Return to play after thigh muscle injury in elite football players: implementation and validation of the Munich muscle injury classification

Background: Owing to the complexity and heterogeneity of muscle injuries, a generally accepted classification system is still lacking. Aims To prospectively implement and validate a novel muscle injury classification and to evaluate its predictive value for return to professional football. Methods: The recently described Munich muscle injury classification was prospectively evaluated in 31 European professional male football teams during the 2011/2012 season. Thigh muscle injury types were recorded by team medical staff and correlated to individual player exposure and resultant time-loss. Results: In total, 393 thigh muscle injuries occurred. The muscle classification system was well received with a 100% response rate. Two-thirds of thigh muscle injuries were classified as structural and were associated with longer lay-off times compared to functional muscle disorders (p<0.001). Significant differences were observed between structural injury subgroups (minor partial, moderate partial and complete injuries) with increasing lay-off time associated with more severe structural injury. Median lay-off time of functional disorders was 5–8 days without significant differences between subgroups. There was no significant difference in the absence time between anterior and posterior thigh injuries. Conclusions: The Munich muscle classification demonstrates a positive prognostic validity for return to play after thigh muscle injury in professional male football players. Structural injuries are associated with longer average lay-off times than functional muscle disorders. Subclassification of structural injuries correlates with return to play, while subgrouping of functional disorders shows less prognostic relevance. Functional disorders are often underestimated clinically and require further systematic study

CLiFF-LHMP: Using Spatial Dynamics Patterns for Long-Term Human Motion Prediction

Human motion prediction is important for mobile service robots and intelligent vehicles to operate safely and smoothly around people. The more accurate predictions are, particularly over extended periods of time, the better a system can, e.g., assess collision risks and plan ahead. In this paper, we propose to exploit maps of dynamics (MoDs, a class of general representations of place-dependent spatial motion patterns, learned from prior observations) for long-term human motion prediction (LHMP). We present a new MoD-informed human motion prediction approach, named CLiFF-LHMP, which is data efficient, explainable, and insensitive to errors from an upstream tracking system. Our approach uses CLiFF-map, a specific MoD trained with human motion data recorded in the same environment. We bias a constant velocity prediction with samples from the CLiFF-map to generate multi-modal trajectory predictions. In two public datasets we show that this algorithm outperforms the state of the art for predictions over very extended periods of time, achieving 45% more accurate prediction performance at 50s compared to the baseline.Comment: Accepted to the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS

Marine phytoplankton community data and corresponding environmental properties from eastern Norway, 1896–2020

Time series are essential for studying the long-term effects of human impact and climatic changes on the natural environment. Although data exist, no long-term phytoplankton dataset for the Norwegian coastal area has been compiled and made publicly available in a standardised format. Here we report on a compilation of phytoplankton data from inner Oslofjorden going back more than a century. The database contains 605 sampling events from 1896 to 2020, and environmental data has also been provided when available. Although the sampling frequency has varied over time, the high taxonomic quality and relatively similar methodology make it very useful. For the last 15 years (2006–2020), the sampling frequency has been almost monthly throughout the year. This dataset can be used for time series analysis to understand community structure and changes over time. It can also be used to study common taxa’ responses to environmental variables and changes, seasonal or annual species diversity and be useful for developing ecological indicators.publishedVersio

Overvåking av Indre Oslofjord i 2011

Denne rapporten gir en kortfattet oversikt over resultatene fra overvåkingen foretatt for Fagrådet for vann- og avløpsteknisk samarbeid i Indre Oslofjord i 2011. En mer utfyllende beskrivelse av resultatene er presentert i en vedleggsrapport (l. nr.6372). Undersøkelsene omfatter fysiske, kjemiske og biologiske forhold. Overgjødsling har vært et hovedtema i overvåkingen, men miljøgiftsproblematikk er nå også inkludert. Overvåkingen i 2011 ble gjennomført av Norsk institutt for vannforskning (NIVA) i samarbeid med Biologisk Institutt ved Universitetet i Oslo (UiO). Havforskningsinstituttet (HI) har også vært involvert.Fagrådet for vann- og avløpsteknis

The ILIAD Safety Stack: Human-Aware Infrastructure-Free Navigation of Industrial Mobile Robots

Safe yet efficient operation of professional service robots within logistics or production in human-robot shared environments requires a flexible human-aware navigation stack. In this manuscript, we propose the ILIAD safety stack comprising software and hardware designed to achieve safe and efficient motion specifically for industrial vehicles with nontrivial kinematics The stack integrates five interconnected layers for autonomous motion planning and control to enable short- and long-term reasoning. The use-case scenario tested requires an autonomous industrial forklift to safely navigate among pick-and-place locations during normal daily activities involving human workers. Our test-bed in the real world consists of a three-day experiment in a food distribution warehouse. The evaluation is extended in simulation with an ablation study of the impact of different layers to show both the practical and the performance-related impact. The experimental results show a safer and more legible robot when humans are nearby with a trade-off in task efficiency, and that not all layers have the same degree of impact in the system

Genome-wide Association Analysis Identifies 14 New Risk Loci for Schizophrenia

Schizophrenia is a heritable disorder with substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases, 6,243 controls) followed by meta-analysis with prior schizophrenia GWAS (8,832 cases, 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls, and 581 trios). In total, 22 regions met genome-wide significance (14 novel and one previously implicated in bipolar disorder). The results strongly implicate calcium signaling in the etiology of schizophrenia, and include genome-wide significant results for CACNA1C and CACNB2 whose protein products interact. We estimate that ∼8,300 independent and predominantly common SNPs contribute to risk for schizophrenia and that these collectively account for most of its heritability. Common genetic variation plays an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this devastating disorder

Thoracic dysfunction in whiplash associated disorders: A systematic review

© 2018 Heneghan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background Research investigating Whiplash Associated Disorder (WAD) has largely focused on the cervical spine yet symptoms can be widespread. Thoracic spine pain prevalence is reported ~66%; perhaps unsurprising given the forceful stretch/eccentric loading of posterior structures of the spine, and the thoracic spine’s contribution to neck mobility/function. Approximately 50% WAD patients develop chronic pain and disability resulting in high levels of societal and healthcare costs. It is time to look beyond the cervical spine to fully understand anatomical dysfunction in WAD and provide new directions for clinical practice and research. Purpose To evaluate the scope and nature of dysfunction in the thoracic region in patients with WAD. Methods A systematic review and data synthesis was conducted according to a pre-defined, registered (PROSPERO, CRD42015026983) and published protocol. All forms of observational study were included. A sensitive topic-based search strategy was designed from inception to 1/06/16. Databases, grey literature and registers were searched using a study population terms and key words derived from scoping search. Two reviewers independently searched information sources, assessed studies for inclusion, extracted data and assessed risk of bias. A third reviewer checked for consistency and clarity. Extracted data included summary data: sample size and characteristics, outcomes, and timescales to reflect disorder state. Risk of bias was assessed using the Newcastle-Ottawa Scale. Data were tabulated to allow enabling a semi-qualitative comparison and grouped by outcome across studies. Strength of the overall body of evidence was assessed using a modified GRADE. Results Thirty eight studies (n>50,000) which were conducted across a range of countries were included. Few authors responded to requests for further data (5 of 9 contacted). Results were reported in the context of overall quality and were presented for measures of pain or dysfunction and presented, where possible, according to WAD severity and time point post injury. Key findings include: 1) high prevalence of thoracic pain (>60%); higher for those with more severe presentations and in the acute stage, 2) low prevalence of chest pain

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups