Plastic regulates its co-pyrolysis process with biomass: Influencing factors, model calculations, and mechanisms

Co-pyrolysis of plastics and biomass can effectively improve the quality of bio-oil and solve the problem of plastic pollution. However, synergistic effect of co-pyrolysis on kinetics and the role of biomass H/Ceff in co-pyrolysis are still not conclusive. In this work, the co-pyrolysis synergistic effects of three different hydrogen-to-carbon ratio (H/Ceff) of biomass-rice husk (RH), sugarcane bagasse (SUG), and poplar wood (PW) with hydrogen-rich polypropylene (PP) were studied using a thermogravimetric method. The total synergy degree (φ) and the difference between experimental and theoretical weight losses (ΔW) were defined, and the activation energies of various experimental materials were calculated by the isoconversional method. The results showed that the addition of PP reduced the dependence of product species on biomass H/Ceff during co-pyrolysis. The synergistic effect of biomass and PP was related to biomass types, pyrolysis temperature, and mass ratio of biomass to PP. The mixture of SUG and PP showed positive synergistic effect at all mass ratios. Simultaneously, at the low temperature of pyrolysis, the synergistic effect is inhibited in all mixtures, which might be due to the melting of PP. Kinetic analysis showed that the activation energy could be reduced by 11.14–31.78% by co-pyrolysis with biomass and PP. A multi-step mechanism was observed in both the pyrolysis of a single sample and the co-pyrolysis of a mixture, according to Criado’s schematic analysis

Inhibition the ubiquitination of ENaC and Na,K-ATPase with erythropoietin promotes alveolar fluid clearance in sepsis-induced acute respiratory distress syndrome

Sepsis-induced acute respiratory distress syndrome (ARDS) causes significant fatalities worldwide and lacks pharmacological intervention. Alveolar fluid clearance (AFC) plays a pivotal role in the remission of ARDS and is markedly impaired in the pathogenesis of ARDS. Here, we demonstrated that erythropoietin could effectively ameliorate lung injury manifestations and lethality, restore lung function and promote AFC in a rat model of lipopolysaccharide (LPS)-induced ARDS. Moreover, it was proven that EPO-induced restoration of AFC occurs through triggering the total protein expression of ENaC and Na,K-ATPase channels, enhancing their protein abundance in the membrane, and suppressing their ubiquitination for degeneration. Mechanistically, the data indicated the possible involvement of EPOR/JAK2/STAT3/SGK1/Nedd4–2 signaling in this process, and the pharmacological inhibition of the pathway markedly eliminated the stimulating effects of EPO on ENaC and Na,K-ATPase, and subsequently reversed the augmentation of AFC by EPO. Consistently, in vitro studies of alveolar epithelial cells paralleled with that EPO upregulated the expression of ENaC and Na,K-ATPase, and patch-clamp studies further demonstrated that EPO substantially strengthened sodium ion currents. Collectively, EPO could effectively promote AFC by improving ENaC and Na,K-ATPase protein expression and abundance in the membrane, dependent on inhibition of ENaC and Na,K-ATPase ubiquitination, and resulting in diminishing LPS-associated lung injuries

CLSTM-AR-Based Multi-Dimensional Feature Fusion for Multi-Energy Load Forecasting

Integrated Energy Systems (IES) are an important way to improve the efficiency of energy, promote closer connections between various energy systems, and reduce carbon emissions. The transformation between electricity, heating, and cooling loads into each other makes the dynamic characteristics of multiple loads more complex and brings challenges to the accurate forecasting of multi-energy loads. In order to further improve the accuracy of IES short-term load forecasting, we propose the Convolutional Neural Network, the Long Short-Term Memory Network, and Auto-Regression (CLSTM-AR) combined with the multi-dimensional feature fusion (MFFCLA). In detail, CLSTM can extract the coupling and periodic characteristics implied in IES load data from multiple time dimensions. AR takes load data as the input to extract features of sequential auto-correlation over adjacent time periods. Then, the diverse and effective features extracted by CLSTM, LSTM, and AR can be fused using the multi-dimensional feature fusion technique. Ultimately, the model achieves the accurate prediction of multiple loads. In conclusion, compared with other forecasting models, the case study results show that MFFCLA has higher forecasting precision compared with the comparable model in the short-term multi-energy load forecasting performance of electricity, heating, and cooling. The accuracy of MFFCLA can help to optimize and dispatch IES to make better use of renewable energy

CLSTM-AR-Based Multi-Dimensional Feature Fusion for Multi-Energy Load Forecasting

Integrated Energy Systems (IES) are an important way to improve the efficiency of energy, promote closer connections between various energy systems, and reduce carbon emissions. The transformation between electricity, heating, and cooling loads into each other makes the dynamic characteristics of multiple loads more complex and brings challenges to the accurate forecasting of multi-energy loads. In order to further improve the accuracy of IES short-term load forecasting, we propose the Convolutional Neural Network, the Long Short-Term Memory Network, and Auto-Regression (CLSTM-AR) combined with the multi-dimensional feature fusion (MFFCLA). In detail, CLSTM can extract the coupling and periodic characteristics implied in IES load data from multiple time dimensions. AR takes load data as the input to extract features of sequential auto-correlation over adjacent time periods. Then, the diverse and effective features extracted by CLSTM, LSTM, and AR can be fused using the multi-dimensional feature fusion technique. Ultimately, the model achieves the accurate prediction of multiple loads. In conclusion, compared with other forecasting models, the case study results show that MFFCLA has higher forecasting precision compared with the comparable model in the short-term multi-energy load forecasting performance of electricity, heating, and cooling. The accuracy of MFFCLA can help to optimize and dispatch IES to make better use of renewable energy

Transcriptomics analysis reveals the effect of Broussonetia papyrifera L. fermented feed on meat quality traits in fattening lamb

To date, utilization of feed grains is increasing, which competes for human food. It is imperative to develop and utilize unconventional feed materials. Broussonetia papyrifera L. (B. papyrifera) is a good feeding material with high crude protein, crude fat, and low crude fiber, which is widely distributed in China. In this study, 12 Dorper ♂×Hu ♀  crossbred weaned male lambs were seleted into four groups based on the feed that ratio of the B. papyrifera fermented feed in the total mixed diet (0%, 6%, 18%, and 100%), to character the lambs’ longissimus dorsi (LD) fatty acids, morphology and transcriptome. Results showed that the muscle fiber’s diameter and area were the smallest in the 100% group. The highest content of beneficial fatty acids and the lowest content of harmful fatty acids in group 18%. RNA-seq identified 443 differentially expressed genes (DEGs) in the LD of lambs from 4 groups. Among these genes, 169 (38.1%) were up-regulated and 274 (61.9%) were down-regulated. The DEGs were mostly enriched in in fatty acid metabolism, arginine and proline metabolism, and PPAR signaling pathways. Our results provide knowledge to understand effect of different ratios of B. papyrifera fermented feed on sheep meat quality traits, also a basis for understanding of the molecular regulation mechanism of B. papyrifera fermented feed affecting on sheep meat quality

HIF-1α and HIF-2α: siblings in promoting angiogenesis of residual hepatocellular carcinoma after high-intensity focused ultrasound ablation.

BACKGROUND: High-intensity focused ultrasound (HIFU) is a widely applied to treatment for unresectable hepatocellular carcinoma. However, insufficient HIFU can result in rapid progression of the residual tumor. The mechanism of such rapid growth of the residual tumor after HIFU ablation is poorly understood. OBJECTIVE: The aim of this study was to investigate the dynamic angiogenesis of residual tumor, and the temporal effect and mechanism of the HIF-1, 2α in the residual tumor angiogenesis. METHODS: Xenograft tumors of HepG2 cells were created by subcutaneously inoculating nude mice (athymic BALB/c nu/nu mice) with hepatoma cells. About thirty days after inoculation, all mice (except control group) were treated by HIFU and assigned randomly to 7 groups according to various time intervals (1st, 3rd, 5th day (d) and 1st, 2nd, 3rd, 4th week (w)). The residual tumor tissues were obtained from the experimental groups at various time points. Protein levels of HIF-1α, HIF-2α, VEGF-A, and EphA2 were quantified by immunohistochemistry analysis and Western Blot assays, and mRNA levels measured by Q-PCR. Microvascular density was calculated with counting of CD31 positive vascular endothelial cells by immunohistochemical staining. RESULTS: Compared with the control group, protein and mRNA levels of HIF-1α reached their highest levels on the 3rd day (P<0.01), then decreased (P<0.05). HIF-2α expression reached its highest level on the 2nd week compared with control group (P<0.01), then decreased (2 w-4 w) (P<0.05). The protein and mRNA levels of VEGF-A and EphA2 in the residual tumor tissues group that received HIFU were significantly decreased until 1 week compared with the control group (P<0.01). However, the levels increased compared to controls in 2-4 weeks (P<0.05). Similar results were obtained for MVD expression (P<0.05). CONCLUSION: Insufficient HIFU ablation promotes the angiogenesis in residual carcinoma tissue over time. The data indicate that the HIF-1, 2α/VEGFA/EphA2 pathway is involved

Efficacy of H2O2 inactivated bovine virus diarrhoea virus (BVDV) type 1 vaccine in mice

Abstract Background Bovine viral diarrhea (BVD) is an acute febrile infectious disease caused by the bovine viral diarrhea virus (BVDV), which has brought huge economic losses to the world's cattle industry. At present, commercial inactivated BVDV vaccines may cause some adverse reactions during use. This study aims to develop a safer and more efficient inactivated BVDV vaccine. Methods Here, we described the generation and preclinical efficacy of a hydrogen peroxide (H2O2) inactivated BVDV type 1 vaccine in mice, and administered it separately with commercial vaccine (formaldehyde inactivated) in mice to study its efficacy. Results The BVDV type 1 IgG, IFN- γ, IL-4 and neutralizing antibody in the serum of the H2O2 inactivated vaccine group can be maintained in mice for 70 days. The IgG level reached its maximum value of 0.67 on the 42nd day, significantly higher than the commercial formaldehyde inactivated BVDV type 1 vaccine. IFN- γ and IL-4 reached their maximum values on the 28th day after immunization, at 123.16 pg/ml and 143.80 pg/ml, respectively, slightly higher than commercial vaccines, but the effect was not significant. At the same time the BVDV—1 neutralizing antibody titer reached a maximum of 12 Nu on the 42nd day post vaccination. Conclusions The H2O2 inactivated BVDV vaccine has good safety and immunogenicity, which provides a potential solution for the further development of an efficient and safe BVDV vaccine