The relationship between the burden of uncomplicated malaria and transmission intensity is unclear and a better understanding of this relationship is important for the implementation of intervention programmes.A 6-month longitudinal study monitoring risk factors for anaemia and febrile malaria episodes was conducted among individuals aged below 20 years, residing in three villages of different altitude in areas of high, moderate and low malaria transmission intensity in North-Eastern Tanzania.Plasmodium falciparum was the only significant parasitic determinant of anaemia. Interestingly, children who carried low-density parasitaemia at the start of the study had a lower risk of contracting a febrile malaria episode but a higher risk of anaemia during the study period, than children who were slide negative at this point in time.The burden of anaemia and malarial fever fell mainly on the youngest children and was highest in the village with high transmission intensity. Although a considerable percentage of individuals in all villages carried intestinal worms, logistic regression models indicated that Young children living in the high transmission village carried a very high anaemia burden, which could be attributed to malaria. The overall incidence of febrile malaria was also highest in the high transmission village particularly among those under five years of age. These data suggest that in rolling back malaria, available resources in prevention programmes should primarily be focussed on young children, particularly those residing in areas of high malaria transmission. Plasmodium falciparum malaria remains an important public health problem in sub-Saharan Africa. To develop and assess the efficacy of control measures, it is important to obtain a better understanding of how the malaria disease burden is distributed among population groups and how this burden is affected by changes in malaria transmission intensity [ntensity . In areantensity , but prontensity ,4. In arntensity ,6. It hantensity -9. To adntensity -12. ThisThe study was conducted in three villages in Tanga region, North-Eastern Tanzania. The three villages were Mgome (5°12'S, 38'51'E) at an altitude of approximately 200 meters, Ubiri (4°72'S, 38°29'E) at an altitude of approximately 1,200 meters, and Magamba (4°75'S, 38°29'E) at an altitude of approximately 1,700 meters.Anopheles gambiae is the most prevalent vector in the lowlands, while Anopheles funestus predominates in the highlands [The climate in the area is characterized by variations in rainfall and temperature related both to season and altitude . The lonighlands . The entighlands . In the ighlands . Villageighlands , whereasLand use in the lowland areas is characterized by subsistence farming of maize, rice, bananas, beans, cassava, coconuts, fruits and other crops, as well as large-scale production of sisal. In the highlands, there is subsistence farming, mainly of maize, beans, bananas, potatoes, cabbages, tomatoes and fruits, and also large-scale production of tea and coffee.Prior to the study, census surveys were done in each village and study individuals randomly selected from a census list. Mgome village is inhabited mainly by the Bondei tribe (60%), while Ubiri and Magamba are inhabited by Sambaa at 97% and 57%, respectively. The aim was to recruit a total of 250 individuals below the age of twenty years from each village, distributed in different age groups as follows: 0–1 year: n = 25, 1 year: n = 25, 2 years: n = 25 3 years: n = 25, 4 years: n = 25, 5–6 years: n = 25, 7–9 years: n = 25, 10–14 years: n = 40 and 15–19 years: n = 40.Malariometric surveys were conducted in each village in April, July and September 2001. During the first survey, the purpose of the study was explained and consent to participate obtained from each study individual or their parents/guardians. Baseline demographic data were collected together with a history of migration and recent movements. The use of malaria preventive measures was also recorded. A history of recent illness was obtained, emphasizing symptoms suggestive of malaria. Physical examination on signs related to malaria such as temperature, pulse, spleen size, pallor and respiratory rate was conducted. Axillary temperature was measured using digital thermometers. Height, weight and upper-arm-circumference were recorded for estimation of nutritional status. For any individual diagnosed with mild disease, appropriate drugs were administered in the field. Individuals with symptoms of malaria were treated with SP. Participants with severe disease were referred to the nearby hospital.® photometer (Ångelholm, Sweden). Whole blood was used to prepare thick and thin blood smears for malarial microscopy. These were stained with 10% Giemsa stain for 15–20 minutes after fixing thin smears with methanol. Asexual and sexual parasites were counted against 200 and 500 white blood cells, respectively. The differentiation of malaria parasite species was confirmed by microscopy of thin smears. A blood smear was declared negative only after examination of 200 high power fields. The density of asexual parasites was calculated assuming 8000 leucocytes per μl of blood and expressed as parasites per μl.Five millilitres of venous blood were collected from study individuals aged three years and above into vacutainer tubes containing citrate buffer. For children below three years, 300–400 μl of capillary blood from a fingerprick were collected into eppendorf tubes containing EDTA. The haemoglobin (Hb) of each participant was measured from drops of blood using a HemoCueDuring the first cross-sectional survey, study participants were asked to collect stool and urine specimens in special containers. Direct smear-technique was used to check for the presence of hookworm ova and other intestinal parasites. A pinhead of stool was collected, put on a slide and emulsified in a drop of normal saline. A cover slip was then applied and the slide examined using low-power microscopy.Local village helpers (two community members per village) and health workers at nearby health facilities performed passive case detection during the 6-month study period. The village helpers were provided with first-line antimalarial drugs (SP), paracetamol, slides, blood lancets, treatment charts, febrile case detection forms and storage boxes. Villagers could seek treatment at any time from these helpers. Patients with symptoms of malaria were treated with first-line antimalarial drugs or, if they had severe symptoms or did not respond adequately to the first-line treatment, they were referred to a health facility. Prior to treatment the village helpers collected clinical information and a malaria blood smear.At each nearby health facility, two permanent staff members monitored study participants seeking medical treatment at the facility. If a study participant presented at the facility with history of fever and/or an axillary temperature ≥ 37.5°C, a form was completed and a blood smear collected. Once per month active febrile case detection was undertaken by the research team. During active case detection, each study participant was seen by a trained physician and a blood smear was taken from any study participant reporting a history of fever within two days and/or those who had an axillary temperature ≥ 37.5°CP. falciparum parasites above a defined density cut-off level. Many individuals carried low density asymptomatic parasitaemia, and fever among parasitaemic individuals may also have been caused by other illness [P. falciparum density cut off levels were applied in each village. To balance between sensitivity and specificity in diagnosing a febrile malaria episode, we aimed at a febrile malaria case specificity >80%. In Magamba (the low transmission village), a cut-off of 40 parasites/μl was applied, while cut-offs of 1000 parasites/μl and 5000 parasites/μl were used in Ubiri (the moderate transmission village), and Mgome (the high transmission village), respectively. Age-specific incidence rates of febrile malaria episodes were calculated as the number of episodes divided by the number of days that individuals in the age group were at risk during the follow-up. After a febrile malaria episode an individual was censored for 28 days [Anaemia was defined as haemoglobin < 11.0 g/dl ,15. To a illness . Thus, t illness , differe 28 days . The eff 28 days .All data were double-entered into a database in Epi-lnfo Version 6.04d (CDC, Atlanta, USA) and statistical analyses were performed with Stata version 8 (Stata Corporation, Texas, USA). Univariate analyses and multivariate logistic regression were performed to determine risk factors for anaemia and febrile malaria episodes.P. falciparum parasitaemia was categorised as no parasitaemia if no parasites were detected microscopically, low-density if parasitaemia was between 40 parasites/μl and 4999 parasites/μl, and high-density if the level was above or equal to 5000 parasites/μl. Thus, the first slide reading of individuals who did not have fever/had normal haemoglobin levels at enrolment was used to predict the risk of developing a subsequent episode of malarial fever/anaemia.For Mgome village, a logistic regression model was developed to determine whether the result of the first slide reading in April could be used to predict the subsequent risk of developing anaemia or febrile malaria during the following six months of morbidity surveillance. In this model, Ethical clearance was granted by the Medical Research Co-ordinating Committee of the National Institute for Medical Research, Tanzania. Prior to the study, meetings were held with local authorities and with the villagers in each study village, during which the aims of the study were explained. Informed consent documents for the study were prepared in English and translated into Kiswahili before administration to both village leaders and participants. Written informed consent to participate was obtained from each study individual or from his/her parents or guardians. Study individuals were free to withdraw from the study at any time without giving any reasons, or being disqualified from any medical services that were provided to all villagers throughout the study period. At the end of the study, preliminary findings were presented at village meetings.Three study villages were selected to represent areas of markedly different malaria transmission intensity. In each village, approximately 250 individuals under the age of 20 years were recruited. Few individuals reported using anti-malarial preventive measures Table . Repeat P. falciparum prevalence and parasite densities  and associated with age (Spearman rho = 0.238, p < 0.001) while in the two other villages the prevalence of splenomegaly was low and with no distinct age-pattern (data not shown). This distribution of splenomegaly remained stable during the study period.P. falciparum parasitaemia were associated with anaemia  adhered to the follow-up scheme and were included in the analysis of febrile episodes. Loss to follow-up was due to death  or emigration. Using the village-specific density cut-off described above, 54 individuals had febrile malaria episodes in Mgome, 10 in Ubiri and none in Magamba during the six-month follow-up period. The mean age of febrile malaria individuals was 1.97 years (95% Cl: 1.50, 2.59) and 3.23 years (95% Cl: 1.59, 5.86) for Mgome and Ubiri, respectively. Children below five years carried the major burden of febrile malaria episodes in Mgome  of developing a febrile malaria episode during follow-up than those who were slide negative  and 95% Cl: 11.2 [10.2, 12.3]) had normal haemoglobin levels during the July and September cross sectional surveys, while 44 developed anaemia during the study (mean age (years) and 95% Cl: 7.9 [6.4, 9.5]). Logistic regression models correcting for age showed that the risk of developing anaemia during the study was 4.4 times (p = 0.038) higher in individuals carrying low-density parasitaemia in April than in those who were slide negative (Table This prospective longitudinal study was designed to compare the burden of uncomplicated malaria in three similar villages situated in areas of markedly different transmission intensity. Not surprisingly, the study showed that individuals living in the village with very high malaria transmission carried a markedly higher burden of both anaemia and febrile malaria episodes compared to villagers at the sites with lower transmission. This result is in agreement with results from previous studies in the area . The vilP. falciparum carriage at the beginning of the study influenced the risk of developing febrile malaria episodes or anaemia during the following study period. Interestingly, multivariate logistic regression models indicated that children carrying low-density parasitaemia during the first cross sectional survey were at a lower risk of developing a febrile malaria episode than children without detectable parasitaemia or children with higher levels of parasitaemia. This apparent protective effect of low-grade parasitaemia was recently also reported in a study from Ghana [The longitudinal design of our study allowed an exploration of whether om Ghana , but in The overall burden of malaria morbidity was found to be highest in the high-transmission area, where infants and children carried a very high malaria burden in the form of febrile episodes and anaemia. Populations in the areas of moderate and low transmission suffered a significantly lower morbidity. Therefore, in order to roll back malaria, available resources in malaria control programmes should focus on underfives residing in the high-transmission areas.JPAL and LSV participated in the planning of the study, carried out field surveys, analysed the data and drafted the manuscript. BPM participated in designing the study, carried out field surveys and managed the data. CJD participated in study planning, in the fieldwork and in editing of the manuscript. CJ participated in the planning of the study and conducted the socio-economic analysis of study villages. JA and ZXS participated in the field surveys and performed microscopy of all blood smears. AYK, MML and TGT participated in study planning, coordination, and analysis of data. All authors participated in the paper writing and approved the final manuscript.


Millions of different proteins exist in nature, each with a unique structure that determines its function. Proteins can have different effects depending on where they are in the cell and which proteins or pathways they associate with. The number of proteins produced by a cell varies, but scientists estimate that the human genome produces some 100,000 proteins, and with thousands of proteins likely to be active in a single cell, it's inevitable that the molecular components of cellular pathways overlap. It is thought that this may be the case for a tumor suppressor named VHL .Caenorhabditis elegans to provide direct evidence of a HIF-1-independent function of VHL.The broad strokes of VHL action have been outlined: VHL is a ubiquitin ligase, an enzyme that targets proteins for destruction. VHL's best characterized target is a transcription factor called hypoxia-inducible factor 1 (HIF-1). When oxygen levels drop below normal—a condition called hypoxia—HIF-1 proteins are not degraded and may enter the nucleus, where they trigger the transcription of roughly 100 genes whose proteins either increase oxygen delivery or engage metabolic pathways that help the cell adapt to hypoxia. Scientists have long suspected that VHL has other targets, yet only HIF-1 has been clearly established. Now Peter Ratcliffe and colleagues use genetic methods in the nematode Previous studies have shown that when cells lack VHL proteins, HIF-1 is not degraded, resulting in the overexpression of HIF target genes. VHL-defective cells also show abnormalities in the extracellular matrix, the structural scaffolding that surrounds the cell. But it has not been clear whether these effects stem from HIF-1 dysregulation or something else.C. elegans. Then they analyzed the gene expression profiles of each of these mutant strains to identify pathways that required VHL but not HIF-1. To their surprise, the authors found, “all of the VHL-regulated genes fell into one of two patterns.” Their expression was either independent of HIF-1 and dependent on a range of genes associated with the extracellular matrix, or vice versa. What's more, these gene sets fell into distinct categories based on their chromosomal location, predicted functional similarities, and pattern of dysregulation.To disentangle the actions of the two proteins, Ratcliffe and colleagues compared the consequences of VHL protein inactivation in a variety of genetic backgrounds in These results, Ratcliffe and colleagues conclude, reflect the disruption of “two discrete aspects of VHL function.” One depends on HIF-1—inhibiting the transcription factor when oxygen concentrations are normal—and one doesn't; disruption of this HIF-1-independent function produces defects similar to those seen in mutants with defects in extracellular matrix assembly. These results also fall in line with other studies that have linked VHL deficiency to extracellular matrix defects, though the precise link remains unclear. It's also not clear whether this HIF-1-independent function means that VHL is still functioning as a ubiquitin ligase but targeting a different substrate or whether it represents a completely different function of VHL. For now, direct evidence of a HIF-1-independent pathway for VHL charts a clear path for researchers interested in pinning down the functions of this undoubtedly multidimensional ubiquitin ligase. It also gives VHL syndrome researchers—who have long suspected that other functions of the VHL tumor suppressor play a role in the onset of the disease—a promising lead to explore.


Are bird-pollinated flowers red because bees - which might rob the flower of its nectar - cannot easily detect them, or might it be because of more subtle evolutionary trade-offs? Most bird-pollinated flowers are both red and rich in nectar. The traditional explanation for this association is that, since red is inconspicuous to bees, it evolved to prevent bees from depleting the nectar of bird-pollinated flowers without effecting pollination. But bees can see, and they actually visit red flowers. So why are most bird-pollinated flowers red? To help answer this question, we need to consider how the outcomes of foraging decisions are affected by the community in which individuals live, and by the foraging options of other individuals.Plants face a trade-off between attracting pollinators and remaining hidden from flower parasites (such as nectar robbers and seed predators). Consequently, there is often strong selection pressure for highly specific communication channels that can advertise the presence of their flowers to effective pollinators but not to other individuals. Many aspects of pollinator syndromes are best understood in these terms . For exaIpomopsis aggregata) and the scarlet monkeyflower  (Echium wildpretii, an endemic of the Canary Islands, presents an entomophylous (‘insect-loving’) and an ornithophyllous (‘bird-loving’) subspecies  deplete the nectar and displace nectar-feeding birds  , are roudinalis) . Moreovebspecies  that difng birds .So if red flowers are not invisible to bees, why are most bird-pollinated flowers red? Perhaps birds are particularly apt at detecting red objects ? Again, One clue might come from the visual system of bees. Humans perceive light with a wavelength above approximately 600 nm as red . Most beBecause of the structure of their visual system, bees trained to feed at artificial red flowers take longer to find their goals than bees trained to feed at other-coloured flowers . In a reThe fact that bees require more time to find red flowers than other-coloured flowers, together with some results from optimal-foraging theory, outlined here, could unlock the mystery and explain the association between red coloration and bird pollination in flowers.When different animals, either from the same or different species, are forced to share some resources, any degree of specialization tends to result in habitat selection . In 1992Consider a community that includes bees and birds, and red and blue flowers. Let us assume that the flowers differ only in their colour, that there are only two patches of flowers (one of blue, the other of red flowers), and that the density of flowers is the same in both patches.  divided by the time it takes to find and exploit a flower. If the flowers are the same distance apart and birds can detect red and blue flowers equally well, then travel time is independent of flower colour. Under these circumstances, an ecological equilibrium, with birds exploiting red and blue flowers equally, would indicate that the amount of nectar available from both flower colours was identical.Now add a few bees to this community of birds, sufficiently few that their intake of nectar is negligible. We know that the standing crop is the same at red and blue flowers. However, we also know that bees require more time to find red flowers than blue ones , so theiIf we continue to add bees one at a time to this community, then sooner or later, the number of bees will no longer be sufficiently low for us to ignore their depleting effect on the nectar available. What will happen at that point? Will bees now start visiting red flowers? Not yet. For a bee to visit the red patch, the difference in standing crop between red and blue flowers would have to be large enough to compensate for the difference in detection time. Before that happens, some birds will shift to the red patch. Indeed, since birds require the same time to detect red or blue flowers, some birds will move from the blue to the red patch as soon as bees start to noticeably reduce the nectar available from the blue flowers.What Possingham's model predicts, therefore, is that when the number of bees is large enough, all birds will forage at the red patch. Only when the difference in standing crop between red and blue flowers is so large that it compensates for the reduced detectability of red flowers, will bees start visiting the red patch.To conclude, there will be an association between red flowers and birds. Birds will exploit red flowers, and bees blue flowers. In addition, depending on the relative abundance of bees and birds (and of red and blue flowers), either birds or bees, but never both simultaneously, can also exploit the other flower type .Penstemon strictus, provides a good example  visits to collect nectar are only common when hummingbird visits are rare .In fact, there is even no need to perform experimental bird removals, because plants provide us with a ready-made design: bees visit flowers searching for both nectar and pollen, while most birds exploit only the nectar. Hence, bees should readily collect pollen at red bird flowers. There are numerous examples of this, although in most cases they are indirectly documented. For example, solitary bees and syrphid and muscoid flies visit the red, hummingbird-pollinated flowers of are rare . OutsideAmphicoma beetles are more efficient pollinators of these flowers than commonly occurring bees (Cistus and Helianthemum) are commonly visited by pollen-collecting bees and bumblebees. A particularly interesting test case is provided by the corn poppy Papaver rhoeas; in the eastern Mediterranean region, it is pollinated by beetles and does not reflect in the UV , the detection time of red flowers against a natural background, and the effect of flower colour and size on flight mode in the field. Only then will we be able to fully unravel the factors that solve this fascinating mystery.


While experimental designs and statistical analysis methods have been proposed to reduce these errors, few studies have tested their accuracy and ability to identify small, but biologically important, changes. Here, we have compared two cDNA microarray experimental design methods with northern blot confirmation to reveal changes in gene expression that could contribute to the early antiproliferative effects of neuregulin on MCF10AT human breast epithelial cells.We performed parallel experiments on identical samples using a dye-swap design with ANOVA and an experimental design that excludes systematic biases by "correcting" experimental/control hybridization ratios with control/control hybridizations on a spot-by-spot basis. We refer to this approach as the "control correction method" (CCM). Using replicate arrays, we identified a decrease in proliferation genes and an increase in differentiation genes. Using an arbitrary cut-off of 1.7-fold and p values <0.05, we identified a total of 32 differentially expressed genes, 9 with the dye-swap method, 18 with the CCM, and 5 genes with both methods. 23 of these 32 genes were subsequently verified by northern blotting. Most of these were <2-fold changes. While the dye-swap method  detected a smaller number of genes (14–16) compared to the CCM (46), it was more accurate (89–92% vs. 75%). Compared to the northern blot results, for most genes, the microarray results underestimated the fold change, implicating the importance of detecting these small changes.We validated two experimental design paradigms for cDNA microarray experiments capable of detecting small (<2-fold) changes in gene expression with excellent fidelity that revealed potentially important genes associated with the anti-proliferative effects of neuregulin on MCF10AT breast epithelial cells. Spotted cDNA microarrays are used in high-throughput experiments that interrogate the relative expression of thousands of genes simultaneously for many biological processes with wide applications in biological and medical research. Typically in a two-dye spotted cDNA microarray experiment, two mRNA samples are transcribed into cDNAs, labeled with two different fluorescent dyes, commonly Cy3 and Cy5, and hybridized on the same slide. The relative gene expression level is then measured as a ratio of the intensities of the fluorescent dyes. However, the signal intensity of the dye, which indirectly represents the gene expression level, can be affected by many other sources of error such as dye efficiency, sample preparation, and the variability of the biological samples ,2.An important question is how to identify differentially expressed genes, some of which change only minimally <2-fold), given many known and potentially unknown sources of variance in the microarray experiment. In order to reduce false positive rates, many published experiments use a cut-off of 2- to 3-fold . This li-fold, giIn this paper we compared two experimental design and analysis methods performed on quadruplicate arrays that include a dye-swap design ,19 and aThe results presented in this paper demonstrate two, complementary cDNA microarray methods capable of reliably revealing small changes in gene expression in transformed human breast epithelial MCF10AT cells after treatment with neuregulin. Since, as shown in Fig. As with most experimental methods, replicate measurements can reduce random errors. Equally important are systematic errors. Systematic errors result from a constant tendency to over- and under-estimate true values and cannot be eliminated by replicate analysis, since they are often highly reproducible. An example of such a systematic error is a gene-specific dye effect, also called "dye–gene" interaction , and is Given the unavoidable presence of these systematic errors, methods to correct these errors are needed. One way to correct for systematic errors in microarray experiments is to take advantage of C/C hybridizations to correct the T/C hybridizations. This requires a modified reference design, which we refer to as a "control correction" design. This is different from a common reference design used previously ,20. HereA flow chart for the control correction method is shown in Fig. However, despite this relatively even distribution, histograms of normalized log ratios for T/C and C/C display long tails to the left as shown in the histograms in Fig. As a final step, a t-test was performed to compare the normalized log ratios of T/C and C/C for each gene. This yields p values for each control-corrected fold change calculated as log (T/C)-log (C/C). In Fig. Many have proposed that a dye-swap experimental design combined with an ANOVA will correct for systematic errors -19. To vTable To confirm these gene expression changes and to determine the accuracy of each experimental method, we selected 23 genes for verification by northern blot. We chose all 5 genes detected by both methods, 6 up-regulated and 5 down-regulated genes from the control correction design, and 7 genes from the dye-swap experiment. The selection of genes was not random, as we selected a balanced complement of genes of variable intensity that were both up- and down-regulated. The probes used for northern blots were generated by PCR from clones used to spot the arrays. Each blot contained triplicate control and treated samples and was re-probed multiple times. Fig. Since the ANOVA method we used can sometimes underestimate the variance, we re-analyzed our dye-swap data with a Bayesian method using a regularized t-test as implemented in Cyber-T . This anMCF10AT cells are a human breast epithelial cell line stably transfected with a mutant ras oncogene. These cells are pre-malignant, but can progress to invasive carcinoma ,26. GiveOne of the important tasks in microarray technology is to design experiments and develop statistical tools to obtain data efficiently and accurately to answer fundamental questions in biology. In many experiments, this requires the ability to detect small changes in gene expression with high fidelity. In this study we compared two common experimental design paradigms for cDNA microarrays and determined their accuracy by northern blot. Both methods identified small expression changes with considerable accuracy. In the control correction design, we used control hybridizations to correct for systematic errors on a spot-by-spot basis. The method is based on an assumption that systematic errors from slides made from the same lot and processed identically do not vary significantly. To minimize the possible variance of systematic errors in T/C slides and C/C slides we maintained strict experimental conditions, such as same-day sample preparation and same-day hybridization. We also used the same control samples for both the T/C and C/C hybridizations instead of using an arbitrary control sample that might be quite different in mRNA composition . This reA summary of the results from this study are shown in the Venn diagrams in Fig. The t-test used for the CCM and ANOVA for the dye-swap method depend on assumptions of Gaussian distributions that may or may not be present in a microarray experiment with a small number of replicates. Some efforts have been made to develop Bayesian frameworks that incorporate prior distributions in order to estimate the noise ,29,30. WIn our analysis, we selected genes based on their p values obtained from replicates of individual spots and did not adjust these p-values for multiple comparisons. This may be a major cause for the higher false positive rates for both of our experimental designs. For the CCM, if we apply Bonferroni correction, while we can eliminate all false positives, we would also miss a majority of the differentially expressed genes verified by Northern blotting. Therefore, if accuracy is the main purpose of a study, multiple comparison corrections should be used, while if sensitivity is the main purpose, then it should not be used with the understanding that the accuracy will be lower.For our experimental design, the dye-swap method had a higher confirmation rate than the control correction method. This is, in part, due to the smaller variance that results from an effective doubling of the number of treated samples in the dye-swap method compared to the control correction method. Despite the higher degree of accuracy, the dye-swap design identified fewer genes and only detected down-regulated genes, whereas the control correction identified 3-times the number of genes that were both up- and down-regulated. However the control correction method was less specific for up-regulated genes. These differences may not solely reflect methodological differences, but likely result from experimental variability produced by performing the experiments independently on different days. Nonetheless, the results presented here suggest that both methods have clear merit in their abilities to show true gene expression changes, particularly for expression changes of 2-fold or less, and for genes with low signal intensities and/or low abundance.The final decision as to which method is preferred depends on the experimental design. For example, the amount of sample and number of replicates required are important considerations both in terms of how difficult the RNA is to obtain and the number of samples that need to be compared. This also translates into the cost to perform the experiment. For instance, the dye-swap method generates a larger sample size for the same number of slides, thus producing greater significance when comparing gene expression between two samples. However this method requires a minimum of two slides and two different labeling reactions per sample. If the amount of sample is limited or population level replication is more desirable than individual sample replication, the control correction is more efficient since individual replicates for reverse dye labeling are not required and each sample can be run with only one slide. For example, to compare 6 treatment samples with a single control sample would require a minimum of 12 microarrays using the dye-swap method, whereas the minimum number of 8 arrays is possible using the control correction method; 6 for treatment samples and 2 for controls.Another common experimental design used for time course or dose response studies is the reference design. In fact, the control correction method described here is essentially a modified reference design method where the zero time or dose point is the control-control comparison. As discussed above, using a very similar control sample to correct the series will give less false positives and negatives and a more accurate absolute value of the observed change than a dissimilar, pooled reference sample.Although our cDNA microarray results were accurate, the measured changes generally underestimated the actual changes measured by northern blots. Yuen et al.  similarlThis study demonstrated that dye-swap and control correction experimental design paradigms for cDNA microarray experiments are capable of detecting small, biologically important changes in gene expression with excellent fidelity while revealing important down-stream anti-proliferative effects of neuregulin on breast epithelial cells for future studies.Human cDNA glass microarrays, called the Alphamax Genechip, were obtained from Alphagene Inc. (Woburn, MA) containing 3333 cDNAs spotted in duplicate. The cDNAs used are identical to commercially available Micromax 2400 slides from Perkin Elmer Life Sciences (Boston, MA), most of which were derived from a human fetal brain cDNA library, with an additional 933 genes (gene list available upon request).2 incubator.MCF10AT cell culture – MCF10AT cells were from Dr. Robert Pauley at the Karmanos Cancer Institute (Detroit, MI). The cells were cultured in DMEM/F12 media (Invitrogen) supplemented with 5% horse serum (Invitrogen), 10 mM HEPES buffer (Invitrogen), 10 μg/ml insulin (Sigma), 20 ng/ml EGF (Upstate Biotechnology), 100 ng/ml cholera enterotoxin  and 0.5 μg/ml hydrocortisone (Sigma) at 37°C in 5% CONeuregulin treatment and RNA extraction – A recombinant human NRG β1 polypeptide (amino acids 14–246) was generously provided by AMGEN (Thousand Oaks, CA). After 3 days of culture, MCF10AT cells were treated with human recombinant neuregulin β1 form for 24 hours. MCF10AT cells grown under similar conditions without neuregulin treatment were used as a control. The cells were then harvested and total RNA was extracted using Ultraspec (Biotecx laboratories). The total RNA was cleaned up by Rneasy kit (Qiagen) and quantified using a fluorescent dye binding assay, Ribogreen (Molecular Probes). RNA purity was assessed by agarose gel electrophoresis. Proliferation assays were performed by counting quadruplicate cultures plated at 5000 cells/well using a hemocytometer.Microarray hybridization – cDNA microarrays were used in a 2-step hybridization protocol that was optimized for the Genisphere dendrimer labeling method. Total RNA was reverse transcribed into cDNA containing a unique 5' primer tag, using the Genisphere 3DNA expression array detection kit. In brief, for each reaction, 3 μg of total RNA was reverse transcribed using 0.2 μM oligo-dT-Genisphere capture primer, 0.5 mM dNTP, 200 U Superscript II (Invitrogen) in 1X first strand Superscript II buffer at 42°C for 2 h. The RNA from the DNA/RNA hybrids was denatured with 0.5 M NaOH / 50 mM EDTA at 65°C for 10 min. The reaction was neutralized using 1 M Tris-HCl ph 7.5. The contents of the tube containing the NRG-treated and control cDNA were then mixed together and 3 μl linear acrylamide (Ambion) and 250 μl of 3 M ammonium acetate were added to them. cDNA was precipitated by adding 100% Ethanol and incubating at -20°C for 30 min. The cDNA was collected in a pellet by centrifugation at 13000 rpm for 15 min in a microcentrifuge. and resuspended in Alternate (formamide-containing) Hybridization buffer (Genisphere) at 65°C for 10 min and modified LNA blocker (Genisphere) with denatured Cot 1 DNA.The entire mixture was added to the pre-hybridized array (Alphamax) for hybridization at 55°C for at 36 hr. A clear increase in signal was obtained with a 36 h hybridization compared to 16 h. After hybridization, the arrays were washed with 2X SSC and 0.2% SDS at 60°C for 15 min, followed by a wash with 2X SSC and another with 0.2X SSC at room temperature. For fluorescence detection, a second hybridization with the dendrimer was optimal. 2.5 μl each of the Cy3 and Cy5 dendrimer in Hybridization Buffer  were mixed with denatured Cot1 DNA and differential expander and the mixture was added to the pre-hybridized slides for hybridization at 60°C for 2 hrs. The slides were washed again as described above.Arrays were scanned with a GenePix 4000 A scanner (Axon Instruments, Inc., Union City, CA). Images were quantified using ImaGene Software (Biodiscovery, Inc. Marina del Rey, CA) that uses a local background subtracted from the signal. Signals not consistently detectable  were eliminated.We fitted loess curve to the log transformed data using the "loess" function in SAS software (SAS Institute Inc., NC) for intensity dependent normalization followed by a t-test to compare T/C with C/C ratio, gene by gene. The t-test was performed on the normalized log ratio with Welch correction for unequal variance. The control corrected fold change was calculated as:log (fold) = log(T/C)-log(C/C) to identify differentially expressed genes. First we use a normalization model for log-transformed intensity measurements:For the dye-swap method we performed the same background correction and data filtering for absent genes and log transformations. We then used a two interconnect ANOVA model ,23 and Myij = μ + Ai + Dj + ADij + εijAi is the effect of ith array, Dj is the effect of dye cy3 or cy5, ADij is array dye interaction and εij is random error. The residue from normalization model is then used in following gene model to find treatment effects on each gene:Where μ is the sample mean, rijkg = Aig + Djg + Tkgrijkg is the residual of each gene from the normalization model, Tkg is the treatment effect (control or treated), and Aig and Djg are the array and dye effects, respectively. The expression change for each gene is thus:Where Ttreated-Tcontrollog (fold) = 5 μg total RNA isolated from MCF10AT cells was run on a 1.3% Agarose/2.2M Formaldehyde gel as described previously [eviously . Probes eviously . For timBY analyzed microarray data. SR carried out microarray experiment. QL conducted MCF10AT cell culture and mRNA extraction. SA carried out northern blots experiments. RK provide input on microarray experiments. SD contributed ideas to data analysis. JAL conceived and design the experiment.


Curious Minds: How a Child Becomes a Scientist.A review of John Brockman's new book  Curious Minds: How a Child Becomes a Scientist.Do you want your child to grow up to be a scientist? If so, then by all means follow the roadmaps set down by the 27 scientists who contributed their personal histories to John Brockman's You could do worse than start with a family history rich in science, like Nicholas Humphrey whose grandfather, Nobel laureate A. V. Hill, remembers being startled by a solar eclipse while out rabbit hunting as a boy in England and having the presence of mind to smear the rabbit's blood over the glass from his pocket watch in order to watch the phenomenon in safety. Or, if you don't have a healthy lineup of scientific superstars in your family history, you could educate yourself about the wonders of science, like Murray Gell-Man's autodidactic father, and insist that your son at least try majoring in physics before settling on linguistics or archaeology. If you cannot be inspired to teach yourself quantum physics, you might also try the more commonplace achievement of a bad marriage to create an unstable emotional life for your daughter, so she might retreat into “solitary and bookish tendencies,” as the evolutionist Lynn Margulis did.Perhaps you cannot bring yourself to actively steer your child into science, but hope this book might guide you to at least watch for the signs of future genius. You might watch for a young Freeman Dyson in his crib, bored by the stuffed animals and mobiles, occupying his time by adding infinite series of fractions. Or you might watch for your daughter sneaking into your study to read your medical reference books on the sly, as Janna Levin did before ultimately becoming a professor of physics. Then again, you could watch for your son to emulate David Buss by reaching high for a C+ grade point average in school, indulging in recreational drugs, and taking a night shift job at a truck stop, before a scientifically minded girlfriend and a fortuitous lottery-based scholarship to the University of Texas turned him to the pursuit of evolutionary psychology.some sort of childhood. Who's to say whether any particular factor carried the weight that our self-narrative now likes to attribute to it.”The pattern is clear: there is no pattern. And the book's strong contingent of psychologists is not shy about commenting on the dubious reliability of self-narrative. Steven Pinker writes, “Don't believe a word of what you read in this essay on the childhood influences that led me to become a scientist. Don't believe a word of what you read in the other essays, either….Recounting childhood influences is a mental process no less subject to quirks and errors than falling for the visual illusions on the back of a cereal box….None of us has taken part in the experiments that would isolate the causes of our choices in life.” Or as Nicholas Humphrey puts it more simply, “Each of us is who we are, and we must each have had This book, then, is not a guide to the prescientific childhood, but a set of memoirs bound by their common conclusion. Many of them are highly entertaining, some of them are self-conscious and pedantic. All of them highlight the passion of childish curiosity extending into adulthood, either by family tradition or because a mentor appeared at the right place and time to ensure that this curiosity was not abandoned. As the developmental psychologist Allison Gopnik notes, “I suspect that there are few reports of scientists with a childhood fascination for babies, because most of those children turned into nursery school teachers or children's librarians or just stay at home mothers….It seems to me now that I was destined to become either a psychologically minded philosopher or a philosophically minded pscyhologist. But given slightly different contingencies, I might have become a frustrated preschool teacher or faculty wife.”We wish we could find prescriptions for guiding our children towards success, but the nature versus nurture debate has long since been replaced by the more sophisticated understanding of just how inextricably intertwined these two influences are in creating even a lowly zebrafish, let alone anything as behaviorally complex as a human being. This understanding can lead to frustration, as simple causes and cures become more elusive. Selling Mozart recordings for expectant mothers to play to their wombs can help assuage the fears and ignite the hopes of overachieving, yuppie parents, but there is little evidence that such interventions create the sought after intellectual advantage for the newborn.Mostly what we see in these essays are stories about people—stories that people tell about themselves. Stories of childhoods interrupted by war, of mentors persecuted by McCarthyism. Would a book tracing the self-styled childhood influences of outstanding politicians or judges have been so different? Possibly fewer socially awkward children and less gadget-building in the mix, possibly not.The contributors to this book are all outstanding, motivated scientific leaders who have chosen or stumbled into their intellectual paths. But I am not convinced that reading their brief reflections compares with the unique opportunity of interviewing Albert Einstein that John Brockman identified as one inspiration for this book—for turning what began as dinner party conversation into a methodical attempt at biographical anthology. Much of these pages are in fact dinner party conversation, whether it is Robert Sapolsky's horror of the white Southern gentlemen of Harvard's intellectual elite playing cards and drinking while dividing the spoils of sociobiology, or Allison Gopnik's personal relief that there were no prohibitions against sleeping with teaching assistants when she was a nubile college student. Some of it is heart-rendingly personal, as when Jaron Lanier talks about his futile attempt at age 11 to attract friends to his homemade electronic Halloween haunted house. All it really tells us is that there are as many ways of forming a scientist as there are of forming a human being.


Maurice Wilkins's autobiography provides an engaging perspective of the events leading to the discovery of the structure of DNA Maurice Wilkins, now 87, postpones the account of his involvement in the DNA affair until the second half of the book. Recounting his background and interesting life before DNA (34 years) in plain but telling sentences brings to life a character that is almost as much out of the ordinary as those of the more flamboyant James Watson and Francis Crick.Wilkins' first six years in New Zealand (a Garden of Eden) were followed by a long, vividly described trip to England, where the family eventually settled in Birmingham. His boyhood was marked by immersion in astronomy and telescope-making, but saddened by the painful illness of his sister. Success in school physics was the key for getting into Cambridge, where he reveled in the world of Ernest Rutherford, Mark Oliphant, and John Bernal. Given his leftist leanings, it was inevitable that Wilkins would become involved in the pacifist movement in Cambridge, with its close connection to the Communist Party. Perhaps too much involvement led to a low degree grade in 1938 and no hope of remaining at Cambridge. Instead, he returned to Birmingham and joined the Luminescence Lab being established by John Randall, a man with whom he would be closely connected for many decades. The work there contributed to Randall's scheme for making radar practical in air defense—the cavity magnetron that may have turned the course of World War II.What Is Life? Along with others who were to unravel the secrets of DNA, this planted the seed. When, after three transitional years, Randall became head of Kings College London's physics department and director of a biophysics research unit sponsored by the Medical Research Council (MRC), Wilkins was his deputy. The attack on DNA structure soon began.Early in 1944, Oliphant, then at Birmingham, left to work on the atomic bomb at Berkeley and took Wilkins along. Life in Berkeley was exciting, but beneath the excitement of bomb work and mixed feelings upon its success at Hiroshima, Wilkins read Erwin Schrodinger's That X-ray diffraction might play a major role in this search rested on two pillars unique to England. One was the British lead in using X-ray diffraction to determine molecular structures—a crown jewel built on the work of the Braggs (father and son), Bernal, and Dorothy Hodgkin. The other was the pre-World War II work of William Astbury in showing that DNA fibers displayed some crystallinity that, if developed, might be the basis of helping to determine the structure. Wilkins confides that in 1950 he knew little of how such X-ray analysis might be done. But in that year he was presented with an opportunity in the form of samples of carefully prepared calf DNA, given to him by a Swiss chemist, Rudolf Signer. With this DNA, much better fibers could be obtained and much sharper diffraction diagrams emerged.The exploitation of this advance, however, became mired in a colossal error in Randall's management of the group. Without telling Wilkins, he wrote to Rosalind Franklin, who was on her way to join the DNA effort, that Wilkins was withdrawing from DNA work and that she would take over. Unaware of this, Wilkins and Alec Stokes continued their work and reported at a meeting in Cambridge in July 1951 that DNA chains were probably in a helical conformation with a diameter of 20 Å. At the close of the meeting, Franklin assailed Wilkins, saying that he should stop his DNA work . Understandably, but regrettably, the two groups continued working in isolation from each other.Matters worsened. In October, Watson arrived at Cambridge and set up DNA structure studies with Crick. They quickly arrived at a three-stranded helical structure. But Franklin and Wilkins soon demolished it. Likewise, a three-stranded model at Kings College had a very short life. As if to trump these failures, Bragg at Cambridge and Randall at Kings agreed that DNA studies at Cambridge should stop and that the work should continue only at Kings. Mismanagement and noncooperation were taking their toll. Franklin was moving toward a two-stranded structure, but away from helices. Indeed, in mid-1952 she initiated a discussion with an announcement about the death of the helix. Mysteriously, she put aside a striking photo of the diffraction pattern of B-DNA  that emerged in early 1953 as a perfect signature of the helical form. But 1952 continued downhill. Even Wilkins stopped DNA work that November.Suddenly, in the new year, life returned to the DNA effort. Linus Pauling had just published a structure (three-stranded) that did not long survive, but the entrance of the world's leading structural chemist into the race reawakened everyone to the centrality of DNA structure. In January, Raymond Gosling gave to Wilkins the very well-oriented diffraction photo of B-DNA that he and Franklin had taken in July 1952. Wilkins assumed that it was given to him to do as he wished; a few days later, he showed it to Watson. Though hardly an expert in X-ray diffraction, Watson sensed that it was strong evidence for helices and sketched it for Crick on his return to Cambridge. Later that January, Franklin announced she would be moving from Kings College to Birkbeck College to join Bernal's group. In giving her final seminar, she switched from her earlier insistence that B-DNA was nonhelical, but did not show the photo that gave the strongest evidence for helicity. This shift put Franklin in a position to move forward on the structure of DNA, but without others' resorting to model building, the goal would have remained elusive.Finally, in mid-February, Max Perutz, who was a member of the MRC committee overseeing the Biophysics Unit at Kings College, passed on to Crick his copy of a report from that unit. This report contained Franklin's results that the phosphates were on the outside and that the A-form of DNA had a special crystalline arrangement called the monoclinic C2 space group. From his work with proteins, Crick saw immediately that the chains in the helical structure must be antiparallel and that there were probably two chains entwined. Watson used other data in the report to deduce that there were indeed two chains, not three or four. Erwin Chargaff had recently shown that in the base composition of all DNAs examined, adenines and thymines as well as guanines and cytosines are equal, i.e., A = T and G = C. Now released from the ban on DNA studies, Watson and Crick engaged in a frantic search using model building. They found a unique way to fit the bases in the structure by pairing, and by March 7 they had the double-helix model constructed: it obeyed the Chargaff ratios, it fit the X-ray data for B-DNA, and it provided a rational way to encode and transmit genetic information to subsequent generations.Wilkins was invited to view the model in Cambridge. He found it stunning. Watson asked him to be a coauthor of the paper. Wilkins, true to his character, declined, as he had not been involved in the final monumental stage. Back in London, Franklin had already moved to Birkbeck. She received the news of the discovery with equanimity. But a later examination of her notebooks showed that she had moved to favor helices and a two-chain (or possibly a one-chain) model.With the rather complicated story of the greatest discovery in biology in the century now reasonably complete, what is one to make of it? There are many answers. I will mention only three.The first is the key role played by model building. In fiber diffraction there is not enough information, by orders of magnitude, to locate every atom, as would be possible in diffraction by perfect crystals that give thousands of sharp reflections. Instead, the fiber diagram can only provide cues and some specifics, such as the repeat distance. Model building is a way of bringing into the picture previously determined bond distances and bond angles of components such as the purine and pyrimidine bases and the sugars that are unavailable from the fiber diagram. That this was not seen at Kings College left the researchers there well behind in a field that they had pioneered.A second lesson is the importance of bringing the full knowledge of single crystal analysis to fiber diagram interpretation. That Franklin and Wilkins missed noting that the monoclinic C2 space group meant that the chains in the fiber had to be antiparallel robbed them of an important clue to the structure.And third, the management of the Biophysics Unit at Kings College was a recipe for failure. Riddled by secrecy, diffuse lines of authority, the absence of strategies, and a lack of open congeniality, all so well described by Wilkins, who refers to it as Randall's Circus, this unit is a model of how not to succeed in group research.The Double Helix. The final chapter of his own autobiography addresses the criticism that some have leveled against his cold relation with Franklin, but also his happiness in newfound family life. Research gradually gave way to the pursuit of pacifist goals in a number of organizations and to the popularization of science. His has been a useful life, a part of which contributed to the great revolution in biology. It is good to have the insight that this book presents in a candid and personal way.DNA research continued at Kings College in a gradually improving environment: important details were worked out. But there was no real renewal, such as aiming at how DNA is configured to accommodate proteins in the nucleus. Wilkins enjoyed being included in the subsequent awards—the Lasker and the Nobel prizes. With Crick, he was annoyed by Watson's rendering of events in


Plasmodium falciparum-infected erythrocytes to adhere to the microvasculature endothelium is thought to play a causal role in malaria pathogenesis. Cytoadhesion to endothelial receptors is generally found to be highly sensitive to trypsinization of the infected erythrocyte surface. However, several studies have found that parasite adhesion to placental receptors can be markedly less sensitive to trypsin. This study investigates whether chondroitin sulphate A (CSA) binding parasites express trypsin-resistant variant surface antigens (VSA) that bind female-specific antibodies induced as a result of pregnancy associated malaria (PAM).The ability of P. falciparum clone FCR3 cultures were used to assay surface IgG binding before and after selection of the parasite for adhesion to CSA. The effect of proteolytic digestion of parasite erythrocyte surface antigens on surface IgG binding and adhesion to CSA and hyaluronic acid (HA) was also studied.Fluorescence activated cell sorting (FACS) was used to measure the levels of adult Scottish and Ghanaian male, and Ghanaian pregnant female plasma immunoglobulin G (IgG) that bind to the surface of infected erythrocytes. P. falciparum infected erythrocytes selected for adhesion to CSA were found to express trypsin-resistant VSA that are the target of naturally acquired antibodies from pregnant women living in a malaria endemic region of Ghana. However in vitro adhesion to CSA and HA was relatively trypsin sensitive. An improved labelling technique for the detection of VSA expressed by CSA binding isolates has also been described.P. falciparum isolates are currently considered potential targets for a vaccine against PAM. This study identifies discordance between the trypsin sensitivity of CSA binding and surface recognition of CSA selected parasites by serum IgG from malaria exposed pregnant women. Thus, the complete molecular definition of an antigenic P. falciparum erythrocyte surface protein that can be used as a malaria in pregnancy vaccine has not yet been achieved.The VSA expressed by CSA binding  Rapid clearance of parasitaemia following transfusion of IgG from malaria immune adults to clinically ill recipients illustrates that naturally acquired antibodies have a parasite clearing role in human malaria infection -3. NeithPlasmodium falciparum infected erythrocytes in the intervillous spaces of the placenta. Infected erythrocytes adhere to low-sulphated forms of CSA present on the extracellular proteoglycan matrix of syncytiotrophoblasts [In vitro selection of infected erythrocytes for adhesion to CSA concomitantly selects for expression of VSA that share characteristics with postnatal placental isolates. Thus plasma antibodies from malaria exposed pregnant, or multi-gravid women, recognize the VSA of CSA binding parasites (here referred to as VSAPAM). These sera can also block adhesion of CSA-selected infected erythrocytes to CSA in vitro [in vitro CSA-selected parasites [P. falciparum isolates taken from infected placentae at delivery [PAM is characterized by the sequestration of hoblasts . In vitrin vitro . Interesarasites ,13 and Pdelivery -16. Furtdelivery , the levdelivery  and posiPAM is, thus, the clearest example in malaria pathology research of a strong association between infected erythrocyte sequestration and a particular disease syndrome. The VSA recognized by female-specific, parity-dependent antibodies are, therefore, rational and exceptionally interesting candidates for inclusion in an experimental vaccine to protect women against PAM, a major cause of stillbirth, maternal anaemia and low birthweight.P. falciparum erythrocyte membrane protein 1 (PfEMPl), a polymorphic, high molecular weight membrane protein (200–450 kDa) encoded by the var multi-gene family [To date, the best characterized VSA is e family -20. Membvar genes encode large extracellular domains rich in lysine and arginine residues, it is not surprising that PfEMP-1 molecules and adhesion to endothelial receptors have been reported to be highly sensitive to trypsin treatment [PAM expressed by CSA-selected parasite clone FCR3 with regard to recognition by antibodies acquired during PAM and adhesion to placental receptors.Since reatment ,21-24. Lreatment -27 or whreatment ,29, can Parasites were maintained in group O erythrocytes under standard conditions , using RSerum samples from 20 men living in a malaria endemic region of Ghana were pooled to produce the male serum pool. Serum samples collected at the time of birth from the placentas of 15 women living in a malaria endemic region of Ghana were pooled to produce the pregnant female serum pool. This pool included five primigravidae, nine secundigravidae and one multigravid woman. Serum samples from six Scottish malaria naïve individuals were pooled and used as a control.6 cells from sorbitol treated late stage cultures of 8–10 % parasitaemia were washed twice with phosphate-buffered saline (PBS) and then incubated with the appropriate concentration of trypsin-TPCK  or pronase (Boehringer-Mannheim) in a final volume of 1.0 ml in PBS, for 10 minutes at 37°C. The reaction was terminated either by adding soybean trypsin inhibitor  to a final concentration of 1 mg/ml or by adding 10% human serum. Cells were washed twice with PBS before further use.Protease treatment of infected erythrocytes was carried out as previously described . Brieflyet al [6 cells form late stage P. falciparum cultures of 8–10 % parasitaemia were washed twice with PBS. Cells were incubated sequentially with plasma antibodies diluted 1:20 in PBS, goat anti-human IgG diluted 1:200 in PBS (Dako) and fluorescein isothiocyante (FITC)-conjugated rabbit anti-goat (Dako) diluted 1:25 in PBS. All incubations were in a total volume of 100 μl for 30 minutes at room temperature and were followed by two washes with 1 ml of PBS. Samples were analysed immediately on a FACSCAN apparatus (Becton-Dickinson). FITC fluorescence due to cell surface antibody recognition was determined for 5000–10000 ethidium bromide gated infected erythrocytes.Flow cytometry was used to measure the levels of plasma IgG binding to the VSA of late stage parasites essentially following the method previously described by Staalsoe et al ,32. 3 × In order to circumvent the non-specific labeling of the VSA by the tertiary antibody, new reagents have been introduced. The procedure follows the method detailed above with the following modifications. A biotinylated rabbit anti-human IgG antibody (DAKO) was used diluted 1:25 to replace the secondary antibody. In the place of a tertiary antibody, FITC-conjugated streptavidin (DAKO) was used at a 1:2000 dilution. In these experiments the control sera was a pool of malaria naïve Danish volunteer serum.Human umbilical cord hyaluronic acid (Sigma) and bovine trachea CSA (Sigma) were used at a concentration of 10 μg/ml in PBS (pH 7.2). 20 μl of each receptor was spotted in triplicate onto 5 cm diameter petri dishes . Receptors were adsorbed onto the plastic petri dishes overnight at 4°C. 10 μg/ml BSA in PBS was similarly adsorbed as a negative control. Plates were then blocked by removing the receptor solution and adding 20 μl of 2% BSA in PBS. Following the removal of this blocking solution late stage parasites, suspended in 2 ml of complete RPMI-HEPES medium (8–10% parasitaemia, 5% haematocrit), were added to the petri dish. Parasites were incubated with the immobilized receptor for 60 minutes at 37°C with occasional agitation. Unbound cells were removed by four gentle washes with incomplete RPMI-HEPES medium; bound cells were fixed with 0.5% (v/v) glutaraldehyde in PBS for 10 minutes and Giesma Stained. Bound cells were counted by light microscopy. Protease treatment of intact cells was carried out as described above.Statistical analyses were performed using Analyses of Variance in Minitab 13.30 (Minitab Inc.), using protease, protease concentration and serum pool as explanatory variables. Statistical models were tested for homogeneity of variance and normality of error distributions. Where possible, maximal models with interactions between these variables were fitted first, after which models were minimized by removing nonsignificant (p > 0.05) terms.preg) . The unselected FCR3 clone expressed VSA that were equally well recognized by antibodies in the IgGmale and IgGpreg serum pools (figure 2,24 9.5, P = 0.001).It was first established that selection of clone FCR3 for adhesion to CSA resulted in the concomitant selection for VSA specifically recognized by plasma IgG from malaria exposed Ghanaian pregnant women (IgG) figure . Howevers figure . These ipreg binding of FCR3CSA was significantly more trypsin-resistant than was binding of the same serum to the unselected clone (figure 1,416.4, p = 0.015). Although the mean surface fluorescence due to the IgGpreg binding of FCR3CSA was slightly reduced by 0.1 mg/ml trypsin this reduction was not significant (figure 1,2 11.3, p = 0.078). The effect of 0.1 mg/ml trypsin on VSA recognition by IgGmale and IgGcontrol was comparable before and after CSA selection of the parasite (figure The trypsin sensitivity of this VSA/IgG binding interaction and of parasite adhesion to CSA was then measured. Parasitized erythrocyte surface trypsinization at a concentration of 0.1 mg/ml showed that the IgGpreg binding to FCR3CSA (figure 1,4 0.35, p = 0.587). However, treatment of the intact infected erythrocyte with 0.1 mg/ml pronase did significantly reduce IgGpreg recognition of FCR3CSA .The effect of a 10-fold higher trypsin concentration and the effect of the non-specific protease, pronase, on IgG recognition of FCR3CSA was also determined. Trypsinization with 1 mg/ml did not significantly reduce the mean surface fluorescence due to IgGcontrol binding to the infected erythrocyte surface increased following CSA selection of the parasite (figure 4,183.11, p = 0.041). This indicates that the epitopes recognized by the IgGcontrol serum pool and the epitopes recognized by the IgGpreg serum pool are distinct entities. An increase in apparent non-immune immunoglobulin binding to the infected erythrocyte surface has been observed for a number of parasite clones after selection for adhesion to CSA (data not shown). The source of this background labelling of FCR3CSA by naïve sera was found to be due to non-specific binding by the FITC-labelled tertiary rabbit anti-goat antibody. By using the modified antibody labelling procedure, which employs a biotin-labelled secondary antibody and FITC-labelled streptavidin, binding of malaria naive IgG to FCR3CSA (mean fluorescence index = 16) was comparable to the unselected parasite (mean fluorescence index = 17). Thus the recognition of VSAPAM by malaria naive IgG was abolished .Following the identification of trypsin-resistant epitopes that appear to be concomitantly selected with CSA adhesion, the trypsin sensitivity of CSA adhesion itself was determined. FCR3CSA binding to immobilised CSA was markedly more sensitive to trypsin than IgGe figure . Parasite figure . A tryps3,19 20.44, p < 0.001), at 71% that observed for CSA. Interestingly, as has previously been shown for other P. falciparum isolates [1,8 7.7, p = 0.024). Parasite adhesion to hyaluronic acid was found to be more sensitive to trypsinization than adhesion to CSA.Human umbilical cord hyaluronic acid (HA) was also included in these assays to investigate the binding capacity of the CSA selected clone with respect to this receptor. FCR3CSA was found to bind both HA and CSA, although binding to HA was significantly lower  was identified. Var2csa is predicted to possess distinctly different DBL domains and appears to be the major var expressed by CSA-selected parasites that are recognized by parity-dependent antibodies [The acquisition of antibodies to the surface of placental isolates correlates with protection from malaria in pregnancy and the targets of these antibodies are potential vaccine candidates ,15. Two tibodies . Proteomtibodies . The moltibodies . Howevervar (FCR3varCSA) in parasite clone FCR3 abolishes CSA binding, but the 'knock-out' parasites still bind the syncytio-trophoblast of ex vivo placental cryosections [Although PfEMPl-mediated CSA adhesion appears to play a role in placental malaria the molecular interactions triggering this syndrome are more complex than initially thought. Several studies implicate additional receptors and binding phenotypes of placental parasites, such as non-immune IgM , hyalurosections . Monoclosections . It is cSurface epitopes of the FCR3CSA parasite are both highly resistant to trypsin and are recognized by antibodies from malaria-exposed pregnant women. This agrees with a number of studies that have found parasite adhesion to placental receptors to be resistant to surprisingly high trypsin concentrations. However, binding assays with the parasite clone used in this study showed CSA and HA adhesion to be relatively trypsin-sensitive. This is also compatible with the results of Beeson and his colleagues who demonstrated trypsin-resistant CSA adhesion to be a clone dependent phenomenon . AnotherPAM and previously characterized VSA. Apart from being recognized only by female sera in a parity-dependent manner, VSAPAM show other distinct characteristics such as; i) VSAPAM rarely form infected erythrocyte rosettes when compared to CD36 binding VSA [PAM do not generally mediate adhesion to CD36 [PAM mediated adhesion to the placenta and CSA can be resistant to concentrations of trypsin known to remove most PfEMPl molecules from the infected cell surface. In combination with the findings of this study, these distinct properties of VSAPAM suggest the involvement of either an unusually protease-resistant PfEMPl structure, such has been shown to exist in the A4tres PfEMPl molecule [PAM can be exploited in comparative proteomic analysis to aid in the identification of the molecules whose phenotype is described here.This study supports the view that major differences exist between VSAding VSA ,45, ii) ding VSA , iii) VS to CD36 ,46, and molecule  or an alP. falciparum erythrocyte protein 1, PAM – Pregnancy associated malaria, VSA – variant surface antigens, VSAPAM – variant surface antigens expressed by placental or CSA binding parasites, IgG – immunoglobulin G, DBL-γ-Duffy like binding domain-gamma, FITC – fluorescein isothiocyanate.TPCK – L-(tosylamido-2-phenyl) ethyl chloromethyl ketone, CSA – chondroitin sulphate A, PfEMPl – P. falciparum culture, performed FACS analysis and binding assays, AE performed the modified labelling FACS experiments and participated in manuscript preparation, MS participated in the design of the study, TS helped develop some methodologies used in this study. DA helped conceive and fund the study and write the manuscript. All authors read and approved the final manuscript.LS conceived of the study, maintained None declared.


Clinicians require brief outcome measures in their busy daily practice to document global client outcomes. Based on the UK Therapy Outcome Measure, the Australian Therapy Outcome Measures were designed to capture global therapy outcomes of occupational therapy, physiotherapy and speech pathology in the Australian clinical context. The aim of this study was to investigate the construct (convergent) validity of the Australian Therapy Outcome Measures (AusTOMs) by comparing it with the EuroQuol-5D (EQ-5D).The research was a prospective, longitudinal cohort study, with data collected over a seven month time period. The study was conducted at a total of 13 metropolitan and rural health-care sites including acute, sub-acute and community facilities. Two-hundred and five clients were asked to score themselves on the EQ-5D, and the same clients were scored by approximately 115 therapists  using the AusTOMs at admission and discharge. Clients were consecutive admissions who agreed to participate in the study. Clients of all diagnoses, aged 18 years and over (a criteria of the EQ-5D), and able to give informed consent were scored on the measures. Spearman rank order correlation coefficients were used to analyze the relationships between scores from the two tools. The clients were scored on the AusTOMs and EQ-5D.There were many health care areas where correlations were expected and found between scores on the AusTOMs and the EQ-5D.In the quest to measure the effectiveness of therapy services, managers, health care founders and clinicians are urgently seeking to undertake the first step by identifying tools that can measure therapy outcome. AusTOMs is one tool that can measure global client outcomes following therapy. In this study, it was found that on the whole, the AusTOMs and the EQ-5D measure similar constructs. Hence, although the validity of a tool is never 'proven', this study offers preliminary support for the construct validity of AusTOMs. The costs of operating public health services in Australia are rapidly rising. Health administrators and practitioners are under pressure to document client outcomes and demonstrate the effectiveness of therapy interventions -3. IncreThe original TOM was developed for use by speech and language therapists in the UK for therapists to measure client outcomes in a clinical setting . Later, The AusTOMs was designed to measure client therapy outcome separately for occupational therapists, speech pathologists and physiotherapists. Similar to TOM, AusTOMs provides a 'snapshot' rating that is determined by the clinical judgment of the therapist, which broadly reflects the client's status. The development of the scales and content validity of AusTOMs has been published , as has The researchers attempted to find a 'gold standard' tool to investigate the concurrent validity of the AusTOMs. Health-related quality of life (HRQoL) tools have increasingly been used to assess multiple aspects of health-related quality of life in clinical trials . Tools sWhile in principle, health professionals support the notion of measuring health status, there is no consensus regarding the method of measurement ,27. WhilThe purpose of this study was to examine the measurement properties of the AusTOMs and to compare them with the EQ-5D in 'real practice'. The main question being; does AusTOMs perform in a similar manner to the EQ-5D? The study sought to investigate the following hypotheses:1. There will be a clear pattern of correlations for the admission, discharge and change scores between the AusTOMs domains and the EQ-5D Health Status and Thermometer. Several scale-specific correlations are expected. For example :a. There will be a moderate negative correlation of the admission, discharge and change scores between the PT AusTOMs Scale 'Pain', Impairment domain and the EQ-5D Health Status Subscale 'Pain'.b. There will be a moderate negative correlation of the admission, discharge and change scores between OT AusTOMs Scale 'Functional Mobility and Walking', Activity Limitation Domain and the EQ-5D Health Status Subscale 'Mobility'.c. There will be a moderate negative correlation of the admission, discharge and change scores between OT AusTOMs Scale 'Self-care', Activity Limitation domain, and the EQ-5D Health Status Subscale 'Self-care'.2. There will be a moderate positive correlation of the admission, discharge and change scores between all the Physiotherapy, Occupational Therapy and Speech Pathology AusTOMs Scales for the Wellbeing /Distress scores and the EQ-5D Thermometer.The research was designed as a prospective, longitudinal cohort study, with data collected over a seven month time period.Thirty-eight occupational therapists, 30 physiotherapists and 47 speech pathologists were trained at 13 participating facilities to collect AusTOMs data, and to present the EQ-5D for clients to complete. However, it is possible that not all these therapists collected data (data collection forms did not require therapists to record their identity). The facilities included acute hospitals, rehabilitation hospitals, and community care facilities. Therapists recorded AusTOMs data and obtained client EQ-5D ratings from 205 clients . These clients were from a larger group of 1007 clients who participated in the study . While some of these participants refused to complete the EQ-5D, or the therapists chose not to burden the client with completing this form, many were children or non-cognizant adults and the EQ-5D is not validated for these groups. Otherwise, the sample was sequential admissions to therapist caseloads over a seven month period.AusTOMs is comprised of three separate sets of scales for Occupational Therapy 12 scales), Speech Pathology  and Physiotherapy . The title of each scale is provided in Table 2 scales,Each scale requires a rating for four domains of client function, that is, Impairment, Activity Limitation, Participation Restriction and Wellbeing/Distress. An additional optional rating can be made of a caregiver's level of Wellbeing/Distress if the clinician has had contact with a caregiver, and feels that therapy is directed toward the caregiver in some way. Each of the domains are rated by therapists on an 11-point ordinal scale . Although clinicians are only required to use the 6 defined scale points, clinicians overwhelmingly chose to include the half points in the AusTOM scoring system to increase scale sensitivity. The use of the half points also facilitates international benchmarking of data against the UK TOM. A generic description of each of the domains of client function is presented in Table The EQ-5D consists of two parts; the self -classifier or questionnaire, and the EQ-Vas or Thermometer. The EQ-5D self-classifier is a one-page questionnaire, which captures respondent descriptions of health problems on a 5-dimensional classification of mobility, self-care, usual activities, pain and discomfort and anxiety and depression. Each dimension is rated by respondents on a three-level scale from 1 (no problem) to 3 (unable or extreme problem) . The EQ-Approval from the Human Ethics Committee at La Trobe University and the participating facilities was obtained. Study packs were collated for the collection of data. Each pack contained AusTOMs Scale Manual, AusTOMs and EQ-5D data collection forms, informed consent information and consent forms (if these were required by the facility ethics committee). The packs were sent to a contact person in occupational therapy, speech pathology and physiotherapy departments at each site participating in the project. The role of the contact at each site was to receive the packs, disseminate the packs to therapists, check the packs after completion and return them by postage paid envelope.On admission, the therapists  briefed each client about the study and after verbal agreement, clients were given a statement of informed consent to read and sign. Clinicians then recorded relevant demographic information and established with the client a specific goal or set of goals for the first episode of care. The therapist then chose the AusTOMs scale/s that best described the main areas targeted for therapy intervention. An admission rating was made by the therapist for each of the four domains of AusTOMs (impairment, activity limitation, participation and wellbeing/distress) on a scale from 0 (most severe) to 5 (least severe). A rating for Wellbeing/ distress was also made for the client's carer if this was applicable to the client's situation. Therapists report that the AusTOMs takes approximately 5 minutes to complete. The therapist then asked the client to complete the self -classifier section of the EQ-5D and the EQ-Vas (Thermometer). Clients were instructed to indicate which statements best described their own health state today, by placing a tick in one box for each of the dimension of mobility, personal care, usual activities, pain/discomfort and anxiety depression. Finally, clients completed the EQ-Vas. Information on the form stated, 'to help people say how good or bad a health state is, we have drawn a scale (rather like a thermometer) on which the best state you can imagine is marked 100 and the worst state you can imagine is marked 0. We would like you to indicate on this scale how good or bad your own health is today, in your opinion. Please do this by drawing a line from the box below to whichever point on the scale indicates how good or bad your health state is today' . ClientsThe data were analyzed separately for each profession given the differences in the AusTOMs scales. Correlational analyses were performed to investigate the relationship between AusTOMs and EQ-5D. Given the ordinal nature of the scales, a non-parametric approach was adopted, hence all analyses use Spearman's rank-order correlation coefficients (Spearman's Rho). Given the number of correlations performed, alpha  was set at .01, and magnitude of the relationship was considered using the guidelines from Colton  where .0Sample sizes were not sufficient to enable individual scale analysis for speech pathology scales. The analyses were conducted using only the first scaled selected by the therapist to rate the client. It is also important to note the directions of relationships reported. The EQ-5D Health Status subscales are 1 = no problem -> 3 = unable or extreme problem and the AusTOMs scores are 5 = Normal -> 0 = unable or extreme problem, hence, we expect to see negative correlations. However, the EQ-5D Thermometer scores 0 as the worst state and 100 as the best state and the overall EQ-5D Health Status self classifier score also indicates a better outcome as the score increases, and the AusTOMs scores are 5 = Normal -> 0 = unable or extreme problem. Hence, we expect to see positive correlations between these scores. In the 'Results' the statement is made that the results are in the 'expected direction'.In line with the research aims and hypotheses, the following analyses were undertaken across each profession's data set. First, a correlation considering all the AusTOMs scales for each domain with EQ-5D Health Status (self classifier score and the 5 dimensions) and Thermometer at admission was performed. Next, AusTOMs scores for each domain for a subset of the most frequently used OT and PT scales with EQ-5D Health Status (self classifier score and the 5 dimensions) and Thermometer at admission were obtained. Then, considering all the AusTOMs scales for each domain were correlated with EQ-5D Health Status (self classifier score and the 5 dimensions) and Thermometer at discharge. Following this, AusTOMs scores for each domain for a subset of the most frequently used occupational therapy and physiotherapy scales were correlated with EQ-5D Health Status (self classifier score and the 5 dimensions) and the Thermometer at discharge. Finally, correlations were obtained for change from admission to discharge scores for AusTOMs  with change from admission to discharge scores for EQ-5D Health Status (self classifier score and the 5 dimensions) and the Thermometer.A brief summary of demographic data from the sample is provided in Table Over all AusTOMs scales for each domain with EQ-5D Health Status (self-classifier score and the 5 dimensions) correlated with the Thermometer at admission .These results are reported in the first 4 rows of Tables AusTOMs scores for each domain for a subset of the most frequently used OT and PT scales with EQ-5D Health Status (self-classifier score and the 5 dimensions) correlated with the Thermometer at admission.Several moderate to strong correlations were found that were expected and these are presented in Table Over all AusTOMs scales for each domain with EQ-5D Health Status (self-classifier score and the 5 dimensions) correlated with the Thermometer at discharge.In relation to this correlation, the results are reported in the first 4 rows of Tables AusTOMs scores for each domain for a subset of the most frequently used OT and PT scales (only) with EQ-5D Health Status (self-classifier score and the 5 dimensions) correlated with the Thermometer at discharge.The correlations expected that were found are presented in Table Change from admission to discharge scores for AusTOMs  with change from admission to discharge scores for EQ-5D Health Status (self-classifier score and the 5 dimensions) correlated with the Thermometer.The moderate to good, statistically significant correlations expected between change on the EQ-5D and AusTOMs overall, or in relation to the six AusTOMs scales where sample size permitted are presented as follows: for physiotherapy '. There were several areas where relationships between constructs measured on AusTOMs and EQ-5D were expected (as described below), and it generally appeared that these two tools are measuring similar constructs. This lends some support to the construct (convergent) validity of AusTOMs. However, not all expected correlations were found and while AusTOMs seems to be measuring global change from the therapist's perspective in relation to four distinct domains (Impairment, Activity Limitation, Participation Restriction and Wellbeing), EQ-5D (as expected), is measuring client perceptions of how they feel about their health status. Hence, while both assessments attempt to capture global health-related outcomes, the differing perceptions of the raters (clinicians versus clients) does seem to impact on the establishment of construct validity. Suggestions for overcoming this problem are described below.The next sub-hypotheses dealt with specific correlations that were expected in these data. Unfortunately, there were insufficient data to determine if a moderate negative correlation between admission, discharge and change scores between the PT AusTOMs Scale 'Pain', Impairment domain and the EQ-5D Health Status Subscale 'Pain' existed. Similarly, there were insufficient data (n = 13) to explore the hypothesis that '...there will be a moderate negative correlation between admission, discharge and change scores between the OT AusTOMs Scale 'Functional Mobility and Walking', Activity Limitation Domain and the EQ-5D Health Status Subscale Mobility'. The final scale-specific hypothesis predicted a moderate negative correlation between admission, discharge and change scores between the OT AusTOMs Scale 'Self-care', Activity Limitation domain and the EQ-5D Health Status Subscale Self-care. This hypothesis was supported. The results indicate that therapist and client perceptions of client self-care ability status on admission, discharge (and in relation to the change scores) were moderately correlated. Since many occupational therapists spend considerable time working on self-care with clients, and talking about progress in this area, it is reasonable that clients and therapists would rate client status in this area in a similar manner.Finally, it was hypothesised that there would be a moderate positive correlation between admission, discharge and change scores across all the PT, OT and SP AusTOMs Scales for the Wellbeing domains and the EQ-5D Thermometer. There was only limited support for this hypothesis. However, in some cases the sample sizes were on the small side. There were no moderate, statistically significant correlations when analyzing across all combined OT and SP AusTOMs Scales for the Wellbeing domains and the EQ-5D Thermometer. However, there were moderate to good correlations at both admission and at discharge across all PT AusTOMs Scales for the Wellbeing domains and the EQ-5D Thermometer.Given the number of correlations performed for this study, it is important not to over-interpret the relatively small number of moderate and good correlations found. When considering these findings it is also important to note the relatively small sample size since a larger EQ-5D data set may have produced more, significant correlations. The low EQ-5D return rate from speech pathology is not surprising considering that clients seen by speech pathologists often have communication/ cognitive difficulties, and this increases the difficulty in using a self-administered tool such as the EQ-5D. Clinicians also reported that it was difficult to ask quite acutely unwell clients to complete the EQ-5D although they were able to score the client using the AusTOMs.The validity of a tool is never confirmed. Rather, many studies are required over time to demonstrate that a tool is operating in the manner which developers intended. Future validity studies could investigate the ability of AusTOMs to predict client discharge data from admission status, and to determine the capacity of the tool to discriminate between clients with differing severity levels of impairments and activity limitations. This has already been reported for the physiotherapy profession in relation to the UK TOM . In addiThe EQ-5D is used extensively in cost effectiveness analysis . It is bThe use of different tools across different disciplines to measure improvement can lead to different conclusions about benefits. If outcome measures of cost effectiveness are based on client perceptions it could well be the case that therapy interventions which are seen by therapists to lead to statistically significant improvements in outcome may not be so valued by clients. As a result, those interventions may not be found to be cost effective in an economic sense, if such an evaluation is based on measures of client perception, such as EQ-5D. These differences in perceptions may then contribute to conflict between policy makers, therapists and clients. Alternative economic measures of client outcome, such as return to work, may not be suitable in environments where a significant proportion of clients are beyond working age.Although the tools appear to be measuring somewhat similar constructs, the results of this study suggest that therapy outcome measures such as AusTOMs may need to be supplemented by client-based measures. As part of the treatment process, differences between responses should be discussed to improve understanding between client and therapist about expectations and achievable outcomes from therapy. This may in turn assist goal setting for the therapy process.CU and SD have made substantial contributions to conception and design of the study, analysis and interpretation of data and have been involved in drafting the article and revising it critically for important intellectual content. DD has made substantial contributions in the acquisition of data, and has been involved in drafting the article and revising it critically for important intellectual content. APand JS have made substantial contributions to conception and design of the study, acquisition of data, and have been involved in revising the article critically for important intellectual content. NT has made substantial contributions in the acquisition of data and has been involved in revising the article critically for important intellectual content. All authors have given final approval of the version to be published.


Scientists searching for clues to our origins have long relied on studying fossils to piece together our evolutionary history. Now, with the tools of molecular genetics, they can reach beyond morphological evidence to retrieve traces of DNA preserved in the remnants of bone. And in these ancient DNA sequences, they're finding bits and pieces of the evolutionary record. Over the course of evolution, changes in DNA sequences accumulate at a predictable rate. These mutations can reveal not only how closely related we are but also when evolutionary lineages diverged. Identifying both a typical range of genetic variation and rate of mutation for a given species or population, for example, can serve as a frame of reference for analyzing DNA sequences from other species or populations. Most molecular anthropologists use DNA found in mitochondria—intracellular structures that convert food into energy—to reconstruct human evolution. Distinct from nuclear DNA, mitochondrial DNA (mtDNA) exists in the cytoplasm of a fertilized egg and is passed on only through the maternal lineage.Homo sapiens and Homo Neanderthalensis interbred, since the two species coexisted. Neandertals lived roughly 150,000 to 30,000 years ago, toward the end of the Pleistocene era, and inhabited Europe, parts of Asia, and the Middle East. Modern-day humans arose between 100,000 and 200,000 years ago. Recently, an international multidisciplinary team of scientists led by Svante Pbo of the Max Planck Institute for Evolutionary Anthropology have analyzed the largest sample of Neandertal and early human remains to date and conclude that Neandertals could not have made a significant genetic contribution to early modern humans.An ongoing debate about human origins has revolved around the theory that Part of the challenge of resolving the human–Neandertal interbreeding issue stems from the fact that so many fossil samples—of both early humans and more archaic humans—are contaminated with the DNA of the contemporary humans who have handled them. So even if a Neandertal sample contained a “real” (or endogenous) DNA sequence resembling early humans—which would indicate intimacy between the two groups—it might be considered contaminated. When Pääbo and colleagues looked for modern DNA, they found it in every sample they examined: in the Neandertal and early human fossils—and even in cave bear teeth. To circumvent this problem, they looked only for Neandertal mtDNA as evidence of interbreeding. Since it is easy to distinguish modern human mtDNA sequences from the four Neandertal mtDNA samples that have been sequenced so far, the researchers decided to determine whether Neandertal-like mtDNA could be found in other Neandertal fossils as well as in early human remains.As these fossils are precious commodities, Pbo's group applied a technique developed in their lab that uses amino acid content as a measure of extractable endogenous DNA and requires removing just 10 mg of bone from a specimen rather than much larger pieces of bone. Of 24 Neandertal and 40 early modern human fossils analyzed, they found four Neandertal and five early human specimens that passed the amino acid test. These fossils included samples classified as “transitional” between the two groups and represented a wide distribution across Europe, where the two groups would likely have encountered one another. When they analyzed these samples for Neandertal mtDNA, they found mtDNA sequences that are absent in contemporary human mtDNA genes but quite similar to those found in the four previously sequenced Neandertals. They found no Neandertal-like mtDNA in the early human samples.While the authors explain that it's impossible to definitively conclude that no genetic flow occurred between early humans and Neandertals given the limited number of early human fossils available, they point out that even fossil samples considered as anatomically transitional between modern humans and Neandertals failed to show evidence of mtDNA exchange. Thus, Pääbo and colleagues conclude, while it's possible that Neandertals made a small contribution to the genetic makeup of contemporary humans, the evidence cannot support the possibility of a large contribution.