Comparative Analysis of Cervical Spine Management in a Subset of Severe Traumatic Brain Injury Cases Using Computer Simulation

BACKGROUND: No randomized control trial to date has studied the use of cervical spine management strategies in cases of severe traumatic brain injury (TBI) at risk for cervical spine instability solely due to damaged ligaments. A computer algorithm is used to decide between four cervical spine management strategies. A model assumption is that the emergency room evaluation shows no spinal deficit and a computerized tomogram of the cervical spine excludes the possibility of fracture of cervical vertebrae. The study's goal is to determine cervical spine management strategies that maximize brain injury functional survival while minimizing quadriplegia. METHODS/FINDINGS: The severity of TBI is categorized as unstable, high risk and stable based on intracranial hypertension, hypoxemia, hypotension, early ventilator associated pneumonia, admission Glasgow Coma Scale (GCS) and age. Complications resulting from cervical spine management are simulated using three decision trees. Each case starts with an amount of primary and secondary brain injury and ends as a functional survivor, severely brain injured, quadriplegic or dead. Cervical spine instability is studied with one-way and two-way sensitivity analyses providing rankings of cervical spine management strategies for probabilities of management complications based on QALYs. Early collar removal received more QALYs than the alternative strategies in most arrangements of these comparisons. A limitation of the model is the absence of testing against an independent data set. CONCLUSIONS: When clinical logic and components of cervical spine management are systematically altered, changes that improve health outcomes are identified. In the absence of controlled clinical studies, the results of this comparative computer assessment show that early collar removal is preferred over a wide range of realistic inputs for this subset of traumatic brain injury. Future research is needed on identifying factors in projecting awakening from coma and the role of delirium in these cases

Leaf photosynthesis and respiration of three bioenergy crops in relation to temperature and leaf nitrogen: how conserved are biochemical model parameters among crop species?

Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model

Lablab purpureus—A Crop Lost for Africa?

In recent years, so-called ‘lost crops’ have been appraised in a number of reviews, among them Lablab purpureus in the context of African vegetable species. This crop cannot truly be considered ‘lost’ because worldwide more than 150 common names are applied to it. Based on a comprehensive literature review, this paper aims to put forward four theses, (i) Lablab is one of the most diverse domesticated legume species and has multiple uses. Although its largest agro-morphological diversity occurs in South Asia, its origin appears to be Africa. (ii) Crop improvement in South Asia is based on limited genetic diversity. (iii) The restricted research and development performed in Africa focuses either on improving forage or soil properties mostly through one popular cultivar, Rongai, while the available diversity of lablab in Africa might be under threat of genetic erosion. (iv) Lablab is better adapted to drought than common beans (Phaseolus vulgaris) or cowpea (Vigna unguiculata), both of which have been preferred to lablab in African agricultural production systems. Lablab might offer comparable opportunities for African agriculture in the view of global change. Its wide potential for adaptation throughout eastern and southern Africa is shown with a GIS (geographic information systems) approach

Transpiration and leaf growth of potato clones in response to soil water deficit

Potato (Solanum tuberosum ssp. Tuberosum) crop is particularly susceptible to water deficit because of its small and shallow root system. The fraction of transpirable soil water (FTSW) approach has been widely used in the evaluation of plant responses to water deficit in different crops. The FTSW 34 threshold (when stomatal closure starts) is a trait of particular interest because it is an indicator of tolerance to water deficit. The FTSW threshold for decline in transpiration and leaf growth was evaluated in a drying soil to identify potato clones tolerant to water deficit. Two greenhouse experiments were carried out in pots, with three advanced clones and the cultivar Asterix. The FTSW, transpiration and leaf growth were measured on a daily basis, during the period of soil drying. FTSW was an efficient method to separate potato clones with regard to their response to water deficit. The advancedclones SMINIA 02106-11 and SMINIA 00017-6 are more tolerant to soil water deficit than the cultivar Asterix, and the clone SMINIA 793101-3 is more tolerant only under high solar radiation

Enhanced risk management and decision-making capability across the sugarcane industry value chain based on seasonal climate forecasts

Sugarcane industries worldwide are exposed to uncertainty associated with variable climate. This variability produces impacts across an integrated value chain comprising of the following industry sectors: cane growing, harvesting and transport, milling, and marketing. The purpose of this paper is to advocate a comprehensive systems approach for using seasonal climate forecast systems to improve risk management and decision-making capability across all sugarcane industry sectors. The application of this approach is outlined for decisions relating to yield forecasting, harvest management, and the use of irrigation. Key lessons learnt from this approach include the need for a participative R&D approach with stakeholders and the need to consider the whole industry value chain. Additionally, there is the need for climate forecast systems to target the varying needs of sugarcane industries