Combined Use of Tumor Markers in Gastric Cancer: A Novel Method with Promising Prognostic Accuracy and Practicality.

BACKGROUND: The effect of a single tumor marker on the prognosis of gastric cancer patients is not ideal. This study explored a novel prognostic assessment method for gastric cancer (GC) patients using a combination of three important tumor markers (CEA, CA72-4, and CA19-9). METHOD: Data from 1966 GC patients who underwent curative gastrectomy at Sun Yat-Sen University Cancer Center (Guangzhou, China) were included. Hazard ratios (HR) for all factors for overall survival (OS) were analyzed by Cox regression. A nomogram and calibration curve were used to establish the survival prediction model. The prediction accuracy was evaluated with the concordance index (C-index). RESULTS: All patients were divided into four groups (C0-C3) according to the number of elevated tumor markers. The 5-year OS rates of the patients in preoperative groups C0-C3 were 83.8% (81.3-86.4%), 72.8% (68.5-77.4%), 58.9% (50.4-68.9%), and 18.5% (4.0-33.0%), respectively, and those in postoperative groups C0-C3 were 82.1% (79.4-84.8%), 76.1% (72.2-80.3%), 57.6% (48.4-68.5%), and 16.8% (5.1-28.5%), respectively, with significant differences between each C0-C3 subgroup in both preoperative and postoperative cohorts. Multivariate analysis showed that preoperative (HR: 6.001, 95% CI: 3.523-10.221) and postoperative (HR: 8.149, 95% CI: 4.962-13.528) elevated tumor markers were independent risk factors for GC patients. The C-index for the combined use of tumor markers was 0.65-0.66, which was higher than that for using a single tumor marker (0.53-0.56). CONCLUSION: The combined use of tumor markers significantly improved the prognostic value compared with using a single tumor marker. The survival prediction model including the combined tumor markers was accurate and effective.

Adjuvant Chemotherapy for Patients with Adenocarcinoma of the Esophagogastric Junction: A Retrospective, Multicenter, Observational Study.

BACKGROUND: Although the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been increasing since the past decade, the proportion of AEG cases in two previous clinical trials (ACTS-GC and CLASSIC) that investigated the efficacy of adjuvant chemotherapy was relatively small. Therefore, whether AEG patients can benefit from adjuvant chemotherapy remains unclear. METHODS: Patients who were diagnosed with pathological stage II/III, Siewert II/III AEG, and underwent curative surgery at three high-volume institutions were assessed. Clinical outcomes were analyzed by using Kaplan-Meier curves, log-rank test, and Cox regression model. Propensity score matching (PSM) was used to reduce the selection bias. RESULTS: A total of 927 patients were included (the chemotherapy group: 696 patients; the surgery-only group: 231 patients). The median follow-up was 39.0 months. The 5-year overall survival was 63.1% (95% confidence interval [CI]: 59.0-67.6%) for the chemotherapy group and 50.2% in the surgery-only group (hazard ratio [HR] = 0.69, 95% CI: 0.54-0.88; p = 0.003). The 5-year, disease-free survival was 35.4% for the chemotherapy group and 16.6% for the surgery-only group (HR = 0.66, 95% CI: 0.53-0.83; p < 0.001). After PSM, the survival benefit of adjuvant chemotherapy for AEG was maintained. Multivariate analysis for overall survival and disease-free survival further demonstrated the survival benefit of adjuvant chemotherapy, with HRs of 0.63 (p < 0.001) and 0.52 (p < 0.001), respectively. CONCLUSIONS: Postoperative adjuvant chemotherapy was associated with improved overall survival and disease-free survival in patients with operable stage II or III AEG after D2 gastrectomy.

The role of computed tomography features in assessing response to neoadjuvant chemotherapy in locally advanced gastric cancer.

OBJECTIVE: To compare the computed tomography (CT) images of patients with locally advanced gastric cancer (GC) before and after neoadjuvant chemotherapy (NAC) in order to identify CT features that could predict pathological response to NAC. METHODS: We included patients with locally advanced GC who underwent gastrectomy after NAC from September 2016 to September 2021. We retrieved and collected the patients' clinicopathological characteristics and CT images before and after NAC. We analyzed CT features that could differentiate responders from non-responders and established a logistic regression equation based on these features. RESULTS: We included 97 patients (69 [71.1%] men; median [range] age, 60 [26-75] years) in this study, including 66 (68.0%) responders and 31 (32.0%) non-responders. No clinicopathological variable prior to treatment was significantly associated with pathological response. Out of 16 features, three features (ratio of tumor thickness reduction, ratio of reduction of primary tumor attenuation in arterial phase, and ratio of reduction of largest lymph node attenuation in venous phase) on logistic regression analysis were used to establish a regression equation that demonstrated good discrimination performance in predicting pathological response (area under receiver operating characteristic curve 0.955; 95% CI, 0.911-0.998). CONCLUSION: Logistic regression equation based on three CT features can help predict the pathological response of patients with locally advanced GC to NAC.

Preoperative diagnosis of metastatic lymph nodes by CT-histopathologic matching analysis in gastric adenocarcinoma using dual-layer spectral detector CT.

OBJECTIVES: There still remain challenges to accurate diagnosis of lymph node (LN) involvement in gastric cancer (GC) on conventional CT. This study evaluated the quantitative data derived from dual-layer spectral detector CT (DLCT) for preoperative diagnosis of metastatic LNs compared to conventional CT images. METHODS: Patients with adenocarcinoma scheduled for gastrectomy were enrolled in this prospective study from July, 2021, to February, 2022. Regional LNs were labeled on preoperative DLCT. The LNs were located and matched using carbon nanoparticle solution during surgery according to their locations and anatomic landmarks on preoperative images. The matched LNs were randomly split into training and validation cohorts in a ratio of 2:1. The DLCT quantitative parameters in the training cohort were investigated using logistic regression models to identify independent predictors of metastatic LNs, and these predictors were subsequently applied to the validation cohort. Receiver operating characteristic curves were compared between the DLCT parameters and conventional CT images. RESULTS: Fifty-five patients were included in the study, with 267 successfully matched LNs (90 metastatic, 177 nonmetastatic). Independent predictors included arterial phase CT attenuation on 70-keV images, venous phase electron density, and clustered feature. These combination predictors had areas under the curve (AUC) of 0.855 and 0.907 in the training and validation cohorts, respectively. Compared to conventional CT criteria alone, the model had higher AUC and accuracy (0.741 vs. 0.907, 75.28% vs. 87.64%; p < 0.01) for LN diagnosis. CONCLUSION: Incorporating DLCT parameters improved preoperative diagnosis of LN metastasis in GC, increasing the accuracy of clinical N stage. CLINICAL RELEVANCE STATEMENT: Compared to conventional CT criteria, quantitative parameters from dual-layer spectral detector CT showed higher diagnostic efficacy for the preoperative diagnosis of lymph node metastases in gastric cancer, increasing the accuracy of clinical N stage. KEY POINTS: • Quantitative parameters from dual-layer spectral detector CT are useful for the preoperative diagnosis of lymph node metastases in gastric adenocarcinoma, increasing the accuracy of clinical N stage. • The values for metastatic lymph nodes are higher than those of nonmetastatic ones. The arterial phase of CT attenuation on 70-keV images, venous phase of electron density, and clustered feature independently predicted lymph node metastases. • Prediction model had area under the curve of 0.907, sensitivity of 81.82%, specificity of 91.07%, and accuracy of 87.64% for the preoperative diagnosis of lymph node metastasis.

Efficacy and safety of herbal medicines intervention for cachexia associated with cancer: A systematic review and meta-analysis.

As a worldwide public health issue, cancer-induced cachexia can result in decreasing physical function and survival rate. However, the therapeutic effects of conventional approaches, including pharmacotherapy, exercise and nutritional intervention, are far from satisfactory. Herbal medicines (HMs), especially Traditional Chinese Medicine (TCM), are reported to effectively treat cachexia for centuries. The inclusion criteria of all participants in this study pointed to the diagnosis of cachexia, the trial group used herbal medicine (HM) in complementary and alternative medicine, etc. Twelve databases, including EMbase, PubMed, Web of science, Cochrane CENTRAL, CINAHL, CINAHLPlus, PsycINFO, AMED, China Biology Medicine disc (CBM), China National Knowledge Infrastructure (CNKI), Wanfang and Chongqing VIP (CQVIP) were retrieved from inception to March 28, 2022. We conducted the meta-analysis utilizing RevMan 5.3. A trial sequential analysis (TSA) was conducted to assess the adequacy of the sample size for the outcomes. We have registered the protocol and the registration number was CRD42022336446. A total of 66 studies were included, containing 3654 patients diagnosed with cancer cachexia, of which 1833 patients were assigned to the trial group and 1821 patients were treated in the control group. Outcomes cover the primary indicator KPS (RR = 1.84, 95%CI = [1.61, 2.09], p < 0.00001), and other outcomes including adverse events rate (RR = 0.37, 95%CI = [0.23, 0.58], p < 0.0001), albumin (MD = 2.14, 95%CI = [1.56, 2.71], p < 0.00001), haemoglobin (MD = 4.88, 95%CI = [3.26, 6.50], p < 0.00001), TCM syndrome effect (MD = 1.47, 95%CI = [1.31, 1.65], p < 0.00001), effect of weight (RR = 1.62, 95%CI = [1.34, 1.95], p < 0.00001), effect of appetite (RR = 1.23, 95%CI = [1.13, 1.34], p < 0.00001), FAACT (RR = 7.81, 95%CI = [6.12, 9.50], p < 0.00001), PG-SGA (MD = -2.16, 95%CI = [-2.65, -1.67], p < 0.00001) and QOL (MD = 5.76, 95%CI = [4.04, 7.48], p < 0.00001), suggesting that HMs or HMs combined with conventional treatment have an ameliorating effect on cachexia in each respect. Subgroup analysis showed that the five HMs with the best effect on improving KPS and their optimal doses were Coicis Semen (Yiyiren) in 10 g group, Citri Reticulatae Pericarpium (Chenpi) in 15 g group, Dioscoreae Rhizoma (Shanyao) in 10 g group, Ophiopogonis Radix (Maidong) in 10 g group and Ginseng Radix Et Rhizoma (Renshen) in 20 g group. In addition, there were HM combinations of levels 2-6. Egger's test showed publication bias for five outcomes. HMs have a significant effect on improving cancer cachexia on FAACT, TCM syndrome, KPS, QOL, appetite, nutritional status (evaluated by PG-SGA scale), weight, levels of albumin and haemoglobin. And the Adverse events rate is less than that of Western Medicine. The herbs with the best curative effect and their optimal dose were Dioscoreae R. (10 g), Citri R.P. (15 g), Coicis S. (10 g), Ophiopogonis R. (10 g) and Ginseng R.E.R. (20 g). Due to the quality of included studies is not high, further high-quality studies are needed to firmly establish the clinical efficacy of HM.

Advanced Computer Vision-Based Subsea Gas Leaks Monitoring: A Comparison of Two Approaches.

Recent years have witnessed the increasing risk of subsea gas leaks with the development of offshore gas exploration, which poses a potential threat to human life, corporate assets, and the environment. The optical imaging-based monitoring approach has become widespread in the field of monitoring underwater gas leakage, but the shortcomings of huge labor costs and severe false alarms exist due to related operators' operation and judgment. This study aimed to develop an advanced computer vision-based monitoring approach to achieve automatic and real-time monitoring of underwater gas leaks. A comparison analysis between the Faster Region Convolutional Neural Network (Faster R-CNN) and You Only Look Once version 4 (YOLOv4) was conducted. The results demonstrated that the Faster R-CNN model, developed with an image size of 1280 × 720 and no noise, was optimal for the automatic and real-time monitoring of underwater gas leakage. This optimal model could accurately classify small and large-shape leakage gas plumes from real-world datasets, and locate the area of these underwater gas plumes.

Development and verification of a nomogram for predicting the prognosis of resectable gastric cancer with outlet obstruction.

BACKGROUND: The prognosis of patients with gastric cancer (GC) with gastric outlet obstruction (GOO) after gastrectomy is highly variable. In this study, we aimed to develop a nomogram to predict the prognosis of these patients. PATIENTS AND METHODS: Data from 218 GC patients with GOO who underwent gastrectomy at Sun Yat-sen University Cancer Center were retrospectively collected as a training cohort. The data of 59 patients with the same diagnosis who underwent gastrectomy at the First Affiliated Hospital of Guangxi Medical University were collected as an external verification cohort. A nomogram for the overall survival (OS) was developed using the Cox regression model in the training cohort, which was validated in a verification cohort. RESULTS: Multivariate analysis showed that the surgical procedure (P < 0.001), period of chemotherapy (P < 0.001), T stage (P = 0.006), N stage (P = 0.040), systemic immune-inflammatory index (SII) (P < 0.001), and fibrinogen level (P = 0.026) were independent factors affecting OS. The nomogram constructed on the aforementioned factors for predicting the 1- and 3-year OS achieved a Harrell's concordance index (C-index) of 0.756 and 0.763 for the training and verification cohorts, respectively. Compared with the 8th American Joint Committee on Cancer (AJCC) Tumour-Node-Metastasis (TNM) staging system, the nomogram had higher C-index values and areas under the curve (AUCs) and slightly higher net clinical benefit. CONCLUSION: Compared to the 8th AJCC staging system, the newly developed nomogram showed superior performance in predicting the survival of GC patients with GOO after gastrectomy.

Palliative Gastrectomy versus Gastrojejunostomy for advanced Gastric cancer with outlet obstruction: a propensity score matching analysis.

BACKGROUND: Gastric outlet obstruction (GOO) is a late complication of advanced gastric cancer, and it is controversial how to select the therapeutic strategies: gastrojejunostomy and palliative gastrectomy? Therefore, this study was to compare the surgical and survival outcomes of gastrojejunostomy and palliative gastrectomy. METHODS: In total, 199 gastric cancer patients with outlet obstruction treated by surgery between January 2000 and December 2015 at Sun Yat-sen University Cancer Center were retrospectively reviewed. Patients were divided into gastrojejunostomy group and palliative gastrectomy group. Propensity score matching (PSM) was performed to balance the selection bias. RESULTS: After 1:1 PSM, a total of 104 patients were included for final analysis. The median overall survival (OS) times in the gastrojejunostomy group and palliative gastrectomy group were 8.50 and 11.87 months, respectively (P = 0.243). The postoperative complication rates in the gastrojejunostomy group and palliative gastrectomy group were 19.23% (10/52) and 17.31% (9/52), respectively (P = 0.800), and no treatment-related death was observed. Multivariate analysis showed that periton0eal seeding (P = 0.014) and chemotherapy (P < 0.001) were independent prognostic factors. Among them, peritoneal seeding was a risk factor and postoperative chemotherapy was a protective factor. CONCLUSIONS: Our results indicated that although the surgical complications of palliative gastrectomy were manageable, it showed no survival benefit. Therefore, relieving obstruction symptom, improving patients' quality of life and creating better conditions for chemotherapy appear to be the main therapeutic strategies for advanced gastric cancer with GOO.

Can large doses of glucocorticoids lead to Perthes? a case report and review of the literature.

BACKGROUND: Perthes disease (Legg-Calvé-Perthes, LCP) is a self-limited and non-systemic disease occurring in the femoral heads of children, which is mainly manifested as an ischemic necrosis of the femoral head epiphysis, leading to subchondral ossification injury of the femoral head. CASE PRESENTATION: Here we report a case of 11-year-old child with long-term use of high-dose glucocorticoids. With MRI examination finding the epiphyseal necrosis of right humeral head, femur and tibia, and X-ray examination finding bilateral femoral head necrosis, the child was diagnosed as Perthes disease based on his clinical and imaging data. CONCLUSIONS: Long-term and high-dose glucocorticoids may be one of the causes of Perthes disease.

Exploratory study on classification of chronic obstructive pulmonary disease combining multi-stage feature fusion and machine learning.

BACKGROUND: Due to the complexity and high heterogeneity of the acute exacerbation of chronic obstructive pulmonary disease (AECOPD), the guidelines (global initiative for chronic obstructive, GOLD) is unable to fully guide the treatment of AECOPD. OBJECTIVES: To provide a rapid treatment in line with the development of the AECOPD after admission. In this paper, we propose a multi-stage feature fusion (MSFF) framework combining machine learning to track the diseases deterioration risk of the AECOPD. METHODS: First, we identify 408 AECOPD patients as the study population. Then, feature segment and fusion methods are applied to generate the phased data set. Finally, human studies are designed to evaluate the performance of the MSFF framework. RESULTS: The experimental results show that the proposed framework is potential to obtain the full-process tracking of deterioration risk for the AECOPD patients. The proposed MSFF framework achieves a higher overall accuracy average and F1 scores than the four physician groups i.e., IM, Surgery, Emergency, and ICU. CONCLUSIONS: The proposed MSFF model may serve as a useful disease tracking tool to estimate the deterioration risk at each stage, and finally achieve the disease monitoring and management for AECOPD patients.

[Analysis of prescription regularity of traditional Chinese medicine for colorectal cancer based on data mining].

The tumor prescriptions contained in Dictionary of Tumor Formulas, Compendium of Good Tumor Formulas, Chinese Pharmacopoeia, Ministry of Health Drug Standards for Chinese Medicine Formulas and National Compilation of Standards for Proprietary Chinese Medicines were selected and organized to construct a database for tumor prescriptions, and the data mining techniques were applied to investigate the prescription regularity of colorectal cancer prescriptions. The formula data were extracted after screening in strict accordance with the inclusion and exclusion criteria, and were then analyzed with Microsoft Excel 2010 for frequency statistics, Apriori block provided by SPSS Clementine 12.0 software for correlation rule analysis, and arules and arulesViz packages in R 4.0.2 software for correlation rule visualization. In addition, SPSS 18.0 software was used for cluster analysis and factor analysis, in which cluster analysis was performed by Ochiai algorithm with bicategorical variables in systematic clustering method and factor analysis was performed mainly with principal component analysis. A total of 285 prescriptions were included in the statistical analysis, and the frequency statistics showed that 43 herbs had been used more than 16 times. The association rules analysis showed that 26 high-frequency me-dicine pair rules were obtained, and the association rules for those dispelling evil spirits, strengthening the body, resolving stasis, dispelling dampness, etc. were visualized. In the cluster analysis, we generated a dendrogram from which 7 groups of traditional Chinese medicines with homogeneity were extracted. 10 common factors were obtained in the factor analysis. The types of herbal medicines involved in the colorectal cancer prescription included anti-cancer antidotes, strengthening and tonifying medicines, blood-regulating medicines, and expectorant medicines, corresponding to the treatment for eliminating evil spirits, strengthening, resolving stasis, and expectorating dampness. The prescriptions for anti-cancer detoxification were normally based on the pairs composed of Scutellaria barbata-Hedyotis diffusa and Sophora flavescens, Sargentodoxa cuneata, S. barbata, often combined with stasis relieving drug and dampness eliminating drug, reflecting the characteristics of treatment for both toxicity and stasis, dampness and toxicity simultaneously. The prescriptions for strengthening the righteousness and tonifying the deficiency were composed of Astragalus membranaceus and Atractylodes macrocephala mainly, exerting the effect of benefiting Qi, strengthening the spleen and drying dampness, tonifying kidney and essence, tonifying blood and invigorating blood. Meanwhile, anti-cancer detoxification medicines shall be reduced as much as possible. The compatibility of the medicines for the intestinal tract reflected the principle of using the right medicine for the right condition and eliminating evil spirits or strengthening the body, as appropriate.

Surgical Outcome and Long-Term Survival of Conversion Surgery for Advanced Gastric Cancer.

BACKGROUND: The present study aims to report the surgical outcome and long-term survival of conversion surgery and clarify its role in advanced gastric cancer. PATIENTS AND METHODS: A total of 95 primary advanced gastric adenocarcinoma patients who underwent systemic chemotherapy and conversion surgery were reviewed retrospectively. The survival of conversion surgery was analyzed by Cox regression and the Kaplan-Meier method. Surgical outcomes were analyzed according to the Clavien-Dindo classification. RESULTS: The median survival time (MST) of the 95 patients was 26.8 months, and the postoperative MST was 19.3 months. The MSTs of the patients in categories 1, 2, 3, and 4 were 28.8, 25.5, 43.6, and 11.3 months, respectively. The MSTs of the patients who underwent R0 resection (47 cases) and R1/2 resection (48 cases) were 49.3 months and 21.9 months, respectively. The MST of patients treated with total gastrectomy was shorter (21.9 months) than that of patients who underwent proximal (55.0 months) or distal (46.3 months) gastrectomy. Patients who received more than 6 cycles of induction chemotherapy had a longer MST than patients who received 3-5 cycles or 1-2 cycles (MST: 55.0 months versus 21.1 months versus 21.7 months). The incident postoperative complications and postoperative mortality rates were 10.5% and 1.1%, respectively. CONCLUSIONS: Advanced gastric cancer patients may obtain a survival benefit from conversion surgery, except category 4. Performing a sufficient number of cycles of induction chemotherapy (usually ≥ 6 cycles) is recommended. Surgical oncologists should perform R0 resection and avoid total gastrectomy.

Disease-free survival as a surrogate endpoint for overall survival in adjuvant trials of pancreatic cancer: a meta-analysis of 20 randomized controlled trials.

BACKGROUND: We aimed to assess whether disease-free survival (DFS) could serve as a reliable surrogate endpoint for overall survival (OS) in adjuvant trials of pancreatic cancer. METHODS: We systematically reviewed adjuvant randomized trials for non-metastatic pancreatic cancer after curative resection that reported a hazard ratio (HR) for DFS and OS. We assessed the correlation between treatment effect (HR) on DFS and OS, weighted by sample size or precision of hazard ratio estimate, assuming fixed and random effects, and calculated the surrogate threshold effect (STE). We also performed sensitivity analyses and a leave-one-out cross validation approach to evaluate the robustness of our findings. RESULTS: After screening 450 relevant articles, we identified a total of 20 qualifying trails comprising 5170 patients for quantitative analysis. We noted a strong correlation between the treatment effects for DFS and OS, with coefficient of determination of 0.82 in the random effect model, 0.82 in the fixed effect model, and 0.80 in the sample size weighting; the robustness of this finding was further verified by the leave-one-out cross-validation approach. Sensitivity analyses with restriction to phase 3 trials, large trials, trials with mature follow-up periods, and trials with adjuvant therapy versus adjuvant therapy strengthened the correlation (0.75 to 0.88) between DFS and OS. The STE was 0.96 for DFS. CONCLUSIONS: Therefore, DFS could be regarded as a surrogate endpoint for OS in adjuvant trials of pancreatic cancer. In future similar adjuvant trials, a hazard ratio for DFS of 0.96 or less would predict a treatment impact on OS.

Identification of Tiny Surface Cracks in a Rugged Weld by Signal Gradient Algorithm using the ACFM Technique.

It is still a big challenge to identify tiny surface cracks in a rugged weld due to the lift-off variations using the nondestructive testing (NDT) method. In this paper, the signal gradient algorithm is presented to identify the tiny surface crack in the rugged weld using the alternating current field measurement (ACFM) technique. The ACFM simulation model and testing system was set up to obtain the insensitive signal to the lift-off variations. The signal gradient algorithm was presented to process the insensitive signal for the identification of the tiny surface crack in the rugged weld. The results show that the Bz signal is the insensitive signal to lift-off variations caused by the rugged weld. The signal to noise ratio (SNR) of the crack identification signal was greatly improved by the signal gradient algorithm, and a tiny surface crack can be identified effectively in the weld and the heat affected zone (HAZ).

[Research rules of famous veteran traditional Chinese medicine practitioners in treating infertility].

To explore the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility based on medical cases of infertility collected from book series of Hundred Traditional Chinese Medicine Clinicians of Hundred Years in China and Prescription Proven by Traditional Chinese Medicine Masters. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then, Excel 2010, SPSS Clementine(ver.12.0) and SPSS(ver. 22.0) were adopted respectively for frequency analysis, association rules analysis, cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data, which was a systematic clustering method. And principal component analysis was used for factor analysis. Besides, KMO test and Bartlett spherical test were used for factor adaptation test. Finally, 151 medical cases and 396 prescriptions were included in total. A total of 60 kinds of frequently used herbs were identified according to the results of frequency analysis for medication, they were mainly used for activating blood and resolving stasis, tonifying and clearing heat respectively. The association rules analysis found out 25 drug pair association rules and 14 3-drug combination association rules. A total of 15 medicine groups were extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis, and 21 common factors were respectively extracted by factor analysis. Association rules indicated the characteristics of the therapeutic methods, like tonifying Qi and replenishing blood. The famous veteran traditional Chinese medicine practitioners utilized modified Siwu Decoction for tonifying blood and preferred Atractylodis Macrocephalae Rhizoma(Baizhu) for tonifying Qi. The results of both cluster analysis and factor analysis demonstrated the characteristics of the therapies for tonifying kidney, activating blood, tonifying spleen and dispelling dampness. In addition, factor analysis could reflect the therapies for nourishing Yin, tonifying kidney, warming the meridian, dissipating cold, nourishing blood and dispelling blood stasis. These results of analysis comprehensively showed out the medication characteristics of famous veteran traditional Chinese medicine practitioners of strictly following the pathogenesis, making good use of classical formulas and providing proper compatibility. In conclusion, data mining techniques(including frequency analysis, association rules analysis, cluster analysis and factor analysis) were used to comprehensively analyze the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility, which is helpful for guiding the clinical practice of treating infertility with traditional Chinese medicine.

[Analysis on regularity of traditional Chinese patent medicine in treating hyperlipidemia].

To explore the regularity of traditional Chinese patent medicines for the treatment of hyperlipidemia recorded in Newly Edited National Chinese Traditional Patent Medicines,the Composition Principles of Chinese Patent Drugs,New Drug Conversion Standard,the Compilation of National Standard for Traditional Chinese Medicines and Chinese Pharmacopoeia. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then microsoft excel 2010 was used to conduct frequency statistics and count the frequency of traditional Chinese medicine. SPSS Clementine( ver.12. 0) and SPSS( ver. 18. 0)were adopted respectively for frequency analysis,association rules analysis,cluster analysis and factor analysis. Besides,KMO test and Bartlett spherical test were performed for factor adaptation test. Finally,a total of 173 traditional Chinese medicines were included,involving 94 Chinese patent medicine prescriptions. The frequency results of traditional Chinese medicine showed that there were 33 kinds of high-frequency traditional Chinese medicine,mainly including those for tonifying medicine,activating blood and resolving stasis and blood-stasis,and clearing damp. The association rules analysis found out 12 association rules of drug pairs,3-herb pairs of 25 and4-herb pairs of 6. Totally 11 medicine groups with relevance were respectively extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis and 11 common factors were respectively extracted by factor analysis. The association rules reflected the therapeutic method for tonify the liver and kidney,activating blood and resolving stasis. Cluster analysis and factor analysis showed the therapeutic method of Qi-enriching and Yin-nourishing,and the factor analysis focused more on removing blood stasis and dampness. The decision tree with hawthorn as the dependent variable reflects the importance of alisma orientalis and fructus schisandrae in the drug matching. In conclusion,data mining technique can comprehensively analyze the regularity of prescriptions of traditional Chinese patent medicine for hyperlipidemia,and is helpful for guiding the development of Chinese patent medicines and the clinical practice of traditional Chinese medicine.

[Famous veteran traditional Chinese medicine doctors' medication rules in treating spermatorrhea].

To explore famous veteran traditional Chinese medicine( TCM) doctors' medication rules in treating spermatorrhea based on the medical cases about spermatorrhea collected from Hundred TCM Clinical Doctors of Hundred Years in China and Proven Cases and National Medical Master Test Case. Researchers extracted such data as medicinal and therapies from these cases according to the inclusion and exclusion criteria. Then,Excle 2010,SPSS Clementine 12. 0 and SPSS 22. 0 were adopted respectively for frequency analysis,association rules analysis,cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data,one of the systematic clustering methods. And principal component analysis was used for factor analysis. Finally,27 medical cases and 41 prescriptions were included in total. The frequency analysis showed that the most common therapy was the astringent therapy( n = 28),which was followed by the tonifying method,tranquilizing method,heat-clearing method,damp-dispelling method and Qiregulating method. The top three kinds of high-frequency traditional Chinese medicines were Poria,Ostreae Concha and Dioscoreae Rhizoma. The association rules analysis found out 11 association rules of medicine pairs,23 association rules of medicine combinations of the three kinds of herbs and 6 association rules of medicine combinations of five kinds of herbs. Among them,the representatives were Rubi Fructus→Fossilia Ossis Mastodi,Rehmanniae Radix Praeparata + Corni Fructus→Dioscoreae Rhizoma,and Pinelliae Rhizoma→Citri Reticulatae Pericarpium,which showed the therapeutic characteristics of astringing,tonifying the kidney and replenishing essence,fortifying the spleen and dispelling dampness. Moreover,7 medicine groups with relevance were extracted from the tree map generated by cluster analysis,including " Phellodendri Chinensis Cortex and Anemarrhenae Rhizoma" and " Angelicae Sinensis Radix,Rehmanniae Radix,Bupleuri Radix and Glycyrrhizae Radix et Rhizoma",which demonstrated the effects of nourishing Yin and purging fire,tonifying and soothing the liver. Besides,totally 12 common factors were obtained according to factor analysis,including 14 drug combinations,like " Amomi Fructus,Anemarrhenae Rhizoma and Phellodendri Chinensis Cortex" and " Nelumbinis Stamen,Moutan Cortex,Poria and Scrophulariae Radix",which indicated the compatibility characteristics of tonifying the spleen and purging fire,dispelling dampness and clearing heat. In conclusion,data mining techniques( including frequency analysis,association rules analysis,cluster analysis and factor analysis) were used to comprehensively analyze the famous veteran TCM doctors' medication rules in treating spermatorrhea,which was helpful for guiding the clinical practice of treating spermatorrhea in TCM.