Cationized magnetoferritin enables rapid labeling and concentration of Gram-positive and Gram-negative bacteria in magnetic cell separation columns

In order to identify pathogens rapidly and reliably, bacterial capture and concentration from large sample volumes into smaller ones are often required. Magnetic labeling and capture of bacteria using a magnetic field hold great promise for achieving this goal, but the current protocols have poor capture efficiency. Here, we present a rapid and highly efficient approach to magnetic labeling and capture of both Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria using cationized magnetoferritin (cat-MF). Magnetic labeling was achieved within a 1-min incubation period with cat-MF, and 99.97% of the labeled bacteria were immobilized in commercially available magnetic cell separation (MACS) columns. Longer incubation times led to more efficient capture, with S. aureus being immobilized to a greater extent than E. coli. Finally, low numbers of magnetically labeled E. coli bacteria (<100 CFU per ml) were immobilized with 100% efficiency and concentrated 7-fold within 15 min. Therefore, our study provides a novel protocol for rapid and highly efficient magnetic labeling, capture, and concentration of both Gram-positive and Gram-negative bacteria. IMPORTANCE Antimicrobial resistance (AMR) is a significant global challenge. Rapid identification of pathogens will retard the spread of AMR by enabling targeted treatment with suitable agents and by reducing inappropriate antimicrobial use. Rapid detection methods based on microfluidic devices require that bacteria are concentrated from large volumes into much smaller ones. Concentration of bacteria is also important to detect low numbers of pathogens with confidence. Here, we demonstrate that magnetic separation columns capture small amounts of bacteria with 100% efficiency. Rapid magnetization was achieved by exposing bacteria to cationic magnetic nanoparticles, and magnetized bacteria were concentrated 7-fold inside the column. Thus, bacterial capture and concentration were achieved within 15 min. This approach could be extended to encompass the capture and concentration of specific pathogens, for example, by functionalizing magnetic nanoparticles with antibodies or small molecule probes

Ultra-fast stem cell labelling using cationised magnetoferritin

Efficient magnetic labelling of stem cells is achieved within a one minute incubation period using cationised magnetoferritin.</p

Glycosylated superparamagnetic nanoparticle gradients for osteochondral tissue engineering

In developmental biology, gradients of bioactive signals direct the formation of structural transitions in tissue that are key to physiological function. Failure to reproduce these native features in an in vitro setting can severely limit the success of bioengineered tissue constructs. In this report, we introduce a facile and rapid platform that uses magnetic field alignment of glycosylated superparamagnetic iron oxide nanoparticles, pre-loaded with growth factors, to pattern biochemical gradients into a range of biomaterial systems. Gradients of bone morphogenetic protein 2 in agarose hydrogels were used to spatially direct the osteogenesis of human mesenchymal stem cells and generate robust osteochondral tissue constructs exhibiting a clear mineral transition from bone to cartilage. Interestingly, the smooth gradients in growth factor concentration gave rise to biologically-relevant, emergent structural features, including a tidemark transition demarcating mineralized and non-mineralized tissue and an osteochondral interface rich in hypertrophic chondrocytes. This platform technology offers great versatility and provides an exciting new opportunity for overcoming a range of interfacial tissue engineering challenges

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant

B:Ionic Glove: A Soft Smart Wearable Sensory Feedback Device for Upper Limb Robotic Prostheses

Upper limb robotic prosthetic devices currently lack adequate sensory feedback, contributing to a high rejection rate. Incorporating affective sensory feedback into these devices reduces phantom limb pain and increases control and acceptance. To address the lack of sensory feedback we present the B:Ionic glove, wearable over a robotic hand which contains sensing, computation and actuation on board. It uses shape memory alloy (SMA) actuators integrated into an armband to gently squeeze the user's arm when pressure is sensed in novel electro-fluidic fingertip sensors and decoded through soft matter logic. We found that a circular electro-fluidic sensor cavity generated the most sensitive fingertip sensor and considered a computational configuration to convey different information from robot to user. A user study was conducted to characterise the tactile interaction capabilities of the device. No significant difference was found between the skin sensitivity threshold of participants' lower and upper arm. They found it easier to distinguish stimulation locations than strengths. Finally, we demonstrate a proof-of-concept of the complete device, illustrating how it could be used to grip an object, solely from the affective tactile feedback provided by the B:Ionic glove. The B:Ionic glove is a step towards the integration of natural, soft sensory feedback into robotic prosthetic devices.</p

Stretchable Piezoelectric Sensing Systems for Self-Powered and Wireless Health Monitoring

Continuous monitoring of human physiological signals is critical to managing personal healthcare by early detection of health disorders. Wearable and implantable devices are attracting growing attention as they show great potential for real-time recording of physiological conditions and body motions. Conventional piezoelectric sensors have the advantage of potentially being self-powered, but have limitations due to their intrinsic lack of stretchability. Herein, a kirigami approach to realize a novel stretchable strain sensor is introduced through a network of cut patterns in a piezoelectric thin film, exploiting the anisotropic and local bending that the patterns induce. The resulting pattern simultaneously enhances the electrical performance of the film and its stretchability while retaining the mechanical integrity of the underlying materials. The power output is enhanced from the mechano-electric piezoelectric sensing effect by introducing an intersegment, through-plane, electrode pattern. By additionally integrating wireless electronics, this sensing network could work in an entirely battery-free mode. The kirigami stretchable piezoelectric sensor is demonstrated in cardiac monitoring and wearable body tracking applications. The integrated soft, stretchable, and biocompatible sensor demonstrates excellent in vitro and ex vivo performances and provides insights for the potential use in myriad biomedical and wearable health monitoring applications

Does the white coat influence satisfaction, trust and empathy in the doctor-patient relationship in the General and Family Medicine consultation? Interventional study

Objectives To understand the influence of the white coat on patient satisfaction, opinions about medical clothing, perception about confidence, empathy and medical knowledge and the satisfaction and comfort level of physicians in consultation. Setting An interventional study was conducted with a representative sample of the population attending primary care in central Portugal. Participants The sample was composed by 286 patients divided into two groups exposed or not to a doctor wearing a white coat. The first and last patients in consultation every day for 10 consecutive days were included. Interventions Every other day the volunteer physicians consulted with or without the use of a white coat. At the end of the consultation, a questionnaire was distributed to the patient with simple questions with a Likert scale response, the Portuguese version of the ‘Trust in physician’ scale and the Jefferson Scale of Patient Perceptions of Physician Empathy - Portuguese Version (JSPPPE-VP scale). A questionnaire was also distributed to the physician. Outcomes Planned and measured primary outcomes were patient satisfaction, trust and perception about empathy and secondary outcomes were opinion about medical clothing, satisfaction and comfort level of physicians in consultation. Results The sample was homogeneous in terms of sociodemographic variables. There were no statistically significant differences between the groups in terms of satisfaction, trust, empathy and knowledge perceived by the patients. There were differences in the opinion of the patients about the white coat, and when the physician was wearing the white coat this group of patients tended to think that this was the only acceptable attire for the physician (p<0.001). But when the family physician was in consultation without the white coat, this group of patients tended to agree that communication was easier (p=0.001). Conclusions There was no significant impact of the white coat in patient satisfaction, empathy and confidence in the family physician. Trial registration number ClinicalTrials. gov ID number: NCT0396541