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In order to solve the contradiction between large aperture elements and high-resolution images, in this study, we propose an improved image-resolution method based on generative adversarial network (GAN). First, we analyze the imaging principle of the optical synthetic aperture. Further, we improve a super-resolution GAN; especially, this network uses a multi-scale convolutional cascade to obtain global features of the image, and a multi-scale receptive field block and residual in residual dense block are built to obtain image details. In addition, this study uses the Mish function as the activation function of the discriminator to solve the problems of neuron extreme, gradient explosion, and poor generalization ability of the model. Through simulation, the results show that the proposed method can achieve a peak signal-to-noise ratio (PSNR) of 30 dB compared with traditional image super-resolution reconstruction methods for synthetic aperture image. The method proposed has an improvement of 2 dB in the PSNR and 0.016 in structure similarity index measure compared with the original super-resolution GAN. Therefore, this method can effectively reduce the image distortion and improve the quality of image reconstruction.

In order to explore the effects of different production processes (cold pressing, leaching, and their combination) on the quality and flavor of soybean oil of third grade, the physicochemical properties and fatty acid composition of the three soybean oils were determined, and their volatile compounds were identified and analyzed by electronic nose, headspace-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS), and headspace-gas chromatography-ion mobility spectroscopy (HS-GC-IMS). Differential analysis of the volatile compound data among the soybean oils was performed by clustering heatmap analysis, principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The results showed that cold-pressed soybean oil had the lowest moisture content; the peroxide value of leached soybean oil was significantly higher and its color was the darkest. Fragrant soybean oil had the highest linoleic acid content and a higher nutritional value; and among the detected volatile components, alcohols, aldehydes and pyrazine compounds mainly contributed to the formation of soybean oil flavor, and the reasons for the formation of some flavor compounds were clarified. Finally, 45 volatile compounds with high contributions were selected by OPLS-DA, and a reliable model was constructed for identifying fragrant soybean oil. In addition, a correlation was found between the quality and flavor of soybean oil.

Objective To understand the research hotspots and research trends about convolutional neural networks in the field of oncology imaging diagnosis by analyzing the characteristics of published literature at home and abroad over the past decade. Methods The SCI-E database was used as the data source to retrieve literature about convolutional neural networks in the field of oncology imaging diagnosis published from 2012 to 2022. The distribution characteristics of countries, institutions, journals, co-cited authors, and keywords of the studies were analyzed by CiteSpace software. Results A total of 1088 papers were eventually included, and they were mostly from China, the United States, and India. A total of 39 papers were published by Sun Yat-sen University, the research institution with the highest number of publications. Radiology Nuclear Medicine Medical Imaging was the journal with the highest number of publications. A total of 25 high-frequency keywords and 15 burst keywords were obtained. The formation of 12 author co-citation clusters such as image segmentation and lung nodule, as well as 11 keyword clusters such as automatic segmentation and breast cancer, was observed. Conclusion Current research on convolutional neural networks for oncology imaging diagnosis focuses on oncology segmentation, lung-nodule recognition, assisted diagnosis of breast cancer, and other high-frequency oncology.

This paper considers the generalized sectorial decompositions of semi-sectorial operators and quasi-sectorial operators on the complex Hilbert space. Under an invariant subspace condition, a necessary and sufficient condition for the existence of the generalized sectorial decomposition of a semi-sectorial operator is given. The generalized sectorial decomposition of a quasi-sectorial operator is given without any conditions. Some sufficient conditions for a block upper triangular operator matrix to be a semi-sectorial operator or a quasi-sectorial operator are given. [ABSTRACT FROM AUTHOR]

Alkyl phosphonates are important motifs in medicinal chemistry, yet their efficient synthesis by direct C(sp3)−H functionalization remains a challenge. Here, we report straightforward access to benzylic phosphonates by direct C(sp3)−H functionalization in a cross‐dehydrogenative‐coupling reaction between non‐specialized alkylarenes and unfunctionalized phosphites. Notably, the C−H substrates are used as the limiting reagents. The scope of benzylic C−H substrates is broad, and the mild reaction conditions allow for good functional group tolerance. Mechanistic studies indicate that the reaction proceeds via a radical pathway rather than the cationic pathway followed for specialized benzylic C−H substrates in previous methods. [ABSTRACT FROM AUTHOR]

As the largest terrestrial ecosystem covering extensive expanses of the Earth's surface, forests offer crucial health benefits to humans, both directly and indirectly. Presently, health services derived from forest resources have presented significant opportunities for enhancing human well-being. Nonetheless, the absence of a comprehensive understanding regarding the mechanisms by which forests impact human health jeopardizes the potential gains in health. Regrettably, there remains a dearth of scholarly work elucidating these pathways. This paper aims to furnish a thorough examination of how forests influence human health. We initiate by formulating a conceptual framework upon which we delineate the various pathways through which forests impact human health. These encompass the provisioning of resources, preventive services, and forest therapies. Concurrently, we outline the moderating influence of social, economic, and individual characteristics as mediators within this pathway. These characteristics are classified into two overarching dimensions: accessibility and behavioral choices, which notably affect marginalized demographics such as those with lower socioeconomic status, women, the elderly, individuals with disabilities, and children in developing nations. Consequently, we build upon these foundational insights to propose six strategies aimed at perpetuating the positive impact of forests on human health in the foreseeable future. In the future, the development of forest management policies, the assessment of long-term health benefits, social practices, and international cooperation must be considered holistically to attain the dual objective of sustainable forest management and the advancement of human well-being. [ABSTRACT FROM AUTHOR]

Metformin, a traditional first-line pharmacological treatment for type 2 diabetes, has recently been shown to have anti-cancer effects on hepatocellular carcinoma (HCC). However, the molecular mechanism underlying the anti-tumor activity of metformin remains unclear. The Sonic hedgehog (Shh) signaling pathway is closely associated with the initiation and progression of HCC. Therefore, the aim of the current study was to investigate the effects of metformin on the biological behavior of HCC and the underlying functional mechanism of metformin in the Shh pathway. HCC was induced in HepG2 cells using recombinant human Shh (rhShh). The effects of metformin on proliferation and metastasis were evaluated using in vitro proliferation, wound healing, and invasion assays. The mRNA and protein expression levels of proteins related to the Shh pathway were measured using western blotting, quantitative PCR, and immunofluorescence staining. Metformin inhibited rhShh-induced proliferation and metastasis. Furthermore, metformin decreased the mRNA and protein expression of Shh pathway components, including Shh, Ptch, Smo, and Gli-1. Silencing of AMPK in the presence of metformin revealed that metformin exerted its inhibitory effects via AMPK. Our findings demonstrate that metformin suppresses the migration and invasion of HepG2 cells via AMPK-mediated inhibition of the Shh pathway. Key words: liver cancer, Sonic hedgehog signaling pathway, metformin, AMPK, HepG2 cells. La metformine, un traitement pharmacologique conventionnel de premiere ligne pour le diabete de type 2, s'est recemment revelee exercer des effets anticancereux sur le carcinome hepatocellulaire (CHC). Cependant, le mecanisme moleculaire de la metformine quant a son activite antitumorale n'est pas encore completement elucide. La voie de signalisation Sonic Hedgehog (Shh) est etroitement associee a l'initiation et a la progression du CHC. Ainsi, l'objectif de la presente etude consistait a examiner les effets de la metformine sur le comportement biologique du CHC et le mecanisme fonctionnel sous-jacent de la metformine sur la voie Shh. Le CHC a ete induit dans les cellules HepG2 par la Shh humaine recombinante (rhShh). Les effets de la metformine sur la proliferation et la metastase ont ete evalues par des tests de proliferation, de cicatrisation et d'invasion in vitro. Les niveaux d'expression de l'ARNm et des proteines liees a la voie Shh ont ete mesures par transfert Western, PCR quantitative et coloration par immunofluorescence. La metformine inhibait la proliferation et la metastase induites par rhShh. En outre, la metformine diminuait l'expression de l'ARNm et des proteines des composants de la voie Shh, notamment Shh, Ptch, Smo et Gli-1. Le silencage de l'AMPK en presence de metformine a revele que la metformine pouvait exercer son effet inhibiteur par l'intermediaire de l'AMPK. Ces resultats demontrent que la metformine peut supprimer la migration et l'invasion des cellules HepG2 par une inhibition de la voie Shh mediee par l'AMPK. [Traduit par la Redaction] Mots-cles : cancer du foie, voie de signalisation Sonic Hedgehog, metformine, AMPK, cellules HepG2., Introduction In 2020, liver cancer was the sixth most commonly diagnosed cancer and the third leading cause of cancer-related deaths worldwide (Sung et al. 2021). The risk factors for liver [...]

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden.