A Study of (

We deal with topics regarding (λ,μ)-fuzzy subgroups, mainly (λ,μ)-fuzzy cosets and (λ,μ)-fuzzy normal subgroups. We give basic properties of (λ,μ)-fuzzy subgroups and present some results related to (λ,μ)-fuzzy cosets and (λ,μ)-fuzzy normal subgroups

An Aquaporin 3-Notch1 Axis in Keratinocyte Differentiation and Inflammation

Aquaporin 3 (AQP3) is an aquaglyceroporin which transports water, glycerol and small solutes across the plasma membrane. Its functions are not limited to fluid transport but also involve the regulation of cell proliferation, migration, skin hydration, wound healing and tumorigenesis. While AQP3 has been reported to play an important role in keratinocyte proliferation, its role in differentiation remains controversial. Our study demonstrated that the expression of AQP3 was regulated during differentiation and that it participated in keratinocyte differentiation control. We further revealed that AQP3 was a transcriptional target of Notch signaling, a critical pathway regulating keratinocyte differentiation and tumor suppression, and it regulated differentiation through a reciprocal negative feedback loop with Notch1. When the expression level of AQP3 was elevated, impaired barrier integrity and increased pro-inflammatory cytokine production ensued, mimicking the pathological conditions in Notch deficient mice and in atopic dermatitis. Dysregulation of AQP3 and Notch receptors has been reported in several skin diseases, including skin cancer. Our discovery of the novel AQP3-Notch1 axis may provide insight into epidermal homeostasis control and possible translational applications, including its potential use as a biomarker for molecular diagnosis in environmental studies

Predicting bacterial transport through saturated porous media using an automated machine learning model

Escherichia coli, as an indicator of fecal contamination, can move from manure-amended soil to groundwater under rainfall or irrigation events. Predicting its vertical transport in the subsurface is essential for the development of engineering solutions to reduce the risk of microbiological contamination. In this study, we collected 377 datasets from 61 published papers addressing E. coli transport through saturated porous media and trained six types of machine learning algorithms to predict bacterial transport. Eight variables, including bacterial concentration, porous medium type, median grain size, ionic strength, pore water velocity, column length, saturated hydraulic conductivity, and organic matter content were used as input variables while the first-order attachment coefficient and spatial removal rate were set as target variables. The eight input variables have low correlations with the target variables, namely, they cannot predict target variables independently. However, using the predictive models, input variables can effectively predict the target variables. For scenarios with higher bacterial retention, such as smaller median grain size, the predictive models showed better performance. Among six types of machine learning algorithms, Gradient Boosting Machine and Extreme Gradient Boosting outperformed other algorithms. In most predictive models, pore water velocity, ionic strength, median grain size, and column length showed higher importance than other input variables. This study provided a valuable tool to evaluate the transport risk of E.coli in the subsurface under saturated water flow conditions. It also proved the feasibility of data-driven methods that could be used for predicting other contaminants’ transport in the environment

Modelling the thickness of landfast sea ice in Prydz Bay, East Antarctica

Landfast sea ice forms and remains fixed along the coast for most of its life time. In Prydz Bay, landfast ice is seasonal due to melting, mechanical breakage and drift of ice in summer. Its annual cycle of thickness and temperature was examined using a one-dimensional thermodynamic model. Model calibration was made for March 2006 to March 2007 with forcing based on the Chinese National Antarctic Research Expedition data, which consisted of in situ ice and snow observations and meteorological records at the Zhongshan Station. The observed maximum annual ice thickness was 1.74 m. The ice broke and drifted out in summer when its thickness was 0.5-1.0 m. Oceanic heat flux was estimated by tuning the model with observed ice thickness. In the growth season, it decreased from 25 Wm(-2) to 5W m(-2), and in summer it recovered back to 25 W m(-2). Albedo was important in summer; by model tuning the estimated value was 0.6, consistent with the ice surface being bare all summer. Snow cover was thin, having a minor role. The results can be used to further our understanding of the importance of landfast ice in Antarctica for climate research and high-resolution ice-ocean modelling.Peer reviewe

Upregulation of CD94 on CD8+T Cells in Anterior Chamber-Associated Immune Deviation

<p>Abstract</p> <p>Background</p> <p>CD8⁺regulatory T cells (Treg) have been considered to be involved in a model of ocular-induced tolerance, known as anterior chamber-associated immune deviation (ACAID). The phenotype and characteristics of CD8⁺Treg in ACAID remain only poorly understood. Recent studies have reported that the CD94-Qa-1 system is implicated in the induction of ACAID CD8⁺Treg, but the functions and characteristics of CD8⁺CD94⁺T cells remain unclear.</p> <p>Results</p> <p>Both mRNA and protein of CD94 and NKG2A were markedly up-regulated on splenic CD8⁺T cells of ACAID mice compared with controls. Flow cytometric analysis showed that very few CD8⁺CD94⁺T cells express granzyme B, perforin and Foxp3. CD8⁺CD94⁺T cells, but not CD8⁺CD94^-T cells, magnetically isolated from the spleens of ACAID mice, produced large amounts of TGF-beta1 and exhibited suppressive activity in vitro. Neutralization of TGF-beta1 caused reversal of suppression mediated by CD8⁺CD94⁺T cells.</p> <p>Conclusion</p> <p>CD8⁺CD94⁺T cells from ACAID mice exhibited suppressive activity in association with enhanced expression of TGF-beta1, suggesting that CD8⁺Treg are mainly distributed in CD94⁺T cell subpopulations.</p

What Are the New Challenges of the Current Cancer Biomarkers?

Biomarkers are emerging research filed in the past decade. Even though numerous biomarkers were reported, the efficiency of cancer therapy remains low. So the question emerges as to how much can we trust the current biomarkers on cancer therapy? In this upcoming chapter, we would like to illustrate the outcomes of classical cancer therapies on advanced pancreatic cancer disclosed successful, neutral and failed in clinical trials. The analysis will be carried on the perspective interdisciplinary on the biomarkers including anatomy, physiology, pharmacology, biochemistry, history path and development of pharmacy. Particular in-depth insight may open a window for new researches and lighting the therapies

Thermal Diffusivity Identification of Distributed Parameter Systems to Sea Ice

A method of optimal control is presented as a numerical tool for solving the sea ice heat transfer problem governed by a parabolic partial differential equation. Taken the deviation between the calculated ice temperature and the measurements as the performance criterion, an optimal control model of distributed parameter systems with specific constraints of thermal properties of sea ice was proposed to determine the thermal diffusivity of sea ice. Based on sea ice physical processes, the parameterization of the thermal diffusivity was derived through field data. The simulation results illustrated that the identified parameterization of the thermal diffusivity is reasonably effective in sea ice thermodynamics. The direct relation between the thermal diffusivity of sea ice and ice porosity is physically significant and can considerably reduce the computational errors. The successful application of this method also explained that the optimal control model of distributed parameter systems in conjunction with the engineering background has great potential in dealing with practical problems

Characterization of cellulase production by carbon sources in two Bacillus species

The induction of cellulase production in two Bacillus spp. was studied by means of measuring cellulase activities under the condition of different carbon sources. The results indicate that cellulase could not be induced by cellulose material as a sole carbon source. Instead, they could be induced by monosaccharide or disaccharide with reducing group. Moreover, the expression of cellulase components was synergistic. When cell wall/envelope enzyme and endoenzyme from two Bacillus spp. acted on these inducers, analysis of reaction products by high performance liquid chromatography (HPLC) revealed that cell wall/envelope enzyme and endoenzyme from two Bacillus spp. were inactive on these inducers. It also indicated that these inducers entered cells directly and served function of induction.Keywords: Bacillus, cellulase, induction, carbon source