Due to the energy crisis within recent decades, renewable energies such as solar, wind and tide energies have received a lot of attention. However, these renewable energies are dependent on the time and season. Consequently, energy storage systems are needed to fully utilize these energies including their connection with smart grids. Aqueous rechargeable lithium batteries (ARLBs) may be an ideal energy storage system due to its excellent safety and reliability. However, since the introduction of ARLBs in 1994, the progress on improving their performance has been very limited. Recently, their rate performance, especially superfast charging performance, reversible capacity and cycling life of their electrode materials were markedly improved. The present work reviews the latest advances in the exploration of the electrode materials and the development of battery systems. Also the main challenges in this field are briefly commented on and discussed. Broader contextFor large-scale energy storage systems, their safety and reliability are more challenging than those required for electric vehicles. New rechargeable batteries are urgently needed. It has been well realized that an aqueous electrolyte is one of the safest choices for rechargeable batteries. In addition, the ionic conductivity of aqueous electrolytes is higher than those of nonaqueous and solid electrolytes, which is one prerequisite for a fast redox reaction, i.e., fast charge and discharge processes. In the case of aqueous rechargeable lithium batteries (ARLBs), the rst was invented in 1994. Only until recently has great progress been achieved. The main reasons are ascribed to the nanostructuring and surface coating on their electrode materials. The reversible capacities of their electrode materials are markedly increased, which can be similar to those achieved in organic electrolytes. Their cycling life is excellent. For example, in the case of LiMn 2 O 4 , its capacity retention can be 93% aer 10 000 full cycles. In addition, their electrode materials and the ARLBs can be charged at a super fast rate, which is comparable with gasoline lling for car engines. These progresses show that ARLBs provide another promising choice as a power source for smart grids and hybrid electric vehicles, and can assist the power sources of electric vehicles and range-extenders.

Gut microbiome disturbances have been implicated in major depressive disorder (MDD). However, little is known about how the gut virome, microbiome, and fecal metabolome change, and how they interact in MDD. Here, using whole-genome shotgun metagenomic and untargeted metabolomic methods, we identified 3 bacteriophages, 47 bacterial species, and 50 fecal metabolites showing notable differences in abundance between MDD patients and healthy controls (HCs). Patients with MDD were mainly characterized by increased abundance of the genus Bacteroides and decreased abundance of the genera Blautia and Eubacterium. These multilevel omics alterations generated a characteristic MDD coexpression network. Disturbed microbial genes and fecal metabolites were consistently mapped to amino acid (γ-aminobutyrate, phenylalanine, and tryptophan) metabolism. Furthermore, we identified a combinatorial marker panel that robustly discriminated MDD from HC individuals in both the discovery and validation sets. Our findings provide a deep insight into understanding of the roles of disturbed gut ecosystem in MDD.

Discriminating depressive episodes of bipolar disorder (BD) from major depressive disorder (MDD) is a major clinical challenge. Recently, gut microbiome alterations are implicated in these two mood disorders; however, little is known about the shared and distinct microbial characteristics in MDD versus BD. Here, using 16S ribosomal RNA (rRNA) gene sequencing, the microbial compositions of 165 subjects with MDD are compared with 217 BD, and 217 healthy controls (HCs). It is found that the microbial compositions are different between the three groups. Compared to HCs, MDD is characterized by altered covarying operational taxonomic units (OTUs) assigned to the Bacteroidaceae family, and BD shows disturbed covarying OTUs belonging to Lachnospiraceae, Prevotellaceae, and Ruminococcaceae families. Furthermore, a signature of 26 OTUs is identified that can distinguish patients with MDD from those with BD or HCs, with area under the curve (AUC) values ranging from 0.961 to 0.986 in discovery sets, and 0.702 to 0.741 in validation sets. Moreover, 4 of 26 microbial markers correlate with disease severity in MDD or BD. Together, distinct gut microbial compositions are identified in MDD compared to BD and HCs, and a novel marker panel is provided for distinguishing MDD from BD based on gut microbiome signatures.

Major depressive disorder (MDD) is a serious mental illness, characterized by high morbidity, which has increased in recent decades. However, the molecular mechanisms underlying MDD remain unclear. Previous studies have identified altered metabolic profiles in peripheral tissues associated with MDD. Using curated metabolic characterization data from a large sample of MDD patients, we meta-analyzed the results of metabolites in peripheral blood. Pathway and network analyses were then performed to elucidate the biological themes within these altered metabolites. We identified 23 differentially expressed metabolites between MDD patients and controls from 46 studies. MDD patients were characterized by higher levels of asymmetric dimethylarginine, tyramine, 2-hydroxybutyric acid, phosphatidylcholine (32:1), and taurochenodesoxycholic acid and lower levels of L-acetylcarnitine, creatinine, L-asparagine, L-glutamine, linoleic acid, pyruvic acid, palmitoleic acid, L-serine, oleic acid, myo-inositol, dodecanoic acid, L-methionine, hypoxanthine, palmitic acid, L-tryptophan, kynurenic acid, taurine, and 25-hydroxyvitamin D compared with controls. L-tryptophan and kynurenic acid were consistently downregulated in MDD patients, regardless of antidepressant exposure. Depression rating scores were negatively associated with decreased levels of L-tryptophan. Pathway and network analyses revealed altered amino acid metabolism and lipid metabolism, especially for the tryptophan-kynurenine pathway and fatty acid metabolism, in the peripheral system of MDD patients. Taken together, our integrated results revealed that metabolic changes in the peripheral blood were associated with MDD, particularly decreased L-tryptophan and kynurenic acid levels, and alterations in the tryptophan-kynurenine and fatty acid metabolism pathways. Our findings may facilitate biomarker development and the elucidation of the molecular mechanisms that underly MDD.