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Implementing artificial intelligence technologies allows for the accurate prediction of radiation therapy dose distributions, enhancing treatment planning efficiency. However, esophageal cancers present unique challenges because of tumor complexity and diverse prescription types. Additionally, limited data availability hampers the effectiveness of existing artificial intelligence models. This study developed a deep learning model, trained on a diverse data set of esophageal cancer prescriptions, to improve dose prediction accuracy. We retrospectively collected data from 530 patients with esophageal cancer, including single-target and simultaneous integrated boost prescriptions, for model building. The proposed Asymmetric ResNeSt (AS-NeSt) model features novel 3-dimensional (3D) ResNeSt blocks and an asymmetrical architecture. We constructed a loss function targeting global and local doses and validated the model's performance against existing alternatives. Model-assisted experiments were used to validate its clinical benefits. The AS-NeSt model maintained an absolute prediction error below 5% for each dosimetric metric. The average Dice similarity coefficient for isodose volumes was 0.93. The model achieved an average relative prediction error of 2.02%, statistically lower than Hierarchically Densely Connected U-net (4.17%), DoseNet (2.35%), and Densely Connected Network (3.65%). It also demonstrated significantly fewer parameters and shorter prediction times. Clinically, the AS-NeSt model raised physicians' ability to accurately preassess appropriate treatment methods before planning from 95.24% to 100%, reduced planning time by over 61% for junior dosimetrists and 52% for senior dosimetrists, and decreased both inter- and intra-dosimetrist discrepancies by more than 50%. The AS-NeSt model, developed with innovative 3D ResNeSt blocks and an asymmetrical encoder-decoder structure, has been validated using clinical esophageal cancer patient data. It accurately predicts 3D dose distributions for various prescriptions, including simultaneous integrated boost, showing potential to improve the management of esophageal cancer treatment in a clinical setting. [ABSTRACT FROM AUTHOR]

Avalanche multiphoton photoluminescence (AMPL) is observed from coupled Au–Al nanoantennas under intense laser pumping, which shows more than one order of magnitude emission intensity enhancement and distinct spectral features compared with ordinary metallic photoluminescence. The experiments are conducted by altering the incident laser intensity and polarization using a home-built scanning confocal optical microscope. The results show that AMPL originates from the recombination of avalanche hot carriers that are seeded by multiphoton ionization. Notably, at the excitation stage, multiphoton ionization is shown to be assisted by the local electromagnetic field enhancement produced by coupled plasmonic modes. At the emission step, the giant AMPL intensity can be evaluated as a function of the local field environment and the thermal factor for hot carriers, in accordance with a linear relationship between the power law exponent coefficient and the emitted photon energy. The dramatic change in the spectral profile is explained by spectral linewidth broadening mechanisms. This study offers nanospectroscopic evidence of both the potential optical damages for plasmonic nanostructures and the underlying physical nature of light–matter interactions under a strong laser field; it illustrates the significance of the emerging topics of plasmonic-enhanced spectroscopy and laser-induced breakdown spectroscopy. [ABSTRACT FROM AUTHOR]

Employees’ feedback-seeking behavior is an important way to develop and maintain self-awareness and interpersonal acuity, reduce uncertainty, boost creativity and improve innovative behavior and performance. Especially during the COVID-19 pandemic, working from home has become the new normal, supervisor feedback and employees feedback-seeking has an increasingly important impact on team creativity and team innovation performance.In the practice of organizational management, there is frequently a “feedback vacuum” between managers and employees. There is increasing research on feedback-seeking behavior in the field of OBHRM. This paper is the first to evaluate the impact of work meaning and positive attributions on workers’ feedback-seeking behavior, and the cross-level effects of supervisor development feedback including variable valence. The paper analyzes supervisor-employee paired data from 158 supervisors and 659 employees using multi-source, multi-temporal data to draw the following conclusions: (1) Positive supervisor development feedback has a significant cross-level positive effect on employee feedback-seeking behavior, whereas negative supervisor development feedback does not affect employee feedback-seeking behavior; (2) Work meaningfulness mediates the cross-level relationship between positive supervisor development feedback and employees’ feedback-seeking behaviors, whereas negative supervisor development feedback and employees’ feedback-seeking behaviors do not; (3) Positive attributions positively moderate the relationship between positive supervisor development feedback and work meaningfulness; while positively moderating the relationship between negative supervisor development feedback and work meaningfulness; (4) Positive attributions have a moderating effect on supervisor development feedback that influences the indirect relationship to feedback-seeking behavior by work meaningfulness. [ABSTRACT FROM AUTHOR]

In smart grid-based manufacturing, nanoparticles can play a significant role in enhancing efficiency, productivity, and sustainability. They can be employed in areas such as materials synthesis, fabrication, sensing, and energy storage. With combining smart grid technologies and nanoparticles, manufacturers can benefit from improved process control, reduced energy consumption, enhanced product quality, and increased resource efficiency. Hence, this paper concentrate on the design of smart grid with nanoparticles with unique properties with the evolutionary optimization process. The paper uses Dempster–Shafer probability framework (DS-PF) in smart grid-based manufacturing using nanoparticles. The DS-PF perform the mathematical reasoning under uncertainty and combining evidence, making it suitable for addressing the complex and uncertain nature of smart grid manufacturing processes. With the estimation of the mathematical derivatives, an evolutionary process is implemented with the probability detection–based fuzzy rules. Based on the optimal value of the evolutionary optimization fuzzy rules, the nanoparticles are integrated with the smart grid manufacturing. Through experimental results and simulations, the paper demonstrates the effectiveness of DS-PF in handling uncertainties and optimizing decision-making in smart grid-based manufacturing. The results expressed that the with DS-PF model energy consumption is significantly reduced to 235 J, with network lifetime of 24 h and packet delivery ratio of 96.5%. The findings of this research contribute to the advancement of smart grid-based manufacturing by offering a comprehensive framework for handling uncertainties and making informed decisions. The proposed methodologies and approaches based on DS-PF have the potential to enhance the efficiency, reliability, and optimization of manufacturing processes in smart grid environments. [ABSTRACT FROM AUTHOR]

Purpose: The suppression of pulmonary vessels in chest computed tomography (CT) images can enhance the conspicuity of lung nodules, thereby improving the detection rate of early lung cancer. This study aimed to develop two key techniques in vessel suppression, that is, segmentation and removal of pulmonary vessels while preserving the nodules. Methods: Pulmonary vessel segmentation and removal methods in CT images were developed. The vessel segmentation method used a framework of two cascaded convolutional neural networks (CNNs). A bi‐class segmentation network was utilized in the first step to extract high‐intensity structures, including both vessels and nonvascular tissues such as nodules. A tri‐class segmentation network was employed in the second step to distinguish the vessels from nonvascular tissues (mainly nodules) and the lung parenchyma. In the vessel removal method, the voxels in the segmented vessels were replaced with randomly selected voxels from the surrounding lung parenchyma. The dataset in this study comprised 50 three‐dimensional (3D) low‐dose chest CT images. The labels for vessel and nodule segmentation were annotated with a semi automatic approach. The two cascaded networks for pulmonary vessel segmentation were trained with CT images of 40 cases and tested with CT images of ten cases. Pulmonary vessels were removed from the ten testing scans based on the predicted segmentation results. In addition to qualitative evaluation to the effects of segmentation and removal, the segmentation results were quantitatively evaluated using Dice coefficient (DICE), Jaccard index (JAC), and volumetric similarity (VS) and the removal results were evaluated using contrast‐to‐noise ratio (CNR). Results: In the first step of vessel segmentation, the mean DICE, JAC, and VS for high‐intensity tissues, including both vessels and nodules, were 0.943, 0.893, and 0.991, respectively. In the second step, all the nodules were separated from the vessels, and the mean DICE, JAC, and VS for the vessels were 0.941, 0.890, and 0.991, respectively. After vessel removal, the mean CNR for nodules was improved from 4.23 (6.26 dB) to 6.95 (8.42 dB). Conclusions: Quantitative and qualitative evaluations demonstrated that the proposed method achieved a high accuracy for pulmonary vessel segmentation and a good effect on pulmonary vessel suppression. [ABSTRACT FROM AUTHOR]

All living organisms are constantly exposed to stresses from internal biological processes and surrounding environments, which induce many adaptive changes in cellular physiology and gene expression programs. Unexpectedly, constitutive heterochromatin, which is generally associated with the stable maintenance of gene silencing, is also dynamically regulated in response to stimuli. In this review we discuss the mechanism of constitutive heterochromatin assembly, its dynamic nature, and its responses to environmental changes. [ABSTRACT FROM AUTHOR]

Chromatin is generally classified as euchromatin or heterochromatin, each with distinct histone modifications, compaction levels, and gene expression patterns. Although the proper formation of heterochromatin is essential for maintaining genome integrity and regulating gene expression, heterochromatin can also spread into neighboring regions in a sequence-independent manner, leading to the inactivation of genes. Because the distance of heterochromatin spreading is stochastic, the formation of boundaries, which block the spreading of heterochromatin, is critical for maintaining stable gene expression patterns. Here we review the current understanding of the mechanisms underlying heterochromatin spreading and boundary formation. [ABSTRACT FROM AUTHOR]

Mammalian target of rapamycin complex 2 (mTORC2) phosphorylates AGC protein kinases including protein kinase C (PKC) and regulates cellular functions such as cell migration. However, its regulation remains poorly understood. Here we show that lysophosphatidic acid (LPA) induces two phases of PKC-? hydrophobic motif phosphorylation. The late phase is mediated by G?12, which specifically activates ARAF, leading to upregulation of the RFFL E3 ubiquitin ligase and subsequent ubiquitylation and degradation of the PRR5L subunit of mTORC2. Destabilization of PRR5L, a suppressor of mTORC2-mediated hydrophobic motif phosphorylation of PKC-?, but not AKT, results in PKC-? hydrophobic motif phosphorylation and activation. This G?12-mediated signalling pathway for mTORC2 regulation is critically important for fibroblast migration and pulmonary fibrosis development. [ABSTRACT FROM AUTHOR]

The nonlinearity of sinusoidal doubly salient electro-magnetic machine (SDSEM) leads to the fuzzy optimization range of its design parameters. And there is a conflict problem in multiple optimization objectives. Therefore, the multi-objective optimization of SDSEM with two different excitation modes is carried out based on the Gray-Fuzzy-Taguchi method. Firstly, the proposed sinusoidal method of square wave back electromotive force (EMF) phase modulation is introduced. And the key parameters to improve the symmetry and sinusoidal degree of the back EMF waveform are pointed out. Then, the sensitivity of key parameters is analyzed and the signal-to-noise (S/N) ratio is calculated by Taguchi orthogonal test. Secondly, the S/N ratio is linearly normalized by grey correlation analysis. Then, fuzzy reasoning is used to synthesize multiple performance indexes of the motor into a multiple performance characteristics index (MPCI) value, and the optimal scheme is obtained. Finally, the optimized SDSEM with concentrated magneto-motive forces (SDSEM-CF) and SDSEM with distributed magneto-motive forces (SDSEM-DF) are simulated and compared. The SDSEM-DF prototype is developed and verified by experiments. The results show that the no-load back EMF of the prototype has a good sinusoidal degree. Based on vector control, the sinusoidal drive of DSEM is realized without increasing the control complexity, which greatly reduces the torque ripple of the flux reluctance motor. [ABSTRACT FROM AUTHOR]

There has been increasing interest in the role of epigenetic modification in cancers recently. Among the various modifications, sialylation has emerged as a dominant subtype implicated in tumor progression, metastasis, immune evasion, and chemoresistance. The prognostic significance of sialylation-related molecules has been demonstrated in colorectal cancer. However, the potential roles and regulatory mechanisms of sialylation in lung adenocarcinoma (LUAD) have not been thoroughly investigated. Through Pearson correlation, univariate Cox hazards proportional regression, and random survival forest model analyses, we identified several prognostic long non-coding RNAs (lncRNAs) associated with aberrant sialylation and tumor progression, including LINC00857, LINC00968, LINC00663, and ITGA9-AS1. Based on the signatures of four lncRNAs, we classified patients into two clusters with different landscapes using a non-negative matrix factorization approach. Collectively, patients in Cluster 1 (C1) exhibited worse prognoses than those in Cluster 2 (C2), as well as heavier tumor mutation burden. Functional enrichment analysis showed the enrichment of several pro-tumor pathways in C1, differing from the upregulated Longevity and programmed cell death pathways in C2. Moreover, we profiled immune infiltration levels of important immune cell lineages in two subgroups using MCPcounter scores and single sample gene set enrichment analysis scores, revealing a relatively immunosuppressive microenvironment in C1. Risk analysis indicated that LINC00857 may serve as a pro-tumor regulator, while the other three lncRNAs may be protective contributors. Consistently, we observed upregulated LINC00857 in C1, whereas increased expressive levels of LINC00968, LINC00663, and ITGA9-AS1 were observed in C2. Finally, drug sensitivity analysis suggested that patients in the two groups may benefit from different therapeutic strategies, contributing to precise treatment in LUAD. By integrating multi-omics data, we identified four core sialylation-related lncRNAs and successfully established a prognostic model to distinguish patients with different characterizations. These findings may provide some insights into the underlying mechanism of sialylation, and offer a new stratification way as well as clinical guidance in LUAD. [ABSTRACT FROM AUTHOR]

A workshop was held in China in October 2023 to discuss the conservation of the Chinese giant salamander, which is currently categorized as Critically Endangered due to overexploitation and habitat loss. The workshop attendees, representing various stakeholders, agreed on several key actions, including research to resolve taxonomic issues, field surveys to protect remaining populations, and investigations into how salamander farming could benefit conservation efforts. Other actions included refining the process for releasing individuals from farms, advocating for legislative changes, studying the species' behavior and ecology, and implementing better practices to prevent the introduction and transmission of pathogens. [Extracted from the article]

Histone H3 lysine 36 methylation (H3K36me) is critical for epigenetic regulation and mutations at or near H3K36 are associated with distinct types of cancers. H3K36M dominantly inhibits H3K36me on wild-type histones, whereas H3G34R/V selectively affects H3K36me on the same histone tail. Here we report the crystal structures of SETD2 SET domain in complex with an H3K36M peptide and SAM or SAH. There are large conformational changes in the substrate binding regions of the SET domain, and the K36M residue interacts with the catalytic pocket of SETD2. H3G34 is surrounded by a very narrow tunnel, which excludes larger amino acid side chains. H3P38 is in the trans configuration, and the cis configuration is incompatible with SETD2 binding. Finally, mutations of H3G34 or H3P38 alleviate the inhibitory effects of H3K36M on H3K36me, demonstrating that the stable interaction of H3K36M with SETD2 is critical for its inhibitory effects. [ABSTRACT FROM AUTHOR]

We investigate the role of tip-sample interaction in nonlinear optical scanning near-field microscopy. The experiment was performed by tightly focusing femtosecond laser pulses onto a sharp gold tip that was positioned in close proximity to the surface of a sample with gold nanostructures on a Si-substrate by shear force feedback. The nonlinear optical signal consists of two-photon photoluminescence and second harmonic signal from the gold tip and the gold nanostructures. These signals can be used to characterize different coupling parameters such as geometry, material and width of the tip-sample gap and enable to reveal the mechanism responsible for the image contrast. Under the excitation with 776-nm and 110-fs laser pulses nonlinear imaging is almost background free and yields super resolution showing features with dimensions significantly below the diffraction limit with a signal intensity following quadratic excitation power law. [ABSTRACT FROM AUTHOR]

• We report the use of hairy roots of F. cymosum induced by A. rhizogenes. • TrMYB4 regulates rutin biosynthesis in hairy roots of F. cymosum. • The hairy roots of F. cymosum can be used as a versatile tool for the metabolic engineering of buckwheat. Fagopyrum cymosum has been considered as a traditional medicinal plant that belongs to Fagopyrum , which has exhibited great pharmaceutical potential due to its abundant flavonoid accumulation. The hairy roots induced by Agrobacterium rhizogenes has been utilized to produce valuable specialized metabolites or reveals plant metabolic processes, whereas the underlying regulatory networks of flavonoid biosynthesis in hairy roots of F. cymosum remained unexplored. Here, the regulatory transcription factor TrMYB4 cloned from Trifolium repens with purple striped leaves was considered to investigate the mechanism of flavonoids biosynthesis in hairy roots of F. cymosum. Results showed that the expression of key genes involved in rutin biosynthesis pathway from TrMYB4 hairy roots were significantly up-regulated compared with non-transgenic hairy roots, while the content of total flavonoids and rutin in TrMYB4 hairy roots also increased consistently. It revealed the TrMYB4 transcription factor could regulate the rutin biosynthesis in F. cymosum. Meanwhile, our research provided a theoretical reference for the industrial production of rutin using F. cymosum hairy roots. [ABSTRACT FROM AUTHOR]

Licorice, the root and rhizome of Glycyrrhiza uralansis Fisch, is one of the most frequently used Traditional Chinese Medicines in rigorous clinical trials to remove toxins and sputum, and to relieve coughing. However, the aerial parts are not used so widely at present. It has been reported that the aerial parts have many bioactivities such as anti-microbial and anti-HIV activities. In this study, we aimed to discover the bioactive compounds from the leaves of G. uralensis. Four new compounds, licostilbene A-B (1–2) and licofuranol A-B (3–4), together with eight known flavonoids (5–12), were isolated and identified from the leaves of G. uralensis. Their structures were elucidated mainly by the interpretation of high-resolution electrospray mass spectrometry (HR-ESI-MS) and nuclear magnetic resonance (NMR) spectroscopic data. Compared with quercetin, which showed a 50% inhibitory concentration (IC50) value of 4.08 μg/mL, compounds 1–9 showed significant anti-inflammatory activities by inhibiting lipopolysaccharide (LPS)-induced nitric oxide (NO) production with IC50 values of 2.60, 2.15, 3.21, 3.25, 2.00, 3.45, 2.53, 3.13 and 3.17 μg/mL, respectively. The discovery of these active compounds is important for the prevention and treatment of inflammation. [ABSTRACT FROM AUTHOR]