Discovering complex interrelationships between socioeconomic status and health in Europe: A case study applying Bayesian Networks

Studies assume that socioeconomic status determines individuals’ states of health, but how does health determine socioeconomic status? And how does this association vary depending on contextual differences? To answer this question, our study uses an additive Bayesian Networks model to explain the interrelationships between health and socioeconomic determinants using complex and messy data. This model has been used to find the most probable structure in a network to describe the interdependence of these factors in five European welfare state regimes. The advantage of this study is that it offers a specific picture to describe the complex interrelationship between socioeconomic determinants and health, producing a network that is controlled by socio demographic factors such as gender and age. The present work provides a general framework to describe and understand the complex association between socioeconomic determinants and health.

Influence of laparoscopy and laparotomy on gasometry, leukocytes and cytokines in a rat abdominal sepsis model

Laparoscopic surgery is associated with reduced surgical trauma, and less acute phase response, as compared with open surgery. Cytokines are important regulators of the biological response to surgical and anesthetic stress. The aim of this study was to determine if CO2 pneumoperitoneum would change cytokine expression, gas parameters and leukocyte count in septic rats. Methods: Wistar rats were randomly assigned to five groups: control (anesthesia only), laparotomy, CO2 pneumoperitoneum, cecum ligation and puncture by laparotomy, and laparoscopic cecum ligation and puncture. After 30 min of the procedures, arterial blood samples were obtained to determine leukocytes subpopulations by hemocytometer. TNFα, IL-1β, IL-6 were determined in intraperitoneal fluid (by ELISA). Gas parameters were measured on arterial blood, intraperitoneal and subperitoneal exsudates. Results: Peritoneal TNFα, IL-1β and IL-6 concentrations were lower in pneumoperitoneum rats than in all other groups (p<0.05). TNFα, IL-1β and IL-6 expression was lower in the laparoscopic than in laparotomic sepsis (p<0.05). Rats from laparoscopic cecum ligation and puncture group developed significant hypercarbic acidosis in blood and subperitoneal fluid when compared to open procedure group. Total white blood cells and lymphocytes were significantly lower in laparoscopic cecum ligation and puncture rats than in the laparotomic (p<0.01). Nevertheless, the laparotomic cecum ligation rats had a significant increase in blood neutrophils and eosinophils when compared with controls (p<0.05). Conclusions: This study demonstrates that the CO2 pneumoperitoneum reduced the inflammatory response in an animal model of peritonitis with respect to intraperitoneal cytokines, white blood cell count and clinical correlates of sepsis. The pneumoperitoneum produced hypercarbic acidosis in septic animals

Bayesian nonparametric latent variable models

L’un des problèmes importants en apprentissage automatique est de déterminer la complexité du modèle à apprendre. Une trop grande complexité mène au surapprentissage, ce qui correspond à trouver des structures qui n’existent pas réellement dans les données, tandis qu’une trop faible complexité mène au sous-apprentissage, c’est-à-dire que l’expressivité du modèle est insuffisante pour capturer l’ensemble des structures présentes dans les données. Pour certains modèles probabilistes, la complexité du modèle se traduit par l’introduction d’une ou plusieurs variables cachées dont le rôle est d’expliquer le processus génératif des données. Il existe diverses approches permettant d’identifier le nombre approprié de variables cachées d’un modèle. Cette thèse s’intéresse aux méthodes Bayésiennes nonparamétriques permettant de déterminer le nombre de variables cachées à utiliser ainsi que leur dimensionnalité. La popularisation des statistiques Bayésiennes nonparamétriques au sein de la communauté de l’apprentissage automatique est assez récente. Leur principal attrait vient du fait qu’elles offrent des modèles hautement flexibles et dont la complexité s’ajuste proportionnellement à la quantité de données disponibles. Au cours des dernières années, la recherche sur les méthodes d’apprentissage Bayésiennes nonparamétriques a porté sur trois aspects principaux : la construction de nouveaux modèles, le développement d’algorithmes d’inférence et les applications. Cette thèse présente nos contributions à ces trois sujets de recherches dans le contexte d’apprentissage de modèles à variables cachées. Dans un premier temps, nous introduisons le Pitman-Yor process mixture of Gaussians, un modèle permettant l’apprentissage de mélanges infinis de Gaussiennes. Nous présentons aussi un algorithme d’inférence permettant de découvrir les composantes cachées du modèle que nous évaluons sur deux applications concrètes de robotique. Nos résultats démontrent que l’approche proposée surpasse en performance et en flexibilité les approches classiques d’apprentissage. Dans un deuxième temps, nous proposons l’extended cascading Indian buffet process, un modèle servant de distribution de probabilité a priori sur l’espace des graphes dirigés acycliques. Dans le contexte de réseaux Bayésien, ce prior permet d’identifier à la fois la présence de variables cachées et la structure du réseau parmi celles-ci. Un algorithme d’inférence Monte Carlo par chaîne de Markov est utilisé pour l’évaluation sur des problèmes d’identification de structures et d’estimation de densités. Dans un dernier temps, nous proposons le Indian chefs process, un modèle plus général que l’extended cascading Indian buffet process servant à l’apprentissage de graphes et d’ordres. L’avantage du nouveau modèle est qu’il admet les connections entres les variables observables et qu’il prend en compte l’ordre des variables. Nous présentons un algorithme d’inférence Monte Carlo par chaîne de Markov avec saut réversible permettant l’apprentissage conjoint de graphes et d’ordres. L’évaluation est faite sur des problèmes d’estimations de densité et de test d’indépendance. Ce modèle est le premier modèle Bayésien nonparamétrique permettant d’apprendre des réseaux Bayésiens disposant d’une structure complètement arbitraire.

A New Mouse Model That Spontaneously Develops Chronic Liver Inflammation and Fibrosis

Here we characterize a new animal model that spontaneously develops chronic inflammation and fibrosis in multiple organs, the non-obese diabetic inflammation and fibrosis (N-IF) mouse. In the liver, the N-IF mouse displays inflammation and fibrosis particularly evident around portal tracts and central veins and accompanied with evidence of abnormal intrahepatic bile ducts. The extensive cellular infiltration consists mainly of macrophages, granulocytes, particularly eosinophils, and mast cells. This inflammatory syndrome is mediated by a transgenic population of natural killer T cells (NKT) induced in an immunodeficient NOD genetic background. The disease is transferrable to immunodeficient recipients, while polyclonal T cells from unaffected syngeneic donors can inhibit the disease phenotype. Because of the fibrotic component, early on-set, spontaneous nature and reproducibility, this novel mouse model provides a unique tool to gain further insight into the underlying mechanisms mediating transformation of chronic inflammation into fibrosis and to evaluate intervention protocols for treating conditions of fibrotic disorders.

Influence of laparoscopy and laparotomy on gasometry, leukocytes and cytokines in a rat abdominal sepsis model

Laparoscopic surgery is associated with reduced surgical trauma, and less acute phase response, as compared with open surgery. Cytokines are important regulators of the biological response to surgical and anesthetic stress. The aim of this study was to determine if CO2 pneumoperitoneum would change cytokine expression, gas parameters and leukocyte count in septic rats. Methods: Wistar rats were randomly assigned to five groups: control (anesthesia only), laparotomy, CO2 pneumoperitoneum, cecum ligation and puncture by laparotomy, and laparoscopic cecum ligation and puncture. After 30 min of the procedures, arterial blood samples were obtained to determine leukocytes subpopulations by hemocytometer. TNFα, IL-1β, IL-6 were determined in intraperitoneal fluid (by ELISA). Gas parameters were measured on arterial blood, intraperitoneal and subperitoneal exsudates. Results: Peritoneal TNFα, IL-1β and IL-6 concentrations were lower in pneumoperitoneum rats than in all other groups (p<0.05). TNFα, IL-1β and IL-6 expression was lower in the laparoscopic than in laparotomic sepsis (p<0.05). Rats from laparoscopic cecum ligation and puncture group developed significant hypercarbic acidosis in blood and subperitoneal fluid when compared to open procedure group. Total white blood cells and lymphocytes were significantly lower in laparoscopic cecum ligation and puncture rats than in the laparotomic (p<0.01). Nevertheless, the laparotomic cecum ligation rats had a significant increase in blood neutrophils and eosinophils when compared with controls (p<0.05). Conclusions: This study demonstrates that the CO2 pneumoperitoneum reduced the inflammatory response in an animal model of peritonitis with respect to intraperitoneal cytokines, white blood cell count and clinical correlates of sepsis. The pneumoperitoneum produced hypercarbic acidosis in septic animals

Correção fenotípica do nanismo avaliada por diferentes parâmetros de crescimento após administração de DNA plasmidial em modelo animal de deficiência isolada do hormônio do crescimento

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Characterization of bone pathologies in the ins2+/akita mouse, a new model for diabetes insulindependent: contribution for a better understanding of the disease in humans

Tese de Doutoramento, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

Dynamic Bayesian network for semantic place classification in mobile robotics

In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.

Incorporating uncertainty in environmental models informed by imagery

In this thesis, the issue of incorporating uncertainty for environmental modelling informed by imagery is explored by considering uncertainty in deterministic modelling, measurement uncertainty and uncertainty in image composition. Incorporating uncertainty in deterministic modelling is extended for use with imagery using the Bayesian melding approach. In the application presented, slope steepness is shown to be the main contributor to total uncertainty in the Revised Universal Soil Loss Equation. A spatial sampling procedure is also proposed to assist in implementing Bayesian melding given the increased data size with models informed by imagery. Measurement error models are another approach to incorporating uncertainty when data is informed by imagery. These models for measurement uncertainty, considered in a Bayesian conditional independence framework, are applied to ecological data generated from imagery. The models are shown to be appropriate and useful in certain situations. Measurement uncertainty is also considered in the context of change detection when two images are not co-registered. An approach for detecting change in two successive images is proposed that is not affected by registration. The procedure uses the Kolmogorov-Smirnov test on homogeneous segments of an image to detect change, with the homogeneous segments determined using a Bayesian mixture model of pixel values. Using the mixture model to segment an image also allows for uncertainty in the composition of an image. This thesis concludes by comparing several different Bayesian image segmentation approaches that allow for uncertainty regarding the allocation of pixels to different ground components. Each segmentation approach is applied to a data set of chlorophyll values and shown to have different benefits and drawbacks depending on the aims of the analysis.

Repair of calvarial defects with customized tissue-engineered bone grafts - I. Evaluation of osteogenesis in a three-dimensional culture system

Bone generation by autogenous cell transplantation in combination with a biodegradable scaffold is one of the most promising techniques being developed in craniofacial surgery. The objective of this combined in vitro and in vivo study was to evaluate the morphology and osteogenic differentiation of bone marrow derived mesenchymal progenitor cells and calvarial osteoblasts in a two-dimensional (2-D) and three-dimensional (3-D) culture environment (Part I of this study) and their potential in combination with a biodegradable scaffold to reconstruct critical-size calvarial defects in an autologous animal model [Part II of this study; see Schantz, J.T., et al. Tissue Eng. 2003;9(Suppl. 1):S-127-S-139; this issue]. New Zealand White rabbits were used to isolate osteoblasts from calvarial bone chips and bone marrow stromal cells from iliac crest bone marrow aspirates. Multilineage differentiation potential was evaluated in a 2-D culture setting. After amplification, the cells were seeded within a fibrin matrix into a 3-D polycaprolactone (PCL) scaffold system. The constructs were cultured for up to 3 weeks in vitro and assayed for cell attachment and proliferation using phase-contrast light, confocal laser, and scanning electron microscopy and the MTS cell metabolic assay. Osteogenic differentiation was analyzed by determining the expression of alkaline phosphatase (ALP) and osteocalcin. The bone marrow-derived progenitor cells demonstrated the potential to be induced to the osteogenic, adipogenic, and chondrogenic pathways. In a 3-D environment, cell-seeded PCL scaffolds evaluated by confocal laser microscopy revealed continuous cell proliferation and homogeneous cell distribution within the PCL scaffolds. On osteogenic induction mesenchymal progenitor cells (12 U/L) produce significantly higher (p < 0.05) ALP activity than do osteoblasts (2 U/L); however, no significant differences were found in osteocalcin expression. In conclusion, this study showed that the combination of a mechanically stable synthetic framework (PCL scaffolds) and a biomimetic hydrogel (fibrin glue) provides a potential matrix for bone tissue-engineering applications. Comparison of osteogenic differentiation between the two mesenchymal cell sources revealed a similar pattern.

Effect of surgical approach on bone vascularisation, fracture and soft tissue healing : comparison of less invasive to open approach

Over the past ten years, minimally invasive plate osteosynthesis (MIPO) for the fixation of long bone fractures has become a clinically accepted method with good outcomes, when compared to the conventional open surgical approach (open reduction internal fixation, ORIF). However, while MIPO offers some advantages over ORIF, it also has some significant drawbacks, such as a more demanding surgical technique and increased radiation exposure. No clinical or experimental study to date has shown a difference between the healing outcomes in fractures treated with the two surgical approaches. Therefore, a novel, standardised severe trauma model in sheep has been developed and validated in this project to examine the effect of the two surgical approaches on soft tissue and fracture healing. Twenty four sheep were subjected to severe soft tissue damage and a complex distal femur fracture. The fractures were initially stabilised with an external fixator. After five days of soft tissue recovery, internal fixation with a plate was applied, randomised to either MIPO or ORIF. Within the first fourteen days, the soft tissue damage was monitored locally with a compartment pressure sensor and systemically by blood tests. The fracture progress was assessed fortnightly by x-rays. The sheep were sacrificed in two groups after four and eight weeks, and CT scans and mechanical testing performed. Soft tissue monitoring showed significantly higher postoperative Creatine Kinase and Lactate Dehydrogenase values in the ORIF group compared to MIPO. After four weeks, the torsional stiffness was significantly higher in the MIPO group (p=0.018) compared to the ORIF group. The torsional strength also showed increased values for the MIPO technique (p=0.11). The measured total mineralised callus volumes were slightly higher in the ORIF group. However, a newly developed morphological callus bridging score showed significantly higher values for the MIPO technique (p=0.007), with a high correlation to the mechanical properties (R2=0.79). After eight weeks, the same trends continued, but without statistical significance. In summary, this clinically relevant study, using the newly developed severe trauma model in sheep, clearly demonstrates that the minimally invasive technique minimises additional soft tissue damage and improves fracture healing in the early stage compared to the open surgical approach method.

In vitro and in vivo evaluation of adenovirus combined silk fibroin scaffolds for BMP-7 gene delivery

Introduction and aims: For a scaffold material to be considered effective and efficient for tissue engineering it must be biocompatible as well as bioinductive. Silk fiber is a natural biocompatible material suitable for scaffold fabrication; however, silk is tissue-conductive and lacks tissue-inductive properties. One proposed method to make the scaffold tissue-inductive is to introduce plasmids or viruses encoding a specific growth factor into the scaffold. In this study, we constructed adenoviruses encoding bone morphogenetic protein-7 (BMP-7) and incorporated these into silk scaffolds. The osteo-inductive and new bone formation properties of these constructs were assessed in vivo in a critical-sized skull defect animal model. Materials and methods: Silk fibroin scaffolds containing adenovirus particles coding BMP-7 were prepared. The release of the adenovirus particles from the scaffolds was quantified by tissue-culture infective dose (TCID50) and the bioactivity of the released viruses was evaluated on human bone marrow mesenchymal stromal cells (BMSCs). To demonstrate the in vivo bone forming ability of the virus-carrying silk fibroin scaffold, the scaffold constructs were implanted into calvarial defects in SCID mice. Results: In vitro studies demonstrated that the virus-carrying silk fibroin scaffold released virus particles over a 3 week period while preserving their bioactivity. In vivo test of the scaffold constructs in critical-sized skull defect areas revealed that silk scaffolds were capable of delivering the adenovirus encoding BMP-7, resulting significantly enhanced new bone formation. Conclusions: Silk scaffolds carrying BMP-7 encoding adenoviruses can effectively transfect cells and enhance both in vitro and in vivo osteogenesis. The findings of this study indicate silk fibroin is a promising biomaterial for gene delivery to repair critical-sized bone defects.

The effect of endotracheal suction on regional tidal ventilation and end-expiratory lung volume

Purpose: To examine the impact of different endotracheal tube (ETT) suction techniques on regional end-expiratory lung volume (EELV) and tidal volume (VT) in an animal model of surfactant-deficient lung injury. Methods: Six 2-week old piglets were intubated (4.0 mm ETT), muscle-relaxed and ventilated, and lung injury was induced with repeated saline lavage. In each animal, open suction (OS) and two methods of closed suction (CS) were performed in random order using both 5 and 8 French gauge (FG) catheters. The pre-suction volume state of the lung was standardised on the inflation limb of the pressure-volume relationship. Regional EELV and VT expressed as a proportion of the impedance change at vital capacity (%ZVCroi) within the anterior and posterior halves of the chest were measured during and for 60 s after suction using electrical impedance tomography. Results: During suction, 5 FG CS resulted in preservation of EELV in the anterior (nondependent) and posterior(dependent) lung compared to the other permutations, but these only reached significance in the anterior regions (p\0.001 repeated-measures ANOVA). VT within the anterior, but not posterior lung was significantly greater during 5FG CS compared to 8 FG CS; the mean difference was 15.1 [95% CI 5.1, 25.1]%ZVCroi. Neither catheter size nor suction technique influenced post-suction regional EELV or VT compared to pre-suction values (repeated-measures ANOVA). Conclusions: ETT suction causes transient loss of EELV and VT throughout the lung. Catheter size exerts a greater influence than suction method, with CS only protecting against derecruitment when a small catheter is used, especially in the non-dependent lung.