ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveTo evaluate the effects of Tongnaoyin on the blood-brain barrier status and neurological impairment in acute ischemic stroke （AIS） patients with the syndrome of phlegm-stasis blocking collaterals by dynamic contrast-enhanced magnetic resonance imaging （DCE-MRI）. MethodsA total of 63 patients diagnosed with AIS in the Jiangsu Province Hospital of Chinese Medicine from October 2022 to December 2023 were enrolled in this study. According to random number table method，the patients were assigned into a control group （32 cases） and an observation group （31 cases）. The control group received conventional Western medical treatment，and the observation group took 200 mL Tongnaoyin after meals，twice a day from day 2 of admission on the basis of the treatment in the control group. After 7 days of treatment，the patients were examined by DCE-MRI. The baseline data for two groups of patients before treatment were compared. The National Institute of Health Stroke Scale （NIHSS） score and modified Rankin Scale （mRS） score were recorded before treatment and after 90 days of treatment for both groups. The rKtrans，rKep，and rVe values were obtained from the region of interest （ROI） of the infarct zone/mirror area and compared between the two groups. ResultsThere was no significant difference in the NIHSS or mRS score between the two groups before treatment. After 90 days of treatment，the NIHSS and mRS scores declined in both groups，and the observation group had lower scores than the control group （P<0.05）. After treatment，the rKtrans and rVe in the observation group were lower than those in the control group （P<0.01）. ConclusionCompared with conventional Western medical treatment alone，conventional Western medical treatment combined with Tongnaoyin accelerates the repair of the blood-brain barrier in AIS patients，thereby ameliorating neurological impairment after AIS to improve the prognosis.

Medicinal plants， with diverse species， high heterozygosity， and special breeding objectives， can be hardly bred with conventional hybridization techniques. Plant genetic transformation is highly selective and can specifically change the traits of plants， serving as an important technical means for the breeding of medicinal plants. The commonly used plant genetic transformation technologies include Agrobacterium-mediated transformation and particle bombardment. Agrobacterium-mediated transformation is the most widely used method， while it is not applicable to all medicinal plants due to the high specificity. Although not specific， particle bombardment is limited in application due to the low conversion efficiency and external force damage to cells and tissue. With the rise and development of nanotechnology， the emerging nanomaterial-mediated transformation has solved the problems of the above two technologies. However， limited by its late development， the mechanism of nanomaterial-mediated introduction of genetic materials into plant cells remains unclear， and thus this technology is rarely used in medicinal plants. This article summarizes the development status of several commonly used or emerging plant genetic transformation technologies such as Agrobacterium-mediated transformation， particle bombardment， and nanomaterial-mediated transformation， as well as their application in different medicinal plants. Furthermore， this article looks forward to the development trend of genetic transformation technologies for plants and their application prospects in medicinal plants and Chinese materia medica resources， aiming to provide new technical ideas for the genetic improvement and germplasm innovation of medicinal plants and inject new impetus into the sustainable development of Chinese materia medica resources.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Exercise-induced metabolic remodeling is a fundamental adaptive process whereby the body reorganizes systemic and cellular metabolism to meet the dynamic energy demands posed by physical activity. Emerging evidence reveals that such remodeling not only enhances energy homeostasis but also profoundly influences immune function through complex molecular interactions involving glucose, lipid, and protein metabolism. This review presents an in-depth synthesis of recent advances, elucidating how exercise modulates immune regulation via metabolic reprogramming, highlighting key molecular mechanisms, immune-metabolic signaling axes, and the authors’ academic perspective on the integrated “exercise-metabolism-immunity” network. In the domain of glucose metabolism, regular exercise improves insulin sensitivity and reduces hyperglycemia, thereby attenuating glucose toxicity-induced immune dysfunction. It suppresses the formation of advanced glycation end-products (AGEs) and interrupts the AGEs-RAGE-inflammation positive feedback loop in innate and adaptive immune cells. Importantly, exercise-induced lactate, traditionally viewed as a metabolic byproduct, is now recognized as an active immunomodulatory molecule. At high concentrations, lactate can suppress immune function through pH-mediated effects and GPR81 receptor activation. At physiological levels, it supports regulatory T cell survival, promotes macrophage M2 polarization, and modulates gene expression via histone lactylation. Additionally, key metabolic regulators such as AMPK and mTOR coordinate immune cell energy balance and phenotype; exercise activates the AMPK-mTOR axis to favor anti-inflammatory immune cell profiles. Simultaneously, hypoxia-inducible factor-1α (HIF-1α) is transiently activated during exercise, driving glycolytic reprogramming in T cells and macrophages, and shaping the immune landscape. In lipid metabolism, exercise alleviates adipose tissue inflammation by reducing fat mass and reshaping the immune microenvironment. It promotes the polarization of adipose tissue macrophages from a pro-inflammatory M1 phenotype to an anti-inflammatory M2 phenotype. Moreover, exercise alters the secretion profile of adipokines—raising adiponectin levels while reducing leptin and resistin—thereby influencing systemic immune balance. At the circulatory level, exercise improves lipid profiles by lowering pro-inflammatory free fatty acids (particularly saturated fatty acids) and triglycerides, while enhancing high-density lipoprotein (HDL) function, which has immunoregulatory properties such as endotoxin neutralization and macrophage cholesterol efflux. Regarding protein metabolism, exercise triggers the expression of heat shock proteins (HSPs) that act as intracellular chaperones and extracellular immune signals. Exercise also promotes the secretion of myokines (e.g., IL-6, IL-15, irisin, FGF21) from skeletal muscle, which modulate immune responses, facilitate T cell and macrophage function, and support immunological memory. Furthermore, exercise reshapes amino acid metabolism, particularly of glutamine, arginine, and branched-chain amino acids (BCAAs), thereby influencing immune cell proliferation, biosynthesis, and signaling. Leucine-mTORC1 signaling plays a key role in T cell fate, while arginine metabolism governs macrophage polarization and T cell activation. In summary, this review underscores the complex, bidirectional relationship between exercise and immune function, orchestrated through metabolic remodeling. Future research should focus on causative links among specific metabolites, signaling pathways, and immune phenotypes, as well as explore the epigenetic consequences of exercise-induced metabolic shifts. This integrated perspective advances understanding of exercise as a non-pharmacological intervention for immune regulation and offers theoretical foundations for individualized exercise prescriptions in health and disease contexts.

ObjectiveTo study the regulatory effect of the partial sequence within the 3’ untranslated region （3’UTR） of slit guidance ligand 1 （Slit1） （Slit1-3’UTR） on the fibrotic phenotypes of cardiac fibroblasts （CFs） and its potential mechanism. MethodsThe adenovirus vector was used to overexpress the 1526nt sequence of Slit1-3’UTR in ICR neonatal mouse CFs （mCFs）. The expression of fibrosis-related genes in mCFs， such as collagen type 1 alpha1（COL1A1）， collagen type 3 alpha3 （COL3A1） and alpha smooth muscle actin （α-SMA） were detected by Western blot assay. The effect of Slit1-3’UTR 1526nt on the proliferation and migration of mCFs was assessed by EdU staining and Trans-well assays. Angiotensin Ⅱ （Ang Ⅱ） was used to treat mCFs， and the impact of Slit1-3’UTR 1526nt on the fibrotic phenotypes of Ang Ⅱ-induced mCFs was evaluated. After overexpression of Slit1-3’UTR 1526nt， miR-34a-5p mimic was transfected into mCFs， followed by actinomycin D treatment to detect the mRNA stability of Slit1-3’UTR 1526nt， and the levels of miR-34a-5p and its target gene SIRT1（si-SIRT1） in mCFs were determined. The effects of miR-34a-5p and small interfering RNA targeting SIRT1 on the Slit1-3’UTR 1526nt-mediated regulation of fibrotic phenotypes were also determined. ResultsAdenovirus-mediated overexpression of Slit 1-3’UTR 1526nt was achieved in mCFs. Overexpression of Slit 1-3’UTR 1526nt markedly inhibited the expression of the fibrosis-related genes， proliferation and migration of mCFs and fibrotic phenotypes of Ang Ⅱ. The results of actinomycin D assay showed that miR-34a-5p inhibited the stability of Slit1-3’UTR 1526nt in mCFs， while the level of miR-34a-5p was reduced in mCFs with overexpression of Slit1-3’UTR 1526nt. Transfection of miR-34a-5p promoted the fibrotic phenotypes， and reversed the inhibitory effect of Slit1-3’UTR 1526nt on the fibrotic phenotypes of mCFs. Overexpression of Slit1-3’UTR 1526nt significantly increased the level of miR-34a-5p target gene SIRT1 in mCFs. Transfection of miR-34a-5p and si-SIRT1 consistently reversed the inhibitory effects of Slit1-3’UTR 1526nt on the fibrotic phenotypes of mCFs. ConclusionSlit1-3’UTR1526nt inhibits the fibrotic phenotypes of mCFs by binding to miR-34a-5p and increasing the expression of its target gene of SIRT1.

Objective To clone and express the heat shock cognate protein 20 (SjHsc20) of Schistosoma japonicum, and to preliminarily investigate its biological characteristics. Methods The target fragment of the SjHsc20 gene was amplified using PCR assay and cloned into the pET-28a(+) expression plasmid to generate the recombinant expression vector pET-28a(+)-SjH-sc20, which was then transformed into Escherichia coli BL21 (DE3) competent cells. The recombinant SjHsc20 (rSjHsc20) protein was induced with isopropyl β-D-thiogalactopyranoside (IPTG) and purified, and the expression of the rSjHsc20 protein was checked with sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The immunogenicity of the rSjHsc20 protein was detected using Western blotting, and the transcriptional levels of SjHsc20 were quantified in S. japonicum worms at different developmental stages and in male and female adult worms using real-time quantitative PCR (RT-qPCR) assay. Thirty female BALB/c mice at ages 6 to 8 weeks were divided into three groups, including the rSjHsc20 immunization group, the PBS control group, and the ISA 206 adjuvant group, of 10 mice in each group. Mice in the rSjHsc20 immunization group were subcutaneously immunized with 20 μg rSjHsc20 on days 1, 15 and 31, and animals in the PBS control group were subcutaneously injected with the same volume of PBS on days 1, 15 and 31, while mice in the ISA 206 adjuvant group were subcutaneously immunized with the same volume of ISA 206 adjuvant on days 1, 15 and 31, respectively. All mice in each group were infected with (40 ± 2) S. japonicum cercariae via the abdomen 14 day following the last immunization. Levels of serum specific IgG and its subtypes IgG1 and IgG2 antibodies against rSjHsc20, and the serum titers of anti-rSjHsc20 antibody were detected in mice using indirect enzyme-linked immunosorbent assay (ELISA). All mice were sacrifice 42 days post-infection, and S. japonicum worms were collected from the hepatic portal vein and counted. The eggs per gram (EPG), worm burden reductions and egg burden reductions were estimated to evaluate the protective efficacy of the rSjHsc20 protein. Results The SjHsc20 gene had an open reading frame (ORF) with 756 bp in length and encoded 252 amino acids, and the rSjHsc20 protein had a relative molecular mass of approximately 29 kDa. The rSjHsc20 protein was recognized by the serum of mice infected with S. japonicum and the serum of mice immunized with the rSjHsc20 protein, indicating that rSjHsc20 had a good immunogenicity. There was a significant difference in the transcriptional levels of the SjHsc20 gene among the 7-day (1.001 4 ± 0.065 7), 12-day (2.268 3 ± 0.129 2), 21-day (1.378 5 ± 0.160 4), 28-day (1.196 4 ± 0.244 0), 35-day (1.646 3 ± 0.226 1), 42-day worms of S. japonicum (1.758 0 ± 0.611 1) (F = 38.45, P < 0.000 1), and the transcriptional level of the SjHsc20 gene was higher in the 12-day worms than in worms at other developmental stages (all P values < 0.000 1). The serum levels of anti-rSjHsc20 IgG antibody were 0.106 6 ± 0.010 7, 0.108 3 ± 0.010 4, and 0.553 2 ± 0.069 1 in the PBS control group, ISA 206 adjuvant group, and rSjHsc20 immunization group following the last immunization, respectively, and the serum levels of IgG1 antibody were 0.137 3 ± 0.054 0, 0.181 1 ± 0.096 8, and 1.765 8 ± 0.221 1, while the levels of IgG2a antibody were 0.280 3 ± 0.197 6, 0.274 0 ± 0.146 3, and 1.560 4 ± 0.106 0, respectively. There were significant differences in the serum levels of anti-rSjHsc20 IgG (F = 397.70, P < 0.000 1), IgG1 (F = 401.00, P < 0.000 1) and IgG2a antibodies (F = 229.70, P < 0.000 1) among the three groups, and the serum levels of anti-rSjHsc20 IgG, IgG1 and IgG2a antibodies were higher in the rSjHsc20 immunization group than in the PBS control group and the ISA 206 adjuvant group (all P values < 0.000 1). There was a significant difference in the IgG1/IgG2a ratio among the rSjHsc20 immunization group (1.177 2 ± 0.143 6), the PBS control group (0.428 4 ± 0.199 8) and the ISA 206 adjuvant group (0.559 9 ± 0.181 1) (F = 43.97, P < 0.000 1), and the IgG1/IgG2a ratio was > 1 in the rSjHsc20 immunization group, which was higher than in the PBS control group and the ISA 206 adjuvant group (both P values < 0.000 1). The titers of serum anti-rSjHsc20 antibody were all above 1∶16 384 in the rSjHsc20 immunization group following immunizations on days 1, 15 and 31, indicating that the rSjHsc20 protein had a strong immunogenicity. The mean worm burdens were (16.60±5.75), (15.80±5.58) worms per mouse and (14.40±5.75) worms per mouse in the PBS control group, the ISA 206 adjuvant group and the rSjHsc20 immunization group 42 days post-infection with S. japonicum cercariae (F = 0.50, P > 0.05), and the EPG were 68 370 ± 22 690, 67 972 ± 19 502, and 41 075 ± 13 251 in the PBS control group, the ISA 206 adjuvant group and the rSjHsc20 immunization group (F = 4.55, P < 0.05), with lower EPG in the PBS control group and the ISA 206 adjuvant group than in the rSjHsc20 immunization group (both P values < 0.05). Immunization with the rSjHsc20 protein resulted in a worm burden reduction of 13.25% and an egg burden reduction of 39.92% relative to the PBS control group. Conclusions SjHsc20 is successfully cloned and expressed, and the rSjHsc20 protein induces partial immunoprotective effects in mice, which provides a basis for deciphering the biological functions of SjHsc20 and assessing the potential of SjH-sc20 as a vaccine candidate.

OBJECTIVE To optimize the salt-processing technology for Anemarrhena asphodeloides. METHODS Taking soaking time， stir-frying temperature， and stir-frying time as factors， Box-Behnken response surface methodology was employed to optimize the salt-processing technology of A. asphodeloides using the contents of mangiferin， neomangiferin， isomangiferin， timosaponin BⅡ， timosaponin AⅢ， timosaponin BⅢ， total flavonoids， and total saponins as evaluation indicators. The entropy weight method was applied to determine the weight of each indicator and calculate the comprehensive score. Based on the 17 sets of Box-Behnken response surface methodology results， a genetic algorithm （GA）-back propagation （BP） neural network was used to further optimize the salt-processing technology， with soaking time， stir-frying temperature， and stir-frying time as input layers and the comprehensive score as the output layer. The salt-processing parameters obtained from the two methods were validated and compared to determine the optimal salt-processing technology for A. asphodeloides. RESULTS The optimal salt-processing conditions obtained via the Box-Behnken response surface methodology were as follows： soaking time of 23 min， stir-frying temperature of 160 ℃ ， and stir-frying time of 12 min， yielding a comprehensive score of 63.370 2. The GA-BP neural network optimization resulted in the following conditions： soaking time of 24 min， stir-frying temperature of 163 ℃， and stir-frying time of 12 min， with a comprehensive score of 65.163 8. The GA-BP neural network optimization outperformed the results obtained by Box-Behnken response surface methodology. CONCLUSIONS This study successfully optimized the salt-processing technology for A. asphodeloides. Specifically， the technology involves adding 15 mL of 0.1 g/mL saline solution to 50 g of the herbal slices， allowing them to moisten for 24 minutes， and then stir-frying at 163 ℃ for 12 minutes.