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Background Proprotein convertase subtilisin/kexin type 9 (PCSK9) is the ninth member of the proprotein convertase family that regulates lipoprotein homeostasis and altered PCSK9 expression was reportedly associated with tumor development and progression. This study assessed PCSK9 expression and functions in human colon cancer and then explored the underlying molecular events. Methods Colon cancer tissues were utilized for analysis of PCSK9 expression for association with clinicopathological factors from patients by immunohistochemistry assay. Manipulation of PCSK9 expression was assessed in vitro and in vivo for colon cancer cell proliferation, migration, and invasion using cell viability CCK-8, Transwell tumor cell migration and invasion, and wound-healing assays. Next, proteomic analysis, Western blot, qRT-PCR and Flow cytometry were conducted to assess downstream targets and tumor cell-derived PCSK9 action on macrophage polarization. Results PCSK9 expression was upregulated in colon cancer tissues versus the normal tissues, and associated with advanced tumor pathological grade. Knockdown of PCSK9 expression reduced colon cancer cell proliferation, migration, and invasion and suppressed tumor metastasis in vivo. PCSK9 directly or indirectly upregulated Snail 1 and in turn to downregulate E-cadherin expression, but upregulate N-cadherin and MMP9 levels and thereafter, to induce colon cancer cell epithelial-mesenchymal transition (EMT) process and activated PI3K/AKT signaling. However, PCSK9 overexpression showed the inverse effects on colon cancer cells. Knockdown of PCSK9 expression inhibited M2 macrophage polarization, but also promoted M1 macrophage polarization by reduction of lactate, protein lactylation and macrophage migration inhibitory factor (MIF) levels. Conclusion PCSK9 played an important role in the progression and metastasis of colon cancer by regulation of tumor cell EMT and PI3K/AKT signaling and in the phenotypic polarization of macrophages by mediating MIF and lactate levels. Targeting PCSK9 expression or activity could be used to effectively control colon cancer.

In Ten Little Indians, Sherman Alexie presents nine poignant and emotionally resonant stories about Native Americans’ struggle with alienation and stereotypes. Instead of focusing merely on the ethnic identity of American Indians, Alexie writes about a particular group of people sharing similar circumstances and addresses their common humanity, namely their search for love and respect in urban spaces. Alexie questions the authenticity of Indian identity and asserts that a “mental reservation” exists in the minds of Indian people which significantly influences their perceptions of self and community. Race, as a medium of seeing “the other” permeates U.S. society, especially in the wake of terrorist attacks. However, racial profiling has proven to be an ineffective means of detecting criminals and criminal activities, and has obstructed social relationships, bringing emotions of fear, loneliness and grief to urban Indians. In response to the modernity crisis, Alexie explores the American Indian cosmopolitanism in Ten Little Indians, and envisions a human social community based on reciprocity and mutual respect. His concerns regarding ordinary people’s life experiences and their ways of forming healthy relationships exhibit his considerable hope for “the triumph of the ordinary”.

Carbon neutrality is a critical pathway to achieving a sustainable future. Investigating the driving factors for carbon neutrality can provide empirical evidence to support ecosystem protection. Prior studies used mean regression to investigate carbon neutrality, concealing the heterogeneity of carbon neutrality. In this paper, we introduce a dynamic spatial Durbin quantile regression (DSDQR) model along with its estimation method, and derive the marginal effect formulas for independent variables at different quantiles. Then we apply this methodology to examine the impact mechanisms of environmental governance pressure, economic growth, and their interaction effects on carbon neutrality performance using Chinese provincial data spanning 2011–2022. Key findings include: (1) Temporal, spatial, and path dependencies in carbon neutrality performance are prevalent across nearly all provinces. (2) Environmental governance pressure exhibits an inhibitory short-term effect on carbon neutrality in provinces at medium and low quantiles, while it has a positive long-term impact in high quantile provinces. (3) Economic growth generally hinders carbon neutrality performance in most provinces. However, economic growth in high quantile provinces exerts a positive long-term influence on carbon neutrality performance after the COVID-19 pandemic. (4) The interaction between environmental governance pressure and economic growth demonstrates a significant positive short-term impact on carbon neutrality performance post-epidemic, yet it has a negative long-term effect in high quantile provinces. Finally, this article calls for differentiated decarbonization strategies based on provincial carbon neutrality development stages.

In this paper, we compared the concept of agricultural drought and its relationship with other types of droughts and reviewed the progress of research on agricultural drought monitoring indices on the basis of station data and remote sensing. Applicability and limitations of different drought monitoring indices were also compared. Meanwhile, development history and the latest progress in agricultural drought monitoring were evaluated through statistics and document comparison, suggesting a transformation in agricultural drought monitoring from traditional single meteorological monitoring indices to meteorology and remote sensing-integrated monitoring indices. Finally, an analysis of current challenges in ag- ricultural drought monitoring revealed future research prospects for agricultural drought monitoring, such as investigating the mechanism underlying agricultural drought, identifying factors that influence agricultural drought, developing multi-spatiotemporal scales models for agricultural drought monitoring, coupling qualitative and quantitative agricultural drought evaluation models, and improving the application levels of remote sensing data in agricultural drought monitoring.

In vitro oocyte maturation (IVM) is a pivotal process influencing the success of embryo production in laboratory and clinical settings. However, oxidative stress (OS) often compromises oocyte quality during IVM. Antioxidants such as melatonin and epigallocatechin-3-gallate (EGCG) are known to mitigate OS by neutralizing reactive oxygen species (ROS) and bolstering antioxidant defenses. Despite extensive studies on their individual effects, the synergistic impact of melatonin and EGCG remains underexplored. Utilizing a mouse model, this study evaluated their combined effect on oocyte maturation, focusing on nuclear and cytoplasmic development, intracellular ROS, glutathione (GSH) levels, and subsequent embryonic competence. The results demonstrated that melatonin and EGCG significantly enhanced the polar body extrusion rate (p < 0.05), with the combination group achieving the highest rate of 91.96%. Cumulus expansion was observed to improve across all treated groups, with the combination treatment showing the highest cumulus expansion index (CEI) of 3.06. Furthermore, the combination treatment significantly reduced ROS levels and increased GSH content, indicating enhanced antioxidant capacity (p < 0.01). Embryonic development outcomes, including cleavage and blastocyst rates, were markedly higher in the combination group at 75.23% and 53.97%, respectively, demonstrating superior developmental potential (p < 0.01). These findings suggest that the melatonin–EGCG combination offers a novel and effective strategy to combat oxidative damage during IVM, thereby improving oocyte quality and embryonic development potential in mice.

Recently, various object detection frameworks have been applied to text detection tasks and have achieved good performance in the final detection. With the further expansion of text detection application scenarios, the research value of text detection topics has gradually increased. Text detection in natural scenes is more challenging for horizontal text based on a quadrilateral detection box and for curved text of any shape. Most networks have a good effect on the balancing of target samples in text detection, but it is challenging to deal with small targets and solve extremely unbalanced data. We continued to use PSENet to deal with such problems in this work. On the other hand, we studied the problem that most of the existing scene text detection methods use ResNet and FPN as the backbone of feature extraction, and improved the ResNet and FPN network parts of PSENet to make it more conducive to the combination of feature extraction in the early stage. A SEMPANet framework without an anchor and in one stage is proposed to implement a lightweight model, which is embodied in the training time of about 24 h. Finally, we selected the two most representative datasets for oriented text and curved text to conduct experiments. On ICDAR2015, the improved network’s latest results further verify its effectiveness; it reached 1.01% in F-measure compared with PSENet-1s. On CTW1500, the improved network performed better than the original network on average.

Highlights Hierarchical polyimide (PI) nonwoven fabric is fabricated by alkali treatment, in-situ growth of magnetic particles, and \"self-activated\" electroless Ag plating process. Impedance matching structure by assembling Fe 3 O 4 /Ag-loaded PI nonwoven fabric (PFA) and pure Ag-coated PI nonwoven fabric (PA) induces more electromagnetic waves enter PFA/PA and be dissipated. The fluffy 3D space structure of PFA with strong adhesion interaction and low infrared emissivity of PA endow PFA/PA with excellent thermal stability in electromagnetic interference shielding and high-temperature resistant infrared stealth performance. Designing and fabricating a compatible low-reflectivity electromagnetic interference (EMI) shielding/high-temperature resistant infrared stealth material possesses a critical significance in the field of military. Hence, a hierarchical polyimide (PI) nonwoven fabric is fabricated by alkali treatment, in-situ growth of magnetic particles and \"self-activated\" electroless Ag plating process. Especially, the hierarchical impedance matching can be constructed by systematically assembling Fe 3 O 4 /Ag-loaded PI nonwoven fabric (PFA) and pure Ag-coated PI nonwoven fabric (PA), endowing it with an ultralow-reflectivity EMI shielding performance. In addition, thermal insulation of fluffy three-dimensional (3D) space structure in PFA and low infrared emissivity of PA originated from Ag plating bring an excellent infrared stealth performance. More importantly, the strong bonding interaction between Fe 3 O 4 , Ag, and PI fiber improves thermal stability in EMI shielding and high-temperature resistant infrared stealth performance. Such excellent comprehensive performance makes it promising for military tents to protect internal equipment from electromagnetic interference stemmed from adjacent equipment and/or enemy, and inhibit external infrared detection.

Event-based extreme precipitation (EEP), defined as an extreme precipitation event (no less than 1 mm for continuous days) having at least one daily precipitation exceeding the 90th percentile, are categorized into three types according to the time distribution pattern (TDP) of extreme precipitation: daily intense precipitation appearing only at the first half of event (TDP1), at both the first and second halves (TDP2), and only at the second half of event (TDP3). This study focuses on the TDP1 and TDP2 types, which occur much more frequently in the central-eastern China and investigates associated distinguishing large-scale teleconnection patterns. The TDP1 events dominantly occur in mid-to-late spring, which are associated with the Silk Road pattern (SRP) wave train manifested from western Europe to northwest Pacific along the subtropical westerly jet. The tripolar sea surface temperature (SST) anomalous pattern over the North Atlantic Ocean, i.e., low SST anomalies in the Azores Islands, two high SST anomalies over the Greenland and subtropical North Atlantic are mainly attributed to force the SRP wave. Meanwhile, the enhanced northwestward moisture transport from the South China converges with the southeastward moisture transport related to the SRP from the North China, resulting in the TDP1 extreme precipitation events over the central-eastern China. The TDP2 events are closely conjunction with the Meiyu precipitation in the Yangtze-Huai River basin in summer. During the TDP2 events, the East Asia/Pacific (EAP) teleconnection is exhibited along the East Asia coasts, which is triggered by the anomalous convection in the western North Pacific. An anomalous anticyclone related to the EAP teleconnection contributes to the westward stretch of the western Pacific subtropical high, providing significant enhanced moisture transportation toward the Yangtze-Huai River basin. Correspondingly, the meridional gradient of the equivalent potential temperature θe is intensified and favored of forming Meiyu front precipitation. This study highlights the definition of EEP event emphasizing the TDP of extreme precipitation and distinguished features of occurring seasons and large-scale circulations associated with the two dominant types of EEP events.

Irrational application of chemical fertilizers causes soil nutrient imbalance, reduced microbial diversity, soil diseases, and other soil quality problems and is one of the main sources of non-point pollution. The application of microbial inoculant (MI) can improve the soil environment and crop growth to reduce problems caused by irrational application of chemical fertilizers. Field experiments were carried out in high-phosphorus soils to study the effects of the addition of various MIs combined with chemical fertilizers on soil properties, wheat growth, and soil microbial composition and structure. The MIs consisted of one fungal agent: Trichoderma compound agent (TC) and five bacterial agents, namely soil remediation agent (SR), anti-repeat microbial agent (AM), microbial agent (MA), plant growth-promoting rhizobacteria (PG), and biological fertilizer agent (BF). The wheat yield increased by 15.2–33.4% with the addition of MIs, and PG with Bacillus subtilis as the core microorganism had the most obvious effect on increasing the production ( p  < 0.05). For the entire growth period of wheat, all MIs applied significantly increased the available nitrogen (AN) ( p  < 0.05) but did not significantly affect the available phosphorus (AP). BF has the best effect on increasing AN in the soil. The 16S rRNA sequencing results indicated that the dominant phyla of soil bacteria were Proteobacteria, Acidobacteria, Bacteroidetes, Actinobacteria, and Verrucomicrobia. The addition of MIs increased the relative abundance of Acidobacteria, Actinobacteria, Chloroflexi and decreased Proteobacteria and Bacteroidetes. The diversity of soil bacterial community (Chao1) was significantly higher in the soil added with TC than that added with BF ( p  < 0.05). All bacterial agents significantly enriched various genera ( p  < 0.05), while the fungal agent (TC) did not enrich the genera significantly. pH and AN, but not TP, were closely related to the dominant bacteria phylum in high-P soil. The application of MIs improved AN in soil, increased the wheat yield, and changed the relative abundance of the soil dominant phylum, and these changes were closely related to the type of MIs. The results provide a scientific basis for rational use of different types of MIs in high-P soil.