ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

ObjectiveTo optimize Tusizi prescription for ovarian reserve function based on the uniform design method combined with in vitro experiments and explore the underlying mechanisms of this prescription. MethodsThe uniform design method was adopted to design a 5-factor 11-level experiment on the water extract of Tusizi prescription. The cell-counting kit-8 （CCK-8） assay was employed to measure the viability of human ovarian granulosa cells （KGN cells） treated with Tusizi prescription extracts 1-11， and multivariate regression analysis was performed to determine the optimal herb ratio in this prescription. The potential targets of active ingredients in the prescription were retrieved from traditional Chinese medicine systems pharmacology database and analysis platform （TCMSP） and encyclopedia of traditional Chinese medicine （ETCM）. The common targets shared by Tusizi prescription and diminished ovarian reserve （DOR） were selected and imported into search tool for the retrieval of interacting genes/proteins （STRING） to construct a protein-protein interaction （PPI） network and into gene function annotation database （DAVID） for gene ontology （GO） analysis. The CCK-8 assay was used to measure the viability of ovarian germline stem cells treated with hyperoside. The CCK-8 assay， 5-ethynyl-2'-deoxyuridine （EdU） staining， terminal-deoxynucleoitidyl transferase mediated nick-end labeling （TUNEL）， and enzyme-linked immunosorbent assay （ELISA） were employed to examine the proliferation， apoptosis， and estradiol （E₂） secretion of KGN cells treated with the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design. On this basis， the optimal prescription composition for maximizing the effect on ovarian reserve function was determined and preliminary insights into the underlying mechanisms of this prescription were gained. ResultsA total of 147 common targets were obtained from 278 targets of Tusizi prescription and 1 721 targets of DOR. GO analysis revealed 194 biological processes， primarily involving cellular responses to exogenous compound stimuli， negative regulation of apoptotic process， and positive regulation of cell proliferation. It identified 84 cellular components， including cell membrane， mitochondria， and neuronal cell body， as well as 144 molecular functions such as enzyme binding， estrogen response element binding， and nuclear estrogen receptor binding. The multivariate regression analysis revealed that when Tusizi prescription was composed of Cuscutae Semen， Lycii Fructus， Dioscoreae Rhizoma， Poria， and Nelumbinis Semen in a ratio of 27∶30∶17∶12∶14， the water extract of Tusizi prescription had the best effect of enhancing the viability of KGN cells. CCK-8 results showed that compared with the normal group， the hyperoside group demonstrated increased viability of ovarian germline stem cells （P<0.01）. The CCK-8， EdU， and ELISA results showed that compared with the normal group， the optimal prescription screened by uniform design and the water extract 11 of Tusizi prescription increased the proliferation and reduced the apoptosis of KGN cells （P<0.05， P<0.01）. ELISA results showed that compared with the normal group， the water extract 11 of Tusizi prescription promoted the E₂ secretion of KGN cells （P<0.05）， while the optimal prescription screened by uniform design had no significant effect on the E₂ secretion. ConclusionBoth the water extract 11 of Tusizi prescription （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 4∶4∶2∶1∶1） and the optimal prescription screened by uniform design （Cuscutae Semen-Lycii Fructus-Dioscoreae Rhizoma-Poria-Nelumbinis Semen 27∶30∶17∶12∶14） can improve the ovarian reserve function， and the former has better effect. Tusizi prescription can modulate biological processes （such as cell proliferation and apoptosis） and molecular functions （such as enzyme binding and estrogen response element binding） through active components like hyperoside to promote the proliferation and E₂ secretion and inhibit the apoptosis of KGN cells， thereby protecting the ovarian reserve function.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

To investigate whether Tasquinimod can influence cisplatin resistance in drug-resistant ovarian cancer (OC) cell lines by regulating histone deacetylase 4 (HDAC4) or p21, we explored its effects on the cell cycle, and associated mechanisms.RT-PCR and Western blot analyses, flow cytometry, CCK8 assay, and immunofluorescence were utilized to investigate the effects of Tasquinimod on gene expression, cell cycle, apoptosis, viability, and protein levels in OC cells. The results showed that Tasquinimod inhibited cell viability and promoted apoptosis in SKOV3/DDP (cisplatin) and A2780/DDP cells more effectively than DDP alone. In combination with cisplatin, Tasquinimod further enhanced cell apoptosis and reduced cell viability in these cell lines, an effect that could be reversed following HDAC4 overexpression. Tasquinimod treatment down-regulated HDAC4, Bcl-2, and cyclin D1, and CDK4 expression and up-regulated the cleaved-Caspase-3, and p21 expression in SKOV3/DDP and A2780/ DDP cells. Additionally, Tasquinimod inhibited DDP resistance in OC/DDP cells. These effects were similarly observed in OC mouse models treated with Tasquinimod. In conclusion, Tasquinimod can improve OC cells' sensitivity to DDP by down-regulating the HDAC4/p21 axis, offering insights into potential strategies for overcoming cisplatin resistance in OC.

In recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

OBJECTIVE To systematically investigate the changes of volatile components in Euphorbia wallichii after milk and wine processing， and preliminarily elucidate the material basis for reducing toxicity. METHODS Using headspace gas chromatography-mass spectrometry technology， the volatile components in raw E. wallichii， milk-processed E. wallichii， and wine- processed E. wallichii were isolated and identified， and the relative percentage content of each component was calculated by the peak area normalization method. Combining chemometric methods such as principal component analysis and orthogonal partial least- squares discriminant analysis， changes in volatile components in samples after milk and wine processing were compared. Differential components were screened. RESULTS A total of 66 volatile components were identified from the three samples， with the types of compounds primarily comprising alkanes， olefins， heterocycles and esters， among others. A total of 39， 24 and 36 volatile components were identified from raw E. wallichii， milk-processed E. wallichii， and wine-processed E. wallichii， respectively， with 10 components common to all three preparations. Compared with raw E. wallichii， the relative percentage of other components in milk-processed E. wallichii decreased， except for alkanes and esters. The relative percentage of alkanes， olefins， aldehydes and esters in wine-processed E. wallichii increased， but the contents of heterocyclic compounds， ketones， ethers and alcohols decreased. The results of chemometric analysis showed that the volatile components of raw and processed products were significantly different. A total of 5 kinds of differential components in milk-processed products and 3 kinds of differential components in wine-processed products were screened out. Among them， the relative percentage of potential toxic components such as linalool， octanal and 3-pentanone decreased significantly after processing（P＜0.05）. CONCLUSIONS Milk and wine processing may exert a toxicity-reducing effect by reducing the contents of toxic components such as linalool， octanal and 3-pentanonein E. wallichii.