The dynamic impact approach (DIA) represents an alternative to overrepresentation analysis (ORA) for functional analysis of time-course experiments or those involving multiple treatments. The DIA can be used to estimate the biological impact of the differentially expressed genes (DEGs) associated with particular biological functions, for example, as represented by the Kyoto encyclopedia of genes and genomes (KEGG) annotations. However, the DIA does not take into account the correlated dependence structure of the KEGG pathway hierarchy. We have developed herein a path analysis model (KEGG-PATH) to subdivide the total effect of each KEGG pathway into the direct effect and indirect effect by taking into account not only each KEGG pathway itself, but also the correlation with its related pathways. In addition, this work also attempts to preliminarily estimate the impact direction of each KEGG pathway by a gradient analysis method from principal component analysis (PCA). As a result, the advantage of the KEGG-PATH model is demonstrated through the functional analysis of the bovine mammary transcriptome during lactation.

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Milling tool wear state recognition plays an important role in controlling the quality of milled parts and reducing machine tool downtime. However, the characteristics of milling process limit the accuracy and stability of tool condition monitoring (TCM) employing vibration signals. To improve this problem, this paper explores the use of vibration signals as sensing approach for recognizing tool wear states during milling operation by using the stacked generalization (SG) ensemble model. In this study, vibration signals collected during the milling process are analyzed through the time domain, frequency domain, and time-frequency domain to extract signal features. The support vector machine recursive feature elimination (SVM-RFE) algorithm is used to select the main features which are most relevant to tool wear states. The SG ensemble model based on SVM, decision tree (DT), naive Bayes (NB), and SG ensemble strategy is constructed to recognize tool wear states. The proposed method is experimental verified, and the results show that the recognition accuracy of the established SG ensemble model is 98.74% and the overall G-mean and AUC evaluation value of the model is 0.98 and 0.98, respectively. In addition, compared with other ensemble models and single models, the SG ensemble model based on vibration signals has better recognition accuracy and stability than other models.

Glioblastomas are highly malignant brain tumors. Knowledge of growth rates and growth patterns is useful for understanding tumor biology and planning treatment logistics. Based on untreated human glioblastoma data collected in Trondheim, Norway, we first fit the average growth to a Gompertz curve, then find a best fitted white noise term for the growth rate variance. Combining these two fits, we obtain a new type of Gompertz diffusion dynamics, which is a stochastic differential equation (SDE). Newly collected untreated human glioblastoma data in Seattle, US, re-verify our model. Instead of growth curves predicted by deterministic models, our SDE model predicts a band with a center curve as the tumor size average and its width as the tumor size variance over time. Given the glioblastoma size in a patient, our model can predict the patient survival time with a prescribed probability. The survival time is approximately a normal random variable with simple formulas for its mean and variance in terms of tumor sizes. Our model can be applied to studies of tumor treatments. As a demonstration, we numerically investigate different protocols of surgical resection using our model and provide possible theoretical strategies.

Background Intrauterine growth restriction (IUGR) is a major inducer of higher morbidity and mortality in the pig industry and catch-up growth (CUG) before weanling could significantly restore this negative influence. But there was limited knowledge about the underlying mechanism of CUG occurrence. Methods Eighty litters of newborn piglets were divided into normal birth weight (NBW) and IUGR groups according to birth weight. At 26 d, those piglets with IUGR but over average body weight of eighty litters of weaned piglets were considered as CUG, and the piglets with IUGR still below average body weight were considered as NCUG. This study was conducted to systemically compare the intestinal difference among NBW, CUG and NCUG weaned piglets considering the crucial role of the intestine for piglet growth. Results The results indicated that the mRNA expression of nutrients (amino acids, glucose, and fatty acids) transporters, and mitochondrial electron transport chain (ETC) I were upregulated in CUG piglets’ gut with improved morphology compared with those NCUG, as well as the ratio of P-AMPK/AMPK protein expression which is the indicator of energy metabolism. Meanwhile, CUG piglet’s gut showed higher antioxidative capacity with increased SOD and GSH-Px activity, decreased MDA levels, as well as higher mRNA expressions of Nrf2, Keap1, SOD, and GSH-Px. Furthermore, inflammatory parameters including TNF-α, IL-1β, IL-6, and IL-12 factors, and the activation of MAPK and NF-κB signaling pathways were significantly elevated in the NCUG intestine, while the protein expression of ZO-1, Occludin and Claudin-1 was reduced. The alpha diversity of fecal microbiota was higher in CUG piglets in contrast with NCUG piglets, and the increased beneficial bacteria and decreased pathogenic bacteria was also observed in CUG piglets. Conclusions CUG piglet’s intestine showed comprehensive restoration including higher nutrients transport, energy metabolism, antioxidant capacity, and intestinal physical barrier, while lower oxidative stress, inflammatory response, and pathogenic microbiota.

Frequent occurrence of intrauterine growth restriction (IUGR) causes huge economic losses in the pig industry. Accelerated catch-up growth (CUG) in the early stage of life could restore multiple adverse outcomes of IUGR offspring; however, there is little knowledge about this beneficial phenomenon. We previously found that nutrient absorption related to intestinal function was globally promoted in CUG-IUGR piglets before weaning, which might be the dominant reason for CUG, but what this alteration could lead to in subsequent liver metabolism is still unknown. Firstly, a Normal, CUG, and non-catch-up growth (NCUG) piglet model before weaning was established by dividing eighty litters of newborn piglets into normal birth weight (NBW) and IUGR groups according to birth weight, and those piglets with IUGR but above-average weanling body weight were considered CUG, and the piglets with IUGR still below average body weight were considered NCUG at weaning day (d 26). Liver samples were collected and then systematically compared in glycolipid metabolism, mitochondrial function, antioxidant status, and inflammatory status among these three different growth models. Enhanced hepatic uptake of fatty acids, diminished de novo synthesis of fatty acids, and increased oxidation of fatty acids were observed in CUG livers compared to Normal and NCUG. In contrast, the NCUG liver showed enhanced glucose uptake and gluconeogenesis compared to Normal and CUG. We also observed deteriorating hepatic vacuolation in NCUG piglets, while increasing hepatic lipid deposition in CUG piglets. Besides, the expression of genes related to mitochondrial energy metabolism and biogenesis was reduced in CUG piglets and the phosphorylation level of AMPK was significantly higher compared to Normal (p < 0.05). Moreover, NCUG liver showed decreased T-AOC (p < 0.01) and GSH-PX (p < 0.05), increased MDA concentrations (p < 0.01), upregulated phosphorylation levels of ERK and NF-κB (p < 0.05), and elevated pro-inflammatory factors IL-1β, IL-6 and TNF-α (p < 0.05) compared to Normal. Furthermore, correlation analysis revealed a significant positive correlation between glucose metabolism and inflammatory factors, while a negative correlation between mitochondrial function-related genes and fatty acid transport. NGUG piglets showed simultaneous enhancement of glucose uptake and gluconeogenesis, as well as reduced antioxidant capacity and increased inflammatory status, whereas CUG comes at the expense of impaired hepatic mitochondrial function and pathological fat accumulation.