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IntroductionThe rapid evolution of the Internet of Things (IoT) and Artificial Intelligence (AI) has opened new possibilities for public healthcare. Effective integration of these technologies is essential to ensure precise and efficient healthcare delivery. This study explores the application of IoT-enabled, AI-driven systems for detecting and managing Dry Eye Disease (DED), emphasizing the use of prompt engineering to enhance system performance.MethodsA specialized prompt mechanism was developed utilizing OpenAI GPT-4.0 and ERNIE Bot-4.0 APIs to assess the urgency of medical attention based on 5,747 simulated patient complaints. A Bidirectional Encoder Representations from Transformers (BERT) machine learning model was employed for text classification to differentiate urgent from non-urgent cases. User satisfaction was evaluated through composite scores derived from Service Experiences (SE) and Medical Quality (MQ) assessments.ResultsThe comparison between prompted and non-prompted queries revealed a significant accuracy increase from 80.1% to 99.6%. However, this improvement was accompanied by a notable rise in response time, resulting in a decrease in SE scores (95.5 to 84.7) but a substantial increase in MQ satisfaction (73.4 to 96.7). These findings indicate a trade-off between accuracy and user satisfaction.DiscussionThe study highlights the critical role of prompt engineering in improving AI-based healthcare services. While enhanced accuracy is achievable, careful attention must be given to balancing response time and user satisfaction. Future research should optimize prompt structures, explore dynamic prompting approaches, and prioritize real-time evaluations to address the identified challenges and maximize the potential of IoT-integrated AI systems in medical applications.

This study explores the potential of Artificial Intelligence (AI) in early screening and prognosis of Dry Eye Disease (DED), aiming to enhance the accuracy of therapeutic approaches for eye-care practitioners. Despite the promising opportunities, challenges such as diverse diagnostic evidence, complex etiology, and interdisciplinary knowledge integration impede the interpretability, reliability, and applicability of AI-based DED detection methods. The research conducts a comprehensive review of datasets, diagnostic evidence, and standards, as well as advanced algorithms in AI-based DED detection over the past five years. The DED diagnostic methods are categorized into three groups based on their relationship with AI techniques: (1) those with ground truth and/or comparable standards, (2) potential AI-based methods with significant advantages, and (3) supplementary methods for AI-based DED detection. The study proposes suggested DED detection standards, the combination of multiple diagnostic evidence, and future research directions to guide further investigations. Ultimately, the research contributes to the advancement of ophthalmic disease detection by providing insights into knowledge foundations, advanced methods, challenges, and potential future perspectives, emphasizing the significant role of AI in both academic and practical aspects of ophthalmology.

BackgroundHigher thyroid-stimulating hormone (TSH) amidst normal thyroid hormone (TH) levels may contribute to a negative impact on cardiovascular health (CVH). We sought to probe the associations between Life’s Essential 8 (LE8), a newly revised CVH evaluation, and low thyroid function among US adults.MethodsThe datasets from the 2007-2012 National Health and Nutrition Examination Survey (NHANES) were applied to the study. Low-normal thyroid function and subclinical hypothyroidism (SCH) were both regarded to be low thyroid function. Multivariable logistic regressions were utilized to inquire about the relationship between LE8 and low thyroid function.ResultsAmong the 6,315 participants (age ≥20 years), 1,375 (21.77%) were ascertained to be low thyroid function. After adjusting possible confounders, a higher LE8 score was linked to a lower probability of experiencing low thyroid function (Odds ratio [OR] for each 10-point increase: 0.923 [95% CI, 0.884-0.964]). A similar correlation was found between the health factors score and low thyroid function (OR for each 10-point increase: 0.905 [95% CI, 0.876-0.935]). Also, scoring better on physical activity (PA), body mass index (BMI), blood lipid, blood glucose (BG), and blood pressure (BP) may be conducive to reducing the rates of low thyroid function. Furthermore, subgroup and sensitivity analyses indicated that the negative correlations were generally robust.ConclusionsThe LE8 score and health factors score were nonlinearly and negatively related to the prevalence concerning low thyroid function. Promoting the regulation of optimum CVH levels could work on mitigating the load of low thyroid function and cardiovascular diseases (CVDs).

Owing to the unique features of low Gilbert damping, long spin‐diffusion lengths, and zero Ohmic losses, magnetic insulators are promising candidate materials for next‐generation spintronic applications. However, due to the localized magnetic moments and the complex metal–oxide interface between magnetic insulators and heavy metals, spin‐functional Dzyaloshinskii–Moriya interactions or spin Hall and Edelstein effects are weak, which diminishes the performance of these typical building blocks for spintronic devices. Herein, the exchange coupling between metallic and insulating magnets is exploited for efficient electrical manipulation of heavy metal/magnetic insulator heterostructures. By inserting a thin Co layer, the spin‐orbit torque efficiency is enhanced by more than 20 times, which significantly reduces the switching current density. Moreover, field‐free current‐induced magnetization switching caused by a symmetry‐breaking non‐collinear magnetic texture is demonstrated. This work launches magnetic insulators as an alternative platform for low‐power spintronic devices.

The sensitivity and dependence of polarization and scattering on target orientation and radar incident angle pose a significant challenge in interpreting polarimetric synthetic aperture radar (PolSAR) images. Previous studies have emphasized the potential advantages of compensating for target orientation and acquiring diverse scattering information by rotating the polarimetric matrix. To fully exploit interpixel polarization information and achieve consistency in the targets' polarization orientation angle (POA), we propose a transformer-based framework that combines POA align with cyclic channel attention for PolSAR image classification. First, we select relevant features and introduce an implicit layer to facilitate unsupervised learning of POA, guiding the alignment of target orientation. Second, considering the inherent correlation between input POA channels and the necessity for more rational and efficient utilization of channel information, we devise a lightweight channel attention module with local cross-channel interaction and a cyclic padding strategy. Finally, this article is devoted to presenting a unified global modeling framework based on transformers. The primary objective is to overcome the limitations of local modeling capability in CNNs and comprehensively capture distinctions between polarization channels and intricate relationships among polarimetric information across pixels. Extensive experiments and analyses have demonstrated the robustness and effectiveness of the proposed method.

Abstract Three‐dimensional Geographic Information System (3D GIS) technology is often used in geology, mining, hydrology and other fields. It is also used in intelligent management of urban comprehensive pipe gallery projects, because the real environment with the sky, ground, and underground can be intuitively simulated in the virtual reality environment by 3D GIS platform. Through the research on data integration and application technology of urban comprehensive pipe gallery, the 3D model of comprehensive pipe gallery project data can be created based on Building Information Modelling and GIS technologies, and a comprehensive underground pipelines network management information system has been developed to realise the integration of various data, including 3D data of comprehensive pipe gallery model and underground pipe network model, 2D or 3D GIS data of the ground and underground etc. On this basis, the functions of intelligent planning and approval management, the safety analysis and disaster prevention planning and decision‐making of urban comprehensive pipe gallery projects can be further realised. The research results have been applied to the planning and construction process management of the comprehensive pipe gallery project in the sub‐centre of Beijing.

Interleukin-17A (IL-17A) levels are elevated in patients with asthma. Ferroptosis has been identified as the non-apoptotic cell death type associated with asthma. Data regarding the relation of ferroptosis with asthma and the effect of IL-17A on modulating ferroptosis in asthma remain largely unclear. The present work focused on investigating the role of IL-17A in allergic asthma-related ferroptosis and its associated molecular mechanisms using public datasets, clinical samples, human bronchial epithelial cells, and an allergic asthma mouse model. We found that IL-17A was significantly upregulated within serum in asthma cases. Adding IL-17A significantly increased ferroptosis within human bronchial epithelial cells (BEAS-2B). In ovalbumin (OVA)-induced allergic asthmatic mice, IL-17A regulated and activated lipid peroxidation induced ferroptosis, whereas IL-17A knockdown effectively inhibited ferroptosis in vivo by protection of airway epithelial cells via the xCT-GSH-GPX4 antioxidant system and reduced airway inflammation. Mouse mRNA sequencing results indicated that the tumor necrosis factor (TNF) pathway was the differential KEGG pathway in the OVA group compared to healthy controls and the OVA group compared to the IL-17A knockout OVA group. We further used N-acetylcysteine (TNF inhibitor) to inhibit the TNF signaling pathway, which was found to protect BEAS-2B cells from IL-17A induced lipid peroxidation and ferroptosis damage. Our findings reveal a novel mechanism for the suppression of ferroptosis in airway epithelial cells, which may represent a new strategy for the use of IL-17A inhibitors against allergic asthma.