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In this paper, the computational complexity of the marginalized particle filter is analyzed and a general method to perform this analysis is given. The key is the introduction of the equivalent flop measure. In an extensive Monte Carlo simulation, different computational aspects are studied and compared with the derived theoretical results.

An essential part of future collision avoidance systems is to be able to predict road curvature. This can be based on vision data, but the lateral movement of leading vehicles can also be used to support road geometry estimation. This paper presents a method for detecting lane departures, including lane changes, of leading vehicles. This information is used to adapt the dynamic models used in the estimation algorithm in order to accommodate for the fact that a lane departure is in progress. The goal is to improve the accuracy of the road geometry estimates, which is affected by the motion of leading vehicles. The significantly improved performance is demonstrated using sensor data from authentic traffic environments.

This paper deals with the problem of estimating the vehicle surroundings (lane geometry and the position of other vehicles), which is needed for intelligent automotive systems, such as adaptive cruise control, collision avoidance and lane guidance. This results in a nonlinear estimation problem. For automotive tracking systems, these problems are traditionally handled using the extended Kalman filter. In this paper we describe the application of the marginalized particle filter to this problem. Studies using both synthetic and authentic data show that the marginalized particle filter can in fact give better performance than the extended Kalman filter. However, the computational load is higher.

We hypothesized that the ability of BCG vaccination to protect against Mycobacterium tuberculosis is less in hosts exposed to chronic helminthes infection compared to unexposed individuals. To test this hypothesis we evaluated the efficacy of BCG vaccination in protecting against M. tuberculosis challenge in Schistosoma mansoni pre-infected mice by analyzing their ability to limit the replication of TB bacilli in the lung and liver and the histology of lung sections. The results show that BCG vaccinated mice with prior S. mansoni infection show significantly higher number of colony forming units of TB bacilli as well as significant reduction in air exchange area in the lung compared to controls. In addition, spleen cells from S. mansoni infected mice were found to produce significantly less IFN-gamma and nitric oxide when stimulated in vitro with PPD and several fold higher soluble egg antigen (SEA) and Concanavalin A induced IL-4 and IL-5 secretion. Taken together, our data show that S. mansoni infection reduces the protective efficacy of BCG vaccination against M. tuberculosis possibly by attenuation of protective immune responses to mycobacterial antigens and/or by polarizing the general immune responses to the Th2 profile.

Antimicrobial pharmacokinetic-pharmacodynamic (PK/PD) science and clinical trial simulations have not been adequately applied to the design of doses and dose schedules of antituberculosis regimens because many researchers are skeptical about their clinical applicability. We compared findings of preclinical PK/PD studies of current first-line antituberculosis drugs to findings from several clinical publications that included microbiologic outcome and pharmacokinetic data or had a dose-scheduling design. Without exception, the antimicrobial PK/PD parameters linked to optimal effect were similar in preclinical models and in tuberculosis patients. Thus, exposure-effect relationships derived in the preclinical models can be used in the design of optimal antituberculosis doses, by incorporating population pharmacokinetics of the drugs and MIC distributions in Monte Carlo simulations. When this has been performed, doses and dose schedules of rifampin, isoniazid, pyrazinamide, and moxifloxacin with the potential to shorten antituberculosis therapy have been identified. In addition, different susceptibility breakpoints than those in current use have been identified. These steps outline a more rational approach than that of current methods for designing regimens and predicting outcome so that both new and older antituberculosis agents can shorten therapy duration.

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is a global disease that kills about two million people each year. Leprosy is caused by Mycobacterium leprae, and primarily affects the skin and peripheral nervous system. About 10-20% of leprosy patients suffer from reactions associated with acute inflammation that can lead to rapid and severe nerve damage. Most individuals infected with Mtb or M leprae do not develop clinical disease, which indicates that human hosts have effective defence mechanisms. In macrophages activated by cytokines such as IFN-γ, inducible nitric oxide synthase (iNOS) catalyses the production of nitric oxide (NO) from L-arginine. In an inflammatory environment, NO reacts with the superoxide radical (O2-) to yield peroxynitrite, an unstable metabolite that can rapidly nitrosylate tyrosine residues on proteins to form the stabile end product nitrotyrosine (NT). Many studies using experimental models have indicated that NO is important in host response to M leprae and Mtb, but this is controversial in human disease. Thus, our aim was to investigate the presence and the role of NO in the human mycobacterial infectious diseases TB and leprosy.Levels of the NO metabolites nitrite and nitrate were initially increased in urine from patients with reactional leprosy but were normalised by treatment with prednisolone, and this was associated with clinical improvement. Immunohistochemistry revealed local production of NO in skin biopsies from patients with borderline leprosy and reversal reactions, which was detected as reactivity to iNOS and NT in macrophage-rich granulomas. Ultrastructural studies showed NT-positive aggregations of neurofilaments in dermal nerves from leprosy patients. Patients with active tuberculosis had increased urinary levels of NO metabolites, which were normalised after anti-TB treatment. Household contacts of patients with tuberculosis had increased levels of NO metabolites in plasma and serum. Immunohistochemical examination of biopsies from patients with TB indicated local, iN OS-mediated generation ofNO in macrophage-rich granulomas. In an experimental model of TB, local production of NO in the lungs was substantial in the acute phase of infection, and immunoelectron microscopy detected NT in phagosomes containing Mtb and on the surface of the bacteria. In an in vitro model, NO and peroxynitrite killed Mtb H37Ra and induced upregulation of several bacterial proteins. Peroxynitrite also mediated tyrosine nitration of albumin associated with the surface of Mtb. In a randomised, double-blind trial in Ethiopia, arginine supplementation in patients receiving conventional chemotherapy increased sputum conversion and reduced the prevalence of cough in HIV -negative, smear-positive patients with active TB.In conclusion, these results demonstrate that iNOS-mediated production of NO occurs in human tuberculosis and leprosy; NO and peroxynitrite can kill Mtb and modify protein expression in the bacteria; and arginine leads to clinical improvement in TB patients.

Evidence is accumulating that nitric oxide (NO) produced by macrophages has a role in the pathogenesis of reactions in leprosy. We followed the urinary levels of the metabolites of NO [nitrite (NO2-) and nitrate (NO3-)] and the clinical response to prednisolone treatment in leprosy patients (n = 9) admitted to ALERT leprosy hospital Addis Ababa, Ethiopia, because of reversal reaction (RR) or erythema nodosum leprosum (ENL). In untreated reactional leprosy patients, the levels of urinary NO metabolites (1645 +/- 454 microM, n = 9, ENL = 4, RR = 5) decreased significantly 2 weeks after high dose prednisolone treatment (1075 +/- 414 microM, P < 0.05), and remained stable 4 (895 +/- 385 microM, P < 0.02) and 6 weeks following treatment initiation (1048 +/- 452 microM, P < 0.02). This decrease was also present when the reactional patients were subdivided according to the type of reaction (ENL, RR) and coincided with a clinical improvement. In patients showing a poor clinical response to steroids, no or minor effects on the urinary NO metabolite levels were observed. We conclude that there is a correlation between the decrease in urinary NO metabolites and a favourable clinical response after high dose prednisolone treatment of reactional leprosy patients.

Tuberculosis (TB) caused by Mycobacterium tuberculosis (Mtb) is a global disease that kills about two million people each year. Leprosy is caused by Mycobacterium leprae, and primarily affects the skin and peripheral nervous system. About 10-20% of leprosy patients suffer from reactions associated with acute inflammation that can lead to rapid and severe nerve damage. Most individuals infected with Mtb or M leprae do not develop clinical disease, which indicates that human hosts have effective defence mechanisms. In macrophages activated by cytokines such as IFN-γ, inducible nitric oxide synthase (iNOS) catalyses the production of nitric oxide (NO) from L-arginine. In an inflammatory environment, NO reacts with the superoxide radical (O2-) to yield peroxynitrite, an unstable metabolite that can rapidly nitrosylate tyrosine residues on proteins to form the stabile end product nitrotyrosine (NT). Many studies using experimental models have indicated that NO is important in host response to M leprae and Mtb, but this is controversial in human disease. Thus, our aim was to investigate the presence and the role of NO in the human mycobacterial infectious diseases TB and leprosy.Levels of the NO metabolites nitrite and nitrate were initially increased in urine from patients with reactional leprosy but were normalised by treatment with prednisolone, and this was associated with clinical improvement. Immunohistochemistry revealed local production of NO in skin biopsies from patients with borderline leprosy and reversal reactions, which was detected as reactivity to iNOS and NT in macrophage-rich granulomas. Ultrastructural studies showed NT-positive aggregations of neurofilaments in dermal nerves from leprosy patients. Patients with active tuberculosis had increased urinary levels of NO metabolites, which were normalised after anti-TB treatment. Household contacts of patients with tuberculosis had increased levels of NO metabolites in plasma and serum. Immunohistochemical examination of biopsies from patients with TB indicated local, iN OS-mediated generation ofNO in macrophage-rich granulomas. In an experimental model of TB, local production of NO in the lungs was substantial in the acute phase of infection, and immunoelectron microscopy detected NT in phagosomes containing Mtb and on the surface of the bacteria. In an in vitro model, NO and peroxynitrite killed Mtb H37Ra and induced upregulation of several bacterial proteins. Peroxynitrite also mediated tyrosine nitration of albumin associated with the surface of Mtb. In a randomised, double-blind trial in Ethiopia, arginine supplementation in patients receiving conventional chemotherapy increased sputum conversion and reduced the prevalence of cough in HIV -negative, smear-positive patients with active TB.In conclusion, these results demonstrate that iNOS-mediated production of NO occurs in human tuberculosis and leprosy; NO and peroxynitrite can kill Mtb and modify protein expression in the bacteria; and arginine leads to clinical improvement in TB patients.

We measured the metabolites of NO [nitrite (NO2-) and nitrate (NO3-)] in urine from Ethiopian patients suffering from leprosy. The urinary level of NO2-/NO3- in a group of healthy Ethiopians was 1020 +/- 471 microM (n = 22). Leprosy patients in reversal reaction had significantly higher levels of NO2-/NO3- (1817 +/- 492 microM, p0.001, n = 12) than both the control group and leprosy patients who were not in reversal reaction (1079 +/- 446 microM, n = 12). We conclude that the reversal reaction in leprosy in associated with increased urinary levels of nitric oxide metabolites.

The problem of estimating the position and orientation (pose) of a camera is approached by fusing measurements from inertial sensors (accelerometers and rate gyroscopes) and a camera. The sensor fusion approach described in this contribution is based on nonlinear filtering using the measurements from these complementary sensors. This way, accurate and robust pose estimates are available for the primary purpose of augmented reality applications, but with the secondary effect of reducing computation time and improving the performance in vision processing. A real-time implementation of a nonlinear filter is described, using a dynamic model for the 22 states, where 100 Hz inertial measurements and 12.5 Hz vision measurements are processed. An example where an industrial robot is used to move the sensor unit, possessing almost perfect precision and repeatability, is presented. The results show that position and orientation accuracy is sufficient for a number of augmented reality applications.

The emergence of multidrug-resistant strains of Mycobacterium tuberculosis (MTB), the bacterium responsible for tuberculosis (TB), has rekindled the interest in the role of nutritional supplementation of micronutrients, such as vitamin D, as adjuvant treatment. Here, the growth of virulent MTB in macrophages obtained from the peripheral blood of patients with and without TB was studied. The H37Rv strain genetically modified to express Vibrio harveyi luciferase was used to determine the growth of MTB by luminometry in the human monocyte-derived macrophages (hMDMs) from study subjects. Determination of cytokine levels in culture supernatants was performed using a flow cytometry-based bead array technique. No differences in intracellular growth of MTB were observed between the different study groups. However, stimulation with 100nM 1,25-dihydroxyvitamin D significantly enhanced the capacity of hMDMs isolated from TB patients to control the infection. This effect was not observed in hMDMs from the other groups. The interleukin (IL)-1β and IL-10 release by hMDMs was clearly increased upon stimulation with 1,25-dihydroxyvitamin D. Furthermore, the 1,25-dihydroxyvitamin D stimulation also led to elevated levels of TNF-α (tumor necrosis factor-alpha) and IL-12p40. It was concluded that vitamin D triggers an inflammatory response in human macrophages with enhanced secretion of cytokines, as well as enhancing the capacity of hMDMs from patients with active TB to restrict mycobacterial growth.

Statistical phylogenetic analysis currently relies on complex, dedicated software packages, making it difficult for evolutionary biologists to explore new models and inference strategies. Recent years have seen more generic solutions based on probabilistic graphical models, but this formalism can only partly express phylogenetic problems. Here, we show that universal probabilistic programming languages (PPLs) solve the expressivity problem, while still supporting automated generation of efficient inference algorithms. To prove the latter point, we develop automated generation of sequential Monte Carlo (SMC) algorithms for PPL descriptions of arbitrary biological diversification (birth-death) models. SMC is a new inference strategy for these problems, supporting both parameter inference and efficient estimation of Bayes factors that are used in model testing. We take advantage of this in automatically generating SMC algorithms for several recent diversification models that have been difficult or impossible to tackle previously. Finally, applying these algorithms to 40 bird phylogenies, we show that models with slowing diversification, constant turnover and many small shifts generally explain the data best. Our work opens up several related problem domains to PPL approaches, and shows that few hurdles remain before these techniques can be effectively applied to the full range of phylogenetic models., Ronquist, Kudlicka, Senderov and colleagues present universal probabilistic programming as a powerful method for modeling and inference in statistical phylogenetics. They provide an accessible introduction to these techniques and apply them in inferring complex patterns of diversification and turnover in birds.

The 12-lead electrocardiogram (ECG) is a major diagnostic test for cardiovascular diseases and enhanced automated analysis tools might lead to more reliable diagnosis and improved clinical practice. Deep neural networks are models composed of stacked transformations that learn tasks by examples. Inspired by the success of these models in computer vision, we propose an end-to-end approach for the task at hand. We trained deep convolutional neural network models in the heterogeneous dataset provided in the Physionet 2020 Challenge and used an ensemble of seven of these convolutional models for the classification of abnormalities present in the ECG records. Ensembles use the output of multiple models to generate a combined prediction and are known to improve performance and generalization when compared to the individual models. In our submission, we use an ensemble of neural networks with the architecture similar to the one described in Nat Commun 11, 1760 (2020) for 12-lead ECGs classification. Our approach achieved a challenge validation score of 0.657, and full test score of 0.132, placing us, the “Code Team”, in 28 out of 41 in the official ranking.

BACKGROUND: The aim of this study was to evaluate diagnostic tests in order to introduce a diagnostic strategy to identify the most common gram-positive bacteria (pneumococci, enterococci, β-haemolytic streptococci and S. aureus) found in blood cultures within 6 hours after signalling growth. METHODS: The tube coagulase test was optimized and several latex agglutination tests were compared and evaluated before a validation period of 11 months was performed on consecutive positive blood culture patient samples from Kalmar County Hospital, Sweden. RESULTS: During the validation period 150 (91%) of a total of 166 gram-positive cocci (119 in clusters, 45 in chains or pairs and 2 undefined morphology) were correctly identified as S. aureus, CoNS, Pneumococci, Enterococci or group A streptococci (GAS), group B streptococci (GBS), group G streptococci (GGS) within 6 hours with a minimal increase in work-load and costs. The remaining samples (9%) were correctly identified during the next day. No samples were incorrectly grouped with this diagnostic strategy and no patient came to risk by early reporting. CONCLUSION: A simple strategy gives reliable and cost-effective reporting of >90% of the most common gram-positive cocci within 6 hours after a blood cultures become positive. The high specificity of the tests used makes preliminary reports reliable. The reports can be used to indicate the focus of infection and not the least, support faster administration of proper antimicrobial treatment for patients with serious bacterial infections.

The Kalman filter computes the maximum a posteriori (MAP) estimate of the states for linear state space models with Gaussian noise. We interpret the Kalman filter as the solution to a convex optimization problem, and show that we can generalize the MAP state estimator to any noise with a log-concave density function and any combination of linear equality and convex inequality constraints on the states. We illustrate the principle on a hidden Markov model, where the state vector contains probabilities that are positive and sum to one.

The marginalized particle filter is a powerful combination of the particle filter and the Kalman filter, which can be used when the underlying model contains a linear sub-structure, subject to Gaussian noise. This paper will illustrate several positioning and target tracking applications, solved using the marginalized particle filter. Furthermore, we analyze several properties of practical importance, such as its computational complexity and how to cope with quantization effects.

General approaches to modeling, for instance using object-oriented software, lead to differential-algebraic equations (DAE). As the name reveals, it is a combination of differential and algebraic equations. For state estimation using observed system inputs and outputs in a stochastic framework similar to Kalman filtering, we need to augment the DAE with stochastic disturbances ("process noise"), whose covariance matrix becomes the tuning parameter. We will determine the subspace of possible causal disturbances based on the linear DAE model. This subspace determines all degrees of freedom in the filter design, and a Kalman filter algorithm is given. We illustrate the design on a system with two interconnected rotating masses.

Background: Nitric oxide (NO) is essential for host defense in rodents, but the role of NO during tuberculosis (TB) in man remains controversial. However, earlier observations that arginine supplementation facilitates anti-TB treatment, supports the hypothesis that NO is important in the host defense against TB. Local production of NO measured in fractional exhaled air (FeNO) in TB patients with and without HIV co-infection has not been reported previously. Thus, our aim was to investigate levels of FeNO in relation to clinical symptoms and urinary NO metabolites (uNO). Methods: In a cross sectional study, FeNO and uNO were measured and clinical symptoms, chest x-ray, together with serum levels of arginine, tumor necrosis factor alpha (TNF-alpha) and interleukin 12 (IL-12) were evaluated in sputum smear positive TB patients (HIV+/TB, n = 36, HIV-/TB, n = 59), their household contacts (n = 17) and blood donors (n = 46) from Gondar University Hospital, Ethiopia. Results: The proportion of HIV-/TB patients with an increased FeNO level (> 25 ppb) was significantly higher as compared to HIV+/TB patients, but HIV+/TB patients had significantly higher uNO than HIV-/TB patients. HIV+ and HIV-/TB patients both had lower levels of FeNO compared to blood donors and household contacts. The highest levels of both uNO and FeNO were found in household contacts. Less advanced findings on chest x-ray, as well as higher sedimentation rate were observed in HIV+/TB patients as compared to HIV-/TB patients. However, no significant correlation was found between FeNO and uNO, chest x-ray grading, clinical symptoms, TNF-alpha, IL-12, arginine levels or sedimentation rate. Conclusion: In both HIV negative and HIV co infected TB patients, low levels of exhaled NO compared to blood donors and household were observed. Future studies are needed to confirm whether low levels of exhaled NO could be a risk factor in acquiring TB and the relative importance of NO in human TB. Original Publication: Jonna Idh, Anna Westman, Daniel Elias, Feleke Moges, Assefa Getachew, Aschalew Gelaw, Tommy Sundqvist, Tony Forslund, Addis Alemu, Belete Ayele, Ermias Diro, Endalkachew Melese, Yared Wondmikun, Sven Britton, Olle Stendahl and Thomas Schoen, Nitric oxide production in the exhaled air of patients with pulmonary tuberculosis in relation to HIV co-infection, 2008, BMC INFECTIOUS DISEASES, (8), 146. http://dx.doi.org/10.1186/1471-2334-8-146 Publisher: BioMed Central http://www.biomedcentral.com/