Uridine-Modified Ruthenium(II) Complex as Lysosomal LIMP-2 Targeting Photodynamic Therapy Photosensitizer for the Treatment of Triple-Negative Breast Cancer.

Lysosome-targeted photodynamic therapy, which enhances reactive oxygen species (ROS)-responsive tumor cell death, has emerged as a promising strategy for cancer treatment. Herein, a uridine (dU)-modified Ru(II) complex (RdU) was synthesized by click chemistry. It was found that RdU exhibits impressive photo-induced inhibition against the growth of triple-negative breast cancer (TNBC) cells in normoxic and hypoxic microenvironments through ROS production. It was further revealed that RdU induces ferroptosis of MDA-MB-231 cells under light irradiation (650 nm, 300 mW/cm2). Additional experiments showed that RdU binds to lysosomal integral membrane protein 2 (LIMP-2), which was confirmed by the fact that RdU selectively localizes in the lysosomes of MDA-MB-231 cells and significantly augments the levels of LIMP-2. Molecular docking simulations and an isothermal titration calorimetry assay also showed that RdU has a high affinity to LIMP-2. Finally, in vivo studies in tumor-bearing (MDA-MB-231 cells) nude mice showed that RdU exerts promising photodynamic therapeutic effects on TNBC tumors. In summary, the uridine-modified Ru(II) complex has been developed as a potential LIMP-2 targeting agent for TNBC treatment through enhancing ROS production and promoting ferroptosis.

Vertical Cross-Alignments of 2D Semiconductors with Steered Internal Electric Field for Urea Electrooxidation via Balancing Intermediates Adsorption.

Single-component electrocatalysts generally lead to unbalanced adsorption of OH- and urea during urea oxidation reaction (UOR), thus obtaining low activity and selectivity especially when oxygen evolution reaction (OER) competes at high potentials (>1.5 V). Herein, a cross-alignment strategy of in situ vertically growing Ni(OH)2 nanosheets on 2D semiconductor g-C3N4 is reported to form a hetero-structured electrocatalyst. Various spectroscopy measurements including in situ experiments indicate the existence of enhanced internal electric field at the interfaces of vertical Ni(OH)2 and g-C3N4 nanosheets, favorable for balancing adsorption of reaction intermediates. This heterojunction electrocatalyst shows high-selectivity UOR compared to pure Ni(OH)2, even at high potentials (>1.5 V) and large current density. The computational results show the vertical heterojunction could steer the internal electric field to increase the adsorption of urea, thus efficiently avoiding poisoning of strongly adsorbed OH- on active sites. A membrane electrode assembly (MEA)-based electrolyzer with the heterojunction anode could operate at an industrial-level current density of 200 mA cm-2. This work paves an avenue for designing high-performance electrocatalysts by vertical cross-alignments of active components.

Induction of therapeutic immunity and cancer eradication through biofunctionalized liposome-like nanovesicles derived from irradiated-cancer cells.

Immunotherapy has revolutionized the treatment of cancer. However, its efficacy remains to be optimized. There are at least two major challenges in effectively eradicating cancer cells by immunotherapy. Firstly, cancer cells evade immune cell killing by down-regulating cell surface immune sensors. Secondly, immune cell dysfunction impairs their ability to execute anti-cancer functions. Radiotherapy, one of the cornerstones of cancer treatment, has the potential to enhance the immunogenicity of cancer cells and trigger an anti-tumor immune response. Inspired by this, we fabricate biofunctionalized liposome-like nanovesicles (BLNs) by exposing irradiated-cancer cells to ethanol, of which ethanol serves as a surfactant, inducing cancer cells pyroptosis-like cell death and facilitating nanovesicles shedding from cancer cell membrane. These BLNs are meticulously designed to disrupt both of the aforementioned mechanisms. On one hand, BLNs up-regulate the expression of calreticulin, an "eat me" signal on the surface of cancer cells, thus promoting macrophage phagocytosis of cancer cells. Additionally, BLNs are able to reprogram M2-like macrophages into an anti-cancer M1-like phenotype. Using a mouse model of malignant pleural effusion (MPE), an advanced-stage and immunotherapy-resistant cancer model, we demonstrate that BLNs significantly increase T cell infiltration and exhibit an ablative effect against MPE. When combined with PD-1 inhibitor (α-PD-1), we achieve a remarkable 63.6% cure rate (7 out of 11) among mice with MPE, while also inducing immunological memory effects. This work therefore introduces a unique strategy for overcoming immunotherapy resistance.

Mesoporous Single Atom-Cluster Fe-N/C Oxygen Evolution Electrocatalysts Synthesized with Bottlebrush Block Copolymer-Templated Rapid Thermal Annealing.

Current electrocatalysts for oxygen evolution reaction (OER) are either expensive (such as IrO2, RuO2) or/and exhibit high overpotential as well as sluggish kinetics. This article reports mesoporous earth-abundant iron (Fe)-nitrogen (N) doped carbon electrocatalysts with iron clusters and closely surrounding Fe-N4 active sites. Unique to this work is that the mechanically stable mesoporous carbon-matrix structure (79 nm in pore size) with well-dispersed nitrogen-coordinated Fe single atom-cluster is synthesized via rapid thermal annealing (RTA) within only minutes using a self-assembled bottlebrush block copolymer (BBCP) melamine-formaldehyde resin composite template. The resulting porous structure and domain size can be tuned with the degree of polymerization of the BBCP backbone, which increases the electrochemically active surface area and improves electron transfer and mass transport for an effective OER process. The optimized electrocatalyst shows a required potential of 1.48 V (versus RHE) to obtain the current density of 10 mA/cm2 in 1 M KOH aqueous electrolyte and a small Tafel slope of 55 mV/decade at a given overpotential of 250 mV, which is significantly lower than recently reported earth-abundant electrocatalysts. Importantly, the Fe single-atom nitrogen coordination environment facilitates the surface reconstruction into a highly active oxyhydroxide under OER conditions, as revealed by X-ray photoelectron spectroscopy and in situ Raman spectroscopy, while the atomic clusters boost the single atoms reactive sites to prevent demetalation during the OER process. Density functional theory (DFT) calculations support that the iron nitrogen environment and reconstructed oxyhydroxides are electrocatalytically active sites as the kinetics barrier is largely reduced. This work has opened a new avenue for simple, rapid synthesis of inexpensive, earth-abundant, tailorable, mechanically stable, mesoporous carbon-coordinated single-atom electrocatalysts that can be used for renewable energy production.

Three Copies of zbed1 Specific in Chromosome W Are Essential for Female-Biased Sexual Size Dimorphism in Cynoglossus semilaevis.

The sex chromosome, especially specific in one sex, generally determines sexual size dimorphism (SSD), a phenomenon with dimorphic sexual difference in the body size. For Cynoglossus semilaevis, a flatfish in China, although the importance of chromosome W and its specific gene zbed1 in female-biased SSD have been suggested, its family members and regulation information are still unknown. At present, three zbed1 copies gene were identified on chromosome W, with no gametologs. Phylogenetic analysis for the ZBED family revealed an existence of ZBED9 in the fish. Nine members were uncovered from C. semilaevis, clustering into three kinds, ZBED1, ZBED4 and ZBEDX, which is less than the eleven kinds of ZBED members in mammals. The predominant expression of zbed1 in the female brain and pituitary tissues was further verified by qPCR. Transcription factor c/ebpα could significantly enhance the transcriptional activity of zbed1 promoter, which is opposite to its effect on the male determinant factor-dmrt1. When zbed1 was interfered with, piwil1, esr2 and wnt7b were up-regulated, while cell-cycle-related genes, including cdk4 and ccng1, were down-regulated. Thus, zbed1 is involved in cell proliferation by regulating esr2, piwil1, cell cycle and the Wnt pathway. Further research on their interactions would be helpful to understand fish SSD.

Severe megaloblastic anemia in a patient with advanced lung adenocarcinoma during treatment with erlotinib: a case report and literature review.

BACKGROUND: Erlotinib is a first-generation, tyrosine kinase inhibitor of the epidermal growth factor receptor (EGFR-TKI) used for the treatment patients with NSCLC. Erlotinib is considered as a safe and effective treatment option, with generally good tolerance. Diarrhea and rash are the most common side effects, and more rare side effects appear in long-term real-world applications. Severe erlotinib related megaloblastic anemia is rare and remains unreported. This is the first case report of severe megaloblastic anemia in a patient with advanced lung adenocarcinoma with an EGFR L858R mutation treated with erlotinib. In this report, the clinical manifestations, diagnosis and treatment of erlotinib related severe megaloblastic anemia are described, and the possible pathogenesis and related treatment options are discussed. CASE DESCRIPTION: Herein, we present a 57- year-old non-smoking female diagnosed with metastatic lung adenocarcinoma harboring an EGFR L858R mutation, who had received erlotinib as the first-line therapy. After 44 weeks of treatment, the patient developed severe anemia. Anemia was manifested as megaloblastic anemia with elevated mean corpuscular volume and mean corpuscular hemoglobin. The total vitamin B12 level was below the detection limit of 50.00 pg /mL. Bone marrow smear suggested megaloblastic anemia. Her hematologic parameters were markedly recovered following the withdrawal of erlotinib and vitamin B12 supplement. As a result, the patient was diagnosed with erlotinib-associated megaloblastic anemia. CONCLUSIONS: This is the first case of severe megaloblastic anemia reported with erlotinib. Few of these hematologic adverse effects have been observed in studies on erlotinib, this case report highlights this possibility for long-term erlotinib administration. Close clinical and blood monitoring is recommended for patients receiving long-term TKI therapy.

Biodegradation of phenolic pollutants and bioaugmentation strategies: A review of current knowledge and future perspectives.

The widespread use of phenolic compounds renders their occurrence in various environmental matrices, posing ecological risks especially the endocrine disruption effects. Biodegradation-based techniques are efficient and cost-effective in degrading phenolic pollutants with less production of secondary pollution. This review focuses on phenol, 4-nonylphenol, 4-nitrophenol, bisphenol A and tetrabromobisphenol A as the representatives, and summarizes the current knowledge and future perspectives of their biodegradation and the enhancement strategy of bioaugmentation. Biodegradation and isolation of degrading microorganisms were mainly investigated under oxic conditions, where phenolic pollutants are typically hydroxylated to 4-hydroxybenzoate or hydroquinone prior to ring opening. Bioaugmentation efficiencies of phenolic pollutants significantly vary under different application conditions (e.g., increased degradation by 10-95% in soil and sediment). To optimize degradation of phenolic pollutants in different matrices, the factors that influence biodegradation capacity of microorganisms and performance of bioaugmentation are discussed. The use of immobilization strategy, indigenous degrading bacteria, and highly competent exogenous bacteria are proposed to facilitate the bioaugmentation process. Further studies are suggested to illustrate 1) biodegradation of phenolic pollutants under anoxic conditions, 2) application of microbial consortia with synergistic effects for phenolic pollutant degradation, and 3) assessment on the uncertain ecological risks associated with bioaugmentation, resulting from changes in degradation pathway of phenolic pollutants and alterations in structure and function of indigenous microbial community.

Facilitating effects of the synergy with zero-valent iron and peroxysulfate on the sludge anaerobic fermentation system: Combined biological enzyme, microbial community and fermentation mechanism assessment.

This study evaluated a synergetic waste activated sludge treatment strategy with environmentally friendly zero-valent iron nanoparticles (Fe0) and peroxysulfate. To verify the feasibility of the synergistic treatment, Fe0, peroxysulfate, and the mixture of peroxysulfate and Fe0 (synergy treatment) were added to different sludge fermentation systems. The study demonstrated that the synergy treatment fermentation system displayed remarkable hydrolysis performance with 435.50 mg COD/L of protein and 197.67 mg COD/L of polysaccharide, which increased 1.13-2.85 times (protein) and 1.12-1.49 times (polysaccharide) for other three fermentation system. Additionally, the synergy treatment fermentation system (754.52 mg COD/L) exhibited a well acidification performance which was 1.35-41.73 times for other systems (18.08-557.27 mg COD/L). The synergy treatment fermentation system had a facilitating effect on the activity of protease, dehydrogenase, and alkaline phosphatase, which guaranteed the transformation of organic matter. Results also indicated that Comamonas, Soehngenia, Pseudomonas, and Fusibacter were enriched in synergy treatment, which was beneficial to produce SCFAs. The activation of Fe0 on peroxysulfate promoting electron transfer, improving the active groups, and increasing the enrichment of functional microorganisms showed the advanced nature of synergy treatment. These results proved the feasibility of synergy treatment with Fe0 and peroxysulfate to enhance waste activated sludge anaerobic fermentation.

Synergistic Lewis and Brønsted Acid Sites Promote OH* Formation and Enhance Formate Selectivity: Towards High-efficiency Glycerol Valorization.

As a sustainable valorization route, electrochemical glycerol oxidation reaction (GOR) involves in formation of key OH* and selective adsorption/cleavage of C-C(O) intermediates with multi-step electron transfer, thus suffering from high potential and poor formate selectivity for most non-noble-metal-based electrocatalysts. So, it remains challenging to understand the structure-property relationship as well as construct synergistic sites to realize high-activity and high-selectivity GOR. Herein, we successfully achieve dual-high performance with low potentials and superior formate selectivity for GOR by forming synergistic Lewis and Brønsted acid sites in Ni-alloyed Co-based spinel. The optimized NiCo oxide solid-acid electrocatalyst exhibits low reaction potential (1.219 V@10 mA/cm2) and high formate selectivity (94.0 %) toward GOR. In situ electrochemical impedance spectroscopy and pH-dependence measurements show that the Lewis acid centers could accelerate OH* production, while the Brønsted acid centers are proved to facilitate high-selectivity formation of formate. Theoretical calculations reveal that NiCo alloyed oxide shows appropriate d-band center, thus balancing adsorption/desorption of C-O intermediates. This study provides new insights into rationally designing solid-acid electrocatalysts for biomass electro-upcycling.

Fate of sulfamethoxazole in wetland sediment under controlled redox conditions.

Redox condition is an important controlling factor for contaminant removal in constructed wetlands; however, the redox-sensitivity of antibiotic removal in wetland sediments under controlled conditions with specific electron acceptors remains unclear. Here, using a 14C radioactive tracer, we explored fate of sulfamethoxazole (SMX) in a wetland sediment slurry under oxic, nitrate-reducing, iron-reducing, and methanogenic conditions. In the sterile treatment, unlike the comparable SMX dissipation from the water phase under four redox conditions, non-extractable residues (NERs) of SMX was highest formed in the sediment under oxic condition, mainly in sequestered and ester/amide-linked forms. Microorganisms markedly promoted SMX transformation in the slurry. The dissipation rate of SMX and its transformation products (TPs) followed the order: oxic ≈ iron-reducing > methanogenic >> nitrate-reducing conditions, being consistent with the dynamics of microbial community in the sediment, where microbial diversity was greater and networks connectivity linking dominant bacteria to SMX transformation were more complex under oxic and iron-reducing conditions. Kinetic modeling indicated that the transformation trend of SMX and its TPs into the endpoint pool NERs depended on the redox conditions. Addition of wetland plant exudates and sediment dissolved organic matter at environmental concentrations affected neither the abiotic nor the biotic transformation of SMX. Overall, the iron-reducing condition was proven the most favorable and eco-friendly for SMX transformation, as it resulted in a high rate of SMX dissipation from water without an increase in toxicity and subsequent formation of significant stable NERs in sediment. Our study comprehensively revealed the abiotic and biotic transformation processes of SMX under controlled redox conditions and demonstrated iron-reducing condition allowing optimal removal of SMX in constructed wetlands.

A Highly Selective Implantable Electrochemical Fiber Sensor for Real-Time Monitoring of Blood Homovanillic Acid.

Homovanillic acid (HVA) is a major dopamine metabolite, and blood HVA is considered as central nervous system (CNS) dopamine biomarker, which reflects the progression of dopamine-associated CNS diseases and the behavioral response to therapeutic drugs. However, facing blood various active substances interference, particularly structurally similar catecholamines and their metabolites, real-time and accurate monitoring of blood HVA remains a challenge. Herein, a highly selective implantable electrochemical fiber sensor based on a molecularly imprinted polymer is reported to accurately monitor HVA in vivo. The sensor exhibits high selectivity, with a response intensity to HVA 12.6 times greater than that of catecholamines and their metabolites, achieving 97.8% accuracy in vivo. The sensor injected into the rat caudal vein tracked the real-time changes of blood HVA, which paralleled the brain dopamine fluctuations and indicated the behavioral response to dopamine increase. This study provides a universal design strategy for improving the selectivity of implantable electrochemical sensors.

Unveiling the Intrinsic Photophysics in Quasi-Two-Dimensional Perovskites.

The two-dimensional (2D) perovskites have drawn intensive attention due to their unique stability and outstanding optoelectronic properties. However, the debate surrounding the spatial phase distribution and band alignment among different 2D phases in the quasi-2D perovskite has created complexities in understanding the carrier dynamics, hindering material and device development. In this study, we employed highly sensitive transient absorption spectroscopy to investigate the carrier dynamics of (BA)2(MA)n-1PbnI3n+1 quasi-2D Ruddlesden-Popper perovskite thin films, nominally prepared as n = 4. We observed the carrier-density-dependent electron and hole transfer dynamics between the 2D and three-dimensional (3D) phases. Under a low carrier density within the linear response range, we successfully resolved three ultrafast processes of both electron and hole transfers, spanning from hundreds of femtoseconds to several picoseconds, tens to hundreds of picoseconds, and hundreds of picoseconds to several nanoseconds, which can be attributed to lateral-epitaxial, partial-epitaxial, and disordered-interface heterostructures between 2D and 3D phases. By considering the interplay among the phase structure, band alignment, and carrier dynamics, we have proposed material synthesis strategies aimed at enhancing the carrier transport. Our results not only provide deep insights into an accurate intrinsic photophysics of quasi-2D perovskites but also inspire advancements in the practical application of these materials.

Insight into the potentiality of nano zero-valent iron on enhancing the nitrite accumulation and phosphorus removal performance of endogenous partial denitrification systems.

Endogenous partial denitrification (EPD) has drawn a lot of interest due to its abundant nitrite (NO2--N) accumulation capacity. However, the poor phosphate (PO43--P) removal rate of EPD restricts its promotion and application. In this study, the potentiality of various nano zero-valent iron (nZVI) concentrations (0, 20, 40, and 80 mg/L) on NO2--N accumulation and PO43--P removal in EPD systems had been investigated. Results showed that nZVI improved NO2--N accumulation and PO43--P removal, with the greatest nitrate-to-nitrite transformation ratio (NTR) and PO43--P removal rate of 97.74 % and 64.76 % respectively at the optimum nZVI level (80 mg/L). Microbial community analysis also proved that nZVI had a remarkable influence on the microbial community of EPD. Candidatus_Competibacter was contribute to NO2--N accumulation which was enriched from 24.74 % to 40.02 %. The enrichment of Thauera, Rhodobacteraceae, Pseudomonas were contributed to PO43--P removal. The chemistry of nZVI not only compensated for the deficiency of biological PO43--P removal, but also enhanced NO2--N enrichment. Therefore, nZVI had the huge potentiality to improve the operational performance of the EPD system.

FBW7/GSK3ß mediated degradation of IGF2BP2 inhibits IGF2BP2-SLC7A5 positive feedback loop and radioresistance in lung cancer.

BACKGROUND: The development of radioresistance seriously hinders the efficacy of radiotherapy in lung cancer. However, the underlying mechanisms by which radioresistance occurs are still incompletely understood. The N6-Methyladenosine (m6A) modification of RNA is involved in cancer progression, but its role in lung cancer radioresistance remains elusive. This study aimed to identify m6A regulators involved in lung cancer radiosensitivity and further explore the underlying mechanisms to identify therapeutic targets to overcome lung cancer radioresistance. METHODS: Bioinformatic mining was used to identify the m6A regulator IGF2BP2 involved in lung cancer radiosensitivity. Transcriptome sequencing was used to explore the downstream factors. Clonogenic survival assays, neutral comet assays, Rad51 foci formation assays, and Annexin V/propidium iodide assays were used to determine the significance of FBW7/IGF2BP2/SLC7A5 axis in lung cancer radioresistance. Chromatin immunoprecipitation (ChIP)-qPCR analyses, RNA immunoprecipitation (RIP) and methylated RNA immunoprecipitation (MeRIP)-qPCR analyses, RNA pull-down analyses, co-immunoprecipitation analyses, and ubiquitination assays were used to determine the feedback loop between IGF2BP2 and SLC7A5 and the regulatory effect of FBW7/GSK3ß on IGF2BP2. Mice models and tissue microarrays were used to verify the effects in vivo. RESULTS: We identified IGF2BP2, an m6A "reader", that is overexpressed in lung cancer and facilitates radioresistance. We showed that inhibition of IGF2BP2 impairs radioresistance in lung cancer both in vitro and in vivo. Furthermore, we found that IGF2BP2 enhances the stability and translation of SLC7A5 mRNA through m6A modification, resulting in enhanced SLC7A5-mediated transport of methionine to produce S-adenosylmethionine. This feeds back upon the IGF2BP2 promoter region by further increasing the trimethyl modification at lysine 4 of histone H3 (H3K4me3) level to upregulate IGF2BP2 expression. We demonstrated that this positive feedback loop between IGF2BP2 and SLC7A5 promotes lung cancer radioresistance through the AKT/mTOR pathway. Moreover, we found that the ubiquitin ligase FBW7 functions with GSK3ß kinase to recognize and degrade IGF2BP2. CONCLUSIONS: Collectively, our study revealed that the m6A "reader" IGF2BP2 promotes lung cancer radioresistance by forming a positive feedback loop with SLC7A5, suggesting that IGF2BP2 may be a potential therapeutic target to control radioresistance in lung cancer.

AutoEdge-CCP: A novel approach for predicting cancer-associated circRNAs and drugs based on automated edge embedding.

The unique expression patterns of circRNAs linked to the advancement and prognosis of cancer underscore their considerable potential as valuable biomarkers. Repurposing existing drugs for new indications can significantly reduce the cost of cancer treatment. Computational prediction of circRNA-cancer and drug-cancer relationships is crucial for precise cancer therapy. However, prior computational methods fail to analyze the interaction between circRNAs, drugs, and cancer at the systematic level. It is essential to propose a method that uncover more valuable information for achieving cancer-centered multi-association prediction. In this paper, we present a novel computational method, AutoEdge-CCP, to unveil cancer-associated circRNAs and drugs. We abstract the complex relationships between circRNAs, drugs, and cancer into a multi-source heterogeneous network. In this network, each molecule is represented by two types information, one is the intrinsic attribute information of molecular features, and the other is the link information explicitly modeled by autoGNN, which searches information from both intra-layer and inter-layer of message passing neural network. The significant performance on multi-scenario applications and case studies establishes AutoEdge-CCP as a potent and promising association prediction tool.

Model-Heterogeneous Semi-Supervised Federated Learning for Medical Image Segmentation.

Medical image segmentation is crucial in clinical diagnosis, helping physicians identify and analyze medical conditions. However, this task is often accompanied by challenges like sensitive data, privacy concerns, and expensive annotations. Current research focuses on personalized collaborative training of medical segmentation systems, ignoring that obtaining segmentation annotations is time-consuming and laborious. Achieving a perfect balance between annotation cost and segmentation performance while ensuring local model personalization has become a valuable direction. Therefore, this study introduces a novel Model-Heterogeneous Semi-Supervised Federated (HSSF) Learning framework. It proposes Regularity Condensation and Regularity Fusion to transfer autonomously selective knowledge to ensure the personalization between sites. In addition, to efficiently utilize unlabeled data and reduce the annotation burden, it proposes a Self-Assessment (SA) module and a Reliable Pseudo-Label Generation (RPG) module. The SA module generates self-assessment confidence in real-time based on model performance, and the RPG module generates reliable pseudo-label based on SA confidence. We evaluate our model separately on the Skin Lesion and Polyp Lesion datasets. The results show that our model performs better than other methods characterized by heterogeneity. Moreover, it exhibits highly commendable performance even in homogeneous designs, most notably in region-based metrics. The full range of resources can be readily accessed through the designated repository located at HSSF(github.com) on the platform of GitHub.

Accelerating electrosynthesis of ammonia from nitrates using coupled NiO/Cu nanocomposites.

Herein, we report a nanocomposite electrocatalyst with coupled Cu and NiO, showing a high Faraday efficiency of 97% and excellent ammonia production rate (450 mg h-1 cm-2) for nitrate reduction. In situ UV-vis spectroscopic studies confirmed that the synergy between NiO and Cu could avoid NO2- enrichment and promote tandem nitrate reduction to ammonia synthesis.

A Durable and High-Voltage Mn-Graphite Dual-Ion Battery Using Mn-Based Hybrid Electrolytes.

Rechargeable Mn-metal batteries (MMBs) can attract considerable attention because Mn has the intrinsic merits including high energy density (976 mAh g-1 ), high air stability, and low toxicity. However, the application of Mn in rechargeable batteries is limited by the lack of proper cathodes for reversible Mn2+ intercalation/de-intercalation, thus leading to low working voltage (<1.8 V) and poor cycling stability (≤200 cycles). Herein, a high-voltage and durable MMB with graphite as the cathode is successfully constructed using a LiPF6 -Mn(TFSI)2 hybrid electrolyte, which shows a high discharge voltage of 2.34 V and long-term stability of up to 1000 cycles. Mn(TFSI)2 can reduce the plating/stripping overpotential of Mn ions, while LiPF6 can efficiently improve the conductivity of the electrolyte. Electrochemical in-situ characterization implies the dual-anions intercalation/de-intercalation at the cathode and Mn2+ plating/stripping reaction at the anode. Theoretical calculations unveil the top site of graphite is the energetically favorable for anions intercalation and TFSI- shows the low migration barrier. This work paves an avenue for designing high-performance rechargeable MMBs towards electricity storage.

Interface-Stabilized Fiber Sensor for Real-Time Monitoring of Amniotic Fluid During Pregnancy.

Diseases in pregnancy endanger millions of fetuses worldwide every year. The onset of these diseases can be early warned by the dynamic abnormalities of biochemicals in amniotic fluid, thus requiring real-time monitoring. However, when continuously penetrated by detection devices, the amnion is prone to loss of robustness and rupture, which is difficult to regenerate. Here, an interface-stabilized fiber sensor is presented for real-time monitoring of biochemical dynamics in amniotic fluid during pregnancy. The sensor is seamlessly integrated into the amnion through tissue adhesion, amniotic regeneration, and uniform stress distribution, posing no risk to the amniotic fluid environment. The sensor demonstrates a response performance of less than 0.3% fluctuation under complex dynamic conditions and an accuracy of more than 98% from the second to the third trimester. By applying it to early warning of diseases such as intrauterine hypoxia, intrauterine infection, and fetal growth restriction, fetal survival increases to 95% with timely intervention.

FedDP: Dual Personalization in Federated Medical Image Segmentation.

Personalized federated learning (PFL) addresses the data heterogeneity challenge faced by general federated learning (GFL). Rather than learning a single global model, with PFL a collection of models are adapted to the unique feature distribution of each site. However, current PFL methods rarely consider self-attention networks which can handle data heterogeneity by long-range dependency modeling and they do not utilize prediction inconsistencies in local models as an indicator of site uniqueness. In this paper, we propose FedDP, a novel fed erated learning scheme with d ual p ersonalization, which improves model personalization from both feature and prediction aspects to boost image segmentation results. We leverage long-range dependencies by designing a local query (LQ) that decouples the query embedding layer out of each local model, whose parameters are trained privately to better adapt to the respective feature distribution of the site. We then propose inconsistency-guided calibration (IGC), which exploits the inter-site prediction inconsistencies to accommodate the model learning concentration. By encouraging a model to penalize pixels with larger inconsistencies, we better tailor prediction-level patterns to each local site. Experimentally, we compare FedDP with the state-of-the-art PFL methods on two popular medical image segmentation tasks with different modalities, where our results consistently outperform others on both tasks. Our code and models are available at https://github.com/jcwang123/PFL-Seg-Trans.