Search

Background: The liver is anatomically divided into eight segments based on the distribution of Glisson's triad. However, the molecular mechanisms underlying each segment and its association with hepatocellular carcinoma (HCC) heterogeneity are not well understood. In this study, our objective is to conduct a comprehensive multiomics profiling of the segmentation atlas in order to investigate potential subtypes and therapeutic approaches for HCC. Methods: A high throughput liquid chromatography‐tandem mass spectrometer strategy was employed to comprehensively analyse proteome, lipidome and metabolome data, with a focus on segment‐resolved multiomics profiling. To classify HCC subtypes, the obtained data with normal reference profiling were integrated. Additionally, potential therapeutic targets for HCC were identified using immunohistochemistry assays. The effectiveness of these targets were further validated through patient‐derived organoid (PDO) assays. Results: A multiomics profiling of 8536 high‐confidence proteins, 1029 polar metabolites and 3381 nonredundant lipids was performed to analyse the segmentation atlas of HCC. The analysis of the data revealed that in normal adjacent tissues, the left lobe was primarily involved in energy metabolism, while the right lobe was associated with small molecule metabolism. Based on the normal reference atlas, HCC patients with segment‐resolved classification were divided into three subtypes. The C1 subtype showed enrichment in ribosome biogenesis, the C2 subtype exhibited an intermediate phenotype, while the C3 subtype was closely associated with neutrophil degranulation. Furthermore, using the PDO assay, exportin 1 (XPO1) and 5‐lipoxygenase (ALOX5) were identified as potential targets for the C1 and C3 subtypes, respectively. Conclusion: Our extensive analysis of the segmentation atlas in multiomics profiling defines molecular subtypes of HCC and uncovers potential therapeutic strategies that have the potential to enhance the prognosis of HCC. [ABSTRACT FROM AUTHOR]

Magnesium phosphate bone cement (MPBC) is a bone repair material that has been extensively studied. For better availability of clinical medicine, its degradation rate needs to be effectively controlled. Hydroxypropyl methylcellulose (HPMC) has often been used as a drug carrier for controlled drug release. This property was utilized to influence the release kinetics of MPBC. This work investigated the degradation mechanism of MPBC controlled by HPMC. It was found that MPBC samples with 3 wt. % HPMC had the optimal properties. In this case, the setting time was 11 min and the maximum strength was 63.9 ± 2.5 MPa. The study found HPMC primarily controlled the degradation of MPBC hydration products via the combined actions of gradual diffusion, and release of MPBC hydration products, which subsequently caused the swelling, corrosion, and dissolution of the HPMC skeleton. Besides, the results showed that HPMC‐modified MPBC has good bioactivity, which is beneficial to bone repair. This bioactive HPMC‐modified MPBC showed a controllable degradation rate and proper mechanic properties, which may be applied to bone repair. [ABSTRACT FROM AUTHOR]

Reducing the overapplication of nitrogen fertilizers to potatoes (Solanum tuberosum L.) can reduce production costs and their impact on the environment. One approach to produce these impacts is to reduce overapplications of fertilizers by using the nitrogen nutrition index (NNI = plant nitrogen concentration/critical nitrogen concentration) as a basis for in‐season nitrogen recommendations. The objective of this study was to create a remote sensing–based algorithm to estimate NNI. This study collected hyperspectral data (350–1830 nm) during the potato tuber formation period in 2022 and 2023. The climate regime for the study area was a mid‐temperate semiarid continental monsoon; in our study, three different spectral parameter calculation methods were employed. First, the empirical vegetation index, determined through a fixed two‐band calculation. Second, the optimal vegetation index, computed on a band‐by‐band basis. Lastly, the trilateral spectral approach, wherein the indicators are typically associated with the red edge, blue edge, and green edge. The optimum vegetation index had the highest correlation with NNI. The support vector machine, random forest (RF), and back propagation neural network models were used to create NNI prediction models. All machine learning models effectively estimated NNI, and during validation, the R2 (coefficient of determination) was >0.700. In general, the RF model outperformed the other models and during validation had an R2 of 0.869, a root mean square error of 0.052, and a relative error of 5.504%. This study demonstrates the scalability, simplicity, and cost‐effectiveness of combining hyperspectral technology and machine learning for rapid potato NNI estimation. Core Ideas: Hyperspectral assessment efficiently gauges nitrogen levels in growing potatoes.Spectral parameters and machine learning enhance potato nitrogen balance accuracy.The calculated indices at 718 and 760 nm ensure precise nitrogen balance. [ABSTRACT FROM AUTHOR]

The development of a novel and reliable surface‐enhanced Raman scattering (SERS) substrate for the surface corrosion analysis of bronze relics is an attractive research topic in cultural relic protection. A high‐performance SERS substrate was developed in the current investigation using Ag/ZIF‐8/Polyacrylonitrile (Ag/ZIF‐8/PAN) nanofibers. Silver nanoparticles were grown in situ by zeolite imidazolate framework‐8 (ZIF‐8) nanoparticles, and the substrate was examined in the surface corrosion analysis of bronze relics. In situ, growth of silver nanoparticles was ensured by the porous structure and active centers on ZIF‐8, coated on PAN nanofibers. Simultaneously, the adsorption of harmful rust‐alkaline copper chloride was enhanced on the surface of bronze relics. The extensive metal network was perturbed by the deposits, which substantially increased the intensity of the Raman characteristic peaks of the test objects. The signal strength of alkaline copper chloride at 118 cm−1 on the bronze surface increased from 1094 to 20,790. The exceptional SERS performance of silver nanoparticles with sharp edges demonstrates that the synergistic effect of ZIF‐8 nanoparticles and PAN nanofibers offers a considerable number of Raman‐enhanced hot spots. These results indicate that MOF‐based nanostructures offer a novel approach to enhancing the morphology of silver nanoparticles and expanding their potential applications in the field of cultural relic protection. [ABSTRACT FROM AUTHOR]

2D moiré superlattices offer a versatile platform for manipulating quantum materials, exploiting their spatially varying atomic registry to modify electronic structures, resulting in the emergence of flat electronic minibands, enhanced electronic interactions, and the onset of novel quantum phenomena. Despite extensive investigations into moiré excitons within twisted bilayer moiré superlattices, the interplay between moiré superlattices and optical microcavities remains elusive. Here, a WSe2 homobilayer with a small twist angle positioned on optical microcavities atop a SiO2 (285 nm)/Si substrate is investigated. Utilizing low‐temperature photoluminescence (PL) spectroscopy, it is observed that the twisted homobilayer at the edge of the optical cavity (Edge‐THB) exhibits enhanced localization of moiré excitons and a deeper moiré potential. This behavior is attributed to the combined influence of strain induced by the optical microcavity structure on the moiré superlattice and the amplification of the electromagnetic field. Furthermore, the existence of moiré excitons through a comprehensive analysis, encompassing temperature‐dependent PL spectra, circularly polarized PL spectra, and Landé g‐factor measurements for Edge‐THB is validated. These findings provide valuable insights into the intricate interaction between moiré superlattices and optical microcavities, paving the way for future applications in quantum technologies. [ABSTRACT FROM AUTHOR]