Browse Articles

The impact of wind turbines on the distribution and abundance of raptors at an important wintering and migration stopover site in Ontario, Canada

Comprehensive benchmarking of tools for nanopore-based detection of DNA methylation

Abstract Oxford Nanopore (ONT) sequencing offers direct detection of DNA base modifications. Numerous tools have been developed to leverage this advantage. However, their performance remains unclear. Here, using diverse bacterial, plant, and mammalian datasets, we systematically evaluate the current landscape of nanopore methylation tools. We demonstrate that although most recent tools perform well, older models remain the reliable choice for studying CpG methylation. Conversely, newer models show substantial improvement in identifying 5-methylcytosine in non-CpG contexts, 6-methyladenine, and 4-methylcytosine. Further, we highlight the sensitivity of tools to confounding methylation nearby, assess their computational performance, and evaluate the effects of sequencing depth, methylation abundance, read quality, and basecalling mode. We provide reusable pipelines and open access datasets to empower future benchmarking efforts. Our work thus details the strengths and limitations of the state-of-the-art methylation models and outlines practical guidelines for researchers using nanopore sequencing to study DNA methylation.

Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults

Novel polymyxin resistance gene family mcr-12 from environmental Pigmentiphaga litoralis

Abstract The emergence of mobile colistin resistance ( mcr ) genes threatens the efficacy of polymyxins as last-resort antibiotics for treating multidrug-resistant bacterial infections. Here, we identify a novel environmental mcr gene, mcr-12 , discovered in Pigmentiphaga litoralis from Australian sediment, and evaluate its potential role in the intersection between environmental resistance reservoirs and clinically relevant bacteria. Gene mcr-12 was located within a metal-resistance gene cluster on plasmid pPLE30.2, which also carried a predicted novel β-lactamase gene ( bla OXA-1383 ). Removal of pPLE30.2 increased polymyxin susceptibility 32-fold, while reintroduction of mcr-12 restored resistance. Despite its low amino-acid identity to known MCR enzymes, MCR-12 confers polymyxin resistance by phosphoethanolamine transferase modification of lipid A. Expression of mcr-12 in Pseudomonas spp. and Acinetobacter baumannii conferred polymyxin resistance, suggesting that mcr-12 is compatible between environmental strains and clinical pathogens. The discovery of a new mcr gene from an environmental source and from outside Gammaproteobacteria highlights the need for further surveillance efforts within a One Health framework.

Optically Detected Magnetic Resonance of a Cerium-Doped Nanocrystal: Toward the Generality of a Direct Spin-Optical Interface

Numerical investigation of a three-lobe gas foil bearing with a double-ring microgrooved top foil based on fluid-structure interaction

Marine fish ranges are expanding and shifting deeper across the European continental shelf

Abstract Understanding how climate change and exploitation affect marine species distribution is key for biodiversity conservation. While warming is typically expected to drive species poleward and into deeper waters, unexpected patterns such as equatorward shifts and shallowing also occur. Fishing pressure may further contract species’ ranges. Yet, the mechanisms underpinning these 3-dimensional range shifts remain largely unresolved. Using 92,961 bottom trawl samples across the European continental shelf, covering 607 fish species over four decades, we show that deepening is predominant, with 60% of populations experiencing an increase in their average depth. Contrary to expectations, latitudinal shifts are balanced, with 49% of populations shifting poleward and 51% equatorward. Here, we quantify how population relocations are driven by the interplay between environmental factors and species traits as species track their optimal ecological niches. We also highlight that the recent reduction in fishing pressure has likely facilitated spatial expansions and increases in populations abundance.

OptiRanker: a simulation and optimization framework for efficient in vivo validation of drug prioritization algorithms

Low-temperature liquid-assisted vibrational stress-relief strategy enables stable and efficient perovskite solar cells

Record Carrier Diffusion Lengths in Large, Dense Nonfullerene Electron Acceptor Crystals Grown from Polar Aromatic Solvents

Antigenic stimulation in conjunction with cytokine is required for mediating IL-17A production in human MAIT cells

Oncogene inactivation-induced senescence facilitates tumor relapse

Abstract Oncogene-directed therapies can induce profound tumor regression in oncogene-addicted cancers, but their long-term benefit is often limited by resistance and relapse. Here we show that oncogene inactivation rapidly induces senescence and a pro-inflammatory senescence-associated secretory phenotype (SASP). In vivo, oncogene inactivation-induced senescence (OIIS) predisposes tumors to relapse, accompanied by polyploidy, chromosomal instability, acquisition of alternative oncogenic pathways including mouse double minute 2 homolog (Mdm2) upregulation, and tumor microenvironmental remodeling toward neovascularization and immunosuppression. Spectral flow cytometry reveals a shift from an immune-activated to an immunosuppressive milieu during relapse. OIIS features are also observed in human BRAF V600E melanoma cells treated with vemurafenib, supporting clinical relevance. Together, our findings establish OIIS as a double-edged process: it initially restrains tumor growth but simultaneously creates conditions that favor recurrence. By defining the genetic, metabolic and microenvironmental hallmarks of OIIS, our study highlights adaptations to oncogene deprivation that limit the durability of targeted therapies.

How the Unconventional Oxidation State Au ²⁺ Is Stabilized in the Halide Perovskite Cs ₄ Au ₃ Cl ₁₂ : A First-Principles Study of Its Polaron Crystal Nature

Regulation of Tumor-Immune Cell Communications via Enantioselectively Targeting SLC G-Quadruplexes

Simulation of a multi-parameter indoor air purification control system using fuzzy logic–PID hybrid control tuned by genetic algorithms

Abstract Indoor Environmental Quality (IEQ) critically impacts human health, comfort, and productivity, yet existing air purification systems often rely on single-sensor data, manual monitoring, or cloud-based processing, resulting in limited intelligence, increased latency, and reduced suitability for resource-constrained environments such as Uganda. To address these challenges, this paper presents the design, mathematical modelling, and simulation of a novel multi-parameter indoor air purification control system. The proposed framework integrates six environmental sensors (dust, smoke, gas, volatile organic compounds (VOC), temperature, and humidity) with a hybrid Fuzzy Logic–Proportional–Integral–Derivative (PID) controller whose parameters are optimally tuned using a Genetic Algorithm (GA). A first-principles mathematical model of the DC motor-driven purifier actuator is developed to describe the relationship between the input voltage and volumetric airflow. To enhance the physical realism of the simulations, the system model incorporates practical operating factors, including fan inertia, room-air mixing, pollutant transport, filter dynamics, and environmental sensor noise. The complete system is implemented in the MATLAB/Simulink environment using a Mamdani-type fuzzy inference system with 49 rules and a GA-based multi-objective fitness function to minimise overshoot, settling time, and steady-state error. Simulation results demonstrate that the proposed GA-tuned Fuzzy-PID controller achieves a stable and well-damped response with a rise time of 53.93 s, a settling time of 119.99 s, and a maximum overshoot of 2.14%, reflecting the expected dynamics of practical indoor air purification systems. The proposed framework provides a scalable, low-latency, and network-independent intelligent control solution that establishes a realistic foundation for future prototype development and experimental validation in low-resource environments.

Efficient Gillespie algorithms for spreading phenomena in large and heterogeneous higher-order networks

Skipped Dienes via Radical Allylic Heck Reaction

Master stability function for networks of coupled piecewise-smooth oscillators

Abstract The Master Stability Function (MSF) is a well-established framework for analyzing the synchronization stability of networks composed of identical oscillators. It simplifies the analysis by reformulating the stability problem in terms of a low-dimensional variational equation defined in the vicinity of the synchronization manifold. However, for oscillators governed by piecewise-smooth vector fields, such a variational equation cannot be directly derived due to the presence of non-differentiable points in the system dynamics. This paper introduces a novel extension of the MSF framework specifically designed to address synchronization stability in networks of identical piecewise-smooth oscillators. The proposed method builds upon a previously developed Jacobian matrix estimation technique, enabling its application to piecewise-smooth systems. The formulation is presented in detail, along with a discussion of its advantages and disadvantages compared to alternative methods. Additionally, the MSF is computed for both linear and nonlinear impact oscillator systems using the proposed method, and a detailed description of its application is provided. The effectiveness of the method is demonstrated through validation against an alternative MSF estimation approach.

Direct coupling of nod factor signaling to vesicular trafficking initiates legume nodulation

Children with lower language skill show additional recruitment of bilateral neural mechanisms during sentence comprehension

Abstract Multi-voxel pattern analysis was used to determine whether a support vector machine (SVM) could distinguish between grammatically correct sentences and sentences with a morphological violation related to tense-marking in 7-year-old children ( N  = 92) undergoing functional magnetic resonance imaging. SVM classifier accuracy was examined in regions of interest (ROIs) related to phonological processing (inferior frontal gyrus, pars opercularis and posterior superior temporal gyrus) and semantic processing (inferior frontal gyrus, pars triangularis and posterior middle temporal gyrus) determined with independent functional localizers using sound and meaning judgements. In these ROIs, the classifier performed around chance indicating that grammatical sentences and sentences with a morphological violation have a similar underlying representation for the whole sample. We also investigated correlations of standardized measures of language skill with classifier accuracy in the ROIs and in the whole brain. Whole brain analyses showed lower skill was associated with higher classification accuracy in bilateral brain areas implicated in semantic processing, in articulation and phonological processing and in verbal working memory. Overall, children with lower language skill seem to use widespread mechanisms in both hemispheres for sentence comprehension, possibly indicating increasing use of rehearsal mechanisms and semantic compensation for detecting morphological errors.