Key role of adsorption site abundance in the direct electrochemical co-detection of estradiol and dopamine.

Estradiol (E2) is a hormone that influences various aspects of women's health. Beyond its reproductive functions, E2 impacts neurotransmitter systems such as dopamine (DA). Vertically aligned carbon nanofibers (VACNFs) have shown good sensitivity, selectivity against ascorbic acid (AA) and uric acid (UA), biocompatibility, and reduced fouling in DA sensing.

Modulating the Geometry of the Carbon Nanofiber Electrodes Provides Control over Dopamine Sensor Performance.

One of the major challenges for in vivo electrochemical measurements of dopamine (DA) is to achieve selectivity in the presence of interferents, such as ascorbic acid (AA) and uric acid (UA). Complicated multimaterial structures and ill-defined pretreatments have been frequently utilized to enhance selectivity. The lack of control over the realized structures has prevented establishing associations between the achieved selectivity and the electrode structure.

Nanoscale geometry determines mechanical biocompatibility of vertically aligned nanofibers.

Vertically aligned carbon nanofibers (VACNFs) are promising material candidates for neural biosensors due to their ability to detect neurotransmitters in physiological concentrations. However, the expected high rigidity of CNFs could induce mechanical mismatch with the brain tissue, eliciting formation of a glial scar around the electrode and thus loss of functionality. We have evaluated mechanical biocompatibility of VACNFs by growing nickel-catalyzed carbon nanofibers of different lengths and inter-fiber distances.

Tactile sensory coding and learning with bio-inspired optoelectronic spiking afferent nerves.

The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Inspired by biological somatosensory systems, we report an optoelectronic spiking afferent nerve with neural coding, perceptual learning and memorizing capabilities to mimic tactile sensing and processing. Our system senses pressure by MXene-based sensors, converts pressure information to light pulses by coupling light-emitting diodes to analog-to-digital circuits, then integrates light pulses using a synaptic photomemristor.