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• A transfer learning model is proposed to predict heat transfer behaviors of S-CO 2. • Multi-fidelity data was sampled for pretrain and fine-tuning in transfer learning. • The transfer learning model shows higher accuracy than the deep learning model. • The transfer learning model performs well in data sparsely-distributed areas. • Discussion on R 2 for preventing "physical overfitting" was carried out. The flow and heat transfer characteristics of supercritical CO 2 are important for heat exchanger design and the safe operation of supercritical CO 2 power cycles. However, it is difficult to predict the supercritical heat transfer behaviors due to the non-monotonic temperature distribution in the case of the heat transfer deterioration (HTD) phenomenon. For low-cost, fast and accurate prediction of the supercritical heat transfer behavior, this study proposed a transfer learning model based on multi-fidelity data to achieve fast prediction with acceptable accuracy over a wide range of working conditions. This method fully utilized the low fidelity data (empirical correlations) and the medium fidelity data (numerical results) to generate a large amount of data for pretraining, in which the Latin Hypercube Sampling (LHS) method combined with the HTD correlation was used for sampling. For fine-tuning, high fidelity data from experiments was employed. Compared to the deep learning model trained directly with high fidelity dataset, the transfer learning model demonstrated vastly improved predictive performance on both the test and validation datasets. Additionally, the coefficient of determination R 2 was discussed to preventing from "physical overfitting". Instead of excessively pursuing the high R 2 (close to 1), the validity of the prediction should be concerned, especially when using the non-smooth experimental data as the dataset for model training. Moreover, the trained models and the relative files are available at Supplementary materials. [ABSTRACT FROM AUTHOR]

Background Glioblastoma multiforme (GBM) is the most prevalent primary malignancy of the brain. This study was designed to investigate whether icaritin exerts anti-neoplastic activity against GBM in vitro . Materials and methods Cell Counting Kit-8 (CCK-8) assay was utilized to examine the viability of GBM cells. The apoptotic cell population was measured by flow cytometry analysis. Cell cycle distribution was detected by flow cytometry as well. Western blot analysis was performed to examine the level of biomarker proteins in GBM cells. Levels of PPARγ mRNA and protein were detected by qPCR and western blot analysis, respectively. To examine the role of PPARγ in the anti-neoplastic activity of icaritin, PPARγ antagonist GW9662 or PPARγ siRNA was used. The activity of PPARγ was determined by DNA binding and luciferase assays. Results Our findings revealed that icaritin markedly suppresses cell growth in a dose-dependent and time-dependent fashion. The cell population at the G0/G1 phase of the cell cycle was significantly increased following icaritin treatment. Meanwhile, icaritin promoted apoptotic cell death in T98G and U87MG cells. Further investigation showed upregulation of PPARγ played a key role in the anti-neoplastic activities of icaritin. Moreover, our result demonstrated activation of AMPK signaling by icaritin mediated the modulatory effect of icaritin on PPARγ. Conclusion Our results suggest the PPARγ may mediate anti-neoplastic activities against GBM. [ABSTRACT FROM AUTHOR]

Abstract: With the Gullstrand–Le Grand eye model, the effects of various measurement errors on refractive outcomes for pseudophakic eye are studied. An equation to calculate the postoperative refractive error for pseudophakic eyes is derived. The accuracy to get a refractive error less than ca. 25D is ±0.1mm for the axial length, ±0.03mm for the radius of the corneal anterior surface, ±0.12D for the corneal power and ±0.16mm for the postoperative anterior chamber depth (ACD). An error of 1D in intraocular lens (IOL) power leads to a postoperative refractive error of −0.69D. K-reading leads to a postoperative hyperopia from 0.18 to 0.74D for eye with different refractive errors previously corrected. The constant velocity in ultrasound biometry assumption overestimates the axial length from 0.17 to 0.31mm with actual axial length ranging from 21.31 to 32.31mm. Errors in axial length, corneal power or radius of the corneal anterior surface and postoperative ACD play critical roles in determining the refractive outcomes. The constant-velocity assumption tends to overestimate the axial length. The change of the ratio of corneal anterior to the posterior surface is of minor importance for the overestimation of K-reading. [Copyright &y& Elsevier]

Ischemia/reperfusion (I/R) injury is the major cause of neurological deficit following stroke. Our previous study showed neuroprotective effects of hispidulin against cerebral ischemia reperfusion injury (IRI). In this study, we further examined the involvement of pyroptosis in this neuroprotective function. IRI was simulated in a rat model by middle cerebral artery occlusion (MCAO) surgery, and the animals were treated with different doses of hispidulin. The neurological function of the rats was evaluated by the neural function defect score (NFDS), balance beam test and limb placement test. The infarct volume and brain water content were measured 72 h following IRI. Neuronal cell survival and pyroptosis in the ischemic cortex were respectively detected by Nissl staining and TUNEL assay. The relative expression of pyroptosis markers was determined by qRT-PCR, Western blotting and ELISA as appropriate. IRI was simulated in vitro in primary cerebral astrocytes using the OGD/R procedure. AMPKα was blocked genetically or pharmacologically using siRNA and compound C respectively. CCK-8 and LDH release assays were performed using suitable kits. Hispidulin improved the neurological symptoms of the rats after IRI, in addition to decreasing the infarct size and brain edema. Mechanistically, hispidulin exerted its neuroprotective effects in vivo and in vitro by suppressing NLRP3-mediated pyroptosis by modulating the AMPK/GSK3β signaling pathway. Hispidulin is a neuroprotective agent with clinical potential against IR-induced neurological injury. [ABSTRACT FROM AUTHOR]