Increased risk of lower limb osteoarthritis among former professional soccer (football) players

Background: Soccer is a high-speed contact sport with risk of injury. Despite long-standing concern, evidence to date remains inconsistent as to the association between playing professional-level soccer and lifelong musculoskeletal consequences. Aims: The objectives were to assess risk of osteoarthritis in former professional soccer players compared to matched general population controls, and subsequently assess associated musculoskeletal disorders which may contribute to, or result from, osteoarthritis—specifically meniscal injury and joint replacement. Methods: We conducted a retrospective cohort study using national electronic health records (EHRs) on a cohort of 7676 former professional soccer players aged 40 or over at recruitment, matched on year of birth, sex (all male) and socio-economic status with 23 028 general population controls. Outcomes of interest were obtained by utilizing individual-level record linkage to EHRs from general hospital inpatient and day-case admissions. Results: Compared to controls, former soccer players showed a greater risk of hospital admission for osteoarthritis (hazard ratio [HR] 3.01; 95% confidence interval [CI] 2.80–3.25; P < 0.001). This increased risk appeared age dependant, normalizing over age 80 years and reflective of increased risk of lower limb osteoarthritis. Further, risk of hospital admissions for meniscal injury (HR 2.73; 95% CI 2.42–3.08; P < 0.001) and joint replacement (HR 2.82; 95% CI 2.23–3.57; P < 0.001) were greater among former soccer players. Conclusions: We report an increased risk of lower limb osteoarthritis in former soccer players when compared with matched population controls. The results of this research add data in support of lower limb osteoarthritis among former soccer players representing a potential industrial injury

Tomato: a crop species amenable to improvement by cellular and molecular methods

Tomato is a crop plant with a relatively small DNA content per haploid genome and a well developed genetics. Plant regeneration from explants and protoplasts is feasable which led to the development of efficient transformation procedures. In view of the current data, the isolation of useful mutants at the cellular level probably will be of limited value in the genetic improvement of tomato. Protoplast fusion may lead to novel combinations of organelle and nuclear DNA (cybrids), whereas this technique also provides a means of introducing genetic information from alien species into tomato. Important developments have come from molecular approaches. Following the construction of an RFLP map, these RFLP markers can be used in tomato to tag quantitative traits bred in from related species. Both RFLP's and transposons are in the process of being used to clone desired genes for which no gene products are known. Cloned genes can be introduced and potentially improve specific properties of tomato especially those controlled by single genes. Recent results suggest that, in principle, phenotypic mutants can be created for cloned and characterized genes and will prove their value in further improving the cultivated tomato.

A review of techniques for parameter sensitivity analysis of environmental models

Mathematical models are utilized to approximate various highly complex engineering, physical, environmental, social, and economic phenomena. Model parameters exerting the most influence on model results are identified through a ‘sensitivity analysis’. A comprehensive review is presented of more than a dozen sensitivity analysis methods. This review is intended for those not intimately familiar with statistics or the techniques utilized for sensitivity analysis of computer models. The most fundamental of sensitivity techniques utilizes partial differentiation whereas the simplest approach requires varying parameter values one-at-a-time. Correlation analysis is used to determine relationships between independent and dependent variables. Regression analysis provides the most comprehensive sensitivity measure and is commonly utilized to build response surfaces that approximate complex models.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42691/1/10661_2004_Article_BF00547132.pd