Versatile hybrid technique for passive straight micromixer manufacturing by combining pulsed laser ablation, stereolithographic 3D printing and computational fluid dynamics.

There is a need to develop new and versatile fabrication methods to achieve efficient mixing of fluids in microfluidic channels using microstructures. This work presents a new technique that combines stereolithography (SLA) and pulsed laser ablation (PLA) to manufacture a straight micromixer for uniform mixing of two samples. Computational fluid dynamics (CFD) simulation is performed to deeply understand the physical mechanisms of the process.

Development of a novel streamlined workflow (AACRE) and database (inCREDBle) for genomic analysis of carbapenem-resistant Enterobacterales.

In response to the threat of increasing antimicrobial resistance, we must increase the amount of available high-quality genomic data gathered on antibiotic-resistant bacteria. To this end, we developed an integrated pipeline for high-throughput long-read sequencing, assembly, annotation and analysis of bacterial isolates and used it to generate a large genomic data set of carbapenemase-producing Enterobacterales (CPE) isolates collected in Spain. The set of 461 isolates were sequenced with a combination of both Illumina and Oxford Nanopore Technologies (ONT) DNA sequencing technologies in order to provide genomic context for chromosomal loci and, most importantly, structural resolution of plasmids, important determinants for transmission of antimicrobial resistance.

Diagnostic tool for surveillance, detection and monitoring of the high-risk clone K. pneumoniae ST15.

Background: The global spread of Klebsiella pneumoniae ST15, causing multi-continental outbreaks, contributes to the movement of resistance genes between clones increasing the antimicrobial resistance crisis. The genomic traits providing it with the ability to outcompete other bacteria and cause epidemics remain unclear.

Aim: To identify the specific genomic traits of K.

Direct Detection of Carbapenemase-Producing Klebsiella pneumoniae by MALDI-TOF Analysis of Full Spectra Applying Machine Learning.

MALDI-TOF MS is considered to be an important tool for the future development of rapid microbiological techniques. We propose the application of MALDI-TOF MS as a dual technique for the identification of bacteria and the detection of resistance, with no extra hands-on procedures. We have developed a machine learning approach that uses the random forest algorithm for the direct prediction of carbapenemase-producing Klebsiella pneumoniae (CPK) isolates, based on the spectra of complete cells.