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Are simple verbal instructions sufficient to ensure that bladder volume does not deteriorate prostate position reproducibility during spot scanning proton therapy?

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BJR Open 2021年第1期3卷 20210064页

作者： Nishioka, Kentaro Gotoh, Kento Hashimoto, Takayuki Abe, Takashige Osawa, Takahiro Matsumoto, Ryuji Yokota, Isao Katoh, Norio Kinoshita, Rumiko Yasuda, Koichi Yakabe, Toshiaki Yoshimura, Takaaki Takao, Seishin Shinohara, Nobuo Aoyama, Hidefumi Shimizu, Shinichi Shirato, Hiroki Department of Radiation Medical Science and Engineering Faculty of Medicine Hokkaido University Sapporo Hokkaido Japan Department of Radiation Medical Science and Engineering Radiation Medical Physics Hokkaido University Sapporo Hokkaido Japan Department of Renal and Genitourinary Surgery Hokkaido University Graduate School of Medicine School of Medicine Sapporo Hokkaido Japan Department of Biostatistics Hokkaido University Graduate School of Medicine Sapporo Hokkaido Japan Department of Radiation Oncology Faculty of Medicine Hokkaido University Sapporo Hokkaido Japan Department of Radiation Oncology Hokkaido University Hospital Sapporo Hokkaido Japan Department of Health Sciences and Technology Faculty of Health Sciences Hokkaido University Sapporo Hokkaido Japan Global Center for Biomedical Science and Engineering Faculty of Medicine Hokkaido University Sapporo Hokkaido Japan

Objectives: The purpose of this study is to investigate whether verbal instructions are sufficient for bladder volume (BV) control not to deteriorate prostate position reproducibility in image-guided spot scanning proton therapy (SSPT) for localized prostate cancer. Methods: A total of 268 treatment sessions in 12 consecutive prostate cancer patients who were treated with image-guided SSPT with fiducial markers were retrospectively analyzed. In addition to strict rectal volume control procedures, simple verbal instructions to void urine one hour before the treatment were used here. The BV was measured by a Bladder Scan just before the treatment, and the prostate motion was measured by intraprostatic fiducial markers and two sets of X-ray fluoroscopy images. The correlation between the BV change and prostate motion was assessed by linear mixed-effects models and systematic and random errors according to the reproducibility of the BV. Results: The mean absolute BV change during treatment was from ?98.7 to 86.3 ml (median 7.1 ml). The mean absolute prostate motion of the patients in the left-right direction was ?1.46 to 1.85 mm;in the cranial-caudal direction it was ?6.10 to 3.65 mm, and in the anteroposterior direction ?1.90 to 5.23 mm. There was no significant relationship between the BV change and prostate motion during SSPT. The early and late genitourinary and gastrointestinal toxicity was minimal with a minimum follow up of 4.57 years. Conclusions: Simple verbal instructions about urination was suggested to be sufficient to control the BV not to impact on the prostate motion and clinical outcomes in image-guided SSPT. Careful attention to BV change is still needed when the seminal vesicle is to be treated. Advances in knowledge: Our data demonstrated that there was no apparent relationship between BV changes and prostate position reproducibility and simple verbal instruction about urination could be sufficient for image-guided SSPT. © 2021 The Authors.

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Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study

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The Lancet Digital Health 2025年第5期7卷 100868页

作者： Meng, Ziyao Guan, Zhouyu Yu, Shujie Wu, Yilan Zhao, Yaoning Shen, Jie Lim, Cynthia Ciwei Chen, Tingli Yang, Dawei Ran, An Ran He, Feng Hamzah, Haslina Singh, Sarkaaj Abd Raof, Anis Syazwani Lee-Boey, Jian Wen Samuel Lim, Soo-Kun Sun, Xufang Ge, Shuwang Xu, Gang Su, Hua Cheng, Yang Lu, Feng Liao, Xiaofei Jin, Hai Deng, Chenxin Ruan, Lei Zhang, Cuntai Wu, Chan Dai, Rongping Jin, Yixiao Wang, Wenxiao Li, Tingyao Liu, Ruhan Li, Jiajia Shu, Jia Lu, Yuwei Wang, Xiangning Wu, Qiang Qin, Yiming Tang, Jin Sheng, Xiaohua Jiao, Qiong Yang, Xiaokang Guo, Minyi McKay, Gareth J Hogg, Ruth E Liew, Gerald Chee, Evelyn Yi Lyn Hsu, Wynne Lee, Mong Li Szeto, Simon Luk, Andrea O Y Chan, Juliana C N Cheung, Carol Y Tan, Gavin Siew Wei Tham, Yih-Chung Cheng, Ching-Yu Sabanayagam, Charumathi Lim, Lee-Ling Jia, Weiping Li, Huating Sheng, Bin Wong, Tien Yin Shanghai Belt and Road International Joint Laboratory of Intelligent Prevention and Treatment for Metabolic Diseases Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Institute for Proactive Healthcare Shanghai Jiao Tong University Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai Diabetes Institute Shanghai Clinical Centre for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Beijing Tsinghua Changgung Hospital Eye Center School of Clinical Medicine Tsinghua Medicine Tsinghua University Beijing China Medical Records and Statistics Office Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine Shanghai China Department of Renal Medicine Singapore General Hospital SingHealth-Duke Academic Medical Centre Singapore Singapore Department of Ophthalmology Shanghai Health and Medical Center Wuxi China Department of Ophthalmology and Visual Sciences The Chinese University of Hong Kong Hong Kong Special Administrative Region China Singapore Eye Research Institute Singapore National Eye Centre Singapore Department of Medicine Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Department of Ophthalmology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Hubei Wuhan China Department of Nephrology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Nephrology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China Department of Ophthalmology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan China National Engineering Research Centre for Big Dat

Background: Improving the accessibility of screening diabetic kidney disease (DKD) and differentiating isolated diabetic nephropathy from non-diabetic kidney disease (NDKD) are two major challenges in the field of diabetes care. We aimed to develop and validate an artificial intelligence (AI) deep learning system to detect DKD and isolated diabetic nephropathy from retinal fundus images. Methods: In this population-based study, we developed a retinal image-based AI-deep learning system, DeepDKD, pretrained using 734 084 retinal fundus images. First, for DKD detection, we used 486 312 retinal images from 121 578 participants in the Shanghai Integrated Diabetes Prevention and Care System for development and internal validation, and ten multi-ethnic datasets from China, Singapore, Malaysia, Australia, and the UK (65 406 participants) for external validation. Second, to differentiate isolated diabetic nephropathy from NDKD, we used 1068 retinal images from 267 participants for development and internal validation, and three multi-ethnic datasets from China, Malaysia, and the UK (244 participants) for external validation. Finally, we conducted two proof-of-concept studies: a prospective real-world study with 3 months' follow-up to evaluate the effectiveness of DeepDKD in screening DKD;and a longitudinal analysis of the effectiveness of DeepDKD in differentiating isolated diabetic nephropathy from NDKD on renal function changes with 4·6 years' follow-up. Findings: For detecting DKD, DeepDKD achieved an area under the receiver operating characteristic curve (AUC) of 0·842 (95% CI 0·838–0·846) on the internal validation dataset and AUCs of 0·791–0·826 across external validation datasets. For differentiating isolated diabetic nephropathy from NDKD, DeepDKD achieved an AUC of 0·906 (0·825–0·966) on the internal validation dataset and AUCs of 0·733–0·844 across external validation datasets. In the prospective study, compared with the metadata model, DeepDKD could detect DKD wit

关键词： Deep learning

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A Sparse Model-inspired Deep Thresholding Network for Exponential Signal Reconstruction—Application in Fast Biological Spectroscopy

arXiv

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arXiv 2020年

作者： Wang, Zi Guo, Di Tu, Zhangren Huang, Yihui Zhou, Yirong Wang, Jian Feng, Liubin Lin, Donghai You, Yongfu Agback, Tatiana Orekhov, Vladislav Qu, Xiaobo Department of Electronic Science Biomedical Intelligent Cloud R&D Center Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance National Institute for Data Science in Health and Medicine Xiamen University China School of Computer and Information Engineering Xiamen University of Technology Xiamen China College of Chemistry and Chemical Engineering Key Laboratory for Chemical Biology of Fujian Province High-field NMR Center Xiamen University Xiamen China China Mobile Group Xiamen China Biomedical Intelligent Cloud R&D Center Xiamen University Xiamen China Department of Molecular Sciences Swedish University of Agricultural Sciences Uppsala Sweden Department of Chemistry and Molecular Biology University of Gothenburg Gothenburg Sweden

The non-uniform sampling is a powerful approach to enable fast acquisition but requires sophisticated reconstruction algorithms. Faithful reconstruction from partial sampled exponentials is highly expected in general signal processing and many applications. Deep learning has shown astonishing potential in this field but many existing problems, such as lack of robustness and explainability, greatly limit its applications. In this work, by combining merits of the sparse model-based optimization method and data-driven deep learning, we propose a deep learning architecture for spectra reconstruction from undersampled data, called MoDern. It follows the iterative reconstruction in solving a sparse model to build the neural network and we elaborately design a learnable soft-thresholding to adaptively eliminate the spectrum artifacts introduced by undersampling. Extensive results on both synthetic and biological data show that MoDern enables more robust, high-fidelity, and ultra-fast reconstruction than the state-of-the-art methods. Remarkably, MoDern has a small number of network parameters and is trained on solely synthetic data while generalizing well to biological data in various scenarios. Furthermore, we extend it to an open-access and easy-to-use cloud computing platform (XCloud-MoDern), contributing a promising strategy for further development of biological applications. Copyright © 2020, The Authors. All rights reserved.

关键词： Signal reconstruction

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Effect of pectin integration in biowaste chicken bones to produce hydroxyapatite

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AIP Conference Proceedings 2023年第1期2643卷

作者： M. W. Teoh C. K. Ng K. Y. Sara Lee S. Ramesh C. H. Ting Y. D. Chuah C. Y. Tan U. Sutharsini 1Centre for Advanced Materials Department of Materials Engineering Faculty of Engineering & Technology Tunku Abdul Rahman University College 53300 Kuala Lumpur Malaysia 2Center of Systematic Innovation Research Department of Mechanical Engineering Faculty of Engineering & Technology Tunku Abdul Rahman University College 53300 Kuala Lumpur Malaysia 3Center of Advanced Manufacturing and Material Processing Department of Mechanical Engineering Faculty of Engineering University of Malaya 50603 Kuala Lumpur Malaysia 4Faculty of Engineering Universiti Teknologi Brunei Tungku Highway Gadong BE1410 Brunei Darussalam 5Department of Mechanical and Materials & Manufacturing Engineering Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Jalan Sungai Long Bandar Sungai Long Cheras Kajang 43000 Malaysia 6Department of Mechatronics and BioMedical Engineering Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Jalan Sungai Long Bandar Sungai Long Cheras Kajang 43000 Malaysia 7Department of Physics University of Jaffna Jaffna JA 40000 Sri Lanka

Hydroxyapatite (HA) derived from chicken bones was successfully synthesized by calcination and compared with biomimetic HA prepared via chemical precipitation, using pectin-mediated synthesis process. Pectin was extracted from orange peels via microwave irradiation and integrated into chicken bone-HA with the assistance of ultrasonication and ball milling. The synthesized powders were then characterized through Fourier Transform Infrared Spectroscopy (FTIR) and energy dispersive spectroscopy (EDX). In general, all synthesized HA powders show similar elements and minerals as the pure HA despite deviation in Ca/P ratio. It was revealed that the integration of pectin was beneficial in enhancing the densification and Vickers hardness of chicken bone-HA. A high relative density of 85.53% and Vickers hardness of 3.53 GPa were achieved by the pectin-integrated cooked chicken bone-HA upon sintering at 1250 °C.

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Floquet engineering of strongly driven inelastic heat engines

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Physical Review B 2025年第24期111卷 245407-245407页

作者： Jincheng Lu Junjie Liu Jian-Hua Jiang Chen Wang Key Laboratory of Intelligent Optoelectronic Devices and Chips of Jiangsu Higher Education Institutions School of Physical Science and Technology Suzhou University of Science and Technology Suzhou 215009 People's Republic of China Advanced Technology Research Institute of Taihu Photon Center School of Physical Science and Technology Suzhou University of Science and Technology Suzhou 215009 People's Republic of China Institute for Quantum Science and Technology Shanghai Key Laboratory of High Temperature Superconductors Department of Physics International Center of Quantum and Molecular Structures Shanghai University Shanghai 200444 People's Republic of China School of Physical Science and Technology & Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou 215006 People's Republic of China School of Biomedical Engineering Division of Life Sciences and Medicine University of Science and Technology of China Hefei 230026 People's Republic of China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou 215123 People's Republic of China School of Physical Sciences University of Science and Technology of China Hefei 230026 People's Republic of China Department of Physics Zhejiang Normal University Jinhua Zhejiang 321004 People's Republic of China

Inelastic heat engines are thermodynamic machines governed by inelastic electron-photon scattering processes that promise efficient energy transport and high thermodynamic efficiency. Here we investigate thermodynamic performances and fluctuations in double quantum dots with inelastic electron-photon interactions under strong periodic driving. Using a Floquet-based quantum master equation framework, we analyze both energy conversion efficiency and thermodynamic uncertainty relations in the fast-driving regime. Our study shows that the fast-driving frequency and strong-driving amplitude play crucial roles in optimizing the performances of the inelastic heat engine. The output power and thermodynamic efficiency are greatly improved with respect to the case in absence of Floquet driving by generating multiple incoherent transition channels. They also exceed the counterparts of the elastic engines. Simultaneously, we reveal that periodic driving breaks the thermodynamic uncertainty constraints. Our findings offer a Floquet perspective for optimizing inelastic heat engines.

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Effects of sintering on the properties of ceria co-doped scandia stabilised zirconia

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AIP Conference Proceedings 2023年第1期2643卷

作者： Ignatius Lim Yuze C. K. Ng K. L. Poon C. H. Ting S. Ramesh Y. D. Chuah C. Y. Tan K. Y. Sara Lee U. Sutharsini 1Department of Mechanical and Materials & Manufacturing Engineering Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Jalan Sungai Long Bandar Sungai Long Cheras Kajang 43000 Malaysia 2Centre for Advanced Materials Department of Materials Engineering Faculty of Engineering & Technology Tunku Abdul Rahman University College 53300 Kuala Lumpur Malaysia 3Center of Advanced Manufacturing and Material Processing Department of Mechanical Engineering Faculty of Engineering University of Malaya 50603 Kuala Lumpur Malaysia 4Faculty of Engineering Universiti Teknologi Brunei Tungku Highway Gadong BE1410 Brunei Darussalam 5Department of Mechatronics and BioMedical Engineering Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul Rahman Jalan Sungai Long Bandar Sungai Long Cheras Kajang 43000 Malaysia 6Center of Systematic Innovation Research Department of Mechanical Engineering Faculty of Engineering & Technology Tunku Abdul Rahman University College 53300 Kuala Lumpur Malaysia 7Department of Physics University of Jaffna Jaffna JA 40000 Sri Lanka

Scandia stabilised zirconia (ScSZ) ceramics are promising materials for use as electrolyte in solid oxide fuel cells (SOFCs) for cleaner energy conversion and storage owing to their high ionic conductivity at high temperatures (∼850°C). However, its ionic conductivity drops when it operates at intermediate temperatures (500 -700°C) where its crystal structure transforms from the cubic phase to rhombohedral phase. Hence, ScSZ is often co-doped with trivalent cations like cerium oxide to enhance the cubic phase stability and improve its performance at intermediate temperatures. In this study, ScSZ co-doped with ceria was sintered at 1200 – 1500°C for 2 hours and quenched at different intervals to study the sintering process, and its effect on the porosity, relative density and mechanical properties (Vickers hardness and fracture toughness). Three stages of sintering were observed, where necks between particles start to form, grow and form grains while the network of porosity break down into discontinuous, closed pores. Increasing the sintering temperature accelerates the sintering process, therefore yielding parts with higher relative density but with larger grain sizes. However, it was found that the densification rate slows down with increasing sintering temperature as the pores becomes smaller and get engulfed by the grains, while the grain growth process becomes more active and uses up the energy for densification. The 1Ce10ScSZ pellet sintered at the highest sintering temperature of 1500°C for 2 hours produced the highest relative density (93.4%), Vickers hardness (6.3 GPa) and fracture toughness (2.9 MPa√m).

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Author Correction: Multiparity increases the risk of diabetes by impairing the proliferative capacity of pancreatic β cells

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Experimental & molecular medicine 2023年第12期55卷 2610页

作者： Joon Ho Moon Joonyub Lee Kyun Hoo Kim Hyun Jung Kim Hyeongseok Kim Hye-Na Cha Jungsun Park Hyeonkyu Lee So-Young Park Hak Chul Jang Hail Kim Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 Korea. Department of Internal Medicine Seoul National University Bundang Hospital Seoul National University College of Medicine Seoul Korea. Division of Endocrinology and Metabolism Department of Internal Medicine Seoul St. Mary's Hospital College of Medicine The Catholic University of Korea Seoul Republic of Korea. Biomedical Research Center Korea Advanced Institute of Science and Technology Daejeon 34141 Korea. Department of Biochemistry College of Medicine Chungnam National University Daejeon Korea. Department of Physiology College of Medicine Yeongnam University Daegu Korea. Department of Internal Medicine Seoul National University Bundang Hospital Seoul National University College of Medicine Seoul Korea. janghak@snu.ac.kr. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon 34141 Korea. hailkim@kaist.edu. Biomedical Research Center Korea Advanced Institute of Science and Technology Daejeon 34141 Korea. hailkim@kaist.edu.

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Ultrabright ratiometric Raman-guided epilepsy surgery by intraoperatively visualizing proinflammatory microglia

Cell reports. Medicine

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Cell reports. Medicine 2025年 102155页

作者： Cong Wang Zhi Li Xiao Zhu Wanbing Sun Yue Ding Wenjia Duan Difei Wang Yiqing Jiang Ming Chen Yuncan Chen Jiayi Hu Zheping Cai Jing Zhao Junfeng Wang Zhen Fan Faming Zheng Xingyu Zhou Fang Xie Jianping Zhang Yihui Guan Kui Yan Zuhai Lei Qinyue Wang Luting Wang Xiao Xiao Hairong Zheng Liang Chen Cong Li Ying Mao MOE Key Laboratory of Smart Drug Delivery MOE Innovative Center for New Drug Development of Immune Inflammatory Diseases School of Pharmacy Zhongshan Hospital Fudan University Shanghai China Greater Bay Area Institute of Precision Medicine (Guangzhou) Fudan University Guangzhou China The Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences State Key Laboratory of Biomedical Imaging Science and System Shenzhen 518055 China. Electronic address: cong_wang@***. Department of Neurosurgery Huashan Hospital Fudan University Shanghai China Department of Neurosurgery/Neuro-oncology State Key Laboratory of Oncology in South China Guangdong Provincial Clinical Research Center for Cancer Sun Yat-sen University Cancer Center Guangzhou China. Department of Clinical Pharmacy and Pharmacy Administration School of Pharmacy Fudan University Shanghai China. Department of Neurology and Research Center of Neurology in Second Affiliated Hospital and Key Laboratory of Medical Neurobiology of Zhejiang Province Zhejiang University School of Medicine Hangzhou China. Shanghai Mental Health Center Shanghai Jiao Tong University School of Medicine Shanghai China. Academy of Forensic Science Shanghai Key Laboratory of Forensic Medicine (21DZ2270800) Shanghai Key Laboratory of Forensic Medicine Key Laboratory of Forensic Science Ministry of Justice 200063 Shanghai China. Department of Neurosurgery Kings College Hospital NHS Foundation Trust Denmark Hill London UK. MOE Key Laboratory of Smart Drug Delivery MOE Innovative Center for New Drug Development of Immune Inflammatory Diseases School of Pharmacy Zhongshan Hospital Fudan University Shanghai China. Department of Neurosurgery Huashan Hospital Fudan University Shanghai China. Department of Neurology Huashan Hospital Fudan University Shanghai China. Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Ministry of Education Behavioral and Cognitive Neuroscience Center Institute of S

Resective surgery is an effective approach for long-term seizure control in drug-resistant focal epilepsy when the epileptic focus (EF) can be accurately delineated and removed. However, intraoperative mapping of EF with electrocorticography is laborious, time-consuming, and highly vulnerable to the effects of anesthesia. Here, we demonstrated that activated microglia can be reliable biomarkers for EF localization. Leveraging a newly developed ratiometric Raman nanosensor, ultraHOCls, we successfully visualize proinflammatory microglia in live epileptic mice, allowing for precise EF delineation without the interference of anesthesia. Compared to electrocorticography-guided surgery, ultraHOCl-guided surgery results in a substantial 61% reduction in total seizure burden in epileptic mouse models. Notably, ultraHOCls sprayed on freshly excised human brain tissues can effectively discriminate epileptic regions from non-epileptic tissues with high sensitivity (94.89%) and specificity (93.3%). This work provides an alternative strategy for delineating the EF intraoperatively, potentially revolutionizing surgery outcomes in epilepsy patients.

关键词： HOCl Raman imaging electrocorticography epilepsy microglia myeloperoxidase ratiometric surgery

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A 3R (remove-remodel-repair)-Integrated Self-Assembled Chlorella-Gelatin-PEG Hydrogel for Diabetic Wound Healing

Materials Today Bio

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Materials Today Bio 2025年

作者： Yulin Li Ruiying He Yu Huang Tinglin Zhang Lan Xiao Yin Xiao Haifeng Liu He Bai Shiyong Wu Minghao Xue Huifen Qiang Yan Wu Meng Li Chuan Yin Jie Gao The Key Laboratory for Ultrafine Materials of Ministry of Education State Key Laboratory of Bioreactor Engineering Engineering Research Center for Biomedical Materials of Ministry of Education School of Materials Science and Engineering East China University of Science and Technology Shanghai China College of Chemistry and Chemical Engineering Hubei University Wuhan China Wenzhou Institute of Shanghai University Wenzhou China College of Life Science Mudanjiang Medical University Mudanjiang China Department of Obstetrics and Gynecology Renmin Hospital of Wuhan University Wuhan China Changhai Clinical Research Unit Shanghai Changhai Hospital Naval Medical University Shanghai China School of Medicine and Dentistry Griffith University Gold Coast Australia Department of Dermatology Shanghai Ninth People’s Hospital Shanghai Jiaotong University Shanghai China Department of Gastroenterology Changzheng Hospital Naval Medical University Shanghai China

Diabetic wound healing remains a critical clinical challenge due to persistent bacterial infections, oxidative stress, and chronic inflammation. Inspired by the principles of traditional Chinese medicine, we developed a multifunctional hydrogel (CPGel) via solvent-driven self-assembly of bioactive Chlorella extracts, gelatin, and polyethylene glycol (PEG). The CPGel synergizes the 3R strategy: (1) Remove—complete eradication of E. coli and S. aureus via intrinsic antibacterial activity; (2) Remodel—65% ROS scavenging and immunomodulation by polarizing macrophages from proinflammatory M1 to anti-inflammatory M2 phenotypes to resolve chronic inflammation; and (3) Repair—accelerated tissue regeneration via 9-fold angiogenesis (α-SMA) and 2-fold collagen I deposition. Mechanically robust (compressive strength: 4.16 MPa; tensile strength: 627 kPa) and antifreezing (-100°C), CPGel demonstrated exceptional transparency and adhesion, ensuring seamless integration with wound sites. In diabetic mice, CPGel achieved 100% wound closure within 21 days, surpassing controls (73%), while promoting neovascularization and hair follicle regeneration. This study bridges traditional herbal medicine with advanced biomaterial engineering, offering a scalable, toxin-free platform that addresses the triad of diabetic wound pathogenesis. By harmonizing the 3R strategy-Remove, Remodel, and Repair-CPGel represents a paradigm shift in chronic wound management, with high potential for clinical translation and sustainable therapeutic design.

关键词： Chlorella Chinese herbal medicine Anti-freezing Immunomodulation Diabetic wound healing

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Neural representation of self-initiated locomotion in the secondary motor cortex of mice across different environmental contexts

Communications Biology

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Communications Biology 2025年第1期8卷 1-17页

作者： Sun, Guanglong Yu, Chencen Cai, Ruolan Li, Mingxuan Fan, Lingzhu Sun, Hao Lyu, Chenfei Lin, Yingxu Gao, Lixia Wang, Kuan Hong Li, Xinjian Department of Neurology of the Second Affiliated Hospital Interdisciplinary Institute of Neuroscience and Technology Zhejiang University School of Medicine and Key Laboratory of Medical Neurobiology of Zhejiang Province Hangzhou 310020 China Nanhu Brain-computer Interface Institute Hangzhou 311100 China McGovern Institute of Brain Research Tsinghua University Beijing 100084 China NHC and CAMS Key Laboratory of Medical Neurobiology MOE Frontier Science Center for Brain Science and Brain-machine Integration School of Brain Science and Brain Medicine Zhejiang University Hangzhou 310058 China Shanghai Ping He School Shanghai China Key Laboratory of Biomedical Engineering of Ministry of Education College of Biomedical Engineering and Instrument Science Zhejiang University Hangzhou 310027 China Unit on Neural Circuits and Adaptive Behaviors National Institute of Mental Health National Institutes of Health Bethesda 20892 MD United States Department of Neuroscience Del Monte Institute for Neuroscience University of Rochester Medical Center Rochester 14642 NY United States Key Laboratory of Medical Neurobiology of Zhejiang Province Hangzhou 310020 China

The secondary motor cortex (M2) plays an important role in the adaptive control of locomotor behaviors. However, it is unclear how M2 neurons encode the same type of locomotor control variables in different environmental contexts. Here we image the neuronal activity in M2 with a miniscope while mice are moving freely in each of three environments: a Y-maze, a running-wheel, and an open-field. These animals show distinct locomotor patterns in different environmental contexts. Surprisingly, a large population of M2 neurons are active before starting and after ceasing locomotion, while maintaining decreased neural activity during locomotion. Furthermore, the majority of these neurons are consistently engaged across various contexts, suggesting egocentric voluntary control functions. In contrast, the smaller populations of locomotion-activated M2 neurons are mostly context-specific, suggesting exocentric navigation functions. Thus, our results demonstrate that M2 neurons encode motor control variables for self-initiated locomotor behaviors in both context-dependent and context-independent manners. (Figure presented.) © The Author(s) 2025.

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