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Cell Organoid

Metformin: a potential game-changer in skin cancer treatment

Dermatofibrosarcoma protuberans (DFSP) is a rare skin sarcoma known for its high recurrence rates, making treatment particularly challenging. While surgery remains the standard option, it often leads to scarring and other complications. Current in vitro models struggle to capture the complexity of the skin tumor environment, especially the role of immune cells. These limitations highlight the need for more accurate models to explore new treatment strategies. Due to these issues, advancing alternative therapies that can minimize surgical impact while effectively controlling tumor growth is crucial. Published by Tsinghua University Press, Cell Organoid featured the findings (DOI: 10.26599/CO.2024.9410001) of researchers from Shanghai Lisheng Biotech and Shanghai Ninth People’s Hospital in 2024. The team successfully developed patient-derived organoids from DFSP tumors, closely replicating the histological and genetic characteristics of clinical samples. Using these organoids, they tested both metformin and imatinib, a drug already approved for DFSP treatment. Their study revealed that, beyond inhibiting tumor growth, metformin uniquely impacted immune pathways, suggesting a new therapeutic role for the drug in cancer treatment. The researchers developed DFSP organoids without the use of enzymes, maintaining the tumor’s natural immune environment. These organoids contained 11 different cell types, including immune cells, offering a detailed model for drug testing. Both metformin and imatinib were shown to reduce tumor growth, but metformin stood out by significantly altering the expression of genes related to immune system activity and cancer cell signaling. This indicates that metformin doesn’t just target tumor cells but also influences the surrounding immune environment, providing a dual mechanism of action. This ability to modulate immune responses highlights metformin’s potential as a repurposed cancer treatment, particularly for rare skin tumors like DFSP. By preserving the tumor’s complexity, the organoids provide a valuable platform for screening drugs and exploring personalized therapies that go beyond standard treatments. Dr. Jun Chen, a lead researcher, explained the significance of the findings: “By creating DFSP organoids, we’ve gained crucial insights into how drugs affect both tumor and immune cells. Metformin’s unique ability to modulate immune signaling opens up new treatment possibilities that could minimize the need for surgery. This approach not only helps us better understand the biology of these tumors but also suggests ways to improve outcomes for patients with difficult-to-treat cancers like DFSP.” The success of metformin in modulating immune pathways within DFSP organoids suggests broader applications for cancer treatment. These organoids provide a highly accurate model for testing other drugs and personalized therapies, especially in cancers that are difficult to treat. By replicating the tumor microenvironment, this model opens new doors for developing targeted treatments. As researchers continue to explore metformin’s effects, its repurposing for cancer therapy could revolutionize treatment strategies for rare skin cancers and improve patient outcomes. The work was supported by the National Natural Science Foundation of China (Nos. 82373719, 82173662, and 32200581), Natural Science Foundation of Shanghai (No. 21ZR1436800), and Clinical Research Project of Multi-Disciplinary Team, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine (No. 201901). See the article: Patient-derived skin tumor organoids with immune cells respond to metformin About Cell Organoid Cell Organoid aims to provide a worldwide platform for research into all aspects of organoids and their applications in medicine. It is an open access, peer-reviewed journal that publishes high-quality articles dealing with a wide range of basic research, clinical and translational medicine study topics in the field.
Life Sciences and Medicine
Tsinghua Science and Technology

Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives

With the rapid development of cloud computing, more and more applications have migrated or will migrate to cloud platforms. Cloud platforms provide applications with powerful computing capabilities, flexible resource allocation, and high scalability, ensuring that applications can achieve better performance, cost, and energy efficiency. In addition, cloud computing brings other advantages to applications, such as global deployment, high availability, and robust data processing capabilities, enabling applications to flexibly meet user requirements, deliver faster and more stable services, and provide a seamless experience for users worldwide. However, due to dynamic cloud environments, diverse user requests and services, and elastic cloud resource provisioning, the resource management for cloud applications faces significant challenges, and applications often suffer from long queue time, erratic performance, resource contention and idleness, and high energy consumption. To address the above problems, the MAPE cycle, a proactive application intelligence O&M framework, has been proposed and promoted. It consists of four steps: monitoring, analysis, planning, and execution, where the analysis step is to predict the future workloads of applications and guide the proper resource management decisions in the planning step to avoid QoS degradation, cost and energy inefficiencies, etc. Therefore, workload prediction is a critical step in intelligent O&M and is essential for execution quality assurance throughout the application lifecycle. A team led by Prof. Zhijun Ding at Tongji University, China, recently reviewed the latest cloud workload prediction papers and related key technologies. This work classifies existing cloud workload prediction work from the new perspective of "application-oriented," deeply analyses the variability and heterogeneity of application workloads, and systematically explains how existing work can guide workload prediction by using application evolution characteristics and how to guide proactive long- and short-term resource management practices based on workload prediction results. Based on this, it summarises the technical challenges and future research directions that have yet to be addressed by existing research. The team published their review in Tsinghua Science and Technology (DOI: 10.26599/TST.2024.9010024) on 11 September 2024. Specifically: (1) It provides an overview of the basic features associated with workload prediction, including prediction goals, modeling techniques, evaluation metrics, and datasets. (2) It analyses two characteristics of cloud applications, including variability and heterogeneity, and how application-specific features affect their workload variations. And it classifies recently published work on workload prediction based on the features of cloud applications as well as research ideas, summarises research motivations, main contributions and core ideas. (3) It classifies work on proactive cloud application resource management based on workload prediction, including long-term management, such as proactive capacity planning, application deployment, and dynamic migration, and short-term management, such as proactive request scheduling, resource allocation, and elastic scaling. (4) It reveals outstanding technical challenges and potential development opportunities in current research on workload prediction, including the following aspects: large-scale application, serverless application, multi-topology awareness, large prediction model, model interpretability, and model unreliability. The authors include Binbin Feng and Zhijun Ding from the Key Laboratory of Embedded System and Service Computing, Ministry of Education, and the Department of Computer Science and Technology at Tongji University in Shanghai, China. This work was supported by the National Natural Science Foundation of China (62372330). About the Authors Zhijun Ding received the PhD degree in computer application technology from Tongji University, Shanghai, China, in 2007. Currently, he is a professor with the Department of Computer Science and Technology, Tongji University, Shanghai, China. His research interests include formal methods, Petri nets, services computing, and workflow. He has published more than 100 papers in domestic and international academic journals and conference proceedings. Binbin Feng is a doctoral student in the Department of Computer Science and Technology at Tongji University. His research direction is cloud workload online prediction method and its application. Until now, he has published academic papers at TPDS, TSC, TSE journals and WWW, ICWS and IEEE CLOUD conferences. [1] B. Feng and Z. Ding, "Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives," in Tsinghua Science and Technology, vol. 30, no. 1, pp. 34-54, February 2025, doi: 10.26599/TST.2024.9010024.  See the article: Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives About Tsinghua Science and Technology Tsinghua Science and Technology is sponsored by Tsinghua University and published bimonthly, 2023 Impact Factor of 5.2, ranking in Q1 in the "Computer Science, Software Engineering", "Computer Science, Information System", and "Engineering, Electrical & Electronic" areas in SCIE, according to JCR 2023. This journal aims at presenting the achievements in computer science, electronic engineering, and other IT fields. This journal has been indexed by SCIE, EI, Scopus, etc. Contributions all over the world are welcome.
Information Sciences
Energy and Climate Management

The C-REM 4.0 model: A CGE model for provincial analysis of China’s carbon neutrality target

Computable General Equilibrium (CGE) models have become increasingly prevalent 31 climate policy assessment, offering valuable insights into the complex and interconnected economic and environmental impacts of climate mitigation strategies. The China Regional Energy Model (C-REM) is a recursive-dynamic, multi-sector, multi-regional CGE model extensively used in modeling China’s energy and climate policies, focusing on the distribution of effects across provinces. The development team of C-REM from Tsinghua University and Massachusetts Institute of Technology recently outlined the model’s historical applications, described the modeling methods used in its newly updated version, and illustrated its features by showing illustrative simulation results for China’s carbon neutrality target. It can help foster transparency and knowledge sharing within the community of CGE modelers and researchers in the field of climate policies. The team published their review in Energy and Climate Management (DOI: 10.26599/ECM.2024.9400006) on July 31, 2024. “C-REM aims to assess the impacts of China’s existing and prospective carbon emissions reduction targets, propose methods for distributing the national target to the provincial level, evaluate different emissions reduction actions, and finally provide well-founded policy recommendations,” said Da Zhang, corresponding author of the paper, associate professor in the Institute of Energy, Environment and Economy at Tsinghua University. The team presents an overview of the evolution and historical applications of the C-REM. From the initial static version, the C-REM model has gradually expanded to a recursive dynamic model and integrated with other models (such as the atmospheric chemistry transport model) to assess the economic and environmental impacts of climate policies comprehensively. The C-REM model has been applied to the provincial impact assessment of climate policy in China, the analysis of interprovincial migration impact on climate policy, and the co-benefits of climate policy on air quality and human health. The model has been updated to the 4.0 version to address long-term emissions reduction challenges, such as how to achieve the carbon neutrality target. “We updated the model with 2017 as the base year and extended the projection horizon to 2060. We also introduced carbon capture and storage (CCS) technologies into the model, recognizing the growing importance of negative emissions technologies in realizing carbon neutrality,” said Da Zhang. The modeling methods used in the C-REM 4.0 are described in detail, including the model sectors and regions, data preparation procedures, representation of the economic activities of different sectors, climate policy simulation methods, dynamic process, and programming implementation. An illustrative example of applying the updated model is provided under the context of the carbon neutrality target in China. “We find that the 2060 carbon neutrality target will lead to a lower and earlier peak in total primary energy consumption with a transition towards non-fossil energy sources compared to the prior target, which focused only on the timing of the carbon peak. Our scenarios further suggest that the electricity and metal smelting sectors are the main contributors to CO2 reduction between 2025 and 2060. Assuming the current effort-sharing principle continues to be used for emissions reduction target allocation among provinces, more developed provinces and provinces that rely more on fossil-based energy will bear higher costs in a net zero energy transition. Certain northwest provinces are projected to experience positive impacts due to industry relocation, driven by abundant renewable resources and carbon storage capacity,” said Da Zhang. The research team expects the paper to guide model users and spur further development of CGE modeling in China. Da Zhang said, “The C-REM 4.0 is well-equipped for future applications in climate policy analysis under China’s carbon neutrality target. We expect to link our model further with other models, such as earth system models, to capture the environment and climate feedback on the human system. We also plan to use the updated model to explore more alternative policy designs in greater detail toward carbon neutrality.” Other contributors include Hantang Peng, Chenfei Qu from the Institute of Energy, Environment and Economy at Tsinghua University, and Valerie J. Karplus from the Department of Engineering and Public Policy at Carnegie Mellon University. This work was supported by Special Projects No. 72140005 and No. 42341202 of the National Natural Science Foundation of China. See the article: The C-REM 4.0 model: A CGE model for provincial analysis of China’s carbon neutrality target About Energy and Climate Management Managing the changing climate and energy transition are two closely related scientific and policy challenges of our society. Energy and Climate Management is an open access, peer-reviewed scholarly, policy-oriented academic journal dedicated to publishing interdisciplinary scientific papers on cutting-edge research on contemporary energy and climate management analysis. The Journal is exclusively available via SciOpen and aims to incentivize a meaningful dialogue between academics, think tanks, and public authorities worldwide. Contributions are welcomed covering areas related to energy and climate management, especially policy, economics, governance, and finance. Online submission portal available at https://mc03.manuscriptcentral.com/jecm.
Humanities and Social Sciences
Journal of Advanced Ceramics

Effect of Sc substitution on the phase composition, microstructure, and properties of (Tb1-xScx)3(Al1-yScy)2Al3O12 transparent ceramics

A team of material scientists led by Jiang Li from Shanghai Institute of Ceramics, Chinese Academy of Sciences, in Shanghai, China recently reported (Tb1-xScx)3(Al1-yScy)2Al3O12 (TSAG) magneto-optical ceramics with high optical quality. The effect of Sc substitution on the crystal structure, sintering process, microstructure, optical transmittance, and magneto-optical property of the TSAG ceramics is studied in detail. Antisite defects (ADs) and Sc replacement in TAG are further studied by first-principles calculations to figure out the working mechanism of Sc. It was found that Sc can suppress the secondary phase and improve the optical quality of TAG ceramics. As optical quality occupies one of the most important parts of the practical performance of magneto-optical ceramics, Sc2O3 is considered to be a promising and effective additive. The team published their research article in Journal of Advanced Ceramics (DOI: 10.26599/JAC.2024.9220948) on August 1, 2024. In high-performance laser devices, Faraday isolators are one of the important components that can prevent the front-end system from disturbance and damage caused by a back-reflected beam. Magneto-optical materials are thus widely studied as they are key elements of Faraday isolators. Among magneto-optical materials applied in the visible to near-infrared wavelength band, TAG ceramics have been considered to be one of the most promising materials thanks to their high Verdet constant and good thermo-optic properties. However, the manufacturing process of TAG ceramics should be further optimized to reduce the optical loss and make them applicable for practical use. Optical scattering from the secondary phases is one of the most important problems for TAG ceramics, originated from the narrow solid-solution range. Based on the existing problems and difficulties of TAG ceramics, the research team proposed their own solutions. “If Sc3+ tends to occupy both Tb3+ and Al3+ sites, it is possible that a slight deviation of Tb/Al ratio will not bring secondary phase in TAG ceramics after adding sufficient Sc3+, because the Sc3+ might ‘automatically’ fill either of the vacant sites,” said Jiang Li, senior author of the research paper, vice director of the Transparent Ceramics Research Center, Shanghai Institute of Ceramics, Chinese Academy of Sciences. Dr. Li is also a professor in Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences. “The mechanism of Sc2O3 eliminating the secondary phases in TAG was discussed by combining the experiment and calculations. The results indicate that Sc2O3 is an effective additive for improving the optical quality of TAG ceramics,” Jiang Li said. The result is that Sc2O3 improves the optical transmittance of the ceramics by suppressing the secondary phase, thanks to the increase of solubility. “The in-line transmittance of the TSAG ceramics reaches 82.2% at 1064 nm and 81.2% at 633 nm, which are close to the theoretical transmittance of TAG. No secondary phase or residual pores can be detected by FESEM,” said Jiang Li. “To figure out the solubility of TAG, the limit of Sc replacement, and to further understand the mechanism of Sc2O3 suppressing secondary phases, first-principles calculations on antisite defects (ADs) and Sc replacement were performed,” said Jiang Li,“ The range of Tb/Al becomes 0.5332~0.9747 at 2023 K after Sc substitution with adequate quantity, which is much wider than that in TAG (0.6000~0.6027) calculated from ADs. The solid-solution range of TAG can be enlarged and the secondary phase can be suppressed by Sc doping, no matter which component is excess. Conceivably, Sc2O3 will be an effective additive for the stability of optical quality of the ceramics in mass production.” The research team also found the side-effects caused by Sc substitution. “As the concentration of magneto-optical ion (Tb3+) decreases with increasing Sc content, the Verdet constant decreases from -188.1 rad·T-1·m-1 to -161.4 rad·T-1·m-1 at 633 nm. All the values are higher than that of the commercial TGG (-136 rad·T-1·m-1) and TSAG crystals (-152 rad·T-1·m-1), and the results show that Sc2O3 is an effective additive improving the optical quality of TAG and maintain the superiority in magneto-optical property.” said Jiang Li. After considering the factors comprehensively, the research team makes the assessment. Jiang Li said, “These results demonstrate that Sc substitution brings significant benefits to the fabrication of TSAG ceramics with both high optical quality and high Verdet constant.” In the future, the research team will further reduce the optical loss coefficient and fabricate the TSAG ceramics with larger aperture and thickness. Other contributors include Lixuan Zhang, Chen Hu, Xiao Li, Zhenzhen Zhou, Tingsong Li, Yiyang Liu, and Lexiang Wu from the Transparent Ceramics Research Center at Shanghai Institute of Ceramics, Chinese Academy of Sciences in Shanghai, China. This work was supported by the National Key R&D Program of China (Grant No. 2023YFB3812000), the General Project of Shanghai Natural Science Foundation (Grant No. 22ZR1471500), and the Prospective Basic Research and Applied Basic Research of Hengdian Group. See the article: Effect of Sc substitution on the phase composition, microstructure, and properties of (Tb1−xScx)3(Al1−yScy)2Al3O12 transparent ceramics About Journal of Advanced Ceramics Journal of Advanced Ceramics (JAC) is an international academic journal that presents the state-of-the-art results of theoretical and experimental studies on the processing, structure, and properties of advanced ceramics and ceramic-based composites. JAC is Fully Open Access, monthly published by Tsinghua University Press, and exclusively available via SciOpen. JAC’s 2023 IF is 18.6, ranking in Top 1 (1/31, Q1) among all journals in “Materials Science, Ceramics” category, and its 2023 CiteScore is 21.0 (top 5%) in Scopus database. ResearchGate homepage: https://www.researchgate.net/journal/Journal-of-Advanced-Ceramics-2227-8508
Ceramics
Journal of Intelligent Construction

Urban flooding alert: subway tunnels get early warning system

In recent years, urban waterlogging disasters have become more frequent due to rapid urbanization and climate change, severely threatening city infrastructure. Subway tunnels, with their semi-enclosed structure, face significant risks during floods, leading to difficult evacuations and substantial casualties. Statistics show that over 160 cities in China experience flood disasters annually, causing severe economic losses and fatalities. Due to these challenges, in-depth research on flood monitoring and early warning systems for subway tunnels is essential to enhance urban disaster prevention and mitigation capabilities. Researchers from Tsinghua University, in collaboration with Beijing Urban Construction Design & Development Group Co., Ltd., have developed an innovative monitoring system. Published in the Journal of Intelligent Construction on May 16, 2024, the study (DOI: 10.26599/JIC.2024.9180011) presents a comprehensive approach to flood inundation depth monitoring and prediction in subway tunnels. The study introduces an intelligent system designed for real-time monitoring and early warning of flood invasions in subway tunnels. Through scaled model experiments, the researchers identified fundamental flood patterns and developed formulas to predict water depth and flow dynamics. This system can quickly determine the flow rate and entry point of floodwater, forecasting future flood trends at a relatively low cost. The workflow is divided into three phases: pre-disaster, disaster outbreak, and during-disaster, each with specific monitoring requirements. This comprehensive approach allows the system to provide accurate and timely information for emergency decision-making. By integrating meteorological and hydrological data with real-time tunnel monitoring, the system enhances the ability to track flood risks and respond effectively to emergencies, offering a practical tool for improving subway safety during urban waterlogging events. Dr. Hong Huang, the lead researcher, stated, "Our system represents a significant advancement in urban safety technology. By integrating real-time data and predictive modeling, we can offer immediate and actionable insights during flood emergencies, potentially saving lives and reducing economic losses." This innovative flood monitoring and early warning system has broad applications in enhancing subway safety and urban infrastructure resilience. It can be integrated into smart city frameworks, providing critical data for disaster management and emergency response teams. The system's predictive capabilities offer a proactive approach to flood disaster mitigation, ensuring safer and more resilient urban environments. This work was supported by the National Natural Science Foundation of China (No. 72091512) and Department of Engineering Physics, Tsinghua University–Beijing Urban Construction Design & Development Group Co., Limited Joint Research Center for Urban Disaster Prevention and Safety. See the article: Monitoring and early warning mechanism of flood invasion into subway tunnels based on the experimental study of flooding patterns About Journal of Intelligent Construction Journal of Intelligent Construction (JIC), sponsored by Tsinghua University and the China National Committee on Large Dams, published by Tsinghua University Press (TUP) and exclusively available via SciOpen, is a peer-reviewed journal for publishing original research papers, case studies, reviews and comments regarding the use of novel technologies in all domains of civil engineering, e.g., hydraulic engineering, structural engineering, geotechnical engineering, transportation, and construction management. The journal focuses on the application of advanced theories, methodologies, and tools, such as machine learning, sensors, robotics, 5G, the Internet of Things, artificial intelligence, building information modelling, and computational methods, etc., in all stages of the construction life cycle, which makes the process more intelligent and efficient. The journal also covers other essential areas of civil engineering, e.g., planning and design, operation and maintenance, and disaster mitigation.
Physical Sciences and Engineering
CAAI Artificial Intelligence Research

AI is learning to read your emotions, and here’s why that can be a good thing

Using a fusion of traditional and novel technological methods, researchers are hoping to better quantify emotions to transform the face of the emotion quantification field Human emotions are complex and are not always easily able to be boiled down to a recognizable pattern. Determining one’s emotional state can be difficult human-to-human, and the many nuances of existence as an emotional entity seem impossible to train a non-human entity to understand, identify and learn from. However, a considerable amount of work and research has been put into training artificial intelligence (AI) to observe, quantify and recognize various states of emotion in humans. The fusion of tried and true psychological methods combined with the intelligence and trainability of AI can make emotion recognition technology invaluable in fields such as healthcare and education. Results were published in CAAI Artificial Intelligence Research (DOI: 10.26599/AIR.2024.9150040) on August 21, 2024. Where conventional techniques are limited, AI can improve. Through the use of a multitude of developments, such as gesture recognition technology, facial emotion recognition (FER) and multi-modal emotional recognition, emotional recognition technology stands a chance to be transformational for many individuals and fields of study as a whole.  “This technology has the potential to transform fields such as healthcare, education, and customer service, facilitating personalized experiences and enhanced comprehension of human emotions,” said Feng Liu, author and researcher of the review. An artificial intelligence that understands human emotion and can appropriately interact given the emotional input of the human can be revolutionary for human-computer interactions and can be a key in assessing the mental health status of an individual. This isn’t done through just one form of input, but instead can also take physiology into account. For example, some techniques can take input from the electrical activity of the brain through an EEG scan and combine that with eye movement technology to monitor people’s expressions. Other measurements of emotional arousal such as heart-rate variability and electrical skin response are also tools that are used to convert the intangible “emotion” into patterns and recognizable, readable data for AI to learn from and improve. Multi-modal emotion recognition similarly combines different perceptual channels, such as sight, hearing and touch to gain a more complete picture of what emotions can entail. The combination of different fields and techniques is necessary to create an accurate and well-rounded representation of the complexities of human emotion. “It is believed that interdisciplinary collaboration between AI, psychology, psychiatry and other fields will be key in achieving this goal and unlocking the full potential of emotion quantification for the benefit of society,” said Liu. Having AI be able to correctly recognize human emotions can be especially useful in a world where mental health is quickly becoming a top priority. Emotion quantification AI can help in monitoring an individual’s mental health and create personalized experiences for that individual, all without having to entangle another person in the process. Successful use of emotion recognition and quantification AI requires a few major components. One concern that would need to be addressed is safety and transparency, especially as it relates to more sensitive topics such as medical and psychological counseling. Data handling practices and privacy measures taken by the entities using this type of AI will have to be stringent. Additionally, ensuring the AI can adapt to the nuances of cultures is of utmost importance, as this will maintain the integrity and reliability of the AI for future referencing and learning. Feng Liu of the School of Computer Science and Technology at East China Normal University is the author and researcher of this study. The Beijing Key Laboratory of Behavior and Mental Health supported this research.  See the article: Artificial Intelligence in Emotion Quantification: A Prospective Overview About CAAI Artificial Intelligence Research CAAI Artificial Intelligence Research (CAAI AIR) is an Open Access, peer-reviewed scholarly journal, published by Tsinghua University Press, released exclusively on SciOpen. CAAI AIR aims to publish the state-of-the-art achievements in the field of artificial intelligence and its applications, including knowledge intelligence, perceptual intelligence, machine learning, behavioral intelligence, brain and cognition, AI chips and applications, etc. Original research and review articles on but not limited to the above topics are welcome. The journal is completely Open Access with no article processing fees for authors.
Information Sciences
Energy Materials and Devices

Harnessing the power of porosity: a new era for aqueous zinc-ion batteries and large-scale energy storage

As the global demand for energy storage solutions grows, the limitations of current lithium-ion batteries, such as safety concerns and high costs, have driven the exploration of alternative technologies. Aqueous zinc-ion batteries (AZIBs) have emerged as a promising candidate due to their inherent safety, cost-effectiveness, and environmental sustainability. However, challenges like zinc dendrite growth continue to hinder their widespread adoption. Due to these challenges, there is a pressing need to delve deeper into innovative solutions to improve AZIB performance. The study (DOI: 10.26599/EMD.2024.9370040), conducted by researchers from Tsinghua University and the University of Technology Sydney, was published in Energy Materials and Devices on August 16, 2024. It provides a comprehensive review of recent advancements in the engineering of porous zinc metal anodes for AZIBs. The focus of the research is on the structural orderliness of these porous anodes and their critical role in enhancing battery performance. The review underscores the potential of porous zinc anodes in overcoming the limitations of traditional planar zinc anodes. The research highlights the significant advantages of porous zinc anodes over traditional planar zinc anodes. The porous structures provide numerous nucleation sites, which reduce the nuclear energy barriers and mitigate localized charge accumulation. This, in turn, suppresses dendrite growth, ensuring a longer battery lifespan. The study also emphasizes the role of three-dimensional porous structures in facilitating uniform electric field distribution and homogeneous ion flux, which are crucial for stable zinc deposition and stripping. Additionally, the substantial internal volume in these anodes accommodates volume changes and deposition stress, further enhancing battery performance. The review presents various fabrication techniques for porous zinc anodes, including etching, self-assembly, laser lithography, electrochemical methods, and 3D printing. The researchers also provide strategic insights into the design of porous zinc anodes to facilitate the practical implementation of AZIBs for grid-scale energy storage applications. Prof. Dong Zhou, one of the lead researchers, remarked, "The development of porous zinc anodes represents a significant step forward in the advancement of zinc-ion batteries. By addressing the dendrite growth issue, we are moving closer to making AZIBs a commercially viable alternative to lithium-ion batteries. Our work not only provides a comprehensive understanding of the current advancements but also offers strategic insights into future research directions." The innovative design of porous zinc anodes has the potential to revolutionize the field of energy storage. By improving the performance and safety of AZIBs, these anodes could enable the development of large-scale, sustainable energy storage systems, crucial for integrating renewable energy sources into the grid. Moreover, the advancements in porous zinc anodes could also lead to the development of safer and more cost-effective batteries for a wide range of applications, from electric vehicles to portable electronics, thus contributing to the global transition towards cleaner energy solutions. Funding information This work is granted by National Natural Science Foundation of China (Grant No. 22309102), China Postdoctoral Science Foundation (Grant No. 2222M711788), National Key Research and Development Program of China (Grant No.2022YFB2404500), Fundamental Research Project of Shenzhen (Grant No. JCYJ20230807111702005), the Australian Research Council through the ARC Discovery Project (Grant No. DP230101579) and ACR Linkage Project (Grant No. LP200200926).   See the article: Porous zinc metal anodes for aqueous zinc-ion batteries: Advances and prospectives About Energy Materials and Devices Energy Materials and Devices is launched by Tsinghua University, published quarterly by Tsinghua University Press, exclusively available via SciOpen, aiming at being an international, single-blind peer-reviewed, open-access and interdisciplinary journal in the cutting-edge field of energy materials and devices. It focuses on the innovation research of the whole chain of basic research, technological innovation, achievement transformation and industrialization in the field of energy materials and devices, and publishes original, leading and forward-looking research results, including but not limited to the materials design, synthesis, integration, assembly and characterization of devices for energy storage and conversion etc.
Physical Sciences and Engineering
Food Science of Animal Products

Edible insects show promise as sustainable nutritional source

As the global population grows and traditional livestock production increasingly strains environmental resources, there is a rising interest in alternative protein sources. Edible insects, particularly grasshoppers, are abundant in regions like Cameroon and provide essential nutrients, including proteins, amino acids, and minerals vital for health and growth. Addressing these challenges calls for in-depth studies on the nutritional benefits of insects such as Ruspolia nitidula. Conducted by the University of Dschang, Cameroon, and published (DOI: 10.26599/FSAP.2024.9240068) in the journal Food Science of Animal Products on August 30, this study examined the effects of substituting traditional Clupea harengus fish meal with Ruspolia nitidula grasshopper meal in rat diets. Over 12 weeks, researchers evaluated how this dietary change impacted libido, sleep, hair growth, and overall health, assessing the insect meal's potential as a viable alternative protein source. The study demonstrated that replacing fish meal with Ruspolia nitidula grasshopper meal resulted in significant health improvements in rats. Those on the grasshopper diet exhibited enhanced libido, with increased intromissions and ejaculations compared to rats on fish meal or protein-deficient diets. Sleep quality also improved, with rats experiencing longer, more restful sleep. Hair quality was notably superior, with 94.58% of hairs in optimal condition in the grasshopper-fed group, compared to just 5.55% and 0.27% in the fish meal and protein-deficient groups. Additionally, the grasshopper-fed rats showed greater body weight gain, indicating overall better health and nutrition. These findings underscore the grasshopper meal's potential as a sustainable and nutritionally superior alternative protein source. Dr. Ngnaniyyi Abdoul, the study's lead researcher, remarked, "Our findings highlight the significant potential of edible insects like Ruspolia nitidula as alternative protein sources. The grasshopper meal not only meets nutritional needs but also offers substantial health benefits, including improved libido, better sleep, and enhanced hair quality, with far-reaching implications for both animal and human diets." This research emphasizes the potential of Ruspolia nitidula as a sustainable, nutrient-rich protein alternative. Beyond animal feed, the findings suggest that grasshopper meal could play a role in addressing human malnutrition, particularly in low-resource settings. With ecological advantages and health benefits, edible insects present a compelling solution for future food security and dietary enhancement. The North Cameroon Association for Ecological and Food Transition (ABC-ECOLO) for funding this study. See the article: Nutritional and health benefits of Cameroonian grasshopper (Ruspolia nitidula) meal: effects on libido, sleep, hair growth and hunger in rats About Food Science of Animal Products Food Science of Animal Products, sponsored by Beijing Academy of Food Sciences, published by Tsinghua University Press and exclusively available via SciOpen, is a peer-reviewed, open access international journal that publishes the latest research findings in the field of animal-origin foods, involving food materials such as meat, aquatic products, milk, eggs, animal offals and edible insects. The research scope includes the quality and processing characteristics of food raw materials, the relationships of nutritional components and bioactive substances with human health, product flavor and sensory characteristics, the control of harmful substances during processing or cooking, product preservation, storage and packaging; microorganisms and fermentation, illegal drug residues and food safety detection; authenticity identification; cell-cultured meat, regulations and standards.
Life Sciences and Medicine
Food & Medicine Homology

Blending medicine with cuisine: a new chapter in health

A paradigm shift is underway in healthcare, as the ancient concept of "medicine and food homology" seamlessly transitions into modern "food-medicine homology" practices. This evolution, catalyzed by global health trends and the COVID-19 pandemic, integrates traditional Chinese medicine's intrinsic link between food and medicinal properties, laying a foundation for contemporary diet therapy and health maintenance. The transformation is set to significantly influence global health and wellness by assimilating into modern lifestyles, promoting a more conscious approach to food as a therapeutic agent. Long the bedrock of traditional Chinese medicine, the "medicine and food homology" principle has long dictated health-conscious eating. Yet, in the face of modernization and the blending of global health trends, there's an urgent call to innovate upon these historical guidelines. The complex interplay of evolving consumer attitudes, groundbreaking science, and shifting lifestyles poses challenges that demand a deeper dive into how this age-old philosophy can be modernized for today's world. Academics from the National R&D Center for Edible Fungus Processing Technology and the University of Auckland present a comprehensive review (DOI: 10.26599/FMH.2024.9420014) in the Food & Medicine Homology journal, published on 25 July 2024. This scholarly work provides an in-depth review of how the age-old concept of medicine and food homology is being revolutionized to fit contemporary lifestyles and health needs. The study illuminates the transition of "medicine and food homology" from a traditional framework to a modern health strategy. With meticulous attention to historical development and current trends, it showcases the COVID-19 pandemic's significant role in accelerating this shift. The research provides a critical view of how this transformation affects food processing, dietary habits, consumer perceptions, and life choices, advocating for a comprehensive health approach that blends ancient insights with modern imperatives. The study's in-depth analysis strongly advocates for the modernization and globalization of the food-medicine homology theory, charting a course for future exploration and advancement in this field. Professor Wen-Yi Kang (the corresponding author) and Professor Dong-Xiao Sun-Waterhouse (the first author) underscore the importance of integrating traditional wisdom with contemporary healthcare, "Our review is designed to showcase the potential of integrating ancient dietary practices with modern living, enhancing health and preventing diseases through the strategic use of food as medicine." The study's findings have profound implications for the future of healthcare, signaling a move towards personalized nutrition and proactive health management. The potential integration of medicine-food dual-use substances into mainstream healthcare could instigate a fundamental change in disease prevention and treatment. This research points towards an integrated, sustainable approach to wellness, aligning with the growing consumer preference for holistic health solutions. See the article: Transformation from traditional medicine-food homology to modern food-medicine homology About the Authors Professor Dong-Xiao Sun-Waterhouse has experience in not only on-farm research to improve the properties of foods like fruits, vegetables, grains or raw milk, but also post-farm studies on food processing and development. Areas of expertise include functional/wellness foods and personalized diets for optimizing human physical, mental and emotional wellness as well as body functional performance. In 2016, she received an award for outstanding contribution by the International Commission of Agricultural and Biosystems Engineering in Denmark. In 2018, she received the 2018 NZIFST “Leadership in the Food Industry” Award in New Zealand. In 2020, 2021, 2022 and 2023, she was named in the Stanford University's list of Top 2% scientists in the world. Prof. Wenyi Kang’s research field is the biological effect of food and medicine homology. He already obtains 40 projects including National Key R&D Program of China, National Natural Science Foundation, Department of Key Research Projects in Henan Province and Key R&D Program. Participated in the formulation of 9 national standards. More than 400 research papers have been published in esteemed international journals including Carbohydrate Polymers, International Journal of Biological Macromolecules and Food Chemistry.  About Food & Medicine Homology Food & Medicine Homology is a peer-reviewed, cross-disciplinary, open access journal dedicated to cutting-edge research integrating findings in food science and medicine. The journal publishes papers dealing with plants, animals and microorganisms, reporting the food resources and base materials with nutritional and medicinal values and health-promoting effects that are discovered and confirmed using modern scientific theories and technologies, and providing insights into their health-promoting functions, underlying molecular mechanisms of action and regulatory modes.
Life Sciences and Medicine
Carbon Future

Development strategies for using carbon-based catalysts in CO2 conversion

One of the primary drivers of climate change, CO2 emissions, have reached over 35 million tons worldwide. With global annual temperatures still rising, reducing CO2 emissions has become a necessity. To turn this necessity into an opportunity, researchers have been working to find ways to capture the CO2, thereby reducing emissions and then converting that CO2 into valuable chemicals and fuels.   One of the difficulties in working with CO2 is that it is very thermodynamically stable. To overcome this, additional energy and a strong catalyst are needed to drive the reaction. A research group at China University of Petroleum (East China) has been investigating the use of carbon-based catalysts in the conversion process. They have designed several different very effective synthesis strategies using these catalysts in the catalytic conversion of CO2. A review of their work was published in Carbon Future on September 10. “In this review, we summarized the development strategy of catalysts by carbon species assisting method in our research group, which can be applied for CO2 thermochemical and electrochemical hydrogenation. This review aims to inspire new ideas for CO2 hydrogenation through the design of carbon-based catalysts,” said Mingbo Wu, a professor at the College of New Energy, State Key Laboratory of Heavy Oil Processing at the China University of Petroleum (East China) and lead author of the paper. The researchers chose to focus on carbon species because their physical and chemical properties make them good candidates as catalysts, they can be relatively inexpensive and are very stable. Carbon-based catalysts can also play various roles in the preparation and process of CO2 catalytic conversion. They can be used to modify the structure of catalyst, as supports of catalyst, as electronic regulators of catalyst and as the bulk catalysts. CO2 conversion occurs via CO2 hydrogenation, the addition of hydrogen atoms to the CO2 and removing its oxygen atoms. This is accomplished using either the energy from electrocatalysis, which uses electricity to drive the process, or thermocatalysis, which uses heat to drive the process. In order to avoid increasing the amount of pollutants and green-house gases, Wu’s team recommends using green renewable energy as the energy source wherever possible. Wu’s team has designed and researched several different catalyst strategies. An example of one of these strategies is the electrocatalysis reduction of CO2 via a carbon-based catalytic material. In essence, CO2 is converted to HCOO, formate, which is a nontoxic, easy to transport and very promising green fuel. The difficulty in designing these strategies lies in building a process that is both efficient and stable, hence the importance of the design of the process and the type of catalyst used. The researchers carried out the conversion using carburized iridium oxide nanorods, a metallic oxide. The process they designed uses the carbon species’ ability to modulate the electronic structure of metals, thus enhancing the activity of catalysts and selectivity of formate, said Wenhang Wang, a researcher from the School of Chemistry and Chemical Engineering at Liaocheng University and first author of the paper. “We will always be committed to the development and application of carbon-based catalysts. With the development on the design concept of the catalyst and characterization technology, we strongly believe that a clear roadmap of the utilization of carbon materials for catalysts is drawn and the breakthrough in this field will be witnessed in the near future,” Wu said. Other contributors include Wenhang Wang from the Shandong Provincial Key Laboratory of Chemical Energy Storage and Novel Cell Technology, School of Chemistry and Chemical Engineering, Liaocheng University, China and the College of New Energy, State Key Laboratory of Heavy Oil Processing, China University of Petroleum (East China), Qingdao, China; Yang Wang and Hui Ning from the College of New Energy, State Key Laboratory of Heavy Oil Processing, China University of Petroleum (East China), Qingdao, China; and Xiangjin Kong from the Shandong Provincial Key Laboratory of Chemical Energy Storage and Novel Cell Technology, School of Chemistry and Chemical Engineering, Liaocheng University, China.   This work was supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China and the Taishan Scholar Project.   See the article: Carbon-based material for CO2 catalytic conversion applications   About Carbon Future Carbon Future is an open access, peer-reviewed and international interdisciplinary journal, published by Tsinghua University Press and exclusively available via SciOpen. Carbon Future reports carbon-related materials and processes, including catalysis, energy conversion and storage, as well as low carbon emission process and engineering. Carbon Future will publish Research Articles, Reviews, Minireviews, Highlights, Perspectives, and News and Views from all aspects concerned with carbon. Carbon Future will publish articles that focus on, but not limited to, the following areas: carbon-related or -derived materials, carbon-related catalysis and fundamentals, low carbon-related energy conversion and storage, low carbon emission chemical processes.
Physical Sciences and Engineering
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