Competitive Exclusion and Coexistence of Universal Grammars

Developed after a meeting at the Santa Fe Institute on extinction modeling, this book comments critically on the various modeling approaches. In the last decade or so, scientists have started to examine a new approach to the patterns of evolution and extinction in the fossil record. This approach may be called "statistical paleontology," since it looks at large-scale patterns in the record and attempts to understand and model their average statistical features, rather than their detailed structure. Examples of the patterns these studies examine are the distribution of the sizes of mass extinction events over time, the distribution of species lifetimes, or the apparent increase in the number of species alive over the last half a billion years. In attempting to model these patterns, researchers have drawn on ideas not only from paleontology, but from evolutionary biology, ecology, physics, and applied mathematics, including fitness landscapes, competitive exclusion, interaction matrices, and self-organized criticality. A self-contained review of work in this field.

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Searching for universal model of amyloid signaling motifs using probabilistic context-free grammars

BMC Bioinformatics ◽

10.1186/s12859-021-04139-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Witold Dyrka ◽

Marlena Gąsior-Głogowska ◽

Monika Szefczyk ◽

Natalia Szulc

Keyword(s):

Functional Relationship ◽

High Sensitivity ◽

Alternative Methods ◽

Discriminative Power ◽

Context Free Grammar ◽

Protein Motifs ◽

Functional Features ◽

Universal Grammars ◽

Context Free ◽

Probabilistic Context

Abstract Background Amyloid signaling motifs are a class of protein motifs which share basic structural and functional features despite the lack of clear sequence homology. They are hard to detect in large sequence databases either with the alignment-based profile methods (due to short length and diversity) or with generic amyloid- and prion-finding tools (due to insufficient discriminative power). We propose to address the challenge with a machine learning grammatical model capable of generalizing over diverse collections of unaligned yet related motifs. Results First, we introduce and test improvements to our probabilistic context-free grammar framework for protein sequences that allow for inferring more sophisticated models achieving high sensitivity at low false positive rates. Then, we infer universal grammars for a collection of recently identified bacterial amyloid signaling motifs and demonstrate that the method is capable of generalizing by successfully searching for related motifs in fungi. The results are compared to available alternative methods. Finally, we conduct spectroscopy and staining analyses of selected peptides to verify their structural and functional relationship. Conclusions While the profile HMMs remain the method of choice for modeling homologous sets of sequences, PCFGs seem more suitable for building meta-family descriptors and extrapolating beyond the seed sample.

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Limosilactobacillus fermentum CECT5716: Mechanisms and Therapeutic Insights

Nutrients ◽

10.3390/nu13031016 ◽

2021 ◽

Vol 13 (3) ◽

pp. 1016

Author(s):

María Jesús Rodríguez-Sojo ◽

Antonio Jesús Ruiz-Malagón ◽

María Elena Rodríguez-Cabezas ◽

Julio Gálvez ◽

Alba Rodríguez-Nogales

Keyword(s):

Competitive Exclusion ◽

Intestinal Barrier ◽

Mechanisms Of Action ◽

Intestinal Barrier Function ◽

Therapeutic Approaches ◽

Beneficial Effects ◽

Host Health ◽

Inflammatory Processes ◽

Immunomodulatory Properties ◽

Immunological Alterations

Probiotics microorganisms exert their health-associated activities through some of the following general actions: competitive exclusion, enhancement of intestinal barrier function, production of bacteriocins, improvement of altered microbiota, and modulation of the immune response. Among them, Limosilactobacillus fermentum CECT5716 has become one of the most promising probiotics and it has been described to possess potential beneficial effects on inflammatory processes and immunological alterations. Different studies, preclinical and clinical trials, have evidenced its anti-inflammatory and immunomodulatory properties and elucidated the precise mechanisms of action involved in its beneficial effects. Therefore, the aim of this review is to provide an updated overview of the effect on host health, mechanisms, and future therapeutic approaches.

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Competitive exclusion of Salmonella enteritidis in chicks by treatment with a single culture plus dietary lactose

International Journal of Food Microbiology ◽

10.1016/0168-1605(94)90002-7 ◽

1994 ◽

Vol 22 (1) ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Robert G. Behling ◽

Amy C.L. Wong

Keyword(s):

Salmonella Enteritidis ◽

Competitive Exclusion ◽

Single Culture

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Biological Control and Mitigation of Aflatoxin Contamination in Commodities

Toxins ◽

10.3390/toxins13020104 ◽

2021 ◽

Vol 13 (2) ◽

pp. 104

Author(s):

Ferenc Peles ◽

Péter Sipos ◽

Szilvia Kovács ◽

Zoltán Győri ◽

István Pócsi ◽

...

Keyword(s):

Biological Control ◽

Secondary Metabolites ◽

Competitive Exclusion ◽

Aflatoxin Contamination ◽

Post Harvest ◽

Physical Chemical ◽

Synthetic Chemicals ◽

Ruminal Degradation

Aflatoxins (AFs) are toxic secondary metabolites produced mostly by Aspergillus species. AF contamination entering the feed and food chain has been a crucial long-term issue for veterinarians, medicals, agroindustry experts, and researchers working in this field. Although different (physical, chemical, and biological) technologies have been developed, tested, and employed to mitigate the detrimental effects of mycotoxins, including AFs, universal methods are still not available to reduce AF levels in feed and food in the last decades. Possible biological control by bacteria, yeasts, and fungi, their excretes, the role of the ruminal degradation, pre-harvest biocontrol by competitive exclusion or biofungicides, and post-harvest technologies and practices based on biological agents currently used to alleviate the toxic effects of AFs are collected in this review. Pre-harvest biocontrol technologies can give us the greatest opportunity to reduce AF production on the spot. Together with post-harvest applications of bacteria or fungal cultures, these technologies can help us strictly reduce AF contamination without synthetic chemicals.

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