Advanced SciencePub Date : 2024-11-20DOI: 10.1002/advs.202407662
Xinwen Wang, Min Wang, Qijun Lin, Lixin He, Baolin Zhang, Xin Chen, Guanhong Chen, Hong Du, Chuandong Lang, Xinsheng Peng, Yuhu Dai
{"title":"Osteoblast-Derived ECM1 Promotes Anti-Androgen Resistance in Bone Metastatic Prostate Cancer.","authors":"Xinwen Wang, Min Wang, Qijun Lin, Lixin He, Baolin Zhang, Xin Chen, Guanhong Chen, Hong Du, Chuandong Lang, Xinsheng Peng, Yuhu Dai","doi":"10.1002/advs.202407662","DOIUrl":"https://doi.org/10.1002/advs.202407662","url":null,"abstract":"<p><p>Acquired resistance to hormonal therapy, particularly enzalutamide (ENZ), remains a significant obstacle in the treatment of advanced bone metastatic prostate cancer. Here, it is demonstrated that under ENZ treatment, osteoblasts in the bone microenvironment secrete increased levels of extracellular matrix protein 1 (ECM1), which affects surrounding prostate cancer cells, promoting tumor cell proliferation and anti-androgen resistance. Mechanistically, ECM1 interacts with the enolase 1 (ENO1) receptor on the prostate cancer cell membrane, leading to its phosphorylation at the Y189 site. This event further recruits adapter proteins including growth factor receptor-bound protein 2 (GRB2) and son of sevenless homolog 1 (SOS1), which activates the downstream mitogen-activated protein kinase (MAPK) signaling pathway to induce anti-androgen resistance. Furthermore, inhibiting ECM1 or utilizing the ENO1-targeting inhibitor phosphonoacetohydroxamate (PhAH) significantly restores tumor cell sensitivity to ENZ. Taken together, a potential mechanism is identified through which osteoblast-derived ECM1 drives resistance in bone metastatic prostate cancer under ENZ treatment. Additionally, the findings indicate that ECM1 and ENO1 may serve as potential targets for developing therapies for bone metastatic castration-resistant prostate cancer.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2407662"},"PeriodicalIF":14.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-20DOI: 10.1002/advs.202404920
Alessio Lugnan, Samarth Aggarwal, Frank Brückerhoff-Plückelmann, C David Wright, Wolfram H P Pernice, Harish Bhaskaran, Peter Bienstman
{"title":"Emergent Self-Adaptation in an Integrated Photonic Neural Network for Backpropagation-Free Learning.","authors":"Alessio Lugnan, Samarth Aggarwal, Frank Brückerhoff-Plückelmann, C David Wright, Wolfram H P Pernice, Harish Bhaskaran, Peter Bienstman","doi":"10.1002/advs.202404920","DOIUrl":"https://doi.org/10.1002/advs.202404920","url":null,"abstract":"<p><p>Plastic self-adaptation, nonlinear recurrent dynamics and multi-scale memory are desired features in hardware implementations of neural networks, because they enable them to learn, adapt, and process information similarly to the way biological brains do. In this work, these properties occurring in arrays of photonic neurons are experimentally demonstrated. Importantly, this is realized autonomously in an emergent fashion, without the need for an external controller setting weights and without explicit feedback of a global reward signal. Using a hierarchy of such arrays coupled to a backpropagation-free training algorithm based on simple logistic regression, a performance of 98.2% is achieved on the MNIST task, a popular benchmark task looking at classification of written digits. The plastic nodes consist of silicon photonics microring resonators covered by a patch of phase-change material that implements nonvolatile memory. The system is compact, robust, and straightforward to scale up through the use of multiple wavelengths. Moreover, it constitutes a unique platform to test and efficiently implement biologically plausible learning schemes at a high processing speed.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2404920"},"PeriodicalIF":14.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-20DOI: 10.1002/advs.202407628
Tong Ni, Yu Sun, Zefeng Li, Tao Tan, Wei Han, Miao Li, Li Zhu, Jing Xiao, Huiying Wang, Wenpei Zhang, Yitian Ma, Biao Wang, Di Wen, Teng Chen, Justin Tubbs, Xiaofeng Zeng, Jiangwei Yan, Hongsheng Gui, Pak Sham, Fanglin Guan
{"title":"Integrated Transcriptome Analysis Reveals Novel Molecular Signatures for Schizophrenia Characterization.","authors":"Tong Ni, Yu Sun, Zefeng Li, Tao Tan, Wei Han, Miao Li, Li Zhu, Jing Xiao, Huiying Wang, Wenpei Zhang, Yitian Ma, Biao Wang, Di Wen, Teng Chen, Justin Tubbs, Xiaofeng Zeng, Jiangwei Yan, Hongsheng Gui, Pak Sham, Fanglin Guan","doi":"10.1002/advs.202407628","DOIUrl":"https://doi.org/10.1002/advs.202407628","url":null,"abstract":"<p><p>Schizophrenia (SCZ) is a complex psychiatric disorder presenting challenges for characterization. The current study aimed to identify and evaluate disease-responsive essential genes (DREGs) to enhance the molecular characterization of SCZ. RNA-sequencing data from PsychENCODE (536 SCZ patients, 832 controls) and peripheral blood transcriptome data from 144 recruited subjects (59 SCZ patients, 6 non-SCZ psychiatric patients, 79 controls) are analyzed. Shared differential expression genes are obtained using three algorithms. Support vector machine (SVM)-based recursive feature elimination is employed to identify DREGs. The biological relevance of these DREGs is examined through protein-protein interaction network, pathway enrichment, polygenic scoring, and brain tissue expression. Key DREGs are validated in SCZ animal models. A DREGs-based machine-learning model for SCZ characterization is developed and its performance is assessed using multiple datasets. The analysis identified 184 DREGs forming an interconnected network involved in synaptic plasticity, inflammation, neuronal development, and neurotransmission. DREGs exhibited distinct expression in SCZ-related brain regions and animal models. Their genetic contributions are comparable to genome-wide polygenic risk scores. The DREG-based SVM model demonstrated high performance (AUC 85% for SCZ characterization, 79% for specificity). These findings provide new insights into the molecular mechanisms underlying SCZ and emphasize the potential of DREGs in improving SCZ characterization.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2407628"},"PeriodicalIF":14.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142674618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-19DOI: 10.1002/advs.202407239
Chong Wu, Xiaoting Liu, Rong Liu, Shiyao Song, Zi-Fan Zheng, Yilin Zeng, Yong Mei, Jing-Yang Zhang, Qijia Duan, Run Lin, Jin-Zhi Du, Weiling He
{"title":"Sustained Endocytosis Inhibition via Locally-Injected Drug-Eluting Hydrogel Improves ADCC-Mediated Antibody Therapy in Colorectal Cancer.","authors":"Chong Wu, Xiaoting Liu, Rong Liu, Shiyao Song, Zi-Fan Zheng, Yilin Zeng, Yong Mei, Jing-Yang Zhang, Qijia Duan, Run Lin, Jin-Zhi Du, Weiling He","doi":"10.1002/advs.202407239","DOIUrl":"10.1002/advs.202407239","url":null,"abstract":"<p><p>The epidermal growth factor receptor (EGFR) is a validated therapeutic target for RAS/RAF wild-type colorectal cancer (CRC). However, monoclonal antibody-based anti-EGFR therapies such as cetuximab have limited effectiveness. Herein, it is identified that EGFR internalization is associated with poor treatment response and prognosis in patients with CRC, based on a retrospective analysis of patients treated with cetuximab. It is further demonstrated that the endocytosis inhibitor prochlorperazine (PCZ) can move EGFR, which is hidden inside the cell, to the cell surface to improve therapeutic antibody binding. Thus, a thermosensitive hydrogel co-loaded with cetuximab and PCZ (Gel@Cmab/PCZ) is constructed for sustained inhibition of endocytosis and effective cetuximab delivery. Peritumoral injection of Gel@Cmab/PCZ shows strong antitumor efficacy in subcutaneous and orthotopic CRC tumor models and completely abrogated liver metastasis when combined with chemotherapy. In a humanized patient-derived xenograft model, a single injection of Gel@Cmab/PCZ with one-third of the conventional cetuximab dose achieved 91% tumor growth inhibition, which promoted NK cell infiltration into tumor tissues and their antibody-dependent cell-mediated cytotoxicity effect. This study represents a novel strategy to boost the monoclonal antibody-mediated anti-tumor response in CRC.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2407239"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-19DOI: 10.1002/advs.202411187
Hao Feng, Wenhao Song, Ruyi Li, Linxin Yang, Xiaoxuan Chen, Jiajun Guo, Xuan Liao, Lei Ni, Zhou Zhu, Junyu Chen, Xibo Pei, Yijun Li, Jian Wang
{"title":"A Fully Integrated Orthodontic Aligner With Force Sensing Ability for Machine Learning-Assisted Diagnosis.","authors":"Hao Feng, Wenhao Song, Ruyi Li, Linxin Yang, Xiaoxuan Chen, Jiajun Guo, Xuan Liao, Lei Ni, Zhou Zhu, Junyu Chen, Xibo Pei, Yijun Li, Jian Wang","doi":"10.1002/advs.202411187","DOIUrl":"10.1002/advs.202411187","url":null,"abstract":"<p><p>Currently, the diagnosis of malocclusion is a highly demanding process involving complicated examinations of the dental occlusion, which increases the demand for innovative tools for occlusal data monitoring. Nevertheless, continuous wireless monitoring within the oral cavity is challenging due to limitations in sampling and device size. In this study, by embedding high-performance piezoelectric sensors into the occlusal surfaces using flexible printed circuits, a fully integrated, flexible, and self-contained transparent aligner is developed. This aligner exhibits excellent sensitivity for occlusal force detection, with a broad detection threshold and continuous pressure monitoring ability at eight distinct sites. Integrated with machine learning algorithm, this fully integrated aligner can also identify and track adverse oral habits that can cause/exacerbate malocclusion, such as lip biting, thumb sucking, and teeth grinding. This system achieved 95% accuracy in determining malocclusion types by analyzing occlusal data from over 1400 malocclusion models. This fully-integrated sensing system, with wireless monitoring and machine learning processing, marks a significant advancement in the development of intraoral wearable sensors. Moreover, it can also facilitate remote orthodontic monitoring and evaluation, offering a new avenue for effective orthodontic care.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2411187"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"RNA-Binding Protein Hnrnpa1 Triggers Daughter Cardiomyocyte Formation by Promoting Cardiomyocyte Dedifferentiation and Cell Cycle Activity in a Post-Transcriptional Manner.","authors":"Chuling Li, Yijin Chen, Qiqi Chen, Haoxiang Huang, Michael Hesse, Yilin Zhou, Ming Jin, Yu Liu, Yifei Ruan, Xiang He, Guoquan Wei, Hao Zheng, Senlin Huang, Guojun Chen, Wangjun Liao, Yulin Liao, Yanmei Chen, Jianping Bin","doi":"10.1002/advs.202402371","DOIUrl":"10.1002/advs.202402371","url":null,"abstract":"<p><p>Stimulating cardiomyocyte (CM) dedifferentiation and cell cycle activity (DACCA) is essential for triggering daughter CM formation. In addition to transcriptional processes, RNA-binding proteins (RBPs) are emerging as crucial post-transcriptional players in regulating CM DACCA. However, whether post-transcriptional regulation of CM DACCA by RBPs could effectively trigger daughter CM formation remains unknown. By performing integrated bioinformatic analysis of snRNA-seq data from neonatal and adult hearts, this study identified Hnrnpa1 as a potential RBP regulating CM DACCA. Hnrnpa1 expression decreased significantly during postnatal heart development. With the use of α-MHC-H2B-mCh/CAG-eGFP-anillin transgenic mice, Hnrnpa1 overexpression promoted CM DACCA, thereby triggering daughter CM formation and enhancing cardiac repair after myocardial infarction (MI). In contrast, CRISPR/Cas9 technology is used to generate CM-specific Hnrnpa1 knockout mice. Hnrnpa1 knockout inhibited cardiac regeneration and worsened cardiac function in the neonatal MI model. Nanopore RNA sequencing, RIP assay, IP-MS, MeRIP-qPCR, PAR-CLIP and luciferase reporter experiments showed that Hnrnpa1 induced Mettl3 post-transcriptional splicing to inhibit m6A-dependent Pbx1 and E2F1 degradation, thereby increasing Runx1, Ccne1, Cdk2 and Ccnb2 expression to promote CM DACCA. In conclusion, Hnrnpa1 triggered daughter CM formation by promoting CM DACCA in a post-transcriptional manner, indicating that Hnrnpa1 might serve as a promising target in cardiac repair post-MI.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2402371"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-19DOI: 10.1002/advs.202409291
Bowen Jiang, Xiang Chen, Xiaoxin Pan, Li Tao, Yuangqiang Huang, Jiahao Tang, Xiaoqing Li, Peixiong Wang, Guokun Ma, Jun Zhang, Hao Wang
{"title":"Advances in Metal Halide Perovskite Memristors: A Review from a Co-Design Perspective.","authors":"Bowen Jiang, Xiang Chen, Xiaoxin Pan, Li Tao, Yuangqiang Huang, Jiahao Tang, Xiaoqing Li, Peixiong Wang, Guokun Ma, Jun Zhang, Hao Wang","doi":"10.1002/advs.202409291","DOIUrl":"10.1002/advs.202409291","url":null,"abstract":"<p><p>The memristor has recently demonstrated considerable potential in the field of large-scale data information processing. Metal halide perovskites (MHPs) have emerged as the leading contenders for memristors due to their sensitive optoelectronic response, low power consumption, and ability to be prepared at low temperatures. This work presents a comprehensive enumeration and analysis of the predominant research advancements in mechanisms of resistance switch (RS) behaviors in MHPs-based memristors, along with a summary of useful characterization techniques. The impact of diverse optimization techniques on the functionality of perovskite memristors is examined and synthesized. Additionally, the potential of MHPs memristors in data processing, physical encryption devices, artificial synapses, and brain-like computing advancement of MHPs memristors is evaluated. This review can prove a valuable reference point for the future development of perovskite memristors applications. In conclusion, the current challenges and prospects of MHPs-based memristors are discussed in order to provide insights into potential avenues for the development of next-generation information storage technologies and biomimetic applications.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2409291"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ginkgetin Alleviates Inflammation and Senescence by Targeting STING.","authors":"Yadan Liu, Jialin Ye, Zisheng Fan, Xiaolong Wu, Yinghui Zhang, Ruirui Yang, Bing Jiang, Yajie Wang, Min Wu, Jingyi Zhou, Jingyi Meng, Zhiming Ge, Guizhen Zhou, Yuan Zhu, Yichuan Xiao, Mingyue Zheng, Sulin Zhang","doi":"10.1002/advs.202407222","DOIUrl":"10.1002/advs.202407222","url":null,"abstract":"<p><p>Ginkgo biloba extract is reported to have therapeutic effects on aging-related disorders. However, the specific component responsible for this biological function and its mechanism of action remain largely unknown. This study finds that Ginkgetin, an active ingredient of Ginkgo biloba extract, can alleviate cellular senescence and improve pathologies in multiple tissues of aging mice. To reveal the molecular mechanism of Ginkgetin's anti-aging effect, a graph convolutional network-based drug \"on-target\" pathway prediction algorithm for prediction is employed. The results indicate that the cGAS-STING pathway may be a potential target for Ginkgetin. Subsequent cell biological and biophysical data confirmed that Ginkgetin directly binds to the carboxy-terminal domain of STING protein, thereby inhibiting STING activation and signal transduction. Furthermore, in vivo pharmacodynamic data showed that Ginkgetin effectively alleviates systemic inflammation in Trex1<sup>-/-</sup> mice and inhibits the abnormally activated STING signaling in aging mouse model. In summary, this study, utilizing an artificial intelligence algorithm combined with pharmacological methods, confirms STING serves as a critical target for Ginkgetin in alleviating inflammation and senescence. Importantly, this study elucidates the specific component and molecular mechanism underlying the anti-aging effect of Ginkgo biloba extract, providing a robust theoretical basis for its therapeutic use.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2407222"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-19DOI: 10.1002/advs.202412419
Peng Tian, Jie Zheng, Keying Qiao, Yuxiao Fan, Yue Xu, Tao Wu, Shuting Chen, Yinuo Zhang, Bingyue Zhang, Chiara Ambrogio, Haiyun Wang
{"title":"scPharm: Identifying Pharmacological Subpopulations of Single Cells for Precision Medicine in Cancers.","authors":"Peng Tian, Jie Zheng, Keying Qiao, Yuxiao Fan, Yue Xu, Tao Wu, Shuting Chen, Yinuo Zhang, Bingyue Zhang, Chiara Ambrogio, Haiyun Wang","doi":"10.1002/advs.202412419","DOIUrl":"10.1002/advs.202412419","url":null,"abstract":"<p><p>Intratumour heterogeneity significantly hinders the efficacy of anticancer therapies. Compared with drug perturbation experiments, which yield pharmacological data at the bulk cell level, single-cell RNA sequencing (scRNA-seq) technology provides a means to capture molecular heterogeneity at single-cell resolution. Here, scPharm is introduced, a computational framework that integrates pharmacological profiles with scRNA-seq data to identify pharmacological subpopulations of cells within a tumour and prioritize tailored drugs. scPharm uses the normalized enrichment scores (NESs) determined from gene set enrichment analysis to assess the distribution of cell identity genes in drug response-determined gene lists. Based on the strong correlation between the NES and drug response at single-cell resolution, scPharm successfully identified the sensitive subpopulations in ER-positive and HER2-positive human breast cancer tissues, revealed dynamic changes in the resistant subpopulation of human PC9 cells treated with erlotinib, and expanded its ability to a mouse model. Its superior performance and computational efficiency are confirmed through comparative evaluations with other single-cell prediction tools. Additionally, scPharm predicted combination drug strategies by gauging compensation or booster effects between drugs and evaluated drug toxicity in healthy cells in the tumour microenvironment. Overall, scPharm provides a novel approach for precision medicine in cancers by revealing therapeutic heterogeneity at single-cell resolution.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2412419"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Advanced SciencePub Date : 2024-11-19DOI: 10.1002/advs.202408683
Zhendong Luo, Peng Zhang, Huwang Hou, Yiming Li, Binzhao Li, Yanji Yi, Lianjie Xu, Ting Meng, Zihan Geng, Mu Ku Chen, Yang Zhao
{"title":"Colorimetric Thermography by a Long-Infrared Dual-Band Metalens.","authors":"Zhendong Luo, Peng Zhang, Huwang Hou, Yiming Li, Binzhao Li, Yanji Yi, Lianjie Xu, Ting Meng, Zihan Geng, Mu Ku Chen, Yang Zhao","doi":"10.1002/advs.202408683","DOIUrl":"10.1002/advs.202408683","url":null,"abstract":"<p><p>Infrared (IR) radiation thermography is extensively utilized in diverse fields due to its non-contact capability. Nevertheless, its effectiveness is often compromised by the significant emissivity variations among different objects, limiting its application to specific setups or focused object types. Colorimetric thermography is introduced as an alternative emissivity-independent method of radiation thermometry. This technique involves measuring radiance across two or more spectral bands and calculating the object's temperature based on the signal ratio, thereby mitigating emissivity effects under certain conditions. However, this method has the trade-off of necessitating bulky optical systems, complex filter imaging configurations, and sensor structures. To meet the requirements of IR thermography for compact structure, lightweight design, and customizability, a dual-band metalens is developed for the IR colorimetric thermography. The central wavelengths targeted are 9.5 and 12.5 µm. The dual-band IR imaging by the fabricated dual-band metalens is demonstrated, and the colorimetric thermography of low-emissivity objects is performed without presetting emissivity values. This approach significantly eliminates measurement errors associated with emissivity by an average of 50.16% across a temperature range of 60-180 °C. This innovation paves the way for dynamic and multi-target thermography using compact IR systems in complex environments.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e2408683"},"PeriodicalIF":14.3,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142666877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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