scholarly journals The use of bacteriophages for differentiating plasmids ofPseudomonas aeruginosa

1974 ◽  
Vol 23 (3) ◽  
pp. 327-334 ◽  
Author(s):  
V. Krishnapillai
Keyword(s):  
Antibiotic Resistance ◽  
Geographical Origin ◽  
Original Strain ◽  
Sex Factors ◽  
Phenotypic Characteristics ◽  
Host Chromosome ◽  
Geographical Regions ◽  
R Factors ◽  
Isogenic Strains

SUMMARYSix bacteriophages have been used in the classification of 19 plasmids (antibiotic resistance-mediating R factors and FP sex factors which promote host chromosome transfer) ofP. aeruginosaisolated in different geographical regions. On the basis of phage-plating responses on isogenic strains of bacteria differing only in the plasmids carried, five groups of plasmids were distinguishable. In general the groups could be correlated with their geographical origin although differences between plasmids from the same region were found. The unique phage-plating responses were also useful in establishing the possible identity of plasmids isolated from the same original strain and given different designations by independent investigators. The classification of the plasmids derived here on the basis of phage-plating responses could be correlated with classifications based upon other phenotypic characteristics described elsewhere. The nature of inhibition of plating of phages B39 and G101 by R18–1 and R18–3 respectively was shown to be due to interference with some aspect of intra-cellular phage replication rather than to plasmid-mediated restriction.

scholarly journals Geographical Differentiation of Hom Mali Rice Cultivated in Different Regions of Thailand Using FTIR-ATR and NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 1951
Author(s):  
Wannee Srinuttrakul ◽  
Alina Mihailova ◽  
Marivil D. Islam ◽  
Beatrix Liebisch ◽  
Florence Maxwell ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Spectral Data ◽  
Geographical Origin ◽  
Nir Spectroscopy ◽  
Screening Tools ◽  
Correct Classification ◽  
Orthogonal Projections ◽  
Test Dataset ◽  
Geographical Regions

Although Hom Mali rice is considered the highest quality rice in Thailand, it is susceptible to adulteration and substitution. There is a need for rapid, low-cost and efficient analytical techniques for monitoring the authenticity and geographical origin of Thai Hom Mali rice. In this study, two infrared spectroscopy techniques, Fourier-transform infrared spectroscopy with attenuated total reflection (FTIR-ATR) and near-infrared (NIR) spectroscopy, were applied and compared for the differentiation of Thai Hom Mali rice from two geographical regions over two production years. The Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) model, built using spectral data from the benchtop FTIR-ATR, achieved 96.97% and 100% correct classification of the test dataset for each of the production years, respectively. The OPLS-DA model, built using spectral data from the portable handheld NIR, achieved 84.85% and 86.96% correct classification of the test dataset for each of the production years, respectively. Direct NIR analysis of the polished rice grains (i.e., no sample preparation) was determined as reliable for analysis of ground rice samples. FTIR-ATR and NIR spectroscopic analysis both have significant potential as screening tools for the rapid detection of fraud issues related to the geographical origin of Thai Hom Mali rice.

scholarly journals Verifying the Geographical Origin and Authenticity of Greek Olive Oils by Means of Optical Spectroscopy and Multivariate Analysis

Molecules ◽  
2020 ◽  
Vol 25 (18) ◽  
pp. 4180
Author(s):  
Renate Kontzedaki ◽  
Emmanouil Orfanakis ◽  
Georgia Sofra-Karanti ◽  
Katerina Stamataki ◽  
Aggelos Philippidis ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Optical Spectroscopy ◽  
Near Infrared ◽  
Geographical Origin ◽  
Multivariate Statistical ◽  
Olive Oils ◽  
Machine Learning Methods ◽  
Geographical Regions

Olive oil samples from three different Greek regions (Crete, Peloponnese and Lesvos) were examined by optical spectroscopy in a wide spectral region from ultraviolet to near infrared using absorption, fluorescence and Raman spectroscopies. With the aid of machine learning methods, such as multivariate partial least squares discriminant analysis, a clear classification of samples originating from the different Greek geographical regions was revealed. Moreover, samples produced in different subareas of Crete and Peloponnese were also well discriminated. Furthermore, mixtures of olive oils from different geographical origins were studied employing partial least squares as a tool to establish a model between the actual and predicted compositions of the mixtures. The results demonstrated that optical spectroscopy combined with multivariate statistical analysis can be used as an emerging innovative alternative to the classical analytical methods for the identification of the origin and authenticity of olive oils.

The Chemistry Of Antibiofilm Phytocompounds.

2020 ◽  
Vol 20 ◽  
Author(s):  
Dibyajit Lahiri ◽  
Moupriya Nag ◽  
Sayantani Garai ◽  
Rina Rani Ray
Keyword(s):  
Antimicrobial Activity ◽  
Antibiotic Resistance ◽  
Antibiotic Therapy ◽  
Antimicrobial Agents ◽  
Chemical Nature ◽  
Rapid Development ◽  
Wide Spread ◽  
Chronic Infections ◽  
Therapeutic Uses

: Phytocompounds are long known for their therapeutic uses due to their competence as antimicrobial agents. The antimicrobial activity of these bioactive compounds manifests their ability as an antibiofilm agent and is thereby proved to be competent to treat the wide spread of biofilm-associated chronic infections. Rapid development of antibiotic resistance in bacteria has made the treatment of these infections almost impossible by conventional antibiotic therapy, which forced in the switch over to the use of phytocompounds. The present overview deals with the classification of the huge array of phytocompounds according to their chemical nature, detection of their target pathogen, and elucidation of their mode of action.

scholarly journals Relationships of Hydrological Seasons in Rivers and Groundwaters in Selected Catchments in Poland

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 250
Author(s):  
Przemysław Tomalski ◽  
Edmund Tomaszewski ◽  
Dariusz Wrzesiński ◽  
Leszek Sobkowiak
Keyword(s):  
River Flow ◽  
Geographical Location ◽  
Base Flow ◽  
Water Shortages ◽  
Groundwater Levels ◽  
Average Value ◽  
Geographical Regions ◽  
New Variables ◽  
Mixed Types

The study applied the method of hydrological season identification in a time series of river total and base flows and in groundwater levels. The analysis covered a series of daily measurements from the period 2008–2017 in nine catchments located in different geographical regions of Poland. The basis of the classification of hydrological seasons, previously applied for river discharges only, was the transformation of the original variables into a series reflecting three statistical features estimated for single-name days of a year from a multiyear: average value, variation coefficient, and autocorrelation coefficient. New variables were standardized and after hierarchical clustering, every day of a year had a defined type, valorizing three features which refer to quantity, variability, and the stochastic nature of total and base river flow as well as groundwater stage. Finally, sequences of days were grouped into basic (homogenous) seasons of different types and transitional seasons including mixed types of days. Analysis indicated determinants of types, length, and frequency of identified hydrological seasons especially related to river regime, hydrogeological and hydrometeorological conditions as well as physiographical background were directly influenced by geographical location. Analysis of the co-occurrence of the same types of hydrological seasons allowed, in some catchments, periods of synchronic alimentation (groundwater and base flow, mainly in the cold half-year) and water shortages (all three components, mainly in the warm half-year) to be identified.

scholarly journals Chromosome transfer inPseudomonas aeruginosamediated by R factors

1971 ◽  
Vol 17 (2) ◽  
pp. 169-172 ◽  
Author(s):  
Vilma A. Stanisich ◽  
B. W. Holloway
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Specific Resistance ◽  
Host Chromosome ◽  
Chromosome Transfer ◽  
R Factors

SUMMARYR factors present inPseudomonas aeruginosastrains of clinical origin can be transferred to other strains ofP. aeruginosaand may act to promote host chromosome transfer. In general, their properties are similar to those R factors in Enterobacteria. The different R factors studied vary with respect to transferability, transfer of specific resistance properties, repressibility, and ability to promote chromosome transfer.

scholarly journals Estimativa da erosividade da chuva por diferentes métodos e seu impacto na equação universal de perdas de solo, no semiárido pernambucano (Estimation of erosivity by different methods and their impact on the universal soil loss equation in Pernambuco semi-arid)

2019 ◽  
Vol 12 (3) ◽  
pp. 859
Author(s):  
Joaquim Pedro de Santana Xavier ◽  
Alexandre Hugo Cezar Barros ◽  
Daniel Chaves Webber ◽  
Luciano José de Oliveira Accioly ◽  
Flávio Adriano Marques ◽  
...  
Keyword(s):  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
R Factor ◽  
Semi Arid Region ◽  
Erosion Loss ◽  
R Factors ◽  
Semi Arid ◽  
Soil Loss Equation

Dentre os diversos métodos indiretos para estimar as perdas de solo por erosão, a Equação Universal de Perdas de Solo (EUPS) é a mais utilizada devido a sua robustez e por ser constituída de uma simples estrutura fatorial, que integra fatores naturais e antrópicos atuantes na perda de solos. A erosão é um dos fenômenos mais danosos ao solo e às atividades humanas e por isso seu estudo é importante. Para o cálculo das perdas de solo por meio da EUPS, a avaliação da erosividade das chuvas (fator R) é essencial, pois estima o fenômeno produzido pelas chuvas. O objetivo deste trabalho foi avaliar três metodologias disponíveis de obtenção da erosividade das chuvas para a região do semiárido pernambucano, avaliando sua influência nos resultados da EUPS. Os três modelos selecionados para estimar o Fator R foram desenvolvidos por Wischmeier e Smith (mais conhecido e utilizado), por Silva que estimou valores para diversas regiões do País e por Cantalice e outros que trabalharam especificamente para cada região climática do estado de Pernambuco. Os resultados indicam que as metodologias de Wischmeier e Smith e Silva obtiveram resultados de erosividade da chuva semelhantes, tendo Silva alcançado valores maiores. Cantalice e outros obtiveram os resultados mais baixos. Os resultados da EUPS indicam que, quantitativamente, os diferentes fatores R geram grande diferença nas perdas de solo, porém, qualitativamente chegam a resultados semelhantes na classificação de áreas de maior erosão, de acordo com a FAO. Logo, as três metodologias são viáveis na identificação de áreas prioritárias para a mitigação da erosão.   A B S T R A C TAmong several indirect methods to estimate soil erosion loss, the Universal Soil Loss Equation (EUPS) is the most used due to its robustness and because it is constituted of a simple factorial structure that integrates natural and anthropic factors which act in the loss of soils. Erosion is one of the most damaging phenomena to the soil and the human activities, evidencing the importance of studying it. The evaluation of rainfall erosivity (R factor) is essential for the calculation of soil loss through the EUPS, since it is possible to estimate how significant rainfall is to the occurrence of this phenomenon. The objective of this work was to evaluate three methodologies to obtain the rainfall erosivity available for the semi - arid region of Pernambuco, evaluating its influence on the results of the EUPS. The three models used to estimate the R-factor were developed by Wischmeier and Smith, the best known and used model, Silva who estimated values for several regions of the country and Cantalice and others who worked specifically for each climatic region of the state of Pernambuco. As a result, very similar results of rainfall erosivity were obtained between Wischmeier and Smith´s and Silva´s methodology, with Silva reaching higher values of energy amplitude, while Cantalice and others obtained the lowest results. The results of EUPS indicate that, quantitatively, the different R factors generate a large difference in soil loss, but qualitatively they reach similar results in the classification of areas where erosion are greater, according to the FAO. Therefore, the three methodologies are feasible in the identification of priority areas for erosion mitigation.Keywords: soil, rainfall erosivity, USLE, GIS

scholarly journals Classification of the geographical origin of argan kernels by infrared spectroscopy and chemometrics

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Abdelkhalek Oussama ◽  
Fatiha Elabadi ◽  
Noureddine Barka ◽  
Fatima Mahjoubi ◽  
Fouzia Kzaiber
Keyword(s):  
Infrared Spectroscopy ◽  
Geographical Origin

scholarly journals Linear discriminant analysis based on gas chromatographic measurements for geographical prediction of USA medical domestic cannabis

2020 ◽  
Author(s):  
Ramia Z. Al Bakain ◽  
Yahya S. Al-Degs ◽  
James V. Cizdziel ◽  
Mahmoud A. Elsohly
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Principal Components ◽  
Supervised Classification ◽  
Geographical Origin ◽  
Active Components ◽  
Linear Discriminant ◽  
Sample Extraction ◽  
Analytical Range

AbstractFifty four domestically produced cannabis samples obtained from different USA states were quantitatively assayed by GC–FID to detect 22 active components: 15 terpenoids and 7 cannabinoids. The profiles of the selected compounds were used as inputs for samples grouping to their geographical origins and for building a geographical prediction model using Linear Discriminant Analysis. The proposed sample extraction and chromatographic separation was satisfactory to select 22 active ingredients with a wide analytical range between 5.0 and 1,000 µg/mL. Analysis of GC-profiles by Principle Component Analysis retained three significant variables for grouping job (Δ9-THC, CBN, and CBC) and the modest discrimination of samples based on their geographical origin was reported. PCA was able to separate many samples of Oregon and Vermont while a mixed classification was observed for the rest of samples. By using LDA as a supervised classification method, excellent separation of cannabis samples was attained leading to a classification of new samples not being included in the model. Using two principal components and LDA with GC–FID profiles correctly predict the geographical of 100% Washington cannabis, 86% of both Oregon and Vermont samples, and finally, 71% of Ohio samples.

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