Pub Date : 2025-12-01eCollection Date: 2026-02-02DOI: 10.1016/j.xinn.2025.101216
{"title":"A brilliant, if imperfect, legacy: In memory of James Watson.","authors":"","doi":"10.1016/j.xinn.2025.101216","DOIUrl":"https://doi.org/10.1016/j.xinn.2025.101216","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"7 2","pages":"101216"},"PeriodicalIF":25.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12881744/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143966","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-31eCollection Date: 2026-02-02DOI: 10.1016/j.xinn.2025.101170
Ting Luo, Yun Hu, Yonghong Zhou, Puyou Jia, Ye Sha
{"title":"Degradable thermosets with tailored properties using a single monomer.","authors":"Ting Luo, Yun Hu, Yonghong Zhou, Puyou Jia, Ye Sha","doi":"10.1016/j.xinn.2025.101170","DOIUrl":"https://doi.org/10.1016/j.xinn.2025.101170","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"7 2","pages":"101170"},"PeriodicalIF":25.7,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12881747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-06eCollection Date: 2026-02-02DOI: 10.1016/j.xinn.2025.101123
Tianjie Yang, Jia He, Xian'ao Zhao, Congmin Ren, Zhuoli Ding, Lu Wang, Hanqing Zhao, Ling Chu, Siyuan Luo, Chaojing Shi, Lusheng Gu, Tao Xu, Ge Yang, Wei Ji
In deep learning super-resolution microscopy, concerns exist about the generation of artifacts, and methods for artifact suppression are lacking. We developed a self-adaptive fine-tuning method that dynamically adjusts the parameters of the models to minimize the loss function, which includes direct quantification of artifacts from live-cell imaging. Integrating self-adaptive fine-tuning with super-resolution models enables significant artifact reduction in the visualization of nanoscale organelle interactions at high spatial-temporal resolution.
{"title":"Self-adaptive fine-tuning of deep learning super-resolution microscopy for artifact suppression in live-cell imaging.","authors":"Tianjie Yang, Jia He, Xian'ao Zhao, Congmin Ren, Zhuoli Ding, Lu Wang, Hanqing Zhao, Ling Chu, Siyuan Luo, Chaojing Shi, Lusheng Gu, Tao Xu, Ge Yang, Wei Ji","doi":"10.1016/j.xinn.2025.101123","DOIUrl":"https://doi.org/10.1016/j.xinn.2025.101123","url":null,"abstract":"<p><p>In deep learning super-resolution microscopy, concerns exist about the generation of artifacts, and methods for artifact suppression are lacking. We developed a self-adaptive fine-tuning method that dynamically adjusts the parameters of the models to minimize the loss function, which includes direct quantification of artifacts from live-cell imaging. Integrating self-adaptive fine-tuning with super-resolution models enables significant artifact reduction in the visualization of nanoscale organelle interactions at high spatial-temporal resolution.</p>","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"7 2","pages":"101123"},"PeriodicalIF":25.7,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12881779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.xinn.2025.101110
Samuel Hundessa, Wenzhong Huang, Rongbin Xu, Zhengyu Yang, Qi Zhao, Antonio Gasparrini, Ben Armstrong, Michelle L Bell, Veronika Huber, Aleš Urban, Micheline Coelho, Francesco Sera, Shilu Tong, Dominic Royé, Jan Kyselý, Francesca de'Donato, Malcolm Mistry, Aurelio Tobias, Carmen Íñiguez, Martina S Ragettli, Simon Hales, Souzana Achilleos, Jochem Klompmaker, Shanshan Li, Yuming Guo
An unprecedented heatwave swept the globe in 2023, marking it one of the hottest years on record and raising concerns about its health impacts. However, a comprehensive assessment of the heatwave-related mortality and its attribution to human-induced climate change remains lacking. We aim to address this gap by analyzing high-resolution climate and mortality data from 2,013 locations across 67 countries/territories using a three-stage modeling approach. First, we estimated historical heatwave-mortality associations using a quasi-Poisson regression model with distributed lag structures, considering lag effects, seasonality, and within-week variations. Second, we pooled the estimates in meta-regression, accounting for spatial heterogeneity and potential changes in heatwave-mortality associations over time. Third, we predicted grid-specific (0.5 0.5) association in 2023 and calculated the heatwave-related excess deaths, death ratio, and death rate per million people. Attribution analysis was conducted by comparing heatwave-related mortality under factual and counterfactual climate scenarios. We estimated 178,486 excess deaths (95% empirical confidence interval [eCI], 159,892≥204,147) related to the 2023 heatwave, accounting for 0.73% of global deaths, corresponding to 23 deaths per million people. The highest mortality rates occurred in Southern (120, 95% eCI, 116≥126), Eastern (107, 95% eCI, 100≥114), and Western Europe (66, 95% eCI, 62≥70), where the excess death ratio was also higher. Notably, 54.29% (95% eCI, 45.71%≥61.36%) of the global heatwave-related deaths were attributable to human-induced climate change. These results underscore the urgent need for adaptive public health interventions and climate mitigation strategies to reduce future mortality burdens in the context of increasing global warming.
{"title":"Global excess deaths associated with heatwaves in 2023 and the contribution of human-induced climate change.","authors":"Samuel Hundessa, Wenzhong Huang, Rongbin Xu, Zhengyu Yang, Qi Zhao, Antonio Gasparrini, Ben Armstrong, Michelle L Bell, Veronika Huber, Aleš Urban, Micheline Coelho, Francesco Sera, Shilu Tong, Dominic Royé, Jan Kyselý, Francesca de'Donato, Malcolm Mistry, Aurelio Tobias, Carmen Íñiguez, Martina S Ragettli, Simon Hales, Souzana Achilleos, Jochem Klompmaker, Shanshan Li, Yuming Guo","doi":"10.1016/j.xinn.2025.101110","DOIUrl":"10.1016/j.xinn.2025.101110","url":null,"abstract":"<p><p>An unprecedented heatwave swept the globe in 2023, marking it one of the hottest years on record and raising concerns about its health impacts. However, a comprehensive assessment of the heatwave-related mortality and its attribution to human-induced climate change remains lacking. We aim to address this gap by analyzing high-resolution climate and mortality data from 2,013 locations across 67 countries/territories using a three-stage modeling approach. First, we estimated historical heatwave-mortality associations using a quasi-Poisson regression model with distributed lag structures, considering lag effects, seasonality, and within-week variations. Second, we pooled the estimates in meta-regression, accounting for spatial heterogeneity and potential changes in heatwave-mortality associations over time. Third, we predicted grid-specific (0.5 0.5) association in 2023 and calculated the heatwave-related excess deaths, death ratio, and death rate per million people. Attribution analysis was conducted by comparing heatwave-related mortality under factual and counterfactual climate scenarios. We estimated 178,486 excess deaths (95% empirical confidence interval [eCI], 159,892≥204,147) related to the 2023 heatwave, accounting for 0.73% of global deaths, corresponding to 23 deaths per million people. The highest mortality rates occurred in Southern (120, 95% eCI, 116≥126), Eastern (107, 95% eCI, 100≥114), and Western Europe (66, 95% eCI, 62≥70), where the excess death ratio was also higher. Notably, 54.29% (95% eCI, 45.71%≥61.36%) of the global heatwave-related deaths were attributable to human-induced climate change. These results underscore the urgent need for adaptive public health interventions and climate mitigation strategies to reduce future mortality burdens in the context of increasing global warming.</p>","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"6 10","pages":"101110"},"PeriodicalIF":25.7,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7618246/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145287448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-30eCollection Date: 2026-02-02DOI: 10.1016/j.xinn.2025.101144
Ricardo Vinuesa, Pilar Manchón, Sergio Hoyas, Javier García-Martínez
{"title":"Balancing AI and human insights in scientific discovery: Challenges and guidelines.","authors":"Ricardo Vinuesa, Pilar Manchón, Sergio Hoyas, Javier García-Martínez","doi":"10.1016/j.xinn.2025.101144","DOIUrl":"https://doi.org/10.1016/j.xinn.2025.101144","url":null,"abstract":"","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"7 2","pages":"101144"},"PeriodicalIF":25.7,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12881746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Since the 20th century, the global soybean trade has undergone major changes, shaped by rising demand, climate-related risks, and shifting international dynamics. Despite its global importance, important gaps remain in understanding the complex drivers and sustainability challenges of this transformation. This review synthesizes both direct and indirect forces reshaping trade flows, spanning market dynamics, supply chain logistics, policy shifts, and technological innovation. We examine how soybean trade expansion has impacted deforestation, inequality, and food security, and assess the responses of governments and companies to address these challenges. Finally, we provide a forward-looking perspective on the strategic pathways needed to ensure a more resilient and sustainable global soybean system. The integrated insights offered in this review can inform sustainable trade strategies and foster cross-scale policy coordination for a more resilient global agri-food system.
{"title":"Global soybean trade dynamics: Drivers, impacts, and sustainability.","authors":"Dailiang Peng, Hongchi Zhang, Yizhou Zhang, Le Yu, Minpeng Chen, Jing M Chen, Liangzhi You, Peiwu Li, Jianguo Liu, Xiaoyang Zhang, Damien Arvor, Patrick Kuchler, Jianxi Huang, Hankui Zhang, Pengyu Hao, Jingfeng Huang, Zhou Shi, Fumin Wang, Kaishan Song, Zhiyuan Pei, Cunjun Li, Yue Xie, Qi Zhang, Meijuan Liang, Hui Li, Jinkang Hu, Zihang Lou, Shijun Zheng, Xuxiang Feng, Hao Peng, Xiyu Li, Alfredo Huete, Bing Zhang","doi":"10.1016/j.xinn.2025.101124","DOIUrl":"https://doi.org/10.1016/j.xinn.2025.101124","url":null,"abstract":"<p><p>Since the 20th century, the global soybean trade has undergone major changes, shaped by rising demand, climate-related risks, and shifting international dynamics. Despite its global importance, important gaps remain in understanding the complex drivers and sustainability challenges of this transformation. This review synthesizes both direct and indirect forces reshaping trade flows, spanning market dynamics, supply chain logistics, policy shifts, and technological innovation. We examine how soybean trade expansion has impacted deforestation, inequality, and food security, and assess the responses of governments and companies to address these challenges. Finally, we provide a forward-looking perspective on the strategic pathways needed to ensure a more resilient and sustainable global soybean system. The integrated insights offered in this review can inform sustainable trade strategies and foster cross-scale policy coordination for a more resilient global agri-food system.</p>","PeriodicalId":36121,"journal":{"name":"The Innovation","volume":"7 2","pages":"101124"},"PeriodicalIF":25.7,"publicationDate":"2025-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12881757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}