•Flux stabilization of GDM process occurred under high Mn pollution.•An extremely short ripening period (<10 days) of Mn removal was achieved.•Fe and Mn were efficiently removed by > 90% and > 50% in ...GDM process.•A highly porous biofilm formed on the membrane surface under Mn pollution.•Pre-coating manganese oxides could improve the stable flux and Mn removal.
Severe membrane fouling caused by iron and manganese limited the intensive application of ultrafiltration (UF) technologies. In the present study, an innovative biofilm based UF process, gravity driven membrane (GDM) filtration, was employed to evaluate its possibility to directly treat manganese-contaminated surface water at high concentration. Surprisingly, an extremely short and stable ripening period (less than 10 d) of iron and manganese removal was achieved in GDM filtration, with average removals of 90% and 58%, respectively, attributing to the effective rejection of active catalytic manganese oxides and fast colonization of iron- and manganese-oxidizing bacteria (e.g Acinetobacter and Lysobacter) within the biofilm due to the efficient rejection by UF membrane. Importantly, the presence of iron and manganese did not influence the occurrence of flux stabilization, and fluxes stabilized at 7–9 L m−2 h−1 during long-term filtration. Furthermore, a highly rough, porous and heterogeneous biofilm was observed on the membrane surface, which was potentially responsible for the flux stabilization. Additionally, pre-coating manganese oxides on the membrane surface can efficiently enhance the removals of manganese and iron, and engineer even highly heterogeneous structures of biofilm to improve the stable flux. Therefore, the findings are relevant to develop new strategies for the treatments of manganese-contaminated water resource at high concentration, and to encourage extensive applications of membrane technologies for decentralized drinking water supply.
•The GSTM1 null/ deletion polymorphism is showed significant association with the incident of GDM with 3.36 folds higher risk.•The relative mRNA expression of GSTM1 and GSTT1 genes were observed ...considerably.•down-regulated in GDM women as compared to healthy pregnant women.•Down-expressed genes (GSTM1 and GSTT1) showed significant association with null/deletion polymorphism.•Advanced maternal age, plasma glucose, TC, HDL, LDL, and BMI also found statically associated with the risk of GDM. Anthro-biochemical factors that increase risk can serve as a preventative biomarker.
Gestational Diabetes Mellitus (GDM) is a medical complication during the gestational period in which woman who had never been diagnosed with diabetes develops hyperglycemia. Prior studies have demonstrated that the advancement of GDM and its consequences arises from a disparity between oxidants and antioxidants in the cells. The observed outcomes can be attributed to an excessive formation of reactive oxygen species (ROS) within the cells, coupled with a reduced activity of anti-oxidative enzymes. Glutathione S-transferase (GSTs) is recognized as an antioxidant enzyme that is belong to as a phase II family member of detoxifying enzymes. These metabolic multigene catalysts are found into the cytoplasm of the cell. GSTs play a vital part in the elimination of cellular ROS or free radicals. The study involves total 300 pregnant women, (150 GDM cases and 150 healthy controls). The polymorphism study of GSTs genes (GSTM1 and GSTT1) was determined by conventional Polymerase Chain Reaction (PCR). The mRNA expression study of GSTM1 and GSTT1 genes analysed by qPCR/ RT-PCR (quantitative PCR/Real-Time PCR) followed by statistical analysis done using Prism8 software (version 8.01). The study revealed statistically significant variations in biochemical parameters between GDM cases and controls. It was found GSTM1-null (GSTM1-/-) polymorphism significantly (P < 0.0001) most prevalent in GDM cases (56.7%) when compared to healthy control (28%). However, no significant difference was observed for GSTT1 null and present polymorphism (P = 0.906). The gene expression levels of both GSTM1 and GSTT1 were found considerably downregulated in individuals with GDM as compared to the control group (P < 0.0001). The downregulation of gene expression has a significant (P<0.0001) association with the null/deletion polymorphism of both GSTM1/ GSTT1 genes respectively. Null/deletion genotype of GSTM1 gene and its expression showed significant association with GDM. Therefore, this gene variant has the potential to be used as a prognostic biomarker for GDM. However, there is need to study this gene variant in larger sample size and different ethnicity.
Nowadays, societal and technological trends demand the management of large scale of decision makers in group decision-making (GDM) contexts. In a large-scale GDM, decision makers often have ...individual concerns and satisfactions, and also they will use heterogeneous preference representation structures to express their preferences. Meanwhile, it is difficult to set the numerical consensus threshold to judge whether a consensus degree can be acceptable or not in the consensus reaching process in a large-scale GDM. This study proposes a novel consensus reaching model for the heterogeneous large-scale GDM with the individual concerns and satisfactions. In this consensus reaching model, a selection process is proposed to obtain the individual preference vectors, to divide decision makers into different clusters, and to yield the preference vector of the large group. Following this, a consensus measure method that considers the individual concerns on alternatives is defined for measuring the consensus degree, and a linguistic approach is developed to measure the individual and collective satisfactions regarding the consensus degree. Finally, a feedback adjustment process is proposed and utilized to help decision makers adjust their preferences. A practical example and a simulation analysis are presented to demonstrate the validity of the proposed consensus reaching model.
Intuitionistic multiplicative preference relations (IMPRs) have been widely applied in decision making for their ability to efficiently express the uncertainty of information. This paper investigates ...the decision making with incomplete IMPRs. First, a new consistency of incomplete IMPRs is defined. Then, we present some optimization models for estimating missing values by maximizing the consistency level. After that, the group IMPR is derived by using membership degrees in individual intuitionistic multiplicative judgments. Subsequently, a transformation method is offered to build a consistent IMPR through a normalized intuitionistic fuzzy priority weight vector. Moreover, a model is presented to get intuitionistic fuzzy priority weights. Finally, we propose a group decision making (GDM) method with incomplete IMPRs. A practical GDM problem on venue selection for communication drills is offered to indicate the specific application of main theoretical results.
Incretins are crucial stimulators of insulin secretion following food intake. Data on incretin secretion and action during pregnancy are sparse.
The aim of the study was to investigate the incretin ...response during an oral glucose tolerance test (OGTT) in pregnant women with and without gestational diabetes mellitus (GDM).
We analyzed data from the ongoing observational PREG study (NCT04270578).
The study was conducted at the University Hospital Tübingen.
We examined 167 women (33 with GDM) during gestational week 27 ± 2.2.
Subjects underwent 5-point OGTT with a 75-g glucose load.
We assessed insulin secretion and levels of total glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic peptide (GIP), glicentin, and glucagon during OGTT. Linear regression was used to analyze the relation of GLP-1 and glucose with insulin secretion and the association of incretin levels on birth outcome.
Insulin secretion was significantly lower in women with GDM (P < 0.001). Postload GLP-1 and GIP were ~20% higher in women with GDM (all P < 0.05) independent of age, body mass index, and gestational age. GLP-1 increase was associated with insulin secretion only in GDM, but not in normal glucose tolerance. Postprandial GLP-1 levels were negatively associated with birth weight.
The more pronounced GLP-1 increase in women with GDM could be part of a compensatory mechanism counteracting GLP-1 resistance. Higher GLP-1 levels might be protective against fetal overgrowth.
The ability of arginine-rich peptides to cross the lipid bilayer and enter cytoplasm, unlike their lysine-based analogues, is intensively studied in the context of cell-penetrating peptides. Although ...the experiments have not yet reconstructed their internalization mechanism, the computational studies have shown that the type or charge of lipid polar groups is one of the crucial factors in their translocation. In order to gain more detailed insight into the interaction of guanidinium (Gdm+) and ammonium (NH4+) cations, as important building blocks in arginine and lysine amino acids, with lipid bilayers, we conducted the experimental and computational study that tackles this phenomenon. The adsorption of Gdm+ and NH4+ on lipid bilayers prepared from a zwitterionic (DPPC) and an anionic (DPPS) lipid was examined by thermoanalytic and spectroscopic techniques. Using temperature-dependent UV–Vis spectroscopy and DSC calorimetry we determined the impact of Gdm+ and NH4+ on the thermotropic properties of lipid bilayers. FTIR data, along with molecular dynamics simulations, unraveled the molecular-level details on the nature of their interactions, showing the proton transfer between NH4+ and DPPS, but not between Gdm+ and DPPS. The findings originated from this work imply that Gdm+ and NH4+ form qualitatively different interactions with lipids of different charge which is reflected in the physico-chemical interactions that arginine-and lysine-based peptides establish at a complex and chemically heterogeneous environment such as the biological membrane.
Display omitted
•Interaction of Gdm+/NH4+/Na+ and DPPC/DPPS bilayers was explored.•Adsorption of Gdm+, unlike NH4+ and Na+, strongly modulates DPPC pretransition.•DPPC bilayers show selectivity towards Gdm+ over NH4+ (and Na+).•FTIR spectra revealed proton transfer between NH4+ and DPPS upon adsorption.
Consensus commonly improves the efficiency of subsequent implementation of the solution in large-scale group decision making (LSGDM). The maximum expert consensus model (MECM) is a significance ...decision method for consensus reaching processes. In the MECM, the unit adjustment cost of each decision maker and a consensus budget are assumed to be deterministic. Within real-world decision environment, however, it is scarcely possible to obtain an exact numerical value of them. To solve this problem, novel MECMs are constructed on the basis of robust optimization under uncertainty circumstances. Considering the uncertainty of costs, we propose three mixed integer robust maximum expert consensus models (MIR-MECMs) by introducing uncertain box, ellipsoid and polyhedron sets, respectively. Further, we take the aggregation operators into these proposed models. Additionally, to comprehensively analyze the impact of the uncertain parameters in MECM, we develop two models under indeterminacy of the costs and a consensus budget. Finally, an improved genetic algorithm is provided to solve the proposed models in large-scale GDM. Numerical example is used to demonstrate that the solution of the deterministic MECM is too optimistic and the solution of the proposed models are more robust under the uncertainty circumstances. A simulation analysis shows that the ordered weighed averaging (OWA) operator is more stable performance with parameters perturbation.
•We take the uncertainty costs and a consensus budget into the maximum expert consensus model.•The mixed integer robust maximum expert consensus models are proposed.•We propose an improved Genetic Algorithm(GA) algorithm to solve the proposed models.•The results prove the robustness of the proposed optimization models.•We discuss the performance of the aggregation operators under uncertainty circumstances.
•We propose an additive consistency definition for q-ROFPRs.•We propose the models for dealing with incomplete and inconsistent q-ROFPRs.•We propose a method to increase the consensus degrees of ...q-ROFPRs.•We propose a new GDM method in incomplete q-ROFPRs environments.•The proposed GDM method can overcome the drawbacks of the existing GDM methods.
In this paper, we propose a novel group decision making (GDM) method in incomplete q-rung orthopair fuzzy preference relations (q-ROFPRs) environments. We propose an additive consistency definition, which is characterized by a q-rung orthopair fuzzy priority vector. The property of the proposed additive consistency definition is offered and a model to obtain missing judgments in incomplete q-ROFPRs is proposed. We present an approach to adjust the inconsistency for q-ROFPRs, propose a model to obtain the priority vector, and propose a method to increase consensus degrees of q-ROFPRs. Finally, we present a GDM method in incomplete q-ROFPRs environments and use two illustrative examples and some comparisons to illustrate that our method outperforms the existing methods for GDM in incomplete q-ROFPRs environments. The proposed GDM method offers us a useful way for GDM in incomplete q-ROFPRs environments.
A fundamental goal in community ecology is to understand what factors drive community assembly processes. The factors affecting ectomycorrhizal fungal communities are unknown in many regions, ...particularly in the southern hemisphere. We investigate community assembly using ITS2 metabarcoding of ectomycorrhizal fungi sampled from 3943 hyphal ingrowth bags buried in 81 Nothofagus forests across New Zealand's South Island. By applying zeta diversity analysis and multisite generalized dissimilarity modelling (MS‐GDM) we quantify the effects of 43 biotic and environmental variables on community turnover. Unlike traditional beta diversity analyses that are heavily influenced by rare species, the zeta diversity framework differentiates between factors driving turnover of rare and common species, providing a more complete picture of community dynamics. We found that community assembly was dominated by deterministic rather than stochastic processes and identified ecological factors affecting all taxa, as well as others that were specifically important to rare or common taxa. Soil variables were important drivers of turnover for all species, whereas ground cover variables, forest patch size, precipitation and host tree identity had greater effects on rarer species, and tree size and temperature effects were specific to more common species. Interestingly, the effect of temperature on common species is in line with recent evidence from other Kingdoms, pointing to possible generality, and highlighting the importance of considering common species. Applying these methods to fungi has allowed us to identify the distinct ecological processes that structure rare and common taxa during community assembly. This has important implications for understanding the functional effects of community responses to environmental change.
The q-rung orthopair fuzzy preference relations are useful tools to represent hesitant and uncertain judgments of decision makers. In this paper, we propose a new group decision making method based ...on multiplicative consistency-and-consensus preference analysis for incomplete q-rung orthopair fuzzy preference relations. First, we provide a novel concept of multiplicative consistency for q-rung orthopair fuzzy preference relations. Then, a multiplicative consistency index is offered, by which we derive the concept of acceptable multiplicative consistency for q-rung orthopair fuzzy preference relations. Following this concept, optimization models for ascertaining unknown values in an incomplete q-rung orthopair fuzzy preference relation are built. Furthermore, optimization models for obtaining acceptable multiplicative q-rung orthopair fuzzy preference relation are proposed. Then, an optimization model for group decision making is proposed to attain an enough consensus. Afterward, a group decision making method with incomplete and unacceptable multiplicative consistent q-rung orthopair fuzzy preference relations is proposed. Finally, we use an application example to show the practicality of the proposed group decision making method. The proposed group decision making method outperforms the existing group decision making methods for group decision making in incomplete q-rung orthopair fuzzy environments.
PDF
