Accumulation and Distribution of Zn in the Shoots and Reproductive Structures of the Halophyte Plant Species Kosteletzkya Virginica as a Function of Salinity.

Accumulation and distribution of Zn in the shoots and reproductive structures of the halophyte plant species Kosteletzkya virginica as a function of salinity.

Planta. 2013 Jun 2;
Han R, Quinet M, André E, van Elteren JT, Destrebecq F, Vogel-Mikuš K, Cui G, Debeljak M, Lefèvre I, Lutts S

Kosteletzkya virginica is a wetland halophyte that is a good candidate for rehabilitation of degraded salt marshes and production of oil as biodiesel. Salt marshes are frequently contaminated by heavy metals. The distribution of Zn in vegetative and reproductive organs of adult plants, and the NaCl influence on this distribution remain unknown and were thus explored in the present study. Plants were cultivated in a nutrient film technique system, from seedling stage until seed maturation in a control, Zn (100 ?M), NaCl (50 mM) or Zn + NaCl medium. Photosynthesis, ion nutrition, malondialdehyde and non-protein thiol concentrations were quantified. Zinc distribution in reproductive organs was estimated by a laser ablation-inductively coupled plasma-mass spectrometry procedure (LA-ICP-MS). Adult plants accumulated up to 2 mg g(-1) DW Zn in the shoots. Zinc reduced plant growth, inhibited photosynthesis and reduced seed yield. Zinc accumulation in the seeds was only two times higher in Zn-treated plants than in controls. Exogenous NaCl neutralized the damaging action of Zn and modified the Zn distribution through a preferential accumulation of toxic ions in older leaves. Zinc was present in seed testa, endosperm and, to a lower extent, in embryo. Additional NaCl induced a chalazal retention of Zn during seed maturation and reduced final Zn seed content. It is concluded that NaCl 50 mM had a positive impact on the response of K. virginica to Zn toxicity and acts through a modification in Zn distribution rather than a decrease in Zn absorption. HubMed – rehab


Rationale and resources for teaching the mathematical modeling of athletic training and performance.

Adv Physiol Educ. 2013 Jun; 37(2): 134-152
Clarke DC, Skiba PF

A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call “performance modeling,” is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual’s performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences. HubMed – rehab


The Italian cardiological guidelines for eligibility in competitive sports: food for thought in preventive cardiology.

J Cardiovasc Med (Hagerstown). 2013 Jul; 14(7): 518-519
Mezzani A, Giannuzzi P

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Clarification on the Scoring of the Mini-BESTest.

Phys Ther. 2013 Jun; 93(6): 860
Jacobs JV, Kasser SL, Padgett PK

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