What's the Situation with Intelligent Mesh Generation: A Survey and Perspectives

Intelligent Mesh Generation (IMG) represents a novel and promising field of research, utilizing machine learning techniques to generate meshes. Despite its relative infancy, IMG has significantly broadened the adaptability and practicality of mesh generation techniques, delivering numerous breakthroughs and unveiling potential future pathways. However, a noticeable void exists in the contemporary literature concerning comprehensive surveys of IMG methods. This paper endeavors to fill this gap by providing a systematic and thorough survey of the current IMG landscape. With a focus on 113 preliminary IMG methods, we undertake a meticulous analysis from various angles, encompassing core algorithm techniques and their application scope, agent learning objectives, data types, targeted challenges, as well as advantages and limitations. We have curated and categorized the literature, proposing three unique taxonomies based on key techniques, output mesh unit elements, and relevant input data types. This paper also underscores several promising future research directions and challenges in IMG. To augment reader accessibility, a dedicated IMG project page is available at \url{https://github.com/xzb030/IMG_Survey}

pLMFPPred: a novel approach for accurate prediction of functional peptides integrating embedding from pre-trained protein language model and imbalanced learning

Functional peptides have the potential to treat a variety of diseases. Their good therapeutic efficacy and low toxicity make them ideal therapeutic agents. Artificial intelligence-based computational strategies can help quickly identify new functional peptides from collections of protein sequences and discover their different functions.Using protein language model-based embeddings (ESM-2), we developed a tool called pLMFPPred (Protein Language Model-based Functional Peptide Predictor) for predicting functional peptides and identifying toxic peptides. We also introduced SMOTE-TOMEK data synthesis sampling and Shapley value-based feature selection techniques to relieve data imbalance issues and reduce computational costs. On a validated independent test set, pLMFPPred achieved accuracy, Area under the curve - Receiver Operating Characteristics, and F1-Score values of 0.974, 0.99, and 0.974, respectively. Comparative experiments show that pLMFPPred outperforms current methods for predicting functional peptides.The experimental results suggest that the proposed method (pLMFPPred) can provide better performance in terms of Accuracy, Area under the curve - Receiver Operating Characteristics, and F1-Score than existing methods. pLMFPPred has achieved good performance in predicting functional peptides and represents a new computational method for predicting functional peptides.Comment: 20 pages, 5 figures,under revie

Using polysaccharides for the enhancement of functionality of foods: A review

peer-reviewedBackground: Flavor, taste and functional ingredients are important ingredients of food, but they are easily lost or react during heating and are not stable. Carbohydrate-carbohydrate interactions (CCIs) and carbohydrate-protein interactions (CPIs) are involved in a variety of regulatory biological processes in nature, including cell differentiation, proliferation, adhesion, inflammation and immune responses. Polysaccharides have high molecular weights and many intramolecular hydrogen bonds, can be easily modified chemically and biochemically to enhance bioadhesive and biostability of tissues. Therefore, polysaccharides are the foundation for building complex and stable biosystems that are non-toxic with highydrophilicity and easily biodegradable. Scope and approach: In this review, we summarize the principles and applications of polysaccharide delivery systems in a variety of foods. Key findings and conclusions: This review focuses on the self-assembly of carbohydrates with complex structures and discusses the latest advances in self-assembly systems. The host-guest complexes formed by polyvalent sugar conjugates have the potential to provide, control or target delivery or release systems. They can also extend the shelf life of food and prevent oxidation and isomerization during food storage. Moreover, very few studies have outlined a comprehensive overview of the use of various types of food polysaccharide matrixes for the assembly and protection of food ingredients, which is a very important area for further study

Super-resolution hyper-spectral imaging for the direct visualization of local bandgap heterogeneity

Optical hyperspectral imaging based on absorption and scattering of photons at the visible and adjacent frequencies denotes one of the most informative and inclusive characterization methods in material research. Unfortunately, restricted by the diffraction limit of light, it is unable to resolve the nanoscale inhomogeneity in light-matter interactions, which is diagnostic of the local modulation in material structure and properties. Moreover, many nanomaterials have highly anisotropic optical properties that are outstandingly appealing yet hard to characterize through conventional optical methods. Therefore, there has been a pressing demand in the diverse fields including electronics, photonics, physics, and materials science to extend the optical hyperspectral imaging into the nanometer length scale. In this work, we report a super-resolution hyperspectral imaging technique that simultaneously measures optical absorption and scattering spectra with the illumination from a tungsten-halogen lamp. We demonstrated sub-5 nm spatial resolution in both visible and near-infrared wavelengths (415 to 980 nm) for the hyperspectral imaging of strained single-walled carbon nanotubes (SWNT) and reconstructed true-color images to reveal the longitudinal and transverse optical transition-induced light absorption and scattering in the SWNTs. This is the first time transverse optical absorption in SWNTs were clearly observed experimentally. The new technique provides rich near-field spectroscopic information that had made it possible to analyze the spatial modulation of band-structure along a single SWNT induced through strain engineering.Comment: 4 Figure

The safety and efficacy of systemic delivery of a new liver-de-targeted TGFβ signaling inhibiting adenovirus in an immunocompetent triple negative mouse mammary tumor model

Aberrant TGFβ signaling is linked to metastasis and tumor immune escape of many cancers including metastatic triple negative breast cancer (mTNBC). Previously, we have found that oncolytic adenoviruses expressing a TGFβ signaling inhibitory protein (sTGFβRIIFc) induced immune activation in a mouse TNBC (4T1) immunocompetent subcutaneous model with intratumoral injection. Systemic administration of adenoviruses can be a superior route to treat mTNBC but faces the challenges of increased toxicity and viral clearance. Thus, we created a liver-de-targeted sTGFβRIIFc- and LyP-1 peptide-expressing adenovirus (mHAdLyp.sT) with enhanced breast cancer cell tropism. Its safety and immune response features were profiled in the 4T1 model. Our data showed that the systemic administration of mHAdLyp.sT resulted in reduced hepatic and systemic toxicity. mHAdLyp.sT was also effective in increasing Th1 cytokines and anti-tumor cell populations by cytokine analysis, spleen/tumor qRT-PCR, and flow cytometry. We further tested the therapeutic effects of mHAdLyp.sT alone and in combination with immune checkpoint inhibitors (ICIs). mHAdLyp.sT alone and with all ICI combinations elicited significant inhibition of lung metastasis by histological analysis. When mHAdLyp.sT was combined with both anti-PD-1 and anti-CTLA-4 antibodies, primary 4T1 tumor growth was also significantly inhibited. We are confident in advancing this new treatment option for mTNBC

Taxonomic and phylogenetic characterisations of six species of Pleosporales (in Didymosphaeriaceae, Roussoellaceae and Nigrogranaceae) from China

Pleosporales comprise a diverse group of fungi with a global distribution and significant ecological importance. A survey on Pleosporales (in Didymosphaeriaceae, Roussoellaceae and Nigrogranaceae) in Guizhou Province, China, was conducted. Specimens were identified, based on morphological characteristics and phylogenetic analyses using a dataset composed of ITS, LSU, SSU, tef1 and rpb2 loci. Maximum Likelihood (ML) and Bayesian analyses were performed. As a result, three new species (Neokalmusia karka, Nigrograna schinifolium and N. trachycarpus) have been discovered, along with two new records for China (Roussoella neopustulans and R. doimaesalongensis) and a known species (Roussoella pseudohysterioides). Morphologically similar species and phylogenetically close taxa are compared and discussed. This study provides detailed information and descriptions of all newly-identified taxa

A nomogram based on CT intratumoral and peritumoral radiomics features preoperatively predicts poorly differentiated invasive pulmonary adenocarcinoma manifesting as subsolid or solid lesions: a double-center study

BackgroundThe novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models’ generalization ability.MethodsWe retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance.ResultsThe AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05).ConclusionThe nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively

Genome-Wide Analysis of Sorbitol Dehydrogenase (SDH) Genes and Their Differential Expression in Two Sand Pear (Pyrus pyrifolia) Fruits

Through RNA-seq of a mixed fruit sample, fourteen expressed sorbitol dehydrogenase (SDH) genes have been identified from sand pear (Pyrus pyrifolia Nakai). Comparative phylogenetic analysis of these PpySDHs with those from other plants supported the closest relationship of sand pear with Chinese white pear (P. bretschneideri). The expression levels varied greatly among members, and the strongest six (PpySDH2, PpySDH4, PpySDH8, PpySDH12, PpySDH13 and PpySDH14) accounted for 96% of total transcript abundance of PpySDHs. Tissue-specific expression of these six members was observed in nine tissues or organs of sand pear, with the greatest abundance found in functional leaf petioles, followed by the flesh of young fruit. Expression patterns of these six PpySDH genes during fruit development were analyzed in two sand pear cultivars, “Cuiguan” and “Cuiyu”. Overall, expression of PpySDHs peaked twice, first at the fruitlet stage and again at or near harvest. The transcript abundance of PpySDHs was higher in “Cuiguan” than in “Cuiyu”, accompanied by a higher content of sugars and higher ratio of fructose to sorbitol maintained in the former cultivar at harvest. In conclusion, it was suggested that multiple members of the SDH gene family are possibly involved in sand pear fruit development and sugar accumulation and may affect both the sugar amount and sugar composition