A Novel Oversampling Method for Imbalanced Datasets Based on Density Peaks Clustering

Imbalanced data classification is a major challenge in the field of data mining and machine learning, and oversampling algorithms are a widespread technique for re-sampling imbalanced data. To address the problems that existing oversampling methods tend to introduce noise points and generate overlapping instances, in this paper, we propose a novel oversampling method based on density peaks clustering. Firstly, density peaks clustering algorithm is used to cluster minority instances while screening outlier points. Secondly, sampling weights are assigned according to the size of clustered sub-clusters, and new instances are synthesized by interpolating between cluster cores and other instances of the same sub-cluster. Finally, comparative experiments are conducted on both the artificial data and KEEL datasets. The experiments validate the feasibility and effectiveness of the algorithm and improve the classification accuracy of the imbalanced data

Standard metabolic rate predicts growth trajectory of juvenile Chinese crucian carp (Carassius auratus) under changing food availability

Phenotypic traits vary greatly within populations and can have a significant influence on aspects of performance. The present study aimed to investigate the effects of individual variation in standard metabolic rate (SMR) on growth rate and tolerance to food-deprivation in juvenile crucian carp (Carassius auratus) under varying levels of food availability. To address this issue, 19 high and 16 low SMR (individuals were randomly assigned to a satiation diet for 3 weeks, whereas another 20 high and 16 low SMR individuals were assigned to a restricted diet (approximately 50% of satiation) for the same period. Then, all fish were completely food-deprived for another 3 weeks. High SMR individuals showed a higher growth rate when fed to satiation, but this advantage of SMR did not exist in food-restricted fish. This result was related to improved feeding efficiency with decreased food intake in low SMR individuals, due to their low food processing capacity and maintenance costs. High SMR individuals experienced more mass loss during food-deprivation as compared to low SMR individuals. Our results here illustrate context-dependent costs and benefits of intraspecific variation in SMR whereby high SMR individuals show increased growth performance under high food availability but had a cost under stressful environments (i.e., food shortage)

Prediction of protein structural class with Rough Sets

BACKGROUND: A new method for the prediction of protein structural classes is constructed based on Rough Sets algorithm, which is a rule-based data mining method. Amino acid compositions and 8 physicochemical properties data are used as conditional attributes for the construction of decision system. After reducing the decision system, decision rules are generated, which can be used to classify new objects. RESULTS: In this study, self-consistency and jackknife tests on the datasets constructed by G.P. Zhou (Journal of Protein Chemistry, 1998, 17: 729–738) are used to verify the performance of this method, and are compared with some of prior works. The results showed that the rough sets approach is very promising and may play a complementary role to the existing powerful approaches, such as the component-coupled, neural network, SVM, and LogitBoost approaches. CONCLUSION: The results with high success rates indicate that the rough sets approach as proposed in this paper might hold a high potential to become a useful tool in bioinformatics

2-Amino-4-tert-butyl-5-(2,4-dichloro­benz­yl)thia­zol-3-ium bromide

The asymmetric unit of the title compound, C14H17Cl2N2S+·Br−, contains one cation and two Br− ions with site symmetry . The dihedral angle between the planes of the thia­zol and the dichloro­phenyl rings is 77.8 (6)°. In the crystal, the ions are connected by N–H⋯Br hydrogen bonds

SIRT2, ERK and Nrf2 Mediate NAD+ Treatment-Induced Increase in the Antioxidant Capacity of PC12 Cells Under Basal Conditions

NAD+ (oxidized form of nicotinamide adenine dinucleotide) administration is highly beneficial in numerous models of diseases and aging. It is becoming increasingly important to determine if NAD+ treatment may directly increase the antioxidant capacity of cells under basal conditions. In the current study, we tested our hypothesis that NAD+ can directly enhance the antioxidant capacity of cells under basal conditions by using PC12 cells as a cellular model. We found that NAD+ treatment can increase the GSH/GSSG ratios in the cells under basal conditions. NAD+ can also increase both the mRNA and protein level of γ-glutamylcysteine ligase (γ-GCL)—a key enzyme for glutathione synthesis, which appears to be mediated by the NAD+-induced increase in Nrf2 activity. These NAD+-induced changes can be prevented by both SIRT2 siRNA and the SIRT2 inhibitor AGK2. The NAD+-induced changes can also be blocked by the ERK signaling inhibitor U0126. Moreover, the NAD+-induced ERK activation can be blocked by both SIRT2 siRNA and AGK2. Collectively, our study has provided the first evidence that NAD+ can enhance directly the antioxidant capacity of the cells under basal conditions, which is mediated by SIRT2, ERK, and Nrf2. These findings have suggested not only the great nutritional potential of NAD+, but also a novel mechanism underlying the protective effects of the NAD+ administration in the disease models: the NAD+ administration can enhance the resistance of the normal cells to oxidative insults by increasing the antioxidant capacity of the cells