Proteomics was used to identify a protein encoded by ORF 3a in a SARS-associated coronavirus (SARS-CoV). Immuno-blotting revealed that interchain disulfide bonds might be formed between this protein and the spike protein. ELISA indicated that sera from SARS patients have significant positive reactions with synthesized peptides derived from the 3a protein. These results are concordant with that of a spike protein-derived peptide. A tendency exists for co-mutation between the 3a protein and the spike protein of SARS-CoV isolates, suggesting that the function of the 3a protein correlates with the spike protein. Taken together, the 3a protein might be tightly correlated to the spike protein in the SARS-CoV functions. The 3a protein may serve as a new clinical marker or drug target for SARS treatment.

Diabetic wounds are recalcitrant to healing. However, the mechanism causing this dysfunction is not fully understood. High expression of matrix metalloproteinase-9 (MMP-9) is indicative of poor wound healing. In this study, we show that specificity protein-1 (Sp1), a regulator of MMP-9, binds directly to its promoter and enhances its expression. Additionally, we demonstrated that Sp1 is the direct target of two microRNAs (miRNAs), miR-129 and -335, which are significantly downregulated in diabetic skin tissues. In vitro experiments confirmed that miR-129 or -335 overexpression inhibits MMP-9 promoter activity and protein expression by targeting Sp1, whereas the inhibition of these miRNAs has the opposite effect. The beneficial role of miR-129 or miR-335 in diabetic wound healing was confirmed by the topical administration of miRNA agomirs in diabetic animals. This treatment downregulated Sp1-mediated MMP-9 expression, increased keratinocyte migration, and recovered skin thickness and collagen content. The combined treatment with miR-129 and miR-335 induced a synergistic effect on Sp1 repression and MMP-9 downregulation both in vitro and in vivo. This study demonstrates the regulatory mechanism of Sp1-mediated MMP-9 expression in diabetic wound healing and highlights the potential therapeutic benefits of miR-129 and -335 in delayed wound healing in diabetes.

Spike protein is one of the major structural proteins of severe acute respiratory syndrome-coronavirus. It is essential for the interaction of the virons with host cell receptors and subsequent fusion of the viral envelop with host cell membrane to allow infection. Some spike proteins of coronavirus, such as MHV, HCoV-OC43, AIBV and BcoV, are proteolytically cleaved into two subunits, S1 and S2. In contrast, TGV, FIPV and HCoV-229E are not. Many studies have shown that the cleavage of spike protein seriously affects its function. In order to investigate the maturation and proteolytic processing of the S protein of SARS CoV, we generated S1 and S2 subunit specific antibodies (Abs) as well as N, E and 3CL protein-specific Abs. Our results showed that the antibodies could efficiently and specifically bind to their corresponding proteins from E.coli expressed or lysate of SARS-CoV infected Vero-E6 cells by Western blot analysis. Furthermore, the anti-S1 and S2 Abs were proved to be capable of binding to SARS CoV under electron microscope observation. When S2 Ab was used to perform immune precipitation with lysate of SARS-CoV infected cells, a cleaved S2 fragment was detected with S2-specific mAb by Western blot analysis. The data demonstrated that the cleavage of S protein was observed in the lysate, indicating that proteolytic processing of S protein is present in host cells.

Based on the collected weather data from the agricultural Internet of Things (IoT) system, changes in the weather can be obtained in advance, which is an effective way to plan and control sustainable agricultural production. However, it is not easy to accurately predict the future trend because the data always contain complex nonlinear relationship with multiple components. To increase the prediction performance of the weather data in the precision agriculture IoT system, this study used a deep learning predictor with sequential two-level decomposition structure, in which the weather data were decomposed into four components serially, then the gated recurrent unit (GRU) networks were trained as the sub-predictors for each component. Finally, the results from GRUs were combined to obtain the medium- and long-term prediction result. The experiments were verified for the proposed model based on weather data from the IoT system in Ningxia, China, for wolfberry planting, in which the prediction results showed that the proposed predictor can obtain the accurate prediction of temperature and humidity and meet the needs of precision agricultural production.

The topological entropy of various gap-sets on periodic-like recurrence and Birkhoff regularity were considered in [69] but some Banach recurrence and Lyapunov regularity are not considered. In this paper we introduce five new levels on Banach recurrence and show they all carry full topological entropy, and simultaneously combine with Lyapunov regularity to get some refined theory on mixed multifractal analysis of [8,29].In this process, we strengthen Pfister and Sullivan's result of [58] from saturated property to transitively-saturated property (and from single-saturated property to transitively-convex-saturated property).

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Because the influencing factor of metastatic thyroid cancers in Graves' disease is young age, every suspicious nodule in Graves' disease patients should be evaluated and treated carefully, especially in younger patients because of the potential for metastasis.

Our findings that early postnatal sibling deprivation influences maternal licking/grooming behavior, as well as anxiety-like behavior and vulnerability to drugs in pups that have grown to adulthood, suggests that both sibling interaction and maternal behavior, play critical roles in individual development.