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Caffeine is chemically stable and not readily oxidized under normal physiological conditions but also has antioxidant effects, although the underlying molecular mechanism is not well understood. Superoxide dismutase (SOD) 2 is a manganesecontaining enzyme located in mitochondria that protects cells against oxidative stress by scavenging reactive oxygen species (ROS). SOD2 activity is inhibited through acetylation under conditions of stress such as exposure to ultraviolet (UV) radiation. Sirtuin 3 (SIRT3) is the major mitochondrial nicotinamide adenine dinucleotide (NAD +)-dependent deacetylase, which deacetylates two critical lysine residues (lysine 68 and lysine 122) on SOD2 and promotes its antioxidative activity. In this study, we investigated whether the antioxidant effect of caffeine involves modulation of SOD2 by SIRT3 using in vitro and in vivo models. The results show that caffeine interacts with SIRT3 and promotes direct binding of SIRT3 with its substrate, thereby enhancing its enzymatic activity. Mechanistically, caffeine bound to SIRT3 with high affinity (K D = 6.858 × 10 −7 M); the binding affinity between SIRT3 and its substrate acetylated p53 was also 9.03 (without NAD +) or 6.87 (with NAD +) times higher in the presence of caffeine. Caffeine effectively protected skin cells from UV irradiation-induced oxidative stress. More importantly, caffeine enhanced SIRT3 activity and reduced SOD2 acetylation, thereby leading to increased SOD2 activity, which could be reversed by treatment with the SIRT3 inhibitor 3-(1H-1,2,3-triazol-4-yl) pyridine (3-TYP) in vitro and in vivo. Taken together, our results show that caffeine targets SIRT3 to enhance SOD2 activity and protect skin cells from UV irradiation-induced oxidative stress. Thus, caffeine, as a small-molecule SIRT3 activator, could be a potential agent to protect human skin against UV radiation.

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Vip3Aa was first identified as a protein secreted during the vegetative growth phase of Bacillus thuringiensis (Bt) bacteria and which shows high insecticidal toxicity against lepidopteran insect pests (Estruch et al., 1996). Bt strains formulated as bio-insecticides only had low amounts of Vip3Aa secreted to the medium. Here, we report that Vip3Aa proteins produced by three different Bt strains, including an industrial strain, were indeed not secreted to the culture solution when grown in sporulation medium, but were retained in the mother cell compartment. In order to further investigate the Vip3Aa secretion and location, we grew the strains in rich medium. We found that in rich medium, a fraction of Vip3Aa was secreted, suggesting that Vip3Aa secretion is nutrient-dependent. Regardless of the growth conditions, we found that Vip3Aa retained in cell pellets exhibited high toxicity against Spodoptera frugiperda larvae. Hence, we speculate that the accumulation of Vip3Aa protein in the mother cell compartment under sporulation conditions could still be used as an efficient strategy for industrial production in commercial Bt strains.

Mechanical equipment in actual motion can produce noise interference with the vibration signal of rolling bearings, which have non-constant load and speed. These factors lead to variable and unstable vibration signals of rolling bearings, so it is very difficult to accurately diagnose the actual running rolling bearings. In this paper, a Residual Denoising Dynamic Adaptive Network (RDDAN) is proposed, which uses the signal knowledge under known working conditions to diagnose the rolling bearing faults under unknown working conditions. The method mainly consists of data pre-processing, feature extraction, and dynamic distribution adaptation. First, Gaussian noise is added in the data pre-processing stage to emulate the noise perturbation in the reality of rolling bearing operation. Secondly, a Deep Residual Shrinkage Network (DRSN) is used for noise reduction and feature extraction. Finally, the marginal probability distribution and conditional probability distribution under different working conditions are calculated depending on the characteristics. The network is disciplined using the relative weight of the marginal probability distribution and the conditional probability distribution. And the fault classification results are output after multiple iterations. The method was tested on the Case Western Reserve University bearing dataset and the Machine Fault Simulator Magnum bearing dataset respectively. By comparing other models, RDDAN improves the average accuracy by about 23%. The results show that RDDAN can effectively solve the problem of inconsistent data distribution in rolling bearings under operating conditions influenced by multiple variables such as noise, load, and speed.

ASAE ameliorates ovariectomy-induced bone loss in middle-aged mice by inhibiting RANKL-induced osteoclastogenesis through suppression of RANK signaling pathways and could be potentially used in mediated treatment of osteoporosis.

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