3DGAUnet: 3D Generative Adversarial Networks with a 3D U-Net Based Generator to Achieve the Accurate and Effective Synthesis of Clinical Tumor Image Data for Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) presents a critical global health challenge, and early detection is crucial for improving the 5-year survival rate. Recent medical imaging and computational algorithm advances offer potential solutions for early diagnosis. Deep learning, particularly in the form of convolutional neural networks (CNNs), has demonstrated success in medical image analysis tasks, including classification and segmentation. However, the limited availability of clinical data for training purposes continues to represent a significant obstacle. Data augmentation, generative adversarial networks (GANs), and cross-validation are potential techniques to address this limitation and improve model performance, but effective solutions are still rare for 3D PDAC, where the contrast is especially poor, owing to the high heterogeneity in both tumor and background tissues. In this study, we developed a new GAN-based model, named 3DGAUnet, for generating realistic 3D CT images of PDAC tumors and pancreatic tissue, which can generate the inter-slice connection data that the existing 2D CT image synthesis models lack. The transition to 3D models allowed the preservation of contextual information from adjacent slices, improving efficiency and accuracy, especially for the poor-contrast challenging case of PDAC. PDAC's challenging characteristics, such as an iso-attenuating or hypodense appearance and lack of well-defined margins, make tumor shape and texture learning challenging. To overcome these challenges and improve the performance of 3D GAN models, our innovation was to develop a 3D U-Net architecture for the generator, to improve shape and texture learning for PDAC tumors and pancreatic tissue. Thorough examination and validation across many datasets were conducted on the developed 3D GAN model, to ascertain the efficacy and applicability of the model in clinical contexts. Our approach offers a promising path for tackling the urgent requirement for creative and synergistic methods to combat PDAC. The development of this GAN-based model has the potential to alleviate data scarcity issues, elevate the quality of synthesized data, and thereby facilitate the progression of deep learning models, to enhance the accuracy and early detection of PDAC tumors, which could profoundly impact patient outcomes. Furthermore, the model has the potential to be adapted to other types of solid tumors, hence making significant contributions to the field of medical imaging in terms of image processing models.

radioGWAS: link radiome to genome to discover driver genes with somatic mutations for heterogeneous tumor image phenotype in pancreatic cancer.

Addressing the significant level of variability exhibited by pancreatic cancer necessitates the adoption of a systems biology approach that integrates molecular data, biological properties of the tumors, and clinical features of the patients. In this study, a comprehensive multi-omics methodology was employed to examine a distinctive collection patient dataset containing rapid autopsy tumor and normal tissue samples as well as longitudinal imaging with a focus on pancreatic cancer. By performing a whole exome sequencing analysis on tumor and normal tissues to identify somatic gene variants and a radiomics feature analysis to tumor CT images, the genome-wide association approach established a connection between pancreatic cancer driver genes and relevant radiomics features, enabling a thorough and quantitative assessment of the heterogeneity of pancreatic tumors. The significant association between sets of genes and radiomics features revealed the involvement of genes in shaping tumor morphological heterogeneity. Some results of the association established a connection between the molecular level mechanism and their outcomes at the level of tumor structural heterogeneity. Because tumor structure and tumor structural heterogeneity are related to the patients' overall survival, patients who had pancreatic cancer driver gene mutations with an association to a certain radiomics feature have been observed to experience worse survival rates than cases without these somatic mutations. Furthermore, the outcome of the association analysis has revealed potential gene mutations and radiomics feature candidates that warrant further investigation in future research endeavors.

Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications.

As the most lethal major cancer, pancreatic cancer is a global healthcare challenge. Personalized medicine utilizing cutting-edge multi-omics data holds potential for major breakthroughs in tackling this critical problem. Radiomics and deep learning, two trendy quantitative imaging methods that take advantage of data science and modern medical imaging, have shown increasing promise in advancing the precision management of pancreatic cancer via diagnosing of precursor diseases, early detection, accurate diagnosis, and treatment personalization and optimization. Radiomics employs manually-crafted features, while deep learning applies computer-generated automatic features. These two methods aim to mine hidden information in medical images that is missed by conventional radiology and gain insights by systematically comparing the quantitative image information across different patients in order to characterize unique imaging phenotypes. Both methods have been studied and applied in various pancreatic cancer clinical applications. In this review, we begin with an introduction to the clinical problems and the technology. After providing technical overviews of the two methods, this review focuses on the current progress of clinical applications in precancerous lesion diagnosis, pancreatic cancer detection and diagnosis, prognosis prediction, treatment stratification, and radiogenomics. The limitations of current studies and methods are discussed, along with future directions. With better standardization and optimization of the workflow from image acquisition to analysis and with larger and especially prospective high-quality datasets, radiomics and deep learning methods could show real hope in the battle against pancreatic cancer through big data-based high-precision personalization.

Ornithinimicrobium cerasi sp. nov., isolated from the fruit of Cerasus pseudocerasus and emended description of the genus Ornithinimicrobium.

Strain CPCC 203383T, isolated from the surface-sterilized fruit of Cerasus pseudocerasus (Lindl.) G. Don, was taxonomically characterized based on a polyphasic investigation. It had the highest 16S rRNA gene sequence similarities with Ornithinimicrobium pekingense DSM 21552 (97.2 %) and O. kibberense DSM 17687T (97.2%). Phylogenetic analysis based on 16S rRNA gene sequences showed that the strain formed a distinct phyletic branch within the genus Ornithinimicrobium and the whole genome sequence data analyses supported that strain CPCC 203383T was phylogenetically related to the Ornithinimicrobium species. The isolate shared a range of phenotypic patterns reported for members of the genus Ornithinimicrobium, but also had a range of cultural, physiological and biochemical characteristics that separated it from related Ornithinimicrobium species. The menaquinone was MK-8(H4). The polar lipid profile consisted of diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylinositol (PI) and unidentified lipids (ULs). The major fatty acids (>5 %) were iso-C15 : 0, anteiso-C15 : 0, iso-C16:0, 9-methyl C16 : 0, iso-C17 : 0 and anteiso-C17 : 0. The cell wall peptidoglycan contains l-ornithine as diagnostic diamino acid and an interpeptide bridge consisting of L-Orn←L-Ala←Gly←D-Asp. The combined genotypic and phenotypic data indicated that the isolate represents a novel species of the genus Ornithinimicrobium, for which the name Ornithinimicrobium cerasi sp. nov. is proposed, with CPCC 203383T(=NBRC 113522T=KCTC 49200T) as the type strain. The DNA G+C composition is 72.3 mol%. The availability of new data allows for an emended description of the genus Ornithinimicrobium.

A multiscale hybrid mathematical model of epidermal-dermal interactions during skin wound healing.

Following injury, skin activates a complex wound healing programme. While cellular and signalling mechanisms of wound repair have been extensively studied, the principles of epidermal-dermal interactions and their effects on wound healing outcomes are only partially understood. To gain new insight into the effects of epidermal-dermal interactions, we developed a multiscale, hybrid mathematical model of skin wound healing. The model takes into consideration interactions between epidermis and dermis across the basement membrane via diffusible signals, defined as activator and inhibitor. Simulations revealed that epidermal-dermal interactions are critical for proper extracellular matrix deposition in the dermis, suggesting these signals may influence how wound scars form. Our model makes several theoretical predictions. First, basal levels of epidermal activator and inhibitor help to maintain dermis in a steady state, whereas their absence results in a raised, scar-like dermal phenotype. Second, wound-triggered increase in activator and inhibitor production by basal epidermal cells, coupled with fast re-epithelialization kinetics, reduces dermal scar size. Third, high-density fibrin clot leads to a raised, hypertrophic scar phenotype, whereas low-density fibrin clot leads to a hypotrophic phenotype. Fourth, shallow wounds, compared to deep wounds, result in overall reduced scarring. Taken together, our model predicts the important role of signalling across dermal-epidermal interface and the effect of fibrin clot density and wound geometry on scar formation. This hybrid modelling approach may be also applicable to other complex tissue systems, enabling the simulation of dynamic processes, otherwise computationally prohibitive with fully discrete models due to a large number of variables.

Intermediate cell states in epithelial-to-mesenchymal transition.

The transition of epithelial cells into a mesenchymal state (epithelial-to-mesenchymal transition or EMT) is a highly dynamic process implicated in various biological processes. During EMT, cells do not necessarily exist in 'pure' epithelial or mesenchymal states. There are cells with mixed (or hybrid) features of the two, which are termed as the intermediate cell states (ICSs). While the exact functions of ICS remain elusive, together with EMT it appears to play important roles in embryogenesis, tissue development, and pathological processes such as cancer metastasis. Recent single cell experiments and advanced mathematical modeling have improved our capability in identifying ICS and provided a better understanding of ICS in development and disease. Here, we review the recent findings related to the ICS in/or EMT and highlight the challenges in the identification and functional characterization of ICS.

Modeling craniofacial development reveals spatiotemporal constraints on robust patterning of the mandibular arch.

How does pattern formation occur accurately when confronted with tissue growth and stochastic fluctuations (noise) in gene expression? Dorso-ventral (D-V) patterning of the mandibular arch specifies upper versus lower jaw skeletal elements through a combination of Bone morphogenetic protein (Bmp), Endothelin-1 (Edn1), and Notch signaling, and this system is highly robust. We combine NanoString experiments of early D-V gene expression with live imaging of arch development in zebrafish to construct a computational model of the D-V mandibular patterning network. The model recapitulates published genetic perturbations in arch development. Patterning is most sensitive to changes in Bmp signaling, and the temporal order of gene expression modulates the response of the patterning network to noise. Thus, our integrated systems biology approach reveals non-intuitive features of the complex signaling system crucial for craniofacial development, including novel insights into roles of gene expression timing and stochasticity in signaling and gene regulation.

Multiscale modeling of layer formation in epidermis.

The mammalian skin epidermis is a stratified epithelium composed of multiple layers of epithelial cells that exist in appropriate sizes and proportions, and with distinct boundaries separating each other. How the epidermis develops from a single layer of committed precursor cells to form a complex multilayered structure of multiple cell types remains elusive. Here, we construct stochastic, three-dimensional, and multiscale models consisting of a lineage of multiple cell types to study the control of epidermal development. Symmetric and asymmetric cell divisions, stochastic cell fate transitions within the lineage, extracellular morphogens, cell-to-cell adhesion forces, and cell signaling are included in model. A GPU algorithm was developed and implemented to accelerate the simulations. These simulations show that a balance between cell proliferation and differentiation during lineage progression is crucial for the development and maintenance of the epidermal tissue. We also find that selective intercellular adhesion is critical to sharpening the boundary between layers and to the formation of a highly ordered structure. The long-range action of a morphogen provides additional feedback regulations, enhancing the robustness of overall layer formation. Our model is built upon previous experimental findings revealing the role of Ovol transcription factors in regulating epidermal development. Direct comparisons of experimental and simulation perturbations show remarkable consistency. Taken together, our results highlight the major determinants of a well-stratified epidermis: balanced proliferation and differentiation, and a combination of both short- (symmetric/asymmetric division and selective cell adhesion) and long-range (morphogen) regulations. These underlying principles have broad implications for other developmental or regenerative processes leading to the formation of multilayered tissue structures, as well as for pathological processes such as epidermal wound healing.

Gene Expression Noise Enhances Robust Organization of the Early Mammalian Blastocyst.

A critical event in mammalian embryo development is construction of an inner cell mass surrounded by a trophoectoderm (a shell of cells that later form extraembryonic structures). We utilize multi-scale, stochastic modeling to investigate the design principles responsible for robust establishment of these structures. This investigation makes three predictions, each supported by our quantitative imaging. First, stochasticity in the expression of critical genes promotes cell plasticity and has a critical role in accurately organizing the developing mouse blastocyst. Second, asymmetry in the levels of noise variation (expression fluctuation) of Cdx2 and Oct4 provides a means to gain the benefits of noise-mediated plasticity while ameliorating the potentially detrimental effects of stochasticity. Finally, by controlling the timing and pace of cell fate specification, the embryo temporally modulates plasticity and creates a time window during which each cell can continually read its environment and adjusts its fate. These results suggest noise has a crucial role in maintaining cellular plasticity and organizing the blastocyst.

Tuning water transport through nanochannels by changing the direction of an external electric field.

The transport properties of water through a nanochannel influenced by the direction of an external electric field has been investigated by using molecular dynamics simulations. Water molecules flow unidirectionally across the nanochannel under a uniform external electric field without an osmotic pressure. It is found that the direction of the external field plays an important role in the interactions and dipole orientations of water molecules in the nanochannel, accordingly changing the net water flux dramatically. Most importantly, a critical angle (θC) between the external field and the nanochannel axis is found. The average net water flux increases as θ increases for θ≤θC but decreases sharply to a near-zero value for a further increase of θ. The maximum value of the average net water flux is 7.33 times as high as the value when the electric field is along the nanochannel axis. Our findings are of great practical importance for nanomolecular engineering, which provide a possible strategy for designing novel controllable water nanopumps.

The Interplay between Wnt Mediated Expansion and Negative Regulation of Growth Promotes Robust Intestinal Crypt Structure and Homeostasis.

The epithelium of the small intestinal crypt, which has a vital role in protecting the underlying tissue from the harsh intestinal environment, is completely renewed every 4-5 days by a small pool of stem cells at the base of each crypt. How is this renewal controlled and homeostasis maintained, particularly given the rapid nature of this process? Here, based on the recent observations from in vitro "mini gut" studies, we use a hybrid stochastic model of the crypt to investigate how exogenous niche signaling (from Wnt and BMP) combines with auto-regulation to promote homeostasis. This model builds on the sub-cellular element method to account for the three-dimensional structure of the crypt, external regulation by Wnt and BMP, internal regulation by Notch signaling, as well as regulation by internally generated diffusible signals. Results show that Paneth cell derived Wnt signals, which have been observed experimentally to sustain crypts in cultured organs, have a dramatically different influence on niche dynamics than does mesenchyme derived Wnt. While this signaling can indeed act as a redundant backup to the exogenous gradient, it introduces a positive feedback that destabilizes the niche and causes its uncontrolled expansion. We find that in this setting, BMP has a critical role in constraining this expansion, consistent with observations that its removal leads to crypt fission. Further results also point to a new hypothesis for the role of Ephrin mediated motility of Paneth cells, specifically that it is required to constrain niche expansion and maintain the crypt's spatial structure. Combined, these provide an alternative view of crypt homeostasis where the niche is in a constant state of expansion and the spatial structure of the crypt arises as a balance between this expansion and the action of various sources of negative regulation that hold it in check.

[Isolation and physiological characteristics of endophytic actinobacteria from medicinal plants].

OBJECTIVE: To isolate, incubate and characterize cultivable endophytic antinobacteria from medicinal plants, and analyze the diversity of the endophytic antinobacteria, then explore the novel microbial resources. METHODS: Ten media were used to isolate endophytic antinobacteria from 37 fresh medicinal plant tissue samples. The optimal cultivation conditions for endophytic antinobacteria were determined by comparison. Based on the morphology of the colonies and cells of the new isolates, we chose 174 isolates to analyze their 16S rRNA gene sequences and the diversity of the medicinal plant endophytic antinobacteria. The physiological characteristics of 27 representative strains were studied using Biolog GEN III MicroPlates, API 50CH and API ZYM kits. RESULTS: In total 940 endophytics affiliated to 47 genera of 30 families were isolated, among which more than 600 actinobacteria belonged to 34 genera and 7 unknown taxa. Good growth of the endophytic antinobacteria on PYG (peptone-yeast-glycerol) medium with pH 7.2 at 28-32 degrees C was observed. Physiological characteristics differences of these isolates related to their phylogenetic relationships. Greater differences were shown among the strains from the same host plants than those from differ,ent plants grown in the same area. CONCLUSION: There are great diverse endophytic actinobacteria inside the medicinal plants. No direct relationship of the endophytic actinobacteria from medicinal plants with the host plants in the sole carbon source utilization, fermentation of carbon sources to produce acid and the enzyme activities was found, while it seemed that the physiological characteristics of the isolates related to the geographical distribution of their host.

Luteimonas huabeiensis sp. nov., isolated from stratum water.

A yellow-coloured bacterial strain, designated HB2(T), isolated from stratum water was investigated using a polyphasic taxonomic approach. Cells were Gram-stain-negative, aerobic, non-spore-forming, non-flagellated and rod-shaped. Phylogenetic analysis based on 16S rRNA gene sequences showed that the strain was a member of the genus Luteimonas, its three closest neighbours being Luteimonas aquatica BCRC 17731(T) (97.5% similarity), Luteimonas marina JCM 12488(T) (97.3%) and Luteimonas aestuarii DSM 19680(T) (96.9%). Strain HB2(T) could clearly be distinguished from these type strains based on phylogenetic analysis, DNA-DNA hybridization, fatty acid composition and a range of physiological and biochemical characteristics. It is evident from the genotypic and phenotypic data that strain HB2(T) represents a novel species of the genus Luteimonas, for which the name Luteimonas huabeiensis sp. nov. is proposed. The type strain is HB2(T) ( =DSM 26429(T) =CICC 11005s(T)).

Allonocardiopsis opalescens gen. nov., sp. nov., a new member of the suborder Streptosporangineae, from the surface-sterilized fruit of a medicinal plant.

An endophytic actinomycete, designated strain I10A-01259(T), was isolated from a surface-sterilized fruit of Lonicera maackii (Rupr.) Maxim., a medicinal plant, which was collected from a suburb of Beijing, China. Whole-cell hydrolysates of the isolate contained galactose and meso-diaminopimelic acid. The predominant phospholipids were phosphatidylglycerol and diphosphatidylglycerol; the menaquinones consisted mainly of MK-9, MK-11 and MK-12, with a minor amount of MK-10. The major fatty acids were iso-C16 : 0, anteiso-C15 : 0 and iso-C15 : 0. Comparative analysis of 16S rRNA gene sequences indicated that strain I10A-01259(T) was most closely related to Nocardiopsis arabia S186(T) (93.2 % sequence similarity), Thermobifida halotolerans YIM 90462(T) (93.0 %) and other strains of genera within the families Nocardiopsaceae and Thermomonosporaceae. On the phylogenetic tree based on 16S rRNA gene sequences, strain I10A-01259(T) fell within the radius of the suborder Streptosporangineae, in which the strain formed a distinct lineage next to the genera of the families Nocardiopsaceae and Thermomonosporaceae. Based on the data from our polyphasic taxonomic study, a novel genus and species, Allonocardiopsis opalescens gen. nov., sp. nov., are proposed within the suborder Streptosporangineae. The type strain of Allonocardiopsis opalescens is strain I10A-01259(T) ( = CPCC 203428(T)  = DSM 45601(T)  = KCTC 19844(T)).

Nocardioides perillae sp. nov., isolated from surface-sterilized roots of Perilla frutescens.

A Gram-stain-positive, rod-shaped actinobacterium, designated strain I10A-01402(T), was isolated from surface-sterilized roots of a medicinal plant, Perilla frutescens, collected in a suburb of Beijing, China. Chemotaxonomically, the strain contained ll-diaminopimelic acid as the diagnostic diamino acid and MK-8(H4) as the predominant menaquinone. The phospholipids were diphosphatidylglycerol, phosphatidylglycerol and phosphatidylinositol. The major fatty acids were C17 : 1ω9c, C18 : 1ω9c, C17 : 0, C16 : 0 and iso-C16 : 0. The genomic DNA G+C content was 70.4 mol%. 16S rRNA gene sequence analysis indicated that strain I10A-01402(T) belonged to the genus Nocardioides. Phylogenetic analyses based on 16S rRNA gene sequences showed that the isolate formed a robust cluster with Nocardioides ginsengisegetis Gsoil 485(T), N. koreensis MSL-09(T) and N. alkalitolerans KSL-1(T). On the basis of the evidence from our polyphasic taxonomic study, a novel species, Nocardioides perillae sp. nov., is proposed. The type strain is I10A-01402(T) ( = CPCC 203382(T)  = DSM 24552(T)  = KCTC 29022(T)).

[Recent advance on the genus nocardioides--a review].

The Nocardioides genus was established by Prauser H. in 1976 according to morphological and physiological characteristics, as well as partial chemotaxonomic analyses of 17 nocardio-form actinobacteria isolated from soil, based on which a novel species Nocardioides albus was proposed as the type species. With the development in the technologies of isolation, purification and taxonomy, more and more members of this genus with varied morphological, physiological and biochemical characteristics were increasingly discovered from different sources, while all of them shared the same diagnostic characteristics of the genus. In the past 50 years, some of the members of the genus Nocardioides were ever transferred in or out and then some species description was ever emended. Till date, there were 56 validly described species in this genus. Some members of this genus were used in agriculture and industry. The objective of this review is to summarize the research advances in the genus Nocardioides, such as the changes of the taxonomic position and emendation description of the species as well as the application prospect in industry and agriculture.

High density waves of the bacterium Pseudomonas aeruginosa in propagating swarms result in efficient colonization of surfaces.

This work describes a new, to our knowledge, strategy of efficient colonization and community development where bacteria substantially alter their physical environment. Many bacteria move in groups, in a mode described as swarming, to colonize surfaces and form biofilms to survive external stresses, including exposure to antibiotics. One such bacterium is Pseudomonas aeruginosa, which is an opportunistic pathogen responsible for both acute and persistent infections in susceptible individuals, as exampled by those for burn victims and people with cystic fibrosis. Pseudomonas aeruginosa often, but not always, forms branched tendril patterns during swarming; this phenomena occurs only when bacteria produce rhamnolipid, which is regulated by population-dependent signaling called quorum sensing. The experimental results of this work show that P. aeruginosa cells propagate as high density waves that move symmetrically as rings within swarms toward the extending tendrils. Biologically justified cell-based multiscale model simulations suggest a mechanism of wave propagation as well as a branched tendril formation at the edge of the population that depends upon competition between the changing viscosity of the bacterial liquid suspension and the liquid film boundary expansion caused by Marangoni forces. Therefore, P. aeruginosa efficiently colonizes surfaces by controlling the physical forces responsible for expansion of thin liquid film and by propagating toward the tendril tips. The model predictions of wave speed and swarm expansion rate as well as cell alignment in tendrils were confirmed experimentally. The study results suggest that P. aeruginosa responds to environmental cues on a very short timescale by actively exploiting local physical phenomena to develop communities and efficiently colonize new surfaces.

Interconnected cavernous structure of bacterial fruiting bodies.

The formation of spore-filled fruiting bodies by myxobacteria is a fascinating case of multicellular self-organization by bacteria. The organization of Myxococcus xanthus into fruiting bodies has long been studied not only as an important example of collective motion of bacteria, but also as a simplified model for developmental morphogenesis. Sporulation within the nascent fruiting body requires signaling between moving cells in order that the rod-shaped self-propelled cells differentiate into spores at the appropriate time. Probing the three-dimensional structure of myxobacteria fruiting bodies has previously presented a challenge due to limitations of different imaging methods. A new technique using Infrared Optical Coherence Tomography (OCT) revealed previously unknown details of the internal structure of M. xanthus fruiting bodies consisting of interconnected pockets of relative high and low spore density regions. To make sense of the experimentally observed structure, modeling and computer simulations were used to test a hypothesized mechanism that could produce high-density pockets of spores. The mechanism consists of self-propelled cells aligning with each other and signaling by end-to-end contact to coordinate the process of differentiation resulting in a pattern of clusters observed in the experiment. The integration of novel OCT experimental techniques with computational simulations can provide new insight into the mechanisms that can give rise to the pattern formation seen in other biological systems such as dictyostelids, social amoeba known to form multicellular aggregates observed as slugs under starvation conditions.

MULTISCALE MODELING OF PSEUDOMONAS AERUGINOSA SWARMING.

Experiments have shown that wild type P. aeruginosa swarms much faster than rhlAB mutants on 0.4% agar concentration surface. These observations imply that development of a liquid thin film is an important component of the self-organized swarming process. A multiscale model is presented in this paper for studying interplay of key hydrodynamical and biological mechanisms involved in the swarming process of P. aeruginosa. This model combines a liquid thin film equation, convection-reaction-diffusion equations and a cell-based stochastic discrete model. Simulations demonstrate how self-organized swarming process based on the microscopic individual bacterial behavior results in complicated fractal type patterns at macroscopic level. It is also shown that quorum sensing mechanism causing rhamnolipid synthesis and resulting liquid extraction from the substrate lead to the fast swarm expansion. Simulations also demonstrate formation of fingers (tendrils) at the edge of a swarm which have been earlier observed in experiments.

Antioxidant compounds from propolis collected in Anhui, China.

The antioxidant activities of the chloroform, ethyl acetate and n-butanol extract fractions from propolis collected in Anhui, China were evaluated in this study. The ethyl acetate fraction contained the highest amount of total phenolics and total flavonoids, and showed the greatest 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) radical scavenging capacities and Ferric Reducing/Antioxidant Power (FRAP). The antioxidant activity of twenty-two compounds isolated from the ethyl acetate fraction was also evaluated using the above-mentioned three assays. The results indicated that phenolics contributed to the antioxidant activity of propolis collected in Anhui, China. Therefore, propolis collected in Anhui, China and its phenolics might be used as a natural antioxidant.