Three-year results of visual outcome with disease activity-guided ranibizumab algorithm for the treatment of exudative age-related macular degeneration

PURPOSE To evaluate 3-year follow-up treatment outcomes with ranibizumab (Lucentis(®)) 0.5 mg administered either monthly or quarterly on a pro re nata (PRN) basis according to a disease activity-guided monitoring and treatment algorithm. METHODS A total of 316 treatment-naive eyes of 316 patients with exudative age-related macular degeneration met the criteria for inclusion in this retrospective, interventional case series. Patients were treated with ranibizumab 0.5 mg according to a disease activity-guided algorithm with monthly monitoring. Optical coherence tomography and fluorescein angiography were routinely used to assess disease activity: active lesions were treated with a series of three monthly injections, whereas inactive lesions were treated with quarterly injections. RESULTS Mean Early Treatment Diabetic Retinopathy Study best-corrected visual acuity improved from 52 letters at baseline to 59 letters at 12 months, achieved with a mean of 7.1 injections, 61 letters at 24 months with a mean of 5.0 injections administered in the second year and 60 letters at 36 months with a mean number of 5.2 injections. CONCLUSIONS Monthly visits and a morphology-driven PRN regimen with 3 injections in case of recurrence plus quarterly injections in case of inactive CNV resulted in an average VA gain of 7-9 letters that could be maintained over 3 years.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

Search for WH production with a light Higgs boson decaying to prompt electron-jets in proton-proton collisions at sqrts=7 TeV with the ATLAS detector

A search is performed for WH production with a light Higgs boson decaying to hidden-sector particles resulting in clusters of collimated electrons, known as electron-jets. The search is performed with 2.04 fb(-1) of data collected in 2011 with the ATLAS detector at the Large Hadron Collider in proton-proton collisions at root s = 7 TeV. One event satisfying the signal selection criteria is observed, which is consistent with the expected background rate. Limits on the product of the WH production cross section and the branching ratio of a Higgs boson decaying to prompt electron-jets are calculated as a function of a Higgs boson mass in the range from 100 to 140 GeV.

Mutation in beta1-tubulin correlates with macrothrombocytopenia in Cavalier King Charles Spaniels.

BACKGROUND Cavalier King Charles Spaniels (CKCS) have a high prevalence of inherited macrothrombocytopenia. The purpose of this study was to determine if a mutation in beta1-tubulin correlated with presumptive inherited macrothrombocytopenia. HYPOTHESIS A mutation in beta1-tubulin results in synthesis of an altered beta1-tubulin monomer. alpha-beta tubulin dimers within microtubule protofilaments are unstable, resulting in altered megakaryocyte proplatelet formation. ANIMALS Blood samples were obtained from CKCS and non-CKCS dogs. METHODS DNA was used in polymerase chain reaction (PCR) assays to evaluate beta1-tubulin. Platelet numbers and mean platelet volume (MPV) were evaluated for a correlation with the presence or absence of a mutation identified in beta1-tubulin. Platelets obtained from homozygous, heterozygous, and clear CKCS were further evaluated using electron microscopy and immunofluorescence. RESULTS A mutation in the gene encoding beta1-tubulin correlated with macrothrombocytopenia in CKCS. Electron microscopy and immunofluorescence studies suggest that platelet microtubules are present but most likely are unstable and decreased in number. CONCLUSIONS AND CLINICAL IMPORTANCE The macrothrombocytopenia of CKCS correlated with a mutation in beta1-tubulin. alpha-beta tubulin dimers within protofilaments most likely are unstable, leading to altered proplatelet formation by megakaryocytes. This information will aid in distinguishing inherited from acquired thrombocytopenia. It also provides insight into the mechanism of platelet production by megakaryocytes, and also may prove useful in understanding heart-related changes in macrothrombocytopenic CKCS with concurrent mitral valve regurgitation.

Search for pair and single production of new heavy quarks that decay to a ℤ boson and a third-generation quark in pp collisions at √ s=8 TeV with the ATLAS detector

A search is presented for the production of new heavy quarks that decay to a Z boson and a third-generation Standard Model quark. In the case of a new charge +2/3 quark (T), the decay targeted is T → Zt, while the decay targeted for a new charge −1/3 quark (B) is B → Zb. The search is performed with a dataset corresponding to 20.3 fb−1 of pp collisions at √ s = 8TeV recorded in 2012 with the ATLAS detector at the CERN Large Hadron Collider. Selected events contain a high transverse momentum Z boson candidate reconstructed from a pair of oppositely charged same-flavor leptons (electrons or muons), and are analyzed in two channels defined by the absence or presence of a third lepton. Hadronic jets, in particular those with properties consistent with the decay of a b-hadron, are also required to be present in selected events. Different requirements are made on the jet activity in the event in order to enhance the sensitivity to either heavy quark pair production mediated by the strong interaction, or single production mediated by the electroweak interaction. No significant excess of events above the Standard Model expectation is observed, and lower limits are derived on the mass of vector-like T and B quarks under various branching ratio hypotheses, as well as upper limits on the agnitude of electroweak coupling parameters.

T Cell Motility as Modulator of Interactions with Dendritic Cells

It is well established that the balance of costimulatory and inhibitory signals during interactions with dendritic cells (DCs) determines T cell transition from a naïve to an activated or tolerant/anergic status. Although many of these molecular interactions are well reproduced in reductionist in vitro assays, the highly dynamic motility of naïve T cells in lymphoid tissue acts as an additional lever to fine-tune their activation threshold. T cell detachment from DCs providing suboptimal stimulation allows them to search for DCs with higher levels of stimulatory signals, while storing a transient memory of short encounters. In turn, adhesion of weakly reactive T cells to DCs presenting peptides presented on major histocompatibility complex with low affinity is prevented by lipid mediators. Finally, controlled recruitment of CD8(+) T cells to cognate DC-CD4(+) T cell clusters shapes memory T cell formation and the quality of the immune response. Dynamic physiological lymphocyte motility therefore constitutes a mechanism to mitigate low avidity T cell activation and to improve the search for "optimal" DCs, while contributing to peripheral tolerance induction in the absence of inflammation.

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging.

Towards the Natural Optimization with Particle Swarm Optimization.

This paper shows the Particle Swarm Optimization algorithm with a Differential Evolution. Each candidate solution is sampled in the interval [?5, 5] D where D indicates the dimension of the search space, and the evolution is performed with a classical PSO algorithm and a classical DE/x/1 algorithm according to a random threshold. Moreover, this paper provides concepts to deal with non-linear optimization through the use of PSO.

Foreground segmentation in depth imagery using depth and spatial dynamic models for video surveillance applications

Low-cost systems that can obtain a high-quality foreground segmentation almostindependently of the existing illumination conditions for indoor environments are verydesirable, especially for security and surveillance applications. In this paper, a novelforeground segmentation algorithm that uses only a Kinect depth sensor is proposedto satisfy the aforementioned system characteristics. This is achieved by combininga mixture of Gaussians-based background subtraction algorithm with a new Bayesiannetwork that robustly predicts the foreground/background regions between consecutivetime steps. The Bayesian network explicitly exploits the intrinsic characteristics ofthe depth data by means of two dynamic models that estimate the spatial and depthevolution of the foreground/background regions. The most remarkable contribution is thedepth-based dynamic model that predicts the changes in the foreground depth distributionbetween consecutive time steps. This is a key difference with regard to visible imagery,where the color/gray distribution of the foreground is typically assumed to be constant.Experiments carried out on two different depth-based databases demonstrate that theproposed combination of algorithms is able to obtain a more accurate segmentation of theforeground/background than other state-of-the art approaches.

Functional outcomes after stabilization with Dynesys in patients with spinal degenerative diseases

Objective: To know the impact of the Dynesys system on the functional outcomes in patients with spinal degenerative diseases. Summary of background data: Dynesys system has been proposed as an alternative to vertebral fusion for several spinal degenerative diseases. The fact that it has been used in people with different diagnosis criteria using different tools to measure clinical outcomes makes very difficult unifying the results available nowadays. Methods: The data base of Medlars Online International Literature (MEDLINE) via PubMed©, EMBASE©, and the Cochrane Library Plus were reviewed in search of all the studies published until November 2012 in which an operation with Dynesys in patients with spinal degenerative diseases and an evaluation of the results by an analysis of functional outcomes had taken place. No limits were used to article type, date of publication or language. Results: A total of 134 articles were found, 26 of which fulfilled the inclusion criteria after being assessed by two reviewers. All of them were case series, except for a multicenter randomized clinical trial (RCT) and a prospective case-control study. The selected articles made a total of 1507 cases. The most frequent diagnosis were lumbar spinal canal stenosis (LSCS), degenerative disc disease (DDD), degenerative spondylolisthesis (DS) and lumbar degenerative scoliosis (LDS). In cases of lumbar spinal canal stenosis Dynesys was associated to surgical decompression. Several tools to measure the functional disability and general health status were found. Oswestry Disability Index (ODI), the ODI Korean version (K-Odi), Prolo, Sf-36, Sf-12, Roland-Morris disability questionnaire (RMDQ), and the pain Visual Analogue Scale (VAS) were the most used. They showed positive results in all cases series reviewed. In most studies the ODI decreased about 25% (e.g. from a score of 85% to 60%). Better results when dynamic fusion was combined with nerve root decompression were found. Functional outcomes and leg pain scores with Dynesys were statistically non-inferior to posterolateral spinal fusion using autogenous bone. When Dynesys and decompression was compared with posterior interbody lumbar fixation (PLIF) and decompression, differences in ODI and VAS were not statistically significant. Conclusions: In patients with spinal degenerative diseases due to degenerative disc disorders, spinal canal stenosis and degenerative spondylolisthesis, surgery with Dynesys and decompression improves functional outcomes, decreases disability, and reduces back and leg pain. More studies are needed to conclude that dynamic stabilization is better than posterolateral and posterior interbody lumbar fusion. Studies comparing Dynesys with decompression against decompression alone should be done in order to isolate the effect of the dynamic stabilization.

Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

Genetic algorithm based distance spectrum technique for performance union bound of space-time trellis coded OFDM

This paper derives the performance union bound of space-time trellis codes in orthogonal frequency division multiplexing system (STTC-OFDM) over quasi-static frequency selective fading channels based on the distance spectrum technique. The distance spectrum is the enumeration of the codeword difference measures and their multiplicities by exhausted searching through all the possible error event paths. Exhaustive search approach can be used for low memory order STTC with small frame size. However with moderate memory order STTC and moderate frame size the computational cost of exhaustive search increases exponentially, and may become impractical for high memory order STTCs. This requires advanced computational techniques such as Genetic Algorithms (GAS). In this paper, a GA with sharing function method is used to locate the multiple solutions of the distance spectrum for high memory order STTCs. Simulation evaluates the performance union bound and the complexity comparison of non-GA aided and GA aided distance spectrum techniques. It shows that the union bound give a close performance measure at high signal-to-noise ratio (SNR). It also shows that GA sharing function method based distance spectrum technique requires much less computational time as compared with exhaustive search approach but with satisfactory accuracy.

Component scheduling for chip shooter machines: a hybrid genetic algorithm approach

A chip shooter machine for electronic component assembly has a movable feeder carrier, a movable X–Y table carrying a printed circuit board (PCB), and a rotary turret with multiple assembly heads. This paper presents a hybrid genetic algorithm (HGA) to optimize the sequence of component placements and the arrangement of component types to feeders simultaneously for a chip shooter machine, that is, the component scheduling problem. The objective of the problem is to minimize the total assembly time. The GA developed in the paper hybridizes different search heuristics including the nearest-neighbor heuristic, the 2-opt heuristic, and an iterated swap procedure, which is a new improved heuristic. Compared with the results obtained by other researchers, the performance of the HGA is superior in terms of the assembly time. Scope and purpose When assembling the surface mount components on a PCB, it is necessary to obtain the optimal sequence of component placements and the best arrangement of component types to feeders simultaneously in order to minimize the total assembly time. Since it is very difficult to obtain the optimality, a GA hybridized with several search heuristics is developed. The type of machines being studied is the chip shooter machine. This paper compares the algorithm with a simple GA. It shows that the performance of the algorithm is superior to that of the simple GA in terms of the total assembly time.

A morphometric study of the spatial patterns of TDP-43 immunoreactive neuronal inclusions in frontotemporal lobar degeneration (FTLD) with progranulin (GRN) mutation

Mutations of the progranulin (GRN) gene are a major cause of familial frontotemporal lobar degeneration with transactive response (TAR) DNA-binding protein of 43 kDa (TDP-43) proteinopathy (FTLD-TDP). We studied the spatial patterns of TDP-43 immunoreactive neuronal cytoplasmic inclusions (NCI) and neuronal intranuclear inclusions (NII) in histological sections of the frontal and temporal lobe in eight cases of FTLD-TDP with GRN mutation using morphometric methods and spatial pattern analysis. In neocortical regions, the NCI were clustered and the clusters were regularly distributed parallel to the pia mater; 58% of regions analysed exhibiting this pattern. The NII were present in regularly distributed clusters in 35% of regions but also randomly distributed in many areas. In neocortical regions, the sizes of the regular clusters of NCI and NII were 400-800 µm, approximating to the size of the modular columns of the cortico-cortical projections, in 31% and 36% of regions respectively. The NCI and NII also exhibited regularly spaced clustering in sectors CA1/2 of the hippocampus and in the dentate gyrus. The clusters of NCI and NII were not spatially correlated. The data suggest degeneration of the cortico-cortical and cortico-hippocampal pathways in FTLD-TDP with GRN mutation, the NCI and NII affecting different clusters of neurons.

Defective peroxisomal proliferators activated receptor gamma activity due to dominant-negative mutation synergizes with hypertension to accelerate cardiac fibrosis in mice

Aims: Humans with inactivating mutations in peroxisomal proliferators activated receptor gamma (PPAR?) typically develop a complex metabolic syndrome characterized by insulin resistance, diabetes, lipodystrophy, hypertension, and dyslipidaemia which is likely to increase their cardiovascular risk. Despite evidence that the activation of PPAR? may prevent cardiac fibrosis and hypertrophy, recent evidence has suggested that pharmacological activation of PPAR? causes increased cardiovascular mortality. In this study, we investigated the effects of defective PPAR? function on the development of cardiac fibrosis and hypertrophy in a murine model carrying a human dominant-negative mutation in PPAR?. Methods and results: Mice with a dominant-negative point mutation in PPAR? (P465L) and their wild-type (WT) littermates were treated with either subcutaneous angiotensin II (AngII) infusion or saline for 2 weeks. Heterozygous P465L and WT mice developed a similar increase in systolic blood pressure, but the mutant mice developed significantly more severe cardiac fibrosis to AngII that correlated with increased expression of profibrotic genes. Both groups similarly increased the heart weight to body weight ratio compared with saline-treated controls. There were no differences in fibrosis between saline-treated WT and P465L mice. Conclusion: These results show synergistic pathogenic effects between the presence of defective PPAR? and AngII-induced hypertension and suggest that patients with PPAR? mutation and hypertension may need more aggressive therapeutic measures to reduce the risk of accelerated cardiac fibrosis. © The Author 2009.