Effects of Fu brick tea polysaccharides on gut microbiota and fecal metabolites of HFD/STZ-induced type 2 diabetes rats.

The prevalence of type 2 diabetes mellitus (T2DM) has dramatically increased globally, and the antidiabetic effects and underlying mechanisms of the polysaccharides extracted from Fu brick tea (FBTP) were investigated in high-fat diet (HFD)/streptozotocin (STZ)-induced T2DM rats. Administration of FBTP at 200 and 400 mg per kg bw significantly relieved dyslipidemia ( TC, TG, LDL-C and HDL-C), insulin resistance (IR) and pancreas oxidative stress ( CAT and GSH-P) in T2DM rats. Mechanistically, FBTP rescued the HFD/STZ-induced alterations in the abundance of , , and .

[Preparation of Iron-improved Blue Algae Biochar and Its Co-adsorption Mechanism for Phosphorus in Surface Water].

To alleviate the problems of eutrophication and blue algae accumulation in water, biochar was prepared from blue algae dehydrated using polymerized ferrous sulfate(PFS) to absorb phosphate in water, and the biochar was activated using steam to adjust the pore structure. The preparation conditions of blue algae biochar were optimized using the response surface method. The optimal results were as follows:the dosage of PFS was 458 mg·L, the carbonization temperature was 433℃, and the mass ratio of biochar precursor to steam was 1:11.

HCTMFS: A multi-modal feature selection framework with higher-order correlated topological manifold for ESRDaMCI.

Background And Objective: The diagnosis of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) mainly relies on objective cognitive assessment, clinical observation, and neuro-psychological evaluation, while only adopting clinical tools often limits the diagnosis accuracy.

Methods: We proposed a multi-modal feature selection framework with higher-order correlated topological manifold (HCTMFS) to classify ESRDaMCI patients and identify the discriminative brain regions. It constructed brain structural and functional networks with diffuse kurtosis imaging (DKI) and functional magnetic resonance imaging (fMRI) data, and extracted node efficiency and clustering coefficient from the brain networks to construct multi-modal feature matrices.

Multi-modal feature selection with self-expression topological manifold for end-stage renal disease associated with mild cognitive impairment.

Effectively selecting discriminative brain regions in multi-modal neuroimages is one of the effective means to reveal the neuropathological mechanism of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI). Existing multi-modal feature selection methods usually depend on the Euclidean distance to measure the similarity between data, which tends to ignore the implied data manifold. A self-expression topological manifold based multi-modal feature selection method (SETMFS) is proposed to address this issue employing self-expression topological manifold.

Multimodal Classification Framework Based on Hypergraph Latent Relation for End-Stage Renal Disease Associated with Mild Cognitive Impairment.

Combined arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI) can reveal more comprehensive properties of the spatiotemporal and quantitative properties of brain networks. Imaging markers of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) will be sought from these properties. The current multimodal classification methods often neglect to collect high-order relationships of brain regions and remove noise from the feature matrix.

Characterizing Topological Properties of Brain Functional Networks Using Multi-Threshold Derivative for End-Stage Renal Disease with Mild Cognitive Impairment.

Patients with end-stage renal disease (ESRD) experience changes in both the structure and function of their brain networks. In the past, cognitive impairment was often classified based on connectivity features, which only reflected the characteristics of the binary brain network or weighted brain network. It exhibited limited interpretability and stability.

Caloric Restriction, Friend or Foe: Effects on Metabolic Status in Association with the Intestinal Microbiome and Metabolome.

Daily calorie restriction (CR) has shown benefits on weight loss and alleviation of metabolic disorders. We investigated the effects of three CR regimens, i.e.