An evaluation of the taxonomy of Propionibacterium

1968 ◽  
Vol 14 (11) ◽  
pp. 1185-1191 ◽  
Author(s):  
A. C. Malik ◽  
G. W. Reinbold ◽  
E. R. Vedamuthu
Keyword(s):  
Host Range ◽  
Numerical Taxonomy ◽  
Similar Group ◽  
Propionibacterium Shermanii

The object of this study was to reevaluate speciation of Propionibacterium by using numerical taxonomy. Fifty-six cultures representing eight species were studied. Thirty-eight morphological and physiological features were employed in the calculation of matching coefficients which were used to sort the cultures into groups. The results suggest a need for species consolidation; for example, Propionibacterium shermanii could appropriately become P. freudenreichii var. shermanii. Close resemblances were found between P. rubrum, P. peterssonii, and P. jensenii. Propionibacterium arabinosum and P. pentosaceum formed another mutually similar group. Further studies using additional cultural, physiological, serological, genetic, and phage host-range characteristics should be instituted to establish an improved classification of propionibacteria.

scholarly journals Classification of Aphasic Phenomena

1976 ◽  
Vol 3 (2) ◽  
pp. 135-139 ◽  
Author(s):  
Andrew Kertesz
Keyword(s):  
Numerical Taxonomy ◽  
Comprehensive Survey

SUMMARY:A brief but comprehensive survey of classifying aphasia reveals that most investigators describe at least four major groups, conveniently labelled Broca's, Wernicke's, anomic and global. Conduction and transcortical aphasias are less generally described and modality specific syndromes rarely, if ever, exist purely. The controversy between unifiers and splitters continues but objective numerical taxonomy may solve some of the problems of classification.

DNA base composition, nature of intracellular DNA, morphology, and classification of bacteriophages infecting Micrococcus luteus

1979 ◽  
Vol 25 (9) ◽  
pp. 1027-1035 ◽  
Author(s):  
Scott W. Compton ◽  
John A. Mayo ◽  
Melanie Ehrlich ◽  
H. W. Ackermann ◽  
Lise Tremblay ◽  
...  
Keyword(s):  
Host Range ◽  
Base Composition ◽  
Micrococcus Luteus ◽  
Gc Content ◽  
Dna Base Composition ◽  
Bacterial Virus ◽  
Double Stranded Dna ◽  
Dna Base

Ten bacteriophages infecting Micrococcus luteus have been characterized. All phages contain double-stranded DNA, of 64.3–73.5 mol% guanine plus cytosine (GC). The DNA of phage N7 has the highest GC content reported for any bacterial virus. No unusual bases have been found. The intracellular replicating DNAs of six phages are covalently closed circular molecules. All 10 phages have isometric, probably icosahedral, heads and long, flexible, noncontractile tails and can be sorted into two morphological groups based on size and presence or absence of a collar. Host-range studies indicate six host-range groups.

scholarly journals Floral morphology resolves the taxonomy of Camellia L. (Theaceae) Sect. Oleifera and Sect. Paracamellia

2012 ◽  
Vol 19 (2) ◽  
pp. 155-165 ◽  
Author(s):  
W. Jiang ◽  
M. Nitin ◽  
B. Jiang ◽  
Y. P. Zheng ◽  
S. S. Hong ◽  
...  
Keyword(s):  
Numerical Taxonomy ◽  
Floral Morphology ◽  
Cladistic Analysis ◽  
Floral Organ ◽  
Morphological Characters ◽  
Species Classification ◽  
Plant Taxon

Numerical taxonomy and cladistic analysis of 19 species of Camellia L. were performed using floral morphology containing continuous and discrete units. The current study mostly supports the classifications of 19 species as proposed in previous works. In addition, it also agrees with combining the following species together: C. oleifera and C. vietnamensis; C. sasanqua and C. hiemalis; C. brevistyla and C. puniceiflora; and C. grijsii and C. shensiensis. Further, we propose that C. maliflora be recognized as a variety of C. sasanqua, and C. phaeoclada is best placed in sect. Paracamellia. Moreover, we conclude that these species can be combined: C. tenii and C. miyagii; and C. confusa and C. fluviatilis. Our study indicates that the numerical taxonomy and cladistic analysis based on morphological characters of floral organ is useful in species classification, and this technique appreciated in sect. Oleifera and sect. Paracamellia can be used for identification and classification of other taxa. DOI: http://dx.doi.org/10.3329/bjpt.v19i2.13130 Bangladesh J. Plant Taxon. 19(2): 155-165, 2012 (December)

scholarly journals Classification of Lytic Bacteriophages Attacking Dairy Leuconostoc Starter Strains

2013 ◽  
Vol 79 (12) ◽  
pp. 3628-3636 ◽  
Author(s):  
Yahya Ali ◽  
Witold Kot ◽  
Zeynep Atamer ◽  
Jörg Hinrichs ◽  
Finn K. Vogensen ◽  
...  
Keyword(s):  
Host Range ◽  
Detection System ◽  
Structural Genes ◽  
Phage Group ◽  
Content Type ◽  
Phage Types ◽  
Species Specific ◽  
Leuconostoc Pseudomesenteroides ◽  
Different Sources

ABSTRACTA set of 83 lytic dairy bacteriophages (phages) infecting flavor-producing mesophilic starter strains of theLeuconostocgenus was characterized, and the first in-depth taxonomic scheme was established for this phage group. Phages were obtained from different sources, i.e., from dairy samples originating from 11 German dairies (50Leuconostoc pseudomesenteroides[Ln. pseudomesenteroides] phages, 4Ln. mesenteroidesphages) and from 3 external phage collections (17Ln. pseudomesenteroidesphages, 12Ln. mesenteroidesphages). All phages belonged to theSiphoviridaefamily of phages with isometric heads (diameter, 55 nm) and noncontractile tails (length, 140 nm). With the exception of one phage (i.e., phage ΦLN25), allLn. mesenteroidesphages lysed the same host strains and revealed characteristic globular baseplate appendages. Phage ΦLN25, with different Y-shaped appendages, had a unique host range. Apart from two phages (i.e., phages P792 and P793), allLn. pseudomesenteroidesphages shared the same host range and had plain baseplates without distinguishable appendages. They were further characterized by the presence or absence of a collar below the phage head or by unique tails with straight striations. Phages P792 and P793 with characteristic fluffy baseplate appendages could propagate only on other specific hosts. AllLn. mesenteroidesand allLn. pseudomesenteroidesphages were members of two (host species-specific) distinct genotypes but shared a limited conserved DNA region specifying their structural genes. A PCR detection system was established and was shown to be reliable for the detection of allLeuconostocphage types.

scholarly journals PELATIHAN TAKSONOMI NUMERIK SEBAGAI STRATEGI UNTUK MENINGKATKAN TECHNOLOGICAL PEDAGOGICAL CONTENT KNOWLEDGE GURU BIOLOGI

2020 ◽  
Vol 7 (2) ◽  
pp. 64-78
Author(s):  
Amalianneisha Rafadewi Andhanatami Putri ◽  
Topik Hidayat ◽  
Widi Purwianingsih
Keyword(s):  
Learning Strategies ◽  
Numerical Taxonomy ◽  
Biology Teachers ◽  
Average Percentage ◽  
Technology And Learning ◽  
Living Things ◽  
Significant Difference ◽  
Before And After ◽  
Post Test

TPACK is the ability to integrate knowledges of content, pedagogical, and technology that must be possessed by teachers in facing the era of education in the 21st century. To improve TPACK can be done with training strategies, in this study numerical taxonomy training is a training program for biology teachers about TPACK and CoRes, and content which is related to concepts, technology, and learning strategies for classification of living things that discuss about numerical taxonomy, as a strategy to improve TPACK biology teachers in classifying living things learning. The method used was pre-experimental one group pre-post test design. The data about teachers’ TPACK was gained from CoReS and lesson plans prepared by teachers, and teachers’ prespective on TPACK was gained from responses toward questionnaires. The result showed after training,  analysis of CoRes reveals that 80% of Biology teachers’ is on the Growing TPACK, and 20% is on the Pre TPACK category. The average percentage of N-gain TPACK ability of teachers is 60% in the medium category, the result of significant test (t test) indicates t score t table (16.88 2.13), it showed a significant difference in the TPACK ability of biology teachers before and after numerical taxonomy training. Teachers’ prespective on TPACK in classification of living things learning have a positive changes, teachers starts to be able to determine the technology, strategy, and understanding the content of living things learning especially the numerical taxonomy. It can be concluded that numerical taxonomy training can improve TPACK’s ability.

A classification of marine microorganisms by numerical taxonomy

1968 ◽  
Vol 2 (1-2) ◽  
Author(s):  
Frank M�ller ◽  
Corrado Peroni
Keyword(s):  
Numerical Taxonomy ◽  
Marine Microorganisms

Numerical Taxonomy Applied to Leonhard’s Classification of Endogenous Psychoses

1997 ◽  
Vol 30 (5) ◽  
pp. 291-297 ◽  
Author(s):  
Gabriela Meda ◽  
Gabriela Martinez ◽  
Eduardo Morgante
Keyword(s):  
Numerical Taxonomy ◽  
Endogenous Psychoses

scholarly journals The classification of bacteriophages lysing staphylococci

1956 ◽  
Vol 54 (2) ◽  
pp. 213-226 ◽  
Author(s):  
Joan E. Rippon
Keyword(s):  
Host Range ◽  
Coagulase Negative Staphylococci ◽  
Serological Group ◽  
Wide Host Range ◽  
Coagulase Positive Staphylococci

Staphylococcal phages may be divided into three broad divisions:(1) Phages lysing coagulase-positive staphylococci with a restricted host range. Phages in this division may be further divided into five lytic groups I, II, III, IV and Miscellaneous.(2) ‘Polyvalent’ phages; phages with a wide host range among coagulase-positive cocci, and sometimes also active on coagulase-negative strains.(3) Phages lysing only coagulase-negative staphylococci.Within each division the phages can be further grouped by their serological reactions. Nine serological groups have been defined. Phages of any single serological group also share other characteristics, e.g. stability, and the ability to form lysogenic systems.

scholarly journals The taxonomy, host range and pathogenicity of coronaviruses and other viruses in the Nidovirales order

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Zhijian Zhou ◽  
Ye Qiu ◽  
Xingyi Ge
Keyword(s):  
Host Range ◽  
Viral Genome ◽  
Viral Disease ◽  
Research Progress ◽  
New Classification ◽  
Highly Pathogenic ◽  
Natural Hosts ◽  
Genome Analyses

AbstractThe frequent emergence of coronavirus (CoV) epidemics has seriously threatened public health and stock farming. The major hosts for CoVs are birds and mammals. Although most CoVs inhabit their specific natural hosts, some may occasionally cross the host barrier to infect livestock and even people, causing a variety of diseases. Since the beginning of the new century, increasing attention has been given to research on CoVs due to the emergence of highly pathogenic and genetically diverse CoVs that have caused several epidemics, including the recent COVID-19 pandemic. CoVs belong to the Coronaviridae family of the Nidovirales order. Recently, advanced techniques for viral detection and viral genome analyses have enabled characterization of many new nidoviruses than ever and have greatly expanded the Nidovirales order with new classification and nomenclature. Here, we first provide an overview of the latest research progress in the classification of the Nidovirales order and then introduce the host range, genetic variation, genomic pattern and pathogenic features of epidemic CoVs and other epidemic viruses. This information will promote understanding of the phylogenetic relationship and infectious transmission of various pathogenic nidoviruses, including epidemic CoVs, which will benefit virological research and viral disease control.

A Simple Technique for the Detection and Classification of Latent Avian RNA Tumor Viruses

1972 ◽  
Vol 27 (3) ◽  
pp. 223-226 ◽  
Author(s):  
Thomas Graf
Keyword(s):  
Host Range ◽  
Simple Technique ◽  
Tumor Viruses ◽  
Phenotypic Mixing ◽  
Rna Tumor Viruses

A rapid and simple technique for the detection of latent RNA tumor viruses has been described. It is based on phenotypic mixing between the latent agent (s) and a nondefective strain of RSV used as indicator virus. Most of the embryos from two different chicken lines tested so far contain such agents. According to their host range and serological properties they belong to subgroup E. The phenotypic mixing assay may also be applied for the titration of nontransforming viruses in general.

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