An immune cell atlas reveals the dynamics of human macrophage specification during prenatal development.

Macrophages are heterogeneous and play critical roles in development and disease, but their diversity, function, and specification remain inadequately understood during human development. We generated a single-cell RNA sequencing map of the dynamics of human macrophage specification from PCW 4-26 across 19 tissues. We identified a microglia-like population and a proangiogenic population in 15 macrophage subtypes. Microglia-like cells, molecularly and morphologically similar to microglia in the CNS, are present in the fetal epidermis, testicle, and heart. They are the major immune population in the early epidermis, exhibit a polarized distribution along the dorsal-lateral-ventral axis, and interact with neural crest cells, modulating their differentiation along the melanocyte lineage. Through spatial and differentiation trajectory analysis, we also showed that proangiogenic macrophages are perivascular across fetal organs and likely yolk-sac-derived as microglia. Our study provides a comprehensive map of the heterogeneity and developmental dynamics of human macrophages and unravels their diverse functions during development.

Zn-Leaching Induced Rapid Self-Reconstruction of NiFe-Layered Double Hydroxides for Boosted Oxygen Evolution Reaction.

Optimizing the active centers through reconstruction is recognized as the key to construct high-performance oxygen evolution reaction (OER) catalysts. Herein, a simple and rapid in situ leaching strategy to promote the self-reconstruction of NiFe-layered double hydroxides (LDHs) catalysts is reported. The trace Zn dopants are introduced in advance by a facile and one-step hydrothermal method, followed by leaching over the electrochemical activation process, which can remarkably reduce the formation potential of NiFeOOH active centers to enable the deeper self-reconstruction for the formation of abundant highly active centers. Moreover, the self-restructured NiFeOOH-VZn cannot only significantly lower the dehydrogenation energy barrier for the transformation from Ni(OH)2 to NiOOH, but also decrease the free energy barrier of rate determining step for the *OH converted to *O through a deprotonation process, thus significantly boosting the OER behaviors. As a proof of concept, the obtained NiFeOOH-VZn catalyst just requires a low overpotential of 240 mV at 10 mA cm-2, and delivers robust stability at 50 mA cm-2 over 120 h, which outperforms the benchmark of noble metal RuO2 and those of most non-noble metal catalysts ever reported.

Cerebellar transcranial magnetic stimulation for improving balance capacity and activity of daily living in stroke patients: a systematic review and meta-analysis.

BACKGROUND: The application of cerebellar transcranial magnetic stimulation (TMS) in stroke patients has received increasing attention due to its neuromodulation mechanisms. However, studies on the effect and safety of cerebellar TMS to improve balance capacity and activity of daily living (ADL) for stroke patients are limited. This systematic review and meta-analysis aimed to investigate the effect and safety of cerebellar TMS on balance capacity and ADL in stroke patients. METHOD: A systematic search of seven electronic databases (PubMed, Embase, Web of Science, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, Wanfang and Chinese Scientific Journal) were conducted from their inception to October 20, 2023. The randomized controlled trials (RCTs) of cerebellar TMS on balance capacity and/or ADL in stroke patients were enrolled. The quality of included studies were assessed by Physiotherapy Evidence Database (PEDro) scale. RESULTS: A total of 13 studies involving 542 participants were eligible. The pooled results from 8 studies with 357 participants showed that cerebellar TMS could significantly improve the post-intervention Berg balance scale (BBS) score (MD = 4.24, 95%CI = 2.19 to 6.29, P < 0.00001; heterogeneity, I2 = 74%, P = 0.0003). The pooled results from 4 studies with 173 participants showed that cerebellar TMS could significantly improve the post-intervention Time Up and Go (TUG) (MD=-1.51, 95%CI=-2.8 to -0.22, P = 0.02; heterogeneity, I2 = 0%, P = 0.41). The pooled results from 6 studies with 280 participants showed that cerebellar TMS could significantly improve the post-intervention ADL (MD = 7.75, 95%CI = 4.33 to 11.17, P < 0.00001; heterogeneity, I2 = 56%, P = 0.04). The subgroup analysis showed that cerebellar TMS could improve BBS post-intervention and ADL post-intervention for both subacute and chronic stage stroke patients. Cerebellar high frequency TMS could improve BBS post-intervention and ADL post-intervention. Cerebellar TMS could still improve BBS post-intervention and ADL post-intervention despite of different cerebellar TMS sessions (less and more than 10 TMS sessions), different total cerebellar TMS pulse per week (less and more than 4500 pulse/week), and different cerebellar TMS modes (repetitive TMS and Theta Burst Stimulation). None of the studies reported severe adverse events except mild side effects in three studies. CONCLUSIONS: Cerebellar TMS is an effective and safe technique for improving balance capacity and ADL in stroke patients. Further larger-sample, higher-quality, and longer follow-up RCTs are needed to explore the more reliable evidence of cerebellar TMS in the balance capacity and ADL, and clarify potential mechanisms.

CD6 and CCR7 as Genetic Biomarkers in Evaluating Intracranial Aneurysm Rupture Risk.

BACKGROUND: This study used bioinformatics combined with statistical methods to identify plasma biomarkers that can predict intracranial aneurysm (IA) rupture and provide a strong theoretical basis for the search for new IA rupture prevention methods. METHODS: We downloaded gene expression profiles in the GSE36791 and GSE122897 datasets from the Gene Expression Omnibus (GEO) database. Data were normalized using the "sva" R package and differentially expressed genes (DEGs) were identified using the "limma" R package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were used for DEG function analysis. Univariate logistic regression analysis, least absolute shrinkage and selection operator (LASSO) regression modeling, and the support vector machine recursive feature elimination (SVM-RFE) algorithm were used to identify key biomarker genes. Data from GSE122897 and GSE13353 were extracted to verify our findings. RESULTS: Eight co-DEG mRNAs were identified in the GSE36791 and GSE122897 datasets. Genes associated with inflammatory responses were clustered in the co-DEG mRNAs in IAs. CD6 and C-C chemokine receptor 7 (CCR7) were identified as key genes associated with IA. CD6 and CCR7 were upregulated in patients with IA and their expression levels were positively correlated. There were significant differences in the infiltration of immune cells between IAs and normal vascular wall tissues (p < 0.05). A predictive nomogram was designed using this two-gene signature. Binary transformation of CD6 and CCR7 was performed according to the cut-off value to construct the receiver-operating characteristic (ROC) curve and showed a strong predictive ability of the CD6-CCR7 gene signature (p < 0.01; area under the curve (AUC): 0.90; 95% confidence interval (CI): 0.88-0.92). Furthermore, validation of this two-gene signature using the GSE122897 and GSE13353 datasets proved it to be valuable for clinical application. CONCLUSIONS: The identified two-gene signature (CD6-CCR7) for evaluating the risk of IA rupture demonstrated good clinical application value.

Comprehensive analysis of cuproptosis genes and cuproptosis-related genes as prognosis factors in esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a common invasive and pernicious cancer with a low five-year survival rate. To identify potential therapeutic targets, we first investigated the characteristics of cuproptosis genes (CUGs) in ESCC. The expression patterns of 10 CUGs (FDX1, LIPT1, LIAS, DLAT, DLD, PDHA1, PDHB, GLS, MTF1, and CDKN2A) were analyzed to identify ESCC-relevant targets. Weighted correlation network analysis (WGCNA) was performed to obtain CUG-related genes (CRGs). A total of seven differentially expressed genes were identified (FDX1, DLAT, LIAS, PDHB, MTF1, GLS, and CDKN2A). DLAT was upregulated in stage III, and LIPT1 was upregulated in N0 + N1 cancers. The high expression of CDKN2A, and PDHA1, was related to better overall survival, whereas the low expression of LIAS was related to better clinical outcomes. WGCNA was performed to get CUG-related genes (CRGs) and showed three key modules that related to FDX1, DLAT, and LIPT1. Moreover, CRGs (BTLA, CT47A1, and PRRX1) were selected to construct a risk score model in order to predict the survival and prognosis of patients with ESCC. Additionally, the cuproptosis score based on CUGs and a nomogram constructed based on it helped accurately predict the prognosis of patients with ESCC; thus, maybe it can be used for the clinical diagnosis of ESCC. The results also showed that milciclib might inhibit the proliferation and migration of KYSE150 and KYSE510 cells by targeting CDKN2A. In conclusion, the abovementioned CUGs and CRGs play a crucial role in tumorigenesis and cancer progression in ESCC, indicating their potential as therapeutic targets.

[Consistency evaluation of multidimensional quality attributes of Atractylodis Macrocephalae Rhizoma by fusion of multi-source information].

The quality control of Chinese medicinal decoction pieces is one of the key tasks in the traditional Chinese medicine industry. In this study, multi-source information fusion was employed to fuse the data from near-infrared spectroscopy, electronic tongues, and other tests and establish an overall quality consistency evaluation method for Atractylodis Macrocephalae Rhizoma, which provided methodological support for the overall quality evaluation of Atractylodis Macrocephalae Rhizoma. The near-infrared spectroscopy information was measured in both static and dynamic states for 23 batches of Atractylodis Macrocephalae Rhizoma samples from different sources, and the electronic tongue sensory information, moisture content, and leachate content were measured. The overall quality of Atractylodis Macrocephalae Rhizoma was evaluated by multi-source information fusion. The results showed that the near-infrared spectroscopy information of 16122103, 801000509, 801000352, 701003656, HX21L01, and 160956 was different from that of other batches of Atractylodis Macrocephalae Rhizoma powder in the static state, and 701003298, 16122103, 701003656, 701003107, 801000229, and 18090404 were the different batches in the dynamic state. The moisture content showed no significant difference between batches. The leachate content in the batch 801000509 was different from that in other batches. The electronic tongue sensory information of 150721004, 151237, 160703004, HX21M01, HX21K04, HX21K01, and 601003516 was different from that of other batches. Furthermore, data layer fusion was employed to analyze the overall quality of Atractylodis Macrocephalae Rhizoma. Four batches, 150721004, HX21M01, HX21K04, and HX21K01, showed the parameters exceeding the 95% control limits and differed from the other samples in terms of the overall quality. This study integrated the information of moisture, near-infrared spectroscopy, and other sources to evaluate the quality consistency among 23 batches of Atractylodis Macrocephalae Rhizoma samples, which provides a reference for the quality consistency evaluation of Chinese medicinal decoction pieces.

Focused ultrasound-mediated blood-brain barrier opening combined with magnetic targeting cytomembrane based biomimetic microbubbles for glioblastoma therapy.

Glioblastoma is the most common type of brain tumor. Due to the presence of the blood-brain barrier, the effects of chemotherapy have been unsatisfactory. The combination of focused ultrasound and microbubbles to reversibly open the blood-brain barrier is now considered a key factor in improving treatment outcomes of glioblastoma. In this study, we developed bionic drug delivery microbubbles, which in combination with focused ultrasound had an obvious inhibitory effect on glioblastoma. We extracted the brain microvascular cell membranes, combined them with lipid components, and loaded them with superparamagnetic iron oxide and doxorubicin to prepare biomimetic drug delivery microbubbles (FeDOX@cellMBs). We demonstrated that FeDOX@cellMBs retained the intrinsic properties of loading, such as magnetic properties and drug toxicity, both in vitro and in vivo. FeDOX@cellMBs exhibited good tumor targeting and uptake under the combined action of magnetic and focused ultrasound. Importantly, the FeDOX@cellMBs demonstrated excellent internal stability and effectively inhibited tumor growth in orthotopic glioblastoma mice. Finally, organ H&E staining confirmed that FeDOX@cellMBs were safe for use. In conclusion, FeDOX@cellMBs successfully penetrated the blood-brain barrier and effectively inhibited glioblastoma growth under the combined effects of focused ultrasound and magnetic stimulation. These results provide a new approach for the treatment of glioblastoma, with implications for future clinical translation.

[Four critical engineering and technical problems in manufacturing measurement of traditional Chinese medicine].

Focusing on the development and quality improvement strategy of the traditional Chinese medicine(TCM) industry, the scientific and technological innovation of the new engineering of TCM should be paid attention to solve the "stuck neck" dilemma. Under the background of the ecological and industrial revolution of the scientific and technological innovation system, the super-scale information interaction and multi-dimensional integration will inevitably lead to profound changes in the manufacturing mode of TCM. Manufacturing measurement of TCM is formed on the basis of the reliability engineering theory of process control of TCM production. It is the development extension of system theory and system science ideas and a cross-fertilization discipline that combines theory with practice and adheres to the "four-oriented" re-epistemology improvement of the TCM discipline. In response to the problems of complex raw material sources, coarse process technology, unclear material basis, and poor applicability of equipment and technology in the manufacture of TCM, the transformation research mode of "aiming at the integration of pharmaceutical industry-developing intelligent production line-enabling industrial transformation" has been developed. This paper proposed the four key engineering technical problems, i.e., the identification of critical quality attributes(CQA) in the manufacture of TCM, the quality by design(QbD) and product development of the manufacturing process of TCM, the quality transfer principle and multivariate process capability index of TCM manufacturing, and the development of measurement technology and equipment of the manufacturing measurement of TCM, to achieve the systematization of quality control indicators, real-time process control, digitalization of manufacturing process, transparency of quality transfer, and intelligent whole-process control. In this paper, the new concepts, new theories, and new technologies provide a reference for the industrialization of TCM.

Human herpesvirus 6A promotes glycolysis in infected T cells by activation of mTOR signaling.

Human herpesvirus 6 (HHV-6) is an important immunosuppressive and immunomodulatory virus worldwide. However, whether and how HHV-6 infection influences the metabolic machinery of the host cell to provide the energy and biosynthetic resources for virus propagation remains unknown. In this study, we identified that HHV-6A infection promotes glucose metabolism in infected T cells, resulting in elevated glycolytic activity with an increase of glucose uptake, glucose consumption and lactate secretion. Furthermore, we explored the mechanisms involved in HHV-6A-mediated glycolytic activation in the infected T cells. We found increased expressions of the key glucose transporters and glycolytic enzymes in HHV-6A-infected T cells. In addition, HHV-6A infection dramatically activated AKT-mTORC1 signaling in the infected T cells and pharmacological inhibition of mTORC1 blocked HHV-6A-mediated glycolytic activation. We also found that direct inhibition of glycolysis by 2-Deoxy-D-glucose (2-DG) or inhibition of mTORC1 activity in HHV-6A-infected T cells effectively reduced HHV-6 DNA replication, protein synthesis and virion production. These results not only reveal the mechanism of how HHV-6 infection affects host cell metabolism, but also suggest that targeting the metabolic pathway could be a new avenue for HHV-6 therapy.

[Critical quality attribute characterization of big brand TCM: taste formulation optimization strategy and application of Xiaoer Ganmao Oral Liquid based on taste quality attribute].

The taste is the quality attribute for the development and production of traditional Chinese medicine(TCM). To improve the medication compliance of the big brand TCM, Xiaoer Ganmao Oral Liquid, a correlation model between the electronic tongue sensor signal value and human sensory evaluation score was established, and an optimization strategy of taste improvement for Xiaoer Ganmao Oral Liquid was developed with the key techniques of statistical experimental design. Based on the above model, the optimal formulation was determined as follows: aspartame content of 1-2 mg·mL~(-1), acesulfame-K content of 1.5-3 mg·mL~(-1), and steviol glycoside content of 1-2 mg·mL~(-1). Furthermore, the optimal formulation was verified by human sensory evaluation. Therefore, the taste of Xiaoer Ganmao Oral Liquid was improved. Taking Xiaoer Ganmao Oral Liquid as an example, the present study developed the taste formulation optimization method based on the correlation between the electronic tongue and human sensory evaluation, which is expected to provide an important reference to improve the taste of oral liquid of TCM.

gp96 Is Critical for both Human Herpesvirus 6A (HHV-6A) and HHV-6B Infections.

Human herpesviruses 6A and 6B (HHV-6A and HHV-6B, respectively) are two virus species in the betaherpesvirus subfamily that exhibit T cell tropism. CD46 and CD134 are the cellular receptors for HHV-6A and HHV-6B, respectively. Interestingly, the efficiency of HHV-6A/6B entry is different among different types of target cells despite similar receptor expression levels on these cells. Here, we found that the cellular factor gp96 (also known as glucose-regulated protein 94 [GRP94]) is expressed on the cell surface and interacts with viral glycoprotein Q1 (gQ1) during virus entry. gp96 cell surface expression levels are associated with the efficiency of HHV-6A and HHV-6B entry into target cells. Both loss-of-function and gain-of-function experiments indicated that gp96 plays an important role in HHV-6 infection. Our findings provide new insight into the HHV-6 entry process and might suggest novel therapeutic targets for HHV-6 infection.IMPORTANCE Although new clinical importance has been revealed for human herpesviruses 6A (HHV-6A) and 6B, much is still unknown about the life cycles of these viruses in target cells. We identified a novel cellular factor, gp96, that is critical for both HHV-6A and -6B entry into host cells. As gp96 can function as an adjuvant in vaccine development for both infectious agents and cancers, it can be a potential therapeutic target for infection by these two viruses.

System optimisation quantitative model of on-line NIR: a case of Glycyrrhiza uralensis Fisch extraction process.

INTRODUCTION: The on-line analysis of active pharmaceutical ingredients (APIs) during the extraction process in herbal medicine is a challenge. Establishing a reliable and robust model is a critical procedure for the industrial application of on-line near-infrared (NIR) technology. OBJECTIVE: To evaluate the advantages of on-line NIR model development using system optimisation strategy, Glycyrrhiza uralensis Fisch was used as a case. The content of liquiritin and glycyrrhizic acid was monitored during pilot scale extraction process of Glycyrrhiza uralensis Fisch in three batches. METHODS: High-performance liquid chromatography (HPLC) was used as reference method for content determination of liquiritin and glycyrrhizic acid. The quantitative models of on-line NIR were developed by system optimisation of processing trajectory. For comparison, the models were simultaneously developed by stepwise optimisation. Moreover, the modelling parameters obtained through system optimisation and stepwise optimisation were reused in three batches. Root mean square error of prediction (RMSEP) and residual predictive deviation (RPD) were used to assess the model quality. RESULTS: The average values of RMSEP and RPD of systematic model for liquiritin in three batches were 0.0361, 4.1525 (first batch), 0.0348, 4.7286 (second batch) and 0.0311, 4.9686 (third batch), respectively. In addition, the modelling parameters of systematic model for glycyrrhizic acid in three batches were same, and the average values of RMSEP and RPD were 0.0665 and 5.2751, respectively. The predictive performance and robustness of systematic models for the three batches were better than the comparison models. CONCLUSION: The work demonstrated that system optimisation quantitative model of on-line NIR could be used to determine the contents of liquiritin and glycyrrhizic acid during Glycyrrhiza uralensis Fisch extraction process.

Protective effects of Re-yan-ning mixture on Streptococcus pneumonia in rats based on network pharmacology.

CONTEXT: Re-yan-ning mixture (RYNM) is a new national drug approved by China's State Food and Drug Administration for the treatment of colds, simple pneumonia and acute bronchitis. OBJECTIVE: To determine the mechanism of action of RYNM in the treatment of bacterial pneumonia. MATERIALS AND METHODS: Using the network pharmacology approach, the multiple components, component candidate targets and multiple therapeutic targets of RYNM were screened and functionally enriched. Also, we established a rat Streptococcus pneumonia model to verify the results of network pharmacology enrichment analysis. Forty male SPF Sprague Dawley rats were divided into four groups of 10 rats: control (normal saline), model (normal saline), levofloxacin-intervened and RYNM-intervened groups. IL-10, NOS2, COX-1, IL-6, TNF-α and NF-κB in serum and BALF were detected by ELISA. Western blot detected IL-17, IL-6, TNF-α, COX-2 and Bcl-2. RESULTS: The network pharmacology approach successfully identified 48 bioactive components in RYNM, and 65 potential targets and 138 signal pathways involved in the treatment of Streptococcus pneumonia with RYNM. The in vivo experiments indicated that model group has visible inflammation and lesions while RYNM and levofloxacin groups have not. The RYNM exhibited its therapeutic effects on Streptococcus pneumonia mainly via the regulation of cell proliferation and survival through the IL-6/IL-10/IL-17, Bax/Bcl-2, COX-1/COX-2, NF-κB and TNF-α signalling pathways. DISCUSSION AND CONCLUSIONS: The present study demonstrated the protective effects of RYNM on Streptococcus pneumonia, providing a potential mechanism for the treatment of bacterial pneumonia with RYNM.

[Critical quality attribute assessment of big brand traditional Chinese medicine: online NIR quality control research on boiling time during extraction process].

Assessment of the status property(boiling time) is a challenge for the quality control of extraction process in pharmaceutical enterprises. In this study, the pilot extraction process of Phellodendron chinense was used as the research carrier to develop an online near-infrared(NIR) quality control method based on the status property(boiling time). First, the NIR spectra of P. chinense were collected during the two pilot-scale extraction processes, and the status property(boiling time) was assessed by observing the state of bubbles in the extraction tank using a transparent window during the extraction process, which was then used as a reference standard. Based on the moving block standard deviation(MBSD) algorithm, the assessment model using online NIR spectra for boiling time during extraction process was established. In addition, the model was optimized as follows: standard normal variable(SNV) for spectral pretreatment, modeling band of 800-2 200 nm, and window size of 4. The results showed that, with 0.002 0 as the MBSD model threshold, the boiling time can be accurately assessed using online NIR spectra during extraction process. Furthermore, the principal component analysis-moving block standard deviation(PCA-MBSD) model was developed by our group to reduce the influence of online NIR spectral noise and background signal on the model, and the number of principal components was optimized into 2 in the PCA-MBSD model. The results showed that, with 0.000 075 as the PCA-MBSD model threshold, the boiling time can be accurately assessed using online NIR spectra during extraction process, with improved reliability. This study can provide a assessment method for boiling time during extraction process using online NIR spectra, which can replace the empirical judgment in manual observation, and realize the digitalization of the extraction process for big brand traditional Chinese medicine.

[Critical quality attribute assessment of big brand traditional Chinese medicine: visualization of blending process for rare medicines in Tongren Niuhuang Qingxin Pills based on spatial distribution uniformity].

The spatial distribution uniformity of valuable medicines is the critical quality attribute in the process control of Tongren Niuhuang Qingxin Pills. With the real world sample of the mixed end-point powder of Tongren Niuhuang Qingxin Pills as the research object, hyperspectral imaging technology was used to collect a total of 32 400 data points with a size of 180 pix×180 pix. Spectral angle matching(SAM), classical least squares and mixed tuned matched filtering(MTMF) were used to identify the spatial distribution of rare medicines. MTMF model showed higher identification accuracy, therefore the spatial distribution of the blended intermediates was identified based on the MTMF model. The histogram method was also used to evaluate the spatial distribution uniformity of rare medicines. The results showed that the standard deviation was 4.78, 6.5, 3.48, 1.96, and 3.00 respectively for artificial bezoar, artificial musk, Borneol, Antelope horn and Buffalo horn; the variance was 22.8, 42.3, 12.1, 3.82, and 9.00, and the skewness was 1.26, 1.71, 0.06,-0.86, and 1.04, respectively. The final results showed that the most even blending was achieved in concentrated powder of Borneol, Antelope horn and Buffalo horn, followed by artificial bezoar, and last artificial musk. A visualization method was established for quality attributes of distribution uniformity in blending process of Tongren Niuhuang Qingxin Pills. It could provide evidences of quality control methods in the mixing process of big brand traditional Chinese medicine.

[Critical quality attribute assessment of big brand traditional Chinese medicine: study on NIR field detection method of chemical properties of moisture in Tongren Niuhuang Qingxin Pills].

For the field detection problems of critical quality attribute(CQA) of moisture content in traditional Chinese medicine(TCM) manufacturing process, big brand TCM Tongren Niuhuang Qingxin Pills were used as the carrier, to establish a moisture content NIR field detection model with or without cellophane in real world production with use of near infrared(NIR) spectroscopy combined with stoichiometry. With the moisture content determined by drying method as reference value, the partial least square method(PLS) was used to analyze the correlation between the spectrum and the moisture reference value. Then the spectral pretreatment methods were screened and optimized to further improve the accuracy and stability of the model. The results showed that the best quantitative model was developed by the spectral data pretreatment of standard normal variate(SNV) with the latent variable factor number of 2 and 7 of Tongren Niuhuang Qingxin Pills with or without cellophane samples. The prediction coefficient of determination(R_(pre)~2) and standard deviation of prediction(RMSEP) of the model with cellophane samples were 0.765 7 and 0.157 2%; R_(pre)~2 and RMSEP of the model without cellophane samples were 0.772 2 and 0.207 8%. The NIR quantitative models of moisture content of Tongren Niuhuang Qingxin Pills with and without cellophane both showed good predictive performance to realize the rapid, accurate and non-destructive quantitative analysis of moisture content in such pills, and provide a method for the field quality control of the critical chemical attributes of moisture in the manufacturing of big brand TCM.

[Critical quality attribute assessment of big brand traditional Chinese medicine: quality control of Tongren Niuhuang Qingxin Pills in texture and sensory attributes].

Texture sensory attributes are the key items in quality control of Chinese medicinal honeyed pills. The purpose of this study is to develop a quality control method for assessing the texture sensory attributes of Chinese medicinal honeyed pills based on real-world Tongren Niuhuang Qingxin pilular masses and finished products. First, parameters of texture profile analysis(TPA) were optimized through single factor and central composite design(CCD) experiments to establish a detection method for texture sensory attri-butes of Tongren Niuhuang Qingxin Pills. The results showed that the established detection method was stable and reliable, with the optimal parameters set up as follows: deformation percentage of 70%, detection speed at 30 mm·min~(-1), and interval time of 15 s. Furthermore, 540 data points yielded form six texture sensory attributes of pills from 30 batches were subjected to multivariate statistical process control(MSPC) with Hotelling T~2 and squared prediction error(SPE) control charts to establish the quality control method of Tongren Niuhuang Qingxin Pills. This study is expected to provide a reference for improving the quality control system of Chinese medicinal honeyed pills.

[Critical quality attribute assessment of big brand traditional Chinese medicine: modular identification of Tongren Niuhuang Qingxin Pills based on efficacy with chemical properties].

Identification of critical quality attribute(CQA) is crucial in quality control of Tongren Niuhuang Qingxin Pills(TRNHQXP). In this study, 661 active components in TRNHQXP were selected by liquid chromatography-mass spectrometry(LC-MS) and network pharmacology based on reported data and TCMSP, BATMAN-TCM, and TCMID databases, as well as mass spectrometry data, and 1 413 targets of the active components were obtained through SwissTargetPrediction. The 152 potential targets obtained from the intersection of predicted targets with 456 stroke targets underwent functional enrichment analysis by Metascape. The 27 Chinese medicinals in TRNHQXP were divided into four sets according to efficacies. Thirty-seven key targets in the blood-activating and stasis-resolving set and 41 in the tonifying set were screened out. On the basis of these potential key targets, 137 potential key CQA of TRNHQXP for stroke were reversely predicted. This study revealed the possible mechanism of TRNHQXP in treating stroke and established a modular identification method for the potential CQA of big brand traditional Chinese medicine(TCM) based on efficacies and chemical properties. Consequently, the CQA of TRNHQXP were identified by this method, which has provided a reference for the following experimental studies of CQA.

[Criticalquality attribute assessment of big brand traditional Chinese medicine: visualization method for quality control of Ginkgo Leaves Tablets based on spatial distribution uniformity].

Spatial distribution uniformity is the critical quality attribute(CQA) of Ginkgo Leaves Tablets, a variety of big brand traditional Chinese medicine. The evaluation of the spatial distribution uniformity of active pharmaceutical ingredients(APIs) in Ginkgo Leaves Tablets is important in ensuring their stable and controllable quality. In this study, hyperspectral imaging technology was used to construct the spatial distribution map of API concentration based on three prediction models, further to realize the visualization research on the spatial distribution uniformity of Ginkgo Leaves Tablets. The region of interest(ROI) was selected from each Ginkgo Leaves Tablet, with length and width of 50 pixels, and a total of 2 500 pixels. Each pixel had 288 spectral channels, and the number of content prediction data could reach 1×10~5 for a single sample. The results of the three models showed that the Partial Least Squares(PLS) model had the highest prediction accuracy, with calibration set determination coefficient R_(pre)~2 of 0.987, prediction set determination coefficient R_(pre)~2 of 0.942, root mean square error of calibration(RMSEC) of 0.160%, and root mean square error of prediction(RMSEP) of 0.588%. The classical least-squares(CLS) model had a greater prediction error, with the RMSEP of 0.867%. Multivariate Curve Resolution-Alternating Least Square(MCR-ALS) model showed the worst predictive ability among the three models, and it couldn't realize content prediction. Based on the prediction results of PLS and CLS models, the spatial distribution map of APIs concentration was obtained through three-dimensional data reconstruction. Furthermore, histogram method was used to evaluate the spatial distribution uniformity of API. The data showed that the spatial distribution of APIs in Ginkgo Leaves Tablets was relatively uniform. The study explored the feasibility of visualization of spatial distribution of Ginkgo Leaves Tablets based on three models. The results showed that PLS model had the highest prediction accuracy, and MCR-ALS model had the lowest prediction accuracy. The research results could provide a new strategy for the visualization method of quality control of Ginkgo Leaves Tablets.

[Critical quality attribute assessment of big brand traditional Chinese medicine: quality control method of ginkgo leaves extract material based on powder physical properties].

The physical properties of ginkgo leaves extract(GLE) are the critical quality attributes for the control of the manufacturing process of ginkgo leaves preparations. In this study, 53 batches of GLE with different sources from the real world were used as the objects to carry out the research from 3 levels. First, based on micromeritics evaluation method, a total of 29 physical attribute quality parameters in five dimensions were comprehensively characterized, with a total of 1 537 data points. Further, with use of physical fingerprinting technology combined with similarity evaluation, the powder physical properties of 53 batches of GLE showed obvious differences from an overall perspective, and the similarity of the physical fingerprints was 0.876 to 1.000. Secondly, hierarchical clustering analysis(HCA) and principal component analysis(PCA) models were constructed to realize the reliable identification and differentiation of real-world materials produced by GLE from different sources. Multivariate statistical process control(MSPC) model was used to create GLE material Hotelling T~2 and squared prediction error(SPE) control charts. It was found that the SPE score of B_(21) powder exceeded the 99% confidence control limit by 22.495 9, and the SPE scores of A_1 and C_(10) powder exceeded the 95% confidence control limit by 16.099 2, realizing the determination of abnormal samples in the materials of GLE from the production in real world. Finally, the physical quality control method of GLE in the production process of ginkgo leaves preparations was established in this study, providing a reference for the quality control methods of ginkgo leaves preparations in their manufacturing process.