Salmonella that sometimes progressed to problematic proportions, known as “sepsis”. Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-α ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies.We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by  Sepsis is initially activated by the presence and growth of pathogens in an organism. Under normal healthy circumstances, intruding pathogens are eliminated by the activation of immune cells, such as tissue macrophages and activated neutrophils, in the immune system , 2. If aSevere sepsis and septic shock during an infection are the major causes of death in intensive care settings . An averet al. . Th. Th42]. lmonella . To mimilmonella . In the IMMABM was developed as an agent-oriented computer program to describe agent rules and behaviors. Each agent type was defined as “breed” in NetLogo, and each “breed” in IMMABM had specific state variables. By assigning various values to the state variables, the agents were regulated to execute a series of functions based on various locations and environmental interfaces. Interactions between agents were highly stochastic, and we incorporated mathematical expressions such as logistic growth functions, mass-action kinetics, Michaelis-Menten kinetics, and decay functions to quantitatively measure complicated biological processes. Furthermore, the process of writing computer codes strictly followed conditional statement “if-then” rules. Those rules conformed to biological mechanisms of HIR.Salmonella, and degradation rate of associated mediators allowed us to advance the ABM application by mapping biological processes that occur during HIR to our IMMABM. By integrating experimental data and mathematical expressions derived from hypothesized kinetics, we attempted to quantitatively simulate dynamic patterns of HIR. In addition, a global variable defined as “Infection Time” in IMMABM reflected simulation execution time and mimicked kinetic associations between a series of responses. In our simulation, 1 tick (representing 1 simulation step in the simulation software) represented 1 hr in an actual biological process, and numeric counts of an agent were updated per tick to correspond to the biological response time in the experiments.The primary objective of our IMMABM was to incorporate available experimental data into the computational simulation. Data such as infiltration time of immune cells, replication rate of Salmonella infections and infectious disease processes motivated us to select a total of 23 essential cells and cytokines as agent types in this IMMABM. In this paper, we use italic format to highlight agent type for convenience. Each agent type, further defined as “breed”, could contain multiple entities. Among the 23 types of agent, we defined 20 primary agent types: Hepatocyte, Hepatocyte Debris, Kupffer Cell, Salmonella, Mast Cell, Resting Neutrophil, Activated Neutrophil, Resting Monocyte, MDMI (monocyte-derived type 1 macrophage), MDMII (monocyte-derived type 2 macrophage), TNF-α (tumor necrosis factor-α), HMGB-1 (high mobility group box-1), IL-10 (interleukin-10), CD4 T Cell, CD8 T Cell, B Cell, Antibody, CRP (C-reactive protein), NET (neutrophil extracellular traps), and Histamine. We also defined three auxiliary agent types: SEC , Signal, or Anti-Signal. The rule system for these agents was based on the literature. A sequence of interactions among primary agents and primary agent behaviors during interactions are introduced in Section 2.4.1.Incorporation of data from 210 publications and our experience with Salmonella, a “trigger” to begin HIR, was the first agent to move and interact with Kupffer Cells, thereby initializing HIR. The percentage of Salmonella killed by Kupffer Cells was set from 15% to 16% of the total Salmonella population per hour because 90% to 95% of Salmonella were phagocytosed (engulfed) by Kupffer Cells in 6 hrs [Salmonella that survived in Kupffer Cells turned Kupffer Cells into an “apoptotic” state and “proliferated” within Kupffer Cells [Salmonella that “proliferate” within one Kupffer Cell was limited to 50 [Salmonella were released to liver tissue after “apoptotic” Kupffer Cells “died” between 6 and 14 hrs [Salmonella were assigned to a state variable “SalmonellaNewlyReleasedFromKupfferCell” in order to express aborted interaction with Kupffer Cells and prepare for “proliferation” in surrounding Hepatocytes or SECs [Activated Neutrophils or MDMIs were recruited to the site of infection, Neutrophils or MDMIs “killed” Salmonella [Salmonella per hour, and every MDMI phagocytized approximately 1 to 7 Salmonella per hour [CRP released from Hepatocytes and Antibody released from B Cells also contributed to the “killing” of Salmonella [in 6 hrs . Salmoneer Cells , 47. “Died to 50 . The newd 14 hrs . These r or SECs , 48. Whelmonella , 49, 50.per hour . In addilmonella –56.Hepatocytes account for approximately 60% of the total number of cells in the liver [Hepatocytes were primary locations for Salmonella “proliferation”, and the Hepatocytes become “apoptotic” once they interacted with Salmonella or TNF-α [Hepatocytes released acute stress proteins such as CRP, or cytokines such as TNF-α, and HMGB-1 [Hepatocytes could undergo a natural aging process or interact with infiltrating Activated Neutrophils [Hepatocytes that interacted with Activated Neutrophils “died” immediately and released their interacted Salmonella to the liver tissue [Hepatocytes underwent natural aging and became Hepatocyte Debris after 2 or 3 hrs [Hepatocyte was also regenerated at a rate of 1.32×10−3 to 6.80×10−3 per hour to simulate proliferation of Hepatocyte in a mouse’s liver [he liver . In our or TNF-α , 45, 48.d HMGB-1 , 57, 58.trophils –61. “Apoor 3 hrs . In addi’s liver .Kupffer Cell, Mast Cell, Activated Neutrophil, MDMI, and MDMII. Kupffer Cells reside principally within the lumen of liver sinusoids, adherent to SECs that comprise blood vessel walls [Salmonella in the liver [Kupffer Cells that killed approximately 90% to 95% of the Salmonella population in 6 hrs; however, 5% to 10% of Kupffer Cells were killed by Salmonella during the same time period [Kupffer Cells released cytokines such as TNF-α which helped recruit other phagocytic cells such as Activated Neutrophils to the site of infection or incurs further damage to Hepatocytes [Kupffer Cells also released IL-10. IL-10 represents anti-inflammatory cytokines in this model and is capable of inhibiting the release of TNF-α. As typical phagocytic cells, Kupffer Cells “killed” various types of cell debris such as hepatocyte debris (to represent their scavenging or “clean up” function), Antibody-opsonized Salmonella, and CRP-opsonized cell debris [Kupffer Cells occurs at a rate of 4.20 ×10−3 to 3.20×10−2 per hour [Kupffer Cells came from MDMIs and MDMIIs at a rate of 6.30×10−3 to 7.90×10−3 per hour [Kupffer Cells, Activated neutrophils also “killed” Salmonella, Antibody-opsonized Salmonella, CRP-opsonized cell debris, and released cytokines such as TNF-α or IL-10 [Activated Neutrophils were recently recognized to release NETs to eliminate Salmonella [Activated Neutrophils underwent natural aging or were “killed” by Kupffer Cells [Activated neutrophils underwent apoptosis, indicated by a state variable labeled “apoptotic.” The “apoptotic” Activated Neutrophils were killed by MDMIs [MDMIs were activated from Monocytes between 6 hrs to 24 hrs post-infection [Monocytes was dependent on the existing number of Salmonella, TNF-α, HMGB-1, “apoptotic” Activated neutrophil, CD4+ T cell, and CD8+ T cell. The activation amount was calculated based on Michaelis-Menten kinetics, as discussed in Section 2.4.4. Upon activation, Monocyte became MDMI or MDMII [MDMI “killed” Salmonella and released TNF-α [MDMII “killed” “apoptotic” Activated Neutrophils and released HMGB-1 and IL-10 as mediators to resolve the inflammation [MDMI and MDMII helped activate T cell recruitment [MDMI and MDMII released IL-10 when they “killed” apoptotic CD4+ T Cell or CD8+ T Cell [We modeled five primary phagocytic cells in our IMMABM, including el walls . The firhe liver –66 were e period . Kupfferatocytes , 67. Kupl debris , 55. Theper hour . Repleniper hour . Similaror IL-10 , 70. Biolmonella , 72. Acter Cells . “Apoptoby MDMIs . MDMIs wnfection , 75. Theor MDMII . MDMI “ked TNF-α , while Mammation , 76. MDMruitment , and bot+ T Cell .CD4+ T Cell, CD8+ T Cell, and B Cell occupied spaces in the portal triad [CD4+ T Cell, CD8+ T Cell, or B Cell occurred when MDMI or MDMII were detected [CD4+ T Cell, CD8+ T Cell, or B Cell moved from the portal triad to the liver sinusoid [CD4+ T Cell released TNF-α or IL-10 when they interacted with phagocytic cells interacting with Salmonella, and CD 4+ T Cell improved the phagocytic rate of phagocytic cells [CD8+ T Cell “killed” phagocytic cells that interacted with Salmonella [CD4+ T Cell and CD8+ T Cell underwent natural apoptosis, and both “apoptotic” CD4+ T Cell and CD8+ T Cell were “killed” by MDMI or MDMII [B Cell released Antibody to form an Antibody-Salmonella complex, and the Antibody-Salmonella complex was killed by phagocytic cells, simulating opsonization [al triad , 79. Actdetected , at whicsinusoid . CD4+ T ic cells . CD8+ T lmonella , 56. CD4or MDMII . B Cell TNF-α, HMGB-1, and IL-10 are cytokines released from phagocytic cells. TNF-α was released from Kupffer Cell, Mast Cell, “apoptotic” Activated Neutrophil, MDMI, and Hepatocyte [TNF-α caused Hepatocyte to become “apoptotic” [HMGB-1 was released from MDMII and “apoptotic” Hepatocyte [IL-10 was released from Activated Neutrophil, MDMII, and CD4 T Cell [IL-10 prevented secretion of TNF-α, HMGB-1, and IL-10 from interacting with phagocytic cells or T cells [TNF-α, HMGB-1, and IL-10 “died” to reflect their clearance away from the simulation. An overview of agent behaviors is provided in patocyte , 81–84. optotic” . HMGB-1 patocyte –87, and 4 T Cell . IL-10 p T cells , 90–94. Resting Neutrophils or Resting Monocytes moving to SECs were driven by Signals released from cytokines or cells [Signals appeared on SECs, Resting Neutrophils or Resting Monocytes moved to SEC locations. Mass-action kinetics determined the number of moving Resting Neutrophils or Resting Monocytes, as described in Section 2.4.4. Biological interaction between two agents occurred in IMMABM simulation if two agents occupied the same patch.Agent movement in IMMABM was determined by agent behaviors described in or cells , 95–97. Salmonella that replicated within Kupffer Cells, MDMIs, SECs, and Hepatocytes [Salmonella randomly moved to the nearest Hepatocytes and damaged those Hepatocytes.atocytes –48, 73 wAntibody-Salmonella complex or CRP-cell complexes because the two components of the complex need to move simultaneously. For example, when an Antibody-Salmonella complex moved to one phagocytic cell, Antibody and Salmonella moved in the same direction for the same distance [Antibody-Salmonella complex’s killing process using the phagocytic cell occurred when the distance between the complex and the phagocytic cell was less than one patch-size.We used a “link” breed to model movements of the distance . The Antvivo is provided in Kupffer Cell had a state variable named “kupfferCellBindToIL10”. The value of the state variable was equal to 1 when Kupffer Cell interacted with IL-10, and individual Kupffer Cells that had the state variable “kupfferCellBindToIL10” equal to 1 did not release TNF-α. Salmonella that proliferated within Kupffer Cell had a state variable named “SalmonellaReplicateWithinKupfferCell” equal to 1; Salmonella that had “SalmonellaReplicateWithinKupfferCell” equal to 1 generated new agents until the state variable “SalmonellaReplicateWithinKupfferCell” was reset to 0. Kupffer Cell was assigned to a state variable named “kupfferCellKillBy Salmonella” equal to 1 when Kupffer Cells interacted with Salmonella that had the state variable “SalmonellaReplicateWithinKupfferCell” equal to 1. Kupffer Cells had the state variable “kupfferCellKillBy Salmonella” equal to 1 “die” after 6 simulation ticks, and the state variable “SalmonellaReplicateWithinKupfferCell” of interacted Salmonella was reset to 0. Resting neutrophil were activated in order to move to SECs in response to signaling by TNF-α, HMGB-1, or Salmonella signaling, consequently becoming Activated neutrophil. Activated neutrophil moved to the “apoptotic” Hepatocytes with a state variable labeled “hepatocyteUndergoApoptosis” equal to 1. “Apoptotic” Hepatocytes that interacted with Activated neutrophils “died” immediately due to the killing process of “apoptotic” Hepatocyte by Activated neutrophil [Each agent type had its own state variables in the IMMABM. By assigning various values to the state variables, the agents were regulated to execute a series of functions based on locations and environment interfaces. During a simulation, some state variable are fixed through the simulation, and others change as the simulation runs. The change in values of state variables is based on the change of agent behaviors during the simulation. A detailed description of agent behaviors in utrophil , 74. A cIn order to calibrate quantitative changes in agent number during HIR, we used a standard logistic function to measure cell population increases, Michaelis-Menten kinetics to calibrate cytokine release, mass-action kinetics to calibrate the activation process of circulating neutrophils and monocytes, and a decay function to measure the natural process of apoptosis by cells or catabolism of cytokines.Salmonella population to increase using a standard logistic growth function [For example, we calibrated the function  as folloP represents the Salmonella count, Kpg represents a constant growth rate for Salmonella, and P∞ represents maximum carrying capacity of the Salmonella. Growth rates and carrying capacities of Salmonella varied when Salmonella replicated within various cells. Corresponding experimental data is presented in In Eq , P repreSalmonella, and HMGB-1 [The activation process of circulating neutrophils was promoted by the pro-inflammatory mediator TNF-α, d HMGB-1 , 85, 95.d HMGB-1  to calibN represents Activated Neutrophil count and NR represents Resting Neutrophil count. T* denotes concentration of TNF-α, P* denotes concentration of Salmonella, and H* denotes concentration of HMGB-1.In Eq , N repreThe release of cytokines obeyed trafficking machinery, and cytokines were released via protein-protein interactions initiated by ligand binding to receptors , 101. ThC represents cytokine count and Kmax represents the maximum production rate of cytokines secretion by the cell. Cell denotes current numbers of the cell intending to release the cytokine and Cellhalf denotes cell numbers when half the maximum production rate of the cytokine was reached in the IMMABM.In Eq , C repreNatural cell apoptosis or cytokine catabolism occurred at every tick; thus, we assumed that the decrease in cell or cytokine counts followed a simple decay function as follows:In Eq , C repreSalmonella by phagocytic cells, activation rates of circulating neutrophils or monocytes, and apoptotic rate of cells or catabolism of cytokines from existing experimental studies. These data were incorporated into IMMABM as system parameters. We collected experimental data from studies that were most similar to our simulation setting. We also estimated parameters during simulation if data were not available from experimental studies. For example, we estimated that the CRP-opsonized debris moved to inflammatory cells  with an equal chance of 0.2. An overview of estimated experimental data is provided in In addition to mathematical models, we calibrated experimental data such as replication rates of cells, production rate of cytokines, killing rates of Salmonella infection studies that were published in papers available in the NCBI. When necessary, we used data from broader systems such as Gram-negative infections (i.e. E. coli) or even Gram-positive bacterial infections. Therefore, we are aware that some of these assumptions may not be correct.In order to smoothly translate estimated experimental data to agent-based modeling, we made corresponding assumptions in terms of data estimation. In general, we assume the change in rate is constant because we observed changes in data of interests in most of experimental studies following linear curves. Some experimental data is comprised of multiple linear segments, and therefore we calibrated rates for each linear segment to measure various rates for multiple responding time periods. These multiple rates are explained in −17 g IL-10 from experimental data [−17 g IL-10 in real experiments. Similarly, 1.25×10−11 g CRP could bind to one phagocytic cell based on our calibration [−11 g CRP in real experiments. Data showed that 2.82×10−17 g TNF-α damaged one hepatocyte per hour [−17 g TNF-α in order to transform experimental units into the agent count. Unfortunately, however, NET structure is fragile, thereby making it difficult to quantify NETs in experiments [Salmonella was also difficult to establish [NET formation and NE is an essential component of NET [Salmonella to substitute for the rate at which NETs kill Salmonella.In IMMABM, we used agent count to represent cell number with the awareness that cytokine production rate has a unique experimental unit compared to cell number. Thereby, cytokine production rate had to be transformed into an agent number in order to make the experimental data consistent in IMMABM. Therefore, we used one agent count to represent one real experimental unit. For example, we estimated that one phagocytic cell can bind 1.23×10tal data . Therefoibration . Thus, wper hour , so we ueriments . The ratstablish . Therefot of NET , we usedU tests were conducted to compare groups. All tests were performed using R 3.1.2. [P < 0.05 was considered statistically significant at the significance level α = 0.05.Results are expressed as mean ± standard error (SE). Data normality was checked using both histogram and quantile-quantile (Q-Q) plot. For normally distributed data, group comparisons were performed using one-way analysis of variance (ANOVA). For non-normally distributed data, Mann-Whitney R 3.1.2. . A P < 0Salmonella counts . The input data, converted as described to mathematical expressions and incorporated into the computer code, assembled cellular and molecular variables in order to generate a hypothetical immune response. Clinical and experimental data showed that the risk of patients dying from sepsis is significantly correlated to the initial dose of pathogen [silico simulations were carried out using Salmonella doses of 200 counts, 600 counts, 800 counts, and 1200 counts, and 100 replicated runs for each proposed Salmonella dose to explore the possible stochastic nature of the model. Results from these simulations were initially generated to identify dynamic patterns of indicators in HIR with various initial Salmonella doses, as shown in The IMMABM generated quantitative results by running simulations with various initial pathogen , 110. ThSalmonella “counts” . We observed that Salmonella counts, phagocytic cell (MDMI and MDMII) counts, and pro- and anti-inflammatory cytokine  counts increased as Salmonella infection (load) increased. Specifically, the number of phagocytic cells and the concentration of inflammatory cytokines significantly increased (based on one-way ANOVA tests with significance level α = 0.05 and P < 0.05) when Salmonella infection (load) increased from 800 counts to 1200 counts. A significant decrease (based on one-way ANOVA tests with significance level α = 0.05 and P < 0.05) in hepatocyte counts was also observed when Salmonella infection (load) increased from 800 counts to 1200 counts. The dose-response hypothesis test initially indicated that the HIR was correlated to Salmonella infection, which was consistent with experimental outcomes [One significant finding from the simulations was that outcomes of HIR were highly correlated to initial outcomes .We found four identifiable patterns in simulated HIR. Corresponding changes in the interface of NetLogo simulation were captured. The simulated results and changes in the interface of NetLogo are shown in Figs Salmonella was 200 counts, the number of Hepatocyte Debris and CRP increased for the first 18 hrs of simulation but then progressively decreased to 0, demonstrating no additional pathology at later stages of the simulation. The Salmonella counts, Activated Neutrophil, NET, TNF-α, HMGB-1, MDMI, and MDMII levels in the simulation sharply increased at the beginning of the infection but progressively decreased as the infection progressed. We inferred that this combination of variables is similar to a host curing an infection, so we referred to it as a healing process  hepatocytes as the simulation proceeded  [TNF-α and HMGB-1 pattern. We found that the peak level of TNF-α ranged from 1.40 × 10−3 to 2.64 × 10-3pg. Because we modeled liver dimensions based on the model size (401 × 401 2-D grid), we assumed that TNF-α secretion was proportional to the model size and that intensity of TNF-α secretion was proportional to the initial challenge of Salmonella dose. Under those two assumptions, this response paralleled TNF-α levels (160 to 210 pg) found in a mouse model responding to 107 CFU Escherichia coli (a medium dose) [HMGB-1 correlated with the peak level of an HMGB-1 response seen in experimental observations if model size was taken into account [HMGB-1 levels began later in our model compared to production kinetics observed in in vitro stimulation assays [HMGB-1 is proposed to have during sepsis [Experimental studies in mice have shown early expression of pro-inflammatory cytokines in response to nfection . A compafection) , 113. Ouum dose) , 82. Sim account . We obsen assays , Howeverg sepsis .Salmonella decrease within 6 hrs after initiation of HIR  of hepatocytes was detected after 7 days and continued for approximately 30 days [Detectable hepatocyte damage began at simulation step 10 (10 hrs post infection), and a significant increase in hepatocyte damage was observed beginning at stimulation step 15 (15 hrs post infection). Hepatocyte damage was persistently observed for 7 days. As the persistent infection proceeded, a large area of hepatocyte damage, which would translate to liver damage in an animal model, was observed . Our sim 30 days . These dSalmonella counts dropped within the first 24 hrs of HIR  within the first 48 hrs of infection during HIR characterized as hyperinflammatory (data not shown). These data suggest that a hyperinflammatory response could lead to a higher mortality rate compared to a persistent infection because of the acute and severely damaged hepatocytes observed.HIR could also result in a pattern we termed as a hyperinflammatory response Figs  and 9. Ds of HIR . Howevers of HIR  and infls of HIR  compareds of HIR . Interess of HIR  were mors of HIR  and 6. Tresponse , this seSalmonella counts. Under this condition, Salmonella and inflammatory cytokines continued to rise as the simulation proceeded. Therefore, we classified the combined pattern of increasing Salmonella counts and inflammatory cytokine counts  as “organ dysfunction”, as shown in Figs Salmonella, TNF-α and, HMGB-1 counts and continued high levels of CRP. The acute rise and a slow decrease in CRP levels observed in our model were consistent with CRP concentration patterns identified in patients with septic shock [The last pattern of HIR that we observed was characterized by progressively increasing ic shock . This adSalmonella, other phagocytic cells, and inflammatory cytokines quickly fell below threshold levels, was more likely to occur when the initial Salmonella load was low. We identified a persistent infection pattern if inflammatory responses were active . However, if the initial Salmonella load was high, a hyperinflammatory response or organ dysfunction was most likely to occur, leading to the death of infected individuals. In addition, when these simulated results were compared to experimental data, the simulations paralleled indicator patterns reported in actual mouse experiments [Salmonella loads were above 500 counts . For example, when the initial Salmonella load was 800 counts, all four dynamic patterns of HIR could emerge. Nevertheless, when initial Salmonella counts were below 500, the healing response was identified over 98% of the time. However, when the initial Salmonella count exceeded 1300 counts, only hypothetical death status (hyperinflammatory response or organ dysfunction) was identified from IMMABM simulations. In order to compare potential survival and mortality rates of HIR under various initial Salmonella challenge loads, we generated a probability histogram that ended with the healing response, persistent infection, hyperinflammatory response, or organ dysfunction of HIR against various Salmonella initial loads  in the lung [in vivo situation.As function . AlthougSalmonella killing rate by one neutrophil can range from 2.94 to 12.94 Salmonella/per neutrophil/hr according to a human model [Salmonella initial loads increased, the probability increased that HIR would end with hyperinflammatory response or organ dysfunction. In contrast, lower initial challenge doses were more likely to be identified as healing response or persistent infection.The experimental data and stochastic processes embedded in IMMABM were essential to a computational simulation because an HIR is an inherently stochastic process. Experimental data show that cellular and soluble mediator interactions and concentrations change and their levels are dependent on location and time. For example, the an model . The datHMGB-1 and CRP emerged as biomarkers for HIR because their expression patterns closely correlated to HIR outcomes. Similar to our simulated results, persistent elevation of HMGB-1 and CRP was also observed in experimental studies [As described in Section 3.3,  studies , 128.IL-10: TNF-α ratio is one recommended biomarker used to monitor the progression of sepsis [IL-10: TNF-α ratio for a healing response, a hyperinflammatory response, and organ dysfunction during infection in 10 simulation runs. Results in IL-10: TNF-α ratios in both the hyperinflammatory and organ dysfunction were significantly lower compared to the healing response . Therefore, the IL-10: TNF-α ratio in the IMMABM accurately captured the elevated IL-10: TNF-α ratio associated with patients’ healing process [In clinical practice, the f sepsis , 130. Th process .CD4+ T cell: CD8+ T cell are relatively lower in patients with sepsis, compared to non-sepsis patients [CD4+ T cell: CD8+ T cell ratio when the HIR progressed to hyperinflammatory (P = 0.0083) or organ dysfunction responses (P = 0.0041) after 15 hours of infection. Therefore, this basic clinical measure of T cell response [The ratios of patients , 132. Thresponse , 132 alsMDMII: MDMI ratio was less significantly correlated to the outcomes of HIR compared to the IL-10: TNF-α ratio and the CD4+ T cell: CD8+ T cell ratio. During the healing response, the MDMII: MDMI ratio was not significantly higher (P = 0.2623) than the ratio during hyperinflammatory response but it was significantly elevated (P = 0.0019) compared to the ratio in organ dysfunction, as shown in MDMI polarization is common in bacterial infections [in vivo ambiguity. Alternatively, MDMII: MDMI ratio may not be appropriate in the liver compartment. Refinement of the model will be necessary to help resolve this. In spite of this, the IMMABM in its current format, has identified some biomarkers that reflect the in vivo situation , an anti-TNF-α agent (i.e. an antibody therapy), and a combination of anti-HMGB-1 agent and anti-TNF-α agent. We incorporated these treatments into the IMMABM, and compared the effects of the three hypothetical treatments to the outcomes of HIR. Simulated data showed that the treatment effectiveness was highly correlated with treatment start time during the simulation . SpecifiSalmonella. In contrast, administration of anti-TNF-α and/or anti-HMGB-1 at a later stage could result in an overwhelming hyperinflammatory response because TNF-α and HMGB-1 levels remained persistently elevated  at selected time points could improve the survival rates for septic individuals. Moreover, these data suggest additional experimental directions for the development of effective treatment bundles in experimental animals and/or in preclinical trials.Salmonella. The IMMABM described interactions between selected agents as a representation of a HIR during Salmonella infection and required the understanding of key cellular and molecular processes of HIR at the tissue level. Most importantly, the IMMABM was validated through a series of comparisons between simulated results and experimental studies.This paper describes an IMMABM developed to simulate HIR in a mouse infected with Salmonella counts. When the initial Salmonella counts were below 900, hepatic infection had 97% probability to develop into a healing response during 100 simulation runs  were identified during the IMMABM simulation. One significant finding from the simulations was that the outcomes of a HIR were highly correlated to the initial ion runs . When thncertain . As the in vivo [+ and CD8+ T cells, as well as B cells, into our simulation. We found that incorporation of T cells and other acquired immune components could induce changes to the course of the infection. Indeed, in immunocompetent mice, the hyperinflammatory response that we identified in the simulations paralleled observations made during mouse sepsis [Salmonella we calibrated [This IMMABM began to capture the essence of adaptive immunity during HIR. T cell activation occurs within 24 hrs of HIR in vivo . Therefoe sepsis . In addilibrated –141.Salmonella. Furthermore, we calibrated the probability of HIR ending in each possible outcome under a range of initial Salmonella loads  with the same initial loads of Salmonella. These observations could explain the reason why effectiveness of therapeutic intervention is different from patient to patient.During dose response simulations, we observed HIR is correlated to initial loads of ads Figs  and 13. P = 0.0061 and P = 0.0152, respectively, using the Mann-Whitney U tests, as shown in HMGB-1. This approach could be more accurate to predict the progression of HIR.Our results suggest that levels of TNF-α, HMGB-1, CRP, and IL-10: TNF-α ratios, and CD4+ T cell: CD8+ T cell ratios could be recognized as biomarkers for HIR because these indicators and/or ratios have distinct patterns between a healthy state  and hypothetical death state (i.e. hyperinflammatory response or organ dysfunction). Specifically, our simulation results showed that averaged IL-10: TNF-α ratios were significantly elevated in the healing response from 8 to 14 hours compared to the ratios in the hyperinflammatory response and during organ dysfunction  [TNF-α would induce hepatocyte apoptosis if TNF-α were bound to hepatocytes.We modeled that atocytes . HoweverD (ActD) . BecauseSalmonella that bind to mast cells eventually die because of the substances secreted by mast cells. Therefore, in order to simplify our ABM, we considered only some main functions of mast cells during inflammation. For many years, mast cells were believed to phagocytize Salmonella [Salmonella, making them unable to phagocytize Salmonella. Therefore, we did not model that mast cells phagocytize Salmonella. Instead, we modeled that Salmonella binds to mast cells which initiates the release of TNF-α from the engaged mast cells.Mast cells release many biologically active molecules and chemical substances, such as protease and IL-6, which decrease or increase survival rates of septic patients –153. Sallmonella . Howeverlmonella  that masIL-10 under various conditions [IL-10 production. Because IL-10 levels released from T cells varies due to the type or concentration of stimuli, we modeled that CD4+ T cells produce IL-10 and we estimated the average release rate of IL-10. We did not differentiate helper T cells to specific types (e.g. Th2 or Treg) identified in biological process.T cell subpopulations have been reported to express nditions , making H cells define the isotype of the antibody [Salmonella are phagocytized better by neutrophils and macrophages compared to Salmonella alone [Plasma cells secrete antibody , but we antibody . Howeverantibody , 158. Wela alone .IL-1, IL-12, and IL-8. Also, biological immune responses to infection are recognized as a series of complex processes including intracellular signal transductions (including activation of gene transcription) and intercellular interactions between cells. These biological processes can be developed over time and will evolved as our understanding of these processes becomes more sophisticated [We did not model natural killer cells in our ABM and we ignored effects of other pro-inflammatory cytokines such as sticated . TherefoOne final important consideration is that an ABM requires a high level of computational effort in order to simulate the detailed interactions between classes of agents in the HIR. This is particularly true because the ABM is designed to describe the aggregated level of components by simulating individual agent behavior and interactions. These processes are occurring in parallel and require extensive computational effort and high computational efficiency . An averLimitations of current ABMs provide opportunities for future enhancements. A major step forward will include the addition of one or more of the sophisticated cellular and molecular pathways discussed in Section 4.The activation of the coagulation cascade is characteristically seen in patients with sepsis . Activatin silico. Initial silico simulation of IMMABM allowed us to recognize that a combination of anti-TNF-α and anti-HMGB-1 agents could significantly improve survival rates in HIR. Furthermore, we also observed that the time drugs were administered also impacts HIR outcomes. This not only provides evidence that the core IMMABM is sound, it also provides hope that it can be developed into an effective tool to assist in physicians in their clinical decision-making process.Mediator-directed treatments could be incorporated into this IMMABM in order to implement pre-clinical treatment tests Current ABMs also require computational resources. For the current 401 × 401 2D grid simulation size, the average simulation implementation time ranged from 18 mins to 50 hrs per replication. Computational time exponentially increased as the number of interactions among agents increased because of the numerous repetitive interactions. Therefore, another future direction of ABM research could be to reduce this computational hurdle by designing new and efficient computational algorithms.S1 FigMean values of IL-10: TNF-α ratios were measured at each simulation time point (replications = 10).(TIF)Click here for additional data file.S2 FigSalmonella initial loads range from 200 to 3200 counts.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.


Klebsiella pneumonia is a well-known human pathogen, and recently, a distinct invasive syndrome caused by K. pneumoniae serotypes K1 and K2 has been recognized in Southeast Asia. This syndrome is characterized by primary liver abscess and extrahepatic complications resulting from bacteremic dissemination. We report the first adult case of primary liver abscess caused by the definite K2 serotyped pathogen, with endogenous endophthalmitis in Japan.K. pneumonia was highly suspected and immediately administered broad-spectrum antibiotics for severe sepsis. Concurrently, endogenous endophthalmitis was diagnosed, and we performed vitrectomy on the day of admission. The blood culture showed K. pneumoniae infection. Percutaneous drainage of the liver abscess was also performed. Although she was discharged in a good general condition on day 22, she had complete ablepsia of the right eye. The K2A gene was detected by polymerase chain reaction (PCR), which is consistent with the K2 serotype. PCR was also positive for the virulence-associated gene rmpA. Final diagnosis was invasive liver abscess syndrome caused by K2 serotype K. pneumonia.A 64-year-old woman was admitted to a nearby hospital for a high fever and diarrhea. She had visual loss of her right eye, renal dysfunction, and thrombocytopenia within 24 h from admission. She was transferred to our institution. On admission, she had no alteration of mental status and normal vital signs; however, she had almost complete ablepsia of the right eye. Laboratory data showed severe inflammation, liver dysfunction, thrombocytopenia, an increased serum creatinine level, and coagulopathy. Computed tomography showed a low density area in the right lobe of the liver. Invasive liver abscess syndrome probably caused by K. pneumoniae with a hypermucoviscous phenotype is infrequently reported outside Southeast Asia, physicians should recognize this syndrome, and appropriate diagnosis and treatment is essential for saving patients’ lives and preserving organ function, especially for visual acuity.Although the primary liver abscess caused by  Klebsiella pneumoniae is a well-known human pathogen, and recently, a distinct invasive syndrome caused by K. pneumoniae serotypes K1 and K2 has been recognized in Southeast Asia, which is becoming an emerging disease worldwide [K. pneumoniae strains include a hypermucoviscous phenotype associated with serotypes K1 and K2, and the regulator of the mucoid phenotype A gene (rmpA) [K. pneumoniae strains expressing the capsular type K1 or K2 antigen have been reported to be especially virulent [The invasive nature of some virulent . These svirulent .K. pneumoniae with definite serotyping of K1 [This invasive syndrome has been reported in Southeast Asian countries . Howeverng of K1 , 5 and ong of K1  have beeK. pneumoniae with definite K2 serotyping, complicated with endogenous endophthalmitis resulting in complete ablepsia in a healthy woman in Japan.Herein, we present the first adult case with invasive liver abscess syndrome and severe sepsis caused by K. pneumoniae, and the antibiotic therapy was changed to ceftriaxone (2 g/day) on day 4 because all of the cephalosporin had high susceptibility  and K2A (serotype K2) genes was performed by using the magA-specific primers  and k2A-specific primers  as previously described[rmpA was also screened using PCR by using the rmpA-specific primers  as previously described [K2A gene, which is consistent with the K2 serotype, was detected by PCR. PCR was also positive for the virulence-associated gene rmpA. To assess for the presence of hypermucoviscosity, a string test was performed on the organism grown in 5 % sheep blood agar. The formation of a mucous string of >5 mm in length after touching a colony with a loop was considered positive [K. pneumoniae had a positive string test consistent with a hypermucoviscous phenotype , and thrombocytopenia  within 48 h from initial presentation. Therefore, she was transferred to our institution for treatment of severe infectious disease. On admission, she was alert and had no alteration of mental status, no hypoxia on room air, and normal vital signs . However, she had almost complete ablepsia of the right eye. Laboratory data showed severe inflammation , liver dysfunction , thrombocytopenia , an increased serum creatinine level (1.35 mg/dL), and coagulopathy Table . Broad-sty Table . The culK. pneumoniae extending to complete ablepsia despite improvement of the pathophysiology of severe sepsis. One systematic review reported K. pneumoniae had been the most common causative organism (27 %) in endogenous bacterial endophthalmitis. Following other organisms were Staphylococcus aureus (10 %), Pseudomonas aeruginosa (6 %), Group B streptococci (6 %), and Neisseria meningitidis (5 %) [We present the case of invasive liver abscess syndrome with endogenous endophthalmitis caused by the K2 serotype of s aureus  %, PseudK. pneumoniae is the first adult case in Japan. This invasive syndrome caused by K. pneumoniae serotypes K1 or K2 has been reported mainly in Southeast Asian countries, especially in Taiwan. We found around 50 cases with liver abscess caused by K. pneumoniae serotype K2 all over the world [Klebsiella pneumoniae,” “liver abscess,” “K1” or “K2,” except minutes and selected articles about this invasive syndrome published by Japanese authors.This case of a primary liver abscess caused by the definite K2 serotyping of he world , 12. Howhe world –6, when K. pneumoniae with endogenous endophthalmitis have been reported in Japan ; we conducted a search of the medical literature published using the Igaku Chuo Zasshi database and “liver abscess,” “endophthalmitis,” and “Klebsiella pneumoniae” as search terms. In addition, we could find two more Japanese literatures related to invasive liver abscess syndrome when we searched Igaku Chuo Zasshi database by using following keywords: “Klebsiella pneumoniae,” “liver abscess,” and “rmpA” [K. pneumoniae may not be rare in Japan.Almost 30 cases of primary liver abscess caused by d “rmpA” , 14. ThermpA was positive in our case. rmpA is not an independent factor contributing to a liver abscess, but it aids in capsule synthesis. One report showed that all K. pneumoniae strains that cause liver abscesses and abscesses at other sites are rmpA-positive. rmpA has been confirmed as a gene that regulates capsular polysaccharide synthesis [rmpA was probably associated with liver abscess formation.The virulence-associated gene ynthesis . Thus, iK. pneumoniae with a hypermucoviscous phenotype is infrequently reported outside Southeast Asia, physicians should recognize this syndrome, and appropriate diagnosis and treatment is essential for both saving patients’ lives and preserving organ function, especially for visual acuity.Although a primary liver abscess caused by Written informed consent was obtained from the patient for publication of this case report and any accompanying images. A copy of the written consent form is available for review by the Editor-in-Chief of this journal.K. pneumonia, Klebsiella pneumonia; PCR, polymerase chain reaction; rmpA, mucoid phenotype A gene


Currently, many surgeons place a prophylactic drain in the abdominal or pelvic cavity after colorectal anastomosis as a conventional treatment. However, some trials have demonstrated that this procedure may not be beneficial to the patients.To determine whether prophylactic placement of a drain in colorectal anastomosis can reduce postoperative complications.We systematically searched all the electronic databases for randomized controlled trials (RCTs) that compared routine use of drainage to non-drainage regimes after colorectal anastomosis, using the terms “colorectal” or “colon/colonic” or “rectum/rectal” and “anastomo*” and “drain or drainage.” Reference lists of relevant articles, conference proceedings, and ongoing trial databases were also screened. Primary outcome measures were clinical and radiological anastomotic leakage. Secondary outcome measures included mortality, wound infection, re-operation, and respiratory complications. We assessed the eligible studies for risk of bias using the Cochrane Risk of Bias Tool. Two authors independently extracted data.P = 0.47), (2) clinical anastomotic leakage , (3) radiologic anastomotic leakage , (4) mortality , (5) wound infection , (6) re-operation , and (7) respiratory complications .Eleven RCTs were included . Meta-analysis showed that there was no statistically significant differences between the drain group and the no drain group in (1) overall anastomotic leakage (relative risk (RR) = 1.14, 95 % confidence interval (CI) 0.80–1.62, Routine use of prophylactic drainage in colorectal anastomosis does not benefit in decreasing postoperative complications.The online version of this article (doi:10.1007/s00384-016-2509-6) contains supplementary material, which is available to authorized users. Currently, many surgeons routinely place a drain after the completion of colorectal anastomosis in case of postoperative complications, such as anastomotic leakage and wound infection. However, prophylactic drainage has remained controversial since it was firstly introduced by Theodore Billroth in 1877 . In addiTo better provide practice guideline for surgeons, we performed this meta-analysis to determine whether the prophylactic placement of a drain after colorectal anastomosis could reduce postoperative complications.Our study was carried out according to the recommendations of the PRISMA statement .A systematic literature search was performed up to June 24, 2015 using the terms “colorectal” or “colon/colonic” or “rectum/rectal” and “anastomo*” and “drain or drainage” in the following databases: MEDLINE, EMBASE, the Cochrane Library, the Controlled Clinical Trials Database, China National Knowledge Infrastructure (CNKI), and Wanfang Standards Database (WFSD). The reference lists of the identified relevant articles, conference proceedings, and ongoing trial databases were further screened for potentially relevant studies.We excluded observational studies, quasi-randomized trials, crossover trials, and cluster-randomized trials. We did not exclude any study based on language of publication or publication status.Titles and abstracts of all the identified articles were screened, and the trials were included according to the following criteria: (a) prospective randomized controlled trials (RCTs) that compared the routine use of prophylactic drainage of colonic and/or rectal anastomoses to no drainage; (b) patients with colonic or rectal tumor, diverticular disease, volvulus, and inflammatory disease located anywhere along the colon and the rectum that need to be treated with surgical re-section and anastomosis; and (c) outcomes included anastomotic leakage , mortality (patients were followed at least 30 days), wound infection , re-operation, and respiratory complications . Studies were excluded if they were retrospective and had no control arm or data regarding the efficacy or complications.Two investigators (Zhang HY and Ye YW) independently extracted the following data from all the included trials: patient characteristics, study design, patient inclusion and exclusion criteria, preoperative preparation, procedure process, and incidence of postoperative complications. Details of randomization , number of patients allocated to each group, type of drainage, site of anastomosis , duration of drainage, and number of patients that lost follow-up were recorded. The methodological quality of each trial was assessed by the same reviewers. If there were any discrepancies, a third investigator (Xie J) was consulted and consensus was reached by discussion. The quality of each study was assessed using the Cochrane Collaboration’s tool for assessing the risk of bias, a value of “low risk,” “high risk,” or “unclear” was assigned to the seven domains: (a) random sequence generation, (b) allocation concealment, (c) blinding of participants and personnel, (d) blinding of outcome assessment, (e) incomplete outcome data, (f) selective reporting, and (g) other bias .We included only parallel group trials. If a study contained more than two groups, we fused two groups (by using the appropriate formula for adding the standard deviations when required) when we thought that they were equivalent according to the criteria of our protocol or separated them and split the control in half.We contacted the authors for apparent missing data. We did not use imputed results. Data were entered as intention-to-treat (ITT) data as much as is feasible. If not, the study was quoted as at high risk of bias for selective reporting and then the data were entered on a per protocol basis.2 test and the Ι2 test. Statistically significant heterogeneity was considered to be present when P was <0.10 and the Ι2 value was >50 % [P > 0.10 and Ι2 < 50 %). If heterogeneity existed, the random-effect model was applied [Statistical analyses were performed with the recommendations of the Cochrane Collaboration Guidelines . The metas >50 % . The fix applied . Funnel Sensitivity analyses were performed with high quality of trials. Subgroup analyses were performed by stratifying the RCTs based on the site of anastomosis , the type of drainage (active drain with suction and passive drain without suction), and the race (Asian and European).In total, 814 potential relevant publications were identified; 18 trials were suitable for systematic review. We excluded seven retrospective trials with insufficient data. Eleven trials with 1803 patients met the inclusion criteria and underwent further analysis  [Ι2 = 0 %). Through stratifying by sites of anastomosis, we found no significant difference between the subgroup of intraperitoneal anastomosis  [n = 291, RR = 0.99, 95 % CI 0.54–1.83, P = 0.98; Fig. n = 798, RR = 1.13, 95 % CI 0.74–1.71, P = 0.57) [n = 688, RR = 1.35, 95 % CI 0.67–2.74, P = 0.40; Fig. n = 369) [n = 1434) [P = 0.82) and 1.18 , respectively, indicating no significant difference.All eleven trials reported this outcome. There was no statistical significant difference in the occurrence of overall anastomotic leakage between the drain group and the no drain group  –25. Ther = 0.76) –22 and e = 0.57) , 22–24 an = 369) , 16, 25  = 1434) –24. The n = 1,493, RR = 1.39, 95 % CI 0.80–2.39, P = 0.24). We used a fixed-effect model because no heterogeneity existed . Heterogeneity was not found , the type of drainage , and the race . In three subgroup analyses, no statistical significance was found both in the primary and the secondary outcomes between the drain group and the no drain group  and passive drain (drain without suction) subgroups showed no significant difference in anastomotic leakage rates and other complications between the drain group and the no drain group according to our meta-analysis. In addition, suction-irrigation drainage is an independent risk factor of anastomotic leakage after rectal anastomosis while the other types of drainage  are not associated with this complication . AnastomIn the drain group of all the included trials, drainage time is less than 8 days. Only one of the included trials compared 3- and 7-day placement time of drainage with no drain, and no significant difference was found in the three groups in the incidence of complications and the length of hospital stay . A studyOur meta-analysis has several strengths. We did a comprehensive search of the topic and strict quality assessment of the trial methodology according to the recommendations of the Cochrane Collaboration. The participants included came from six countries, and the number was comparatively large. We conducted sensitivity analyses and three subgroup analyses including the site of anastomosis , the type of drainage (active and passive), and the race (Asian and European), which helped to address the potential issue of clinical heterogeneities as far as possible. All of the included trials were perspective and randomized, which could make the results convincing and robust.Our meta-analysis has some limitations. The proportion of disease category included was not the same. The drainage regimens and materials between trials may affect the outcomes. The effect of surgeons’ experience and surgical methods on the procedure outcomes is also a concern. Large randomized controlled trials comparing drainage to non-drainage in colorectal anastomosis is necessary in the future.Routine use of prophylactic drainage in colorectal anastomosis shows no benefit in reducing postoperative complications.Supplementary Fig. 1a overall anastomotic leakage, b clinical anastomotic leakage, c radiologic anastomotic leakage, d mortality, e wound infection, f re-operation, and g respiratory complications. (GIF 73 kb)Outcomes of sensitivity analyses. Forest plots of the relative risk (RR) for High-resolution image (TIF 1.99 mb)Supplementary Fig. 2a overall anastomotic leakage, b clinical anastomotic leakage, c radiologic anastomotic leakage, d mortality, e wound infection, f re-operation, and g respiratory complications. (GIF 144 kb)Outcomes of site of anastomosis subgroup analysis. Forest plots of the relative risk (RR) for High-resolution image (TIF 3.51 mb)Supplementary Fig. 3a overall anastomotic leakage, b clinical anastomotic leakage, c radiologic anastomotic leakage, d mortality, e wound infection, f re-operation, and g respiratory complications. (GIF 141 kb)Outcomes of type of drainage subgroup analysis. Forest plots of the relative risk (RR) for High-resolution image (TIF 3.74 mb)Supplementary Fig. 4a overall anastomotic leakage, b clinical anastomotic leakage, c radiologic anastomotic leakage, d mortality, e wound infection, f re-operation, and g respiratory complications. (GIF 120 kb)Outcomes of race subgroup analysis. Forest plots of the relative risk (RR) for High-resolution image (TIF 2.39 mb)Below is the link to the electronic supplementary material.


Ixeridium calcicola (Compositae) endemic to middle altitude  limestone mountains of eastcentral Taiwan is described based on morphological and chromosome cytological observations and molecular phylogenetic analyses. Ixeridium calcicola resembles Ixeridium transnokoense, endemic to upper montane and alpine ranges  of Taiwan, in the dwarf habit, but differs in the oblong to lanceolate leaf blades (vs. linear to linear-lanceolate), the presence of mucronulate teeth on the leaf margin and petiole (vs. smooth to very sparse), the dark purple lower leaf surface (vs. greenish), the capitulum with 10 to 12 florets (vs. 5 to 7) and 8 to 10 inner phyllaries . The basic chromosome number in Ixeridium was known as X = 7. However, the new species has a basic chromosome number of X = 8, as recorded also in the closely related Ixeris. Molecular phylogenetic analyses with the expanded sampling of Ixeridium and Ixeris including both type species supported the monophyly of each of the genera and the placement of the new species in Ixeridium. The result of the phylogenetic analyses and detailed observation of the chromosome morphology revealed that X = 8 in Ixeridium calcicola is derived from centric fission in an ancestral karyomorphotype with X = 7 in Ixeridium. Ixeridium calcicola and Ixeridium transnokoense formed a Taiwan endemic lineage and their estimated divergence time was in the middle Pleistocene. Their common ancestral lineage may have experienced altitudinal distribution shifts in response to glacial-interglacial temperature fluctuation, and a lineage which had not retreated to alpine ranges in an interglacial period likely survived in a limestone refugium, where ordinary plant species did not grow, leading to allopatric speciation.A new species  Limestone environments harbor plant species adapted to highly alkaline and thin soils and desiccation on porous limestone bedrock Ixeridium (A.Gray) Tzvelev  was discovered. Ixeridium comprises about 15 species predominantly in East and Southeast Asia Ixeridium laevigatum (Blume) Pak & Kawano and Ixeridium transnokoense (Sasaki) Pak & Kawano Ixeridium transnokoense, a plant of 10–20 cm tall endemic to the upper montane and alpine areas  of Taiwan Island occurring on grassy slopes Ixeridium laevigatum grows up to 90 cm tall and has the widest distribution among the congeners, ranging from East and Southeast Asia to New Guinea. It occurs from sea level to about 2,300 m asl but predominantly in lowlands and grows in various environments such as forest margins, grassy areas, riverbanks, cliffs, roadsides, and on gravelly limestone Ixeridium but diagnostic for an allied genus Ixeris (Cass.) Cass. of the same subtribe Crepidinae. Ixeris comprises about eight species in East and South Asia Ixeridium and Ixeris are separated based on the following morphological  and karyological features: number of florets per capitulum , achene morphology , pappus color , and basic chromosome number  Ixeridium species with a white pappus IxerisTaroko National Park in eastcentral Taiwan  containsIxeridium and Ixeris with the expanded sampling including the type species of the two genera. We discussed the phylogenetic placement and taxonomic treatment of the new species, the evolution of the unusual chromosome number, and the origin of the new species.The present study conducted detailed morphological and chromosome cytological observations and constructed a dated molecular phylogeny of Sampling of the new species in Taroko National Park was conducted with the collect permits issued by the Headquarters of the national park.The electronic version of this article in Portable Document Format (PDF) in a work with an ISSN or ISBN will represent a published work according to the International Code of Nomenclature for algae, fungi, and plants, and hence the new name contained in the electronic publication of a PLOS ONE article is effectively published under that Code from the electronic edition alone, so there is no longer any need to provide printed copies.http://ipni.org/. The online version of this work is archived and available from the following digital repositories: PubMed Central, LOCKSS.In addition, the new name contained in this work has been submitted to IPNI, from where the name will be made available to the Global Names Index. The IPNI LSIDs can be resolved and the associated information viewed through any standard web browser by appending the LSID contained in this publication to the prefix Shih-Wen Chung 11141, 11693, TAIF and HAST). In addition, by checking herbarium specimens labelled as Ixeridium transnokoense in HAST, KYO, TAI, TAIF, TAIM, and TNM, we found a number of specimens representing the new species and used them. Specimens of genuine Ixeridium transnokoense in these herbaria , were used for morphological comparison with the new species.Living materials of the new species were used for morphological observations  (Ixeridium parvum (Kitam.) Pak & Kawano in Yakushima Island of Japan Ixeridium yunnanense C.Shih in Yunnan of China Ixeris longirostra Nakai in Ogasawara Islands of Japan Ixeridium aculeolatum C.Shih and Ixeridium sagittarioides (C.B.Clarke) Pak & Kawano, which are considered to be misplaced in Ixeridium and are probably not members of Crepidinae Ixeridium dentatum (Thunb. ex Thunb.) Tzvelev and Ixeris polycephala Cass. Five of the six subspecies of Ixeridium dentatumCrepidiastrum lanceolatum (Houtt.) Nakai, Paraixeris denticulata (Houtt.) Nakai, and Youngia japonica (L.) DC. were used as outgroups as these genera formed a sister clade of Ixeridium–Ixeris in a preceding study Ixeridium transnokoense, and Ixeridium laevigatum, four, nine, and seven samples, respectively were collected from across the distribution ranges in Taiwan. For the other species one sample each was used. ITS sequences generated in this study (GenBank accession numbers AB972273–AB972301) and ITS sequences obtained from GenBank are denoted in To test the generic assignment of the new species in hybrids) . This inMolecular analyses hired the nuclear ribosomal internal transcribed spacer (ITS) region, which has been proven to be highly useful in resolving intra- and intergeneric relationships in Cichorieae in previous studies P<0.0001) based on the likelihood ratio test −9–10.8×10−9 substitutions site−1 year−1−9, mean value = 4.22×10−9, median = 3.72×10−9, maximum value = 8.34×10−9) Bayesian phylogenetic and molecular dating analyses were conducted using BEAST ver. 1.7.5 –reconnection (TBR) branch swapping, and MULTREES and STEEPEST DESCENT options on. Statistical support for each clade was assessed by bootstrap analysis Phylogenetic analysis was also conducted based on maximum parsimony (MP) criterion using PAUP* ver. 4.0b10 Ching-I Peng 23905, HAST) and, for comparison, two congeners in Taiwan, Ixeridium laevigatum  and Ixeridium transnokoense . Root tips were pre-treated in 2 mM 8-hydroxyquinoline solution at 15–18°C for 6–8 h, and then fixed overnight in a 31 ethanol-acetic acid solution below 4°C. Chromosomes were macerated and stained in 2% acetic orcein with 1 N hydrochloric acid (101) and observed. Classification of chromosome morphology was based on the position of centromere Somatic chromosomes were examined for the new species . In the Ixeridium clade, two subclades were recovered; one comprised of the new species, Ixeridium transnokoense, and Ixeridium laevigatum (0.99/90.4%) and the other comprised of the rest of the species (0.99/53.9%). In the former subclade, the new species was sister to Ixeridium transnokoense (1.0/97.9%), forming a Taiwan endemic lineage. The age of the most recent common ancestor (MRCA) of Ixeridium and Ixeris was calculated as 5.37 million years ago (Ma) . The MRCA age of the clade of the new species–Ixeridium transnokoense–Ixeridium laevigatum was estimated to be 1.39 Ma (2.31–0.71 Ma). The MRCA age of the Taiwan endemic lineage was 0.49 Ma (0.95–0.20 Ma), and that of the new species was 0.10 Ma (0.29–0.008 Ma), and that of Ixeridium transnokoense was 0.28 Ma (0.53–0.10 Ma).The aligned length of the ITS sequences was 641 bp. Two hundreds nucleotide substitutions were found in 175 variable sites and 123 sites were parsimony informative among them. The Bayesian maximum clade credibility tree is shown . The MP n = 16 (n = 16 = 8 m+2 m/sm+2 sm (SC)+4 t. Ixeridium laevigatum . Their karyotype formula was determined as 2n = 14 = 14 m (2SC). Small constrictions (indicated with arrowheads) were observed at the t-chromosomes in the new species but at the longest m-chromosomes in the other two species.Somatic chromosome number of the new species was determined to be 2n = 16  A, D. Ofevigatum  B, E andnokoense  C, F in Ixeridium and to separate it from Ixeridium transnokoense .Bayesian and MP phylogenetic analyses indicated that Ixeridium calcicola exhibited atypical chromosome number for the genus, 2n = 16  and this is likely the result of secondarily contact after altitudinal isolation, given the above scenario. There is no edaphic barrier between the two species but no hybrid has been found. Hybridization between plants of different karyomorphotypes is largely inhibited Ixeridium calcicola may result in a postmating barrier to gene flow, although further field survey and population genetic analyses are needed before reaching a conclusion.Divergence time of Ixeridium calcicola C.-I Peng, S.W.Chung & T.C. Hsu, sp. nov. [urn:lsid:ipni.org:names:77142104-1] .42104-1] , 5. Typen = 16 11(–12), yellow, ligule 5-dentate, 8.0–9.0×3.0–4.0 mm, much exceeding involucre. Anthers 2.5–3.0 mm long, filaments 2.5–3.0 mm long, appendages ovate, apex obtuse. Style branch ca. 1.5 mm long, papillate. Achene pale brown, subfusiform, (2.5–)4–5 mm long, apex attenuate into a slender (0.5–)1–1.5 mm beak, ca. 10-ribbed, surface minutely scaly, glabrous. Pappus uniseriate, bristles many, ca 3.5 mm long, persistent, straw-colored. Somatic chromosome number, 2n = 16  A, D.Additional specimen examined:–TAIWAN. Taiwan Island, Hualien Hsien: Terminus of the cable way at the beginning of Yenhai Forest Road, 24°0951″N, 121°3111″E, ca. 1,150 m asl, 20 July 2013, Shih-Wen Chung 11141 (TAIF); Hoping (‘Hopin’) forest trail 41–36 K, 24°1731″N, 121°4139″E, 1,700–1,900 m asl, 25 May 1993, S.-F. Huang 5177 (TAI); On Prov. Hwy 8 , at Pilu, 2,000 m asl, 6 August 2006, Pi-Fong Lu 12241 (HAST); En route from Pilushan to Pilushan Shenmu, 2,250 m asl, 5 July 1986, Ching-I Peng 9246 (HAST); Tien-tsang Cliff, Taroko, 9 April 2008, Ching-I Peng 23905 (HAST); Luanshan to Mt. Potolushan in the Tailuko Forestry, northwest of Hualien, 2,000–2,200 m asl, 4 August 1963, Michio Tamura 21641 (HAST).Distribution, habitat, and ecology:–Ixeridium calcicola is very rare, presently known from only five populations on semi-shaded to open, moist rocky ridges and cliff faces on metamorphosed limestone mountains of Taroko National Park and its vicinities in eastcentral Taiwan, ca. 1,150–2,250 m asl , but differs from the latter in the oblong to lanceolate leaf blade (vs. linear to linear-lanceolate), the mucronulate teeth on radical leaf margin and sparsely on petiole (vs. smooth to very sparse mucronulate teeth), dark purple lower leaf surface (vs. greenish), 10 to 12 florets per capitulum (vs. 5 to 7), 8 to 10 inner phyllaries  and a basic chromosome number of X = 8 (vs X = 7).IUCN Red list category:–Vulnerable (VU D2). Ixeridium calcicola is currently known only from a narrow area of Hualien Hsien. Although three out of five populations are located in Taroko National Park, habitat disturbance brought about by human activities such as tourism and maintenance/building of roads/walking trails may have a negative impact on the species. Additionally, the land composed mainly of deformed marble is prone to landslides especially after heavy rainfall and frequent seismic activities, which can potentially have a fatal impact on the survival of the small populations of the species.I. laevigatum1. Plants 10–90 cm tall; leaves usually larger than 10×1.5 cm, often pinnatilobed…………………………………. .1. Plants less than 30 cm tall; leaves usually smaller than 10×1.5 cm, unlobed…………………………………………….. 2I. transnokoense2. Leaves linear to linear-lanceolate, inconspicuously petiolate; florets 5 to 7 per capitulum; inner phyllaries 5 (rarely to 7)………………………………. I. calcicola2. Leaves oblong to lanceolate, long-petiolate; florets 10 to 12 per capitulum, inner phyllaries 8 to 10……………… Appendix S1Ixeridium transnokoense specimens examined for morphological comparisons with the new species Ixeridium calcicola.(DOCX)Click here for additional data file.Appendix S2Species included in the molecular phylogenetic analyses. Voucher information  and GenBank accession numbers of the ITS sequences are shown.(DOCX)Click here for additional data file.


Endothelial microparticles (EMP) are complex vesicular structures shed from activated or apoptotic endothelial cells. As endurance exercise affects the endothelium, the objective of the study was to examine levels of EMP and angiogenic growth factors following different endurance exercise protocols.12 subjects performed 3 different endurance exercise protocols: 1. High volume training ; 2. 4×4 min at 95% PPO; 3. 4×30 sec all-out. EMPs were quantified using flow cytometry after staining platelet-poor-plasma. Events positive for Annexin-V and CD31, and negative for CD42b, were classified as EMPs. Vascular endothelial growth factor (VEGF), migratory inhibiting factor (MIF) and hepatocyte growth factor (HGF) were determined by ELISA technique. For all these measurements venous blood samples were taken pre, 0′, 30′, 60′ and 180′ after each intervention. Furthermore, in vitro experiments were performed to explore the effect of collected sera on target endothelial functions and MP uptake capacities.VEGF and HGF significantly increased after HIT interventions. All three interventions caused a significant decrease in EMP levels post exercise compared to pre values. The sera taken after exercise increased the uptake of EMP in target endothelial cells compared to sera taken under resting conditions, which was shown to be phosphatidylserin-dependent. Increased EMP uptake was associated with an improved protection of target cells against apoptosis. Sera taken prior and after exercise promoted target endothelial cell migration, which was abrogated after inhibition of VEGF.Physical exercise leads to decreased EMP levels and promotes a phosphatidylserin-dependent uptake of EMP into target endothelial cells, which is associated with a protection of target cells against apoptosis. In the past years there has been a lively discussion about high intensity training (HIT) and high volume training (HVT), their similarities and differences in adaptations. It was shown, that HIT is not only a useful tool in elite sports, but also in terms of health prevention and rehabilitation. Most studies focused on changes of endurance performance, muscle adaptations or health benefits, giving us a better idea of the molecular mechanisms Vascular endothelial growth factor (VEGF), hepatocyte growth factor (HGF) and macrophage migration inhibitory factor (MIF) are angiogenic agents known to be involved in the regulation of growth of new blood vessels. These growth factors play a role in transcapillary permeability, matrix deposition and degradation and stimulate cell differentiation, proliferation, migration, and survival In the context of angiogenic processes, endothelial microparticles (EMP) are becoming an upcoming marker of endothelial health. EMP are complex vesicular structures shed from activated or apoptotic endothelial cells. They are considered to play a remarkable role in coagulation, inflammation, endothelial function, and angiogenesis. Besides their role as marker of cell damage, recent reports have underlined their function as signalling elements in cell–cell communication. It has been reported that profiles of EMP reflect endothelial status and that EMP are generated under certain blood flow conditions (shear stress) and/or by a number of cytokines and apoptotic stimuli 2max: 64.3±9.7 ml·min−1·kg−1) participated in the present study. All subjects were informed orally and in writing of the study's purpose and the possible risks involved before providing written informed consent to participate. The study was approved by the Ethic Committee of the German Sport University Cologne in compliance with the Declaration of Helsinki. Subjects were assigned an anonymous ID during the study.Twelve healthy, non-smoking male triathletes/cyclists   and maximal peak power output (PPO) in order to determine the proper intensity for warming-up, recovery and the main training load (HVT & 4×4 min) for each subject for the main experiments. The step test consisted of cycling at ≥80 rpm with an initial workload of 100 W for 5 minutes and incremental 40-W increases every 5 minutes until volitional exhaustion was reached.Before the participation, subjects performed a step test to determine maximal oxygen uptake  were determined.To test the hypothesis subjects participated in three experimental trials on a cycle ergometer , each separated by one week in a randomized order  a–c. 1) The food intake before the tests was partially standardized. That is, certain foods containing carbohydrates were recommended to the subjects, and the subjects were advised to ingest the same amount and composition of food before each test. Therefore, food intake was recorded before the first test and reproduced before the following. A last light meal was allowed 2 hours before the test. 30 minutes after each of the three tests, subjects received 500 ml of a low fat chocolate milk  and additional corn-bars according to their calculated energy expenditure of the trials. After the ingestion, subjects were only allowed to drink water until the last blood sample was withdrawn. The subjects were not allowed to perform strenuous exercise 24 hours before testing.WU), EE during the intervals (EEInt) and EE during the recovery periods (EERec). For each of the periods, EE was calculated separately according to Scott et al. Total energy expenditure (EE) [kJ] and total work were determined for each session. Total EE was considered as the sum of EE during warm-up , MIF (ng·mL−1) and HGF (pg·mL−1) were determined by using human ELISA kits for VEGF ), MIF , and HGF ) R&D Systems, Inc. USA. All results of the growth factor analysis were adjusted for changes in plasma volume (PV) [PV changes in percentage of pre values  =  [(Hbpre/Hbpost)•(100-Hctpost)/[(100-Hctpre)-1]]•100 Venous blood samples were collected for the determination of vascular endothelial growth factor (VEGF), migratory inhibiting factor (MIF), and hepathocyte growth factor (HGF) before exercise (pre), and 0 min (0′), 30 min (30′), 60 min (60′) and 180 min (180′) post exercise  a–c. A vFor the determination of EMP, monocytic micropartilces (MMP) and platelet-derived microparticles (PMP) 8 mL of heparin blood was withdrawn pre, 0′, 60′ and 180′. EMPs were quantified (number/μl) using flow cytometry after staining platelet-poor-plasma with the cell surface markers. Events positive for Annexin-V and CD31, and negative for CD42b, were classified as EMPs. For more detailed information see During each of the three sessions capillary samples from the earlobe were collected for blood gas  and lactate analysis  at the following time points during each intervention:1) HVT: Blood gas/lactate: resting condition, post WU, and every 30 min during exercise.2) 4×4 min: Blood gas: resting condition, post WU, and 30 sec/2∶30 min after each 4 min exercise bout. Lactate: resting condition, post WU, and 0 sec/3 min after each 4 min exercise bout.3) 4×30 sec: Blood gas: resting condition, post WU, and 30 sec/6∶30 min after each 30 sec exercise bout. Lactate: resting condition, post WU, and 0 sec/3∶30 min/7 min after each 30 sec exercise bout.For the comparison of lactate and blood gas values of the 3 interventions the mean of all measurements and all subjects during each intervention was calculated.5 EMP were generated from starved HCAEC, labeled with PKH26 and diluted in 1 mL PBS as previously described The collected sera from 3 randomly chosen athletes of different conditions (4×4 and 4×30) were used for ex vivo stimulation of human coronary artery endothelial cells (HCAEC). HCAEC were incubated for 4 h (37°C) with 10% of the conditioned serum samples  as previously described by Rautou et al. To explore whether annexin V binding to phosphatidylserin (PS) modulates EMP uptake, EMPs were preincubated with or without annexin V (3 µg/mL) for 1 hour in the presence of CaClApoptosis was assessed using Caspase-3 ELISA as previously described Migration and proliferation were assessed using scratch assay as previously described p-value corresponding to the main intervention effect and time effect. Statistical differences were considered to be significant for p<0.05. Furthermore, the effect size “partial η2” was calculated according to the main effect over time for each intervention and parameter. The thresholds for small, moderate, and large effects were defined as 0.1, 0.25 and 0.4, respectively.Statistical analyses of the data were performed by using a statistics software package . Descriptive statistics of the data are presented as means ± SD, unless described otherwise. All data were normally distributed (Shapiro-Wilk test). To assess the effect of the three different interventions on circulating angiogenic growth factors and EMP, a 2-factor  repeated-measures ANOVA with Fisher post-hoc test was used. For each growth factor/EMP we reported the 2, mean pCO2, total work, energy expenditure, total oxygen consumption, heart rate (HR) and rate of perceived exertion (RPE) for all three interventions are shown in In order to characterize the three interventions, the results for the mean power (MP) output, mean lactate concentrations [La], mean pH, mean base excess (BE), mean pO−1 up to 834 pg•mL−1 . Post-hoc analysis revealed that both HIT interventions (4×30 sec & 4×4 min) significantly increased VEGF levels 0′ after exercise (p = 0.004 & p = 0.006) compared to pre-values. However, VEGF levels decreased back to pre values 30′ after the exercise  significantly increased HGF levels 180′ after exercise (p<0.001 & p = 0.01) compared to pre-values . HVT did2” are given in Post-hoc analysis revealed that both HIT interventions (4×30 sec & 4×4 min) significantly decreased MIF levels 60′ (p = 0.05 & p = 0.02) and 180′ after exercise (p = 0.03 & p = 0.004) compared to pre-values . HoweverIn summary, HIT seems to stimulate a transient increase in circulating levels of VEGF and HGF but a decrease of MIF.2” are given in For EMP over-all ANOVA showed significant differences for different points in time of one condition  but not for different conditions . Post-hoc analysis revealed that all three interventions  significantly decreased EMP levels 60′  and 180′  after exercise compared to pre-values . Values 2” are given in For MMP over-all ANOVA showed significant differences for different points in time of one condition  but not for different conditions . Post-hoc analysis revealed that both interval protocols  significantly decreased MMP levels 60′ (p = 0.003 and p = 0.04) and 180′ (p = 0.003 and p = 0.004) after exercise compared to pre-values . Values 2” are given in For PMP over-all ANOVA showed significant differences for different points in time of one condition  but not for different conditions . Post-hoc analysis revealed that all three interventions  significantly decreased PMP levels 60′  and 180′  after exercise compared to pre-values . Values As we previously studied the role of EMP in vascular biology in detail, To analyze whether the decrease of circulating EMP levels after physical exercise is mediated by an increased capacity of the endothelium to take up EMP, HCAEC were incubated with sera collected prior and after exercise . After incubation, HCAEC were treated with PKH26-labelled EMP for four hours and the number EMP per cell were analyzed. Interestingly, The sera collected 180′ after two different exercise protocols (4×4 min and 4×30 s) significantly promoted the uptake of EMP into target HCAEC compared to sera taken under resting conditions (pre) -dependent As EMP have been shown to protect target HCAEC from apoptosis In order to explore whether sera collected prior and after exercise might modulate other biological functions of target cells in addition to apoptosis, we stimulated HCAEC with sera (4×4 pre and 180′) and assessed migration and proliferation capacities of target cells using scratch assay. Both conditions significantly promoted migration of target cells after 6 and 20 hours . However3−, pO2, PCO2) was highest during and after 4×30 sec, followed by 4×4 min and HVT. In contrast, total work, total energy expenditure and total oxygen consumption were ∼2/∼3times higher in HVT compared to 4×4 min and 4×30 sec. Furthermore all three training interventions acutely decreased the circulating EMP, MMP and PMP levels. In accordance with these results, incubated HCAEC showed an increased uptake of EMP after stimulation with conditioned serum samples of athletes, whereas MMP uptake was not influenced after serum stimulation of target cells. These findings suggest that microparticles derived from different cell types experience different clearance mechanisms. In this context, we and others demonstrated that the endothelium in vivo might be a potential locus for circulating microparticle uptake The present study demonstrates that high intensity training (4×30 and 4×4) stimulates a transient increase in circulating levels of VEGF and HGF and a decrease of MIF, whereas HVT training had no influence on VEGF, HGF and MIF, despite a much higher training volume and time commitment  compared to HVT). Metabolic stress, characterized by values of lactate and blood gas measurements , MIF showed a significant decrease after high intensity exercise in the present study , −17,1% (4×4 min)), which might favour the migratory activity of endothelial cells MIF also has a role in promoting angiogenic processes VO2peak As increases in microparticles were described following cell activation or apoptosis and in diseases with altered shear forces in blood vessels, we expected circulating EMP to be increased after endurance exercise, especially after higher intensities, as exercise is known to increase the blood flow/shear stress at the vascular wall. However, circulating EMP significantly decreased after all three exercise interventions in the present study. Although a few other studies have investigated EMP following exercise in humans, this has been the first to examine EMP after different endurance training regimes. The findings of studies investigating the acute response of circulating EMP to exercise are heterogeneous. No changes in circulating EMP concentrations were observed after 100 min exercise at 70% Importantly, we found that increased uptake of EMP was associated with an improved protection of endothelial target cells against apoptosis. These findings are in accordance with previous data, showing that EMP protect target cells from apoptosis in an annexin I- phosphatidylserinreceptor-dependent manner The influence of sera on the uptake of EMP to endothelial cells could be mediated by soluble factors. As the present study showed, physical activity up-regulates angiogenic growth factors (VEGF), which are pro-angiogenic and inhibit apoptosis of endothelial cells (EC) on the one hand, but simultaneously induces the expression of developmentally regulated endothelial cell locus 1 (DEL-1) However, it should be recognized that baseline values (pre) showed great inter-individual differences, which is a clear limitations of the present study. Even though not statistically different, pre-values for 4×30 sec were higher compared to both other interventions. Nevertheless, it can be speculated that the combination of increased angiogenic growth factors and an increased EMP uptake protects the vascular system against apoptosis, despite massive stress. Additionally, low shear stress associates with increased EMP levels, suggesting that physiological shear stress like during exercise, known to contribute to endothelial survival, may limit EMP release in-vitro studies showed that low concentrations of EMP could promote angiogenesis, whereas high concentrations could suppress angiogenesis Furthermore, the reduction of EMP in the circulation might lead to pro-angiogenic conditions. In particular, Based on the data of VEGF, HGF and EMP it appears that especially intense training protocols may promote pro-angiogenic conditions. It can be speculated, that the acute hormonal increases and metabolic perturbations, might play a positive role in optimizing training adaptations. The described hormonal reactions may contribute to the positive effects of HIT even in highly trained athletes, as it has been shown by previous studies using similar exercise protocols. Finally, strenuous physical activity leads to an increased uptake of EMP which might protect EC and therefore the whole vascular system against apoptosis. This could be a mechanism how the endothelium is protected against distinct damage, despite massive stressors like high shear stress and/or decreases in pH. Although we tested well trained athletes in the present study, the results might also be important for therapeutic strategies. Our results may lead to the assumption, that the shear stress induced by exercise has positive effects in contrast to the shear stress in certain pathological conditions. In terms of a decrease in circulating EMP, the present study supports previous findings, that short-term high intensity exercise elicits similar results than HVT. As Mezentsev et al. 2005 stated, future therapeutic strategies aimed at reducing the number of circulating endothelium-derived microparticles or blocking their effects may be reasonable in different pathological processes where abnormalities of neovascularization and angiogenesis prevail Figure S1Changes in circulating MMP and PMP in conditioned serum of athletes. 4×30 sec , 4×4 min  and HVT . * significantly different compared to pre-values (p≤0.05). Values are presented as means ± SD.(TIFF)Click here for additional data file.Figure S2Uptake of MMP into target endothelial cells. HCAEC were stimulated with MMP and sera for 4 hours. N>3.(TIFF)Click here for additional data file.Figure S3Migration of endothelial cells after stimulation with conditioned sera. HCAEC were stimulated with sera and with our without VEGF and HGF inhibitors. HAEC pretreated with growth factor deprived medium served as control. Migration was assessed after six (A) and twenty (B) hours. N = 5. A: ** = p<0.01 vs. Control, pre/180′ + VEGF-inhibitor and 180′ + HGF-inhibitor, #  =  p<0.001 vs. all other groups except control. B: *** = p<0.001 vs. Control and pre/180′ + VEGF-inhibitor, #  =  p<0.001 vs. all other groups except control.(TIFF)Click here for additional data file.