Highly Stable Lithium Metal Batteries Enabled by Tuning the Molecular Polarity of Diluents in Localized High-Concentration Electrolytes.

Electrolyte plays a crucial role in ensuring stable operation of lithium metal batteries (LMBs). Localized high-concentration electrolytes (LHCEs) have the potential to form a robust solid-electrolyte interphase (SEI) and mitigate Li dendrite growth, making them a highly promising electrolyte option. However, the principles governing the selection of diluents, a crucial component in LHCE, have not been clearly determined, hampering the advancement of such a type of electrolyte systems. Herein, the diluents from the perspective of molecular polarity are rationally designed and developed. A moderately fluorinated solvent, 1-(1,1,2,2-tetrafluoroethoxy)propane (TNE), is employed as a diluent to create a novel LHCE. The unique molecular structure of TNE enhances the intrinsic dipole moment, thereby altering solvent interactions and the coordination environment of Li-ions in LHCE. The achieved solvation structure not only enhances the bulk properties of LHCE, but also facilitates the formation of more stable anion-derived SEIs featured with a higher proportion of inorganic species. Consequently, the corresponding full cells of both Li||LiFePO4 and Li||LiNi0.8Co0.1Mn0.1O2 cells utilizing Li thin-film anodes exhibit extended long-term stability with significantly improved average Coulombic efficiency. This work offers new insights into the functions of diluents in LHCEs and provides direction for further optimizing the LHCEs for LMBs.

Bacterial interactome disturbance in chronic obstructive pulmonary disease clinical stability and exacerbations.

RATIONALE: Our understanding of airway dysbiosis in chronic obstructive pulmonary disease (COPD) remains incomplete, which may be improved by unraveling the complexity in microbial interactome. OBJECTIVES: To characterize reproducible features of airway bacterial interactome in COPD at clinical stability and during exacerbation, and evaluate their associations with disease phenotypes. METHODS: We performed weighted ensemble-based co-occurrence network analysis of 1742 sputum microbiomes from published and new microbiome datasets, comprising two case-control studies of stable COPD versus healthy control, two studies of COPD stability versus exacerbation, and one study with exacerbation-recovery time series data. RESULTS: Patients with COPD had reproducibly lower degree of negative bacterial interactions, i.e. total number of negative interactions as a proportion of total interactions, in their airway microbiome compared with healthy controls. Evaluation of the Haemophilus interactome showed that the antagonistic interaction networks of this established pathogen rather than its abundance consistently changed in COPD. Interactome dynamic analysis revealed reproducibly reduced antagonistic interactions but not diversity loss during COPD exacerbation, which recovered after treatment. In phenotypic analysis, unsupervised network clustering showed that loss of antagonistic interactions was associated with worse clinical symptoms (dyspnea), poorer lung function, exaggerated neutrophilic inflammation, and higher exacerbation risk. Furthermore, the frequent exacerbators (≥ 2 exacerbations per year) had significantly reduced antagonistic bacterial interactions while exhibiting subtle compositional changes in their airway microbiota. CONCLUSIONS: Bacterial interactome disturbance characterized by reduced antagonistic interactions, rather than change in pathogen abundance or diversity, is a reproducible feature of airway dysbiosis in COPD clinical stability and exacerbations, which suggests that we may target interactome rather than pathogen alone for disease treatment.

Kinetic understanding of lithium metal electrodeposition for lithium anodes.

Lithium, a representative alkali metal, holds the coveted status of the "holy grail" in the realm of next-generation rechargeable batteries, owing to its remarkable theoretical specific capacity and low electrode potential. However, the inherent reactivity of Li metal inevitably results in the formation of the solid-electrolyte interphase (SEI) on its surface, adding complexity to the Li electrodeposition process compared to conventional metal electrodeposition. Attaining uniform Li deposition is crucial for ensuring stable, long-cycle performance and high Coulombic efficiency in Li metal batteries, which requires a comprehensive understanding of the underlying factors governing the electrodeposition process. This review delves into the intricate kinetics of Li electrodeposition, elucidating the multifaceted factors that influence charge and mass transfer kinetics. The intrinsic relationship between charge transfer kinetics and Li deposition is scrutinized, exploring how parameters such as current density and electrode potential impact Li nucleation and growth, as well as dendrite formation. Additionally, the applicability of classical mass-transfer-controlled electrodeposition models to Li anode systems is evaluated, considering the influence of ionic concentration and solvation structure on Li+ transport, SEI formation, and subsequent deposition kinetics. The pivotal role of SEI compositional structure and physicochemical properties in governing charge and mass transfer processes is underscored, with an emphasis on strategies for regulating Li deposition kinetics from both electrolyte and SEI perspectives. Finally, future directions in Li electrodeposition research are outlined, emphasizing the importance of ongoing exploration from a kinetic standpoint to fully unlock the potential of Li metal batteries.

Application of machine learning in the preoperative radiomic diagnosis of ameloblastoma and odontogenic keratocyst based on cone-beam CT.

OBJECTIVES: Preoperative diagnosis of oral ameloblastoma (AME) and odontogenic keratocyst (OKC) has been a challenge in dentistry. This study uses radiomics approaches and machine learning (ML) algorithms to characterize cone-beam CT (CBCT) image features for the preoperative differential diagnosis of AME and OKC and compares ML algorithms to expert radiologists to validate performance. METHODS: We retrospectively collected the data of 326 patients with AME and OKC, where all diagnoses were confirmed by histopathologic tests. A total of 348 features were selected to train six ML models for differential diagnosis by a 5-fold cross-validation. We then compared the performance of ML-based diagnoses to those of radiologists. RESULTS: Among the six ML models, XGBoost was effective in distinguishing AME and OKC in CBCT images, with its classification performance outperforming the other models. The mean precision, recall, accuracy, F1-score, and area under the curve (AUC) were 0.900, 0.807, 0.843, 0.841, and 0.872, respectively. Compared to the diagnostics by radiologists, ML-based radiomic diagnostics performed better. CONCLUSIONS: Radiomic-based ML algorithms allow CBCT images of AME and OKC to be distinguished accurately, facilitating the preoperative differential diagnosis of AME and OKC. ADVANCES IN KNOWLEDGE: ML and radiomic approaches with high-resolution CBCT images provide new insights into the differential diagnosis of AME and OKC.

Preoperative prediction for early recurrence of hepatocellular carcinoma using machine learning-based radiomics.

Objective: To develop a contrast-enhanced computed tomography (CECT) based radiomics model using machine learning method and assess its ability of preoperative prediction for the early recurrence of hepatocellular carcinoma (HCC). Methods: A total of 297 patients confirmed with HCC were assigned to the training dataset and test dataset based on the 8:2 ratio, and the follow-up period of the patients was from May 2012 to July 2017. The lesion sites were manually segmented using ITK-SNAP, and the pyradiomics platform was applied to extract radiomic features. We established the machine learning model to predict the early recurrence of HCC. The accuracy, AUC, standard deviation, specificity, and sensitivity were applied to evaluate the model performance. Results: 1,688 features were extracted from the arterial phase and venous phase images, respectively. When arterial phase and venous phase images were employed correlated with clinical factors to train a prediction model, it achieved the best performance (AUC with 95% CI 0.8300(0.7560-0.9040), sensitivity 89.45%, specificity 79.07%, accuracy 82.67%, p value 0.0064). Conclusion: The CECT-based radiomics may be helpful to non-invasively reveal the potential connection between CECT images and early recurrence of HCC. The combination of radiomics and clinical factors could boost model performance.

Adaptive Fuzzy Tracking Control With Global Prescribed-Time Prescribed Performance for Uncertain Strict-Feedback Nonlinear Systems.

For strict-feedback systems with mismatched uncertainties, adaptive fuzzy control techniques are developed to provide global prescribed performance with prescribed-time convergence. First, a class of prescribed-time prescribed performance functions are designed to quantify the performance constraints of the tracking error. Additionally, a novel error transformation function is provided to eliminate the initial value limitations and resolve the singularity issue in previous research. To ensure the convergence of the tracking error into a prescribed bounded region within a prescribed time and satisfactory transient performance, controllers with or without approximating structures are established. Notably, the settling time and initial condition of the prescribed performance function are completely independent of the initial tracking error and system parameters, thereby improving upon existing results. Furthermore, the disadvantage of the semi-global boundedness of tracking error induced by dynamic surface control can be eliminated through the use of a novel Lyapunov-like energy function. Finally, the effectiveness of the proposed strategies is validated through numerical simulations performed on practical examples.

In Situ Electrochemical Atomic Force Microscopy: From Interfaces to Interphases.

The electrochemical interface formed between an electrode and an electrolyte significantly affects the rate and mechanism of the electrode reaction through its structure and properties, which vary across the interface. The scope of the interface has been expanded, along with the development of energy electrochemistry, where a solid-electrolyte interphase may form on the electrode and the active materials change properties near the surface region. Developing a comprehensive understanding of electrochemical interfaces and interphases necessitates three-dimensional spatial resolution characterization. Atomic force microscopy (AFM) offers advantages of imaging and long-range force measurements. Here we assess the capabilities of AFM by comparing the force curves of different regimes and various imaging modes for in situ characterizing of electrochemical interfaces and interphases. Selected examples of progress on work related to the structures and processes of electrode surfaces, electrical double layers, and lithium battery systems are subsequently illustrated. Finally, this review provides perspectives on the future development of electrochemical AFM.

Andrographolide Attenuates NLRP3 Inflammasome Activation and Airway Inflammation in Exacerbation of Chronic Obstructive Pulmonary Disease.

Purpose: The aim of this study is to uncover the anti-inflammatory propertity of andrographolide (AGP) in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) and the underlying mechanisms related to the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome pathway. Methods: An in vivo experiment was conducted on murine model of AECOPD through endotracheal atomization of elastase and lipopolysaccharide (LPS). Intraperitoneal AGP was administered four times. NLRP3 inflammasome pathway molecules were examined using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot analysis. By using enzyme-linked immunosorbent assay (ELISA), we tested interleukin (IL)-1ß levels in bronchoalveolar lavage fluid. An in vitro study was conducted to determine how AGP impacts the NLRP3 inflammasome in THP-1 derived macrophages. The levels of molecules involved in the pathway were measured. Furthermore, molecular docking analyses were carried out to investigate the interactions between AGP and pathway targets. Results: In the in vivo study, NLRP3 inflammasome activation was observed in mice experiencing AECOPD. The administration of high-dose AGP demonstrated a mitigating effect on inflammatory cells infiltration in the lungs. Moreover, AGP administration effectively suppressed the expression of NLRP3, apoptosis associated speck-like protein that contains a CARD (PYCARD), cysteinyl aspartate-specific protease-1 (Caspase-1), IL-1ß, and IL-18 at both the genetic and protein levels. In the in vitro experiment, IL-1ß levels were significantly elevated in THP-1 derived macrophages with activated inflammasome compared to the control group. Furthermore, the downregulation of NLRP3, CASP1, and IL1B genes was observed upon the inhibition of NLRP3 expression through small interfering RNA (siRNA). AGP demonstrated inhibitory effects on the gene expression and protein levels of NLRP3, Caspase-1, and IL-1ß. Additionally, molecular docking analysis confirmed that AGP exhibited a favorable binding affinity with all five targets of the pathway. Conclusion: AGP effectively inhibited NLRP3 inflammasome activation and mitigated the inflammatory reaction of AECOPD both in animal models and in vitro experiments, highlighting the potential of AGP as a treatment for AECOPD with anti-inflammatory properties.

Efficacy and cerebral mechanisms of acupuncture for chronic obstructive pulmonary disease: study protocol for a multicenter, randomized controlled neuroimaging trial.

Introduction: Although acupuncture is recommended by chronic obstructive pulmonary disease (COPD) treatment guidelines owing to its effects on dyspnea, the underlying neurobiological mechanisms of these effects remain unclear. This study aims to evaluate the efficacy of acupuncture in patients with stable COPD and explore the possible involvement of specific brain regions. Methods: This is a prospective, multicenter, single-blind, randomized controlled trial. A total of 90 participants will be recruited from three centers and will be randomly assigned in a 1:1 ratio to undergo acupuncture at acupoints on the disease-affected meridian (DAM) or non-acupoints on the non-affected meridian (NAM), in addition to routine pharmacological treatments. All participants will undergo 30 min of acupuncture three times a week for 8 weeks and will be followed up for 12 months. The primary outcome will be the severity of dyspnea, as measured using the Borg Dyspnea Scale and a visual analog scale at rest and after exercise. The secondary outcomes will include the multidimensional profile of dyspnea using Dyspnea-12, the modified Medical Research Council Dyspnea Scale, and the COPD assessment test; quality of life assessments using St George's Respiratory Questionnaire and the Hospital Anxiety and Depression Scale; and additional measurements of exacerbation frequency, pulmonary function, and the 6-min walking distance. Magnetic resonance imaging (MRI) will be performed before and after exercise to explore the potential neurobiological mechanisms of exertional dyspnea. Anxiety and depression will be measured and analyzed for their correlation with the activation of specific brain areas involved in dyspnea. Discussion: This randomized controlled trial aims to use a multidimensional evaluation of the efficacy of acupuncture in relieving dyspnea in patients with COPD in terms of emotion and quality of life and explore the neurobiological mechanisms underlying the effects of acupuncture on dyspnea from an imaging perspective. It is expected to provide strong evidence to support the use of acupuncture in relieving dyspnea in patients with COPD and those with aother diseases involving dyspnea. Additionally, it provides novel insights into the central mechanisms of acupuncture intervention and dyspnea. Trial registration: Chinese Clinical Trial Registry (https://www.chictr.org.cn/): ChiCTR2300071725.

Citronellal can alleviate vascular endothelial dysfunction by reducing ectopic miR-133a expression.

AIMS: Endothelial dysfunction (ED) is the initial cause of atherosclerosis (AS) and an early marker of many cardiovascular diseases (CVD). Citronellal (CT), a monoterpenoid natural product extracted from grass plant Citronella, has been shown to have anti-thrombotic, anti-hypertensive and anti-diabetic cardiomyopathy activities. The aim of this study is to investigate the effects of citronellal on vascular endothelial dysfunction and the underlying mechanisms. MATERIALS AND METHODS: The left common carotid artery was subjected to one-time balloon injury to cause vascular endothelial injury, and the AS model was established by feeding with high-fat diet. Use of HUVECs H2O2 treatment induced HUVECs oxidative stress damage model. The blood lipid level, histopathology, Western blot, immunohistochemistry, RT-PCR, ELISA and in situ fluorescence hybridization of common carotid artery tissues and HUVECs were studied. KEY FINDINGS: CT significantly reduced vascular plate area and endothelial lipid and cholesterol deposition in the common carotid artery of mice in a dose-dependent manner. CT increased the expression of activated protein 2α (AP-2α/TFAP2A) and circRNA_102979, and inhibited the ectopic expression level of miR-133a. However, the constructed lentivirus with AP-2α silencing and circRNA_102979 silencing reversed this phenomenon. SIGNIFICANCE: The current study verifies CT can increase the expression levels of AP-2α and circRNA_102979 in vascular endothelium, increase the adsorption effect of circRNA_102979 on miR-133a and relieve the inhibitory effect of miR-133a on target genes, thereby alleviating AS-induced ED.

Acupuncture for dyspnea and breathing physiology in chronic respiratory diseases: A systematic review and meta-analysis of randomized controlled trials.

Background: Dyspnea, a common symptom of chronic respiratory diseases (CRDs), is closely linked to higher levels of functional impairment and death, leading to significant societal and financial challenges. Despite numerous clinical trials and systematic reviews suggested the potential benefits of acupuncture for chronic obstructive pulmonary disease (COPD) and lung cancer, there is currently insufficient evidence to conclusively prove its effectiveness in alleviating dyspnea in patients with CRDs. Methods: To compile and evaluate the existing data on the effectiveness and safety of acupuncture for managing dyspnea in CRDs. Randomized controlled trials investigating acupuncture for the treatment of dyspnea in patients with CRDs, such as COPD, lung cancer, asthma, bronchiectasis, interstitial lung disease, chronic pulmonary heart disease and bronchitis, were searched and retrieved from five electronic databases in English or Chinese. Results: A total of 23 studies meeting the inclusion criteria were found in databases, covering various CRDs such as COPD, lung cancer, and asthma. A meta-analysis that compared acupuncture to a control group (which included no acupuncture and sham acupuncture) found significant advantages for acupuncture in reducing dyspnea severity (P = 0.0003), increasing 6MWD (P < 0.00001), improving quality of life measured by St. George's Respiratory Questionnaire (P = 0.03) and karnofsky performance status score (P < 0.00001). No significance was found in breathing physiology represented by FEV1 (P = 0.34) and FVC (P = 0.15). There was a comparable incidence of negative outcomes in both groups (P = 0.07). Results were consistent when compared to sham acupuncture. In addition, subgroup analyses were also consistent when different diseases or types of acupuncture were analyzed. Conclusions: Acupuncture may be an effective and safe non-pharmacological complementary intervention to relief dyspnea for patients with CRDs. Nevertheless, research with high quality and large sample sizes is needed for further investigation.

Unraveling the energy storage mechanism in graphene-based nonaqueous electrochemical capacitors by gap-enhanced Raman spectroscopy.

Graphene has been extensively utilized as an electrode material for nonaqueous electrochemical capacitors. However, a comprehensive understanding of the charging mechanism and ion arrangement at the graphene/electrolyte interface remain elusive. Herein, a gap-enhanced Raman spectroscopic strategy is designed to characterize the dynamic interfacial process of graphene with an adjustable number of layers, which is based on synergistic enhancement of localized surface plasmons from shell-isolated nanoparticles and a metal substrate. By employing such a strategy combined with complementary characterization techniques, we study the potential-dependent configuration of adsorbed ions and capacitance curves for graphene based on the number of layers. As the number of layers increases, the properties of graphene transform from a metalloid nature to graphite-like behavior. The charging mechanism shifts from co-ion desorption in single-layer graphene to ion exchange domination in few-layer graphene. The increase in area specific capacitance from 64 to 145 µF cm-2 is attributed to the influence on ion packing, thereby impacting the electrochemical performance. Furthermore, the potential-dependent coordination structure of lithium bis(fluorosulfonyl) imide in tetraglyme ([Li(G4)][FSI]) at graphene/electrolyte interface is revealed. This work adds to the understanding of graphene interfaces with distinct properties, offering insights for optimization of electrochemical capacitors.

Step-induced double-row pattern of interfacial water on rutile TiO2(110) under electrochemical conditions.

Metal oxides are promising (photo)electrocatalysts for sustainable energy technologies due to their good activity and abundant resources. Their applications such as photocatalytic water splitting predominantly involve aqueous interfaces under electrochemical conditions, but in situ probing oxide-water interfaces is proven to be extremely challenging. Here, we present an electrochemical scanning tunneling microscopy (EC-STM) study on the rutile TiO2(110)-water interface, and by tuning surface redox chemistry with careful potential control we are able to obtain high quality images of interfacial structures with atomic details. It is interesting to find that the interfacial water exhibits an unexpected double-row pattern that has never been observed. This finding is confirmed by performing a large scale simulation of a stepped interface model enabled by machine learning accelerated molecular dynamics (MLMD) with ab initio accuracy. Furthermore, we show that this pattern is induced by the steps present on the surface, which can propagate across the terraces through interfacial hydrogen bonds. Our work demonstrates that by combining EC-STM and MLMD we can obtain new atomic details of interfacial structures that are valuable to understand the activity of oxides under realistic conditions.