A prognostic signature based on snoRNA predicts the overall survival of lower-grade glioma patients

IntroductionSmall nucleolar RNAs (snoRNAs) are a group of non-coding RNAs enriched in the nucleus which direct post-transcriptional modifications of rRNAs, snRNAs and other molecules. Recent studies have suggested that snoRNAs have a significant role in tumor oncogenesis and can be served as prognostic markers for predicting the overall survival of tumor patients. MethodsWe screened 122 survival-related snoRNAs from public databases and eventually selected 7 snoRNAs that were most relevant to the prognosis of lower-grade glioma (LGG) patients for the establishment of the 7-snoRNA prognostic signature. Further, we combined clinical characteristics related to the prognosis of glioma patients and the 7-snoRNA prognostic signature to construct a nomogram.ResultsThe prognostic model displayed greater predictive power in both validation set and stratification analysis. Results of enrichment analysis revealed that these snoRNAs mainly participated in the post-transcriptional process such as RNA splicing, metabolism and modifications. In addition, 7-snoRNA prognostic signature were positively correlated with immune scores and expression levels of multiple immune checkpoint molecules, which can be used as potential biomarkers for immunotherapy prediction. From the results of bioinformatics analysis, we inferred that SNORD88C has a major role in the development of glioma, and then performed in vitro experiments to validate it. The results revealed that SNORD88C could promote the proliferation, invasion and migration of glioma cells. DiscussionWe established a 7-snoRNA prognostic signature and nomogram that can be applied to evaluate the survival of LGG patients with good sensitivity and specificity. In addition, SNORD88C could promote the proliferation, migration and invasion of glioma cells and is involved in a variety of biological processes related to DNA and RNA

Classification related to immunogenic cell death predicts prognosis, immune microenvironment characteristics, and response to immunotherapy in lower-grade gliomas

BackgroundImmunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).Materials and methodsWe identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.Results32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.ConclusionWe established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy

Impact of recycler information sharing on supply chain performance of construction and demolition waste resource utilization

In recent years, the generation of a large amount of construction and demolition waste (CDW) has threatened the public environment and human health. The inefficient supply chain of CDW resource utilization hinders the green development of countries around the world, including China. This study aims to reveal the impact of information sharing regarding recyclers’ market demand forecast on the performance of CDW resource utilization supply chains. Therefore, this paper uses the incomplete information dynamic game method to establish and solve the decision-making model of the construction and demolition waste resource utilization supply chain under the conditions of recyclers sharing and not sharing their information. The paper then obtains the Bayesian equilibrium solution and the optimal expected profit for each party. Finally, a numerical simulation was used in order to verify the validity of the model and conclusions. The main conclusions are as follows. In the CDW resource utilization supply chain, if the recycler is more pessimistic about the market’s demand forecast, their information sharing makes the remanufacturer more motivated to improve their level of environmental responsibility. In addition, information sharing by recyclers is always beneficial in increasing the profit of the remanufacturer, but it also may make the recycler lose profit. When the efficiency of the environmental responsibility investment of remanufacturers is in a high range, information sharing increases the profits of recyclers. Conversely, information sharing has no significant effect on the profits of recyclers. The impact on the profits of the entire CDW resource utilization supply chain depends on the intensity of competition among channels, the market share of offline recycling channels and the efficiency of environmental responsibility investments

MELK is an oncogenic kinase essential for mitotic progression in basal-like breast cancer cells

Despite marked advances in breast cancer therapy, basal-like breast cancer (BBC), an aggressive subtype of breast cancer usually lacking estrogen and progesterone receptors, remains difficult to treat. In this study, we report the identification of MELK as a novel oncogenic kinase from an in vivo tumorigenesis screen using a kinome-wide open reading frames (ORFs) library. Analysis of clinical data reveals a high level of MELK overexpression in BBC, a feature that is largely dependent on FoxM1, a master mitotic transcription factor that is also found to be highly overexpressed in BBC. Ablation of MELK selectively impairs proliferation of basal-like, but not luminal breast cancer cells both in vitro and in vivo. Mechanistically, depletion of MELK in BBC cells induces caspase-dependent cell death, preceded by defective mitosis. Finally, we find that Melk is not required for mouse development and physiology. Together, these data indicate that MELK is a normally non-essential kinase, but is critical for BBC and thus represents a promising selective therapeutic target for the most aggressive subtype of breast cancer. DOI: http://dx.doi.org/10.7554/eLife.01763.00

Microstructure and soft magnetic properties of nanocrystalline Fe–Si–B–Cu–Nb soft magnetic alloy by laser annealing

The impact of laser annealing on the nanocrystalline Fe–Si–B–Cu–Nb soft magnetic alloy has been investigated. The experimental results showed that the microstructure of nanocrystals produced by laser annealing is comparable to that of furnace annealing. However, the annealing time plays a crucial role in determining the grain size and crystalline fraction evolution, thereby affecting both the coercivity and saturation magnetization. Nonetheless, the volume crystalline fraction of the laser annealed samples is lower than that of the furnace annealed ones due to the ultrahigh heating and cooling rate, which hinders the growth of nanocrystals and crystallization region. In addition, laser annealed samples demonstrate no distinct crystallization at high scanning speeds, even with noticeable changes in soft magnetic properties. Furthermore, the correlation between coercivity and grain size is examined, revealing a progressive decline in coercivity with a decrease in grain size. It is also found that the rule Hc ∝ D6 is also valid in laser annealing for relatively larger grains, whereas the rule becomes Hc ∝ D3 for smaller grains

Considering Consumers’ Green Preferences and Government Subsidies in the Decision Making of the Construction and Demolition Waste Recycling Supply Chain: A Stackelberg Game Approach

Resource utilization of construction and demolition waste (CDW) is regarded to be an important means of achieving the sustainable development of the economy and the environment. However, previous research has not fully considered the green degree of products in the demand function of CDW remanufactured products. This study aimed to clarify how consumers’ green preferences and government subsidies affect decision making in the supply chain. First, a CDW resource utilization supply chain model composed of building materials manufacturers and retailers was constructed using consumer behavior theory. Second, the optimal decision making of members under conditions of decentralized and centralized decision making was analyzed using the Stackelberg game solution. Finally, the validity of the model and conclusions were verified by numerical simulation. The main conclusions are as follows. Government subsidies have a different impact on the pricing of new building materials products and CDW remanufactured products. Under decentralized decision making, the optimal profit of the CDW resource utilization supply chain with government subsidies is higher. However, under centralized decision making, the optimal profit is also related to consumers’ green preferences. According to consumers’ green preferences, choosing different decision-making models can not only improve the total profit of the CDW resource utilization supply chain, but also improve the reuse rate of CDW