Mushroom polysaccharides from Grifola frondosa (Dicks.) Gray and Inonotus obliquus (Fr.) Pilat ameliorated dextran sulfate sodium-induced colitis in mice by global modulation of systemic metabolism and the gut microbiota

Introduction: Polysaccharides from Grifola frondosa (Dicks.) Gray (HSH) and Inonotus obliquus (Fr.) Pilat (BHR) showed noticeable effects on dextran sulfate sodium (DSS)-induced colitis, but their systemic modulation effects have not been fully revealed. This study aimed to investigate the regulation of the gut microbiota and systemic metabolism by HSH and BHR in DSS-induced colitis.Methods: C57BL/6J mice were given DSS (2.5%) in water and were treated with HSH and BHR (200 mg/kg/day) by gavage. Body weight and colon length were recorded, and H&E and AB-PAS staining of the colon were conducted to evaluate the model and the protective effect of the polysaccharides. Additionally, an LC-QTOF/MS-based untargeted metabolomic platform was used to identify the metabolites in the serum, colon tissue, gut contents, and faeces and investigate differential metabolites and metabolic pathways. 16S rDNA gene sequencing was used to measure the composition of bacterial communities.Results: The results showed that the mouse colitis model was established successfully, as evidenced by an increased disease activity index score [2.83 ± 0.62 vs. 0.06 ± 0.14 (p < 0.001)] and shortened colon length [5.43 ± 0.64 cm vs. 7.04 ± 0.29 cm (p < 0.001)], and HSH and BHR ameliorated DSS-induced colitis by improving the disease activity index (2.17 ± 0.28 and 1.83 ± 0.29, respectively) and restoring the colon length (6.12 ± 0.30 cm and 6.62 ± 0.35 cm, respectively). HSH and BHR significantly modulated metabolites involved in aromatic amino acid metabolism, the citrate cycle, purine metabolism, pyrimidine metabolism, etc. HSH and BHR increased the Chao1 index by 64.25% and 60.25%, respectively, and they increased the Shannon index by 13.02% and 10.23%, respectively. They both reversed the increase in the abundances of g_Odoribacter, g_Clostridium, g_AF12, g_Parabacteroides and g_Turicibacter and reversed the decrease in the abundance of g_unclassified_Bacteria induced by DSS. Specifically, HSH reversed the reductions in g_unclassified_Lactobacillales and g_Ruminococcus, and BHR reversed the decreases in g_unidentified_Coriobacteriaceae and g_unclassified_Firmicutes.Discussion: These results suggested that HSH and BHR may ameliorate DSS-induced colitis by global modulation of systemic metabolism and the gut microbiota. Targeting the gut microbiota may be a potentially effective strategy to modulate systemic metabolism and treat colitis

Orally Administered Crocin Protects Against Cerebral Ischemia/Reperfusion Injury Through the Metabolic Transformation of Crocetin by Gut Microbiota

Our pilot study suggested that orally administered crocin was hardly absorbed into circulatory system, but it was effective against cerebral ischemic/reperfusion (I/R) injury. The pharmacologically active component and targeting site of crocin remain elusive. In this study, the cerebral-protective effect of crocin was evaluated on a rat transient middle cerebral artery occlusion (MCAO) model. Our data showed that oral administration of crocin had better effectiveness in cerebral protection than an intravenous injection. Neither crocin nor its metabolite crocetin were determined in the brain of cerebral I/R rats, indicating a target site of periphery. Abundant crocetin was detected in plasma after oral administration instead of intravenous injection of crocin. Meanwhile, orally administered crocetin showed similar cerebral protection to that of crocin, but this exciting effect was not clearly observed by intravenous administration of crocetin, indicating the importance of crocetin in gut. Moreover, orally administered crocin showed less cerebral-protective effect in pseudo germ-free (pGF) MCAO rats. In vitro and in vivo experiments confirmed that crocin could be deglycosylated to crocetin in gut content of normal rats, rather than that of pGF rats, indicating that gut microbiota facilitated the transformation of crocin into crocetin, which played a key role in the activation of the pharmacological effect. Metabolomic study revealed that microbial-host co-metabolic molecules were significantly perturbed after oral administration of crocin, indicating a regulation on intestinal ecosystem. It was further suggested that gut microbiota may be the potential target of the cerebral-protective effect of crocin

Purine Catabolism Shows a Dampened Circadian Rhythmicity in a High-fat Diet-Induced Mouse Model of Obesity

High-calorie diet, circadian rhythms and metabolic features are intimately linked. However, the mediator(s) between nutritional status, circadian rhythms and metabolism remain largely unknown. This article aims to clarify the key metabolic pathways bridging nutritional status and circadian rhythms based on a combination of metabolomics and molecular biological techniques. A mouse model of high-fat diet-induced obesity was established and serum samples were collected in obese and normal mice at different zeitgeber times. Gas chromatography/mass spectrometry, multivariate/univariate data analyses and metabolic pathway analysis were used to reveal changes in metabolism. Metabolites involved in the metabolism of purines, carbohydrates, fatty acids and amino acids were markedly perturbed in accordance with circadian related variations, among which purine catabolism showed a typical oscillation. What’s more, the rhythmicity of purine catabolism dampened in the high-fat diet group. The expressions of clock genes and metabolic enzymes in the liver were measured. The mRNA expression of Xanthine oxidase (Xor) was highly correlated with the rhythmicity of Clock, Rev-erbα and Bmal1, as well as the metabolites involved in purine catabolism. These data showed that a high-fat diet altered the circadian rhythm of metabolic pathways, especially purine catabolism. It had an obvious circadian oscillation and a high-fat diet dampened its circadian rhythmicity. It was suggested that circadian rhythmicity of purine catabolism is related to circadian oscillations of expression of Xor, Uox and corresponding clock genes

The Role of SLC7A11 in Cancer: Friend or Foe?

SLC7A11 controls the uptake of extracellular cystine in exchange for glutamate at a ratio of 1:1, and it is overexpressed in a variety of tumours. Accumulating evidence has shown that the expression of SLC7A11 is fine-tuned at multiple levels, and plays diverse functional and pharmacological roles in tumours, such as cellular redox homeostasis, cell growth and death, and cell metabolism. Many reports have suggested that the inhibition of SLC7A11 expression and activity is favourable for tumour therapy; thus, SLC7A11 is regarded as a potential therapeutic target. However, emerging evidence also suggests that on some occasions, the inhibition of SLC7A11 is beneficial to the survival of cancer cells, and confers the development of drug resistance. In this review, we first briefly introduce the biological properties of SLC7A11, including its structure and physiological functions, and further summarise its regulatory network and potential regulators. Then, focusing on its role in cancer, we describe the relationships of SLC7A11 with tumourigenesis, survival, proliferation, metastasis, and therapeutic resistance in more detail. Finally, since SLC7A11 has been linked to cancer through multiple approaches, we propose that its contribution and regulatory mechanism require further elucidation. Thus, more personalised therapeutic strategies should be adapted when targeting SLC7A11

Hirsutella sinensis Treatment Shows Protective Effects on Renal Injury and Metabolic Modulation in db/db Mice

Hirsutella sinensis (HS) is the anamorph of the traditional Chinese medicine Cordyceps sinensis. Although the renal protective effect of HS has been reported, its effect on diabetic nephropathy (DN) remains unclear. In this study, db/db mice were used as the DN model, and the renal protective effect was evaluated after oral administration of HS for 6 and 12 weeks. Plasma, urine, and kidney samples were collected, and biochemical indicator measurements, pathological analysis, and metabolomics studies were performed. Biochemical assays showed that HS reduced the levels of fasting blood glucose (FBG), urinary albumin/creatinine ratio (ACR), and N-acetyl-beta-D-glucosaminidase (NAG) and increased the creatinine clearance (Ccr). HS alleviated glomerular and tubular glycogen accumulation and fibrosis and normalized the disordered ultrastructure of the glomerular filtration barrier. Metabolomics analysis of metabolites in the plasma, urine, and kidney indicated that HS modulated the perturbed glycolipid metabolism and amino acid turnover. HS reduced the elevated levels of metabolites involved in energy metabolism (TCA cycle, glycolysis, and pentose phosphate pathway) and nucleotide metabolism (pyrimidine metabolism and purine metabolism) in the kidneys of db/db mice. These results suggest that HS can protect against renal injury and that its efficacy involved metabolic modulation of the disturbed metabolome in db/db mice

Identification of Biomarkers for Methamphetamine Exposure Time Prediction in Mice Using Metabolomics and Machine Learning Approaches

Methamphetamine (METH) abuse has become a global public health and safety problem. More information is needed to identify the time of drug abuse. In this study, methamphetamine was administered to male C57BL/6J mice with increasing doses from 5 to 30 mg kg−1 (once a day, i.p.) for 20 days. Serum and urine samples were collected for metabolomics studies using gas chromatography–mass spectrometry (GC-MS). Six machine learning models were used to infer the time of drug abuse and the best model was selected to predict administration time preliminarily. The metabolic changes caused by methamphetamine were explored. As results, the metabolic patterns of methamphetamine exposure mice were quite different from the control group and changed over time. Specifically, serum metabolomics showed enhanced amino acid metabolism and increased fatty acid consumption, while urine metabolomics showed slowed metabolism of the tricarboxylic acid (TCA) cycle, increased organic acid excretion, and abnormal purine metabolism. Phenylalanine in serum and glutamine in urine increased, while palmitic acid, 5-HT, and monopalmitin in serum and gamma-aminobutyric acid in urine decreased significantly. Among the six machine learning models, the random forest model was the best to predict the exposure time (serum: MAE = 1.482, RMSE = 1.69, R squared = 0.981; urine: MAE = 2.369, RMSE = 1.926, R squared = 0.946). The potential biomarker set containing four metabolites in the serum (palmitic acid, 5-hydroxytryptamine, monopalmitin, and phenylalanine) facilitated the identification of methamphetamine exposure. The random forest model helped predict the methamphetamine exposure time based on these potential biomarkers

A locality aware convolutional neural networks accelerator

\u3cp\u3eThe advantages of Convolutional Neural Networks (CNNs) with respect to traditional methods for visual pattern recognition have changed the field of machine vision. The main issue that hinders broad adoption of this technique is the massive computing workload in CNN that prevents real-time implementation on low-power embedded platforms. Recently, several dedicated solutions have been proposed to improve the energy efficiency and throughput, nevertheless the huge amount of data transfer involved in the processing is still a challenging issue. This work proposes a new CNN accelerator exploiting a novel memory access scheme which significantly improves data locality in CNN related processing. With this scheme, external memory access is reduced by 50% while achieving similar or even better throughput. The accelerator is implemented using 28nm CMOS technology. Implementation results show that the accelerator achieves a performance of 102GOp/s @800MHz while consuming 0.303mm2 in silicon area. Power simulation shows that the dynamic power of the accelerator is 68mW. Its flexibility is demonstrated by running various different CNN benchmarks.\u3c/p\u3