[Objective]By integrating multi-parameter magnetic resonance imaging(MRI)radiomics features,an interpretable machine learning model was constructed to accurately predict pre-operative traditional Chinese medicine(TCM)syndromes in breast cancer patients,providing objective and quantitative basis for clinical TCM syndrome types differentiation.[Methods]A total of 315 patients pathologically diagnosed breast cancer from the First Affiliated Hospital of Zhejiang Chinese Medical University between June 2019 to October 2023 were retrospectively included.The preoperative TCM syndromes of the patients were classified into liver depression with phlegm coagulation,chongren dysregulation and positive deficiency blazing toxin type.These patients were randomly allocated to the training(221 cases)and validation sets(94 cases)in a ratio of 7:3.Radiomics features in dynamic contrast-enhanced imaging(DCE),diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)images of each patient were extracted by using Kruskal-Wallis rank sum test,Spearman correlation analysis and least absolute shrinkage and selection operator(LASSO)polynomial Logistic regression screening for radiomics features.Then,light gradient boosting machine(LightGBM)was used to construct the syndrome prediction model.[Results]A total of 2 832 radiomics features were extracted from the DCE,DWI and ADC images of each patient.After a series of feature selection methods,the total numbers of features for DCE,DWI,ADC and three-sequence combination were 3,3,3 and 7 respectively.The machine learning model integrating multi-sequence MRI image information had the best performance,with micro-averaged area under the curve(AUC)of 0.852 and 0.838 for the training and validation sets,and macro-averaged AUC of 0.833 and 0.810 for the training and validation sets respectively.Shapley additive explanation(SHAP)analysis showed that inverse difference moment normalization(Idmn)of the ADC sequence,average gray level(Mean)of the ADC sequence and inverse variance of the DCE sequence were the three features that contributed most to the prediction results.[Conclusion]The interpretable machine learning model constructed in this study can accurately predict pre-operative TCM syndromes in breast cancer patients.SHAP interpretability analysis provides quantitative contribution value information,which can help clinicians understand the model prediction process and provide a new perspective for the application of traditional Chinese medicine in the treatment of breast cancer.

The data from outpatient prescriptions of small-size aspirin enteric-coated tablets(25 mg/tablet)in a community hospital were analyzed to provide reference for rational clinical drug use.Patients'medication information of 1 325 prescriptions was collected and analyzed by defined daily dose system(DDDs)and drug utilization index(DUI),and the rationality of drug use was analyzed according to drug instructions and literature.The mean age of males and females were(73.70±8.33)years old and(72.95±8.34)years old,respectively.The top 3 DDDs age groups were women aged 60-79 years,men aged 60-79 years and women aged 80-99 years.The proportion of prescriptions in female patients was 59.62%.DUI ranges from 0.75 to 0.85.Irrational drug use was found in 123 prescriptions,including 89 prescriptions(72.35%)of inappropriate drug selection,19 prescriptions(15.45%)with low dose,6 prescriptions(4.88%)with contraindication,5 prescriptions(4.06%)with inconsistent frequency of administration,2 prescriptions(1.63%)of out-of-indication drug use,and 2 prescriptions(1.63%)of high dose.For the phenomenon of irrational drug use,it is necessary to conduct real-time intervention to ensure the safety and effectiveness of drug use.

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.

[Objective]By integrating multi-parameter magnetic resonance imaging(MRI)radiomics features,an interpretable machine learning model was constructed to accurately predict pre-operative traditional Chinese medicine(TCM)syndromes in breast cancer patients,providing objective and quantitative basis for clinical TCM syndrome types differentiation.[Methods]A total of 315 patients pathologically diagnosed breast cancer from the First Affiliated Hospital of Zhejiang Chinese Medical University between June 2019 to October 2023 were retrospectively included.The preoperative TCM syndromes of the patients were classified into liver depression with phlegm coagulation,chongren dysregulation and positive deficiency blazing toxin type.These patients were randomly allocated to the training(221 cases)and validation sets(94 cases)in a ratio of 7:3.Radiomics features in dynamic contrast-enhanced imaging(DCE),diffusion-weighted imaging(DWI)and apparent diffusion coefficient(ADC)images of each patient were extracted by using Kruskal-Wallis rank sum test,Spearman correlation analysis and least absolute shrinkage and selection operator(LASSO)polynomial Logistic regression screening for radiomics features.Then,light gradient boosting machine(LightGBM)was used to construct the syndrome prediction model.[Results]A total of 2 832 radiomics features were extracted from the DCE,DWI and ADC images of each patient.After a series of feature selection methods,the total numbers of features for DCE,DWI,ADC and three-sequence combination were 3,3,3 and 7 respectively.The machine learning model integrating multi-sequence MRI image information had the best performance,with micro-averaged area under the curve(AUC)of 0.852 and 0.838 for the training and validation sets,and macro-averaged AUC of 0.833 and 0.810 for the training and validation sets respectively.Shapley additive explanation(SHAP)analysis showed that inverse difference moment normalization(Idmn)of the ADC sequence,average gray level(Mean)of the ADC sequence and inverse variance of the DCE sequence were the three features that contributed most to the prediction results.[Conclusion]The interpretable machine learning model constructed in this study can accurately predict pre-operative TCM syndromes in breast cancer patients.SHAP interpretability analysis provides quantitative contribution value information,which can help clinicians understand the model prediction process and provide a new perspective for the application of traditional Chinese medicine in the treatment of breast cancer.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Objective:To investigate alterations in the immune lineage of T-cell large granular lymphocytic leukemia (T-LGLL) at the single-cell transcriptome level and to elucidate its pathogenic mechanisms.Methods:Peripheral blood samples were collected from 5 T-LGLL patients before and after treatment (from June 2019 to December 2020) and 3 healthy controls at the Institute of Hematology & Blood Diseases Hospital, CAMS & PUMC. Single-cell transcriptome sequencing libraries were prepared and sequenced using 10× Genomics technology. Differentially expressed genes in immune cells were compared between patients and healthy donors, followed by pathway enrichment analyses.Results:Profiling 67,237 immune cells revealed that, in T-LGLL: 1) Effector CD8+ T cells exhibited increased numbers, enhanced cytotoxicity, and greater proliferative capacity. Following effective immunosuppressive therapy, both the proliferative capacity and effector functions of these cells significantly decreased ( P<0.05). 2) The proportion of regulatory T (Treg) cells was reduced, accompanied by increased apoptosis. After effective immunosuppressive therapy leading to remission, Treg cell proportions increased, and apoptotic pathways were downregulated ( P<0.05). 3) Antigen-presenting cells (APCs) showed enhanced functionality. Monocytes and dendritic cells were enriched in antigen synthesis and presentation pathways, while B cells displayed increased antigen-binding capacity and were enriched in pathways related to T-cell activation ( P<0.05). 4) Natural killer (NK) cells exhibited attenuated cytotoxic function but demonstrated an enhanced regulatory capacity over T cells ( P<0.05) . Conclusions:T-LGLL patients present a characteristic immunological profile marked by an imbalance in immune homeostasis. This profile includes abnormal activation and expansion of effector CD8 + T cells, and a reduction in Treg cell numbers accompanied by functional impairment. Furthermore, APCs and NK cells were found to positively regulate T-lymphocyte activation, differentiation, and proliferation.

Objective:To evaluate the efficacy of cyclophosphamide in patients with T-cell large granular lymphocytic leukemia (T-LGLL) and the maintenance of treatment-free remission (TFR) following drug discontinuation.Methods:Clinical data were collected from 37 patients with T-LGLL who received oral cyclophosphamide at the Regenerative Medicine Clinic of the Institute of Hematology and Blood Diseases Hospital between June 2019 and March 2024. Patient clinical characteristics, treatment efficacy, and long-term TFR were analyzed.Results:The median age of the 37 patients was 60 years (range: 37-86), and 22 (59.5%) were male. Anemia was observed in 30 patients (81.1%), and 28 (75.7%) met the diagnostic criteria for secondary pure red cell aplasia. Neutropenia occurred in 15 patients (40.5%), lymphocytosis in 11 (29.7%), and thrombocytopenia in three (8.1%). Sixteen patients (43.2%) had not received prior immunosuppressive therapy (treatment-naive group), while 21 patients (56.8%) were refractory to or had relapsed after immunosuppressive treatment (refractory/relapsed group). All patients met the treatment criteria and received oral cyclophosphamide at doses of 50-100 mg/day. Among the 36 evaluable patients, hematologic remission was achieved in 25 (69.4%), with a median time of 2.0 months (range: 0.7-7.0). There was no statistically significant difference in remission rates between the treatment-naive and refractory/relapsed groups (68.5% vs. 66.7%, P=0.589). Among the 25 patients who achieved hematologic remission, 24 discontinued cyclophosphamide. With a median follow-up of 39.0 months (range: 8.0-56.0), the median TFR duration was not reached. The estimated TFR rates were (90.87± 6.16) % at 12 months and (75.72±11.04) % at 36 months. No significant difference in TFR was observed between the treatment-naive and refractory/relapsed groups ( P=0.451) . Conclusion:Oral cyclophosphamide is effective in the treatment of T-LGLL, and patients may maintain long-term TFR following drug discontinuation.

The efficacy of Xiangmei Pills on rats with ulcerative colitis(UC) was investigated by characterizing the spectrum of the active chemical components of Xiangmei Pills. Rapid identification and classification of the main chemical components were performed,and the therapeutic effects of Xiangmei Pills on the proteins and intestinal flora of UC rats were analyzed to explore the mechanism of its action in treating UC. Fifty SD rats were acclimatized to feeding for 3 d and randomly divided into blank group, model group,mesalazine group(0. 4 g·kg~(-1)), low-dose group of Xiangmei Pills(1. 89 g·kg~(-1)), and high-dose group of Xiangmei Pills(5. 67 g·kg~(-1)), with 10 rats in each group. 5% dextrose sodium sulfate(DSS) was given by gavage to induce the male SD rat model with UC,and the corresponding medicinal solution was given by gavage after 10 days, respectively. The therapeutic effect of Xiangmei Pills on rats with UC was evaluated according to body mass, disease activity index(DAI), and hematoxylin-eosin(HE) staining, and the histopathological changes in the colon were observed. Ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high-resolution mass spectrometry(UHPLC-Q-Orbitrap HRMS) technique was used to rapidly and accurately identify the main chemical constituents of Xiangmei Pills. Immunohistochemistry was used to detect the expression of aryl hydrocarbon receptor(AhR),interferon-γ(IFN-γ), mucin-2(MUC-2), and cytochrome P450 1A1(CYP1A1) in colon tissue. Interleukin-22(IL-22) expression in colon tissue was detected by immunofluorescence. The 16S r DNA high-throughput sequencing technique was used to study the modulatory effects of Xiangmei Pills on the intestinal flora structure of rats with UC. Pharmacodynamic results showed that compared with that of the blank group, the colon tissue of the model group was congested, and ulcers were visible in the mucosa; compared with that in the model group, the histopathology of the colon of the rats with UC in the groups of Xiangmei Pills were improved, with scattered ulcers and reduced inflammatory cell infiltration. Chemical analysis showed that a total of 45 components were identified by mass spectrometry information, including 15 phenolic acids, 8 coumarins, 15 organic acids, 3 amino acids, 2 flavonoids, and 2 other components. Compared with those in the blank group, the levels of Ah R, CYP1A1, MUC-2, and IL-22 proteins in the colon tissue of rats in the model group were significantly decreased, and the level of IFN-γ protein was significantly increased; the intestinal flora of rats in the model group was disorganized, with a decrease in the abundance of the flora; the relative abundance of Bacteroidetes,unclassified genera of Ascomycetes, Prevotella of the Prevotella family, and Prevotella decreased significantly, and that of Firmicutes decreased, but the difference was not statistically significant. The relative abundance of Bacteroidetes, Bifidobacterium, and Lactobacillus increased significantly. Compared with those of the model group, the levels of Ah R, CYP1A1, MUC-2, and IL-22proteins in the colonic tissue of the groups of Xiangmei Pills were significantly higher, and the levels of IFN-γ proteins were significantly lower. The recovery of the intestinal flora was accelerated, and the diversity of the intestinal flora was significantly increased. The relative abundance of Bacteroidetes was significantly increased, and that of unclassified genera of Ascomycetes,Lactobacillus, Prevotella of the Prevotella family, and Prevotella was significantly increased. The relative abundance of Bacteroidetes and Bifidobacterium was significantly decreased. This study demonstrated that Xiangmei Pills can effectively treat UC, mainly through the phenolic acid and organic acid components to stimulate the intestinal barrier, regulate protein expression and the relative abundance and diversity of intestinal flora, and play a role in the treatment of UC.
Animals ; Colitis, Ulcerative/metabolism* ; Drugs, Chinese Herbal/chemistry* ; Rats, Sprague-Dawley ; Male ; Rats ; Gastrointestinal Microbiome/genetics* ; Chromatography, High Pressure Liquid ; Humans ; Mass Spectrometry ; RNA, Ribosomal, 16S/genetics* ; Bacteria/drug effects*

OBJECTIVES: To determine the pharmacological impact of hesperidin, the main component of Citri Reticulatae Pericarpium, on depressive behavior and elucidate the mechanism by which hesperidin treats depression, focusing on the gut-brain axis. METHODS: Fifty-four Sprague Dawley male rats were randomly allocated to 6 groups using a random number table, including control, model, hesperidin, probiotics, fluoxetine, and Citri Reticulatae Pericarpium groups. Except for the control group, rats in the remaining 5 groups were challenged with chronic unpredictable mild stress (CUMS) for 21 days and housed in single cages. The sucrose preference test (SPT), immobility time in the forced swim test (FST), and number in the open field test (OFT) were performed to measure the behavioral changes in the rats. Enzyme-linked immunosorbent assay was used to determine the levels of 5-hydroxytryptamine (5-HT) and brain-derived neurotrophic factor (BDNF) in brain tissue, and the histopathology was performed to evaluate the changes of colon tissue, together with sequencing of the V3-V4 regions of 16S rRNA gene on feces to explore the changes of intestinal flora in the rats. RESULTS: Compared to the control group, the rats in the model group showed notable reductions in body weight, SPF, and number in OFT (P<0.01). Hesperidin was found to ameliorate depression induced by CUMS, as seen by improvements in body weight, SPT, immobility time in FST, and number in OFT (P<0.05 or P<0.01). Regarding neurotransmitters, it was found that at a dose of 50 mg/kg hesperidin treatment upregulated the levels of 5-HT and BDNF in depressed rats (P<0.05). Compared to the control group, the colon tissue of the model group exhibited greater inflammatory cell infiltration, with markedly reduced numbers of goblet cells and crypts and were significantly improved following treatment with hesperidin. Simultaneously, the administration of hesperidin demonstrated a positive impact on the gut microbiome of rats treated with CUMS, such as Shannon index increased and Simpson index decreased (P<0.01), while the abundance of Pseudomonadota and Bacteroidota increased in the hesperidin-treated group (P<0.05). CONCLUSION The mechanism responsible for the beneficial effects of hesperidin on depressive behavior in rats may be related to inhibition of the expressions of BDNF and 5-HT and preservation of the gut microbiota.
Animals ; Hesperidin/therapeutic use* ; Rats, Sprague-Dawley ; Depression/drug therapy* ; Male ; Stress, Psychological/drug therapy* ; Brain/metabolism* ; Brain-Derived Neurotrophic Factor/metabolism* ; Serotonin/metabolism* ; Gastrointestinal Microbiome/drug effects* ; Behavior, Animal/drug effects* ; Rats ; Brain-Gut Axis/drug effects* ; Chronic Disease ; Colon/drug effects*

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.