Our analysis shows that diffusion barriers of cytotoxic molecules conspire with γδ T-cell scarcity in tissue to limit the inhibitory effects of γδ T-cells on cancer cells. This may increase the necessary ratios of γδ T-cells to cancer cells within tissue to unrealistic values for having an intended therapeutic effect, and decrease the effectiveness of the immunotherapeutic treatment.Molecular-focused cancer therapies, e.g., molecularly targeted therapy and immunotherapy, so far demonstrate only limited efficacy in cancer patients. We hypothesize that underestimating the role of biophysical factors that impact the delivery of drugs or cytotoxic cells to the target sites  may be responsible for the poor clinical outcome. Therefore, instead of focusing exclusively on the investigation of molecular mechanisms in cancer cells, convection-diffusion of cytotoxic molecules and migration of cancer-killing cells within tumor tissue should be taken into account to improve therapeutic effectiveness. To test this hypothesis, we have developed a mathematical model of the interstitial diffusion and uptake of small cytotoxic molecules secreted by T-cells, which is capable of predicting breast cancer growth inhibition as measured both  Despite advances in both the diagnosis and management of early-stage disease, breast cancer remains the most frequently diagnosed cancer among women and leading cause of death in women worldwide T cells play a significant role in the immunosurveillance and destruction of cancer cells. The tumoricidal potential of γδ T-cells was derived from the observation of preferential expansion and infiltration of γδ T-cells in various types of tumors T cells expressing γ and δ T cell receptor (TCR) chains represent only a small subset (2%–5%) of the total T cell population. γδ T cells recognize antigens directly without any requirement for antigen processing and presentation or major histocompatibility complex (MHC) molecules in vitro (nearly complete response) and in vivo , here we focus on modeling spatial effects that are present in tissue in vivo but virtually absent in cell monolayers in vitro, specifically the diffusion of IFN-γ through tumor tissue. Our hypothesis is that diffusion gradients in relative scarcity of T-cells are a major factor in limiting immunotherapy efficacy. We test this hypothesis by comparing the mathematical model predictions of tumor cell kill (or inhibition) with our in vitro and in vivo measurements of γδ T-cell-mediated breast cancer growth control, and demonstrate the model’s predictive accuracy.Spatial effects associated with tumor-induced angiogenesis and vascular flow Methods):We model the diffusion of IFN-γ released by γδ T-cells. The fraction of tumor kill (or inhibition) L of the small cytotoxic molecules, defined in Eq. (3) and (4)). One way to experimentally achieve This equation relates in vitro to investigate the effect of diffusion and T-cell scarcity under different ratios in vitro experiments). The maximum cancer cell growth inhibition was observed at in vitro data of cancer cell survival with accuracy. This confirms that diffusion gradients may play a role in reducing the effect of the treatment under T-cell scarcity, i.e., at smaller values of Discussion. Herein, the dashed curves represent the most accurate prediction as they do not include the two outliers.We devised MTT cell viability and proliferation assays in-vivo experimental approaches. First, we determined whether growth inhibitory effects of γδ T-cells observed in vitro translate to an ectopic xenograft model using NOD/SCID mice and co-injected (at time Methods). We found that at t = 4 weeks, the tumor size was remarkably smaller in mice . To quantify the amount of apoptosis in CC3 stained images, the following formulation was used:cBr) and white (cW) classes, respectively, while Area represents the total number of pixels in an image (see Methods). The average apoptotic index measured was 2–4% (Methods), we confirmed a persisting small presence of γδ T-cells: t = 4 weeks (data not shown).Using immunohistochemical techniques on the tissue obtained from the sacrificed mice after 4 weeks of injection, we found that animals that received γδ T-cells have a higher number of apoptotic cells  where we injected the γδ T-cells in the tail-vein at t = 2 weeks, when the tumors were already established . After injecting 100 million γδ T-cells, tumors were allowed to grow for four additional weeks. The tumor volume was then assessed at t = 6 weeks. In the absence of direct measurement, we calculated the fraction of γδ T-cells in the tumors by assuming a tumor tissue density equal to water and exponential growth of the tumor; thus, from the tumor control size of ca. 285 million cells at t = 4 weeks, we estimated that there were ca. 17 million tumor cells at t = 2 weeks (when the tail-injection of γδ T-cells occurred). Considering that the tumor mass was 0.285 g whereas the weight of the mouse was 25 g, the above reasoning led to the estimate: To confirm these conclusions, we performed a second set of experiments  to tumor cells should be taken into account, in addition to exploring the underlying molecular mechanisms that regulate cancer cell behavior.The at t = 0 Fig. 1 wIn vitro, this was expected since at those high ratios less cell inhibition observed in vivo at Eq. (1) was derived by assuming that T-cells are scarce enough that, at any point in space, the concentration of IFN-γ is well approximated assuming the presence of only one T-cell source. The last experimental points in γδ T cells can be treated as chemotherapy drugs (while γδ T cells are live and more active), and thus with appropriate modifications, the general modeling method (Eq. (1)) can be used for studying tumor drug response to correlate tumor microenvironment to chemotherapy effectiveness. For instance, we have recently developed a model of mass transport using the same method presented herein to study the diffusion of chemotherapy drugs in colorectal cancer (CRC) metastases in the human liver. The model accurately predicts the fraction of dead tumor cells due to treatment, and agrees well with the patient samples (data not shown).Image Analysis).The amount of apoptosis was calculated automatically using image analysis algorithms. These algorithms provide the consistency needed for the accurate measurement of parameters needed for mathematical modeling. In case of human readers, there is a large intra- and inter-reader variability, so a model depending on the readers’ subjective determination may fail to explain the underlying mechanism. The challenge when developing image analysis algorithms is to account for the differences in the images of the immunohistochemically stained slides, that are caused by inevitable differences in slice thickness and the amount of stain used between different labs, even within the same lab or same slide. Here, we have successfully developed algorithms that are adaptive to these changes , may limit the effects of IFN-γ on inhibiting cancer cell growth. For example, if L is too small and γδ T cells are scare, IFN-γ may not be able to reach and bind to its receptors expressed on the surface of tumor cells.IFN-γ, released by γδ T cells, induces antiproliferative and proapoptotic effects on many types of cancer cells through a rather complex, interconnected signaling mechanism λ is the uptake rate of IFN-γ by the cancer cells, and D is the interstitial diffusion constant of IFN-γ. The diffusion penetration distance of IFN-γ is then:The concentration of IFN-γ across the tissue region (a mixture of γδ T cells and cancer cells) is described using the following partial differential equation:L. Note that L was estimated by comparing with doxorubicin’s values dλ, dL, and dM are uptake rate, penetration length, and molecule weight for doxorubicin, and gλ, gL, and gM are for IFN-γ, respectively. We find the decaying solution:Assuming that the diffusion penetration distance is small compared to the inter T-cell distance, we can ignore the overlap of the diffusion fields around multiple T-cells, and thus define the fraction of tumor kill by integrating Eq. (6) across a spherical volume Human peripheral blood (30 ml) was collected from healthy adult donors after obtaining the IRB approval from Wexner Medical Center at The Ohio State University and written consents from donors. Freshly collected blood was processed to isolate peripheral blood mononuclear cells (PBMC) following previously published protocols Immunocompromised (NOD/SCID) male mice (8 weeks old) were categorized into four groups. Each NOD/SCID mouse was subcutaneously injected with either tumor cells  or γδ T cells (15 million) separately or co-injected, i.e., SKBR7 plus γδ T cells, at a ratio of 1∶15 or 1∶30. Breast tumor cells were plated and cultured in 10 cm cell culture sterile petri dishes, three days before the injection. After three days, cells were trypsinized and counted. The cells were washed with 1 × PBS to get rid of the cell culture medium and diluted at the concentration of 1 million cells per 200 µl (1 × PBS). Similarly, on day 17 of culture, γδ T cells were isolated, washed and diluted at the concentration of either 15 million or 30 million per 200 µl (1 × PBS) and injected. After four weeks of injection, tumors were harvested and weighed, divided into 2 equal halves for further experiments. One half was formalin fixed for histology, immunohistochemistry or frozen at −80 C for later use or used for isolation of total protein.The harvested tissues were formalin fixed, paraffin-blocked, sectioned and immuno labeled with cleaved caspase-3 or anti-CD3 primary antibody and stained using horse peroxidase conjugated DAB staining by pathology core facility personnel at College of Veterinary Medicine, the Ohio State University.# 2010A00000139, dated 8/18/2010 and renewed annually). Each tissue sample was cut at a thickness of 4 µm and stained by Cleaved Caspase 3 (CC3) staining. Each stained slide was digitized using a ScanScope T2 digitizer  at 40× magnifications. Three representative areas of size equivalent to one high power field  were randomly selected by a blinded investigator, resulting in 12 images corresponding to the four different conditions.Four different conditions were analyzed . The tissue samples were obtained in accordance with the approval of Institutional Animal Care and Use Committee (IACUC), The Ohio State University Office of Research Integrity, protocol The objective of image analysis is to quantitatively determine the amount of apoptosis, which is manifested as brown hues in CC3 stains. A typical CC3 image generally contains three major hue classes: white  and (9), rows of X correspond to the pixels in I while the three columns of X represent the intensity values in I. It is worth mentioning that this rearrangement of pixels from I to X is necessary to simplify the computation of P.Principle component analysis (PCA) is one of the most widely used linear transformations where the eigenvectors serve as the new orthogonal coordinate system P, after PCA transformation, will consist of the same number of channels as the original image I. It is expected that the first channel in P will directly correspond to the I, as I is much richer in information content as compared to the other two channels. The second channel in the P image will highlight the region corresponding to the I. The third channel generally corresponds to noise and is ignored.As we are just changing the coordinate system, the projected image P are subjected to entropy based histogram threshold t such that the sum of the entropies of these probability distributions is maximized. More precisely, the value of j which maximizes the following objective function is set to t.To properly segment the brown and the blue pixels in the iy represents the number of pixels with intensity value i, while n represents the highest intensity value from the set of pixels under consideration. The resulting binary image is post-processed with morphological operations to fill small holes and to remove the small isolated components. Here,


Here, we subjected primary mouse astrocytes to glucose deprivation (GD), OGD and combinations of both conditions varying in duration and sequence. Changes in Δψm, visualized by change in the fluorescence of JC-1, were investigated within one hour after reconstitution of oxygen and glucose supply, intended to model in vivo reperfusion. In all experiments, astrocytes showed resilience to extended periods of OGD, which had little effect on Δψm during reperfusion, whereas GD caused a robust Δψm negativation. In case no Δψm negativation was observed after OGD, subsequent chemical oxygen deprivation (OD) induced by sodium azide caused depolarization, which, however, was significantly delayed as compared to normoxic group. When GD preceded OD for 12 h, Δψm hyperpolarization was induced by both GD and subsequent OD, but significant interaction between these conditions was not detected. However, when GD was extended to 48 h preceding OGD, hyperpolarization enhanced during reperfusion. This implicates synergistic effects of both conditions in that sequence. These findings provide novel information regarding the role of the two main substrates of electron transport chain (glucose and oxygen) and their hyperpolarizing effect on Δψm during substrate deprivation, thus shedding new light on mechanisms of astrocyte resilience to prolonged ischemic injury.Astrocytes can tolerate longer periods of oxygen and glucose deprivation (OGD) as compared to neurons. The reasons for this reduced vulnerability are not well understood. Particularly, changes in mitochondrial membrane potential (Δψ This is realized by respiratory proton (H+) pumps as core elements of the electron transport chain . Lack of the two main substrates of the ETC, glucose (electron donor) and oxygen (electron acceptor), causes a breakdown of the vital trans-membrane potential and thereby ceases oxidative phosphorylation.Oxidative phosphorylation is the major adenosine triphosphate (ATP) synthesis pathway in mitochondria. Energy required to drive this process is stored as the mitochondrial membrane potential  can lead to disastrous consequences on the cellular level already within seconds to minutes, and causes macroscopic brain infarction in the long run. However, there are remarkable differences regarding the tolerance of ischemic conditions among the major brain cell populations. In contrast to neurons, astrocytes are more resistant to ischemic conditions in vitro than in vivo. The cells were reported to be relatively resistant to sole oxygen deprivation (OD) or glucose deprivation (GD) when compared to combined oxygen-glucose deprivation (OGD). Less than 3 h of OGD do not produce irreversible astrocyte injury Since the brain lacks sufficient oxygen and glucose storage capabilities, interruption of continuous blood supply to the organ m fluctuations in cultured astrocytes A relatively short period of oxygen withdrawal (up to 20 min) causes mitochondrial depolarization thereby abolishing Δψm decrease 4 h after GD onset. Even though not immediately followed by significant LDH increase or astrocyte death m dynamics already between 45 min and 2 h of exposure to OGD. However, the exact time point of these early Δψm imbalances onset is discussed controversy m during simulated reperfusion after extended OGD exposures were not investigated in detail yet.On the other hand, already 1.5 h of GD under normoxic conditions induce mitochondrial membrane hyperpolarization, followed by Δψm during simulated reperfusion within one hour after extended exposure of cultured primary mouse astrocytes to GD or OGD. Since it has been proposed that either OD or low cytosolic ATP/ADP ratio can up-regulate glycolysis and thus support Δψm via ATP hydrolysis 3) during the simulated reperfusion, we have investigated the effect of “chemical OD” on Δψm which was already affected by preceding OGD.Therefore, the present study investigated ΔψAll animal experiments were performed according to the NIH Guide for Care and Use of Laboratory Animals (1985) and the European Communities Council Directive (86/609/EEC), and were approved by the responsible animal welfare authority at the Leipzig Regional Board (protocol number T22/12). All efforts were made to minimize animal suffering and to reduce the number of animals used.2 cell culture flasks (10 hemispheres per flask) and incubated at 37°C under a humidified 5% CO2-containing atmosphere. After 7 days in vitro (DIV7), flasks were vigorously shaken for several minutes to displace microglia and loosely adhered oligodendrocytes. Cells were washed with phosphate buffered saline (PBS), and medium was changed twice a week. After DIV14, the cells were trypsinized, split 1∶2, and further grown in DMEM containing 10% FBS for additional 10–14 days before being plated at a density of 5×104 cells on poly-L-lysine-coated 14 mm cover slips. Cells were used in experiments 4 days later.Primary brain cells were prepared from the dissociated forebrain cortices of fetal BALB/c mice on gestation day 18 (E18) as previously described The experimental procedure was divided into three steps: glucose preconditioning in normoxic conditions (i.e. GD), OGD and reperfusion. We used three different culturing media: “high glucose” (hG), “low glucose” (lG) and “no glucose” (nG) medium .2, 5% CO2 and 94% N2 at 37°C. Control astrocyte cultures were incubated under normoxic conditions. Following OGD, cultures were reoxygenated and fresh medium was provided for 10 min at 37°C under normoxic conditions in a humidified atmosphere containing 5% CO2, simulating reperfusion in vivo. Subsequently, astrocytes were stained for microscopic imaging (see below).For OGD, astrocytes on cover slips were rinsed two times with incubation medium, either lG or nG. The culture medium was replaced with the incubation medium shortly before transferring plates to an incubator  containing a humidified gas mixture of 1% O3), a potent inhibitor of the cytochrome c oxidase (complex IV) and FOF1-ATPase’s hydrolyzing function 2O2) to verify the results observed with NaN3 since such concentrations of H2O2 inflict both loss of Δψm and cell membrane integrity Sodium azide . Dye equilibration was allowed for 10 min at room temperature prior to imaging. Images were taken using Nikon Eclipse Ti-E inverted microscope with a Plan Fluor 10x objective. Samples were illuminated with Nikon C-HGFIE Intensilight (Precentered Fiber Illuminator) and fluorescence was recorded using Nikon DS-Qi1Mc digital camera. Stained, polarized mitochondria were detected with fluorescence settings for Cy3 . Loss of mitochondrial integrity was detected with settings for FITC . Images were analyzed using the NIS-Elements v3.0 software  by assessing the average fluorescence intensity from an individual image. Micrographs were slightly enhanced for printing (ImageJ 1.48a) and modification parameters  were strictly the same for each micrograph depicted in one panel to ensure comparability.The mitochondrial membrane potential was examined by staining astrocytes with JC-1 , a lipophilic, cationic dye that exhibits a fluorescence emission shift upon aggregation from 530 nm (green monomer) to 590 nm (red “J-aggregates”) post hoc test (GraphPad Prism 5.03). We used approximations of two-way ANOVA to examine the effect of culture media in comparison to OGD. All values are presented as mean ± standard deviation (SD). P-values <0.01 were considered as statistically highly significant .Measurements from individual plates were performed at least in triplicates with fluorescence intensities of all images obtained from a single experimental setting being averaged. The JC-1 fluorescence values were first normalized to its respective control for red and green signal separately before the ratio between them was calculated. All data sets were tested for normal distribution with Shapiro-Wilk’s normality test. Statistically significant differences between average values obtained in different experimental settings were analyzed by one-way ANOVA and Holm-Sidak’s multiple comparisons test as a m were investigated by JC-1 staining . On the other hand, astrocytes subjected to 6 h of OGD and treated with 5 mM NaN3 afterwards did not show any significant change of JC-1 red/green fluorescence ratio when compared to control levels. Therefore, addition of 5 mM NaN3 during simulated reperfusion to both normoxic and OGD astrocytes led to significant differences between these groups . Although normoxic astrocytes treated with 10 mM NaN3 exhibited lower fluorescence ratio when compared to respective OGD protocols , there was no statistically significant difference between them.There was no significant difference between control and OGD astrocytes p>0.01, . However3 and H2O2 on Δψm , since the effect of NaN3 was found transient and reversible already 15 min after washing out the inhibitor in previous experiments (data not shown). A dose-dependent, significant decrease of JC-1 red/green fluorescence ratio was observed for both NaN3  and H2O2 . When red and green signals were analyzed separately, we found that NaN3 increased solely the green signal to 188.6±25.4% , while H2O2 decreased the green signal to 90.0±33.3% and also decreased the red signal to 39.8±13.5%. Loading the dye under ETC inhibition did not show any significant difference in JC-1 red/green fluorescence ratio when compared to pre-dye loading procedure.Our next aim was to compare the effect of NaN2 on Δψm . To thism, we subjected astrocytes to 8 h of OGD in either lG or nG medium, as well as solely GD in normoxic conditions . OGD alone did not exert significant effects with level of significance being noticable low (p = 0.059), but the effect of culturing media alone did show significance . There was a significant increase in JC-1 red/green fluorescence ratio from the control in astrocytes cultured for 8 h in normoxic conditions in nG medium . Astrocytes cultured in nG medium and subjected to 8 h of OGD also showed a slight increase in fluorescence ratio (111.0±11.4%), however, this difference was not statistically significant (p>0.01). Astrocytes cultured in lG conditions and subjected to 8 h of OGD, also did not show any statistically significant change of fluorescence ratio .m during reperfusion between astrocytes subjected to 8 hours of OGD either in lG or nG , but there were statistically significant differences between all tested groups . Astrocytes that were cultured in lG medium and subjected to 6 h of OGD showed a significant increase in JC-1 red/green fluorescence ratio as compared to astrocytes incubated under normoxic conditions . Incubation in nG also showed a significant increase in fluorescence ratio as compared to astrocytes incubated in lG . In addition, astrocytes incubated in nG subjected to 6 h of OGD showed a further increase of fluorescence ratio (145.8±4.0%) which was significantly different from all three previously mentioned conditions (p<0.01).Further, the effect of extending preconditioning was studied. Astrocytes in normoxic conditions that were incubated for two days in lG showed significant increase of JC-1 red/green fluorescence ratio when compared to control astrocytes cultivated for 48 h in hG  caused by treatment with 5 mM NaN3 during simulated reperfusion. This highly interesting phenomenon may be related to NaN3 inhibition of the hydrolyzing function of the FOF1-ATPase and differences in oxidative mitochondrial metabolism between incubation in normoxia in hG and OGD in lG. This should be addressed in further studies. In general, the effect of NaN3 on Δψm has been found transient and reversible c oxidase 3 also binds to FOF1-ATPase and its sensitivity to NaN3 increases after bound ATP is hydrolyzed to produce bound ADP m dissipation by NaN3 quicker as compared to ETC inhibition alone when ATP/ADP ratio is low. As compared to relative fluorescence signals in H2O2 and ETC inhibition trials, it can be concluded that NaN3 has not affected the plasma membrane organization allowing at the same time JC-1 to enter the cytoplasm and mitochondria within. Namely, hydrogen peroxide decreases the activity of α-ketoglutarate dehydrogenase and NAD(P)H levels In our study there was no significant effect on Δψm during simulated reperfusion. First, these results corroborate data on the enhanced tolerance of astrocytes to extended oxygen and glucose deprivation (showing unchanged Δψm following OGD as compared to normoxic hG (control conditions). Second, we compared effects of DMEM and Neurobasal-A since the nG medium inhibits glial growth without usage of antimitotic agents simultaneously providing sustainable glucose- and serum-free environment, used commonly e.g. for culturing feeder layer of astrocytes in co-culture with neurons. On the other hand lG medium contains some residual glucose from 1% FBS which translates roughly to >700-fold reduction in glucose level, considered here as GD as similarly described elsewhere Similar results were obtained for 8 h of OGD regardless of whether astrocytes were incubated in lG or nG media. However, hyperpolarization was measurable to some extent (∼11% increase) during simulated reperfusion after OGD in nG medium. We were also able to demonstrate a significant effect of GD in normoxic conditions in nG yielding a ∼20% increase in Δψm dissipation and exhibit cell death upon treatment with complex I inhibitor rotenone regardless of the presence of glucose. Accordingly, glucose withdrawal for 6 h does not induce extensive oxidative stress and apoptosis in astrocytes, while GD is compensated by increased fatty acid oxidation m after OGD. Both conditions led to an increase in Δψm, but did not act synergistically. Those differences between media should be addressed in further studies.Astrocytes withstand Δψm during reperfusion affecting both normoxic and OGD group. Hyperpolarization was also observable after the OGD in nG medium following culturing in hG medium. These results suggested that lowering glucose in the culture medium several hours prior to OGD promotes hyperpolarization during the simulated reperfusion in astrocytes. Results also point to a significant interaction between preconditioning with GD and following OGD, implicating synergistic effects of both conditions in that sequence on Δψm, as well as further stressing out the difference between lG and nG media.Finally, we exposed astrocytes to even longer incubation (48 h) in the lG medium before subjecting them to 6 h of OGD in nG medium. Preconditioning with lG medium led to an increase in Δψm (both as GD and OGD), its effect became apparent when cells were cultured for 48 h in lG medium and then subjected to 6 h of OGD in nG medium. This led to the highest mitochondrial hyperpolarization observed. Such increase in Δψm has been demonstrated following the lack of either oxygen or glucose as the main substrates of the ETC Although lG alone didn’t exhibit any effect on Δψm while the effect of OGD on Δψm is limited and, to some extent, reversible. Although latter finding seams rather peculiar, it is in line with current literature data on enhanced astrocytic tolerance to such insult. Only 14% of cells die after 6 h of OGD and that number increase to 24% after 9 h of OGD (measured 24 h after the insult) 3. These finding may contribute to understand the impact of cerebral ischemia on astroglial populations and to the evaluation of results, related to the glucose level and glucose deprivation, obtained by studying ischemic injury in vitro. Astrocyte energy metabolism seems to be directly influenced by the level of glucose. Ultimately, these results point to the protective capacity of mitochondrial hyperpolarization against apoptotic cell death, and shed light on astrocytic resistance to prolonged ischemic injury.In conclusion, in all experiments astrocytes showed tolerance to extended periods of oxygen and glucose deprivation regardless of whether lG or nG medium was used. We confirmed that GD is a major contributor to the increase in Δψ


Drosophila melanogaster Genetics Reference Panel on standard medium and following chronic exposure to medium supplemented with 3 mM menadione sodium bisulfite (MSB). We found substantial genetic variation in sensitivity to oxidative stress with respect to locomotor phenotypes. We performed genome-wide association analyses to identify candidate genes associated with variation in sensitivity to ROS-induced decline in locomotor performance, and confirmed the effects for 13 of 16 mutations tested in these candidate genes. Candidate genes associated with variation in sensitivity to MSB-induced oxidative stress form networks of genes involved in neural development, immunity, and signal transduction. Many of these genes have human orthologs, highlighting the utility of genome-wide association in Drosophila for studying complex human disease.Reactive oxygen species (ROS) are a common byproduct of mitochondrial energy metabolism, and can also be induced by exogenous sources, including UV light, radiation, and environmental toxins. ROS generation is essential for maintaining homeostasis by triggering cellular signaling pathways and host defense mechanisms. However, an imbalance of ROS induces oxidative stress and cellular death and is associated with human disease, including age-related locomotor impairment. To identify genes affecting sensitivity and resistance to ROS-induced locomotor decline, we assessed locomotion of aged flies of the sequenced, wild-derived lines from the  The production of free radicals is an inevitable consequence of aerobic life Superoxide dismutase (Sod), Catalase (Cat), Glutathione reductase (GSR), and Glutathione peroxidase (GPx) as ROS scavengers age-1 in Caenorhabditis elegansmethuselah (mth) in Drosophila 66shc in mice Cellular defense mechanisms against oxidative stress include enzymatic antioxidants 2O2, which have commonly been used as agents to induce acute oxidative stress. MSB is milder, persists stably in the growth medium for prolonged time periods, and is effective in inducing chronic oxidative stress in adult flies during a two week exposure period, more closely mimicking human exposure. MSB at low concentrations mimics oxidant signaling and at higher concentrations induces lethal oxidant stress in cells from mice and chickens PARP-1 confers protection from MSB-induced cell death Chronic exposure of flies to rotenone Drosophila melanogaster Genetic Reference Panel (DGRP) Here, we capitalized on natural variation in the Flies from 192 inbred lines of the DGRP Five DGRP lines  were used to assess the effects of different concentrations of MSB on lifespan 2 exposure into vials containing 5 ml of standard cornmeal-agar-molasses medium, were left overnight. Startle responses were quantified the following morning by subjecting each fly to a mechanical disturbance by tapping the vial twice against a surface and recording the amount of time the fly is active in the 45 second period immediately following the disturbance. All measurements were taken from 8 a.m.–12 p.m., 2–6 hours after lights on. Startle response scores were obtained for 2 replicates of 15 males and 15 females for each of the 192 lines in a randomized design for both control and MSB exposure conditions. To account for temporal fluctuations and sampling assay bias, a block design was implemented, where 15–20 lines were tested during a two week period for each block.Startle response was assessed as described previously 2 exposure into vials containing 5 ml of standard cornmeal-agar-molasses media were left overnight to acclimate to the new environment. Flies were transferred to glass assay tubes  during 8 a.m.–12 p.m., 2–6 hours after lights on, the next day. To measure negative geotaxis, flies were tapped to the bottom of the glass tube and allowed to climb up along the wall of the tube for a period of 5 seconds. Each fly received a score for the highest point reached during the assay period according to 26 divisions of 5 mm each so that scores ranged from 0 to 26. Geotaxis scores were obtained for 2 replicates of 15 males and 15 females for each of the 192 lines for both control and MSB exposure conditions in the same randomized block design as startle response.Single 13–16 day old flies, collected under COvs. MSB supplemented medium), we used the full mixed model ANOVA y = μ+B+L(B)+S+T+S×L(B)+S×T+T×L(B)+S×T×L(B)+R(S×T×L(B))+E. The model was used to partition variation between blocks , line within blocks (L(B), random), sex , treatment , and all interactions, vial replicate , and error (E). When a significant block term was found, we corrected by subtracting the overall mean by block, treatment, and sex from each corresponding raw data point. To ensure a positive number we then added back the overall mean by sex and treatment: [(ix(BST)−(BST))+(ST)]. Using the transformed data, we removed block effects and tested for the effects of treatment using the mixed model ANOVA y = μ+L+S+T+S×L+S×T+T×L+S×T×L+R(S×T×L)+E. Correlations across environments were calculated as GEr = σ2L/(σ2L+σ2LT+σ2LST). In addition, we performed reduced analyses within each treatment for the block-corrected data using mixed model ANOVAs of form y = μ+L+S+L×S+R(L×S)+E. Broad sense heritabilities were estimated as H2 = (σ2L+σ2LS)/(σ2L+σ2LS+σ2E), and genetic correlations between sexes and traits were estimated as G = covr12/(σ1×σ2), where 1 and 2 represent either males and females or control and MSB medium To test for effects of treatment (control LineiC −LineiMSB )/(PopC −PopMSB )], which is the difference in individual line means under control and MSB treated conditions divided by the difference in overall population mean in both control and MSB conditions σ2M = 0.25(σ2L C+σ2L MSB)+0.5σ2L C, MSB. The variance of sensitivity across pairs of environments was estimated as σ2S = /D2. The difference between means is D = MS = cov(σ2L C−σ2L MSB)/2D. The genetic correlation between the mean and sensitivity is calculated as MS = covMSr/(Mσ×Sσ) In order to identify which lines are more sensitive or resistant to MSB treatment, we computed the measure of sensitivity as [(y = μ+M+S+M×S+L(M×S)+E, where M is the fixed effect of the polymorphic site, S is the fixed effect of sex, and L(M×S) is the random effect of line within marker and sex. Reduced analyses were performed on males and females using the fixed effects reduced model y = μ+M+E. An arbitrary threshold of P<10−5 was used to nominate SNPs for further study. Effects (a) of SNPs were estimated as the average difference in trait mean between the major and minor alleles .All analyses were performed on line means of 167 of the 192 DGRP lines P<10−5) within 1 kb of an annotated gene. The most significant marker from the GWA was first fit into the model, and subsequent markers were added until the maximum 2r was attained. Missing marker data SNPs in the model were imputed based on nearest marker information for the final model.To estimate the fraction of total phenotypic and genetic variation accounted for by markers, we used multiple regression, because single marker analysis can lead to biased estimates of allelic effects when multiple markers jointly affect the trait P{MiET1} elements inserted within candidate genes, in a common co-isogenic 1118w background μ+G+S+T+G×S+G×T+T×S+G×S×T+E for sexes pooled and the reduced ANOVA y = μ+G+T+G×T+E for sexes separately, where G is the fixed effect of genotype (mutant or control), S is the fixed effect of sex, and T is the fixed effect for treatment (MSB or control media), and all interactions. A significant G×T term indicates that the mutant genotype behaves differently in the treatment environments than the control genotype. Within the MSB environment, we performed comparisons of line means using Dunnett's test to nominate significant differences between mutants (P{MiET1} elements) and its control (1118w).We tested whether mutations in 16 of the candidate genes in which polymorphisms were associated with sensitivity/resistance to ROS-induced behavioral deficits also affected MSB effects on geotaxis and startle behaviors. The mutations were homozygous www.bioprofiling.de) Gene ontology analysis of all genes harboring SNPs associated with variation in sensitivity to chronic oxidative stress was performed with DAVID To determine an optimal discerning MSB concentration to assess natural variation in sensitivity to oxidative stress, we chose five DGRP lines with a range of startle responses under standard conditions To assess whether there is genetic variation in sensitivity to chronic oxidative stress in the DGRP, we quantified startle response and negative geotaxis of 13–16 day old flies from 192 DGRP lines reared on standard medium or 3 mM MSB supplemented medium, in a randomized block design . We detei.e., there is genotype by environment interaction for locomotor performance, or equivalently, variation in sensitivity among the lines). This is also evident from the complex pattern of crossing reaction norms   directional. Not surprisingly, the two traits are positively correlated within each treatment, but the correlations are moderate (eatment) . TherefoPr = 0.14)  . TherefoGr, a measure of the extent to which the means are correlated across environments), and the correlation (MSr) between mean performance and sensitivity Gr = 0.82 for both startle response and negative geotaxis, MSr = 0.29 for startle response and MSr = 0.10 for negative geotaxis)  . Thus, wP<10−5, we found 251 SNPs in 235 genes associated with startle response in the presence of MSB; 291 SNPs in 244 genes associated with startle response sensitivity; 468 SNPs in 227 genes associated with negative geotaxis in flies treated with MSB; and 220 SNPs in 192 genes associated with negative geotaxis sensitivity  and 6% (P<10−6). It is not possible to compute true false discovery rates because SNPs are not independent, and thus the correct value for the numerator and denominator are not known. Although linkage disequilibrium (LD) declines rapidly on average with physical distance 2L associated with variation in negative geotaxis following MSB treatment for which the average R2>0.8 , regulation of transcription , calcium and calmodulin binding and transport , receptor signaling , actin organization (spir), and regulation of apoptosis (DLP). We measured startle responses for NetA, CG34411 (2 insertions), Lar, DLP, spir, A2bp1, beatIV, Vsx2 mutants, and negative geotaxis for form3, Lar, Eip63-1, luna, CG13579, side, igl, and CG33291 mutants.Next, we sought to confirm whether novel genes in which naturally occurring variants are associated with variation in susceptibility to chronic oxidative stress show similar associations for mutant alleles. We chose candidate genes for these tests based on the availability of co-isogenic homozygous P{MiET1} element insertion. Six of eight mutants tested for altered sensitivity of startle behavior to MSB treatment and seven of eight mutants tested for altered sensitivity of negative geotaxis to MSB treatment showed a significant genotype by treatment effect , comprising 32 candidate genes for which natural variation is associated with variation in oxidative stress-induced behavioral decline , whereby some lines were highly sensitive and others actually had improved performance when reared in MSB-supplemented medium. The correlation between sensitivity and the mean performance for each trait was low, indicating that the genotype by environment interaction is not caused by a scale effect We have taken advantage of natural variation in the sequenced, inbred lines comprising the P-value<10−5. In contrast to results from human GWA studies Our GWA identified 1,218 SNPs and 796 genes associated with the effects of chronic MSB exposure on geotaxis and startle behavior at a nominal Minos insertional mutations that were generated in a common isogenic background However, testing the effects of over 2.5 million SNPs in only 200 lines presents a statistical problem: there are many different multiple regression models utilizing subsets of SNPs that provide equally good prediction models in terms of variance explained. However, we can utilize the evolutionary conservation of biological pathways and the power of the Drosophila model system to assess which of the variants nominated by the GWA study are potentially true positives and which may be false positives. We hypothesized that the variants identified in the GWA analysis are enriched for true positives, and that these loci are likely to interact in known pathways. Indeed, our bioinformatics analysis reveals an over-representation of candidate genes associated with nervous system development and neural signaling, as well as immune defense, consistent with the established association of exposure to oxidative stress and increased risk for development of neurodegenerative diseases, such as Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis CG5703, NDUFV2, has been linked to Parkinson's disease GRIP2, the human homolog of Grip, has been implicated in Alzheimer's disease ANKS1B, the homolog of CG4393, interacts with amyloid beta protein precursor, which has been implicated in the pathogenesis of Alzheimer's disease PTPRD, the human counterpart of Lar, interacts with IL1RAPL1, which is implicated in mental retardation and autism CG7394, DNAJC19, is associated with cardiomyopathy Drosophila melanogaster genetic model system can guide future translational research on human diseases associated with exposure to oxidative stress.Approximately 25% of the confirmed genes with mutational effects on locomotion-related behaviors under MSB-induced chronic oxidative stress are evolutionarily conserved and have human homologs. The human homolog of Sod and Cat, as well as other loci known to affect sensitivity to oxidative stress, in our analysis. Possibly these loci are under such strong purifying natural selection that they are either invariant or that the variation is too rare to be included in our GWA study, which is blind to variants detected in fewer than four DGRP lines. In addition, we only assessed the effects of SNP variants. In the future, we will be able to evaluate the effects of the full spectrum of naturally occurring mutations, including insertion/deletion mutations, microsatellites and other structural variants. Finally, future systems genetics analyses Most of the candidate genes implicated by our GWA study are novel and have not previously been associated with either geotaxis or startle behavior or sensitivity/resistance to oxidative stress. This highlights the value of interrogating the effects of natural variants that have survived the sieve of natural selection to understand the genetic architecture of quantitative traits. In this regard, GWA analyses using the DGRP are complementary to traditional mutant screens. On the other hand, we did not detect variants in Figure S1Reaction norms for locomotor performance on control (C) and MSB-supplemented (T) medium. (A) Startle response. (B) Negative geotaxis.(PDF)Click here for additional data file.Figure S2Correlation between startle response and negative geotaxis. (A) Control medium. (B) MSB-supplemented medium.(PDF)Click here for additional data file.Figure S3Correlation between sensitivity of startle response and negative geotaxis.(PDF)Click here for additional data file.Figure S4Correlation of locomotor behavior between control and MSB-supplemented medium. (A) Startle response. (B) Negative geotaxis.(PDF)Click here for additional data file.Figure S5Correlation between mean and sensitivity of locomotor behavior. (A) Startle response. (B) Negative geotaxis.(PDF)Click here for additional data file.Table S1Mean startle responses and negative geotaxis scores for DGRP lines.(DOCX)Click here for additional data file.Table S2ANOVA of locomotor traits across treatments.(DOCX)Click here for additional data file.Table S3ANOVA of locomotor traits within treatments.(DOCX)Click here for additional data file.Table S4Quantitative genetic analysis of sensitivity.(DOCX)Click here for additional data file.Table S5Significant GWA results.(XLSX)Click here for additional data file.Table S6Overlap between SNPs and genes from GWA analysis.(DOCX)Click here for additional data file.Table S7Gene-centered prediction models.(DOCX)Click here for additional data file.Table S8Gene Ontology enrichment analysis.(XLSX)Click here for additional data file.Table S9Human orthologs of Drosophila genes.(XLSX)Click here for additional data file.Table S10Overlap of genes in this study and GWA for acute oxidative stress.(DOCX)Click here for additional data file.Table S11Gene Ontology enrichment analysis of genes in common between chronic and acute oxidative stress.(XLSX)Click here for additional data file.


In endothelial cells over-expression of BAMBI reduced, whereas knock-down enhanced capillary growth and migration in response to TGFβ. In vivo angiogenesis was enhanced in matrigel implants and in glomerular hypertrophy after unilateral nephrectomy in BAMBI−−/ compared to BAMBI+/+ mice consistent with an endothelial phenotype for BAMBI−−/ mice. BAMBI’s mechanism of action in endothelial cells was examined by canonical and alternative TGFβ signaling in HUVEC with over-expression or knock-down of BAMBI. BAMBI knockdown enhanced basal and TGFβ stimulated SMAD1/5 and ERK1/2 phosphorylation, while over-expression prevented both.Identifying BAMBI’s functions requires identification of cell-specific expression of BAMBI. By immunohistology we found BAMBI expression restricted to endothelial cells and by electron microscopy BAMBI−−/ mice, and provide in vitro and in vivo evidence that BAMBI contributes to endothelial and vascular homeostasis. Further, we demonstrate that in endothelial cells BAMBI interferes with alternative TGFβ signaling, most likely through the ALK 1 receptor, which may explain the phenotype observed in BAMBI−−/ mice. This newly described role for BAMBI in regulating endothelial function has potential implications for understanding and treating vascular disease and tumor neo-angiogenesis.Thus we provide a first description of a vascular phenotype for BAMBI The multiple and often opposing actions of TGFβ are due to the cell-type specific expression of the diverse members of the TGFβ family, their multiple receptors and signaling pathways, which can be further influenced by cell-restricted modulator proteins −−/ mice could escape detection. TGFβ plays an important role in angiogenesis and signals through alternative pathways in endothelial cells We argued that the interaction of BAMBI with the TGF family would require co-expression of the respective receptors and BAMBI in the same cell type in vitro and in vivo angiogenesis assays show that BAMBI decreases angiogenesis, whereas BAMBI elimination enhances angiogenesis under all experimental conditions. Furthermore BAMBI−−/ mice have an endothelial phenotype as evidenced by electron microscopy of capillaries in heart and kidney tissue, and by larger renal glomerular capillary convolutions, which show enhanced neo-angiogenesis during compensatory renal hypertrophy in BAMBI−−/ as compared to BAMBI+/+ mice. In HUVEC the effects of BAMBI are mediated predominantly through interactions with alternative TGFβ signaling through SMAD1/5 and ERK 1/2 phosphorylation. Taken together we identify for the first time a vascular endothelial phenotype in BAMBI−−/ mice, and provide evidence for a physiological role for BAMBI in endothelial biology and vascular homeostasis, observations that may be of considerable interest for the modification of the vascular actions of TGFβ by BAMBI, including neo-angiogenesis during tissue injury and during tumor growth.We now report that BAMBI expression is restricted to vascular endothelial cells in all major organs examined. Results of A detailed Methods section can be found as an online supplement. .All animal studies were carried out with compliance with the Mount Sinai School of Medicine Institutional Animal Care and Use Committee approved protocols (protocol number LA08-00399).−−/ mice were generated as reported The BAMBIPrimary human endothelial cells, HUVEC,  were transfected with BAMBI siRNA  using Lipofectamine RNAiMAX , according to the manufacturers’ protocol. The endothelial cell line EA.hy926  was transfected with BAMBI or control lentiviral constructs as previously described Endothelial cells were seeded on cytokine depleted Matrigel (BD Bioscience) and cultured with/without addition of TGFβ-1  or vehicle at 37°C. Cells were photographed using a Nikon TE2000-U microscope equipped with a CCD camera (Diagnostic Instruments) Angiogenesis was evaluated using the modification of the matrigel implant assay as described by Guedez et al. with the assay kit DIVAA TM  EM was performed as previously reported +/+ and BAMBI−−/ male 6 weeks old mice was surgically removed as previously described The right kidney of BAMBIData are presented as mean ± SEM. For all assays, statistical analysis was performed using a Mann-Whitney test. For the matrigel implant and the unilateral nephrectomy experiments, where the same animal was sampled at different times, the Wilcoxon test was used. We deemed a P<0.05 as significant. We used Statview software for all analyses.+/+ mice, . Knock-down of BAMBI by siRNA significantly enhanced migration in the absence of TGFβ , TGFβ or LY364947. Angiogenesis was significantly enhanced in the BAMBI−−/ mice under basal conditions as well as with addition of VEGF and FGF . However, the number of endothelial cells per capillary cross section was increased in BAMBI−−/ mice from only one cell in 100% of capillary cross sections of BAMBI+/+ myocardium to two cells in 70% of BAMBI −−/ hearts . Epithelial foot-processes were distinct but occasionally appeared broadened. The prominence of endothelial cells was also seen in the renal peritubular capillaries of the BAMBI−−/ mice  and BAMBI−−/ mice . However, by computer-assisted morphometrical analysis of overall glomerular area (determined as area within Bowman’s space on hematoxylin and eosin stained sections) was significantly larger (P<0.05) in BAMBI−−/ mice  as compared to age and sex matched BAMBI+/+ mice (2749±108 µm2n = 87 glomeruli from 4 mice).Because of the glomerular changes we examined the number, size and endothelial areas of glomeruli from adult BAMBI/− mice . The num+/+ and BAMBI−−/ mice .Total glomerular tuft area and glomerular endothelial area by iso-lectin B4 staining were determined in parallel before and after unilateral nephrectomy in BAMBI/− mice , as the mparable . In cont/− mice . These dertrophy  B and C −−/ mice did not significantly influence glomerular perm-selectivity as evidenced by lack of albuminuria in BAMBI−−/ mice aged 4 to 18 weeks or at 2 weeks after unilateral nephrectomy Click here for additional data file.Figure S2Levels of mRNA for BAMBI in HUVEC after transfection with either scrambled siRNA or siRNA for BAMBI. Comparable results were obtained in three independent series of experiments. Western blot for BAMBI and GAPDH from HUVEC treated as above.(TIF)Click here for additional data file.Figure S3Illustration for the method used for determinations of glomerular area, capillary tuft and endothelial, isolectin B4 positive areas in slides from kidney tissue. For the determination of capillary endothelial tuft, images of frozen sections of renal cortex were taken at 20-fold magnification, first using the appropriate fluorescence channel for the isolectin B4 marker  and second using differential interference contrast microscopy settings (DIC Nomarski). The left panel shows the image obtained with DIC-Nomarski microscopy, the central one the determination of the capillary tuft and the right picture the isolectin B4 positive area which was determined by an observer blinded to the origin of the slides using METAMORPH computer analysis.(TIF)Click here for additional data file.Figure S4+/+ and BAMBI−/− mice.Immunofluorescence staining for BAMBI performed on different organs from BAMBI(TIF)Click here for additional data file.Methods S1(DOC)Click here for additional data file.


Parasitic helminths present one of the most pervasive challenges to grazing herbivores. Many macro-parasite transmission models focus on host physiological defence strategies, omitting more complex interactions between hosts and their environments. This work represents the first model that integrates both the behavioural and physiological elements of gastro-intestinal nematode transmission dynamics in a managed grazing system. A spatially explicit, individual-based, stochastic model is developed, that incorporates both the hosts’ immunological responses to parasitism, and key grazing behaviours including faecal avoidance. The results demonstrate that grazing behaviour affects both the timing and intensity of parasite outbreaks, through generating spatial heterogeneity in parasite risk and nutritional resources, and changing the timing of exposure to the parasites’ free-living stages. The influence of grazing behaviour varies with the host-parasite combination, dependent on the development times of different parasite species and variations in host immune response. Our outputs include the counterintuitive finding that under certain conditions perceived parasite avoidance behaviours  can increase parasite risk, for certain host-parasite combinations. Through incorporating the two-way interaction between infection dynamics and grazing behaviour, the potential benefits of parasite-induced anorexia are also demonstrated. Hosts with phenotypic plasticity in grazing behaviour, that make grazing decisions dependent on current parasite burden, can reduce infection with minimal loss of intake over the grazing season. This paper explores how both host behaviours and immunity influence macro-parasite transmission in a spatially and temporally heterogeneous environment. The magnitude and timing of parasite outbreaks is influenced by host immunity and behaviour, and the interactions between them; the incorporation of both regulatory processes is required to fully understand transmission dynamics. Understanding of both physiological and behavioural defence strategies will aid the development of novel approaches for control. Parasitic helminths present one of the most pervasive challenges to grazing herbivores Both nutritional resources and infective larvae are unevenly distributed in both space and time In addition to the potential influence of grazing behavior, the host immune response plays a crucial role in transmission dynamics. Prolonged exposure to the infective stages of GINs leads to a decrease in the establishment, fecundity and survival of parasites in the host Physiological and behavioural elements of transmission should not be considered in isolation, as there is a two-way interaction between host grazing behaviour and parasite burden. In grazing herbivores, parasitism can induce inappetence, reduction in grazing time and changes in grazing behaviour This paper develops a framework which integrates a stochastic version of the parasite transmission model of Roberts & Grenfell (1991) This framework is subsequently applied to explore how host behaviours influence macro-parasite transmission in a spatially and temporally heterogeneous environment, with the following objectives: 1) Determine how host parasite burden is influenced by spatial aggregation of both nutritional resources and infective larvae on pasture; 2) Determine the impact of host faecal avoidance behaviour on the timing and intensity of parasite outbreaks, for parasites with different on-pasture development times; 3) Determine the influence of faecal avoidance on parasite dynamics, for hosts with differing abilities to mount an immune response; and finally 4) Explore the interactions between host grazing behaviour and parasitised state, to elucidate potential benefits that anorexia can provide the host.Using values outlined in the main parameterisation section, the model successfully reproduces the parasite dynamics empirically observed in livestock grazing systems As the size of faecal deposits increases the level of clustering of larvae increases, leading to a rise in the severity of outbreaks for small to moderate clustering levels . HoweverIn runs with realistic levels of clustering  Grazing behaviour also has a great influence on parasite transmission affecting both the timing and level of exposure to the parasite’s free living stages. For directly-transmitted pathogens that are infective immediately or develop quickly on pasture, faecal avoidance can decrease risk . HoweverThe efficacy of faecal avoidance in minimising parasite risk varies with the host’s ability to mount an immune response. For hosts with a very limited ability to gain resistance, a range of faecal avoidance levels are advantageous .Showing no faecal avoidance is a preferable strategy for parasite-host combinations where the host has an effective immune response and for pathogens with long on-pasture development times. In contrast, faecal avoidance is an effective defence strategy for parasite-host combinations where the host has limited ability to mount an immune response and for parasites with quick development times on pasture  and 4a. To begin to explore the interactions between grazing behaviour and parasite dynamics, in the previous simulations grazing behaviour was conditionally independent of parasite burden –5. In reThe infection dynamics shown in Transmission dynamics are influenced by processes which regulate infection (maintaining parasite population density within certain bounds), and those which control infection (perturbatory processes) Transmission dynamics are influenced by the spatial heterogeneity that is created and maintained in the system; the clumped release of host faeces and parasite progeny, and the host’s selective grazing, create uneven distributions of resources (grass), risk (infective larvae) and perceived risk  on pasture.For simulations parameterised with realistically-sized faecal deposits, spatial heterogeneity in infection risk is qualitatively consistent with field observations  [9]. HigIn addition to influencing the spatial distribution of parasites, grazing behaviour also alters the timing of ingestion of the parasites’ free living stages. Hosts with no faecal avoidance encounter parasites when they are fresh on pasture, whilst increasing levels of faecal avoidance delay contact. For parasites that are immediately infective, or have quick development times on pasture, faecal avoidance decreases infection risk, as the host is less likely to graze contaminated patches when the population of infectious larvae is at its highest.However, for parasites with delayed development on pasture (2 to 3 weeks), hosts without faecal avoidance have the lowest parasite burdens . This isHosts with higher faecal avoidance levels take more bites from verdant patches once faeces has decayed, grass has grown tall and larvae have developed into their infective stage. This illustrates how faecal avoidance can increase parasite risk, and that faecal contamination level alone is not a reliable proxy for infection potential. This has previously been demonstrated by Van Der Wal et al. The increased parasite risk incurred through faecal avoidance as demonstrated here could be amplified by environmental factors not currently included in the model. For example, contaminated patches that have been left ungrazed for an extended period would enable greater survival of L3 due to increased protection from heat and desiccation. A corollary to this has been demonstrated as a decrease in parasite intensity in cattle co-grazed with sows; the sows’ rooting behaviour breaks up the cattle faeces, reducing survival and availability of infective larvae k = 2, have lower burdens than those with no avoidance, see The extent to which grazing behaviour influences parasite transmission varies with the host’s ability to mount an immune response . DevelopHigh levels of faecal avoidance can reduce parasite intensity for parasite-host combinations where the host has low levels of resistance acquisition . HoweverFor hosts with a greater ability to mount an immune response, the low-level trickle infection received by hosts with no faecal avoidance is enough to engender an immune response, but not enough to lead to high levels of parasite establishment. If these hosts had high levels of faecal avoidance and delayed their encounters with infected patches until all larvae on that patch had matured, they would ingest large numbers of fully-developed larvae in one go, which could allow significant numbers of parasites to complete their lifecycle. This effect of faecal avoidance on parasite risk will vary across parasite species with different development times see .In addition to changing the intensity of parasite outbreaks, grazing behaviour also affects the timing of peak parasite burdens . Faecal In the initial simulations –5, host Our findings qualitatively demonstrate the influence of anorexia on transmission dynamics. However anorexia is part of the generic acute phase response common to most infections In conclusion, grazing behaviour affects the timing and intensity of macro-parasite outbreaks, by generating spatial heterogeneity and changing the timing of exposure to the parasites free living stages. The influence of grazing behaviour varies with the host-parasite combination, with faecal avoidance behaviour being most beneficial when hosts have a limited ability to mount an immune response, and against parasites with fast on pasture development times. For macro-parasites with prolonged development times on pasture, faecal avoidance behaviour can increase risk. Further development of the model to incorporate co-infection with parasite species which exhibit varying development times could reveal an optimal grazing strategy. Our results also indicate that parasite-induced anorexia can be beneficial for the host through minimising both intake losses and parasite burdens over a grazing season.Transmission models usually focus on the role of host immunity in regulating parasite dynamics. Our results illustrate that timing and magnitude of parasite outbreaks is driven by a combination of both grazing behaviour and host immunity, and the interactions between these regulatory processes. The structure of the model will facilitate the exploration of different control strategies; from chemotherapeutic applications and breeding for host resistance, to changes in grazing management. Manipulation of behavioural responses via grazing management could in many cases enhance existing intervention strategies. Furthermore, understanding the importance of both regulatory processes could aid the development of novel approaches for control. This integrated approach will also allow more informed predictions to be made about how outbreaks will be affected by future changes in the system.k = 1…D) move around a lattice of N patches (labelled i = 1…N), making grazing decisions based on the sward height ih at that patch and the level of faecal contamination if. The patch and animal state variables are outlined in Individual grazing is incorporated as in the model developed by Marion et al. i to patch j is modelled as v is the intrinsic movement rate and jh is the sward height at patch j, using the normalisation factor:Swain et al. F follows the power-law i and j. The normalisation prevents animals accumulating near the boundaries by avoiding lower movement rates at the boundary. If the search coefficient, α, is large, animals are restricted to nearest neighbour movement, while if α = 0 animals will search the whole lattice uniformly. In addition the total movement rates remain constant as α changes.The search kernel i given by:γ is the intrinsic growth rate of the sward and maxh is the maximum sward height attainable. The sward height of a given patch is reduced by B when an animal grazes at that location, while the stomach content ks of the corresponding animal is increased by one unit of size B. An individual takes a bite on its current patch at a rate:Sward growth is modelled logistically with the rate of increase at patch if represents the level of faecal contamination at patch i, µ is the level of faecal avoidance, k+Aka is the total number of parasites in host k, Λ is the anorexia coefficient, and ho is the minimum grazable portion in each patch. Thus the bite rate is monotonically decreasing with the amount of faecal contamination and level of avoidance, and non-zero values of g allow for the avoidance to be amplified with increased parasite burden. The model also includes a daily intake requirement kR for each animal  develop through multiple larval stages before reaching their infective third stage (L3) (termed iL here). After ingestion by an herbivorous host, they moult and develop onto fourth stage larvae (L4), before maturing into fecund adults (L5) i = 1…N) is assigned a number il of pre-infective larvae as well as a number iL of infective L3 stage larvae. Similarly, within each host (labelled k = 1…D) separate variables ka, kA and ek are introduced for the number of immature parasites, mature parasites and eggs respectively. Incorporating these developmental delays Grazing behaviour affects the timing of host contact with the parasites’ free living stages. To understand the interactions between grazing behaviours and parasite transmission, it is important to consider the multiple delays in the development of monoxenous nematodes. After release from the host the non-infective free living parasites  and infective larvae (iL) on its current patch, decrease by:When an animal takes a bite of size B, the number of immature parasites in host kk, a, increases by:θ is the probability of ingested L3 larvae establishing and becoming immature larvae in the host, and is a monotonic non-increasing function of r, representing the detrimental effect of resistance on parasite establishment.When an animal takes a bite of size k, here denoted kr, was a function only of the number of L3 ingested. In reality, helminth populations are regulated by multiple density-dependent mechanisms Roberts and Grenfell kr of host k increases by:ψ is a resistance gain coefficient. k,r also increases as a function of the current parasite burden, at rate (ka+kA)η, where η is a second resistance gain coefficient. Death of immature parasites in the host occurs at a rate ζak. Immature parasites develop into mature, egg producing adult parasites at a rate χak. Death of adults in host k occurs at rate τ(kr)kA, where τ(kr) >0 is a monotonic non-decreasing function which models the influence of acquired immunity on parasite mortality in the host. The loss of resistance in host k occurs at rate kσr.When infective larvae are ingested, the resistance ke represents the number of eggs in host k. Egg production from the dioecious parasites within host k occurs at a rate of:λ(kr), the rate of egg production of adult parasites, is a monotonic non increasing function of kr.k,s are greater than the faecal deposit size, 0s, and is otherwise zero. When a defecation event occurs, ek decreases by ii, l, increases by the same quantity. The non-infective il larvae develop into infective iL larvae on pasture at a rate of εil. The decay rate for faecal contamination at patch i is iφf, and the death rates of L and L3 larvae are iωl and iρL respectively. The stochastic model is simulated on the state-space variables , and a bite rate representing approximately 20,000 bites per day β = 0.1). When a bite event occurs, one unit of forage is removed. Each 0.5 m2 patch contains 50 bite areas of forage, as each cattle bite is approximately 0.01 m2γ = 0.00004 depf = 1.0, 0S = 2000.0), and the field is initialised with no faecal contamination . Faeces decays at a rate where 10% of the faecal deposit remains 3 months post deposition φ = 0.00001776). Faecal avoidance for animal k varies from no avoidance (kμ = 0) to effectively complete avoidance (kμ = 10) kμ = 5) results in a bite rate from freshly-contaminated patches <1% of the bite rate from non-contaminated patches Where parameter values are not stated for specific simulations, parameter values detailed in this section are used. The model was parameterised to simulate five hosts over one grazing season, in a set-stocked temperate grassland system, as described by Smith et al. ω = 0.0001) results in approximately 1% of larvae remaining after 1 month ρ = 0.000015).The parasite’s lifecycle is representative of a typical gastrointestinal helminth of grazing herbivores in a temperate climate, with the extensive study of GIN lifecycles allowing the model to be meaningfully parameterised p = 0.4). The proportion that establish is monotonically non-increasing with increased levels of acquired resistance. Increase in resistance is dependent upon ingestion of L3 (ψ = 0.25) and the size of the host’s parasite population (η = 0.025). In the absence of parasitism, immunity wanes over time (σ = 1.9×10−8) λ = 2). The life expectancy of the adult parasites in the host is approximately 5 weeks τ = 0.00002). With these parameter values, the model successfully reproduces the parasite dynamics empirically observed in livestock grazing systems Following ingestion of the infective stages approximately 40% of L3 larvae establish within a naïve host ka = 0, kA = 0, k = 1…D) on a pasture with 24000 infective L3, distributed over 20 randomly selected patches to reflect the aggregated distribution of larvae on pasture The starting condition of each simulation was representative of naïve hosts being released onto contaminated pasture. Each simulation was initialised with five uninfected hosts . To investigate the impact of aggregation of faeces and infective on-pasture larvae on parasite burden, simulations were run with varying sizes of faecal deposit (0s). Simulations were run with the number of faecal deposits ranging from 200 to 5 per day . Faecal avoidance was set at kμ = 3.Pre-infective larvae are released with host faeces, so aggregation of faeces results in uneven distributions of parasitic larvae on pasture. Cattle normally deposit faeces approximately 10–15 times per day ε = 0.00003 (development time of 3 weeks), ε = 0.00005 (development time of 2 weeks) and ε = 0.0001 (development time of 1 week), over differing faecal avoidance levels ranging from no avoidance (kμ = 0), to effectively complete avoidance (kμ = 10).There is substantial inter-species variation in observed larvae development rates ψ = 0.01, η = 0.0075), low resistance , medium resistance , and high resistance . For each resistance level, simulations were run over differing faecal avoidance levels ranging from no avoidance (kμ = 0), to complete avoidance (kμ = 10).A host’s ability to mount an effective immune response varies with factors such as the parasite species, host age, genotype, nutritional and hormonal status Λ = 0). However hosts can have phenotypic plasticity, with parasitised animals exhibiting heightened faecal avoidance compared to non-parasitised animals kμ = 3, Λ = 0.0006, such that min kμ = 3, max kμ = 8, and mean kμ = 4). When parasite burden was highest, these hosts exhibited realistic levels of reduction in intake of approximately 40% compared to control hosts (Λ = 0) with low faecal avoidance (kμ = 3) kμ = 3, Λ = 0), high faecal avoidance , and average faecal avoidance .To elucidate the fundamental dynamics of the system, initial runs were performed with no explicit interaction between the host’s parasitised state and its behavioural response ( peak parasite intensity, day of peak parasite intensity, and mean daily intake. Peak parasite burden was used as a measure of infection, as host morbidity and mortality are directly proportional to parasite intensity


As important members of nuclear receptor superfamily, Peroxisome proliferator-activated receptors (PPAR) play essential roles in regulating cellular differentiation, development, metabolism, and tumorigenesis of higher organisms. The PPAR receptors have 3 identified subtypes: PPARα, PPARβ and PPARγ, all of which have been treated as attractive targets for developing drugs to treat type 2 diabetes. Due to the undesirable side-effects, many PPAR agonists including PPARα/γ and PPARβ/γ dual agonists are stopped by US FDA in the clinical trials. An alternative strategy is to design novel pan-agonist that can simultaneously activate PPARα, PPARβ and PPARγ. Under such an idea, in the current study we adopted the core hopping algorithm and glide docking procedure to generate 7 novel compounds based on a typical PPAR pan-agonist LY465608. It was observed by the docking procedures and molecular dynamics simulations that the compounds generated by the core hopping and glide docking not only possessed the similar functions as the original LY465608 compound to activate PPARα, PPARβ and PPARγ receptors, but also had more favorable conformation for binding to the PPAR receptors. The additional absorption, distribution, metabolism and excretion (ADME) predictions showed that the 7 compounds  hold high potential to be novel lead compounds for the PPAR pan-agonist. Our findings can provide a new strategy or useful insights for designing the effective pan-agonists against the type 2 diabetes. Type 2 diabetes are characterized by hyperglycemia, insulin resistance and defects in insulin secretion, thus the patient with type 2 diabetes often suffer from symptoms of dyslipidemia, hypertension as well as obesity PPARα is expressed at high level in the brown adipose tissue, liver, kidney, heart, and skeletal muscle PPARβ is widely distributed in various body tissues with responsibility for controlling blood lipid concentration and insulin sensitivity As attractive targets for type 2 diabetes, many PPAR agonists, including PPARα/γ and PPARβ/γ dual agonists, have been designed and synthesized. Due to the undesirable side-effects, many PPAR agonists  are stopped by US FDA in the clinical trials The initial structures of PPARα, PPARβ and PPARγ receptors were obtained from the Protein Data Bank (PDB) with PDB entries of 1k7l.pdb Molecular docking technology has been increasingly used in the course of drug research and development www.schrodinger.com). The second step is to define the receptor grid file in the Receptor Preparation panel in Schrodinger. The third step is the core preparation with the Protocore Preparation module in Schrodinger to find the core attaching to the scaffold using the fragment database derived from ZINC database (http://zinc.docking.org). The last step is to align and dock the entire molecular structures built up by the core and scaffold into PPAR receptors. The cores are sorted and filtered by goodness of alignment and then redocked into the receptor after attaching the scaffold, followed by using the docking scores to sort the final molecules.The first step is to define some possible points at which the cores are attached to the scaffold. It is also the define combinations step from the Combinatorial Screening panel packaged in Schrodinger (The candidates obtained from the core hopping docking procedure were then subjected to a series of molecular dynamic simulations by the open software GROMACS 4.0 Linear Constraint Solver (LINCS) algorithm During the molecular dynamics simulations, all bonds in the simulation systems were constrained by the In the current study, QikProp was employed for predicting the absorption, distribution, metabolism and excretion (ADME) properties for all the candidates. QikProp is designed by Prof. William L. Jorgensen, and can predict physically significant descriptors  and pharmaceutically relevant properties for small drug-like molecules. This software also provides ranges for comparing a particular properties of molecules with those of 95% known drugs, and flags 30 types of reactive functional groups that may cause false positives in high-throughput screening assays.Experimental evidences showed that the biological functions of PPAR receptors is regulated by the precise shape of their ligand-binding domain induced by the binding of ligands including a number of coactivators and corepressor proteins. These ligands can significantly simulate or inhibit PPAR receptor functions. According to the X-ray crystallography studies, the ligand-binding domains of PPARα, PPARβ and PPARγ receptors are very similar with the RMS deviations between Cα atoms less than 1 Å. Besides, they also share some common features Figure 1Addition to the common features mentioned above, the ligand-binding domains for PPARα, PPARβ and PPARγ receptors also have their unique features. For instance, it is significantly narrower in the region adjacent to the AF2 helix in PPARβ, which is not suitable for the ligands containing larger polar heads. Compared with the PPARβ ligand-binding domain, the one of PPARα is comparatively more lipophilic, while the one of PPARγ is more hydrophilic. The largest variation among the three ligand-binding domains is found in the omega loop displaying a comparatively high RMS deviation and differing among a number of reported crystal structures.During the core hoping processes, LY465608 is selected as a guiding structure. This small molecule is firstly reported as a PPARα/γ dual agonist, latter proved to excite PPARβ as well. Owe to playing a positive role in keeping lipid and cholesterol homeostasis stability by reducing serum triglycerides and increasing HDL cholesterol, LY465608 has been treated as a typical PPAR pan-agonist to lower plasma glucose levels and improve insulin sensitivity. The structure of LY465608 can be divided into 3 major components Figure 2st core hoppling operation was aimed at the Core B , PPARβ (1gwx.pdb) and PPARγ receptors (1k74.pdb), respectively. The 20 derivative compounds were then ranked roughly according to their docking scores to PPARα, PPARβ and PPARγ receptors, respectively. The derivative compounds that employed stronger binding affinities than the original LY465608 with all the PPAR receptors were listed in Table S1). Of the top 7 derivative compounds, the Cpd#1 with Core A-Fragment B1-Fragment C1 has the strongest binding affinity with all the PPAR receptors, and hence it was singled out for further studies.The 1As shown in Addition to the conserved hydrogen bonding network mentioned above, Cpd#1 formed an additional hydrogen bond with Thr288 in PPARβ receptor, which could notably enhance the binding affinity compared to the guiding molecule LY465608. The hydrophobic tail of the Core C in both LY465608 and Cpd#1 were buried well in the hydrophobic pocket of the ligand-binding domains of PPARα, PPARβ and PPARγ receptors. However, due to the suitable size, Cpd#1 was more fitted to the hydrophobic arm II, resulting in the stronger binding affinities than LY465608 also see Table 1.Molecular dynamics can provide useful information for characterizing the internal motions of biomacromolecules with time To further study the conversed hydrogen bonding network mentioned above, 200 snapshots for the LY465608-bound and Cpd#1-bound states of PPARα, PPARβ and PPARγ receptors were retrieved from the last 1-ns segment on the molecular dynamics simulation trajectories with an interval of 5 ps, and statistical analyses were further performed on the conversed hydrogen bonding network  describes the druggable dispositions of the lead compounds in pharmacokinetics and pharmacology. In our study, some pharmaceutically relevant properties of the new designed agonist derivatives as well as the original LY465608 compound, such as the “molecular mass” (Mol_MW), “hydrogen bond donors” (DonorHB), “hydrogen bond acceptor” (AccptHB), “partition coefficient” (logP o/w), “van der Waals surface area of polar nitrogen and oxygen atoms” (PSA), and “aqueous solubility” (logS), were predicted by means of the QikProp module packaged in the Schrodinger 2009. The predicted ADME results were listed in According to the Lipinski’s Rule of Five, the orally active drugs should have no more than one violation of the following criteria: i) no more than 5 hydrogen bond donors (DonorHB ≤5); ii) no more than 10 hydrogen bond acceptors (AccptHB ≤10); iii) molecular mass less than 500 Daltons (Mol_MW ≤500); and iv) the octanol-water partition coefficient logP in −0.4 to 5.6 range (−0.4≥ logP o/w ≤5.6). All the criteria for the original LY465608 compound were within the acceptable ranges of the Lipinski’s Rule of Five, except the logP o/w value which was comparatively higher and had high-risk to induce unfavorable distributions of the compound on fat and body fluid. This also might be the reason why the original LY465608 compound shows comparatively high toxicity. However, after rational design with the core hopping approach, the ADME properties of the 7 candidates are all within the acceptable range for human beings, indicating that these derivatives found in the current study can be utilized as potential candidates for the purpose of developing novel drugs.In summary, we employed the core hopping approach to generate a series of novel compounds with an aim of finding new and powerful pan-agonists for PPARα, PPARβ and PPARγ receptors. After flexible docking procedures and molecular dynamics simulations, a set of 7 novel compounds were found using LY465608, a typical PPAR pan-agonist, as a guiding structure. Compared with the existing pan-agonist LY465608, the 7 candidates found in the core hopping processes not only had the similar function in activating PPARα, PPARβ and PPARγ receptors, but also assumed the conformation more favorable in binding to the PPAR receptors. It is anticipated that the 7 candidates, especially Cpd#1, may become potential lead compounds for designing novel pan-agonist against PPARα, PPARβ and PPARγ receptors with comparatively lower toxicities.Table S1The chemical structures of the top 7 hits in the core hopping and glide docking. For comparison, the typical PPAR pan-agonists bezafibrate, Ly465608 and GW677954 are also involved.(DOC)Click here for additional data file.


There has been a longstanding debate on whether amyloid plaques are pathogenic by causing physical damage to surrounding tissue or protective by sequestering more toxic soluble forms of amyloid β (Aβ) peptide. Numerous studies in mouse models have documented a complex relationship between soluble Aβ, deposited aggregates, and cognitive decline, but few experimental systems have been capable of dissecting how each form of the peptide contributes to the progressive memory deficits of Alzheimer’s disease. Here we use a controllable transgenic model expressing a mutant form of amyloid precursor protein (APP) to distinguish the impact of APP and soluble Aβ from that of deposited amyloid on cognitive function and synaptic structure.We created a transgenic model in which the tetracycline transactivator drives expression of APPswe/ind in neurons throughout the forebrain. After 6 months of transgene expression when amyloid burden reached approximately 10%, we placed half of the mice on doxycycline to suppress further production of transgenic APP and human Aβ. All animals were then tested for cognitive function using the Morris water maze, radial arm water maze, and fear conditioning. Once testing was complete, we harvested the mice to examine amyloid pathology, synapse density, oligomeric Aβ, and synaptic protein levels.Doxycycline treatment suppressed expression of transgenic APP by > 90% and diminished production of human Aβ by 70% while leaving pre-existing amyloid deposits intact. Remarkably, this treatment restored cognitive performance to the level of healthy controls in all of the behavioral tasks examined. Cognitive improvement coincided with reduced levels of synaptotoxic Aβ oligomers, greater synaptic density surrounding amyloid plaques, and increased expression of pre- and post-synaptic markers. To demonstrate that recovery was due to reduction of Aβ and not simply suppression of APP, we treated a second cohort of mice with the γ-secretase inhibitor LY411575 and observed similar although somewhat less complete recovery in both Morris water maze and synaptic markers. Finally, transgene suppression normalized activation of the actin-depolymerizing protein cofilin in a PAK-independent manner, suggesting that APP/oAβ may alter synaptic structure through the opposing Rho/ROCK pathway.These findings indicate that transient forms of APP and Aβ underlie much of the behavioral and synaptic recovery observed in this model. Our work further suggests that residual amyloid deposits need not be removed for successful intervention at this early stage of disease.


Plasmodium falciparum malaria in sub-Saharan Africa.In this study we aimed to assess site heterogeneity of early, intermediate, and late mortality prediction in children with severe Plasmodium falciparum malaria in six hospital research centers between December 2000 to May 2005 were analyzed. Demographic, clinical and laboratory data of children who died within 24 hours (early), between 24 and 47 hours (intermediate) and thereafter  were compared between groups and survivors.Medical records of 26,036 children admitted with severe P<0·001), ranging from 8h (3h–52h) in Lambaréné to 40h (10h–100h) in Kilifi. Fifty-eight percent of deaths occurred within 24 hours and intermediate and late mortality rate were 19% and 23%, respectively. Combining all sites, deep breathing, prostration and hypoglycemia were independent predictors for early, intermediate and late mortality (P<0·01). Site specific independent predictors for early death included prostration, coma and deep breathing at all sites (P<0·001). Site specific independent predictors for intermediate and late death largely varied between sites (P<0·001) and included between 1 and 7 different clinical and laboratory variables.Overall mortality was 4·3% . Median time to death varied across sites (Site heterogeneity for mortality prediction is evident in African children with severe malaria. Prediction for early mortality has the highest consistency between sites. Plasmodium falciparum malaria remains an important health problem affecting approximately 200 million patients a year._ENREF_1Despite decreasing transmission rates, Disease severity and morbidity strongly depend on patient-, disease-, and parasite-specific factors.In the present work we aim to explore site heterogeneity for mortality prediction in six sites in sub-Saharan Africa using multivariate models for early, intermediate and late mortality.P. falciparum malaria to six hospital-based research units in sub-Saharan Africa between December 2000 and May 2005.The Severe Malaria in African Children (SMAC) clinical research network is a cross-sectional observational database of patients hospitalized with malaria. The study used data from 26,296 consecutively hospitalized children, who presented with severe Data collection and quality control measures were processed at each site, and standard operating procedures were developed as previously described.We defined the time to death or discharge as the interval between the time of hospital presentation and the time of death or when the patient was discharged. We assigned all participants to one of four categories derived from time between admission and death: early (0–23 hours), intermediate (24–47 hours), late mortality (≥48 hours), and those discharged alive.To investigate potential differences on admission in demographic, clinical and laboratory manifestations of severe falciparum malaria in different survival group, variables were summarized as frequencies, means (standard deviation), medians (interquartile range) and compared using chi-square test, Anova, or non-parametric testing  as appropriate. Bonferroni’s test was performed for multiple comparisons of time and site. The chi-square test for trend was used to identify the linear trend between early, middle and late mortality groups.P<0·05 were considered significant. All reported p-values are two-tailed.Mortality prediction: in the first step, we performed separate stepwise backward multivariable logistic regression analysis to assess the effect of predefined variables on early, intermediate and late mortality. Two-way interaction terms between variables were tested, but none were significant. We did not include variables with more than 5% missing data points and therefore had to exclude plasma lactate from all regression models. Due to the small proportion of subjects dying in Lambaréné, we combined data from both Gabonese sites. The effect estimates are the odds ratios with their 95% confidence interval for each of early, middle and late mortality compared with those discharged alive. In the second step site specific model were analyzed using the same variables and outcome measures. To validate our results, we have estimated the power of each logistic regression by running in G*POWER 3.1.5 package , the post-hoc power calculation for beta-coefficents/odds ratios in logistic regression models for early, middle and late death by site with covariates. Statistical analysis was performed using Stata, version 12 . Information about a variable was “missing” if the case record did not mention the variable and was “unknown” if the case record mentioned that the variable was not tested for. Analyses resulting in values of P<0.001, Kruskal Wallis rank test).Of the 26,296 children with severe malaria in six SMAC centers  260 were excluded due to missing data, leaving 26,036 patients eligible for analysis. Demograhpics, clinical and admission laboratory findings were stratified by time to death and are illustrated in The overall median time to death was 19h (6–44h) and varied across sites, ranging from 8h (3–52h) in Lambaréné to 40h (10–104h) in Kilifi; (Libreville 10h (2–23h); Banjul 16h (6–32h); Kumasi 18h (7–36h); and Blantyre 20h (5–32h)). Time to death was significantly longer in Kilifi when compared to all other sites . .P<0·001). The early mortality was highest in Banjul  ; 58% (N = 658) of deaths occurred within 24h, 19% (N = 214) within 48h, and 23% (N = 257) after more than 47h (P<0·001) .P<0·001) except in Lambaréné and Kilifi . Site-specific analysis revealed a significant association between severe malnutrition and mortality over time in all site except in Lambaréné (P = 0·8) and Libreville (P = 0·09).P<0·01).Results of a multivariate logistic regression analysis are shown in P<0·001)  Table 2In this study we show that prediction of mortality in African children with severe malaria differs between sites. The most consistent predictive model included 3 admission variables, namely deep breathing, prostration and coma for death within 24 hours. Predictive models for intermediate and late mortality were highly variable between sites.Plasmodium falciparum malaria.Mortality was highest in the first 24 hours after admission, which is well described in Median time to death significantly differed from site to site: Site specific uncontrollable factors contributing to this finding may be the transmission intensities and seasonality at each site.P. falciparum related mortality. Cerebral malaria is still associated with a high mortality even when appropriate therapy and optimal care are provided.Multivariate analysis predicting early, intermediate and late mortality at all sites were prostration, deep breathing and hypoglycaemia. This finding underlines the importance of neurologic manifestations of Plasmodium falciparum malaria.Lactate concentrations is a known predictor for poor outcome in Malnutrition is also a risk factor for death in hospitalized African children and is considered to be the underlying cause of more than 50% of all childhood deaths in the world.We observed a large variability of predictors for intermediate and late mortality between sites. It has been reported, that various manifestations of severe malaria have different predictablity for mortality at different sites.The limitations of this study have been previously well described In conclusion, different features of severe malaria were strongly associated with time to death in the largest multicentre clinical trial in Africa. Patients with severe malaria who died earlier have more frequently the life threatening symptoms of severe malaria than those who died later. However, important site differences exist with regards to clinical and biological manifestations of malaria in spite of the quality control measures installed and standard operating procedures developed at each site. These findings reinforce the continued attention that needs to be devoted to the early identification of patients at risk for severe malaria, the application of timely and effective treatment strategies and reevaluation of clinical symptoms and signs during hospitalization.