Uniform categorization of biocommunication in bacteria, fungi and plants

On thresholds: signs, symbols and significance

Purpose

This paper reviews research developments in semiosis (sign activity) as theorized by Peirce, Eco and Sebeok, focusing specifically on the current study of “semiotic threshold zones,” which range from the origins of life through various nonhuman life forms to artificial life forms, including those symbolic thresholds most familiar to library and information science (LIS) researchers. The intent is to illustrate potential opportunities for LIS research beyond its present boundaries.

Design/methodology/approach

The paper provides a framework that describes six semiotic threshold zones (presemiotic, protosemiotic, phytosemiotic, zoosemiotic, symbolic and polysemiotic) and notable work being done by researchers in each.

Findings

While semiotic researchers are still defining the continuum of semiotic thresholds, this focus on thresholds can provide a unifying framework for significance as human and nonhuman interpretations of a wide variety of signs accompanied by a better understanding of their relationships becomes more urgent in a rapidly changing global environment.

Originality/value

Though a variety of semiotic-related topics have appeared in the LIS literature, semiotic thresholds and their potential relationships to LIS research have not been previously discussed there. LIS has traditionally tasked itself with the recording, dissemination and preservation of knowledge, and in a world that faces unprecedented environmental and global challenges for all species, the importance of these thresholds may well be considered as part of our professional obligations in potentially documenting and archiving the critical differences in semiosis that extend beyond purely human knowledge.

Cryptococcus strains with different pathogenic potentials have diverse protein secretomes

Secreted proteins are the frontline between the host and pathogen. In mammalian hosts, secreted proteins enable invasive infection and can modulate the host immune response. Cryptococcosis, caused by pathogenic Cryptococcus species, begins when inhaled infectious propagules establish to produce pulmonary infection, which, if not resolved, can disseminate to the central nervous system to cause meningoencephalitis. Strains of Cryptococcus species differ in their capacity to cause disease, and the mechanisms underlying this are not well understood. To investigate the role of secreted proteins in disease, we determined the secretome for three genome strains of Cryptococcus species, including a hypovirulent and a hypervirulent strain of C. gattii and a virulent strain of C. neoformans. Sixty-seven unique proteins were identified, with different numbers and types of proteins secreted by each strain. The secretomes of the virulent strains were largely limited to proteolytic and hydrolytic enzymes, while the hypovirulent strain had a diverse secretome, including non-conventionally secreted canonical cytosolic and immunogenic proteins that have been implicated in virulence. The hypovirulent strain cannot establish pulmonary infection in a mouse model, but strains of this genotype have caused human meningitis. To directly test brain infection, we used intracranial inoculation and found that the hypovirulent strain was substantially more invasive than its hypervirulent counterpart. We suggest that immunogenic proteins secreted by this strain invoke a host response that limits pulmonary infection but that there can be invasive growth and damage if infection reaches the brain. Given their known role in virulence, it is possible that non-conventionally secreted proteins mediate this process.

Can mathematics explain the evolution of human language?

Investigation into the sequence structure of the genetic code by means of an informatic approach is a real success story. The features of human language are also the object of investigation within the realm of formal language theories. They focus on the common rules of a universal grammar that lies behind all languages and determine generation of syntactic structures. This universal grammar is a depiction of material reality, i.e., the hidden logical order of things and its relations determined by natural laws. Therefore mathematics is viewed not only as an appropriate tool to investigate human language and genetic code structures through computer science-based formal language theory but is itself a depiction of material reality. This confusion between language as a scientific tool to describe observations/experiences within cognitive constructed models and formal language as a direct depiction of material reality occurs not only in current approaches but was the central focus of the philosophy of science debate in the twentieth century, with rather unexpected results. This article recalls these results and their implications for more recent mathematical approaches that also attempt to explain the evolution of human language.

Can mathematics explain the evolution of human language?

Investigation into the sequence structure of the genetic code by means of an informatic approach is a real success story. The features of human language are also the object of investigation within the realm of formal language theories. They focus on the common rules of a universal grammar that lies behind all languages and determine generation of syntactic structures. This universal grammar is a depiction of material reality, i.e., the hidden logical order of things and its relations determined by natural laws. Therefore mathematics is viewed not only as an appropriate tool to investigate human language and genetic code structures through computer science-based formal language theory but is itself a depiction of material reality. This confusion between language as a scientific tool to describe observations/experiences within cognitive constructed models and formal language as a direct depiction of material reality occurs not only in current approaches but was the central focus of the philosophy of science debate in the twentieth century, with rather unexpected results. This article recalls these results and their implications for more recent mathematical approaches that also attempt to explain the evolution of human language.