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Although many types of halogenated compounds are known to bioaccumulate in humans, few are routinely biomonitored and many have remained uncharacterized in human exposome studies due to a lack of high-sensitivity and high-resolution analytical methods. In this study, we discovered tetraphenylphosphonium chloride (Ph

Most research in machine learning for data streams has focused on classification algorithms, whereas regression methods have received a lot less attention. This paper proposes Self-Optimising K-Nearest Leaves (SOKNL), a novel forest-based algorithm for streaming regression problems. Specifically, the Adaptive Random Forest Regression, a state-of-the-art online regression algorithm is extended like this: in each leaf, a representative data point – also called centroid – is generated by compressing the information from all instances in that leaf. During the prediction step, instead of letting all trees in the forest participate, the distances between the input instance and all centroids from relevant leaves are calculated, only k trees that possess the smallest distances are utilised for the prediction. Furthermore, we simplify the algorithm by introducing a mechanism for tuning the k values, which is dynamically and automatically optimised based on historical information. This new algorithm produces promising predictive results and achieves a superior ranking according to statistical testing when compared with several standard stream regression methods over typical benchmark datasets. This improvement incurs only a small increase in runtime and memory consumption over the basic Adaptive Random Forest Regressor.

It is challenging to investigate fast supramolecular processes due to the lack of appropriate characterization methods with high structural resolution. In thisstudy, microfluidic nuclear magnetic resonance (μFNMR) spectroscopy was employed to monitor the kinetics of threading and dethreading of a pseudo[6]rotaxane system. By employing high time resolution μF-NMR, 1H and two-dimensional (2D) rotating frame nuclear Overhauser effect spectroscopy (ROESY) NMR spectra were recorded at any timepoint within 1.5 s after the onset of the process. This technique enabled the successful identification of kinetic intermediates and rate-determining steps,usually impossible to determine by other spectroscopic techniques. Thus, our study demonstrates the capability of μF-NMR in investigating the mechanismof complex supramolecular systems.

Inspired by life assembly systems, the construction of transient assembly systems with spatiotemporal control is crucial for developing intelligent materials. A widely adopted strategy is to couple the self-assembly with chemical reaction networks. However, orchestrating the kinetics of multiple reactions and assembly/disassembly processes without crosstalk in homogeneous solutions is not an easy task. To address this challenge, we propose a generic strategy by separating components into different phases, therefore, the evolution process of the system could be easily regulated by controlling the transport of components through different phases. Interference of multiple components that are troublesome in homogeneous systems could be diminished. Meanwhile, limited experimental parameters are involved in tuning the mass transfer instead of the complex kinetic matching and harsh reaction selectivity requirements. As a proof of concept, a transient metallo-supramolecular polymer (MSP) with dynamic luminescent color was constructed in an oil-water biphasic system by controlling the diffusion of the deactivator (water molecules) from the water phase into the oil phase. The lifetime of transient MSP could be precisely regulated not only by the content of chemical fuel, but also factors that affect the efficiency of mass transfer in between phases, such as the volume of the water phase, the stirring rate, and the temperature. We believe this strategy can be further extended to multi-compartment systems with passive diffusion or active transport of components, towards life-like complex assembly systems.

Kinetic control over structures and functions of complex assembly systems has aroused widespread interest. Understanding the complex pathway and transient intermediates is helpful to decipher how multiple components evolve into complex assemblies. However, for supramolecular polymerizations, thorough and quantitative kinetic analysis is often overlooked. Challenges remain in collecting the information of structure and content of transient intermediates

Numerous studies have implicated Gα-interacting, vesicle-associated protein (GIV) in the development and metastasis of various cancers. However, its role remains unclear in liver hepatocellular carcinoma (LIHC). We aimed to demonstrate the relationship between GIV and LIHC based on The Cancer Genome Atlas database. We use the Gene Expression Profiling Interactive Analysis and UALCAN to explore the expression of GIV and the survive analysis of GIV in patients with LIHC, genetic alteration analysis, immune infiltration analysis, functional enrichment, protein-protein interaction network analyses, and transcription factor targets of GIV-correlated genes and GIV-interacting genes were performed this study. GIV expression was significantly elevated in LIHC tissues. Remarkable correlation was established between GIV expression and LIHC pathological stage. Low expression of GIV in tumor tissues had a better prognosis than GIV-high expression. GIV alteration frequency was 1.44% in patients with LIHC. GIV-unaltered patients had better survival than GIV-altered ones. Moreover, GIV expression level in LIHC significantly correlated with the infiltration level of immune cells and cancer-associated fibroblasts. The functions of differentially expressed GIVs are associated with the cell cycle pathway. Our data imply that E2F4, E2F1, MYC, and MYCN are key transcription factors for GIV-correlated genes and GIV-interacted genes. GIV may be an adverse prognostic factor for patients with LIHC; it also can be a potential therapeutic target against LIHC. Further studies are required to validate our findings.

Interfacial host–guest complexation offers a versatile way to functionalize nanomaterials. However, the complicated interfacial environment and trace amounts of components present at the interface make the study of interfacial complexation very difficult. Herein, taking the advantages of near-single-molecule level sensitivity and molecular fingerprint of surface-enhanced Raman spectroscopy (SERS), we reveal that a cooperative effect between cucurbit[7]uril (CB[7]) and methyl viologen (MV2+2I−) in aggregating Au NPs originates from the cooperative adsorption of halide counter anions I−, MV2+, and CB[7] on Au NPs surface. Moreover, similar SERS peak shifts in the control experiments using CB[n]s but with smaller cavity sizes suggested the occurrence of the same guest complexations among CB[5], CB[6], and CB[7] with MV2+. Hence, an unconventional exclusive complexation model is proposed between CB[7] and MV2+ on the surface of Au NPs, distinct from the well-known 1:1 inclusion complexation model in aqueous solutions. In summary, new insights into the fundamental understanding of host–guest interactions at nanostructured interfaces were obtained by SERS, which might be useful for applications related to host–guest chemistry in engineered nanomaterials.

Inflammatory bowel disease (IBD) is a global disease that is in increasing incidence. The gut, which contains the largest amount of lymphoid tissue in the human body, as well as a wide range of nervous system components, is integral in ensuring intestinal homeostasis and function. By interacting with gut microbiota, immune cells, and the enteric nervous system, the intestinal barrier, which is a solid barrier, protects the intestinal tract from the external environment, thereby maintaining homeostasis throughout the body. Destruction of the intestinal barrier is referred to as developing a "leaky gut," which causes a series of changes relating to the occurrence of IBD. Changes in the interactions between the intestinal barrier and gut microbiota are particularly crucial in the development of IBD. Exploring the leaky gut and its interaction with the gut microbiota, immune cells, and the neuroimmune system may help further explain the pathogenesis of IBD and provide potential therapeutic methods for future use.

Chlorinated paraffins (CPs) are chemicals with high production volumes that can accumulate at high levels in general populations. The pharmacokinetics of CPs as pollutants is unknown, and there is no evidence that the medium chain chlorinated paraffins (MCCPs) and long chain chlorinated paraffins (LCCPs) are safe replacements for short chain chlorinated paraffins (SCCPs). In this study, SCCPs, MCCPs, and LCCPs were first in vivo and in vitro exposed to rat and liver microsomes, respectively. Toxicokinetics of these compounds were assessed and used to establish the corresponding physiologically based pharmacokinetic (PBPK) models in rats. More than 90% of ingested CPs were deposited in the liver and fat, and the compounds were extremely resistant to metabolism and mostly eliminated via biliary excretion. Then, humans' external and internal exposures to CPs were investigated for one year in Shenzhen, South China. The results were used to calibrate the key parameters for the establishment of a PBPK model in humans. In the PBPK models of rats and humans, the rate of biliary excretion had the greatest influence on the accumulated levels and half-lives of CPs. The body half-lives of human were estimated to be 5.1, 1.2, and 0.6 years for SCCPs, MCCPs, and LCCPs, respectively, suggesting the high accumulation of SCCPs in humans compared to other CPs.

Cage catalysis has emerged as an important approach for mimicking enzymatic reactions by increasing the reaction rate and/or product selectivity of various types of covalent reactions. Here, we extend the catalytic application of cage compounds to the field of non-covalent molecular assembly. Acid-stable chiral imine cages are found to catalyze the supramolecular polymerization of porphyrins with an accelerated assembling rate and increased product enantioselectivity. Because the imine cages have a stronger interaction with porphyrin monomers and a weaker interaction with porphyrin assemblies, they can fully automatically detach from the assembled products without being consumed during the catalytic process. We reveal the kinetics of the auto-detachment of cages and the chirality growth of the assemblies using spectroscopic characterization studies. We find that the passivation groups attached to the cages are important for maintaining the structural stability of the cages during catalyzed assembly, and that the steric geometries of the cages can profoundly affect the efficiency of chiral regulation. This strategy demonstrates a new type of catalytic application of cage compounds in the field of molecular assembly, and paves the way to controlling supramolecular polymerization through a catalytic pathway.

Rheumatoid arthritis (RA) is an chronic autoimmune disease and characterized by high incidence. However, there is no effective therapies for RA. Therefore, it is urgent to discover new drugs for RA treatment. Nuclear factor erythroid 2 (NF-E2)-related factor (Nrf2) can effectively protect against arthritic inflammatory diseases through diverse stages, such as regulating redox balance, detoxification, metabolism and inflammation. Dimethyl fumarate (DMF), targets the Nrf2 pathway, was approved by FDA for the clinical treatment of multiple sclerosis (MS), which is another autoimmune disease. The latest report shown that DMF ameliorates complete Freund's adjuvant-induced arthritis in rats through activation of the Nrf2/HO-1 signaling pathway. Hence, Nrf2 serves as an important target for inflammation interference and oxidative stress of macrophages and RASFs in RA; therefore, it can be adopted as an effective therapeutic approach in the future. Rheumatoid arthritis synovial fibroblasts (RASFs) play crucial roles in the RA pathogenesis. Our results revealed that 7-deacetyl-gedunin (7-d-GDN), derived from fruits of Toona sinensis (A. Juss.) Roem, significantly inhibited RASFs proliferation in dose- and time- dependent manners and inhibited cell viability in MH7A cells, which is a kind of immortal cell line from joints of patients with RA. Additionally, 7-d-GDN remarkably down-regulated MMP-1/3/9/13 in RASFs, IL-6 and IL-33 in MH7A cells. Besides, 7-d-GDN sharply inhibited reactive oxygen species (ROS) in RASFs. Further mechanistic study demonstrated that 7-d-GDN induced heme oxygenase-1 (HO-1), NAD(P)H dehydrogenase quinone 1(NQO1), which all participated in suppressing of oxidative stress. Additionally, 7-d-GDN increased sequestosome 1 (SQSTM1, p62), causing down-regulating Kelch-like ECH-associated protein 1 (Keap1), which resulting in NF-E2-related factor 2 (Nrf2) cytoplasm accumulation and subsequently translocation into nucleus. Collectively, 7-d-GDN exerts the anti-inflammatory effect through regulating anti-oxidative enzymes via p62/ Nrf2/ARE signaling. All suggest that the potential of 7-d-GDN in suppression of inflammation, especially antagonizing RA severity. Our works support for drugs discovery in RA treatment.

Dendrobium mixture (DM) is a patent Chinese herbal formulation consisting of Dendrobii Caulis, Astragali Radix, Rehmanniae Radix as the main ingredients. DM has been shown to alleviate diabetic related symptoms attributed to its anti-hyperglycaemic and anti-inflammatory activities. However, the effect on diabetic induced cognitive dysfunction has not been investigated. This study aims to investigate the effect of DM in improving diabetic cognitive impairment and associated mechanisms. Our study confirmed the anti-hyperglycaemic effect of DM and showed its capacity to restore the cognitive and memory function in high fat/high glucose and streptozotocin-induced diabetic rats. The neuroprotective effect was manifested as improved learning and memory behaviours, restored blood-brain barrier tight junction, and enhanced expressions of neuronal survival related biomarkers. DM protected the colon tight junction, and effectively lowered the circulated proinflammatory mediators including tumour necrosis factor-α, interleukin-6 and lipopolysaccharides. In the gut microbiota, DM corrected the increase in the abundance of Firmicutes, the increase in the ratio of Firmicutes/Bacteroidetes, and the decrease in the abundance of Bacteroidetes in diabetic rats. It also reversed the abundance of Lactobacillus, Ruminococcus and Allobaculum genera. Short chain fatty acids, isobutyric acid and ethylmethylacetic acid, were negatively and significantly correlated to Ruminococcus and Allobaculum. Isovaleric acid was positively and significantly correlated with Lactobacillus, which all contributing to the improvement in glucose level, systemic inflammation and cognitive function in diabetic rats. Our results demonstrated the potential of DM as a promising therapeutic agent in treating diabetic cognitive impairment and the underlying mechanism may be associated with regulating gut microbiota.

Background: Lens opacity seriously affects the visual development of infants. Slit-illumination images play an irreplaceable role in lens opacity detection; however, these images exhibited varied phenotypes with severe heterogeneity and complexity, particularly among pediatric cataracts. Therefore, it is urgently needed to explore an effective computer-aided method to automatically diagnose heterogeneous lens opacity and to provide appropriate treatment recommendations in a timely manner.Methods: We integrated three different deep learning networks and a cost-sensitive method into an ensemble learning architecture, and then proposed an effective model called ECCNN-Ensemble (ensemble of cost-sensitive convolutional neural networks) for automatic lens opacity detection. A total of 470 slit-illumination images of pediatric cataracts were used for training and comparison between the CCNN-Ensemble model and conventional methods. Finally, we used two external datasets (132 independent test images and 79 Internet-based images) to further evaluate the model’s generalizability and effectiveness.Results: Experimental results and comparative analyses demonstrated that the proposed method was superior to conventional approaches and provided clinically meaningful performance in terms of three grading indices of lens opacity: area (specificity and sensitivity; 92.00% and 92.31%), density (93.85% and 91.43%) and opacity location (95.25% and 89.29%). Furthermore, the comparable performance on the independent testing dataset and the internet-based images verified the effectiveness and generalizability of the model. Finally, we developed and implemented a website-based automatic diagnosis software for pediatric cataract grading diagnosis in ophthalmology clinics. Conclusions: The CCNN-Ensemble method demonstrates higher specificity and sensitivity than conventional methods on multi-source datasets. This study therefore provides a practical strategy for heterogeneous lens opacity diagnosis and has the potential to be applied to the analysis of other medical images.

NLRP3 inflammasome is a key mediator in ischemic stroke-induced neuroinflammation and subsequent brain injury. Our previous study demonstrated the potent activity of Pien-Tze-Huang (PTH), a well-known Chinese patent formula, in reducing mitochondria-mediated neuronal apoptosis in cerebral ischemia/reperfusion impaired rats. This study aims to elucidate the mechanistic action of PTH related to neuroinflammation in LPS-induced BV2 microglial cells and cerebral ischemia/reperfusion impaired rats. BV2 cells were stimulated with LPS for 12 h and treated with PTH with various concentrations. Modulation by PTH of relevant genes (IL-6, IL-1β, IL-18, TNF-α, COX-2 and iNOS mRNA) and proteins (NLRP3 inflammasome, autophagy and AMPK/mTOR/ULK signaling) was analyzed by real-time PCR and western blot, respectively. Similar analyses were conducted in middle cerebral artery occlusion rat model including neurological deficit, infarct volume, microglial activation, and key genes and proteins in modulating autophagy and NLRP3. Our results showed that PTH significantly inhibited the production of key proinflammatory mediators and protein expressions of NLRP3 and caspase-1 p20 in LPS induced BV2 cells. It also enhanced the autophagy response by modulating the key autophagy proteins via AMPK/mTOR/ULK related pathway. The reduced inflammatory responses and NLRP3 expressions by PTH were partially blocked by the autophagy inhibitor (3-MA) and AMPK blocker (compound C). In rats, PTH significantly reduced infarct size, suppressed microglial activation, and improved neuron deficit. It also promoted autophagy and reduced NLRP3 activity. Our study demonstrated that PTH inhibited NLRP3 inflammasome-mediated neuroinflammation, which was associated with enhanced autophagy via AMPK/mTOR/ULK1 pathway in vitro and in vivo.

To facilitate the design and construction of complex functional materials, the field of molecular assembly can learn from the well-established field of catalysis including its branches such as electrocatalysis and photo-electrocatalysis. In this study, we establish a “photo-electro-catassembly” strategy to repeatedly fabricate two-dimensional molecular assemblies on electrode surface by learning from the concept of photo-electrocatalysis. With the rational design of the linear diacetylene building blocks, Au electrode surface itself and the thiol-functionalized electrode both can assist the formation of two-dimensional assemblies and their subsequent covalent stabilization through the polymerization of diacetylene groups. Nevertheless, when using the Au electrode surface as a direct template, the polymerized product would be hardly removed from the electrode due to the strong synergistical interactions through multivalent Au-S bonds. By contrast, when using the thiol-functionalized electrode as an indirect template, the diacetylene building block forms a well-ordered second layer over the thiol monolayer due to the solvent-phobic and solvent-philic effects. After photo-polymerization, the polymerized product can still be removed from the electrode along the electro-induced removal of the thiol monolayer. Driven by electricity and photoirradiation, the thiol-functionalized electrode assists the combined process of assembly and photo-polymerization as a “photo-electrocatassembler”, and it works repeatedly to produce covalently stabilized two-dimensional assemblies.

Background Lens opacity seriously affects the visual development of infants. Slit-illumination images play an irreplaceable role in lens opacity detection; however, these images exhibited varied phenotypes with severe heterogeneity and complexity, particularly among pediatric cataracts. Therefore, it is urgently needed to explore an effective computer-aided method to automatically diagnose heterogeneous lens opacity and to provide appropriate treatment recommendations in a timely manner. Methods We integrated three different deep learning networks and a cost-sensitive method into an ensemble learning architecture, and then proposed an effective model called CCNN-Ensemble [ensemble of cost-sensitive convolutional neural networks (CNNs)] for automatic lens opacity detection. A total of 470 slit-illumination images of pediatric cataracts were used for training and comparison between the CCNN-Ensemble model and conventional methods. Finally, we used two external datasets (132 independent test images and 79 Internet-based images) to further evaluate the model's generalizability and effectiveness. Results Experimental results and comparative analyses demonstrated that the proposed method was superior to conventional approaches and provided clinically meaningful performance in terms of three grading indices of lens opacity: area (specificity and sensitivity; 92.00% and 92.31%), density (93.85% and 91.43%) and opacity location (95.25% and 89.29%). Furthermore, the comparable performance on the independent testing dataset and the internet-based images verified the effectiveness and generalizability of the model. Finally, we developed and implemented a website-based automatic diagnosis software for pediatric cataract grading diagnosis in ophthalmology clinics. Conclusions The CCNN-Ensemble method demonstrates higher specificity and sensitivity than conventional methods on multi-source datasets. This study provides a practical strategy for heterogeneous lens opacity diagnosis and has the potential to be applied to the analysis of other medical images.

Chlorinated paraffins (CPs) have been extensively examined to identify their components. Short-chain CPs with a carbon number of 10–13 have been strictly restricted or banned due to their addition to the list of Persistent Organic Pollutants in the world. However, more constituents with potential toxicities in these complicated mixtures are still unclear. In the present study, a purification method based on the protein affinity of thyroid hormone-related proteins (transthyretin and thyroid receptor) was established. The protein-based affinity extraction coupled with high-throughput scanning successfully discover a new group of chlorinated compounds (CP(O2)) in commercial CP mixtures. The CP(O2)s were purified from the commercial mixtures and identified to be chlorinated fatty acid methyl esters (CFAMEs) with a carbon chain length of 17–19 and 3–11 chlorines by a combination of liquid-liquid extraction, hydrolysis, Fourier transform infrared spectrometry and Orbitrap mass spectrometry. The newly identified CFAMEs were found to be ubiquitous in the environmental matrices, and concentration ratios of ∑CFAMEs/∑CPs ranged from 0.01 to 35 in air, soil and food samples. CFAMEs were also detected in blood samples of general populations, and accumulated in humans through dietary uptake. CFAMEs can compete with T4 for binding TTR with higher potencies than CPs, possibly leading to disruptions of thyroid hormone homeostasis.

New oscillation criteria are established for higher-order Emdn-Fowler dynamic equation q ( v ) x β ( δ ( v ) ) + ( r ( v ) ( z Δ n - 1 ( v ) ) α ) Δ = 0 $ q(v)x^{\beta } (\delta (v)) + (r(v)(z^{{\Delta ^{{n - 1}} }} (v))^{\alpha } )^{\Delta } = 0 $ on time scales, z ( v ) : = p ( v ) x ( τ ( v ) ) + x ( v ) $ z(v): = p(v)x(\tau (v)) + x(v) $ Our results extend and supplement those reported in literatures in the sense that we study a more generalized neutral delay equation and do not require r Δ ( v ) ≥ 0 $ r^{\Delta } (v) \ge 0 $ and the commutativity of the jump and delay operators.

Microfluidic-NMR spectroscopy has been extended to study the kinetics in supramolecular chemistry and molecular assembly. Kinetics of a multicomponent host-guest supramolecular system containing viologen derivatives, β-cyclodextrins and cucurbit [7]urils are studied by a PMMA based microfluidic chip combined with a dedicated transmission line probe for NMR detection. By combining microfluidic technology with NMR spectroscopy, the amount of material required for a full kinetic study could be minimized. This is crucial in supramolecular chemistry, which often involves highly sophisticated and synthetically costly building blocks. The small size of the microfluidic structure is crucial in bringing the time scale for kinetic monitoring down to seconds. At the same time, the transmission line NMR probe provides sufficient sensitivity to work at low (2 mM) concentrations.

A new optoelectronic hybrid method of spatial frequency spectrum analyzing (SFSA) is put forward and a complete system of SFSA is set up. A lot of experiments show that this method and system can be used widely in the field of computer vision, pattern recognition and on-line products inspection.

This paper introduces a practical platform called the System Qualification Platform (SQP). The SQP is designed to execute FPGA Software (SW) and Silicon (HW) co-verification at the board level and becomes an effective complementary solution to current SW validation methods which are based on simulation. With the SQP the user can develop cases, manage test suites/boards, launch testing, and analyze on-board running results on a PC. Moreover, the SQP's flexible architecture makes it a best practice for integrating new SW products and correspondingly-supported HW products, while offering more test cases to improve coverage. Automated regression can be easily fulfilled when the development phase ends.

In this paper, we conduct research on the electrical business logistics system optimization model based on the evolutionary game and node analysis. For warehouse layout is not reasonable, do not have a high level of the storage technology, automated storage utilization rate is low, the lack of warehouse management personnel, to optimize the storage management mechanism, the need to pay attention to the following principles: clear the optimization goal, optimization model of the real can type, accurate real-time operational data, data of complete integration, earnestly implement scheme, practical optimization algorithm, instant effective optimization scheme, solid support professionals, scalability optimization process, the overall return on investment evaluation. To achieve this goal, this paper proposes the new countermeasures that will be meaningful.

In nature, protein subunits on the capsids of many icosahedral viruses form rotational patterns, and mathematicians also incorporate asymmetric patterns into faces of polyhedra. Chemists have constructed molecular polyhedra with vacant or highly symmetric faces, but very little is known about constructing polyhedra with asymmetric faces. Here we report a strategy to embellish a C3h truxene unit with rotational patterns into the faces of an octahedron, forming chiral octahedra that exhibit the largest molar ellipticity ever reported, to the best of our knowledge. The directionalities of the facial rotations can be controlled by vertices to achieve identical rotational directionality on each face, resembling the homo-directionality of virus capsids. Investigations of the kinetics and mechanism reveal that non-covalent interaction among the faces is essential to the facial homo-directionality., Protein subunits on the capsids of icosahedral viruses can form patterns with rotational symmetry, which are difficult to recreate in the laboratory. Here the authors report a strategy to construct 3D chiral polyhedra with rotational faces from 2D chiral truxene-based units through dynamic covalent chemistry.

In this study, three scales urban green space landscapes were generated by multi-resolution segmentation. With 50 and 300 pixels as the object segmentation thresholds, the small- and large-scale landscape object image layers were produced, and the two object image layers were obtained by the nearest neighbor classification method. The result of small-scale landscape classification image was segmented into middle-scale landscape image, and then classified. Green space information was extracted through vector form of object image layers of three scales landscape classification. The landscape indexes diversity, dominance, evenness, fractal dimension, fragmentation, and interior to edge ration were calculated, with the largest values of the former four indexes being 2.2, 0.681, 0.948, and 0.326, and the smallest values being 1.641, 0. 122, 0.707, and 0.113, respectively, indicating that the diversity, evenness and fragmentation decreased, while the dominance increased with increasing landscape scale. The method of multi-resolution segmentation to generate multi-scale landscape could meet the needs of urban green space landscape research.

Many studies have suggested that elevated estrogens and androgens may be etiologically related to the development of breast cancer, endometrial cancer and uterine leiomyomas. We and other investigators have previously shown that estrogen and androgen are synergistic in the induction of mammary carcinogenesis in the Noble rat. However, the mechanisms behind the synergy is unknown, and it is unclear whether such synergy is unique for the Noble rat and for the mammary gland. In this study we treated female FVB mice with 17beta-estradiol (E2) and 5alpha-dihydrotestosterone-bezonate (DHT-B), alone and in combination, using silastic tubing for 2-7 months. The results showed that DHT-B alone induced proliferation of uterine endometrial epithelium and myometrial smooth muscle cells, whereas E2 alone induced much more pronounced growth of endometrial epithelium without affecting smooth muscle cells. Combined treatment with E2+DHT-B caused an even more severe hyperplasia of endometrial epithelium and myometrial muscle cells, compared with the treatment with each hormone alone. Uterine leiomyomas were observed in 2 of 6 mice at 7 months of combined treatment but not in any of 6 or 7 mice receiving each single hormone. DHT-B alone induced growth and secretion of mammary ductal cells, as well as growth of mammary stroma. E2 alone stimulated much more pronounced growth of both ductal cells and alveolar cells and secretion of alveolar cells, but had no effect on mammary stroma. Treatment with both E2 and DHT-B caused more severe hyperplasia of mammary ducts and alveoli, compared to the treatment with each hormone alone. Intraductal hyperplasia occurred early and frequently in the E2+DHT-B- treated mice, but no mammary tumors were observed. These results suggest that E2 and DHT-B have synergistic effects on the growth of uterine endometrial epithelium and myometrial muscle cells, as well as mammary epithelial ducts and alveoli.

Closed unlined landfills can found in many cities in China, as a side product of economic and urban development in last century. The degradation velocity of municipal solid waste (MSW) in such landfills can be very slow due to lack of moisture and its stabilization time can reach twenty years or more if no measure is enforced from outside. Recently aerobic bioreactor landfill technology has been applied to accelerate MSW decomposition by introducing water and air into the landfill. However, excessive water could also result in secondary pollution to ground water. In order to apply the aerobic bioreactor landfill technology for unlined landfills treatment without leachate across the site boundary, an appropriate water injection volume has to be determined. In this paper, a 3D mathematical model is established from mass balance and Darcy's law in a cylindrical coordinate system for the simulation of moisture distribution in an unlined aerobic bioreactor landfill. Moisture profile in landfills is obtained by coupling the aerobic bio-reaction with the water generation term at different scales. The aerobic bio-reaction rate is considered as the function of moisture content, temperature, matrix concentration, oxygen concentration and microorganism concentration. Two water injection styles, surface ponding and vertical well, were investigated. To avoid ground water contamination, moisture filtration rate is assumed to be zero at the site bottom. A feasible water injection volume is determined under quasi-steady- state.