Structural basis of peptidomimetic agonism revealed by small- molecule GLP-1R agonists Boc5 and WB4-24.

Glucagon-like peptide-1 receptor (GLP-1R) agonists are effective in treating type 2 diabetes and obesity with proven cardiovascular benefits. However, most of these agonists are peptides and require subcutaneous injection except for orally available semaglutide. Boc5 was identified as the first orthosteric nonpeptidic agonist of GLP-1R that mimics a broad spectrum of bioactivities of GLP-1 in vitro and in vivo. Here, we report the cryoelectron microscopy structures of Boc5 and its analog WB4-24 in complex with the human GLP-1R and Gs protein. Bound to the extracellular domain, extracellular loop 2, and transmembrane (TM) helices 1, 2, 3, and 7, one arm of both compounds was inserted deeply into the bottom of the orthosteric binding pocket that is usually accessible by peptidic agonists, thereby partially overlapping with the residues A8 to D15 in GLP-1. The other three arms, meanwhile, extended to the TM1-TM7, TM1-TM2, and TM2-TM3 clefts, showing an interaction feature substantially similar to the previously known small-molecule agonist LY3502970. Such a unique binding mode creates a distinct conformation that confers both peptidomimetic agonism and biased signaling induced by nonpeptidic modulators at GLP-1R. Further, the conformational difference between Boc5 and WB4-24, two closed related compounds, provides a structural framework for fine-tuning of pharmacological efficacy in the development of future small-molecule therapeutics targeting GLP-1R.

Thermally Stable and Chemically Recyclable Poly(ketal-ester)s Regulated by Floor Temperature.

Chemical recycling to monomers (CRM) offers a promising closed-loop approach to transition from current linear plastic economy toward a more sustainable circular paradigm. Typically, this approach has focused on modulating the ceiling temperature (Tc) of monomers. Despite considerable advancements, polymers with low Tc often face challenges such as inadequate thermal stability, exemplified by poly(γ-butyrolactone) (PGBL) with a decomposition temperature of ∼200 °C. In contrast, floor temperature (Tf)-regulated polymers, particularly those synthesized via the ring-opening polymerization (ROP) of macrolactones, inherently exhibit enhanced thermodynamic stability as the temperature increases. However, the development of those Tf regulated chemically recyclable polymers remains relatively underexplored. In this context, by judicious design and efficient synthesis of a biobased macrocyclic diester monomer (HOD), we developed a type of Tf -regulated closed-loop chemically recyclable poly(ketal-ester) (PHOD). First, the entropy-driven ROP of HOD generated high-molar mass PHOD with exceptional thermal stability with a Td,5% reaching up to 353 °C. Notably, it maintains a high Td,5% of 345 °C even without removing the polymerization catalyst. This contrasts markedly with PGBL, which spontaneously depolymerizes back to the monomer above its Tc in the presence of catalyst. Second, PHOD displays outstanding closed-loop chemical recyclability at room temperature within just 1 min with tBuOK. Finally, copolymerization of pentadecanolide (PDL) with HOD generated high-performance copolymers (PHOD-co-PPDL) with tunable mechanical properties and chemical recyclability of both components.

Prognostic value of the Naples prognostic score in patients with intrahepatic cholangiocarcinoma after hepatectomy.

BACKGROUND: The Naples Prognostic Score (NPS), integrating inflammatory and nutritional biomarkers, has been reported to be associated with the prognosis of various malignancies, but there is no report on intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the prognostic value of NPS in patients with ICC. METHODS: Patients with ICC after hepatectomy were collected, and divided into three groups. The prognosis factors were determined by Cox regression analysis. Predictive efficacy was evaluated by the time-dependent receiver operating characteristic (ROC) curves. RESULTS: A total of 174 patients were included (Group 1: 33 (19.0%) patients; Group 2: 83 (47.7%) patients; and Group 3: 58 (33.3%) patients). The baseline characteristics showed the higher the NPS, the higher the proportion of patients with cirrhosis and Child-Pugh B, and more advanced tumors. The Kaplan-Meier curves reflect higher NPS were associated with poor survival. Multivariable analysis showed NPS was an independent risk factor of overall survival (NPS group 2 vs. 1: HR = 1.671, 95% CI: 1.022-3.027, p = 0.009; NPS group 3 vs. 1: HR = 2.208, 95% CI: 1.259-4.780, p = 0.007) and recurrence-free survival (NPS group 2 vs. 1: HR = 1.506, 95% CI: 1.184-3.498, p = 0.010; NPS group 3 vs. 1: HR = 2.141, 95% CI: 2.519-4.087, P = 0.001). The time ROC indicated NPS was superior to other models in predicting prognosis. CONCLUSIONS: NPS is a simple and effective tool for predicting the long-term survival of patients with ICC after hepatectomy. Patients with high NPS require close follow-up, and improving NPS may prolong the survival time.

Deep Learning for Discrimination of Hypertrophic Cardiomyopathy and Hypertensive Heart Disease on MRI Native T1 Maps.

BACKGROUND: Native T1 and radiomics were used for hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) differentiation previously. The current problem is that global native T1 remains modest discrimination performance and radiomics requires feature extraction beforehand. Deep learning (DL) is a promising technique in differential diagnosis. However, its feasibility for discriminating HCM and HHD has not been investigated. PURPOSE: To examine the feasibility of DL in differentiating HCM and HHD based on T1 images and compare its diagnostic performance with other methods. STUDY TYPE: Retrospective. POPULATION: 128 HCM patients (men, 75; age, 50 years ± 16) and 59 HHD patients (men, 40; age, 45 years ± 17). FIELD STRENGTH/SEQUENCE: 3.0T; Balanced steady-state free precession, phase-sensitive inversion recovery (PSIR) and multislice native T1 mapping. ASSESSMENT: Compare HCM and HHD patients baseline data. Myocardial T1 values were extracted from native T1 images. Radiomics was implemented through feature extraction and Extra Trees Classifier. The DL network is ResNet32. Different input including myocardial ring (DL-myo), myocardial ring bounding box (DL-box) and the surrounding tissue without myocardial ring (DL-nomyo) were tested. We evaluate diagnostic performance through AUC of ROC curve. STATISTICAL TESTS: Accuracy, sensitivity, specificity, ROC, and AUC were calculated. Independent t test, Mann-Whitney U-test and Chi-square test were adopted for HCM and HHD comparison. P < 0.05 was considered statistically significant. RESULTS: DL-myo, DL-box, and DL-nomyo models showed an AUC (95% confidential interval) of 0.830 (0.702-0.959), 0.766 (0.617-0.915), 0.795 (0.654-0.936) in the testing set. AUC of native T1 and radiomics were 0.545 (0.352-0.738) and 0.800 (0.655-0.944) in the testing set. DATA CONCLUSION: The DL method based on T1 mapping seems capable of discriminating HCM and HHD. Considering diagnostic performance, the DL network outperformed the native T1 method. Compared with radiomics, DL won an advantage for its high specificity and automated working mode. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 2.

Deep learning using contrast-enhanced ultrasound images to predict the nuclear grade of clear cell renal cell carcinoma.

PURPOSE: To assess the effectiveness of a deep learning model using contrastenhanced ultrasound (CEUS) images in distinguishing between low-grade (grade I and II) and high-grade (grade III and IV) clear cell renal cell carcinoma (ccRCC). METHODS: A retrospective study was conducted using CEUS images of 177 Fuhrmangraded ccRCCs (93 low-grade and 84 high-grade) from May 2017 to December 2020. A total of 6412 CEUS images were captured from the videos and normalized for subsequent analysis. A deep learning model using the RepVGG architecture was proposed to differentiate between low-grade and high-grade ccRCC. The model's performance was evaluated based on sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Class activation mapping (CAM) was used to visualize the specific areas that contribute to the model's predictions. RESULTS: For discriminating high-grade ccRCC from low-grade, the deep learning model achieved a sensitivity of 74.8%, specificity of 79.1%, accuracy of 77.0%, and an AUC of 0.852 in the test set. CONCLUSION: The deep learning model based on CEUS images can accurately differentiate between low-grade and high-grade ccRCC in a non-invasive manner.

Photothermal Conversion Perylene-Based Metal-Organic Framework with Panchromatic Absorption Bandwidth across the Visible to Near-Infrared.

Recently, facilely designable metal-organic frameworks have gained attention in the construction of photothermal conversion materials. Nonetheless, most of the previously reported photothermal conversion metal-organic frameworks exhibit limited light absorption capabilities. In this work, a distinctive metal-organic framework with heterogeneous periodic alternate spatial arrangements of metal-oxygen clusters and perylene-based derivative molecules was prepared by in situ synthesis. The building blocks in this inimitable structure behave as both electron donors and electron acceptors, giving rise to the significant inherent charge transfer in this crystalline material, resulting in a narrow band gap with excellent panchromatic absorption, with the ground state being the charge transfer state. Moreover, it can retain excellent air-, photo-, and water-stability in the solid state. The excellent stability and broad light absorption characteristics enable the effective realization of near-infrared (NIR) photothermal conversion, including infrequent NIR-II photothermal conversion, in this perylene-based metal-organic framework.

A qualitative study on inner experience of self-management behavior among elderly patients with type 2 diabetes in rural areas.

BACKGROUND: As a chronic metabolic disease, diabetes poses a serious threat to human health and has become a major public health problem in China and worldwide. In 2020, 30% of Chinese people (aged ≥ 60 years) reported having diabetes mellitus. Moreover, individuals with diabetes living in rural areas face a significantly higher mortality risk compared to those in urban areas. In this study, we explored the inner experience of self-management behaviors in elderly patients with type 2 diabetes in rural areas to inform targeted interventions. METHODS: A phenomenological research design was used to explore the inner experience of self-management in rural elderly diabetes. Ten elderly diabetic patients were sampled from December 2022 to March 2023 in rural areas of Yangcheng County, Jincheng City, ShanXi Province, China. The seven-step Colaizzi phenomenological was used to analyze the interview data and generate themes. RESULTS: Four themes emerged: "Insufficient self-management cognition", "Negative self-management attitude", "Slack self-management behavior", and "No time for self-management". CONCLUSION: The level of self-management among elderly patients with type 2 diabetes in rural areas is low. Healthcare professionals should develop targeted interventions aimed at enhancing their cognitive levels, modifying their coping styles, and improving their self-management abilities to improve their quality of life.

Bioinformatics Analysis and Experimental Validation of Differential Genes and Pathways in Bone Nonunions.

Non-union fractures pose a significant clinical challenge, often leading to prolonged pain and disability. Understanding the molecular mechanisms underlying non-union fractures is crucial for developing effective therapeutic interventions. This study integrates bioinformatics analysis and experimental validation to unravel key genes and pathways associated with non-union fractures. We identified differentially expressed genes (DEGs) between non-union and fracture healing tissues using bioinformatics techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were employed to elucidate the biological processes and pathways involved. Common DEGs were identified, and a protein-protein interaction (PPI) network was constructed. Fibronectin-1 (FN1), Thrombospondin-1 (THBS1), and Biglycan (BGN) were pinpointed as critical target genes for non-union fracture treatment. Experimental validation involved alkaline phosphatase (ALP) and Alizarin Red staining to confirm osteogenic differentiation. Our analysis revealed significant alterations in pathways related to cell behavior, tissue regeneration, wound healing, infection, and immune responses in non-union fracture tissues. FN1, THBS1, and BGN were identified as key genes, with their upregulation indicating potential disruptions in the bone remodeling process. Experimental validation confirmed the induction of osteogenic differentiation. The study provides comprehensive insights into the molecular mechanisms of non-union fractures, emphasizing the pivotal roles of FN1, THBS1, and BGN in extracellular matrix dynamics and bone regeneration. The findings highlight potential therapeutic targets and pathways for further investigation. Future research should explore interactions between these genes, validate results using in vivo fracture models, and develop tailored treatment strategies for non-union fractures, promising significant advances in clinical management.

A few-shot identification method for stochastic dynamical systems based on residual multipeaks adaptive sampling.

Neural networks are popular data-driven modeling tools that come with high data collection costs. This paper proposes a residual-based multipeaks adaptive sampling (RMAS) algorithm, which can reduce the demand for a large number of samples in the identification of stochastic dynamical systems. Compared to classical residual-based sampling algorithms, the RMAS algorithm achieves higher system identification accuracy without relying on any hyperparameters. Subsequently, combining the RMAS algorithm and neural network, a few-shot identification (FSI) method for stochastic dynamical systems is proposed, which is applied to the identification of a vegetation biomass change model and the Rayleigh-Van der Pol impact vibration model. We show that the RMAS algorithm modifies residual-based sampling algorithms and, in particular, reduces the system identification error by 76% with the same sample sizes. Moreover, the surrogate model accurately predicts the first escape probability density function and the P bifurcation behavior in the systems, with the error of less than 1.59×10-2. Finally, the robustness of the FSI method is validated.

Role of Micelle Size in Cell Transcytosis-Based Tumor Extravasation, Infiltration, and Treatment Efficacy.

Transcytosis-based active transport of cancer nanomedicine has shown great promise for enhancing its tumor extravasation and infiltration and antitumor activity, but how the key nanoproperties of nanomedicine, particularly particle size, influence the transcytosis remains unknown. Herein, we used a transcytosis-inducing polymer, poly[2-(N-oxide-N,N-diethylamino)ethyl methacrylate] (OPDEA), and fabricated stable OPDEA-based micelles with different sizes (30, 70, and 140 nm in diameter) from its amphiphilic block copolymer, OPDEA-block-polystyrene (OPDEA-PS). The study of the micelle size effects on cell transcytosis, tumor extravasation, and infiltration showed that the smallest micelles (30 nm) had the fastest transcytosis and, thus, the most efficient tumor extravasation and infiltration. So, the 7-ethyl-10-hydroxyl camptothecin (SN38)-conjugated OPDEA micelles of 30 nm had much enhanced antitumor activity compared with the 140 nm micelles. These results are instructive for the design of active cancer nanomedicine.

Enabling Closed-Loop Circularity of "Non-Polymerizable" α, ß-Conjugated Lactone Towards High-Performance Polyester with the Assistance of Cyclopentadiene.

Chemical recycling of polymers to monomers presents a promising solution to the escalating crisis associated with plastic waste. Despite considerable progress made in this field, the primary efforts have been focused on redesigning new monomers to produce readily recyclable polymers. In contrast, limited research into the potential of seemingly "non-polymerizable" monomers has been conducted. Herein, we propose a paradigm that leverages a "chaperone"-assisted strategy to establish closed-loop circularity for a "non-polymerizable" α, ß-conjugated lactone, 5,6-dihydro-2H-pyran-2-one (DPO). The resulting PDPO, a structural analogue of poly(δ-valerolactone) (PVL), exhibits enhanced thermal properties with a melting point (Tm) of 114 °C and a decomposition temperature (Td,5%) of 305 °C. Notably, owing to the structural similarity between DPO and δ-VL, the copolymerization generates semi-crystalline P(DPO-co-VL)s irrespective of the DPO incorporation ratio. Intriguingly, the inherent C=C bonds in P(DPO-co-VL)s enable their convenient post-functionalization via Michael-addition reaction. Lastly, PDPO was demonstrated to be chemically recyclable via ring-closing metathesis (RCM), representing a significant step towards the pursuit of enabling the closed-loop circularity of "non-polymerizable" lactones without altering the ultimate polymer structure.

Single-nucleus RNA sequencing and mRNA hybridization indicate key bud events and LcFT1 and LcTFL1-2 mRNA transportability during floral transition in litchi.

In flowering plants, floral induction signals intersect at the shoot apex to modulate meristem determinacy and growth form. Here, we report a single-nucleus RNA sequence analysis of litchi apical buds at different developmental stages. A total of 41 641 nuclei expressing 21 402 genes were analyzed, revealing 35 cell clusters corresponding to 12 broad populations. We identify genes associated with floral transition and propose a model that profiles the key events associated with litchi floral meristem identity by analyzing 567 identified floral meristem cells at single cell resolution. Interestingly, single-nucleus RNA-sequencing data indicated that all putative FT and TFL1 genes were not expressed in bud nuclei, but significant expression was detected in bud samples by RT-PCR. Based on the expression patterns and gene silencing results, we highlight the critical role of LcTFL1-2 in inhibiting flowering and propose that the LcFT1/LcTFL1-2 expression ratio may determine the success of floral transition. In addition, the transport of LcFT1 and LcTFL1-2 mRNA from the leaf to the shoot apical meristem is proposed based on in situ and dot-blot hybridization results. These findings allow a more comprehensive understanding of the molecular events during the litchi floral transition, as well as the identification of new regulators.

Alternating [1.1.1]Propellane-(Meth)Acrylate Copolymers: A New Class of Dielectrics with High Energy Density for Film Capacitors.

Polymer dielectrics with high energy density are of urgent demand in electric and electronic devices, but the tradeoff between dielectric constant and breakdown strength is still unsolved. Herein, the synthesis and molar mass control of three alternating [1.1.1]propellane-(meth)acrylate copolymers, denoted as P-MA, P-MMA, and P-EA, respectively, are reported. These copolymers exhibit high thermal stability and are semi-crystalline with varied glass transition temperatures and melting temperatures. The rigid bicyclo[1.1.1]pentane units in the polymer backbone promote the orientational polarization of the polar ester groups, thus enhancing the dielectric constants of these polymers, which are 4.50 for P-EA, 4.55 for P-MA, and 5.11 for P-MMA at 10 Hz and room temperature, respectively. Moreover, the high breakdown strength is ensured by the non-conjugated nature of bicyclo[1.1.1]pentane unit. As a result, these copolymers show extraordinary energy storage performance; P-MA exhibits a discharge energy density of 9.73 J cm-3 at 750 MV m-1 and ambient temperature. This work provides a new type of promising candidates as polymer dielectrics for film capacitors, and offers an efficient strategy to improve the dielectric and energy storage properties by introducing rigid non-conjugated bicyclo[1.1.1]pentane unit into the polymer backbone.

Protective effect of vitamin B6 against doxorubicin-induced cardiotoxicity by modulating NHE1 expression.

Doxorubicin (DOX) has been used to treat various types of cancer, but its application is limited due to its heart toxicity as well as other drawbacks. Chronic inhibition of Na+ /H+ exchanger (NHE1) reduces heart failure and reduces the production of reactive oxygen species (ROS); vitamin B6 (VitB6 ) has been demonstrated to have a crucial role in antioxidant mechanism. So, this study was designed to explore the effect of VitB6 supplement on the DOX-induced cardiotoxicity and to imply whether NHE1 is involved. Ultrasonic cardiogram analysis revealed that VitB6 supplement could alleviate DOX-induced cardiotoxicity; hematoxylin and eosin (HE) and Masson's staining further confirmed this effect. Furthermore, VitB6 supplement exhibited significant antioxidative stress and antiapoptosis effect, which was evidenced by decreased serum malondialdehyde (MDA) content and increased serum superoxide dismutase (SOD) content, and decreased Bcl-2-associated X protein/B-cell lymphoma-2 ratio, respectively. Collectively, VitB6 supplement may exert antioxidative and antiapoptosis effects to improve cardiac function by decreasing NHE1 expression and improve DOX-induced cardiotoxicity.

Regularized least absolute deviation-based sparse identification of dynamical systems.

This work develops a regularized least absolute deviation-based sparse identification of dynamics (RLAD-SID) method to address outlier problems in the classical metric-based loss function and the sparsity constraint framework. Our method uses absolute derivation loss as a substitute of Euclidean loss. Moreover, a corresponding computationally efficient optimization algorithm is derived on the basis of the alternating direction method of multipliers due to the non-smoothness of both the new proposed loss function and the regularization term. Numerical experiments are performed to evaluate the effectiveness of RLAD-SID using several exemplary nonlinear dynamical systems, such as the van der Pol equation, the Lorenz system, and the 1D discrete logistic map. Furthermore, detailed numerical comparisons are provided with other existing methods in metric-based sparse regression. Numerical results demonstrate that (1) RLAD-SID shows significant robustness toward a large outlier and (2) RLAD-SID can be seen as a particular metric-based sparse regression strategy that exhibits the effectiveness of the metric-based sparse regression framework for solving outlier problems in a dynamical system identification.

Exerkine fibronectin type-III domain-containing protein 5/irisin-enriched extracellular vesicles delay vascular ageing by increasing SIRT6 stability.

AIMS: Exercise confers protection against cardiovascular ageing, but the mechanisms remain largely unknown. This study sought to investigate the role of fibronectin type-III domain-containing protein 5 (FNDC5)/irisin, an exercise-associated hormone, in vascular ageing. Moreover, the existence of FNDC5/irisin in circulating extracellular vesicles (EVs) and their biological functions was explored. METHODS AND RESULTS: FNDC5/irisin was reduced in natural ageing, senescence, and angiotensin II (Ang II)-treated conditions. The deletion of FNDC5 shortened lifespan in mice. Additionally, FNDC5 deficiency aggravated vascular stiffness, senescence, oxidative stress, inflammation, and endothelial dysfunction in 24-month-old naturally aged and Ang II-treated mice. Conversely, treatment of recombinant irisin alleviated Ang II-induced vascular stiffness and senescence in mice and vascular smooth muscle cells. FNDC5 was triggered by exercise, while FNDC5 knockout abrogated exercise-induced protection against Ang II-induced vascular stiffness and senescence. Intriguingly, FNDC5 was detected in human and mouse blood-derived EVs, and exercise-induced FNDC5/irisin-enriched EVs showed potent anti-stiffness and anti-senescence effects in vivo and in vitro. Adeno-associated virus-mediated rescue of FNDC5 specifically in muscle but not liver in FNDC5 knockout mice, promoted the release of FNDC5/irisin-enriched EVs into circulation in response to exercise, which ameliorated vascular stiffness, senescence, and inflammation. Mechanistically, irisin activated DnaJb3/Hsp40 chaperone system to stabilize SIRT6 protein in an Hsp70-dependent manner. Finally, plasma irisin concentrations were positively associated with exercise time but negatively associated with arterial stiffness in a proof-of-concept human study. CONCLUSION: FNDC5/irisin-enriched EVs contribute to exercise-induced protection against vascular ageing. These findings indicate that the exerkine FNDC5/irisin may be a potential target for ageing-related vascular comorbidities.

[Manufacturing classification system for oral solid dosage forms of traditional Chinese medicines (â ¡): classification of tablets disintegration behavior].

In this paper, 50 batches of representative traditional Chinese medicine tablets were selected and the disintegration time was examined with the method in Chinese Pharmacopoeia. The disintegration time and disintegration phenomenon were recorded, and the dissolution behaviors of water-soluble and ultraviolet-absorbent components during the disintegration process of tablets were characterized by self-control method. The results revealed that coating type and raw material type influenced the disintegration time of tablets. It was found that only 4% of traditional Chinese medicine tablets had obvious fragmentation during the disintegration process, while 96% of traditional Chinese medicine tablets showed gradual dissolution or dispersion. Furthermore, according to the disintegration speed, disintegration phenomenon, and whether the cumulative dissolution of measured components was > 90% at complete disintegration, a disintegration behavior classification system(DBCS) was created for the regular-release traditional Chinese medicine tablets. As a result, the disintegration behaviors of 50 batches of traditional Chinese medicine tablets were classified into four categories, i.e. ⅠA_2, ⅠB_1, ⅡB_1, and ⅡB_2. traditional Chinese medicine tablets(Class I) with disintegration time ≤ 30 min were defined to be rapid in disintegration, which can be the objective of optimization or improvement of Chinese herbal extract(semi extract) tablets. Different drug release models were used to fit the dissolution curve of traditional Chinese medicine tablets with gradual dissolution or dispersion phenomenon(i.e. Type B tablets). The results showed that the dissolution curves of water-soluble components in the disintegration process conformed to the zero order kinetics and the Ritger-Peppas model. It could be inferred that the disintegration mechanisms of type B tablets were a combination of dissolution controlled and swelling controlled mechanisms. This study contributes to understanding the disintegration behavior of traditional Chinese medicine tablets, and provides a reference for the design and improvement of disintegration performance of traditional Chinese medicine tablets.

[Patent application of intelligent quality control technology in traditional Chinese medicine production process: a review].

In the new stage for intelligent manufacturing of traditional Chinese medicine(TCM) from pilot demonstration to in-depth application and comprehensive promotion, how to raise the degree of intelligence for the process quality control system has become the bottleneck of the development of TCM production process control technology. This article has sorted out 226 TCM intelligent manufacturing projects that have been approved by the national and provincial governments since the implementation of the "Made in China 2025" plan and 145 related pharmaceutical enterprises. Then, the patents applied by these pharmaceutical enterprises were thoroughly retrieved, and 135 patents in terms of intelligent quality control technology in the production process were found. The technical details about intelligent quality control at both the unit levels such as cultivation, processing of crude herbs, preparation pretreatment, pharmaceutical preparations, and the production workshop level were reviewed from three aspects, i.e., intelligent quality sensing, intelligent process cognition, and intelligent process control. The results showed that intelligent quality control technologies have been preliminarily applied to the whole process of TCM production. The intelligence control of the extraction and concentration processes and the intelligent sensing of critical quality attributes are currently the focus of pharmaceutical enterprises. However, there is a lack of process cognitive patent technology for the TCM manufacturing process, which fails to meet the requirements of closed-loop integration of intelligent sensing and intelligent control technologies. It is suggested that in the future, with the help of artificial intelligence and machine learning methods, the process cognitive bottleneck of TCM production can be overcome, and the holistic quality formation mechanisms of TCM products can be elucidated. Moreover, key technologies for system integration and intelligent equipment are expected to be innovated and accelerated to enhance the quality uniformity and manufacturing reliability of TCM.

[Manufacturing classification system for oral solid dosage forms of traditional Chinese medicines(â £): classification of hygroscopicity behaviors of capsules].

Hard capsules of traditional Chinese medicine(TCM) have different degrees of hygroscopicity, which affects the stability and efficacy of drugs. In this paper, 30 kinds of commercially available TCM capsules were used as the research object. The hygroscopicity curves of capsule contents, capsule shells, and capsules were tested respectively, and the first-order kinetic equation was used for fitting. The results show that during the 24 h hygroscopicity process, the capsule shell can reduce the weight gain caused by the hygroscopicity of the contents by 0.80%-53.0% and the hygroscopicity rate of the capsule contents by 1.74%-91.3%, indicating that the capsule shell has a strong delay effect on the hygroscopicity of the contents of the TCM capsules. Seven physical parameters of the contents of 30 kinds of TCM capsules were determined, and 14 prescription process-related parameters were sorted out. A partial least squares model for predicting the hygroscopicity rate of the contents of TCM capsules(with shell) for 24 h was established. It is found that the hygroscopicity rate of the capsule shell is positively correlated with the hygroscopicity of the contents of TCM capsules(with shell), suggesting that the capsule shell with a low hygroscopicity rate is helpful for moisture prevention. In addition, the pre-treatment process route of the preparation and the type of molding raw materials affect the hygroscopicity. A larger proportion of the extract in the capsule content and a smaller proportion of the fine powder of the decoction pieces indicate stronger hygroscopicity of the capsule content. The 24 h hygroscopicity rate of 15% was used as the classification node of hygroscopicity strength, and the hygroscopicity rate constant of 0.58 was used as the classification node of hygroscopicity speed. The classification system of hygroscopicity behaviors of TCM capsules was established: the varieties with strong and fast hygroscopicity accounted for about 6.67%, while those with strong and slow hygroscopicity accounted for about 33.3%; the varieties with weak and fast hygroscopicity accounted for about 26.7%, while those with weak and slow hygroscopicity accounted for about 33.3%. The classification system is helpful to quantify and compare the hygroscopicity behavior of different TCM capsules and provides a reference for the quality improvement, moisture prevention technologies, and material research of TCM capsules.

[Research progress and maturity assessment of continuous manufacturing of traditional Chinese medicine].

The pharmaceutical manufacturing model is gradually changing from intermittent manufacturing to continuous manufacturing and intelligent manufacturing. This paper briefly reviewed the supervision and research progress in continuous pharmaceutical manufacturing in China and abroad and described the definition and advantages of continuous pharmaceutical manufacturing. The continuous manufacturing of traditional Chinese medicine(TCM) at the current stage was summarized in the following three terms: the enhancement of the continuity of intermittent manufacturing operations, the integration of continuous equipment to improve physical continuity between units, and the application of advanced process control strategies to improve process continuity. To achieve continuous manufacturing of TCM, the corresponding key technologies, such as material property characterization, process modeling and simulation, process analysis technology, and system integration, were analyzed from the process and equipment, respectively. It was proposed that the continuous manufacturing equipment system should have the characteristics of high speed, high response, and high reliability, "three high(H~3)" for short. Considering the characteristics and current situation of TCM manufacturing, based on the two dimensions of product quality control and production efficiency, a maturity assessment model for continuous manufacturing of TCM, consisting of operation continuity, equipment continuity, process continuity, and quality control continuity, was proposed to provide references for the application of continuous manufacturing technology for TCM. The implementation of continuous manufacturing or the application of key continuous manufacturing technologies in TCM can help to systematically integrate advanced pharmaceutical technology elements and promote the uniformity of TCM quality and the improvement of production efficiency.