrocytes, which serves as a model system for attachment. Alanine substitution of the single arginyl residue in CooA, the major pilin, had no effect on the assembly of pili or on hemagglutination. In contrast, substitution of alanine for R181 in CooD, the minor pilin associated with the pilus tip, abolished hemagglutination, and substitution of R20 reduced hemagglutination. Neither of these substitutions affected CS1 pilus assembly. This shows that CooD is essential for CS1-mediated attachment and identifies specific residues that are involved in receptor binding but not in pilus assembly. In addition to mediating agglutination of bovine erythrocytes, CFA/I also mediates agglutination of human erythrocytes. Substitution of R181 by alanine in the CooD homolog, CfaE, abolished both of these reactions. We conclude that the same region of the pilus tip protein is involved in adherence of CS1 and CFA/I pili, although their receptor specificities differ. This suggests that the region of the pilus tip adhesin protein that includes R181 might be an appropriate target for therapeutic intervention or for a vaccine to protect against human diarrhea caused by enterotoxigenic E. coli strains that have serologically different pili.

Effectiveness and Content Analysis of Interventions to Enhance Oral Antidiabetic Drug Adherence in Adults with Type 2 Diabetes : Systematic Review and Meta-Analysis

Peer reviewed

Lipoxin A4 stable analogs inhibit leukocyte rolling and adherence in the rat mesenteric microvasculature: Role of P-selectin

Three different stable lipoxin A4 (LXA4) analogs (i.e., 16-phenoxy-LXA4-Me, 15-cyclohexyl-LXA4-Me, and 15-R/S-methyl-LXA4-Me) were studied for their ability to modulate leukocyte-endothelial cell interactions in the rat mesenteric microvasculature. Superfusion of the rat mesentery with 50 μmol/liter NG-nitro-l-arginine methyl ester (l-NAME) caused a significant, time-dependent increase in leukocyte rolling (56 ± 8 cells/min; P < 0.01 vs. control) and leukocyte adherence (12.5 ± 1.2 cells/100 μm length of venule; P < 0.01 vs. control) after 120 min of superfusion. Concomitant superfusion of the rat mesentery with 10 nmol/liter of each of three lipoxin analogs consistently and markedly attenuated l-NAME-induced leukocyte rolling to 10 ± 4 (P < 0.01), 4 ± 1 (P < 0.01), and 32 ± 7 (P < 0.05) cells/min, and adherence to 4 ± 0.8 (P < 0.01), 1.1 ± 0.4 (P < 0.01), and 7 ± 0.7 (P < 0.05) cells/100 μm length of venule (16-phenoxy-LXA4-Me, 15-cyclohexyl-LXA4-Me, and 15-R/S- methyl-LXA4-Me, respectively). No alterations of systemic blood pressure or mesenteric venular shear rates were observed in any group. Immunohistochemical up-regulation of P-selectin expression on intestinal venular endothelium was significantly increased (P < 0.01) after exposure to l-NAME, and this was significantly attenuated by these lipoxin analogs (P < 0.01). Thus, in vivo superfusion of the rat mesentery with stable lipoxin analogs at 10 nmol/liter reduces l-NAME-induced leukocyte rolling and adherence in the mesenteric rat microvasculature by attenuating P-selectin expression. This anti-inflammatory mechanism may represent a novel and potent regulatory action of lipoxins on the immune system.

Regulation of Adherence and Virulence by the Entamoeba histolytica Lectin Cytoplasmic Domain, Which Contains a β2 Integrin Motif

Killing of human cells by the parasite Entamoeba histolytica requires adherence via an amebic cell surface lectin. Lectin activity in the parasite is regulated by inside-out signaling. The lectin cytoplasmic domain has sequence identity with a region of the β2 integrin cytoplasmic tail implicated in regulation of integrin-mediated adhesion. Intracellular expression of a fusion protein containing the cytoplasmic domain of the lectin has a dominant negative effect on extracellular lectin-mediated cell adherence. Mutation of the integrin-like sequence abrogates the dominant negative effect. Amebae expressing the dominant negative mutant are less virulent in an animal model of amebiasis. These results suggest that inside-out signaling via the lectin cytoplasmic domain may control the extracellular adhesive activity of the amebic lectin and provide in vivo demonstration of the lectin’s role in virulence.

Ongoing immunoglobulin somatic mutation in germinal center B cell-like but not in activated B cell-like diffuse large cell lymphomas

B cell diffuse large cell lymphoma (B-DLCL) is a heterogeneous group of tumors, based on significant variations in morphology, clinical presentation, and response to treatment. Gene expression profiling has revealed two distinct tumor subtypes of B-DLCL: germinal center B cell-like DLCL and activated B cell-like DLCL. In a separate study, we determined that B-DLCL can also be subdivided into two groups based on the presence or absence of ongoing Ig gene hypermutation. Here, we evaluated the correlation between these B-DLCL subtypes established by the two different methods. Fourteen primary B-DLCL cases were studied by gene expression profiling using DNA microarrays and for the presence of ongoing mutations in their Ig heavy chain gene. All seven cases classified as germinal center B cell-like DLCL by gene expression showed the presence of ongoing mutations in the Ig genes. Five of the seven cases classified by gene expression as activated B cell-like DLCL had no ongoing somatic mutations, whereas, in the remaining two cases, a single point mutation was observed in only 2 of 15 and 21 examined molecular clones of variable heavy (VH) chain gene, respectively. These two cases were distantly related to the rest of the activated B cell-like DLCL tumors by gene expression. Our findings validate the concept that lymphoid malignancies are derived from cells at discrete stages of normal lymphocyte maturation and that the malignant cells retain the genetic program of those normal cells.

Visualization of Cavitated Vessels in Winter and Refilled Vessels in Spring in Diffuse-Porous Trees by Cryo-Scanning Electron Microscopy1

Xylem cavitation in winter and recovery from cavitation in the spring were visualized in two species of diffuse-porous trees, Betula platyphylla var. japonica Hara and Salix sachalinensis Fr. Schm., by cryo-scanning electron microscopy after freeze-fixation of living twigs. Water in the vessel lumina of the outer three annual rings of twigs of B. platyphylla var. japonica and of S. sachalinensis gradually disappeared during the period from January to March, an indication that cavitation occurs gradually in these species during the winter. In April, when no leaves had yet expanded, the lumina of most of the vessels of both species were filled with water. Many vessel lumina in twigs of both species were filled with water during the period from the subsequent growth season to the beginning of the next winter. These observations indicate that recovery in spring occurs before the onset of transpiration and that water transport through twigs occurs during the subsequent growing season. We found, moreover, that vessels repeat an annual cycle of winter cavitation and spring recovery from cavitation for several years until irreversible cavitation occurs.

Cellular adherence elicits ligand-independent activation of the Met cell-surface receptor.

Cell adhesion has a fundamental role in the proliferation and motility of normal cells and the metastasis of tumor cells. To identify signaling pathways activated by the adherence of tumor cells, we analyzed the tyrosine phosphorylation of proteins in mouse melanoma cells before and after attachment to substrata. We discovered that cellular adherence activated the protein-tyrosine kinase of the cell surface receptor Met, whose ligand is hepatocyte growth factor and scatter factor. The activation was exceedingly prompt, affected the great majority of Met in the cells, persisted so long as the cells remained adherent, and was rapidly reversed as soon as the cells were detached from substrata. Activation of Met required that cells be adherent but not that they spread on the substratum, and it occurred in the absence of any apparent ligand for the receptor. Ligand-independent activation of Met occurred in several varieties of tumor cells but not in normal endothelial cells that express the receptor. The activation of Met described here may represent a means by which cells respond to mechanical as opposed to biochemical stimuli.

Deregulation of PAX-5 by translocation of the Emu enhancer of the IgH locus adjacent to two alternative PAX-5 promoters in a diffuse large-cell lymphoma.

Analyses of the human PAX-5 locus and of the 5' region of the mouse Pax-5 gene revealed that transcription from two distinct promoters results in splicing of two alternative 5' exons to the common coding sequences of exons 2-10. Transcription from the upstream promoter initiates downstream of a TATA box and occurs predominantly in B-lymphocytes, whereas the TATA-less downstream promoter is active in all Pax-5-expressing tissues. The human PAX-5 gene is located on chromosome 9 in region p13, which is involved in t(9;14)(pl3;q32) translocations recurring in small lymphocytic lymphomas of the plasmacytoid subtype and in derived large-cell lymphomas. A previous molecular analysis of a t(9;14) breakpoint from a diffuse large-cell lymphoma (KIS-1) demonstrated that the immunoglobulin heavy-chain (IgH) locus on 14q32 was juxtaposed to chromosome 9p13 sequences of unknown function [Ohno, H., Furukawa, T., Fukuhara, S., Zong, S. Q., Kamesaki, H., Shows, T. B., Le Beau, M. M., McKeithan, T. W., Kawakami, T. & Honjo, T. (1990) Proc. Natl. Acad. Sci. USA 87,628-632]. Here we show that the KIS-1 translocation breakpoint is located 1807 base pairs upstream of exon 1A of PAX-5, thus bringing the potent Emu enhancer of the IgH gene into close proximity of the PAX-5 promoters. These data suggest that deregulation of PAX-5 gene transcription by the t(9;14)(pl3;q32) translocation contributes to the pathogenesis of small lymphocytic lymphomas with plasmacytoid differentiation.

Plasmodium falciparum erythrocyte membrane protein 1 is a parasitized erythrocyte receptor for adherence to CD36, thrombospondin, and intercellular adhesion molecule 1.

Adherence of mature Plasmodium falciparum parasitized erythrocytes (PRBCs) to microvascular endothelium contributes directly to acute malaria pathology. We affinity purified molecules from detergent extracts of surface-radioiodinated PRBCs using several endothelial cell receptors known to support PRBC adherence, including CD36, thrombospondin (TSP), and intercellular adhesion molecule 1 (ICAM-1). All three host receptors affinity purified P. falciparum erythrocyte membrane protein 1 (PfEMP1), a very large malarial protein expressed on the surface of adherent PRBCs. Binding of PfEMP1 to particular host cell receptors correlated with the binding phenotype of the PRBCs from which PfEMP1 was extracted. Preadsorption of PRBC extracts with anti-PfEMP1 antibodies, CD36, or TSP markedly reduced PfEMP1 binding to CD36 or TSP. Mild trypsinization of intact PRBCs of P. falciparum strains shown to express antigenically different PfEMP1 released different (125)I-labeled tryptic fragments of PfEMP1 that bound specifically to CD36 and TSP. In clone C5 and strain MC, these activities resided on different tryptic fragments, but a single tryptic fragment from clone ItG-ICAM bound to both CD36 and TSP. Hence, the CD36- and TSP-binding domains are distinct entities located on a single PfEMP1 molecule. PfEMP1, the malarial variant antigen on infected erythrocytes, is therefore a receptor for CD36, TSP, and ICAM-1. A therapeutic approach to block or reverse adherence of PRBCs to host cell receptors can now be pursued with the identification of PfEMP1 as a malarial receptor for PRBC adherence to host proteins.