Ibuprofen-loaded calcium phosphate granules : combination of innovative characterization methods to relate mechanical strength to drug location

This paper studies the impact of the location of a drug substance on the physicochemical and mechanical properties of two types of calcium phosphate granules loaded with seven different contents of ibuprofen, ranging from 1.75% to 46%. These implantable agglomerates were produced by either low or high shear granulation. Unloaded Mi-Pro pellets presented higher sphericity and mechanical properties, but were slightly less porous than Kenwood granules (57.7% vs 61.2%). Nevertheless, the whole expected quantity of ibuprofen could be integrated into both types of granules. A combination of surface analysis, using near-infrared (NIR) spectroscopy coupling chemical imaging, and pellet porosity, by mercury intrusion measurements, allowed ibuprofen to be located. It was shown that, from 0% to 22% drug content, ibuprofen deposited simultaneously on the granule surface, as evidenced by the increase in surface NIR signal, and inside the pores, as highlighted by the decrease in pore volume. From 22%, porosity was almost filled, and additional drug substance coated the granule surfaces, leading to a large increase in the surface NIR signal. This coating was more regular for Mi-Pro pellets owing to their higher sphericity and greater surface deposition of drug substance. Unit crush tests using a microindenter revealed that ibuprofen loading enhanced the mechanical strength of granules, especially above 22% drug content, which was favorable to further application of the granules as a bone defect filler

Identification of road user related risk factors, deliverable 4.1 of the H2020 project SafetyCube.

Safety CaUsation, Benefits and Efficiency (SafetyCube) is a European Commission supported Horizon 2020 project with the objective of developing an innovative road safety Decision Support System (DSS). The DSS will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures, and cost-effective approaches to reduce casualties of all road user types and all severities. This document is the first deliverable (4.1) of work package 4 which is dedicated to identifying and assessing human related risk factors and corresponding countermeasures as well as their effect on road safety. The focus of deliverable 4.1 is on identification and assessment of risk factors and describes the corresponding operational procedure and corresponding outcomes. The following steps have been carried out: Identification of human related risk factors – creation of a taxonomy Consultation of relevant stakeholders and policy papers for identification of topic with high priority (‘hot topics’) Systematic literature search and selection of relevant studies on identified risk factors •Coding of studies •Analysis of risk factors on basis of coded studies •Synopses of risk factors, including accident scenarios The core output of this task are synopses of risk factors which will be available through the DSS. Within the synopses, each risk factor was analysed systematically on basis of scientific studies and is further assigned to one of four levels of risk (marked with a colour code). Essential information of the more than 180 included studies were coded and will also be available in the database of the DSS. Furthermore, the synopses contain theoretical background on the risk factor and are prepared in different sections with different levels of detail for an academic as well as a non-academic audience. These sections are readable independently. It is important to note that the relationship between road safety and road user related risk factors is a difficult task. For some risk factors the available studies focused more on conditions of the behaviour (in which situations the behaviour is shown or which groups are more likely to show this behaviour) rather than the risk factor itself. Therefore, it cannot be concluded that those risk factors that have not often been studied or have to rely more indirect and arguably weaker methodologies, e.g. self-reports , do not increase the chance of a crash occurring. The following analysed risk factors were assessed as ‘risky’, ‘probably risky’ or ‘unclear’. No risk factors were identified as ‘probably not risky’. Risky Probably risky Unclear • Influenced driving – alcohol • Influenced Driving – drugs (legal & illegal) • Speeding and inappropriate speed • Traffic rule violations – red light running • Distraction – cell phone use (hand held) • Distraction – cell phone use (hands free) • Distraction – cell phone use (texting) • Fatigue – sleep disorders – sleep apnea • Risk taking – overtaking • Risk taking – close following behaviour • Insufficient knowledge and skills • Functional impairment – cognitive impairment • Functional impairment – vision loss • Diseases and disorders – diabetes • Personal factors – sensation seeking • Personal factors – ADHD • Emotions – anger, aggression • Fatigue – Not enough sleep/driving while tired • Distraction – conversation with passengers • Distraction – outside of vehicle • Distraction – cognitive overload and inattention • Functional impairment – hearing loss (few studies) • Observation errors (few studies) • Distraction – music – entertainment systems (many studies, mixed results) • Distraction – operating devices (many studies, mixed results) The next step in SafetyCube’s WP4 is to identify and assess the effectiveness of measures and to establish a link to the identified risk factors. The work of this first task indicates a set of risk factors that should be centre of attention when identifying corresponding road safety measures (category ‘risky’)

Identification of road user related risk factors, Deliverable 4.1 of the H2020 project SafetyCube (Safety CaUsation, Benefits and Efficiency).

Safety CaUsation, Benefits and Efficiency (SafetyCube) is a European Commission supported Horizon 2020 project with the objective of developing an innovative road safety Decision Support System (DSS). The DSS will enable policy-makers and stakeholders to select and implement the most appropriate strategies, measures, and cost-effective approaches to reduce casualties of all road user types and all severities. This document is the first deliverable (4.1) of work package 4 which is dedicated to identifying and assessing human related risk factors and corresponding countermeasures as well as their effect on road safety. The focus of deliverable 4.1 is on identification and assessment of risk factors and describes the corresponding operational procedure and corresponding outcomes. The following steps have been carried out: * Identification of human related risk factors — creation of a taxonomy; * Consultation of relevant stakeholders and policy papers for identification of topic with high priority (‘hot topics’); * Systematic literature search and selection of relevant studies on identified risk factors; * Coding of studies; * Analysis of risk factors on basis of coded studies; and * Synopses of risk factors, including accident scenarios The core output of this task are synopses of risk factors which will be available through the DSS. Within the synopses, each risk factor was analysed systematically on basis of scientific studies and is further assigned to one of four levels of risk (marked with a colour code). Essential information of the more than 180 included studies were coded and will also be available in the database of the DSS. Furthermore, the synopses contain theoretical background on the risk factor and are prepared in different sections with different levels of detail for an academic as well as a non-academic audience. These sections are readable independently. It is important to note that the relationship between road safety and road user related risk factors is a difficult task. For some risk factors the available studies focused more on conditions of the behaviour (in which situations the behaviour is shown or which groups are more likely to show this behaviour) rather than the risk factor itself. Therefore, it cannot be concluded that those risk factors that have not often been studied or have to rely more indirect and arguably weaker methodologies, e.g. self-reports , do not increase the chance of a crash occurring. The following analysed risk factors were assessed as ‘risky’, ‘probably risky’ or ‘unclear’. No risk factors were identified as ‘probably not risky’. The next step in SafetyCube’s WP4 is to identify and assess the effectiveness of measures and to establish a link to the identified risk factors. The work of this first task indicates a set of risk factors that should be centre of attention when identifying corresponding road safety measures (category ‘risky’). (Author/publisher

Effectiveness of two cognitive training programs on the performance of older drivers with a cognitive self-assessment bias

Purpose: Depending on the calibration of their cognitive abilities, some older drivers (ODs) might stop driving prematurely (under-estimators, UEs) and others could expose themselves to risky situations (over-estimators, OEs). The aim of the study was to compare the effectiveness of two cognitive training (CT) programs intended for ODs presenting a cognitive calibration bias. We hypothesized that CT with feedback on performance can help ODs to correctly calibrate their abilities and consequently adapt their driving behavior.Method: One hundred and six ODs (≥70 years) were assigned to two CT groups (with or without a driving simulator experience, DS). These interventions lasted about 36 h and were distributed over a 3-month period. ODs completed objective and subjective cognitive evaluations and an on-road driving evaluation before and after training.Results: The first results on 67 participants (40 from the CT group, and 27 from the CT + DS group) showed an improvement of their visual processing speed, their divided attention and their selective attention after training. Participants from both groups also had an improved TRIP tactical sub-score (Test Ride for Investigating Practical fitness to drive), indicating a better driving behavioral adaptation. Finally, although both training programs seemed to be equally effective in correcting cognitive calibration bias, the results indicated that 21 UEs and 10 OEs were well calibrated and thus correctly self-assessed their cognitive abilities after training.Conclusion: Both CT programs (with or without DS experience) seem to improve the visual attention of ODs. UEs appeared to be more susceptible than OEs to this training and were better calibrated after it