Immunogold Nanoparticles for Rapid Plasmonic Detection of C. sakazakii.

Cronobacter sakazakii is a foodborne pathogen that can cause a rare, septicemia, life-threatening meningitis, and necrotizing enterocolitis in infants. In general, standard methods for pathogen detection rely on culture, plating, colony counting and polymerase chain reaction DNA-sequencing for identification, which are time, equipment and skill demanding. Recently, nanoparticle- and surface-based immunoassays have increasingly been explored for pathogen detection. We investigate the functionalization of gold nanoparticles optimized for irreversible and specific binding to C. sakazakii and their use for spectroscopic detection of the pathogen. We demonstrate how 40-nm gold nanoparticles grafted with a poly(ethylene glycol) brush and functionalized with polyclonal antibodies raised against C. sakazakii can be used to specifically target C. sakazakii. The strong extinction peak of the Au nanoparticle plasmon polariton resonance in the optical range is used as a label for detection of the pathogens. Individual binding of the nanoparticles to the C. sakazakii surface is also verified by transmission electron microscopy. We show that a high degree of surface functionalization with anti-C. sakazakii optimizes the detection and leads to a detection limit as low as 10 CFU/mL within 2 h using a simple cuvette-based UV-Vis spectrometric readout that has great potential for further optimization.

Immediate lymphatic reconstruction: Lessons learned over eight years.

Immediate lymphatic reconstruction (ILR) is recognized as a surgical approach used to reduce the risk of developing secondary lymphedema, and evidence demonstrating the efficacy of ILR is favorable. Our Lymphatic Center has become a centralized location offering ILR for the risk-reduction in breast cancer-related lymphedema (BCRL) in New England. Over the course of our experience, we made several modifications and adapted our approach to enhance the operative success of this procedure. These include advancements in our use of indocyanine green (ICG) imaging to identify baseline lymphatic anatomical variation, utilization of fluorescein isothiocyanate for lymphatic vessel visualization, application of the lymphosome concept to guide arm injection sites, verification of anastomotic patency (using ICG), localization of reconstruction to guide radiation therapy, incorporation of intraoperative tools to facilitate better anatomic visualization of the axilla, and addition of a lower extremity vein graft to mitigate venous-related complications. Collecting information from each surgery in a standardized manner, including intraoperative lymphatic channel measurements, and deploying clips for possible future radiation exposure, enables future studies on ILR patient outcomes. In this contribution, we aimed to share our institutional modifications with the surgical community to facilitate further adoption, conversation, and advancement of ILR for the risk-reduction in BCRL.

Whole Genome Sequencing-Based Comparison of Food Isolates of Cronobacter sakazakii.

Cronobacter sakazakii is an emerging foodborne pathogen, which is linked to life-threatening infections causing septicemia, meningitis, and necrotizing enterocolitis. These infections have been epidemiologically connected to ingestion of contaminated reconstituted powder infant formula. Even at low water activity C. sakazakii can survive for a long time; it is capable of protective biofilm formation and occasionally shows high virulence and pathogenicity even following stressful environmental conditions. Hence it is a challenging task for the food industry to control contamination of food ingredients and products through the entire production chain, since an increasing number of severe food-related outbreaks of C. sakazakii infections has been observed. The seemingly great capability of C. sakazakii to survive even strict countermeasures combined with its prevalence in many food ingredients requires a greater in depth understanding of its virulence factors to master the food safety issues related to this organism. In this context, we present the whole genome sequence (WGS) of two different C. sakazakii isolated from skimmed milk powder (C7) and ready-to-eat salad mix (C8), respectively. These are compared to other, already sequenced, C. sakazakii genomes. Sequencing of the fusA allele revealed that both isolates were C. sakazakii. We investigated the molecular characteristics of both isolates relevant for genes associated with pathogenesis and virulence factors, resistance to stressful environmental conditions (e.g., osmotic and heat), survival in desiccation as well as conducted a comparative genomic analysis. By using multi-locus sequence typing (MLST), the genetic type of both isolates is assessed and the number of unique genes is determined. DNA of C. sakazakii C8 is shown to hold a novel and unique sequence type; the number of unique genes identified in the genomic sequence of C. sakazakii C7 and C8 were 109 and 188, respectively. Some of the determined unique genes such as the rhs and VgrG genes are linked to the Type VI Secretion System cluster, which is associated with pathogenicity and virulence factors. Moreover, seven genes encoding for multi-drug resistance were found in both isolates. The finding of a number of genes linked to producing capsules and biofilm are likely related to the observed resistance to desiccation.

Characterization of Biofilm Formation by Cronobacter spp. Isolates of Different Food Origin under Model Conditions.

Cronobacter spp. are opportunistic human pathogens that cause serious diseases in neonates and immunocompromised people. Owing to their biofilm formation on various surfaces, both their detection and their removal from production plants constitute a major challenge. In this study, food samples were randomly collected in Austria and examined for the presence of Cronobacter spp. Presumptive isolates were identified by a polyphasic approach. Five percent of the samples were positive for C. sakazakii and 2.4% for C. dublinensis. Individual growth of the isolates was characterized based on lag time, growth rate, and generation time. During an incubation period of 6 to 72 h, biofilm formation of 11 selected isolates was quantified under model conditions by a crystal violet staining assay with 96-well plates with different carbon sources (lactose, glucose, maltose, sucrose, and sodium acetate) and NaCl levels and under variable temperature and pH conditions. Biofilm formation was more pronounced at lactose concentrations between 0.25 and 3% compared with 5% lactose, which lead to thinner layers. C. sakazakii isolate C7, isolated from infant milk powder, was the strongest biofilm producer at 10 mM Mg2+ and 5 mM Mn2+, 0.5% sodium acetate, at pH levels between 7 and 9 at 37°C for 24 h. C. sakazakii strain C6 isolated from a plant air filter was identified as a moderate biofilm former and C. sakazakii strain DSM 4485, a clinical isolate, as a weak biofilm former. Based on PCR detection, genes bcsA, bcsB, and bcsG encoding for cellulose could be identified as markers for biofilm formation. Isolates carrying bcsA and bcsB showed significantly stronger biofilm formation than isolates without these genes ( P < 0.05), in strong correlation with the results obtained in the crystal violet assay. Further investigations using confocal laser scanning microscopy revealed that extracellular polymeric substances and glycocalyx secretions were the dominating components of the biofilms and that the viable fraction of bacteria in the biofilm decreased over time.

Sparse basis selection: new results and application to adaptive prediction of video source traffic.

Real-time prediction of video source traffic is an important step in many network management tasks such as dynamic bandwidth allocation and end-to-end quality-of-service (QoS) control strategies. In this paper, an adaptive prediction model for MPEG-coded traffic is developed. A novel technology is used, first developed in the signal processing community, called sparse basis selection. It is based on selecting a small subset of inputs (basis) from among a large dictionary of possible inputs. A new sparse basis selection algorithm is developed that is based on efficiently updating the input selection adaptively. When a new measurement is received, the proposed algorithm updates the selected inputs in a recursive manner. Thus, adaptability is not only in the weight adjustment, but also in the dynamic update of the inputs. The algorithm is applied to the problem of single-step-ahead prediction of MPEG-coded video source traffic, and the developed method achieves improved results, as compared to the published results in the literature. The present analysis indicates that the adaptive feature of the developed algorithm seems to add significant overall value.