西藏墨脱格当乡野生虎捕食家畜现状与保护建议

曾经在西藏东南的阔叶林中广泛分布的孟加拉虎,目前仅有一个小种群残留在墨脱县境内。2000年5－6月间,在大型家畜遭受野生虎捕食最严重的墨脱县格当乡展开调查,试图寻找减轻虎害的方法。结果表明：1994－1995年虎的捕食率达到最高,对牛和骡马的捕食率分别是17．9％和9．4％;但1996年后,捕食率分别降低到7．8％和1．8％,这可能与1996年当地曾捕杀过一头虎有关。1993－1999年间,全乡牛的数量下降了11％,但骡马数量上升了23％,这是因为当地为增加运输能力而从别处购得骡马。据反映,目前格当乡境内大约有4－5头虎。1997年和1999年,均见母虎和小虎同行,说明该种群尚有繁殖。在抽样的21户居民家中,1999年4月到2000年5月间,66．6％的人家有大型牲畜遭虎捕杀,共损失牛27头,马12匹,而自1993年以来,21户中共有18户（85．8％）,有牲畜被杀记录,共计损失117头。其中对牛的捕食率达19．7％,对马达11．9％,平均每户损失牛1．2头,骡马0．5匹。非法狩猎减少了虎的猎物如野猪、羚牛等的数量,是老虎转向家畜的主要原因之一。虎害已对格当乡群众的经济造成较大负面影响。但格当乡以及周边地区保护着中国最后的野生孟加拉虎种群,为确保虎的长期生存同时减少人－虎冲突,建议改变目前放牧方式,尽可能联合放牧、增加看护;改善放牧地条件,清除牧场周围蕨草丛;减少对羚牛等有蹄类的猎杀,以减少对老虎猎物种群的破坏;对部分家畜移入棚内试行圈养,既保护家畜,又提高乳制品产量和增加农家肥料;实行多种经营方法,建议养一些山羊和家禽;政府应该帮助安置好部分愿意外迁的居民,这样既满足这些居民的需要,同时也减轻对当地野生动物种群的压力。     

Design Study of a Cable-based Gait Training Machine

This paper deals with a design approach of a gait training machine based on a quantitative gait analysis.The proposed training machine is composed of a body weight support device and a cable-driven parallel robot.This paper is focused on the cable-driven robot,which controls the pose of the lower limb through an orthosis placed on the patient's leg.The cable robot reproduces a normal gait movement through the motion of the orthosis.A motion capture system is used to perform the quantitative analysis of a normal gait,which will be used as an input to the inverse dynamic model of the cable robot.By means of an optimization algorithm,the optimal design parameters,which minimize the tensions in the cables,are determined.Two constraints are considered,i.e.,a non-negative tension in the cables at all times,and a free cable/end-effector collision.Once the optimal solution is computed,a power analysis is carried out in order to size the robot actuators.The proposed approach can be easily extended for the design study of a similar type of cable robots.     

Sample size determination for classifiers based on single-nucleotide polymorphisms

Single-nucleotide polymorphisms (SNPs), believed to determine human differences, are widely used to predict risk of diseases. Typically, clinical samples are limited and/or the sampling cost is high. Thus, it is essential to determine an adequate sample size needed to build a classifier based on SNPs. Such a classifier would facilitate correct classifications, while keeping the sample size to a minimum, thereby making the studies cost-effective. For coded SNP data from 2 classes, an optimal classifier and an approximation to its probability of correct classification (PCC) are derived. A linear classifier is constructed and an approximation to its PCC is also derived. These approximations are validated through a variety of Monte Carlo simulations. A sample size determination algorithm based on the criterion, which ensures that the difference between the 2 approximate PCCs is below a threshold, is given and its effectiveness is illustrated via simulations. For the HapMap data on Chinese and Japanese populations, a linear classifier is built using 51 independent SNPs, and the required total sample sizes are determined using our algorithm, as the threshold varies. For example, when the threshold value is 0.05, our algorithm determines a total sample size of 166 (83 for Chinese and 83 for Japanese) that satisfies the criterion.     

Genome wide association studies in presence of misclassified binary responses

Background

Misclassification has been shown to have a high prevalence in binary responses in both livestock and human populations. Leaving these errors uncorrected before analyses will have a negative impact on the overall goal of genome-wide association studies (GWAS) including reducing predictive power. A liability threshold model that contemplates misclassification was developed to assess the effects of mis-diagnostic errors on GWAS. Four simulated scenarios of case–control datasets were generated. Each dataset consisted of 2000 individuals and was analyzed with varying odds ratios of the influential SNPs and misclassification rates of 5% and 10%.

Results

Analyses of binary responses subject to misclassification resulted in underestimation of influential SNPs and failed to estimate the true magnitude and direction of the effects. Once the misclassification algorithm was applied there was a 12% to 29% increase in accuracy, and a substantial reduction in bias. The proposed method was able to capture the majority of the most significant SNPs that were not identified in the analysis of the misclassified data. In fact, in one of the simulation scenarios, 33% of the influential SNPs were not identified using the misclassified data, compared with the analysis using the data without misclassification. However, using the proposed method, only 13% were not identified. Furthermore, the proposed method was able to identify with high probability a large portion of the truly misclassified observations.

Conclusions

The proposed model provides a statistical tool to correct or at least attenuate the negative effects of misclassified binary responses in GWAS. Across different levels of misclassification probability as well as odds ratios of significant SNPs, the model proved to be robust. In fact, SNP effects, and misclassification probability were accurately estimated and the truly misclassified observations were identified with high probabilities compared to non-misclassified responses. This study was limited to situations where the misclassification probability was assumed to be the same in cases and controls which is not always the case based on real human disease data. Thus, it is of interest to evaluate the performance of the proposed model in that situation which is the current focus of our research.

     

Simulation study for analysis of binary responses in the presence of extreme case problems

Background

Estimates of variance components for binary responses in presence of extreme case problems tend to be biased due to an under-identified likelihood. The bias persists even when a normal prior is used for the fixed effects.

Methods

A simulation study was carried out to investigate methods for the analysis of binary responses with extreme case problems. A linear mixed model that included a fixed effect and random effects of sire and residual on the liability scale was used to generate binary data. Five simulation scenarios were conducted based on varying percentages of extreme case problems, with true values of heritability equal to 0.07 and 0.17. Five replicates of each dataset were generated and analyzed with a generalized prior (g-prior) of varying weight.

Results

Point estimates of sire variance using a normal prior were severely biased when the percentage of extreme case problems was greater than 30%. Depending on the percentage of extreme case problems, the sire variance was overestimated when a normal prior was used by 36 to 102% and 25 to 105% for a heritability of 0.17 and 0.07, respectively. When a g-prior was used, the bias was reduced and even eliminated, depending on the percentage of extreme case problems and the weight assigned to the g-prior. The lowest Pearson correlations between true and estimated fixed effects were obtained when a normal prior was used. When a 15% g-prior was used instead of a normal prior with a heritability equal to 0.17, Pearson correlations between true and fixed effects increased by 11, 20, 23, 27, and 60% for 5, 10, 20, 30 and 75% of extreme case problems, respectively. Conversely, Pearson correlations between true and estimated fixed effects were similar, within datasets of varying percentages of extreme case problems, when a 5, 10, or 15% g-prior was included. Therefore this indicates that a model with a g-prior provides a more adequate estimation of fixed effects.

Conclusions

The results suggest that when analyzing binary data with extreme case problems, bias in the estimation of variance components could be eliminated, or at least significantly reduced by using a g-prior.     

Novel bacterial bioassay for a high-throughput screening of 4-hydroxyphenylpyruvate dioxygenase inhibitors

Plant 4-hydroxyphenylpyruvate dioxygenase (HPPD) is the molecular target of a range of synthetic β-triketone herbicides that are currently used commercially. Their mode of action is based on an irreversible inhibition of HPPD. Therefore, this inhibitory capacity was used to develop a whole-cell colorimetric bioassay with a recombinant Escherichia coli expressing a plant HPPD for the herbicide analysis of β-triketones. The principle of the bioassay is based on the ability of the recombinant E. coli clone to produce a soluble melanin-like pigment, from tyrosine catabolism through p-hydroxyphenylpyruvate and homogentisate. The addition of sulcotrione, a HPPD inhibitor, decreased the pigment production. With the aim to optimize the assay, the E. coli recombinant clone was immobilized in sol–gel or agarose matrix in a 96-well microplate format. The limit of detection for mesotrione, tembotrione, sulcotrione, and leptospermone was 0.069, 0.051, 0.038, and 20 μM, respectively, allowing to validate the whole-cell colorimetric bioassay as a simple and cost-effective alternative tool for laboratory use. The bioassay results from sulcotrione-spiked soil samples were confirmed with high-performance liquid chromatography.     

A Cost Effectiveness Analysis of Salt Reduction Policies to Reduce Coronary Heart Disease in Four Eastern Mediterranean Countries

Background

Coronary Heart Disease (CHD) is rising in middle income countries. Population based strategies to reduce specific CHD risk factors have an important role to play in reducing overall CHD mortality. Reducing dietary salt consumption is a potentially cost-effective way to reduce CHD events. This paper presents an economic evaluation of population based salt reduction policies in Tunisia, Syria, Palestine and Turkey.

Methods and Findings

Three policies to reduce dietary salt intake were evaluated: a health promotion campaign, labelling of food packaging and mandatory reformulation of salt content in processed food. These were evaluated separately and in combination. Estimates of the effectiveness of salt reduction on blood pressure were based on a literature review. The reduction in mortality was estimated using the IMPACT CHD model specific to that country. Cumulative population health effects were quantified as life years gained (LYG) over a 10 year time frame. The costs of each policy were estimated using evidence from comparable policies and expert opinion including public sector costs and costs to the food industry. Health care costs associated with CHDs were estimated using standardized unit costs. The total cost of implementing each policy was compared against the current baseline (no policy). All costs were calculated using 2010 PPP exchange rates. In all four countries most policies were cost saving compared with the baseline. The combination of all three policies (reducing salt consumption by 30%) resulted in estimated cost savings of $235,000,000 and 6455 LYG in Tunisia; $39,000,000 and 31674 LYG in Syria; $6,000,000 and 2682 LYG in Palestine and $1,3000,000,000 and 378439 LYG in Turkey.

Conclusion

Decreasing dietary salt intake will reduce coronary heart disease deaths in the four countries. A comprehensive strategy of health education and food industry actions to label and reduce salt content would save both money and lives.     

Morphological and biochemical changes in maize under drought and salinity stresses in a semi-arid environment

Abstract

This study investigated some morphological and biochemical responses of maize to drought and salinity in open field in Tunisia with the aim of gaining insights into tolerance mechanisms. After seedling emergence, five treatments were applied until maturity: optimal water supply (control, 100% of maximum evapotranspiration - ETM); irrigation at 70% ETM (moderate drought) and at 35% ETM (severe drought); optimal supply of water containing 3?g NaCl L^?1 (moderate salinity) and 6?g NaCl L^?1 (severe salinity). Here, we demonstrated that extreme drought and salinity severely decreased the leaf area (?74% and ?55%, respectively) and the above-ground biomass (?35% and ?31%, respectively) at silking stage, indicating that the photosynthetic leaf apparatus is highly sensitive and that drought has a greater effect than salinity. Grain yield losses were also exacerbated under extreme stress conditions, viz. severe drought (?85% versus controls) and severe salinity (?73%), while productivity under moderate salinity approximated that of moderate drought, possibly due to increases in leaf chlorophyll and carotenoid content and K/Na ratio. The leaf area and its relative water content were positively correlated with grain yield under both salinity and drought stresses, and may therefore be used as markers for effective screening of maize genotypes for better stress tolerance.     

Update of the spectrum of GJB2 gene mutations in Tunisian families with autosomal recessive nonsyndromic hearing loss

Hearing loss is the most frequent sensory disorder. It affects 3 in 1000 newborns. It is genetically heterogeneous with 60 causally-related genes identified to date. Mutations in GJB2 gene account for half of all cases of non-syndromic deafness. The aim of this study was to determine the relative frequency of GJB2 allele variants in Tunisia. In this study, we screened 138 patients with congenital hearing loss belonging to 131 families originating from different parts of Tunisia for mutations in GJB2 gene. GJB2 mutations were found in 39% of families (51/131). The most common mutation was c.35delG accounting for 35% of all cases (46/131). The second most frequent mutation was p.E47X present in 3.8% of families. Four identified mutations in our cohort have not been reported in Tunisia; p.V37I, c.235delC, p.G130A and the splice site mutation IVS1+1G>A (0.76%). These previously described mutations were detected only in families originating from Northern and not from other geographical regions in Tunisia. In conclusion we have confirmed the high frequency of c.35delG in Tunisia which represents 85.4% of all GJB2 mutant alleles. We have also extended the mutational spectrum of GJB2 gene in Tunisia and revealed a more pronounced allelic heterogeneity in the North compared to the rest of the country.     

Molecular and biochemical characterization of a novel intronic single point mutation in a Tunisian family with glycogen storage disease type III

Genetic deficiency of the glycogen debranching enzyme causes glycogen storage disease type III, an autosomal recessive inherited disorder. The gene encoding this enzyme is designated as AGL gene. The disease is characterized by fasting hypoglycemia, hepatomegaly, growth retardation, progressive myopathy and cardiomyopathy. In the present study, we present clinical features and molecular characterization of two consanguineous Tunisian siblings suffering from Glycogen storage disease type III. The full coding exons of the AGL gene and their corresponding exon–intron boundaries were amplified for the patients and their parents. Gene sequencing identified a novel single point mutation at the conserved polypyrimidine tract of intron 21 in a homozygous state (IVS21-8A>G). This variant cosegregated with the disease and was absent in 102 control chromosomes. In silico analysis using online resources showed a decreased score of the acceptor splice site of intron 21. RT-PCR analysis of the AGL splicing pattern revealed a 7 bp sequence insertion between exon 21 and exon 22 due to the creation of a new 3′ splice site. The predicted mutant enzyme was truncated by the loss of 637 carboxyl-terminal amino acids as a result of premature termination. This novel mutation is the first mutation identified in the region of Bizerte and the tenth AGL mutation identified in Tunisia. Screening for this mutation can improve the genetic counseling and prenatal diagnosis of GSD III.