As a subclass of the biopharmaceutical classification system (BCS) class II, basic drugs (BCS IIB) exhibit pH-dependent solubility and tend to generate supersaturation in the gastrointestinal tract, leading to less qualified in vitro–in vivo correlation (IVIVC). This study aims to develop a physiologically based multi-cup dissolution approach to improve the evaluation of the supersaturation for a higher quality of IVIVC and preliminarily explores the molecular mechanism of supersaturation and precipitation of ketoconazole affected by Polyvinylpyrrolidone–vinyl acetate copolymer (PVPVA) and hydroxypropyl methyl-cellulose (HPMC). The concentration of ketoconazole in each cup of the dynamic gastrointestinal model (DGIM) was measured using fiber optical probes. Molecular interactions between ketoconazole and PVPVA or HPMC were simulated by Materials Studio. The results demonstrated that PVPVA and HPMC improved and maintained the supersaturation of ketoconazole. PVPVA exhibited superior precipitation inhibitory effect on ketoconazole molecule aggregation due to slightly stronger van der Waals forces as well as unique electrostatic forces, thereby further enhancing in vitro drug absorption, which correlated well with in vivo drug absorption. Compared with a conventional dissolution apparatus paddle method, the DGIM improved the mean prediction error through the IVIVC from 19.30% to 9.96%, reaching the qualification criteria. In conclusion, the physiologically based multi-cup dissolution approach enables improved evaluation of supersaturation in gastrointestinal transportation of BCS IIB drug ketoconazole, enabling screening screen precipitation inhibitors and achieving qualified IVIVC for drug formulation studies.

Temperature can reflect vital activities, and researchers have attempted to guide Chinese medicine diagnosis and treatment by observing acupoint temperature changes. Integrating a temperature sensor at the needle tip enables in situ acupoint temperature measurement. However, the sensor needles for acupoint temperature monitoring designed in previous studies were fabricated by manually soldering thermistor beads and metal wires, making mass production difficult. In this work, using MEMS manufacturing technology, a flexible temperature sensor that can be integrated at the needle tip is proposed and can be mass-produced on silicon wafers. The sensor uses a Pt thermistor as the temperature-sensing element and has a slender flexible structure with dimensions of 125 μm width by 3.2 cm length. As the sensor is inserted into a hollow needle, the Pt thermistor is glued to the needle tip. In the temperature range of 30 °C to 50 °C, the fabricated temperature sensor has a sensitivity of 5.00 Ω∙°C⁻¹, a nonlinearity of ±0.39%FS, and a repeatability error of ±2.62%FS. Additionally, the sensor has been applied to in vivo acupoint temperature monitoring experiments in rats and demonstrated good performance, suggesting its promise for future research on acupoint temperature.

As a pivotal research method in the field of granular computing (GrC), fuzzy rough sets (FRSs) have garnered significant attention due to their successful overcoming of the limitations of traditional rough sets in handling continuous data. This paper is dedicated to exploring the application potential of FRS models within the framework of multi-source complex information systems, which undoubtedly holds profound research significance. Firstly, a novel multi-source mixed information system (MsMIS), encompassing five distinct data types, is introduced, thereby enriching the dimensions of data processing. Subsequently, a similarity function, designed based on the unique attributes of the data, is utilized to accurately quantify the similarity relations among objects. Building on this foundation, fuzzy T-norm operators are employed to integrate the similarity matrices derived from different data types into a cohesive whole. This integration not only lays a solid foundation for subsequent model construction but also highlights the value of multi-source information fusion in the analysis of the MsMIS. The integrated results are subsequently utilized to develop FRS models. Through rigorous examination from the perspective of information granularity, the rationality of the FRS model is proven, and its mathematical properties are explored. This paper contributes to the theoretical advancement of FRS models in GrC and offers promising prospects for their practical implementation.

Real-time monitoring of local muscle response during acupuncture could reveal mechanisms underlying acupuncture and provide objective feedback to support more precise needle control. However, the small dimensions of acupuncture needles impose stringent constraints on sensor miniaturization and packaging. This study presents an ultraminiature pressure sensor integrated into the tip of a 450-μm-diameter acupuncture needle. The sensor measures 200 × 1250 × 50 μm³ and incorporates an elongated pressure-sensitive diaphragm. Wafer-level AuSn solder deposition and thermocompression soldering connect the chip to an ultrafine wire ribbon routed through the 230-μm-diameter needle lumen. A 1.3-μm-thick Parylene C coating provides electrical insulation. After coating, the sensor exhibited a sensitivity of 40.3 μV/kPa at a 3.3 V excitation, retaining 78.4% of its uncoated sensitivity. Characterization over 90–150 kPa absolute and 25–45 °C yielded a maximum nonlinearity of approximately 0.73% of full scale (FS). The coated sensor exhibited a maximum hysteresis of 2.52% FS. In vivo experiments at the Zusanli acupoint in rats recorded pressure variations during thrusting–lifting manipulation. These results demonstrate the feasibility of monitoring local muscle response during acupuncture and their potential to provide quantitative feedback for needle manipulation.