Browse Articles

Interpretable early warnings using machine learning in an online game-experiment

Stemming from physics and later applied to other fields such as ecology, the theory of critical transitions suggests that some regime shifts are preceded by statistical early warning signals. Reddit’s r/place experiment, a large-scale social game, provides a unique opportunity to test these signals consistently across thousands of subsystems undergoing critical transitions. In r/place, millions of users collaboratively created “compositions”, or pixel-art drawings, in which transitions occur when one composition rapidly replaces another. We develop a machine-learning-based early warning system that combines the predictive power of multiple system-specific time series via gradient-boosted decision trees with memory-retaining features. Our method significantly outperforms standard early warning indicators. Trained on the 2022 r/place data, our algorithm detects half of the transitions occurring within 20 min at a false positive rate of just 3.6%. Its performance remains robust when tested on the 2023 r/place event, demonstrating generalizability across different contexts. Using SHapley Additive exPlanations (SHAP) for interpreting the predictions, we investigate the underlying drivers of warnings, which could be relevant to other complex systems, especially online social systems. We reveal an interplay of patterns preceding transitions, such as critical slowing down or speeding up, a lack of innovation or coordination, turbulent histories, and a lack of image complexity. These findings show the potential of machine learning indicators in socio-ecological systems for predicting regime shifts and understanding their dynamics.

Deep learning-assisted discovery of a potent and cell-active inhibitor of RNA N6-methyladenosine recognition protein YTHDC2

Quantum and thermodynamic evaluation of C24 fullerene-based nanosensors for detection of mydayis in biomedical and drug detection applications

Abstract From a public health and forensic perspective, the detection of Mydayis (a long-acting amphetamine-based drug) is crucial due to its psychotropic effects. In this work, Density Functional Theory (DFT), Time-Dependent DFT (TD-DFT), and Quantum Theory of Atoms in Molecules (QTAIM) were employed to evaluate pristine C 24 fullerene and its doped derivatives (BC 23 and SiC 23 ) as nanosensors for Mydayis. Key electronic, thermodynamic, optical, and adsorption-based parameters were calculated, and the IR spectrum simulated using DFT showed strong agreement with experimental IR data reported in the literature, confirming the reliability of the computational approach. Among the investigated structures, pristine C24 was identified as the most effective disposable electrochemical sensor, exhibiting moderate adsorption energy (− 23.88 kcal.mol −1 ), a measurable conductivity increase (2.74 × 10 9  → 2.77 × 10 9 A.m −2 ), and significant enhancements in dipole moment (0.00 → 11.253 D) and polarizability (170.8 → 285.994 a.u.). In contrast, BC 23 and SiC 23 demonstrated exceptionally strong adsorption behavior (− 53.09 and − 54.00 kcal.mol −1 , respectively) and extremely long recovery times (8.13 × 10 26 and 3.80 × 10 27  s), establishing them as excellent high-capacity absorbers for irreversible Mydayis capture. Additionally, BC 23 exhibited the most pronounced colorimetric response, with a dramatic bathochromic shift from 432 to 655 nm upon Mydayis binding, confirming its role as the best disposable colorimetric sensor. These findings highlight the complementary roles of C 24 , BC 23 , and SiC 23 in the electrochemical, optical, and adsorptive detection of Mydayis and provide a robust theoretical foundation for future experimental sensor development.

Polyserine domains are toxic and exacerbate tau pathology in mice

Polyserine domains mediate the association of some nuclear RNA-binding proteins with cytoplasmic tau aggregates occurring in tauopathy models and patient samples. In cell lines, polyserine domains mediate colocalization with tau aggregates and promote formation, suggesting that the cytoplasmic mislocalization of polyserine-containing proteins could contribute to human disease. Moreover, polyserine can be produced by repeat-associated non-AUG translation in CAG repeat expansion diseases. However, whether polyserine expressed in a mammalian brain is toxic and/or can exacerbate tau pathology is unknown. We used AAV9-mediated delivery to express a 42-repeat polyserine protein in wild-type and tau transgenic mouse models. We observe that polyserine expression has toxic effects in wild-type animals indicated by reduced weight, behavioral abnormalities, and a striking loss of Purkinje cells. Moreover, in the presence of a pathogenic variant of human tau, polyserine exacerbates disease markers such as phosphorylated and insoluble tau levels and the seeding capacity of brain extracts. These findings demonstrate that polyserine domains can promote tau-mediated pathology in a mouse model and support the hypothesis that polyserine-containing proteins could contribute to the progression of human tauopathies.

Persistent river heatwaves are emerging worldwide under climate change

Impact of partial cement dust replacement in unsaturated polyester: assessing material performance and waste valorization for sustainable management

Abstract This study is a continuation of the earlier studies (The effective treatment of dye‑containing simulated wastewater by using the cement kiln dust as an industrial waste adsorbent) and (The effective remediation of heavy metal-laden wastewater by employing cement dust derived from industrial activities as a sorbent) as an attempt to provide a comprehensive image of the possible useful uses of cement dust.  In this research, a polymer composite consisting of an unsaturated polyester (UP) thermoset matrix and micro-sized cement kiln dust (CKD) as filler with an addition percentage range of 0–10% was synthesized to achieve maximum utilization of this harmful waste that influences the environment and public health. Studying the structure revealed the presence of characteristic UP and CKD peaks in all the XRD and IR spectra, confirming the physical interaction between the filler and the matrix. The inclusion of CKD up to 10% decreased the degradation temperature of the UP resin. The water absorption data for the UP–CKD composites revealed a maximum water uptake of 0.55% with nonlinear behavior compared to UP doped with other inorganic fillers. An increase in the CKD content to 10% increased the limiting oxygen index (LOI) of UP above the oxygen percentage in the air (21%), promoting the fire resistance properties of the system. Prime mechanical properties in terms of ultimate tensile strength, Young’s modulus, bending (flexural) strength, and flexural modulus decreased from 27.54 to 7.57 MPa, and from 1118.4 to 260.45 MPa, and from 25 to 11.49 MPa, and from 4.68 to 2.15 MPa, respectively, while both elongation (%) at break and hardness revealed fluctuating behavior with increasing CKD content. Poor dispersion and agglomeration, and hence low adhesion and poor bonding between the CKD filler and the UP, were the main reasons for this observed declining behavior, as exhibited from SEM illustrations. The as-prepared UP–CKD can be used in various applications where there is no need for distinctive mechanical performance, such as tables and benches manufacturing.

Dietary folic acid prevents peripheral neuropathy in mouse models of neural tube defects and type 2 diabetes

Folate-mediated one-carbon metabolism is implicated in several pathologies including neural tube defects (NTDs), cancer, and neurodegenerative disorders, whereas diabetes is associated with NTDs and peripheral neuropathy (PN). The development of peripheral neuropathy was assessed in Shmt1 +/− and Shmt1 −/− mice, which are models of human folic acid–responsive NTDs, and diabetic ( Lepr db ) mice to determine whether NTDs and PN have a shared etiology. From 6 wk of age, male and female mice with reduced Shmt1 expression exhibited PN, with greater severity in females compared to males. The neuropathic progression was distinct from diabetic peripheral neuropathy (DPN) observed in Lepr db mice. Excess dietary folic acid prevented PN in both Shmt1 −/− and Lepr db/db mice, whereas dietary uridine caused demyelinating PN in mice independent of genotype and folate status. The transcriptome from L3-L5 dorsal root ganglia (DRG) exhibited distinct sex-specific differences in glial cell gene expression when comparing Shmt1 +/+ and Shmt1 −/− mice. DRG sensory neurons exhibited changes in the expression of solute carriers and ion channels involved in nociception, neurotransmission, and structural support. We conclude that reduced thymidylate synthesis causes folic acid–responsive NTDs and PN in mice and that diabetes sensitizes mice to folic acid–responsive PN. Diabetes induces a special nutritional requirement for high intake of folic acid to prevent PN.

Ultra-wide spectrum photosynapse array with 64k-scale for neuromorphic fusion imaging

Artificial intelligence classification of rectal neoplasia by endoscopic fluorescence perfusion analysis

Machine learning reveals hidden dimensions of functional similarity in proteins

Visualization and quantification of lattice strain in battery cathode particles through electron backscatter diffraction imaging

Dynamical model of aperiodic locomotor activity effects on mouse core body temperature removes transient perturbations from longitudinal temperature signals

Abstract Mammalian temperature changes across time due to multiple endogenous and exogenous factors including circadian rhythms, hormonal changes, and locomotor activity. These multiple factors make it difficult to disentangle each of their effects to understand their independent contributions. This is especially problematic due to the relatively high-amplitude, aperiodic heating effects of locomotor activity on core body temperature. These heating effects, combined with innate cooling effects back to core body temperature steady state, mean that locomotor activity can contribute apparent power to both circadian and ultradian rhythms in observed temperature data. We propose that the effect from locomotor activity to core body temperature is not simply the linear addition of circadian and ultradian oscillations, but rather a heating effect that can be offset by a cooling effect dependent on core temperature displacement from resting temperature. Since these effects appear to contribute power to independent rhythms in spectral analysis, in this work we develop an interpretable, parsimonious mathematical model of murine core body temperature that removes them in the time-domain. The model only depends on the initial observed core body temperature as well as minute-level locomotor activity data, making it robust to aperiodic mouse activity. We show that coefficients obtained after fitting the model to each mouse return physiologically relevant differences between sexes, as well as reflect directional changes within female mice between their non-estrous and estrous temperature data. We believe this work should be of use to researchers interested in how core body temperature dynamics change in response to experimental interventions, especially if locomotor activity may be affected as well.

Reply to Benito et al.: Problems in the Cretaceous evolution of the avian palatobasal joint

Spatially decoupled electrochemical strategy for lime passivation prevention and sustainable phosphate recovery

A hybrid differential evolution algorithm for distributed assembly flexible job shop scheduling with batch delivery and inventory

Modeling and inferring metacommunity dynamics with Maximum Caliber

A major challenge for community ecology is using spatiotemporal data to infer parameters of dynamical models without conducting laborious experiments. We present a framework from statistical physics—Maximum Caliber—to characterize the temporal dynamics of complex ecological systems in spatially extended landscapes and infer parameters from empirical data. As an extension of Maximum Entropy modeling, Maximum Caliber aims at modeling the probability of possible trajectories of a stochastic system, rather than focusing on system states. We demonstrate the ability of the Maximum Caliber framework to capture ecological processes ranging from near to far from equilibrium, using an array of species interaction motifs including random interactions, apparent competition, intraguild predation, and nontransitive competition, along with dispersal among multiple patches. For spatiotemporal data of species occupancy in a metacommunity, the parameters of a Maximum Caliber model can be estimated through a simple logistic regression to reveal migration rates between patches, interactions between species, and local environmental suitabilities. We test the accuracy of the method over a range of system sizes and time periods and find that these parameters can be estimated without bias. We introduce “entropy production” as a measure of irreversibility in system dynamics, and use “pseudo- R 2 ” to characterize predictability of future states. We show that our model can predict the dynamics of metacommunities that are far from equilibrium. The capacity to estimate basic parameters of dynamical metacommunity models from spatiotemporal data represents an important breakthrough for the study of metacommunities with application to practical problems in conservation and restoration ecology.

Filament assembly induced by the recognition of target DNA activates the prokaryotic Argonaute SPARDA system

The course and treatment of odontogenic infections in hospital during the COVID 19 pandemic

Fluorinated lipid nanoparticles enable real-time tracking of mRNA delivery and uncover spatiotemporal mechanisms of immune activation

Messenger RNA (mRNA) vaccines rely on lipid nanoparticles (LNPs) for in vivo delivery, yet conventional formulations exhibit inefficient tissue targeting, undesired hepatic accumulation, and limited understanding of the delivery–response relationship, constraining their therapeutic precision and safety. Here, we report the development of fluorinated LNPs (FLNPs) that enable real-time tracking of mRNA biodistribution and expression via 19 F magnetic resonance spectroscopy/imaging (NMR/MRI)” rather than “magnetic resonance spectroscopy/MRI (NMR). These FLNPs retain robust protein expression comparable to clinical LNPs, while reducing liver accumulation by 94.6%. By integrating fluorine signal quantification with spatial analysis of mRNA translation and antigen presentation, we establish a direct correlation between carrier localization, antigen expression kinetics, and immune cell trafficking. Specifically, we show that antigen-presenting cells internalize FLNP-mRNA at the injection site and subsequently migrate to draining lymph nodes, enabling localized immune priming with minimal systemic exposure. This work provides mechanistic evidence linking in vivo nanocarrier trafficking with spatiotemporal immune activation, offering insights into how delivery kinetics govern vaccine efficacy. The FLNP platform thus enables both precision mRNA delivery and noninvasive tracking, representing a powerful tool for mechanistic studies and rational design of next-generation mRNA vaccines.

A liquid metal dynamic wetting strategy for spatiotemporal monitoring of hand movements