Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective To explore its application value of LNM in patients with gastric adenocarcinoma based on the construction of a radiomic nomogram prediction model for preoperative lymph node metastasis in gastric adenocarcinoma using enhanced CT imaging features and parameters.Methods 131 patients with gastric adenocarcinoma who underwent radical gastric cancer surgery(Billroth Ⅱ)+lymph node dissection in our hospital from August 2019 to October 2023 were retrospectively analysed,and the preoperative enhancement CT extracted lesions,histological features of lymph node images,and pathological examination of LNM were recorded respectively,and the statistically significant Enhanced CT image histological features and parameters,multifactorial logistic regression to analyse the independent risk factors of gastric adenocarcinoma LNM(+)and construct a column-line diagram,and evaluate its performance.The performance and clinical value of the prediction model were evaluated using subject work characteristic(ROC)curves,and the column-line diagram was internally validated.Results The results of univariate analysis showed that the maximum diameter of the tumour,the lymph node status,the short-axis length and volume of the largest lymph node in the lymph node group and the sum of the short-axis lengths of all the lymph nodes were associated with the occurrence of LNM,and the difference was statistically significant(P＜0.05);multifactorial logistic regression analysis suggested that the maximum diameter of the tumour was ≥15 mm and the lymph node status was positive in the enhanced CT imaging examination,maximum lymph node short-axis length ≥ 7 mm in the lymph node group,the sum of short-axis lengths of all lymph nodes ≥ 11 mm,and the maximum lymph node short-axis volume ≥ 300 mm3 in the lymph node group were the independent risk factors for gastric adenocarcinoma patients with LNM(+)(P＜0.05);the area under the curve of the model was plotted using a ROC curve with an AUC=0.816(95％ CI 0.810-0.939),with the sensitivity of 0.91 and the specificity of 0.86.Model validation was performed using the BOOTSTRAP method containing 500 resamples,and the results suggested that the differences between the fitted curves and the ideal curves of the constructed column-line graphical model were not significant,and the validity and reliability were good.Conclusion The radiomic nomogram prediction model based on enhanced CT imaging features and parameters can effectively predict preoperative lymph node metastasis in gastric adenocarcinoma,providing strong support for clinical decision-making in gastric adenocarcinoma patients.

Objective To construct a model for predicting ki-67 expression in hepatocellular carcinoma using the intratumoral and peritumoral radiomic features of contrast enhanced magnetic resonance imaging(CEMRI)in the arterial phase as well as clinical imaging features.Methods A total of 120 patients pathologically diagnosed with hepatocellular carcinoma(HCC)from January 2016 to December 2024 in No.910 Hospital of the Joint Logis-tics Support Force of the Chinese People's Liberation Army were retrospectively enrolled and randomly divided into a training set(84 cases)and a test set(36 cases)in a ratio of 7∶3.ITK-SNAP software was used to delineate the global region of interest(ROI)of HCC on the arterial phase MR images.The ROIs of all patients were automatically expanded outward by 2 mm,and then the intratumoral ROI areas were eliminated to obtain the peritumoral ROI.With the help of PyRadiomics software,1 198 intratumoral and peritumoral radiomic features were extracted.Spearman correlation analysis,maximum relevance-minimum redundancy(mRMR),and least absolute shrinkage and selection operator(LASSO)regression were used to reduce the data dimension and select the best features.Then,a radiomics model of the logistic regression(LR)machine learning algorithm was constructed.A combined model including clinical imaging features and radiomics features was established.The area under the curve(AUC),accuracy,sensitivity,specificity,positive predictive value(PPV),negative predictive value(NPV),calibration curve and decision curve analysis(DCA)were used to evaluate the efficacy of the intratumoral and peritumoral radiomics features combined with clinical imaging features model in predicting ki-67 expression in hepatocellular car-cinoma.Results The intratumor model exhibited an efficacy in predicting the expression of ki-67 in hepatocellular carcinoma with AUC values of 0.817 and 0.787 in the training set and test set,respectively.The peritumoral model showed an efficacy with AUC values of 0.805 and 0.633 in the training set and test set,respectively.The intratumoral and peritumoral model demonstrated AUC values of 0.874 and 0.836 in the training set and test set,respectively.The combined model constructed by integrating the intratumoral and peritumoral model with clinical imaging features yielded AUC values of 0.877 and 0.849 in the training set and test set,respectively,indicating clinical imaging features improved the performance of the model.DCA showed that the combined models all had good clinical benefits,with the intratumoral and peritumoral model performing the best.Conclusion The intratumoral and peritumoral radiomics model based on CEMRI arterial phase combined with clinical imaging data can accurately predict the expression of ki-67 in hepatocellular carcinoma.This combined model yields the best clinical benefit.

Objective To explore its application value of LNM in patients with gastric adenocarcinoma based on the construction of a radiomic nomogram prediction model for preoperative lymph node metastasis in gastric adenocarcinoma using enhanced CT imaging features and parameters.Methods 131 patients with gastric adenocarcinoma who underwent radical gastric cancer surgery(Billroth Ⅱ)+lymph node dissection in our hospital from August 2019 to October 2023 were retrospectively analysed,and the preoperative enhancement CT extracted lesions,histological features of lymph node images,and pathological examination of LNM were recorded respectively,and the statistically significant Enhanced CT image histological features and parameters,multifactorial logistic regression to analyse the independent risk factors of gastric adenocarcinoma LNM(+)and construct a column-line diagram,and evaluate its performance.The performance and clinical value of the prediction model were evaluated using subject work characteristic(ROC)curves,and the column-line diagram was internally validated.Results The results of univariate analysis showed that the maximum diameter of the tumour,the lymph node status,the short-axis length and volume of the largest lymph node in the lymph node group and the sum of the short-axis lengths of all the lymph nodes were associated with the occurrence of LNM,and the difference was statistically significant(P＜0.05);multifactorial logistic regression analysis suggested that the maximum diameter of the tumour was ≥15 mm and the lymph node status was positive in the enhanced CT imaging examination,maximum lymph node short-axis length ≥ 7 mm in the lymph node group,the sum of short-axis lengths of all lymph nodes ≥ 11 mm,and the maximum lymph node short-axis volume ≥ 300 mm3 in the lymph node group were the independent risk factors for gastric adenocarcinoma patients with LNM(+)(P＜0.05);the area under the curve of the model was plotted using a ROC curve with an AUC=0.816(95％ CI 0.810-0.939),with the sensitivity of 0.91 and the specificity of 0.86.Model validation was performed using the BOOTSTRAP method containing 500 resamples,and the results suggested that the differences between the fitted curves and the ideal curves of the constructed column-line graphical model were not significant,and the validity and reliability were good.Conclusion The radiomic nomogram prediction model based on enhanced CT imaging features and parameters can effectively predict preoperative lymph node metastasis in gastric adenocarcinoma,providing strong support for clinical decision-making in gastric adenocarcinoma patients.

Genome-scale metabolomics analysis is increasingly used for pathway and function dis-covery in the post-genomics era.The great potential offered by developed mass spectrometry(MS)-based technologies has been hindered,since only a small portion of detected metabolites were iden-tifiable so far.To address the critical issue of low identification coverage in metabolomics,we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases.The experimental reference spectra and in silico reference spectra were adopted to facilitate the structural annotation.To further characterize the structure of metabolites,two approaches were incorporated into our strategy,i.e.,structural motif search combined with neutral loss scanning and metabolite association network.Untargeted metabolomics analysis was performed on 150 rice cultivars using ultra-performance liquid chromatography coupled with quadrupole-Orbitrap MS.Consequently,a total of 1939 out of 4491 metabolite features in the MS/MS spectral tag(MS2T)library were annotated,representing an extension of annotation coverage by an order of magnitude in rice.The differential accumulation patterns of flavonoids between indica and japon-ica cultivars were revealed,especially O-sulfated flavonoids.A series of closely-related flavonolignans were characterized,adding further evidence for the crucial role of tricin-oligolignols in lignification.Our study provides an important protocol for exploring phytochemical diversity in other plant species.

Buruli ulcer (BU), caused by

Cyclic 3',5'-adenosine monophosphate (cAMP) and cyclic 3',5'-guanosine monophosphate (cGMP) are considered as potential biomarkers for Yin-Yang disharmony in traditional Chinese medicine.However,phosphodiesterase-mediated ex vivo degradation of these molecules in biological samples may result in their underestimation.In the present study,a ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed for determination of cAMP and cGMP in rat plasma,with special consideration of their stability ex vivo.Following precipitation of proteins from plasma samples with 0.4 M perchloric acid,the analytes were chromatographed on a Shimadzu Shim-pack-XR-ODS Ⅱ column with 2.5 mM ammonium acetate and methanol in gradient mode.The MS/MS detection was performed using multiple reaction monitoring in the positive electrospray ionization mode.The lower limit of quantification was 0.27 ng/mL for cAMP and 0.37 ng/mL for cGMP.The method was used to determine the plasma cAMP and cGMP levels in normal and Yin deficiency diabetic rats treated with or without Rehmannia glutinosa.The developed method may be useful for evaluating the regulatory effects of Chinese herbal medicine on the levels of cAMP and cGMP in the body.

Objective:To analyze whether the application of growth hormone (GH) in the frozen-thawed embryo transfer (FET) cycle can improve the pregnancy outcome of patients.Methods:The retrospective cohort study including 1042 FET cycles was carried out between January 2015 to July 2018 in Reproductive Medicine Center,the Fourth Hospital of Hebei Medical University. According to medication before transfer, all patients were divided into GH group (group A ) and no GH group (group B). The pregnancy outcomes were compared between the two groups in aged patients (≥35 years), polycystic ovary syndrome (PCOS) patients and repeated implantation failure (RIF) patients.Results:In group A, the maternal age [(31.1±4.5) years old] and the clinical pregnancy rate [67.1% (114/170)] were higher than those in group B [(30.1±4.4) years old, 57.5% (501/872)]( P=0.010, P=0.020). There were no significant differences in the implantation rate, the clinical pregnancy rate, the abortion rate and the live birth rate between group A and group B in aged patients (all P>0.05). In PCOS patients, the live birth rate in group A [65.8% (25/38)] was significantly higher than that in group B [42.3% (96/227)] ( P=0.007). In the RIF patients, the implantation rate [37.3% (57/153)], the clinical pregnancy rate [50.5% (46/91)] and the live birth rate [37.4% (34/91)] in group A were significantly higher than those in group B [23.0% (115/501), 29.1% (92/316), 21.8% (69/316)] ( P<0.001, P<0.001, P=0.003). Conclusion:For the aged patients, adding GH could not improve pregnancy outcomes. The application of GH in PCOS patients could increase the live birth rate. For the RIF patients, the application of GH could increase the implantation rate, the clinical pregnancy rate and the live birth rate.

Objective:To analyze whether the application of growth hormone (GH) in the frozen-thawed embryo transfer (FET) cycle can improve the pregnancy outcome of patients.Methods:The retrospective cohort study including 1042 FET cycles was carried out between January 2015 to July 2018 in Reproductive Medicine Center,the Fourth Hospital of Hebei Medical University. According to medication before transfer, all patients were divided into GH group (group A ) and no GH group (group B). The pregnancy outcomes were compared between the two groups in aged patients (≥35 years), polycystic ovary syndrome (PCOS) patients and repeated implantation failure (RIF) patients.Results:In group A, the maternal age [(31.1±4.5) years old] and the clinical pregnancy rate [67.1% (114/170)] were higher than those in group B [(30.1±4.4) years old, 57.5% (501/872)]( P=0.010, P=0.020). There were no significant differences in the implantation rate, the clinical pregnancy rate, the abortion rate and the live birth rate between group A and group B in aged patients (all P>0.05). In PCOS patients, the live birth rate in group A [65.8% (25/38)] was significantly higher than that in group B [42.3% (96/227)] ( P=0.007). In the RIF patients, the implantation rate [37.3% (57/153)], the clinical pregnancy rate [50.5% (46/91)] and the live birth rate [37.4% (34/91)] in group A were significantly higher than those in group B [23.0% (115/501), 29.1% (92/316), 21.8% (69/316)] ( P<0.001, P<0.001, P=0.003). Conclusion:For the aged patients, adding GH could not improve pregnancy outcomes. The application of GH in PCOS patients could increase the live birth rate. For the RIF patients, the application of GH could increase the implantation rate, the clinical pregnancy rate and the live birth rate.

Objective:To explore the clinical outcomes of luteal phase stimulation (LPS) for in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) treatment in patients with poor ovarian response (POR). Methods:Retrospective analysis was conducted on the clinical, laboratory data and clinical pregnancy outcome of frozen-thawed embryo transfer of 134 POR patients using LPS protocol for IVF/ICSI treatment in Reproductive Medical Center of the Fourth Hospital of Hebei Medical University from June 2013 to December 2018.Results:Totally 142 IVF/ICSI cycles were completed in 134 POR patients. About 5.63% (8/142) cycles cancelled due to unsuitable follicle, 7.75% (11/142) were failed to obtain oocyte and 37.32% (53/142) had unsuitable embryos for freezing, the total cancellation rate reached 50.70%. The duration of human menopausal gonadotropin (hMG) used was (10.04±3.51) d and the used dosage was (2 330.00±890.48) IU. In 24.64% (35/142) cycles, progesterone decreased to less than 1 μg/L on the trigger day. The number of oocytes retrieved, M II oocytes, two pronucleus (2PN), available embryos, high-quality embryos were 3.13±2.60, 2.98±2.25, 2.17±1.69, 2.04±1.53, 1(0.2), respectively. The rates of oocytes retrieved, M II oocytes, 2PN, available embryos, high-quality embryos were 76.04% (419/551), 86.63% (363/419), 69.97% (254/363), 91.34% (232/254) and 46.06% (117/254), respectively. Before June 2016, high-quality embryos were frozen, and poor-quality embryos were cultured, the blastocyst formation rate was 15.22% (7/46). After June 2016, all available embryos were cultured, the blastocyst formation rate was 41.98% (55/131). In the following frozen-thawed embryo transfer cycles, the clinical pregnancy rate per transfer cycle was 41.67% (25/60), the abortion rate was 44.00% (11/25), and the live birth rate was 23.33% (14/60). Conclusion:The cancellation rate of LPS protocol was high in POR patients. If there were frozen embryos for transfer, the clinical pregnancy rate would be satisfied, but the abortion rate was high.