Fluoride Hafnium/Zirconium-Softened Nanoprobes for Near-Infrared-IIb and CT Dual-Mode Bioimaging.

Fluoride-based lanthanide-doped nanoparticles (LDNPs) featuring second near-infrared (NIR-II, 1000-1700 nm) downconversion emission for bioimaging have attracted extensive attention. However, conventional LDNPs cannot be degraded and eliminated from organisms because of an inert lattice, which obstructs bioimaging applications. Herein, the core-shell LDNPs of Na3HfF7:Yb,Er@CaF2:Ce,Zr(Hf) [labeled as Zr(Hf)Ce-HC] with pH-selective and tunable degradability were synthesized for dual-modal bioimaging. Notably, the "softening" lattice of the Na3HfF7 matrix and different Zr4+(Hf4+) doping amounts in the shell enable Zr(Hf)Ce-HC with acidity-dependent and tunable degradability. After coating of an optimized Ce3+-doped CaF2:Zr shell, the near-infrared-IIb (NIR-IIb, 1500-1700 nm) luminescence intensity of ZrCe-HC is enhanced by 5.2 times compared with that of Na3HfF7:Yb,Er. The Hf element with high X-ray attenuation allows ZrCe-HC as the contrast agent for computed tomography (CT) bioimaging. The modification of oxidized sodium alginate endows ZrCe-HC with satisfying biocompatibility for NIR-IIb/CT dual-modal bioimaging. These findings would benefit the bioimaging applications of degradable fluoride-based LDNPs.

Carbon nanofiber coated ionic crystal architecture withconfinement effect for high-performance microwave absorption along with high-efficiency water harvesting from air.

Water is considered an effective microwave absorber due to its high transmittance and frequency-dispersive dielectric constant, yet it is challenging to form it into a stable state as an absorber. Herein, we developed a water-containing microwave absorber using chemical vapor deposition (CVD), namely, the bifunctional carbon/NaCl multi-interfaces hybrid with excellent water harvesting and microwave absorption performance. Carbon/NaCl exhibits remarkable water harvesting abilities from air, exceeding 210 % of its weight in 12 h. The development of the hydrophilic/hydrophobic heterojunction interface is responsible for this outstanding performance. Additionally, the interfacial polarization provided by carbon/NaCl, along with the dipole polarization induced by the internally captured water and defects, enhances its microwave absorption. The carbon/NaCl hybrid achieved a minimum reflection loss (RLmin) of -69.62 dB at 17.1 GHz with a thickness of 2.13 mm, and a maximum effective absorption bandwidth (EABmax) of 6.74 GHz at a thickness of 2.5 mm. Compared with raw NaCl (RLmin of -24.5 dB, EABmax of 3.88 GHz), the RLmin and EABmax values of the absorber increased by approximately 2.85 and 1.74 times. These results highlight the potential for bifunctional carbon/NaCl hybrid in applications within extreme environments, presenting a promising avenue for further research and development.

Application of preset coronary artery orifice patch in Bentall surgery.

BACKGROUND: Bentall surgery is the main method for treating aortic root lesions, but traditional Bentall method is very difficult for patients with mild aortic sinus dilation to directly anastomose the coronary artery orifice with graft. CASE PRESENTATION: A 41-year-old man was admitted to hospital after severe chest pain. Computed tomography angiography(CTA)revealed a type A aortic dissection. Echocardiography showed moderate aortic valve regurgitation and an aortic sinus diameter of 38 mm( mm). The patient underwent emergency Bentall surgery (using a preset coronary artery orifice patch), total arch replacement, and implantation of a graft into the descending aorta. Follow-up echocardiography showed the patient cardiac function was good, and there was no residual leakage at the coronary artery orifice. CONCLUSIONS: This method is an alternative to traditional Bentall surgery and is suitable for all aortic root lesions, especially those with mild aortic sinus dilation or concomitant aortic dissection.

Photo-electrochemical sensor based on BiOI/ZnIn2S4 heterojunction for detecting hydrogen peroxide and dopamine.

Photoelectrochemical (PEC) detection as a potential development strategy for hydrogen peroxide and dopamine sensors has received extensive attentions. Herein, BiOI/ZnIn2S4-X (X = n (BiOI)/n(ZnIn2S4)) heterojunction was synthesized using various molar ratios via a two-step method. A series of characterization techniques were employed to analyze the composition, surface structure, valence state, and optical properties of BiOI/ZnIn2S4-X. The results show that BiOI/ZnIn2S4-X perform significantly better than both BiOI and ZnIn2S4. Furthermore, BiOI/ZnIn2S4-9% exhibits superior visible light absorption capacity and photocurrent response among all of the BiOI/ZnIn2S4-X tested. Therefore, a PEC sensor was developed using BiOI/ZnIn2S4-9% for the detection of hydrogen peroxide and dopamine. The linear detection range for hydrogen peroxide spans from to 1 ~ 40,000 µM, with the LOD of 0.036 µM (S/N = 3). For dopamine, the corresponding values are 2 ~ 250 µM for the linear detection range, and 0.017 µM for the LOD, respectively. The sensor exhibits demonstrates excellent stability, reproducibility and resistance to interference, enabling the detection of real samples and thus holds promising application potential.

Facile synthesis of hierarchical core-shell carbon@ZnIn2S4 composite for boosted photothermal-assisted photocatalytic H2 production.

Against the backdrop of energy shortage, hydrogen energy has attracted much attention as a green and clean energy source. In order to explore efficient hydrogen production pathways, we designed a composite photocatalyst with carbon-based core-shell photothermal-assisted photocatalytic system (Carbon@ZnIn2S4, denoted as C@ZIS). The well-designed catalyst C@ZIS composites demonstrated a photocatalytic hydrogen precipitation rate of 2.97 mmol g-1 h-1 even in the absence of the noble metal Pt co-catalyst. The incorporation of carbon-based core-shell photocatalysts into a photocatalytic reaction significantly affects the activity of the reaction by triggering a photothermal effect in the reaction solution. The results of the physicochemical experiments demonstrated that the carbon spheres in C@ZIS composite system could provide a greater number of active sites, thereby accelerating the electron transfer and separation efficiency, and thus enhancing the photocatalytic activity. The study presents an efficacious design concept for the development of efficacious carbon-based core-shell photothermal-assisted photocatalysts, which is anticipated to facilitate the efficient conversion of solar energy to hydrogen energy.

Design and optimization of handheld alloy analysis instrument based on microjoule high pulse repetition frequency LIBS.

We briefly describe the design of a handheld metal detection instrument based on microjoule high repetition frequency laser-induced breakdown spectroscopy. The instrument uses a Raspberry Pi as the control core and a laser with a frequency of 10 kHz and a single pulse energy of 100 µJ as the excitation source. In addition, a mini-putter is built into the instrument to move the laser, allowing the ablation of the sample surface line area without external auxiliary equipment. The excitation-generated plasma radiation is collected by a simple optical path and transmitted directly to the spectrometer. We also constructed and trained a Backpropagation Artificial Neural Network (BP-ANN) model based on 12 different grades of alloys and transplanted the feedback process of the BP-ANN to the Raspberry Pi, which realized the rapid classification of the 12 alloys with >95% classification accuracy on the handheld instrument.

Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles.

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

Enhanced efficiency and stability in the degradation of triazophosphorus pesticides by Al6Si2O13/WO2.72 nanocomposites through synergistic action of S-scheme heterojunction and oxygen vacancies.

The environmental contamination caused by organophosphorus pesticides (for example, triazophos) is an escalating concern. To mitigate this issue, this study introduces a novel Al6Si2O13/WO2.72 (ASO/WO) nanocomposite photocatalyst, which markedly enhances the photocatalytic degradation of triazophos. The optimized nanocomposite material with a 60.0 % ASO loading (60-ASO/WO) achieves a degradation rate of 86.3 % for triazophos within 140.0 min, marginally exceeding 60-ASO/WO3 (72.6 %) and significantly outperforming individual ASO (65.0 %), WO (59.5 %), and WO3 (56.2 %). This catalyst retains 88.9 % of its activity after five cycles, showcasing exceptional efficiency and stability. Additionally, its electrochemical surface area (ECSA, 310.0 cm2), total organic carbon (TOC, removal rate of 73.7 %), photocurrent, and electrochemical impedance are all optimal. X-ray photoelectron spectroscopy (XPS), electron paramagnetic resonance (EPR), and theoretical calculations elucidate the critical role of oxygen vacancies and the S-scheme heterojunction in augmenting charge separation and photocatalytic performance, corroborating the synergistic effect of oxygen defects and the S-scheme. While individual factors can enhance photocatalytic activity, their combination results in a more pronounced effect. Liquid chromatography-mass spectrometry (LCMS) identifies the principal degradation intermediates, including 1-phenyl-3-hydroxy-1, 2, 4-triazole, diethyl thiophosphate, and 3, 5, 6-trichloro-2-pyridinol, underscoring the material's potential in environmental remediation.

Identification of key physicochemical properties and volatile flavor compounds for the sensory formation of roasted tilapia.

Tilapia is suitable for industrial roasting production because of its good flavor and processing adaptability. In this study, the key physicochemical properties and volatile compounds for sensory formation of roasted tilapia were identified after roasting condition optimization. The highest sensory score was obtained at 215 °C, 45 min, and 4% oil. During roasting, the a*, b*, hardness, chewiness, and oxidation of proteins and lipids significantly increased, the moisture content decreased, and the myofibrillar protein aggregation was observed by scanning electron microscope. After identification and quantification by headspace-gas chromatography-ion mobility spectrometry, 10 compounds with odor active value ≥1 were selected as characteristic flavor compounds. The correlation network indicated that the sensory formation mainly resulted from Maillard reaction, myofibrillar protein aggregation, and improvement of pleasant volatile flavor compounds induced by oxidation of proteins and lipids and water loss. This study provides an important theoretical basis and technical support for roasted tilapia production.

Hollow CoP-FeP cubes decorating carbon nanotubes heterostructural electrocatalyst for enhancing the bidirectional conversion of polysulfides in advanced lithium-sulfur batteries.

The sluggish redox reaction kinetics and "shuttle effect" of lithium polysulfides (LPSs) impede the advancement of high-performance lithium-sulfur batteries (LSBs). Transition metal phosphides exhibit distinctive polarity, metallic properties, and tunable electron configuration, thereby demonstrating enhanced adsorption and electrocatalytic capabilities towards LPSs. Consequently, they are regarded as exceptional sulfur hosts for LSBs. Moreover, the introduction of a heterogeneous structure can enhance reaction kinetics and expedite the transport of electrons/ions. In this study, a composite of hollow CoP-FeP cubes with heterostructure modified carbon nanotube (CoFeP-CNTs) was fabricated and utilized as sulfur host in advanced LSBs. The presence of carbon nanotubes (CNTs) facilitates enhanced electron and Li+ transport. Meanwhile, the active sites within the heterogeneous interface of CoP-FeP suppress the "shuttle effect" and enhance the conversion kinetics of LPSs. Therefore, the CoFeP-CNTs/S electrode exhibited exceptional cycling stability and demonstrated a capacity attenuation of merely 0.051 % per cycle over 600 cycles at 1C. This study presents a highly effective tactic for synthesizing dual-acting transition metal phosphides with heterostructure, which will play a pivotal role in advancing the development of efficient LSBs.

Nano-photosensitizers with gallic acid-involved Fe-O-Cu "electronic storage station" bridging ligand-to-metal charge transfer for efficient catalytic theranostics.

NH2-MIL-88B (Fe) (MOF) is a promising photocatalytic material for antitumor therapy because of its distinctive electronic structure. However, inadequate separation of photo-generated electrons and slow reaction rate in low/high-valence iron (Fe) cycles limit their clinical application. In the present study, "electronic storage station" as a ligand-to-metal charge transfer bridge bond was constructed to inhibit recombination of electron/hole under 650 nm laser irradiation. Cupric (Cu) ions and gallic acid (GA) were self-assembled into a MOF (denoted as CGMOF) to create an FeO(GA)Cu bridge bond. GA, characterized by robust electron delocalization and abundant electron-donating groups, significantly enhances electron transfer efficiency for photodynamic therapy (PDT). CGMOF can respond to endogenous glutathione and release cuprous ions, accelerating the iron ion/ferrous ion cycles for chemodynamic therapy (CDT). The released Fe species can serve as T2-weighted magnetic resonance imaging contrast. Extended X-ray absorption fine structure spectra confirmed the presence of GA-containing FeOCu bonds in CGMOF. Furthermore, a series of photo-electrochemical tests confirmed that the formation of FeO(GA)Cu bond prominently elevated the redox capacity and increased the carrier density of CGMOF by 2.74-fold compared to that of MOF. In addition, cinnamaldehyde was grafted onto CGMOF for tumor-responsive hydrogen peroxide self-supply. Concurrently, hyaluronic acid was surface-modified to achieve the targeted delivery of nano-photosensitizers. In summary, this study presents an innovative approach for engineering Fe-based metal-organic frameworks for synergetic PDT/CDT applications.

Robust bifunctionality in an oxygen electrode via core-shell heterostructure construction.

A Co-CoSe core-shell heterostructure encapsulated into nitrogen-doped carbon nanotubes enables superior zinc air battery performance (172 mW cm-2) and stability (970 h). The enhanced bifunctionality and stability originates from the modulated d band center and confinement effect, respectively.

Effect of Inverse Solutions, Connectivity Measures, and Node Sizes on EEG Source Network: A Simultaneous EEG Study.

Brain network provides an essential perspective for studying normal and pathological brain activities. Reconstructing the brain network in the source space becomes more needed, for example, as a target in non-invasive neuromodulation. Precise estimating source activities from the scalp EEG is still challenging because it is an ill-posed question and because of the volume conduction effect. There is no consensus on how to reconstruct the EEG source network. This study uses simultaneous scalp EEG and stereo-EEG to investigate the effect of inverse solutions, connectivity measures, and node sizes on the reconstruction of the source network. We evaluated the performance of different methods on both source activity and network. Numerical simulation was also carried out for comparison. The weighted phase-lag index (wPLI) method achieved significantly better performance on the reconstructed networks in source space than five other connectivity measures (directed transfer function (DTF), partial directed coherence (PDC), efficient effective connectivity (EEC), Pearson correlation coefficient (PCC), and amplitude envelope correlation (AEC)). There is no significant difference between the inverse solutions (standardized low-resolution brain electromagnetic tomography (sLORETA), weighted minimum norm estimate (wMNE), and linearly constrained minimum variance (LCMV) beamforming) on the reconstructed source networks. The source network based on signal phases can fit intracranial activities better than signal waveform properties or causality. Our study provides a basis for reconstructing source space networks from scalp EEG, especially for future neuromodulation research.

The m6A-ncRNAs axis in diabetes complications: novel mechanism and therapeutic potential.

Diabetes, a multifaceted metabolic disorder, poses a significant global health burden with its increasing prevalence and associated complications, such as diabetic nephropathy, diabetic retinopathy, diabetic cardiomyopathy, and diabetic angiopathy. Recent studies have highlighted the intricate interplay between N6-methyladenosine (m6A) and non-coding RNAs (ncRNAs) in key pathways implicated in these diabetes complications, like cell apoptosis, oxidative stress, and inflammation. Thus, understanding the mechanistic insights into how m6A dysregulation impacts the expression and function of ncRNAs opens new avenues for therapeutic interventions targeting the m6A-ncRNAs axis in diabetes complications. This review explores the regulatory roles of m6A modifications and ncRNAs, and stresses the role of the m6A-ncRNA axis in diabetes complications, providing a therapeutic potential for these diseases.

Towards metal selenides: a promising anode for sodium-ion batteries.

Metal selenides have garnered significant attention as promising anode materials for sodium-ion batteries, thanks to their high theoretical capacity, excellent conductivity, and natural abundance. However, their potential is hampered by disappointing capacity retention and unsatisfactory lifespan, primarily attributed to volume expansion and unwanted structural collapse resulting from the insertion and extraction of relatively large Na+ ions during the charge and discharge processes. This feature article provides a brief overview of our endeavors to address the challenges associated with metal selenide-based anode materials, aiming to achieve high-performance electrode materials for sodium-ion batteries. Our strategy encompasses nanostructure design, materials composite engineering, heteroatoms doping, and topography and interface engineering. Additionally, future research directions are also outlined.

Research on the generation and annotation method of thin section images of tight oil reservoir based on deep learning.

The cast thin sections of tight oil reservoirs contain important parameters such as rock mineral composition and content, porosity, permeability and stratigraphic characteristics, which are of great significance for reservoir evaluation. The use of deep learning technology for intelligent identification of thin section images is a development trend of mineral identification. However, the difficulty of making cast thin sections, the complexity of the making process and the high cost of thin section annotation have led to a lack of cast thin section images, which cannot meet the training requirements of deep learning image recognition models. In order to increase the sample size and improve the training effect of deep learning model, we proposed a generation and annotation method of thin section images of tight oil reservoir based on deep learning, by taking Fuyu reservoir in Sanzhao Sag as the target area. Firstly, the Augmentor strategy space was used to preliminarily augment the original images while preserving the original image features to meet the requirements of the model. Secondly, the category attention mechanism was added to the original StyleGAN network to avoid the influence of the uneven number of components in thin sections on the quality of the generated images. Then, the SALM annotation module was designed to achieve semi-automatic annotation of the generated images. Finally, experiments on image sharpness, distortion, standard accuracy and annotation efficiency were designed to verify the advantages of the method in image quality and annotation efficiency.

A study on the factors influencing the vulnerability of women of childbearing age to health poverty in rural western China.

The health of women of childbearing age in rural areas is crucial for the development of individuals, families, and society. Research on the identification and influencing factors of health vulnerability in impoverished and disadvantaged groups is important for adjusting and implementing health poverty alleviation policies. However, there is limited research on the health vulnerability of women of childbearing age in rural Western China. Based on panel data from the Rural Residents' Family Health Status Survey in 2019 and 2022, the vulnerability to health poverty of women of childbearing age in rural areas was constructed using the three-stage feasible generalized least squares method. Variables from four dimensions-physical capital, financial capital, social capital, and human capital-were included in the sustainable livelihood analysis framework for analysis. The Tobit model was used to analyze the influencing factors of vulnerability to health poverty among women of childbearing age in rural Western China, and the contribution rates of various factors were studied using the Shapley value decomposition method. In 2019 and 2022, under the poverty line standards of $1.90 and $2.15, respectively, the vulnerability to health poverty among rural women of childbearing age exceeded 20%. Tobit regression analysis revealed that the type of drinking water being well water significantly increased the vulnerability to health poverty of rural women of childbearing age (P < 0.05), whereas the separation of housing and kitchen, registered poor households, household loans, annual per capita household income, expenditures on social interactions, educational level, self-assessed health status, respondent age, and the utilization of hospital services significantly reduced the vulnerability to health poverty of rural women of childbearing age (P < 0.05). Shapley's decomposition shows that annual per capita household income, expenditures on social interactions, respondent age, and household loans are the factors contributing most to the vulnerability to health poverty of rural women of childbearing age, while other variables have a smaller contribution rate. The health poverty situation of women of childbearing age in rural Western China is not optimistic. Preintervention for health poverty should be strengthened among rural women of childbearing age, early warning mechanisms for the risk of falling back into poverty due to illness should be established, the precise identification of highly vulnerable rural women of childbearing age should be improved, and the medical insurance system for rural women of childbearing age should be enhanced to help improve their current health poverty situation.

Abundant Edge Active Sites-Modified High-Crystalline g-C3N5 for Hydrogen Peroxide Production from Pure-Water via a Quasi-Homogeneous Photocatalytic Process.

Ultrathin carbon nitride pioneered a paradigm that facilitates effective charge separation and acceleration of rapid charge migration. Nevertheless, the dissociation process confronts a disruption owing to the proclivity of carbon nitride to reaggregate, thereby impeding the optimal utilization of active sites. In response to this exigency, the adoption of a synthesis methodology featuring alkaline potassium salt-assisted molten salt synthesis is advocated in this work, aiming to craft a nitrogenated graphitic carbon nitride (g-C3N5) photocatalyst characterized by thin layer and hydrophilicity, which not only amplifies the degree of crystallization of g-C3N5 but also introduces a plethora of abundant edge active sites, engendering a quasi-homogeneous photocatalytic system. Under visible light irradiation, the ultra-high H2O2 production rate of this modified high-crystalline g-C3N5 in pure water attains 151.14 µm h-1. This groundbreaking study offers a novel perspective for the innovative design of highly efficient photocatalysts with a quasi-homogeneous photocatalytic system.

A superior zinc-air battery performance achieved by CoO/Fe3O4 heterostructured nanosheets.

CoO/Fe3O4 nanosheets exhibit a superior rechargeable zinc-air battery (ZAB) performance of 276 mW cm-2 and stability over 600 h. The all-solid-state ZAB also affords a high power density of 107 mW cm-2.

Novel insight into the formation and improvement mechanism of physical property in fermented tilapia sausage by cooperative fermentation of newly isolated lactic acid bacteria based on microbial contribution.

Single starter can hardly elevate the gel property of fermented freshwater fish sausage. In this work, in order to improve the physical properties of tilapia sausage, two newly isolated strains of lactic acid bacteria (LAB), Latilactobacillus sakei and Pediococcus acidilactici were used for cooperative fermentation of tilapia sausage, followed by the revelation of their formation mechanisms during cooperative fermentation and their improvement mechanisms after comparison with natural fermentation. Both strains, especially L. sakei possessed good growth, acidification ability, and salt tolerance. The gel strength, hardness, springiness, chewiness, whiteness, acidification, and total plate count significantly elevated during cooperative fermentation with starters. Pediococcus, Acinetobacter, and Macrococcus were abundant before fermentation, while Latilactobacillus quickly occupied the dominant position after fermentation for 18-45 h with the relative abundance over 51.5 %. The influence of each genus on the physical properties was calculated through the time-dimension and group-dimension correlation networks. The results suggested that the increase of Latilactobacillus due to the good growth and metabolism of L. sakei contributed the most to the formation and improvement of gel strength, texture properties, color, acidification, and food safety of tilapia sausage after cooperative fermentation. This study provides a novel analysis method to quantitatively evaluate the microbial contribution on the changes of various properties. The cooperative fermentation of LAB can be used for tilapia sausage fermentation to improve its physical properties.