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Genistein has anti-cancer effects, but its molecular targets in gastric adenocarcinoma (GA) are unclear. This study used single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) to explore genistein’s “drug-gene-cell” interactions in GA. GA- and genistein-related target genes were retrieved and intersected with differentially expressed genes identified from bulk transcriptomic data. Machine learning screened candidates, and survival analysis assessed prognosis. Molecular docking with genistein validated key genes, with molecular dynamics assessing binding stability. HSD17B1, EZH2, CCNB1, CCNB2, CDKN2A, and IGFBP6 were identified as key candidate genes with prognostic value for GA. Specifically, samples in the IGFBP6 high-expression group were associated with higher survival probability, whereas the opposite trend was observed for the other five genes. In addition, HSD17B1 was genistein’s main target in GA treatment, showing a strong binding affinity with genistein (binding energy of −8.1 kcal/mol). scRNA-seq analysis indicated that HSD17B1 was predominantly expressed in epithelial cells and was significantly involved during their malignant transformation (confirmed by ST). This study identified HSD17B1 as a critical target gene for genistein in GA treatment, emphasizing its roles in the malignant transformation of epithelial cells, thus providing a theoretical foundation for understanding the therapeutic mechanism of genistein in GA.

Protein biomarkers from plasma extracellular vesicles (EVs) have been extensively identified in various diseases. To explore biomarkers associated with diabetic retinopathy (DR) progression, we designed two cohorts, discovery and validation cohorts, including four groups: healthy control, type 2 diabetes mellitus, non-proliferative DR (NPDR), and proliferative DR (PDR). A total of 32 differentially expressed proteins (DEPs) were screened by proteomic analysis in the four groups of the discovery cohort. Among them, four hub proteins, CELA3A, CELA3B, GLUD1, and CTRC, were identified to be related to DR progression, and their correlation with clinical characteristics was further analyzed. Subsequently, enzyme-linked immunosorbent assay in the validation cohort confirmed that the expression levels of CELA3A, CELA3B, and CTRC were consistent with the proteomic results. Receiver operator characteristic curve analysis found that the AUC values of three hub proteins and their composed panels distinguishing NPDR/PDR from DM were all > 0.7, except for DM-NPDR of CELA3B. In addition, CELA3A, CELA3B, and CTRC proteins were significantly correlated with some clinical indicators of DR. This study indicates that the plasma EV proteins CELA3A, CELA3B, and CTRC are expected to become biomarkers to monitor DR progression and provide guidance for DR diagnosis.

Pediatric high-grade glioma (pHGG) is a major contributor to cancer-related death in children. In vitro and in vivo disease models reflecting the intimate connection between developmental context and pathogenesis of pHGG are essential to advance understanding and identify therapeutic vulnerabilities. Here we report establishment of 21 patient-derived pHGG orthotopic xenograft (PDOX) models and eight matched cell lines from diverse groups of pHGG. These models recapitulate histopathology, DNA methylation signatures, mutations and gene expression patterns of the patient tumors from which they were derived, and include rare subgroups not well-represented by existing models. We deploy 16 new and existing cell lines for high-throughput screening (HTS). In vitro HTS results predict variable in vivo response to PI3K/mTOR and MEK pathway inhibitors. These unique new models and an online interactive data portal for exploration of associated detailed molecular characterization and HTS chemical sensitivity data provide a rich resource for pediatric brain tumor research. Patient-derived xenografts provide a resource for basic and translational cancer research. Here, the authors generate multiple pediatric high-grade glioma xenografts, use omics technologies to show that they are representative of primary tumours and use them to assess therapeutic response.

Suzanne Baker and colleagues sequenced the whole genomes of seven pediatric brainstem glioblastomas and matched normal tissue. They found that 78% of diffuse intrinsic pontine gliomas and 22% of non-brainstem pediatric glioblastomas contained a mutation in H3F3A , encoding histone H3.3, or in the related HIST1H3B , encoding histone H3.1, causing a p.Lys27Met amino acid substitution in each protein. To identify somatic mutations in pediatric diffuse intrinsic pontine glioma (DIPG), we performed whole-genome sequencing of DNA from seven DIPGs and matched germline tissue and targeted sequencing of an additional 43 DIPGs and 36 non-brainstem pediatric glioblastomas (non-BS-PGs). We found that 78% of DIPGs and 22% of non-BS-PGs contained a mutation in H3F3A , encoding histone H3.3, or in the related HIST1H3B , encoding histone H3.1, that caused a p.Lys27Met amino acid substitution in each protein. An additional 14% of non-BS-PGs had somatic mutations in H3F3A causing a p.Gly34Arg alteration.

This paper studies the modeling method and collaborative optimization of the dynamic responses for barrier-vehicle-occupant (BVO) system in engineering. The mechanical analytical model of BVO system is established to obtain not only the system dynamic responses but also the evaluation indexes of crashworthiness and compatibility. A collaborative optimization method that combines the BVO model and genetic algorithm is presented to obtain the optimal crash pulse of vehicle. An empirical case of an existing vehicle that has been in running in China is applied to verify this constructed model and solution method. Compared with the results of original alternative, the peak occupant acceleration and occupant load criterion ( OLC ) of barrier are reduced by 54.65% and 14.07%, respectively, and avoid the barrier bottoming out effectively. In addition, a sensitivity analysis is conducted and the results could be found that the heights about the middle part have a significant impact on occupant injury, OLC, and the middle backward part have a significant impact on the bottoming out of barrier, respectively. In summary, the concave shape crash pulse can improve crashworthiness and compatibility. This research reveals the principles of the BVO system and provides an effective tool to solve the optimization problem in conceptual design of vehicle.

The safe and effective treatment for dyeing wastewater including harmful metal ions, which are important environmental pollution sources, has not been solved in the realistic industry. Using natural materials with short regeneration cycle should be valued in recognized and effective adsorption techniques. In this study, hydroxyl-rich tannin molecules were successfully modified on palm leaf sheath fibers (PLSF) to obtain multifunctional adsorbent for simultaneous removal of dye molecules and heavy metal ions in dyeing wastewater. As a result, modified PLSF can effectively adsorb reactive yellow 3 (RY3) dye molecules with a maximum adsorption capacity of 83.19 mg/g from dyeing wastewater, while the sample loaded with RY3 can adsorb Cr(VI) with a maximum adsorption capacity of 189.48 mg/g. XRD, SEM, FT-IR, and stereomicroscope are used to characterize the adsorbent samples. The kinetic and thermodynamic analysis results show that the adsorption of RY3 and Cr(VI) by the adsorbent is consistent with pseudo-second-order kinetics and the Langmuir isotherm model. The thermodynamic parameters of Cr(VI) adsorption indicate that adsorption is a spontaneous endothermic process and has good reusability of Cr(VI).

Achieving robust visual detection under challenging conditions such as poor illumination and target deformation remains a critical challenge for computer vision systems. Although the YOLO series of object detection algorithms excel in speed and accuracy, their performance significantly degrades under non-ideal lighting conditions. To address this issue, we propose a Hybrid Dynamic Perception Network (HDPNet), a framework specifically designed for high-precision, real-time object detection in harsh environments. HDPNet integrates three core modules into the YOLOv8n architecture to form a hybrid structure. The Dynamic Illumination-aware Module (DIM) adaptively enhances features under varying illumination through global encoding and a dual-attention mechanism, the Interactive Attention Fusion Network (IAFN) optimizes cross-modal features using a lightweight Transformer-CNN interactive architecture, and the Multi-branch Decomposition Network (MDN) captures multi-scale deformation features by combining deformable convolution and sparse Transformer. Experimental results on the self-built low-light industrial express package dataset named njpackage show that our method achieves an mAP@0.5 of 86.6%, which is 4.4% higher than the baseline YOLOv8n model, while maintaining real-time inference speed of ≥45 FPS. The proposed HDPNet not only provides an effective solution for logistics automation but also offers a robust and versatile hybrid technical framework adaptable to other vision tasks facing similar challenges.

Freshwater scarcity is a critical global issue, exacerbated by water pollution. Solar-driven interfacial evaporation (SDIE) offers a promising solution due to its energy efficiency and environmental benefits. This study presents a light-driven adaptive interfacial solar steam evaporation system enhanced by dynamic water gating. The system addresses the challenge of balancing high evaporation rates with salt accumulation, a common limitation in SDIE technology. An evaporator is developed using modified spiropyran and inexpensive wood, enabling dynamic salt discharge through light variations. Theoretical calculations reveal that the reversible structural changes in spiropyrans facilitate salt removal. The evaporator features a two-layer design, with a light-control layer and a hydrophilic layer, which enhances evaporation by stabilizing the gas-liquid interface and minimizing heat loss. Experimental results confirm the evaporator’s long-term stable salt-discharge and freshwater production capabilities, demonstrating high evaporation rates, reusability, and pollution resistance. Outdoor experiments and water purification tests further validate its effectiveness in producing freshwater and preventing salt accumulation. This research underscores the potential of light-responsive materials in designing efficient, sustainable evaporators, offering a significant advancement in water purification and desalination technologies. A photocontrol dynamic water gate evaporator with light-adaptive dynamic salt discharge was developed in this study to solve the problem of salt crystallization on the solar evaporator’s surface, which achieves efficient evaporation and salt discharge.

A Fe-Co dual-metal co-doped N containing the carbon composite (FeCo-HNC) was prepared by adjusting the ratio of iron to cobalt as well as the pyrolysis temperature with the assistance of functionalized silica template. Fe1Co-HNC, which was formed with 1D carbon nanotubes and 2D carbon nanosheets including a rich mesoporous structure, exhibited outstanding oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) catalytic activities. The ORR half-wave potential is 0.86 V (vs. reversible hydrogen electrode, RHE), and the OER overpotential is 0.76 V at 10 mA cm−2 with the Fe1Co-HNC catalyst. It also displayed superior performance in zinc–air batteries. This method provides a promising strategy for the fabrication of efficient transition metal-based carbon catalysts.

Metal–organic framework (MOF) films are essential for numerous sensor and device applications. However, metal-organic framework materials have poor machinability due to their predominant powder-like nature, and their presence as the active layer in a device can seriously affect the performance and utility of the device. Herein, active layers of field-effect transistor (FETs) devices and chemiresistor gas sensors with high performance were constructed by loading Cu3(HITP)2 (HITP = 2,3,6,7,10,11-hexaiminotriphenylene) in situ-axial anchoring on oriented nanofiber arrays prepared via electrospinning. The strong interaction between polar groups on the polymer chains and metal ions promotes the nucleation of Cu3(HITP)2, steric hindrance makes particles of Cu3(HITP)2 with uniform size, morphology, and good crystallinity during nucleation by liquid phase epitaxial growth (LPE). Influences of differently-oriented Cu3(HITP)2 NFAs-based FETs on the electrical properties were studied, optimally oriented Cu3(HITP)2 NFAs-based FETs showed good mobility of 5.09 cm2/V·s and on/off ratio of 9.6 × 103. Moreover, excellent gas sensing response characteristics were exhibited in sensing volatile organic compounds (VOCs). Chemiresistor gas sensors with high response value, faster response and recovery are widely suited for VOCs. It brings new inspirations for the design and utilization of electrically conductive MOFs as an active layer for FETs and sensor units for chemiresistor gas sensors.