Unleashed Remarkable Energy Storage Performance in Bi0.5K0.5TiO3-based Relaxor Ferroelectrics by Local Structural Fluctuation.

Dielectric capacitors harvest energy through an electrostatic process, which enables an ultrafast charging-discharging rate and ultrahigh power density. However, achieving high energy density (Wrec) and efficiency (η) simultaneously, especially when preserving them across a wide frequency/temperature range or cycling numbers, remains challenging. In this work, by especially introducing NaTaO3 into the representative ferroelectric relaxor of Bi0.5K0.5TiO3-Bi0.5Na0.5TiO3 and leveraging the mismatch between B-site atoms, we proposed a method of enhancing local structural fluctuation to refine the polar configuration and to effectively improve its overall energy-storage performances. As a consequence, the ceramic exhibits an ultrahigh Wrec of 15.0 J/cm3 and high η up to 80%, along with a very wide frequency stability of 10 - 200 Hz and extensive cycling number up to 108. In-depth local structure and chemical environment investigations, consisting of atom-scale electron microscopy, neutron total scattering, and solid-state nuclear magnetic resonance, reveal that the randomly distributed A/B-site atom pairs emerge in the system, leading to the evident local structural fluctuations and concomitant polymorphic polar nanodomains. These key ingredients contribute to the large polarization, minimal hysteresis, and high breakdown strength, thereby promoting energy-storage performances. This work opens a new path for designing high-performance dielectric capacitors via manipulating local structural fluctuations.

Ultrafast and Highly Efficient Laser Extraction of Matrine and Oxymatrine from Sophora flavescens for the Anticancer Activity.

Matrine and oxymatrine are mainly obtained from Sophora flavescens using the high-temperature and prolonged solvent extraction methods currently employed in industries. In this study, an ultrafast and highly efficient method for extracting matrine and oxymatrine from S. flavescens at room temperature using laser technology, specifically, laser extraction, was demonstrated. The laser extraction rates for matrine and oxymatrine from S. flavescens at room temperature for 1 min were 266.40 and 936.80 mg(g·h)-1, respectively. These rates were 1400 times higher than those achieved with conventional solvent extraction. These results mean that 1 min of laser extraction is equivalent to 24 h of solvent extraction. The reason for such a high efficiency is that laser-induced cavitation can accelerate the rapid release of alkaloid molecules in plant cells. Mass spectrum, nuclear magnetic resonance, and Fourier-transform infrared spectrum analyses of the extracted matrine and oxymatrine compounds confirmed that they are the same as the products of solvent extraction. Furthermore, it was found that the anticancer activity of laser-extracted compounds is slightly better than that of conventionally solvent-extracted ones, likely due to the slight change in the microstructure or conformation of these compounds under laser irradiation. These findings demonstrated that the laser extraction method was ultrafast and highly efficient, unveiling a novel approach to alkaloid extraction. This discovery will have significant implications for the extraction and utilization of alkaloids from plants.

Microwave freeze-drying characteristics and crosslinking behavior of wheat starch-laurel acid complex.

This article investigates the effect of different microwave powers on the crosslinking behavior and microwave freeze-drying characteristics of wheat starch-lauroyl arginate complex during the microwave freeze-drying process. During microwave freeze-drying, as microwave power increased from 0.1 W/g to 0.9 W/g, the freeze-drying time of WS-LA was reduced by 50 %, while the uniformity of freeze-drying was not affected by its composition. In the research results obtained from DSC, Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), XRD, and SEM analyses, with the microwave power increased from 0.1 W/g to 0.9 W/g, the enthalpy value of the melting peak of the WS-LA (wheat starch-lauric acid) composite decreased from 1.15 J/g to 0.62 J/g. The full width at half maximum (FWHM) value increased from 25.6 to 30.79. The ratio of absorbance at 1022/995 cm-1 increased from 1.0111 to 1.0707. The recrystallization (RC) value decreased from 8.77 % to 0.07 %. Additionally, in the microstructure, the size of WS-LA composite particles decreased accordingly. The above findings indicated that the increase in microwave power during microwave freeze-drying had a negative impact on the formation of the WS-LA complex and the ordering of its structure in the sample.

Topology-preserving segmentation of abdominal muscle layers from ultrasound images.

BACKGROUND: In clinical anesthesia, precise segmentation of muscle layers from abdominal ultrasound images is crucial for identifying nerve block locations accurately. Despite deep learning advancements, challenges persist in segmenting muscle layers with accurate topology due to pseudo and weak edges caused by acoustic artifacts in ultrasound imagery. PURPOSE: To assist anesthesiologists in locating nerve block areas, we have developed a novel deep learning algorithm that can accurately segment muscle layers in abdominal ultrasound images with interference. METHODS: We propose a comprehensive approach emphasizing the preservation of the segmentation's low-rank property to ensure correct topology. Our methodology integrates a Semantic Feature Extraction (SFE) module for redundant encoding, a Low-rank Reconstruction (LR) module to compress this encoding, and an Edge Reconstruction (ER) module to refine segmentation boundaries. Our evaluation involved rigorous testing on clinical datasets, comparing our algorithm against seven established deep learning-based segmentation methods using metrics such as Mean Intersection-over-Union (MIoU) and Hausdorff distance (HD). Statistical rigor was ensured through effect size quantification with Cliff's Delta, Multivariate Analysis of Variance (MANOVA) for multivariate analysis, and application of the Holm-Bonferroni method for multiple comparisons correction. RESULTS: We demonstrate that our method outperforms other industry-recognized deep learning approaches on both MIoU and HD metrics, achieving the best outcomes with 88.21%/4.98 ( p m a x = 0.1893 $p_{max}=0.1893$ ) on the standard test set and 85.48%/6.98 ( p m a x = 0.0448 $p_{max}=0.0448$ ) on the challenging test set. The best&worst results for the other models on the standard test set were (87.20%/5.72)&(83.69%/8.12), and on the challenging test set were (81.25%/10.00)&(71.74%/16.82). Ablation studies further validate the distinct contributions of the proposed modules, which synergistically achieve a balance between maintaining topological integrity and edge precision. CONCLUSIONS: Our findings validate the effective segmentation of muscle layers with accurate topology in complex ultrasound images, leveraging low-rank constraints. The proposed method not only advances the field of medical imaging segmentation but also offers practical benefits for clinical anesthesia by improving the reliability of nerve block localization.

Multiplex qPCR development for the simultaneous and rapid detection of largemouth bass virus and infectious spleen and kidney necrosis virus in aquaculture.

Largemouth bass virus (LMBV) and infectious spleen and kidney necrosis virus (ISKNV) are both belong to Iridoviridae that cause considerable economic losses in the fish industry. There is no reported literature that can detect these two viruses simultaneously. In this study, we established a multiplex quantitative polymerase chain reaction (qPCR) assay that can specifically and simultaneously detect both LMBV and ISKNV in fish samples. The specificity experiment showed that the method only amplified LMBV and ISKNV but not the other 10 common fish viruses. The slope (m), efficiency (E) and linearity (R2) determined from the generated standard curve were all within the optimal range of qPCR values. The detection limit of the multiplex qPCR assay was as low as 4 copies/µL for LMBV DNA and 7 copies/µL for ISKNV DNA, respectively. The established method exhibited adequate repeatability and reproducibility, and the intra- and inter-assay coefficients of variation were both less than 3 %. The accuracy of the multiplex qPCR method was validated using 229 fish samples and was more precise than that of the conventional PCR assay. In summary, the established multiplex qPCR assay can simultaneously detect LMBV and ISKNV to monitor the risk of infection LMBV and ISKNV and control the disease early.

Composition and metabolic flexibility of hydrocarbon-degrading consortia in oil reservoirs.

Hydrocarbon-degrading consortia (HDC) play an important role in petroleum exploitation. However, the real composition and metabolic mechanism of HDC in the microbial enhanced oil recovery (MEOR) process remain unclear. By combining 13C-DNA stable isotope probing microcosms with metagenomics, some newly reported phyla, including Chloroflexi, Synergistetes, Thermotogae, and Planctomycetes, dominated the HDC in the oil reservoirs. In the field trials, the HDC in the aerobic-facultative-anaerobic stage of oilfields jointly promoted the MEOR process, with monthly oil increments of up to 189 tons. Pseudomonas can improve oil recovery by producing rhamnolipid in the facultative condition. Roseovarius was the novel taxa potentially oxidizing alkane and producing acetate to improve oil porosity and permeability in the aerobic condition. Ca. Bacteroidia were the new members potentially degrading hydrocarbons by fumarate addition in the anaerobic environment. Comprehensive identification of the active HDC in oil reservoirs provides a novel theoretical basis for oilfield regulatory scheme.

Electrochemiluminescence of Ultrasmall Silica Nanoparticles from Size Modulation and Multipath Surface State Adjustment for Ultrasensitive HIV-DNA Fragment Detection.

Here, ultrasmall SiO2 nanoparticles (u-SiO2 NPs, <5 nm) with obvious electrochemiluminescence (ECL) phenomenon, which was absent for conventional silica nanoparticles (c-SiO2 NPs), were reported. In a finite ultrasmall volume, the u-SiO2 NPs exhibited increasing ground state energy and higher optical absorption strength due to the electron-hole confinement model and favored catalyzing the reaction through the rapid diffusion of bulk charge, resulting in apparent ECL emission. Then, Zn2+-induced u-SiO2 nanoaggregates (Zn/u-SiO2-Ov nAGG) were synthesized and exhibited improved ECL performance via multipath surface state adjustment of u-SiO2 from several aspects, including aggregation-induced ECL, the generation of oxygen vacancy (Ov), and more positive surface charge. In addition, an ECL biosensor was constructed for ultrasensitive human immunodeficiency virus-related deoxyribonucleic acid detection from 100 aM to 1 nM with a low limit of 50.48 aM, combining the ECL luminescence of Zn/u-SiO2-Ov nAGG with three-dimensional DNA nanomachine-mediated multioutput amplification for enhanced accuracy and sensitivity compared to the single-output method. Therefore, exploring the ECL of ultrasmall nanoparticles via the adjustment of size and surface state provided a valuable indication to a wider investigation and application of novel ECL materials for clinical diagnostic.

EREG silencing inhibits tumorigenesis via inactivating ERK/p38 MAPK pathway in pancreatic ductal adenocarcinoma.

Epiregulin (EREG) is a member of the epidermal growth factor (EGF) family. An increasing body of evidence has demonstrated the pivotal role of EREG in the pathogenesis and progression of various malignancies. However, the clinical significance and biological role of EREG in pancreatic ductal adenocarcinoma (PDAC) have yet to be fully elucidated. We found that EREG is highly expressed in PDAC tissues compared with paracancerous tissues through public databases and clinical samples. High EREG expression predicted worse overall survival (OS) and recurrence-free survival (RFS) in patients with PDAC. Multivariate analysis revealed that EREG can serve as an independent prognostic indicator. In addition, EREG silencing inhibited PDAC cell proliferation, migration, progression, altered cell cycle, facilitated apoptosis in vitro and suppressed tumor growth in vivo. Conversely, EREG overexpression facilitated the proliferation, migration, and invasion in PaTu-8988 t cell. Through transcriptome sequencing and experimental verification, we found EREG mediates PDAC tumorigenesis through ERK/p38 MAPK signaling pathway. Moreover, we found EREG expression is closely related to PD-L1 expression in PDAC tissues and cells. Therefore, EREG is expected to be a prospective prognostic and therapeutic marker for PDAC.

Novel strategy for optimizing of corn starch-based ink food 3D printing process: Printability prediction based on BP-ANN model.

Although starch has been intensively studied as a raw material for 3D printing, the relationship between several important process parameters in the preparation of starch gels and the printing results is unclear. In this study, the relationship between different processing conditions and the gel printing performance of corn starch was evaluated by printing tests, rheological tests and low-field nuclear magnetic resonance (LF-NMR) tests, and a back-propagation artificial neural network (BP-ANN) model for predicting gel printing performance was developed. The results revealed that starch gels exhibited favorable printing performance when the gelatinization temperature ranged from 75 °C to 85 °C, and the starch content was maintained between 15 % and 20 %. The R2adj of the BP-ANN models were all reached 0.894, which indicated good predictive ability. The results of the study not only provide theoretical support for the application of corn starch gels in 3D food printing, but also present a novel approach for predicting the printing performance of related materials. This method contributes to the optimization of printing parameters, thereby enhancing printing efficiency and quality.

Coupling and interaction mechanism between green urbanization and tourism competitiveness based an empirical study in the Yellow River Basin of China.

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed.

Solvent Regulation Induced Cathode Aggregation-Induced Electrochemiluminescence of Tetraphenylethylene Nanoaggregates for Ultrasensitive Zearalenone Analysis.

Zearalenone (ZEN) is an extremely hazardous chemical widely existing in cereals, and its high-sensitivity detection possesses significant significance to human health. Here, the cathodic aggregation-induced electrochemiluminescence (AIECL) performance of tetraphenylethylene nanoaggregates (TPE NAs) was modulated by solvent regulation, based on which an electrochemiluminescence (ECL) aptasensor was constructed for sensitive detection of ZEN. The aggregation state and AIECL of TPE NAs were directly and simply controlled by adjusting the type of organic solvent and the fraction of water, which solved the current shortcomings of low strength and weak stability of the cathode ECL signal for TPE. Impressively, in a tetrahydrofuran-water mixed solution (volume ratio, 6:4), the relative ECL efficiency of TPE NAs reached 16.03%, which was 9.2 times that in pure water conditions, and the maximum ECL spectral wavelength was obviously red-shifted to 617 nm. In addition, "H"-shape DNA structure-mediated dual-catalyzed hairpin self-assembly (H-D-CHA) with higher efficiency by the synergistic effect between the two CHA reactions was utilized to construct a sensitive ECL aptasensor for ZEN analysis with a low detection limit of 0.362 fg/mL. In conclusion, solvent regulation was a simple and efficient method for improving the performance of AIECL materials, and the proposed ECL aptasensor had great potential for ZEN monitoring in food safety.

NeighborNet: Learning Intra- and Inter-Image Pixel Neighbor Representation for Breast Lesion Segmentation.

Breast lesion segmentation from ultrasound images is essential in computer-aided breast cancer diagnosis. To alleviate the problems of blurry lesion boundaries and irregular morphologies, common practices combine CNN and attention to integrate global and local information. However, previous methods use two independent modules to extract global and local features separately, such feature-wise inflexible integration ignores the semantic gap between them, resulting in representation redundancy/insufficiency and undesirable restrictions in clinic practices. Moreover, medical images are highly similar to each other due to the imaging methods and human tissues, but the captured global information by transformer-based methods in the medical domain is limited within images, the semantic relations and common knowledge across images are largely ignored. To alleviate the above problems, in the neighbor view, this paper develops a pixel neighbor representation learning method (NeighborNet) to flexibly integrate global and local context within and across images for lesion morphology and boundary modeling. Concretely, we design two neighbor layers to investigate two properties (i.e., number and distribution) of neighbors. The neighbor number for each pixel is not fixed but determined by itself. The neighbor distribution is extended from one image to all images in the datasets. With the two properties, for each pixel at each feature level, the proposed NeighborNet can evolve into the transformer or degenerate into the CNN for adaptive context representation learning to cope with the irregular lesion morphologies and blurry boundaries. The state-of-the-art performances on three ultrasound datasets prove the effectiveness of the proposed NeighborNet.

Catalyst-Free Activation and Fixation of Nitrogen by Laser-Induced Conversion.

Ultrafast N2 fixation reactions are quite challenging. Currently used methods for N2 fixation are limited, and strong dinitrogen bonds usually need to be activated via extreme temperature or pressure or by the use of an energy-consuming process with sophisticated catalysts. Herein, we report a novel laser-based chemical method for N2 fixation under ambient conditions without catalysts, this method is called laser bubbling in liquids (LBL), and it directly activates N2 in water (H2O) and efficiently converts N2 into valuable NH3 (max: 4.2 mmol h-1) and NO3- (0.17 mmol h-1). Remarkably, the highest yields of NH3 and NO3- are 4 orders of magnitude greater than the best values for electrocatalysis reported to date. Notably, we further validate the experimental mechanism by using optical emission spectroscopy to detect the production of intermediate plasma and by employing isotope tracing. We also establish that an extremely high-temperature environment far from thermodynamic equilibrium inside a laser-induced bubble and the kinetic process of rapid quenching of bubbles is crucial for N2 activation and fixation to generate NH3 and NOx via LBL. Based on these results, it is shown that LBL is a simple, safe, efficient, green, and sustainable technology that enables the rapid conversion of the renewable feedstocks H2O and N2 to NH3 and NO3-, facilitating new prospects for chemical N2 fixation.

Microencapsulation of fish oil by spray drying, spray freeze-drying, freeze-drying, and microwave freeze-drying: Microcapsule characterization and storage stability.

The objective of this paper was to evaluate the effect of spray drying (SD), spray freeze-drying (SFD), freeze-drying (FD), and microwave freeze-drying (MFD) on the characteristics of fish oil (FO) microcapsules. The physicochemical properties, morphology, fatty acid composition, and stability of the microcapsules were analyzed. The encapsulation efficiencies of microcapsules dried by SD, SFD, FD, and MFD were 86.98%, 77.79%, 63.29%, and 57.89%, respectively. SD microcapsules exhibited superior properties in terms of effective loading capacity, color, and flowability. Conversely, SFD microcapsules demonstrated improved solubility. Microencapsulation positively affected the thermal stability of FO, but the content of unsaturated fatty acids decreased. The findings from the storage experiment indicated that the oxidative stability of SD fish oil microcapsules was marginally lower compared to microcapsules produced through three alternative drying techniques, all of which were based on the FD concept. The comparison of various drying methods and their effects on the quality of FO microcapsules offers valuable insights that can serve as a foundation for the industrial production of high-quality microcapsules.

N vacancy and self-enhancement induced high anodic electrochemiluminescence of 3D g-C3N4 for sensitive staphylococcus aureus analysis.

Here, 3D g-C3N4 with dense N vacancy in its 3D porous interconnected open-framework was synthesized, and the co-reactive 3-(dibutylamino)propylamine (DBAPA) was further covalently coupled onto the surface, resulting in a strong self-enhanced anodic electrochemiluminescence (ECL). Through introduction of high-density N vacancy, for the obtained 3D g-C3N4-NV, the band gap was broadened and the electrical conductivity was enhanced, realizing an obvious ECL improvement. Moreover, after the covalent binding of co-reactive DBAPA, the obtained 3D g-C3N4-NV-DBAPA exhibited a more intensive self-enhanced ECL signal due to the higher co-reaction efficiency originated from shorter electron transfer distance and lower energy loss. Based on the high initial signal of the proposed 3D g-C3N4-NV-DBAPA, a sensitive ECL biosensor with signal "on-off" was fabricated in assistance with multiple horizontal ordered hybridization chain reaction (HO-HCR). Through orderly fixing the reacted DNA chains on the Y-shape DNA structure on the electrode could effectively decrease diffusion process and improve the reaction efficiency of HCR process, resulting in the formation of numerous long horizontal double-strand DNA that could immobilize abundant ferrocene-doxorubicin (Fc-Dox) with ECL quenching effect. Meanwhile, compared to the traditional vertical HCR, the HO-HCR could make the quench reagent closer to the ECL emitter on the electrode surface and obtain a more effective quenching effect to enhance the sensing sensitivity. As a result, the proposed ECL biosensor archived the sensitive measurement of staphylococcus aureus with a detection limit of 10.3 aM.

Effects of Freeze-Thaw Cycles on the Quality of a Novel Mixed Grain Composite Dough and Its Product (Potato-Oat Yu): Hybridization of Potatoes and Oats.

To provide a theoretical basis for the frozen storage of potato-oat composite dough and its products, this investigation examines changes in the quality of potato-oat composite dough and its resulting product during freeze-thaw cycles. The study measured key aspects such as moisture content, dynamic rheological properties, water state, protein secondary structure, color, and sensory assessment. The influence of these factors on the product's quality is analyzed. The findings revealed that the freeze-thaw treatment caused a reduction in water content, freezable water, and deeply bound water, as well as an increase in weakly bound water, ß-sheet, random coil, and α-helix, and a decreased ß-turn of the potato-oat composite dough. Additionally, the dough treated by freeze-thaw cycles resulted in darker color, and the sensory properties of the product were affected significantly after exceeding three freeze-thaw cycles. Moreover, an increase in the number of freeze-thaw cycles resulted in an upward trend of moisture content for the composite dough, whereas G' initially increased and then decreased. The G″ of the composite dough peaked after the third freeze-thaw cycle. Overall, the composite dough quality significantly deteriorated at the fourth freeze-thaw cycle. There was a significant increase in the freezable water content, the largest modulus of elasticity, and the smallest tan δ. Therefore, the usage of the potato-oat composite dough should not exceed three cycles.

Unveiling the culturable and non-culturable actinobacterial diversity in two macroalgae species from the northern Portuguese coast.

Actinomycetota, associated with macroalgae, remains one of the least explored marine niches. The secondary metabolism of Actinomycetota, the primary microbial source of compounds relevant to biotechnology, continues to drive research into the distribution, dynamics, and metabolome of these microorganisms. In this study, we employed a combination of traditional cultivation and metagenomic analysis to investigate the diversity of Actinomycetota in two native macroalgae species from the Portuguese coast. We obtained and taxonomically identified a collection of 380 strains, which were distributed across 12 orders, 15 families, and 25 genera affiliated with the Actinomycetia class, with Streptomyces making up approximately 60% of the composition. Metagenomic results revealed the presence of Actinomycetota in both Chondrus crispus and Codium tomentosum datasets, with relative abundances of 11% and 2%, respectively. This approach identified 12 orders, 16 families, and 17 genera affiliated with Actinomycetota, with minimal overlap with the cultivation results. Acidimicrobiales emerged as the dominant actinobacterial order in both macroalgae, although no strain affiliated with this taxonomic group was successfully isolated. Our findings suggest that macroalgae represent a hotspot for Actinomycetota. The synergistic use of both culture-dependent and independent approaches proved beneficial, enabling the identification and recovery of not only abundant but also rare taxonomic members.

Development of a "Rigid-Flexible" Structure at the Interface Through Aramid Nanofibers@MXene to Enhance Mechanical Properties of Carbon Fiber/Polyamide Composites.

With the increasing development of nanomaterials, the construction of multiscale nanostructured interphase has emerged as a viable technique to reinforce carbon fiber-reinforced polymer composites. Here, "flexible" aramid nanofibers (ANFs) were first introduced on the surface of carbon fibers (CF) by electrophoretic deposition (EPD), and then "rigid" MXene sheets were grafted by ultrasonic impregnation. This feasible two-step treatment introduces a hierarchical "rigid-flexible" structure at the CF/polyamide (PA) interface. Results showed that this "rigid-flexible" multilayer structure improved the roughness, chemical bonding, mechanical interlocking, and wettability of CF/PA composites. At the same time, the modulus variation between the fiber and the matrix is significantly smoothed due to the increased thickness of the interfacial layer, increasing the payload transfer from the PA matrix to the fiber and decreasing the stress concentration. Compared to the desized CF, the interlaminar shear strength (ILSS) and tensile strength of the modified CF-ANF@MX0.2/PA composite increased by 50.02 and 36.11%, respectively. This innovative interfacial design and feasible treatment method facilitate the construction of firmly interacting interfacial layers in CF/PA composites, offering broad prospects for the production of high-performance CF/PA composites.

Bifunctional ligand Co metal-organic framework derived heterostructured Co-based nanocomposites as oxygen electrocatalysts toward rechargeable zinc-air batteries.

Rational construction of efficient and robust bifunctional oxygen electrocatalysts is key but challenging for the widespread application of rechargeable zinc-air batteries (ZABs). Herein, bifunctional ligand Co metal-organic frameworks were first explored to fabricate a hybrid of heterostructured CoOx/Co nanoparticles anchored on a carbon substrate rich in CoNx sites (CoOx/Co@CoNC) via a one-step pyrolysis method. Such a unique heterostructure provides abundant CoNx and CoOx/Co active sites to drive oxygen reduction reaction (ORR) and oxygen evolution reaction (OER), respectively. Besides, their positive synergies facilitate electron transfer and optimize charge/mass transportation. Consequently, the obtained CoOx/Co@CoNC exhibits a superior ORR activity with a higher half-wave potential of 0.88 V than Pt/C (0.83 V vs. RHE), and a comparable OER performance with an overpotential of 346 mV at 10 mA cm-2 to the commercial RuO2. The assembled ZAB using CoOx/Co@CoNC as a cathode catalyst displays a maximum power density of 168.4 mW cm-2, and excellent charge-discharge cyclability over 250 h at 5 mA cm-2. This work highlights the great potential of heterostructures in oxygen electrocatalysis and provides a new pathway for designing efficient bifunctional oxygen catalysts toward rechargeable ZABs.

Identification of the prognostic value of LACTB2 and its correlation with immune infiltrates in ovarian cancer by integrated bioinformatics analyses.

Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. ß-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC. In this study, high expression of LACTB2 was observed in OC compared with normal controls. Kaplan-Meier Plotter analysis revealed that overexpressed LACTB2 is strongly correlated with poor prognosis. We conducted GO/KEGG analysis to investigate the potential biological function of LACTB2 in OC. GESA analysis showed that LACTB2 was closely related to immune-related pathways. Subsequently, we explored the relationship between LACTB2 and 24 types of immune cells in OC. The results suggested that LACTB2 was positively associated with multiple tumor-infiltrating immune cells. Importantly, LACTB2 may modulate immune cell infiltration in OC to influence prognosis. In conclusion, LACTB2 can be used as a promising prognostic biomarker and immunotherapy target for OC.