Exercise training in normobaric hypoxia in endurance runners. I. Improvement in aerobic performance capacity

This study investigates whether a 6-wk intermittent hypoxia training (IHT), designed to avoid reductions in training loads and intensities, improves the endurance performance capacity of competitive distance runners. Eighteen athletes were randomly assigned to train in normoxia [Nor group; n = 9; maximal oxygen uptake (VO2 max) = 61.5 +/- 1.1 ml x kg(-1) x min(-1)] or intermittently in hypoxia (Hyp group; n = 9; VO2 max = 64.2 +/- 1.2 ml x kg(-1) x min(-1)). Into their usual normoxic training schedule, athletes included two weekly high-intensity (second ventilatory threshold) and moderate-duration (24-40 min) training sessions, performed either in normoxia [inspired O2 fraction (FiO2) = 20.9%] or in normobaric hypoxia (FiO2) = 14.5%). Before and after training, all athletes realized 1) a normoxic and hypoxic incremental test to determine VO2 max and ventilatory thresholds (first and second ventilatory threshold), and 2) an all-out test at the pretraining minimal velocity eliciting VO2 max to determine their time to exhaustion (T(lim)) and the parameters of O2 uptake (VO2) kinetics. Only the Hyp group significantly improved VO2 max (+5% at both FiO2, P < 0.05), without changes in blood O2-carrying capacity. Moreover, T(lim) lengthened in the Hyp group only (+35%, P < 0.001), without significant modifications of VO2 kinetics. Despite similar training load, the Nor group displayed no such improvements, with unchanged VO2 max (+1%, nonsignificant), T(lim) (+10%, nonsignificant), and VO2 kinetics. In addition, T(lim) improvements in the Hyp group were not correlated with concomitant modifications of other parameters, including VO2 max or VO2 kinetics. The present IHT model, involving specific high-intensity and moderate-duration hypoxic sessions, may potentialize the metabolic stimuli of training in already trained athletes and elicit peripheral muscle adaptations, resulting in increased endurance performance capacity.

Assessing dynamics of forced livestock movements, livelihoods and future development options for pastoralists/agro-pastoralists in Ruvuma and Lindi Regions, in the Southern Tanzania

The study that aimed at understanding the dynamics of forced livestock movements and pastoral livelihood and development options was conducted in Lindi and Ruvuma regions, using both formal and informal approaches. Data were collected from 60 randomly selected Agro-pastoralists/Pastoralists and native farmers using a structured questionnaire. Four villages were involved; two in Lindi region (Matandu and Mkwajuni) and the other two in Ruvuma region (Gumbiro and Muhuwesi). Data were analyzed using descriptive statistics of SPSS to generate means and frequencies. The results indicate that a large number of animals moved into the study area following the eviction order of the government in Ihefu wetlands in 2006/2007. Lindi region was earmarked by the government to receive all the evicted pastoralists. However, by 2008 only 30% of the total cattle that were expected to move into the region had been received. Deaths of many animals on transit, selling of the animals to pay for transportation and other costs while on transit and many pastoralists settling in Coastal and Ruvuma regions before reaching their destinations were reported to be the reasons for the discrepancy observed. To mitigate anticipated conflicts between farmers and pastoralists, Participatory Land Use Management (PLUM) plans were developed in all the study villages in order to demarcate village land area into different uses, including grazing, cropping, settlement and forests. Land units for grazing were supposed to be provided with all necessary livestock infrastructures (dips, charcoal dams, livestock markets and stock routes). However, the land use plans were not able to prevent the anticipated conflicts because most of the livestock infrastructures were lacking, the land use boundaries were not clearly demarcated and there was limited enforcement of village by-laws, since most had not been enacted by the respective district councils. Similarly, the areas allocated for grazing were inadequate for the number of livestock available and thus the carrying capacity exceeded. Thus, land resource-based conflicts between farmers and pastoralists were emerging in the study areas for the reason that most of the important components in the PLUM plans were not in place. Nevertheless, the arrival of pastoralists in the study areas had positive effects on food security and growth of social interactions between pastoralists and farmers including marriages between them. Environmental degradations due to the arrival of livestock were also not evident. Thus, there is a need for the government to purposely set aside enough grazing land with all necessary infrastructures in place for the agro-pastoral/pastoral communities in the country.

Sustainable Pasture Management : LforS learning and simulation game

Three teams consisting of 2 to 5 persons each play the game. Each team represents a farm. Each team decides jointly on its strategy. In annual meetings in winter, the farm teams jointly discuss, evaluate and decide on how to proceed and actions to be taken. The farms make use of three different pasture areas (village pasture, intensive pasture and summer pasture) for grazing their livestock. The carrying capacity of each pasture area is different and varies according to the season. In each season, the farms have to decide on how many livestock units to graze on which pasture. Overgrazing and pasture degradation occur if the total number of livestock units exceeds the carrying capacity of a specific pasture area. Overgrazing results in a reduction of pasture productivity. To diversify and improve their livelihood strategy farms can make individual investments to increase productivity at the farm level, eg. in fodder production or in income generating activities. At the community level, collective investments can be made which may influence livestock and household economy, e.g. rehabilitate and improve pasture productivity, improve living conditions on remote pastures etc. Events occurring in the course of the game represent different types of (risk) factors such as meteorology, market, politics etc. that may positively or negatively influence livestock production and household economy. A sustainable management of pastures requires that farms actively regulate the development of their herds, that they take measures to prevent pasture degradation and to improve pasture productivity, and that they find a balance between livestock economy and other productive activities. The game has a double aim: a) each farm aims at its economic success and prosperity, and b) the three farm teams jointly have to find and implement strategies for a sustainable use of pasture areas.

Spinal muscular atrophy: SMN2 pre-mRNA splicing corrected by a U7 snRNA derivative carrying a splicing enhancer sequence

Spinal muscular atrophy (SMA) is a lethal hereditary disease caused by homozygous deletion/inactivation of the survival of motoneuron 1 (SMN1) gene. The nearby SMN2 gene, despite its identical coding capacity, is only an incomplete substitute, because a single nucleotide difference impairs the inclusion of its seventh exon in the messenger RNA (mRNA). This splicing defect can be corrected (transiently) by specially designed oligonucleotides. Here we have developed a more permanent correction strategy based on bifunctional U7 small nuclear RNAs (snRNAs). These carry both an antisense sequence that allows specific binding to exon 7 and a splicing enhancer sequence that will improve the recognition of the targeted exon. When expression cassettes for these RNAs are stably introduced into cells, the U7 snRNAs become incorporated into small nuclear ribonucleoprotein (snRNP) particles that will induce a durable splicing correction. We have optimized this strategy to the point that virtually all SMN2 pre-mRNA becomes correctly spliced. In fibroblasts from an SMA patient, this approach induces a prolonged restoration of SMN protein and ensures its correct localization to discrete nuclear foci (gems).