Creating a Novel Mathematical Model of the Kv10.1 Ion Channel and Controlling Channel Activity with Nanoelectromechanical Systems
Round 1
Reviewer 1 Report
The manuscript no. applsci-1657886 entitled “Creating a novel mathematical model of the Kv10.1 ion channel and controlling channel activity with nanoelectromechanical systems'' by Jasmina Lozanović Šajić, Sonja Langthaler and Christian Baumgartner summarizes a quite interesting work. It presents an innovative idea of utilization of nanoelectromechanical systems to control the voltage-activated potassium channels involved in cancer biology.
Although the main concept sounds very promising the Authors neither present a completely novel model nor directly control channel activity by nanorobots.
- The empirical modeling of ion channels based on system theory has been already presented by this group in https://doi.org/10.3390/cells11020239. Thus, its application in the case of Kv 10.1 channels instead of Kv 1.1 can be considered rather as a “copy-paste” approach.
- In the current work, the control function for an ensemble of Kv 10.1 channels is evaluated by the use of an existing MATLAB app. It may effectively alleviate the effects of the channel's activity, which, according to the submitted work, could be utilized in appropriately designed control-nanodevices. I have an impression that this may be attainable only at a conceptual level, but even so, it requires a more detailed explanation. How should such a device work? If it controls a single channel, its effects will be physiologically negligible. If it controls all channels of a certain type within a given cell, it will exert a physiologically significant effect, but how exactly could it be realized? I would recommend that the Authors should postulate a hypothetical solution.
Author Response
We would like to thank the reviewer again for his/her very valuable comments and recommendations, which we have carefully considered in the revised manuscript. Below please find our detailed comments.
The manuscript no. applsci-1657886 entitled "Creating a novel mathematical model of the Kv10.1 ion channel and controlling channel activity with nanoelectromechanical systems'' by Jasmina Lozanović Šajić, Sonja Langthaler and Christian Baumgartner summarizes a quite interesting work. It presents an innovative idea of utilization of nanoelectromechanical systems to control the voltage-activated potassium channels involved in cancer biology.
We thank the reviewer for his/her positive comment on our work.
Although the main concept sounds very promising the Authors neither present a completely novel model nor directly control channel activity by nanorobots.
- The empirical modeling of ion channels based on system theory has been already presented by this group in https://doi.org/10.3390/cells11020239. Thus, its application in the case of Kv 10.1 channels instead of Kv 1.1 can be considered rather as a "copy-paste" approach.
We thank the reviewer for this important comment.
In the paper (https://doi.org/10.3390/cells11020239), we used system identification to create a model of the Kv1.1 and compared the STB model with other known models.
However, Kv10.1 modeled in this work has a different dynamic behavior. Therefore, we assumed the Kv10.1 as a linear, time-invariant model and first-order system. System identification was based on a specific voltage step input protocol, while for the channel Kv1.1 different input stimuli protocols with completely different output characteristics were considered. We assumed a nominal operating point and estimated the model as a transfer function based on the step input function of 70mV. In addition, in this work, we considered mathematical possibilities of controllability and observability. And the controler's parameters were obtained.
It is important to note that each ion channel has a different dynamic behavior, and therefore it is necessary to apply the system identification methodology from this perspective to determine the mathematical model. In the previous paper, we introduced and confirmed the possibility of applying control system theory and system identification methodology in general. In further research, the model parameters' dependence on different physiological temperatures will be investigated.
In summary, system identification in general uses input and output information in the time and frequency domain. The model developed here based on the measurements and analysis of experimental patch clamp data. Similarly, this method can also be used in other, non biological research domains, such as fluid flow models, electronic circuit, servo motor models, etc. The methodology of system identification remains the same.
- In the current work, the control function for an ensemble of Kv 10.1 channels is evaluated by the use of an existing MATLAB app. It may effectively alleviate the effects of the channel's activity, which, according to the submitted work, could be utilized in appropriately designed control-nanodevices. I have an impression that this may be attainable only at a conceptual level, but even so, it requires a more detailed explanation. How should such a device work? If it controls a single channel, its effects will be physiologically negligible. If it controls all channels of a certain type within a given cell, it will exert a physiologically significant effect, but how exactly could it be realized? I would recommend that the Authors should postulate a hypothetical solution.
We added a new section, presenting a potential use case for treating breast cancer using a Kv10.1 controlled nanorobot
"Our hypothesis for the use of floating nanorobots is to control ion channel activity to specifically target cancer cells in breast tumors. We know that Kv10.1 channels in the nervous system contribute to the control of neuronal excitability. However, since activation requires strong depolarization, a single action potential would not be sufficient for activation [34]. In contrast, cancer cells are usually depolarized so that the channels are predominantly open, providing a potential target for a pinpoint destruction by nanorobots. For example, overexpression of Kv10.1 channels is significantly upregulated in invasive breast carcinoma, whereas healthy breast tissue shows hardly any expression or activity of the Kv10.1 channel [34-38]. Floating nanorobots applied via the blood circulation can be guided to the targeted sites and measure and control the Kv10.1 channel activity of the cells in the area of interest. Since nanorobots act as sensors and actuators, if the sensor interface detects an altered behavior of Kv10.1 channel activity, as is present in breast cancer cells, the channels could be controlled accordingly by the Kv10.1 feedback control system of the robot. Alternatively, after detecting a cancer cell based on aberrant channel activity, such MEMS/NEMS based nanorobot devices may also act as a nano-scalpel that mechanically destroys the targeted cell.
Further examples of possible applications are discussed in [31-33]. However, although the practical implementation of this use case has not been performed and validated, this work demonstrates a potential new, forward-looking direction for cancer detection and therapy. “
Figure 10. Illustration of possible application of Kv10.1 controlled nanorobots in breast cancer detection and treatment. The cancerous area will be reached by the nanorobots through the blood vessel system. Created with BioRender"
We thank the reviewer for his important comments and for his/her time and effort in reviewing this article.
Author Response File: 
Author Response.docx
Reviewer 2 Report
One gets the impression that the article is written on a topic that may be of great practical importance for medicine in the future. However, without correcting the following comments, it is difficult to understand the article:
1) the abbreviation "MEMS" should be described in line 43, not 271.
2) In line 72, the meaning of the numeric characters in the designation "Kv10.1" is not explained.
3) The novelty of the work is not explicitly described. What is the difference between this work and [16] which is mentioned in lines 77-78?
4) What is the meaning of "s" in fig. 2a?
5) The following fragments are also not clear: "estimate model the model" (in line 136); "(?)" (in line 146); "AP" (in line 148).
6) Row 141 refers to three levels of temperature "15°, 25°, and 35° C". However, there is no further analysis of the temperature factor.
7) There is no description of the channel structure (shown in Fig. 3) and the processes occurring in it in the “Active”, “Inactive”, “Resting” modes. The change in time of the input signal is not explained.
8) There is no description and reference to figures 4 and 5 in the article.
9) What are the dimensions of the quantities in Equation (3)?
10) The paragraph in lines 260-269 probably needs to be deleted, as it repeats the next paragraph (lines 271-284).
Author Response
We would like to thank the reviewer again for his/her very valuable comments and recommendations, which we have carefully considered in the revised manuscript. Below please find our detailed comments.
"One gets the impression that the article is written on a topic that may be of great practical importance for medicine in the future."
We thank the reviewer for his/her positive comment on our work.
Correcting the following comments:
1) The abbreviation "MEMS" should be described in line 43, not 271.
We added a description in line 43: microelectromechanical systems (MEMS).
2) In line 72, the meaning of the numeric characters in the designation "Kv10.1" is not explained.
We explained the Kv10.1 (potassium voltage-gated channel subfamily H member 1, known as EAG1 or Ether-à-go-go 1).
3) The novelty of the work is not explicitly described. What is the difference between this work and [16] which is mentioned in lines 77-78?
We thank the reviewer for this important comment.
In the paper (https://doi.org/10.3390/cells11020239), we used system identification to create a model of the Kv1.1 and compared the STB model with other known models.
However, Kv10.1 modeled in this work has a different dynamic behavior. Therefore, we assumed the Kv10.1 as a linear, time-invariant model and first-order system. System identification was based on a specific voltage step input protocol, while for the channel Kv1.1 different input stimuli protocols with completely different output characteristics were considered. We assumed a nominal operating point and estimated the model as a transfer function based on the step input function of 70mV. In addition, in this work, we considered mathematical possibilities of controllability and observability. And the controler's parameters were obtained.
It is important to note that each ion channel has a different dynamic behavior, and therefore it is necessary to apply the system identification methodology from this perspective to determine the mathematical model. In the previous paper, we introduced and confirmed the possibility of applying control system theory and system identification methodology in general. In further research, the model parameters' dependence on different physiological temperatures will be investigated.
In summary, system identification in general uses input and output information in the time and frequency domain. The model developed here based on the measurements and analysis of experimental patch clamp data. Similarly, this method can also be used in other, non biological research domains, such as fluid flow models, electronic circuit, servo motor models, etc. The methodology of system identification remains the same.
4) What is the meaning of "s" in fig. 2a?
We explained in the paper (revised version) that "s" is a complex variable in the Laplace (S) domain.
5) The following fragments are also not clear: "estimate model the model" (in line 136); "(?)" (in line 146); "AP" (in line 148).
It should be "estimate model", we corrected the mistake.
AP is an action potential protocol, a specific protocol to mimic excitation in electrically active cells such as neural or cardiac cells and to measure the specific behavior during an action potential.
6) Row 141 refers to three levels of temperature "15°, 25°, and 35° C". However, there is no further analysis of the temperature factor.
Data are available for three temperature levels. We assumed 25° C as the nominal temperature for the modeling and experiments. Temperature effects on time constants and system gain were not considered in this paper. However, experimental data and our preliminary analysis indicate that the gain and the time constant change depending on the temperature.
7) There is no description of the channel structure (shown in Fig. 3) and the processes occurring in it in the "Active", "Inactive", "Resting" modes. The change in time of the input signal is not explained.
An additional short description is added in the revised version of the manuscript.
8) There is no description and reference to figures 4 and 5 in the article.
We added additional descriptions of figures 4 and 5 in the revised version.
9) What are the dimensions of the quantities in Equation (3)?
Units of G(s) = units of Output(s) / units of Input (s)
Transfer function units are not usually given because they are defined by the input and output function considered.
10) The paragraph in lines 260-269 probably needs to be deleted, as it repeats the next paragraph (lines 271-284).
Corrected and deleted.
We thank the reviewer for his important comments and for his/her time and effort in reviewing this article.
Author Response File: Author Response.docx
Reviewer 3 Report
Very well paper , This paper presents a novel methodology that is applied to mathematically model ion channels based on control system theory and system identification.
I suggest the publication in this current form.
Author Response
We would like to thank again the reviewer for his/her very valuable comments and recommendations.
We thank the reviewer for his/her positive comment on our work.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
Thank you for the introduced improvements acccording to my suggestions. The manuscript can be accepted in the present form.
