Handling multi-objective optimization problems with a comprehensive indicator and layered particle swarm optimizer

The multi-objective particle swarm optimization algorithm has several drawbacks, such as premature convergence, inadequate convergence, and inadequate diversity. This is particularly true for complex, high-dimensional, multi-objective problems, where it is easy to fall into a local optimum. To address these issues, this paper proposes a novel algorithm called IMOPSOCE. The innovations for the proposed algorithm mainly contain three crucial factors: 1) an external archive maintenance strategy based on the inflection point distance and distribution coefficient is designed, and the comprehensive indicator (CM) is used to remove the non-dominated solutions with poor comprehensive performance to improve the convergence of the algorithm and diversity of the swarm; 2) using the random inertia weight strategy to efficiently control the movement of particles, balance the exploration and exploitation capabilities of the swarm, and avoid excessive local and global searches; and 3) offering different flight modes for particles at different levels after each update to further enhance the optimization capacity. Finally, the algorithm is tested on 22 typical test functions and compared with 10 other algorithms, demonstrating its competitiveness and outperformance on the majority of test functions

Long non-coding RNA ATB promotes malignancy of esophageal squamous cell carcinoma by regulating miR-200b/Kindlin-2 axis

Esophageal squamous cell carcinoma (ESCC) is one of the leading causes of cancer-related death, especially in China. In addition, the prognosis of late stage patients is extremely poor. However, the biological significance of the long non-coding RNA lnc-ATB and its potential role in ESCC remain to be documented. In this study, we investigated the role of lnc-ATB and the underlying mechanism promoting its oncogenic activity in ESCC. Expression of lnc-ATB was higher in ESCC tissues and cell lines than that in normal counterparts. Upregulated lnc-ATB served as an independent prognosis predictor of ESCC patients. Moreover, loss-of-function assays in ESCC cells showed that knockdown of lnc-ATB inhibited cell proliferation and migration both in vitroand in vivo. Mechanistic investigation indicated that lnc-ATB exerted oncogenic activities via regulating Kindlin-2, as the anti-migration role of lnc-ATB silence was attenuated by ectopic expression of Kindlin-2. Further analysis showed that lnc-ATB functions as a molecular sponge for miR-200b and Kindlin-2. Dysregulated miR-200b/Kindlin-2 signaling mediated the oncogenic activity of lnc-ATB in ESCC. Our results suggest that lnc-ATB predicts poor prognosis and may serve as a potential therapeutic target for ESCC patients

Long Non-Coding RNA XLOC_006753 Promotes the Development of Multidrug Resistance in Gastric Cancer Cells Through the PI3K/AKT/mTOR Signaling Pathway

Background/Aims: The development of multidrug resistance (MDR), which results in disease recurrence and metastasis, is a crucial obstacle to successful chemotherapy for patients with gastric cancer (GC). Long non-coding RNAs (lncRNAs) have been found to play various roles in cancer. This study aimed to investigate the effect of XLOC_006753 on the development of MDR in GC cells. Methods: The expression levels of XLOC_006753 in GC patients and MDR GC cell lines (SGC-7901/5-FU and SGC-7901/DDP cell line) were assessed by qRT-PCR. Statistical analyses were conducted to determine the relationship between XLOC_006753 expression and clinical features and to assess the prognostic value of XLOC_006753 for overall survival and progression-free survival. Then, a CCK-8 assay was used to detect cell proliferation ability and chemosensitivity. Flow cytometry was used to detect cell cycle and cell apoptosis. A wound-healing assay and transwell assay were used to detect cell migration. The expression of markers for MDR, G1/S transition, epithelial–mesenchymal transition (EMT) and PI3K/ AKT/mTOR signaling pathway were examined by western blot. Results: XLOC_006753 was highly expressed in GC patients and MDR GC cell lines (SGC-7901/5-FU and SGC-7901/DDP cell lines), and its high expression was positively associated with metastasis, TNM stage, tumor size, and poor survival in GC patients. Moreover, XLOC_006753 was an independent prognostic biomarker of overall survival and progression-free survival for gastric cancer patients. Knocking down XLOC_006753 in the two MDR GC cell lines significantly inhibited cell proliferation, cell viability, cell cycle G1/S transition, and migration. XLOC_006753 knockdown also promoted apoptosis. Furthermore, western blots showed that XLOC_006753 knockdown decreased some markers of MDR, G1/S transition, and EMT expression, while increasing caspase9 expression and inhibiting the PI3K/AKT/mTOR signaling pathway in SGC-7901/5-FU and SGC-7901/DDP cells. Conclusion: High expression of XLOC_006753 promoted the development of MDR, which was activated by the PI3K/AKT/mTOR pathway in GC cells

Forecasting carbon dioxide emission price using a novel mode decomposition machine learning hybrid model of CEEMDAN‐LSTM

Abstract Global carbon dioxide emissions have become a great threat to economic sustainability and human health. The carbon market is recognized as the most promising mean to curb carbon emissions, furthermore, carbon price forecasting will promote the role of the carbon market in emissions reduction and achieve reduction targets at lower economic costs for emission entities. However, there are still some technical problems in carbon price prediction, such as mode mixing and larger reconstruction error for the traditional empirical mode decomposition‐type models. Therefore, the innovation of this paper is constructing a novel carbon price prediction model of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)‐long short‐term memory (LSTM), that combines the advantages of CEEMDAN in decomposing the multiscale time‐frequency carbon price signals and the LSTM model in fitting the financial signals. The results show the proposed CEEMDAN‐LSTM model has significant accuracy in predicting the complex carbon price signals. The prediction error and expectation indicators of root mean square error, mean absolute error, mean absolute percentage error, and direction accuracy are 0.638342, 0.448695, 0.015666, and 0.687631, respectively, which is better than other benchmark models. Further evidence convince that the short‐term forecasting performance is superior to the long‐term and medium‐term performance. That evidence concludes that the proposed model is a reliable method to reveal the carbon price‐driving mechanism from the point of multiscale time‐frequency characteristics. Particularly, short‐term forecasting is more accurate and can provide a valuable technical reference for reduction entities and green financial companies to judge the market situation and formulate quantitative transactions

China’s Carbon Pricing Based on Heterogeneous Tail Distribution

To address climate change, the carbon emission trading scheme has become one of the main measures to achieve emission reduction goals. One of the core problems in constructing the carbon emissions trading market is determining carbon emissions trading prices. The scientific nature of carbon emissions pricing determines the effectiveness of market regulation. Research on the influencing factors and heterogeneous tail distribution of carbon prices can increase the accuracy of carbon pricing, which is particularly important for the development of the carbon emissions trading market. The current studies have some limitations and lack heterogeneous tail description. We employ the arbitrage pricing theory-standardized standard asymmetric exponential power distribution model to analyze China’s regional carbon emissions trading price and use a genetic algorithm to solve linear programming. The results confirm the theoretical results and efficiency of the proposed algorithm. First, the new model can capture the skewness, fat-tailed distribution, and asymmetric effects of China’s regional carbon emissions trading price. Second, the macroeconomy, similar products, energy price, and exchange rate influence the carbon price fluctuation; investors’ behavior plays an important role in the heterogeneous tail distribution of carbon price. The findings provide references for the government to take appropriate measures to promote carbon emission reduction and improve the effectiveness of China’s carbon market. Therefore, our findings can help enhance emission reduction and achieve sustainable development of a low-carbon environment

Ab-initio calculation study on the formation mechanism of boron-oxygen complexes in c-Si

Boron-oxygen (B-O) complex in crystalline silicon (c-Si) solar cells is responsible for the light-induced efficiency degradation of solar cell. However, the formation mechanism of B-O complex is not clear yet. By Ab-initio calculation, it is found that the stagger-type oxygen dimer (O2ist) should be the component of B-O complex, whose movement occurs through its structure reconfiguration at low temperature, instead of its long-distance diffusion. The O2ist can form two stable “latent centers” with the Bs, which are recombination-inactive. The latent centers can be evolved into the metastable recombination centers via their structure transformation in the presence of excess carriers. These results can well explain the formation behaviors of B-O complexes in c-Si

Long non-coding RNA SNHG1 suppresses cell migration and invasion and upregulates SOCS2 in human gastric carcinoma

Gastric carcinoma (GC) is one of the most common malignancies and the third leading cause of cancer-related deaths worldwide. Long noncoding RNAs (lncRNAs) may be an important class of functional regulators involved in human gastric cancers development. In this study, we investigated the clinical significance and function of lncRNA SNHG1 in GC. SNHG1 was significantly downregulated in GC tumor tissues compared with adjacent noncancerous tissues. Overexpression of SNHG1 in BGC-823 cells remarkably inhibited not only cell proliferation, migration, invasion in vitro, but also tumorigenesis and lung metastasis in the chick embryo chorioallantoic membrane (CAM) assay in vivo. Conversely, inhibition of SNHG1 by transfection of siRNA in AGS cells resulted in opposite phenotype changes. Mechanically, SNHG1 was found interacted with ILF3, NONO and SFPQ. RNA-seq combined with bioinformatic analysis identified a serial of downstream genes of SNHG1, including SOCS2, LOXL2, LTBP3, LTBP4. Overexpression of SNHG1 induced SOCS2 expression whereas knockdown of SNHG1 decreased SOCS2 expression. In addition, knockdown of SNHG1 promoted the activation of JAK2/STAT signaling pathway. Taken together, our data suggested that SNHG1 suppressed aggressive phenotype of GC cells and regulated SOCS2/JAK2/STAT pathway

Long Non-Coding RNA LOC339059 Attenuates IL-6/STAT3-Signaling-Mediated PDL1 Expression and Macrophage M2 Polarization by Interacting with c-Myc in Gastric Cancer

Background: Long non-coding RNA (lncRNA) was identified as a novel diagnostic biomarker in gastric cancer (GC). However, the functions of lncRNAs in immuno-microenvironments have not been comprehensively explored. In this study, we explored a critical lncRNA, LOC339059, that can predict the clinical prognosis in GC related to the modulation of PD-L1 and determined its influence upon macrophage polarization via the IL-6/STAT3 pathway. Methods: To date, accumulating evidence has demonstrated that the dysregulation of LOC339059 plays an important role in the pathological processes of GC. It acts as a tumor suppressor, regulating GC cell proliferation, migration, invasion, tumorigenesis, and metastasis. A flow cytometry assay showed that the loss of LOC339059 enhanced PDL1 expression and M2 macrophage polarization. RNA sequencing, RNA pull-down, RNA immunoprecipitation, Chip-PCR, and a luciferase reporter assay revealed the pivotal role of signaling alternation between LOC339059 and c-Myc. Results: A lower level of LOC339059 RNA was found in primary GC tissues compared to adjacent tissues, and such a lower level is associated with a poorer survival period (2.5 years) after surgery in patient cohorts. Moreover, we determined important immunological molecular biomarkers. We found that LOC339059 expression was correlated with PD-L1, CTLA4, CD206, and CD204, but not with TIM3, FOXP3, CD3, C33, CD64, or CD80, in a total of 146 GC RNA samples. The gain of LOC339059 in SGC7901 and AGS inhibited biological characteristics of malignancy, such as proliferation, migration, invasion, tumorigenesis, and metastasis. Furthermore, our data gathered following the co-culture of THP-1 and U937 with genomic GC cells indicate that LOC339059 led to a reduction in the macrophage cell ratio, in terms of CD68+/CD206+, to 1/6, whereas the selective knockdown of LOC339059 promoted the abovementioned malignant cell phenotypes, suggesting that it has a tumor-suppressing role in GC. RNA-Seq analyses showed that the gain of LOC339059 repressed the expression of the interleukin family, especially IL-6/STAT3 signaling. The rescue of IL-6 in LOC339059-overexpressing cells reverted the inhibitory effects of the gain of LOC339059 on malignant cell phenotypes. Our experiments verified that the interaction between LOC339059 and c-Myc resulted in less c-Myc binding to the IL-6 promoter, leading to the inactivation of IL-6 transcription. Conclusions: Our results establish that LOC339059 acts as a tumor suppressor in GC by competitively inhibiting c-Myc, resulting in diminished IL-6/STAT3-signaling-mediated PDL1 expression and macrophage M2 polarization