Comparison of Flow Resistance Characteristics and Placement of Two Endotracheal Tubes.

BACKGROUND: In a traditional endotracheal tube (ETT), there is a linear outward pull through its attachment to the ventilator tubing that leads to risk of accidental dislodgement. This study was conducted to assess the ETT flow characteristics and to evaluate providers' intubation experience using two ETT's in a simulated setting. METHODS: Respiratory pressure-volume dynamics for the 2 ETTs were studied in a simulation laboratory by using 3 different flow settings and 2 different test lungs. The time taken for successful intubation on a mannikin was compared by direct observation of 33 separate intubation attempts by 11 different providers. Comfort with intubation by using both tubes was assessed with a Likert scale-based survey. The potential increase in physical and cognitive work load of nurses and respiratory therapists was assessed by the NASA task load index. RESULTS: There were slightly lower average tidal volumes delivered with SecureTube compared with the standard tube at different peak inspiratory pressures. Similarly, the same tidal volume delivered with a different flow and bag compliance required slightly higher peak inspiratory pressure compared with the standard ETT. Among providers, there was no difference in the average time to intubate when using either tube. All survey respondents (N = 11) rated intubation attempts with the SecureTube to be very easy compared with the standard tube. The NASA task load index (N = 26) showed very low task loads on all the tasks. CONCLUSIONS: There was minimal impact on flow resistance on pressure or volume with the SecureTube compared with the standard tube. Most providers felt comfortable intubating with the SecureTube and took a comparable amount of time to intubate in a simulated setting. We observed low task load scores for securement, maintenance, and manipulation per nurses and respiratory therapists.

The fundamental theorem of natural selection with mutations.

The mutation-selection process is the most fundamental mechanism of evolution. In 1935, R. A. Fisher proved his fundamental theorem of natural selection, providing a model in which the rate of change of mean fitness is equal to the genetic variance of a species. Fisher did not include mutations in his model, but believed that mutations would provide a continual supply of variance resulting in perpetual increase in mean fitness, thus providing a foundation for neo-Darwinian theory. In this paper we re-examine Fisher's Theorem, showing that because it disregards mutations, and because it is invalid beyond one instant in time, it has limited biological relevance. We build a differential equations model from Fisher's first principles with mutations added, and prove a revised theorem showing the rate of change in mean fitness is equal to genetic variance plus a mutational effects term. We refer to our revised theorem as the fundamental theorem of natural selection with mutations. Our expanded theorem, and our associated analyses (analytic computation, numerical simulation, and visualization), provide a clearer understanding of the mutation-selection process, and allow application of biologically realistic parameters such as mutational effects. The expanded theorem has biological implications significantly different from what Fisher had envisioned.

The waiting time problem in a model hominin population.

BACKGROUND: Functional information is normally communicated using specific, context-dependent strings of symbolic characters. This is true within the human realm (texts and computer programs), and also within the biological realm (nucleic acids and proteins). In biology, strings of nucleotides encode much of the information within living cells. How do such information-bearing nucleotide strings arise and become established? METHODS: This paper uses comprehensive numerical simulation to understand what types of nucleotide strings can realistically be established via the mutation/selection process, given a reasonable timeframe. The program Mendel's Accountant realistically simulates the mutation/selection process, and was modified so that a starting string of nucleotides could be specified, and a corresponding target string of nucleotides could be specified. We simulated a classic pre-human hominin population of at least 10,000 individuals, with a generation time of 20 years, and with very strong selection (50% selective elimination). Random point mutations were generated within the starting string. Whenever an instance of the target string arose, all individuals carrying the target string were assigned a specified reproductive advantage. When natural selection had successfully amplified an instance of the target string to the point of fixation, the experiment was halted, and the waiting time statistics were tabulated. Using this methodology we tested the effect of mutation rate, string length, fitness benefit, and population size on waiting time to fixation. RESULTS: Biologically realistic numerical simulations revealed that a population of this type required inordinately long waiting times to establish even the shortest nucleotide strings. To establish a string of two nucleotides required on average 84 million years. To establish a string of five nucleotides required on average 2 billion years. We found that waiting times were reduced by higher mutation rates, stronger fitness benefits, and larger population sizes. However, even using the most generous feasible parameters settings, the waiting time required to establish any specific nucleotide string within this type of population was consistently prohibitive. CONCLUSION: We show that the waiting time problem is a significant constraint on the macroevolution of the classic hominin population. Routine establishment of specific beneficial strings of two or more nucleotides becomes very problematic.

A new look at an old virus: patterns of mutation accumulation in the human H1N1 influenza virus since 1918.

BACKGROUND: The H1N1 influenza A virus has been circulating in the human population for over 95 years, first manifesting itself in the pandemic of 1917-1918. Initial mortality was extremely high, but dropped exponentially over time. Influenza viruses have high mutation rates, and H1N1 has undergone significant genetic changes since 1918. The exact nature of H1N1 mutation accumulation over time has not been fully explored. METHODS: We have made a comprehensive historical analysis of mutational changes within H1N1 by examining over 4100 fully-sequenced H1N1 genomes. This has allowed us to examine the genetic changes arising within H1N1 from 1918 to the present. RESULTS: We document multiple extinction events, including the previously known extinction of the human H1N1 lineage in the 1950s, and an apparent second extinction of the human H1N1 lineage in 2009. These extinctions appear to be due to a continuous accumulation of mutations. At the time of its disappearance in 2009, the human H1N1 lineage had accumulated over 1400 point mutations (more than 10% of the genome), including approximately 330 non-synonymous changes (7.4% of all codons). The accumulation of both point mutations and non-synonymous amino acid changes occurred at constant rates (µ = 14.4 and 2.4 new mutations/year, respectively), and mutations accumulated uniformly across the entire influenza genome. We observed a continuous erosion over time of codon-specificity in H1N1, including a shift away from host (human, swine, and bird [duck]) codon preference patterns. CONCLUSIONS: While there have been numerous adaptations within the H1N1 genome, most of the genetic changes we document here appear to be non-adaptive, and much of the change appears to be degenerative. We suggest H1N1 has been undergoing natural genetic attenuation, and that significant attenuation may even occur during a single pandemic. This process may play a role in natural pandemic cessation and has apparently contributed to the exponential decline in mortality rates over time, as seen in all major human influenza strains. These findings may be relevant to the development of strategies for managing influenza pandemics and strain evolution.

The effects of low-impact mutations in digital organisms.

BACKGROUND: Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution. RESULTS: When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations. CONCLUSIONS: Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the selection threshold. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.

Skittle: a 2-dimensional genome visualization tool.

BACKGROUND: It is increasingly evident that there are multiple and overlapping patterns within the genome, and that these patterns contain different types of information--regarding both genome function and genome history. In order to discover additional genomic patterns which may have biological significance, novel strategies are required. To partially address this need, we introduce a new data visualization tool entitled Skittle. RESULTS: This program first creates a 2-dimensional nucleotide display by assigning four colors to the four nucleotides, and then text-wraps to a user adjustable width. This nucleotide display is accompanied by a "repeat map" which comprehensively displays all local repeating units, based upon analysis of all possible local alignments. Skittle includes a smooth-zooming interface which allows the user to analyze genomic patterns at any scale.Skittle is especially useful in identifying and analyzing tandem repeats, including repeats not normally detectable by other methods. However, Skittle is also more generally useful for analysis of any genomic data, allowing users to correlate published annotations and observable visual patterns, and allowing for sequence and construct quality control. CONCLUSIONS: Preliminary observations using Skittle reveal intriguing genomic patterns not otherwise obvious, including structured variations inside tandem repeats. The striking visual patterns revealed by Skittle appear to be useful for hypothesis development, and have already led the authors to theorize that imperfect tandem repeats could act as information carriers, and may form tertiary structures within the interphase nucleus.