Nomenclature

Résumé

Une nomenclature est un système de classification (code, tableau, liste, règles d'attribution d'identité…) servant de référence dans le cadre d'une activité professionnelle, industrielle ou d'une discipline donnée (exemples : en chimie, en botanique, en zoologie, en astronomie). La nomenclature est un élément-clé de toute taxonomie. Origine du terme Le mot et l'idée viennent directement du latin nomenclatura. Primitivement, le nomenclator désigne l'esclave qui clame les noms des plats d'un dîner ou annonce les personnes à leur arrivée en un lieu. À Rome, un candidat à une magistrature se fait accompagner de son nomenclateur afin que celui-ci lui rappelle discrètement le nom des citoyens qu'il doit saluer. Plus tard, Pline l'Ancien, auteur de lHistoire naturelle, emploie le terme dans le sens que nous lui connaissons, soit l'. Dans un de ses Nouveaux contes (1674), Le cas de conscience, La Fontaine évoque le privilège royal d'Adam le nomenclateur. Buffon, le naturaliste, i

Source officielle

https://fr.wikipedia.org/wiki/Nomenclature

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vignette|Principaux rangs taxinomiques. Le règne (du latin « regnum », au pluriel « regna ») est, dans la taxonomie de Carl von Linné (qui classe la biodiversité en fonction des caractères communs par

vignette|350px|La classification classique du vivant classe les êtres vivants selon une hiérarchie de groupes de plus en plus vastes. La taxonomie ou taxinomie est une branche des sciences naturelles

En taxinomie (botanique, zoologie, mycologie), le nom binominal, nom binomial, binom ou binôme est une combinaison de deux mots servant à désigner une espèce. Le premier mot, le nom générique, circon

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A community-based transcriptomics classification and nomenclature of neocortical cell types

Parviz Ghaderi, Jean Rossier

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

NATURE PUBLISHING GROUP2020

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New insights into the classification and nomenclature of cortical GABAergic interneurons

Ruth Benavides Piccione, Sean Lewis Hill, Zoltan Kisvarday, Henry Markram, Jean Rossier, Yun Wang

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxononnical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

Nature Publishing Group2013

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The acidity of atmospheric particles and clouds

Athanasios Nenes, Tao Wang

Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semivolatile gases such as HNO3, NH3, HCl, and organic acids and bases as well as chemical reaction rates. It has implications for the atmospheric lifetime of pollutants, deposition, and human health. Despite its fundamental role in atmospheric processes, only recently has this field seen a growth in the number of studies on particle acidity. Even with this growth, many fine-particle pH estimates must be based on thermodynamic model calculations since no operational techniques exist for direct measurements. Current information indicates acidic fine particles are ubiquitous, but observationally constrained pH estimates are limited in spatial and temporal coverage. Clouds and fogs are also generally acidic, but to a lesser degree than particles, and have a range of pH that is quite sensitive to anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient ammonia. Historical measurements indicate that cloud and fog droplet pH has changed in recent decades in response to controls on anthropogenic emissions, while the limited trend data for aerosol particles indicate acidity may be relatively constant due to the semivolatile nature of the key acids and bases and buffering in particles. This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets. It includes recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale.

2020

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