Method for simulating digestion of monogastric animals' small intestine based on peristalsis-like control

Abstract

The application provides a monogastric animal small intestine digestion simulation method based on peristaltic control, relates to the technical field of small intestine digestion simulation analysis, and collects and screens initial digestion liquid secretion rate curves of multiple batches of tests of target type monogastric animals under a unified time reference, then obtains a target aggregate curve capable of representing small intestine secretion dynamics characteristics through aggregate modeling, and screens a high activity time window from the target aggregate curve, and then the small intestine digestion process is segmented into a starting ramp-up section, a high activity section and a decay long tail section, and the digestion liquid drip rate sequence corresponding to each section is determined to initialize the peristaltic control parameters of the small intestine simulator device, and the key process parameters are monitored in real time during the operation of the device, and the peristaltic control parameters are dynamically optimized, so that the data-driven setting, segmented fine control and integrated cooperation of mechanical peristaltic rhythm and chemical secretion peak timing of the peristaltic control parameters are realized.

Description

Technical Field

[0001] This invention relates to the field of small intestinal digestion simulation and analysis technology, and in particular to a method for simulating small intestinal digestion in monogastric animals based on peristalsis control. Background Technology

[0002] In animal nutrition, feed formulation evaluation, and in vivo behavior prediction of oral drugs, the digestion and absorption process in the small intestine of monogastric animals plays a decisive role. The small intestine is not only the main site of final degradation and absorption of nutrients such as proteins, fats, and starches, but also a key link in the release, transport, and inactivation of various functional additives and oral formulations. Traditional research mainly relies on in vivo feeding trials and fistula sampling to obtain information on small intestinal contents and digestive fluids. However, such in vivo trials are time-consuming, involve significant individual animal variations, and are difficult to controllably intervene in single variables, hindering large-scale formulation screening and mechanistic parameter studies. To reduce the scale of in vivo trials and improve evaluation efficiency, there is an urgent need to construct an in vitro method and device that closely approximates the actual physiological state of monogastric animals to simulate small intestinal digestion. Through controllable peristaltic movements and digestive fluid administration, standardized and reproducible simulations and evaluations of small intestinal digestive behavior under different formulations and operating conditions can be achieved.

[0003] Existing monogastric animal small intestine simulation devices typically use a reaction chamber driven by a constant-temperature water bath or flexible tubing as the simulated small intestine lumen, and are equipped with several subsystems to complete fluid transport and environmental control. For example, peristaltic pumps, solenoid valves or injection pumps are used to quantitatively deliver chyme and digestive juices, stirrers and periodic squeezing devices are used to simulate intestinal wall peristalsis and mixing, constant-temperature water baths or heating mantles are used to maintain temperature conditions close to body temperature, pH electrodes, dissolved oxygen electrodes, online turbidity or conductivity sensors are used to monitor changes in the lumen environment, and sampling ports are set up as needed to collect simulated small intestine contents at regular intervals. In a typical simulation process, researchers first add a preset amount of artificial chyme into the simulated small intestine lumen. They then drive a squeezing device according to a pre-set program to squeeze or propel the food at a fixed frequency and stroke. Simultaneously, digestive fluids such as pancreatic juice and bile are added at a constant or segmented rate according to a preset schedule. Throughout the entire operation cycle, a constant temperature is maintained, and the contents of the lumen are sampled at regular intervals or monitored online to obtain nutrient degradation rates, drug dissolution rates, and related physicochemical indicators at different time points. This allows researchers to evaluate the digestive characteristics of feed formulations or preparations in the small intestine.

[0004] For example, Chinese invention patent CN109596837B discloses an in vitro biomimetic digestion method for rapidly determining the digestibility of pig feed protein, which includes the following steps: pulverizing the feed sample and passing it through a standard sieve; preparing gastric buffer and small intestinal buffer; preparing simulated gastric juice, concentrating simulated small intestinal juice, and concentrating supplemented small intestinal juice; placing the gastric buffer and small intestinal buffer into the incubator of a monogastric animal biomimetic digestion system and connecting the pipes connected to the simulated digester; placing the pulverized feed sample into the simulated digester, adding simulated gastric juice, and then placing it into the monogastric animal biomimetic digestion system; automatically completing the in vitro biomimetic digestion process of pig feed protein by setting the biomimetic digestion parameters of each stage of the stomach and small intestine through the control software of the biomimetic digestion system.

[0005] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0006] Existing small intestine simulation devices prioritize engineering implementation in peristalsis control, simplifying peristalsis control into rhythmic modes with fixed frequency, fixed amplitude, or switching only between a few levels. The setting of peristalsis parameters usually only refers to macroscopic statistical indicators such as the average total residence time of the small intestine and the total amount of digestive juice secretion measured in vivo. Based on this, the complete digestion process in vivo is linearly compressed into a uniform in vitro running time at a single ratio, and the flow rate of digestive juice is amplified or scaled up in the same proportion.

[0007] Because this approach assumes that the early postprandial secretion ramp-up process, the highly active phase of secretion and peristalsis in high coordination, and the late postprandial decay long-tail phase are homogeneous time slices that can be scaled proportionally, it fails to distinguish the rhythmic changes of different physiological stages on the time axis. This results in the in vitro peristaltic rhythm and the instantaneous secretion rate of digestive juices being forcibly constrained into a simple linear correspondence throughout the entire process. On the one hand, the nonlinear characteristics that exist in vivo are excessively smoothed out. The ramp-up phase of secretion and peristalsis that rises rapidly in the short period after feeding, the relatively stable but highly sensitive high-activity window near the peak, and the long-tail phase of secretion that decays slowly and is easily affected by external interference are all flattened into the same rhythm in vitro. This makes it difficult to reflect the essential differences in the propulsion, mixing, and local secretion intensity of each stage, thereby weakening the ability of in vitro simulation to represent the real small intestinal digestive dynamics. Summary of the Invention

[0008] To address the technical problem that existing technologies weaken the ability of in vitro simulations to represent the real small intestinal digestive dynamics, embodiments of the present invention provide a method for simulating small intestinal digestion in monogastric animals based on peristalsis-like control. The technical solution is as follows:

[0009] On the one hand, a method for simulating small intestinal digestion in monogastric animals based on peristaltic control is provided. This method includes: Step 1, collecting initial digestive fluid secretion rate curves corresponding to different batches of experiments in monogastric animals of different target types, aligning each initial digestive fluid secretion rate curve to a unified time axis using the time of feeding completion as the time reference, and selecting each effective digestive fluid secretion rate curve; Step 2, analyzing the target aggregated curves that can reflect the secretion law of digestive fluid in the small intestine of the target type of monogastric animals through aggregation modeling, and selecting high-activity windows from the target aggregated curves; Step 3, based on the high-activity windows, transforming the small intestinal digestion process of monogastric animals into an in vitro experimental simulation process, dividing the in vitro experimental simulation process into an initiation ramp segment, a high-activity segment, and a decay long tail segment, determining the digestive fluid dripping rate sequence corresponding to each segment, thereby initializing the peristaltic control parameters of the small intestinal simulator device; Step 4, monitoring the operation process of the small intestinal simulator device, collecting monitoring results, and optimizing the peristaltic control parameters of the small intestinal simulator device based on the monitoring results.

[0010] Beneficial effects

[0011] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0012] 1. The present invention provides a method for simulating small intestinal digestion in monogastric animals based on simulated peristalsis control. This method involves collecting and screening initial digestive fluid secretion rate curves from multiple batches of experiments on target-type monogastric animals under a unified time reference. Then, through aggregation modeling, a target aggregated curve characterizing the small intestinal secretion dynamics is obtained, and a high-activity time window is selected from it. The small intestinal digestion process is then segmented into an initiation ramp-up segment, a high-activity segment, and a decay long-tail segment. The digestive fluid dripping rate sequence corresponding to each segment is determined to initialize the simulated peristalsis control parameters of the small intestinal simulator device. Simultaneously, key process parameters are monitored in real time during device operation, and the simulated peristalsis control parameters are dynamically optimized. This allows the in vitro simulated peristalsis control to be established based on multiple batches of in vivo measured data. Based on statistical regularities, this method can not only finely reconstruct the secretion-peristalsis coupling characteristics of the high-activity stage within a unified short-term simulation window, but also reasonably simplify the timing and total amount matching of the initiation and long-tail stages. This achieves data-driven setting of peristalsis control parameters, segmented fine control, and integrated coordination of mechanical peristalsis rhythm and chemical secretion peak timing. Overall, it improves the physiological relevance, repeatability, and cross-formulation comparability of small intestinal digestion simulation results. It effectively solves the technical problems in existing technologies, such as peristalsis control parameters mainly relying on experience and linear compression setting, simple homogenization of rhythms in different digestion stages, and misalignment of mechanical peristalsis and digestive fluid secretion at key timing, making it difficult to objectively evaluate different diet formulations and working conditions.

[0013] 2. This invention selects a functional form to describe the average secretion trajectory of a population within a unified characteristic time period, constructs a population-individual mixed-effects model, obtains the secretion rate observations of each core sample curve and each reference sample curve at each time point, and uses maximum likelihood estimation or Bayesian estimation to solve for the objective function reflecting the common laws of the population and the individual offsets of each experimental animal. Thus, under the premise of fully eliminating the influence of random noise and explicitly separating individual differences, a target aggregation curve that can accurately characterize the temporal characteristics of small intestinal digestive fluid secretion in monogastric animals of the target type is obtained. Based on this, robust selection of animals with statistical characteristics is performed from this target aggregation curve. By calculating a highly active time window that is representative and physiologically significant, this approach achieves systematic integration and nonlinear feature reconstruction of multiple batches of in vivo measured data at a unified time scale, compared to simple arithmetic averages or single representative curve selection methods. This allows the calibration curves upon which the in vitro peristalsis-like control design relies to reflect the true secretory dynamics of the population without being excessively affected by extreme individuals and tail noise. This fundamentally improves the accuracy and stability of identifying highly active windows and effectively alleviates the technical problems in existing technologies, such as the reliance on experience-based selection of target curves, the difficulty in balancing population patterns and individual differences, and the resulting distortion in time scale mapping and control parameter design.

[0014] 3. This invention constructs a nonlinear time mapping function constrained by a high-activity time window in vivo. The in vivo small intestinal digestion process is divided into an initiation ramp segment, a high-activity segment, and a decay long-tail segment based on the start and end times of the high-activity window. For each segment, a time mapping sub-function satisfying continuity and monotonicity is constructed, thereby applying differentiated time compression strategies to different stages within a unified short-time operating interval in vitro. Based on this, the secretion rate-time curve segment of the target aggregation curve within the high-activity window is extracted. The digestive fluid secretion rate is corrected and mapped according to the ratio between the effective volume of the small intestine in vivo and the volume of the simulated cavity in vitro, resulting in a digestive fluid dripping rate sequence of the small intestinal simulator within the high-activity window. Furthermore, constrained by the total secretion amount and average secretion intensity of each stage in vivo, a low-intensity dripping curve for the initiation ramp segment and the decay long-tail segment, smoothly connected to the beginning and end of the high-activity segment, is constructed, forming a sequence that balances total amount and stage order. The above is equivalent to the segmented digestive fluid addition control trajectory of the in vivo process. Furthermore, based on the mapped digestive fluid secretion rate of each stage, matching peristaltic frequency, squeezing force and propulsion speed parameters are set in the corresponding time interval. The mechanical peristaltic rhythm and chemical secretion peak are integrated and coordinated on the time axis, thereby avoiding the systematic misalignment of secretion peak and peristaltic enhancement period caused by simple linear time compression and proportional flow amplification in the prior art. It effectively prevents the high-activity stage from being over-compressed, the long-tail stage from occupying too much time, and the generation of non-physiological peaks. Thus, it realizes the fine reconstruction of the climbing, high-activity and decay stages of the small intestine digestion process of monogastric animals under uniform short-term operation conditions in vitro. It significantly improves the representativeness and comparability of the peristaltic control parameters to the real digestive kinetics in vivo, and provides higher physiological relevance and reproducibility for standardized evaluation of different diet formulations and different working conditions. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart of a method for simulating small intestinal digestion in a monogastric animal based on simulated peristalsis control, provided in an embodiment of this application;

[0017] Figure 2 A detailed flowchart simulating the digestion of the small intestine in a monogastric animal, provided in the embodiments of this application;

[0018] Figure 3 Schematic diagram of the small intestine simulation device provided in the embodiments of this application Figure 1 ;

[0019] Figure 4 Schematic diagram of the small intestine simulation device provided in the embodiments of this application Figure 2 ;

[0020] Attached reference numerals: 1. Small intestine container; 2. Lid; 3. Small intestine digestive fluid container; 4. Small intestine digestive fluid conduit; 5. Valve; 6. Small intestine gripper frame; 7. Gripper guide rail; 8. Gripper end; 9. Electric cylinder telescopic rod frame; 10. Electric cylinder telescopic rod; 11. Electric push rod motor; 12. Electric cylinder; 13. Motor. Detailed Implementation

[0021] The following provides explanations for some of the terms used in this application. It should be noted that these explanations are for the convenience of those skilled in the art and do not constitute a limitation on the scope of protection claimed in this application.

[0022] In the embodiments of this application, "and / or" merely describes the relationship, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0023] The directional terms mentioned in the embodiments of this application, such as "up", "down", "left", "right", "inner", and "outer", are only for reference to the directions in the accompanying drawings. Therefore, the directional terms used are for better and clearer explanation and understanding of the embodiments of this application, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the embodiments of this application.

[0024] References to “one embodiment,” “in some examples,” or “some embodiments” as described in the embodiments of this application mean that one or more embodiments of this specification include a particular feature, structure, or characteristic described in connection with that embodiment.

[0025] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0026] like Figure 1 The diagram shows a flowchart of a method for simulating small intestinal digestion in monogastric animals based on peristalsis control, provided in an embodiment of this application. The method includes the following steps: Step 1: Collect the initial digestive fluid secretion rate curves of monogastric animals of different target types in different batches of experiments, and use the time of completion of feeding as the time reference to align the initial digestive fluid secretion rate curves to a unified time axis, and select the effective digestive fluid secretion rate curves.

[0027] Step 2: Analyze the effective digestive fluid secretion rate curves from each aggregate model to identify the target aggregate curves that reflect the secretion pattern of digestive fluids in the small intestine of the target type of monogastric animal, and screen out high-activity windows from the target aggregate curves.

[0028] Step 3: Based on the high-activity window, the digestive process of the small intestine of a monogastric animal is transformed into an in vitro experimental simulation process. The in vitro experimental simulation process is divided into an initiation ramping section, a high-activity section, and a decay long tail section. The corresponding digestive fluid dripping rate sequence for each section is determined, thereby initializing the peristaltic control parameters of the small intestine simulator device.

[0029] Step 4: Monitor the operation of the small intestine simulator device, collect monitoring results, and optimize the peristalsis control parameters of the small intestine simulator device based on the monitoring results.

[0030] Currently, technicians can obtain the initial digestive fluid secretion rate curves for different batches of experiments in monogastric animals of different target types using the following method: For different monogastric animals of different target types, a chronic sampling fistula or microcatheter is first established in the proximal duodenum or anterior jejunum. The catheter outlet is connected to a pre-calibrated micro-collection tube or online volumetric flow sensor. After the animals have completed postoperative recovery and have undergone an adaptation period until their feeding behavior and basal secretion levels are stable, multiple batches of standardized feeding trials are performed. In each batch of experiments, the end time of feeding is used as the time base t=0. The catheter outlet is connected to an electronic balance or metering pump with time-stamping acquisition function. Digestive fluid flowing out of the anterior small intestine is continuously collected at fixed time intervals (e.g., every 5 min or 10 min) within a preset observation period. The start and end times of each collection time window and the corresponding mass increment are recorded, and combined with digestive fluid density conversion... The volume increment is calculated, and the average secretion rate for each time window is calculated as volume increment / time window length, resulting in a discrete time-point-digestive fluid secretion rate sequence. The system collects time-point-digestive fluid secretion rate sequences uploaded by technicians, and then performs data preprocessing on the sequence, including removing obvious abnormal points caused by duct blockage, animal strenuous activity, etc., and using linear interpolation or spline interpolation to fill in short-term missing points. High-frequency measurement noise is denoised using smoothing algorithms such as moving average or Savitzky-Golay, so that the secretion rate change between adjacent time windows is continuously transitioned within a physiologically reasonable range. Finally, the discrete points after denoising and interpolation reconstruction are connected in chronological order and fitted into a curve of the initial digestive fluid secretion rate versus time defined on a continuous time axis, i.e., the initial digestive fluid secretion rate curve, which serves as an initial secretion curve for this animal in this batch of experiments.

[0031] The rate of digestive fluid secretion refers to the rate of change in the volume or mass of digestive fluid discharged into the small intestine by secretory structures such as the pancreas, hepatobiliary system, and small intestinal glands per unit time. It is usually expressed in volumetric flow rate or mass flow rate such as mL / h or μL / min, and can be a mixed digestive fluid containing one or more components such as pancreatic juice, bile, and intestinal juice, depending on the sampling location and experimental design.

[0032] In one example embodiment, the moment when the mice stopped feeding was defined as t=0, and the mass increment of digestive fluid was collected sequentially within each 10-minute time window from t=0 to 180 min, with a collection interval of 10 minutes. For example, the mass increment was 12 mg from t=0 to 10 min, 45 mg from t=10 to 20 min, 78 mg from t=20 to 30 min, then 95 mg, 102 mg, and 98 mg from 30 to 60 min, gradually decreasing to 80 mg, 65 mg, 50 mg, and 36 mg from 60 to 120 min, and further decreasing to 24 mg, 15 mg, and 9 mg from 120 to 180 min. The above mass increments were converted into volume increments at a density of 1.0 mg / μL and divided by the corresponding 10-minute time window length to obtain the average secretion at each time point. The secretion rates, for example, are approximately 1.2 μL / min from 0 to 10 min, 7.8 μL / min from 20 to 30 min, 9.5 μL / min from 60 to 70 min, and 2.4 μL / min from 120 to 130 min. After collecting the above data and removing isolated outliers caused by mouse movement, the rate sequence was smoothed using a sliding window and linearly interpolated. The secretion rates corresponding to the center time of each 10 min were connected in chronological order, resulting in a curve showing the initial digestive fluid secretion rate of the small intestine of mice as a function of time, which rapidly increases and remains at a high level from 20 to 60 min after feeding, slowly decreases from 60 to 120 min, and forms a long tail after 120 min. This curve can be used as the basis for subsequent aggregate analysis and screening of high-activity time windows.

[0033] Specifically, each effective digestive fluid secretion rate curve is selected. The specific selection process is as follows: obtain the data completeness of each initial digestive fluid secretion rate curve and compare it with the defined data completeness stored in the database.

[0034] Data completeness refers to the proportion of valid data points in the experimental data corresponding to each curve, out of the total number of data points. It primarily reflects whether the data can completely support curve plotting and subsequent analysis. Its analysis and acquisition can be performed using the following reproducible steps: First, define the pre-set time points and data collection duration for the experiment, and collect the raw secretion rate data corresponding to each curve; then, check each data point one by one, eliminating outliers that clearly exceed the reasonable physiological range (such as extreme values ​​far higher or lower than the average level of similar samples). The remaining data points are the valid data points; defining data completeness refers to the minimum allowable value for data completeness.

[0035] If the data integrity of an initial digestive fluid secretion rate curve is not higher than the defined data integrity, then the initial digestive fluid secretion rate curve is marked as an invalid digestive fluid secretion rate curve, and a data removal operation is performed, meaning it will not participate in the subsequent analysis of the target aggregate curve.

[0036] If the data completeness of an initial digestive fluid secretion rate curve is higher than the defined data completeness, then the initial digestive fluid secretion rate curve is marked as an effective digestive fluid secretion rate curve, thereby filtering out each effective digestive fluid secretion rate curve.

[0037] By excluding invalid digestive fluid secretion rate curves, the nonlinear characteristic distortion problem caused by the linear scaling homogenization process in existing small intestinal simulation devices is avoided, thus improving the accuracy of the target aggregated curve in representing the real small intestinal digestive dynamics. This operation can filter out curve morphology distortions caused by missing data and outliers, avoid invalid data interference in identifying rhythmic differences in the secretion ramp-up phase, high-activity window, and decay long tail phase, and ensure that the original data on which the aggregated analysis is based can reflect the physiological characteristics of the coordination between digestive fluid secretion and peristalsis. It also reduces the error superposition caused by homogeneous time slice processing under linear scaling mode, making the final aggregated curve more closely match the nonlinear change law of the instantaneous secretion rate of digestive fluid in vivo. This provides accurate data support for subsequent optimization of the peristaltic control mode of the small intestinal simulation device and improvement of the realism and reliability of in vitro simulation.

[0038] Specifically, high-activity windows are selected from the target polymerization curves. The selection process is as follows: the digestive fluid secretion rate of the target polymerization curve is selected from left to right, and the moment when the digestive fluid secretion rate first exceeds the digestive fluid secretion rate threshold is marked as the start time of the high-activity window; the digestive fluid secretion rate of the target polymerization curve is selected from right to left, and the moment when the digestive fluid secretion rate first exceeds the digestive fluid secretion rate threshold is marked as the end time of the high-activity window; after the high-activity window selection is completed, the effectiveness of the high-activity window is verified.

[0039] The screening method, which marks the start time from left to right and the end time from right to left, is based on the physiological rhythm of digestive fluid secretion. Digestive fluid secretion gradually increases after ingestion, entering a high-activity phase, and then naturally declines as digestion progresses. The high-activity window is the core range where the secretion rate remains at a high level. This screening logic can accurately pinpoint the complete time period from the first time the secretion rate exceeds the threshold (entering a high-activity state) to the last time it exceeds the threshold (exiting a high-activity state), avoiding omissions of the initial transition or the final decline portion of the high-activity phase, ensuring that the window range is consistent with the high-activity secretion cycle of the actual physiological process. On the one hand, it can accurately separate the initial ramp-up phase of digestive fluid secretion (rate continuously rising but not reaching the high-activity standard) and the long-tail decline phase (rate below the threshold and gradually approaching the baseline level), focusing on the core range where secretion and peristalsis have the strongest synergistic effect and the highest efficiency of nutrient degradation and absorption. This provides a basis for subsequent targeted analysis of key digestive kinetic characteristics of this phase (such as chyme mixing uniformity, enzymatic reaction rate, substrate expansion). This method provides clear and precise data boundaries (such as digestion efficiency), allowing the analysis to focus more on the most physiologically critical stages. On the other hand, it can effectively exclude interference from low-rate data in non-high-activity stages. Such data are often affected by factors such as basal secretion fluctuations and minor changes in the experimental environment. If these data are included in the analysis of the true characteristics of easily diluted high-activity stages, it will lead to deviations in the calculation of kinetic parameters (such as average secretion rate, peak duration, and rhythm fluctuation amplitude). This screening method can reduce such deviations, improve the accuracy and reliability of subsequent parameter calculations and model fitting, and make the high-activity windows under different samples or experimental conditions comparable, which is convenient for subsequent quantitative analysis of the impact of different variables on the core digestion stage.

[0040] The threshold value for digestive juice secretion rate is a quantitative critical value used to determine whether digestive juice secretion has entered a highly active state. It is usually based on the statistical characteristics of the secretion rate in the target aggregation curve (such as taking 30% to 50% of the peak value of the curve, or the measured value of the lowest rate of highly active secretion in vivo under similar physiological conditions).

[0041] Specifically, the effectiveness of the high-activity window was verified. The verification process was as follows: the target aggregation curve was integrated over the characteristic time period, and the result was marked as the total secretion amount; the target aggregation curve was integrated within the high-activity window, and the result was marked as the secretion amount within the window; the ratio coefficient of secretion amount within the window to total secretion amount was analyzed and compared with the secretion amount ratio reference interval stored in the database.

[0042] The ratio of secretory volume within a window to total secretion is the result of dividing the secretory volume within a window by the total secretion volume. The reference range for the proportion of secretion volume refers to the reasonable range of high-activity window secretion volume relative to total secretion volume, determined through statistical analysis (such as calculating the mean ± standard deviation, 95% confidence interval, etc.) based on a large amount of in vivo digestion experiments and standardized in vitro simulation experiments under similar physiological conditions.

[0043] If the ratio of secretion volume to total secretion volume within the window falls within the reference range for the proportion of secretion volume, then the high-activity window is marked as valid; otherwise, the threshold value for digestive fluid secretion rate is adjusted, and high-activity windows are re-screened in the target aggregation curve until a high-activity window is valid.

[0044] The correction of the digestive fluid secretion rate threshold should be carried out according to the principle of adjusting in the direction of deviation and step-by-step calibration: If the ratio of secretion volume to total secretion volume within the window is lower than the lower limit of the reference interval for secretion volume percentage, it indicates that the digestive fluid secretion rate threshold is too high, resulting in an overly narrow high-activity window. The threshold should be lowered in a gradient of 5% to 10%. If the ratio of secretion volume to total secretion volume within the window is higher than the upper limit of the reference interval for secretion volume percentage, it indicates that the threshold is too low, resulting in an overly wide window. The threshold should be raised in a gradient of 5% to 10%. For example, if the original digestive fluid secretion rate threshold is 40% of the peak secretion rate, and the ratio of secretion volume to total secretion volume within the window is only 25% after comparison (lower than the lower limit of the reference interval for secretion volume percentage of 30%), then the threshold should be lowered in a gradient of 10% to 36% of the peak secretion rate, and then re-screened until the ratio falls within the reference interval.

[0045] The initial value of the digestive fluid secretion rate threshold is not an absolutely objective fixed standard, but a preliminary reference value based on the statistical characteristics of the target aggregation curve (such as 30% to 50% of the peak value). Its core function is to provide a screening starting point, not a final judgment basis. Due to individual physiological differences in mice in different batches of experiments (such as metabolic level and digestive function status) and subtle fluctuations in the experimental environment, the initial threshold determined by a single statistical proportion may not accurately match the actual characteristics of highly active secretion in that batch of experiments. Therefore, it needs to be specifically calibrated through subsequent verification. The secretion volume ratio reference range is derived from the statistical analysis of a large number of experimental data under similar physiological conditions. It is a reasonable range of highly active secretion in the total secretion volume. Its core significance is to reflect the general physiological law of highly active secretion. Through the cycle of preliminary screening to verification comparison to adjustment and optimization, the threshold value is gradually brought closer to the real physiological threshold, so as to achieve the goal of selecting highly active windows that are both in line with data laws and physiological logic.

[0046] By employing a closed-loop calibration mechanism, the technical problem of a single fixed threshold value potentially mismatching with specific experimental data and physiological scenarios is resolved. This ensures that the high-activity window not only conforms to the screening logic of achieving the target digestive fluid secretion rate but also meets the core requirement that the secretion percentage aligns with physiological patterns. Essentially, it uses feedback adjustments to make the threshold value more closely reflect the actual secretion characteristics of a single experiment, avoiding situations where the high-activity window is too narrow (missing the core secretion stage) or too wide (including non-core low-activity data) due to threshold setting deviations. This ensures the physiological relevance and data reliability of the high-activity window, laying the foundation for the accurate calculation of subsequent core digestive kinetic parameters (such as secretion efficiency and rhythmic coordination), model fitting, and cross-experimental data comparison. Simultaneously, it improves the accuracy of in vitro simulation experiments in replicating the actual digestive and secretory patterns in vivo.

[0047] Ensuring the effectiveness of the high-activity window is crucial because this window represents the key physiological stage where the synergistic effect of digestive fluid secretion and intestinal peristalsis is strongest, and the efficiency of nutrient enzymatic hydrolysis, chyme mixing, and substrate absorption is highest. The quality of data from this window directly determines the accuracy of in vitro digestion simulations in replicating the core digestive kinetics in vivo. If the high-activity window is invalid (e.g., secretion percentage deviates from the physiological reference range, or the window range is distorted), subsequent analyses of digestive characteristics at the core stage (such as enzymatic reaction rate, chyme propulsion efficiency, and secretion-peristaltic rhythm synergy) will lack a physiological basis. This will not only cause deviations in kinetic parameter calculations and distorted model fitting but also affect the comparability of data under different experimental conditions. It will also make it impossible to accurately quantify the impact of variables on the core digestive process, thereby weakening the technical value and credibility of in vitro simulation experiments and even misleading subsequent parameter optimization and process improvement of small intestine simulation devices.

[0048] Further, the specific analysis process for the target aggregation curve is as follows: Identify and determine the characteristic time period covering the entire time span of each effective digestive fluid secretion rate curve; select a functional form to describe the digestive fluid secretion rate pattern; using each monogastric experimental animal as the individual dimension, decompose the parameters in the initial function of the target aggregation curve into the sum of a target function reflecting the population fixed effect and individual random offsets, thereby constructing a population-individual mixed effect model; obtain the digestive fluid secretion rate of each effective digestive fluid secretion rate curve at time t and input it into the population-individual mixed effect model; solve the target function in the population-individual mixed effect model using maximum likelihood estimation or Bayesian estimation methods; evaluate the solved target function point-by-point throughout the entire characteristic time period to obtain the corresponding digestive fluid secretion rate time-series trajectory, and smooth and connect the trajectory continuously; the resulting continuous curve is denoted as the target aggregation curve.

[0049] In one example embodiment, using mice as an example, the secretion of mixed digestive fluids in the small intestine of mice generally exhibits a single-peak pattern over time, rising from low to high, reaching a peak / plateau, and then declining with a long tail. A function similar to the Gamma type can be used to reflect the objective function of population fixation effects, for example: , The objective function reflects the group fixation effect, where t is the time after feeding, and θ i = (A i α i k i Let A be the parameter of the i-th mouse. i The peak height α of the initial function of the target aggregation curve corresponding to the i-th mouse is controlled by... i The steepness of the initial slope of the target aggregation curve for the i-th mouse is controlled by k. i Control the decay rate of the initial function of the target aggregation curve corresponding to the i-th mouse.

[0050] The power term of this function, i.e. This term is suitable for describing the initial accelerated rise in secretion rate. It can capture the initial acceleration of the small intestinal secretion rate, a process that is very common in many physiological processes, especially in the early stages of digestive fluid secretion. The exponential term, i.e. The function represents the decay of the secretion rate, which closely matches the phenomenon of a peak followed by a gradual decline in the actual digestive process. As food gradually empties, the secretion rate of the small intestine also gradually decreases. The process of digestive juice secretion is usually not linear, especially since the secretion and reaction of enzymes in the small intestine are regulated by different physiological hormones and food stimuli. This function can accurately fit this nonlinear dynamic process, rising rapidly in a short period of time, maintaining a high value, and then gradually decaying, perfectly capturing the asymmetric single-peak structure of small intestinal digestive juice secretion.

[0051] This function can accurately fit the entire time-course process of digestive fluid secretion, including the initial ramp-up phase, the high-activity plateau, and the subsequent decay phase. Compared to traditional linear or average distribution methods, this function form can more accurately reproduce the actual physiological process of digestive fluid secretion, improving the accuracy of peristalsis-like control. By parameterizing the curves of each animal, the population-individual mixed-effects model can provide an independent offset for each animal while ensuring that the population parameters accurately represent the overall characteristics. This method solves the instability caused by in vivo and in vitro digestive fluid secretion rate errors and random noise, improving the robustness of parameters and the repeatability of the model.

[0052] Each parameter is decomposed into a group fixed effect and an individual random offset, for example, A i =A pop +bA i α i =αpop +bα i k i =k pop +bk i , (A pop α pop k pop ) represents the objective function parameters (fixed effects) for the mouse population, and (bA) represents the parameters of the objective function for the mouse population. i ,bα i bk i ) represents the individual random offset of the i-th mouse.

[0053] Initialization function r of target aggregation curve i (t), reflecting the change in the rate of digestive fluid secretion in the i-th mouse over time, r i (t)=f(t;θ i )+c i (t), c i (t) represents the variation of the measurement noise of the i-th mouse over time.

[0054] A population-individual mixed-effects model is constructed, which involves creating initial functions for target aggregation curves of several mice. The relationship between the digestive fluid secretion rate and time of the corresponding mice is input into the corresponding initial functions for target aggregation curves. Maximum likelihood estimation or Bayesian estimation is used to solve the model. On the one hand, the objective function is adjusted to fit the common trend of the curves of all mice. On the other hand, individual random offsets are used to absorb individual differences that are too high or too low overall, and measurement noise is used to represent local short-term fluctuations. Finally, the model is solved to obtain (A). pop α pop k pop Substituting these values ​​into the objective function, the objective function expression is: Within a characteristic time period, values ​​are calculated point by point with a small step size (e.g., 5 min) to obtain a high temporal resolution population average digestive fluid secretion rate-time series trajectory; then, low-amplitude smoothing (e.g., Savitzky-Golay) is applied to this trajectory and continuous connection is made to achieve numerical smoothness and consistency with the physiological curve morphology, finally obtaining the target aggregation curve.

[0055] Specifically, the digestion process of the small intestine in monogastric animals is transformed into an in vitro experimental simulation process. The specific transformation process is as follows: a nonlinear time mapping function constrained by a high-activity window is constructed, and the digestion process of the small intestine in monogastric animals is transformed into an in vitro experimental simulation process by non-uniform scaling and staged mapping of the time process during digestion.

[0056] In one example embodiment, the mapping function is: T activeT is the length of the high-activity window in the target polymerization curve. sim The duration of the in vitro experimental simulation process, t L Let t be the starting time of the high-activity window, and d be an adjustment factor used to control the degree of nonlinearity of the mapping. Essentially, it sets the starting time t of the high-activity window to t. L As the zero point of time, via tt L Complete the translation of the time axis within the body, and then use the scaling factor T. sim Divide by T active The overall length of the highly active window is compressed or expanded to a preset in vitro runtime, and non-uniform scaling is applied to different positions inside the window using a power-law exponent d: when d < 1, the mapping is close to t. L The early time period is more compressed, while the compression is relatively expanded near the peak and in the latter half, thus preserving a higher temporal resolution near the secretion peak within a unified short time interval. When d>1, the temporal characterization of the early part of the window can be strengthened in reverse. Compared with the traditional approach of using a single linear ratio to compress the time of the entire digestion process, this power function-based time mapping achieves fine control over "where to examine closely and where to squeeze" within the highly active window through continuous, monotonic, and parameter-adjustable means, avoiding the systematic misalignment of the secretion peak on the time axis and the problem of over-compression of the highly active phase. On the other hand, its mathematical form is simple, easy to invert, and easy to embed into control programs, which facilitates adaptive recalibration of the highly active window for different animals and different formulations while keeping the total in vitro running time under control. This effectively solves the technical problems in existing technologies, such as the decoupling of mechanical peristalsis and chemical secretion timing and insufficient physiological relevance in in vitro simulation caused by linear compression of the time scale and uniform scaling of the rhythm.

[0057] d is a regulatory factor, the specific value of which is set by relevant technical personnel. After the high activity window is set, the in vitro experimental simulation process is divided into an initiation ramp-up phase, a high activity phase, and a decay long tail phase, with the start and end times of the high activity window as the dividing points. The initiation ramp-up phase starts at the time of completion of feeding and ends at the start time of the high activity window. The high activity phase starts at the start time of the high activity window and ends at the end time of the high activity window. The decay long tail phase starts at the end time of the high activity window and ends at the end time of the in vitro experimental simulation process.

[0058] The initiation and long-tail segments are confined to both sides of the high-activity window, ensuring that the early ramp-up and late decay after feeding are reasonably represented in vitro, while avoiding excessive stretching of control parameters by long-tail noise. This fundamentally alleviates the problems of excessively short high-activity phases, peak misalignment, and non-physiological peaks caused by overall linear compression in existing technologies. On the other hand, the high-activity segment is precisely locked in the middle core area of ​​the in vitro process, which facilitates the concentrated arrangement of enhanced control of peristalsis frequency, squeezing pressure, and digestive fluid dripping rate within this area. The relative durations of the three segments are flexibly proportioned by the adjustment factor d, so that a uniform time structure and comparability can be maintained under different animal types and different formulation conditions. This improves the representativeness of in vitro simulation to the real small intestinal digestive dynamics in vivo and the accuracy of mechanochemical coupling control.

[0059] Specifically, the digestive fluid dripping rate sequence corresponding to each segment is determined. The specific determination process is as follows: the effective volume of the small intestine in vivo is processed by the ratio of the volume of the small intestine simulator device, and the processing result is marked as the correction coefficient; for the high-activity segment, the digestive fluid secretion rate corresponding to the high-activity window in the target aggregation curve is mapped to this stage through timestamps, and the digestive fluid secretion rate is corrected based on the correction coefficient, thereby obtaining the digestive fluid dripping rate sequence corresponding to the high-activity segment.

[0060] For example, taking a monogastric small animal as an example, the effective volume of the small intestine in vivo, after anatomical and literature correction, is approximately 200 mL. The effective volume of the flexible simulation cavity of the small intestine simulator is designed to be 50 mL, so the correction factor is 50 / 200 = 0.25. According to the target aggregation curve obtained from the mixed-effects model, the in vivo time corresponding to the high-activity window is 60–120 min. Within this time period, the equivalent total digestive fluid secretion rate of a representative animal is 5, 6, 6.5, 6, and 5.5 mL / h (one point every 15 min). Through the time mapping function... The 60-120 min interval was mapped to the 30-90 min interval of in vitro operation, and the secretion rate at each time point was multiplied by a correction factor of 0.25 to obtain the digestive fluid drip rate at the corresponding time points of the high-activity phase in vitro as 1.25, 1.50, 1.63, 1.50, and 1.38 mL / h. Based on this, the control system set the target drip curve of the digestive fluid pump in vitro within 30-90 min, so that the relative secretion intensity and peak morphology of the high-activity phase in vivo could still be reproduced in a smaller simulated chamber, while avoiding non-physiological overdosing due to volume mismatch.

[0061] For the initial ramp-up phase, the target total secretion amount for the initial ramp-up phase is extracted from the data volume, and a positive correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid drip rate sequence corresponding to the initial ramp-up phase.

[0062] For the initiation ramp-up phase, in one implementation, the target total secretion volume corresponding to the in vitro running time of the initiation ramp-up phase is first calculated based on the target aggregation curve and the ratio of in vivo volume to in vitro volume. For example, the target total secretion volume of the in vivo initiation phase corresponding to 0-30 minutes is 60 mL after scaling. Then, the running time of the in vitro initiation phase (e.g., 30 minutes) is determined, and a positive correlation linearization determination strategy is performed according to the time dimension within this time interval: the infusion rate at the start time is set to a baseline value q close to zero. min The drip rate at the termination time is q. max A monotonically increasing linear function is constructed with time as the independent variable, such that the infusion rate changes from q within 0 to 30 minutes. min linearly increasing to q max Furthermore, the integral of this linear function over the initiation phase is equal to the aforementioned target total secretion amount; for example, let q min =0, then by (q min +q max ) / 2×30min=60mL, thus obtaining q max =4mL / min, thus obtaining a drip rate sequence that linearly climbs from 0 to 4mL / min, which not only reproduces the climbing process of gradually entering the high-activity stage from the baseline in vivo, but also ensures the consistency between the total dosage in the initiation phase and the target total secretion.

[0063] For the attenuating long tail segment, the target total secretion amount of the attenuating long tail segment is extracted from the data volume, and a negative correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid drip rate sequence corresponding to the attenuating long tail segment.

[0064] For the attenuation of the long tail segment, in another implementation, the target total secretion volume to be compensated during the in vitro running time of the long tail segment is first calculated based on the target aggregation curve and the in vivo-in vitro volume scaling relationship. For example, the target total secretion volume after conversion for the long tail segment corresponding to 120-180 min in vivo is 45 mL. At the same time, the running time of the long tail segment in vitro (e.g., 30 min) is determined. Within this time interval, a negative correlation linearization determination strategy is performed according to the time dimension: the infusion rate at the start of the long tail segment is set as q. head The drip rate at the end of the infusion period is close to the baseline q. base Construct a linear function that monotonically decreases with time, such that the drip rate decreases from q... head linear decay to q base And let the integral of the linear function over the long tail be equal to the target total secretion amount; for example, take q base =0.5mL / min, from (q head +q base ) / 2×30min=45mL to obtain q head=2.5 mL / min, thus obtaining a drip rate sequence that linearly decreases from 2.5 mL / min to 0.5 mL / min. While ensuring that the total dosage in the long tail segment is equivalent to the target in vivo, it describes the process of gradual decrease and return to the baseline level of digestive fluid secretion in a concise linear form.

[0065] Furthermore, the peristaltic control parameters of the small intestine simulator device are initialized. The specific initialization process is as follows: the peristaltic control parameters include peristaltic frequency, squeezing force, and propulsion speed; several mapping tables are extracted from the database, including a digestive fluid dripping rate-peristaltic frequency mapping table, a digestive fluid dripping rate-squeezing force mapping table, and a digestive fluid dripping rate-propulsion speed mapping table; using the digestive fluid dripping rate as an index, the peristaltic frequency, squeezing force, and propulsion speed corresponding to the digestive fluid dripping rate are retrieved from the several mapping tables; based on the digestive fluid dripping rate sequence corresponding to each segment, the digestive fluid dripping rate sequence, squeezing force sequence, and propulsion speed sequence corresponding to each segment are retrieved, thereby initializing the peristaltic control parameters of the small intestine simulator device.

[0066] The infusion rate of digestive juices is a key indicator in the small intestinal digestion process. It reflects not only the intensity of digestive juice secretion but also its close relationship with the mechanodynamics of the small intestine. Specifically, the infusion rate determines the flow characteristics and mixing efficiency of the liquid in the simulated small intestine, thus affecting parameters such as peristalsis frequency, squeezing force, and propulsion speed. These latter parameters directly determine the propulsion, squeezing, and mixing of chyme within the small intestine. Therefore, by mapping the infusion rate of digestive juices to these control parameters, the design of the control system can be simplified while maintaining physiological relevance, enabling in vitro experiments to accurately reproduce multiple physiological phenomena of small intestinal digestion at a uniform infusion rate.

[0067] By utilizing pre-defined mapping tables in the database, such as the relationships between digestive fluid dripping rate and peristaltic frequency, squeezing force, and propulsion speed, the simple control variable of dripping rate can be combined with a complex mechanochemical coupling process. This reduces the complexity of parameter setting while improving the adjustability and response accuracy of the control system. In this way, not only can the simulation system be finely adjusted at different digestion stages, but the ratio of peristalsis and fluid propulsion can also be automatically adjusted according to the secretion characteristics of different digestive fluids, thereby maximizing the physiological consistency of the small intestine digestion process in vivo and improving the accuracy and repeatability of in vitro simulation experiments. This strategy can effectively address the varying needs of different species, formulations, and experimental conditions, providing a flexible and efficient peristalsis-simulated control scheme.

[0068] Furthermore, the peristaltic control parameters of the small intestine simulator device were collected and optimized based on the monitoring results. The specific optimization process was as follows: the peristaltic control deviation coefficient was extracted from the monitoring results and compared with the peristaltic control deviation reference range extracted from the database.

[0069] The peristalsis control deviation coefficient is used to measure the overall deviation of the actual peristalsis state of the current small intestine simulator within a given evaluation window from the preset in vitro experimental simulation process. In an example embodiment, the actual digestive fluid dripping rate within the monitoring window can be integrated, and the result can be marked as the total digestive fluid dripping volume. This is then integrated with the preset digestive fluid dripping rate of the in vitro experimental simulation process within the monitoring window, and the result can be marked as the target total digestive fluid dripping volume. The total digestive fluid dripping volume divided by the target total digestive fluid dripping volume is recorded as the peristalsis control deviation coefficient.

[0070] The deviation range of simulated peristalsis control from the reference range refers to the reasonable range of values ​​for the simulated peristalsis control deviation coefficient that is pre-stored in the database based on standard calibration experiments or historical stable operating data. This range is used to define the acceptable degree of matching between in vivo and in vitro peristalsis rhythms and to determine whether significant corrections to the digestive fluid dripping curve are required.

[0071] If the deviation coefficient of the simulated peristalsis control falls within the reference range of the simulated peristalsis control, then there is no need to optimize the simulated peristalsis control parameters of the small intestine simulator device, and the operation process of the small intestine simulator device is continuously monitored; if the deviation coefficient of the simulated peristalsis control does not fall within the reference range of the simulated peristalsis control, then the deviation value of the simulated peristalsis control is obtained, the simulated peristalsis control parameters of the small intestine simulator device are optimized based on the deviation value of the simulated peristalsis control, and an experimental duration warning is issued.

[0072] If the deviation coefficient of the simulated peristalsis control is higher than the upper limit of the simulated peristalsis control deviation reference range, the simulated peristalsis control deviation value refers to the difference between the simulated peristalsis control deviation coefficient and the upper limit of the simulated peristalsis control deviation reference range. The result of the difference is divided by the simulated peristalsis control deviation coefficient, and the final result is the simulated peristalsis control deviation value. If the deviation coefficient of the simulated peristalsis control is lower than the lower limit of the simulated peristalsis control deviation reference range, the simulated peristalsis control deviation value refers to the difference between the lower limit of the simulated peristalsis control deviation reference range and the simulated peristalsis control deviation coefficient. The result of the difference is divided by the simulated peristalsis control deviation coefficient, and the final result is the simulated peristalsis control deviation value.

[0073] The peristaltic control parameters of the small intestine simulator device are optimized based on the peristaltic control deviation value. If the peristaltic control deviation coefficient is higher than the upper limit of the peristaltic control deviation reference range, the peristaltic control deviation coefficient is multiplied by the current digestive fluid dripping rate to update the digestive fluid dripping rate, thereby updating the peristaltic frequency, squeezing force, and propulsion speed accordingly. If the peristaltic control deviation coefficient is lower than the lower limit of the peristaltic control deviation reference range, the peristaltic control deviation coefficient is multiplied by the current digestive fluid dripping rate, and the result is accumulated with the current digestive fluid dripping rate to update the digestive fluid dripping rate, thereby updating the peristaltic frequency, squeezing force, and propulsion speed accordingly.

[0074] Experiment duration warning refers to the real-time push of prompt information to the experimenters when the simulated peristalsis control parameters need to be optimized. The information includes the degree of parameter deviation, the direction of optimization, and the estimated additional experiment duration, or whether the original duration should be maintained to ensure data integrity. This allows the experimenters to keep abreast of the experimental status and make corresponding adjustments, such as whether to extend the monitoring time or check the stability of the device operation.

[0075] This parameter optimization method, based on the deviation value of simulated peristalsis control, solves the technical pain point of existing small intestine simulation devices that linearly bind simulated peristalsis control to the rhythm of digestive fluid secretion and cannot respond to deviations in secretion ratio. By dynamically updating the digestive fluid drip rate based on the positive or negative direction of the deviation coefficient (higher or lower than the reference range), and simultaneously adjusting the peristalsis frequency, squeezing force, and propulsion speed, the simulated peristalsis parameters can be precisely matched with the real secretion characteristics of the high-activity window. This avoids problems caused by fixed parameters, such as insufficient peristalsis when the secretion ratio is too high, resulting in inability to timely mix high-secretion chyme, or excessive peristalsis when the secretion ratio is too low (causing excessively rapid chyme propulsion and insufficient enzymatic digestion). Furthermore, the quantitative optimization logic brings the synergistic relationship between peristalsis and secretion back to a physiologically reasonable range, thereby correcting the distortion of digestive dynamics in in vitro simulations and improving the device's accuracy in replicating the in vivo secretion-peristalsis coupling rhythm. At the same time, it provides technical support for the accurate quantification of subsequent core digestive parameters (such as enzymatic digestion efficiency and chyme retention time distribution), ensuring the physiological relevance and data reliability of experimental results.

[0076] In another example embodiment, the gripping time of the next gripper in the same set of grippers is set to be 20 seconds apart from the gripping time of the previous gripper, and each simulation set runs for one cycle every 80 seconds. The total running time is 4 hours. Four hours after the simulated small intestine digestion, the small intestine duct and the small intestine peristaltic pump begin to operate, expelling the chyme digested in the simulated small intestine, thus completing the simulation of small intestine digestion in a monogastric animal.

[0077] Figure 2This application provides a detailed flowchart of the small intestine digestion simulation in monogastric animals. Initial digestive fluid secretion rate curves for different target types of monogastric animals in different batches of experiments were collected. Using the time of food ingestion completion as the time reference, each initial digestive fluid secretion rate curve was aligned to a unified time axis. The data completeness of each initial digestive fluid secretion rate curve was obtained and compared with a defined data completeness threshold. If the data completeness of an initial digestive fluid secretion rate curve is not higher than the defined data completeness threshold, it is marked as an invalid digestive fluid secretion rate curve, and data removal is performed. If the data completeness of an initial digestive fluid secretion rate curve is higher than the defined data completeness threshold, it is marked as an effective digestive fluid secretion rate curve. This process filters out effective digestive fluid secretion rate curves and analyzes target aggregation curves. High-activity curves are then selected from the target aggregation curves. The digestive process of the small intestine in monogastric animals is transformed into an in vitro experimental simulation process. The corresponding digestive fluid dripping rate sequence for each segment is determined. For the high-activity segment, the digestive fluid secretion rate corresponding to the high-activity window in the target aggregation curve is mapped to this stage through a timestamp, and the digestive fluid secretion rate is corrected based on a correction coefficient to obtain the digestive fluid dripping rate sequence corresponding to the high-activity segment. For the initiation and ramping segment, the target total secretion volume of the initiation and ramping segment is obtained, and a positive correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid dripping rate sequence corresponding to the initiation and ramping segment. For the decaying long tail segment, the target total secretion volume of the decaying long tail segment is obtained, and a negative correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid dripping rate sequence corresponding to the decaying long tail segment. The peristaltic control parameters of the small intestine simulator device are initialized, monitoring results are collected, and the peristaltic control parameters of the small intestine simulator device are optimized based on the monitoring results.

[0078] It should be explained that the data in the database comes from a large number of standardized experiments under similar physiological conditions. The raw data collected from the experiments are standardized and statistically analyzed in a unified format (such as calculating the mean ± standard deviation, 95% confidence interval, etc.), and extreme outliers caused by experimental errors are removed. Finally, valid data that meet the requirements of physiological logic and experimental repeatability are selected and included in the database according to a unified classification standard to form a reusable quantitative basis.

[0079] The method for simulating the digestion of a monogastric small intestine based on simulated peristalsis control provided by this invention can be applied to devices such as those for simulating the digestion of a monogastric small intestine based on simulated peristalsis control. Figure 3 Schematic diagram of the small intestine simulation device provided in the embodiments of this application Figure 1 ; Figure 4 Schematic diagram of the small intestine simulation device provided in the embodiments of this application Figure 2 , Figure 3 and Figure 4The same small intestine simulation device includes a small intestine container 1, a lid 2, a small intestine digestive fluid container 3, a small intestine digestive fluid conduit 4, a valve 5, a small intestine gripper frame 6, a gripper guide rail 7, a gripper end 8, an electric cylinder telescopic rod frame 9, an electric cylinder telescopic rod 10, an electric push rod motor 11, an electric cylinder 12, and a motor 13.

[0080] With the small intestine container 1 as the central axis, both ends are sealed and fixed by gaskets and lids 2. Warm water enters from the inlet at the bottom of the small intestine container 1 and exits from the outlet. The small intestine container 1 is a double-layered sleeve structure made of flexible silicone material, with a constant temperature water bath layer between the layers. The inner cavity of the sleeve is a simulated small intestine digestive cavity. The warm water flow rate is adjusted from 0.05 m / s to 1 m / s to ensure that the temperature in the small intestine container 1 is stable between 38.5℃ and 39.5℃. The small intestine digestive fluid container 3 is connected to the inlet at the top of the small intestine container 1 through the small intestine digestive fluid conduit 4. The small intestine digestive fluid container 3 is used to control the amount of enzyme added for chemical digestion. The small intestine digestive fluid conduit 4 is connected in series with a valve 5, and a valve handle is installed on the outside. During the simulation, the valve 5 is opened, and the addition of simulated intestinal fluid is controlled by setting the valve opening rate. For example, by setting the parameter range, the simulated intestinal fluid is added at a rate of 1 mm / s. The dripping process is carried out at a rate of up to 100 mm / s. Multiple layers of small intestine gripper frames 6 are sequentially mounted on the outer periphery of the small intestine bucket 1 along the axial direction. Several gripper ends 8 are arranged in each frame and slide along the gripper guide rail 7. The frequency of translation of the gripper ends 8 can be set from 0.5 to 5 times / min. When the gripper ends 8 move inward, they squeeze the small intestine bucket 1 to simulate peristalsis. One side of the small intestine gripper frame 6 is fixed to the electric cylinder telescopic rod 10 through the electric cylinder telescopic rod frame 9. The electric push rod motor 11 is started, which drives the electric cylinder 12 to run. The rotation of the electric cylinder shaft pushes the electric cylinder telescopic rod 10 in the electric cylinder and the gripper ends 8 with silicone heads connected to it to achieve basic squeezing and function. The motor 13 rotates, which drives the small intestine bucket 1 to rotate. Each rotation is 1 / 4 revolution, and the speed is 5 to 20 rpm / min, thereby achieving the effect of omnidirectional simulating squeezing.

[0081] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0082] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1The steps of the function specified in one or more boxes.

[0083] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the scope and intent of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and variations.

Claims

1. A method for simulating small intestinal digestion in a monogastric animal based on peristalsis control, characterized in that, Includes the following steps: Step 1: Collect the initial digestive fluid secretion rate curves of different types of monogastric animals in different batches of experiments, and use the time of completion of feeding as the time reference to align the initial digestive fluid secretion rate curves to a unified time axis, and screen out the effective digestive fluid secretion rate curves. Step 2: Analyze the effective digestive fluid secretion rate curves from each aggregate modeling to identify the target aggregate curves that reflect the secretion pattern of digestive fluids in the small intestine of the target type of monogastric animal, and screen out high-activity windows from the target aggregate curves. Step 3: Based on the high-activity window, the digestion process of the small intestine of monogastric animals is transformed into an in vitro experimental simulation process. The in vitro experimental simulation process is divided into an initiation and ramping section, a high-activity section, and a decaying long tail section. The corresponding digestive fluid dripping rate sequence for each section is determined, thereby initializing the peristalsis control parameters of the small intestine simulator device. Step 4: Monitor the operation of the small intestine simulator device, collect monitoring results, and optimize the peristalsis control parameters of the small intestine simulator device based on the monitoring results.

2. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The specific screening process for each effective digestive fluid secretion rate curve is as follows: Obtain the data completeness of each initial digestive fluid secretion rate curve and compare it with the defined data completeness; If the data integrity of an initial digestive fluid secretion rate curve is not higher than the defined data integrity, then the initial digestive fluid secretion rate curve is marked as an invalid digestive fluid secretion rate curve, and a data removal operation is performed. If the data completeness of an initial digestive fluid secretion rate curve is higher than the defined data completeness, then the initial digestive fluid secretion rate curve is marked as an effective digestive fluid secretion rate curve, thereby filtering out each effective digestive fluid secretion rate curve.

3. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The specific analysis process for the target aggregation curve is as follows: Identify and determine the characteristic time periods that cover the entire time span of each effective digestive fluid secretion rate curve; Select a function form to describe the rate of digestive fluid secretion; Using each monogastric experimental animal as an individual dimension, the parameters in the initial function of the target aggregation curve are decomposed into the sum of the target function that reflects the population fixed effect and the individual random offset, thereby constructing a population-individual mixed effect model; Obtain the digestive fluid secretion rate of each effective digestive fluid secretion rate curve at time t, and input it into the population-individual mixed effect model; The objective function in the population-individual mixed effects model is solved using maximum likelihood estimation or Bayesian estimation methods. The objective function obtained by the solution is evaluated point by point over the entire characteristic time period to obtain the corresponding digestive fluid secretion rate time trajectory. The trajectory is then smoothed and continuously connected, and the resulting continuous curve is denoted as the target aggregation curve.

4. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The process of selecting high-activity windows from the target polymerization curve is as follows: The digestive fluid secretion rate of the target polymerization curve is selected from left to right. The moment when the digestive fluid secretion rate first exceeds the digestive fluid secretion rate threshold is marked as the start time of the high activity window. The digestive fluid secretion rate of the target polymerization curve is selected from right to left. The moment when the digestive fluid secretion rate first exceeds the digestive fluid secretion rate threshold is marked as the end of the high activity window. After the high-activity window screening is completed, the effectiveness of the high-activity window is verified.

5. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 4, characterized in that: The effectiveness of the high-activity window is verified, and the specific verification process is as follows: The target aggregation curve is integrated over a characteristic time period, and the result is labeled as the total secretion amount. The target polymerization curve was integrated within a high-activity window, and the result was labeled as the amount of secretion within the window. Analyze the ratio of endocrine volume to total secretion volume within the analysis window and compare it with the reference interval for the proportion of secretion volume; If the ratio of secretion volume within the window to total secretion volume falls within the reference range for the proportion of secretion volume, then marking a highly active window is valid. Conversely, the threshold value for the digestive fluid secretion rate is revised, and a high-activity window is re-screened in the target polymerization curve until the high-activity window is effective.

6. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The process of converting the digestive process of the small intestine in monogastric animals into an in vitro experimental simulation procedure is as follows: A nonlinear time mapping function constrained by a high-activity window is constructed. By non-uniform scaling and staged mapping of the time process during the digestion of the small intestine of a monogastric animal, the digestion process of the small intestine of a monogastric animal is transformed into an in vitro experimental simulation process. Using the start and end times of the high-activity window as the dividing points, the in vitro experimental simulation process is divided into the start-up ramp-up section, the high-activity section, and the decay long tail section. The starting climbing section begins at the time of completion of feeding and ends at the time of the start of the high-activity window. The high-activity segment begins at the start time of the high-activity window and ends at the end time of the high-activity window. The attenuation long tail segment begins at the end of the high-activity window and ends at the end of the in vitro experimental simulation process.

7. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The specific process for determining the digestive fluid drip rate sequence corresponding to each segment is as follows: The ratio of the effective volume of the small intestine to the volume of the small intestine simulator device was processed, and the result was marked as the correction coefficient. For the high-activity segment, the digestive fluid secretion rate corresponding to the high-activity window in the target polymerization curve is mapped to this stage through a timestamp, and the digestive fluid secretion rate is corrected based on the correction coefficient, thereby obtaining the digestive fluid dripping rate sequence corresponding to the high-activity segment. For the initial ramp-up phase, the target total secretion volume of the initial ramp-up phase is obtained, and a positive correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid drip rate sequence corresponding to the initial ramp-up phase. For the attenuated long tail segment, the target total secretion amount of the attenuated long tail segment is obtained, and a negative correlation linearization determination strategy is performed based on the time dimension to obtain the digestive fluid drip rate sequence corresponding to the attenuated long tail segment.

8. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The initialization process for the peristalsis control parameters of the small intestine simulator device is as follows: The simulated peristalsis control parameters include peristalsis frequency, squeezing force, and propulsion speed; Several mapping tables were extracted from the database, including a digestive fluid dripping rate-peristaltic frequency mapping table, a digestive fluid dripping rate-squeezing force mapping table, and a digestive fluid dripping rate-propulsion speed mapping table. Using the digestive fluid dripping rate as an index, the peristaltic frequency, squeezing force, and propulsion speed corresponding to the digestive fluid dripping rate are retrieved from several mapping tables. Based on the digestive fluid dripping rate sequence corresponding to each segment, the digestive fluid dripping rate sequence, squeezing force sequence, and propulsion speed sequence corresponding to each segment are retrieved, thereby initializing the peristalsis control parameters of the small intestine simulator device.

9. The method for simulating small intestinal digestion in a monogastric animal based on peristalsis control as described in claim 1, characterized in that: The optimization of the peristalsis-simulating control parameters of the small intestine simulator device based on the monitoring results is as follows: Extract the peristaltic control deviation coefficient from the monitoring results and compare it with the peristaltic control deviation reference range; If the deviation coefficient of the simulated peristalsis control falls within the deviation range of the simulated peristalsis control reference range, then there is no need to optimize the simulated peristalsis control parameters of the small intestine simulator device, and the operation process of the small intestine simulator device should be continuously monitored. If the deviation coefficient of the simulated peristalsis control does not belong to the deviation reference range of the simulated peristalsis control, the deviation value of the simulated peristalsis control is obtained, the simulated peristalsis control parameters of the small intestine simulator device are optimized based on the deviation value of the simulated peristalsis control, and an experimental duration warning is issued.

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