Circulating antibodies against Plasmodium falciparum histidine-rich proteins 2 interfere with antigen detection by rapid diagnostic tests

Background Rapid diagnostic tests (RDTs) for detection of Plasmodium falciparum infection that target P. falciparum histidine-rich protein 2 (PfHRP2), a protein that circulates in the blood of patients infected with this species of malaria, are widely used to guide case management. Understanding determinants of PfHRP2 availability in circulation is therefore essential to understanding the performance of PfHRP2-detecting RDTs. Methods The possibility that pre-formed host anti-PfHRP2 antibodies may block target antigen detection, thereby causing false negative test results was investigated in this study. Results Anti-PfHRP2 antibodies were detected in 19/75 (25%) of plasma samples collected from patients with acute malaria from Cambodia, Nigeria and the Philippines, as well as in 3/28 (10.7%) asymptomatic Solomon Islands residents. Pre-incubation of plasma samples from subjects with high-titre anti-PfHRP2 antibodies with soluble PfHRP2 blocked the detection of the target antigen on two of the three brands of RDTs tested, leading to false negative results. Pre-incubation of the plasma with intact parasitized erythrocytes resulted in a reduction of band intensity at the highest parasite density, and a reduction of lower detection threshold by ten-fold on all three brands of RDTs tested. Conclusions These observations indicate possible reduced sensitivity for diagnosis of P. falciparum malaria using PfHRP2-detecting RDTs among people with high levels of specific antibodies and low density infection, as well as possible interference with tests configured to detect soluble PfHRP2 in saliva or urine samples. Further investigations are required to assess the impact of pre-formed anti-PfHRP2 antibodies on RDT performance in different transmission settings.

Signaling pathway genes for blood pressure, folate and cholesterol levels among hypertensives : an epistasis analysis

Irregular atrial pressure, defective folate and cholesterol metabolism contribute to the pathogenesis of hypertension. However, little is known about the combined roles of the methylenetetrahydrofolate reductase (MTHFR), apolipoprotein-E (ApoE) and angiotensin-converting enzyme (ACE) genes, which are involved in metabolism and homeostasis. The objective of this study is to investigate the association of the MTHFR 677 C>T and 1298A>C, ACE insertion–deletion (I/D) and ApoE genetic polymorphisms with hypertension and to further explore the epistasis interactions that are involved in these mechanisms. A total of 594 subjects, including 348 normotensive and 246 hypertensive ischemic stroke subjects were recruited. The MTHFR 677 C>T and 1298A>C, ACE I/D and ApoEpolymorphisms were genotyped and the epistasis interaction were analyzed. The MTHFR 677 C>T and ApoE polymorphisms demonstrated significant associations with susceptibility to hypertension in multiple logistic regression models, multifactor dimensionality reduction and a classification and regression tree. In addition, the logistic regression model demonstrated that significant interactions between the ApoE E3E3, E2E4, E2E2 and MTHFR 677 C>T polymorphisms existed. In conclusion, the results of this epistasis study indicated significant association between the ApoE and MTHFR polymorphisms and hypertension.

Human vs. machine : identification of bat species from their echolocation calls by humans and by artificial neural networks

Automated remote ultrasound detectors allow large amounts of data on bat presence and activity to be collected. Processing of such data involves identifying bat species from their echolocation calls. Automated species identification has the potential to provide more consistent, predictable, and potentially higher levels of accuracy than identification by humans. In contrast, identification by humans permits flexibility and intelligence in identification, as well as the incorporation of features and patterns that may be difficult to quantify. We compared humans with artificial neural networks (ANNs) in their ability to classify short recordings of bat echolocation calls of variable signal to noise ratios; these sequences are typical of those obtained from remote automated recording systems that are often used in large-scale ecological studies. We presented 45 recordings (1–4 calls) produced by known species of bats to ANNs and to 26 human participants with 1 month to 23 years of experience in acoustic identification of bats. Humans correctly classified 86% of recordings to genus and 56% to species; ANNs correctly identified 92% and 62%, respectively. There was no significant difference between the performance of ANNs and that of humans, but ANNs performed better than about 75% of humans. There was little relationship between the experience of the human participants and their classification rate. However, humans with <1 year of experience performed worse than others. Currently, identification of bat echolocation calls by humans is suitable for ecological research, after careful consideration of biases. However, improvements to ANNs and the data that they are trained on may in future increase their performance to beyond those demonstrated by humans.

Identification of New Zealand bats in flight from analysis of echolocation calls by artificial neural networks.

Time-expanded and heterodyned echolocation calls of the New Zealand long-tailed Chalinolobus tuberculatus and lesser short-tailed bat Mystacina tuberculata were recorded and digitally analysed. Temporal and spectral parameters were measured from time-expanded calls and power spectra generated for both time-expanded and heterodyned calls. Artificial neural networks were trained to classify the calls of both species using temporal and spectral parameters and power spectra as input data. Networks were then tested using data not previously seen. Calls could be unambiguously identified using parameters and power spectra from time-expanded calls. A neural network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 40 kHz (the frequency with the most energy of the fundamental of C. tuberculatus call), could identify 99% and 84% of calls of C. tuberculatus and M. tuberculata, respectively. A second network, trained and tested using power spectra of calls from both species recorded using a heterodyne detector set to 27 kHz (the frequency with the most energy of the fundamental of M. tuberculata call), could identify 34% and 100% of calls of C. tuberculatus and M. tuberculata, respectively. This study represents the first use of neural networks for the identification of bats from their echolocation calls. It is also the first study to use power spectra of time-expanded and heterodyned calls for identification of chiropteran species. The ability of neural networks to identify bats from their echolocation calls is discussed, as is the ecology of both species in relation to the design of their echolocation calls.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Deformation of a three-dimensional red blood cell in a stenosed micro-capillary

Red blood cells (RBCs) exhibit different types of motions and deformations when the blood flows through capillaries. Interestingly, due to the complex three-dimensional structure of the RBC membrane, RBCs show three-dimensional motions and deformations in the blood flow. These motions and deformations of the RBCs highly depend on the stiffness of the RBC membrane and on the geometrical parameters of the capillary through which blood flows. However, capillaries always do not have uniform cross sections and some capillaries have stenosed segments, where cross sectional area suddenly reduces. Further, some diseases can alter the stiffness of the RBC membrane drastically. In this study, the deformation behaviour of a single three-dimensional RBC is examined, when it moves through a stenosed capillary. A three-dimensional spring network is used to model the RBC membrane. The RBC’s inside and outside fluids are discretized into a finite number of mass points and treated by smoothed particle hydrodynamics (SPH) method. The capillary is considered as a rigid tube with a stenosed section. The deformation index, mean velocity and total energy of the RBC are analysed when it flows through the stenosed capillary. Further, motion and deformation of the RBCs with different membrane stiffness (KB) are compared when they flow through the stenosed segment of the capillary. The simulation results demonstrate the RBCs are subjected to a larger deformation when they move through the stenosed part of the capillary and the RBCs with lower KBvalues easily pass through the stenosed segment of the capillary. Further, RBCs having higher KBvalues have a lower mean velocity and it leads to slow down the overall blood flow rate

Deformation of a single red blood cell in a microvessel

Red blood cells (RBCs) are the most common type of cells in human blood and they exhibit different types of motions and deformed shapes in capillary flows. The behaviour of the RBCs should be studied in order to explain the RBC motion and deformation mechanism. This article presents a numerical simulation method for RBC deformation in microvessels. A two dimensional spring network model is used to represent the RBC membrane, where the elastic stretch/compression energy and the bending energy are considered with the constraint of constant RBC surface area. The forces acting on the RBC membrane are obtained from the principle of virtual work. The whole fluid domain is discretized into a finite number of particles using smoothed particle hydrodynamics concepts and the motions of all the particles are solved using Navier--Stokes equations. Minimum energy concepts are used to simulate the deformed shape of the RBC model. To verify the model, the motion of a single RBC is simulated in a Poiseuille flow and the characteristic parachute shape of the RBC is observed. Further simulations reveal that the RBC shows a tank treading motion when it flows in a linear shear flow.

Formation of the three-dimensional geometry of the red blood cell membrane

Red blood cells (RBCs) are nonnucleated liquid capsules, enclosed in deformable viscoelastic membranes with complex three dimensional geometrical structures. Generally, RBC membranes are highly incompressible and resistant to areal changes. However, RBC membranes show a planar shear deformation and out of plane bending deformation. The behaviour of RBCs in blood vessels is investigated using numerical models. All the characteristics of RBC membranes should be addressed to develop a more accurate and stable model. This article presents an effective methodology to model the three dimensional geometry of the RBC membrane with the aid of commercial software COMSOL Multiphysics 4.2a and Fortran programming. Initially, a mesh is generated for a sphere using the COMSOL Multiphysics software to represent the RBC membrane. The elastic energy of the membrane is considered to determine a stable membrane shape. Then, the actual biconcave shape of the membrane is obtained based on the principle of virtual work, when the total energy is minimised. The geometry of the RBC membrane could be used with meshfree particle methods to simulate motion and deformation of RBCs in micro-capillaries

Estimating the burden of disease attributable to high blood pressure in South Africa in 2000

Objectives To estimate the burden of disease attributable to high blood pressure (BP) in adults aged 30 years and older in South Africa in 2000. Design World Health Organization comparative risk assessment (CRA) methodology was followed. Mean systolic BP (SBP) estimates by age and sex were obtained from the 1998 South African Demographic and Health Survey adult data. Population-attributable fractions were calculated and applied to revised burden of disease estimates for the relevant disease categories for South Africa in 2000. Monte Carlo simulation modelling techniques were used for uncertainty analysis. Setting South Africa Subjects Adults aged 30 years and older. Outcome measures Mortality and disability-adjusted life years (DALYs) from ischaemic heart disease (IHD), stroke, hypertensive disease and other cardiovascular disease (CVD). Results High BP was estimated to have caused 46 888 deaths (95% uncertainty interval 44 878 - 48 566) or 9% (95% uncertainty interval 8.6 - 9.3%) of all deaths in South Africa in 2000, and 390 860 DALYs (95% uncertainty interval 377 955 - 402 256) or 2.4% of all DALYs (95% uncertainty interval 2.3 - 2.5%) in South Africa in 2000. Overall, 50% of stroke, 42% of IHD, 72% of hypertensive disease and 22% of other CVD burden in adult males and females (30+ years) were attributable to high BP (systolic BP ≥ 115 mmHg). Conclusions High BP contributes to a considerable burden of CVD in South Africa and results indicate that there is considerable potential for health gain from implementing BP-lowering interventions that are known to be highly costeffective.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Blood in our hearts or blood on our hands? The viscosity, vitality and validity of Aboriginal 'blood talk'

Blood metaphors abound in everyday social discourse among both Aboriginal and non-Aboriginal people. However, ‘Aboriginal blood talk’, more specifically, is located within a contradictory and contested space in terms of the meanings and values that can be attributed to it by Aboriginal and non-Aboriginal people. In the colonial context, blood talk operated as a tool of oppression for Aboriginal people via blood quantum discourses, yet today, Aboriginal people draw upon notions of blood, namely bloodlines, in articulating their identities. This paper juxtaposes contemporary Aboriginal blood talk as expressed by Aboriginal people against colonial blood talk and critically examines the ongoing political and intellectual governance regarding the validity of this talk in articulating Aboriginalities.