CovEpiAb: a comprehensive database and analysis resource for immune epitopes and antibodies of human coronaviruses.

Coronaviruses have threatened humans repeatedly, especially COVID-19 caused by SARS-CoV-2, which has posed a substantial threat to global public health. SARS-CoV-2 continuously evolves through random mutation, resulting in a significant decrease in the efficacy of existing vaccines and neutralizing antibody drugs. It is critical to assess immune escape caused by viral mutations and develop broad-spectrum vaccines and neutralizing antibodies targeting conserved epitopes. Thus, we constructed CovEpiAb, a comprehensive database and analysis resource of human coronavirus (HCoVs) immune epitopes and antibodies. CovEpiAb contains information on over 60 000 experimentally validated epitopes and over 12 000 antibodies for HCoVs and SARS-CoV-2 variants. The database is unique in (1) classifying and annotating cross-reactive epitopes from different viruses and variants; (2) providing molecular and experimental interaction profiles of antibodies, including structure-based binding sites and around 70 000 data on binding affinity and neutralizing activity; (3) providing virological characteristics of current and past circulating SARS-CoV-2 variants and in vitro activity of various therapeutics; and (4) offering site-level annotations of key functional features, including antibody binding, immunological epitopes, SARS-CoV-2 mutations and conservation across HCoVs. In addition, we developed an integrated pipeline for epitope prediction named COVEP, which is available from the webpage of CovEpiAb. CovEpiAb is freely accessible at https://pgx.zju.edu.cn/covepiab/.

MATTE: a pipeline of transcriptome module alignment for anti-noise phenotype-gene-related analysis.

A phenotype may be associated with multiple genes that interact with each other in the form of a gene module or network. How to identify these relationships is one important aspect of comparative transcriptomics. However, it is still a challenge to align gene modules associated with different phenotypes. Although several studies attempted to address this issue in different aspects, a general framework is still needed. In this study, we introduce Module Alignment of TranscripTomE (MATTE), a novel approach to analyze transcriptomics data and identify differences in a modular manner. MATTE assumes that gene interactions modulate a phenotype and models phenotype differences as gene location changes. Specifically, we first represented genes by a relative differential expression to reduce the influence of noise in omics data. Meanwhile, clustering and aligning are combined to depict gene differences in a modular way robustly. The results show that MATTE outperformed state-of-the-art methods in identifying differentially expressed genes under noise in gene expression. In particular, MATTE could also deal with single-cell ribonucleic acid-seq data to extract the best cell-type marker genes compared to other methods. Additionally, we demonstrate how MATTE supports the discovery of biologically significant genes and modules, and facilitates downstream analyses to gain insight into breast cancer. The source code of MATTE and case analysis are available at https://github.com/zjupgx/MATTE.

Superantigen-fused T cell engagers for tumor antigen-mediated robust T cell activation and tumor cell killing.

Inadequate T cell activation has severely limited the success of T cell engager (TCE) therapy, especially in solid tumors. Enhancing T cell activity while maintaining the tumor specificity of TCEs is the key to improving their clinical efficacy. However, currently, there needs to be more effective strategies in clinical practice. Here, we design novel superantigen-fused TCEs that display robust tumor antigen-mediated T cell activation effects. These innovative drugs are not only armed with the powerful T cell activation ability of superantigens but also retain the dependence of TCEs on tumor antigens, realizing the ingenious combination of the advantages of two existing drugs. Superantigen-fused TCEs have been preliminarily proven to have good (>30-fold more potent) and specific (>25-fold more potent) antitumor activity in vitro and in vivo. Surprisingly, they can also induce the activation of T cell chemotaxis signals, which may promote T cell infiltration and further provide an additional guarantee for improving TCE efficacy in solid tumors. Overall, this proof-of-concept provides a potential strategy for improving the clinical efficacy of TCEs.

Encapsulation engineering of porous crystalline frameworks for delayed luminescence and circularly polarized luminescence.

Delayed luminescence (DF), including phosphorescence and thermally activated delayed fluorescence (TADF), and circularly polarized luminescence (CPL) exhibit common and broad application prospects in optoelectronic displays, biological imaging, and encryption. Thus, the combination of delayed luminescence and circularly polarized luminescence is attracting increasing attention. The encapsulation of guest emitters in various host matrices to form host-guest systems has been demonstrated to be an appealing strategy to further enhance and/or modulate their delayed luminescence and circularly polarized luminescence. Compared with conventional liquid crystals, polymers, and supramolecular matrices, porous crystalline frameworks (PCFs) including metal-organic frameworks (MOFs), covalent-organic frameworks (COFs), zeolites and hydrogen-bonded organic frameworks (HOFs) can not only overcome shortcomings such as flexibility and disorder but also achieve the ordered encapsulation of guests and long-term stability of chiral structures, providing new promising host platforms for the development of DF and CPL. In this review, we provide a comprehensive and critical summary of the recent progress in host-guest photochemistry via the encapsulation engineering of guest emitters in PCFs, particularly focusing on delayed luminescence and circularly polarized luminescence. Initially, the general principle of phosphorescence, TADF and CPL, the combination of DF and CPL, and energy transfer processes between host and guests are introduced. Subsequently, we comprehensively discuss the critical factors affecting the encapsulation engineering of guest emitters in PCFs, such as pore structures, the confinement effect, charge and energy transfer between the host and guest, conformational dynamics, and aggregation model of guest emitters. Thereafter, we summarize the effective methods for the preparation of host-guest systems, especially single-crystal-to-single-crystal (SC-SC) transformation and epitaxial growth, which are distinct from conventional methods based on amorphous materials. Then, the recent advancements in host-guest systems based on PCFs for delayed luminescence and circularly polarized luminescence are highlighted. Finally, we present our personal insights into the challenges and future opportunities in this promising field.

Customization of Manganese Oxide Cathodes via Precise Electrochemical Lithium-Ion Intercalation for Diverse Zinc-Ion Batteries.

Manganese oxide-based aqueous zinc-ion batteries (ZIBs) are attractive energy storage devices, owing to their good safety, low cost, and ecofriendly features. However, various critical issues, including poor conductivity, sluggish reaction kinetics, and unstable structure still restrict their further development. Oxygen defect engineering is an effective strategy to improve the electrochemical performance of manganese oxides, but challenging in the accurate regulation of oxygen defects. In this work, an effective and controllable defect engineering strategy-controllable electrochemical lithium-ion intercalation - is proposed to tackle this issue. The incorporation of lithium ions and oxygen defects can promote the conductivity, lattice spacing, and structural stability of Mn2O3 (MO), thus improving its capacity (232.7 mAh g-1), rate performance, and long-term cycling stability (99.0% capacity retention after 3000 cycles). Interestingly, the optimal ratio of intercalated lithium-ion varies at different temperature or mass-loading of MO, which provides the possibility to customize diverse ZIBs to meet different application conditions. In addition, the fabricated ZIBs present good flexibility, superior safety, and admirable adaptability under extreme temperatures (-20-100 °C). This work provides an inspiration on the structural customization of metal oxide nanomaterials for diverse ZIBs, and sheds light on the construction of future portable electronics.

Global level of methylation in the sea lamprey (jawless vertebrate) genome is intermediate between invertebrate and jawed vertebrate genomes.

In eukaryotes, cytosine methylation is a primary heritable epigenetic modification of the genome that regulates many cellular processes. In invertebrate, methylated cytosine generally located on specific genomic elements (e.g., gene bodies and silenced repetitive elements) to show a "mosaic" pattern. While in jawed vertebrate (teleost and tetrapod), highly methylated cytosine located genome-wide but only absence at regulatory regions (e.g., promoter and enhancer). Many studies imply that the evolution of DNA methylation reprogramming may have helped the transition from invertebrates to jawed vertebrates, but the detail remains largely elusive. In this study, we used the whole-genome bisulfite-sequencing technology to investigate the genome-wide methylation in three tissues (heart, muscle, and sperm) from the sea lamprey, an extant agnathan (jawless) vertebrate. Strikingly, we found that the methylation level of the sea lamprey is very similar to that in sea urchin (a deuterostome) and sea squirt (a chordate) invertebrates. In sum, the global pattern in sea lamprey is intermediate methylation level (around 30%), that is higher than methylation level in the genomes of pre-bilaterians and protostomes (1%-10%), but lower than methylation level appeared in jawed vertebrates (around 70%, teleost and tetrapod). We anticipate that, in addition to genetic dynamics such as genome duplications, epigenetic dynamics such as global methylation reprograming was also orchestrated toward the emergence and evolution of vertebrates.

Anciently duplicated genes continuously recruited to heart expression in vertebrate evolution are associated with heart chamber increase.

Although gene/genome duplications in the early stage of vertebrates have been thought to provide major resources of raw genetic materials for evolutionary innovations, it is unclear whether they continuously contribute to the evolution of morphological complexity during the course of vertebrate evolution, such as the evolution from two heart chambers (fishes) to four heart chambers (mammals and birds). We addressed this issue by our heart RNA-Seq experiments combined with published data, using 13 vertebrates and one invertebrate (sea squirt, as an outgroup). Our evolutionary transcriptome analysis showed that number of ancient paralogous genes expressed in heart tends to increase with the increase of heart chamber number along the vertebrate phylogeny, in spite that most of them were duplicated at the time near to the origin of vertebrates or even more ancient. Moreover, those paralogs expressed in heart exert considerably different functions from heart-expressed singletons: the former are functionally enriched in cardiac muscle and muscle contraction-related categories, whereas the latter play more basic functions of energy generation like aerobic respiration. These findings together support the notion that recruiting anciently paralogous genes that are expressed in heart is associated with the increase of chamber number in vertebrate evolution.

Remimazolam Attenuates LPS-Derived Cognitive Dysfunction via Subdiaphragmatic Vagus Nerve Target α7nAChR-Mediated Nrf2/HO-1 Signal Pathway.

Sepsis-induced neuroinflammation is significantly associated with sepsis-related brain dysfunction. Remimazolam is a novel ultra-short-acting benzodiazepine anesthetic with multiple organ protective effects. However, it is unknown whether remimazolam can ameliorate LPS-induced brain impairment. In this study, Lipopolysaccharide (5 mg/kg, LPS) severely impaired Sprague-Dawley rats spatial learning ability, memory, and cognitive function. However, remimazolam treatment showed a protective effect on LPS-induced cognitive dysfunction. Remimazolam partly reversed LPS-induced splenomegaly, decreased serum cytokine expression, suppressed hippocampal M1 microglial activation, and mitigated oxidative stress injury and neuroinflammation. Electroacupuncture (EA) or PNU282987 treatment improved LPS-induced cognitive dysfunction and also significantly inhibited neuroinflammation and systemic inflammation. However, MLA, ML385, or subdiaphragmatic vagus nerve (SDV) treatment abolished the protective effects of remimazolam. Further mechanistic studies showed that remimazolam induces protective effects by activating subdiaphragmatic vagus nerve target α7nAChR-mediated Nrf2/HO-1 signaling pathway. These results demonstrate that remimazolam can up-regulate α7nAChR, Cyto-Nrf2, HO-1, and cognitive-related (CREB, BDNF, PSD95) protein expressions, suppress M1 microglia, ameliorate neuroinflammation or systemic inflammation, and reverse cognitive dysfunction. Therefore, this study provides insight into a new therapeutic target for the treatment of sepsis-induced cerebral dysfunction.

LILRB4 signalling in leukaemia cells mediates T cell suppression and tumour infiltration.

Immune checkpoint blockade therapy has been successful in treating some types of cancer but has not shown clinical benefits for treating leukaemia1. This result suggests that leukaemia uses unique mechanisms to evade this therapy. Certain immune inhibitory receptors that are expressed by normal immune cells are also present on leukaemia cells. Whether these receptors can initiate immune-related primary signalling in tumour cells remains unknown. Here we use mouse models and human cells to show that LILRB4, an immunoreceptor tyrosine-based inhibition motif-containing receptor and a marker of monocytic leukaemia, supports tumour cell infiltration into tissues and suppresses T cell activity via a signalling pathway that involves APOE, LILRB4, SHP-2, uPAR and ARG1 in acute myeloid leukaemia (AML) cells. Deletion of LILRB4 or the use of antibodies to block LILRB4 signalling impeded AML development. Thus, LILRB4 orchestrates tumour invasion pathways in monocytic leukaemia cells by creating an immunosuppressive microenvironment. LILRB4 represents a compelling target for the treatment of monocytic AML.

Atomically Precise Chiral Metal Nanoclusters for Circularly Polarized Light Detection.

Circularly polarized light (CPL) detection is of great significance in various applications such as drug identification, sensing and imaging. Atomically precise chiral metal nanoclusters with intense circular dichroism (CD) signals are promising candidates for CPL detection, which can further facilitate device miniaturization and integration. Herein, we report the preparation of a pair of optically active chiral silver nanoclusters [Ag7(R/S-DMA)2(dpppy)3] (BF4)3 (R/S-Ag7) for direct CPL detection. The crystal structure and molecular formula of R/S-Ag7 clusters are confirmed by single-crystal X-ray diffraction and high-resolution mass spectrometry. R/S-Ag7 clusters exhibit strong CD spectra and CPL both in solution and solid states. When used as the photoactive materials in photodetectors, R/S-Ag7 enables effective discrimination between left-handed circularly polarized and right-handed circularly polarized light at 520 nm with short response time, high responsivity and considerable discrimination ratio. This study is the first report on using atomically precise chiral metal nanoclusters for CPL detection.

Unraveling the Drivers of Tumorigenesis in the Context of Evolution: Theoretical Models and Bioinformatics Tools.

Cancer originates from somatic cells that have accumulated mutations. These mutations alter the phenotype of the cells, allowing them to escape homeostatic regulation that maintains normal cell numbers. The emergence of malignancies is an evolutionary process in which the random accumulation of somatic mutations and sequential selection of dominant clones cause cancer cells to proliferate. The development of technologies such as high-throughput sequencing has provided a powerful means to measure subclonal evolutionary dynamics across space and time. Here, we review the patterns that may be observed in cancer evolution and the methods available for quantifying the evolutionary dynamics of cancer. An improved understanding of the evolutionary trajectories of cancer will enable us to explore the molecular mechanism of tumorigenesis and to design tailored treatment strategies.

A scheme for rapid evaluation of the intermolecular three-body polarization effect in water clusters.

The ability to accurately and rapidly evaluate the intermolecular many-body polarization effect of the water system is very important for computer simulations of biomolecule in aqueous. In this paper, a scheme is proposed based on the polarizable dipole-dipole interaction model and used to rapidly estimate the intermolecular many-body polarization effect in water clusters. We use a bond-dipole-based polarization function to evaluate the polarization energy. We regard two OH bonds of a water molecule as two bond-dipoles and set the permanent OH bond-dipole moment of a water molecule to be 1.51 Debye. We estimate the induced OH bond-dipole moment via a simple formula in which only one correction factor is needed. This scheme is then applied to tens of water clusters to calculate the three- and four-body interaction energies. The three-body interaction energies of 93 water clusters produced by our scheme are compared with those produced by the counterpoise-corrected CCSD(T)/aug-cc-pVDZ, MP2/aug-cc-pVDZ, M06-2X/jul-cc-pVTZ methods, by the AMOEBApro13, iAMOEBA, AMOEBA+, AMOEBA+(CF) methods, and by the MB-pol method. The four-body interaction energies of 47 water clusters yielded by our scheme are compared with those yielded by the counterpoise-corrected MP2/aug-cc-pVDZ and M06-2X/ jul-cc-pVTZ methods, by the AMOEBApro13, AMOEBA+, AMOEBA+(CF) methods, and by the MB-pol method. The comparison results show that the scheme proposed in this paper can reproduce the counterpoise-corrected CCSD(T)/aug-cc-pVDZ three-body interaction energies and reproduce the counterpoise-corrected MP2/aug-cc-pVDZ four-body interaction energies both accurately and efficiently. We anticipate the scheme proposed here can be useful for computer simulations of liquid water and aqueous solutions.

Comprehensive analysis reveals distinct mutational signature and its mechanistic insights of alcohol consumption in human cancers.

Alcohol consumption is a critical risk factor for multiple types of cancer. A genome can be attacked and acquire numerous somatic mutations in the environment of alcohol exposure. Mutational signature has the capacity illustrating the complex somatic mutation patterns in cancer genome. Recent studies have discovered distinct mutational signatures associating with alcohol consumption in liver and esophageal cancers. However, their prevalence among diverse cancers, impact of genetic background and origin of alcohol-induced mutational signatures remain unclear. By a comprehensive bioinformatics analysis on somatic mutations from patients of four cancer types with drinking information, we identified nine mutational signatures (signatures B-J), among which signature J (similar to COSMIC signature 16) was distinctive to alcohol drinking. Signature J was associated with HNSC, ESCA and LIHC but not PAAD. Interestingly, patients with mutated allele rs1229984 in ADH1B had lower level of signature J while mutated allele rs671 in ALDH2 exhibited higher signature J abundance, suggesting acetaldehyde is one cause of signature J. Intriguingly, somatic mutations of three potential cancer driver genes (TP53, CUL3 and NSD1) were found the critical contributors for increased mutational load of signature J in alcohol consumption patients. Furthermore, signature J was enriched with early accumulated clonal mutations compared to mutations derived from late tumor growth. This study systematically characterized alcohol-related mutational signature and indicated mechanistic insights into the prevalence, origin and gene-environment interaction regarding the risk oncogenic mutations associated with alcohol intake.

CanDriS: posterior profiling of cancer-driving sites based on two-component evolutionary model.

Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored. Due to the over-excess mutations unrelated to cancer, the great challenge is to identify somatic mutations that are cancer-driven. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model: while the ground component corresponds to passenger mutations, the rapidly evolving component corresponds to driver mutations. Then, we implemented an empirical Bayesian procedure to calculate the posterior probability of a site being cancer-driven. Based on these, we developed a software CanDriS (Cancer Driver Sites) to profile the potential cancer-driving sites for thousands of tumor samples from the Cancer Genome Atlas and International Cancer Genome Consortium across tumor types and pan-cancer level. As a result, we identified that approximately 1% of the sites have posterior probabilities larger than 0.90 and listed potential cancer-wide and cancer-specific driver mutations. By comprehensively profiling all potential cancer-driving sites, CanDriS greatly enhances our ability to refine our knowledge of the genetic basis of cancer and might guide clinical medication in the upcoming era of precision medicine. The results were displayed in a database CandrisDB (http://biopharm.zju.edu.cn/candrisdb/).

MODIG: integrating multi-omics and multi-dimensional gene network for cancer driver gene identification based on graph attention network model.

MOTIVATION: Identifying genes that play a causal role in cancer evolution remains one of the biggest challenges in cancer biology. With the accumulation of high-throughput multi-omics data over decades, it becomes a great challenge to effectively integrate these data into the identification of cancer driver genes. RESULTS: Here, we propose MODIG, a graph attention network (GAT)-based framework to identify cancer driver genes by combining multi-omics pan-cancer data (mutations, copy number variants, gene expression and methylation levels) with multi-dimensional gene networks. First, we established diverse types of gene relationship maps based on protein-protein interactions, gene sequence similarity, KEGG pathway co-occurrence, gene co-expression patterns and gene ontology. Then, we constructed a multi-dimensional gene network consisting of approximately 20 000 genes as nodes and five types of gene associations as multiplex edges. We applied a GAT to model within-dimension interactions to generate a gene representation for each dimension based on this graph. Moreover, we introduced a joint learning module to fuse multiple dimension-specific representations to generate general gene representations. Finally, we used the obtained gene representation to perform a semi-supervised driver gene identification task. The experiment results show that MODIG outperforms the baseline models in terms of area under precision-recall curves and area under the receiver operating characteristic curves. AVAILABILITY AND IMPLEMENTATION: The MODIG program is available at https://github.com/zjupgx/modig. The code and data underlying this article are also available on Zenodo, at https://doi.org/10.5281/zenodo.7057241. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Selenite-Decorated Polycrystalline NiO Nanosheets Generated from Cathodic Reconstruction for Electrocatalytic Hydrogen Production.

Precatalyst reconstruction in alkaline hydrogen evolution reaction (HER) usually leads to changes in the morphology, composition, and structure, thus improving the catalytic activity, which recently receives intensive attention. However, the design strategies of cathodic reconstruction and the structural features of reconstruction products have not achieved a profound understanding. Here, from the point of thermodynamic stability, metastable nickel selenite dihydrate (NiSeO3·2H2O) is deliberately fabricated as a precatalyst to comprehensively study the reconstruction dynamics in alkaline HER. Multiple in/ex situ techniques capture the geometric, component, and phase evolutions, proving that NiSeO3·2H2O can be transformed into SeO32--decorated polycrystalline NiO nanosheets with rich active sites and good conductivity under alkaline HER conditions, which act as a real catalytic active species. Density functional theory calculations demonstrate that the adsorption of SeO32- can further promote the HER activity of NiO due to the optimized free energy of water activation and hydrogen adsorption. As a result, the SeO32--NiO catalyst exhibits a low overpotential at -10 mA cm-2 (90 mV) and long-term stability (>100 h). This work highlights the targeted design of precatalyst to trigger and utilize cathodic reconstruction and provides an available method for the development of adsorption-modulated efficient electrocatalysts.

Proteomic profiling of gastric cancer with peritoneal metastasis identifies a protein signature associated with immune microenvironment and patient outcome.

BACKGROUND: Peritoneal metastasis (PM) frequently occurs in patients with gastric cancer (GC) and is a major cause of mortality. Risk stratification for PM can optimize decision making in GC treatment. METHODS: A total of 25 GC patients (13 with synchronous, 6 with metachronous PM and 6 PM-free) were included in this study. Quantitative proteomics by high-depth tandem mass tags labeling and whole-exome sequencing were conducted in primary GC and PM samples. Proteomic signature and prognostic model were established by machine learning algorithms in PM and PM-free GC, then validated in two external cohorts. Tumor-infiltrating immune cells in GC were analyzed by CIBERSORT. RESULTS: Heterogeneity between paired primary and PM samples was observed at both genomic and proteomic levels. Compared to primary GC, proteome of PM samples was enriched in RNA binding and extracellular exosomes. 641 differently expressed proteins (DEPs) between primary GC of PM group and PM-free group were screened, which were enriched in extracellular exosome and cell adhesion pathways. Subsequently, a ten-protein signature was derived based on DEPs by machine learning. This signature was significantly associated with patient prognosis in internal cohort and two external proteomic datasets of diffuse and mixed type GC. Tumor-infiltrating immune cell analysis showed that the signature was associated with immune microenvironment of GC. CONCLUSIONS: We characterized proteomic features that were informative for PM progression of GC. A protein signature associated with immune microenvironment and patient outcome was derived, and it could guide risk stratification and individualized treatment.

Mechanism of forkhead transcription factors binding to a novel palindromic DNA site.

Forkhead transcription factors bind a canonical consensus DNA motif, RYAAAYA (R = A/G, Y = C/T), as a monomer. However, the molecular mechanisms by which forkhead transcription factors bind DNA as a dimer are not well understood. In this study, we show that FOXO1 recognizes a palindromic DNA element DIV2, and mediates transcriptional regulation. The crystal structure of FOXO1/DIV2 reveals that the FOXO1 DNA binding domain (DBD) binds the DIV2 site as a homodimer. The wing1 region of FOXO1 mediates the dimerization, which enhances FOXO1 DNA binding affinity and complex stability. Further biochemical assays show that FOXO3, FOXM1 and FOXI1 also bind the DIV2 site as homodimer, while FOXC2 can only bind this site as a monomer. Our structural, biochemical and bioinformatics analyses not only provide a novel mechanism by which FOXO1 binds DNA as a homodimer, but also shed light on the target selection of forkhead transcription factors.

Layered double hydroxide-based nanomaterials for biomedical applications.

Against the backdrop of increased public health awareness, inorganic nanomaterials have been widely explored as promising nanoagents for various kinds of biomedical applications. Layered double hydroxides (LDHs), with versatile physicochemical advantages including excellent biocompatibility, pH-sensitive biodegradability, highly tunable chemical composition and structure, and ease of composite formation with other materials, have shown great promise in biomedical applications. In this review, we comprehensively summarize the recent advances in LDH-based nanomaterials for biomedical applications. Firstly, the material categories and advantages of LDH-based nanomaterials are discussed. The preparation and surface modification of LDH-based nanomaterials, including pristine LDHs, LDH-based nanocomposites and LDH-derived nanomaterials, are then described. Thereafter, we systematically describe the great potential of LDHs in biomedical applications including drug/gene delivery, bioimaging diagnosis, cancer therapy, biosensing, tissue engineering, and anti-bacteria. Finally, on the basis of the current state of the art, we conclude with insights on the remaining challenges and future prospects in this rapidly emerging field.

Structural Design of Nanowire Wearable Stretchable Thermoelectric Generator.

Wearable thermoelectric generators as renewable energy conversion technologies have witnessed rapid development in the past decade. Herein, we design a nanowire (NW) film wavy structure which possesses an excellent temperature gradient ratio for stretchable thermoelectric generators. Taking advantage of the photothermal effect of Te NWs as the hot side and p-n NWs heterofilms (n-type Ag2Te and p-type Cu1.75Te NWs) as thermoelectric materials, a considerable output voltage can be achieved under light irradiation. Besides the electricity output, the wearable device can also make our skin warm and comfortable in cold weather. Meanwhile, we combine thermoelectric generators with passive radiative cooling technology to reduce insolation of the human body and improve the performance of the device under intense solar irradiation in hot weather. Interestingly, it can also offer continuous green energy to realize various signal perceptions, suggesting a robust strategy for electricity output and self-powered wearable electronics.