Fooyin Journal of Health Sciences最新文献

The first recorded evidence of the presence of circulating tumor cells (CTCs) in the peripheral blood of cancer patients was documented in 1869. In the past few decades, experiments have shown that cancer-related alterations can be detected at the DNA and RNA levels. Both DNA and mRNA molecular markers can be used for the detection of CTCs in patients with various malignancies. Currently, modern molecular biological and cell sorting techniques make their detection and characterization more practicable. These recent advances in our understanding should lead to the development of new molecular markers for predicting micrometastasis, as well as the identification of new targets for anti-metastatic therapies. This article reviews recent advances in molecular and clinical aspects of CTCs, especially by DNA and mRNA markers, for an early detection of colorectal cancer and other conditions.

Natto, a traditional Japanese soy food, contains nattokinase, a potent fibrinolytic enzyme with fibrinolytic properties. Statistical experimental methods were used to find the optimal conditions of nattokinase production by Bacillus natto. Effects of various nitrogen, carbon, and inorganic salt sources were investigated to select the optimal medium components. In the variable screening, a 2^5–1 fractional factorial design was used to examine the experimental variables. Screening experiments showed that glucose, KH₂PO₄, and MgSO₄ significantly affected the enzyme activity of nattokinase. Based on these results, the Box-Behnken design and response surface methodology were applied to find the optimal conditions. A regression model was built by fitting the experimental results with a second-order polynomial. The regression model was statistically significant since the coefficient of determination (R²) was 0.9352. By analyzing the response surface plots and their corresponding contour plots with the regression model, the optimal variable conditions were obtained as follows: glucose, 0.065%; KH₂PO₄, 0.0016%; and MgSO₄, 0.0016%. The corresponding maximal activity of nattokinase was 12.34 FU/mL. Confirmation experiments were performed and the results showed that the difference between the predicted and experimental values of nattokinase activity were within 15%. A theoretical approach calculated from numerical calculation is in agreement with the experimental data.

Type 2 diabetes mellitus (T2DM) is a polygenetic disease. Its incidence is increasing continuously in Taiwan as the standard of living improves. Current diabetes research is striving to identify those high at risk of T2DM through T2DM- associated gene studies. A number of techniques are available for the molecular detection of T2DM-associated genes, including polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), direct sequencing, and TaqMan genotyping. However, they are capable of analyzing only one molecular target in each experiment. In the present study, we selected eight candidate genes that are potentially associated with T2DM [angiotensinogen (AGT), sulfonylurea receptor-1 (SUR-1), peroxisome proliferators-activated receptor-γ (PPAR-γ), PPAR-γ coactivator-1 (PGC-1), calpain-10 (CAPN10), β2-adrenergic receptor (ADRB2), mannose-binding lectin (MBL2), and insulin receptor substrate-1 (IRS-1)]. We used enzymatic chip array technology, which we had previously established, and analyzed its relevance to diabetes research. We enrolled 1280 Taiwanese patients (700 with T2DM and 580 non-diabetic controls). The genes of all subjects were analyzed by the enzymatic chip array. The results were consistent with direct sequencing. On the basis of multivariate logistic-regression analysis—with adjustment for age—the following variables were associated with a significant risk of T2DM: body mass index, serum cholesterol, triglyceride level, low- and high-density lipoprotein cholesterol levels, and polymorphisms, including PGC-1 Gly482Ser, SUR1 Arg1273Arg, ADRB2 Arg16Gly, CAPN10 SNP43, AGT Met235Thr, and MLB2 Gly54Asp. The enzymatic chip array is a useful tool for multiple gene analysis in diabetes.