In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

OBJECTIVE: To investigate the impact of bone mass and volume of low-density zones beneath the tibial plateau on the maximum von Mises stresses experienced by the cartilage and meniscus in the knee joint. METHODS: The study included one healthy adult volunteer, from whom CT scans were obtained, and one patient diagnosed with knee osteoarthrisis (KOA), for whom X-ray films were acquired. A static model of the knee joint featuring a low-density zone was established based on a normal knee model. In the finite element analysis, axial loads of 1 000 N and 1 800 N were applied to the weight-bearing region of the upper surface of the femoral head for model validation and subsequent finite element studies, respectively. The maximum von Mises stresses in the femoral cartilage, as well as the medial and lateral tibial cartilage and menisci, were observed, and the stress percentage of the medial and lateral components were concurrently analyzed. Additionally, HE staining, as well as alkaline magenta staining, were performed on the pathological specimens of patients with KOA in various low-density regions. RESULTS: The results of model validation indicated that the model was consistent with normal anatomical structures and correlated with previous calculations documented in the literature. Static analysis revealed that the maximum von Mises stress in the medial component of the normal knee was the lowest and increased with the advancement of the hypointensity zone. In contrast, the lateral component exhibited an opposing trend, with the maximum von Mises stress in the lateral component being the highest and decreasing as the hypointensity zone progressed. Additionally, the medial component experienced an increasing proportion of stress within the overall knee joint. HE staining demonstrated that the chondrocyte layer progressively deteriorated and may even disappear as the hypointensity zone expanded. Furthermore, alkaline magenta staining indicated that the severity of microfractures in the trabecular bone increased concurrently with the expansion of the hypointensity zone. CONCLUSION The presence of subtalar plateau low-density zone may aggravate joint degeneration. In clinical practice, it is necessary to pay attention to the changes in the subtalar plateau low-density zone and actively take effective measures to strengthen the bone status of the subtalar plateau low-density zone and restore the complete biomechanical function of the knee joint, in order to slow down or reverse the progression of osteoarthritis.
Humans ; Finite Element Analysis ; Knee Joint/physiology* ; Tibia/anatomy & histology* ; Cartilage, Articular/physiology* ; Menisci, Tibial/physiopathology* ; Tomography, X-Ray Computed ; Osteoarthritis, Knee/diagnostic imaging* ; Weight-Bearing ; Bone Density ; Adult ; Stress, Mechanical ; Male ; Middle Aged ; Biomechanical Phenomena ; Female

OBJECTIVES: To investigate the genomic characteristics and prognostic factors of juvenile myelomonocytic leukemia (JMML) with RAS mutations. METHODS: A retrospective analysis was conducted on the clinical data of JMML children with RAS mutations treated at the Hematology Hospital of Chinese Academy of Medical Sciences, from January 2008 to November 2022. RESULTS: A total of 34 children were included, with 17 cases (50%) having isolated NRAS mutations, 9 cases (27%) having isolated KRAS mutations, and 8 cases (24%) having compound mutations. Compared to children with isolated NRAS mutations, those with NRAS compound mutations showed statistically significant differences in age at onset, platelet count, and fetal hemoglobin proportion (P<0.05). Cox proportional hazards regression model analysis revealed that hematopoietic stem cell transplantation (HSCT) and hepatomegaly (≥2 cm below the costal margin) were factors affecting the survival rate of JMML children with RAS mutations (P<0.05); hepatomegaly was a factor affecting survival in the non-HSCT group (P<0.05). CONCLUSIONS Children with NRAS compound mutations have a later onset age compared to those with isolated NRAS mutations. At initial diagnosis, children with NRAS compound mutations have poorer peripheral platelet and fetal hemoglobin levels than those with isolated NRAS mutations. Liver size at initial diagnosis is related to the prognosis of JMML children with RAS mutations. HSCT can improve the prognosis of JMML children with RAS mutations.
Humans ; Leukemia, Myelomonocytic, Juvenile/therapy* ; Mutation ; Male ; Female ; Child, Preschool ; Retrospective Studies ; Child ; Infant ; GTP Phosphohydrolases/genetics* ; Membrane Proteins/genetics* ; Adolescent ; Hematopoietic Stem Cell Transplantation ; Proportional Hazards Models ; Proto-Oncogene Proteins p21(ras)/genetics* ; Prognosis

OBJECTIVE: To investigate the risk factors, clinical characteristics, and bacterial resistance of bloodstream infections caused by Streptococcus mitis in children with hematological disease, so as to provide a reference for infection control. METHODS: The clinical information and laboratory findings of pediatric patients complicated with blood cultures positive for Streptococcus mitis from January 2018 to December 2020 in the Institute of Hematology & Blood Diseases Hospital were searched and collected. The clinical characteristics, susceptibility factors, and antibiotic resistance of the children were retrospectively analyzed. RESULTS: Data analysis from 2018 to 2020 showed that the proportion of Streptococcus mitis isolated from bloodstream infections in children (≤14 years old) with hematological diseases was the highest (19.91%) and significantly higher than other bacteria, accounting for 38.64% of Gram-positive cocci, and presented as an increasing trend year by year. A total of 427 children tested positive blood cultures, including 85 children with bloodstream infections caused by Streptococcus mitis who tested after fever. Most children experienced a recurrent high fever in the early and middle stages (≤6 d) of neutropenia and persistent fever for more than 3 days. After adjusting the antibiotics according to the preliminary drug susceptibility results, the body temperature of most children (63.5%) returned to normal within 4 days. The 85 children were mainly diagnosed with acute myeloid leukemia (AML), accounting for 84.7%. The proportion of children in the neutropenia stage was 97.7%. The incidence of oral mucosal damage, lung infection, and gastrointestinal injury symptoms was 40%, 31.8%, and 27.1%, respectively. The ratio of elevated C-reactive protein (CRP) and procalcitonin was 65.9% and 9.4%, respectively. All isolated strains of Streptococcus mitis were not resistant to vancomycin and linezolid, and the resistance rate to penicillin, cefotaxime, levofloxacin, and quinupristin-dalfopristin was 10.6%, 8.2%, 9.4%, and 14.1%, respectively. None of children died due to bloodstream infection caused by Streptococcus mitis. CONCLUSION The infection rate of Streptococcus mitis is increasing year by year in children with hematological diseases, especially in children with AML. Among them, neutropenia and oral mucosal damage after chemotherapy are high-risk infection factors. The common clinical symptoms include persistent high fever, oral mucosal damage, and elevated CRP. Penicillin and cephalosporins have good sensitivity. Linezolid, as a highly sensitive antibiotic, can effectively control infection and shorten the course of disease.
Humans ; Child ; Streptococcal Infections/microbiology* ; Retrospective Studies ; Hematologic Diseases/complications* ; Streptococcus mitis ; Drug Resistance, Bacterial ; Risk Factors ; Microbial Sensitivity Tests ; Anti-Bacterial Agents ; Female ; Male ; Bacteremia/microbiology* ; Child, Preschool ; Adolescent

Objective:To investigate the effect of human epidermal growth factor receptor 2 (HER2) on bladder cancer by regulating phosphoinositide 3-kinase (PI3K)-protein kinase B (Akt) signaling pathway via tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon peptide (YWHAE) and to examine its mechanism.Methods:The gene expression profiling interactive analysis (GEPIA) database was used to analyze HER2 expression in 408 bladder cancer tissues and 19 adjacent normal tissues. HER2 expression was then compared between 215 tumor protein 53 ( TP53) mutant and 193 TP53 non-mutant bladder cancer tissues. Tissue samples were obtained from patients who underwent surgical resection for bladder cancer in Tianjin Medical University General Hospital between June 2010 and March 2015. Immunohistochemistry and Western blotting were performed to validate HER2 and p53 protein expression, as well as analyze their correlation. Bladder cancer T24 cells were transfected with short hairpin RNA targeting HER2 (shHER2) control (shCon) or shHER2, designated as shCon and shHER2 groups. Bladder cancer UMUC3 cells were transfected with overexpression control (oeCon), HER2 overexpression (oeHER2), oeYWHAE, or short hairpin RNA targeting murine double minute 2 (MDM2) (shMDM2), and were designated as the oeCon, oeHER2, oeYWHAE and shMDM2 groups, respectively. UMUC3 cells were then treated with either 0.1% dimethyl sulfoxide or 100 mmol/L dihydrotestosterone and designated as the solvent control and dihydrotestosterone groups, respectively. Additionally, oeCon and oeYWHAE UMUC3 cells were treated with the PI3K inhibitor LY294002 (25 μmol/L), designated as the LY294002 and LY294002+oeYWHAE groups. On this basis, shHER2 was transfected into the oeCon and oeYWHAE groups, which were then designated as the shHER2-2 and shHER2-2+oeYWHAE groups. The relative expression levels of HER2, YWHAE mRNA, and HER2, p53, YWHAE, MDM2, phosphorylated Akt (p-Akt), and Akt proteins were determined using quantitative reverse transcription PCR and Western blotting. Cell Counting Kit-8, Transwell, and wound-healing assays were performed to evaluate the impact of HER2 on the proliferation, invasion, and migration of bladder cancer cells. Mass spectrometry and co-immunoprecipitation assays were performed to confirm the interaction between YWHAE and HER2, and immunofluorescence was used to detect p53 expression. BALB/c nude mice were subcutaneously injected with 5×10 6 UMUC3 cells in the scapular region. According to the random number table method, they were divided into negative the control group and the transfection group, with 3 mice in each group, and transfected with oeCon and oeHER2, respectively. Tumor volume and weight were measured and calculated, and HER2 and p53 protein expression in bladder cancer tissues was validated by immunohistochemistry and Western blotting. Independent sample t test or Mann-Whitney U test was used to compare the two groups. One-way analysis of variance or Kruskal-Wallis test was used for comparison of multiple groups. Results:GEPIA database analysis demonstrated significantly higher levels of HER2 expression in bladder cancer tissues and in TP53 mutant bladder cancers compared with adjacent normal tissues (both P<0.01). HER2 expression was inversely correlated with p53 expression ( r=?0.6). Immunohistochemistry and Western blotting confirmed that p53 expression level in the bladder cancer tissues (5.32±0.11) was higher than that in the adjacent normal tissues (2.00±0.01), while HER2 expression level in the bladder cancer tissues (1.13±0.02) was lower than that in the adjacent normal tissues (6.20±0.06) (both P<0.01). HER2 mRNA and protein expression, absorbance at 450 nm wavelength ( A450) values, and cell invasion number and cell migration distance in the shHER2 group were all lower than those in the shCon group [0.25±0.01 vs 1.00±0.05, 1.00± 0.01 vs 3.26±0.09, 1.36±0.04 vs 1.65±0.06, (107.00±5.51) vs (202.70±11.61) cells, and (298.70±6.94) vs (454.30±7.84) μm] ( P<0.05, 0.01). HER2 mRNA and protein expression, absorbance ( A450) values, and cell invasion number and cell migration distance in the oeHER2 group were all higher than those in the oeCon group [0.78±0.02 vs 0.46±0.01, 2.05±0.02 vs 1.00±0.00, 1.23±0.06 vs 0.78±0.03, (136.30±5.24) vs (59.00±5.51) cells, and (153.70±7.27) vs (66.33±33.84) μm] ( P<0.05, 0.01). HER2 protein expression level in the dihydrotestosterone group was higher than that in the solvent control (1.83±0.19 vs 1.00±0.00), while p53 protein expression level in the dihydrotestosterone group was lower than that in the solvent control group (1.10±0.10 vs 1.53±0.15) (both P<0.01). The differentially expressed protein between the dihydrotestosterone group and solvent control group was YWHAE. The expression levels of YWHAE mRNA and protein in the dihydrotestosterone group (1.10±0.12 and 3.05±0.03) were higher than those in the solvent control group (0.30±0.12 and 1.00±0.00) (both P<0.01). YWHAE protein expression level in the oeHER2 group was higher than that in the oeCon group (1.37±0.08 vs 1.00±0.00) ( P<0.01) and YWHAE expression level in the bladder cancer tissues was higher than that in the adjacent normal tissues ( P<0.01). YWHAE expression positively correlated with HER2 expression ( r=0.4). Co-immunoprecipitation confirmed direct binding between HER2 and YWHAE. Overexpression of YWHAE significantly reduced p53 expression. The relative expression level of MDM2 protein in the oeYWHAE group (2.73±0.09) was lower than that in the oeCon group (3.43±0.12) ( P<0.01). The relative expression level of MDM2 protein in the shMDM2 group (1.00±0.00) was lower than that in the oeYWHAE group, and the relative expression level of p53 protein (2.00±0.00) was higher than that in the oeYWHAE group (1.07±0.07) (both P<0.01). The relative expression levels of YWHAE and p-Akt protein in the oeYWHAE group (1.23±0.09, 3.00±0.06) were higher than those in the oeCon group (1.00±0.00, 1.13±0.03) ( P<0.05, 0.01). The relative expression level of p-Akt protein in LY294002 group (2.20±0.06) was lower than that in the oeCon group (3.30±0.10), and the relative expression level of p53 protein (2.10±0.06) was higher than that in the oeCon group (1.00±0.00) (both P<0.01). The relative expression level of p-Akt protein in LY294002+oeYWHAE group (2.00±0.06) was lower than that in the oeYWHAE group (3.53±0.14), and the relative expression level of p53 protein (2.10±0.06) was higher than that in the oeYWHAE group (1.00±0.06) (both P<0.01). The relative expression levels levels of YWHAE, p-Akt and MDM2 protein in the shHER2-2 group (1.60±0.15, 1.70±0.06, 0.80±0.06) were lower than those in the oeCon group (2.30±0.06, 2.30±0.06, 1.13±0.09), and the relative expression level of p53 protein (1.83±0.12) was higher than that in the oeCon group (1.00±0.00) ( P<0.05, 0.01). The relative expression level of YWHAE protein in the shHER2-2+oeYWHAE group (2.00±0.06) was lower than that in the oeCon group ( P<0.01), and the relative expression levels of MDM2 and p53 protein (2.63±0.15, 1.13±0.03) were higher than those in the oeCon group ( P<0.05, 0.01). The tumor volume, tumor weight, and relative expression levels of HER2, YWHAE, p-Akt, and MDM2 proteins on day 28 in the transfection group [(5 133.0±185.6) mm 3, (0.65±0.12) g, 2.23±0.02, 4.00±0.12, 3.33±0.06 and 2.24±0.02] were higher than those in the negative control group [(2 633.0±88.2) mm 3, (0.33±0.07) g, 0.98±0.02, 1.27±0.03, 1.29±0.02 and 1.46±0.06] (all P<0.01). The relative expression level of p53 protein (1.21±0.04) was lower than that in the negative control group (3.29±0.04) ( P<0.01). Conclusions:HER2 may promote the malignant progression of bladder cancer by regulating the PI3K-Akt pathway via YWHAE, thereby facilitating MDM2 nuclear translocation and p53 degradation. This ultimately enhances the proliferative, migratory, and invasive capacities of bladder cancer cells.

Objective To investigate the value of multimodal MRI radiomics in predicting muscle-invasive bladder cancer.Methods A total of 178 patients with pathology diagnosis of bladder cancer were retrospectively collected,including 31 cases of muscle invasive bladder cancer(MIBC)and 147 cases of non-muscle invasive bladder cancer(NMIBC).Patients were randomly divided into training group and testing group at a ratio of 7︰3.The range of bladder tumors in T2WI,diffusion weighted imaging(DWI)and apparent diffusion coefficient(ADC)images were segmented as volume of interest(VOI)by using ITK-SNAP software.Radiomics features were extracted through A.K software.The optimal radiomics features were obtained through radiomics algorithm and least absolute shrinkage and selection operator(LASSO)method.Finally,the logistic regression analysis method and random forest model method were used to construct prediction models.The performance of prediction models was evaluated by the receiver operating characteristic(ROC)curve.Results This study constructed four groups of models containing T2WI prediction model,DWI prediction model,ADC prediction model,and T2WI+DWI+ADC prediction model.The area under the curve(AUC)of T2WI,DWI,and ADC prediction models for identifying MIBC and NMIBC were separately 0.920,0.914,and 0.954 in the training group while those were respectively 0.881,0.773,and 0.871 in the testing group.There was no statistical significance between T2WI,DWI,and ADC prediction models.In training and testing groups,the AUC of T2WI+DWI+ADC prediction model were respectively 0.959 and 0.909,which were higher than the single sequence prediction model.The sensitivity and specificity of the training group were 0.905 and 0.853 and the sensitivity and specificity of the testing group were 0.778 and 0.795.Conclusion MRI radiomics prediction model can effectively differentiate MIBC and NMIBC.The T2WI+DWI+ADC prediction model shows better prediction efficiency.

ObjectiveExosomes are microvesicles which could be secreted by all cell types with diameters between 30 and 150 nm. It was widely distributed in body fluids including blood, urine, and breast milk. Exosomes are considered as potential biomarkers and drug carriers by reason of containing nucleic acids, lipids, proteins and other bioactive molecules. Milk-derived exosomes have been widely used as drug delivery carriers to treat targeted diseases with a lower cost, higher biocompatibility and lower immunogenicity. Until now, there is no research about the milk-derived exosomes phosphorylation to reveal the difference of protein phosphorylation in different species of milk. To investigate the pathways and proteins with specific functions, phosphorylated proteomic analysis of milk-derived exosomes from different species is performed, and provide new ideas for exploring diversified treatments of disease. MethodsWhey and exosomes derived from bovine, porcine and caprine milk were performed for proteomics and phosphoproteomics analysis. The relationship between milk exosome proteins from different species and signaling pathways were analyzed using bioinformatics tools. ResultsA total of 4 191 global proteins, 1 640 phosphoproteins and 4 064 phosphosites were identified from 3 species of milk-derived exosomes, and the exosome proteins and phosphoproteins from different species were significantly higher than those of whey. Meanwhile, some special pathways were enriched like Fcγ-mediated phagocytosis from bovine exosomes, pathways related with neural and immune system from caprine exosomes, positive and negative regulation of multiple activities from porcine exosomes. ConclusionIn this study, the proteomic and phosphoproteomic analyses of exosomes and whey from bovine, porcine and caprine milk were carried out to reveal the difference of composition and related signaling pathways of milk exosome from different species. These results provided powerful support for the application of exosomes from different milk sources in the field of disease treatment.

Objective To investigate the efficacy and safety of camrelizumab monoclonal antibody combined with molecular-targeted therapy in elderly patients with unresectable or advanced hepatocellular carcinoma(HCC).Methods A retrospective analysis was performed for the patients with unresectable/advanced HCC who attended six hospitals from January 1,2019 to March 31,2021,and all patients received camrelizumab monoclonal antibody treatment,among whom 84.8%also received targeted therapy.According to the age of the patients,they were divided into elderly group(≥65 years)and non-elderly group(＜65 years).The two groups were assessed in terms of overall survival(OS),progression-free survival(PFS),objective response rate(ORR),disease control rate(DCR),and immune-related adverse events(irAE).The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups;the independent samples t-test was used for comparison of normally distributed continuous data,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups.The Kaplan-Meier method was used for survival analysis,and the log-rank test was used for comparison of survival curves.Univariate and multivariate Cox proportional hazards regression analyses were used to determine the independent influencing factors for PFS and DCR at 6 months.Results A total of 99 HCC patients were enrolled,with 27 in the elderly group and 72 in the non-elderly group.The elderly group had an OS rate of 67.8%,an ORR of 44.4%,and a DCR of 74.1%at 12 months and a median PFS of 6.4(95%confidence interval[CI]:3.0-12.4)months,with no significant differences compared with the non-elderly group(all P＞0.05).The median OS was unavailable for the elderly group,while the non-elderly group had an OS of 18.9(95%CI:13.0-24.8)months;there was no significant difference between the two groups(P=0.485).The univariate and multivariate Cox regression analyses showed that major vascular invasion(MVI)was an independent risk factor for PFS(hazard ratio[HR]=2.603,95%CI:1.136-5.964,P=0.024)and DCR(HR=3.963,95%CI:1.671-9.397,P=0.002)at 6 months,while age,sex,etiology of HBV infection,presence of extrahepatic metastasis,Child-Pugh class B,and alpha-fetoprotein＞400 ng/mL were not associated with PFS or DCR at 6 months.For the elderly group,the incidence rates of any irAE and grade 3/4 irAE were 51.9%and 25.9%,respectively,with no significant differences compared with the non-elderly group(P＞0.05),and skin disease was the most common irAE in both groups(39.4%).Conclusion Camrelizumab monoclonal antibody combined with molecular-targeted therapy has similar efficacy and safety in patients with unresectable/advanced HCC aged≥65 years and those aged＜65 years.MVI is associated with suboptimal response to immunotherapy and poor prognosis.

Analyze the changes in phenolic components and gene expression profiles of Tetrastigma hemsleyanum leaves with supplemental blue light, and screen differentially expressed genes related to phenolic metabolism, providing a basis for improving the quality of T. hemsleyanum leaves. Using the leaves of T. hemsleyanum under supplemental blue light and visible light as research materials, the content of phenolic components such as neochlorogenic acid, chlorogenic acid, and 3-O-coumaroyl quinic acid was significantly increased by supplemental blue light. A total of 102 949 unigenes were obtained from the transcriptome, including 14 564 differentially expressed unigenes. They can be divided into 52 subclasses by gene ontology (GO) function, kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis showed that these differentially expressed unigenes were significantly enriched in phenolic metabolic pathways such as phenylpropane biosynthesis, flavonoid biosynthesis and isoflavone biosynthesis. A total of 63 differentially expressed unigenes were identified in the pathways related to the biosynthesis of phenolic cpmponents, including 19 key enzymes such as phenylalanine ammonia-lyase (PAL), cinnamyl-alcohol dehydrogenase (CAD), flavonol synthase (FLS), and so on. This study greatly enriched the genetic data information of T. hemsleyanum and laid a foundation for analyzing the mechanism of blue light promoting the biosynthesis of phenols and molecular breeding of T. hemsleyanum.