566 research outputs found
Development of a direct match technique for star identification on the SWAS mission
A direct match technique for star identification was developed for use with the star tracker on the SWAS (Submillimeter Wave Astronomy Satellite) spacecraft. In this technique, tracker searches are used in a two-step process for an implicit direct match star identification. A simulation of the star acquisition process was created and used in the preparation of guide star selection requirements. Flight software implementing this star acquisition technique has been developed and tested
Recovering 6D Object Pose: A Review and Multi-modal Analysis
A large number of studies analyse object detection and pose estimation at
visual level in 2D, discussing the effects of challenges such as occlusion,
clutter, texture, etc., on the performances of the methods, which work in the
context of RGB modality. Interpreting the depth data, the study in this paper
presents thorough multi-modal analyses. It discusses the above-mentioned
challenges for full 6D object pose estimation in RGB-D images comparing the
performances of several 6D detectors in order to answer the following
questions: What is the current position of the computer vision community for
maintaining "automation" in robotic manipulation? What next steps should the
community take for improving "autonomy" in robotics while handling objects? Our
findings include: (i) reasonably accurate results are obtained on
textured-objects at varying viewpoints with cluttered backgrounds. (ii) Heavy
existence of occlusion and clutter severely affects the detectors, and
similar-looking distractors is the biggest challenge in recovering instances'
6D. (iii) Template-based methods and random forest-based learning algorithms
underlie object detection and 6D pose estimation. Recent paradigm is to learn
deep discriminative feature representations and to adopt CNNs taking RGB images
as input. (iv) Depending on the availability of large-scale 6D annotated depth
datasets, feature representations can be learnt on these datasets, and then the
learnt representations can be customized for the 6D problem
An international guideline with six personalised titration schedules for preventing myocarditis and pneumonia associated with clozapine
White blood cell (WBC) monitoring has reduced clozapine-treated patient deaths associated with agranulocytosis to a rarity. However, clozapine protocols and package inserts worldwide provide no instructions for preventing myocarditis or pneumonia during clozapine titrations. Prescribers worldwide are largely unaware of that. Meanwhile, as they worry about agranulocytosis, their clozapine-treated patients are at risk of dying from pneumonia or myocarditis. Consequently, an international guideline with 104 authors from 50 countries/regions was recently published to provide personalised clozapine titration schedules for adult inpatients. This forum article reviews pneumonia and myocarditis occurring during clozapine titration, as well as the three most innovative aspects of this new guideline: (1) personalised titration, (2) C reactive protein (CRP) measures, and (3) dose predictions based on blood levels. Clozapine metabolism is influenced by 3 levels of complexity: (1) ancestry groups, (2) sex-smoking subgroups, and (3) presence/absence of poor metabolizer status. These 3 groups of variables should determine the maintenance dose and speed of clozapine titration; they are summarised in a table in the full-text. The international clozapine titration guideline recommends measuring CRP levels simultaneously with WBC, at baseline and weekly at least for the first 4 weeks of titration, the highest risk period for clozapine-induced myocarditis
Patients’ Knowledge and Attitudes Toward Psychiatric Medication on Admission to an Inpatient Behavioral Health Unit
Evidence-based decision support for pediatric rheumatology reduces diagnostic errors.
BACKGROUND: The number of trained specialists world-wide is insufficient to serve all children with pediatric rheumatologic disorders, even in the countries with robust medical resources. We evaluated the potential of diagnostic decision support software (DDSS) to alleviate this shortage by assessing the ability of such software to improve the diagnostic accuracy of non-specialists.
METHODS: Using vignettes of actual clinical cases, clinician testers generated a differential diagnosis before and after using diagnostic decision support software. The evaluation used the SimulConsult® DDSS tool, based on Bayesian pattern matching with temporal onset of each finding in each disease. The tool covered 5405 diseases (averaging 22 findings per disease). Rheumatology content in the database was developed using both primary references and textbooks. The frequency, timing, age of onset and age of disappearance of findings, as well as their incidence, treatability, and heritability were taken into account in order to guide diagnostic decision making. These capabilities allowed key information such as pertinent negatives and evolution over time to be used in the computations. Efficacy was measured by comparing whether the correct condition was included in the differential diagnosis generated by clinicians before using the software ( unaided ), versus after use of the DDSS ( aided ).
RESULTS: The 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p \u3c 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an open book approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software.
CONCLUSIONS: These findings suggest that decision support can reduce diagnostic errors and improve use of relevant information by generalists. Such assistance could potentially help relieve the shortage of experts in pediatric rheumatology and similarly underserved specialties by improving generalists\u27 ability to evaluate and diagnose patients presenting with musculoskeletal complaints.
TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02205086
Pipamperone Population Pharmacokinetics Related to Effectiveness and Side Effects in Children and Adolescents
Background: Pipamperone is a frequently prescribed antipsychotic in children and adolescents in the Netherlands, Belgium, and Germany. However, pediatric pharmacokinetics and the relationship with side effects and efficacy are unknown. Currently, divergent pediatric dosing recommendations exist. Objectives: The objective of this study was to describe the population pharmacokinetics of pipamperone in children and adolescents; to correlate measured and predicted pipamperone trough concentrations and predicted 24-h area under the curves with effectiveness, extrapyramidal symptoms, and sedation; and to propose dose recommendations based on simulations. Methods: Pipamperone concentrations were collected from Dutch pediatric patients in a prospective naturalistic trial (n = 8), and German pediatric patients in a therapeutic drug monitoring service (n = 22). A total of 70 pipamperone concentrations were used to develop a population pharmacokinetic model with non-linear mixed-effects modeling (NONMEM®). Additionally, an additional random sample of 21 German patients with 33 pipamperone concentrations from the same therapeutic drug monitoring service was used for external validation. Pharmacokinetic parameters were related to clinical improvement, sedation, and extrapyramidal symptoms. Simulations were performed to determine optimal dosages. Results: In a one-compartment model, the apparent volume of distribution was 416 L/70 kg and the apparent clearance was 22.1 L/h/70 kg. Allometric scaling was used to correct for differences in bodyweight. The model was successfully externally validated. The median [25th–75th percentile] measured pipamperone trough concentrations were numerically higher in responders (98.0 µg/L [56.0–180.5 µg/L]) than in non-responders (58.0 µg/L [14.9–105.5 µg/L]), although non-significant (p = 0.14). A twice-daily 0.6-mg/kg dosage was better than a fixed dosage to attain the concentration range observed in responders. Conclusions: Our findings suggest that pipamperone therapeutic reference ranges may be lower for children with behavioral problems than recommended for adults with psychotic symptoms (100–400 µg/L). When dosing pipamperone in children and adolescents, bodyweight should be taken into account
One-year follow-up on liraglutide treatment for prediabetes and overweight/obesity in clozapine- or olanzapine-treated patients
Four small puzzles that Rosetta doesn't solve
A complete macromolecule modeling package must be able to solve the simplest
structure prediction problems. Despite recent successes in high resolution
structure modeling and design, the Rosetta software suite fares poorly on
deceptively small protein and RNA puzzles, some as small as four residues. To
illustrate these problems, this manuscript presents extensive Rosetta results
for four well-defined test cases: the 20-residue mini-protein Trp cage, an even
smaller disulfide-stabilized conotoxin, the reactive loop of a serine protease
inhibitor, and a UUCG RNA tetraloop. In contrast to previous Rosetta studies,
several lines of evidence indicate that conformational sampling is not the
major bottleneck in modeling these small systems. Instead, approximations and
omissions in the Rosetta all-atom energy function currently preclude
discriminating experimentally observed conformations from de novo models at
atomic resolution. These molecular "puzzles" should serve as useful model
systems for developers wishing to make foundational improvements to this
powerful modeling suite.Comment: Published in PLoS One as a manuscript for the RosettaCon 2010 Special
Collectio
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