16 research outputs found
Functional visualization of NK Cell-mediated killing of metastatic single tumor cells
ナチュラルキラー(NK)細胞による転移がん細胞殺傷の可視化 --NK細胞とがん細胞の肺毛細血管上での戦いを実況中継する--. 京都大学プレスリリース. 2022-02-07.Natural killer (NK) cells lyse invading tumor cells to limit metastatic growth in the lung, but how some cancers evade this host protective mechanism to establish a growing lesion is unknown. Here we have combined ultra-sensitive bioluminescence imaging with intravital two-photon microscopy involving genetically-encoded biosensors to examine this question. NK cells eliminated disseminated tumor cells from the lung within 24 hrs of arrival, but not thereafter. Intravital dynamic imaging revealed that 50% of NK-tumor cell encounters lead to tumor cell death in the first 4 hrs after tumor cell arrival, but after 24 hrs of arrival, nearly 100% of the interactions result in the survival of the tumor cell. During this 24 hrs period, the probability of ERK activation in NK cells upon encountering the tumor cells was decreased from 68% to 8%, which correlated with the loss of the activating ligand CD155/PVR/Necl5 from the tumor cell surface. Thus, by quantitatively visualizing the NK-tumor cell interaction at the early stage of metastasis, we have revealed the crucial parameters of NK cell immune surveillance in the lung
Phytoplankton community reorganization driven by eutrophication and warming in Lake Biwa
Abstract We compiled and analyzed long-term data, including chemical, physical and phytoplankton community data, for the Lake Biwa ecosystem from 1962 to 2003. Analyses on environmental data indicate that Lake Biwa had experienced intensified eutrophication (according to total phosphorus concentration) in the late 1960s and returned to a less eutrophic status around 1985, and then exhibited rapid warming and thus increased water column stability since 1990. Total phytoplankton cell volume largely followed the trend of total phosphorus concentration, albeit short-term fluctuations existed. However, phytoplankton community shifted dramatically in response to those changes of environmental states. These shifts were cause by changes in trophic status driven by phosphorus loadings and physical properties in the water column driven by warming. Moreover, most phytoplankton species did not show a strong linear correlation with environmental variables, suggesting nonlinear transitions among different states
Causal networks of phytoplankton diversity and biomass are modulated by environmental context
Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24◦~N58◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management
Does a Decrease in Chlorophyll <I>a</I> Concentration in Lake Biwa Mean a Decrease in Primary Productivity by Phytoplankton?
Appendix B. The truncation of left-hand tail of species abundance distribution in phytoplankton community appeared in four seasons.
The truncation of left-hand tail of species abundance distribution in phytoplankton community appeared in four seasons
Appendix C. Distinguishing temporal variation of species abundance distribution from sampling and statistical artifacts.
Distinguishing temporal variation of species abundance distribution from sampling and statistical artifacts
Appendix F. Multivariate linear model analyses for testing littoral ratio responses to environmental factors.
Multivariate linear model analyses for testing littoral ratio responses to environmental factors
Appendix H. Exploring the water warming-induced size-selection hypothesis.
Exploring the water warming-induced size-selection hypothesis
Appendix D. Using species traits to partition species abundance distribution.
Using species traits to partition species abundance distribution
Appendix E. Time series analysis of phytoplankton littoral ratio and species richness responses to environmental factors.
Time series analysis of phytoplankton littoral ratio and species richness responses to environmental factors