Association between cerebral oxygen metabolic rate and the incidence of nosocomial pneumonia in head injury patients

The development of nosocomial pneumonia was monitored in 96 head-trauma patients requiring mechanical ventilation for up to 10 days. Pneumonia occurred in 28 patients (29.2%) or 53.9 cases per 1,000 admission days. The incidence of nosocomial pneumonia was negatively correlated with cerebral oxygen metabolic rate (CMRO$\sb2$) measured during the first five days. The relative risk of nosocomial pneumonia for patients with CMRO$\sb2$ less than 0.6 umol/gm/min is 2.08 (1.09$-$3.98) times those patients with CMRO$\sb2$ greater than 0.6 umol/gm/min. The association between cerebral oxygen metabolic rate and nosocomial pneumonia was not affected by adjustment of potential confounding factors including age, cimetidine and other infections. These findings provide evidences underlying the CNS-immune system interaction. ^

Potential role of statins as immunomodulators in pneumococcal pneumonia

Background: Mortality in pneumococcal pneumonia remains as high as 20%, and most deaths occur within the first two weeks of hospitalization despite eradication of the causative organisms by antimicrobials in the first 24 hours. An inflammatory response rather than active infection could be responsible for this early mortality. Statins have been shown to have potent immunomodulatory activity in vitro. We investigated whether there was decreased severity or improved outcome in patients who were receiving statins at the time they were admitted for pneumococcal pneumonia. ^ Methods: Patients seen at the Michael E. DeBakey Veterans Affairs Medical Center in Houston, Texas from January, 2000 to June, 2010 with a diagnosis of pneumococcal pneumonia were included in this retrospective cohort study. Electronic medical records were reviewed to record demographic characteristics, comorbidities, laboratory values and statin use at the time of admission. Severity of pneumonia was determined using the Pneumonia Outcomes Research Team (PORT) classification. Uni- and multivariate Cox regression was used to evaluate survival. We adjusted for all variables in the multivariate model if they were significant in the univariate model at p<0.05. ^ Results: Of 347 patients admitted for pneumococcal pneumonia, 90 (25.9%) were taking statins at the time of presentation. Patients in the statin group were older (age: 68.0±9.7 vs. 62.5±12.3 years, p<0.001) and had higher prevalence of diabetes, coronary artery disease and kidney disease (p<0.05 for each comparison). Liver disease and alcohol consumption were less prevalent among statin users (p<0.05). The PORT scores were normally distributed in both groups with statin users having higher mean scores at admission as compared to patients not on statins (108±32 vs. 96±32, p = 0.002). The Cox proportional hazard analyses, adjusted for age, comorbidities, length of stay and PORT scores, showed a significantly reduced risk of mortality among statin users at 14 days (HR: 0.39; 0.15-0.98, p=0.045), 20 days (0.35; 0.14- 0.88, p=0.03) and 30 days(0.41; 0.17-0.95, p=0.01) after presentation. ^ Conclusion: Statin use is associated with improved clinical outcomes in patients with pneumococcal pneumonia.^

The incidence of necrotizing changes in adults with pneumococcal pneumonia

Background. Necrotizing pneumonia is generally considered a rare complication of pneumococcal pneumonia in adults. We systematically studied the incidence of necrotizing changes in adult patients with pneumococcal pneumonia, and examined the severity of infection, the role of causative serotype and the association with bacteremia. ^ Methods. We used a data base of all pneumococcal infections identified at our medical center between 2000 and 2010. Original readings of chest X-rays (CXR) and computerized tomography (CT) were noted. All images were then reread independently by 2 radiologists. The severity of disease was assessed using the SMART-COP scoring system. ^ Results. There were 351 cases of pneumococcal pneumonia. Necrosis was reported in no original CXR readings and 6 of 136 (4.4%) CTs. With re-reading, 8 of 351 (2.3%) CXR and 15 of 136 (11.0%) CT had necrotizing changes. Overall, these changes were found in 23 of 351 (6.6%, 95% CI 4.0 - 9.1) patients. The incidence of bacteremia and the admitting SMART-COP scores were similar in patients with and without necrosis (P=1.00 and P=0.32, respectively). Type 3 pneumococcus was more commonly isolated from patients with than from patients without necrotizing pneumonia (P=0.05), but a total of 10 serotypes were identified among 16 cases in which the organism was available for typing. ^ Conclusions. Necrotizing changes in the lungs were seen in 6.6% (95% CI 4.0 - 9.1) of a large series of adults with pneumococcal pneumonia. Patients with necrosis were not more likely to have bacteremia or more severe disease. Type 3 pneumococcus was commonly implicated, but 9 other serotypes were also identified.^

Risk factors of pneumonia in traumatic spinal-cord-injured patients

Pneumonia is a well-documented and common respiratory infection in patients with acute traumatic spinal cord injuries, and may recur during the course of acute care. Using data from the North American Clinical Trials Network (NACTN) for Spinal Cord Injury, the incidence, timing, and recurrence of pneumonia were analyzed. The two main objectives were (1) to investigate the time and potential risk factors for the first occurrence of pneumonia using the Cox Proportional Hazards model, and (2) to investigate pneumonia recurrence and its risk factors using a Counting Process model that is a generalization of the Cox Proportional Hazards model. The results from survival analysis suggested that surgery, intubation, American Spinal Injury Association (ASIA) grade, direct admission to a NACTN site and age (older than 65 or not) were significant risks for first event of pneumonia and multiple events of pneumonia. The significance of this research is that it has the potential to identify patients at the time of admission who are at high risk for the incidence and recurrence of pneumonia. Knowledge and the time of occurrence of pneumonias are important factors for the development of prevention strategies and may also provide some insights into the selection of emerging therapies that compromise the immune system. ^

A combined measure for quantifying and qualifying the topology preservation of growing self-organizing maps

The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map

Self-organizing Routing Algorithm fo Wireless Sensors Networks (WSN) using Ant Colony Optimization (ACO) with Tinyos.

This paper describes the basic tools to work with wireless sensors. TinyOShas a componentbased architecture which enables rapid innovation and implementation while minimizing code size as required by the severe memory constraints inherent in sensor networks. TinyOS's component library includes network protocols, distributed services, sensor drivers, and data acquisition tools ? all of which can be used asia or be further refined for a custom application. TinyOS was originally developed as a research project at the University of California Berkeley, but has since grown to have an international community of developers and users. Some algorithms concerning packet routing are shown. Incar entertainment systems can be based on wireless sensors in order to obtain information from Internet, but routing protocols must be implemented in order to avoid bottleneck problems. Ant Colony algorithms are really useful in such cases, therefore they can be embedded into the sensors to perform such routing task.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Utzon and the sun path as an organizing element of life in a house

The present text intends to analyze the hypothesis stating that the path of the sun can be an organizing element for how you live in the houses designed by Jørn Utzon. To do so, I have selected twenty houses and building complexes designed by him between the years 1950-94, in Denmark, Sweden, The United Kingdom and Spain. In these projects I will look for elements which are repeated and their possible meaning. The aim is to reach practical conclusions that could help us decide how to orientate a house.

Detecting false testimonies in reputation systems using self-organizing maps

It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

Self-Organizing Architectural design based on Morphogenetic Programming.

In this paper, we present our research into self-organizing building algorithms. This idea of self-organization of animal/plants behaviour interests researchers to explore the mechanisms required for this emergent phenomena and try to apply them in other domains. We were able to implement a typical construction algorithm in a 3D simulation environment and reproduce the results of previous research in the area. LSystems, morphogenetic programming and wasp nest building are explained in order to understand self-organizing models. We proposed Grammatical swarm as a good tool to optimize building structures.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.