Liver cancer remains a leading cause of death, despite advances in anti-cancer therapies. To develop novel drugs, natural products are being considered as a good source for exploration. In this study, a natural product isolated from a soft coral was applied to evaluate its anti-cancer activities in hepatocellular carcinoma SK-HEP-1 cells. Sinularin was determined to have half-maximal inhibitory concentration (IC50) values of ~10 μM after 24, 48, and 72 h. The TUNEL assay and annexin V/PI staining results showed that sinularin induced DNA fragmentation and apoptosis, respectively. An investigation at the molecular level demonstrated that the expression levels of cleaved caspases 3/9 were significantly elevated at 10 μM sinularin. Mitochondrial and intracellular reactive oxygen species (ROS) levels were significantly increased following sinularin treatment, which also affected the mitochondrial membrane potential. In addition, it significantly lowered the mitochondrial respiration parameters and extracellular acidification rates at 10 μM. Further investigation showed that sinularin significantly attenuated wound healing, cell migration, and potential colony formation at 10 μM. Fluorescence microscopic observations showed that the distribution of F-actin filaments was significantly altered at 10 μM sinularin. Supported by Western blot analyses, the expression levels of AKT, p-ERK (extracellular-signal-related kinase), vimentin and VEGF were significantly down-regulated, whereas p-p38, pJNK and E-cadherin were significantly increased. Overall, at the IC50 concentration, sinularin was able to significantly affect SK-HEP-1 cells.

Herein, we report the development of a novel enzymeless electrochemical biosensor for highly specific detection of creatinine utilizing zwitterion-functionalized cuprous oxide nanoparticles (Cu2O NPs). We utilized a simple yet effective alternative to traditionally used cover layers based on the surface engineering of Cu2O NPs with N-hexadecyl-N,N dimethyl-3-ammonio-1-propanesulfonate zwitterion. This surface modification generates a pseudo-proton-exchange membrane which electrostatically hinders interfering agents from reaching the electrode surface, thus resulting in highly specific creatinine detection without loss in sensitivity. To fabricate the enzymeless biosensor, single-crystalline Cu2O NPs were synthesized via a sulfonate ion-directed seed aging protocol and were simply drop-cast onto screen-printed carbon electrodes. The shape directional effect of sulfonate ions to induce truncation in the final morphologies of the synthesized Cu2O NPs is also reported for the first time. The creatinine biosensor demonstrated fast response time (<50 s), good reproducibility (RSD = 2.8%, n = 10), and high specificity against interferents like ascorbic acid, acetic acid, glucose, urea, and uric acid. A linear response to creatinine concentration from 10 to 200 μM (R 2 = 0.9876 and LOD = 5.0 μM) was observed, which covers the entire range of physiological creatinine in human serum. Moreover, robust storage stability with a negligible decrease in signal strength over an extended storage period of 6 months was achieved, thus highlighting the practical feasibility for point-of-care testing of creatinine.

The prevalence of type 2 diabetes (T2D) has been increasing drastically in recent decades. In the same time, it has been noted that dementia is related to T2D. In the past, traditional multiple linear regression (MLR) is the most commonly used method in analyzing these kinds of relationships. However, machine learning methods (Mach-L) have been emerged recently. These methods could capture non-linear relationships better than the MLR. In the present study, we enrolled old T2D and used four different Mach-L methods to analyze the relationships between risk factors and cognitive function. Our goals were first, to compare the accuracy between MLR and Mach-L in predicting cognitive function and second, to rank importance of the risks for impaired cognitive function in T2D. There were 197 old T2D enrolled (98 men and 99 women). Demographic and biochemistry data were used as independent variables and the cognitive function assessment (CFA) score was measured by Montreal Cognitive Assessment which was regarded as independent variable. In addition to traditional MLR, random forest (RF), stochastic gradient boosting (SGB), Naïve Byer’s classifier (NB) and eXtreme gradient boosting (XGBoost) were also applied. Our results showed that all the RF, SGB, NB and XGBoost outperformed than the MLR. Education level, age, frailty score, fasting plasma glucose and body mass index were identified as the important factors from the more to the less important. In conclusion, our study demonstrated that RF, SGB, NB and XGBoost are more accurate than the MLR and in predicting CFA score. By these methods, the importance ranks of the risk factors are education level, age, frailty score, fasting plasma glucose and body mass index accordingly in a Chinese T2D cohort.

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p &lt; 0.001 for men, r = -0.24, p &lt; 0.003 for women; GE: r = 0.66, p &lt; 0.001 for men, r = 0.78, p &lt; 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Aim: Several studies have demonstrated that factors including diabetes, including insulin resistance (IR), glucose effectiveness (GE), and the first and second phase of insulin secretion (FPIS, SPIS) could easily be calculated using basic characteristics and biochemistry profiles. Aging is accompanied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging in the different phases of insulin secretion (ISEC), i.e., the first and second phase of insulin secretion (FPIS, SPIS), and glucose effectiveness (GE). Methods: In total, 169 individuals (43 men and 126 women) recruited from the data bank of the Meei-Jaw (MJ) Health Screening Center and Cardinal Tien Hospital Data Access Center between 1999 and 2008, with a similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. The IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS, and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18 to 78 years. Men had higher FPIS but lower HDL-C levels than women (2.067 ± 0.159, 1.950 ± 0.186 μU/min and 1.130 ± 0.306, 1.348 ± 0.357 mmol/dl, accordingly). The results of the Pearson correlation revealed that age was negatively related to the IR and GE in both genders (IR: r = −0.39, p < 0.001 for men, r = −0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). At the same time, the FPIS was also only found to be negatively correlated with age in females (r = −0.238, p = 0.003), but there was no difference in the SPIS and age among both genders. Conclusions: We have found that in Chinese subjects with a normal FPG level (90 mg/dL) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to the IR and GE among both genders. Only the FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest, are GE, FPIS, and IR. These results should be interpreted with caution because of the small sample size.

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