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Obesity imposes a global health threat and calls for safe and effective therapeutic options. Here, we found that protein-rich diet significantly reduced body fat storage in fruit flies, which was largely attributed to dietary cysteine intake. Mechanistically, dietary cysteine increased the production of a neuropeptide FMRFamide (FMRFa). Enhanced FMRFa activity simultaneously promoted energy expenditure and suppressed food intake through its cognate receptor (FMRFaR), both contributing to the fat loss effect. In the fat body, FMRFa signaling promoted lipolysis by increasing PKA and lipase activity. In sweet-sensing gustatory neurons, FMRFa signaling suppressed appetitive perception and hence food intake. We also demonstrated that dietary cysteine worked in a similar way in mice via neuropeptide FF (NPFF) signaling, a mammalian RFamide peptide. In addition, dietary cysteine or FMRFa/NPFF administration provided protective effect against metabolic stress in flies and mice without behavioral abnormalities. Therefore, our study reveals a novel target for the development of safe and effective therapies against obesity and related metabolic diseases.

Short text classification is a research focus for natural language processing (NLP), which is widely used in news classification, sentiment analysis, mail filtering and other fields. In recent years, deep learning techniques are applied to text classification and has made some progress. Different from ordinary text classification, short text has the problem of less vocabulary and feature sparsity, which raise higher request for text semantic feature representation. To address this issue, this paper propose a feature fusion framework based on the Bidirectional Encoder Representations from Transformers (BERT). In this hybrid method, BERT is used to train word vector representation. Convolutional neural network (CNN) capture static features. As a supplement, a bi-gated recurrent neural network (BiGRU) is adopted to capture contextual features. Furthermore, an attention mechanism is introduced to assign the weight of salient words. The experimental results confirmed that the proposed model significantly outperforms the other state-of-the-art baseline methods.

Obesity is one of the most serious public health challenges in the world. Obesity during early life has been associated with an increased risk of neurodevelopmental disorders, including deficits in learning and memory, yet the underlying mechanisms remain unclear. Here, we show that early life high-fat diet (HFD) feeding impairs hippocampus–dependent contextual/spatial learning and memory, and alters the gut microbiota, particularly by depleting Akkermansia muciniphila(A. muciniphila), in mice. Transplantation of the HFD microbiota confers hippocampus-dependent learning and memory deficits to mice fed a chow diet. Oral treatment of HFD-fed mice with the gut commensal A. muciniphilacorrects gut permeability, reduces hippocampal microgliosis and proinflammatory cytokines (tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and IL-6) expression, and restores neuronal development and synapse plasticity, thus ameliorates defects in learning and memory. Interestingly, treatment of mice with lipopolysaccharide (LPS) mimics HFD-induced hippocampus-dependent cognitive impairment in chow-fed mice. In line with these findings, pharmacologic blockade of Toll-like receptor 4 (TLR4) signalling or antibiotics treatment both effectively prevent hippocampus-dependent learning and memory deficits in HFD-fed mice. Collectively, our findings demonstrate an unexpected pivotal role of gut microbiota in HFD-induced cognitive deficits and identify a potential probiotic therapy for obesity associated with cognitive dysfunction during early life.