The development of high-performance photobioreactors equipped with automatic systems for non-invasive real-time monitoring of cultivation conditions and photosynthetic parameters is a challenge in algae biotechnology. Therefore, we developed a chlorophyll (Chl) fluorescence measuring system for the online recording of the light-induced fluorescence rise and the dark relaxation of the flash-induced fluorescence yield (Qa - re-oxidation kinetics) in photobioreactors. This system provides automatic measurements in a broad range of Chl concentrations at high frequency of gas-tight sampling, and advanced data analysis. The performance of this new technique was tested on the green microalgae Chlamydomonas reinhardtii subjected to a sulfur deficiency stress and to long-term dark anaerobic conditions. More than thousand fluorescence kinetic curves were recorded and analyzed during aerobic and anaerobic stages of incubation. Lifetime and amplitude values of kinetic components were determined, and their dynamics plotted on heatmaps. Out of these data, stress-sensitive kinetic parameters were specified. This implemented apparatus can therefore be useful for the continuous real-time monitoring of algal photosynthesis in photobioreactors.
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http://dx.doi.org/10.1111/ppl.12693 | DOI Listing |
Front Med (Lausanne)
December 2024
Department II of Internal Medicine and Center for Molecular Medicine Cologne, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany.
The number of clinical studies and associated research has increased significantly in the last few years. Particularly in rare diseases, an increased effort has been made to integrate, analyse, and develop new knowledge to improve patient stratification and wellbeing. Clinical databases, including digital medical records, hold significant amount of information that can help understand the impact and progression of diseases.
View Article and Find Full Text PDFLab Chip
January 2025
Department of Biomedical Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, China.
Revealing how individual cells alter their secretions over time is crucial for understanding their responses to environmental changes. Key questions include: When do cells modify their functions and states? What transitions occur? Insights into the kinetic secretion trajectories of various cell types are essential for unraveling complex biological systems. This review highlights seven microfluidic technologies for time-resolved single-cell secretion analysis: 1.
View Article and Find Full Text PDFEar Hear
January 2025
Department of Otorhinolaryngology and Head and Neck Surgery, Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands.
Objectives: Real-time monitoring of cochlear function to predict the loss of residual hearing after cochlear implantation is now possible. Current approaches monitor the cochlear microphonic (CM) during implantation from the electrode at the tip of the implant. A drop in CM response of >30% is associated with poorer hearing outcomes.
View Article and Find Full Text PDFBiomed Microdevices
January 2025
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, 08854, USA.
Wearable and implantable biosensors have rapidly entered the fields of health and biomedicine to diagnose diseases and physiological monitoring. The use of wired medical devices causes surgical complications, which can occur when wires break, become infected, generate electrical noise, and are incompatible with implantable applications. In contrast, wireless power transfer is ideal for biosensing applications since it does not necessitate direct connections between measurement tools and sensing systems, enabling remote use of the biosensors.
View Article and Find Full Text PDFSci Rep
January 2025
Civil and Transportation College, Beihua University, Jilin, China.
An improved concrete structure health monitoring method based on G-S-G is proposed, which fully combines an optimized Gray-Level Co-occurrence Matrix (GLCM) with an improved Self-Organizing Map (SOM) neural network to achieve accurate and real-time concrete structure health monitoring. First of all, in order to obtain a dynamic image of the crack damage region of interest (ROI) with clear contrast and obvious target, the image acquisition system and image optimization method are used to process the damaged image. Moreover, in order to realize the accurate location of crack damage, crack damage identification research based on GLCM-SOM effectively eliminates the interference of honeycomb and pothole damage on crack damage.
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