Anionic Ionomer: Released Surface-Immobilized Cations and an Established Hydrophobic Microenvironment for Efficient and Durable CO2-to-Ethylene Electrosynthesis at High Current over One Month.

Electrosynthesis of multicarbon products, such as C2H4, from CO2 reduction on copper (Cu) catalysts holds promise for achieving carbon neutrality. However, maintaining a steady high current-level C2H4 electrosynthesis still encounters challenges, arising from unstable alkalinity and carbonate precipitation caused by undesired ion migration at the cathode under a repulsive electric field. To address these issues, we propose a universal "charge release" concept by incorporating tiny amounts of an oppositely charged anionic ionomer (e.g., perfluorinated sulfonic acid, PFSA) into a cationic covalent organic framework on the Cu surface (cCOF/PFSA). This strategy effectively releases the hidden positive charge within the cCOF, enhancing surface immobilization of cations to impede both outward migration of generated OH- and inward migration of cations, inhibiting carbonate precipitation and creating a strong alkaline microenvironment. Meanwhile, the ionomer's hydrophobic chains create a hydrophobic environment within the cCOF, facilitating efficient gas transport. In situ characterizations and theoretical calculations demonstrate that the cCOF/PFSA catalyst establishes a hydrophobic strong alkaline microenvironment, optimizing the adsorption strength and configuration of *CO intermediates to promote the C2H4 formation. The optimized catalyst achieves a 70.5% Faradaic efficiency for C2H4 with a partial current density over 470 mA cm-2. Notably, it delivers a high single-pass carbon efficiency of 96.5% for CO2RR and sustains an exceptional stability over 760 h. When implemented in a large-area MEA electrolyzer and a 5-cell MEA stack, the system achieves an industrial current of 15 A and continuous C2H4 production exceeding 19 mL min-1, marking a significant step toward industrial feasibility in CO2RR-to-C2H4 conversion.

Interfacial Electronic Interaction in Amorphous-Crystalline CeOx-Sn Heterostructures for Optimizing CO2 to Formate Conversion.

Formate, a crucial chemical raw material, holds significant promise for industrial applications in the context of CO2 electroreduction reaction (CO2RR). Despite its potential, challenges, such as poor selectivity and low formation rate at high current densities persist, primarily due to the competing hydrogen evolution reaction (HER) and high energy barriers associated with *OCHO intermediate generation. Herein, one-step chemical co-reduction strategy is employed to construct an amorphous-crystalline CeOx-Sn heterostructure, demonstrating remarkable catalytic performance in converting CO2 to formate. The optimized CeOx-Sn heterostructures reach a current density of 265.1 mA cm-2 and a formate Faraday efficiency of 95% at -1.07 V versus RHE. Especially, CeOx-Sn achieves a formate current density of 444.4 mA cm-2 and a formate production rate of 9211.8 µmol h-1 cm-2 at -1.67 V versus RHE, surpassing most previously reported materials. Experimental results, coupled with （density functional theory）DFT calculations confirm that robust interface interaction between CeOx and Sn active center induces electron transfer from crystalline Sn site to amorphous CeOx, some Ce4+of CeOx get electrons and convert to unsaturated Ce3+, optimizing the electronic structure of active Sn. This amorphous-crystalline heterostructure promotes electron transfer during CO2RR, reducing the energy barrier formed by *OCHO intermediates, and thus achieving efficient reduction of CO2 to formate.

Deep learning-enhanced snapshot hyperspectral confocal microscopy imaging system.

Laser-scanning confocal hyperspectral microscopy is a powerful technique to identify the different sample constituents and their spatial distribution in three-dimensional (3D). However, it suffers from low imaging speed because of the mechanical scanning methods. To overcome this challenge, we propose a snapshot hyperspectral confocal microscopy imaging system (SHCMS). It combined coded illumination microscopy based on a digital micromirror device (DMD) with a snapshot hyperspectral confocal neural network (SHCNet) to realize single-shot confocal hyperspectral imaging. With SHCMS, high-contrast 160-bands confocal hyperspectral images of potato tuber autofluorescence can be collected by only single-shot, which is almost 5 times improvement in the number of spectral channels than previously reported methods. Moreover, our approach can efficiently record hyperspectral volumetric imaging due to the optical sectioning capability. This fast high-resolution hyperspectral imaging method may pave the way for real-time highly multiplexed biological imaging.

Morphology, morphogenesis, and molecular characterization of Castula specialis sp. nov. (Ciliophora, Armophorea, Metopida).

The morphology, morphogenesis, and molecular phylogeny of a new metopid ciliate, Castula specialis sp. nov., comprising three strains from geographically distant (China, Mexico, Czech Republic) anoxic freshwater habitats, were studied based on microscopic observation of live and protargol-stained specimens as well as SSU rRNA gene sequence data. The new species is characterized as follows: size in vivo 105-220 × 25-70 µm, body oblong to elongated ellipsoidal and asymmetrical; preoral dome distinctly projecting beyond the body; 32-46 adoral membranelles; 31-52 somatic kineties; and 4-7 setae. This study brings the first morphogenetic investigation of a member of the genus Castula. The morphogenesis of the type population (China) of the new species proceeds as in Metopus spp. comprising drastic changes in body shape and a pleurotelokinetal stomatogenesis; however, the main difference is the origin of the opisthe's paroral membrane that derives from all perizonal rows and some adjacent dome kineties. Phylogenetically, the genus Castula is paraphyletic.

Modulating the Graphitic Domains of Hard Carbons Derived from Mixed Pitch and Resin to Achieve High Rate and Stable Sodium Storage.

Resin derived hard carbons (HCs) generally demonstrate remarkable electrochemical performance for both sodium ion batteries (SIBs) and potassium-ion batteries (KIBs), but their practical applications are hindered by their high price and high temperature pyrolysis (≈1500 °C). Herein, low-cost pitch is coated on the resin surface to compromise the cost, and meanwhile manipulate the microstructure at a relatively low pyrolysis temperature (1000 °C). HC-0.2P-1000 has a large number of short graphitic layer structures and a relatively large interlayer spacing of 0.3743 nm, as well as ≈1 nm sized nanopores suitable for sodium storage. Consequently, the as produced material demonstrates a superior reversible capacity (349.9 mAh g-1 for SIBs and 321.9 mAh g-1 for KIBs) and excellent rate performance (145.1 mAh g-1 at 20 A g-1 for SIBs, 48.5 mAh g-1 at 20 A g-1 for KIBs). Furthermore, when coupled with Na3 V2 (PO4 )3 as cathode, the full cell exhibits a high energy density of 251.1 Wh kg-1 and excellent stability with a capacity retention of 73.3% after 450 cycles at 1 A g-1 .

Preoperative Radiomics Approach to Evaluating Tumor-Infiltrating CD8+ T Cells in Patients With Pancreatic Ductal Adenocarcinoma Using Noncontrast Magnetic Resonance Imaging.

BACKGROUND: CD8+ T cell in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment response of patients. Accurate preoperative CD8+ T-cell expression can better identify the population benefitting from immunotherapy. PURPOSE: To develop and validate a machine learning classifier based on noncontrast magnetic resonance imaging (MRI) for the preoperative prediction of CD8+ T-cell expression in patients with PDAC. STUDY TYPE: Retrospective cohort study. POPULATION: Overall, 114 patients with PDAC undergoing MR scan and surgical resection; 97 and 47 patients in the training and validation cohorts. FIELD STRENGTH/SEQUENCE/3 T: Breath-hold single-shot fast-spin echo T2-weighted sequence and noncontrast T1-weighted fat-suppressed sequences. ASSESSMENT: CD8+ T-cell expression was quantified using immunohistochemistry. For each patient, 2232 radiomics features were extracted from noncontrast T1- and T2-weighted images and reduced using the Wilcoxon rank-sum test and least absolute shrinkage and selection operator method. Linear discriminative analysis was used to construct radiomics and mixed models. Model performance was determined by its discriminative ability, calibration, and clinical utility. STATISTICAL TESTS: Kaplan-Meier estimates, Student's t-test, the Kruskal-Wallis H test, and the chi-square test, receiver operating characteristic curve, and decision curve analysis. RESULTS: A log-rank test showed that the survival duration in the CD8-high group (25.51 months) was significantly longer than that in the CD8-low group (22.92 months). The mixed model included all MRI characteristics and 13 selected radiomics features, and the area under the curve (AUC) was 0.89 (95% confidence interval [CI], 0.77-0.92) and 0.69 (95% CI, 0.53-0.82) in the training and validation cohorts. The radiomics model included 13 radiomics features, which showed good discrimination in the training cohort (AUC, 0.85; 95% CI, 0.77-0.92) and the validation cohort (AUC, 0.76; 95% CI, 0.61-0.87). DATA CONCLUSIONS: This study developed a noncontrast MRI-based radiomics model that can preoperatively determine CD8+ T-cell expression in patients with PDAC and potentially immunotherapy planning. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Two nomograms for differentiating mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis.

OBJECTIVES: To develop and validate a CT nomogram and a radiomics nomogram to differentiate mass-forming chronic pancreatitis (MFCP) from pancreatic ductal adenocarcinoma (PDAC) in patients with chronic pancreatitis (CP). METHODS: In this retrospective study, the data of 138 patients with histopathologically diagnosed MFCP or PDAC treated at our institution were retrospectively analyzed. Two radiologists analyzed the original cross-sectional CT images based on predefined criteria. Image segmentation, feature extraction, and feature reduction and selection were used to create the radiomics model. The CT and radiomics models were developed using data from a training cohort of 103 consecutive patients. The models were validated in 35 consecutive patients. Multivariable logistic regression analysis was conducted to develop a model for the differential diagnosis of MFCP and PDAC and visualized as a nomogram. The nomograms' performances were determined based on their differentiating ability and clinical utility. RESULTS: The mean age of patients was 53.7 years, 75.4% were male. The CT nomogram showed good differentiation between the two entities in the training (area under the curve [AUC], 0.87) and validation (AUC, 0.94) cohorts. The radiomics nomogram showed good differentiation in the training (AUC, 0.91) and validation (AUC, 0.93) cohorts. Decision curve analysis showed that patients could benefit from the CT and radiomics nomograms, if the threshold probability was 0.05-0.85 and > 0.05, respectively. CONCLUSIONS: The two nomograms reasonably accurately differentiated MFCP from PDAC in patients with CP and hold potential for refining the management of pancreatic masses in CP patients. KEY POINTS: • A CT nomogram and a computed tomography-based radiomics nomogram reasonably accurately differentiated mass-forming chronic pancreatitis from pancreatic ductal adenocarcinoma in patients with chronic pancreatitis (CP). • The two nomograms can monitor the cancer risk in patients with CP and hold promise to optimize the management of pancreatic masses in patients with CP.

Effects of corticospinal tract integrity on upper limb motor function recovery in stroke patients treated with repetitive transcranial magnetic stimulation.

BACKGROUND: The bimodal balance-recovery model predicts that corticospinal tract (CST) integrity in the affected hemisphere influences the partterns of brain recovery after stroke. Repetitive transcranial magnetic stimulation (rTMS) has been used to promote functional recovery of stroke patients by modulating motor cortical excitability and inducing reorganization of neural networks. This study aimed to explore how to optimize the efficiency of repetitive transcranial magnetic stimulation to promote upper limb functional recovery after stroke according to bimodal balance-recovery model. METHODS: 60 patients who met the inclusion criteria were enrolled to high CST integrity group (n = 30) or low CST integrity group (n = 30), and further assigned randomly to receive high-frequency rTMS (HF-rTMS), low-frequency rTMS (LF-rTMS) or sham rTMS in addition to routine rehabilitation, with 10 patients in each group. Outcome measures included Fugl-Meyer scale for upper extremity (FMA-UE), Wolf Motor Function (WMFT) scale and Modified Barthel Index (MBI) scale which were evaluated at baseline and after 21 days of treatment. RESULTS: For patients with high CST integrity, the LF group achieved higher FMA-UE, WMFT and MBI scores improvements after treatment when compared to the HF group and sham group. For patients with low CST integrity, after 21 days treatment, only the HF group showed significant improvements in FMA-UE and WMFT scores. For MBI assessment, the HF group revealed significantly better improvements than the LF group and sham group. CONCLUSIONS: For stroke patients with high CST integrity, low-frequency rTMS is superior to high-frequency rTMS in promoting upper limb motor function recovery. However, only high-frequency rTMS can improve upper limb motor function of stroke patients with low CST integrity.

Noncontrast Magnetic Resonance Radiomics and Multilayer Perceptron Network Classifier: An approach for Predicting Fibroblast Activation Protein Expression in Patients With Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Fibroblast activation protein (FAP) in pancreatic ductal adenocarcinoma (PDAC) is closely related to the prognosis and treatment of patients. Accurate preoperative FAP expression can better identify the population benefitting from FAP-targeting drugs. PURPOSE: To develop and validate a machine learning classifier based on noncontrast MRI for the preoperative prediction of FAP expression in patients with PDAC. STUDY TYPE: Retrospective cohort study. POPULATION: Altogether, 129 patients with pathology-confirmed PDAC undergoing MR scan and surgical resection; 90 patients in a training cohort, and 39 patients in a validation cohort. FIELD STRENGTH/SEQUENCE/3T: Breath-hold single-shot fast-spin echo T2-weighted sequence and unenhanced and noncontrast T1-weighted fat-suppressed sequences. ASSESSMENT: FAP expression was quantified using immunohistochemistry. For each patient, 1409 radiomics features were extracted from T1- and T2-weighted images and reduced using the least absolute shrinkage and selection operator logistic regression algorithm. A multilayer perceptron (MLP) network classifier was developed using the training and validation set. The MLP network classifier performance was determined by its discriminative ability, calibration, and clinical utility. STATISTICAL TESTS: Kaplan-Meier estimates, student's t-test, the Kruskal-Wallis H test, and the chi-square test, univariable regression analysis, receiver operating characteristic curve, and decision curve analysis were used. RESULTS: A log-rank test showed that the survival of patients with low FAP expression (24.43 months) was significantly longer (P < 0.05) than that in the FAP-high group (13.50 months). The prediction model showed good discrimination in the training set (area under the curve [AUC], 0.84) and the validation set (AUC, 0.77). The sensitivity, specificity, accuracy, positive predictive value, and negative predictive value for the training set were 75.00%, 79.41%, 0.77, 0.86, and 0.66, respectively, whereas those for the validation set were 85.00%, 63.16%, 0.74, 0.71, and 0.80, respectively. DATA CONCLUSIONS: The MLP network classifier based on noncontrast MRI can accurately predict FAP expression in patients with PDAC. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Morphology and molecular phylogeny of three Parasonderia species including a new species (Ciliophora, Plagiopylea).

Ciliates of the class Plagiopylea play a vital role in various anaerobic environments as consumers of prokaryotes. Yet, the diversity and phylogeny of this group of ciliates, especially marine representatives, remain poorly known. In this study, three Parasonderia species, viz., Parasonderia elongata spec. nov., and the already known P. cyclostoma and P. vestita, discovered in anaerobic sediments from various intertidal zones in China, were investigated based on their living morphology, infraciliature, and small subunit ribosomal rRNA gene sequences. Parasonderia elongata can be recognized by its larger body size, elongated body shape, oval oral opening, number of oral kineties, and significantly shortened leftmost postbuccal polykineties on the cell surface. Improved diagnosis and redescription of P. cyclostoma is provided for the first time, including data on infraciliature and molecular sequence. Phylogenetic analyses revealed that the three species cluster together and with the sequence of a Chinese population of P. vestita already present in the GenBank database, forming a robust clade.

Morphogenesis of an anaerobic ciliate Heterometopus palaeformis (Kahl, 1927) Foissner, 2016 (Ciliophora, Armophorea) with notes on its morphological and molecular characterization.

The morphology, morphogenesis, and molecular phylogeny of Heterometopus palaeformis (Kahl, 1927) Foissner, 2016 were studied using microscopical observations on live and protargol-stained specimens as well SSU rRNA gene sequencing. The morphogenetic data for the genus are presented for the first time. Compared to other metopids, the morphogenesis of H. palaeformis is distinct since its (1) perizonal stripe rows 4 and 5 are involved in the formation of the opisthe's adoral polykinetids; (2) perizonal stripe rows 3-5 and two adjacent preoral dome kineties contribute to most of the opisthe's paroral membrane while perizonal stripe rows 1 and 2 contribute very little; (3) four kinety rows are formed to the left of the opisthe's adoral zone of polykinetids. The Chinese population resembles the original and neotype populations well in terms of general morphology - characterized by a life size of 55-120 × 10-20 µm, an elongate ellipsoidal body with a hardly spiralized flat preoral dome, about 18 somatic kineties and 20 adoral polykinetids. The SSU rDNA sequence of the present population exhibits a disparity of 1.33%-2.22% divergence from sequences of other populations. Nevertheless, phylogenetic analysis reveals that populations of H. palaeformis form a separate, stable cluster within the paraphyletic Metopidae clade.

Synergistic pathways for health investment and economic development in China: a fuzzy-set qualitative comparative analysis.

Background: System coordination is an effective way to achieve high-quality development, and the debate on the interaction between health investment and economic development is still ongoing. To strengthen previous research and offer feasible advice and references for relevant stakeholders, we provide empirical evidence for exploring intersystem coordination and enhancement pathways using data from China. Methods: Based on the data published by the National Bureau of Statistics of China, the current status of the interaction and coordination between health investment and economic development in China was measured by calculating the comprehensive evaluation index, relative development degree, and coupling coordination degree. Subsequently, a fuzzy-set qualitative comparative analysis method was introduced to explore pathways for enhancing system interaction and coordination. Results: There are obvious inter-provincial and regional differences between health investment and economic development in China. Provinces in the west and north are lagging in economic development, while provinces in the east and south are lagging in health investment. There is a clear synergy between health investment and economic development, and there is still much room for improving the degree of coupling coordination between systems. The five conditional configurations derived from the fuzzy-set qualitative comparative analysis yield three pathways for enhancing system coordination: a health expenditure-driven path, an economic development-driven path, and a balanced health investment and economic development-driven path. Conclusion: Health expenditure is sufficient for high coordination, and the level and equity of investment in health expenditure should be improved. The gross regional product is a necessary and sufficient condition for high coordination, and consideration must be given to strengthening the regional economic support capacity. Health investment and economic development can drive the coordinated development of the system in a balanced way. This enlightens us to give full play to the positive synergy between health investment and economic development based on promoting the benign interaction of subsystems.

Reliable deep learning in anomalous diffusion against out-of-distribution dynamics.

Anomalous diffusion plays a crucial rule in understanding molecular-level dynamics by offering valuable insights into molecular interactions, mobility states and the physical properties of systems across both biological and materials sciences. Deep-learning techniques have recently outperformed conventional statistical methods in anomalous diffusion recognition. However, deep-learning networks are typically trained by data with limited distribution, which inevitably fail to recognize unknown diffusion models and misinterpret dynamics when confronted with out-of-distribution (OOD) scenarios. In this work, we present a general framework for evaluating deep-learning-based OOD dynamics-detection methods. We further develop a baseline approach that achieves robust OOD dynamics detection as well as accurate recognition of in-distribution anomalous diffusion. We demonstrate that this method enables a reliable characterization of complex behaviors across a wide range of experimentally diverse systems, including nicotinic acetylcholine receptors in membranes, fluorescent beads in dextran solutions and silver nanoparticles undergoing active endocytosis.

Infrared/microwave (IR/MW) micromirror array beam combiner design and analysis.

We investigated the design method of an infrared (IR)/microwave (MW) micromirror array type of beam combiner. The size of micromirror is in microscopic levels and comparable to MW wavelengths, so that the MW will not react in these dimensions, whereas the much shorter optical wavelengths will be reflected by them. Hence, the MW multilayered substrate was simplified and designed using transmission line theory. The beam combiner used an IR wavefront-division imaging technique to reflect the IR radiation image to the unit under test (UUT)'s pupil in a parallel light path. In addition, the boresight error detected by phase monopulse radar was analyzed using a moment-of method (MoM) and multilevel fast multipole method (MLFMM) acceleration technique. The boresight error introduced by the finite size of the beam combiner was less than 1°. Finally, in order to verify the wavefront-division imaging technique, a prototype of a micromirror array was fabricated, and IR images were tested. The IR images obtained by the thermal imager verified the correctness of the wavefront-division imaging technique.

Generating new protein sequences by using dense network and attention mechanism.

Protein engineering uses de novo protein design technology to change the protein gene sequence, and then improve the physical and chemical properties of proteins. These newly generated proteins will meet the needs of research better in properties and functions. The Dense-AutoGAN model is based on GAN, which is combined with an Attention mechanism to generate protein sequences. In this GAN architecture, the Attention mechanism and Encoder-decoder can improve the similarity of generated sequences and obtain variations in a smaller range on the original basis. Meanwhile, a new convolutional neural network is constructed by using the Dense. The dense network transmits in multiple layers over the generator network of the GAN architecture, which expands the training space and improves the effectiveness of sequence generation. Finally, the complex protein sequences are generated on the mapping of protein functions. Through comparisons of other models, the generated sequences of Dense-AutoGAN verify the model performance. The new generated proteins are highly accurate and effective in chemical and physical properties.

First redescription and molecular phylogeny of Trimyema claviforme Kahl, 1933 with the description of a Chinese population of Plagiopyla nasuta Stein, 1860 (Ciliophora, Plagiopylea).

Ciliates belonging to the class Plagiopylea are obligate anaerobes that are often neglected due to their cryptic lifestyles, difficulty of observation, and overall under-sampling. Here, we investigate two species, namely Trimyema claviforme Kahl, 1933 and Plagiopyla nasuta Stein, 1860, collected in China from marine and freshwater anaerobic sediments, respectively. A complete morphological dataset, together with SSU rRNA gene sequence data were obtained and used to diagnose the species. No molecular sequencing had ever been performed on Trimyema claviforme, with its ciliature also previously unknown. Based on these novel data presented here, the ciliate is characterized by a claviform cell shape, with a size of 35-45 × 10-20 µm in vivo, 28-39 longitudinal somatic ciliary rows forming five ciliary girdles (four complete girdles and a shorter one), two dikinetids left to anterior end of oral kinety 1, and an epaulet. A Chinese population of the well-known ciliate P. nasuta was investigated, and morphological comparisons revealed phenotypic stability of the species. The phylogenetic analyses supported previous findings about the monophyly of the families Trimyemidae and Plagiopylidae, with Trimyema claviforme branching off early in the genus Trimyema. The Chinese population of P. nasuta clusters together with two other populations with full support corroborating their conspecificity.

Interfacial Electronic Interaction in In2O3/Poly(3,4-ethylenedioxythiophene)-Modified Carbon Heterostructures for Enhanced Electroreduction of CO2 to Formate.

Formate, as an important chemical raw material, is considered to be one of the most promising products for industrialization among CO2 electroreduction reaction (CO2RR) products, but it still suffers from poor selectivity and a low formation rate at a high current density on account of the competitory hydrogen evolution reaction. Herein, the heterogeneous nanostructure was constructed by anchoring In2O3 nanoparticles on poly(3,4-ethylenedioxythiophene) (PEDOT)-modified carbon black (In2O3/PC), in which the PEDOT polymer interface layer could immobilize In2O3 nanoparticles and obtain a notable reduction in electron transfer resistance among the In2O3 particles, showing a 27% increase in the total electron transfer rate. The optimized In2O3/PC with rich heterogeneous interfaces selectively reduced CO2 to formate with a high FE of 95.4% and a current density of 251.4 mA cm-2 under -1.18 V vs RHE. Also, the formate production rate for In2O3/PC was up to 7025.1 µmol h-1 cm-2, surpassing most previously reported CO2RR catalysts. The in situ XRD results revealed that In2O3 particles were reduced to metallic indium (In) as catalytic active sites during CO2RR. DFT calculations verified that a strong interface interaction between In sites and PC induced electron transfer from In sites to PC, which could optimize the charge distribution of active sites, accelerate electron transfer, and elevate the p-band center of In sites toward the Fermi level, thereby lowering the adsorption energy of *OCHO intermediates for CO2 conversion to formate.

In-Plane BO3 Configuration in P2 Layered Oxide Enables Outstanding Long Cycle Performance for Sodium Ion Batteries.

P2-phase layered cathode materials with distinguished electrochemical performance for sodium-ion batteries have attracted extensive attention, but they face critical challenges of transition metal layer sliding and unfavorable formation of hydration phase upon cycling, thus showing inferior long cycle life. Herein, a new approach is reported to modulate the local structure of P2 material by constructing a state-of-the-art in-plane BO3 triangle configuration ((Na0.67 Ni0.3 Co0.1 Mn0.6 O1.94 (BO3 )0.02 ). Both are unveiled experimentally and theoretically that such a structure can serve as a robust pillar to hold up the entire structure, by inhibiting the H2 O insertion upon Na (de)intercalation and preventing the structure from deformation, which significantly boost the long cycle capability of P2-materials. Meanwhile, more Na ions in the architecture are enabled to site on the edge sharing octahedrons (Nae ), thus benefiting the Na+ transportation. Consequently, the as produced material demonstrates an ultralow volume variation (1.8%), and an outstanding capacity retention of 80.1% after 1000 cycles at 2 C. This work sheds light on efficient architecture modulation of layered oxides through proper nonmetallic element doping.

Lipid metabolism of hepatocellular carcinoma impacts targeted therapy and immunotherapy.

Hepatocellular carcinoma (HCC) is a common malignant tumor that affecting many people's lives globally. The common risk factors for HCC include being overweight and obese. The liver is the center of lipid metabolism, synthesizing most cholesterol and fatty acids. Abnormal lipid metabolism is a significant feature of metabolic reprogramming in HCC and affects the prognosis of HCC patients by regulating inflammatory responses and changing the immune microenvironment. Targeted therapy and immunotherapy are being explored as the primary treatment strategies for HCC patients with unresectable tumors. Here, we detail the specific changes of lipid metabolism in HCC and its impact on both these therapies for HCC. HCC treatment strategies aimed at targeting lipid metabolism and how to integrate them with targeted therapy or immunotherapy rationally are also presented.

Zinc Single-Atom-Regulated Hard Carbons for High-Rate and Low-Temperature Sodium-Ion Batteries.

Hard carbons, as one of the most commercializable anode materials for sodium-ion batteries (SIBs), have to deal with the trade-off between the rate capability and specific capacity or initial Columbic efficiency (ICE), and the fast performance decline at low temperature (LT) remains poorly understood. Here, a comprehensive regulation on the interfacial/bulk electrochemistry of hard carbons through atomic Zn doping is reported, which demonstrates a record-high reversible capacity (546 mAh g-1 ), decent ICE (84%), remarkable rate capability (140 mAh g-1 @ 50 A g-1 ), and excellent LT capacity (443 mAh g-1 @ -40 °C), outperforming the state-of-the-art literature. This work reveals that the Zn doping can generally induce a local electric field to enable fast bulk Na+ transportation, and meanwhile catalyze the decomposition of NaPF6 to form a robust inorganic-rich solid-electrolyte interphase, which elaborates the underlying origin of the boosted electrochemical performance. Importantly, distinguished from room temperature, the intrinsic Na+ migration/desolvation ability of the electrolyte is disclosed to be the crucial rate-determining factors for the SIB performance at LT. This work provides a fundamental understanding on the charge-storage kinetics at varied temperatures.