Investigation of Burkholderia cepacia nosocomial outbreak with high fatality in patients suffering from diseases other than cystic fibrosis

Over a 1-y period, 26 inpatients at the Jordan University Hospital in Amman were detected with bacteraemia (23 cases) or respiratory tract colonized with B. cepacia (3 cases). A combination of genetic identification and molecular typing has proved that all cases were caused by a single epidemic strain of B. cepacia genomovar IIIa. Nosocomial infections could be documented in 21/26 (81%) patients, mostly with severe underlying or malignant diseases other than cystic fibrosis, but the source of infection was undetected. The overall mortality related to infection with B. cepacia was 42%. All B. cepacia isolates were resistant to ampicillin, amikacin, carbenicillin and gentamicin; and mostly susceptible to piperacillin, chloramphenicol, cotri-moxazole, tetracycline, ceftazidime, and tazocin (62-88%). This study demonstrates the nosocomial and high fatality of B. cepacia genomovar IIIa in Jordanian patients suffering from diseases other than cystic fibrosis

Tracking extracellular vesicle phenotypic changes enables treatment monitoring in melanoma

Monitoring targeted therapy in real time for cancer patients could provide vital information about the development of drug resistance and improve therapeutic outcomes. Extracellular vesicles (EVs) have recently emerged as a promising cancer biomarker, and EV phenotyping shows high potential for monitoring treatment responses. Here, we demonstrate the feasibility of monitoring patient treatment responses based on the plasma EV phenotypic evolution using a multiplex EV phenotype analyzer chip (EPAC). EPAC incorporates the nanomixing-enhanced microchip and the multiplex surface-enhanced Raman scattering (SERS) nanotag system for direct EV phenotyping without EV enrichment. In a preclinical model, we observe the EV phenotypic heterogeneity and different phenotypic responses to the treatment. Furthermore, we successfully detect cancer-specific EV phenotypes from melanoma patient plasma. We longitudinally monitor the EV phenotypic evolution of eight melanoma patients receiving targeted therapy and find specific EV profiles involved in the development of drug resistance, reflecting the potential of EV phenotyping for monitoring treatment responses