Intracellular pressure, a key physical parameter of the intracellular environment, has been found to regulate multiple cell physiological activities and impact cell micromanipulation results. The intracellular pressure may reveal the mechanism of these cells’ physiological activities or improve the micro-manipulation accuracy for cells. The involvement of specialized and expensive devices and the significant damage to cell viability that the current intracellular pressure measurement methods cause significantly limit their wide applications. This paper proposes a robotic intracellular pressure measurement method using a traditional micropipette electrode system setup. First, the measured resistance of the micropipette inside the culture medium is modeled to analyze its variation trend when the pressure inside the micropipette increases. Then, the concentration of KCl solution filled inside the micropipette electrode that is suitable for intracellular pressure measurement is determined according to the tested electrode resistance–pressure relationship; 1 mol/L KCl solution is our final choice. Further, the measurement resistance of the micropipette electrode inside the cell is modeled to measure the intracellular pressure through the difference in key pressure before and after the release of the intracellular pressure. Based on the above work, a robotic measurement procedure of the intracellular pressure is established based on a traditional micropipette electrode system. The experimental results on porcine oocytes demonstrate that the proposed method can operate on cells at an average speed of 20~40 cells/day with measurement efficiency comparable to the related work. The average repeated error of the relationship between the measured electrode resistance and the pressure inside the micropipette electrode is less than 5%, and no observable intracellular pressure leakage was found during the measurement process, both guaranteeing the measurement accuracy of intracellular pressure. The measured results of the porcine oocytes are in accordance with those reported in related work. Moreover, a 90% survival rate of operated oocytes was obtained after measurement, proving limited damage to cell viability. Our method does not rely on expensive instruments and is conducive to promotion in daily laboratories.

The patch clamp technique has become the gold standard for neuron electrophysiology research in brain science. Brain slices have been widely utilized as the targets of the patch clamp technique due to their higher optical transparency compared to a live brain and their intercellular connectivity in comparison to cultured single neurons. However, the narrow working space, small scope, and depth of the field of view make the positioning of the operation’s micropipette to the target neuron a time-consuming task reliant on a high level of experience, significantly slowing down operation of the patch clamp technique in brain slices. Further, the current poor controllability in gigaseal formation, which is the key to electrophysiology signal recording, significantly lowers the patch clamp success rate. In this paper, a stepwise navigation of the micropipette is conducted to accelerate the positioning process of the micropipette tip to the target neuron in the brain slice. Then, a fuzzy proportional–integral–derivative controller is designed to control the gigaseal formation process along a designed resistance curve. The experimental results demonstrate an almost doubled patch clamp technique speed, with a 25% improvement in the success rate compared to the conventional manual method. The above advantages may promote the application of our method in brain science research based on brain slice platforms.

The inside-out patch clamp technique has been widely applied in brain science and neuroscience research due to its ability to detect extremely weak currents flowing through a single ion channel. The current manual inside-out patch clamp operations are highly expertise-requisite and low efficient. Meanwhile, the existing robotic systems are only applicable for suspended cells due to their new system setups. For the first time, this letter proposed a robotic inside-out patch clamp system for adherent cells based on vesicle rupture control. Firstly, impedance models were established to detect the vesicle rupture state. Then, a force analysis that combines the defocusing imaging model was developed to precisely control the exposure time of the vesicle in the air, which is a key factor in the rupture process of the vesicle. Based on the above works, a robotic inside-out patch clamp process for adherent cells was established. Experimental results demonstrate that the proposed robotic system can detect vesicle rupture state with a 100% success rate, control exposure time with an average error of 0.02$\,\text{s}$ and operate adherent HEK-293 cells with a success rate of 70% at an average operation speed of 61.3$\,$seconds/cell. The success rate of our system is more than three times that of manual operation results, laying a solid foundation for subsequent single ion channel functionality research.

The patch clamp technique has been widely utilized to measure extremely weak ion channel signals. In patch clamp technique, the measurement accuracy and duration rely on the tightness and stability of the seal between the aspirated cell membrane and the recording micropipette. The current patch clamp operations utilize a pressure-driven seal formation method that can only provide a 2D driving force on a small part of the aspirated cell membrane, which easily causes looseness or even failures of the seal, significantly limiting the measurement quality of ion channel signals. Addressing this, a robotic precise patch clamp measurement method was proposed in this paper. In this method, a 3D-driven seal formation method is developed to improve the measurement accuracy and duration of ion channel signals by providing a tight and stable gigaohmscale seal (gigaseal). First, the forces applied by aspiration pressure and voltage on the aspirated cell membrane inside the micropipette are analyzed, respectively. Then, a dynamic model of the gigaseal formation process driven by pressure and voltage is established to provide a 3D driving force on the target aspirated cell membrane. Further, a dual-input adaptive sliding mode controller is developed to form a tight and stable gigaseal to improve the measurement accuracy and duration in patch clamp operation. Finally, a robotic precise patch clamp measurement process was established based on the above work. Experimental results on CA1 pyramidal neurons of mouse brain slices demonstrate that, in comparison to the current 2D-driven method, the proposed patch clamp measurement method has a 30% higher gigaseal formation success rate, 52% higher gigaseal resistance, and a fourfold increase in the success rate of 1-hour duration recordings, demonstrating the formation of a tighter and more stable gigaseal using our method. With the above advantages, a 3 dB-higher signal-to-noise ratio (SNR) was achieved, and long-term glycine-induced dynamic increases in amplitude and frequency of spontaneous excitatory postsynaptic currents (sEPSCs) were detected using the proposed method. With aforementioned higher measurement success rate, higher SNR and longer recording time, our patch clamp recording is expected to be applied in brain science and nervous system disease research in the future.