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Checklist and analysis of the vascular flora in river valleys of Altay region Xinjiang China
The role of GALAD score in the surveillance of hepatocellular carcinoma
Deep learning-driven drug response prediction and mechanistic insights in cancer genomics
Regulatory helix plays a key role in genetic ON–OFF switching for the 2′-deoxyguanosine-sensing mRNA element
The modeling and condition analysis of nondestructive testing based on ESPI for internal defects of materials
Electronic speckle pattern interferometry (ESPI) is a non-contact, full field, real-time measurement technology, which judges the position and size of the internal defects of the object through the external deformation caused by the internal defects under certain loading conditions. We present the effect of loading mode and loading parameters to the defect detection. Firstly, the finite element analysis method is used to establish models to simulate the defect detection of aluminum plates under different loading conditions. Mechanical models are established to simulate different loading mode, loading sizes, defect depth and defect sizes. Secondly, the interpolation method based on partial differential equation is applied to obtain the whole field out-of-plane displacement after finite element analysis. Thirdly, by analyzing the interference fringe patterns obtained from the out-of-plane displacement caused by different defects, the deformation rules in the detection of internal defects of aluminum plates are obtained under different loading conditions. Finally, the loading mode and loading range suitable for the internal defect detection of aluminum materials are summarized. This method can provide a basis for the selection of loading mode and parameters in the ESPI experimental system.
Mendelian randomization study reveals causal association between skin microbiome and skin cancers
Effect of fitting tolerance on mechanical performance of CFRP/Al double-lap blind riveted joints
Field study on the utility of fluid obtained from testicles as a sample for detecting antibodies to selected swine pathogens
Abstract Processing fluid is a promising alternative to blood for monitoring porcine diseases, although certain aspects of its routine use remain unclear. This study evaluated serum from females and males, along with corresponding testicular only processing fluid, for antibodies against Actionbacillus pleuropneumonie, hepatitis E virus, porcine epidemic diarrhea virus, influenza A virus, Erysipetothrix rhusiopathie and Mycoplasma hyopneumoniae, using commercial ELISAs (ID Screen APP, Hepatitis E, PEDV, Influenza A from ID Vet, France; Civtest suis SE/MR from Hipra, Spain; and Mycoplasma hyopneumoniae from Idexx, USA). Differences in the proportion of positive results across sample types were analysed to assess the utility of testis-derived processing fluid for litter-level health monitoring. ROC analysis was used to establish optimal cut-offs for processing fluid, followed by evaluation of diagnostic performance using both manufacturer-recommended and ROC-derived thresholds. A pooling simulation was also performed. Results indicate that processing fluid collected exclusively from testes can detect antibodies against selected pathogens effectively. Some ELISA kits validated for serum may be applicable to processing fluid, provided that appropriate cut-off values are determined for this sample type. However, pooling processing fluid samples may reduce sensitivity and increase the risk of false-negative results. These findings highlight the potential of testis-derived processing fluid for large-scale serological surveillance while underscoring the need for test-specific validation.
Yeast-derived glycolipids disrupt Candida biofilm and inhibit expression of genes in cell adhesion
Improvement strategies of athlete’s concentration level based on visual attention model
Novel gut bacteria species Paenibacillus ilasis with phosphorus degrading and soluble starch hydrolysis abilities isolated from fresh feces of rhinoceros
Abstract The genus Paenibacillus, known for its diverse sources, is a valuable reservoir of antimicrobial compounds, enzymes and other valuable chemicals, with applications in medicine, agriculture, and bioremediation. Despite this, Paenibacillus strains, particularly those isolated from unique environments, remain underexplored, limiting our understanding of their potential, capabilities and taxonomic classifications. The gut microbiome of large herbivores, such as rhinoceroses, harbors underexplored microbial diversity with unique metabolic capabilities. In this study, a Gram-stain-negative, facultatively aerobic, motile, spore-forming, rod-shaped bacterial strain, NGMCC 1.200843T (= CGMCC 1.64763T = JCM 37214T), was isolated from fresh rhinoceros feces and characterized its taxonomic status and metabolic potential. Phylogenetic, phenotypic, and chemotaxonomic analyses confirmed the isolate as a novel species within the genus Paenibacillus, closely related to Paenibacillus lautus DSM 3035T (98.62% 16S rRNA gene similarity). The average nucleotide identity (ANI) and the digital DNA–DNA hybridization values were below the threshold for species delineation. The major cellular fatty acids were anteiso-C15:0, C16:0 and iso-C16:0 (> 10%) and the polar lipid profile contained diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), two unidentified phospholipids (PL1–2) and one phosphatidyl choline (PC). The total DNA G + C content was 49.69 mol%. The isolate exhibited significant phosphate solubilization and starch hydrolysis activities in plate assays, suggesting a role in nutrient cycling within the rhinoceros gut. We propose the name Paenibacillus ilasis sp. nov. for this strain. These findings enhance our understanding of gut microbial diversity in herbivores and lay the foundation for future applications in agriculture or industry.
Exploration of shared pathogenic factors and causative genes in early-stage endometrial cancer and osteoarthritis
Breast cancer detection based on histological images using fusion of diffusion model outputs
Abstract The precise detection of breast cancer in histopathological images remains a critical challenge in computational pathology, where accurate tissue segmentation significantly enhances diagnostic accuracy. This study introduces a novel approach leveraging a Conditional Denoising Diffusion Probabilistic Model (DDPM) to improve breast cancer detection through advanced segmentation and feature fusion. The method employs a conditional channel within the DDPM framework, first trained on a breast cancer histopathology dataset and extended to additional datasets to achieve regional-level segmentation of tumor areas and other tissue regions. These segmented regions, combined with predicted noise from the diffusion model and original images, are processed through an EfficientNet-B0 network to extract enhanced features. A transformer decoder then fuses these features to generate final detection results. Extensive experiments optimizing the network architecture and fusion strategies were conducted, and the proposed method was evaluated across four distinct datasets, achieving a peak accuracy of 92.86% on the BRACS dataset, 100% on the BreCaHAD dataset, 96.66% the ICIAR2018 dataset. This approach represents a significant advancement in computational pathology, offering a robust tool for breast cancer detection with potential applications in broader medical imaging contexts.
NDRG1 and its family members: More than just metastasis suppressor proteins and targets of thiosemicarbazones
Sequence–lithofacies paleogeographic evolution and its control on deep and ultra–deep reservoir types: A case study of the Permian Maokou Formation in northeastern Sichuan Basin
The Middle Permian Maokou Formation in northeastern Sichuan Basin has been explored with continuous breakthroughs in recent years, but its sequence–lithofacies paleogeographic characteristics and tectonic–sedimentary evolution process are still unclear. Based on outcrops, well logging and seismic data, this paper focuses on the sequence stratigraphic, lithofacies paleogeography and tectonic–sedimentary evolution of the Maokou Formation in northeastern Sichuan Basin. The results show that two third-order sequences (SQ1, SQ2) are developed in the Middle Permian Maokou Formation. SQ1 can be divided into three fourth-order sequences (SQ1–1, SQ1–2, and SQ1–3). SQ1–1 and SQ1–2 are generally carbonate ramps, SQ1–3 turns to rimmed carbonate platform, and its stratigraphic thickness and sedimentary facies are distributed in NW–SE direction. The succession development of carbonate platform in SQ2 sedimentary period. It is believed that, due to the NE–trending extensional stress generated by the continuous subduction of the Mianlue Ocean and the regional sea level eustacy, the Permian tectonic–sedimentary differentiation in the northeastern Sichuan Basin had begun from the early stage of the Middle Permian and gradually intensified. As a result, the platform–basin dominated deep-water deposits gradually expanded into the basin along SW–NE direction, and evolved into the features of “platform in the south and platform–basin in the north” at the end of the Maokou Formation deposition. As such, large-scale high-energy shoals are developed above the platform region during the SQ1–3 and SQ2 depositional periods, making it a prospect of conventional gas. Potential source rocks are developed in the platform-basin region, which is a potential prospect of unconventional oil and gas. The results suggest that the tectonic–sedimentary differentiation induced by the continuous subduction of Mianlue Ocean makes the Maokou Formation an ideal reservoir for both conventional and unconventional hydrocarbon.
Comprehensive gene expression analysis of organoid-derived healthy human colonic epithelium and cancer cell line stimulated with live probiotic bacteria
Responsiveness of the mini-balance evaluation systems test, dynamic gait index, Berg balance scale, and performance-oriented mobility assessment in parkinson’s disease
Dual-frequency modulation in microwave-optical double resonance for manipulation of atomic populations
Sustainable production of high strength fiber reinforced mortars using volcanic ash and magnetized water treatment technology
Abstract In recent decades, concerns about the high cement consumption and its associated carbon footprint have prompted significant efforts in the construction sector to incorporate alternative materials into cementitious composites. This study focused on the development of a sustainable approach to produce high strength fiber reinforced cementitious mortar (HS-FRCM) and high strength fiber reinforced geopolymer mortar (HS-FRGM). The proposed mortars incorporate volcanic ash (VA) as partial replacements for conventional components, with substitution levels of up to 80%. Furthermore, magnetized water (MW) was utilized as the mixing water in producing both HS-FRCM and HS-FRGM, replacing tap water (TW) for sustainable mortars. Four different curing conditions were used; tap water, seawater, air, and sunlight. The slump values, mechanical performance, durability, and microstructural were conducted and analyzed. The results indicated that VA significantly enhanced HS-FRCM workability by up to 150%, while it had a less pronounced effect on HS-FRGM workability. When 20% VA was used, the 28-day compressive strength of HS-FRCM was not affected, but the compressive strength of HS-FRGM decreased by only 6%. The highest compressive strength was recorded for both HS-FRCM and HS-FRGM when cured in tap water, compared to other conditions of curing. Utilizing MW improved HS-FRCM and HS-FRGM workability by up to 100%, and the compressive strengths increased by as much as 15%. The microstructural analyses revealed that the use of MW resulted in a denser structure with a stronger bond between the fibers and the matrix, as well as fewer microcracks and pores, compared to mixtures prepared with TW. Fourier-transform infrared (FTIR) spectroscopy indicated the effectiveness of using VA and MW in enhancing hydration process.