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In the context of pandemic viruses and pathogenic bacteria, triclosan (TCS), as a typical antibacterial agent, is widely used around the world. However, the health risks from TCS increase with exposure, and it is widespread in environmental and human samples. Notably, environmental transformation and human metabolism could induce potentially undesirable risks to humans, rather than simple decontamination or detoxification. This review summarizes the environmental and human exposure to TCS covering from 2004 to 2023. Particularly, health impacts from the environmental and metabolic transformation of TCS are emphasized. Environmental transformations aimed at decontamination are recognized to form carcinogenic products such as dioxins, and ultraviolet light and excessive active chlorine can promote the formation of these dioxin congeners, potentially threatening environmental and human health. Although TCS can be rapidly metabolized for detoxification, these processes can induce the formation of lipophilic ether metabolic analogs via cytochrome P450 catalysis, causing possible adverse cross-talk reactions in human metabolic disorders. Accordingly, TCS may be more harmful in environmental transformation and human metabolism. In particular, TCS can stimulate the transmission of antibiotic resistance even at trace levels, threatening public health. Considering these accruing epidemiological and toxicological studies indicating the multiple adverse health outcomes of TCS, we call on environmental toxicologists to pay more attention to the toxicity evolution of TCS during environmental transformation and human metabolism.
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BACKGROUND: Radiation-induced brain injury (RBI) represents a major challenge for cancer patients undergoing cranial radiotherapy. However, the molecular mechanisms and therapeutic strategies of RBI remain inconclusive. With the continuous exploration of the mechanisms of RBI, an increasing number of studies have implicated cerebrovascular dysfunction as a key factor in RBI-related cognitive impairment. As pericytes are a component of the neurovascular unit, there is still a lack of understanding in current research about the specific role and function of pericytes in RBI. METHODS: We constructed a mouse model of RBI-associated cognitive dysfunction in vivo and an in vitro radiation-induced pericyte model to explore the effects of senescent pericytes on the blood-brain barrier and normal CNS cells, even glioma cells. To further clarify the effects of pericyte autophagy on senescence, molecular mechanisms were explored at the animal and cellular levels. Finally, we validated the clearance of pericyte senescence by using senolytic drug and all-trans retinoic acid to investigate the role of radiation-induced pericyte senescence. RESULTS: Our findings indicated that radiation-induced pericyte senescence plays a key role in blood-brain barrier dysfunction, leading to RBI and subsequent cognitive decline. Strikingly, pericyte senescence also contributes to the growth and invasion of glioma cells. We further demonstrate that defective autophagy in pericytes is a vital regulatory mechanism for pericyte senescence. Moreover, autophagy activated by rapamycin can reverse pericyte senescence. Notably, the elimination of senescent cells by senolytic drugs significantly mitigated radiation-induced cognitive dysfunction. DISSCUSSION: Our results demonstrated that pericyte senescence may be a promising therapeutic target for RBI and glioma progression.
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Polyene cyclizations are among the most complex and challenging transformations in biology. In a single reaction step, multiple carbon-carbon bonds, ring systems and stereogenic centres are constituted from simple, acyclic precursors1-3. Simultaneously achieving this kind of precise control over product distribution and stereochemistry poses a formidable task for chemists. In particular, the polyene cyclization of (3E,7E)-homofarnesol to the valuable naturally occurring ambergris odorant (-)-ambrox is recognized as a longstanding challenge in chemical synthesis1,4-7. Here we report a diastereoselective and enantioselective synthesis of (-)-ambrox and the sesquiterpene lactone natural product (+)-sclareolide by a catalytic asymmetric polyene cyclization by using a highly Brønsted-acidic and confined imidodiphosphorimidate catalyst in the presence of fluorinated alcohols. Several experiments, including deuterium-labelling studies, suggest that the reaction predominantly proceeds through a concerted pathway in line with the Stork-Eschenmoser hypothesis8-10. Mechanistic studies show the importance of the enzyme-like microenvironment of the imidodiphosphorimidate catalyst for attaining exceptionally high selectivities, previously thought to be achievable only in enzyme-catalysed polyene cyclizations.
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Very-long-chain fatty acids (VLCFAs) are essential precursors for plant membrane lipids, cuticular waxes, suberin, and storage oils. Integral to the fatty acid elongase (FAE) complex, 3-ketoacyl-CoA synthases (KCSs) function as crucial enzymes in the VLCFA pathway, determining the chain length of VLCFA. This study explores the in-planta role of the KCS19 gene. KCS19 is predominantly expressed in leaves and stem epidermis, sepals, styles, early silique walls, beaks, pedicels, and mature embryos. Localized in the endoplasmic reticulum, KCS19 interacts with other FAE proteins. kcs19 knockout mutants displayed reduced total wax and wax crystals, particularly alkanes, while KCS19 overexpression increased these components and wax crystals. Moreover, the cuticle permeability was higher for the kcs19 mutants compared to the wild type, rendering them more susceptible to drought and salt stress, whereas KCS19 overexpression enhanced drought and salt tolerance. Disrupting KCS19 increased C18 species and decreased C20 and longer species in seed fatty acids, indicating its role in elongating C18 to C20 VLCFAs, potentially up to C24 for seed storage lipids. Collectively, KCS19-mediated VLCFA synthesis is required for cuticular wax biosynthesis and seed storage lipids, impacting plant responses to abiotic stress.
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BACKGROUND: The ARAIS trial didn't demonstrate argatroban significantly improve functional outcome at 90 days in acute ischemic stroke. We conducted post hoc analysis of ARAIS to investigate whether baseline neurological deficit was associated with outcomes. METHODS: Patients without endovascular therapy who met screening criteria as protocol and completed argatroban treatment were enrolled and classified into two subgroups according to NIHSS score at admission. Primary outcome was excellent functional outcome at 90 days, defined as mRS score of 0 to 1. Early neurological deterioration (END), defined as an increase of ≥4 in the NIHSS score from baseline within 48 hours, was investigated as secondary outcome. Compared with alteplase alone, we investigated treatment effect of argatroban plus alteplase on outcomes in subgroups and interaction with subgroups. RESULTS: A total of 675 patients from full analysis set were included: 390 were assigned into NIHSS score <10 subgroup and 285 into NIHSS score ≥10 subgroup. For primary outcome, there was similar treatment effect between argatroban plus alteplase and alteplase alone in NIHSS score ≥10 subgroup (adjusted RD, 5.8%; 95% CI, -6.0% to 17.5%; P = 0.33) and in NIHSS score <10 subgroup (adjusted RD, -1.4%; 95% CI, -9.9% to 7.1%; P = 0.75), and no significant interaction (P = 0.43). Occurrence of early neurological deterioration within 48 hours were significantly lower in NIHSS score ≥10 subgroup, compared with NIHSS score <10 subgroup (P = 0.006). CONCLUSION: Among patients with NIHSS score ≥10, argatroban plus alteplase could safely reduce END within 48 hours.
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BACKGROUND: Acute kidney injury (AKI) is a common and serious condition, particularly among elderly patients. It is associated with high morbidity and mortality rates, further compounded by the need for continuous renal replacement therapy in severe cases. To improve clinical decision-making and patient management, there is a need for accurate prediction models that can identify patients at a high risk of mortality. METHODS: Data were extracted from the Dryad Digital Repository. Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) logistic regression analysis to identify independent risk factors and construct a predictive nomogram for mortality within 28 days after continuous renal replacement therapy in elderly patients with acute kidney injury. The discrimination of the model was evaluated in the validation cohort using the area under the receiver operating characteristic curve (AUC), and calibration was evaluated using a calibration curve. The clinical utility of the model was assessed using decision curve analysis (DCA). RESULTS: A total of 606 participants were enrolled and randomly divided into two groups: a training cohort (n = 424) and a validation cohort (n = 182) in a 7:3 proportion. A risk prediction model was developed to identify independent predictors of 28-day mortality in elderly patients with AKI. The predictors included age, systolic blood pressure, creatinine, albumin, phosphorus, age-adjusted Charlson Comorbidity Index (CCI), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and sequential organ failure assessment (SOFA) score. These predictors were incorporated into a logistic model and presented in a user-friendly nomogram. In the validation cohort, the model demonstrated good predictive performance with an AUC of 0.799. The calibration curve showed that the model was well calibrated. Additionally, DCA revealed significant net benefits of the nomogram for clinical application. CONCLUSION: The development of a nomogram for predicting 28-day mortality in elderly patients with AKI receiving continuous renal replacement therapy has the potential to improve prognostic accuracy and assist in clinical decision-making.
Subject(s)
Acute Kidney Injury , Continuous Renal Replacement Therapy , Nomograms , Humans , Female , Acute Kidney Injury/mortality , Acute Kidney Injury/therapy , Male , Aged , Retrospective Studies , Aged, 80 and over , Cohort Studies , Risk Factors , Risk Assessment/methodsABSTRACT
The purpose of this study was to assess the factor structure and the measurement invariance of the Coparenting Relationship Scale (CRS) across 10 countries based on the seven-factor coparenting model (i.e., Coparenting Agreement, Coparenting Closeness, Exposure to Conflict, Coparenting Support, Endorsement of Partner's Parenting; Division of Labor) proposed by Feinberg (2003). The results of research on coparenting from numerous countries have documented its foundational importance for parent mental health, family relationship quality, child development, and psychopathology. Yet, a cross-country perspective is still lacking. Such a perspective can provide insight into which dimensions of coparenting are universally recognized and which are especially prone to variation. A unique multinational data set, comprised of 15 individual studies collected across 10 countries (Belgium, Brazil, China, Israel, Italy, Japan, Portugal, Switzerland, Turkey, USA) in nine languages was established (N = 9,292; 51.1% mothers). Measurement invariance analyses were conducted. A six-factor structure (original seven factors minus Division of Labor) of the measure was consistent across the different contexts and measurement invariance was achieved at the configural level. There was no support for metric or scalar invariance. These findings provide a basis for the CRS to be used across countries and should inspire future quantitative and qualitative research in cross-country coparenting research to understand what aspects are universal and what aspects of coparenting are linked to specific material, relational, or ideational conditions that underlie high-quality coparenting. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Parenting , Humans , Female , Adult , Male , Parenting/psychology , China , Japan , Italy , Belgium , Brazil , Portugal , Israel , Turkey , Switzerland , United States , Cross-Cultural Comparison , Psychometrics/instrumentation , Psychometrics/methods , Family Relations/psychology , Surveys and Questionnaires , Middle Aged , Factor Analysis, Statistical , ChildABSTRACT
BACKGROUND: Wenchang chickens are one of the most popular local chicken breeds in the Chinese chicken industry. However, the low feed efficiency is the main shortcoming of this breed. Therefore, there is a need to find a more precise breeding method to improve the feed efficiency of Wenchang chickens. In this study, we explored important candidate genes and variants for feed efficiency and growth traits through genome-wide association study (GWAS) analysis. RESULTS: Estimates of genomic heritability for growth and feed efficiency traits, including residual feed intake (RFI) of 0.05, average daily food intake (ADFI) of 0.21, average daily weight gain (ADG) of 0.24, body weight (BW) at 87, 95, 104, 113 days of age (BW87, BW95, BW104 and BW113) ranged from 0.30 to 0.44. Important candidate genes related to feed efficiency and growth traits were identified, such as PLCE1, LAP3, MED28, QDPR, LDB2 and SEL1L3 genes. CONCLUSION: The results identified important candidate genes for feed efficiency and growth traits in Wenchang chickens and provide a theoretical basis for the development of new molecular breeding technology.
Subject(s)
Chickens , Genome-Wide Association Study , Polymorphism, Single Nucleotide , Animals , Chickens/genetics , Chickens/growth & development , Phenotype , Animal Feed , Quantitative Trait Loci , Quantitative Trait, HeritableABSTRACT
Long-term excessive intake of sodium negatively impacts human health. Effective strategies to reduce sodium content in foods include the use of salty and salt taste-enhancing peptides, which can reduce sodium intake without compromising the flavor or salt taste. Salty and salt taste-enhancing peptides naturally exist in various foods and predominantly manifest as short-chain peptides consisting of < 10 amino acids. These peptides are primarily produced through chemical or enzymatic hydrolysis methods, purified, and identified using ultrafiltration + gel filtration chromatography + liquid chromatography-tandem mass spectrometry. This study reviews the latest developments in these purification and identification technologies, and discusses methods to evaluate their effectiveness in saltiness perception. Additionally, the study explores four biological channels potentially involved in saltiness perception (epithelial sodium channel, transient receptor potential vanilloid 1, calcium-sensing receptor (CaSR), and transmembrane channel-like 4 (TMC4)), with the latter three primarily functioning under high sodium levels. Among the channels, salty taste-enhancing peptides, such as γ-glutamyl peptides, may co-activate the CaSR channel with calcium ions to participate in saltiness perception. Salty taste-enhancing peptides with negatively charged amino acid side chains or terminal groups may replace chloride ions and activate the TMC4 channel, contributing to saltiness perception. Finally, the study discusses the feasibility of using these peptides from the perspectives of food material constraints, processing adaptability, multifunctional application, and cross-modal interaction while emphasizing the importance of utilizing computational technology. This review provides a reference for advancing the development and application of salty and salt-enhancing peptides as sodium substitutes in low-sodium food formulations.
Subject(s)
Peptides , Sodium Chloride, Dietary , Taste Perception , Taste , HumansABSTRACT
BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification. STUDY DESIGN: Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions. STUDY RESULTS: Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research. CONCLUSIONS: Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.
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Background: The overall survival rate is notably low for esophageal cancer patients with lung metastases (LM), presenting significant challenges in their treatment. Methods: Through the Surveillance, Epidemiology, and End Results (SEER) program, individuals diagnosed with esophageal cancer between 2010 and 2015 were enrolled. Based on whether esophageal cancer metastasized to the lungs, we used propensity score matching (PSM) to balance correlated variables. Propensity score matching was a critical step in our study that helped to minimize the impact of possible confounders on the study results. We balanced variables related to lung metastases using the PSM method to ensure more accurate comparisons between the study and control groups. Specifically, we performed PSM in the following steps. First, we performed a univariate logistic regression analysis to screen for variables associated with lung metastasis. For each patient, we calculated their propensity scores using a logistic regression model, taking into account several factors, including gender, T-stage, N-stage, surgical history, radiotherapy history, chemotherapy history, and bone/brain/liver metastases. We used a 1:1 matching ratio based on the propensity score to ensure more balanced baseline characteristics between the study and control groups after matching. After matching, we validated the balance of baseline characteristics to ensure that the effect of confounders was minimized. We used logistic regression to identify risk variables for LM, while Cox regression was used to find independent prognostic factors. We then created nomograms and assessed their accuracy using the calibration curve, receiver operating curves (ROC), and C index. Results: In the post-PSM cohort, individuals diagnosed with LM experienced a median overall survival (OS) of 5.0 months (95% confidence interval [CI] 4.3-5.7), which was significantly lower than those without LM (P<0.001). LM has been associated to sex, T stage, N stage, surgery, radiation, chemotherapy, and bone/brain/liver metastases. LM survival was affected by radiation, chemotherapy, and bone/liver metastases. The nomograms' predictive power was proved using the ROC curve, C-index, and validation curve. Conclusion: Patients with LM have a worse chance of surviving esophageal cancer. The nomograms can effectively predict the risk and prognosis of lung metastases from esophageal cancer.
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Three-dimensional (3D) porous metal oxide nanomaterials with controllable morphology and well-defined pore size have attracted extensive attention in the field of gas sensing. Herein, hierarchically porous ZnO-450 was obtained simply by annealing Zeolitic Imidazolate Frameworks (ZIF-90) microcrystals at an optimal temperature of 450 °C, and the effect of annealing temperature on the formation of porous nanostructure was discussed. Then the as-obtained ZnO-450 was employed as sensing materials to construct a Micro-Electro-Mechanical System (MEMS) gas sensor for detecting NO2. The MEMS sensor based on ZnO-450 displays the excellent gas-sensing performances at a lower working temperature (190 °C), such as high response value (242.18% @ 10 ppm), fast response/recovery time (9/26 s) and ultralow limit of detection (35 ppb). The ZnO-450 sensor shows better sensing performance for NO2 detection than ZnO-based composites materials or commercial ZnO nanoparticles (NPs), which are attributed to its unique hierarchically structures with high porosity and larger surface area. This ZIFs driven strategy can be expected to pave a new pathway for the design of high-performance NO2 sensors.
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INTRODUCTION: Breast cancer (BC) is the most common malignancy in women with unfavorite prognosis. OBJECTIVES: Tanshinone IIA (Tan IIA) inhibits BC progression, however, the underlying mechanism remains largely undefined. METHODS: The cytotoxicity of Tan IIA was assessed by CCK-8 and LDH assays. Ferroptosis was monitored by the level of MDA, Fe2+, lipid ROS and GSH. IHC and western blot were employed to detect the localization and expression of SLC7A11, PIAS4, KDM1A and other key molecules. The SUMOylation of SLC7A11 was detected by Ni-beads pull-down assay and Co-IP. Luciferase and ChIP assays were employed to detect the direct association between KDM1A and PIAS4 promoter. The proliferative and metastatic properties of BC cells were assessed by colony formation, CCK-8 and Transwell assays, respectively. The in vitro findings were verified in xenograft and lung metastasis models. RESULTS: Tan IIA promoted ferroptosis by suppressing SLC7A11 in BC cells. Silencing of PIAS4 or KDM1A inhibited cell growth and metastasis in BC. Mechanistically, PIAS4 facilitated the SUMOylation of SLC7A11 via direct binding to SLC7A11, and KDM1A acted as a transcriptional activator of PIAS4. Functional studies further revealed that Tan IIA decreased KDM1A expression, thus suppressing PIAS4 expression transcriptionally. The inhibition of PIAS4-dependent SUMOylation of SLC7A11 further induced ferroptosis, thereby inhibiting proliferation and metastasis in BC. CONCLUSION: Tan IIA promoted ferroptosis and inhibited tumor growth and metastasis via suppressing KDM1A/PIAS4/SLC7A11 axis.
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Lipid metabolic reprogramming is closely related to tumor progression with the mechanism not fully elucidated. Here, we report the immune-regulated role of lanosterol synthase (LSS), an essential enzyme in cholesterol synthesis. Database analysis and clinical sample experiments suggest that LSS was lowly expressed in colon and breast cancer tissues, which indicates poor prognosis. The biological activity of tumor cell lines and tumor progression in NOD scid gamma (NSG) mice were not affected after LSS knockdown, whereas LSS deficiency obviously aggravated tumor burden in fully immunized mice. Flow cytometry analysis showed that LSS knockdown significantly promoted the formation of tumor immunosuppressive microenvironment, characterized by the increase in M2 macrophages and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs), as well as the decrease in anti-tumoral T lymphocytes. With the inhibition of myeloid infiltration or loss function of T lymphocytes, the propulsive effect of LSS knockdown on tumor progression disappeared. Mechanistically, LSS knockdown increased programmed death ligand 1 (PDL1) protein stability by 2,3-oxidosqualene (OS) binding to PDL1 protein. Anti-PDL1 therapy abolished LSS deficiency-induced immunosuppressive microenvironment and cancer progression. In conclusion, our results show that LSS deficiency promotes tumor progression by establishing an OS-PDL1 axis-dependent immunosuppressive microenvironment, indicative of LSS or OS as a potential hallmark of response to immune checkpoint blockade.
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With the inclusion of "Building Inclusive, safe, Resilient and Sustainable Cities and human Settlements" (SDG11) in the United Nations Sustainable Development Goals (SDGS), the movement to promote sustainable development from an urban perspective is growing globally. Many studies examine urban sustainability efficiency from multiple dimensions, but scant attention targets the interaction among various dimensions. This research combines the water-energy-industry subsystem to evaluate the sustainable development performance of 29 provinces in China from 2018 to 2020. The results show that 1) a water system plays an important role in promoting a city's overall sustainable performance. 2) Urban sustainable efficiency has the characteristics of low value aggregation and high value dispersion in space. 3) Regional and sub-system sustainability efficiencies exhibit clear heterogeneity. 4) Rainfall improves the sustainable efficiency of cities, mainly through water systems. 5) The coupling between water and industrial subsystems is better than that between energy and industrial subsystems, and the coupling between the central region subsystem is the best. This paper offers a new perspective for understanding the current state of sustainability in China's provinces and provides more specific suggestions for improving regional sustainability efficiency in the future.
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The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.
Subject(s)
Brain , Macaca mulatta , Animals , Macaca mulatta/anatomy & histology , Brain/metabolism , Brain/anatomy & histology , Brain/diagnostic imaging , Humans , Connectome , Atlases as Topic , Male , Brain Mapping/methods , Diffusion Tensor Imaging/methods , Neural Pathways/anatomy & histology , Neural Pathways/metabolism , Neural Pathways/diagnostic imagingABSTRACT
Maximizing the potential of human liver organoids (LOs) for modeling human septic liver requires the integration of innate immune cells, particularly resident macrophage Kupffer cells. In this study, we present a strategy to generate LOs containing Kupffer cells (KuLOs) by recapitulating fetal liver hematopoiesis using human induced pluripotent stem cell (hiPSC)-derived erythro-myeloid progenitors (EMPs), the origin of tissue-resident macrophages, and hiPSC-derived LOs. Remarkably, LOs actively promote EMP hematopoiesis toward myeloid and erythroid lineages. Moreover, supplementing with macrophage colony-stimulating factor (M-CSF) proves crucial in sustaining the hematopoietic population during the establishment of KuLOs. Exposing KuLOs to sepsis-like endotoxins leads to significant organoid dysfunction that closely resembles the pathological characteristics of the human septic liver. Furthermore, we observe a notable functional recovery in KuLOs upon endotoxin elimination, which is accelerated by using Toll-like receptor-4-directed endotoxin antagonist. Our study represents a comprehensive framework for integrating hematopoietic cells into organoids, facilitating in-depth investigations into inflammation-mediated liver pathologies.
Subject(s)
Induced Pluripotent Stem Cells , Liver Diseases , Sepsis , Humans , Kupffer Cells , Liver/pathology , Liver Diseases/pathology , Organoids , Sepsis/pathology , Endotoxins , Cell DifferentiationABSTRACT
Replacing liquid electrolytes and separators in conventional lithium-ion batteries with solid-state electrolytes (SSEs) is an important strategy to ensure both high energy density and high safety. Searching for fast ionic conductors with high electrochemical and chemical stability has been the core of SSE research and applications over the past decades. Based on the atomic-level thickness and infinitely expandable planar structure, numerous two-dimensional materials (2DMs) have been exploited and applied to address the most critical issues of low ionic conductivity of SSEs and lithium dendrite growth in all-solid-state lithium batteries. This review introduces the research process of 2DMs in SSEs, then summarizes the mechanisms and strategies of inert and active 2DMs toward Li+ transport to improve the ionic conductivity and enhance the electrode/SSE interfacial compatibility. More importantly, the main challenges and future directions for the application of 2DMs in SSEs are considered, including the importance of exploring the relationship between the anisotropic structure of 2DMs and Li+ diffusion behavior, the exploitation of more 2DMs, and the significance of in situ characterizations in elucidating the mechanisms of Li+ transport and interfacial reactions. This review aims to provide a comprehensive understanding to facilitate the application of 2DMs in SSEs.
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[This corrects the article DOI: 10.7150/jca.66773.].