Record High Uranium Photoassisted Capture Performance from Fluorine-Containing Wastewater by Ag/WO3-x with Surface Defect and Heterostructure.

The uranium recovery from high concentration fluorine-containing uranium wastewater is a desired research target in the field of environmental radiochemistry but is very challenging due to the formation of stable uranium fluoride complexes that are quite difficult to extract. By employing surface defect engineering and interfacial heterostructure design, we present here the rational design of an efficient photocatalyst (Ag/WO3-x) for U(VI) uptake from fluorine-containing uranium wastewater without any sacrificial agents. The defect-rich surface of Ag/WO3-x facilitates confined adsorption of uranium, while the introduction of Ag nanoparticles enables both efficient electron-hole separation and a plasmon effect upon light irradiation. Ag/WO3-x shows high U(VI) removal efficiency of 96.3% at 8 mg/L U(VI) within 60 min. Notably, even when the ratio of F- to U(VI) is as high as 20:1, the removal efficiency of U(VI) by Ag/WO3-x reaches up to 95%. Additionally, the maximum capture capacity of U(VI) on Ag/WO3-x reaches 676.8 mg/g at 200 mg/L of U(VI) within 60 min, which is superior to ever-reported photocatalysts in fluorine-containing uranium wastewater. This work provides an effective way for the uranium capture from fluorine-containing wastewater through the synergy of plasmon effect and defect engineering.

Evaluation of laparo-endoscopic single-site surgery for adnexal mass in pregnant women.

BACKGROUND: Surgery for adnexal mass does occur in pregnant women and therefore the choice of surgery during pregnancy needs to be carefully considered and studied. This study aimed to evaluate the safety and feasibility of Laparo-endoscopic Single-site Surgery (LESS) for adnexal mass during pregnancy and investigate the perioperative condition, pregnancy complications, and obstetric outcomes of operative women during pregnancy. METHODS: This study retrospectively collected medical records and surgery videos of 20 pregnant women who underwent LESS for adnexal mass between November 2019 and January 2022. Baseline characteristics, operative-related variables, and pregnancy outcomes were followed up. RESULTS: LESS for adnexal mass was successfully performed in 20 pregnant women, with very satisfactory surgery outcomes reported in all cases. The average gestational age at operation was 15+2 weeks (range, 5+1- 25+4 weeks). The median operative time was 80.8 min (range, 40 -185 min) and the average operative bleeding was 28.0 ml (range, 10-50 ml). The average VAS of 24 h postoperatively was 1 (range, 0-2), and the average length of hospital stay was 5.15 days (range, 3-7 days). All these women delivered a healthy newborn at full term except 1 woman induced abortion for her own reasons at 16+5 weeks gestational age (GA). The average GA of delivery was 39+1 weeks (range, 37-40+1 weeks), the average birth weight was 3228.95 g (range, 2740-3930 g), and the average Apgar score at 5 min was 9.95 (range, 9-10). CONCLUSIONS: LESS for adnexal mass is safe and feasible for pregnant women.

Pro-Inflammatory Characteristics of Extracellular Vesicles in the Vitreous of Type 2 Diabetic Patients.

Diabetic retinopathy (DR) is a leading cause of blindness, yet its molecular mechanisms are unclear. Extracellular vesicles (EVs) contribute to dysfunction in DR, but the characteristics and functions of vitreous EVs are unclear. This study investigated the inflammatory properties of type 2 diabetic (db) vitreous EVs. EVs isolated from the vitreous of db and non-db donors were used for nanoparticle tracking analysis (NTA), transmission electron microscopy (TEM), immunogold staining, Western blotting, and proteomic analysis by mass spectrometry. Intracellular uptake of vitreous EVs by differentiated macrophages was evaluated using ExoGlow membrane labeling, and the impact of EVs on macrophage (THP-1) activation was assessed by cytokine levels using RT-qPCR. NTA and TEM analysis of db and non-db vitreous EVs showed non-aggregated EVs with a heterogeneous size range below 200 nm. Western blot detected EV markers (Alix, Annexin V, HSP70, and Flotillin 1) and an upregulation of Cldn5 in db EVs. While the db EVs were incorporated into macrophages, treatment of THP-1 cells with db EVs significantly increased mRNA levels of TNFα and IL-1ß compared to non-db EVs. Proteomic and gene enrichment analysis indicated pro-inflammatory characteristics of db EVs. Our results suggest a potential involvement of EC-derived Cldn5+ EVs in triggering inflammation, offering a novel mechanism involved and presenting a possible therapeutic avenue for DR.

Direct Diazoarylation of [1.1.1]Propellane with Arenediazonium Salts: A Modular Assembly of Arylated Diazo Bicyclo[1.1.1]pentanes.

A mild and concise diazoarylation of [1.1.1]propellane is described, which provides a modular approach to arylated diazo bicyclopentanes (BCPs). This reaction proceeds smoothly under basic conditions without requiring other additives or catalysts. The substrate scope shows that various electron-withdrawing and electron-donating groups are tolerated, and the subsequent modifications provide a novel avenue for assembling arylamino-BCP analogs.

Estrogen-dependent gene regulation: Molecular basis of TIMP-1 as a sex-specific biomarker for acute lung injury.

Increased circulating tissue inhibitor of metalloproteinases-1 (TIMP-1) levels have been observed in patients with acute lung injury (ALI). However, the sex-specific regulation of TIMP-1 and the underlying molecular mechanisms have not been well elucidated. In this study, we found that plasma TIMP-1 levels were significantly higher in COVID-19 and H1N1 patients compared with those in healthy subjects (n = 25). TIMP-1 concentrations were significantly different between males and females in each disease group. Among female but not male patients, TIMP-1 levels significantly correlated with the PaO2/FiO2 ratio and hospital length of stay. Using the mouse model of ALI induced by the H1N1 virus, we found that TIMP-1 is strikingly induced in PDGFRα-positive cells in the murine lungs. Moreover, female mice showed a higher Timp-1 expression in the lungs on day 3 postinfection. Mechanistically, we observed that estrogen can upregulate TIMP-1 expression in lung fibroblasts, not epithelial cells. In addition, overexpression of estrogen receptor α (ERα) increased the TIMP-1 promoter activity. In summary, TIMP-1 is an estrogen-responsive gene, and its promoter activity is regulated by ERα. Circulating TIMP-1 may serve as a sex-specific marker, reflecting the severity and worst outcomes in female patients with SARS-CoV2- and IAV-related ALI.

Arsenic redox disequilibrium in geogenic contaminated groundwater: Bioenergetic insights from organic molecular characterization and gene-informed modeling.

Biotransformation of arsenic (As) influences its speciation and mobility, obscuring mechanistic comprehension on spatiotemporal variation of As concentration in geogenic contaminated groundwater. In particular, unresolved processes underlying As redox disequilibrium in comparison to major redox couples discourage practical efforts to rehabilitate the As-contaminated groundwater. Here, quantitative metagenomic sequencing and ultrahigh-resolution mass spectrometry (FT-ICR-MS) were jointly applied to reveal the links between vertical distribution of As metabolic gene assemblages and that of free energy density of dissolved organic matter (DOM) in As-contaminated groundwater of Datong Basin. Observed small excess of Gibbs free energy available by DOM relative to that required for As(V)-to-As(III) reduction exerts thermodynamic constraint on metabolism-mediated redox transformation of As. Accordingly, the vertical distribution of dissolved As(V)/As(III) ratio correlated significantly with that of ars+acr3 and arr encoding As(V) reduction and aio encoding As(III) oxidation in the moderately/strongly reducing groundwater. Further gene-informed biogeochemical modeling suggests that a net effect of these kinetics-restricted bidirectional metabolic pathways leads to co-preservation of As(V) and As(III) even at relatively high rates of ars+acr3 encoded As(V) reduction. This study therefore provides new insights into bioenergetic constraints on As hydrobiogeochemical behavior, with implications for other redox-sensitive contaminants in the groundwater systems.

Advances in artificial intelligence applications in the field of lung cancer.

Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.

Deep learning-aided respiratory motion compensation in PET/CT: addressing motion induced resolution loss, attenuation correction artifacts and PET-CT misalignment.

PURPOSE: Respiratory motion (RM) significantly impacts image quality in thoracoabdominal PET/CT imaging. This study introduces a unified data-driven respiratory motion correction (uRMC) method, utilizing deep learning neural networks, to solve all the major issues caused by RM, i.e., PET resolution loss, attenuation correction artifacts, and PET-CT misalignment. METHODS: In a retrospective study, 737 patients underwent [18F]FDG PET/CT scans using the uMI Panorama PET/CT scanner. Ninety-nine patients, who also had respiration monitoring device (VSM), formed the validation set. The remaining data of the 638 patients were used to train neural networks used in the uRMC. The uRMC primarily consists of three key components: (1) data-driven respiratory signal extraction, (2) attenuation map generation, and (3) PET-CT alignment. SUV metrics were calculated within 906 lesions for three approaches, i.e., data-driven uRMC (proposed), VSM-based uRMC, and OSEM without motion correction (NMC). RM magnitude of major organs were estimated. RESULTS: uRMC enhanced diagnostic capabilities by revealing previously undetected lesions, sharpening lesion contours, increasing SUV values, and improving PET-CT alignment. Compared to NMC, uRMC showed increases of 10% and 17% in SUVmax and SUVmean across 906 lesions. Sub-group analysis showed significant SUV increases in small and medium-sized lesions with uRMC. Minor differences were found between VSM-based and data-driven uRMC methods, with the SUVmax was found statistically marginal significant or insignificant between the two methods. The study observed varied motion amplitudes in major organs, typically ranging from 10 to 20 mm. CONCLUSION: A data-driven solution for respiratory motion in PET/CT has been developed, validated and evaluated. To the best of our knowledge, this is the first unified solution that compensates for the motion blur within PET, the attenuation mismatch artifacts caused by PET-CT misalignment, and the misalignment between PET and CT.

A Redox-Active Iron-Organic Framework Cathodes for Sustainable Magnesium Metal Batteries.

Rechargeable magnesium metal batteries (RMBs) have shown promising prospects in sustainable energy storage due to the high crustal abundance, safety, and potentially large specific capacity of magnesium. However, their development is constrained by the lack of effective cathode materials that can achieve high capacity and stable magnesium storage at a practically reasonable rate. Herein, we construct a three-dimensional (3D) iron(III)-dihydroxy-benzoquinone (Fe2(DHBQ)3) metal-organic framework (MOF) material with dual redox centers of Fe3+ cations and DHBQ2- anions for reversible storage of Mg2+ in RMBs. Spectroscopic analysis and density functional theory (DFT) calculations reveal the redox chemistry of both Fe3+ ions and carbonyls from DHBQ ligands during electrochemical processes. Benefiting from the rational structure, the Fe2(DHBQ)3∥Mg cells exhibit a high reversible capacity of 395.3 mAh/g, large energy density of 463.5 Wh/kg, and high power density of 2456.0 W/kg. Moreover, the high electronic conductivity (8.35 × 10-5 S/cm) and favorable diffusion path of Mg2+ in Fe2(DHBQ)3 endow the cells with exceptional cycling stability and rate capability with a long life of 5000 cycles at 2000 mA/g. The dual redox-active MOF demonstrates a category of advanced cathode materials for high-performance RMBs.

Photocatalyzed 1,3-Bromodifluoroallylation of [1.1.1]Propellane with α-Trifluoromethylalkenes and KBr Salts.

Herein we unveil a visible-light-driven transition-metal-free 1,3-bromodifluoroallylation of [1.1.1]propellane. This reactivity is harnessed through organophotocatalysis, providing practical synthetic pathways to 1-brominated-3-gem-difluoroallylic bicyclo[1.1.1]pentane derivatives, particularly derived from readily available α-trifluoromethylalkenes and inexpensive KBr salts utilized as precursors for bromine radicals. Mechanistic investigations reveal that bromide anions quench the excited state of the photocatalyst, leading to the formation of bromine radicals, which react in a strain-release radical addition process rather than hydrogen atom abstraction with [1.1.1]propellane.

Mechanochemical Activation of Aryl Diazonium Salts: Synthesis of Polycyclic (Hetero)Aromatics.

Although the synthesis of polycyclic (hetero)aromatics via the [4 + 2] benzannulation process has been thoroughly explored, the restricted availability of energy sources (including thermal, light, and electrical energy) mandates the utilization of substantial quantities of organic solvents, inevitably leading to environmental pollution, resource wastage, and low reaction efficiency. Herein, we report a new method for the synthesis of polycyclic (hetero)aromatics from diazonium salts and alkynes under ball-milling conditions. This mechanochemical approach requires only substoichiometric amounts of DMSO as a liquid-assisted grinding additive and furnishes the desired product in a short time.

Club Cell Secretory Protein-16 (CC16) as a Prognostic Biomarker for COVID-19 and H1N1 Viral Infections.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and H1N1 viruses are inflammatory lung pathogens that can lead to acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). ALI/ARDS are still life-threatening diseases in critically ill patients with 30-40% mortality in the last decade. Currently, there are no laboratory tests for the early diagnosis or prognosis of ALI/ARDS. Club cell secretory protein (CC16) has been investigated as a potential biomarker of lung epithelial damage in various lung diseases. In this study, we evaluated whether plasma CC16 reflects the severity of COVID-19 and H1N1 infections. The plasma CC16 levels showed no significant differences between H1N1 and COVID-19 groups (p = 0.09). Among all subjects, CC16 levels were significantly higher in non-survivors than in survivors (p = 0.001). Upon the area under the receiver operating characteristic (AUROC) analysis, CC16 had an acceptable value to distinguish survivors and non-survivors (p = 0.002). In the COVID-19 group, plasma CC16 levels moderately correlated with the Acute Physiology and Chronic Health Evaluation II (APACHE II) score (r = 0.374, p = 0.003) and Sequential Organ Failure Assessment (SOFA) score (r = 0.474, p < 0.001). In the H1N1 group, a positive correlation was observed between the CC16 levels and hospital length of stay (r = 0.311, p = 0.022). Among all the patients, weak correlations between plasma CC16 levels with the SOFA score (r = 0.328, p < 0.001) and hospital length of stay (r = 0.310, p < 0.001) were observed. Thus, circulating CC16 might reflect the severity of COVID-19 and H1N1 infections.

Role of circulating inflammatory protein in the development of diabetic renal complications: proteome-wide Mendelian randomization and colocalization analyses.

Background: Diabetes ranks among the most widespread diseases globally, with the kidneys being particularly susceptible to its vascular complications. The identification of proteins for pathogenesis and novel drug targets remains imperative. This study aims to investigate roles of circulating inflammatory proteins in diabetic renal complications. Methods: Data on the proteins were derived from a genome-wide protein quantitative trait locus (pQTL) study, while data on diabetic renal complications came from the FinnGen study. In this study, proteome-wide Mendelian randomization (MR) and colocalization analyses were used to assess the relationship between circulating inflammatory proteins and diabetic renal complications. Results: MR approach indicated that elevated levels of interleukin 12B (IL-12B) (OR 1.691, 95%CI 1.179-2.427, P=4.34×10-3) and LIF interleukin 6 family cytokine (LIF) (OR 1.349, 95%CI 1.010-1.801, P=4.23×10-2) increased the risk of type 1 diabetes (T1D) with renal complications, while higher levels of fibroblast growth factor 19 (FGF19) (OR 1.202, 95%CI 1.009-1.432, P=3.93×10-2), fibroblast growth factor 23 (FGF23) (OR 1.379, 95%CI 1.035-1.837, P=2.82×10-2), C-C motif chemokine ligand 7 (CCL7) (OR 1.385, 95%CI 1.111-1.725, P=3.76×10-3), and TNF superfamily member 14 (TNFSF14) (OR 1.244, 95%CI 1.066-1.451, P=5.63×10-3) indicated potential risk factors for type 2 diabetes (T2D) with renal complications. Colocalization analysis supported these findings, revealing that most identified proteins, except for DNER, likely share causal variants with diabetic renal complications. Conclusion: Our study established associations between specific circulating inflammatory proteins and the risk of diabetic renal complications, suggesting these proteins as targets for further investigation into the pathogenesis and potential therapeutic interventions for T1D and T2D with renal complications.

Value of multiparametric magnetic resonance imaging in distinguishing sinonasal lymphoma from sinonasal carcinoma: a case control study.

BACKGROUND: The study aimed to evaluate the diagnostic efficacy of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in distinguishing sinonasal lymphoma from sinonasal carcinoma. METHODS: Forty-two participants with histologically confirmed sinonasal lymphomas and fifty-two cases of sinonasal carcinoma underwent imaging with a 3.0T MRI scanner. DCE-MRI and DWI were conducted, and various parameters including type of time-intensity curve(TIC), time to peak, peak enhancement, peak contrast enhancement, washout rate, apparent diffusion coefficient (ADC), and relative ADC were measured. Binary logistic regression and receiver operating characteristic (ROC) curve analysis were employed to assess the diagnostic capability of individual and combined indices for differentiating nasal sinus lymphoma from nasal sinus carcinoma. RESULTS: Sinonasal lymphoma predominantly exhibited type II TIC(n = 20), whereas sinonasal carcinoma predominantly exhibited type III TIC(n = 23). Significant differences were observed in all parameters except washout ratio (p < 0.05), and ADC value emerged as the most reliable diagnostic tool in single parameter. Combined DCE-MRI parameters demonstrated superior diagnostic efficacy compared to individual parameters, with the highest efficiency (area under curve = 0.945) achieved when combining all parameters of DCE-MRI and DWI. CONCLUSIONS: Multiparametric evaluation involving contrast-enhanced dynamic MRI and DWI holds considerable diagnostic value in distinguishing sinonasal lymphoma from sinonasal carcinoma.

Identification of potential biomarkers for cerebral palsy and the development of prediction models.

Cerebral palsy (CP) is a prevalent motor disorder originating from early brain injury or malformation, with significant variability in its clinical presentation and etiology. Early diagnosis and personalized therapeutic interventions are hindered by the lack of reliable biomarkers. This study aims to identify potential biomarkers for cerebral palsy and develop predictive models to enhance early diagnosis and prognosis. We conducted a comprehensive bioinformatics analysis of gene expression profiles in muscle samples from CP patients to identify candidate biomarkers. Six key genes (CKMT2, TNNT2, MYH4, MYH1, GOT1, and LPL) were validated in an independent cohort, and potential biological pathways and molecular networks involved in CP pathogenesis were analyzed. The importance of processes such as functional regulation, energy metabolism, and cell signaling pathways in the muscles of CP patients was emphasized. Predictive models of muscle sample biomarkers related to CP were developed and visualized. Calibration curves and receiver operating characteristic analysis demonstrated that the predictive models exhibit high sensitivity and specificity in distinguishing individuals at risk of CP. The identified biomarkers and developed prediction models offer significant potential for early diagnosis and personalized management of CP. Future research should focus on validating these biomarkers in larger cohorts and integrating them into clinical practice to improve outcomes for individuals with CP.

Visible-Light-Mediated Ring-Opening Geminal Dibromination of Alkenes via Alkoxy Radicals Enabled by Electron Donor-Acceptor Complex.

An electron donor-acceptor complex was utilized to generate alkoxy radicals from alcohols under mild conditions using visible light. This approach was combined with a hydroxybromination process to achieve the deconstructive functionalization of alkenes, leading to the production of geminal dibromides. Mechanistic investigations indicated the intermediacy of hypervalent iodine (III) compounds.

The impact of diabetes mellitus on blood-tissue barrier regulation and vascular complications: Is the lung different from other organs?

Diabetes Mellitus presents a formidable challenge as one of the most prevalent and complex chronic diseases, exerting significant strain on both patients and the world economy. It is recognized as a common comorbidity among severely ill individuals, often leading to a myriad of micro- and macro-vascular complications. Despite extensive research dissecting the pathophysiology and molecular mechanisms underlying vascular complications of diabetes, relatively little attention has been paid to potential lung-related complications. This review aims to illuminate the impact of diabetes on prevalent respiratory diseases, including chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), tuberculosis (TB), pneumonia infections, and asthma, and compare the vascular complications with other vascular beds. Additionally, we explore the primary mechanistic pathways contributing to these complications, such as the expression modulation of blood-tissue-barrier proteins, resulting in increased paracellular and transcellular permeability, and compromised immune responses rendering diabetes patients more susceptible to infections. The activation of inflammatory pathways leading to cellular injury and hastening the onset of these respiratory complications is also discussed.

Machine-Learning-Based Interatomic Potentials for Group IIB to VIA Semiconductors: Toward a Universal Model.

Rapid advancements in machine-learning methods have led to the emergence of machine-learning-based interatomic potentials as a new cutting-edge tool for simulating large systems with ab initio accuracy. Still, the community awaits universal interatomic models that can be applied to a wide range of materials without tuning neural network parameters. We develop a unified deep-learning interatomic potential (the DPA-Semi model) for 19 semiconductors ranging from group IIB to VIA, including Si, Ge, SiC, BAs, BN, AlN, AlP, AlAs, InP, InAs, InSb, GaN, GaP, GaAs, CdTe, InTe, CdSe, ZnS, and CdS. In addition, independent deep potential models for each semiconductor are prepared for detailed comparison. The training data are obtained by performing density functional theory calculations with numerical atomic orbitals basis sets to reduce the computational costs. We systematically compare various properties of the solid and liquid phases of semiconductors between different machine-learning models. We conclude that the DPA-Semi model achieves GGA exchange-correlation functional quality accuracy and can be regarded as a pretrained model toward a universal model to study group IIB to VIA semiconductors.

Activation and modulation of the AGEs-RAGE axis: Implications for inflammatory pathologies and therapeutic interventions - A review.

Chronic inflammation is a common foundation for the development of many non-communicable diseases, particularly diabetes, atherosclerosis, and tumors. The activation of the axis involving Advanced Glycation End products (AGEs) and their receptor RAGE is a key promotive factor in the chronic inflammation process, influencing the pathological progression of these diseases. The accumulation of AGEs in the body results from an increase in glycation reactions and oxidative stress, especially pronounced in individuals with diabetes. By binding to RAGE, AGEs activate signaling pathways such as NF-κB, promoting the release of inflammatory factors, exacerbating cell damage and inflammation, and further advancing the formation of atherosclerotic plaques and tumor development. This review will delve into the molecular mechanisms by which the AGEs-RAGE axis activates chronic inflammation in the aforementioned diseases, as well as strategies to inhibit the AGEs-RAGE axis, aiming to slow or halt the progression of chronic inflammation and related diseases. This includes the development of AGEs inhibitors, RAGE antagonists, and interventions targeting upstream and downstream signaling pathways. Additionally, the early detection of AGEs levels and RAGE expression as biomarkers provides new avenues for the prevention and treatment of diabetes, atherosclerosis, and tumors.

A Facile Strategy for Constructing High-Performance Polymer Electrolytes via Anion Modification and Click Chemistry for Rechargeable Magnesium Batteries.

Polymer electrolytes play a crucial role in advancing rechargeable magnesium batteries (RMBs) owing to their exceptional characteristics, including high flexibility, superior interface compatibility, broad electrochemical stability window, and enhanced safety features. Despite these advantages, research in this domain remains nascent, plagued by single preparation approaches and challenges associated with the compatibility between polymer electrolytes and Mg metal anode. In this study, we present a novel synthesis strategy to fabricate a glycerol α,α'-diallyl ether-3,6-dioxa-1,8-octanedithiol-based composite gel polymer electrolyte supported by glass fiber substrate (GDT@GF CGPE) through anion modification and thiol-ene click chemistry polymerization. The developed route exhibits novelty and high efficiency, leading to the production of GDT@GF CGPEs featuring exceptional mechanical properties, heightened ionic conductivity, elevated Mg2+ transference number, and commendable compatibility with Mg anode. The assembled modified Mo6S8||GDT@GF||Mg cells exhibit outstanding performance across a wide temperature range and address critical safety concerns, showcasing the potential for applications under extreme conditions. Our innovative preparation strategy offers a promising avenue for the advancement of polymer electrolytes in high-performance rechargeable magnesium batteries, while also opens up possibilities for future large-scale applications and the development of flexible electronic devices.