Identification and Validation of METTL3-Related Molecules for Predicting Prognosis and Efficacy of Immunotherapy in Gastric Cancer Based on m6A Methylome and Transcriptome Sequencing Analysis

Abnormal N6-methyladenosine (m6A) modification levels caused by METTL3 have been identified to be a critical regulator in human cancers, and its roles in the immune microenvironment and the relationship between targeted therapy and immunotherapy sensitivity in gastric cancer (GC) remain poorly understood. In this study, we assessed the transcriptome-wide m6A methylation profile after METTL3 overexpression by m6A sequencing and RNA sequencing in BGC-823 cells. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to analyze the function of core targets of METTL3. Eighteen methylation core molecules were identified in GC patients by combining transcriptome and methylome sequencing. GC patients can be separated into two subtypes based on the expression of 18 methylation core molecules. Furthermore, subgroup analysis showed that patients with different subtypes had a different OS, PFS, stage, grade, and TMB. Gene set enrichment analysis (GSEA) showed that immune-related pathways were enriched among subtype A. The ESTIMATE analysis suggested that the extent of infiltration of immune cells was different in two subtypes of GC patients. Tumor Immune Dysfunction and Exclusion (TIDE) and The Cancer Immunome Atlas (TCIA) database also showed that there were significant differences in the efficacy of immunotherapy among different types of GC patients. Altogether, our results reveal that METTL3-mediated m6A methylation modification is associated with the immune microenvironment and the effects of immunotherapy in GC patients. Our findings provide novel insights for clinicians in the diagnosis and optimal treatment of GC patients

Effect of Chinese Currency Appreciation on Investments in Renewable Energy Projects in Countries along the Belt and Road

Foreign investment in renewable energy generation projects is a critical part of the Belt and Road Initiative. Under the background of the market economy, the electric energy will participate in power market competition among the countries along the line, and the sales revenue will be settled in the local currency. The exchange rate of the countries along the Belt and Road fluctuates frequently and widely, thereby posing significant risks to the investment income of the projects. To address this problem, this paper proposes the concept of Ek as the effective exchange rate expressed by the on-grid price, investment cost per kilowatt electricity generation equipment, and annual operating cost rate of unit power generation capacity. Moreover, this paper presents a model of power generation cost, income, and earning expressed by the real exchange rate. The flexibility formula of the fluctuation of power generation cost, income, profit, and internal rate of return relative(IRR) to Ek is derived, and the effect of exchange rate level and fluctuation on projects is analyzed. With the wind power projects invested by China in Pakistan taken as an example, the trend during the entire life cycle is calculated. The changes in net profit rate, IRR, and levelized cost of energy (LCOE) are calculated under Chinese currency appreciation of 10%, 20%, and 35% and 5% and 10% reduction of investment cost per unit. As the Chinese currency appreciates and the project IRR declines significantly, LCOE decreases slightly, but this decrease is not sufficient to compensate for the losses caused by the decline in IRR. The following effective measures are proposed to deal with the exchange rate fluctuation of foreign renewable energy generation projects: building energy Internet, reducing project cost, and using Chinese currency as the settlement currency. In this paper, a solution is provided for investments in renewable energy projects in regions where exchange rates fluctuate greatly

Effect of Chinese Currency Appreciation on Investments in Renewable Energy Projects in Countries along the Belt and Road

Foreign investment in renewable energy generation projects is a critical part of the Belt and Road Initiative. Under the background of the market economy, the electric energy will participate in power market competition among the countries along the line, and the sales revenue will be settled in the local currency. The exchange rate of the countries along the Belt and Road fluctuates frequently and widely, thereby posing significant risks to the investment income of the projects. To address this problem, this paper proposes the concept of Ek as the effective exchange rate expressed by the on-grid price, investment cost per kilowatt electricity generation equipment, and annual operating cost rate of unit power generation capacity. Moreover, this paper presents a model of power generation cost, income, and earning expressed by the real exchange rate. The flexibility formula of the fluctuation of power generation cost, income, profit, and internal rate of return relative(IRR) to Ek is derived, and the effect of exchange rate level and fluctuation on projects is analyzed. With the wind power projects invested by China in Pakistan taken as an example, the trend during the entire life cycle is calculated. The changes in net profit rate, IRR, and levelized cost of energy (LCOE) are calculated under Chinese currency appreciation of 10%, 20%, and 35% and 5% and 10% reduction of investment cost per unit. As the Chinese currency appreciates and the project IRR declines significantly, LCOE decreases slightly, but this decrease is not sufficient to compensate for the losses caused by the decline in IRR. The following effective measures are proposed to deal with the exchange rate fluctuation of foreign renewable energy generation projects: building energy Internet, reducing project cost, and using Chinese currency as the settlement currency. In this paper, a solution is provided for investments in renewable energy projects in regions where exchange rates fluctuate greatly

AT-CRF: A Chinese Reading Comprehension Algorithm Based on Attention Mechanism and Conditional Random Fields

Machine reading comprehension (MRC) is an important research topic in the field of Natural Language Processing (NLP). However, traditional MRC models often face challenges of information loss, lack of capability to retain long-distance dependence, and inability to deal with unanswerable questions where answers are not available in given texts. In this paper, a Chinese reading comprehension algorithm, called the Attention and Conditional Random Filed (AT-CRF) Reader, is proposed to address the above challenges. Firstly, RoBERTa, a pre-trained language model, is introduced to obtain the embedding representations of input. Then, a depthwise separable convolution neural network and attention mechanisms are used to replace the recurrent neural network for encoding. Next, the attention flow and self-attention mechanisms are used to obtain the context–query internal relation. Finally, the conditional random field is used to handle unanswerable questions and predict the correct answer. Experiments were conducted on the two Chinese machine reading comprehension datasets, CMRC2018 and DuReader-checklist, and the results showed that, compared with the baseline model, the F1 scores achieved by our AT-CRF Reader model has improved by 2.65% and 2.68%, and the EM values increased by 4.45% and 3.88%

A Novel Suppression Method for Low-Order Harmonics Causing Resonance of Induction Motor

In the motor drive system of electric vehicles, there are some nonlinear factors, such as the deadtime and the conduction voltage drop of switching devices, which will generate low-order harmonics of the stator current and the torque ripple. The frequency of the harmonic may coincide with the natural frequency of the motor, so resonance may occur on the motor drive system. To reduce the noise caused by motor resonance, the characteristics of harmonic distortion caused by the deadtime, and the conduction voltage drop of the switching device, are analyzed firstly. Then, a motor vector control strategy with specific low order is proposed. The sixth-order harmonic resonance controller in d-q axis is introduced into the control loop, and the parameter designing principle of the controller is also presented. Without affecting the control performance of the current loop, the sixth-order harmonic of the stator current near the natural frequency can be significantly suppressed. Finally, the simulation and the experiment are carried out to certify the correctness and effectiveness of the proposed harmonic suppression method

Solvent engineering of oxygen-enriched carbon dots for efficient electrochemical hydrogen peroxide production

The development of cost-effective and reliable metal-free carbon-based electrocatalysts has gained significant attention for electrochemical hydrogen peroxide (H2 O2 ) generation through a two-electron oxygen reduction reaction. In this study, a scalable solvent engineering strategy is employed to fabricate oxygen-doped carbon dots (O-CDs) that exhibit excellent performance as electrocatalysts. By adjusting the ratio of ethanol and acetone solvents during the synthesis, the surface electronic structure of the resulting O-CDs can be systematically tuned. The amount of edge active CO group was strongly correlated with the selectivity and activity of the O-CDs. The optimum O-CDs-3 exhibited extraordinary H2 O2 selectivity of up to 96.55% (n = 2.06) at 0.65 V (vs RHE) and achieved a remarkably low Tafel plot of 64.8 mV dec-1 . Furthermore, the realistic H2 O2 productivity yield of flow cell is measured to be as high as 111.18 mg h-1  cm-2 for a duration of 10 h. The findings highlight the potential of universal solvent engineering approach for enabling the development of carbon-based electrocatalytic materials with improved performance. Further studies will be undertaken to explore the practical implications of the findings for advancing the field of carbon-based electrocatalysis.The project was funded by the Shanghai Pujiang Program (21PJD022), the National Natural Science Foundation of China (No. 21901154)

Soyasaponin Ag inhibits triple-negative breast cancer progression via targeting the DUSP6/MAPK signaling

Introduction. Soyasaponins are triterpenoid glycosides discovered in soybean and have anti-cancer properties. Soyasaponin A was reported to repress estrogen-insensitive breast cancer cell proliferation. This study intends to explore the role of one isomer of soyasaponin A, i.e. soyasaponin Ag (Ssa Ag), in triple-negative breast cancer (TNBC) development. Material and methods. Bioinformatic databases were used to predict DUSP6 expression in breast cancer (BC) as well as the correlation between the expression of DUSP6 (or MAPK1, MAPK14) with the prognosis of patients with BC. The expression of DUSP6/MAPK signaling-related genes (DUSP6, MAPK1, and MAPK14) in TNBC cell lines was assessed via Western blot analysis and RT-qPCR. Levels of cell apoptosis proteins (Bax and Bcl-2) in TNBC cells were assessed via Western blot analysis. CCK-8 assay, colony formation assay, and flow cytometry analysis were conducted for the measurement of TNBC cell growth and apoptosis. In vivo xenograft assay was employed for investigating the biological influence of Ssa Ag on tumor growth. Results. The poor prognosis of BC patients was linked to the aberrant expression of DUSP6/MAPK pathwaygenes. Low expression of DUSP6 or high expression of MAPK1 (or MAPK14) was correlated to poor prognosis. DUSP6 was downregulated while MAPK1 and MAPK14 were upregulated in TNBC cells versus normal cells. Ssa Ag upregulated DUSP6 expression while downregulated MAPK1 and MAPK14 expression, inhibiting the MAPK signaling pathway. Additionally, Ssa Ag promoted in vitro TNBC cell apoptosis and restrained cell growth, and repressed in vivo tumor growth. Conclusions. Ssa Ag inhibited TNBC progression via upregulating DUSP6 and inactivating the MAPK signaling pathway

Construction of Co,N-Coordinated Carbon Dots for Efficient Oxygen Reduction Reaction

For the sake of the oxygen reduction reaction (ORR) catalytic performance, carbon dots (CDs) doped with metal atoms have accelerated their local electron flow for the past few years. However, the influence of CDs doped with metal atoms on binding sites and formation mechanisms is still uncertain. Herein, Co,N-doped CDs were facilely prepared by the low-temperature polymerization–solvent extraction strategy from EDTA-Co. The influence of Co doping on the catalytic performance of Co-CDs was explored, mainly in the following aspects: first, the pyridinic N atom content of Co-CDs significantly increased from 4.2 to 11.27 at% compared with the CDs, which indicates that the Co element in the precursor is advantageous in forming more pyridinic-N-active sites for boosting the ORR performance. Second, Co-CDs are uniformly distributed on the surface of carbon black (CB) to form Co-CDs@CB by the facile hydrothermal route, which can expose more active sites than the aggregation status. Third, the highest graphite N content of Co-CDs@CB was found, by limiting the current density of the catalyst towards the ORR. Composite nanomaterials formed by Co and CB are also used as air electrodes to manufacture high-performance zinc–air batteries. The battery has good cycle stability and realizes stable charges and discharges under different current densities. The outstanding catalytic activity of Co-CDs@CB is attributed to the Co,N synergistic effect induced by Co doping, which pioneer a new metal doping mechanism for gaining high-performance electrocatalysts