A dual-column tandem mode was used to establish the fingerprints of Sarcandrae herb from different origins, and their chemical compositions were characterized by UPLC-Q-TOF-MS/MS, which provided an experimental basis for the establishment of a rapid and efficient method for the overall quality control of Sarcandrae herba. For the first time, nine common components were identified from the Sarcandrae herba herbs of 24 origins, which were neochlorogenic acid, chlorogenic acid, 4-caffeoylquinic acid, eleutheroside B1, quercetin-3-O-β-D-glucuronide, neoastilbin, astilbin, isofraxidin, and rosmarinic acid, respectively. A total of 92 compounds were identified by liquid mass spectrometry. The quality of the Sarcandrae herb from 24 origins was analyzed by similarity evaluation, principal component analysis, and cluster analysis, and the chemical components of Sarcandrae herba were identified by UPLC-Q-TOF-MS/MS. The results showed that the overall analysis based on fingerprinting and mass spectrometry could differentiate the origins of the herbs.

Background: Tablet manufacturing is challenged by strong dynamic coupling of process parameters, significant material property fluctuations, and delayed quality control, with tablet weight stability being particularly critical in high-speed production. Traditional static optimization methods relying on empirical judgment struggle to manage these dynamics, leading to substantial variations in tablet weight and hardness that severely compromise production efficiency. Methods: This study proposes a data-driven closed-loop control system centered on a novel Iterative Learning Model Predictive Control (IL-MPC) architecture. The core innovation lies in directly integrating iterative learning constraints within the MPC optimization framework. This constraint-embedding mechanism enables systematic utilization of historical batch data while preserving real-time optimization capabilities. The IL-MPC approach achieves enhanced batch-to-batch performance consistency with reduced computational burden, effectively combining the dual advantages of learning and optimization. Results: Simulation experiments and industrial production data validate the practical feasibility of the IL-MPC algorithm. Implementation results demonstrate that the proposed system effectively manages dynamic process variations, significantly improving control precision for both tablet weight and hardness, outperforming conventional control methods. Conclusions: This research breaks through the technical bottleneck of dynamic regulation in tablet manufacturing. The developed IL-MPC framework provides a reproducible closed-loop control paradigm for intelligent pharmaceutical manufacturing, promoting the industry’s transformation toward data-driven models and advancing intelligent drug production.

Background: This study deeply explores the influence of different dextrose equivalents (DE) values on room-temperature phosphorescence (RTP) properties of maltodextrin (MD) and its luminescence mechanism. The potential applications of MD tablets in non-destructive detection for afterglow visualizing are also explored. Methods: MD tablets with different DE values were prepared to investigate their RTP properties and afterglow effects. MD tablets were validated for afterglow signals and phosphorescence lifetimes under varying environmental conditions. Additionally, the unique afterglow effect of MD was used to detect the uniformity of tablets. Theoretical calculations of MD monomers and dimers were performed using time-dependent density functional theory. Results: The results demonstrated that MD with different DE values exhibited RTP properties, with phosphorescence lifetimes from 186.91 to 618.85 ms. The afterglow signals and phosphorescence lifetimes of MD tablets were influenced by multiple environmental conditions, i.e., relative humidity, temperature, oxygen, ultraviolet light, etc. Based on the afterglow effect of the MD, it is possible to non-destructively detect the uniform tablet. MD is an RTP material regulated by its DE value. Its phosphorescence mechanism is governed by a clustering-triggered emission mechanism, which is dominated by the rich hydrogen bond network. The material’s stimuli-responsive properties and pronounced afterglow effect make it a potential application for non-destructive detection. Conclusions: This study not only investigates the stimulus-responsive behavior of MD but also discovers a common, safe, and edible stimulus-responsive RTP material. These findings provide a new method for non-destructive detection of drugs and reducing the potential pharmacological risks during production, storage, and transportation.