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Background: Anxiety refers to the pathological persistence and intensification of emotional responses to danger, affecting health from psychological and physical aspects. Serotonin is an important neurotransmitter involved in the onset of anxiety., Methods and Results: To explore the biological changes in the formation of anxiety in crustaceans under the regulation of serotonin, we applied the open field-like test method for assessing anxiety states of larval Portunus trituberculatus , a highly aggressive crustacean species with a more simple neural structure compared with rodents and mammals. Compared with the control group, serotonin treatment resulted in a significant decrease in the time spent by the larvae in the central zone, suggesting anxiety-like behavior. Clonazepam treatment reversed this result and provided further evidence that the behavior of larval P. trituberculatus displayed anxiety. Moreover, a non-targeted metabolomic analysis found a significant alteration in the metabolites involved in tryptophan metabolism pathways associated with anxiety, including L-kynurenine, N-acetyl serotonin, and serotonin. These metabolites are involved in the serotonin pathway, the kynurenine pathway, and other pathways that affect anxiety through tryptophan metabolism. There were no significant differences in tryptophan metabolism levels between the control and clonazepam treatment groups., Conclusions: Our results demonstrate the possible existence of anxiety-like behavior in the larvae of P. trituberculatus from two perspectives. Being a species with a simpler neural structure than that of mammals, the larvae of P. trituberculatus offer a convenient model for studying the mechanisms of anxiety in crustaceans.

Polyacetylene (PA) compounds, as natural products, exhibit remarkable properties and distinctive chemical activities. Three structurally similar C14-PA compounds-Echinophorin D, Echinophorin B, and Echinophorin A-extracted from plants demonstrate varying biological activities on the Transient Receptor Potential Channel A1 (TRPA1) protein, which belongs to the TRP (Transient Receptor Potential) family. In the current study, we investigated the binding modes of these three PA compounds with TRPA1 using molecular dynamics (MD), molecular docking, binding free energy calculations, and quantum mechanics/molecular mechanics (QM/MM) methods. Initially, a putative binding site (site-II) in TRPA1 was identified for these compounds; Echinophorin B was found to stabilize the upward A-loop of TRPA1, which is critical for its activation. Furthermore, the binding affinity calculations of PA compounds through molecular fragment decomposition indicate that the arrangement of two triple bonds and one double bond in C14-PA compounds is vital for regulating TRPA1 bioactivity. Additionally, the lipophilic and electronic properties of the three molecules were analyzed in relation to binding affinity, establishing a correlation between TRPA1 activity and these molecular properties.

This work reported gold nanoparticles (AuNPs)-based colorimetric immunoassay with the Cu-based metal-organic framework (MOF) to load pyrroloquinoline quinone (PQQ) for the catalytic oxidation of cysteine. In this method, both Cu 2+ and PQQ in the MOF could promote the oxidation of inducer cysteine by redox cycling, thus limiting the cysteine-induced aggregation of AuNPs and achieving dual signal amplification. Specifically, the recombinant carcinoembryonic antigen (CEA) targets were anchored on the MOF through the metal coordination interactions between the hexahistidine (His 6 ) tag in CEA and the unsaturated Cu 2+ sites in MOF. The CEA/PQQ-loaded MOF could be captured by the antibody-coated ELISA plate to catalyze the oxidation of cysteine. However, once the target CEA in the samples bound to the antibody immobilized on the plate surface, the attachment of CEA/PQQ-loaded MOF would be limited. Cysteine remaining in the solution would trigger the aggregation of AuNPs and cause a color change from red to blue. The target concentration was positively related to the aggregation and color change of AuNPs. The signal-on competitive plasmonic immunoassay exhibited a low detection limit with a linear range of 0.01-1 ng/mL. Note that most of the proteins in commercial ELISA kits are recombinant with a His 6 tag in the N- or C-terminal, so the work could provide a sensitive plasmonic platform for the detection of biomarkers.

Three-color electrophoretic display (EPD) is emerging as a display technology due to its extremely low energy consumption and excellent reflective properties. However, in the process of black and white color image transition, due to the different driving characteristics of red particles, the particles within the three-color EPD cannot be ideally driven to the target position, resulting in the appearance of a red ghost image. For this reason, this study utilized the COMSOL 5.6 finite element simulation method to construct a three-dimensional simulation model to explore the motion characteristics of electrophoretic particles, and then proposed a new driving scheme. The driving scheme aimed to drive red particles to the target position and eliminate the red ghost image by optimizing the pixel erasing stage and employing a high-frequency oscillating voltage. The final experimental results showed that after adopting the proposed driving scheme, the red ghost image was reduced by 8.57% and the brightness of the white color image was increased by 17.50%. This method effectively improved the display performance of three-color EPDs and contributed to the better application of three-color EPDs in the field of high-reflectivity and high-quality display.

Background : Rice blast, caused by Magnaporthe oryzae , seriously damages the yield and quality of rice worldwide. Pi-ta is a durable resistance gene that combats M. oryzae carrying AVR-Pita1 . However, the distribution of the Pi-ta gene in rice germplasms in Yunnan Province has been inadequately studied. Methods : We analyzed the potential molecular evolution pattern of Pi-ta alleles by examining the diversity in the coding sequence (CDS) among rice varieties. Results : The results revealed that 95% of 405 rice landraces collected from different ecological regions in Yunnan Province carry Pi-ta alleles. We identified 17 nucleotide variation sites in the CDS regions of the Pi-ta gene across 385 rice landraces. These variations led to the identification of 28 Pi-ta haplotypes, encoding 12 novel variants. Among these, 5 Pi-ta haplotypes (62 rice landraces) carried R alleles. The evolutionary cluster and network of the Pi-ta haplotypes suggested that the Pi-ta S alleles were the ancestral alleles, which could potentially evolve into R variants through base substitution. Conclusions : This study suggests that Pi-ta alleles are diverse in the rice landraces in Yunnan, and the Pi-ta sites resistant to blast evolved from the susceptible plants of the rice landraces. These results provide the basis for breeding resistant varieties.

Polygonatum cyrtonema polysaccharides have a variety of pharmacological effects. The commonly used extraction methods include traditional hot water extraction, alkaline extraction, enzymatic hydrolysis method, ultrasonic-assisted extraction, etc., but there are problems such as low yield, high temperature, high cost, strict extraction conditions, and insufficient environmental protection. In this study, crude polysaccharide extraction from the Polygonatum cyrtonema Hua was performed using the freeze-thaw method. Response surface methodology (RSM), based on a three-level, three-variable Box-Behnken design (BBD), was employed to obtain the best possible combination of water-to-raw material ratio (A: 30-50), freezing time (B: 2-10 h), and thawing temperature (C: 40-60 °C) for maximum polysaccharide extraction. Using the multiple regression analysis and analysis of variance (ANOVA), the experimental data were fitted to a second-order polynomial equation and were used to generate the mathematical model of optimization experiments. The optimum extraction conditions were as follows: a water-to-raw material ratio of 36.95:1, a freezing time of 4.8 h, and a thawing temperature of 55.99 °C. Under the optimal extraction conditions, the extraction rate of Polygonatum cyrtonema Hua polysaccharide (PCP) was 65.76 ± 0.32%, which is well in close agreement with the value predicted by the model, 65.92%. In addition, PCP has significant antioxidant activity. This result shows that the freeze-thaw method can improve the extraction efficiency, maintain the structural integrity of polysaccharides, simplify the extraction process, promote the dispersion of polysaccharides, and is suitable for large-scale industrial production.

In this study, the thermoforming formability of continuous glass fiber-reinforced polypropylene (CGFRPP) laminates below the melting temperature were investigated. The forming limits of CGFRPP laminates were explored using flexural tests, Erichsen tests and deep drawing tests. The failure mechanism of CGFRPP in thermoforming was investigated by observing typical failure specimens using a microscope. The results show that the flexural performance and Erichsen performance are optimal at 130 °C and 2 mm/min. At 160 °C and 100 mm/min, the deep drawing performance is optimal. The restriction of fibers by the matrix is affected by the deformation temperature, and the creation of defects is affected by the deformation rate. During forming, the CGFRPP laminates undergo shear and extrusion deformations, resulting in wrinkles, delamination, and fiber aggregation.

Severe asthma is characterized by increased cell volume (hypertrophy) and enhanced contractile function (hyperresponsiveness) of the airway smooth muscle cells (ASMCs). The causative relationship and underlying regulatory mechanisms between them, however, have remained unclear. Here, we manipulated the single-cell volume of in vitro cultured human ASMCs to increase from 2.7 to 5.2 and 8.2 × 10 3 μm 3 as a simulated ASMC hypertrophy by culturing the cells on micropatterned rectangular substrates with a width of 25 μm and length from 50 to 100 and 200 μm, respectively. We found that as the cell volume increased, ASMCs exhibited a pro-contractile function with increased mRNA expression of contractile proteins, increased cell stiffness and traction force, and enhanced response to contractile stimulation. We also uncovered a concomitant increase in membrane tension and Piezo1 mRNA expression with increasing cell volume. Perhaps more importantly, we found that the enhanced contractile function due to cell volume increase was largely attenuated when membrane tension and Piezo1 mRNA expression were downregulated, and an auto-regulatory loop between Piezo1 and YAP mRNA expression was also involved in perpetuating the contractile function. These findings, thus, provide convincing evidence of a direct link between hypertrophy and enhanced contractile function of ASMCs that was mediated via Piezo1 mRNA expression, which may be specifically targeted as a novel therapeutic strategy to treat pulmonary diseases associated with ASMC hypertrophy such as severe asthma.

The ability and rapid access to execution data and information in manufacturing workshops have been greatly improved with the wide spread of the Internet of Things and artificial intelligence technologies, enabling real-time unmanned integrated control of facilities and production. However, the widespread issue of data quality in the field raises concerns among users about the robustness of automatic decision-making models before their application. This paper addresses three main challenges relative to field data quality issues during automated real-time decision-making: parameter identification under measurement uncertainty, sensor accuracy selection, and sensor fault-tolerant control. To address these problems, this paper proposes a risk assessment framework in the case of continuous production workshops. The framework aims to determine a method for systematically assessing data quality issues in specific scenarios. It specifies the preparation requirements, as well as assumptions such as the preparation of datasets on typical working conditions, and the risk assessment model. Within the framework, the data quality issues in real-time decision-making are transformed into data deviation problems. By employing the Monte Carlo simulation method to measure the impact of these issues on the decision risk, a direct link between sensor quality and risks is established. This framework defines specific steps to address the three challenges. A case study in the steel industry confirms the effectiveness of the framework. This proposed method offers a new approach to assessing safety and reducing the risk of real-time unmanned automatic decision-making in industrial settings.

The electrowetting display (EWD) device is a new type of electrowetting-on-dielectric (EWOD) equipment that can achieve a paper-like display effect under the control of an electric field. In this microfluidic system, the stability of grayscale can be affected by various factors, such as the physicochemical properties of the materials, the device structure, and electric field distribution. To improve the grayscale stability of active matrix electrowetting displays (AM-EWDs), the impact of different polarities of driving voltage on oil backflow was investigated in this study. Based on the driving principles of AM-EWD, an optimized inter-frame bipolar reset driving waveform was designed to overcome oil backflow. The proposed driving waveform maintained the stability of the oil state by periodically and rapidly releasing trapped charges in the dielectric layer through a reverse driving voltage. Additionally, the effect of feed-through voltage on pixel driving voltage was eliminated by compensating for the driving voltage on a common electrode. Finally, the performance of the designed driving waveform was evaluated with a 6-inch AM-EWD driving platform. Compared to the conventional unipolar reset driving waveform, the backflow speed decreased by 2.70 a.u./s. The standard deviation of the display luminance was also reduced by 11.24 a.u. Experimental results indicated that both the oil backflow speed and the fluctuation range of luminance were effectively suppressed by the proposed driving waveform.

Natural or artificial selection causes animals to adapt to their environment. The adaptive changes generated by the rumen population and metabolism form the basis of ruminant evolution. In particular, the adaptive drive for environmental adaptation reflects the high-quality traits of sheep that have migrated from other places or have been distant from their origins for a long time. The Hu sheep is the most representative sheep breed in the humid and low-altitude environments (Tai Lake region) in East Asia and has been widely introduced into the arid and high-altitude environments (Tibetan Plateau and Hotan region), resulting in environmental adaptive changes in the Hu sheep. In this study, a joint analysis of the rumen microbial metagenome and metabolome was conducted on Hu sheep from different regions (area of origin and area of introduction) with the objective of investigating the quality traits of Hu sheep and identifying microorganisms that influence the adaptive drive of ruminants. The results demonstrated that the growth performance of Hu sheep was altered due to changes in rumen tissue and metabolism following their introduction to the arid area at relatively high altitude. Metagenomic and metabolomic analyses (five ramsper area) revealed that 3580 different microorganisms and 732 different metabolites were identified in the rumen fluid of arid sheep. Among these, the representative upregulated metabolites were 4,6-isocanedione, methanesulfonic acid and N2-succinyl-L-arginine, while the dominant microorganism was Prevotella ruminicola . The downregulated metabolites were identified as campesterol, teprenone and dihydroclavaminic acid, while the disadvantaged microorganisms were Dialister_succinatiphilus , Prevotella_sp._AGR2160 , Prevotella_multisaccharivorax and Selenomonas_bovis . The results of the Pearson analysis indicated that the rumen microbiota and metabolite content of sheep were significantly altered and highly correlated following their relocation from a humid lowland to an arid upland. In particular, the observed changes in rumen microorganisms led to an acceleration of body metabolism, rendering sheep highly adaptable to environmental stress. Prevotella_ruminicola was identified as playing an important role in this process. These findings provide insights into the environmental adaptation mechanisms of sheep.

Dynamic tumor therapies (mainly including photodynamic therapy (PDT) and sonodynamic therapy (SDT)) offer new approaches to cancer treatment. They are often characterized by their noninvasive nature, high selectivity, and low toxicity. Sensitizers are crucial for dynamic therapy. Developing efficient sensitizers with good biocompatibility and controllability is an important aim in dynamic therapy. Porphyrins and metalloporphyrins attract great attention due to their excellent photophysical properties and low cytotoxicity under non-light. Compared to porphyrins, metalloporphyrins show greater potential for dynamic therapy due to their enhanced photochemical and photophysical properties after metal ions coordinate with porphyrin rings. This paper reviews some metalloporphyrin-based sensitizers used in photo/sonodynamic therapy and combined therapy. In addition, the probable challenges and bottlenecks in clinical translation are also discussed.

Leonurine is a natural product unique to the Lamiaceae plant Leonurus japonicus Houtt. , and it has attracted attention due to its anti-oxidative stress, anti-apoptosis, anti-fibrosis, and metabolic regulation properties. Also, it plays an important role in the prevention and treatment of nonalcoholic fatty liver disease (NAFLD) through a variety of biological mechanisms, but its mechanism of action remains to be elucidated. Therefore, this study aims to preliminarily explore the mechanisms of action of leonurine in NAFLD. Mice were randomly divided into four groups: the normal control (NC) group, the Model (M) group, the leonurine treatment (LH) group, and the fenofibrate treatment (FB) group. The NAFLD model was induced by a high-fat high-sugar diet (HFHSD) for 12 weeks, and liver pathological changes and biochemical indices were observed after 12 weeks. Transcriptomic analysis results indicated that leonurine intervention reversed the high-fat high-sugar diet-induced changes in lipid metabolism-related genes such as stearoyl-CoA desaturase 1 ( Scd1 ), Spermine Synthase ( Sms ), AP-1 Transcription Factor Subunit ( Fos ), Oxysterol Binding Protein Like 5 ( Osbpl5 ), and FK506 binding protein 5 ( Fkbp5 ) in liver tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis results suggest that leonurine may exert its lipid-lowering effects through the AMP-activated protein kinase (AMPK) signaling pathway. Liver lipidomic analysis showed that leonurine could alter the abundance of lipid molecules related to fatty acyl (FAs) and glycerophospholipids (GPs) such as TxB3, carnitine C12-OH, carnitine C18:1-OH, and LPC (20:3/0:0). Molecular biology experiments and molecular docking techniques verified that leonurine might improve hepatic lipid metabolism through the alpha-1A adrenergic receptor (ADRA1a)/AMPK/SCD1 axis. In summary, the present study explored the mechanism by which leonurine ameliorated NAFLD by inhibiting hepatic lipid synthesis via the ADRA1a/AMPK/SCD1 axis.

Restricted by a metal-enclosed structure, the internal defects of large transformers are difficult to visually detect. In this paper, a micro-robot is used to visually inspect the interior of a transformer. For the micro-robot to successfully detect the discharge level and insulation degradation trend in the transformer, it is essential to segment the carbon trace accurately and rapidly from the complex background. However, the complex edge features and significant size differences of carbon traces pose a serious challenge for accurate segmentation. To this end, we propose the Hadamard production-Spatial coordinate attention-PixelShuffle UNet (HSP-UNet), an innovative architecture specifically designed for carbon trace segmentation. To address the pixel over-concentration and weak contrast of carbon trace image, the Adaptive Histogram Equalization (AHE) algorithm is used for image enhancement. To realize the effective fusion of carbon trace features with different scales and reduce model complexity, the novel grouped Hadamard Product Attention (HPA) module is designed to replace the original convolution module of the UNet. Meanwhile, to improve the activation intensity and segmentation completeness of carbon traces, the Spatial Coordinate Attention (SCA) mechanism is designed to replace the original jump connection. Furthermore, the PixelShuffle up-sampling module is used to improve the parsing ability of complex boundaries. Compared with UNet, UNet++, UNeXt, MALUNet, and EGE-UNet, HSP-UNet outperformed all the state-of-the-art methods on both carbon trace datasets. For dendritic carbon traces, HSP-UNet improved the Mean Intersection over Union (MIoU), Pixel Accuracy (PA), and Class Pixel Accuracy (CPA) of the benchmark UNet by 2.13, 1.24, and 4.68 percentage points, respectively. For clustered carbon traces, HSP-UNet improved MIoU, PA, and CPA by 0.98, 0.65, and 0.83 percentage points, respectively. At the same time, the validation results showed that the HSP-UNet has a good model lightweighting advantage, with the number of parameters and GFLOPs of 0.061 M and 0.066, respectively. This study could contribute to the accurate segmentation of discharge carbon traces and the assessment of the insulation condition of the oil-immersed transformer.

Despite extensive studies of deposited carbon in Fischer-Tropsch synthesis (FTS), an atomic-level comprehension of the effect of carbon on the morphology of cobalt-based FTS catalysts remains elusive. The adsorption configurations of carbon atoms on different crystal facets of hexagonal close-packed (hcp) Co nanoparticles were studied using density functional theory (DFT) calculations to explore the interaction mechanism between C and Co surfaces. The weaker adsorption strength of C atoms on Co(0001), Co(10-10), and Co(11-20) surfaces accounted for lower diffusion energy, leading to the facile formation of C dimers. Electronic property analysis shows that more electrons are transferred from Co surfaces to C atoms on corrugated facets than on flat facets. The deposition of carbon atoms on Co nanoparticles affects surface energy by forming strong Co-C bonds, which causes the system to reach a more energetically favorable morphology with an increased proportion of exposed Co(10-12) and Co(11-20) areas as the carbon content increases slightly. This transformation in morphology implies that C deposition plays a crucial role in determining the facet proportion and stability of exposed Co surfaces, contributing to the optimization of cobalt-based catalysts with improved performance.

Cognitive impairment (CI) is a type of mental health disorder that mainly affects cognitive abilities, such as learning, memory, perception, and problem-solving. Currently, in clinical practice, the treatment of cognitive impairment mainly focuses on the application of cholinesterase inhibitors and NMDA receptor antagonists; however, there is no specific and effective drug yet. Procatechuic acid (PCA) possesses various functions, including antibacterial, antiasthmatic, and expectorant effects. In recent years, it has received growing attention in the cognitive domain. Therefore, by summarizing the mechanisms of action of procatechuic acid in the treatment of cognitive impairment in this paper, it is found that procatechuic acid has multiple effects, such as regulating the expression of neuroprotective factors, inhibiting cell apoptosis, promoting the autophagy-lysosome pathway, suppressing oxidative stress damage, inhibiting inflammatory responses, improving synaptic plasticity dysfunction, inhibiting Aβ deposition, reducing APP hydrolysis, enhancing the cholinergic system, and inhibiting the excitotoxicity of neuronal cells. The involved signaling pathways include activating Pi3K-akt-mTor and inhibiting JNK, P38 MAPK, P38-ERK-JNK, SIRT1, and NF-κB/p53, etc. This paper aims to present the latest progress in research on procatechuic acid, including aspects such as its chemical properties, sources, pharmacokinetics, mechanisms for treating neurodegenerative diseases.

Hydrogen storage has been a bottleneck factor for the application of hydrogen energy. Hydrogen storage capacity for titanium-decorated boron-doped C 20 fullerenes has been investigated using the density functional theory. Different boron-doped C 20 fullerene absorbents are examined to avoid titanium atom clustering. According to our research, with three carbon atoms in the pentagonal ring replaced by boron atoms, the binding interaction between the Ti atom and C 20 fullerene is stronger than the cohesive energy of titanium. The calculated results revealed that one Ti atom can reversibly adsorb four H 2 molecules with an average adsorption energy of -1.52 eV and an average desorption temperature of 522.5 K. The stability of the best absorbent structure with a gravimetric density of 4.68 wt% has been confirmed by ab initio molecular dynamics simulations. These findings suggest that titanium-decorated boron-doped C 20 fullerenes could be considered as a potential candidate for hydrogen storage devices.

Pregnancy monitoring is always essential for pregnant women and fetuses. According to the report of WHO (World Health Organization), there were an estimated 287,000 maternal deaths worldwide in 2020. Regular hospital check-ups, although well established, are a burden for pregnant women because of frequent travelling or hospitalization. Therefore, home-based, long-term, non-invasive health monitoring is one of the hot research areas. In recent years, with the development of wearable sensors and related data-processing technologies, pregnancy monitoring has become increasingly convenient. This article presents a review on recent research in wearable sensors, physiological data processing, and artificial intelligence (AI) for pregnancy monitoring. The wearable sensors mainly focus on physiological signals such as electrocardiogram (ECG), uterine contraction (UC), fetal movement (FM), and multimodal pregnancy-monitoring systems. The data processing involves data transmission, pre-processing, and application of threshold-based and AI-based algorithms. AI proves to be a powerful tool in early detection, smart diagnosis, and lifelong well-being in pregnancy monitoring. In this review, some improvements are proposed for future health monitoring of pregnant women. The rollout of smart wearables and the introduction of AI have shown remarkable potential in pregnancy monitoring despite some challenges in accuracy, data privacy, and user compliance.

In the process of directed energy deposition (DED), the grain structure of the deposited samples is determined by two aspects. The first is the initial solidification grain structure; the second is the effect of the upper thermal cycle on the solidified grain structure of the lower layer. Dynamic recrystallization and grain growth can be activated under suitable strain and the temperature resulting from thermal cycles. The evolution of grain size and the geometric dislocation density (GND) of austenitic stainless steel 316 L under different strains and temperatures caused by thermal cycles was investigated. It is found that dynamic recrystallization requires an appropriate level of accumulated strain, temperature, and initial grain size. Under <2% accumulated strain and 400-1200 °C conditions caused by 30 layers of thermal cycles, fully dynamic recrystallization occurs with coarse initial grains (CIG), leading to the complete coarsening of grains. However, relatively fine initial grains (FIG) under the same conditions only display partial dynamic recrystallization. The next 2-4% strain and 400-700 °C by 60 layers of thermal cycles make up the driving force of fully dynamic recrystallization, and the grains coarsen completely. Larger accumulated strain (4-6%) and lower temperature (400-600 °C) by 90 layers of thermal cycles and FIG provide more nucleation sites for dynamic recrystallization, which leads to little coarsening of grains even after fully dynamic recrystallization. Temperature, accumulated strain, and the amount of δ-ferrite promote the formation of sub-grains during dynamic recrystallization caused by thermal cycles, which leads to the increase in GND.

We study theoretically the Josephson current through a junction composed of quadruple quantum dots (QDs), of which only one is coupled directly to the left and right superconductor leads (denoted by QD1). The other three QDs are side-coupled to QD1 and free from coupling to the leads. It is found that when the energy levels of all the four QDs are identical, the Josephson current varying with energy level of QD1 develops three peaks with two narrow and one wide, showing the typical Dicke lineshape. With increasing inter-dot coupling strength, the triple-peak configuration is well retained and accompanied by an obviously increased current amplitude. The critical current as a function of the energy level of QD1 shows a single resonance peak whose position and height depend on the energy levels of the side-coupled QDs and the inter-dot coupling strengths. We also find that the curve of the critical current versus energy levels of the side-coupled QDs shows a pair of Fano resonances and the same number Fano antiresonances (valleys). When the energy levels of the side-coupled QDs are different from each other, another Fano resonance and antiresonance are induced due to the quantum interference effect. The present results are compared with those in double and triple QDs systems, and may serve as unique means, such as the combination of quantum Dicke and Fano effects, to manipulate the Josehpson currents.

'Akizuki' pear ( Pyrus pyrifolia Nakai) corky disease is a physiological disease that strongly affects the fruit quality of 'Akizuki' pear and its economic value. In this study, Raman spectroscopy was employed to develop an early diagnosis model by integrating support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) modeling techniques. The effects of various pretreatment methods and combinations of methods on modeling results were studied. The relative optimal index formula was utilized to identify the SG and SG+WT as the most effective preprocessing methods. Following the optimal preprocessing method, the performance of the majority of the models was markedly enhanced through the process of model reconditioning, among which XGBoost achieved 80% accuracy under SG+WT pretreatment, and F1 and kappa both performed best. The results show that RF, GBDT, and XGBoost are more sensitive to the pretreatment method, whereas SVM and CNN are more dependent on internal parameter tuning. The results of this study indicate that the early detection of Raman spectroscopy represents a novel approach for the nondestructive identification of asymptomatic 'Akizuki' pear corky disease, which is of paramount importance for the realization of large-scale detection across orchards.

Background: Intravenous thrombolysis is one of the most effective therapies for the treatment of acute ischemic stroke (AIS), with urokinase offering a cost-effective alternative to newer agents like alteplase and tenecteplase, especially in resource-limited settings., Methods: This review provides a comprehensive overview of the application of intravenous thrombolysis with urokinase for AIS in the clinical practice of stroke management, including the efficacy, safety, and cost-effectiveness of urokinase compared to other thrombolytic agents., Results: Urokinase, a first-generation thrombolytic drug, is a non-specific plasminogen activator that offers a cost-effective alternative. It has been used in clinical practice for over two decades to improve neurological outcomes in patients with AIS if administered within 6 h of ictus. Numerous studies have indicated that urokinase remains a viable option for patients who cannot access alteplase or tenecteplase because of economic constraints, time window limitations, availability, or other reasons., Conclusions: In low- and middle-income countries, urokinase is a cost-effective alternative thrombolytic drug. High-level evidence-based medical research is therefore urgently needed to confirm that urokinase is not inferior to new-generation thrombolytic drugs, and to assess whether it may even be superior in some patient populations.

Glioblastoma (GBM) is a prevalent type of malignancy within the central nervous system (CNS) that is associated with a poor prognosis. The standard treatment for GBM includes the surgical resection of the tumor, followed by radiotherapy and chemotherapy; yet, despite these interventions, overall treatment outcomes remain suboptimal. The blood-brain barrier (BBB), which plays a crucial role in maintaining the stability of brain tissue under normal physiological conditions of the CNS, also poses a significant obstacle to the effective delivery of therapeutic agents to GBMs. Recent preclinical studies have demonstrated that nanomedicine delivery systems (NDDSs) offer promising results, demonstrating both effective GBM targeting and safety, thereby presenting a potential solution for targeted drug delivery. In this review, we first explore the various strategies employed in preclinical studies to overcome the BBB for drug delivery. Subsequently, the results of the clinical translation of NDDSs are summarized, highlighting the progress made. Finally, we discuss potential strategies for advancing the development of NDDSs and accelerating their translational research through well-designed clinical trials in GBM therapy.

Piezoelectric inkjet printing technology, known for its high precision and cost-effectiveness, has found extensive applications in various fields. However, the issue of residual vibration significantly limits its printing quality and efficiency. This paper presents a method for suppressing residual vibration based on the particle swarm optimization (PSO) algorithm. Initially, an improved PI model considering the nonlinear hysteresis characteristics of piezoelectric ceramics is established, and the model is identified through a strain gauge circuit to ensure its accuracy in describing the nonlinear hysteresis characteristics. Subsequently, a dynamic model of the piezoelectric inkjet printing system is constructed, with precise parameter identification achieved using the self-induction principle. This enables precise simulation of residual vibration. Finally, the driving waveform is optimized based on the PSO algorithm, with iterative calculations employed to find the optimal combination of driving waveform parameters, effectively suppressing residual vibration while ensuring sufficient injection energy. The results indicate that this method significantly reduces the amplitude of residual vibration, thereby effectively enhancing printing quality and stability. This research offers a novel solution for residual vibration suppression in piezoelectric inkjet printing technology, potentially advancing its applications in printing and biofabrication.

Propylene-based elastomers (PBEs) have received widespread attention and research in recent years due to their structural diversity and excellent properties, and are also an important area for leading chemical companies to compete for layout, but efficient synthesis of PBEs remains challenging. In this paper, we review the development of PBEs and categorize them into three types, grounded in their unique chain structures, including homopolymer propylene-based elastomers (hPBEs), random copolymer propylene-based elastomers (rPBEs), and block copolymer propylene-based elastomers (bPBEs). The successful synthesis of these diverse PBEs is largely credited to the relentless innovative advancements in homogeneous catalysts (metallocene catalysts, constrained geometry catalysts, and non-metallocene catalysts). Consequently, we summarize the catalytic performance of various homogeneous catalysts employed in PBE synthesis and delve into their effect on molecular weight, molecular weight distribution, and chain structures of the resulting PBEs. In the end, based on the current academic research and industrialization status of PBEs, an outlook on potential future research directions for PBEs is provided.

Polychlorinated naphthalenes (PCNs) are a new type of persistent organic pollutant (POP) characterized by persistence, bioaccumulation, dioxin-like toxicity, and long-range atmospheric transport. Focusing on one type of PCN, monochlorinated naphthalenes (CN-1, CN-2), this study aimed to examine their photodegradation in the environment. In this work, CN-1 and CN-2 were employed as the model pollutants to investigate their photodegradation process under UV-C irradiation. Factors like the pH, initial concentrations of CN-1, and inorganic anions were investigated. Next, the roles of hydroxyl radicals ( • OH), superoxide anion radicals (O 2 •- ), and singlet oxygen ( 1 O 2 ) in the photodegradation process were discussed and proposed via theory computation. The results show that the photodegradation of CN-1 and CN-2 follows pseudo-first-order kinetics. Acidic conditions promote the photodegradation of CN-1, while the effects of pH on the photodegradation of CN-2 are not remarkable. Cl - , NO 3 - , and SO 3 2- accelerate the photodegradation of CN-1, whereas the effect of SO 4 2- and CO 3 2- is not significant. Additionally, the contributions of • OH and O 2 •- to the photodegradation of CN-1 are 20.47% and 38.80%, while, for CN-2, the contribution is 16.40% and 16.80%, respectively. Moreover, the contribution of 1 O 2 is 15.7%. Based on DFT calculations, C4 and C6 of the CN-1 benzene ring are prioritized attack sites for • OH, while C2 and C9 of CN-2 are prioritized attack sites.

Plant AT-rich sequence and zinc-binding proteins (PLATZs) are a novel category of plant-specific transcription factors involved in growth, development, and abiotic stress responses. However, the PLATZ gene family has not been identified in barley. In this study, a total of 11 HvPLATZs were identified in barley, and they were unevenly distributed on five of the seven chromosomes. The phylogenetic tree, incorporating PLATZs from Arabidopsis , rice, maize, wheat, and barley, could be classified into six clusters, in which HvPLATZs are absent in Cluster VI. HvPLATZs exhibited conserved motif arrangements with a characteristic PLATZ domain. Two segmental duplication events were observed among HvPLATZs . All HvPLATZs were core genes present in 20 genotypes of the barley pan-genome. The HvPLATZ5 coding sequences were conserved among 20 barley genotypes, whereas HvPLATZ4/9/10 exhibited synonymous single nucleotide polymorphisms (SNPs); the remaining ones showed nonsynonymous variations. The expression of HvPLATZ2/3/8 was ubiquitous in various tissues, whereas HvPLATZ7 appeared transcriptionally silent; the remaining genes displayed tissue-specific expression. The expression of HvPLATZs was modulated by salt stress, potassium deficiency, and osmotic stress, with response patterns being time-, tissue-, and stress type-dependent. The heterologous expression of HvPLATZ3/5/6/8/9/10/11 in yeast enhanced tolerance to salt and osmotic stress, whereas the expression of HvPLATZ2 compromised tolerance. These results advance our comprehension and facilitate further functional characterization of HvPLATZs .

A major challenge in myocardial tissue engineering is replicating the heart's highly complex three-dimensional (3D) anisotropic structure. Heart-on-a-chip (HOC) is an emerging technology for constructing myocardial tissue in vitro in recent years, but most existing HOC systems face difficulties in constructing 3D myocardial tissue aligned with multiple cell layers. Electrospun nanofibers are commonly used as scaffolds for cell growth in myocardial tissue engineering, which can structurally simulate the extracellular matrix to induce the aligned growth of myocardial cells. Here, we developed an HOC that integrates multi-layered aligned polycaprolactone (PCL) nanofiber scaffolds inside microfluidic chips, and constructed 3D thick and aligned tissue with a layered seeding approach. By culturing human-induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) on chip, the myocardial tissue on the two layered nanofibers reached a thickness of ~53 μm compared with ~19 μm for single-layered nanofibers. The obtained myocardial tissue presented well-aligned structures, with densely distributed α-actinin. By the third day post seeding, the hiPSC-CMs contract highly synchronously, with a contraction frequency of 18 times/min. The HOC with multi-layered biomimetic scaffolds provided a dynamic in vitro culture environment for hiPSC-CMs. Together with the layered cell-seeding process, the designed HOC promoted the formation of thick, well-aligned myocardial tissue.

Drought is a major abiotic stress factor that reduces agricultural productivity. Understanding the molecular regulatory network of drought response in winter rape is of great significance for molecular Brassica rapa . In order to comprehensively analyze the network expression of DEGs and DEMIs in winter rape under drought stress, in this study we used Longyou 7 as the experimental material to identify DEGs and DEMIs related to drought stress by transcriptome and miRNA sequencing. A total of 14-15 key differential mRNA genes related to drought stress and biological stress were screened out under different treatments in the three groups. and 32 differential miRNAs were identified through targeted regulatory relationships, and the mRNA expression of 20 target genes was negatively regulated by the targeting regulatory relationship. It is mainly enriched in starch and sucrose metabolism, carbon metabolism and other pathways. Among them, gra-MIR8731-p3&#95;2ss13GA18GA regulated the expression of multiple mRNAs in the three treatments. miRNA is mainly involved in the drought resistance of Chinese cabbage winter rape by regulating the expression of target genes, such as starch and sucrose metabolism, amino acid biosynthesis, and carbon metabolism. These miRNAs and their target genes play an indispensable role in winter rapeseed drought stress tolerance regulation.

Background: Despite promise in preclinical models of acute respiratory distress syndrome (ARDS), mesenchymal stem cells (MSC) have failed to translate to therapeutic benefit in clinical trials. The MSC is a live cell medicine and interacts with the patient's disease state. Here, we explored this interaction, seeking to devise strategies to enhance MSC therapeutic function., Methods: Human bone-marrow-derived MSCs were exposed to lung homogenate from healthy and E. coli -induced ARDS rat models. Apoptosis and functional assays of the MSCs were performed., Results: The ARDS model showed reduced arterial oxygenation, decreased lung compliance and an inflammatory microenvironment compared to controls. MSCs underwent more apoptosis after stimulation by lung homogenate from controls compared to E. coli , which may explain why MSCs persist longer in ARDS subjects after administration. Changes in expression of cell surface markers and cytokines were associated with lung homogenate from different groups. The anti-microbial effects of MSCs did not change with the stimulation. Moreover, the conditioned media from lung-homogenate-stimulated MSCs inhibited T-cell proliferation., Conclusions: These findings suggest that the ARDS microenvironment plays an important role in the MSC's therapeutic mechanism of action, and changes can inform strategies to modulate MSC-based cell therapy for ARDS.

There is a growing trend in incorporating biomass-based engineered nanomaterials into food products to enhance their quality and functionality. The zeta potential, droplet size, microstructure, and content of free fatty acid (FFA) release were determined to investigate the influence of a plant-derived particle stabilizer, i.e., lignin-containing cellulose nanofibrils (LCNFs). Remarkable differences were observed during digestion stages, which were found to be correlated with the concentrations of LCNFs. The gradual FFA release in the small intestine stage from LCNF-coated lipid droplets was monitored over time, with a final lowest release of FFAs amounting to 26.3% in the emulsion containing 20.0% ( v / v ) of the dispersed phase stabilized by 3 mg/mL of LCNFs. This release can be attributed to the physical barrier at lipid droplet surfaces and the network effect created by the free LCNFs in the continuous phase. This work provides a foundation for the potential application of nature-derived LCNF materials in reducing fat absorbance.

Lung cancer is responsible for a high burden of disease globally. Over the last two decades, the discovery of targetable oncogenic genomic alterations has revolutionized the treatment landscape for early-stage and advanced non-small cell lung cancer (NSCLC). New molecular drivers continue to emerge as promising therapeutic targets, including KRAS non-G12C, RAF/MEK, HER3, Nectin-4, folate receptor alpha, ITGB6, and PRMT5. In this review, we summarize the emerging molecular targets with a potential clinical impact in advanced NSCLC, elaborating on their clinical characteristics and specific mechanisms and molecular pathways for which targeted treatments are currently available. Additionally, we present an aggregate of ongoing clinical trials investigating the available treatment options targeting such alterations, in addition to their current recruitment status and preliminary efficacy data. These advancements may guide further research endeavors and inform future treatment strategies to improve the management of and transform outcomes for patients with advanced NSCLC.

Tumor cells invade normal surrounding tissues through continuous division. In this study, we hypothesized that cell cycle regulation changes the immune efficacy of ovarian cancer. To investigate this hypothesis, a Förster resonance energy transfer (FRET) sensor was constructed to characterize the cell activity in real time. Cell shrinkage caused by apoptosis induces the aggregation of proteins on the cell membrane, leading to variations in the fluorescence lifetime of FRET sensors. Moreover, we tracked cell activity across various cycles following co-culture with an immune checkpoint inhibitor. Consequently, we assessed how cell cycle regulation influences immunotherapy in a tumor mouse model. This approach, which involves inhibiting typical cell cycle processes, markedly enhances the effectiveness of immunotherapy. Our findings suggest that modulating the cycle progression of cancer cells may represent a promising approach to enhance the immune response of ovarian cancer cells and the efficacy of immunotherapy based on immune checkpoint inhibitors.

In this study, novel Fe 2 O 3 /TiO 2 photocatalytic composites were synthesised by combining traditional oxidation roasting with the sol-gel method, using low-cost metallurgical waste (iron scales) as the raw material. The characterisation results revealed that the oxidised iron scales could be transformed into high-purity and porous Fe 2 O 3 particles through oxidation roasting, thereby providing additional sites for the adsorption process and thus serving as an effective carrier for TiO 2 -based photocatalytic materials. During the sol-gel process, TiO 2 was loaded onto the synthesised Fe 2 O 3 particles, generating core-shell heterostructure Fe 2 O 3 /TiO 2 photocatalytic composites. Under visible light irradiation for 90 min, the Fe 2 O 3 /TiO 2 photocatalytic composites achieved a remarkable methylene blue removal rate (97.71%). This reaction process followed the quasi-first-order kinetic model with a rate constant of 0.038 min -1 . The results have demonstrated that this combination of various components in the Fe 2 O 3 /TiO 2 photocatalytic composites improved the adsorption, light utilisation, and charge separation effect of the photocatalysts. Moreover, the material exhibited favourable stability and recyclability, making it a decent candidate for the treatment of wastewater from the biochemical industry. Therefore, this study provides a new strategy for improving the photocatalytic activity of TiO 2 and expanding the high value-added utilisation of iron scales.

A bioactivity-guided separation strategy was used to identify novel antistroke compounds from Gymnadenia conopsea (L.) R. Br., a medicinal plant. As a result, 4 undescribed compounds ( 1-2 , 13 , and 17 ) and 13 known compounds, including 1 new natural product ( 3 ), were isolated from G. conopsea. The structures of these compounds were elucidated through comprehensive spectroscopic techniques, such as 1D/2D nuclear magnetic resonance (NMR) spectroscopy, high-resolution electrospray ionization mass spectrometry (HRESIMS), and quantum chemical calculations. An oxygen-glucose deprivation/reoxygenation (OGD/R)-injured rat pheochromocytoma (PC12) cell model was used to evaluate the antistroke effects of the isolates. Compounds 1-2 , 10-11 , 13-15 , and 17 provided varying degrees of protection against OGD/R injury in the PC12 cells at concentrations of 12.5, 25, and 50 µM. Among the tested compounds, compound 17 demonstrated the most potent neuroprotective effect, which was equivalent to that of the positive control drug (edaravone). Then, transcriptomic and bioinformatics analyses were conducted to reveal the regulatory effect of compound 17 on gene expression. In addition, quantitative real-time PCR (qPCR) was performed to verify the results of the transcriptomic and bioinformatics analyses. These results suggest that the in vitro antistroke effect of compound 17 may be associated with the regulation of the Col27a1 gene. Thus, compound 17 is a promising candidate for the development of novel antistroke drugs derived from natural products, and this topic should be further studied.

In this work, epoxy was added into commercial Sn-3.0Ag-0.5Cu (SAC305) solder paste to enhance the thermal cycling reliability of the joint. The microstructure and fracture surface were observed using a scanning electron microscope/energy dispersive spectrometer (SEM/EDS), and a shear test was performed on the thermally cycled joint samples. The results indicated that during the thermal cycling test, the epoxy protective layer on the surface of the epoxy-enhanced SAC305 solder joint could significantly alleviate the thermal stress caused by coefficients of thermal expansion (CTE) mismatch, resulting in fewer structural defects. The interfacial compound of the original SAC305 solder joints gradually coarsened due to the accelerated atomic diffusion, but epoxy-enhanced SAC305 solder joints demonstrated a thinner interfacial layer and a smaller IMC grain size. Due to the reduced stress concentration and the additional mechanical support provided by the cured epoxy layer, epoxy-enhanced SAC305 solder joints displayed superior shear performance compared to the original joint during the thermal cycling test. After 1000 thermal cycles, Cu-Sn IMC regions were observed on the fracture surfaces of the original SAC305 solder joint, exhibiting brittle fracture characteristics. However, the fracture of the SAC305 solder joint with 8 wt.% epoxy remained within the solder bulk and exhibited a ductile fracture mode. This work indicates that epoxy-enhanced SAC305 solder pastes display high thermal cycling reliability and could meet the design needs of advanced packaging technology for high-performance electronic packaging materials.

This study explores the reasons behind the variations in the enantioselectivity of the sulfoxidation of methyl phenyl sulfide by marine-derived vanadium-dependent haloperoxidases (VHPOs). Twelve new VHPOs of marine organisms were overexpressed, purified, and tested for their ability to oxidize sulfide. Most of these marine enzymes exhibited nonenantioselective behavior, underscoring the uniqueness of An VBPO from the brown seaweed Ascophyllum nodosum and Cp VBPO from the red seaweed Corallina pilulifera , which produce ( R )- and ( S )-sulfoxides, respectively. The enantioselective sulfoxidation pathway is likely due to direct oxygen transfer within the VHPO active site. This was demonstrated through molecular docking and molecular dynamics simulations, which revealed differences in the positioning of sulfide within An VBPO and Cp VBPO, thus explaining their distinct enantioselectivities. Nonenantioselective VHPOs probably follow a different oxidation pathway, initiating with sulfide oxidation to form a positively charged radical. Further insights were gained from studying the catalytic effect of VO 4 3- on H 2 O 2 -driven sulfoxidation. This research improves the understanding of VHPO-mediated sulfoxidation and aids in developing biocatalysts for sulfoxide synthesis.

We study theoretically the supercurrent and the superconducting diode effect (SDE) in a structure comprising parallel-coupled double quantum dots (DQDs) sandwiched between two superconductor leads in the presence of a magnetic flux. The influence of the Rashba spin-orbit interaction (RSOI), which induces a spin-dependent phase factor in the dot-superconductor coupling strength, is taken into account by adopting the nonequilibrium Green's function technique. This RSOI-induced phase factor serves as a driving force for the supercurrent in addition to the usual superconducting phase difference, and it leads to the system's left/right asymmetry. Correspondingly, the magnitude of the positive and negative critical currents become different from each other: the so-called SDE. Our results show that the period, magnitude, and direction of the supercurrents depend strongly on the RSOI-induced phase factor, dots' energy levels, interdot coupling strengths, and the magnetic flux. In the absence of magnetic flux, the diode efficiency is negative and may approach -2, which indicates the perfect diode effect with only negative flowing supercurrent in the absence of a positive one. Interestingly enough, both the sign and magnitude of the diode efficiency can be efficiently adjusted with the help of magnetic flux, the dots' energy levels and the interdot coupling strength and thus provide a controllable SDE by rich means, such as gate voltage or host materials of the system.

Drylands cover more than 40% of global land surface and will continue to expand by 10% at the end of this century. Understanding the resistance mechanisms of native species is of particular importance for vegetation restoration and management in drylands. In the present study, metabolome of a dominant shrub Campylotropis polyantha in a dry-hot valley were investigated. Compared to plants grown at the wetter site, C. polyantha tended to slow down carbon (C) assimilation to prevent water loss concurrent with low foliar reactive oxygen species and sugar concentrations at the drier and hotter site. Nitrogen (N) assimilation and turn over were stimulated under stressful conditions and higher leaf N content was kept at the expense of root N pools. At the drier site, roots contained more water but less N compounds derived from the citric acid cycle. The site had little effect on metabolites partitioning between leaves and roots. Generally, roots contained more C but less N. Aromatic compounds were differently impacted by site conditions. The present study, for the first time, uncovers the apparent metabolic adaptations of C. polyantha to hostile dryland conditions. However, due to the limited number of samples, we are cautious about drawing general conclusions regarding the resistance mechanisms. Further studies with a broader spatial range and larger time scale are therefore recommended to provide more robust information for vegetation restoration and management in dryland areas under a changing climate.

The Varicella zoster virus (VZV), responsible for both varicella (chickenpox) and herpes zoster (shingles), presents significant global health challenges. While primary VZV infection primarily affects children, leading to chickenpox, reactivation in later life can result in herpes zoster and associated post-herpetic neuralgia, among other complications. Vaccination remains the most effective strategy for VZV prevention, with current vaccines largely based on the attenuated vOka strains. Although these vaccines are generally effective, they can induce varicella-like rashes and have sparked concerns regarding cell virulence. As a safer alternative, subunit vaccines circumvent these issues. In this study, we developed a nanoparticle-based vaccine displaying the glycoprotein E (gE) on ferritin particles using the SpyCatcher/SpyTag system, termed FR-gE. This FR-gE nanoparticle antigen elicited substantial gE-specific binding and VZV-neutralizing antibody responses in BALB/c and C57BL/6 mice-responses that were up to 3.2-fold greater than those elicited by the subunit gE while formulated with FH002C, aluminum hydroxide, or a liposome-based XUA01 adjuvant. Antibody subclass analysis revealed that FR-gE produced comparable levels of IgG1 and significantly higher levels of IgG2a compared to subunit gE, indicating a Th1-biased immune response. Notably, XUA01-adjuvanted FR-gE induced a significant increase in neutralizing antibody response compared to the live attenuated varicella vaccine and recombinant vaccine, Shingrix. Furthermore, ELISPOT assays demonstrated that immunization with FR-gE/XUA01 generated IFN-γ and IL-2 levels comparable to those induced by Shingrix. These findings underscore the potential of FR-gE as a promising immunogen for the development of varicella and herpes zoster vaccines.

Frequency conversion process based on periodically poled thin-film lithium niobate (PPTFLN) has been widely recognized as an important component for quantum information and photonic signal processing. Benefiting from the tight confinement of optical modes, the normalized conversion efficiency (NCE) of nanophotonic waveguides is improved by orders of magnitude compared to their bulk counterparts. However, the power conversion efficiency of these devices is limited by inherent nanoscale inhomogeneity of thin-film lithium niobate (TFLN), leading to undesirable phase errors. In this paper, we theoretically present a novel approach to solve this problem. Based on dispersion engineering, we aim at adjusting the waveguide structure, making local waveguide width adjustment at positions of different thicknesses, thus eliminating the phase errors. The adapted waveguide width design is applied for etched and loaded waveguides based on PPTFLN, achieving the ultrahigh power conversion efficiency of second harmonic generation (SHG) up to 2.1 × 10 4 %W -1 and 6936%W -1 , respectively, which surpasses the power conversion efficiency of other related works. Our approach just needs standard periodic poling with a single period, significantly reducing the complexity of electrode fabrication and the difficulty of poling, and allows for the placing of multiple waveguides, without individual poling designs for each waveguide. With the advantages of simplicity, high production, and meeting current micro-nano fabrication technology, our work may open a new way for achieving highly efficient second-order nonlinear optical processes based on PPTFLN.

Single-cell RNA sequencing (scRNA-seq) is now a successful technology for identifying cell heterogeneity, revealing new cell subpopulations, and predicting developmental trajectories. A crucial component in scRNA-seq is the precise identification of cell subsets. Although many unsupervised clustering methods have been developed for clustering cell subpopulations, the performance of these methods is prone to be affected by dropout, high dimensionality, and technical noise. Additionally, most existing methods are time-consuming and fail to fully consider the potential correlations between cells. In this paper, we propose a novel unsupervised clustering method called scVGATAE (Single-cell Variational Graph Attention Autoencoder) for scRNA-seq data. This method constructs a reliable cell graph through network denoising, utilizes a novel variational graph autoencoder model integrated with graph attention networks to aggregate neighbor information and learn the distribution of the low-dimensional representations of cells, and adaptively determines the model training iterations for various datasets. Finally, the obtained low-dimensional representations of cells are clustered using kmeans. Experiments on nine public datasets show that scVGATAE outperforms classical and state-of-the-art clustering methods.