A multi-tissue metabolome atlas of primate pregnancy.

Pregnancy induces dramatic metabolic changes in females; yet, the intricacies of this metabolic reprogramming remain poorly understood, especially in primates. Using cynomolgus monkeys, we constructed a comprehensive multi-tissue metabolome atlas, analyzing 273 samples from 23 maternal tissues during pregnancy. We discovered a decline in metabolic coupling between tissues as pregnancy progressed. Core metabolic pathways that were rewired during primate pregnancy included steroidogenesis, fatty acid metabolism, and arachidonic acid metabolism. Our atlas revealed 91 pregnancy-adaptive metabolites changing consistently across 23 tissues, whose roles we verified in human cell models and patient samples. Corticosterone and palmitoyl-carnitine regulated placental maturation and maternal tissue progenitors, respectively, with implications for maternal preeclampsia, diabetes, cardiac hypertrophy, and muscle and liver regeneration. Moreover, we found that corticosterone deficiency induced preeclampsia-like inflammation, indicating the atlas's potential clinical value. Overall, our multi-tissue metabolome atlas serves as a framework for elucidating the role of metabolic regulation in female health during pregnancy.

Neurulation of the cynomolgus monkey embryo achieved from 3D blastocyst culture.

Neural tube (NT) defects arise from abnormal neurulation and result in the most common birth defects worldwide. Yet, mechanisms of primate neurulation remain largely unknown due to prohibitions on human embryo research and limitations of available model systems. Here, we establish a three-dimensional (3D) prolonged in vitro culture (pIVC) system supporting cynomolgus monkey embryo development from 7 to 25 days post-fertilization. Through single-cell multi-omics analyses, we demonstrate that pIVC embryos form three germ layers, including primordial germ cells, and establish proper DNA methylation and chromatin accessibility through advanced gastrulation stages. In addition, pIVC embryo immunofluorescence confirms neural crest formation, NT closure, and neural progenitor regionalization. Finally, we demonstrate that the transcriptional profiles and morphogenetics of pIVC embryos resemble key features of similarly staged in vivo cynomolgus and human embryos. This work therefore describes a system to study non-human primate embryogenesis through advanced gastrulation and early neurulation.

Primate gastrulation and early organogenesis at single-cell resolution.

Our understanding of human early development is severely hampered by limited access to embryonic tissues. Due to their close evolutionary relationship with humans, nonhuman primates are often used as surrogates to understand human development but currently suffer from a lack of in vivo datasets, especially from gastrulation to early organogenesis during which the major embryonic cell types are dynamically specified. To fill this gap, we collected six Carnegie stage 8-11 cynomolgus monkey (Macaca fascicularis) embryos and performed in-depth transcriptomic analyses of 56,636 single cells. Our analyses show transcriptomic features of major perigastrulation cell types, which help shed light on morphogenetic events including primitive streak development, somitogenesis, gut tube formation, neural tube patterning and neural crest differentiation in primates. In addition, comparative analyses with mouse embryos and human embryoids uncovered conserved and divergent features of perigastrulation development across species-for example, species-specific dependency on Hippo signalling during presomitic mesoderm differentiation-and provide an initial assessment of relevant stem cell models of human early organogenesis. This comprehensive single-cell transcriptome atlas not only fills the knowledge gap in the nonhuman primate research field but also serves as an invaluable resource for understanding human embryogenesis and developmental disorders.

Non-CO2 greenhouse gas separation using advanced porous materials.

Global warming has become a growing concern over decades, prompting numerous research endeavours to reduce the carbon dioxide (CO2) emission, the major greenhouse gas (GHG). However, the contribution of other non-CO2 GHGs including methane (CH4), nitrous oxide (N2O), fluorocarbons, perfluorinated gases, etc. should not be overlooked, due to their high global warming potential and environmental hazards. In order to reduce the emission of non-CO2 GHGs, advanced separation technologies with high efficiency and low energy consumption such as adsorptive separation or membrane separation are highly desirable. Advanced porous materials (APMs) including metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs), porous organic polymers (POPs), etc. have been developed to boost the adsorptive and membrane separation, due to their tunable pore structure and surface functionality. This review summarizes the progress of APM adsorbents and membranes for non-CO2 GHG separation. The material design and fabrication strategies, along with the molecular-level separation mechanisms are discussed. Besides, the state-of-the-art separation performance and challenges of various APM materials towards each type of non-CO2 GHG are analyzed, offering insightful guidance for future research. Moreover, practical industrial challenges and opportunities from the aspect of engineering are also discussed, to facilitate the industrial implementation of APMs for non-CO2 GHG separation.

Amplifying Photon Upconversion in Alloyed Nanoparticles for a Near-Infrared Photodetector.

Photon upconverison has attracted a substantial amount of interest in diverse fields due to its characteristic anti-Stokes emissions. However, obtaining intense emission under low-power laser irradiation has remained a challenge. Here we report a mechanistic design of activator-sensitizer alloyed nanoparticles to achieve bright upconversion under weak infrared irradiation. This design allows a nearest sensitizer-activator separation to facilitate efficient energy transfer that results in remarkably enhanced upconversion (>2 orders of magnitude) under 0.26 W cm-2 irradiation compared to that of the Er sublattice, and the upconversion quantum yield also shows a 20-fold increase. Interestingly, the alloyed nanoparticles exhibit a gradual change in emission color with an increase in Yb3+ content, and moreover, their emission colors can be dynamically controlled by simply modulating the excitation laser power and pulse widths. Such alloyed nanoparticles show great promise for application in a near-infrared photodetector.

A comprehensive analysis of the WRKY family in soybean and functional analysis of GmWRKY164-GmGSL7c in resistance to soybean mosaic virus.

BACKGROUND: Soybean mosaic disease caused by soybean mosaic virus (SMV) is one of the most devastating and widespread diseases in soybean producing areas worldwide. The WRKY transcription factors (TFs) are widely involved in plant development and stress responses. However, the roles of the GmWRKY TFs in resistance to SMV are largely unclear. RESULTS: Here, 185 GmWRKYs were characterized in soybean (Glycine max), among which 60 GmWRKY genes were differentially expressed during SMV infection according to the transcriptome data. The transcriptome data and RT-qPCR results showed that the expression of GmWRKY164 decreased after imidazole treatment and had higher expression levels in the incompatible combination between soybean cultivar variety Jidou 7 and SMV strain N3. Remarkably, the silencing of GmWRKY164 reduced callose deposition and enhanced virus spread during SMV infection. In addition, the transcript levels of the GmGSL7c were dramatically lower upon the silencing of GmWRKY164. Furthermore, EMSA and ChIP-qPCR revealed that GmWRKY164 can directly bind to the promoter of GmGSL7c, which contains the W-box element. CONCLUSION: Our findings suggest that GmWRKY164 plays a positive role in resistance to SMV infection by regulating the expression of GmGSL7c, resulting in the deposition of callose and the inhibition of viral movement, which provides guidance for future studies in understanding virus-resistance mechanisms in soybean.

Recovery of High-Purity SF6 from Humid SF6/N2 Mixture within a Co(II)-Pyrazolate Framework.

Sulfur hexafluoride (SF6) is extensively employed in the power industry. However, its emissions significantly contribute to the greenhouse effect. The direct recovery of high purity SF6 from industrial waste gases would benefit its sustainable use, yet this represents a considerable challenge. Herein, we report the enrichment of SF6 from SF6/N2 mixtures via adsorptive separation in a stable Co(II)-pyrazolate MOF BUT-53 (BUT: Beijing University of Technology), which features dynamic molecular traps. BUT-53 exhibits an excellent SF6 adsorption uptake of 2.82 mmol/g at 0.1 bar and 298 K, as well as an unprecedented SF6/N2 (10:90) selectivity of 2485. Besides, the remarkable SF6/N2 selectivity of BUT-53 enables recovery of high purity (>99.9%) SF6 from a low concentration (10%) mixture through a breakthrough experiment. The excellent SF6/N2 separation efficiency was also well maintained under humid conditions (RH = 90%) over multiple cycles. Molecular simulation, single-crystal diffraction, and adsorption kinetics studies elucidate the associated adsorption mechanism and water tolerance.

BioNet: a large-scale and heterogeneous biological network model for interaction prediction with graph convolution.

MOTIVATION: Understanding chemical-gene interactions (CGIs) is crucial for screening drugs. Wet experiments are usually costly and laborious, which limits relevant studies to a small scale. On the contrary, computational studies enable efficient in-silico exploration. For the CGI prediction problem, a common method is to perform systematic analyses on a heterogeneous network involving various biomedical entities. Recently, graph neural networks become popular in the field of relation prediction. However, the inherent heterogeneous complexity of biological interaction networks and the massive amount of data pose enormous challenges. This paper aims to develop a data-driven model that is capable of learning latent information from the interaction network and making correct predictions. RESULTS: We developed BioNet, a deep biological networkmodel with a graph encoder-decoder architecture. The graph encoder utilizes graph convolution to learn latent information embedded in complex interactions among chemicals, genes, diseases and biological pathways. The learning process is featured by two consecutive steps. Then, embedded information learnt by the encoder is then employed to make multi-type interaction predictions between chemicals and genes with a tensor decomposition decoder based on the RESCAL algorithm. BioNet includes 79 325 entities as nodes, and 34 005 501 relations as edges. To train such a massive deep graph model, BioNet introduces a parallel training algorithm utilizing multiple Graphics Processing Unit (GPUs). The evaluation experiments indicated that BioNet exhibits outstanding prediction performance with a best area under Receiver Operating Characteristic (ROC) curve of 0.952, which significantly surpasses state-of-theart methods. For further validation, top predicted CGIs of cancer and COVID-19 by BioNet were verified by external curated data and published literature.

Oxidized low-density lipoproteins impair the pro-atherosclerotic effect of granulocyte-macrophage-colony-stimulating factor-producing T helper cells on macrophages.

T cells contribute to the pathogenesis of atherosclerosis. However, the presence and function of granulocyte-macrophage-colony-stimulating factor (GM-CSF)-producing T helper (ThGM) cells in atherosclerosis development is unknown. This study aims to characterize the phenotype and function of ThGM cells in experimental atherosclerosis. Atherosclerosis was induced by feeding apolipoprotein E knockout (ApoE-/-) mice with a high-fat diet. Aortic ThGM cells were detected and sorted by flow cytometry. The effect of oxidized low-density lipoprotein (oxLDL) on ThGM cells and the impact of ThGM cells on macrophages were evaluated by flow cytometry, quantitative RT-PCR, oxLDL binding/uptake assay, immunoblotting and foam cell formation assay. We found that GM-CSF+IFN-γ- ThGM cells existed in atherosclerotic aortas. Live ThGM cells were enriched in aortic CD4+CCR6-CCR8-CXCR3-CCR10+ T cells. Aortic ThGM cells triggered the expression of interleukin-1ß (IL-1ß), tumour necrosis factor (TNF), interleukin-6 (IL-6) and C-C motif chemokine ligand 2 (CCL2) in macrophages. Besides, aortic ThGM cells expressed higher CD69 than other T cells and bound to oxLDL. oxLDL suppressed the cytokine expression in ThGM cells probably via inhibiting the signal transducer and activator of transcription 5 (STAT5) signalling. Furthermore, oxLDL alleviated the effect of ThGM cells on inducing macrophages to produce pro-inflammatory cytokines and generate foam cells. The nuclear receptor subfamily 4 group A (NR4A) members NR4A1 and NR4A2 were involved in the suppressive effect of oxLDL on ThGM cells. Collectively, oxLDL suppressed the supportive effect of ThGM cells on pro-atherosclerotic macrophages.

Discriminative detection of soman or VX exposure using europium chelated microparticle-based immunofluorescence microfluidic chip.

The retrospective detection of organophosphorus nerve agents (OPNAs) exposure has been achieved by the off-site analysis of OPNA-human serum albumin (HSA) adducts using mass spectrometry-based detection approaches. However, few specific methods are accessible for on-site detection. To address this, a novel immunofluorescence microfluidic chip (IFMC) testing system combining europium chelated microparticle (EuCM) with self-driven microfluidic chip assay has been established to unambiguously determine soman (GD) and VX exposure within 20 min, respectively. The detection system was based on the principle of indirect competitive enzyme-linked immunosorbent assay. The specific monoclonal antibodies that respectively recognized the phosphonylated tyrosine 411 of GD-HSA and VX-HSA adducts were labeled by EuCM to capture corresponding adducts in the exposed samples. The phosphonylated peptides in the test line and goat-anti-rabbit antibody in the control line were utilized to bind the EuCM-labeled antibodies for signal exhibition. The developed IFMC chip could discriminatively detect exposed HSA adducts with high specificity, demonstrating a low limit of detection at exposure concentrations of 0.5 × 10-6 mol/L VX and 1.0 × 10-6 mol/L GD. The exposed serum samples can be qualitatively detected following an additional pretreatment procedure. This is a novel rapid detection system capable of discriminating GD and VX exposure, providing an alternative method for rapidly identifying OPNA exposure.

Cold tolerance SNPs and candidate gene mining in the soybean germination stage based on genome-wide association analysis.

KEY MESSAGE: Three QTLs associated with low-temperature tolerance were identified by genome-wide association analysis, and 15 candidate genes were identified by haplotype analysis and gene expression analyses. Low temperature is a critical factor affecting the geographical distribution, growth, development, and yield of soybeans, with cold stress during seed germination leading to substantial productivity loss. In this study, an association panel comprising 260 soybean accessions was evaluated for four germination traits and four cold tolerance index traits, revealing extensive variation in cold tolerance. Genome-wide association study (GWAS) identified 10 quantitative trait nucleotides (QTNs) associated with cold tolerance, utilizing 30,799 single nucleotide polymorphisms (SNPs) and four GWAS models. Linkage disequilibrium (LD) analysis positioned these QTNs within three cold-tolerance quantitative trait loci (QTL) and, with QTL19-1, was positioned by three multi-locus models, underscoring its importance as a key QTL. Integrative haplotype analysis, supplemented by transcriptome analysis, uncovered 15 candidate genes. The haplotypes within the genes Glyma.18G044200, Glyma.18G044300, Glyma.18G044900, Glyma.18G045100, Glyma.19G222500, and Glyma.19G222600 exhibited significant phenotypic variations, with differential expression in materials with varying cold tolerance. The QTNs and candidate genes identified in this study offer substantial potential for marker-assisted selection and gene editing in breeding cold-tolerant soybeans, providing valuable insights into the genetic mechanisms underlying cold tolerance during soybean germination.

Posterior capsular radial sign: a novel method to confirm anterior vitreous cortex resection in phacovitrectomy.

BACKGROUND: The main purpose of this paper is to introduce a method that can accurately locate the posterior capsule of the lens to facilitate a relatively complete resection of the anterior vitreous body. METHODS: A total of 51 patients in the experimental group and control group were enrolled in this study. Phacoemulsification combined with vitrectomy was performed in all cases. After the cataract procedure was completed in the control group, the surgeon performed a conventional anterior vitrectomy with the operative eye. In the experimental group, anterior vitrectomy was performed according to the threadiness corrugation of the posterior capsule of the lens. During the operation, with the help of triamcinolone, two surgeons confirmed the resection of the anterior vitreous cortex; the best corrected visual acuity and intraocular pressure of all patients were recorded at 1 week, 1 month and 3 months after surgery. RESULTS: Fifty patients underwent phacoemulsification combined with vitrectomy, except one patient in the experimental group who was lost to follow-up. After surgery, no significant complications were observed in all patients except two patients in the control group with temporary increases in intraocular pressure. There was no significant difference in preoperative visual acuity between the two groups (t = 0.83, P = 0.25). Both groups had varying degrees of improvement in best corrected visual acuity at 1 week, 1 month and 3 months after surgery. Moreover, there was no significant difference in BCVA between the two groups at the three follow-up time points (t=-1.15, -1.65, -1.09, P = 0.53, 0.21, 0.23). After surgery, no significant complications were observed in all patients except two patients in the control group with temporary increases in intraocular pressure. Incomplete resection of the anterior vitreous cortex was observed in 2 patients in each group, but there was no significant difference (χ2 = 7.81, P > 0.05). CONCLUSION: In the process of cataract surgery combined with vitrectomy, thready corrugation appears in the posterior capsule of the lens and is an important sign of its localization. Anterior vitrectomy can be accomplished safely and effectively with the help of thread-like corrugation, and the surgical effect is almost the same as that of traditional surgery. Especially suitable for beginners in vitreous surgery.

A novel chromone Schiff base as Zn2+ turn-on fluorescent chemosensor in a mixed solution.

In this study, a novel fluorescent chemosensor 1 based on chromone-3-carboxaldehyde Schiff base was synthesized and featured through nuclear magnetic resonance (NMR) and mass spectra. Spectroscopic investigation indicated that the fluorescent sensor showed high selectivity toward Zn2+ over other metal ions and that the detection limit of 1 could reach 10-7  M. These indicated that 1 acted as a highly selective and sensitive fluorescence chemosensor for Zn2+ .

Population genetic diversity and structure of Tephritis angustipennis and Campiglossa loewiana (Diptera: Tephritidae) based on COI DNA barcodes in the three-river source region, China.

Tephritis angustipennis (Diptera: Tephritidae) and Campiglossa loewiana (Diptera: Tephritidae) are phytophagous pests in China. Their damage has significantly impacted the collection and cultivation of germplasm resources of native Asteraceae plants. However, the genetic characteristics and structure of their population are unclear. This study focused on the highly damaging species of T. angustipennis and C. loewiana collected from the three-river source region (TRSR). We amplified the mitochondrial cytochrome C oxidase subunit I (mtCOI) gene sequences of these pests collected from this area and compared them with COI sequences from GenBank. We also analyzed their genetic diversity and structure. In T. angustipennis, 5 haplotypes were identified from 5 geographic locations; the genetic differentiation between France population FRPY (from Nylandia, Uusimaa) and China populations GLJZ (from Dehe Longwa Village, Maqin County), GLDR (from Zhique Village, Dari County), and GLMQ (from Rijin Village, Maqin County) was the strongest. GLJZ exhibited strong genetic differentiation from GLDR and GLMQ, with relatively low gene flow. For C. loewiana, 11 haplotypes were identified from 5 geographic locations; the genetic differentiation between the Chinese population GLMQ-YY (from Yangyu Forest Farm, Maqin County) and Finnish population FDNL (from Nylandia, Uusimaa) was the strongest, with relatively low gene flow, possibly due to geographical barriers in the Qinghai-Tibet plateau. Only 1 haplotype was identified across GLDR, GLMQ, and GLBM. High gene flow between distant locations indicates that human activities or wind dispersal may facilitate the dispersal of fruit flies and across different geographic. Geostatistical analysis suggested a recent population expansion of these 2 species in TRSR. Our findings provide technical references for identifying pests in the TRSR region and theoretical support for managing resistance, monitoring pest occurrences, analyzing environmental adaptability, and formulating biological control strategies for Tephritidae pests on Asteraceae plants.

Biogenic elements-informed assessment of the impact of human activities on river ecosystems.

River ecosystems, acting as pivotal conduits linking terrestrial, marine, and atmospheric realms, have faced significant disturbances due to human exploitation of their resources. Recent years have witnessed a heightened intensification of human activities, adversely affecting the equilibrium of water ecosystems. To systematically study the various factors that affect river ecosystems under human activities, we introduce a universally applicable approach that considers the diversity of watersheds, biogenic elements, and human activities. Using this method, this application uncovers the sensitive human activity types, biogenic factors, and species significantly influencing river biodiversity within the study area. Incorporating statistical modelling, sensitivity screening, and advanced correlation analyses within a random forest regression framework, Sensitive biogenic elements and biological types affected by human activities were identified in typical watersheds, and the stability of different aquatic ecosystems was evaluated. Suggestions for watershed management measures were proposed When human activities affect the degree of water resource development and utilization, the forms of sensitive biogenic elements include DIC and Tsi; When human activities affect the discharge of pollutants into rivers, the forms of sensitive biogenic elements include TP, PP, and DEP, and the ratio composition includes TC: TN, TC: TP, TP: TSi, and TN: TP, This study pioneers a novel method for assessing human impacts on river ecosystems and successfully applies this approach to inform management decisions for river segments and tributaries in the middle and upper reaches of the Yangtze River basin. thereby enhancing our understanding of the consequences of human-induced impacts on biodiversity.

Traditional Chinese medicine improved diabetic kidney disease through targeting gut microbiota.

CONTEXT: Diabetic kidney disease (DKD) affects nearly 40% of diabetic patients, often leading to end-stage renal disease that requires renal replacement therapies, such as dialysis and transplantation. The gut microbiota, an integral aspect of human evolution, plays a crucial role in this condition. Traditional Chinese medicine (TCM) has shown promising outcomes in ameliorating DKD by addressing the gut microbiota. OBJECTIVE: This review elucidates the modifications in gut microbiota observed in DKD and explores the impact of TCM interventions on correcting microbial dysregulation. METHODS: We searched relevant articles from databases including Web of Science, PubMed, ScienceDirect, Wiley, and Springer Nature. The following keywords were used: diabetic kidney disease, diabetic nephropathy, gut microbiota, natural product, TCM, Chinese herbal medicine, and Chinese medicinal herbs. Rigorous criteria were applied to identify high-quality studies on TCM interventions against DKD. RESULTS: Dysregulation of the gut microbiota, including Lactobacillus, Streptococcus, and Clostridium, has been observed in individuals with DKD. Key indicators of microbial dysregulation include increased uremic solutes and decreased short-chain fatty acids. Various TCM therapies, such as formulas, tablets, granules, capsules, and decoctions, exhibit unique advantages in regulating the disordered microbiota to treat DKD. CONCLUSION: This review highlights the importance of targeting the gut-kidney axis to regulate microbial disorders, their metabolites, and associated signaling pathways in DKD. The Qing-Re-Xiao-Zheng formula, the Shenyan Kangfu tablet, the Huangkui capsule, and the Bekhogainsam decoction are potential candidates to address the gut-kidney axis. TCM interventions offer a significant therapeutic approach by targeting microbial dysregulation in patients with DKD.

[Reflections on good manufacturing practice and quality control system of personalized traditional Chinese medicine preparations].

Personalized traditional Chinese medicine(TCM) preparations have entered a stage of rapid development. The key to the healthy development of this industry is to establish a sound manufacturing standard and quality control system. This paper analyzed the characteristics of personalized TCM preparations and drew reference from the quality management standards in the production of commissioned decoctions and oral pastes, on the basis of which the production quality management scheme and cautions for the safe production of personalized TCM preparations was put forward with consideration to various problems that may exist and occur in the production of such preparations. It provided references for formulating the production standards and quality management system of personalized TCM preparations. The production standards and quality control system should develop with the times. In the future, modern technologies such as big data and artificial intelligence should be employed to achieve the automated and intelligent production and establish a sound quality traceability system, online control strategy, and safety management mode of personalized TCM preparations, which will ensure the healthy development of this industry under requirement of good manufacturing practice(GMP).

[Application of microwave vacuum drying with process management in extract drying of personalized traditional Chinese medicine preparations].

Extracts are important intermediates in the production of traditional Chinese medicines preparations. The drying effect of extracts will directly affect the subsequent production process and the quality of the preparation. To meet the requirements of high drug loading, short time consumption, and simple production process of personalized traditional Chinese medicine preparations, this study explored the application of multi-program microwave vacuum drying process in the extract drying of personalized traditional Chinese medicine preparations. The influencing factors of microwave vacuum drying process were investigated for 5 excipients and 40 prescriptions. Taking the feasibility of drying, drying rate, drying time, and dried extract status as indicators, this study investigated the feeding requirements of microwave vacuum drying. With the dried extract status as the evaluation indicator, the three drying programs(A, B, and C) were compared to obtain the optimal drying condition. The experimental results showed that the optimal feeding conditions for microwave vacuum drying were material layer thickness of 2 cm and C program(a total of 7 drying processes), which solved the problem of easy scorching in microwave drying with process management. Furthermore, the preset moisture content of the dried extract in microwave drying should be 4%-5%, so that the dried extract of traditional Chinese medicine preparation had uniform quality, complete drying, and no scorching. This study lays a foundation for the application of microwave drying in the production of traditional Chinese medicine preparations, promoting the high-quality development of personalized traditional Chinese medicine preparations.

[Molding matrix formulation of hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine preparations].

This study aims to optimize the matrix formulation for the hot-melt pressure-sensitive adhesive plaster of personalized traditional Chinese medicine(TCM) preparations and verify the applicability of the formulation. The central composite design in JMP Pro 16.1.0 was employed to optimize the dosages of styrene-isoprene-styrene triblock copolymer(SIS), hydrogenated petroleum resin, and lightweight liquid paraffin, with the fine powder of Yipifang as the model drug(drug loading of 10%) and the sensory score and objective evaluation as the comprehensive evaluation indicators. The quality evaluation system of hot-melt pressure-sensitive adhesive plaster of personalized TCM preparations was established. The applicability of the optimized matrix formulation of hot-melt pressure-sensitive adhesive plaster was verified with 16 TCM preparations for external application. Furthermore, the applicability of the matrix formulation was investigated with different drug loadings. The general molding matrix formulation was SIS∶hydrogenated petroleum resin∶lightweight liquid paraffin 3∶3∶5. The optimized matrix formulation showed good molding properties and high quality scores for 16 TCM preparations and were suitable for the plastering of finely powdered decoction pieces with a loading capacity of 10% to 30%. The results suggest that the optimized matrix formulation has good applicability and is suitable for TCM preparations. The findings lay a foundation for the application and promotion of the hot-melt pressure-sensitive adhesive plasters of personalized TCM preparations.

[Optimization of prediction model for personalized water pills based on semantic analysis of traditional Chinese medicine materials].

This study aims to optimize the prediction model of personalized water pills that has been established by our research group. Dioscoreae Rhizoma, Leonuri Herba, Codonopsis Radix, Armeniacae Semen Amarum, and calcined Oyster were selected as model medicines of powdery, fibrous, sugary, oily, and brittle materials, respectively. The model prescriptions were obtained by uniform mixing design. With hydroxypropyl methylcellulose E5(HPMC-E5) aqueous solution as the adhesive, personalized water pills were prepared by extrusion and spheronizaition. The evaluation indexes in the pill preparation process and the multi-model statistical analysis were employed to optimize and evaluate the prediction model of personalized water pills. The prediction equation of the adhesive concentration was obtained as follows: Y_1=-4.172+3.63X_A+15.057X_B+1.838X_C-0.997X_D(adhesive concentration of 10% when Y_1<0, and 20% when Y_1>0). The overall accuracy of the prediction model for adhesive concentration was 96.0%. The prediction equation of adhesive dosage was Y_2=6.051+94.944X_A~(1.5)+161.977X_B+70.078X_C~2+12.016X_D~(0.3)+27.493X_E~(0.3)-2.168X_F~(-1)(R~2=0.954, P<0.001). Furthermore, the semantic prediction model for material classification of traditional Chinese medicines was used to classify the materials contained in the prescription, and thus the prediction model of personalized water pills was evaluated. The results showed that the prescriptions for model evaluation can be prepared with one-time molding, and the forming quality was better than that established by the research group earlier. This study has achieved the optimization of the prediction model of personalized water pills.