The Effect of Littermate Weight on Survival, Weight Gain, and Suckling Behavior of Low-Birth-Weight Piglets in Cross-Fostered Litters

Objective: To determine whether low-birth-weight piglets show better survival, weight gain, and suckling behavior when grouped with other small piglets by cross-fostering. Methods: We manipulated the number and size of foster littermates for low-birth-weight piglets in 31 small (eight or nine piglets) and 22 large (11 or 12 piglets) litters. Experimental litters were composed of four to six piglets of lowest birth weight and either four to six slightly heavier or four to six much heavier piglets from two combined litters. Results: Low-birth-weight piglets raised with much heavier littermates had somewhat lower survival rates, but showed no tendency towards lower weight gains or less successful suckling behavior than low-birth-weight piglets raised with slightly heavier littermates. The somewhat higher survival rate of low-birth-weight piglets raised with slightly heavier littermates was largely offset by more deaths in the foster littermates, so there was no overall reduction in total losses. Low-birth-weight piglets fought more when raised with slightly heavier piglets than with much heavier piglets, and they missed more nursing episodes and had smaller weight gains than littermates, regardless of littermate weight. Implications: Cross-fostering low-birth-weight pigs into litters with other small pigs, compared to fostering into litters with high-birth-weight pigs, slightly improved their survival, but did not affect their weight gain or ability to suckle successfully, nor overall litter survival, even in litters as large as 11 or 12 piglets. Cross-fostering low-birth-weight pigs to litters of similar birth weight increased the level of fighting

Within-Litter Birth Weight Variation in the Domestic Pig and its Relation to Pre-Weaning Survival, Weight Gain, and Variation in Weaning Weights

To determine the relationship between within-litter birth weight variation and pre-weaning survival and weight gain, and to provide practical guidance on fostering low-birth-weight piglets, we analyzed piglet survival and weight gain in litters of piglets from 52 sows followed through eight consecutive parities. Litters with high variation in birth weight had more deaths, especially if the litter’s mean birth weight was low. High variation in birth weight was also associated with high variation in weaning weight, but was not significantly related to mean weaning weight. Piglets with birth weights well below the range of most of the litter (‘low-birth-weight piglets’) were more likely to die than their litter-mates, but their weight gains were normal for their birth weight if they survived. These piglets experienced particularly low survival in larger litters and litters from sows of sixth parity or older. Litters containing low-birth-weight piglets started, on average, with more piglets born alive and had a lower pre-weaning survival (with the majority of deaths being low-birth-weight piglets), but did not wean significantly more piglets than litters without low-birth-weight piglets. The majority of litters had a negatively skewed distribution of birth weights, with more piglets well below the mean than well above it. Our data are consistent with the hypothesis that high variation in birth weight contributes to reduced survival, at least for litters of low mean birth weight, and to variable weaning weights. Our data also support the hypothesis that in terms of survival, small piglets have a competitive disadvantage compared to their heavier litter-mates, a disadvantage that is exacerbated in large litters and litters from older sows. Our data suggest that selection for increased litter size that results in more low-birth-weight piglets per litter may not be beneficial unless measures are undertaken to improve the survival of low-birth-weight piglets

Within-Litter Birth Weight Variation in the Domestic Pig and its Relation to Pre-Weaning Survival, Weight Gain, and Variation in Weaning Weights

To determine the relationship between within-litter birth weight variation and pre-weaning survival and weight gain, and to provide practical guidance on fostering low-birth-weight piglets, we analyzed piglet survival and weight gain in litters of piglets from 52 sows followed through eight consecutive parities. Litters with high variation in birth weight had more deaths, especially if the litter’s mean birth weight was low. High variation in birth weight was also associated with high variation in weaning weight, but was not significantly related to mean weaning weight. Piglets with birth weights well below the range of most of the litter (‘low-birth-weight piglets’) were more likely to die than their litter-mates, but their weight gains were normal for their birth weight if they survived. These piglets experienced particularly low survival in larger litters and litters from sows of sixth parity or older. Litters containing low-birth-weight piglets started, on average, with more piglets born alive and had a lower pre-weaning survival (with the majority of deaths being low-birth-weight piglets), but did not wean significantly more piglets than litters without low-birth-weight piglets. The majority of litters had a negatively skewed distribution of birth weights, with more piglets well below the mean than well above it. Our data are consistent with the hypothesis that high variation in birth weight contributes to reduced survival, at least for litters of low mean birth weight, and to variable weaning weights. Our data also support the hypothesis that in terms of survival, small piglets have a competitive disadvantage compared to their heavier litter-mates, a disadvantage that is exacerbated in large litters and litters from older sows. Our data suggest that selection for increased litter size that results in more low-birth-weight piglets per litter may not be beneficial unless measures are undertaken to improve the survival of low-birth-weight piglets

Roaming: a phase space perspective

In this review we discuss the recently described roaming mechanism for chemical reactions from the point of view of nonlinear dynamical systems in phase space. The recognition of the roaming phenomenon shows the need for further developments in our fundamental understanding of basic reaction dynamics, as is made clear by considering some questions that cut across most studies of roaming: Is the dynamics statistical? Can transition state theory be applied to estimate roaming reaction rates? What role do saddle points on the potential energy surface play in explaining the behavior of roaming trajectories? How do we construct a dividing surface that is appropriate for describing the transformation from reactants to products for roaming trajectories? How should we define the roaming region? We show that the phase space perspective on reaction dynamics provides the setting in which these questions can be properly framed and answered. We illustrate these ideas by considering photodissociation of formaldehyde. The phase-space formulation allows an unambiguous description of all possible reactive events, which also allows us to uncover the phase space mechanism that explains which trajectories roam, as opposed to evolving toward a different reactive event

Stochastic Cooling Overview

The status of stochastic cooling and developments over the years are reviewed with reference to much of the original work. Both theoretical and technological subjects are considered.Comment: 10 pages. Includes an extensive bibliograph

Phase space barriers and dividing surfaces in the absence of critical points of the potential energy: Application to roaming in ozone

We examine the phase space structures that govern reactiondynamics in the absence of critical points on the potential energy surface. We show that in the vicinity of hyperbolic invariant tori, it is possible to define phase space dividing surfaces that are analogous to the dividing surfaces governing transition from reactants to products near a critical point of the potential energy surface. We investigate the problem of capture of an atom by a diatomic molecule and show that a normally hyperbolic invariant manifold exists at large atom-diatom distances, away from any critical points on the potential. This normally hyperbolic invariant manifold is the anchor for the construction of a dividing surface in phase space, which defines the outer or loose transition state governing capture dynamics. We present an algorithm for sampling an approximate capture dividing surface, and apply our methods to the recombination of the ozone molecule. We treat both 2 and 3 degrees of freedom models with zero total angular momentum. We have located the normally hyperbolic invariant manifold from which the orbiting (outer) transition state is constructed. This forms the basis for our analysis of trajectories for ozone in general, but with particular emphasis on the roaming trajectories

Geometric Interpretation of the Mixed Invariants of the Riemann Spinor

Mixed invariants are used to classify the Riemann spinor in the case of Einstein-Maxwell fields and perfect fluids. In the Einstein-Maxwell case these mixed invariants provide information as to the relative orientation of the gravitational and electromagnetic principal null directions. Consideration of the perfect fluid case leads to some results about the behaviour of the Bel-Robinson tensor regarded as a quartic form on unit timelike vectors.Comment: 31 pages, AMS-LaTe

Selecting patients for randomized trials: a systematic approach based on risk group

BACKGROUND: A key aspect of randomized trial design is the choice of risk group. Some trials include patients from the entire at-risk population, others accrue only patients deemed to be at increased risk. We present a simple statistical approach for choosing between these approaches. The method is easily adapted to determine which of several competing definitions of high risk is optimal. METHOD: We treat eligibility criteria for a trial, such as a smoking history, as a prediction rule associated with a certain sensitivity (the number of patients who have the event and who are classified as high risk divided by the total number patients who have an event) and specificity (the number of patients who do not have an event and who do not meet criteria for high risk divided by the total number of patients who do not have an event). We then derive simple formulae to determine the proportion of patients receiving intervention, and the proportion who experience an event, where either all patients or only those at high risk are treated. We assume that the relative risk associated with intervention is the same over all choices of risk group. The proportion of events and interventions are combined using a net benefit approach and net benefit compared between strategies. RESULTS: We applied our method to design a trial of adjuvant therapy after prostatectomy. We were able to demonstrate that treating a high risk group was superior to treating all patients; choose the optimal definition of high risk; test the robustness of our results by sensitivity analysis. Our results had a ready clinical interpretation that could immediately aid trial design. CONCLUSION: The choice of risk group in randomized trials is usually based on rather informal methods. Our simple method demonstrates that this decision can be informed by simple statistical analyses