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Although 5-methylcytosine (m 5 C) is a widespread modification in RNAs, its regulation and biological role in pathological conditions (such as cancer) remain unknown. Here, we provide the single-nucleotide resolution landscape of messenger RNA m 5 C modifications in human urothelial carcinoma of the bladder (UCB). We identify numerous oncogene RNAs with hypermethylated m 5 C sites causally linked to their upregulation in UCBs and further demonstrate YBX1 as an m 5 C ‘reader’ recognizing m 5 C-modified mRNAs through the indole ring of W65 in its cold-shock domain. YBX1 maintains the stability of its target mRNA by recruiting ELAVL1. Moreover, NSUN2 and YBX1 are demonstrated to drive UCB pathogenesis by targeting the m 5 C methylation site in the HDGF 3′ untranslated region. Clinically, a high coexpression of NUSN2, YBX1 and HDGF predicts the poorest survival. Our findings reveal an unprecedented mechanism of RNA m 5 C-regulated oncogene activation, providing a potential therapeutic strategy for UCB. Chen et al. provide an m 5 C landscape in bladder cancer and show m 5 C enrichment at oncogene mRNAs that promotes tumour progression. They identify YBX1 as the m 5 C ‘reader’ that recruits ELAVL1 to stabilize mRNAs.

Long noncoding RNAs (lncRNAs) are emerging as a new class of important regulators of signal transduction in tissue homeostasis and cancer development. Liquid–liquid phase separation (LLPS) occurs in a wide range of biological processes, while its role in signal transduction remains largely undeciphered. In this study, we uncovered a lipid-associated lncRNA, small nucleolar RNA host gene 9 ( SNHG9 ) as a tumor-promoting lncRNA driving liquid droplet formation of Large Tumor Suppressor Kinase 1 (LATS1) and inhibiting the Hippo pathway. Mechanistically, SNHG9 and its associated phosphatidic acids (PA) interact with the C-terminal domain of LATS1, promoting LATS1 phase separation and inhibiting LATS1-mediated YAP phosphorylation. Loss of SNHG9 suppresses xenograft breast tumor growth. Clinically, expression of SNHG9 positively correlates with YAP activity and breast cancer progression. Taken together, our results uncover a novel regulatory role of a tumor-promoting lncRNA (i.e., SNHG9 ) in signal transduction and cancer development by facilitating the LLPS of a signaling kinase (i.e., LATS1).

Background Depression is a leading cause of disability among adolescents and young adults, yet comprehensive assessments of its global burden and associated risk factors in this population remain limited. This study aimed to evaluate the global, regional, and national trends in depression burden among individuals under 30 years of age from 1990 to 2021, and to identify key risk factors and disparities. Methods We analyzed data from the Global Burden of Disease Study 2021, focusing on depression incidence and disability-adjusted life years (DALYs) among individuals aged under 30. Temporal trends were assessed using an age-period-cohort (APC) model. We further examined trends using estimated annual percentage change (EAPC), frontier analysis, and inequality metrics to provide a comprehensive evaluation. Results From 1990 to 2021, both the incidence of depression and related DALYs in individuals under 30 increased by over 50%. Males experienced a larger proportional increase, although females had an age-standardized incidence rate (ASIR) 23 times higher than males in 2021. The highest burden was observed in the 20–24 age group, while the fastest growth occurred among those aged 15–19. Individuals born after 2000 showed a higher prevalence of depression. High sociodemographic index (SDI) regions—particularly high-income North America and Greenland—had the highest ASIR and age-standardized DALY rate (ASDR). The most prominent risk factors were bullying victimization (61.8%), childhood sexual abuse (12.0%), and intimate partner violence (12.6%). Notable regional disparities were observed, with countries like Switzerland, Norway, Monaco, and Germany showing rapid increases in depression burden. Conclusions The burden of depression among young people has risen substantially over the past three decades, with disproportionate impacts on females, post-2000 birth cohorts, and those in high-SDI regions. Interventions targeting modifiable risk factors—particularly bullying, childhood abuse, and intimate partner violence—are essential to reduce the burden. Tailored, region-specific strategies are necessary to effectively address disparities and improve mental health outcomes in youth.

Soft wearable electronics for underwater applications are of interest, but depend on the development of a waterproof, long-term sustainable power source. In this work, we report a bionic stretchable nanogenerator for underwater energy harvesting that mimics the structure of ion channels on the cytomembrane of electrocyte in an electric eel. Combining the effects of triboelectrification caused by flowing liquid and principles of electrostatic induction, the bionic stretchable nanogenerator can harvest mechanical energy from human motion underwater and output an open-circuit voltage over 10 V. Underwater applications of a bionic stretchable nanogenerator have also been demonstrated, such as human body multi-position motion monitoring and an undersea rescue system. The advantages of excellent flexibility, stretchability, outstanding tensile fatigue resistance (over 50,000 times) and underwater performance make the bionic stretchable nanogenerator a promising sustainable power source for the soft wearable electronics used underwater. Flexible devices such as solar cells and nanogenerators are attractive for powering wearable electronics, but waterproof capabilities would extend applications. Here the authors report a bionic stretchable nanogenerator that is capable of harvesting energy and multi-position motion monitoring underwater.

The development of head and neck squamous cell carcinoma (HNSCC) is closely associated with inflammation. Tumor associated macrophages (TAMs), the largest population of inflammatory cells in the tumor stroma, serve an important role in accelerating cancer progression. The present study aimed to investigate the role of TAMs in the metastasis of HNSCC. TAM biomarkers and epithelial to mesenchymal transition (EMT)-associated proteins were detected using immunohistochemical and immunofluorescence staining in HNSCC. Then, direct and indirect co-culture systems of TAMs and HNSCC cells were established. The EMT-associated proteins and associated signaling pathways in HNSCC cells of the co-culture system were measured by reverse transcription-quantitative polymerase chain reaction and western blotting. Finally, hierarchical clustering was performed to analyze associations among TAM biomarkers, epidermal growth factor receptor (EGFR), activated extracellular signal-regulated protein kinase 1/2 (ERK1/2) and EMT-associated proteins in HNSCC tissues. The results indicated that the expression of EMT-associated proteins was positively associated with M2 macrophage biomarkers in HNSCC tissues. Cal27 cells were isolated from the co-culture system by fluorescence-activated cell sorting, and it was identified that E-cadherin was downregulated in Cal27 cells, while Vimentin and Slug were upregulated. Furthermore, the results indicated that EGF released by M2 macrophages in the co-culture served an important role by activating ERK1/2. The correlation and cluster analyses indicated that activated ERK1/2 was positively correlated with cluster of differentiation-163, EGFR, Vimentin and Slug. This suggested that TAMs may induce the EMT of cancer cells by activating the EGFR/ERK1/2 signaling pathway in HNSCC, which may be a promising approach to suppressing cancer metastasis.

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO₂ fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Self-powered implantable medical electronic devices that harvest biomechanical energy from cardiac motion, respiratory movement and blood flow are part of a paradigm shift that is on the horizon. Here, we demonstrate a fully implanted symbiotic pacemaker based on an implantable triboelectric nanogenerator, which achieves energy harvesting and storage as well as cardiac pacing on a large-animal scale. The symbiotic pacemaker successfully corrects sinus arrhythmia and prevents deterioration. The open circuit voltage of an implantable triboelectric nanogenerator reaches up to 65.2 V. The energy harvested from each cardiac motion cycle is 0.495 μJ, which is higher than the required endocardial pacing threshold energy (0.377 μJ). Implantable triboelectric nanogenerators for implantable medical devices offer advantages of excellent output performance, high power density, and good durability, and are expected to find application in fields of treatment and diagnosis as in vivo symbiotic bioelectronics. Implantable medical electronic devices are limited by battery lifetime and inflexibility, but self-powered devices can harvest biomechanical energy. Here the authors demonstrate cardiac pacing and correction of sinus arrhythmia with a symbiotic cardiac pacemaker, which is an implanted self-powered pacing system powered by cardiac motion, in a swine.

Alzheimer's disease (AD) is a neurodegenerative disease that involves multiple systems in the body. Numerous recent studies have revealed bidirectional crosstalk between the brain and bone, but the interaction between bone and brain in AD remains unclear. In this review, we summarize human studies of the association between bone and brain and provide an overview of their interactions and the underlying mechanisms in AD. We review the effects of AD on bone from the aspects of AD pathogenic proteins, AD risk genes, neurohormones, neuropeptides, neurotransmitters, brain‐derived extracellular vesicles (EVs), and the autonomic nervous system. Correspondingly, we elucidate the underlying mechanisms of the involvement of bone in the pathogenesis of AD, including bone‐derived hormones, bone marrow‐derived cells, bone‐derived EVs, and inflammation. On the basis of the crosstalk between bone and the brain, we propose potential strategies for the management of AD with the hope of offering novel perspectives on its prevention and treatment. Highlights The pathogenesis of AD, along with its consequent changes in the brain, may involve disturbing bone homeostasis. Degenerative bone disorders may influence the progression of AD through a series of pathophysiological mechanisms. Therefore, relevant bone intervention strategies may be beneficial for the comprehensive management of AD.

Ice nucleation on the surface plays a vital role in diverse areas, ranging from physics and cryobiology to atmospheric science. Compared to ice nucleation in the bulk, the water-surface interactions present in heterogeneous ice nucleation complicate the nucleation process, making heterogeneous ice nucleation less comprehended, especially the relationship between the kinetics and the structures of the critical ice nucleus. Here we combine Markov State Models and transition path theory to elucidate the ensemble pathways of heterogeneous ice nucleation. Our Markov State Models reveal that the classical one-step and non-classical two-step nucleation pathways can surprisingly co-exist with comparable fluxes at T  = 230 K. Interestingly, we find that the disordered mixing of rhombic and hexagonal ice leads to a favorable configurational entropy that stabilizes the critical nucleus, facilitating the non-classical pathway. In contrast, the favorable energetics promotes the formation of hexagonal ice, resulting in the classical pathway. Furthermore, we discover that, at elevated temperatures, the nucleation process prefers to proceed via the classical pathway, as opposed to the non-classical pathway, since the potential energy contributions override the configurational entropy compensation. This study provides insights into the mechanisms of heterogeneous ice nucleation and sheds light on the rational designs to control crystallization processes. Classically, ice nucleation on foreign surfaces is considered a one-step process. Here, Li et al. uncover a two-barrier pathway which becomes competitive at lower temperatures, facilitated by synergistic, entropic effects of rhombic and hexagonal ice structures.

Background Disease detection is an important aspect of biotherapy. With the development of biotechnology and computer technology, there are many methods to detect disease based on single biomarker. However, biomarker does not influence disease alone in some cases. It’s the interaction between biomarkers that determines disease status. The existing influence measure I -score is used to evaluate the importance of interaction in determining disease status, but there is a deviation about the number of variables in interaction when applying I -score. To solve the problem, we propose a new influence measure Multivariate Gain Ratio (MGR) based on Gain Ratio (GR) of single-variate, which provides us with multivariate combination called interaction. Results We propose a preprocessing verification algorithm based on partial predictor variables to select an appropriate preprocessing method. In this paper, an algorithm for selecting key interactions of biomarkers and applying key interactions to construct a disease detection model is provided. MGR is more credible than I -score in the case of interaction containing small number of variables. Our method behaves better with average accuracy 93.13 % than I -score of 91.73 % in Breast Cancer Wisconsin (Diagnostic) Dataset. Compared to the classification results 89.80 % based on all predictor variables, MGR identifies the true main biomarkers and realizes the dimension reduction. In Leukemia Dataset, the experiment results show the effectiveness of MGR with the accuracy of 97.32 % compared to I -score with accuracy 89.11 % . The results can be explained by the nature of MGR and I -score mentioned above because every key interaction contains a small number of variables in Leukemia Dataset. Conclusions MGR is effective for selecting important biomarkers and biomarker interactions even in high-dimension feature space in which the interaction could contain more than two biomarkers. The prediction ability of interactions selected by MGR is better than I -score in the case of interaction containing small number of variables. MGR is generally applicable to various types of biomarker datasets including cell nuclei, gene, SNPs and protein datasets.