Stabilizing Zn/electrolyte Interphasial Chemistry by a Sustained-Release Drug Inspired Indium-Chelated Resin Protective Layer for High-Areal-Capacity Zn//V2O5 Batteries.

For zinc-metal batteries, the instable chemistry at Zn/electrolyte interphasial region results in severe hydrogen evolution reaction (HER) and dendrite growth, significantly impairing Zn anode reversibility. Moreover, an often-overlooked aspect is this instability can be further exacerbated by the interaction with dissolved cathode species in full batteries. Here, inspired by sustained-release drug technology, an indium-chelated resin protective layer (Chelex-In), incorporating a sustained-release mechanism for indium, is developed on Zn surface, stabilizing the anode/electrolyte interphase to ensure reversible Zn plating/stripping performance throughout the entire lifespan of Zn//V2O5 batteries. The sustained-release indium onto Zn electrode promotes a persistent anticatalytic effect against HER and fosters uniform heterogeneous Zn nucleation. Meanwhile, on the electrolyte side, the residual resin matrix with immobilized iminodiacetates anions can also repel detrimental anions (SO4 2- and polyoxovanadate ions dissolved from V2O5 cathode) outside the electric double layer. This dual synergetic regulation on both electrode and electrolyte sides culminates a more stable interphasial environment, effectively enhancing Zn anode reversibility in practical high-areal-capacity full battery systems. Consequently, the bio-inspired Chelex-In protective layer enables an ultralong lifespan of Zn anode over 2800 h, which is also successfully demonstrated in ultrahigh areal capacity Zn//V2O5 full batteries (4.79 mAh cm-2).

Superhalide-Anion-Motivator Reforming-Enabled Bipolar Manipulation toward Longevous Energy-Type Zn||Chalcogen Batteries.

Neutrophilic superhalide-anion-triggered chalcogen conversion-based Zn batteries, despite latent high-energy merit, usually suffer from a short lifespan caused by dendrite growth and shuttle effect. Here, a superhalide-anion-motivator reforming strategy is initiated to simultaneously manipulate the anode interface and Se conversion intermediates, realizing a bipolar regulation toward longevous energy-type Zn batteries. With ZnF2 chaotropic additives, the original large-radii superhalide zincate anion species in ionic liquid (IL) electrolytes are split into small F-containing species, boosting the formation of robust solid electrolyte interphases (SEI) for Zn dendrite inhibition. Simultaneously, ion radius reduced multiple F-containing Se conversion intermediates form, enhancing the interion interaction of charged products to suppress the shuttle effect. Consequently, Zn||Se batteries deliver a ca. 20-fold prolonged lifespan (2000 cycles) at 1 A g-1 and high energy/power density of 416.7 Wh kgSe-1/1.89 kW kgSe-1, outperforming those in F-free counterparts. Pouch cells with distinct plateaus and durable cyclability further substantiate the practicality of this design.

NPS-2143 inhibit glioma progression by suppressing autophagy through mediating AKT-mTOR pathway.

Gliomas are the most common tumours in the central nervous system. In the present study, we aimed to find a promising anti-glioma compound and investigate the underlying molecular mechanism. Glioma cells were subjected to the 50 candidate compounds at a final concentration of 10 µM for 72 h, and CCK-8 was used to evaluate their cytotoxicity. NPS-2143, an antagonist of calcium-sensing receptor (CASR), was selected for further study due to its potent cytotoxicity to glioma cells. Our results showed that NPS-2143 could inhibit the proliferation of glioma cells and induce G1 phase cell cycle arrest. Meanwhile, NPS-2143 could induce glioma cell apoptosis by increasing the caspase-3/6/9 activity. NPS-2143 impaired the immigration and invasion ability of glioma cells by regulating the epithelial-mesenchymal transition process. Mechanically, NPS-2143 could inhibit autophagy by mediating the AKT-mTOR pathway. Bioinformatic analysis showed that the prognosis of glioma patients with low expression of CASR mRNA was better than those with high expression of CASR mRNA. Gene set enrichment analysis showed that CASR was associated with cell adhesion molecules and lysosomes in glioma. The nude mice xenograft model showed NPS-2143 could suppress glioma growth in vivo. In conclusion, NPS-2143 can suppress the glioma progression by inhibiting autophagy.

Daurisoline suppress glioma progression by inhibiting autophagy through PI3K/AKT/mTOR pathway and increases TMZ sensitivity.

Glioma is one of the most common primary malignant tumors of the central nervous system. Temozolomide (TMZ) is the only effective chemotherapeutic agent, but it easily develops resistance and has unsatisfactory efficacy. Consequently, there is an urgent need to develop safe and effective compounds for glioma treatment. The cytotoxicity of 30 candidate compounds to glioma cells was detected by the CCK-8 assay. Daurisoline (DAS) was selected for further investigation due to its potent anti-glioma effects. Our study revealed that DAS induced glioma cell apoptosis through increasing caspase-3/6/9 activity. DAS significantly inhibited the proliferation of glioma cells by inducing G1-phase cell cycle arrest. Meanwhile, DAS remarkably suppressed the migration and invasion of glioma cells by regulating epithelial-mesenchymal transition. Mechanistically, our results revealed that DAS impaired the autophagic flux of glioma cells at a late stage by mediating the PI3K/AKT/mTOR pathway. DAS could inhibit TMZ-induced autophagy and then significantly promote TMZ chemosensitivity. Nude mice xenograft model revealed that DAS could restrain glioma proliferation and promote TMZ chemosensitivity. Thus, DAS is a potential anti-glioma drug that can improve glioma sensitivity to TMZ and provide a new therapeutic strategy for glioma in chemoresistance.

A fusion model integrating magnetic resonance imaging radiomics and deep learning features for predicting alpha-thalassemia X-linked intellectual disability mutation status in isocitrate dehydrogenase-mutant high-grade astrocytoma: a multicenter study.

Background: The mutational status of alpha-thalassemia X-linked intellectual disability (ATRX) is an important indicator for the treatment and prognosis of high-grade gliomas, but reliable ATRX testing currently requires invasive procedures. The objective of this study was to develop a clinical trait-imaging fusion model that combines preoperative magnetic resonance imaging (MRI) radiomics and deep learning (DL) features with clinical variables to predict ATRX status in isocitrate dehydrogenase (IDH)-mutant high-grade astrocytoma. Methods: A total of 234 patients with IDH-mutant high-grade astrocytoma (120 ATRX mutant type, 114 ATRX wild type) from 3 centers were retrospectively analyzed. Radiomics and DL features from different regions (edema, tumor, and the overall lesion) were extracted to construct multiple imaging models by combining different features in different regions for predicting ATRX status. An optimal imaging model was then selected, and its features and linear coefficients were used to calculate an imaging score. Finally, a fusion model was developed by combining the imaging score and clinical variables. The performance and application value of the fusion model were evaluated through the comparison of receiver operating characteristic curves, the construction of a nomogram, calibration curves, decision curves, and clinical application curves. Results: The overall hybrid model constructed with radiomics and DL features from the overall lesion was identified as the optimal imaging model. The fusion model showed the best prediction performance with an area under curve of 0.969 in the training set, 0.956 in the validation set, and 0.949 in the test set as compared to the optimal imaging model (0.966, 0.916, and 0.936, respectively) and clinical model (0.677, 0.641, 0.772, respectively). Conclusions: The clinical trait-imaging fusion model based on preoperative MRI could effectively predict the ATRX mutation status of individuals with IDH-mutant high-grade astrocytoma and has the potential to help patients through the development of a more effective treatment strategy before treatment.

Dynamically Ion-Coordinated Bipolar Organodichalcogenide Cathodes Enabling High-Energy and Durable Aqueous Zn Batteries.

Bipolar organic cathode materials (OCMs) implementing cation/anion storage mechanisms are promising for high-energy aqueous Zn batteries (AZBs). However, conventional organic functional group active sites in OCMs usually fail to sufficiently unlock the high-voltage/capacity merits. Herein, we initially report dynamically ion-coordinated bipolar OCMs as cathodes with chalcogen active sites to solve this issue. Unlike conventional organic functional groups, chalcogens bonded with conjugated group undergo multielectron-involved positive-valence oxidation and negative-valence reduction, affording higher redox potentials and reversible capacities. With phenyl diselenide (PhSe-SePh, PDSe) as a proof of concept, it exhibits a conversion pathway from (PhSe)- to (PhSe-SePh)0 and then to (PhSe)+ as unveiled by characterization and theoretical simulation, where the diselenide bonds are periodically broken and healed, dynamically coordinating with ions (Zn2+ and OTF-). When confined into ordered mesoporous carbon (CMK-3), the dissolution of PDSe intermediates is greatly inhibited to obtain an ultralong lifespan without voltage/capacity compromise. The PDSe/CMK-3 || Zn batteries display high reversibility capacity (621.4 mAh gPDSe -1), distinct discharge plateau (up to 1.4 V), high energy density (578.3 Wh kgPDSe -1), and ultralong lifespan (12 000 cycles) at 10 A g-1, far outperforming conventional bipolar OCMs. This work sheds new light on conversion-type active site engineering for high-voltage/capacity bipolar OCMs towards high-energy AZBs.

A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma.

OBJECTIVES: To develop a high-accuracy MRI-based deep learning method for predicting cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion status in isocitrate dehydrogenase (IDH)-mutant astrocytoma. METHODS: Multiparametric brain MRI data and corresponding genomic information of 234 subjects (111 positives for CDKN2A/B homozygous deletion and 123 negatives for CDKN2A/B homozygous deletion) were obtained from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) respectively. Two independent multi-sequence networks (ResFN-Net and FN-Net) are built on the basis of ResNet and ConvNeXt network combined with attention mechanism to classify CDKN2A/B homozygous deletion status using MR images including contrast-enhanced T1-weighted imaging (CE-T1WI) and T2-weighted imaging (T2WI). The performance of the network is summarized by three-way cross-validation; ROC analysis is also performed. RESULTS: The average cross-validation accuracy (ACC) of ResFN-Net is 0.813. The average cross-validation area under curve (AUC) of ResFN-Net is 0.8804. The average cross-validation ACC and AUC of FN-Net is 0.9236 and 0.9704, respectively. Comparing all sequence combinations of the two networks (ResFN-Net and FN-Net), the sequence combination of CE-T1WI and T2WI performed the best, and the ACC and AUC were 0.8244, 0.8975 and 0.8971, 0.9574, respectively. CONCLUSIONS: The FN-Net deep learning networks based on ConvNeXt network achieved promising performance for predicting CDKN2A/B homozygous deletion status of IDH-mutant astrocytoma. CLINICAL RELEVANCE STATEMENT: A novel deep learning network (FN-Net) based on preoperative MRI was developed to predict the CDKN2A/B homozygous deletion status. This network has the potential to be a practical tool for the noninvasive characterization of CDKN2A/B in glioma to support personalized classification and treatment planning. KEY POINTS: • CDKN2A/B homozygous deletion status is an important marker for glioma grading and prognosis. • An MRI-based deep learning approach was developed to predict CDKN2A/B homozygous deletion status. • The predictive performance based on ConvNeXt network was better than that of ResNet network.

Preoperative Discrimination of CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytoma: A Deep Learning-Based Radiomics Model Using MRI.

BACKGROUND: Cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion has been verified as an independent and critical biomarker of negative prognosis and short survival in isocitrate dehydrogenase (IDH)-mutant astrocytoma. Therefore, noninvasive and accurate discrimination of CDKN2A/B homozygous deletion status is essential for the clinical management of IDH-mutant astrocytoma patients. PURPOSE: To develop a noninvasive, robust preoperative model based on MR image features for discriminating CDKN2A/B homozygous deletion status of IDH-mutant astrocytoma. STUDY TYPE: Retrospective. POPULATION: Two hundred fifty-one patients: 107 patients with CDKN2A/B homozygous deletion and 144 patients without CDKN2A/B homozygous deletion. FIELD STRENGTH/SEQUENCE: 3.0 T/1.5 T: Contrast-enhanced T1-weighted spin-echo inversion recovery sequence (CE-T1WI) and T2-weighted fluid-attenuation spin-echo inversion recovery sequence (T2FLAIR). ASSESSMENT: A total of 1106 radiomics and 1000 deep learning features extracted from CE-T1WI and T2FLAIR were used to develop models to discriminate the CDKN2A/B homozygous deletion status. Radiomics models, deep learning-based radiomics (DLR) models and the final integrated model combining radiomics features with deep learning features were developed and compared their preoperative discrimination performance. STATISTICAL TESTING: Pearson chi-square test and Mann Whitney U test were used for assessing the statistical differences in patients' clinical characteristics. The Delong test compared the statistical differences of receiver operating characteristic (ROC) curves and area under the curve (AUC) of different models. The significance threshold is P < 0.05. RESULTS: The final combined model (training AUC = 0.966; validation AUC = 0.935; test group: AUC = 0.943) outperformed the optimal models based on only radiomics or DLR features (training: AUC = 0.916 and 0.952; validation: AUC = 0.886 and 0.912; test group: AUC = 0.862 and 0.902). DATA CONCLUSION: Whether based on a single sequence or a combination of two sequences, radiomics and DLR models have achieved promising performance in assessing CDKN2A/B homozygous deletion status. However, the final model combining both deep learning and radiomics features from CE-T1WI and T2FLAIR outperformed the optimal radiomics or DLR model. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Hetero-Solvation-Diluted Strongly-Coordinated Zn2+ -Cosolvent Pairs Downshifting Zn Electrode Potential for High-Voltage Hybrid Batteries.

Mild aqueous Zn batteries (AZBs) generally suffer a low-voltage/energy dilemma, which compromises their competitiveness for large-scale energy storage. Pushing Zn anode potential downshift is an admissible yet underappreciated approach for high-voltage/energy AZBs. Herein, with a mild hybrid electrolyte containing in situ-derived diluted strongly-coordinated Zn2+ -cosolvent pairs, a considerable Zn anode potential downshift is initially achieved for high-voltage Zn-based hybrid batteries. The chosen butylpyridine cosolvent not only strongly coordinates Zn2+ ions but also acts as a hydrogen-bond end-capping agent to inhibit hydrogen evolution reaction (HER). The electrolyte environment with hetero-solvation-diluted strongly-coordinated Zn2+ -cosolvent pairs remarkably lowers Zn2+ activity, responsible for the Zn electrode potential downshift (-0.330 V vs Zn), confirming to modified Nernst law (ΔE = R T n F $\frac{{RT}}{{nF}}$ ln[a(Zn2 + )/a(coordinated solvent)]). With the diluted Zn2+ -containing hybrid electrolyte, the Zn//Zn symmetric cell in the hybrid electrolyte shows a long lifespan over 1270 h at a stripping/plating capacity of 0.4 mA h cm-2 . Compared with in common hybrid electrolytes, the as-assembled Zn-MnO2 hybrid battery delivers a ca. 0.278 V enhanced voltage plateau (1.57 V) and a long-term cyclability of over 736 cycles. This work opens a new avenue toward Zn anode potential downshift for high-voltage AZBs, which can extend to other mild metal batteries.

Crowding Effect-Induced Zinc-Enriched/Water-Lean Polymer Interfacial Layer Toward Practical Zn-Iodine Batteries.

Although the meticulous design of functional diversity within the polymer interfacial layer holds paramount significance in mitigating the challenges associated with hydrogen evolution reactions and dendrite growth in zinc anodes, this pursuit remains a formidable task. Here, a large-scale producible zinc-enriched/water-lean polymer interfacial layer, derived from carboxymethyl chitosan (CCS), is constructed on zinc anodes by integration of electrodeposition and a targeted complexation strategy for highly reversible Zn plating/stripping chemistry. Zinc ions-induced crowding effect between CCS skeleton creates a strong hydrogen bonding environment and squeezes the moving space for water/anion counterparts, therefore greatly reducing the number of active water molecules and alleviating cathodic I3- attack. Moreover, the as-constructed Zn2+-enriched layer substantially facilitate rapid Zn2+ migration through the NH2-Zn2+-NH2 binding/dissociation mode of CCS molecule chain. Consequently, the large-format Zn symmetry cell (9 cm2) with a Zn-CCS electrode demonstrates excellent cycling stability over 1100 h without bulging. When coupled with an I2 cathode, the assembled Zn-I2 multilayer pouch cell displays an exceptionally high capacity of 140 mAh and superior long-term cycle performance of 400 cycles. This work provides a universal strategy to prepare large-scale production and high-performance polymer crowding layer for metal anode-based battery, analogous outcomes were veritably observed on other metals (Al, Cu, Sn).

A compressible porous superhydrophobic material constructed by a multi-template high internal phase emulsion method for oil-water separation.

Superhydrophobic porous materials exhibit remarkable stability and exceptional efficacy in combating marine oil spills and containing oily water discharges. This work employed the multi-template high internal phase emulsion method to fabricate a multi-template porous superhydrophobic foam (MTPSF). The materials were characterized through SEM, IR spectroscopy, contact angle measurement, and an electronic universal testing machine. Moreover, the materials' oil-water separation capability, reusability, and compressibility were thoroughly evaluated. The obtained results demonstrate that the material displays a water contact angle of 143° and an oil contact angle of approximately 0°, thus exhibiting superhydrophobic and superoleophilic properties. Consequently, it effectively facilitates the separation of oil slicks and heavy oil underwater. Furthermore, the MTPSF conforms to the second kinetic and Webber-Morris models concerning the oil absorption process. MTPSF exhibits an outstanding oil absorption capacity, ranging from 39.40 to 102.32 g g-1, while showcasing reliable reusability, high recovery efficiency, and excellent compressibility of up to 55%. The above exceptional attributes render the MTPSF highly suitable for oil-water separation applications.

Lithium Bis(oxalate)borate Additive for Self-repairing Zincophilic Solid Electrolyte Interphases towards Ultrahigh-rate and Ultra-stable Zinc Anodes.

The artificial solid electrolyte interphase (SEI) plays a pivotal role in Zn anode stabilization but its long-term effectiveness at high rates is still challenged. Herein, to achieve superior long-life and high-rate Zn anode, an exquisite electrolyte additive, lithium bis(oxalate)borate (LiBOB), is proposed to in situ derive a highly Zn2+ -conductive SEI and to dynamically patrol its cycling-initiated defects. Profiting from the as-constructed real-time, automatic SEI repairing mechanism, the Zn anode can be cycled with distinct reversibility over 1800 h at an ultrahigh current density of 50 mA cm-2 , presenting a record-high cumulative capacity up to 45 Ah cm-2 . The superiority of the formulated electrolyte is further demonstrated in the Zn||MnO2 and Zn||NaV3 O8 full batteries, even when tested under harsh conditions (limited Zn supply (N/P≈3), 2500 cycles). This work brings inspiration for developing fast-charging Zn batteries toward grid-scale storage of renewable energy sources.

A B- and F-enriched buffering interphase enables a high-rate and high-stability SiOx/C anode.

A facile, universal surface engineering strategy is proposed to address the volume expansion and slow kinetic issues encountered by SiOx/C anodes. A B-/F-enriched buffering interphase is introduced onto SiOx/C by thermal treatment of pre-adsorbed lithium salts at 400 °C. The as-prepared anode integrates both high-rate performance and long-term cycling durability.

Tumor-secreted lactate contributes to an immunosuppressive microenvironment and affects CD8 T-cell infiltration in glioblastoma.

Introduction: Glioblastoma is a malignant brain tumor with poor prognosis. Lactate is the main product of tumor cells, and its secretion may relate to immunocytes' activation. However, its role in glioblastoma is poorly understood. Methods: This work performed bulk RNA-seq analysis and single cell RNA-seq analysis to explore the role of lactate in glioblastoma progression. Over 1400 glioblastoma samples were grouped into different clusters according to their expression and the results were validated with our own data, the xiangya cohort. Immunocytes infiltration analysis, immunogram and the map of immune checkpoint genes' expression were applied to analyze the potential connection between the lactate level with tumor immune microenvironment. Furthermore, machine learning algorithms and cell-cell interaction algorithm were introduced to reveal the connection of tumor cells with immunocytes. By co-culturing CD8 T cells with tumor cells, and performing immunohistochemistry on Xiangya cohort samples further validated results from previous analysis. Discussion: In this work, lactate is proved that contributes to glioblastoma immune suppressive microenvironment. High level of lactate in tumor microenvironment can affect CD8 T cells' migration and infiltration ratio in glioblastoma. To step further, potential compounds that targets to samples from different groups were also predicted for future exploration.

Hydrated Eutectic Electrolytes Stabilizing Quasi-Underpotential Mg Plating/Stripping for High-Voltage Mg Batteries.

Aqueous rechargeable Mg batteries (ARMBs) usually fail from severe anode passivation, alternatively, executing quasi-underpotential Mg plating/stripping chemistry (UPMC) on a proper heterogeneous metal substrate is a crucial remedy. Herein, a stable UPMC on Zn substrate is initially achieved in new hydrated eutectic electrolytes (HEEs), delivering an ultralow UPMC overpotential and high energy/voltage plateau of ARMBs. The unique eutectic property remarkably expands the lower limit of electrochemical stability window (ESW) of HEEs and undermines the competition between hydrogen evolution/corrosion reactions and UPMC, enabling a reversible UPMC. The UPMC is carefully revealed by multiple characterizations, which shows a low overpotential of 50 mV at 0.1 mA cm-2 over 550 h. With sulfonic acid-doped polyaniline (SPANI) cathodes, UPMC-based full cells show high energy/power densities of 168.6 Wh kg-1 /2.1 kWh kg-1 and voltage plateau of 1.3 V, far overwhelming conventional aqueous systems.

Multicenter clinical radiomics-integrated model based on [18F]FDG PET and multi-modal MRI predict ATRX mutation status in IDH-mutant lower-grade gliomas.

OBJECTIVES: To develop a clinical radiomics-integrated model based on 18 F-fluorodeoxyglucose positron emission tomography ([18F]FDG PET) and multi-modal MRI for predicting alpha thalassemia/mental retardation X-linked (ATRX) mutation status of IDH-mutant lower-grade gliomas (LGGs). METHODS: One hundred and two patients (47 ATRX mutant-type, 55 ATRX wild-type) diagnosed with IDH-mutant LGGs (CNS WHO grades 1 and 2) were retrospectively enrolled. A total of 5540 radiomics features were extracted from structural MR (sMR) images (contrast-enhanced T1-weighted imaging, CE-T1WI; T2-weighted imaging, and T2WI), functional MR (fMR) images (apparent diffusion coefficient, ADC; cerebral blood volume, CBV), and metabolic PET images ([18F]FDG PET). The random forest algorithm was used to establish a clinical radiomics-integrated model, integrating the optimal multi-modal radiomics model with three clinical parameters. The predictive effectiveness of the models was evaluated by receiver operating characteristic (ROC) and decision curve analysis (DCA). RESULTS: The optimal multi-modal model incorporated sMR (CE-T1WI), fMR (ADC), and metabolic ([18F]FDG) images ([18F]FDG PET+ADC+ CE-T1WI) with the area under curves (AUCs) in the training and test groups of 0.971 and 0.962, respectively. The clinical radiomics-integrated model, incorporating [18F]FDG PET+ADC+CE-T1WI, three clinical parameters (KPS, SFSD, and ATGR), showed the best predictive effectiveness in the training and test groups (0.987 and 0.975, respectively). CONCLUSIONS: The clinical radiomics-integrated model with metabolic, structural, and functional information based on [18F]FDG PET and multi-modal MRI achieved promising performance for predicting the ATRX mutation status of IDH-mutant LGGs. KEY POINTS: • The clinical radiomics-integrated model based on [18F]FDG PET and multi-modal MRI achieved promising performance for predicting ATRX mutation status in LGGs. • The study investigated the value of multicenter clinical radiomics-integrated model based on [18F]FDG PET and multi-modal MRI in LGGs regarding ATRX mutation status prediction. • The integrated model provided structural, functional, and metabolic information simultaneously and demonstrated with satisfactory calibration and discrimination in the training and test groups (0.987 and 0.975, respectively).

Manipulating OH- -Mediated Anode-Cathode Cross-Communication Toward Long-Life Aqueous Zinc-Vanadium Batteries.

The anode-cathode interplay is an important but rarely considered factor that initiates the degradation of aqueous zinc ion batteries (AZIBs). Herein, to address the limited cyclability issue of V-based AZIBs, Al2 (SO4 )3 is proposed as decent electrolyte additive to manipulate OH- -mediated cross-communication between Zn anode and NaV3 O8 ⋅ 1.5H2 O (NVO) cathode. The hydrolysis of Al3+ creates a pH≈0.9 strong acidic environment, which unexpectedly prolongs the anode lifespan from 200 to 1000 h. Such impressive improvement is assigned to the alleviation of interfacial OH- accumulation by Al3+ adsorption and solid electrolyte interphase formation. Accordingly, the strongly acidified electrolyte, associated with the sedated crossover of anodic OH- toward NVO, remarkably mitigate its undesired dissolution and phase transition. The interrupted OH- -mediated communication between the two electrodes endows Zn||NVO batteries with superb cycling stability, at both low and high scan rates.

A Pan-Cancer Analysis Reveals CLEC5A as a Biomarker for Cancer Immunity and Prognosis.

Background: CLEC5A is a member of the C-type lectin superfamily. It can activate macrophages and lead to a series of immune-inflammation reactions. Previous studies reveal the role of CLEC5A in infection and inflammation diseases. Method: We acquire and analyze data from The Cancer Genome Atlas (TCGA) database, Genotype-Tissue Expression (GTEx) database, and other comprehensive databases via GSCALite, cBioPortal, and TIMER 2.0 platforms or software. Single-cell sequencing analysis was performed for quantifying the tumor microenvironment of several types of cancers. Results: CLEC5A is differentially expressed in a few cancer types, of which overexpression accompanies low overall survival of patients. DNA methylation mainly negatively correlates with CLEC5A expression. Moreover, CLEC5A is positively related to immune infiltration, including macrophages, cancer-associated fibroblasts (CAFs), and regulatory T cells (Tregs). Immune checkpoint genes are significantly associated with CLEC5A expression in diverse cancers. In addition, CLEC5A expression correlates with mismatch repair (MMR) in several cancers. Tumor mutation burden (TMB), microsatellite instability (MSI), and neoantigens show a positive association with CLEC5A expression in several cancers. Furthermore, CLEC5A in cancer correlates with signal transduction, the immune system, EMT, and apoptosis process. The drug sensitivity analysis screens out potential therapeutic agents associated with CLEC5A expression, including FR-180204, Tivozanib, OSI-930, Linifanib, AC220, VNLG/124, Bexarotene, omacetaxine mepesuccinate, narciclasine, leptomycin B, PHA-793887, LRRK2-IN-1, and CR-1-31B. Conclusion: CLEC5A overexpresses in multiple cancers in contrast to normal tissues, and high CLEC5A expression predicts poor prognosis of patients and immune infiltration. CLEC5A is a potential prognostic biomarker of diverse cancers and a target for anti-tumor therapy.

HMGB1 Upregulates RAGE to Trigger the Expression of Inflammatory Factors in the Lung Tissue in a Hypoxic Pulmonary Hypertension Rat Model.

Hypoxic pulmonary hypertension (HPH), a form of pulmonary hypertension (PH) caused by hypoxia, could cause serious complications and has a high mortality rate, and no clinically effective treatments are currently available. In this study, we established an HPH preclinical model in rats by simulating clinicopathological indicators of the disease. Our results showed that high mobility group box-1 protein (HMGB1) aggravated the clinical symptoms of HPH. We aimed at establishing protocols and ideas for the clinical treatment of HPH by identifying downstream HMGB1 binding receptors. Our investigation showed that continuous hypoxia could cause significant lung injury in rats. ELISA and western blotting experiments revealed that HPH induces inflammation in the lung tissue and increases the expression of a hypoxia-inducible factor. Testing of lung tissue proteins in vivo and in human pulmonary artery endothelial cells in vitro revealed that the HMGB1-mediated increase in the receptor for advanced glycation end products (RAGE) expression promoted inflammation. In summary, we successfully established an HPH rat model providing a new model for preclinical HPH research and elucidated the role of HMGB1 in HPH. Furthermore, we describe that HMGB1 induced inflammation in the HPH model via RAGE, causing severe lung dysfunction. This study could potentially provide novel ideas and methods for the clinical treatment of HPH.

MiR-223-3p alleviates trigeminal neuropathic pain in the male mouse by targeting MKNK2 and MAPK/ERK signaling.

BACKGROUND: Trigeminal neuralgia (TN) is a neuropathic pain that occurs in branches of the trigeminal nerve. MicroRNAs (miRNAs) have been considered key mediators of neuropathic pain. This study was aimed to elucidate the pathophysiological function and mechanisms of miR-223-3p in mouse models of TN. METHODS: Infraorbital nerve chronic constriction injury (CCI-ION) was applied in male C57BL/6J mice to establish mouse models of TN. Pain responses were assessed utilizing Von Frey method. The expression of miR-223-3p, MKNK2, and MAPK/ERK pathway protein in trigeminal ganglions (TGs) of CCI-ION mice was measured using RT-qPCR and Western blotting. The concentrations of inflammatory cytokines were evaluated using Western blotting. The relationship between miR-223-3p and MKNK2 was tested by a luciferase reporter assay. RESULTS: We found that miR-223-3p was downregulated, while MKNK2 was upregulated in TGs of CCI-ION mice. MiR-223-3p overexpression by an intracerebroventricular injection of Lv-miR-223-3p attenuated trigeminal neuropathic pain in CCI-ION mice, as well as reduced the protein levels of pro-inflammatory cytokines in TGs of CCI-ION mice. MKNK2 was verified to be targeted by miR-223-3p. Additionally, miR-223-3p overexpression decreased the phosphorylation levels of ERK1/2, JNK, and p38 protein in TGs of CCI-ION mice to inhibit MAPK/ERK signaling. CONCLUSIONS: Overall, miR-223-3p attenuates the development of TN by targeting MKNK2 to suppress MAPK/ERK signaling.