A novel vaccine candidate based on chimeric virus-like particle displaying multiple conserved epitope peptides induced neutralizing antibodies against EBV infection.

Epstein-Barr virus (EBV) is the causative pathogen for infectious mononucleosis and many kinds of malignancies including several lymphomas such as Hodgkin\u27s lymphoma, Burkitt\u27s lymphoma and NK/T cell lymphoma as well as carcinomas such as nasopharyngeal carcinoma (NPC) and EBV-associated gastric carcinoma (EBV-GC). However, to date no available prophylactic vaccine was launched to the market for clinical use

A Cocktail Nanovaccine Targeting Key Entry Glycoproteins Elicits High Neutralizing Antibody Levels Against EBV Infection

Epstein-Barr virus (EBV) infects more than 95% of adults worldwide and is closely associated with various malignancies. Considering the complex life cycle of EBV, developing vaccines targeting key entry glycoproteins to elicit robust and durable adaptive immune responses may provide better protection. EBV gHgL-, gB- and gp42-specific antibodies in healthy EBV carriers contributed to sera neutralizing abilities in vitro, indicating that they are potential antigen candidates. To enhance the immunogenicity of these antigens, we formulate three nanovaccines by co-delivering molecular adjuvants (CpG and MPLA) and antigens (gHgL, gB or gp42). These nanovaccines induce robust humoral and cellular responses through efficient activation of dendritic cells and germinal center response. Importantly, these nanovaccines generate high levels of neutralizing antibodies recognizing vulnerable sites of all three antigens. IgGs induced by a cocktail vaccine containing three nanovaccines confer superior protection from lethal EBV challenge in female humanized mice compared to IgG elicited by individual NP-gHgL, NP-gB and NP-gp42. Importantly, serum antibodies elicited by cocktail nanovaccine immunization confer durable protection against EBV-associated lymphoma. Overall, the cocktail nanovaccine shows robust immunogenicity and is a promising candidate for further clinical trials

Badanie wpływu wielkości cząstek na dokładność identyfikacji węgla i skały płonnej

In order to explore the impact of coal and gangue particle size changes on recognition accuracy and to improve the single particle size of coal and gangue identification accuracy of sorting equipment, this study established a database of different particle sizes of coal and gangue through image gray and texture feature extraction, using a relief feature selection algorithm to compare different particle size of coal and gangue optimal features of the combination, and to identify the points and particle size of coal and gangue. The results show that the optimal features and number of coal and gangue are different with different particle sizes. Based on visible-light coal and gangue separation technology, the change of coal and gangue particle size cause fluctuations in the recognition accuracy, and the fluctuation of recognition accuracy will gradually decrease with increases in the number of features. In the process of particle size classification, if the training model has a single particle size range, the recognition accuracy of each particle size range is low, with the highest recognition accuracy being 98% and the average recognition rate being only 97.2%. The method proposed in this paper can effectively improve the recognition accuracy of each particle size range. The maximum recognition accuracy is 100%, the maximum increase is 4%, and the average recognition accuracy is 99.2%. Therefore, this method has a high practical application value for the separation of coal and gangue with single particle size.W celu zbadania wpływu zmian wielkości cząstek węgla i skały płonnej na dokładność rozpoznawania oraz poprawienia dokładności identyfikacji pojedynczych cząstek węgla i skały płonnej przez urządzenia sortujące, w ramach tej pracy utworzono bazę danych różnych rozmiarów cząstek węgla i skały płonnej za pomocą obrazów szarych i ekstrakcję cech tekstury przy użyciu algorytmu wyboru cech reliefowych w celu porównania różnych rozmiarów cząstek węgla i skały płonnej przy optymalnych cechach kombinacji oraz identyfikacji punktów i wielkości cząstek węgla i skały płonnej. Wyniki pokazują, że optymalne liczby cech węgla i skały płonnej są różne dla różnych rozmiarów cząstek. W oparciu o technologię separacji węgla i skały płonnej w świetle widzialnym, zmiana wielkości cząstek węgla i skały płonnej powoduje fluktuacje dokładności rozpoznawania, a te z kolei będą stopniowo zmniejszać się wraz ze wzrostem liczby cech. W procesie klasyfikacji wielkości cząstek, jeśli model uczący ma jeden zakres wielkości cząstek, dokładność rozpoznawania każdego zakresu wielkości cząstek jest niska, przy czym najwyższa dokładność rozpoznawania wynosi 98%, a średni wskaźnik rozpoznawania wynosi tylko 97,2%. Metoda zaproponowana w tym artykule może skutecznie poprawić dokładność rozpoznawania każdego zakresu wielkości cząstek. Maksymalna dokładność rozpoznawania wynosi 100%, maksymalny wzrost to 4%, a średnia dokładność rozpoznawania to 99,2%. Dlatego ta metoda ma dużą praktyczną wartość użytkową do oddzielania węgla i skały płonnej według rozmiaru pojedynczej cząstki

Integrated optimization modelling framework for low-carbon and green regional transitions through resource-based industrial symbiosis

Abstract The development and utilization of bulk resources provide the basic material needs for industrial systems. However, most current resource utilization patterns are unsustainable, with low efficiencies and high carbon emissions. Here, we report a quantitative tool for resource-based industries to facilitate sustainable and low-carbon transitions within the regional economy. To evaluate the effectiveness of this tool, the saline Qinghai Lake region was chosen as a case study. After optimizing the industrial structure, the benefits of economic output, resource efficiency, energy consumption, solid waste reduction, and carbon emission reduction can be obtained. The scenario analyses exhibit disparities in different transition paths, where the carbon mitigation, economic output, and resource efficiency that benefit from optimal development paths are significantly better than those of the traditional path, indicating the urgency of adopting cleaner technology and industrial symbiosis for regional industries

Informal Institutions and Herders’ Grazing Intensity Reduction Behavior: Evidence from Pastoral Areas in China

Overgrazing is the key factor that has exacerbated grassland degradation in China’s pastoral regions. Herder’s grazing-based livestock production behavior becomes important to grassland conservation. Several formal environmental institutions and policies exist to improve grassland degradation; however, there remain contradicting conclusions regarding the contribution of these policies. Informal institutions become major instruments that might encourage herder’s behavior on overgrazing. Using village rules and conventions (VRC) as a proxy for informal institutions, the article attempts to scrutinize whether the VRC emerge to respond to herders’ willingness to reduce grazing intensity for grassland conservation and elicit factors affecting their reduction behavior using a Double-Hurdle model. Based on a survey of 193 respondents in Inner Mongolia and Xinjiang Autonomous regions of China, the empirical results provide evidence that VRC is effective in reducing herders’ grazing intensity. In detail, the VRC in written form and an unchanging context within five years could significantly improve herders’ willingness to reduce grazing intensity. Herders who consider the VRC as an important impact to their livestock production observe an increased reduction degree of grazing intensity. Additionally, variables referring to herder’s education and religious belief play a significant role in the reduction degree of grazing intensity. Our findings highlight the importance of VRC in controlling herders’ overgrazing behavior

A profile analysis of problematic smartphone usage among college students during coronavirus disease 2019: Relations with the impact of news reports

The coronavirus disease 2019 (COVID-19) outbreak was the first pandemic to occur in a fully globalized society. The aims of the study were to explore the state of problematic smartphone use (PSU) and its risk factors during this incident. A total of 77,211 college students were surveyed online during the COVID-19 pandemic. Conducting latent profile analysis (LPA), we found the most support for a three-class model of subgroups: over-use group (17.3% of the sample), moderate-use group (54.8% of the sample), mild-use group (27.9% of the sample). The results of multinomial logistic regression show that college students who experienced an extreme negative impact from news reports were more likely to be included in the over-use group than in the mild-use group. These results providing insights that may help foster and develop appropriate and effective solutions to prevent PSU among college students during crises, such as reducing the coverage of negative news report

Synthesis of LiNiO2 by two-step solid-state method

LiNiO2 was prepared through two-step solid-state reaction by mechanochemical method and heat treatment, using LiOH (Li2CO3) and Ni(OH)2 as starting materials. The influence of grinding speed and time, heat treatment time, and starting materials on the structure of LiNiO2 was studied. The as-milled samples and products were characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). The results show that uniform as-milled samples can be obtained at grinding speed of 580 rpm for 0.5 h, using LiOH and Ni(OH)2 as raw materials. Perfect crystal LiNiO2 has been prepared by calcining the as-milled samples at 700 °C for 15 h. Composite material powders consisting of Li2Ni8O10 and LiNiO2 have been obtained using Li2CO3 as lithium source

Targeting MYH9 represses USP14-mediated NAP1L1 deubiquitination and cell proliferation in glioma

Abstract Myosin heavy chain 9 (MYH9) plays an important role in a number of diseases. Nevertheless, the function of MYH9 in glioma is unclear. The present research aimed to investigate the role of MYH9 in glioma and determine whether MYH9 is involved in the temozolomide chemoresistance of glioma cells. Our results showed that MYH9 increased the proliferation and temozolomide resistance of glioma cells. The mechanistic experiments showed that the binding of MYH9 to NAP1L1, a potential promoter of tumor proliferation, inhibited the ubiquitination and degradation of NAP1L1 by recruiting USP14. Upregulation of NAP1L1 increased its binding with c-Myc and activated c-Myc, which induced the expression of CCND1/CDK4, promoting glioma cell temozolomide resistance and proliferation. Additionally, we found that MYH9 upregulation was strongly related to patient survival and is therefore a negative factor for patients with glioma. Altogether, our results show that MYH9 plays a role in glioma progression by regulating NAP1L1 deubiquitination. Thus, targeting MYH9 is a potential therapeutic strategy for the clinical treatment of glioma in the future

Effects of Insulin on Proliferation, Apoptosis, and Ferroptosis in Primordial Germ Cells via PI3K-AKT-mTOR Signaling Pathway

Primordial germ cells (PGCs) are essential for the genetic modification, resource conservation, and recovery of endangered breeds in chickens and need to remain viable and proliferative in vitro. Therefore, there is an urgent need to elucidate the functions of the influencing factors and their regulatory mechanisms. In this study, PGCs collected from Rugao yellow chicken embryonic eggs at Day 5.5 were cultured in media containing 0, 5, 10, 20, 50, and 100 μg/mL insulin. The results showed that insulin regulates cell proliferation in PGCs in a dose-dependent way, with an optimal dose of 10 μg/mL. Insulin mediates the mRNA expression of cell cycle-, apoptosis-, and ferroptosis-related genes. Insulin at 50 μg/mL and 100 μg/mL slowed down the proliferation with elevated ion content and GSH/oxidized glutathione (GSSG) in PGCs compared to 10 μg/mL. In addition, insulin activates the PI3K/AKT/mTOR pathway dose dependently. Collectively, this study demonstrates that insulin reduces apoptosis and ferroptosis and enhances cell proliferation in a dose-dependent manner via the PI3K-AKT-mTOR signaling pathway in PGCs, providing a new addition to the theory of the regulatory role of the growth and proliferation of PGC in vitro cultures

The Protective Effects of HJB-1, a Derivative of 17-Hydroxy-Jolkinolide B, on LPS-Induced Acute Distress Respiratory Syndrome Mice

Acute respiratory distress syndrome (ARDS),which is inflammatory disorder of the lung, which is caused by pneumonia, aspiration of gastric contents, trauma and sepsis, results in widespread lung inflammation and increased pulmonary vascular permeability. Its pathogenesis is complicated and the mortality is high. Thus, there is a tremendous need for new therapies. We have reported that HJB-1, a 17-hydroxy-jolkinolide B derivative, exhibited strong anti-inflammatory effects in vitro. In this study, we investigated its impacts on LPS-induced ARDS mice. We found that HJB-1 significantly alleviated LPS-induced pulmonary histological alterations, inflammatory cells infiltration, lung edema, as well as the generation of inflammatory cytokines TNF-α, IL-1β and IL-6 in BALF. In addition, HJB-1 markedly suppressed LPS-induced IκB-α degradation, nuclear accumulation of NF-κB p65 subunit and MAPK phosphorylation. These results suggested that HJB-1 improved LPS-induced ARDS by suppressing LPS-induced NF-κB and MAPK activation