The primate gut microbiota contributes to interspecific differences in host metabolism.

Because large brains are energetically expensive, they are associated with metabolic traits that facilitate energy availability across vertebrates. However, the biological underpinnings driving these traits are not known. Given its role in regulating host metabolism in disease studies, we hypothesized that the gut microbiome contributes to variation in normal cross-vertebrate species differences in metabolism, including those associated with the brain's energetic requirements.

Accurate construction of monolayer, bilayer, sandwich bilayer, four-layer, multi-layer and chiral bilayer 2D pillararene-type supramolecular networks.

The accurate construction of mono-, bi- and multi-layer networks has been an important challenge, especially for bi- and multi-layer networks. Monolayer, bilayer, sandwich bilayer, four-layer, and multi-layer two-dimensional pillararene-type metal-organic coordination networks have been constructed from functionalized pillar[5]arene and pillar[6]arene by utilizing the coordination interaction of cobalt and copper ions and combining with temperature control and guest induction. These two-dimensional coordination networks exhibit the excellent plasticity of pillararenes and structural variety, which are characterized by X-ray single crystal diffraction and PXRD, confirming that pillararenes units can function as excellent tunable scaffolds for structural regulation.

Amplifying hepatic L-aspartate levels suppresses CCl-induced liver fibrosis by reversing glucocorticoid receptor β-mediated mitochondrial malfunction.

Liver fibrosis is a determinant-stage process of many chronic liver diseases and affected over 7.9 billion populations worldwide with increasing demands of ideal therapeutic agents. Discovery of active molecules with anti-hepatic fibrosis efficacies presents the most attacking filed.

Six-Cyclic Crown Ether-Type Pillar[5]Arene: Enhanced Binding Ability to Bispyridinium Derivatives.

A six-cyclic crown ether-type pillar[5]arene was synthesized, and the five ethylene oxide loops were located outside the cavity and not affected by temperature changes which was confirmed by variable-temperature NMR experiment in DMSO-d6 and CDCl and 2D H-H NOESY experiment in CDCl. The six-cyclic pillar[5]-crown also showed greater binding ability of host-guest with bis(pyridinium) derivatives than conventional alkoxy pillar[5]arenes that illustrated through H NMR titration spectroscopic experiment in acetone-d6/CDCl (1 : 1) and UV-vis titration experiments in CHCl at room temperature. The five benzocrown ethers at the periphery were able to bind metal cations by H NMR titration spectroscopic experiment in CDCl/methanol-d4(9 : 1).

Joint ESPGHAN/NASPGHAN Guidelines on Childhood Eosinophilic Gastrointestinal Disorders Beyond Eosinophilic Esophagitis.

Introduction: Eosinophilic gastrointestinal disorders beyond eosinophilic esophagitis (non-EoE EGIDs) are rare chronic inflammatory disorders of the gastrointestinal (GI) tract. Diagnosis is based on clinical symptoms and histologic findings of eosinophilic inflammation after exclusion of a secondary cause or systemic disease. Currently, no guidelines exist for the evaluation of non-EoE EGIDs.

Machine learning-based automated sponge cytology for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction: a nationwide, multicohort, prospective study.

Background: Oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction have a dismal prognosis, and early detection is key to reduce mortality. However, early detection depends on upper gastrointestinal endoscopy, which is not feasible to implement at a population level. We aimed to develop and validate a fully automated machine learning-based prediction tool integrating a minimally invasive sponge cytology test and epidemiological risk factors for screening of oesophageal squamous cell carcinoma and adenocarcinoma of the oesophagogastric junction before endoscopy.

A Novel Early Warning Model for Hand, Foot and Mouth Disease Prediction Based on a Graph Convolutional Network.

Objectives: Hand, foot and mouth disease (HFMD) is a widespread infectious disease that causes a significant disease burden on society. To achieve early intervention and to prevent outbreaks of disease, we propose a novel warning model that can accurately predict the incidence of HFMD.

Methods: We propose a spatial-temporal graph convolutional network (STGCN) that combines spatial factors for surrounding cities with historical incidence over a certain time period to predict the future occurrence of HFMD in Guangdong and Shandong between 2011 and 2019.

Copper and manganese: two concordant partners in the catalytic oxidation of p-cresol to p-hydroxybenzaldehyde.

Copper and manganese were found to be two concordant partners in the synthesis of p-hydroxybenzaldehyde from p-cresol; under mild conditions, this research realised 95.6% selectivity for p-hydroxybenzaldehyde at 98.5% conversion of p-cresol.