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Cryo-EM reveals evolutionarily conserved and distinct structural features of plant CG maintenance methyltransferase MET1
Abstract DNA methylation is essential for genomic function and transposable element silencing. In plants, DNA methylation occurs in CG, CHG, and CHH contexts (where H = A, T, or C), with the maintenance of CG methylation mediated by the DNA methyltransferase MET1. The molecular mechanism by which MET1 maintains CG methylation, however, remains unclear. Here, we report cryogenic electron microscopy structures of Arabidopsis thaliana MET1. We find that the methyltransferase domain of MET1 specifically methylates hemimethylated DNA in vitro. The structure of MET1 bound to hemimethylated DNA reveals the activation mechanism of MET1 resembling that of mammalian DNMT1. Curiously, the structure of apo-MET1 shows an autoinhibitory state distinct from that of DNMT1, where the RFTS2 domain and the connecting linker inhibit DNA binding. The autoinhibition of MET1 is relieved upon binding of a potential activator, ubiquitinated histone H3. Taken together, our structural analysis demonstrates both conserved and distinct molecular mechanisms regulating CG maintenance methylation in plant and animal DNA methyltransferases.
High-dose medetomidine increases functional connectivity in the fear-related regions after electrical stimulation
Comparison of imaging based single-cell resolution spatial transcriptomics profiling platforms using formalin-fixed paraffin-embedded tumor samples
Development and validation of super learner models to predict small and large for gestational age in the second generation
Abstract Prediction of small (SGA) and large for gestational age (LGA) using routinely collected antenatal data remains suboptimal, particularly among nulliparous women. In this study, models for SGA (< 10th percentile) and LGA (> 90th percentile) were developed by combining grandmaternal pregnancy-related information and maternal birth characteristics (“G0 predictors”) with maternal clinical factors available at 26 weeks’ gestation (“G1 predictors”). The study used a cohort of first-born, singleton births to nulliparous women in Nova Scotia, Canada (1981–2011), and their mothers, from the Nova Scotia Atlee Perinatal Database. Models using G0 predictors, G1 predictors, and their combination were developed with Super Learner, an ensemble machine learning algorithm, and internally validated using nested cross-validation. Discrimination was assessed via the area under the receiver operating characteristic curve (AUC-ROC) and the precision-recall curve (AUC-PR); calibration was also evaluated. Among 9,097 grandmother-mother-infant triads, 902 (9.9%) infants were SGA and 891 (9.8%) were LGA. Including G0 predictors improved discrimination compared to G1-only models (AUC-ROC 0.69 vs. 0.66 for SGA and 0.71 vs. 0.66 for LGA; AUC-PR: 0.21 vs. 0.18 for SGA and 0.22 vs. 0.18 for LGA). Models fitted using both sets of predictors were well calibrated. While incorporating intergenerational information modestly improved prediction, overall predictive performance remains poor.
Programmable circuits for analog matrix computations
Research on the construction of cheerleading technique evaluation and teaching system integrating deep visual recognition and cognitive feedback mechanism
Abstract This paper describes an advanced system for the evaluation and teaching of cheerleading techniques that combines deep vision perception with cognitive feedback mechanisms. The method uses spatial feature extraction via convolutional neural networks and temporal movement analysis with recurrent neural networks, along with 3D pose estimation, to facilitate automatic evaluation of the techniques. A cognitive feedback mechanism, which is multi-modal in nature and draws principles from motor learning, supplies customized teaching through the visual, auditory, and haptic pathways. The system achieves 92.4% accuracy in technique classification with real-time processing at 35.4 fps, reduces training time by 35%, and improves skill retention to 89.3% at 4 weeks post-training compared to conventional coaching methods. The paper contributes to the application of artificial intelligence technology to sports education by providing a new way of objective analysis of performance and learning adaptation in the context of cheerleading training.
Physical vitrification and nanowarming at liter-scale CPA volumes: toward organ cryopreservation
Abstract Organ banking via vitrification could transform transplantation, but has never been achieved at human organ scales. This study tested vitrification and rewarming in 0.5–3 L volumes using cryoprotective agents (CPAs): M22, VS55, and 40%EG + 0.6 M Sucrose. Ice formation and cracking was avoided through optimized convective cooling, and successful vitrification was confirmed via visual inspection, thermometry, and X-ray µCT. M22 and EG+sucrose vitrified at 0.5 L, but only M22 succeeded at 3 L; VS55 failed at all volumes. Porcine livers (~0.6–1 L total volume; ~0.23–0.75 L organ volume) were also vitrified using EG+sucrose, though not rewarmed. Future experiments are needed to optimize the protocol and achieve liver rewarming. Using nanowarming with iron-oxide nanoparticles and a newly developed 120 kW RF coil, uniform rewarming was achieved in up to 2 L volumes of M22 at ~88 °C/min. This work serves as a proof-of-concept that human organ scale vitrification and rewarming is physically possible, thereby enabling human organ banking in the future.
Mechanism of sepsis regulation by ELANE via macrophage polarization
Harnessing indole scaffolds to identify small-molecule IRE1α inhibitors modulating XBP1 mRNA splicing
Abstract The inositol-requiring enzyme 1 alpha (IRE1α) is an important sensor protein with dual kinase and ribonuclease function. It induces X-box binding protein 1 (XBP1) mRNA splicing and mediates endoplasmic reticulum (ER) stress-triggered downstream unfolded protein response signaling pathways. The dysregulation of IRE1α has been associated with multiple human diseases, and thus IRE1α-targeting small molecules harbor great therapeutic potential. We herein report a series of substituted indoles as IRE1α inhibitors (such as IA107) of excellent potency and selectivity. We also report a resolved co-crystal structure that reveals a unique inhibition mode of IA107 that allosterically inhibits IRE1α RNase activity via binding to the IRE1α kinase domain but without inhibiting the IRE1α dimerization. The following cellular evaluation results demonstrate that IA107 concentration-dependently inhibits the cellular ER stress-induced XBP1 mRNA splicing, and the ester-containing prodrug exhibits a ~ 50-fold increase in cellular activity. Collectively, our results establish the indoles as a potent and selective IRE1α-inhibiting chemotype that modulates RNA splicing and expands the biological application potential associated with IRE1α targeting via small molecules.
Health-related quality of life and associated factors among people with disabilities in Northwest Ethiopia
Nonreciprocal field theory for decision-making in multi-agent control systems
Abstract Field theories for complex systems traditionally focus on collective behaviours emerging from simple, reciprocal pairwise interaction rules. However, many natural and artificial systems exhibit behaviours driven by microscopic decision-making processes that introduce both nonreciprocity and many-body interactions, challenging these conventional approaches. We develop a theoretical framework to incorporate decision-making into field theories using the shepherding problem from swarm robotics as a paradigmatic example of a multi-agent control system, where agents, the herders, must coordinate to confine another group of agents, the targets, within a prescribed region. By introducing continuous approximations of two key decision-making elements - target selection and trajectory planning - we derive field equations that capture the essential features of this distributed control problem. Our theory reveals that different decision-making strategies emerge at the continuum level, from average attraction to highly selective choices, and from undirected to goal-oriented motion, driving transitions between homogeneous and confined configurations. The resulting nonreciprocal field theory not only describes the shepherding problem but provides a general framework for incorporating decision-making into continuum theories of collective behaviour, with implications for applications ranging from robotic swarms to traffic and crowd management systems.