A method for stable control of cell illumination in optogenetics based on irradiance negative feedback regulation
By monitoring the irradiance of LED light sources in real time in optogenetic experimental equipment and constructing a prediction model, combined with error judgment and compensation strategies, the problem of unstable illumination was solved, and the stability and reproducibility of optogenetic experiments were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHONGQING MEDICAL UNIVERSITY
- Filing Date
- 2026-06-26
- Publication Date
- 2026-07-31
AI Technical Summary
In existing optogenetic experimental equipment, LED light sources suffer from unstable light intensity due to thermal drift, aging degradation, and environmental disturbances. The lack of real-time monitoring and dynamic adjustment affects the accuracy and repeatability of experiments.
By constructing a closed, light-proof space, monitoring the irradiance of LED light sources in real time, building a light fluctuation prediction model, and combining error judgment and multi-level compensation strategies, intelligent dynamic control of LED light intensity is achieved to ensure light stability.
It significantly reduced the long-term light drift rate, improved the responsiveness and robustness of the light control system, and ensured the stability and reproducibility of optogenetic experiments.
Smart Images
Figure CN122496948A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of optogenetics experimental technology, and in particular to an optogenetic method for stable control of cell light exposure based on irradiance negative feedback regulation. Background Technology
[0002] With the development of optogenetics, researchers have been able to precisely regulate cellular behavior, neural activity, or signaling pathways by introducing light-sensitive protein genes into cells, enabling the cells to produce controllable biological responses to specific wavelengths of light stimulation. This technology has been widely applied in neuroscience research, cell signal transduction analysis, and the exploration of disease mechanisms. In optogenetic experiments, cells are extremely sensitive to light conditions, especially the stability of light intensity, which directly affects the activation efficiency of light-sensitive proteins and the cellular response. Therefore, providing stable, uniform, and controllable light conditions in the cell culture environment is crucial for ensuring the accuracy and reproducibility of optogenetic experiments.
[0003] However, in existing light-based culture equipment, LED light sources are typically controlled by fixed driving parameters, lacking a real-time monitoring and dynamic adjustment mechanism for changes in light intensity. When LED light sources operate for extended periods, they are prone to thermal drift due to factors such as device heating, ambient temperature changes, and power supply fluctuations, causing the irradiance to gradually deviate from the initial set value. Simultaneously, as the LED devices are used for longer periods, their photoelectric conversion efficiency gradually decreases, resulting in light intensity decay and causing a deviation between the actual light stimulation dose received by the cells and the expected value. Furthermore, if the culture device needs to be turned on for monitoring or maintenance during experiments, the entry of ambient light can cause instantaneous changes in light intensity, disturbing the cell state. While some existing systems can detect irradiance, they often rely solely on single-point detection or simple feedback adjustment, lacking the ability to analyze light change trends and promptly identify abnormalities such as periodic fluctuations or continuous decay, making it difficult to effectively guarantee light stability during long-term experiments.
[0004] Therefore, how to achieve real-time monitoring, trend prediction, and dynamic compensation adjustment of LED light intensity in a cell culture environment, so that the light intensity remains stable during long-term experiments, and reduces the impact of thermal drift, aging attenuation, and environmental disturbances of the light source, has become an important technical problem that urgently needs to be solved in the field of optogenetic experimental equipment. Summary of the Invention
[0005] This invention provides a method for stabilizing cell illumination in optogenetics based on irradiance negative feedback regulation. By constructing a closed, light-blocked irradiation space, the method monitors and predicts the fluctuation trend of the irradiance (i.e., light power density, used to quantify the light intensity acting on cells) of the LED light source in real time. By integrating the results of static error and dynamic trend analysis, the method intelligently determines the level of illumination deviation and outputs a graded compensation strategy to drive the LED control unit to perform voltage or current regulation, thereby achieving stable maintenance of cell irradiation intensity and ensuring the timeliness, consistency, and reproducibility of the optogenetic stimulation process.
[0006] A method for controlling the stable illumination of optogenetic cells based on irradiance negative feedback regulation, wherein the control method is applied in an illumination control device, the illumination control device comprising a cell culture incubator, a black light shield 1, a culture dish 2 for holding optogenetic genetically modified cells placed inside the black light shield 1, uniformly arranged LED light sources 4 and irradiance monitoring probes 3, wherein the LED light sources 4 are positioned above the culture dish 2, and the irradiance monitoring probes 3 are attached to the bottom of the culture dish 2, with their tops flush with the optogenetic genetically modified cells, characterized in that the control method includes the following steps: S1, In a cell culture incubator, a black light shield 1 is sealed to form a light space that isolates external light interference. The LED light source 4 is controlled to uniformly irradiate the optogenetic gene-modified cells in the culture dish 2. The initial irradiance data of the cells irradiated by the LED light source 4 is obtained by the irradiance detector 5 which is electrically connected to the cell culture incubator. S2, continuously acquire the current real-time irradiance data of LED light source 4 using an irradiance detector, and compare it with the initial irradiance data to generate irradiance offset information reflecting the irradiance fluctuation of LED light source 4; S3. Based on historical time series illumination shift information, construct an illumination fluctuation prediction model to describe the trend of illumination change. By analyzing the approximate periodic or nonlinear fluctuation characteristics and trends, predict the potential irradiance shift trend within a predetermined time in the future. S4. Based on the illumination offset information between the current time and the predicted time period, calculate the comprehensive error index characterizing illumination stability, and combine it with the set threshold to determine whether the offset level of the current LED output has reached the state of needing to perform strong compensation, weak compensation or remain unchanged, and generate a compensation level strategy. S5, the compensation level strategy is input to the LED light source control unit, and the driving voltage or current is adjusted according to the compensation level strategy to realize automatic compensation of the LED output light intensity, so that the irradiance finally irradiated to the optogenetic modified cells is stably maintained near the initial reference level.
[0007] Optionally, S2 includes: S21, Using an irradiance detector 5, the bottom of the culture dish 2 is continuously measured at preset time intervals to obtain real-time irradiance data of multiple points in the LED light source irradiation area at the current moment, forming the current irradiance vector. ; S22, Based on the collected initial irradiance data, construct a baseline irradiance vector. ; S23, For each monitoring point, calculate the illumination offset between its real-time irradiance data and the initial irradiance data. The illumination offset vector is obtained. .
[0008] Optionally, S3 includes: S31, the continuously acquired illumination offset information is constructed into a multi-point time series matrix according to the sampling time order, where each item corresponds to the illumination offset of a monitoring point. Based on the multi-point time series matrix, illumination change features are extracted, including local offset slope, fluctuation frequency, offset variance and local extreme value change rate. S32, based on the extracted illumination change characteristics, construct an illumination fluctuation prediction model, and output the potential offset trend map of each measuring point within the future predetermined time window, which is used to determine whether there is a trend of LED illumination decay, periodic drift or disturbance amplification.
[0009] Optionally, S31 includes: S311, the illumination offset information acquired in chronological order is stored as a multi-point time series matrix. ; S312, perform first-order differencing on the time series of each monitoring point to obtain the local offset slope. ; S313, Perform zero-crossing statistics on the offset sequence of each monitoring point to calculate the fluctuation frequency. ; S314, Calculate the offset variance for each monitoring point. and the rate of change of local extrema It is used to quantify the overall fluctuation of illumination shift and the magnitude of sudden drift.
[0010] Optionally, S32 includes: S321, the illumination shift time series of each monitoring point The time frame is divided into fixed-length sliding windows to capture local change patterns. Each sliding time window corresponds to a training sample, forming a prediction dataset, represented as follows: ; in, For the first Each monitoring point is in A sliding window sequence starting from [starting point] The length of the window; S322, based on the sliding window training samples constructed for each monitoring point, uses an exponentially weighted moving average (EWMA) model to predict future... Predict using step offset values; S323, will bring all monitoring points to the future The predicted offset values at each moment are combined to form a trend prediction map, and pattern recognition is performed based on the trend prediction map. When a continuous downward trend is observed, it is judged as light source attenuation. When periodic up or down fluctuations are observed, it is judged as periodic drift. When the offset amplitude is rapidly expanding, it is judged as a disturbance amplification risk.
[0011] Optionally, S4 includes: S41, based on the current illumination offset information and the predicted offset trend within the future predetermined time window, the offsets of multiple measurement points and multiple times are fused and processed to calculate a comprehensive error index characterizing the overall fluctuation of illumination, which is used to reflect the instantaneous offset amplitude of the current illumination and the offset risk of the future trend. S42 compares the comprehensive error index with the preset multi-level compensation threshold range, classifies the current offset level of LED light source 4 according to the degree of error, determines whether it is a slight offset, obvious offset or severe offset, and corresponds to the compensation level strategy of keeping it unchanged, performing weak compensation or performing strong compensation respectively.
[0012] Optionally, S41 includes: S411, the illumination offset of all monitoring points at the current moment. The fusion process is performed, and the instantaneous illumination shift intensity is calculated using the average absolute shift method. It is used to measure the instantaneous fluctuation of the current LED output; S412, calculating the future Offset trend value at each prediction time By integrating data from all monitoring points and across the entire forecast period, the risk intensity of future trend shifts can be determined. This is used to measure the potential risk of future illumination shifts; S413, the current instantaneous illumination shift intensity Risk intensity of deviation from future trends The fusion is performed using a weighted method to obtain a comprehensive error index that characterizes the overall stability level of illumination. .
[0013] Optionally, S42 includes: S421, based on the requirements of illumination stability, sets the boundary value between slight and significant deviation. And the dividing line between obvious and severe deviations. Through comprehensive error index Determine the different levels of offset when At that time, it was determined to be a slight deviation. When, it is judged as a significant deviation, when At that time, it was determined to be a severe deviation; S422, based on the determined offset level, maps the corresponding compensation level strategy, specifically including: If the offset level range is slightly offset, then it remains unchanged; If the offset level range is a significant offset, then weak compensation is performed; If the offset level range is a severe offset, then strong compensation will be performed.
[0014] Optionally, S5 includes: S51, Receiver output compensation level strategy And convert it into the corresponding current or voltage regulation strategy code, where, This indicates that the current output will remain unchanged, with no adjustment. This indicates the implementation of weak compensation. This indicates that strong compensation will be implemented; S52, based on the current comprehensive error index Compensation level strategy as determined The required voltage or current compensation increment is calculated using a piecewise linear regulation model. ; S53, calculates the voltage or current compensation increment. Add the current driving voltage or current base value Generate updated control signals The light intensity is then output to the LED light source control unit, so that the LED output light intensity is corrected to the target irradiance in real time.
[0015] The beneficial effects of this invention are: This invention, by setting up a uniformly distributed LED light source at the top and an irradiance monitoring probe flush with the bottom in a cell culture incubator, combined with a black light shield to form a stable and closed lighting environment, can effectively avoid external light interference, significantly improve the uniformity of light in the irradiated area, and enable optogenetic cells to obtain consistent light stimulation conditions, providing a reliable foundation for long-term high-precision experiments.
[0016] This invention constructs a closed-loop adjustment mechanism that includes initial reference illuminance acquisition, real-time monitoring, time series modeling, offset prediction, and error judgment. By linking comprehensive error indicators with multi-level compensation strategies, it achieves intelligent dynamic control of LED light intensity. This effectively solves the problem of unstable illumination caused by LED attenuation and environmental fluctuations in existing technologies. It significantly reduces the long-term drift rate of light intensity from the approximately ±10% level common in traditional systems and can stably control the irradiance within approximately ±2%, thereby ensuring that the irradiance received by cells is stably maintained within the set range.
[0017] This invention introduces characteristic parameters such as local slope, variance, fluctuation frequency, and extreme value change rate of illumination offset, and uses an exponentially weighted sliding window model to predict future offset trends. It has the ability to proactively identify abnormal changes in illumination and can determine in advance whether the light source has attenuation, periodic drift, or disturbance amplification trend, thereby triggering corresponding compensation measures more timely and accurately, and improving the responsiveness and robustness of the overall illumination control system. Attached Figure Description
[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0019] Figure 1 This is a schematic diagram of the control method flow according to an embodiment of the present invention; Figure 2 This is an exploded view of the light control device according to an embodiment of the present invention, wherein 1 represents a black light shield, 2 represents a petri dish, 3 represents an irradiance monitoring probe, 4 represents an LED light source, and 5 represents an irradiance detector. Figure 3 This is a schematic diagram of a light control device according to an embodiment of the present invention. Detailed Implementation
[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Those skilled in the art may employ other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.
[0021] like Figures 1-3As shown, a method for controlling the stable illumination of optogenetic cells based on irradiance negative feedback regulation is disclosed. The method is applied in a light control device, which includes a cell culture incubator, a black light shield 1, a culture dish 2 for holding optogenetic cells placed inside the black light shield 1, uniformly distributed LED light sources 4, and an irradiance monitoring probe 3. The LED light source 4 is positioned above the culture dish 2, and the irradiance monitoring probe 3 is attached to the bottom of the culture dish 2, with its top flush with the optogenetic cells. The control method includes the following steps: S1, In a cell culture incubator, a black light shield 1 is sealed to form a light space that isolates external light interference. The LED light source 4 is controlled to uniformly irradiate the optogenetic gene-modified cells in the culture dish 2. The initial irradiance data of the cells irradiated by the LED light source 4 is obtained by the irradiance detector 5 which is electrically connected to the cell culture incubator. S2, continuously acquire the current real-time irradiance data of LED light source 4 using an irradiance detector, and compare it with the initial irradiance data to generate irradiance offset information reflecting the irradiance fluctuation of LED light source 4; S3. Based on historical time series illumination shift information, construct an illumination fluctuation prediction model to describe the trend of illumination change. By analyzing the approximate periodic or nonlinear fluctuation characteristics and trends, predict the potential irradiance shift trend within a predetermined time in the future. S4. Based on the illumination offset information between the current time and the predicted time period, calculate the comprehensive error index characterizing illumination stability, and combine it with the set threshold to determine whether the offset level of the current LED output has reached the state of needing to perform strong compensation, weak compensation or remain unchanged, and generate a compensation level strategy. S5 inputs the compensation level strategy to the LED light source control unit, and adjusts the driving voltage or current according to the compensation level strategy to realize automatic compensation of the LED output light intensity, so that the irradiance finally irradiated to the optogenetic modified cells is stably maintained near the initial reference level.
[0022] S2 includes: S21, Using an irradiance detector 5, the bottom of the culture dish 2 is continuously measured at preset time intervals to obtain real-time irradiance data of multiple points in the LED light source irradiation area at the current moment, forming the current irradiance vector. , is represented as: ; in, For the first The irradiance value at each measuring point at the current moment. , The number of irradiance monitoring points; S22, Based on the collected initial irradiance data, construct a baseline irradiance vector. , is represented as: ; in, For the first The reference irradiance value recorded at each measuring point at the initial moment; S23, For each monitoring point, calculate the illumination offset between its real-time irradiance data and the initial irradiance data. The illumination offset vector is obtained. , is represented as: ; ; in, For the first Illumination offset at each monitoring point.
[0023] S3 includes: S31, the continuously acquired illumination offset information is constructed into a multi-point time series matrix according to the sampling time order, where each item corresponds to the illumination offset of a monitoring point. Based on the multi-point time series matrix, illumination change features are extracted, including local offset slope, fluctuation frequency, offset variance and local extreme value change rate. S32, based on the extracted illumination change characteristics, construct an illumination fluctuation prediction model, and output the potential offset trend map of each measuring point within the future predetermined time window, which is used to determine whether there is a trend of LED illumination decay, periodic drift or disturbance amplification.
[0024] S31 includes: S311, the illumination offset information acquired in chronological order is stored as a multi-point time series matrix. , is represented as: ; in, The length of the time series; S312, perform first-order differencing on the time series of each monitoring point to obtain the local offset slope. , is represented as: ; S313, Perform zero-crossing statistics on the offset sequence of each monitoring point to calculate the fluctuation frequency. , is represented as: ; in, For the first The number of sign changes (alternating positive and negative) in the offset sequence of each monitoring point. This represents the sampling time length of the corresponding sequence; S314, Calculate the offset variance for each monitoring point. and the rate of change of local extrema This is used to quantify the overall fluctuation and sudden drift amplitude of illumination shift, and is expressed as: ; ; in, For the first The monitoring point at the 1st The illumination offset value at each moment For the first The average illumination shift of each monitoring point at all sampling times.
[0025] S32 includes: S321, the illumination shift time series of each monitoring point The time frame is divided into fixed-length sliding windows to capture local change patterns. Each sliding time window corresponds to a training sample, forming a prediction dataset, represented as follows: ; in, For the first Each monitoring point is in A sliding window sequence starting from [starting point] The length of the window; S322, based on the sliding window training samples constructed for each monitoring point, uses an exponentially weighted moving average (EWMA) model to predict future... The step offset value is used for prediction, represented as: ; in, For the first Each monitoring point at time The predicted offset, For smoothing coefficients, The initial value can be set to the predicted value from the previous moment, and can be set to the actual observed offset. ; S323, will bring all monitoring points to the future The predicted offset values at each moment are combined to form a trend prediction map. Pattern recognition is then performed based on this trend prediction map. When a continuous downward trend is observed, it is identified as light source attenuation. When periodic up-and-down fluctuations are observed, it is identified as periodic drift. When the offset amplitude increases rapidly, it is identified as a disturbance amplification risk, as shown below: .
[0026] S4 includes: S41, based on the current illumination offset information and the predicted offset trend within the future predetermined time window, the offsets of multiple measurement points and multiple times are fused and processed to calculate a comprehensive error index characterizing the overall fluctuation of illumination, which is used to reflect the instantaneous offset amplitude of the current illumination and the offset risk of the future trend. S42 compares the comprehensive error index with the preset multi-level compensation threshold range, classifies the current offset level of LED light source 4 according to the degree of error, determines whether it is a slight offset, obvious offset or severe offset, and corresponds to the compensation level strategy of keeping it unchanged, performing weak compensation or performing strong compensation respectively.
[0027] S41 includes: S411, the illumination offset of all monitoring points at the current moment. The fusion process is performed, and the instantaneous illumination shift intensity is calculated using the average absolute shift method. This is used to measure the instantaneous fluctuation of the current LED output, and is expressed as: ; in, Number of monitoring points; S412, calculating the future Offset trend value at each prediction time By integrating data from all monitoring points and across the entire forecast period, the risk intensity of future trend shifts can be determined. This is used to measure the potential risk of future illumination shift, and is expressed as: ; S413, the current instantaneous illumination shift intensity Risk intensity of deviation from future trends The fusion is performed using a weighted method to obtain a comprehensive error index that characterizes the overall stability level of illumination. , is represented as: ; in, This is the instantaneous offset weighting coefficient.
[0028] S42 includes: S421, based on the requirements of illumination stability, sets the boundary value between slight and significant deviation. And the dividing line between obvious and severe deviations. Through comprehensive error index Determine the different levels of offset when At that time, it was determined to be a slight deviation. When, it is judged as a significant deviation, when At that time, it was determined to be a severe deviation; The dividing line between slight and obvious deviation Represented as: ; in, These are empirical weighting coefficients. For the number of monitoring points, For the first Each monitoring point at time Illumination offset, This is the set of sampling times during the short-term stable period; The dividing line between obvious and severe deviations Represented as: ; in, To enhance the factor coefficient, As a safety compensation factor for local fluctuations, The average range of all monitoring points; S422, based on the determined offset level, maps the corresponding compensation level strategy, specifically including: If the offset level range is slightly offset, then it remains unchanged; If the offset level range is a significant offset, then weak compensation is performed; If the offset level range is a severe offset, then strong compensation will be performed.
[0029] S5 includes: S51, Receiver output compensation level strategy And convert it into the corresponding current or voltage regulation strategy code, where, This indicates that the current output will remain unchanged, with no adjustment. This indicates the implementation of weak compensation. This indicates that strong compensation will be implemented; S52, based on the current comprehensive error index Compensation level strategy as determined The required voltage or current compensation increment is calculated using a piecewise linear regulation model. , is represented as: ; in, , The control gain coefficients corresponding to weak compensation and strong compensation, respectively, satisfy the following conditions: ; S53, calculates the voltage or current compensation increment. Add the current driving voltage or current base value Generate updated control signals The output is then sent to the LED light source control unit, so that the LED output light intensity is corrected to the target irradiance in real time, as shown below: .
[0030] Specific examples are as follows: Set the target irradiance to The target value is used as the initial irradiance reference. Irradiance detector 5 selects four monitoring points at the bottom of the culture dish 2 corresponding to the LED illumination area for simultaneous monitoring. The reference irradiance vector acquired at the initial moment is: ; That is, the initial irradiance of the four monitoring points are respectively , , and After 5 minutes of continuous irradiation, the irradiance detector 5 detected the current real-time irradiance vector as follows: ; The illumination offsets at each monitoring point are as follows: ; Therefore, it can be seen that the output of LED light source 4 has decreased overall at this point, exhibiting a relatively obvious uniform decay. Furthermore, the system continuously records the illumination shift information over the first 5 minutes and constructs the time series for each monitoring point. Taking a typical monitoring point as an example, its shift sequence from minute 1 to minute 5 can be as follows: ; The following illumination variation characteristics can be extracted from this sequence: 1. The local offset slope gradually increases, indicating that the rate of irradiance decay is accelerating; 2. The low fluctuation frequency indicates that the change is not a high-frequency random disturbance, but rather closer to a continuous downward trend; 3. The relatively small variance of the offset but the continuous increase in the rate of change of extreme values indicates that the offset is relatively smooth at each time point, but the overall downward trend is clear.
[0031] Based on this, the system uses an exponentially weighted moving average model for prediction. Assuming a smoothing coefficient of 0.6, the predicted offset value for this monitoring point in the next 10 minutes can be estimated from recent offsets. This means that the irradiance at the monitoring point is predicted to decrease to approximately 10 minutes later. ; The prediction results for other monitoring points can be approximated as follows: ; This generates a potential offset trend map for future periods, based on which the system determines that the current LED light source exhibits a continuous attenuation trend. Subsequently, the system enters the comprehensive error calculation stage. The average absolute value of the offset at the four monitoring points at the current moment is: ; That is, the instantaneous light offset intensity is During the future forecast period, the average predicted offset for each monitoring point is approximately... Based on this calculation, the risk intensity of future trend deviation is acceptable: ; Assuming the instantaneous offset weighting coefficient is 0.4, the comprehensive error index is: ; In this embodiment, the dividing line between slight and significant deviation is set to a value. The dividing line between obvious and severe deviation is _____. ,Right now: when At that time, it was determined to be a slight Microsoft offset; when At that time, it was determined to be a significant deviation; when At that time, it was determined to be a severe deviation.
[0032] Due to the comprehensive error index in this embodiment greater than Therefore, the system determines that the current LED light source 4 is in a severely offset state and generates a strong compensation strategy.
[0033] During the compensation phase, the LED light source control unit receives the compensation level strategy. Assume that the compensation level coding remains unchanged as follows: Weak compensation is Strong compensation is Therefore, the output compensation level code in this embodiment is: ; Furthermore, let the current comprehensive error index be... The strong compensation control gain coefficient is taken as The current compensation increment is: ; If the current LED driving current base value is The updated drive current is: ; The control unit outputs the updated drive current to LED light source 4, increasing its luminous intensity. Approximately [time missing] after compensation is performed. After a second check within minutes, the real-time irradiance vector was restored to: ; Its average irradiance is approximately The irradiance has recovered to near the initial baseline level, indicating that the compensation strategy effectively suppressed the decrease in irradiance caused by LED thermal drift and light decay.
[0034] Furthermore, in another scenario with a smaller offset, if the system detects that the average irradiance has only decreased to 97 after 5 minutes... It is predicted that it will drop to about 95 in about 10 minutes. If this is achieved, a lower overall error index can be obtained, such as 5. In this case, the system determines that there is a significant offset and only triggers a weak compensation strategy. By slightly increasing the driving current or voltage, the light intensity can be restored to near the initial reference, thereby avoiding overcompensation.
[0035] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A method for optogenetic cell illumination stable control based on irradiance negative feedback regulation, the control method is applied to an illumination control device, the illumination control device comprises a cell culture dedicated incubator, a black light shield, a culture dish for carrying optogenetic genetically modified cells arranged in the black light shield, a uniformly arranged LED light source arranged above the culture dish, and an irradiance monitoring probe closely attached to the bottom of the culture dish with its top flush with the optogenetic genetically modified cells, characterized in that, The control method includes the following steps: S1. In a cell culture incubator, a black light shield is sealed to form a light space that isolates external light interference. The LED light source is controlled to uniformly irradiate the optogenetic cells in the culture dish. The initial irradiance data of the LED light source irradiating the cell surface is obtained by an irradiance detector electrically connected to the cell culture incubator. S2, continuously acquire the current real-time irradiance data of the LED light source using an irradiance detector, compare it with the initial irradiance data, and generate irradiance offset information that reflects the irradiance fluctuation of the LED light source; S3. Based on historical time series illumination shift information, construct an illumination fluctuation prediction model to describe the trend of illumination change. By analyzing the approximate periodic or nonlinear fluctuation characteristics and trends, predict the potential irradiance shift trend within a predetermined time in the future. S4. Based on the illumination offset information between the current time and the predicted time period, calculate the comprehensive error index characterizing the illumination stability, and combine it with the set threshold to determine whether the offset level of the current LED output has reached the state of needing to perform strong compensation, weak compensation or remain unchanged, and generate a compensation level strategy, including maintaining unchanged, performing weak compensation and performing strong compensation. S5, the compensation level strategy is input to the LED light source control unit, and the driving voltage or current is adjusted according to the compensation level strategy to realize automatic compensation of the LED output light intensity, so that the irradiance finally irradiated to the optogenetic modified cells is stably maintained near the initial reference level.
2. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 1, characterized in that, S2 includes: S21, Using an irradiance detector, continuously measure the bottom of the culture dish at preset time intervals to obtain real-time irradiance data of multiple points in the LED light source irradiated area at the current moment, forming the current irradiance vector. ; S22, Based on the collected initial irradiance data, construct a baseline irradiance vector. ; S23, For each monitoring point, calculate the illumination offset between its real-time irradiance data and the initial irradiance data. The illumination offset vector is obtained. .
3. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 2, characterized in that, S3 includes: S31, the continuously acquired illumination offset information is constructed into a multi-point time series matrix according to the sampling time order, where each item corresponds to the illumination offset of a monitoring point. Based on the multi-point time series matrix, illumination change features are extracted, including local offset slope, fluctuation frequency, offset variance and local extreme value change rate. S32, based on the extracted illumination change characteristics, construct an illumination fluctuation prediction model, and output the potential offset trend map of each measuring point within the future predetermined time window, which is used to determine whether there is a trend of LED illumination decay, periodic drift or disturbance amplification.
4. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 3, characterized in that, S31 includes: S311, the illumination offset information acquired in chronological order is stored as a multi-point time series matrix. ; S312, perform first-order differencing on the time series of each monitoring point to obtain the local offset slope. ; S313, Perform zero-crossing statistics on the offset sequence of each monitoring point to calculate the fluctuation frequency. ; S314, Calculate the offset variance for each monitoring point. and the rate of change of local extrema It is used to quantify the overall fluctuation of illumination shift and the magnitude of sudden drift.
5. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 4, characterized in that, S32 includes: S321, the illumination shift time series of each monitoring point The time frame is divided into fixed-length sliding windows to capture local change patterns. Each sliding time window corresponds to a training sample, forming a prediction dataset, represented as follows: ； in, For the first Each monitoring point is in A sliding window sequence starting from [starting point] The length of the window; S322, based on the sliding window training samples constructed for each monitoring point, uses an exponentially weighted moving average model to predict future... Predict using step offset values; S323, will bring all monitoring points to the future The predicted offset values at each moment are combined to form a trend prediction map, and pattern recognition is performed based on the trend prediction map. When a continuous downward trend is observed, it is judged as light source attenuation. When periodic up or down fluctuations are observed, it is judged as periodic drift. When the offset amplitude is rapidly expanding, it is judged as a disturbance amplification risk.
6. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 5, characterized in that, S4 includes: S41, based on the current illumination offset information and the predicted offset trend within the future predetermined time window, the offsets of multiple measurement points and multiple times are fused and processed to calculate a comprehensive error index characterizing the overall fluctuation of illumination, which is used to reflect the instantaneous offset amplitude of the current illumination and the offset risk of the future trend. S42 compares the comprehensive error index with the preset multi-level compensation threshold range, classifies the current LED light source offset level according to the degree of error, determines whether it is a slight offset, obvious offset or severe offset, and corresponds to the compensation level strategy of keeping it unchanged, performing weak compensation or performing strong compensation respectively.
7. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 6, characterized in that, S41 includes: S411, the illumination offset of all monitoring points at the current moment. The fusion process is performed, and the instantaneous illumination shift intensity is calculated using the average absolute shift method. It is used to measure the instantaneous fluctuation of the current LED output; S412, calculating the future Offset trend value at each prediction time By integrating data from all monitoring points and across the entire forecast period, the risk intensity of future trend shifts can be determined. This is used to measure the potential risk of future illumination shifts; S413, the current instantaneous illumination shift intensity Risk intensity of deviation from future trends The fusion is performed using a weighted method to obtain a comprehensive error index that characterizes the overall stability level of illumination. .
8. The optogenetic cell light stabilization control method based on irradiance negative feedback regulation according to claim 7, characterized in that, S42 includes: S421, based on the requirements of illumination stability, sets the boundary value between slight and significant deviation. And the dividing line between obvious and severe deviations. Through comprehensive error index Determine the different levels of offset when At that time, it was determined to be a slight deviation. When, it is judged as a significant deviation, when At that time, it was determined to be a severe deviation; S422, based on the determined offset level, maps the corresponding compensation level strategy, specifically including: If the offset level range is slightly offset, then it remains unchanged; If the offset level range is a significant offset, then weak compensation is performed; If the offset level range is a severe offset, then strong compensation will be performed.
9. The optogenetic method for stable control of cell light intensity based on irradiance negative feedback regulation according to claim 8, characterized in that, S5 includes: S51, Receiver output compensation level strategy And convert it into the corresponding current or voltage regulation strategy code, where, This indicates that the current output will remain unchanged, with no adjustment. This indicates the implementation of weak compensation. This indicates that strong compensation will be implemented; S52, based on the current comprehensive error index Compensation level strategy as determined The required voltage or current compensation increment is calculated using a piecewise linear regulation model. ; S53, calculates the voltage or current compensation increment. Add the current driving voltage or current base value Generate updated control signals The light intensity is then output to the LED light source control unit, so that the LED output light intensity is corrected to the target irradiance in real time.