A mobile sensing approach to stress detection and memory activation for public bus drivers

Experience of daily stress among bus drivers has shown to affect physical and psychological health, and can impact driving behavior and overall road safety. Although previous research consistently supports these findings, little attention has been dedicated to the design of a stress detection method able to synchronize physiologic and psychological stress responses of public bus drivers in their day-to-day routine work. To overcome this limitation, we propose a mobile sensing approach to detect georeferenced stress responses and facilitate memory recall of the stressful situations. Data was collected among public bus drivers in the city of Porto, Portugal (145 hours, 36 bus drivers, +2300 km) and results supported the validation of our approach among this population and allowed us to determine specific stressor categories within certain areas of the city. Furthermore, data collected through-out the city allowed us to produce a citywide ”stress map” that can be used for spotting areas in need of local authority intervention. The enriching findings suggest that our system can be a promising tool to support applied occupational health interventions for public bus drivers and guide authorities’ interventions to improve these aspects in ”future” cities

Optical fiber-based sensing method for nanoparticle detection through supervised back-scattering analysis: A potential contributor for biomedicine

Background: In view of the growing importance of nanotechnologies, the detection/identification of nanoparticles type has been considered of utmost importance. Although the characterization of synthetic/organic nanoparticles is currently considered a priority (eg, drug delivery devices, nanotextiles, theranostic nanoparticles), there are many examples of “naturally” generated nanostructures - for example, extracellular vesicles (EVs), lipoproteins, and virus - that provide useful information about human physiology or clinical conditions. For example, the detection of tumor-related exosomes, a specific type of EVs, in circulating fluids has been contributing to the diagnosis of cancer in an early stage. However, scientists have struggled to find a simple, fast, and low-cost method to accurately detect/identify these nanoparticles, since the majority of them have diameters between 100 and 150 nm, thus being far below the diffraction limit. Methods: This study investigated if, by projecting the information provided from short-term portions of the back-scattered laser light signal collected by a polymeric lensed optical fiber tip dipped into a solution of synthetic nanoparticles into a lower features dimensional space, a discriminant function is able to correctly detect the presence of 100 nm synthetic nanoparticles in distilled water, in different concentration values. Results and discussion: This technique ensured an optimal performance (100% accuracy) in detecting nanoparticles for a concentration above or equal to 3.89 µg/mL (8.74E+10 particles/mL), and a performance of 90% for concentrations below this value and higher than 1.22E-03 µg/mL (2.74E+07 particles/mL), values that are compatible with human plasmatic levels of tumorderived and other types of EVs, as well as lipoproteins currently used as potential biomarkers of cardiovascular diseases. Conclusion: The proposed technique is able to detect synthetic nanoparticles whose dimensions are similar to EVs and other “clinically” relevant nanostructures, and in concentrations equivalent to the majority of cell-derived, platelet-derived EVs and lipoproteins physiological levels. This study can, therefore, provide valuable insights towards the future development of a device for EVs and other biological nanoparticles detection with innovative characteristics.This work was partly developed under the project NanoSTIMA, funded by the North Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF). It was also funded by the Portuguese Foundation for Science and Technology (PhD research grant PD/BD/135023/2017). Rita SR Ribeiro is currently working at 4Dcell and Elvesys, Paris, France

Author Correction: iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

An amendment to this paper has been published and can be accessed via a link at the top of the paper.This work was partially funded by the projects NanoSTIMA and NORTE-01-0145-FEDER-000029, both supported by the North Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF); and by the Portuguese Foundation for Science and Technology, within the scope of the PhD grant PD/BD/135023/2017 and the projects: PTDC/BBB-EBI/0567/2014 (to CAR) and UID/BIM/04293/2013. It was also funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE (POCI-01-0145-FEDER-016585; POCI-01-0145-FEDER-007274; PPBI-POCI-01-0145-FEDER-022122). MB acknowledges the Marie Sklodowska-Curie grant agreement No. 748880

Ambulatory assessment of psychophysiological stress among police officers: A proof-of-concept study.

Occupational stress has been widely recognized as a global challenge and has received increased attention by the academic community. Ambulatory Assessment methodologies, combining psychophysiological measures of stress, offer a promising avenue for future prevention and/or rehabilitation stress research. Considering that policing is well known for being a particularly stressful occupation, Emergency Responders Officers (EROs) stress levels were investigated. Particularly, this study analyzed: (i) physiological stress data obtained during shifts and compared these data with baseline levels (days off), as well as (ii) with normative values for healthy populations; (iii) stress symptoms differences from beginning to end of shift; (iv) stress events and events intensity and (v) the acceptability and feasibility of this proof-of-concept study in a highly stressful occupation. A Geo-location event system was used to help retrospective accounts of psychological stress, combined with electrocardiogram (ECG) data and mobile self-reports, that include stress symptoms, event types and event intensity. Results suggest that EROs experience high levels of stress (both on-duty and off duty) when compared to healthy populations. Stress symptoms increase from the beginning to end of the shift. However, the mean events intensity was very low. It can be concluded that stress may not always be diagnosed when using merely self-reports. These findings highlight the importance of combining both self-report and physiological stress measures in occupational health contexts. Finally, results confirm the acceptability and feasibility of the multi-method used. Key implications for policy makers and applied practitioners in the area of occupational health and future research directions are discussed

iLoF: An intelligent Lab on Fiber Approach for Human Cancer Single-Cell Type Identification

With the advent of personalized medicine, there is a movement to develop “smaller” and “smarter” microdevices that are able to distinguish similar cancer subtypes. Tumor cells display major differences when compared to their natural counterparts, due to alterations in fundamental cellular processes such as glycosylation. Glycans are involved in tumor cell biology and they have been considered to be suitable cancer biomarkers. Thus, more selective cancer screening assays can be developed through the detection of specific altered glycans on the surface of circulating cancer cells. Currently, this is only possible through time-consuming assays. In this work, we propose the “intelligent” Lab on Fiber (iLoF) device, that has a high-resolution, and which is a fast and portable method for tumor single-cell type identification and isolation. We apply an Artificial Intelligence approach to the back-scattered signal arising from a trapped cell by a micro-lensed optical fiber. As a proof of concept, we show that iLoF is able to discriminate two human cancer cell models sharing the same genetic background but displaying a different surface glycosylation profile with an accuracy above 90% and a speed rate of 2.3 seconds. We envision the incorporation of the iLoF in an easy-to-operate microchip for cancer identification, which would allow further biological characterization of the captured circulating live cells.This work was partially funded by the projects NanoSTIMA and NORTE-01-0145-FEDER-000029, both supported by the North Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF); and by the Portuguese Foundation for Science and Technology, within the scope of the PhD grant PD/BD/135023/2017 and the projects: PTDC/BBB-EBI/0567/2014 (to CAR) and UID/BIM/04293/2013. It was also funded by FEDER funds through the Operational Programme for Competitiveness Factors-COMPETE (POCI-01-0145-FEDER-016585; POCI-01-0145-FEDER-007274; PPBI-POCI-01-0145-FEDER-022122). MB acknowledges the Marie Sklodowska-Curie grant agreement No. 748880