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A century ago, the Warburg effect was first proposed, revealing that cancer cells predominantly rely on glycolysis during the process of tumorigenesis, even in the presence of abundant oxygen, shifting the main pathway of energy metabolism from the tricarboxylic acid cycle to aerobic glycolysis. Recent studies have unveiled the dynamic transfer of mitochondria within the tumor microenvironment, not only between tumor cells but also between tumor cells and stromal cells, immune cells, and others. In this review, we explore the pathways and mechanisms of mitochondrial transfer within the tumor microenvironment, as well as how these transfer activities promote tumor aggressiveness, chemotherapy resistance, and immune evasion. Further, we discuss the research progress and potential clinical significance targeting these phenomena. We also highlight the therapeutic potential of targeting intercellular mitochondrial transfer as a future anti-cancer strategy and enhancing cell-mediated immunotherapy. Graphical Abstract Mitochondrial Transfer in the Tumor Microenvironment. This review elaborates in detail on the molecular mechanisms and pathophysiological significance behind the mitochondrial transfer occurring between tumor cells and their microenvironment. This biological phenomenon of mitochondrial transfer is prevalent in a variety of cancers, including both solid tumors and hematologic malignancies, with a high incidence in acute myeloid leukemia (AML), breast cancer, and gliomas. The review also discusses therapeutic approaches targeting mitochondrial transfer, with a special focus on its application in immunotherapy, particularly in CAR-T cell therapy, where it has begun to show unique advantages

The timely detection of falls and alerting medical aid is critical for health monitoring in elderly individuals living alone. This paper mainly focuses on issues such as poor adaptability, privacy infringement, and low recognition accuracy associated with traditional visual sensor-based fall detection. We propose an infrared video-based fall detection method utilizing spatial-temporal graph convolutional networks (ST-GCNs) to address these challenges. Our method used fine-tuned AlphaPose to extract 2D human skeleton sequences from infrared videos. Subsequently, the skeleton data was represented in Cartesian and polar coordinates and processed through a two-stream ST-GCN to recognize fall behaviors promptly. To enhance the network’s recognition capability for fall actions, we improved the adjacency matrix of graph convolutional units and introduced multi-scale temporal graph convolution units. To facilitate practical deployment, we optimized time window and network depth of the ST-GCN, striking a balance between model accuracy and speed. The experimental results on a proprietary infrared human action recognition dataset demonstrated that our proposed algorithm accurately identifies fall behaviors with the highest accuracy of 96%. Moreover, our algorithm performed robustly, identifying falls in both near-infrared and thermal-infrared videos.

Crop diseases and pests pose a critical threat to global food security and agricultural sustainability. Traditional control methods are often limited by delayed diagnosis and a lack of capability for personalized solutions. To address these challenges, we developed a knowledge-enhanced diagnostic and treatment agent, optimized through multi-source knowledge fusion and farmer feedback. The agent integrates disease identification results from a visual model, multi-factor contextual parameters, and a crop knowledge graph. These components form a unified multi-source knowledge representation. The system converts multi-criteria farmer evaluations into reward signals, enabling continuous optimization of action strategies through interaction with real-world environments. Under the combined guidance of multi-source knowledge and farmer feedback-driven reinforcement learning, the agent can generate accurate and practically applicable treatment recommendations without additional task-specific fine-tuning of the generative model. Experiments on multiple baseline models demonstrate that combining these components consistently achieves the best performance. BERTScore increases by 25.23% on average, accuracy based on large language model evaluation improves by 30.27%, and practicality increases by 37.67%. These results validate the effectiveness and generalization capability of the proposed method.

Circadian pace is modulated by light intensity, known as the Aschoff’s rule, with largely unrevealed mechanisms. Here we report that photoreceptor CRY2 mediates blue light input to the circadian clock by directly interacting with clock core component PRR9 in blue light dependent manner. This physical interaction dually blocks the accessibility of PRR9 protein to its co-repressor TPL/TPRs and the resulting kinase PPKs. Notably, phosphorylation of PRR9 by PPKs is critical for its DNA binding and repressive activity, hence to ensure proper circadian speed. Given the labile nature of CRY2 in strong blue light, our findings provide a mechanistic explanation for Aschoff’s rule in plants, i.e., blue light triggers CRY2 turnover in proportional to its intensity, which accordingly releasing PRR9 to fine tune circadian speed. Our findings not only reveal a network mediating light input into the circadian clock, but also unmask a mechanism by which the Arabidopsis circadian clock senses light intensity. Circadian pace is modulated by light intensity. Here the authors show that CRY2 interacts with PRR9 to mediate blue light input to the circadian clock and is degraded at higher light intensity offering a mechanistic explanation as to how intensity can modify clock place.

Heat stress is a current challenge for livestock production, and its impact could dramatically increase if global temperatures continue to climb. Exposure of agricultural animals to high ambient temperatures and humidity would lead to substantial economic losses because it compromises animal performance, productivity, health, and welfare. The gut microbiota plays essential roles in nutrient absorption, energy balance, and immune defenses through profound symbiotic interactions with the host. The homeostasis of those diverse gut microorganisms is critical for the host’s overall health and welfare status and also is sensitive to environmental stressors, like heat stress, reflected in altered composition and functionality. This article aims to summarize the research progress on the interactions between heat stress and gut microbiome and discuss the potential use of the gut microbiota composition as a biomarker of heat stress in monogastric animal species. A comprehensive understanding of the gut microbiota’s role in responding to or regulating physiological activities induced by heat stress would contribute to developing mitigation strategies.

Brown planthopper (BPH) is the most devastating pest of rice. Host-plant resistance is the most desirable and economic strategy in the management of BPH. To date, 29 major BPH resistance genes have been identified from indica cultivars and wild rice species, and more than ten genes have been fine mapped to chromosome regions of less than 200 kb. Four genes ( Bph14 , Bph26 , Bph17 and bph29 ) have been cloned. The increasing number of fine-mapped and cloned genes provide a solid foundation for development of functional markers for use in breeding. Several BPH resistant introgression lines (ILs), near-isogenic lines (NILs) and pyramided lines (PLs) carrying single or multiple resistance genes were developed by marker assisted backcross breeding (MABC). Here we review recent progress on the genetics and molecular breeding of BPH resistance in rice. Prospect for developing cultivars with durable, broad-spectrum BPH resistance are discussed.

Background Exercise is known to reduce the risk of gestational diabetes mellitus (GDM). However, the effectiveness of various exercise regimens in preventing GDM remains unclear, and the optimal approach has yet to be identified. This study aims to perform a systematic review and network meta-analysis to evaluate the preventive effects of different exercise interventions on GDM and to identify the most effective exercise strategy for its prevention. Methods A comprehensive search of seven databases was conducted for studies published before March 2025 that examined the relationship between exercise during pregnancy and the risk of GDM. All literature underwent a rigorous screening process based on pre-defined inclusion and exclusion criteria. The quality of evidence was assessed using the Cochrane Risk of Bias (RoB) tool. Data analysis, heterogeneity testing, publication bias assessment, and sensitivity analysis were performed using the Stata 17.0 software. Results (1) Meta-analysis revealed that the risk of GDM was significantly lower in the exercise intervention group compared to the conventional care group (OR 0.56, 95% CI = 0.44–0.71). (2) Subgroup analysis indicated that aerobic exercise (OR 0.40, 95% CI = 0.25–0.64), yoga (OR 0.19, 95% CI = 0.05–0.69), and diet and exercise guidance (OR 0.53, 95% CI = 0.37–0.76) significantly reduced the risk of GDM compared to the control group. Exercise intervention during pregnancy effectively reduced the risk of GDM in healthy individuals (OR 0.63, 95% CI = 0.43–0.93), overweight and/or obese individuals (OR 0.53, 95% CI = 0.36–0.79), and pregnant women at risk of GDM (OR 0.53, 95% CI = 0.34–0.82). Additionally, exercise intervention initiated in early pregnancy significantly prevented the development of GDM (OR 0.51, 95% CI = 0.39–0.68). (3) Network meta-analysis results demonstrated that yoga had the lowest surface under the cumulative ranking curve (SUCRA = 6.8%), suggesting that yoga was the most effective intervention in reducing the risk of GDM. Conclusion Various types of exercise, including yoga, aerobic exercise, and diet and exercise guidance, are effective in preventing GDM during pregnancy. Among these, yoga appears to be particularly promising and could be considered for inclusion in preventive care strategies for pregnant women. Trial registration The study was registered on the International Prospective Registry of Systematic Reviews (PROSPERO) database (CRD42024552641) on 10 June 2024.

Plant auxin response factor (ARF) transcription factors are an important class of key transcriptional modulators in auxin signaling. Despite the well-studied roles of ARF transcription factors in plant growth and development, it is largely unknown whether, and how, ARF transcription factors may be involved in plant resistance to pathogens. We show here that two fijiviruses (doublestranded RNA viruses) utilize their proteins to disturb the dimerization of OsARF17 and repress its transcriptional activation ability, while a tenuivirus (negative-sense single-stranded RNA virus) directly interferes with the DNA binding activity of OsARF17. These interactions impair OsARF17-mediated antiviral defense. OsARF17 also confers resistance to a cytorhabdovirus and was directly targeted by one of the viral proteins. Thus, OsARF17 is the common target of several very different viruses. This suggests that OsARF17 plays a crucial role in plant defense against different types of plant viruses, and that these viruses use independently evolved viral proteins to target this key component of auxin signaling and facilitate infection.

Rice grain is widely consumed as a staple food, providing essential nutrition for households, particularly marginalized families. It plays a crucial role in ensuring food security, promoting human nutrition, supporting good health, and contributing to global food and nutritional security. Addressing the diverse quality demands of emerging diverse and climate-risked population dietary needs requires the development of a single variety of rice grain that can meet the various dietary and nutritional requirements. However, there is a lack of concrete definition for rice grain quality, making it challenging to cater to the different demands. The lack of sufficient genetic study and development in improving rice grain quality has resulted in widespread malnutrition, hidden hunger, and micronutrient deficiencies affecting a significant portion of the global population. Therefore, it is crucial to identify genetically evolved varieties with marked qualities that can help address these issues. Various factors account for the declining quality of rice grain and requires further study to improve their quality for healthier diets. We characterized rice grain quality using Lancastrians descriptor and a multitude of intrinsic and extrinsic quality traits. Next, we examined various components of rice grain quality favored in the Asia–Pacific region. This includes preferences by different communities, rice industry stakeholders, and value chain actors. We also explored the biological aspects of rice grain quality in the region, as well as specific genetic improvements that have been made in these traits. Additionally, we evaluated the factors that can influence rice grain quality and discussed the future directions for ensuring food and nutritional security and meeting consumer demands for grain quality. We explored the diverse consumer bases and their varied preferences in Asian-Pacific countries including India, China, Nepal, Bhutan, Vietnam, Sri Lanka, Pakistan, Thailand, Cambodia, Philippines, Bangladesh, Indonesia, Korea, Myanmar and Japan. The quality preferences encompassed a range of factors, including rice head recovery, grain shape, uniform size before cooking, gelatinization, chalkiness, texture, amylose content, aroma, red-coloration of grain, soft and shine when cooked, unbroken when cooked, gelatinization, less water required for cooking, gelatinization temperature (less cooking time), aged rice, firm and dry when cooked (gel consistency), extreme white, soft when chewed, easy-to-cook rice (parboiled rice), vitamins, and minerals. These preferences were evaluated across high, low, and medium categories. A comprehensive analysis is provided on the enhancement of grain quality traits, including brown rice recovery, recovery rate of milled rice, head rice recovery, as well as morphological traits such as grain length, grain width, grain length–width ratio, and grain chalkiness. We also explored the characteristics of amylose, gel consistency, gelatinization temperature, viscosity, as well as the nutritional qualities of rice grains such as starch, protein, lipids, vitamins, minerals, phytochemicals, and bio-fortification potential. The various factors that impact the quality of rice grains, including pre-harvest, post-harvest, and genotype considerations were explored. Additionally, we discussed the future direction and genetic strategies to effectively tackle these challenges. These qualitative characteristics represent the fundamental focus of regional and national breeding strategies employed by different countries to meet consumer preference. Given the significance of rice as a staple food in Asia–Pacific countries, it is primarily consumed domestically, with only a small portion being exported internationally. All the important attributes must be clearly defined within specific parameters. It is crucial for geneticists and breeders to develop a rice variety that can meet the diverse demands of consumers worldwide by incorporating multiple desirable traits. Thus, the goal of addressing global food and nutritional security, and human healthy can be achieved.

Qifa Zhang and colleagues report the map-based cloning of the quantitative trait locus GS5, which regulates grain size and yield in rice. GS5 encodes a putative serine carboxypeptidase and increased expression is associated with larger grain. Increasing crop yield is one of the most important goals of plant science research. Grain size is a major determinant of grain yield in cereals and is a target trait for both domestication and artificial breeding 1 . We showed that the quantitative trait locus (QTL) GS5 in rice controls grain size by regulating grain width, filling and weight. GS5 encodes a putative serine carboxypeptidase and functions as a positive regulator of grain size, such that higher expression of GS5 is correlated with larger grain size. Sequencing of the promoter region in 51 rice accessions from a wide geographic range identified three haplotypes that seem to be associated with grain width. The results suggest that natural variation in GS5 contributes to grain size diversity in rice and may be useful in improving yield in rice and, potentially, other crops 2 .