Strategies, effectiveness and rationale of vector-borne disease control in the pastoralist system of south-western Uganda

In Uganda, control of vector-borne diseases is mainly in form of vector control, and chemotherapy. There have been reports that acaricides are being misused in the pastoralist systems in Uganda. This is because of the belief by scientists that intensive application of acaricide is uneconomical and unsustainable particularly in the indigenous cattle. The objective of this study was to investigate the strategies, rationale and effectiveness of vector-borne disease control by pastoralists. To systematically carry out these investigations, a combination of qualitative and quantitative research methods was used, in both the collection and the analysis of data. Cattle keepers were found to control tick-borne diseases (TBDs) mainly through spraying, in contrast with the control of trypanosomosis for which the main method of control was by chemotherapy. The majority of herders applied acaricides weekly and used an acaricide of lower strength than recommended by the manufacturers. They used very little acaricide wash, and spraying was preferred to dipping. Furthermore, pastoralists either treated sick animals themselves or did nothing at all, rather than using veterinary personnel. Oxytetracycline (OTC) was the drug commonly used in the treatment of TBDs. Nevertheless, although pastoralists may not have been following recommended practices in their control of ticks and tick-borne diseases, they were neither wasteful nor uneconomical and their methods appeared to be effective. Trypanosomosis was not a problem either in Sembabule or Mbarara district. Those who used trypanocides were found to use more drugs than were necessary.

A novel variant on chromosome 7q22.3 associated with mean platelet volume, counts, and function

Mean platelet volume (MPV) and platelet count (PLT) are highly heritable and tightly regulated traits. We performed a genome-wide association study for MPV and identified one SNP, rs342293, as having highly significant and reproducible association with MPV (per-G allele effect 0.016 +/- 0.001 log fL; P < 1.08 x 10(-24)) and PLT (per-G effect -4.55 +/- 0.80 10(9)/L; P < 7.19 x 10(-8)) in 8586 healthy subjects. Whole-genome expression analysis in the 1-MB region showed a significant association with platelet transcript levels for PIK3CG (n = 35; P = .047). The G allele at rs342293 was also associated with decreased binding of annexin V to platelets activated with collagen-related peptide (n = 84; P = .003). The region 7q22.3 identifies the first QTL influencing platelet volume, counts, and function in healthy subjects. Notably, the association signal maps to a chromosome region implicated in myeloid malignancies, indicating this site as an important regulatory site for hematopoiesis. The identification of loci regulating MPV by this and other studies will increase our insight in the processes of megakaryopoiesis and proplatelet formation, and it may aid the identification of genes that are somatically mutated in essential thrombocytosis. (Blood. 2009; 113: 3831-3837)

A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)

This paper presents in detail a theoretical adaptive model of thermal comfort based on the “Black Box” theory, taking into account factors such as culture, climate, social, psychological and behavioural adaptations, which have an impact on the senses used to detect thermal comfort. The model is called the Adaptive Predicted Mean Vote (aPMV) model. The aPMV model explains, by applying the cybernetics concept, the phenomena that the Predicted Mean Vote (PMV) is greater than the Actual Mean Vote (AMV) in free-running buildings, which has been revealed by many researchers in field studies. An Adaptive coefficient (λ) representing the adaptive factors that affect the sense of thermal comfort has been proposed. The empirical coefficients in warm and cool conditions for the Chongqing area in China have been derived by applying the least square method to the monitored onsite environmental data and the thermal comfort survey results.

What do we mean when we refer to Bacteroidetes populations in the human gastrointestinal microbiota?

Recent large-scale cloning studies have shown that the ratio of Bacteroidetes to Firmicutes may be important in the obesity-associated gut microbiota, but the species these phyla represent in this ecosystem has not been examined. The Bacteroidetes data from the recent Turnbaugh study were examined to determine those members of the phylum detected in human faecal samples. In addition, FISH analysis was performed on faecal samples from 17 healthy, nonobese donors using probe Bac303, routinely used by gut microbiologists to enumerate BacteroidesPrevotella populations in faecal samples, and another probe (CFB286) whose target range has some overlap with that of Bac303. Sequence analysis of the Turnbaugh data showed that 23/519 clones were chimeras or erroneous sequences; all good sequences were related to species of the order Bacteroidales, but no one species was present in all donors. FISH analysis demonstrated that approximately one-quarter of the healthy, nonobese donors harboured high numbers of Bacteroidales not detected by probe Bac303. It is clear that Bacteroidales populations in human faecal samples have been underestimated in FISH-based studies. New probes and complementary primer sets should be designed to examine numerical and compositional changes in the Bacteroidales during dietary interventions and in studies of the obesity-associated microbiota in humans and animal model systems.

Borg's rating of perceived exertion scales: do the verbal anchors mean the same for different clinical groups?

Objective: To examine the interpretation of the verbal anchors used in the Borg rating of perceived exertion (RPE) scales in different clinical groups and a healthy control group. Design: Prospective experimental study. Setting: Rehabilitation center. Participants: Nineteen subjects with brain injury, 16 with chronic low back pain (CLBP), and 20 healthy controls. Interventions: Not applicable. Main Outcome Measures: Subjects used a visual analog scale (VAS) to rate their interpretation of the verbal anchors from the Borg RPE 6-20 and the newer 10-point category ratio scale. Results: All groups placed the verbal anchors in the order that they occur on the scales. There were significant within-group differences (P > .05) between VAS scores for 4 verbal anchors in the control group, 8 in the CLBP group, and 2 in the brain injury group. There was no significant difference in rating of each verbal anchor between the groups (P > .05). Conclusions: All subjects rated the verbal anchors in the order they occur on the scales, but there was less agreement in rating of each verbal anchor among subjects in the brain injury group. Clinicians should consider the possibility of small discrepancies in the meaning of the verbal anchors to subjects, particularly those recovering from brain injury, when they evaluate exercise perceptions.

Investigation of support vector machine for the detection of architectural distortion in mammographic images

This paper investigates detection of architectural distortion in mammographic images using support vector machine. Hausdorff dimension is used to characterise the texture feature of mammographic images. Support vector machine, a learning machine based on statistical learning theory, is trained through supervised learning to detect architectural distortion. Compared to the Radial Basis Function neural networks, SVM produced more accurate classification results in distinguishing architectural distortion abnormality from normal breast parenchyma.

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is computationally more efficient.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.