Perceptions of attitudes toward statistics among medical undergraduates: insights from a regional medical college in China.

BACKGROUND: Among Chinese medical students, medical statistics is often perceived as a formidable subject. While existing research has explored the attitudes of Chinese postgraduate medical students towards statistics and its impact on academic performance, there is a scarcity of studies examining the attitudes of Chinese medical undergraduates on this subject. This study endeavors to scrutinize the attitudes of Chinese medical undergraduates towards statistics, assessing their ramifications on learning achievements, and delving into the influence of demographic factors. METHODS: 1266 medical undergraduates participated in this study, completing a questionnaire that included SATS-36 and additional queries. Furthermore, an examination was administered at the end of the medical statistics course. The analysis encompassed the SATS score and exam scores, examining both the overall participant population and specific demographic subgroups. RESULTS: Undergraduate medical students generally exhibit a favorable disposition towards statistics concerning Affect, Cognitive Competence, and Value components, yet harbor less favorable sentiments regarding the Difficulty component of SATS-36, aligning with previous research findings. In comparison to their postgraduate counterparts, undergraduates display heightened enthusiasm for medical statistics. However, they demonstrate a lower cognitive capacity in statistics and tend to underestimate both the value and difficulty of learning statistics. Despite these disparities, undergraduate medical students express a genuine interest in statistics and exhibit a strong dedication to mastering the subject. It is noteworthy that students' attitudes toward statistics may be influenced by their major and gender. Additionally, there exists a statistically significant positive correlation between learning achievement and the Affect, Cognitive Competence, Value, Interest, and Effort components of the SATS-36, while a negative correlation is observed with the Difficulty component. CONCLUSION: Educators should carefully consider the influence of attitudes toward statistics, especially the variations observed among majors and genders when formulating strategies and curricula to enhance medical statistics education.

Environmental taxes, technological innovation and firm performance: Evidence from China's manufacturing firms.

Based on panel data from 2011 to 2019 for heavily polluting listed firms in the manufacturing industry, this paper examines the impact of environmental taxes on technological innovation and firm performance using the propensity score matching (PSM) and differences-in-differences (DID) methods. The empirical results show the following: (i) Firm performance and innovation quantity are positively affected by environmental taxes. The average effects of environmental taxes on firm performance and innovation quantity are 1.28 and 0.219, respectively. However, environmental taxes have no significant impact on innovation quality. (ii) A mechanism analysis reveals that innovation quantity plays a significant partial mediating role in the positive effect of environmental taxes on firm performance. (iii) Heterogeneity analysis shows that different environmental tax rates lead to a variation in innovation quantity and firm performance across regions. The positive effect of environmental taxes on innovation quantity is only confirmed in high-tax and low-tax areas. Meanwhile, high environmental taxes are related to better firm performance. Based on the research, policy recommendations are put forward to optimise environmental taxes, such as improving the environmental tax system and coordinating environmental tax and innovation policies.

Analysis of the expression level and predictive value of CLEC16A|miR-654-5p|RARA regulatory axis in the peripheral blood of patients with ischemic stroke based on biosignature analysis.

Introduction: Ischemic stroke (IS) is a cerebrovascular disease that can be disabling and fatal, and there are limitations in the clinical treatment and prognosis of IS. It has been reported that changes in the expression profile of circRNAs have been found during injury in ischemic stroke, and circRNAs play an important role in the IS cascade response. However, the specific mechanisms involved in the pathogenesis of IS are not yet fully understood, and thus in-depth studies are needed. Methods: In this study, one circRNA dataset (GSE161913), one miRNA dataset (GSE60319) and one mRNA dataset (GSE180470) were retrieved from the Gene Expression Omnibus (GEO) database and included, and the datasets were differentially expressed analyzed by GEO2R and easyGEO to get the DEcircRNA, DEmiRNA and DEmRNA, and DEmRNA was enriched using ImageGP, binding sites were predicted in the ENCORI database, respectively, and the competitive endogenous RNA (ceRNA) regulatory network was visualized by the cytoscape software, and then selected by MCC scoring in the cytoHubba plugin Hub genes. In addition, this study conducted a case-control study in which blood samples were collected from stroke patients and healthy medical examiners to validate the core network of ceRNAs constructed by biosignature analysis by real-time fluorescence quantitative qRT-PCR experiments. Results: A total of 233 DEcircRNAs, 132 DEmiRNAs and 72 DEmRNAs were screened by bioinformatics analysis. circRNA-mediated ceRNA regulatory network was constructed, including 148 circRNAs, 43 miRNAs and 44 mRNAs. Finally, CLEC16A|miR-654-5p|RARA competitive endogenous regulatory axis was selected for validation by qRT-PCR, and the validation results were consistent with the bioinformatics analysis. Discussion: In conclusion, the present study establishes a new axis of regulation associated with IS, providing new insights into the pathogenesis of IS.

Prognostic and immunological values of SKA3 for overall survival in lung adenocarcinoma and its RNA binding protein involved mechanisms.

This article aimed to investigate the correlations among SKA3 expression and prognosis, clinical relevance, tumor immunity, and RNA-binding protein (RBP)-involved mechanisms for overall survival (OS) in lung adenocarcinoma (LUAD). To explore the SKA3 expression level in LUAD by analyzing the genomic data as well as related clinical characteristics from the database of TCGA. Nomogram and gene set enrichment analysis (GSEA) were applied, respectively, to evaluate the performance of SKA3 in LUAD. Correlations between SKA3 and immunity and RBP-involved mechanisms were also performed. SKA3 had a higher expression level in LUAD samples than in adjacent normal lung samples, with shorter survival times in the high-SKA3-expressed LUAD subgroup (P < 0.05). qRT-PCR results remained consistent (P < 0.05). Uni-/multivariate Cox analyses revealed that SKA3 could have independent prognostic ability for LUAD (both P < 0.05). The nomogram model constructed with clinical pathological parameters and SKA3 expression levels predicted OS rates for LUAD and GSEA revealed SKA3-related pathways. In aspects of tumor immunity, SKA3 was significantly involved with tumor neoantigen burden, tumor mutational burden, immune cell pathways, and immune checkpoint inhibitor (ICI) molecules (all P < 0.05). The CellMiner database also found significant correlations between SKA3 and the antitumor drug sensitivity of chemotherapy, fenretinide, and PX-316. Besides, a total of nine LncRNA/RBP/SKA3 networks were revealed in LUAD for their RBP-involved mechanisms. SKA3 could serve as a potential biomarker for OS prognosis and immunotherapy in LUAD. LncRNA/RBP/SKA3 networks were identified in LUAD for their RBP-involved mechanisms, paving the way for further experimental verifications.

Environmental taxes, enterprise innovation, and environmental total factor productivity-effect test based on Porter's hypothesis.

Under the increasingly severe environmental constraints, improving environmental total factor productivity (ETFP) is the fundamental way for the sustainable development of heavily polluting enterprises. Based on 3463 panel data of A-share listed companies in China from 2011 to 2019, this paper employs Porter's hypothesis (PH) framework to explore the impact of environmental tax (EN_T) on enterprise innovation and environmental total factor productivity for the heavily polluting manufacturing industry using the propensity score matching (PSM) method. The empirical results show the following. (i) Environmental taxes positively affect enterprise innovation (EI) and environmental total factor productivity (ETFP). (ii) Mechanism analysis verifies a partial mediating effect for EI between EN_T and ETFP. (iii) Regional heterogeneity analysis illustrates the differences in the impact of environmental taxes on innovation quality. (iv) Individual heterogeneity analysis shows that the "strong Porter hypothesis" is only valid for large-scale enterprises. The results are of great importance for both government and enterprises to improve the EN_T system and optimize the allocation of resources in realistic practice.

circ_0000376 knockdown suppresses non-small cell lung cancer cell tumor properties by the miR-545-3p/PDPK1 pathway.

Non-small cell lung cancer (NSCLC) accounts for 80% of total lung cancers, which are the main killer of cancer-related death worldwide. Circular RNA (circRNA) has been found to modulate NSCLC development. However, the role of circ_0000376 in NSCLC development has been underreported. The present work showed that circ_0000376 and 3-phos-phoinositide-dependent protein kinase-1 (PDPK1) expression were dramatically increased, but miR-545-3p was decreased in NSCLC tissues and cells. circ_0000376 expression was closely associated with lymph node metastasis, tumor-node-metastasis stage, and tumor size of NSCLC patients. circ_0000376 knockdown repressed NSCLC cell proliferation, migration, invasion, and glutaminolysis but induced cell apoptosis. Additionally, miR-545-3p bound to circ_0000376, and circ_0000376 regulated cell phenotypes by associating with miR-545-3p. MiR-545-3p also participated in NSCLC cell proliferation, migration, invasion, apoptosis, and glutaminolysis by targeting PDPK1. Further, circ_0000376 absence repressed tumor formation in vivo. Collectively, circ_0000376 regulated NSCLC cell tumor properties by the miR-545-3p/PDPK1 axis, suggesting that circ_0000376 could be employed as a therapeutic target for NSCLC.

A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy.

To develop an individualized gene-based risk score to predict the prognosis of muscle-invasive bladder cancer (MIBC) patients who received GC regimens. We downloaded transcriptome profiling data and clinical information from the Cancer Genome Atlas (TCGA) database. We identified 1854 survival-associated genes and then constructed the risk score based on six special genes selected from the survival-associated genes. We divided patients into high-risk and low-risk groups according to the median risk score. High-risk patients have significantly poorer overall survival than low-risk patients (log-rank test chi-square = 38.08, p = 7e-10, C-index = 0.785, se = 0.032). The risk score was evaluated by Kaplan-Meier survival curve, time-dependent ROC curves, and C-index. Multivariate Cox regression and nomogram suggested that the risk score was an independent prognostic indicator. Gene set enrichment analysis indicated that the survival-associated genes were significantly enriched in immune-related terms. Among six special genes, CHPF2, TRAV26-2, and BTF3P12 were found to be immune-related genes. In conclusion, our risk score provided an indicator to predict the prognosis of MIBC patients who received GC regimens and potential immunotherapeutic targets for MIBC.

Ethical Risk Factors and Mechanisms in Artificial Intelligence Decision Making.

While artificial intelligence (AI) technology can enhance social wellbeing and progress, it also generates ethical decision-making dilemmas such as algorithmic discrimination, data bias, and unclear accountability. In this paper, we identify the ethical risk factors of AI decision making from the perspective of qualitative research, construct a risk-factor model of AI decision making ethical risks using rooting theory, and explore the mechanisms of interaction between risks through system dynamics, based on which risk management strategies are proposed. We find that technological uncertainty, incomplete data, and management errors are the main sources of ethical risks in AI decision making and that the intervention of risk governance elements can effectively block the social risks arising from algorithmic, technological, and data risks. Accordingly, we propose strategies for the governance of ethical risks in AI decision making from the perspectives of management, research, and development.

Circular RNA circ_0003028 contributes to tumorigenesis by regulating GOT2 via miR-1298-5p in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is a common malignant tumor, with high morbidity and mortality. Circular RNA (circRNA) circ_0003028 was reported to be upregulated in NSCLC. This study is designed to explore the role and mechanism of circ_0003028 on NSCLC progression. In this work, circ_0003028, microRNA-1298-5p (miR-1298-5p), and glutamic oxaloacetic transaminase 2 (GOT2) level were detected by real-time quantitative polymerase chain reaction (RT-qPCR). The localization of circ_0003028 was analyzed by subcellular fractionation assay. Cell proliferation, colony number, cell cycle progression, apoptosis, migration, invasion, and angiogenesis were measured by Cell Counting Kit-8 (CCK-8), colony formation, flow cytometry, transwell, and tube formation assays. Protein levels of Beclin1, light chain 3 (LC3)-II/LC3-I, GOT2, proliferating cell nuclear antigen (PCNA) were examined by western blot assay. The binding relationship between miR-1298-5p and circ_0003028 or GOT2 was predicted by circular RNA Interactome or starbase and then verified by dual-luciferase reporter, RNA Immunoprecipitation (RIP), and RNA pull-down assays. The biological role of circ_0003028 on NSCLC tumor growth was examined by the xenograft tumor model in vivo. We reported that circ_0003028 and GOT2 were upregulated, and miR-1298-5p was decreased in NSCLC tissues and cells. Moreover, circ_0003028 knockdown curbed cell proliferative ability, migration, invasion, angiogenesis, and facilitate apoptosis and autophagy in NSCLC cells in vitro. Mechanical analysis discovered that circ_0003028 regulated GOT2 expression by sponging miR-1298-5p. Circ_0003028 silencing hindered the cell growth of NSCLC in vivo. Taken together, circ_0003028 knockdown could suppress NSCLC progression partly by regulating the miR-1298-5p/GOT2 axis, providing an underlying therapeutic target for NSCLC.

DNA methylation patterns of SOCS1 gene in peripheral blood identifies risk loci associated with bladder cancer based on principal component analysis.

Bladder cancer (BCa) is a common carcinoma of the urinary tract, which occurs in the bladder mucosa. In recent years, people have recognized that epigenetic changes such as DNA methylation play important roles in the development of BCa but the specific mechanism is unclear. In this study, we detected the methylation rates in the SOCS1 gene of 490 subjects (including 247 patients with BCa and 243 healthy controls) using the MassARRAY EpiTYPER system. Principal component analysis (PCA) was conducted with the aim of identifying common underlying patterns that could explain the largest part of common variance in methylation across units. A logistic regression model was used to assess the relation of SOCS1 methylation patterns with factors related to BCa risk. The methylation rates varied for different CpG units and were significantly different in BCa patients compared to controls. Six principal component factors were extracted by combining initial eigenvalue, explanatory power, and Scree Plot. After adjusting for age, gender, family history of bladder cancer, smoking, and drinking, we observed that Factor 1 (OR=0.051, 95% CI: 0.015-0.178, p<0.001), Factor 2 (OR=0.146, 95% CI: 0.073-0.295, p<0.001), Factor 3 (OR=0.346, 95% CI: 0.198-0.606, p<0.001), and Factor 4 (OR=0.270, 95% CI: 0.135-0.537, p<0.001) were associated with BCa. Based on follow-up results, we found that the 1-, 3-, 5-year survival rates in the hypermethylated group were lower than in the hypomethylated group. We found that several CpG units in methylation patterns were associated with the incidence of BCa showing the important DNA methylation patterns for BCa pathogenesis. Our findings provided new insights into understanding this disease and new potential targets for therapeutic intervention for BCa patients in the future.

Aberrant Methylation of Suppressor of Cytokine Signaling 1 (SOCS1) Gene as a Biomarker for Early Prediction and Diagnosis of Bladder Cancer.

BACKGROUND: SOCS1 protein, the negative regulatory protein of the Janus kinase (JAK)/signal transducers and activators of transcription (STAT) signaling pathway, may inhibit signaling of JAK-STAT pathway by several cytokines and has tumor suppressor activity. Methylation of CpG island in the promoter region of SOCS1 gene has often been shown to inactivate the SOCS1 gene in certain human cancers. However, the precise role of SOCS1 in bladder cancer is unclear. METHODS: Two hundred forty-seven patients with BCa and 243 healthy controls were enrolled from Tumour Hospital Affiliated to Harbin Medical University, Hongqi Hospital Affiliated to Mudanjiang Medical University, and Mudanjiang Tumour Hospital from September 2013 to March 2019. The methylation rate in the promoter region of the SOCS1 among all participants were detected using the MassARRAY EpiTYPER system. A ROC curve was set out to analyze SOCS1 gene promoter CpG island methylation for BCa diagnosis. RESULTS: There was a significantly higher methylation rate in BCa compared to controls. Then we assessed the methylation rate of different CpG islands in SOCS1 gene among BCa cases and normal controls. Methylation rate was shown to vary among different CpG islands. The methylation rates of CpG islands were shown to vary among different grades. We observed that the methylation rate of different CpG islands vary according to pathological grades. CONCLUSIONS: Our study demonstrates that aberrant methylation of CpG island in the promoter region of SOCS1 gene may be involved in occurrence, progression, and prognosis of BCa and, thus, may serve as an independent diagnosis and prognostic biomarker.

Mangiferin Improved Palmitate-Induced-Insulin Resistance by Promoting Free Fatty Acid Metabolism in HepG2 and C2C12 Cells via PPARα: Mangiferin Improved Insulin Resistance.

Elevated free fatty acid (FFA) is a key risk factor for insulin resistance (IR). Our previous studies found that mangiferin could decrease serum FFA levels in obese rats induced by a high-fat diet. Our research was to determine the effects and mechanism of mangiferin on improving IR by regulating FFA metabolism in HepG2 and C2C12 cells. The model was used to quantify PA-induced lipid accumulation in the two cell lines treated with various concentrations of mangiferin simultaneously for 24 h. We found that mangiferin significantly increased insulin-stimulated glucose uptake, via phosphorylation of protein kinase B (P-AKT), glucose transporter 2 (GLUT2), and glucose transporter 4 (GLUT4) protein expressions, and markedly decreased glucose content, respectively, in HepG2 and C2C12 cells induced by PA. Mangiferin significantly increased FFA uptake and decreased intracellular FFA and triglyceride (TG) accumulations. The activity of the peroxisome proliferator-activated receptor α (PPARα) protein and its downstream proteins involved in fatty acid translocase (CD36) and carnitine palmitoyltransferase 1 (CPT1) and the fatty acid ß-oxidation rate corresponding to FFA metabolism were also markedly increased by mangiferin in HepG2 and C2C12 cells. Furthermore, the effects were reversed by siRNA-mediated knockdown of PPARα. Mangiferin ameliorated IR by increasing the consumption of glucose and promoting the FFA oxidation via the PPARα pathway in HepG2 and C2C12 cells.

A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation.

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

A novel stock forecasting model based on High-order-fuzzy-fluctuation Trends and Back Propagation Neural Network.

In this paper, we propose a hybrid method to forecast the stock prices called High-order-fuzzy-fluctuation-Trends-based Back Propagation(HTBP)Neural Network model. First, we compare each value of the historical training data with the previous day's value to obtain a fluctuation trend time series (FTTS). On this basis, the FTTS blur into fuzzy time series (FFTS) based on the fluctuation of the increasing, equality, decreasing amplitude and direction. Since the relationship between FFTS and future wave trends is nonlinear, the HTBP neural network algorithm is used to find the mapping rules in the form of self-learning. Finally, the results of the algorithm output are used to predict future fluctuations. The proposed model provides some innovative features:(1)It combines fuzzy set theory and neural network algorithm to avoid overfitting problems existed in traditional models. (2)BP neural network algorithm can intelligently explore the internal rules of the actual existence of sequential data, without the need to analyze the influence factors of specific rules and the path of action. (3)The hybrid modal can reasonably remove noises from the internal rules by proper fuzzy treatment. This paper takes the TAIEX data set of Taiwan stock exchange as an example, and compares and analyzes the prediction performance of the model. The experimental results show that this method can predict the stock market in a very simple way. At the same time, we use this method to predict the Shanghai stock exchange composite index, and further verify the effectiveness and universality of the method.

A Forecasting Model Based on High-Order Fluctuation Trends and Information Entropy.

Most existing high-order prediction models abstract logical rules that are based on historical discrete states without considering historical inconsistency and fluctuation trends. In fact, these two characteristics are important for describing historical fluctuations. This paper proposes a model based on logical rules abstracted from historical dynamic fluctuation trends and the corresponding inconsistencies. In the logical rule training stage, the dynamic trend states of up and down are mapped to the two dimensions of truth-membership and false-membership of neutrosophic sets, respectively. Meanwhile, information entropy is employed to quantify the inconsistency of a period of history, which is mapped to the indeterminercy-membership of the neutrosophic sets. In the forecasting stage, the similarities among the neutrosophic sets are employed to locate the most similar left side of the logical relationship. Therefore, the two characteristics of the fluctuation trends and inconsistency assist with the future forecasting. The proposed model extends existing high-order fuzzy logical relationships (FLRs) to neutrosophic logical relationships (NLRs). When compared with traditional discrete high-order FLRs, the proposed NLRs have higher generality and handle the problem caused by the lack of rules. The proposed method is then implemented to forecast Taiwan Stock Exchange Capitalization Weighted Stock Index and Heng Seng Index. The experimental conclusions indicate that the model has stable prediction ability for different data sets. Simultaneously, comparing the prediction error with other approaches also proves that the model has outstanding prediction accuracy and universality.

Methylation of the suppressor of cytokine signaling 3 gene (SOCS3) in bladder cancer.

BACKGROUND: It has been identified consequences of dysregulation of JAK-STAT signalling, particularly in regard to JAK-STAT signalling that has been shown to have roles in the oncogenesis of several cell types. SOCS3 protein, the negative regulatory protein of JAK-STAT signaling pathway, may also plays critical regulatory roles in cancer initiation and progression. SOCS3 promoter hypermethylation has often been identified in human cancers; however, the precise role of SOCS3 in bladder cancer is unclear. METHODS: The methylation status of the SOCS3 was analyzed in an age (±5 years) and sex-matched case-control study, including 112 bladder cancer cases and 118 normal controls, using the MassARRAY EpiTYPER system. RESULTS: Methylation rate of JAK2, SOCS3 and STAT3 gene were shown to vary among different CpG island. The methylation rate of SOCS3 gene was also much higher in BCa than in normal control participants, but the methylation rate of JAK2, STAT3 gene weren't different in Bca and normal control participants. CONCLUSIONS: Our study demonstrates that promoter hypermethylation of SOCS3 gene is associated with BCa and thus, may serve as an independent prognostic biomarker.

Association of selenoprotein S gene polymorphism with ischemic stroke in a Chinese case-control study.

Previous studies showed that selenoprotein S (SELS) was associated with a range of inflammatory markers, and its gene expression was influenced by a polymorphism in the promoter region. The genetic basis of the ischemic stroke has now been largely determined, so the aim of the study was to examine the role of SELS genetic variants in the ischemic stroke risk in a Chinese population. We conducted a case-control study with 239 ischemic stroke patients and 240 controls. Two single-nucleotide polymorphisms (SNPs) in SELS genes were analyzed for association with the risk of ischemic stroke in the Chinese Han population. No evidence of ischemic stroke association was observed with the SNP rs34713741. Interestingly, the strongest evidence showed that SELS SNP rs4965814 was associated with ischemic stroke (P < 0.05). We found a significant association with increased ischemic stroke risk in women carrying the CC genotype of rs4965814 [hazard ratio: 2.43(1.03-5.75)]; a similar trend was also found in men carrying the TC genotype of rs4965814 [hazard ratio: 1.81(1.06-3.08)]. SNP rs4965814 of SELS may affect the susceptibility to ischemic stroke. Understanding the inflammatory mechanisms of ischemic stroke may give new therapeutic targets to pharmacologists.

Determination of purine contents in different parts of pork and beef by high performance liquid chromatography.

Determination of adenine, hypoxanthine, guanine and xanthine in different parts of pork and beef using high performance liquid chromatography was described. Chromatographic separation was carried out on Waters Atlantis T3 column (4.6 mm × 250 mm × 5 µm) with column temperature at 30 °C. The mobile phase contained 99% 10.0 mmol/L ammonium formate solution at pH 3.6 and 1.0% methanol. Chromatography was achieved at a flow rate of 1.0 mL/min and detection wavelength at 254 nm. The results indicated that total purine amounts in pork rump and beef sirloin were higher than those in other parts (P<0.05). The principal purine bases were hypoxanthine and adenine, and hypoxanthine content was the most highest in all samples (P<0.05). As pork rump and beef sirloin contain considerable amounts of total purine and uricogenic purine base, we suggest that excess consumption of them be avoid, whereas pork loin chop and beef rib eye are more suitable for a low-purine diet.