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This study aimed to evaluate the anti-pancreatic cancer effects of flavonoids in Plumula Nelumbinis. High-performance liquid chromatography/quadrupole time-of-flight mass spectrometry showed that apiin, rhoifolin, and vitexin were three principal components in total flavonoids derived from Plumula Nelumbinis, with vitexin being the most abundant component. Cell viability assay revealed that apiin, rhoifolin, and vitexin could inhibit proliferation of PANC-1 and ASPC-1, with rhoifolin showing the maximum inhibitory effect. Rhoifolin inhibited cell proliferation and promoted apoptosis of pancreatic cancer cells, which was associated with up-regulated JNK and p-JNK as well as down-regulated p-AKT. Rhoifolin also inhibited cell migration and invasion, and increased the antioxidant capacity in PANC-1 and ASPC-1. Besides, AKT activator (SC79) or JNK inhibitor (SP600125) effectively reversed the anticancer effects of rhoifolin in pancreatic cancer. Quantitative proteomics analysis showed that rhoifolin altered proteomic profiles in pancreatic cancer cells. Western blot analysis showed that rhoifolin down-regulated transforming growth factor beta 2 (TGF-β2), the regulator of proteoglycan synthesis, with the concomitant down-regulation of phosphorylated SMAD family member 2 (SMAD2), the downstream effector of TGF-β2. In conclusion, rhoifolin regulates the AKT/JNK/caspase-3 and TGF-β2/SMAD2 signaling pathways, which may contribute to its anti-pancreatic cancer effects.

Coal gasification fine slag (FS) is a typical solid waste generated in coal gasification. Its current disposal methods of stockpiling and landfilling have caused serious soil and ecological hazards. Separation recovery and the high-value utilization of residual carbon (RC) in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits. The structural properties, such as pore, surface functional group, and microcrystalline structures, of RC in FS (FS-RC) not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC. In this paper, the characteristics of FS-RC in terms of pore structure, surface functional groups, and microcrystalline structure are sorted out in accordance with gasification type and FS particle size. The reasons for the formation of the special structural properties of FS-RC are analyzed, and their influence on the flotation separation and high-value utilization of FS-RC is summarized. Separation methods based on the pore structural characteristics of FS-RC, such as ultrasonic pretreatment–pore-blocking flotation and pore breaking–flocculation flotation, are proposed to be the key development technologies for improving FS-RC recovery in the future. The design of low-cost, low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future. The high-value utilization of FS should be based on the physicochemical structural properties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to establish an environmentally friendly utilization method. This review is of great theoretical importance for the comprehensive understanding of the unique structural properties of FS-RC, the breakthrough of the technological bottleneck in the efficient flotation separation of FS, and the expansion of the field of the high value-added utilization of FS-RC.

Background Drought is a critical abiotic stress that influences maize yield and reduces grain yield when it occurs at the flowering or filling stage. To dissect the genetic architecture of grain yield under drought stress (DS), a genome-wide association analysis was conducted in a maize population composed of diverse inbred lines from five locations under well-watered and DS conditions at flowering in 2019 and 2020. Results Using a fixed and random model circulating probability unification model, a total of 147 loci associated with grain yield or the drought resistance index (DRI) were identified, of which 54 loci were associated with a DRI with an average phenotypic variation explanation of 4.03%. Further, 10 of these loci explained more than 10% of the phenotypic variation. By integrating two public transcriptome datasets, 22 differentially expressed genes were considered as candidate genes, including the cloned gene ZmNAC49 , which responds to drought by regulating stomatal density. Enrichment and protein interaction network showed that signaling pathways responded to drought resistance, including jasmonic acid and salicylic acid, mitogen-activated protein kinase, and abscisic acid-activated. Additionally, several transcription factors involved in DS were identified, including basic leucine zipper ( GRMZM2G370026 ), NAC ( GRMZM2G347043 ), and ethylene-responsive element binding protein ( GRMZM2G169654 ). Conclusions In this study, we nominated several genes as candidate genes for drought resistance by intergrating association maping and transcription analysis. These results provide valuable information for understanding the genetic basis of drought tolerance at the mature stage and for designing drought-tolerant maize breeding.

Climate change has led to an increase in the frequency of extreme precipitation events in recent years, which had a significant impact on local economic and social activities. To elucidate the impact of Chagan Nur Lake on an extreme precipitation process in the marginal region of the East Asian monsoon during summer and to contribute to the knowledge concerning extreme weather variability in mid-latitude semi-arid regions, this study focused on the extreme precipitation event that transpired between 24 and 27 July 2021 within the Chagan Nur Lake basin using the Weather Research and Forecasting (WRF) Model. The experiment involved modifying the subsurface characteristics of Chagan Nur Lake to simulate scenarios with and without the lake. The results indicated that the large-scale circulation triggered intense convective processes in the Chagan Nur Lake area, while the lake itself affected the local climate and regional precipitation patterns. Overall, Chagan Nur Lake exerted a negative influence on the precipitation process, leading to a reduction of 20-30 mm in the total precipitation. In the six hours preceding the precipitation, Chagan Nur Lake caused an average decrease of 0.2-0.4 °C in both the 2 m temperature (T2) and dew point temperature (TD), as well as a decrease of 0-10 m in the planetary boundary layer height (PBLH). The \"cold\" effect of Chagan Nur Lake inhibited atmospheric convective processes, thereby reducing the development of vertical motion. Subsequent to the terrestrialization of the lake, stronger thermal and dynamical conditions led to an increase in precipitation in the region. This study highlights the pivotal role of lakes in the occurrence of extreme precipitation in watersheds. It will be of paramount importance to consider the impact of the lake climate when forecasting precipitation in the semi-arid lake regions.

A contrasting trend pattern of sea surface salinity (SSS) between the western tropical Pacific (WTP) and the southeastern tropical Indian Ocean (SETIO) is observed during 2004–2013, with significant salinity increase in the WTP and freshening in the SETIO. In this study, we show that increased precipitation around the Maritime Continent (MC), decreased precipitation in the western-central tropical Pacific and ocean advection processes contribute to the salinity trends in the region. From a longer historical record, these salinity trends started in the mid-1990s, a few years before the Global Warming Hiatus from 1998 to present. The salinity trends are associated a strengthening trend of the Walker Circulation over the tropical Indo-Pacific, which have reversed the long-term salinity changes in the tropical Indo-Pacific as a consequence of global warming. Understanding decadal variations of SSS in the tropical Indo-Pacific will better inform on how the tropical hydrological cycle will be affected by the natural variability and a warming climate.

Two peptides with antioxidant activity were isolated from Pseudosciaena crocea proteins. Pseudosciaena crocea muscle was hydrolyzed with neutral protease to obtain Pseudosciaena crocea protein hydrolysates (PCPH). After ultrafiltration through molecular weight cut-off membranes of 10, 5 and 3 kDa and assessment of free radical scavenging ability, the fraction (PCPH-IV) with the highest antioxidant activity was obtained. Several purification steps, i.e., ion exchange chromatography, gel filtration chromatography and reversed phase high performance liquid chromatography, were applied to further purify PCPH-IV. Two antioxidant peptides with the amino acid sequences Ser-Arg-Cys-His-Val and Pro-Glu-His-Trp were finally identified by LC-MS/MS.

Immune checkpoint inhibitors (ICIs) are effective for non-small cell lung cancer (NSCLC) treatment, but the response rate remains low. Programmed cell death ligand 1 (PD-L1) in peripheral blood, including soluble form (sPD-L1), expression on circulating tumor cells (CTCs PD-L1) and exosomes (exoPD-L1), are minimally invasive and promising markers for patient selection and management, but their prognostic significance remains inconclusive. Here, we performed a meta-analysis for the prognostic value of PD-L1 blood markers in NSCLC patients treated with ICIs. Eligible studies were obtained by searching PubMed, EMBAS, Web of Science, and Cochrane Library prior to November 30, 2023. The associations between pre-treatment, post-treatment and dynamic changes of blood PD-L1 levels and progression-free survival (PFS)/over survival (OS) were analyzed by estimating hazard ratio (HR) and 95% confidence interval (CI). A total of 26 studies comprising 1606 patients were included. High pre- or post-treatment sPD-L1 levels were significantly associated with worse PFS (pre-treatment: HR=1.49, 95%CI 1.13-1.95; post-treatment: HR=2.09, 95%CI 1.40-3.12) and OS (pre-treatment: HR=1.83, 95%CI 1.25-2.67; post-treatment: HR=2.60, 95%CI 1.09-6.20, P=0.032). High pre-treatment exoPD-L1 levels predicted a worse PFS (HR=4.24, 95%CI 2.82-6.38, P<0.001). Pre-treatment PD-L1 CTCs tended to be correlated with prolonged PFS (HR=0.63, 95%CI 0.39-1.02) and OS (HR=0.58, 95%CI 0.36-0.93). Patients with up-regulated exoPD-L1 levels, but not sPD-L1, after ICIs treatment had significantly favorable PFS (HR=0.36, 95%CI 0.23-0.55) and OS (HR=0.24, 95%CI 0.08-0.68). PD-L1 blood markers, including sPD-L1, CTCs PD-L1 and exoPD-L1, can effectively predict prognosis, and may be potentially utilized for patient selection and treatment management for NSCLC patients receiving ICIs.

Objective The prognosis of sepsis, a pathological condition associated with high mortality and rapid progression, can be improved with precise diagnosis, effective treatment, and nursing care. This study investigated the expression and clinical significance of the long non-coding RNA (lncRNA) EPB41L4A-AS1 in sepsis. Methods The serum EPB41L4A-AS1 levels in patients with sepsis were quantified using quantitative real-time polymerase chain reaction (RT-qPCR). The diagnostic value of EPB41L4A-AS1 was determined using the receiver operating characteristic curves. The correlation of EPB41L4A-AS1 with clinical parameters was evaluated using Pearson correlation. Kaplan–Meier assessment of prognostic value. Lipopolysaccharide (LPS)-treated THP-1 cells served as an in vitro cell model for sepsis. The mRNA and protein levels of inflammatory factors were examined using RT-qPCR analysis and enzyme-linked immunosorbent assay, respectively. Finally, the binding of EPB41L4A-AS1 to miR-146a-5p was determined using the dual-luciferase reporter and RNA immunoprecipitation assays. Results EPB41L4A-AS1 was significantly downregulated in patients with sepsis. The downregulation was inversely correlated with inflammatory cytokines and severity scores (APACHE II and SOFA). EPB41L4A-AS1 expression had a high diagnostic value in sepsis. The overexpression of EPB41L4A-AS1 downregulated inflammatory factor expression and release. However, miR-146a-5p mitigated the inhibitory effects of EPB41L4A-AS1 overexpression on inflammatory factors expression and release. EPB41L4A-AS1 was a target of miR-146a-5p. Conclusion lncRNA EPB41L4A-AS1 alleviates sepsis-related inflammation by targeting miR-146a-5p and may serve as a diagnostic biomarker for sepsis.

Pilot behavior is crucial for aviation safety. This study aims to investigate the EEG characteristics of pilots, refine training assessment methodologies, and bolster flight safety measures. The collected EEG signals underwent initial preprocessing. The EEG characteristic analysis was performed during left and right turns, involving the calculation of the energy ratio of beta waves and Shannon entropy. The psychological workload of pilots during different flight phases was quantified as well. Based on the EEG characteristics, the pilots’ psychological workload was classified through the use of a support vector machine (SVM). The study results showed significant changes in the energy ratio of beta waves and Shannon entropy during left and right turns compared to the cruising phase. Additionally, the pilots’ psychological workload was found to have increased during these turning phases. Using support vector machines to detect the pilots’ psychological workload, the classification accuracy for the training set was 98.92%, while for the test set, it was 93.67%. This research holds significant importance in understanding pilots’ psychological workload.

The diversity in fruit posture has become the key factor that limits improvements in stem recognition precision during cherry tomato harvesting. To effectively enhance the recognition of small target features in cherry tomato stems, data augmentation strategies are employed to expand the dataset selectively, improving the model’s adaptability to complex scenarios. First, based on the YOLO11n model, the Large Separable Kernel Attention (LSKA) mechanism is integrated into the Spatial Pyramid Pooling-Fast (SPPF) to construct the SPPL module. This design effectively improves detection accuracy and model robustness while expanding the receptive field and enhancing feature extraction capabilities. This reduces computational complexity and enhances model robustness. Second, the Spatial and Channel Reconstruction Convolution (ScConv) module is embedded into the Bottleneck architecture to replace the original C3K2 module, thereby reducing feature redundancy and improving the extraction of fine-grained features. Finally, the BAFPN module was designed, which integrates the Asymptotic Feature Pyramid Network (AFPN) module to enhance the perception capability for small objects. Experimental results indicate that the YOLO-LSBA model achieves a precision of 97.1% and a recall of 78.3% for fruit stem recognition, with an AP of 92.4%. These metrics show improvements of 3.9%, 0.6%, and 2.2%, respectively, compared to the baseline model. Field trials further demonstrate that this model outperforms baseline models in detecting fruit stems under real agricultural conditions. This method offers new insights for intelligent harvesting.