Browse Articles

Dartmouth’s AI summer and what came next

The 70th anniversary of the first AI workshop invites reflection on the technology’s wider legacies

Genetic screening of potential traits probiotics of lactic acid bacteria isolated from traditional curdled milk of cow, camel and goat in Burkina Faso

Nepal’s new science ministry must strengthen scientific capacity

Industrial-scale nanocrystalline Ni–Mo–MgO catalysts for hybrid reforming of waste to fuels

Strategies for lowering carbon emissions from hydrocarbons and waste must overcome the challenges related to catalyst durability and the presorting of waste. Reforming low-value carbon sources with carbon dioxide (CO 2 ) offers an industrial-scale pathway for recycling waste streams into fuels and chemicals. We developed a nickel-molybdenum alloy nanocatalyst on single-crystalline magnesium oxide (NiMoCat) in pellet form on a kilogram scale suitable for high-pressure industrial reactors. Aliphatic hydrocarbons (methane, n -butane) and aromatics (benzene, toluene) under pressurized CO 2 yielded quantitative syngas without methanation or undesired oxidative by-products, such as butadiene or polyaromatics. Scaled-up NiMoCat maintains activity during long-term operation and enables a two-step process involving gasification of unsorted waste followed by hybrid reforming under realistic flue gas or CO 2 flow. A detailed life-cycle analysis of biogas-to-dimethyl ether conversion showcases a scalable, sustainable CO 2 utilization compatible with current fuel and chemical infrastructures.

Enhanced brain tumour prediction using quantum: a hybrid deep learning approach

Europe must seize the moment to lead on free and open science

Large-scale discovery, analysis and design of protein energy landscapes

Abstract All folded proteins continuously fluctuate between their low-energy native structures and higher-energy conformations that can be partially or fully unfolded. These rare states influence protein function 1,2 , interactions 3 , aggregation 4–7 and immunogenicity 8,9 , yet they remain far less understood than protein native states. Although native protein structures are now often predictable with impressive accuracy, conformational fluctuations and their energies remain largely invisible 10 and unpredictable 11–14 , and experimental challenges have prevented large-scale measurements that could improve machine learning and physics-based modelling. Here we introduce a multiplexed experimental approach to analyse the energies of conformational fluctuations for hundreds of protein domains in parallel using intact protein hydrogen–deuterium exchange mass spectrometry. We analysed 5,778 domains 28–64 amino acids in length, revealing hidden variation in conformational fluctuations, even between sequences sharing the same fold and global folding stability. Site-resolved hydrogen exchange nuclear magnetic resonance analysis of 13 domains showed that these fluctuations often involve entire secondary structural elements with lower stability than the overall fold. Computational modelling of our domains identified structural features that correlated with the experimentally observed fluctuations, enabling us to design mutations that stabilized low-stability structural segments. Our dataset enables new machine-learning-based analysis of protein energy landscapes, and our experimental approach promises to profile these landscapes at considerable scale.

Genetic effects put into context

The physiological state of neurons controls the expression of gene variants linked with psychiatric disease

Comparative scenario analysis for improved oil recovery in a heterogeneous carbonate reservoir

Europe as science superpower: what it will take to rival the US and China

Single-cell multiomics of neuron activation reveals context-specific genetics of brain disorders

Most causal variants for neuropsychiatric disorders (NPD) remain unknown. A major hurdle is that disease variants may act in specific contexts, such as during neuronal activation, which is difficult to study in vivo at the population level. We profiled single-nucleus neuron-activation multiomics in human induced pluripotent stem cell–derived neurons from 100 donors, revealing the NPD-relevant transcriptomic and epigenomic landscape of neuronal activation. We identified abundant genetic variants associated with activity-dependent gene expression and chromatin accessibility, the latter explaining larger proportions of NPD heritability. Integrating multiomics data with genome-wide association studies further revealed NPD risk variants and genes with effects detected only upon stimulation, such as activity-dependent cholesterol metabolism. Our work highlights the power of cell stimulation to reveal context-specific “hidden” genetic effects.

Association of the C-reactive protein–triglyceride glucose index with cardiovascular disease risk across cardiovascular–kidney–metabolic syndrome

Coordinated demise of harmful algal blooms

Iron-mediated programmed cell death spreads through colonies of toxic cyanobacteria

Edge-AI enabled secure IoT framework for real-time patient monitoring and anomaly detection in smart healthcare systems

The halo effect: how academic hierarchy undermines peer review and enables fraud

Erratum for the Report “Covalently bonded single-molecule junctions with stable and reversible photoswitched conductivity” by C. Jia <i>et al</i> .

Diffusion of water and sweat-like aqueous solutions into silicone-based pressure-sensitive adhesives for transdermal therapeutic systems investigated with dielectric analysis

Abstract Transdermal therapeutic systems (TTS) remain adhered to human skin for periods of up to seven days, during which water or vapor continuously diffuses from the skin into the pressure sensitive adhesive (PSA) layer. This water uptake can alter the mechanical and adhesive properties of the PSA, potentially affecting both drug delivery and patient comfort. Despite its clinical relevance, the diffusion behavior of water in silicone-based TTS-PSA has not been systematically characterized to date. Here, we demonstrate that dielectric analysis (DEA) in terms of the ion viscosity enables quantitative characterization of water diffusion in silicone-based PSA. The ion viscosity is linked to polymer chain mobility and free volume, allowing for extraction of diffusion coefficients from time-resolved measurements. Application to six silicone PSA formulations differing in end-group chemistry (nonpolar -CH₃ vs. polar -OH) and resin content, showed that diffusion coefficients increase with decreasing resin content, and are up to 70% higher for PSA with -CH₃ end groups compared to those bearing -OH end groups. Diffusion of 0.9% NaCl solution was consistently slower than that of deionized water across all formulations. Additionally, the DEA method yields parameters that may serve as a quality assurance indicator in TTS-PSA production. These results demonstrate that DEA is a fast, non-destructive, and cost-effective technique with a strong potential as a tool for rational design and quality control of TTS-PSA.

Impact heating and the hidden Hadean

The nature of Earth’s crust during the Hadean eon [≥4.03 billion years ago (Ga)] is uncertain. Numerical models of early Earth geodynamics emphasize the control of mantle temperature but generally consider only internally derived heat, despite empirical evidence for an intense Hadean impact flux. Using a stochastic model of that flux, we show that the time-integrated heat due to impacts would have dwarfed that produced internally throughout the Hadean. Earth’s Hadean crust would have been extensively molten at depths below a few kilometers, causing gravitational segregation of dense, iron- and magnesium-rich material and driving average crustal compositions to become increasingly silica rich. Globally, impact heating would have become much less important after 3.9 Ga, allowing the crust to thicken. That enduring continental crust appeared around this time is likely not a coincidence.

Prediction of all-cause mortality in older adults in Colombia: real-world evidence from a middle-income country

Has NSF slashed research to support tech initiative?

Belated shift in funds has meant sharp drop in grants