Asymmetric Convolution: An Efficient and Generalized Method to Fuse Feature Maps in Multiple Vision Tasks.

Fusing features from different sources is a critical aspect of many computer vision tasks. Existing approaches can be roughly categorized as parameter-free or learnable operations. However, parameter-free modules are limited in their ability to benefit from offline learning, leading to poor performance in some challenging situations. Learnable fusing methods are often space-consuming and timeconsuming, particularly when fusing features with different shapes. To address these shortcomings, we conducted an in-depth analysis of the limitations associated with both fusion methods. Based on our findings, we propose a generalized module named Asymmetric Convolution Module (ACM). This module can learn to encode effective priors during offline training and efficiently fuse feature maps with different shapes in specific tasks. Specifically, we propose a mathematically equivalent method for replacing costly convolutions on concatenated features. This method can be widely applied to fuse feature maps across different shapes. Furthermore, distinguished from parameter-free operations that can only fuse two features of the same type, our ACM is general, flexible, and can fuse multiple features of different types. To demonstrate the generality and efficiency of ACM, we integrate it into several state-of-the-art models on three representative vision tasks: visual object tracking, referring video object segmentation, and monocular 3D object detection. Extensive experimental results on three tasks and several datasets demonstrate that our new module can bring significant improvements and noteworthy efficiency.

Influence of Etchants on Etched Surfaces of High-Strength and High-Conductivity Cu Alloy of Different Processing States.

With the continuous integration of semiconductor devices, the requirements of the size accuracy and surface quality of etched lead frames are stricter. The etchant is a key factor in the etching process and etched surface quality, while the effects of the difference in etchants on the etched surface morphology of Cu alloy have not been directly studied. In this study, aqua regia, acidic FeCl3 and two CuCl2 solutions were used as etchants, and different CuCrSn specimens were etched and characterized. The results show that the etching rate in aqua regia is high, and the grain orientation, grain boundary (GB) and dislocations have significant influences on the local etching rate. The preferential etching of some atomic planes forms steps between the grains with different orientations, and preferential etching around the GB and dislocation group forms grooves, resulting in high surface roughness. For the surfaces etched by the FeCl3 and CuCl2 etchants, the steps and grooves are blurred; thus, they are less rough. The CuCrSn alloy surface etched by the aqua regia is clean, with little Cr-rich particles, while high-density Cr-rich particles remain on the surfaces etched by the FeCl3 and CuCl2 etchants. For the same kind of etchant, the ion concentration can affect the etching mechanism, rate and the etched surface morphology.

Temperature, humidity, and ionisation effect of iodine oxoacid nucleation.

Iodine oxoacids are recognised for their significant contribution to the formation of new particles in marine and polar atmospheres. Nevertheless, to incorporate the iodine oxoacid nucleation mechanism into global simulations, it is essential to comprehend how this mechanism varies under various atmospheric conditions. In this study, we combined measurements from the CLOUD (Cosmic Leaving OUtdoor Droplets) chamber at CERN and simulations with a kinetic model to investigate the impact of temperature, ionisation, and humidity on iodine oxoacid nucleation. Our findings reveal that ion-induced particle formation rates remain largely unaffected by changes in temperature. However, neutral particle formation rates experience a significant increase when the temperature drops from +10 °C to -10 °C. Running the kinetic model with varying ionisation rates demonstrates that the particle formation rate only increases with a higher ionisation rate when the iodic acid concentration exceeds 1.5 × 107 cm-3, a concentration rarely reached in pristine marine atmospheres. Consequently, our simulations suggest that, despite higher ionisation rates, the charged cluster nucleation pathway of iodic acid is unlikely to be enhanced in the upper troposphere by higher ionisation rates. Instead, the neutral nucleation channel is likely to be the dominant channel in that region. Notably, the iodine oxoacid nucleation mechanism remains unaffected by changes in relative humidity from 2% to 80%. However, under unrealistically dry conditions (below 0.008% RH at +10 °C), iodine oxides (I2O4 and I2O5) significantly enhance formation rates. Therefore, we conclude that iodine oxoacid nucleation is the dominant nucleation mechanism for iodine nucleation in the marine and polar boundary layer atmosphere.

Deletion of Nrf2 induced severe oxidative stress and apoptosis in mice model of diabetic bladder dysfunction.

The nuclear factor erythroid 2-related factor 2 (Nrf2) pathway has been confirmed as a therapeutic target for type 2 diabetes mellitus (T2DM), however few studies revealed its effect in diabetic bladder dysfunction (DBD). Herein, we reported a Nrf2 deletion diabetic mouse model induced by 8-week high-fat diet feeding combined with streptozocin (STZ) injection in Nrf2 knockout mice. Besides, wild-type mice (WT) were used as control group, wild-type mice with high-fat diet feeding and STZ injection as diabetic group (WT-T2DM), and Nrf2 knockout mice as Nrf2 deletion group (KO). The pathophysiological indexes and bladder morphology showed typical pathological features of diabetic bladder dysfunction in Nrf2 knockout diabetic mouse mice (KO-T2DM). ELISA results showed that advanced glycation end products (AGEs), ROS and malondialdehyde (MDA) levels in bladder was were up-regulated in both WT-T2DM and KO-T2DM group, while superoxide dismutase (SOD) and glutathione (GSH) levels decreased in these two groups. Compared with WT-T2DM group, western blot analysis of the bladder showed down-regulated expression of NQO1 and HO-1 in KO-T2DM group. However, apoptosis, marked by Caspase3 and bax/bcl-2 ratio, was increased in KO-T2DM group. Neurotrophic factor (NGF) was significantly decreased in DBD model, and even much lower in KO-T2DM group. Collectively, our findings demonstrated that deletion of Nrf2 lead to severe oxidative stress, apoptosis, and lower level of neurotrophic factor, and provided the first set of experimental evidence, in a mouse model, to support Nrf2 as a promising target for DBD.

Evaluation of an automated clinical decision system with deep learning dose prediction and NTCP model for prostate cancer proton therapy.

OBJECTIVE: To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on the normal tissue complication probability (NTCP) model. Approach: Two 3D UNets were established to predict photon and proton doses. A dataset of 95 patients with localized prostate cancer was randomly partitioned into 55, 10, and 30 for training, validation, and testing, respectively. We selected NTCP models for late rectum bleeding and acute urinary urgency of grade 2 or higher to quantify the benefit of proton therapy. Propagated uncertainties of predicted ΔNTCPs resulting from the dose prediction errors were calculated. Patient selection accuracies for a single endpoint and a composite evaluation were assessed under different ΔNTCP thresholds. Main results: Our deep learning-based dose prediction technique can reduce the time spent on plan comparison from approximately 2 days to as little as 5 seconds. The expanded uncertainty of predicted ΔNTCPs for rectum and bladder endpoints propagated from the dose prediction error were 0.0042 and 0.0016, respectively, which is less than one-third of the acceptable tolerance. The averaged selection accuracies for rectum bleeding, urinary urgency, and composite evaluation were 90%, 93.5%, and 93.5%, respectively. Significance: Our study demonstrates that deep learning dose prediction and NTCP evaluation scheme could distinguish the NTCP differences between photon and proton treatment modalities. In addition, the dose prediction uncertainty does not significantly influence the decision accuracy of NTCP-based patient selection for proton therapy. Therefore, automated deep learning dose prediction and NTCP evaluation schemes can potentially be used to screen large patient populations and to avoid unnecessary delays in the start of prostate cancer radiotherapy in the future.

Nanoskiving of van der Waals Materials toward Edge/Basal Plane Contact Heterojunctions for High-Performance Photodetection.

The unique features of edges in van der Waals materials may lead to edge-basal plane contacts that could provide new opportunities for electronic and optoelectronic devices. However, few studies have addressed edge/basal plane contact heterojunctions owing to the formidable challenges in integrating edges with the basal plane to form a heterojunction. Here, taking the example of black phosphorus (BP)/ReS2, a heterojunction with contact between the edge and the basal plane was successfully achieved by the introduction of a nanoskiving technique to fabricate BP edges with controlled orientation, followed by the dry transfer of a ReS2 flake. The deformation of BP during the nanoskiving process was clearly revealed, where interlayer slipping in the BP determined the formation of the edges. The edge/basal plane contact heterojunctions based on BP/ReS2 exhibited a reverse-rectifying behavior upon contact, and a high rectifying current was attributed to direct tunneling and Fowler-Nordheim tunneling in low and high bias regimes, respectively. As a photodetector, the heterojunction diode demonstrated an impressive responsivity of 65 A/W, a rapid response time (<10 ms), and polarization-sensitive detection under 532 nm illumination without gate biasing.

A comprehensive genetic map of cytokine responses in Lyme borreliosis.

The incidence of Lyme borreliosis has risen, accompanied by persistent symptoms. The innate immune system and related cytokines are crucial in the host response and symptom development. We characterized cytokine production capacity before and after antibiotic treatment in 1,060 Lyme borreliosis patients. We observed a negative correlation between antibody production and IL-10 responses, as well as increased IL-1Ra responses in patients with disseminated disease. Genome-wide mapping the cytokine production allowed us to identify 34 cytokine quantitative trait loci (cQTLs), with 31 novel ones. We pinpointed the causal variant at the TLR1-6-10 locus and validated the regulation of IL-1Ra responses at transcritpome level using an independent cohort. We found that cQTLs contribute to Lyme borreliosis susceptibility and are relevant to other immune-mediated diseases. Our findings improve the understanding of cytokine responses in Lyme borreliosis and provide a genetic map of immune function as an expanded resource.

Global research trend and hotspot in the low FODMAP diet: a bibliometric analysis.

BACKGROUND: According to national guidelines, a diet low in fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAP) is a second-line therapy option for irritable bowel syndrome (IBS) and improves functional intestinal symptoms. Numerous noteworthy results have been published in this field over the past fifteen years. This study aims to analyze the global research trend and hotspot of the low FODMAP diet research, and provide a comprehensive perspective and direction for researchers. METHODS: The Science Citation Index-Expanded of the Web of Science Core Collection (WoSCC) was used to identify low FODMAP diet-related articles and reviews. Three bibliometric programs (CiteSpace, VOSviewer, Scimago Graphic) were utilized to analyze and visualize the annual publications, authors, countries, institutions, journals, citations, and keywords. RESULTS: In total, 843 documents related to the low FODMAP diet research were published in 227 journals by 3,343 authors in 1,233 institutions from 59 countries. The United States, which was the most engaged nation in international collaboration, had the largest annual production and the fastest growth. The most productive organization was Monash University, and the most fruitful researcher was Gibson PR. Nutrients ranked first in terms of the number of published documents. The article "A diet low in FODMAPs reduces symptoms of irritable bowel syndrome" (Halmos EP, 2014) received the most co-citations. Keywords that appear frequently in the literature mainly involve two main aspects: the clinical efficacy evaluation and mechanism exploration of the low FODMAP diet. The term "gut microbiota" stands out as the most prominent keyword among the burst keywords that have remained prevalent till date. CONCLUSION: The restriction stage of the low FODMAP diet is superior to other dietary therapies for IBS in terms of symptom response, but it has a negative impact on the abundance of gut Bifidobacteria and diet quality. Identification of biomarkers to predict response to the low FODMAP diet is of great interest and has become the current research hotspot.

Covid-19 pandemic, social normative compliance, and sustainable consumption: Evidence from experiments.

This research aims to investigate the causal effects of consumers' Covid-19 pandemic experiences on their preferences for sustainable consumption. Drawing on social identity theory, we argue that pandemic experiences heighten consumers' awareness of the importance of adhering to collective social norms, subsequently motivating them to adopt sustainable consumption practices that promote collective interests. Through three preregistered experiments, we demonstrate that: (i) Covid-19 pandemic experiences increase consumers' preferences for sustainable consumption; (ii) this effect is more pronounced for individuals with severer pandemic experiences and females; (iii) pandemic experiences influence sustainable consumption preferences by enhancing consumers' social normative compliance. This study contributes to the understanding of Covid-19's consequences from a micro-level perspective of consumer behavior and offers insights into the factors driving consumers' sustainable consumption preferences.

Carbon quaternization of redox active esters and olefins by decarboxylative coupling.

The synthesis of quaternary carbons often requires numerous steps and complex conditions or harsh reagents that act on heavily engineered substrates. This is largely a consequence of conventional polar-bond retrosynthetic disconnections that in turn require multiple functional group interconversions, redox manipulations, and protecting group chemistry. Here, we report a simple catalyst and reductant combination that converts two types of feedstock chemicals, carboxylic acids and olefins, into tetrasubstituted carbons through quaternization of radical intermediates. An iron porphyrin catalyst activates each substrate by electron transfer or hydrogen atom transfer, and then combines the fragments using a bimolecular homolytic substitution (SH2) reaction. This cross-coupling reduces the synthetic burden to procure numerous quaternary carbon---containing products from simple chemical feedstocks.

Dual-space high-frequency learning for transformer-based MRI super-resolution.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) can provide rich and detailed high-contrast information of soft tissues, while the scanning of MRI is time-consuming. To accelerate MR imaging, a variety of Transformer-based single image super-resolution methods are proposed in recent years, achieving promising results thanks to their superior capability of capturing long-range dependencies. Nevertheless, most existing works prioritize the design of transformer attention blocks to capture global information. The local high-frequency details, which are pivotal to faithful MRI restoration, are unfortunately neglected. METHODS: In this work, we propose a high-frequency enhanced learning scheme to effectively improve the awareness of high frequency information in current Transformer-based MRI single image super-resolution methods. Specifically, we present two entirely plug-and-play modules designed to equip Transformer-based networks with the ability to recover high-frequency details from dual spaces: 1) in the feature space, we design a high-frequency block (Hi-Fe block) paralleled with Transformer-based attention layers to extract rich high-frequency features; while 2) in the image intensity space, we tailor a high-frequency amplification module (HFA) to further refine the high-frequency details. By fully exploiting the merits of the two modules, our framework can recover abundant and diverse high-frequency information, rendering faithful MRI super-resolved results with fine details. RESULTS: We integrated our modules with six Transformer-based models and conducted experiments across three datasets. The results indicate that our plug-and-play modules can enhance the super-resolution performance of all foundational models to varying degrees, surpassing the capabilities of existing state-of-the-art single image super-resolution networks. CONCLUSION: Comprehensive comparison of super-resolution images and high-frequency maps from various methods, clearly demonstrating that our module possesses the capability to restore high-frequency information, showing huge potential in clinical practice for accelerated MRI reconstruction.

Secure State Estimation for Artificial Neural Networks With Unknown-But-Bounded Noises: A Homomorphic Encryption Scheme.

This article is concerned with the secure state estimation problem for artificial neural networks (ANNs) subject to unknown-but-bounded noises, where sensors and the remote estimator are connected via open and bandwidth-limited communication networks. Using the encoding-decoding mechanism (EDM) and the Paillier encryption technique, a novel homomorphic encryption scheme (HES) is introduced, which aims to ensure the secure transmission of measurement information within communication networks that are constrained by bandwidth. Under this encoding-decoding-based HES, the data being transmitted can be encrypted into ciphertexts comprising finite bits. The emphasis of this research is placed on the development of a secure set-membership state estimation algorithm, which allows for the computation of estimates using encrypted data without the need for decryption, thereby ensuring data security throughout the entire estimation process. Taking into account the unknown-but-bounded noises, the underlying ANN, and the adopted HES, sufficient conditions are determined for the existence of the desired ellipsoidal set. The related secure state estimator gains are then derived by addressing optimization problems using the Lagrange multiplier method. Lastly, an example is presented to verify the effectiveness of the proposed secure state estimation approach.

Effect of structural support size and position on depressed tibial plateau fractures: A finite element analysis.

Objective: Structural support for depressed tibial plateau fractures is receiving increasing attention. Currently, there has been little biomechanical evaluation of structural support. This work aimed to investigate the effect of structural support size and position on fracture fixation stability. Methods: A split-depressed tibial plateau fracture model was created according to the fracture map. Cortical screws combined with structural filler were used for fracture fixation. The filler diameter was set to small, medium and large, and the filler position was set to the center and offset by 1, 2 and 3 mm to study the effect of position and size on stability. Results: The maximum stress on the implant in all scenarios occurs at the lower contact surface between the anterior screw and the filler. Increased support size resulted in increased mean maximum screw stress, depressed fragment axial displacement and separated fragment transverse displacement (screw stress: 266.6 ± 37.7 MPa vs. 266.7 ± 51.0 MPa vs. 273.8 ± 41.5 MPa; depressed displacement: 0.123 ± 0.036 mm vs. 0.133 ± 0.049 mm vs. 0.158 ± 0.050 mm; separated displacement: 0.402 ± 0.031 mm VS 0.412 ± 0.047 mm VS 0.437 ± 0.049 mm). The larger the offset of the support position was, the larger the peak screw stress and the larger the reduction loss of depressed and separated fragment reduction, regardless of the support size. The medium support combined with the central position presented the minimum of peak stress and reduction loss. Cortical bone was below 2 % and trabecular strain was below 10 % for all scenarios. Conclusion: Central placement of structural support provides superior stability for the treatment of depressed tibial plateau fractures compared to the eccentric placement. When a support is placed centrally, optimal stability is achieved when the diameter matches the diameter of the depressed region. Thus, the utilization of equal-diameter fillers to provide central support appears to be an ideal selection for depressed tibial plateau fractures.

Abnormal longitudinal changes of structural covariance networks of cortical thickness in mild traumatic brain injury with posttraumatic headache.

BACKGROUND: It is widely acknowledged that mild traumatic brain injury (MTBI) leads to either functionally or anatomically abnormal brain regions. Structural covariance networks (SCNs) that depict coordinated regional maturation patterns are commonly employed for investigating brain structural abnormalities. However, the dynamic nature of SCNs in individuals with MTBI who suffer from posttraumatic headache (PTH) and their potential as biomarkers have hitherto not been investigated. METHODS: This study included 36 MTBI patients with PTH and 34 well-matched healthy controls (HCs). All participants underwent magnetic resonance imaging scans and were assessed with clinical measures during the acute and subacute phases. Structural covariance matrices of cortical thickness were generated for each group, and global as well as nodal network measures of SCNs were computed. RESULTS: MTBI patients with PTH demonstrated reduced headache impact and improved cognitive function from the acute to subacute phase. In terms of global network metrics, MTBI patients exhibited an abnormal normalized clustering coefficient compared to HCs during the acute phase, although no significant difference in the normalized clustering coefficient was observed between the groups during the subacute phase. Regarding nodal network metrics, MTBI patients displayed alterations in various brain regions from the acute to subacute phase, primarily concentrated in the prefrontal cortex (PFC). CONCLUSIONS: These findings indicate that the cortical thickness topography in the PFC determines the typical structural-covariance topology of the brain and may serve as an important biomarker for MTBI patients with PTH.

Prognostic value of pre-treatment [18F] FDG PET/CT in recurrent nasopharyngeal carcinoma without distant metastasis.

BACKGROUND: [18 F]-Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) has the ability to detect local and/or regional recurrence as well as distant metastasis. We aimed to evaluate the prognosis value of PET/CT in locoregional recurrent nasopharyngeal (lrNPC). METHODS: A total of 451 eligible patients diagnosed with recurrent I-IVA (rI-IVA) NPC between April 2009 and December 2015 were retrospectively included in this study. The differences in overall survival (OS) of lrNPC patients with and without PET/CT were compared in the I-II, III-IVA, r0-II, and rIII-IVA cohorts, which were grouped by initial staging and recurrent staging (according to MRI). RESULTS: In the III-IVA and rIII-IVA NPC patients, with PET/CT exhibited significantly higher OS rates in the univariate analysis (P = 0.045; P = 0.009; respectively). Multivariate analysis revealed that with PET/CT was an independent predictor of OS in the rIII-IVA cohort (hazard ratio [HR] = 0.476; 95% confidence interval [CI]: 0.267 to 0.847; P = 0.012). In the rIII-IVA NPC, patients receiving PET/CT sacns before salvage surgery had a better prognosis compared with MRI alone (P = 0.036). The recurrent stage (based on PET/CT) was an independent predictor of OS. (r0-II versus [vs]. rIII-IVA; HR = 0.376; 95% CI: 0.150 to 0.938; P = 0.036). CONCLUSION: The present study showed that with PET/CT could improve overall survival for rIII-IVA NPC patients. PET/CT appears to be an effective method for assessing rTNM staging.

Effect of Extrusion on Mechanical Property, Corrosion Behavior, and In Vitro Biocompatibility of the As-Cast Mg-Zn-Y-Sr Alloy.

The effect of extrusion on the microstructure, mechanical property, corrosion behavior, and in vitro biocompatibility of as-cast Mg-1.5Zn-1.2Y-0.1Sr (wt.%) alloy was investigated via tensile tests, electrochemical methods, immersion tests, methylthiazolyl diphenyltetrazolium bromide (MTT), and analytical techniques. Results showed that the as-cast and as-extruded Mg-1.5Zn-1.2Y-0.1Sr alloys comprised an α-Mg matrix and Mg3Y2Zn3 phase (W-phase). In the as-cast alloy, the W-phase was mainly distributed at the grain boundaries, with a small amount of W-phase in the grains. After hot extrusion, the W-phase was broken down into small particles that were dispersed in the alloy, and the grains were refined considerably. The as-extruded alloy exhibited appropriate mechanical properties that were attributed to refinement strengthening, dispersion strengthening, dislocation strengthening, and precipitation strengthening. The as-cast and as-extruded alloys exhibited galvanic corrosion between the W-phase and α-Mg matrix as the main corrosion mechanism. The coarse W-phase directly caused the poor corrosion resistance of the as-cast alloy. The as-extruded alloy obtained via hydrogen evolution and mass loss had corrosion rates of less than 0.5 mm/year. MTT, high-content screening (HCS) analysis, and cell adhesion tests revealed that the as-extruded alloy can improve L929 cell viability and has great potential in the field of biomedical biodegradable implant materials.

Maximakinin reversed H2O2 induced oxidative damage in rat cardiac H9c2 cells through AMPK/Akt and AMPK/ERK1/2 signaling pathways.

Maximakinin (MK), a homolog of bradykinin (BK), is extracted from skin venom of the Chinese toad Bombina maxima. Although MK has a good antihypertensive effect, its effect on myocardial cells is unclear. This study investigates the protective effect of MK on hydrogen peroxide (H2O2)-induced oxidative damage in rat cardiac H9c2 cells and explores its mechanism of action. A 3-(4,5-Dimethyl-2-Thiazolyl)-2,5-Diphenyl Tetrazolium Bromide (MTT) assay was selected to detect the effect of MK on H9c2 cell viability, while flow cytometry was used to investigate the influence of MK and H2O2 on intracellular reactive oxygen species (ROS) levels. Protein expression changes were detected by western blot. In addition, specific protein inhibitors were applied to confirm the induction of ROS-related signaling pathways by MK. MTT assay results show that MK significantly reversed H2O2-induced cell growth inhibition. Flow cytometry Dichlorodihydrofluorescein diacetate (DCFH-DA) staining shows that MK significantly reversed H2O2-induced increases in intracellular ROS production in H9c2 cells. Moreover, the addition of specific protein inhibitors suggests that MK reverses H2O2-induced oxidative damage by activating AMP-activated protein kinase (AMPK)/protein kinase B (Akt) and AMPK/extracellular-regulated kinase 1/2 (ERK1/2) pathways. Finally, an inhibitor of bradykinin B2 receptors (B2Rs), HOE-140, was applied to investigate potential targets of MK in H9c2 cells. HOE-140 significantly blocked induction of AMPK/Akt and AMPK/ERK1/2 pathways by MK, suggesting a potentially important role for B2Rs in MK reversing H2O2-induced oxidative damage. Above all, MK protects against oxidative damage by inhibiting H2O2-induced ROS production in H9c2 cells. The protective mechanism of MK may be achieved by activation of B2Rs to activate downstream AMPK/Akt and AMPK/ERK1/2 pathways.

In Situ Plasma Polymerization of Self-Stabilized Polythiophene Enables Dendrite-Free Lithium Metal Anodes with Ultra-Long Cycle Life.

Constructing a flexible and chemically stable multifunctional layer for the lithium (Li) metal anodes is a highly effective approach to improve the uneven deposition of Li+ and suppress the dendrite growth. Herein, an organic protecting layer of polythiophene is in situ polymerized on the Li metal via plasma polymerization. Compared with the chemically polymerized thiophene (C-PTh), the plasma polymerized thiophene layer (P-PTh), with a higher Young's modulus of 8.1 GPa, shows strong structural stability due to the chemical binding of the polythiophene and Li. Moreover, the nucleophilic C─S bond of polythiophene facilitates the decomposition of Li salts in the electrolytes, promoting the formation of LiF-rich solid electrolyte interface (SEI) layers. The synergetic effect of the rigid LiF as well as the flexible PTh-Li can effectively regulate the uniform Li deposition and suppress the growth of Li dendrites during the repeated stripping-plating, enabling the Li anodes with long-cycling lifespan over 8000 h (1 mA cm-2 , 1 mAh cm-2) and 2500 h (10 mA cm-2 , 10 mAh cm-2 ). Since the plasma polymerization is facile (5-20 min) and environmentally friendly (solvent-free), this work offers a novel and promising strategy for the construction of the forthcoming generation of high-energy-density batteries.