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A combination of measures limits demand for critical materials in Sweden’s electric car transition

Electrification of passenger cars will result in an increased demand for critical raw materials. Here we estimate the quantities of nickel, manganese, cobalt, lithium, and graphite that could be required for a transition to electric cars in Sweden and how different measures can limit material demand. We find notable reduction potentials for shorter battery range—enabled by improved charging infrastructure, increased vehicle energy efficiency, and reduced travel demand compared to a reference scenario. The reduction potentials for downsizing and more lightweight cars, and car sharing are more modest. The combined impact of these measures would be 50–75% reduction in cumulative demand and 72–87% reduction in in-use stock in 2050, depending on the material and battery chemistry pathway. Generally, the reduction potentials are larger than the potential contributions from recycling, suggesting that these complementary measures may be more effective in reducing material demand.

Comprehensive discovery and functional characterization of the noncanonical proteome

The systematic identification and functional characterization of noncanonical translation products, such as novel peptides, will facilitate the understanding of the human genome and provide new insights into cell biology. Here, we constructed a high-coverage peptide sequencing reference library with 11,668,944 open reading frames and employed an ultrafiltration tandem mass spectrometry assay to identify novel peptides. Through these methods, we discovered 8945 previously unannotated peptides from normal gastric tissues, gastric cancer tissues and cell lines, nearly half of which were derived from noncoding RNAs. Moreover, our CRISPR screening revealed that 1161 peptides are involved in tumor cell proliferation. The presence and physiological function of a subset of these peptides, selected based on screening scores, amino acid length, and various indicators, were verified through Flag-knockin and multiple other methods. To further characterize the potential regulatory mechanisms involved, we constructed a framework based on artificial intelligence structure prediction and peptide‒protein interaction network analysis for the top 100 candidates and revealed that these cancer-related peptides have diverse subcellular locations and participate in organelle-specific processes. Further investigation verified the interacting partners of pep1-nc-OLMALINC, pep5-nc-TRHDE-AS1, pep-nc-ZNF436-AS1 and pep2-nc-AC027045.3, and the functions of these peptides in mitochondrial complex assembly, energy metabolism, and cholesterol metabolism, respectively. We showed that pep5-nc-TRHDE-AS1 and pep2-nc-AC027045.3 had substantial impacts on tumor growth in xenograft models. Furthermore, the dysregulation of these four peptides is closely correlated with clinical prognosis. Taken together, our study provides a comprehensive characterization of the noncanonical proteome, and highlights critical roles of these previously unannotated peptides in cancer biology.

Anthropogenic organic aerosol in Europe produced mainly through second-generation oxidation

Exposure to anthropogenic atmospheric aerosol is a major health issue, causing several million deaths per year worldwide. The oxidation of aromatic hydrocarbons from traffic and wood combustion is an important anthropogenic source of low-volatility species in secondary organic aerosol, especially in heavily polluted environments. It is not yet established whether the formation of anthropogenic secondary organic aerosol involves mainly rapid autoxidation, slower sequential oxidation steps or a combination of the two. Here we reproduced a typical urban haze in the ‘Cosmics Leaving Outdoor Droplets’ chamber at the European Organization for Nuclear Research and observed the dynamics of aromatic oxidation products during secondary organic aerosol growth on a molecular level to determine mechanisms underlying their production and removal. We demonstrate that sequential oxidation is required for substantial secondary organic aerosol formation. Second-generation oxidation decreases the products’ saturation vapour pressure by several orders of magnitude and increases the aromatic secondary organic aerosol yields from a few percent to a few tens of percent at typical atmospheric concentrations. Through regional modelling, we show that more than 70% of the exposure to anthropogenic organic aerosol in Europe arises from second-generation oxidation.

Probing out-of-distribution generalization in machine learning for materials

Scientific machine learning (ML) aims to develop generalizable models, yet assessments of generalizability often rely on heuristics. Here, we demonstrate in the materials science setting that heuristic evaluations lead to biased conclusions of ML generalizability and benefits of neural scaling, through evaluations of out-of-distribution (OOD) tasks involving unseen chemistry or structural symmetries. Surprisingly, many tasks demonstrate good performance across models, including boosted trees. However, analysis of the materials representation space shows that most test data reside within regions well-covered by training data, while poorly-performing tasks involve data outside the training domain. For these challenging tasks, increasing training size or time yields limited or adverse effects, contrary to traditional neural scaling trends. Our findings highlight that most OOD tests reflect interpolation, not true extrapolation, leading to overestimations of generalizability and scaling benefits. This emphasizes the need for rigorously challenging OOD benchmarks.

Chemical linkers switch triglycerol detergents from bacterial protein purification to mild antibiotic amplification

Non-ionic detergents enable the investigation of cell membranes, including biomolecule purification and drug delivery. The question of whether non-ionic detergents associated with satisfying protein yields following extraction and affinity purification of proteins from lysed E. coli membranes can amplify antibiotics on whole-cell E. coli remains to be addressed. We unlock the modular chemistry of linear triglycerol detergents to reveal that more polar, non-ionic detergents that form globular micelles work better in amplifying antimicrobial activities of antibiotics than in purifying the membrane proteins mechanosensitive channel and aquaporin Z. Less polar detergents that form worm-like micelles indicate poor performances in both applications. With chromatography we demonstrate how fine-tuning the polarity of chemical linkers between detergent headgroups and tails can switch the utility of detergents from protein purification to antibiotic amplification. We anticipate our findings to be a starting point for structure-property studies to better understand detergent designs in supramolecular chemistry and membrane research.

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