1,148 research outputs found

    Evolution and complexity: the double-edged sword

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    We attempt to provide a comprehensive answer to the question of whether, and when, an arrow of complexity emerges in Darwinian evolution. We note that this expression can be interpreted in different ways, including a passive, incidental growth, or a pervasive bias towards complexification. We argue at length that an arrow of complexity does indeed occur in evolution, which can be most reasonably interpreted as the result of a passive trend rather than a driven one. What, then, is the role of evolution in the creation of this trend, and under which conditions will it emerge? In the later sections of this article we point out that when certain proper conditions (which we attempt to formulate in a concise form) are met, Darwinian evolution predictably creates a sustained trend of increase in maximum complexity (that is, an arrow of complexity) that would not be possible without it; but if they are not, evolution will not only fail to produce an arrow of complexity, but may actually prevent any increase in complexity altogether. We conclude that, with regard to the growth of complexity, evolution is very much a double-edged sword

    A Fully Bayesian Approach for Combining Multilevel Failure Information in Fault Tree Quantification and Corresponding Optimal Resource Allocation

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    This paper presents a fully Bayesian approach that simultaneously combines basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, sub-system or system failure events. The full Bayesian approach also allows the highest-level data that are usually available for existing facilities to be automatically propagated to lower levels. A simple example illustrates the proposed approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm

    Avalanche dynamics in Bak-Sneppen evolution model observed with standard distribution width of fitness

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    We introduce the standard distribution width of fitness to characterize the global and individual features of a ecosystem in the Bak-Sneppen evolution model. Through tracking this quantity in evolution, a different hierarchy of avalanche dynamics, w0w_{0} avalanche is observed. The corresponding gap equation and the self-organized threshold wcw_{c} are obtained. The critical exponents τ,\tau , γ\gamma and ρ\rho , which describe the behavior of the avalanche size distribution, the average avalanche size and the relaxation to attractor, respectively, are calculated with numerical simulation. The exact master equation and γ\gamma equation are derived. And the scaling relations are established among the critical exponents of this new avalanche.Comment: 14 pages, 3 figure

    TailFindR: Alignment-free poly(A) length measurement for Oxford Nanopore RNA and DNA sequencing

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    Polyadenylation at the 3′-end is a major regulator of messenger RNA and its length is known to affect nuclear export, stability, and translation, among others. Only recently have strategies emerged that allow for genome-wide poly(A) length assessment. These methods identify genes connected to poly(A) tail measurements indirectly by short-read alignment to genetic 3′-ends. Concurrently, Oxford Nanopore Technologies (ONT) established full-length isoform-specific RNA sequencing containing the entire poly(A) tail. However, assessing poly(A) length through base-calling has so far not been possible due to the inability to resolve long homopolymeric stretches in ONT sequencing. Here we present tailfindr, an R package to estimate poly(A) tail length on ONT long-read sequencing data. tailfindr operates on unaligned, base-called data. It measures poly(A) tail length from both native RNA and DNA sequencing, which makes poly(A) tail studies by full-length cDNA approaches possible for the first time. We assess tailfindr’s performance across different poly(A) lengths, demonstrating that tailfindr is a versatile tool providing poly(A) tail estimates across a wide range of sequencing conditions.publishedVersio

    PROMoter uPstream Transcripts share characteristics with mRNAs and are produced upstream of all three major types of mammalian promoters

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    PROMoter uPstream Transcripts (PROMPTs) were identified as a new class of human RNAs, which are heterologous in length and produced only upstream of the promoters of active protein-coding genes. Here, we show that PROMPTs carry 3′-adenosine tails and 5′-cap structures. However, unlike mRNAs, PROMPTs are largely nuclear and rapidly turned over by the RNA exosome. PROMPT-transcribing DNA is occupied by RNA polymerase II (RNAPII) complexes with serine 2 phosphorylated C-terminal domains (CTDs), mimicking that of the associated genic region. Thus, the inefficient elongation capacity of PROMPT transcription cannot solely be assigned to poor CTD phosphorylation. Conditions that reduce gene transcription increase RNAPII occupancy of the upstream PROMPT region, suggesting that they reside in a common transcription compartment. Surprisingly, gene promoters that are actively transcribed by RNAPI or RNAPIII also produce PROMPTs that are targeted by the exosome. RNAPIII PROMPTs bear hallmarks of RNAPII promoter-associated RNAs, explaining the physical presence of RNAPII upstream of many RNAPIII-transcribed genes. We propose that RNAPII activity upstream gene promoters are wide-spread and integral to the act of gene transcription

    Endangered Black Marsh Turtle, Siebenrockiella crassicollis (Gray, 1831) (Reptilia, Testudines, Geoemydidae): distribution extension and first record from Belitung Island, Indonesia

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    Black Marsh Turtle, Siebenrockiella crassicollis (Gray, 1831), is a freshwater turtle native across Southeast Asia and is categorized as Endangered according to the IUCN Red List. We report the first record of this species from Belitung, a remote island in Indonesia, based on photographs. The new record is approximately 200 km to the east of the nearest locality in Sumatra, and 250 km to the west of the nearest locality in Borneo

    Prognostic Value of Patient-Reported Symptom Interference in Patients with Late-stage Lung Cancer

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    Purpose Patient-reported outcomes (PROs) have been found to be significant predictors of clinical outcomes such as overall survival (OS), but the effect of demographic and clinical factors on the prognostic ability of PROs is less understood. Several PROs derived from the 12-item Short-Form Health Survey (SF-12) and M. D. Anderson Symptom Inventory (MDASI) were investigated for association with OS, with adjustments for other factors, including performance status. Methods A retrospective analysis was performed on data from 90 patients with stage IV non-small cell lung cancer. Several baseline PROs were added to a base Cox proportional hazards model to examine the marginal significance and improvement in model fit attributable to the PRO: mean MDASI symptom interference level; mean MDASI symptom severity level for five selected symptoms; SF-12 physical and mental component summaries; and the SF-12 general health item. Bootstrap resampling was used to assess the robustness of the findings. Results The MDASI mean interference level had a significant effect on OS (p = 0.007) when the model was not adjusted for interactions with other prognostic factors. Further exploration suggested the significance was due to an interaction with performance status (p = 0.001). The MDASI mean symptom severity level and the SF-12 physical component summary, mental component summary, and general health item did not have a significant effect on OS. Conclusions Symptom interference adds prognostic information for OS in advanced lung cancer patients with poor performance status, even when demographic and clinical prognostic factors are accounted for

    A Universal Lifetime Distribution for Multi-Species Systems

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    Lifetime distributions of social entities, such as enterprises, products, and media contents, are one of the fundamental statistics characterizing the social dynamics. To investigate the lifetime distribution of mutually interacting systems, simple models having a rule for additions and deletions of entities are investigated. We found a quite universal lifetime distribution for various kinds of inter-entity interactions, and it is well fitted by a stretched-exponential function with an exponent close to 1/2. We propose a "modified Red-Queen" hypothesis to explain this distribution. We also review empirical studies on the lifetime distribution of social entities, and discussed the applicability of the model.Comment: 10 pages, 6 figures, Proceedings of Social Modeling and Simulations + Econophysics Colloquium 201

    Does the Red Queen reign in the kingdom of digital organisms?

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    In competition experiments between two RNA viruses of equal or almost equal fitness, often both strains gain in fitness before one eventually excludes the other. This observation has been linked to the Red Queen effect, which describes a situation in which organisms have to constantly adapt just to keep their status quo. I carried out experiments with digital organisms (self-replicating computer programs) in order to clarify how the competing strains' location in fitness space influences the Red-Queen effect. I found that gains in fitness during competition were prevalent for organisms that were taken from the base of a fitness peak, but absent or rare for organisms that were taken from the top of a peak or from a considerable distance away from the nearest peak. In the latter two cases, either neutral drift and loss of the fittest mutants or the waiting time to the first beneficial mutation were more important factors. Moreover, I found that the Red-Queen dynamic in general led to faster exclusion than the other two mechanisms.Comment: 10 pages, 5 eps figure
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