Search Results
Elastomeric Optical Waveguides by Extrusion Printing
2022, Feng, Jun, Zheng, Yijun, Jiang, Qiyang, Włodarczyk‐Biegun, Małgorzata K., Pearson, Samuel, del Campo, Aránzazu
Advances in optogenetics and the increasing use of implantable devices for therapies and health monitoring are driving demand for compliant, biocompatible optical waveguides and scalable methods for their manufacture. Molding, thermal drawing, and dip-coating are the most prevalent approaches in recent literature. Here the authors demonstrate that extrusion printing at room temperature can be used for continuous fabrication of compliant optical waveguides with polydimethylsiloxane (PDMS) core and crosslinked Pluronic F127-diacrylate (Pluronic-DA) cladding. The optical fibers are printed from fluid precursor inks and stabilized by physical interactions and photoinitiated crosslinking in the Pluronic-DA. The printed fibers show optical loss values of 0.13–0.34 dB cm–1 in air and tissue within the wavelength range of 405–520 nm. The fibers have a Young's Modulus (Pluronic cladding) of 150 kPa and can be stretched to more than 5 times their length. The optical loss of the fibers shows little variation with extension. This work demonstrates how printing can simplify the fabrication of compliant and stretchable devices from materials approved for clinical use. These can be of interest for optogenetic or photopharmacology applications in extensible tissues, like muscles or heart.
Trade-off for survival: Microbiome response to chemical exposure combines activation of intrinsic resistances and adapted metabolic activity
2022, Adi Wicaksono, Wisnu, Braun, Maria, Bernhardt, Jörg, Riedel, Katharina, Cernava, Tomislav, Berg, Gabriele
The environmental microbiota is increasingly exposed to chemical pollution. While the emergence of multi-resistant pathogens is recognized as a global challenge, our understanding of antimicrobial resistance (AMR) development from native microbiomes and the risks associated with chemical exposure is limited. By implementing a lichen as a bioindicator organism and model for a native microbiome, we systematically examined responses towards antimicrobials (colistin, tetracycline, glyphosate, and alkylpyrazine). Despite an unexpectedly high resilience, we identified potential evolutionary consequences of chemical exposure in terms of composition and functioning of native bacterial communities. Major shifts in bacterial composition were observed due to replacement of naturally abundant taxa; e.g. Chthoniobacterales by Pseudomonadales. A general response, which comprised activation of intrinsic resistance and parallel reduction of metabolic activity at RNA and protein levels was deciphered by a multi-omics approach. Targeted analyses of key taxa based on metagenome-assembled genomes reflected these responses but also revealed diversified strategies of their players. Chemical-specific responses were also observed, e.g., glyphosate enriched bacterial r-strategists and activated distinct ARGs. Our work demonstrates that the high resilience of the native microbiota toward antimicrobial exposure is not only explained by the presence of antibiotic resistance genes but also adapted metabolic activity as a trade-off for survival. Moreover, our results highlight the importance of native microbiomes as important but so far neglected AMR reservoirs. We expect that this phenomenon is representative for a wide range of environmental microbiota exposed to chemicals that potentially contribute to the emergence of antibiotic-resistant bacteria from natural environments.
Nanotopography mediated osteogenic differentiation of human dental pulp derived stem cells
2017, Bachhuka, Akash, Delalat, Bahman, Ghaemi, Soraya Rasi, Gronthos, Stan, Voelcker, Nicolas H., Vasilev, Krasimir
Advanced medical devices, treatments and therapies demand an understanding of the role of interfacial properties on the cellular response. This is particularly important in the emerging fields of cell therapies and tissue regeneration. In this study, we evaluate the role of surface nanotopography on the fate of human dental pulp derived stem cells (hDPSC). These stem cells have attracted interest because of their capacity to differentiate to a range of useful lineages but are relatively easy to isolate. We generated and utilized density gradients of gold nanoparticles which allowed us to examine, on a single substrate, the influence of nanofeature density and size on stem cell behavior. We found that hDPSC adhered in greater numbers and proliferated faster on the sections of the gradients with higher density of nanotopography features. Furthermore, greater surface nanotopography density directed the differentiation of hDPSC to osteogenic lineages. This study demonstrates that carefully tuned surface nanotopography can be used to manipulate and guide the proliferation and differentiation of these cells. The outcomes of this study can be important in the rational design of culture substrates and vehicles for cell therapies, tissue engineering constructs and the next generation of biomedical devices where control over the growth of different tissues is required.
Phenomenology of ultrafine particle concentrations and size distribution across urban Europe
2023, Trechera, Pedro, Garcia-Marlès, Meritxell, Liu, Xiansheng, Reche, Cristina, Pérez, Noemí, Savadkoohi, Marjan, Beddows, David, Salma, Imre, Vörösmarty, Máté, Casans, Andrea, Casquero-Vera, Juan Andrés, Hueglin, Christoph, Marchand, Nicolas, Chazeau, Benjamin, Gille, Grégory, Kalkavouras, Panayiotis, Mihalopoulos, Nikos, Ondracek, Jakub, Zikova, Nadia, Niemi, Jarkko V., Manninen, Hanna E., Green, David C., Tremper, Anja H., Norman, Michael, Vratolis, Stergios, Eleftheriadis, Konstantinos, Gómez-Moreno, Francisco J., Alonso-Blanco, Elisabeth, Gerwig, Holger, Wiedensohler, Alfred, Weinhold, Kay, Merkel, Maik, Bastian, Susanne, Petit, Jean-Eudes, Favez, Olivier, Crumeyrolle, Suzanne, Ferlay, Nicolas, Martins Dos Santos, Sebastiao, Putaud, Jean-Philippe, Timonen, Hilkka, Lampilahti, Janne, Asbach, Christof, Wolf, Carmen, Kaminski, Heinz, Altug, Hicran, Hoffmann, Barbara, Rich, David Q., Pandolfi, Marco, Harrison, Roy M., Hopke, Philip K., Petäjä, Tuukka, Alastuey, Andrés, Querol, Xavier
The 2017–2019 hourly particle number size distributions (PNSD) from 26 sites in Europe and 1 in the US were evaluated focusing on 16 urban background (UB) and 6 traffic (TR) sites in the framework of Research Infrastructures services reinforcing air quality monitoring capacities in European URBAN & industrial areaS (RI-URBANS) project. The main objective was to describe the phenomenology of urban ultrafine particles (UFP) in Europe with a significant air quality focus. The varying lower size detection limits made it difficult to compare PN concentrations (PNC), particularly PN10-25, from different cities. PNCs follow a TR > UB > Suburban (SUB) order. PNC and Black Carbon (BC) progressively increase from Northern Europe to Southern Europe and from Western to Eastern Europe. At the UB sites, typical traffic rush hour PNC peaks are evident, many also showing midday-morning PNC peaks anti-correlated with BC. These peaks result from increased PN10-25, suggesting significant PNC contributions from nucleation, fumigation and shipping. Site types to be identified by daily and seasonal PNC and BC patterns are: (i) PNC mainly driven by traffic emissions, with marked correlations with BC on different time scales; (ii) marked midday/morning PNC peaks and a seasonal anti-correlation with PNC/BC; (iii) both traffic peaks and midday peaks without marked seasonal patterns. Groups (ii) and (iii) included cities with high insolation. PNC, especially PN25-800, was positively correlated with BC, NO2, CO and PM for several sites. The variable correlation of PNSD with different urban pollutants demonstrates that these do not reflect the variability of UFP in urban environments. Specific monitoring of PNSD is needed if nanoparticles and their associated health impacts are to be assessed. Implementation of the CEN-ACTRIS recommendations for PNSD measurements would provide comparable measurements, and measurements of <10 nm PNC are needed for full evaluation of the health effects of this size fraction.
Calibrating mini-mental state examination scores to predict misdiagnosed dementia patients
2021, Vyas, Akhilesh, Aisopos, Fotis, Vidal, Maria-Esther, Garrard, Peter, Paliouras, George
Mini-Mental State Examination (MMSE) is used as a diagnostic test for dementia to screen a patient’s cognitive assessment and disease severity. However, these examinations are often inaccurate and unreliable either due to human error or due to patients’ physical disability to correctly interpret the questions as well as motor deficit. Erroneous data may lead to a wrong assessment of a specific patient. Therefore, other clinical factors (e.g., gender and comorbidities) existing in electronic health records, can also play a significant role, while reporting her examination results. This work considers various clinical attributes of dementia patients to accurately determine their cognitive status in terms of the Mini-Mental State Examination (MMSE) Score. We employ machine learning models to calibrate MMSE score and classify the correctness of diagnosis among patients, in order to assist clinicians in a better understanding of the progression of cognitive impairment and subsequent treatment. For this purpose, we utilize a curated real-world ageing study data. A random forest prediction model is employed to estimate the Mini-Mental State Examination score, related to the diagnostic classification of patients.This model uses various clinical attributes to provide accurate MMSE predictions, succeeding in correcting an important percentage of cases that contain previously identified miscalculated scores in our dataset. Furthermore, we provide an effective classification mechanism for automatically identifying patient episodes with inaccurate MMSE values with high confidence. These tools can be combined to assist clinicians in automatically finding episodes within patient medical records where the MMSE score is probably miscalculated and estimating what the correct value should be. This provides valuable support in the decision making process for diagnosing potential dementia patients.