Integrative genomic and transcriptomic analysis for pinpointing recurrent alterations of plant homeodomain genes and their clinical significance in breast cancer

A wide range of the epigenetic effectors that regulate chromatin modification, gene expression, genomic stability, and DNA repair contain structurally conserved domains called plant homeodomain (PHD) fingers. Alternations of several PHD finger-containing proteins (PHFs) due to genomic amplification, mutations, deletions, and translocations have been linked directly to various types of cancer. However, little is known about the genomic landscape and the clinical significance of PHFs in breast cancer. Hence, we performed a large-scale genomic and transcriptomic analysis of 98 PHF genes in breast cancer using TCGA and METABRIC datasets and correlated the recurrent alterations with clinicopathological features and survival of patients. Different subtypes of breast cancer had different patterns of copy number and expression for each PHF. We identified a subset of PHF genes that was recurrently altered with high prevalence, including PYGO2 (pygopus family PHD finger 2), ZMYND8 (zinc finger, MYND-type containing 8), ASXL1 (additional sex combs like 1) and CHD3 (chromodomain helicase DNA binding protein 3). Copy number increase and overexpression of ZMYND8 were more prevalent in Luminal B subtypes and were significantly associated with shorter survival of breast cancer patients. ZMYND8 was also involved in a positive feedback circuit of the estrogen receptor (ER) pathway, and the expression of ZMYND8 was repressed by the bromodomain and extra terminal (BET) inhibitor in breast cancer. Our findings suggest a promising avenue for future research—to focus on a subset of PHFs to better understand the molecular mechanisms and to identify therapeutic targets in breast cancer

Experimental study on mix proportion of transparent similar materials for rock mass

Traditional rock mass is opaque and the internal deformation and fracture process cannot be observed directly, using transparent materials to make similar models is an effective solution. E-44 type epoxy resin is used as aggregate, triethanolamine is used as curing agent, and alcohol rosin saturated solution (RSS) is added to adjust brittleness. Based on comprehensive experimental methods, the influence of the ratio of epoxy resin to triethanolamine and the content of RSS on the density, uniaxial compressive strength, peak strain, elastic modulus, tensile strength, cohesion and friction angle of transparent rock mass are studied in series. The results show that the ratio of epoxy resin to triethanolamine plays a leading role in the compressive strength, elastic modulus, tensile strength, cohesion and friction angle of similar transparent materials, while the content of the RSS plays a leading role in the density and peak strain. The density and peak strain is positively correlated with the ratio of epoxy resin to triethanolamine, and negatively correlated with the content of RSS. When the ratio of epoxy resin to triethanolamine is 3∶1, the compressive strength of the specimen is negatively correlated with the content of RSS, while at other ratios, the compressive strength does not change significantly. The elastic modulus and friction angle of the test piece is positively correlated with the ratio of epoxy resin and triethanolamine. When the ratio of epoxy resin to triethanolamine is 3∶1, the elastic modulus of the test piece is negatively correlated with the content of RSS. While at other ratios, the elastic modulus of the specimen is positively correlated with the content of RSS. The tensile strength and cohesion decreased with the increase of RSS content, and first increased and then decreased with the increase of the ratio of epoxy resin to triethanolamine. In the same ratio of epoxy resin to triethanolamine, the tensile strength was negatively correlated with RSS content. Based on multiple linear regression analysis, an empirical formula between the mechanical properties of transparent rock mass and the ratio of epoxy resin to triethanolamine and RSS content is established, which provides a reference for the proportion of similar materials in transparent rock mass

AcoMYB4, an Ananas comosus L. MYB transcription factor, functions in osmotic stress through negative regulation of ABA signaling

Drought and salt stress are the main environmental cues affecting the survival, development, distribution, and yield of crops worldwide. MYB transcription factors play a crucial role in plants’ biological processes, but the function of pineapple MYB genes is still obscure. In this study, one of the pineapple MYB transcription factors, AcoMYB4, was isolated and characterized. The results showed that AcoMYB4 is localized in the cell nucleus, and its expression is induced by low temperature, drought, salt stress, and hormonal stimulation, especially by abscisic acid (ABA). Overexpression of AcoMYB4 in rice and Arabidopsis enhanced plant sensitivity to osmotic stress; it led to an increase in the number stomata on leaf surfaces and lower germination rate under salt and drought stress. Furthermore, in AcoMYB4 OE lines, the membrane oxidation index, free proline, and soluble sugar contents were decreased. In contrast, electrolyte leakage and malondialdehyde (MDA) content increased significantly due to membrane injury, indicating higher sensitivity to drought and salinity stresses. Besides the above, both the expression level and activities of several antioxidant enzymes were decreased, indicating lower antioxidant activity in AcoMYB4 transgenic plants. Moreover, under osmotic stress, overexpression of AcoMYB4 inhibited ABA biosynthesis through a decrease in the transcription of genes responsible for ABA synthesis (ABA1 and ABA2) and ABA signal transduction factor ABI5. These results suggest that AcoMYB4 negatively regulates osmotic stress by attenuating cellular ABA biosynthesis and signal transduction pathways

Prognostic and immunological significance of calcium-related gene signatures in renal clear cell carcinoma

Background: Calcium signaling is implicated in multiple processes including immune response that important in tumor progression. Kidney renal clear cell carcinoma (KIRC) is the most frequent histological type of renal cell carcinoma with up to a third of cases develop metastases. As a result of a lack of in-depth understanding of the mechanisms underlying KIRC, treatment options have been limited. Here, we aim to comprehensively investigate the landscape of Ca2+ channels, pumps and exchangers in KIRC patients.Methods: The mRNA expression profiles and gene variations of 58 calcium-related genes (CRGs) in KIRC patients and normal control cases were downloaded from TCGA database. CRGs-related risk score was constructed to quantify calcium patterns by using least absolute shrinkage and selection operator (LASSO) regression. The prognostic value, biological functions, immune landscape and therapeutic sensitivities based on CRGs-related risk score were then evaluated using multiple methods. Finally, key gene of CRGs was identified by weighted gene co-expression network analysis (WGCNA). TCGA-CPTAC, GSE53757 datasets, as well as human tissues were used for validation.Results: KIRC patients had significant differences in CRG expression, prognosis, and biological functions between two CRG clusters. CRGs-related risk score was then determined. The prognosis, tumor mutation burden, immune cell infiltration, immune checkpoints, and the response of targeted inhibitors were remarkably different between high and low CRGs-related risk subtypes. CRGs-related high-risk subtype was characterized by immunosuppressive microenvironment with poor prognosis. Meanwhile, several targeted drugs showed distinct sensitivity between CRGs-related risk subtypes. Finally, TRPM3 was identified as a key CRG based on risk score in KIRC patients. TRPM3 mRNA and protein expression were significantly lower in KIRC tumors than in normal controls. Low TRPM3 expression was associated with poor prognosis in KIRC patients.Conclusion: Our study highlighted the promising prognostic value of CRGs in KIRC tumors. The evaluation of CRGs-related risk score will contribute to predicting prognosis and clinical therapy in KIRC patients

ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts

Recent progress in diffusion models has revolutionized the popular technology of text-to-image generation. While existing approaches could produce photorealistic high-resolution images with text conditions, there are still several open problems to be solved, which limits the further improvement of image fidelity and text relevancy. In this paper, we propose ERNIE-ViLG 2.0, a large-scale Chinese text-to-image diffusion model, which progressively upgrades the quality of generated images~by: (1) incorporating fine-grained textual and visual knowledge of key elements in the scene, and (2) utilizing different denoising experts at different denoising stages. With the proposed mechanisms, ERNIE-ViLG 2.0 not only achieves the state-of-the-art on MS-COCO with zero-shot FID score of 6.75, but also significantly outperforms recent models in terms of image fidelity and image-text alignment, with side-by-side human evaluation on the bilingual prompt set ViLG-300

Bacterial Microbiota and Metabolic Character of Traditional Sour Cream and Butter in Buryatia, Russia

Traditional sour cream and butter are widely popular fermented dairy products in Russia for their flavor and nutrition, and contain rich microbial biodiversity, particularly in terms of lactic acid bacteria (LAB). However, few studies have described the microbial communities and metabolic character of traditional sour cream and butter. The objective of this study was to determine the bacterial microbiota and metabolic character of eight samples collected from herdsmen in Buryatia, Russia. Using single-molecule real-time (SMRT) sequencing techniques, we identified a total of 294 species and/or subspecies in 169 bacterial genera, belonging to 14 phyla. The dominant phylum was Firmicutes (81.47%) and the dominant genus was Lactococcus (59.28%). There were differences between the bacterial compositions of the sour cream and butter samples. The relative abundances of Lactococcus lactis, Lactococcus raffinolactis, and Acetobacter cibinongensis were significantly higher in sour cream than in butter, and the abundance of Streptococcusthermophilus was significantly lower in sour cream than in butter. Using a pure culture method, 48 strains were isolated and identified to represent seven genera and 15 species and/or subspecies. Among these isolates, Lactococccus lactis subsp. lactis (22.50%) was the dominant LAB species. Ultra-performance liquid chromatography–quadrupole–time of flight mass spectrometry at elevated energy was used in combination with statistical methods to detect metabolite differences between traditional sour cream and butter. A total of 27,822 metabolites were detected in all samples, and Lys-Lys, isohexanal, palmitic acid, Leu-Val, and 2′-deoxycytidine were the most dominant metabolites found in all samples. In addition, 27 significantly different metabolites were detected between the sour cream and butter samples, including short peptides, organic acids, and amino acids. Based on correlation analyses between the most prevalent bacterial species and the main metabolites in sour cream, we conclude that there may be a connection between the dominant LAB species and these metabolites. This study combined omics techniques to analyze the bacterial diversity and metabolic character of traditional sour cream and butter, and we hope that our findings will enrich species resource libraries and provide valuable resources for further research on dairy product flavor

Quantitative Evaluation of the Phase Function Effects on Light Scattering and Radiative Transfer in Dispersed Systems

The light scattering properties of particles play important roles in radiative transfer in many dispersed systems, such as turbid atmosphere, ocean water, nanofluids, composite coatings and so on. As one of the scattering property parameters, the scattering phase functions of particles are strongly dependent on the particle size, size distribution, and morphology, as well as on the complex refractive indices of the particles and surrounding media. For the sake of simplicity, the empirical phase function models are widely used in many practical applications. In this work, we focus on the radiative transfer problem in dispersed systems composed of spherical particles, and give quantitative analyses of the impact of scattering phase functions on the radiative transfer process. We fit the scattering phase functions of four different types of practical dispersed systems using four previously proposed empirical phase function models, including the Henyey–Greenstein (HG) model, Cornette Shanks (CS) model, Reynold and McCormick (RM) model and two-term Reynolds–McCormick (TTRM) model. By comparing the radiative transfer characteristics (i.e., hemispherical reflectance, hemispherical transmittance and total absorptance) of dispersed layers calculated using the Monte Carlo method, the relative errors caused by using the empirical phase functions are systematically investigated. The results demonstrate that the HG, CS and RM models cause obvious errors in the calculation of hemispherical reflectance in many cases. Meanwhile, the induced errors show no obvious regularity, but are related to the particle size and layer optical thickness. Due to the good fitting effect in both forward and backward directions, the TTRM model provides significantly higher performances in fitting the phase functions of all considered cases than the widely used single-term parametrizations. Moreover, for different particle sizes and layer optical thicknesses, the induced errors of the TTRM model in radiative transfer characteristics are very small, especially for the case of polydisperse particles. Our results can be used to guide the design, analysis and optimization of dispersed systems in practical optics and photonics applications