Obstacle Avoidance and Proscriptive Bayesian Programming

Unexpected events and not modeled properties of the robot environment are some of the challenges presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a probabilistic approach called Bayesian Programming, which aims to deal with the uncertainty, imprecision and incompleteness of the information handled to solve the obstacle avoidance problem. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. A video illustration of the developed experiments can be found at http://www.inrialpes.fr/sharp/pub/laplac

Proscriptive Bayesian Programming Application for Collision Avoidance

Evolve safely in an unchanged environment and possibly following an optimal trajectory is one big challenge presented by situated robotics research field. Collision avoidance is a basic security requirement and this paper proposes a solution based on a probabilistic approach called Bayesian Programming. This approach aims to deal with the uncertainty, imprecision and incompleteness of the information handled. Some examples illustrate the process of embodying the programmer preliminary knowledge into a Bayesian program and experimental results of these examples implementation in an electrical vehicle are described and commented. Some videos illustrating these experiments can be found at http://www-laplace.imag.fr

Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge

Endotoxemia related to cardiopulmonary bypass is associated with increased risk of infection after cardiac surgery: a prospective observational study

Abstract Introduction Previous studies have documented a high frequency of endotoxemia associated with cardiopulmonary bypass (CPB). Endotoxemia may be responsible for some of the complications associated with cardiac surgery. The purpose of the study was to examine the prevalence of endotoxemia during cardiopulmonary bypass supported aortocoronary bypass grafting surgery (ACB) using a new assay, the Endotoxin Activity Assay (EAA), and explore the association between endotoxemia and post-operative infection. Methods The study was a single center prospective observational study measuring EAA during the perioperative period for elective ACB. Blood samples were drawn at induction of anesthesia (T1), immediately prior to release of the aortic cross-clamp (T2), and on the first post-operative morning (T3). The primary outcome was the prevalence of endotoxemia. Secondary outcomes assessed included infection rates, intensive care unit (ICU) and hospital length of stay. An EAA of < 0.40 units was interpreted as "low", 0.41 to 0.59 units as "intermediate", and ≥0.60 units as "high". Results A total of 57 patients were enrolled and 54 patients were analyzable. The mean EAA at T1 was 0.38 +/- 0.14, at T2 0.39 +/- 0.18, and at T3 0.33 +/- 0.18. At T2 only 13.5% (7/52) of patients had an EAA in the high range. There was a positive correlation between EAA and duration of surgery (P = 0.02). In patients with EAA ≥0.40 at T2, 26.1% (6/23) of patients developed post-operative infections compared to 3.5% (1/29) of those that had a normal EAA (P = 0.0354). Maximum EAA over the first 24 hours was also strongly correlated with risk of post-operative infection (P = 0.0276). Conclusions High levels of endotoxin occur less frequently during ACB than previously documented. However, endotoxemia is associated with a significantly increased risk of the development of post-operative infection. Measuring endotoxin levels during ACB may provide a mechanism to identify and target a high risk patient population

The short-term effects of CGRP monoclonal antibodies on bone turnover: A prospective cohort study

BACKGROUND: Calcitonin gene-related peptide monoclonal antibodies (CGRP mAb) are an effective treatment of migraine however may have possible off-target effects. Pre-clinical studies implicate CGRP in several aspects of bone turnover and homeostasis. The clinical effect of CGRP mAb on bone turnover is not known, however. METHODS: Between June 2021 and July 2022, a multi-centre prospective cohort study was undertaken with eligible patients undergoing paired testing of the validated bone turnover markers procollagen type I N-terminal propeptide (P1NP) and serum C-terminal telopeptide of type I collagen (CTX) prior to and at least three months following administration of a CGRP mAb. RESULTS: A total of 45 patients with a mean age of 41.8 (SD 11.9) were included in the final analysis, all of whom received a ligand-targeting CGRP mAb. Administration of a CGRP mAb was associated with a statistically significant increase in P1NP from 44.5 microg/L to 51.5 microg/L (p = 0.004), but no significant change in CTX. CONCLUSION: In otherwise homeostatic conditions, short-term administration of a CGRP mAb is associated with increased P1NP, a bone formation marker but not with increased CTX, a bone resorption marker. Further study is required to validate these findings over longer time periods, in a larger cohort, and in pre-existing states of increased calcium stress and bone-turnover

Improving the Diagnosis of Acute Heart Failure Using a Validated Prediction Model

ObjectivesWe sought to derive and validate a prediction model by using N-terminal pro–B-type natriuretic peptide (NT-proBNP) and clinical variables to improve the diagnosis of acute heart failure (AHF).BackgroundThe optimal way of using natriuretic peptides to enhance the diagnosis of AHF remains uncertain.MethodsPhysician estimates of probability of AHF in 500 patients treated in the emergency department from the multicenter IMPROVE CHF (Improved Management of Patients With Congestive Heart Failure) trial recruited between December 2004 and December 2005 were classified into low (0% to 20%), intermediate (21% to 79%), or high (80% to 100%) probability for AHF and then compared with the blinded adjudicated AHF diagnosis. Likelihood ratios were calculated and multiple logistic regression incorporated covariates into an AHF prediction model that was validated internally by the use of bootstrapping and externally by applying the model to another 573 patients from the separate PRIDE (N-Terminal Pro-BNP Investigation of Dyspnea in the Emergency Department) study of the use of NT-proBNP in patients with dyspnea.ResultsLikelihood ratios for AHF with NT-proBNP were 0.11 (95% confidence interval [CI]: 0.06 to 0.19) for cut-point values <300 pg/ml; increasing to 3.43 (95% CI: 2.34 to 5.03) for values 2,700 to 8,099 pg/ml, and 12.80 (95% CI: 5.21 to 31.45) for values ≥8,100 pg/ml. Variables used to predict AHF were age, pre-test probability, and log NT-proBNP. When applied to the external data by use of its adjudicated final diagnosis as the gold standard, the model appropriately reclassified 44% of patients by intermediate clinical probability to either low or high probability of AHF with negligible (<2%) inappropriate redirection.ConclusionsA diagnostic prediction model for AHF that incorporates both clinical assessment and NT-proBNP has been derived and validated and has excellent diagnostic accuracy, especially in cases with indeterminate likelihood for AHF

Overlapping but disparate inflammatory and immunosuppressive responses to SARS-CoV-2 and bacterial sepsis: An immunological time course analysis

Both severe SARS-CoV-2 infections and bacterial sepsis exhibit an immunological dyscrasia and propensity for secondary infections. The nature of the immunological dyscrasias for these differing etiologies and their time course remain unclear. In this study, thirty hospitalized patients with SARS-CoV-2 infection were compared with ten critically ill patients with bacterial sepsis over 21 days, as well as ten healthy control subjects. Blood was sampled between days 1 and 21 after admission for targeted plasma biomarker analysis, cellular phenotyping, and leukocyte functional analysi

M. tuberculosis Reprograms Hematopoietic Stem Cells to Limit Myelopoiesis and Impair Trained Immunity

A greater understanding of hematopoietic stem cell (HSC) regulation is required for dissecting protective versus detrimental immunity to pathogens that cause chronic infections such as Mycobacterium tuberculosis (Mtb). We have shown that systemic administration of Bacille Calmette-Guérin (BCG) or ß-glucan reprograms HSCs in the bone marrow (BM) via a type II interferon (IFN-II) or interleukin-1 (IL1) response, respectively, which confers protective trained immunity against Mtb. Here, we demonstrate that, unlike BCG or ß-glucan, Mtb reprograms HSCs via an IFN-I response that suppresses myelopoiesis and impairs development of protective trained immunity to Mtb. Mechanistically, IFN-I signaling dysregulates iron metabolism, depolarizes mitochondrial membrane potential, and induces cell death specifically in myeloid progenitors. Additionally, activation of the IFN-I/iron axis in HSCs impairs trained immunity to Mtb infection. These results identify an unanticipated immune evasion strategy of Mtb in the BM that controls the magnitude and intrinsic anti-microbial capacity of innate immunity to infection