Выращивание ремонтного молодняка кур при использовании пробиотических препаратов «Бацелл» и «Моноспорин»

Применение пробиотических препаратов с первых дней жизни цыплят позволит получить в дальнейшем здоровую птицу с высокой реализацией генетического потенциала

Epidemiological dynamics on heterogeneous spatial configurations of target cells randomly generated with varying pair correlation <i>p</i>_<i>CC</i> but fixed mean density of target cell <i>x</i>_<i>C</i> = 0.5.

<p>Each column denotes the configuration for <i>p</i>_<i>CC</i> = 0.1 (a, d, g), <i>p</i>_<i>CC</i> = 0.25 which corresponds to complete spatial randomness (b, e, h), and <i>p</i>_<i>CC</i> = 0.4 (c, f, i). (a-c) Examples of spatial structure, where target cells are shown in white. (d-f) The regions in the parameter space of recovery rate (<i>α</i>) and the proportion of global infection (<i>G</i>) in which viruses are either maintained in endemic equilibrium (shaded) or go extinct (white). The endemic condition is obtained by Eq (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005952#pcbi.1005952.e021" target="_blank">7</a>). (g-i) The results of Monte-Carlo simulation showing the fraction of trials in 20 independent simulation runs in which viruses didn’t become extinct until 500 time steps as a function <i>G</i>. The recovery rate is fixed at <i>α</i> = 4 (g, h), or <i>α</i> = 5.5 (i). Other parameters are <i>β</i>_<i>G</i> = <i>β</i>_<i>L</i> = 10.</p

Evolutionary outcomes on randomly and deterministically generated structures (Top) The deterministically generated spatial structures, where target cells are shown by white.

<p>(a) The vertical stripe pattern with the line width 1, (b) the Sierpinski gasket, (c) checkerboard pattern with each cell sized as 5x5. (Middle) The corresponding randomly generated spatial patterns that have the same global and pair densities as those in the top row. (a) <i>x</i>_<i>C</i> = 0.5 and <i>p</i>_<i>CC</i> = 0.25, (b) <i>x</i>_<i>C</i> = 0.16 and <i>p</i>_<i>CC</i> = 0.07, (c) <i>x</i>_<i>C</i> = 0.5 and <i>p</i>_<i>CC</i> = 0.4. (Bottom) Comparison of the results of Monte Carlo simulations for the evolution of the fraction of global infection (<i>G</i>). For each spatial structure, 20 simulation runs are conducted, and the resulting population mean fractions of global infection are plotted as dots. In randomly generated structures, the spatial configurations are regenerated in each simulation run. Other parameters are <i>α</i> = 1, <i>β</i>_<i>G</i> = <i>β</i>_<i>L</i> = 10.</p

The final size of epidemic and the arrival time of epidemic at local populations.

<p>The final size of the local epidemic (A) and the time until the infected individuals first appear in the local population (B) (i.e., the arrival time of epidemic) plotted against the local population size. The population size is on a logarithmic scale. (A1–2) and (B1–2): results of the individual-based model (IBM) simulations; each point (dots) gives the mean value of the Monte Carlo ensemble averaged over 100 Monte Carlo runs for each local population, and the blue and red dots correspond to the results for the home and work populations, respectively. The black lines in (A1–2) give the mean value of the final size of the local epidemic for each population size class. The black lines in (B1–2) represent the regression line of the arrival time of the epidemic in the local population versus the logarithm of the population size. The regression line for the arrival time in the -th home population with population size , , was highly significant, with a P-value of in the test ( with the degrees of freedom (1, 1084)), . The estimated intercept and slope and their confidence intervals (CIs) are ( CI) and ( CI). The same was true for the arrival times in the work population; the regression was highly significant (, with ), with estimated intercept and slope ( CI) and ( CI), respectively. (A3) and (B3): corresponding results obtained from the population size class model (PSCM); the blue line shows the result for the home population and the red line the result for the work population (refer main text for details). The infection rate was . A person commuting from “Gyotoku” station to “Aoyama-itchome” station was designated the initially infectious individual.</p

Commuter flow data for the Tokyo metropolitan area.

<p>(A) Geographical location of the Tokyo metropolitan area within Kanto region, Japan. The framed rectangle shows the central part of the Tokyo metropolitan area. (B) Distribution of the station sizes on a double-logarithmic plot. Blue line, distribution of home-node stations; red line, distribution of work-node stations. (C) and (D) Geographical distributions of the sizes of home- and work-node stations, respectively, within the central part of the Tokyo metropolitan area. The color indicates the size of the station: black, commuters; blue, commuters; green, commuters; red, commuters. All numbers are from the 139,841 collected questionnaires of UTC. The red-colored stations in the middle of (D) correspond to Tokyo's inner urban area (along the loop of the Yamanote line); the 2 red stations in the lower left of (D) are the Kawasaki and Yokohama stations. The longitude and latitude of each station were acquired from the Station Database [<a href="http://www.ekidata.jp" target="_blank">http://www.ekidata.jp</a>].</p

The effect of countermeasures at each of the major stations in the Tokyo metropolitan area.

<p>The basic reproductive ratio <i>R</i>₀ (A) and the global final size of epidemic Ψ (B) are given as a function of the number of vaccinated/quarantined, respectively. The vaccination/quarantine is independently applied to each of the following major stations: Shinjuku (the largest working population, red lines), Tokyo (the second largest working population, green lines), and Shibuya (the third largest working population, blue lines). The results of random vaccination/quarantine are given in black dotted lines. Each column denotes the results for different <i>β</i>, which is defined as the infection rate from a single infectious host per unit time (relation between <i>R</i>₀ and <i>β</i> is given in Methods section).</p

Results of Monte-Carlo simulation.

<p>Parameters that are not denoted below are the same as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005952#pcbi.1005952.g002" target="_blank">Fig 2A</a>, <i>x</i>_<i>C</i> = 0.5, <i>α</i> = 1, <i>β</i>_<i>G</i> = <i>β</i>_<i>L</i> = 10. (a) Examples of evolutionary trajectories of mean proportion of global infection <i>G</i>. The red line denotes results for <i>p</i>_<i>CC</i> = 0.25, the green line for <i>p</i>_<i>CC</i> = 0.1, and the blue line for <i>p</i>_<i>CC</i> = 0.4. (b)-(c) Dependence of evolutionally outcomes after 5,000 time step simulation. We conduct 20 simulations for each value of (horizontal axis), and the long-term average of the population mean <i>G</i> are shown (vertical axis). Bars denotes the standard deviation. (b) The red line denotes results for <i>x</i>_<i>C</i> = 0. 5, the green line for <i>x</i>_<i>C</i> = 0. 4, and the blue line for <i>x</i>_<i>C</i> = 0. 7. (c) The red line denotes the results for <i>β</i>_<i>G</i> = <i>β</i>_<i>L</i> = 10, the green line for <i>β</i>_<i>G</i> = 10, <i>β</i>_<i>L</i> = 8, and the blue line for <i>β</i>_<i>G</i> = 8, <i>β</i>_<i>L</i> = 10.</p

The final size and the peak time of global epidemic.

<p>The final size of the global epidemic (A) and the time until an epidemic initiated by a single host reaches its peak (B) plotted against the infection rate . (A1) and (B1): results observed in the individual-based model (IBM) simulations; each point gives the Monte Carlo ensemble average value corresponding to different epidemic parameters, and the color indicates the sum of the sizes of the initially infected home and work populations. Here, the cases for initial extinction of disease are excluded from the ensemble. (A2) and (B2): corresponding results from the population size class model (PSCM) calculations.</p

Schematic representation of the population size class model (PSCM).

<p>(A) Geographical distribution of the railway network; each node corresponds to a station and each line corresponds to a commuter railway of commuter trains. Every station has a home population (those who reside in the area) and a work population (those who travel to as a workplace/school in the area). There are multiple commuters using the commuter train between each pair of populations. (B) The commuter network utilized in the individual-based model (IBM) calculations. The nodes correspond to the home and work populations of each station, forming a bipartite network in which each line denotes a connection via commuter flow between home and work populations. Local populations with different population sizes are represented by different colors and sizes. (C) The commuter network utilized in the PSCM calculation. Local populations with similar population sizes are grouped into population size classes, which form the nodes, while the total commuter flows between pairs of population size classes form the lines. (D) Joint distribution of the home and work population sizes of commuters in the Tokyo metropolitan area. The number of commuters that live in a home population of size class and commute to a work population of size class is plotted as a density plot. The data were obtained from the Urban Transportation Census (UTC) commute data (Ministry of Land, Infrastructure, Transport and Tourism, The 10th Urban Transportation Census Report, 2007; in Japanese).</p

Commute network model of the Tokyo metropolitan area.

<p>Geographical distribution of daytime working/studying population (A) and nighttime residing population (B) at each station. Each dot corresponds to a single station, with the color indicating its population size. The red colored stations near the center of (A) corresponds to the inner urban area of the Tokyo metropolitan area, which include the largest working station Shinjuku station, the second largest Tokyo station, and the third largest Shibuya station; the two red stations in the lower left are the Kawasaki and Yokohama stations. The longitude and latitude of each station were acquired from the Station Database [<a href="http://www.ekidata.jp" target="_blank">http://www.ekidata.jp</a>]. (C) Population size distribution of the daytime working/studying population (red line) and the nighttime residing population (blue line) at each station. (D) Illustration of the commute network model. Each station has a working/studying area (daytime “work population”, red circles) and a residing area (nighttime “home population”, blue circles) connected by a commuting flow (“commuting population”). The non-commuting population at each station (“resident population”, green circles) is connected to the corresponding home population.</p