scholarly journals Re-analysis of plant CO2 responses during the exponential growth phase: interactions with light, temperature, nutrients and water availability

2015 ◽  
Vol 42 (10) ◽  
pp. 989 ◽  
Author(s):  
Miko U. F. Kirschbaum ◽  
Suzanne M. Lambie
Keyword(s):  
Plant Growth ◽  
Growth Phase ◽  
Exponential Growth ◽  
Cost Effective ◽  
C3 Plants ◽  
Exponential Growth Phase ◽  
Initial Growth ◽  
Short Term ◽  
Co2 Response ◽  
Explicit Consideration

Many short-term experiments have been conducted under increasing CO2 but results have been varied and have not yet led to a conclusive quantitative understanding of the CO2 response of plant growth. This may have been partly due to a lack of explicit consideration of the positive feedback inherent in plant growth during periods of exponential growth. This feedback can increase an initial physiological enhancement of relative growth rate (RGR) into a much larger biomass enhancement. To overcome this problem, we re-analysed existing experimental data from 78 publications. We calculated the RGRs of C3 plants and their relative enhancement under elevated CO2 and derived response indices that were independent of the duration of experiments and the RGR at normal atmospheric CO2. The RGR of unstressed plants increased by 14 ± 2% under doubled CO2, with observed RGR enhancement linearly correlated with calculated photosynthetic enhancements (based on the Farquhar-von Caemmerer-Berry photosynthesis model), but at only half their numeric values. Calculated RGR enhancements did not change significantly for temperatures from 12 to 40°C, but were reduced under nutrient limitation, and were increased under water stress or low irradiance. We concluded that short-term experiments can offer simple and cost-effective insights into plant CO2 responses, provided they are analysed by calculating relative changes in RGR during the strictly exponential initial growth phase.

scholarly journals Comparative estimation of the reproduction number for pandemic influenza from daily case notification data

2006 ◽  
Vol 4 (12) ◽  
pp. 155-166 ◽  
Author(s):  
Gerardo Chowell ◽  
Hiroshi Nishiura ◽  
Luís M.A Bettencourt
Keyword(s):  
Growth Phase ◽  
Pandemic Influenza ◽  
Exponential Growth ◽  
Goodness Of Fit ◽  
Reproduction Number ◽  
Exponential Growth Phase ◽  
Initial Growth ◽  
Epidemic Curve ◽  
Spanish Flu ◽  
The City

The reproduction number, , defined as the average number of secondary cases generated by a primary case, is a crucial quantity for identifying the intensity of interventions required to control an epidemic. Current estimates of the reproduction number for seasonal influenza show wide variation and, in particular, uncertainty bounds for for the pandemic strain from 1918 to 1919 have been obtained only in a few recent studies and are yet to be fully clarified. Here, we estimate using daily case notifications during the autumn wave of the influenza pandemic (Spanish flu) in the city of San Francisco, California, from 1918 to 1919. In order to elucidate the effects from adopting different estimation approaches, four different methods are used: estimation of using the early exponential-growth rate (Method 1), a simple susceptible–exposed–infectious–recovered (SEIR) model (Method 2), a more complex SEIR-type model that accounts for asymptomatic and hospitalized cases (Method 3), and a stochastic susceptible–infectious–removed (SIR) with Bayesian estimation (Method 4) that determines the effective reproduction number at a given time t . The first three methods fit the initial exponential-growth phase of the epidemic, which was explicitly determined by the goodness-of-fit test. Moreover, Method 3 was also fitted to the whole epidemic curve. Whereas the values of obtained using the first three methods based on the initial growth phase were estimated to be 2.98 (95% confidence interval (CI): 2.73, 3.25), 2.38 (2.16, 2.60) and 2.20 (1.55, 2.84), the third method with the entire epidemic curve yielded a value of 3.53 (3.45, 3.62). This larger value could be an overestimate since the goodness-of-fit to the initial exponential phase worsened when we fitted the model to the entire epidemic curve, and because the model is established as an autonomous system without time-varying assumptions. These estimates were shown to be robust to parameter uncertainties, but the theoretical exponential-growth approximation (Method 1) shows wide uncertainty. Method 4 provided a maximum-likelihood effective reproduction number 2.10 (1.21, 2.95) using the first 17 epidemic days, which is consistent with estimates obtained from the other methods and an estimate of 2.36 (2.07, 2.65) for the entire autumn wave. We conclude that the reproduction number for pandemic influenza (Spanish flu) at the city level can be robustly assessed to lie in the range of 2.0–3.0, in broad agreement with previous estimates using distinct data.

Activation of the expression of the microcin C51 operon upon glucose starvation of cells at the exponential growth phase

2005 ◽  
Vol 41 (1) ◽  
pp. 40-43
Author(s):  
A. M. Veselovskii ◽  
A. Z. Metlitskaya ◽  
V. A. Lipasova ◽  
I. A. Bass ◽  
I. A. Khmel
Keyword(s):  
Growth Phase ◽  
Exponential Growth ◽  
Exponential Growth Phase ◽  
Glucose Starvation

scholarly journals Differences in power-law growth over time and indicators of COVID-19 pandemic progression worldwide

2020 ◽  
Author(s):  
Jack Merrin
Keyword(s):  
Error Analysis ◽  
Real Time ◽  
Power Law ◽  
Growth Phase ◽  
Exponential Growth ◽  
Spreading Rate ◽  
Exponential Growth Phase ◽  
Power Law Exponent ◽  
Disease Spreading ◽  
Over Time

1AbstractAn automated statistical and error analysis of 45 countries or regions with more than 1000 cases of COVID-19 as of March 28, 2020, has been performed. This study reveals differences in the rate of disease spreading rate over time in different countries. This survey observes that most countries undergo a beginning exponential growth phase, which transitions into a power-law phase, as recently suggested by Ziff and Ziff. Tracking indicators of growth, such as the power-law exponent, are a good indication of the relative danger different countries are in and show when social measures are effective towards slowing the spread. The data compiled here are usefully synthesizing a global picture, identifying country to country variation in spreading, and identifying countries most at risk. This analysis may factor into how best to track the effectiveness of social distancing policies and quarantines in real-time as data is updated each day.

scholarly journals Biosynthesis and turnover of outer-membrane proteins in Escherichia coli ML308-225

1979 ◽  
Vol 182 (2) ◽  
pp. 407-412 ◽  
Author(s):  
R J Allen ◽  
G K Scott
Keyword(s):  
Escherichia Coli ◽  
Protein Synthesis ◽  
Outer Membrane ◽  
Bacterial Growth ◽  
Growth Phase ◽  
Exponential Growth ◽  
Outer Membrane Proteins ◽  
Exponential Growth Phase ◽  
Outer Membranes ◽  
Dilution Experiments

Isolated outer membranes and outer-membrane extracts from Escherichia coli ML308-225 in the early-exponential growth phase contain more protein than do corresponding preparations from late-exponential- or stationary-phase bacteria. Isotope-dilution experiments show that this is due to a loss of protein from the membrane during the exponential growth phase. Inhibition of bacterial growth and protein synthesis stabilizes the outer-membrane-protein concentration. Protein synthesis in the absence of bacterial growth results in higher concentrations of protein in the outer membrane.

Exponential growth phase ofPseudomonas methanolica batch cultures

1973 ◽  
Vol 13 (6) ◽  
pp. 523-528 ◽  
Author(s):  
E. M. Shulgovskaya ◽  
I. I. Ivanova ◽  
G. G. Sotnicov
Keyword(s):  
Growth Phase ◽  
Exponential Growth ◽  
Exponential Growth Phase ◽  
Batch Cultures

scholarly journals The Putrescine Importer PuuP of Escherichia coli K-12

2009 ◽  
Vol 191 (8) ◽  
pp. 2776-2782 ◽  
Author(s):  
Shin Kurihara ◽  
Yuichi Tsuboi ◽  
Shinpei Oda ◽  
Hyeon Guk Kim ◽  
Hidehiko Kumagai ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Gene Cluster ◽  
Growth Phase ◽  
Exponential Growth ◽  
Minimal Medium ◽  
Exponential Growth Phase ◽  
E Coli ◽  
Genes Encoding ◽  
K 12 ◽  
Utilization Pathway

ABSTRACT The Puu pathway is a putrescine utilization pathway involving gamma-glutamyl intermediates. The genes encoding the enzymes of the Puu pathway form a gene cluster, the puu gene cluster, and puuP is one of the genes in this cluster. In Escherichia coli, three putrescine importers, PotFGHI, PotABCD, and PotE, were discovered in the 1990s and have been studied; however, PuuP had not been discovered previously. This paper shows that PuuP is a novel putrescine importer whose kinetic parameters are equivalent to those of the polyamine importers discovered previously. A puuP + strain absorbed up to 5 mM putrescine from the medium, but a ΔpuuP strain did not. E. coli strain MA261 has been used in previous studies of polyamine transporters, but PuuP had not been identified previously. It was revealed that the puuP gene of MA261 was inactivated by a point mutation. When E. coli was grown on minimal medium supplemented with putrescine as the sole carbon or nitrogen source, only PuuP among the polyamine importers was required. puuP was expressed strongly when putrescine was added to the medium or when the puuR gene, which encodes a putative repressor, was deleted. When E. coli was grown in M9-tryptone medium, PuuP was expressed mainly in the exponential growth phase, and PotFGHI was expressed independently of the growth phase.

scholarly journals Functional elucidation of the non-coding RNAs of Kluyveromyces marxianus in the exponential growth phase

BMC Genomics ◽  
2016 ◽  
Vol 17 (1) ◽  
Author(s):  
Yoo-Bok Cho ◽  
Eun Ju Lee ◽  
Suhyung Cho ◽  
Tae Yong Kim ◽  
Jin Hwan Park ◽  
...  
Keyword(s):  
Growth Phase ◽  
Exponential Growth ◽  
Kluyveromyces Marxianus ◽  
Exponential Growth Phase ◽  
Non Coding Rnas

Soy Peptides Enhance Heterologous Membrane Protein Productivity during the Exponential Growth Phase ofSaccharomyces cerevisiae

2012 ◽  
Vol 76 (3) ◽  
pp. 628-631 ◽  
Author(s):  
Keisuke ITO ◽  
Aya HIKIDA ◽  
Sayuri KITAGAWA ◽  
Takumi MISAKA ◽  
Keiko ABE ◽  
...  
Keyword(s):  
Membrane Protein ◽  
Growth Phase ◽  
Exponential Growth ◽  
Exponential Growth Phase ◽  
Soy Peptides ◽  
Protein Productivity

Giardia lamblia: axenic growth in autoclaved and filtered Diamond's TYI-S-33 medium

1982 ◽  
Vol 60 (7) ◽  
pp. 1673-1675 ◽  
Author(s):  
M. Belosevic ◽  
G. M. Faubert ◽  
N. A. Croll ◽  
J. D. MacLean
Keyword(s):  
Growth Phase ◽  
Exponential Growth ◽  
Giardia Lamblia ◽  
Culture Medium ◽  
Exponential Growth Phase ◽  
Growth Studies ◽  
Generation Times ◽  
The Mean ◽  
Axenic Growth

The trophozoites of Giardia lamblia were gradually adapted to grow in both autoclaved and filtered Diamond's TYI-S-33 culture medium. Comparative growth studies indicated that the growth of organisms was significantly higher in filtered TYI-S-33 medium. In both types of media the exponential growth phase occurred between 48 and 96 h postinoculation. The mean number of trophozoites at 96 h was 1.94 × 105 and 4.82 × 105 cells/mL for autoclaved and filtered media, respectively. The generation times for the exponential growth phase were 9.66 h. for autoclaved and 7.69 h for filtered medium. The percentage of dead trophozoites was similar in both media and was 14% for the first 8 days postinoculation.

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