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Optical edge detection is a useful method for characterizing boundaries, which is also in the forefront of image processing for object detection. As the field of metamaterials and metasurface is growing fast in an effort to miniaturize optical devices at unprecedented scales, experimental realization of optical edge detection with metamaterials remains a challenge and lags behind theoretical proposals. Here, we propose a mechanism of edge detection based on a Pancharatnam–Berry-phase metasurface. We experimentally demonstrated broadband edge detection using designed dielectric metasurfaces with high optical efficiency. The metasurfaces were fabricated by scanning a focused laser beam inside glass substrate and can be easily integrated with traditional optical components. The proposed edge-detection mechanism may find important applications in image processing, high-contrast microscopy, and realtime object detection on compact optical platforms such as mobile phones and smart cameras.

The Solute Carrier 1A (SLC1A) family includes two major mammalian transport systems—the alanine serine cysteine transporters (ASCT1-2) and the human glutamate transporters otherwise known as the excitatory amino acid transporters (EAAT1-5). The EAATs play a critical role in maintaining low synaptic concentrations of the major excitatory neurotransmitter glutamate, and hence they have been widely researched over a number of years. More recently, the neutral amino acid exchanger, ASCT2 has garnered attention for its important role in cancer biology and potential as a molecular target for cancer therapy. The nature of this role is still being explored, and several classes of ASCT2 inhibitors have been developed. However none have reached sufficient potency or selectivity for clinical use. Despite their distinct functions in biology, the members of the SLC1A family display structural and functional similarity. Since 2004, available structures of the archaeal homologues Glt Ph and Glt Tk have elucidated mechanisms of transport and inhibition common to the family. The recent determination of EAAT1 and ASCT2 structures may be of assistance in future efforts to design efficacious ASCT2 inhibitors. This review will focus on ASCT2, the present state of knowledge on its roles in tumour biology, and how structural biology is being used to progress the development of inhibitors.

This study examined the effects of two performance assessment approaches on students' learning achievement, attitude, computational thinking, and 4C key competencies in an introductory robotics course. An experimental study was conducted with 72 students in a middle school for 16 weeks. A performance assessment given at the end of the course was used as a reflection tool in one group (RPA), while given during the learning process as a guidance tool in another group (GPA). Results indicated that GPA showed a significantly better effect than RPA on students' learning attitude and computational thinking, although the improvement in learning performance and 4C key competencies was not evident. Within the 4C sub-dimensions, GPA outperformed RPA in promoting students' creativity and collaboration. However, the RPA group performed significantly better in improving critical thinking. The results confirmed that both GPA and RPA played an important role in robotics education. GPA provides a structured learning experience with clear goals and expectations, allowing students to effectively adjust their learning strategies through immediate feedback and a greater sense of control over their learning process with a positive attitude. In contrast, RPA encourages students to critically reflect on their learning journey from a holistic perspective, which increases student autonomy and deep learning during the process, while requiring a level of self-awareness and introspection that may be challenging for some students. The advantages and disadvantages of both approaches were discussed. The findings highlight the importance of adopting an appropriate approach to performance assessment and avoiding over-guidance in robotics education.

Atherosclerosis (AS) is a chronic inflammatory disease characterized by the gradual accumulation of plaques in arterial walls, with its pathogenesis remaining incompletely understood. Recent studies have highlighted that development of AS is closely associated with the aberrant activation of the NLRP3 inflammasome in the arteries. Inhibition of the NLRP3 inflammasome by natural products and formulae derived from Chinese herbal medicines (CHMs) has been shown to alleviate AS-associated pathologies. However, therapies that effectively and safely target the NLRP3 inflammasome remain limited. This review aims to summarize the key discoveries from recent studies on the effects of these natural products and formulae on the NLRP3 inflammasome in the context of AS treatment. A comprehensive literature search was conducted on databases such as PubMed/MEDLINE up to January 2025, yielding 38 eligible studies. Our analysis indicates that certain therapies can effectively prevent arterial inflammation in animal models by targeting multiple pathways and mechanisms related to the NLRP3 inflammasome. This review summarizes the primary findings of these studies, focusing on the therapeutic effects and underlying mechanisms of action. Based on these insights, we propose future strategies to enhance the efficacy, specificity, and safety of existing natural products and formulae for AS treatment. Additionally, this study offers a perspective for future research that may enhance our understanding of the roles and the mechanisms of CHM-derived phytochemicals and formulae in regulating the NLRP3 inflammasome and treating AS.

Label-free optical detection of nanometer-scale bioparticles is highly desirable for noninvasive biological studies but challenging due to the weak scattering signals that are difficult to distinguish from the illumination background. Interferometric scattering microscopy (iSCAT) has enabled high-sensitivity imaging by detecting the interference between the particle’s scattered light and a reference beam. However, enhancing the detection sensitivity and the image contrast for small particles continues to be a challenge in iSCAT. Here, we introduce meta-amplified dark-field interferometric scattering microscopy (MAD-iSCAT), which leverages a plasmonic metasurface to drastically enhance nanoparticle detection sensitivity in iSCAT. By employing a metasurface comprising sub-diffraction plasmonic meta-atom arrays, MAD-iSCAT generates bright radiation modes that intensely scatter light toward the far field in the presence of a detection nanoparticle, substantially amplifying the sensitivity. In the absence of a nanoparticle, the metasurface produces minimal background due to the dark collective mode, resulting in improved image contrast. We present a theoretical analysis of amplified interferometric imaging using designed metasurfaces and experimentally demonstrate enhancements in contrast and signal-to-noise ratio for detecting dielectric nanoparticles, exosomes, and proteins. Our approach offers broad applications in label-free biosensing and optical mass spectrometry, enabling significantly improved throughput and sensitivity. We introduce meta-amplified dark-field interferometric scattering microscopy, which uses a plasmonic metasurface to enhance sensitivity and contrast by converting nanoparticle-induced phase perturbations into strong far-field scattering signals.

Glutamate is the predominant excitatory neurotransmitter in the mammalian central nervous system (CNS). Excitatory amino acid transporters (EAATs) regulate extracellular glutamate by transporting it into cells, mostly glia, to terminate neurotransmission and to avoid neurotoxicity. EAATs are also chloride (Cl-) channels, but the physiological role of Cl- conductance through EAATs is poorly understood. Mutations of human EAAT1 (hEAAT1) have been identified in patients with episodic ataxia type 6 (EA6). One mutation showed increased Cl- channel activity and decreased glutamate transport, but the relative contributions of each function of hEAAT1 to mechanisms underlying the pathology of EA6 remain unclear. Here we investigated the effects of 5 additional EA6-related mutations on hEAAT1 function in Xenopus laevis oocytes, and on CNS function in a Drosophila melanogaster model of locomotor behavior. Our results indicate that mutations resulting in decreased hEAAT1 Cl- channel activity but with functional glutamate transport can also contribute to the pathology of EA6, highlighting the importance of Cl- homeostasis in glial cells for proper CNS function. We also identified what we believe is a novel mechanism involving an ectopic sodium (Na+) leak conductance in glial cells. Together, these results strongly support the idea that EA6 is primarily an ion channelopathy of CNS glia.

Extracellular vesicles (EVs) have emerged as promising therapeutics for regenerative medicine, but the efficacy of current exogenous EV‐based therapies for treating chronic tissue injury is still unsatisfactory. Exercise can affect skeletal muscle EV secretion and that this process regulates the systemic health‐promoting role of exercise, suggesting that fine‐tuning of endogenous tissue EV secretion may provide a new therapeutic avenue. Here, this work reports that in vivo reprogramming of EV secretion via metabolic engineering is a promising strategy for treating chronic diseases. Briefly, exercise enhanced mitochondrial metabolism and EV production in healthy skeletal muscles, and EVs from healthy skeletal muscles subjected to exercise or metabolic engineering (boosting mitochondrial biogenesis via AAV‐mediated muscle‐specific TFAM overexpression) exerted cellular protective effects in vitro. In injured skeletal muscles, in vivo metabolic engineering therapy could reprogram EV secretion patterns (reducing pathological EV compositions while increasing beneficial EV compositions) by regulating multiple EV biogenesis and cargo sorting pathways. Reprogrammed muscle‐derived EVs could reach major organs and tissues via the circulation and then simultaneously attenuated multiple‐tissue (e.g., muscle and kidney) injury in chronic kidney disease. This study highlights that in vivo reprogramming of tissue‐derived EVs via a metabolic engineering approach is a potential strategy for treating diverse chronic diseases. Inspired by exercise‐induced metabolic rewiring and EV secretion, this study shows that in vivo metabolic engineering strategy can reprogram EV secretion pattern and simultaneously attenuate multiple tissue injury in CKD status, highlighting that it is a potential strategy for treating diverse chronic diseases.

This study investigated the effect of classroom settings on teacher-student interaction in higher education by comparing the behavioural sequences in smart classrooms (SCs) and traditional multimedia classrooms (TMCs). Twenty in-classroom teaching sessions were randomly selected from six universities in South China, involving 1,043 students and 23 teachers. Half of the sessions were taken in SCs as the experimental group, and half were in TMCs as the control group. A teacher-student interaction behaviour coding schema was developed, and a total of 17,805 observable behaviours were collected and coded sequentially via a review of classroom videos. Then, the behavior pattern diagram was set up to visualise a lag sequential analysis results by four themes, namely teacher-talk, teacher-action, student-talk and student-action. Results show that compared to TMCs, the SCs triggered significantly more self-initiated student actions and student-driven teacher talk, while teacher-initiated talk decreased significantly, indicating that students’ autonomy was strengthened in the SC. Furthermore, teachers’ workload was somewhat reduced, and they obtained more support with trying new pedagogies with mobile terminals in the data-rich environment. These findings provide evidence to validate the effect of SCs on increasing teacher-student interaction and strengthening the students’ dominant position.

Background: The prevalence of major depressive disorder (MDD) among patients with inflammatory bowel disease (IBD) is significantly higher compared to the general population, suggesting a potential link between their pathogeneses. Cuproptosis, defined as cell death caused by intracellular copper accumulation, has not been thoroughly investigated in the context of IBD and MDD. This study aims to uncover the molecular mechanisms of cuproptosis-related genes (CRGs) in both conditions and to explore novel therapeutic strategies by the modulation of CRGs. Methods: In this study, we identified differentially expressed CRGs between normal and disease samples. We calculated the correlation among CRGs and between CRGs and immune cell infiltrations across various tissues. Four machine learning algorithms were employed to identify key CRGs associated with IBD and MDD. Additionally, drug sensitivity, molecular docking, and molecular dynamics simulations were conducted to predict therapeutic drugs for IBD and MDD. Results: We identified DLD, DLAT, DLST, PDHB, and DBT as common DE-CRGs, and DLD, LIAS, SLC31A1, SCO2, and CDKN2A as key CRGs associated with both IBD and MDD. Consequently, DLD was recognized as a shared biomarker in both diseases. A total of 37 potential therapeutic drugs were identified for IBD and MDD. Based on the molecular docking and molecular dynamics simulation analyses, barasertib and NTP-TAE684, which target DLAT, were predicted to be the most effective compounds. Conclusions: These findings have substantially enhanced our understanding of the similarities and differences in the regulatory mechanisms of CRGs within brain–gut axis diseases. Key biomarkers have been identified, and potential therapeutic drugs have been predicted to effectively target IBD and MDD.

Timely and accurate mastery of the spatial and temporal development process of landslides is crucial for emergency rescue work. In the early morning of July 5, 2022, under the influence of continuous heavy rainfall, the left embankment slope of a highway in Guangdong Province, slipped as a whole, and a truck fell and was buried, resulting in the interruption of highway traffic. In order to accurately carry out landslide analysis and management, and to provide information support for emergency rescue and relief work, whole-process survey and analysis of the landslide area was carried out based on unmanned aerial vehicle tilt photography, 3D reconstruction and spatial analysis technology. In situations where traditional surveying and mapping work is difficult to carry out, it is possible to accurately grasp the whole process of the development of landslides in space and time under the circumstances and construct corresponding realistic three-dimensional models to provide effective reference information for on-site rescue and relief work. At the same time, through the comprehensive analysis of the acquired information, it is inferred that the landslide is a traction landslide under the effect of continuous rainfall.