scholarly journals Longevity and survival curves of Rhinella icterica (Anura, Bufonidae) under laboratory conditions

2014 ◽  
Vol 74 (2) ◽  
pp. 438-443 ◽  
Author(s):  
MSCS. Lima ◽  
J. Pederassi ◽  
CAS. Souza
Keyword(s):  
Life Expectancy ◽  
Growth Curve ◽  
Negative Correlation ◽  
Survival Curve ◽  
Mortality Trend ◽  
Survival Curves ◽  
Abiotic Conditions ◽  
Laboratory Conditions ◽  
Logarithmic Growth ◽  
Great Mortality

Life tables and survival curves of tadpoles from Rhinella icterica species were studied in the laboratory, under abiotic conditions controlled by a purification filter, a timer and a chiller. The survival curve for larval stage confirms a great mortality trend in the initial stages, which decreases when reaching the mature morphological condition (r = –0.94). Stages 37, 38, 39, 40 and 41 showed gradual values for their age structures, while stages 42, 43 and 44 presented high variations. Based on the results under laboratory conditions, it can be concluded that the maturity of R. icterica tadpoles development between 37 and 44 stages has a negative correlation and their predicted life expectancy is a logarithmic growth curve (y=–761.96Ln(x)+5298.5).

Use of a Modified Gompertz Equation to Predict the Effects of Temperature, pH, and NaCl on the Inactivation of Listeria monocytogenes Scott A Heated in Infant Formula

1996 ◽  
Vol 59 (1) ◽  
pp. 16-23 ◽  
Author(s):  
R. H. LINTON ◽  
W. H. CARTER ◽  
M. D. PIERSON ◽  
C. R. HACKNEY ◽  
J. D. EIFERT
Keyword(s):  
Listeria Monocytogenes ◽  
Infant Formula ◽  
Nonlinear Regression ◽  
Survival Curve ◽  
Interactive Effects ◽  
Parameter Estimates ◽  
Survival Curves ◽  
Gompertz Equation ◽  
Nacl Concentration ◽  
Effects Of Temperature

The heat resistance of Listeria monocytogenes was determined in infant formula for all possible combinations of temperature (50, 55, and 60°C), pH level (5, 6, and 7), and NaCl concentration (0, 2, and 4%). Survival curves were fit using nonlinear regression with a Gompertz equation. The Gompertz equation was flexible enough to fit the three most commonly observed survival curves: linear curves, those with an initial lag region followed by a linear region, and sigmoidal shaped. Parameter estimates obtained by the method of nonlinear least squares were used to describe the effect(s) of different heating treatments on the lag region, death rate, and tailing region of survival curves. These estimates were further used to predict single and interactive effects of temperature, pH, and percentage of NaCl on the log of the surviving fraction (LSF) of bacteria. Interactions among these variables significantly (P ≤ .05) affected the LSF. Generally, increased pH or NaCl concentration lead to an increased LSF, whereas increased time or temperature lead to a decreased LSF. All multiple-factor interactions significantly (P ≤ .05) affected the LSF. The correlation of observed LSF versus predicted LSF (R2 = .92) indicated that the estimated Gompertz equation was in close agreement with the observation. This study demonstrated that the Gompertz equation and nonlinear regression can be used as an effective means to predict survival curve shape and response to heat of L. monocytogenes under many different environmental conditions.

A unified degree day model describes survivorship of Copitarsia corruda Pogue & Simmons (Lepidoptera: Noctuidae) at different constant temperatures

2008 ◽  
Vol 99 (1) ◽  
pp. 65-72 ◽  
Author(s):  
N.N. Gómez ◽  
R.C. Venette ◽  
J.R. Gould ◽  
D.F. Winograd
Keyword(s):  
Survival Curve ◽  
The United States ◽  
Physiological Age ◽  
Alien Invasive Species ◽  
Temperature Threshold ◽  
Base Temperature ◽  
Survival Curves ◽  
Degree Day ◽  
Effects Of Temperature ◽  
Lepidoptera Noctuidae

AbstractPredictions of survivorship are critical to quantify the probability of establishment by an alien invasive species, but survival curves rarely distinguish between the effects of temperature on development versus senescence. We report chronological and physiological age-based survival curves for a potentially invasive noctuid, recently described as Copitarsia corruda Pogue & Simmons, collected from Peru and reared on asparagus at six constant temperatures between 9.7 and 34.5°C. Copitarsia spp. are not known to occur in the United States but are routinely intercepted at ports of entry. Chronological age survival curves differ significantly among temperatures. Survivorship at early age after hatch is greatest at lower temperatures and declines as temperature increases. Mean longevity was 220 (±13 SEM) days at 9.7°C. Physiological age survival curves constructed with developmental base temperature (7.2°C) did not correspond to those constructed with a senescence base temperature (5.9°C). A single degree day survival curve with an appropriate temperature threshold based on senescence adequately describes survivorship under non-stress temperature conditions (5.9–24.9°C).

Calculating Salmonella Inactivation in Nonisothermal Heat Treatments from Isothermal Nonlinear Survival Curves

2001 ◽  
Vol 64 (5) ◽  
pp. 606-613 ◽  
Author(s):  
K. L. MATTICK ◽  
J. D. LEGAN ◽  
T. J. HUMPHREY ◽  
M. PELEG
Keyword(s):  
Differential Equation ◽  
Heat Treatment ◽  
Mathematical Models ◽  
Survival Curve ◽  
Survival Ratio ◽  
Survival Curves ◽  
Time Intervals ◽  
Heat Treated ◽  
Rich Media ◽  
Nonisothermal Conditions

Salmonella cells in two sugar-rich media were heat treated at various constant temperatures in the range of 55 to 80°C and their survival ratios determined at various time intervals. The resulting nonlinear semilogarithmic survival curves are described by the model log10S(t) = −b(T)tn(T), where S(t) is the momentary survival ratio N(t)/N0, and b(T) and n(T) are coefficients whose temperature dependence is described by two empirical mathematical models. When the temperature profile, T(t), of a nonisothermal heat treatment can also be expressed algebraically, b(T) and n(T) can be transformed into a function of time, i.e., b[T(t)] and n[T(t)]. If the momentary inactivation rate primarily depends on the momentary temperature and survival ratio, then the survival curve under nonisothermal conditions can be constructed by solving a differential equation, previously suggested by Peleg and Penchina, whose coefficients are expressions that contain the corresponding b[T(t)] and n[T(t)] terms. The applicability of the model and its underlying assumptions was tested with a series of eight experiments in which the Salmonella cells, in the same media, were heated at various rates to selected temperatures in the range of 65 to 80°C and then cooled. In all the experiments, there was an agreement between the predicted and observed survival curves. This suggests that, at least in the case of Salmonella in the tested media, survival during nonisothermal inactivation can be estimated without assuming any mortality kinetics.

scholarly journals Modelling Dose Effects from Space Irradiations: Combination of High-LET and Low-LET Radiations with a Modified Microdosimetric Kinetic Model

Life ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 161 ◽  
Author(s):  
Alejandro Bertolet ◽  
Alejandro Carabe
Keyword(s):  
Kinetic Model ◽  
Poisson Distribution ◽  
Survival Curve ◽  
X Rays ◽  
Linear Quadratic ◽  
Survival Curves ◽  
Survival Fraction ◽  
High Let ◽  
Combined Action ◽  
High Linear Energy Transfer

The Microdosimetric Kinetic Model (MKM) to predict the effects of ionizing radiation on cell colonies is studied and reformulated for the case of high-linear energy transfer (LET) radiations with a low dose. When the number of radiation events happening in a subnuclear domain follows a Poisson distribution, the MKM predicts a linear-quadratic (LQ) survival curve. We show that when few events occur, as for high-LET radiations at doses lower than the mean specific energy imparted to the nucleus, zF,n, a Poisson distribution can no longer be assumed and an initial pure linear relationship between dose and survival fraction should be observed. Predictions of survival curves for combinations of high-LET and low-LET radiations are produced under two assumptions for their comparison: independent and combined action. Survival curves from previously published articles of V79 cell colonies exposed to X-rays, α particles, Ar-ions, Fe-ions, Ne-ions and mixtures of X-rays and each one of the ions are predicted according to the modified MKM. We conclude that mixtures of high-LET and low-LET radiations may enhance the effect of individual actions due to the increase of events in domains provided by the low-LET radiation. This hypothesis is only partially validated by the analyzed experiments.

scholarly journals INFLUENCE OF DEATH CRITERIA ON THE X-RAY SURVIVAL CURVES OF THE FUNGUS, NEUROSPORA

1934 ◽  
Vol 17 (4) ◽  
pp. 577-590 ◽  
Author(s):  
Fred M. Uber ◽  
David R. Goddard
Keyword(s):  
Survival Curve ◽  
X Rays ◽  
Survival Curves ◽  
Single Spore ◽  
Accurate Analysis ◽  
Single Well ◽  
Growth Production ◽  
Multiple Hit ◽  
Neurospora Tetrasperma ◽  
Ascospore Production

1. When ascospores of Neurospora tetrasperma were irradiated with 11 kv. X-rays, the single spore cultures obtained displayed a wide variety of mutated forms. 2. Control germinations of ascospores showed uniform behavior, ranging from 92–95 per cent germination. 3. The shape of the survival curves was found to be a function of the criterion of death. The following criteria were used: germination, growth, production of mature ascospores, and the production of normal perithecia. 4. The germination survival curve exhibited a rhythmic variation with dosage. Germination is not a significant criterion of death. 5. Half-survival dosages for growth and ascospore production were approximately 30,000 and 20,000 roentgens, respectively. 6. Multiple hit-to-kill relations were found on the basis of the quantum hit theory; no accurate analysis was possible. 7. The studies indicate that ascospore death does not result from a single well defined reaction, but rather from the integrated effects of several deleterious processes initiated by the radiation.

Death rate of populations of Bact. lactis aerogenes III. Interpretation of survival curves

1953 ◽  
Vol 141 (902) ◽  
pp. 137-145 ◽  
Keyword(s):  
Molecular Species ◽  
Death Rate ◽  
Critical Level ◽  
Survival Curve ◽  
Survival Times ◽  
Survival Curves ◽  
Independent Events ◽  
Random Events ◽  
Decline Curves ◽  
Frequent Observation

Most theories of the survival curve postulate either a progressive action of the lethal agent on cells with large inherent differences of resistance, or random events such as encounters between the agent and a sensitive region of the cells. A survey of the experimental evidence, however, suggests that death of the bacterial cell involves not only a progressive destruction of essential cell activities, but may also be conditioned at some stage by a random combina­tion of various independent events. The form of the survival curve depends essentially on the speed of the former process in relation to the probability of the latter. Factors modifying this form are: (1) intrinsic differences between individual cells, which, however, appear not to be the major cause of variation of survival times, and (2) the occurrence, in favourable circumstances, of adaptive adjustments. It is the element of chance in survival that accounts for the frequent observation of extremely skew distributions of survival times (and in the limit nearly logarithmic decline curves). It probably arises from the fact that the concentrations of various molecular species show complex fluctuations, at the appropriate phase of which certain cell activities fall below a critical level for viability.

scholarly journals Superposition of survival curves as a tool for epistasis analysis of longevity interventions

2017 ◽  
Author(s):  
Stefan Nowak ◽  
Johannes Neidhart ◽  
Jonas Rzezonka ◽  
Ivan G. Szendro ◽  
Rahul Marathe ◽  
...  
Keyword(s):  
Survival Curve ◽  
Null Model ◽  
Published Data ◽  
Survival Curves ◽  
Standard Analysis ◽  
Data Set ◽  
Epistasis Analysis ◽  
The Individual ◽  
Superposition Principles ◽  
Standing Problem

A long-standing problem in ageing research is to understand how different factors contributing to longevity should be expected to act in combination under the assumption that they are independent. Standard epistasis analysis compares the extension of mean lifespan achieved by a combination of interventions to the prediction under an additive or multiplicative null model, but neither model is fundamentally justified. Moreover, the target of longevity interventions is not mean life span but the entire survival curve. Here we formulate superposition principles that predict the survival curve resulting from a combination of two interventions based on the survival curves of the individual treatments, and quantify epistasis as the deviation from this prediction. We test the method on a published data set comprising survival curves for all combinations of 4 different longevity interventions in Caenorhabditis elegans. We find that epistasis is generally weak even when the standard analysis indicates otherwise.

scholarly journals Asymptotic convergence in distribution of the area bounded by prevalence-weighted Kaplan–Meier curves using empirical process modelling

2018 ◽  
Vol 5 (11) ◽  
pp. 180496
Author(s):  
Aaron Heuser ◽  
Minh Huynh ◽  
Joshua C. Chang
Keyword(s):  
Empirical Process ◽  
Survival Curve ◽  
Population Level ◽  
Weighted Averaging ◽  
Event Analysis ◽  
Social Security Administration ◽  
Survival Curves ◽  
Kaplan Meier ◽  
Population Survival ◽  
Product Limit

The Kaplan–Meier product-limit estimator is a simple and powerful tool in time to event analysis. An extension exists for populations stratified into cohorts where a population survival curve is generated by weighted averaging of cohort-level survival curves. For making population-level comparisons using this statistic, we analyse the statistics of the area between two such weighted survival curves. We derive the large sample behaviour of this statistic based on an empirical process of product-limit estimators. This estimator was used by an interdisciplinary National Institutes of Health–Social Security Administration team in the identification of medical conditions to prioritize for adjudication in disability benefits processing.

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