The SensorOverlord predicts the accuracy of measurements with ratiometric biosensors

Evidence for reduced plasmodesmata callose accumulation in Nicotiana benthamiana leaves with increased symplastic cell-to-cell communication caused by RNA processing defects of chloroplasts

RNA processing defects in chloroplasts were previously associated with increased plasmodesmata (PD) permeability. However, the underlying mechanisms for such association are still unknown. To provide insight into this, we silenced the expression of chloroplast-located INCREASED SIZE EXCLUSION LIMIT 2 (ISE2) RNA helicase in Nicotiana benthamiana leaves and determined an increase in PD permeability which is caused by a reduction of PD callose deposition. Moreover, the silencing of two other nuclear genes encoding chloroplastic enzymes involved in RNA processing, RH3, and CLPR2, also increased PD permeability accompanied by reduced callose accumulation at PD. In addition, we quantified the plastidic hydrogen peroxide levels using the chloroplast-targeted fluorescent sensor, HyPer, in ISE2, RH3, and CLPR2 silenced N. benthamiana leaves. The levels of chloroplastic hydrogen peroxide were not correlated with the increased cell-to-cell movement of the marker protein GFP2X. We, therefore, propose that defects in chloroplast RNA metabolism mediate PD gating by suppressing PD callose deposition, and hydrogen peroxide levels in the organelles are not directly linked to this process.

Genetically encoded sensors for Chloride concentration

Insights into chloride regulation in neurons have come slowly, but they are likely to be critical for our understanding of how the brain works. The reason is that the intracellular Cl^- level ([Cl^-]_i) is the key determinant of synaptic inhibitory function, and this in turn dictates all manner of neuronal network function. The true impact on the network will only be apparent, however, if Cl^- is measured at many locations at once (multiple neurons, and also across the subcellular compartments of single neurons), which realistically, can only be achieved using imaging. The development of genetically-encoded anion biosensors (GABs) brings the additional benefit that Cl^- imaging may be done in identified cell-classes and hopefully in subcellular compartments. Here, we describe the historical background and motivation behind the development of these sensors and how they have been used so far. There are, however, still major limitations for their use, the most important being the fact that all GABs are sensitive to both pH and Cl^-. Disambiguating the two signals has proved a major challenge, but there are potential solutions; notable among these is ClopHensor, which has now been developed for in vivo measurements of both ion species. We also speculate on how these biosensors may yet be improved, and how this could advance our understanding of Cl^- regulation and its impact on brain function.

Shining a light on NAD- and NADP-based metabolism in plants

The pyridine nucleotides nicotinamide adenine dinucleotide [NAD(H)] and nicotinamide adenine dinucleotide phosphate [NADP(H)] simultaneously act as energy transducers, signalling molecules, and redox couples. Recent research into photosynthetic optimisation, photorespiration, immunity, hypoxia/oxygen signalling, development, and post-harvest metabolism have all identified pyridine nucleotides as key metabolites. Further understanding will require accurate description of NAD(P)(H) metabolism, and genetically encoded fluorescent biosensors have recently become available for this purpose. Although these biosensors have begun to provide novel biological insights, their limitations must be considered and the information they provide appropriately interpreted. We provide a framework for understanding NAD(P)(H) metabolism and explore what fluorescent biosensors can, and cannot, tell us about plant biology, looking ahead to the pressing questions that could be answered with further development of these tools.

Review of Wearable Devices and Data Collection Considerations for Connected Health

Wearable sensor technology has gradually extended its usability into a wide range of well-known applications. Wearable sensors can typically assess and quantify the wearer’s physiology and are commonly employed for human activity detection and quantified self-assessment. Wearable sensors are increasingly utilised to monitor patient health, rapidly assist with disease diagnosis, and help predict and often improve patient outcomes. Clinicians use various self-report questionnaires and well-known tests to report patient symptoms and assess their functional ability. These assessments are time consuming and costly and depend on subjective patient recall. Moreover, measurements may not accurately demonstrate the patient’s functional ability whilst at home. Wearable sensors can be used to detect and quantify specific movements in different applications. The volume of data collected by wearable sensors during long-term assessment of ambulatory movement can become immense in tuple size. This paper discusses current techniques used to track and record various human body movements, as well as techniques used to measure activity and sleep from long-term data collected by wearable technology devices.