Mixture Dilution on a Natural Gas SI Engine Operating at Low Load

V článku je prezentován výsledek experimentálního průzkumu spalování zředěné směsi zemního plynu se vzduchem při nízkém zatížení zážehového motoru. Zředění směsi vzduchem a recirkulujícími spalinami bylo porovnáno s provozem na stechiometrickou směs. Byla provedená detailní termodynamická analýza záznamu průběhu tlaku ve válci a byl vyhodnocen a analyzován průběh hoření. Výsledky naznačují potenciál ke zlepšení účinnosti motoru a současně možnost významného snížení emise NOX v surových spalinách v porovnání se spalováním homogenní stechiometrické směsi

Uncovering Microbial Composition in Human Breast Cancer Primary Tumour Tissue Using Transcriptomic RNA-seq

Recent research studies are showing breast tissues as a place where various species of microorganisms can thrive and cannot be considered sterile, as previously thought. We analysed the microbial composition of primary tumour tissue and normal breast tissue and found differences between them and between multiple breast cancer phenotypes. We sequenced the transcriptome of breast tumours and normal tissues (from cancer-free women) of 23 individuals from Slovakia and used bioinformatics tools to uncover differences in the microbial composition of tissues. To analyse our RNA-seq data (rRNA depleted), we used and tested Kraken2 and Metaphlan3 tools. Kraken2 has shown higher reliability for our data. Additionally, we analysed 91 samples obtained from SRA database, originated in China and submitted by Sichuan University. In breast tissue, the most enriched group were Proteobacteria, then Firmicutes and Actinobacteria for both datasets, in Slovak samples also Bacteroides, while in Chinese samples Cyanobacteria were more frequent. We have observed changes in the microbiome between cancerous and healthy tissues and also different phenotypes of diseases, based on the presence of circulating tumour cells and few other markers

Validation of a novel automatic deposition of bacteria and yeasts on MALDI target for MALDI-TOF MS-based identification using MALDI Colonyst robot

<div><p>Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) -based identification of bacteria and fungi significantly changed the diagnostic process in clinical microbiology. We describe here a novel technique for bacterial and yeast deposition on MALDI target using an automated workflow resulting in an increase of the microbes’ score of MALDI identification. We also provide a comparison of four different sample preparation methods. In the first step of the study, 100 Gram-negative bacteria, 100 Gram-positive bacteria, 20 anaerobic bacteria and 20 yeasts were spotted on the MALDI target using manual deposition, semi-extraction, wet deposition onto 70% formic acid and by automatic deposition using MALDI Colonyst. The lowest scores were obtained by manual toothpick spotting which significantly differ from other methods. Identification score of semi-extraction, wet deposition and automatic wet deposition did not significantly differ using calculated relative standard deviation (RSD). Nevertheless, the best results with low error rate have been observed using MALDI Colonyst robot. The second step of validation included processing of 542 clinical isolates in routine microbiological laboratory by a toothpick direct spotting, on-plate formic acid extraction (for yeasts) and automatic deposition using MALDI Colonyst. Validation in routine laboratory process showed significantly higher identification scores obtained using automated process compared with standard manual deposition in all tested microbial groups (Gram-positive, Gram-negative, anaerobes, and yeasts). As shown by our data, automatic colony deposition on MALDI target results in an increase of MALDI-TOF MS identification scores and reproducibility.</p></div

Identification score of microbes processed by four different methods of deposition on MALDI target.

<p>Identification score of microbes processed by four different methods of deposition on MALDI target.</p

Comparison of identification scores in the second stage of the study.

<p>Routine clinical samples were identified by direct spotting or semi-extraction (yeasts) and by automatic deposition using MALDI Colonyst from the same culture.</p

Comparison of different deposition methods with plotted RSD.

<p>Statistically significant differences are indicated by asterisks.</p

Repeatibility of automatic bacterial deposition using MALDI Colonyst determined by standard deviation (SD) and relative standard deviation (RSD%).

<p>Each strain was spotted ten times from the same culture plate and identified using MALDI-TOF MS.</p