Single-Particle Imaging Photoinduced Charge Transfer of Ferroelectric Polarized Heterostructures for Photocatalysis.

Piezoelectric-assisted photocatalysis has a huge potential in solving the energy shortage and environmental pollution problems, and imaging their detailed charge-transfer process can provide in-depth understanding for the development of high-active piezo-photocatalysts; however, it is still challenging. Herein, topotactic heterostructures of TiO2@BaTiO3 (TO@BTO-S) were constructed by the epitaxial growth of ferroelectric BaTiO3 mesocrystals on TiO2-{001} facets, resulting in a ferroelectric photocatalyst with a polarization orientation on the surface. Notably, the photoinduced charge transfer in ferroelectric TiO2@BaTiO3 was accurately monitored and directly visualized at the single-particle level by the advanced photoluminescence (PL) imaging microscopy systems. The longer PL lifetime of TO@BTO-S demonstrated the efficient charge separation caused by a built-in electric field, which is constructed by the polarization orientation of BaTiO3 mesocrystals. Therefore, the TO@BTO-S heterostructure exhibits efficient piezoelectric-assisted photocatalytic pure water splitting, which is 290 times higher than photocatalysis. This work revealed time/spatial-resolved photoinduced charge transfer in piezoelectric assistance photocatalysts at the single-particle level and demonstrated the great role of polarization orientation in promoting charge transfer for photocatalysis.

Tailoring Copper Single-Atoms-Stabilized Metastable Transition-Metal-Dichalcogenides for Sustainable Hydrogen Production.

Unconventional 1T' phase transition metal dichalcogenides (TMDs) show great potential for hydrogen evolution reaction (HER). However, they are susceptible to transitioning into the stable 2H phase, which reduces their catalytic activity and stability. Herein, we present a scalable approach for designing thermally stable 1T'-TMDs hollow structures (HSs) by etching Cu1.94S templates from pre-synthesized Cu1.94S@TMDs heterostructures, including 1T'-MoS2, MoSe2, WS2, and WSe2 HSs. Furthermore, taking 1T'-MoS2 HSs as an example, the etched Cu ions can be firmly adsorbed on their surface in the form of single atoms (SAs) through Cu-S bonds, thereby elevating the phase transition temperature from 149 ºC to 373 ºC. Due to the advantages conferred by the 1T' phase, hollow structure, and synergistic effect between Cu SAs and 1T'-MoS2 supports, the fabricated 1T'-MoS2 HSs demonstrate superior HER performance. Notably, their high-phase stability enables continuous operation of designed 1T'-MoS2 HSs for up to 200 hours at an ampere-level current density without significant activity decay. This work provides a universal method for synthesizing highly stable 1T'-TMDs electrocatalysts, with a particular focus on the relationship between their phase and catalytic stability.

The dual role of ribosomal protein SA in pathogen infection: the key role of structure and localization.

Ribosomal protein SA (RPSA) plays multiple roles in cells, including ribosomal biogenesis and translation, cellular migration, and cytoskeleton reorganization. RPSA is crucial in the process of pathogen infection. Extensive research has examined RPSA's role in pathogen adhesion and invasion, but its broader functions, particularly its anti-infective capabilities, have garnered increasing attention in recent years. This dual role is closely related to its structural domains, which influence its localization and function. This review summarizes key research findings concerning the functional domains of RPSA and analyzes the relationship between its membrane localization and structural domains. Additionally, the functional implications of RPSA are categorized based on its different localizations during pathogen infection. Specifically, when RPSA is located on the cell surface, it promotes pathogen adhesion and invasion of host cells; conversely, when RPSA is located intracellularly, it exhibits anti-infective properties. Overall, RPSA shows a dual nature, both in facilitating pathogen invasion of the host and in possessing the ability to resist pathogen infection. This review comprehensively examines the dual role of RPSA in pathogen infection by analyzing its structural domains, localization, and interactions with cellular and pathogen molecules. Our aim is to update and deepen researchers' understanding of the various functions of RPSA during pathogen infection.

Relations between dimensions of self-perceptions and academic achievement in Chinese children: A cross-lagged panel analysis.

The goal of the present study was to examine the associations between different dimensions of self-perceptions and academic achievement in Chinese children. Participants were 604 children in Grades 4-7 attending primary and middle schools in mainland China (342 boys, 262 girls; Mage = 11.25 years). Measures of children's self-perceptions and academic achievement were collected via self-reports and school records at two time points over one academic year. Results from cross-lagged panel analysis indicated that after controlling for the effects of gender, grade, and stabilities, Time 1 perceived scholastic competence positively predicted Time 2 academic achievement (ß = .08, p < .05), and Time 1 academic achievement predicted Time 2 perceived scholastic competence (ß = .10, p < .05). Time 1 perceived athletic competence negatively predicted Time 2 academic achievement (ß = -.08, p < .01). The findings provide evidence that self-perceptions have different facets and are differently associated with academic achievement and emphasize the reciprocal predictive relations between perceived scholastic competence and academic achievement and the negative impact of perceived athletic competence self-perception on academic achievement. The implications of these results are discussed in the context of self-development and academic performance within Chinese culture, as well as their educational implications for school practices. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Effectiveness of repetitive transcranial magnetic stimulation combined with intelligent Gait-Adaptability Training in improving lower limb function and brain symmetry after subacute stroke: a preliminary study.

OBJECTIVES: Persistent lower limb dysfunction is a major challenge in post-stroke recovery. Repetitive transcranial magnetic stimulation is recognized for addressing post-stroke motor deficits. Our study explores the efficacy of combining rTMS with gait-adaptive training to enhance lower limb function and regulatory mechanisms in subacute stroke. MATERIALS AND METHODS: This randomized controlled trial enrolled 27 patients with subacute hemiparesis, dividing them into experimental and control groups. Both groups underwent gait-adaptability training 5 times/week for 4 weeks, with the experimental group receiving daily low-frequency transcranial magnetic stimulation before training. Primary outcomes included the pairwise derived brain symmetry index, lower-extremity Fugl-Meyer Assessment, 10-meter walk test, and Berg Balance Scale. Assessments occurred before and after the four-week intervention. RESULTS: The experimental and control groups showed significant improvements in the Fugl-Meyer Assessment, 10-meter walk test, and Berg Balance Scale after the 4-week intervention compared to baseline (all p<0.05). However, the experimental group demonstrated significantly greater improvements compared to the control group in the Fugl-Meyer Assessment (p=0.024) and the 10-meter walk test (p=0.033). Additionally, the experimental group exhibited a more pronounced decrease in the pairwise derived brain symmetry index (p=0.026) compared to the control group. Within the experimental group, the cortical subgroup's pairwise derived brain symmetry index was significantly lower than that of the control group (p=0.006). CONCLUSIONS: Combining low-frequency transcranial magnetic stimulation with Gait-Adaptive Training effectively enhances lower limb function and Regulatory mechanisms of the cerebral hemisphere in subacute stroke recovery, and it can provide rapid and effective rehabilitation effect compared with gait adaptation training alone.

Peptide-based supramolecular hydrogels and their biotherapeutic applications.

In recent years, supramolecular hydrogels have made groundbreaking research progress in biomedical fields such as drug delivery, biosensing, imaging analysis, and tissue engineering. Peptides, with their unique characteristics of facile preparation, low immunogenicity and easy biodegradability, are commonly used as building blocks of supramolecular hydrogels. Peptide-based supramolecular hydrogels loaded with drugs, prepared via physical means or covalent crosslinking, exhibit unique three-dimensional network structures and strong water retention capacities. These properties enhance drug bioavailability and reduce side effects, enabling drug accumulation and responsive release at disease sites, significantly improving the therapeutic efficacy. Here, we review recent advancements in peptide-based supramolecular hydrogels and their biotherapeutic applications, including chemotherapy, photothermal therapy, photodynamic therapy, immunotherapy, gene therapy, antibacterial and anti-inflammatory treatments, and other biological applications. This review aims to provide new inspiration for the development of biomaterials in the therapeutic field and provide more personalized options for disease treatment. Additionally, challenges and limitations in this field are briefly discussed.

Polycyclic polyprenylated acylphloroglucinols from the pericarps of Garcinia multiflora champ. ex Benth. with cytotoxic property.

The phytochemical investigation on the pericarps of Garcinia multiflora resulted in the isolation of 12 previously undescribed polycyclic polyprenylated acylphloroglucinols (PPAPs, 1-12) with a variety of skeletons. Their structures were determined by comprehensive spectroscopic analyses, ECD calculations, and single-crystal X-ray diffraction. Compounds 6-9 possess a rare bicyclo[4.3.1]decane skeleton. Additionally, the anti-tumor activity of the 12 isolates was evaluated. The results indicated that compounds 5, 9, and 12 exhibited significant cytotoxicity in a wide range of cancer cell lines, including the human breast cancer MDA-MB-231 cells, human lung cancer A549 cells, human colon cancer SW480 cells and human ovarian cancer HEY cells. Further studies indicated that compound 5 induced cell cycle arrest and apoptosis, to inhibit the growth of MDA-MB-231 cells. Taken together, these findings expand the chemical diversity of PPAPs and further demonstrate the potential of PPAPs as candidates for cancer treatment.

Epigenetic Dynamics in Meniscus Cell Migration and its Zonal Dependency in Response to Inflammatory Conditions: Implications for Regeneration Strategies.

Meniscus injuries pose significant challenges in clinical settings, primarily due to the intrinsic heterogeneity of the tissue and the limited efficacy of current treatments. Endogenous cell migration is crucial for the healing process, yet the regulatory mechanisms of meniscus cell migration and its zonal dependency within the meniscus are not fully understood. Thus, this study investigates the role of epigenetic mechanisms in governing meniscus cell migration under inflammatory conditions, with a focus on their implications for injury healing and regeneration. Here, we discovered that a proinflammatory cytokine, TNF-α treatment significantly impedes the migration speed of inner meniscus cells, while outer meniscus cells are unaffected, underscoring a zonal-dependent response within the meniscus. Our analysis identified distinct histone modification patterns and chromatin dynamics between inner and outer meniscus cells during migration, highlighting the necessity to consider these zonal-dependent properties in devising repair strategies. Specifically, we found that TNF-α differentially influences histone modifications, particularly H3K27me3, between the two cell types. Transcriptome analysis further revealed that TNF-α treatment induces substantial gene expression changes, with inner meniscus cells exhibiting more pronounced alterations than outer cells. Gene cluster analysis pointed to distinct responses in chromatin remodeling, extracellular matrix assembly, and wound healing processes between the zonal cell populations. Moreover, we identified potential therapeutic targets by employing existing epigenetic drugs, GSKJ4 (a histone demethylase inhibitor) and C646 (a histone acetyltransferase inhibitor), to successfully restore the migration speed of inner meniscus cells under inflammatory conditions. This highlights their potential utility in treating meniscus tear injuries. Overall, our findings elucidate the intricate interplay between epigenetic mechanisms and meniscus cell migration, along with its meniscus zonal dependency. This study provides insights into potential targets for enhancing meniscus repair and regeneration, which may lead to improved clinical outcomes for patients with meniscus injuries and osteoarthritis.

Atractylenolide II combined with Interferon-γ synergistically ameliorates colorectal cancer progression in vivo and in vitro by blocking the NF-kB p65/PD-L1 pathway.

Purpose: Atractylodes macrocephala Koidz is a widely used classical traditional Chinese herbal medicine, that has shown remarkable efficacy in cancers. Colorectal cancer (CRC) is the most common malignant tumor globally. Interferon (IFN)-γ, a prominent cytokine involved in anti-tumor immunity that has cytostatic, pro-apoptotic, and immune-stimulatory properties for the detection and removal of transformed cells. Atractylenolides-II (AT-II) belongs to the lactone compound that is derived from Atractylodes macrocephala Koidz with anti-cancer activity. However, whether AT-II combined with IFN-γ modulates CRC progression and the underlying mechanisms remain unclear. The present study aimed to elucidate the efficacy and pharmaceutical mechanism of action of AT-II combined with IFN-γ synergistically against CRC by regulating the NF-kB p65/PD-L1 signaling pathway. Methods: HT29 and HCT15 cells were treated with AT-II and IFN-γ alone or in combination and cell viability, migration, and invasion were then analyzed using Cell Counting Kit-8 (CCK-8) and Transwell assays, respectively. Furthermore, the underlying mechanism was investigated through western blot assay. The role of AT-II combined with IFN-γ on tumor growth and lung metastases was estimated in vivo. Finally, the population of lymphocytes in tumor tissues of lung metastatic C57BL/6 mice and the plasma cytokine levels were confirmed by flow cytometry and enzyme-linked immunosorbent assay (ELISA). Results: AT-II or the combination IFN-γ significantly inhibited the growth and migration abilities of CRC cells in vitro and in vivo. The biological mechanisms behind the beneficial effects of AT-II combined with IFN-γ were also measured and inhibition of p38 MAPK, FAK, Wnt/ß-catenin, Smad, and NF-kB p65/PD-L1 pathways was observed. Moreover, AT-II combined with IFN-γ significantly inhibited HCT15 xenograft tumor growth and lung metastases in C57BL/6 mice, which was accompanied by lymphocyte infiltration into the tumor tissues and inflammatory response inactivation. Conclusions: The results showed that the AT-II in combination with IFN-γ could be used as a potential strategy for tumor immunotherapy in CRC. More importantly, the mechanism by which AT-II suppressed CRC progressions was by inhibiting the NF-kB p65/PD-L1 signal pathway.

Inhibition of PLA2G4A attenuated valproic acid- induced lysosomal membrane permeabilization and restored impaired autophagic flux: Implications for hepatotoxicity.

Valproic acid (VPA) has broad efficacy against several seizures but causes liver injury limiting its prolonged clinical use. Some studies have demonstrated that VPA-induced hepatotoxicity is characterized by microvesicular hepatic steatosis. However, novel detailed mechanisms to explain VPA-induced hepatic steatosis and experimentally rigorously validated protective agents are still lacking. In this study, 8-week-old C57BL/6J mice were gavaged with VPA (500 mg/kg/d) for 4 weeks to establish an in vivo model of VPA-induced chronic liver injury. Quantitative proteomic and non-targeted lipidomic analyses were performed to explore the underlying mechanisms of VPA-induced hepatotoxicity. As a result, VPA-induced hepatotoxicity is associated with impaired autophagic flux, which is attributed to lysosomal dysfunction. Further studies revealed that VPA-induced lysosomal membrane permeabilization (LMP), allows soluble lysosomal enzymes to leak into the cytosol, which subsequently led to impaired lysosomal acidification. A lower abundance of glycerophospholipids and an increased abundance of lysophospholipids in liver tissues of mice in the VPA group strongly indicated that VPA-induced LMP may be mediated by the activation of phospholipase PLA2G4A. Metformin (Met) acted as a potential protective agent attenuating VPA-induced liver dysfunction and excessive lipid accumulation. Molecular docking and cellular thermal shift assays demonstrated that Met inhibited the activity of PLA2G4A by directly binding to it, thereby ameliorating VPA-induced LMP and autophagic flux impairment. In conclusion, this study highlights the therapeutic potential of targeting PLA2G4A-mediated lysosomal dysfunction in VPA-induced hepatotoxicity.

A few-shot identification method for stochastic dynamical systems based on residual multipeaks adaptive sampling.

Neural networks are popular data-driven modeling tools that come with high data collection costs. This paper proposes a residual-based multipeaks adaptive sampling (RMAS) algorithm, which can reduce the demand for a large number of samples in the identification of stochastic dynamical systems. Compared to classical residual-based sampling algorithms, the RMAS algorithm achieves higher system identification accuracy without relying on any hyperparameters. Subsequently, combining the RMAS algorithm and neural network, a few-shot identification (FSI) method for stochastic dynamical systems is proposed, which is applied to the identification of a vegetation biomass change model and the Rayleigh-Van der Pol impact vibration model. We show that the RMAS algorithm modifies residual-based sampling algorithms and, in particular, reduces the system identification error by 76% with the same sample sizes. Moreover, the surrogate model accurately predicts the first escape probability density function and the P bifurcation behavior in the systems, with the error of less than 1.59×10-2. Finally, the robustness of the FSI method is validated.

Deep Learning-Based State-of-Health Estimation of Proton-Exchange Membrane Fuel Cells under Dynamic Operation Conditions.

Proton-exchange membrane fuel cells (PEMFCs) play a crucial role in the transition to sustainable energy systems. Accurately estimating the state of health (SOH) of PEMFCs under dynamic operating conditions is essential for ensuring their reliability and longevity. This study designed dynamic operating conditions for fuel cells and conducted durability tests using both crack-free fuel cells and fuel cells with uniform cracks. Utilizing deep learning methods, we estimated the SOH of PEMFCs under dynamic operating conditions and investigated the performance of long short-term memory networks (LSTM), gated recurrent units (GRU), temporal convolutional networks (TCN), and transformer models for SOH estimation tasks. We also explored the impact of different sampling intervals and training set proportions on the predictive performance of these models. The results indicated that shorter sampling intervals and higher training set proportions significantly improve prediction accuracy. The study also highlighted the challenges posed by the presence of cracks. Cracks cause more frequent and intense voltage fluctuations, making it more difficult for the models to accurately capture the dynamic behavior of PEMFCs, thereby increasing prediction errors. However, under crack-free conditions, due to more stable voltage output, all models showed improved predictive performance. Finally, this study underscores the effectiveness of deep learning models in estimating the SOH of PEMFCs and provides insights into optimizing sampling and training strategies to enhance prediction accuracy. The findings make a significant contribution to the development of more reliable and efficient PEMFC systems for sustainable energy applications.

Effects of combining rTMs and augmented reality gait adaptive training on walking function of patients with stroke based on three-dimensional gait analysis and sEMG: a randomized controlled trial.

BACKGROUND: Augmented reality gait adaptive training (ARGAT) and repetitive transcranial magnetic stimulation (rTMS) have both demonstrated efficacy in improving lower limb motor function in survivors of stroke. PURPOSE: To investigate the effects of combining rTMS and ARGAT on motor function in survivors of stroke. METHODS: The experimental group received a combination of rTMS and ARGAT, while the control group received ARGAT alone. The interventions comprised a total of 20 sessions, conducted over four weeks with five consecutive daily sessions. Outcome measures included three-dimensional gait analysis (3DGA), surface electromyography (sEMG), Fugl-Meyer assessment for the lower extremity (FMA-LE), and the Berg Balance Scale (BBS). RESULTS: Following the intervention, both groups showed significant improvements in walking speed, symmetry index, affected step length, affected stride length, FMA-LE, and BBS scores (p < .05). Furthermore, the experimental group demonstrated greater improvements in walking speed (F = 4.58, p = .040), cadence (F = 5.67, p = .023), affected step length (F = 5.79, p = .022), affected stride length (F = 4.84, p = .035), FMA-LE (Z = 2.43, p = .019), and BBS (F = 4.76, p = .036) compared to the control group. The experimental group demonstrated a significant improvement in the co-contraction index (CCI) of the knee joint (F = 14.88, p < .001), a change not observed in the control group (F = 2.16, p = .151). However, neither group showed significant alterations in CCI of the ankle joint (F = 1.58, p = .218), step width (F = 0.24, p = .630), unaffected step length (F = 0.22, p = .641), or unaffected stride length (F = 2.99, p = .093). CONCLUSION: The combination of low-frequency rTMS and ARGAT demonstrated superior effects on motor function recovery compared to ARGAT alone in survivors of stroke.

A unified framework to control estimation error in reinforcement learning.

In reinforcement learning, accurate estimation of the Q-value is crucial for acquiring an optimal policy. However, current successful Actor-Critic methods still suffer from underestimation bias. Additionally, there exists a significant estimation bias, regardless of the method used in the critic initialization phase. To address these challenges and reduce estimation errors, we propose CEILING, a simple and compatible framework that can be applied to any model-free Actor-Critic methods. The core idea of CEILING is to evaluate the superiority of different estimation methods by incorporating the true Q-value, calculated using Monte Carlo, during the training process. CEILING consists of two implementations: the Direct Picking Operation and the Exponential Softmax Weighting Operation. The first implementation selects the optimal method at each fixed step and applies it in subsequent interactions until the next selection. The other implementation utilizes a nonlinear weighting function that dynamically assigns larger weights to more accurate methods. Theoretically, we demonstrate that our methods provide a more accurate and stable Q-value estimation. Additionally, we analyze the upper bound of the estimation bias. Based on two implementations, we propose specific algorithms and their variants, and our methods achieve superior performance on several benchmark tasks.

Enzyme-Enabled Droplet Biobattery for Powering Synthetic Tissues.

Enzyme-enabled biobatteries are promising green options to power the next-generation of bioelectronics and implantable medical devices. However, existing power sources based on enzymatic biofuel chemistry exhibit limited scale-down feasibility due to the solid and bulky battery structures. Therefore, miniature and soft alternatives are needed for integration with implants and tissues. Here, a biobattery built from nanolitre droplets, fuelled by the enzyme-enabled oxidation of reduced nicotinamide adenine dinucleotide, generates electrical outputs and powers ion fluxes in droplet networks. Optimization of the droplet biobattery components ensures a stable output current of ~13,000 pA for over 24 h, representing a more than 600-fold increase in output over previous approaches, including light-driven processes. The enzyme-enabled droplet biobattery opens new avenues in bioelectronics and bioiontronics, exemplified by tasks such as the ability to drive chemical signal transmission in integrated synthetic tissues.

Metabolomic Profiling Reveals the Anti-Herbivore Mechanisms of Rice (Oryza sativa).

The use of secondary metabolites of rice to control pests has become a research hotspot, but little is known about the mechanism of rice self-resistance. In this study, metabolomics analysis was performed on two groups of rice (T1, with insect pests; T2, without pests), indicating that fatty acids, alkaloids, and phenolic acids were significantly up-regulated in T1. The up-regulated metabolites (p-value < 0.1) were enriched in linoleic acid metabolism, terpene, piperidine, and pyridine alkaloid biosynthesis, α-linolenic acid metabolism, and tryptophan metabolism. Six significantly up-regulated differential metabolites in T1 were screened out: N-trans-feruloyl-3-methoxytyramine (1), N-trans-feruloyltyramine (2), N-trans-p-coumaroyltyramine (3), N-cis-feruloyltyramine (4), N-phenylacetyl-L-glutamine (5), and benzamide (6). The insect growth inhibitory activities of these six different metabolites were determined, and the results show that compound 1 had the highest activity, which significantly inhibited the growth of Chilo suppressalis by 59.63%. Compounds 2-4 also showed a good inhibitory effect on the growth of Chilo suppressalis, while the other compounds had no significant effect. RNA-seq analyses showed that larval exposure to compound 1 up-regulated the genes that were significantly enriched in ribosome biogenesis in eukaryotes, the cell cycle, ribosomes, and other pathways. The down-regulated genes were significantly enriched in metabolic pathways, oxidative phosphorylation, the citrate cycle (TCA cycle), and other pathways. Eighteen up-regulated genes and fifteen down-regulated genes from the above significantly enriched pathways were screened out and verified by real-time quantitative PCR. The activities of detoxification enzymes (glutathione S-transferase (GST); UDP-glucuronosyltransferase (UGT); and carboxylesterase (CarE)) under larval exposure to compound 1 were measured, which indicated that the activity of GST was significantly inhibited by compound 1, while the activities of the UGT and CarE enzymes did not significantly change. As determined by UPLC-MS, the contents of compound 1 in the T1 and T2 groups were 8.55 ng/g and 0.53 ng/g, respectively, which indicated that pest insects significantly induced the synthesis of compound 1. Compound 1 may enhance rice insect resistance by inhibiting the detoxification enzyme activity and metabolism of Chilo suppressalis, as well as promoting cell proliferation to affect its normal growth and development process. The chemical-ecological mechanism of the insect resistance of rice is preliminarily clarified in this paper.

High Overexpression of SiAAP9 Leads to Growth Inhibition and Protein Ectopic Localization in Transgenic Arabidopsis.

Amino acid permeases (AAPs) transporters are crucial for the long-distance transport of amino acids in plants, from source to sink. While Arabidopsis and rice have been extensively studied, research on foxtail millet is limited. This study identified two transcripts of SiAAP9, both of which were induced by NO3- and showed similar expression patterns. The overexpression of SiAAP9L and SiAAP9S in Arabidopsis inhibited plant growth and seed size, although SiAAP9 was found to transport more amino acids into seeds. Furthermore, SiAAP9-OX transgenic Arabidopsis showed increased tolerance to high concentrations of glutamate (Glu) and histidine (His). The high overexpression level of SiAAP9 suggested its protein was not only located on the plasma membrane but potentially on other organelles, as well. Interestingly, sequence deletion reduced SiAAP9's sensitivity to Brefeldin A (BFA), and SiAAP9 had ectopic localization on the endoplasmic reticulum (ER). Protoplast amino acid uptake experiments indicated that SiAAP9 enhanced Glu transport into foxtail millet cells. Overall, the two transcripts of SiAAP9 have similar functions, but SiAAP9L shows a higher colocalization with BFA compartments compared to SiAAP9S. Our research identifies a potential candidate gene for enhancing the nutritional quality of foxtail millet through breeding.

Photocatalytic Hydrogen and Oxygen Evolution Performed by a Long-Afterglow Material.

A micron-sized long-afterglow material, Sr2MgSi2O7:Eu,Ce, was utilized to conduct the hydrogen evolution reaction and oxygen evolution reaction, two half-reactions of water splitting, in the presence of sacrificial agents under both light and dark conditions for the first time. The as-synthesized Sr2MgSi2O7:Eu,Ce exhibited higher photocatalytic activity compared to that of the referenced Sr2MgSi2O7:Eu and Sr2MgSi2O7:Ce samples. Herein, in addition to benefiting from the long photogenerated carrier lifetime of long-afterglow materials, the higher photocatalytic activity was attributed to the conjugated electronic structure between Eu and Ce ions. This structure facilitates charge and energy transfer between them, leading to an enhanced photocatalytic efficiency. This research provides a new strategy for designing efficient long-afterglow material photocatalysts through the construction of conjugated electronic structures.

Multi-Stage Image-Language Cross-Generative Fusion Network for Video-Based Referring Expression Comprehension.

Video-based referring expression comprehension is a challenging task that requires locating the referred object in each video frame of a given video. While many existing approaches treat this task as an object-tracking problem, their performance is heavily reliant on the quality of the tracking templates. Furthermore, when there is not enough annotation data to assist in template selection, the tracking may fail. Other approaches are based on object detection, but they often use only one adjacent frame of the key frame for feature learning, which limits their ability to establish the relationship between different frames. In addition, improving the fusion of features from multiple frames and referring expressions to effectively locate the referents remains an open problem. To address these issues, we propose a novel approach called the Multi-Stage Image-Language Cross-Generative Fusion Network (MILCGF-Net), which is based on one-stage object detection. Our approach includes a Frame Dense Feature Aggregation module for dense feature learning of adjacent time sequences. Additionally, we propose an Image-Language Cross-Generative Fusion module as the main body of multi-stage learning to generate cross-modal features by calculating the similarity between video and expression, and then refining and fusing the generated features. To further enhance the cross-modal feature generation capability of our model, we introduce a consistency loss that constrains the image-language similarity and language-image similarity matrices during feature generation. We evaluate our proposed approach on three public datasets and demonstrate its effectiveness through comprehensive experimental results.