A genre analysis of reprint request emails written by EFL and physics professionals

The present study aimed to analyze reprint request e-mail messages written by postgraduates (MA students) of two fields of study, namely Physics and EFL, to realize the differences and similarities between the two email types. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing<br /

Correlation between biofilm formation and antibiotic resistance in pseudomonas aeruginosa: A meta-analysis

Biofilm formation is one of the important resistance mechanisms in Pseudomonas aeruginosa. This study aimed to consider the correlation between biofilm formation and antibiotic resistance in Pseudomonas aeruginosa through a systematic review and meta-analysis. This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) strategies. Scientific databases were searched by MeSH terms and keywords such as �Pseudomonas aeruginosa�, �biofilm formation�, �antibiotic resistance�, �prevalence� AND �Iran�, to obtain articles published from 1st January 2016 to 30th November 2019. Studies recording biofilm formation and antibiotic resistance in P. aeruginosa recovered from clinical samples of Iranian patients were included. Data analysis was performed using CMA software. The combined biofilm formation rate was reported as 87.6 (95 CI: 80-92.5). The heterogeneity index among the selected articles was Q2=96.5, I2=85.5, and t=0.26 (p=0.16). The pooled occurrences of strong, moderate and weak biofilms were 47.7 (95 CI: 28.7-67.3), 30.2 (95 CI: 19.4-43.8), and 27.4 (95 CI: 8.8-59.8), respectively. The pooled prevalence of MDR P. aeruginosa strains was as follows: 62.5 (95 CI: 40-77.2). The highest combined rates of antibiotic resistance were against ceftriaxone and tobramycin with the rates of 79.2.9 (95 CI: 54.2-96.2) and 64.4 (95 CI: 36.3-92), respectively. Also, the lowermost antibiotic resistance rates were against colistin and polymyxin B, with the prevalence of 2.1 (95 CI: 0.2-18.1), and 3 (95 CI: 0.5-17.3), respectively. More than half of the studies included in the present review showed a significant correlation between biofilm formation and antibiotic resistance pattern. © 2020, EDIMES Edizioni Medico Scientifiche. All rights reserved

Genome-wide gene expression changes of Pseudomonas veronii 1YdBTEX2 during bioaugmentation in polluted soils.

Bioaugmentation aims to use the capacities of specific bacterial strains inoculated into sites to enhance pollutant biodegradation. Bioaugmentation results have been mixed, which has been attributed to poor inoculant growth and survival in the field, and, consequently, moderate catalytic performance. However, our understanding of biodegradation activity mostly comes from experiments conducted under laboratory conditions, and the processes occurring during adaptation and invasion of inoculants into complex environmental microbiomes remain poorly known. The main aim of this work was thus to study the specific and different cellular reactions of an inoculant for bioaugmentation during adaptation, growth and survival in natural clean and contaminated non-sterile soils, in order to better understand factors limiting bioaugmentation. As inoculant we focused on the monoaromatic compound-degrading bacterium Pseudomonas veronii 1YdBTEX2. The strain proliferated in all but one soil types in presence and in absence of exogenously added toluene. RNAseq and differential genome-wide gene expression analysis illustrated both a range of common soil responses such as increased nutrient scavenging and recycling, expression of defense mechanisms, as well as environment-specific reactions, notably osmoprotection and metal homeostasis. The core metabolism of P. veronii remained remarkably constant during exponential growth irrespective of the environment, with slight changes in cofactor regeneration pathways, possibly needed for balancing defense reactions. P. veronii displayed a versatile global program, enabling it to adapt to a variety of soil environments in the presence and even in absence of its target pollutant toluene. Our results thus challenge the widely perceived dogma of poor survival and growth of exogenous inoculants in complex microbial ecosystems such as soil and provide a further basis to developing successful bioaugmentation strategies

Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data.

The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flow cytometry data using a supervised machine learning algorithm of standard cell type recognition (CellCognize). As a proof-of-concept, we trained neural networks with 32 microbial cell and bead standards. The resulting classifiers were extensively validated in silico on known microbiota, showing on average 80% prediction accuracy. Furthermore, the classifiers could detect shifts in microbial communities of unknown composition upon chemical amendment, comparable to results from 16S-rRNA-amplicon analysis. CellCognize was also able to quantify population growth and estimate total community biomass productivity, providing estimates similar to those from &lt;sup&gt;14&lt;/sup&gt; C-substrate incorporation. CellCognize complements current sequencing-based methods by enabling rapid routine cell diversity analysis. The pipeline is suitable to optimize cell recognition for recurring microbiota types, such as in human health or engineered systems

Effects of enriched daphnia with microscopic algae on some growth indices and survival rate of Persian sturgeon (Acipenser persicus) larvae

Microalgae as a source of valuable compounds such as fatty acids are isolated from the natural environments and their mass production with high nutritional value is one the necessities of many hatcheries. The present study aimed to determine the effects of enriched daphnia with microscopic algae on some growth indices and survival rate of Persian sturgeon (Acipenser persicus) larvae. Chlorella vulgaris and Scenedesmus dimorphus were purified and cultured. Then, Daphnia longispina was fed microalgae including Chlorella vulgaris and Scenedesmus dimorphus enriched with Docosahexaenoic acid (DHA). The microalgae density to enrich daphnia was estimated at 5× 107 cells mL-1. Three treatments with three replicates and a control group were considered in this study. A total of 30 Acipenser persicus larvae were allocated to each sixty liters tank. Experimental fish were fed daphnia enriched with Chlorella vulgaris (treatment 1), daphnia enriched with Scenedesmus dimorphus (treatment 2) and daphnia enriched with Chlorella vulgaris and Scenedesmus dimorphus (at the rates of 50%) (treatment 3). Persian sturgeon larvae in the control group were fed like VNIRO stage from daphnia caught in pond. Larvae were fed 30% of body weight per day for four times. During the experimental period, water temperature, dissolved oxygen concentration and pH ranged between 18-24°C, 5.8-7.2 mg l-1 and 5.6-8.2, respectively. The minimum (219 ± 98.4 mg) and maximum (315.16 ± 140.8 mg) mean (±SD) weights were observed in the control group and treatment 3, respectively. The results obtained from the body weight increase (BWI %) revealed that there were significant differences between treatment 3 and other treatments. Highest (4.6±1.13% day-1) and lowest (5.5±1.24% day-1) mean (±SD) specific growth rates (SGR) were recorded in fish fed the control group and treatment 3, respectively. Lowest (68%) and highest (85%) survival rates were recorded in the control group and treatment 3, respectively

Ekstraksi Maserasi Sayur Okra (Abelmoschus esculentus L.) Sebagai BAhan Pembuatan Kapsul Ekstrak Okra

Okra (Abelmoschus esculentus L.) merupakan sayuran yang kaya akan serat α-selulosa dan hemiselulosa yang merupakan komponen anti-diabetes. Secara umum okra mempunyai manfaat pada kesehatan khususnya terhadap penderita diabetes karena sifat okra dapat mengurangi penyerapan glukosa, sehingga dapat mengurangi kadar gula darah. Di Indonesia sementara ini, cara mengonsumsi sayur okra dengan meminum rendaman irisan sayur okra atau diolah menjadi juice okra. Untuk mempermudah cara konsumsi, okra dieksrak dan dapat dikemas dalam bentuk kapsul. Pada penelitian ini ekstrak dilakukan dengan menggunakan pelarut etanol. Tahapan yang digunakan pada penelitian ini antara lain pembuatan bubuk okra yaitu mengeringkan okra dalam oven dengan suhu 110°C selama 3 jam. Selanjutnya tahap ekstraksi maeserasi dengan merendam bubuk okra kedalam etanol 75%, selama 24, 36, dan 48 jam. Setelah itu larutan ekstrak dimasukkan kedalam rotary vacuum evaporator dan dikeringkan dalam oven sehingga menghasilkan bubuk ekstrak okra. Bubuk ekstrak diuji dengan uji spektro sehingga diketahui kandungan dari bubuk okra tersebut. Dari hasil praktikum, dididapatkan yield praktikum terbesar yaitu 45% pada variabel ekstraksi buah dan biji okra selama 45 jam. Lalu yield praktikum terkecil yaitu 16,67% pada variabel buah selama 24 jam. Yield praktikum memiliki delta yang tinggi dikarenakan faktor terlalu lama membiarkan ekstrak sehingga tumbuh sedikit jamur dibeberapa variabel. Lalu dari hasil praktikum didapatkan pula hasil uji kadar flavonoid. Kadar flavonoid tertinggi yang didapatkan yaitu 1,9% pada variabel ekstraksi buah dan biji okra selama 36 jam. Lalu kadar flavonoid terendah didapatkan yaitu 0% pada variabel ekstraksi buah selama 24 jam. Delta yang tinggi ini dikarenakan faktor terlalu lama membiarkan ekstrak sehingga tumbuh jamur dibeberapa variabel. ================================================================================== Okra (Abelmoschus esculentus L.) is a vegetable rich in α-cellulose, hemicellulose and flavonoids, which is an anti-diabetic component. In general, okra has health benefits, especially for diabetics because the nature of okra can reduce the absorption of glucose, so as to reduce blood sugar levels. In Indonesia in the meantime, how to consume okra vegetables by drinking marinated slices of okra vegetables or processed into juice okra. To simplify the way of consumption, okra is executed and can be packed in capsule form. In this study the extract was done by using ethanol solvent. Stages used in this research include the manufacture of okra powder that is drying okra in the oven with a temperature of 110 ° C for 3 hours. Furthermore, the maeserasi extraction step by soaking the okra powder into 75% ethanol, for 24, 36, and 48 hours. Afterwards the extract solution is introduced into the rotary vacuum evaporator and dried in the oven to produce the okra extract powder. The extract powder was tested with a spectro test so that it was known that the powder of the okra. From the results of the lab, the highest practicum yield obtained was 45% in the extraction variables of fruit and okra seeds for 45 hours. Then the smallest laboratory yield of 16.67% in fruit variables for 24 hours. The practicum yield has a high delta due to the factor of allowing too long the extract to grow slightly mushrooms in some variables. Then from the lab results also obtained the test results of flavonoid levels. The highest levels of flavonoids obtained were 1.9% in the extraction variables of fruit and okra seeds for 36 hours. Then the lowest flavonoid level obtained 0% on fruit extraction variables for 24 hours. The high delta is due to the factor too long to let the extract grow mushrooms in some variables

Environmental evaluation and employee's exposure of a thermal power plant with extremely low frequency magnetic fields

Background and aims: Extremely low frequency magnetic field (ELF) is a Spectrum of electromagnetic waves with the range of 30 to 300 Hz. The average magnetic field exposures in the workplace have been found to be higher in "electrical occupations" compared to the other occupations such as office work. The interaction between magnetic fields produced by power lines and substations with living organisms are not fully understood and still open to many researchers. Methods: The three axes TES-1394 was used for magnetic field measurement. Magnetic field measurement conducted based on the IEEE std 644-1994 standard. Firstly all magnetic field sources were detected, then the measuring stations were determined nearby and around the source. The occupational groups with exposure to magnetic field were identified to determine the maximum exposure level and then to compare with ISIRI 8567 national standard. Results: The minimum and maximum measured magnetic field were in near of 63 Kv lines (1.03 μT) and generators (17.6 μT), respectively. The mean of magnetic flux density nearby the generators building source was significantly different from the other sources. The environmental amount of magnetic flux density in 230 Kv (1.58 μT) post was higher than the other environments. Maximum exposure (17.6 μT) of occupational groups was related to engineer's of generators building. Conclusion: Our results of the magnetic flux density measurement close to sources matched with the other relevant studies except for control room. The maximum exposure level of the occupational groups was not higher than the occupational exposure standard value

Meta-Analysis of Biofilm Formation, Antibiotic Resistance Pattern, and Biofilm-Related Genes in Pseudomonas aeruginosa Isolated from Clinical Samples

Resistant microorganisms such as Pseudomonas aeruginosa grow by developing biofilms in hospitals. We aimed to investigate the biofilm formation and the frequencies of biofilm-related genes and their associations with antibiotic resistance pattern in P. aeruginosa isolated from Iranians' clinical samples. This review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We conducted a systematic literature search in scientific databases using medical subject heading terms, including "Pseudomonas aeruginosa,""biofilm formation,""biofilm-related genes,""antibiotic resistance,"and "prevalence,"to obtain related articles published from 1st January, 2000, to 30th March, 2019. The studies reporting the prevalence of biofilm formation, the frequencies of biofilm-related genes, and the antibiotic resistance pattern in P. aeruginosa retrieved from Iranian patients were included. Meta-analysis was performed using the Comprehensive Meta-Analysis software. The pooled rate of biofilm formation was calculated as 86.5 (95 confidence interval CI: 79-91.6). The combined frequencies of strong, moderate, and weak biofilms were 51% (95% CI: 37.4-64.4), 29.2% (95% CI: 20.9-39.1), and 25.4% (95% CI: 11.5-47.2), respectively. The pooled prevalence of laslR, algD, algU, ppyR, and pelF genes were 93.6% (95% CI: 88.1-96.6), 91.4% (95% CI: 80.8-96.4), 89.3% (95% CI: 85.2-92.3), 98.7% (95% CI: 96.5-99.6), and 93% (95% CI: 82.7-97.3), respectively. The highest combined antibiotic resistance rates of P. aeruginosa isolates were against piperacillin/tazobactam (90%). This study showed that biofilm formation was higher in multidrug-resistant (MDR) P. aeruginosa than non-MDRs. A significant correlation was observed between biofilm formation and antibiotic resistance in 50% of studies included in this review. © Copyright 2020, Mary Ann Liebert, Inc., publishers 2020

Mechanistic insights into bacterial metabolic reprogramming from omics-integrated genome-scale models.

Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems