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Human APOBEC single-strand (ss) specific DNA and RNA cytidine deaminases change cytosines to uracils and function in antiviral innate immunity, RNA editing, and can cause hypermutation in chromosomes. The resulting uracils can be directly replicated, resulting in C to T mutations, or uracil-DNA glycosylase can convert the uracils to abasic (AP) sites which are then fixed as C to T or C to G mutations by translesion DNA polymerases. We noticed that in yeast and in human cancers, contributions of C to T and C to G mutations depends on the origin of ssDNA mutagenized by APOBECs. Since ssDNA in eukaryotic genomes readily binds to replication protein A (RPA) we asked if RPA could affect APOBEC-induced mutation spectrum in yeast. For that purpose, we expressed human APOBECs in the wild-type yeast and in strains carrying a hypomorph mutation rfa1-t33 in the large RPA subunit. We confirmed that the rfa1-t33 allele can facilitate mutagenesis by APOBECs. We also found that the rfa1-t33 mutation changed the ratio of APOBEC3A-induced T to C and T to G mutations in replicating yeast to resemble a ratio observed in long-persistent ssDNA in yeast and in cancers. We present the data suggesting that RPA may shield APOBEC formed uracils in ssDNA from Ung1, thereby facilitating C to T mutagenesis through the accurate copying of uracils by replicative DNA polymerases. Unexpectedly, we also found that for uracils shielded from Ung1 by wild-type RPA the mutagenic outcome is reduced in the presence of translesion DNA polymerase zeta.

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Human APOBEC single-strand (ss) specific DNA and RNA cytidine deaminases change cytosines to uracils and function in antiviral innate immunity, RNA editing, and can cause hypermutation in chromosomes. The resulting uracils can be directly replicated, resulting in C to T mutations, or uracil-DNA glycosylase can convert the uracils to abasic (AP) sites which are then fixed as C to T or C to G mutations by translesion DNA polymerases. We noticed that in yeast and in human cancers, contributions of C to T and C to G mutations depends on the origin of ssDNA mutagenized by APOBECs. Since ssDNA in eukaryotic genomes readily binds to replication protein A (RPA) we asked if RPA could affect APOBEC-induced mutation spectrum in yeast. For that purpose, we expressed human APOBECs in the wild-type yeast and in strains carrying a hypomorph mutation rfa1-t33 in the large RPA subunit. We confirmed that the rfa1-t33 allele can facilitate mutagenesis by APOBECs. We also found that the rfa1-t33 mutation changed the ratio of APOBEC3A-induced T to C and T to G mutations in replicating yeast to resemble a ratio observed in long-persistent ssDNA in yeast and in cancers. We present the data suggesting that RPA may shield APOBEC formed uracils in ssDNA from Ung1, thereby facilitating C to T mutagenesis through the accurate copying of uracils by replicative DNA polymerases. Unexpectedly, we also found that for uracils shielded from Ung1 by wild-type RPA the mutagenic outcome is reduced in the presence of translesion DNA polymerase zeta.

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APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

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Structural properties of the currency market were examined with the use of topological networks. Relationships between currencies were analyzed by constructing minimal spanning trees (MSTs). The dissimilarities between time series of currency returns were measured in various ways: by applying Euclidean distance, Pearson's linear correlation coefficient, Spearman's rank correlation coefficient, Kendall's coefficient, partial correlation, dynamic time warping measure, and Kullback-Leibler relative entropy. For the constructed MSTs, their topological characteristics were analyzed and conclusions were drawn regarding the influence of the dissimilarity measure used. It turned out that the strength of most types of correlations was highly dependent on the choice of the numeraire currency, while partial correlations were invariant in this respect. It can be stated that a network built on the basis of partial correlations provides a more adequate illustration of pairwise relationships in the foreign exchange market. The data for quotations of 37 of the most important world currencies and four precious metals in the period from 1 January 2019 to 31 December 2022 were used. The outbreak of the COVID-19 pandemic in 2020 and Russia's invasion of Ukraine in 2022 triggered changes in the topology of the currency network. As a result of these crises, the average distances between tree nodes decreased and the centralization of graphs increased. Our results confirm that currencies are often pegged to other currencies due to countries' geographic locations and economic ties. The detected structures can be useful in descriptions of the currency market, can help in constructing a stable portfolio of the foreign exchange rates, and can be a valuable tool in searching for economic factors influencing specific groups of countries.

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X-ray free-electron lasers are sources of coherent, high-intensity X-rays with numerous applications in ultra-fast measurements and dynamic structural imaging. Due to the stochastic nature of the self-amplified spontaneous emission process and the difficulty in controlling injection of electrons, output pulses exhibit significant noise and limited temporal coherence. Standard measurement techniques used for characterizing two-coloured X-ray pulses are challenging, as they are either invasive or diagnostically expensive. In this work, we employ machine learning methods such as neural networks and decision trees to predict the central photon energies of pairs of attosecond fundamental and second harmonic pulses using parameters that are easily recorded at the high-repetition rate of a single shot. Using real experimental data, we apply a detailed feature analysis on the input parameters while optimizing the training time of the machine learning methods. Our predictive models are able to make predictions of central photon energy for one of the pulses without measuring the other pulse, thereby leveraging the use of the spectrometer without having to extend its detection window. We anticipate applications in X-ray spectroscopy using XFELs, such as in time-resolved X-ray absorption and photoemission spectroscopy, where improved measurement of input spectra will lead to better experimental outcomes.

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Correction for 'Cumulant mapping as the basis of multi-dimensional spectrometry' by Leszek J. Frasinski, Phys. Chem. Chem. Phys., 2022, 24, 20776-20787, https://doi.org/10.1039/D2CP02365B.

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Organic semiconductors are a family of pi-conjugated compounds used in many applications, such as displays, bioelectronics, and thermoelectrics. However, their susceptibility to processing-induced contamination is not well understood. Here, it is shown that many organic electronic devices reported so far may have been unintentionally contaminated, thus affecting their performance, water uptake, and thin film properties. Nuclear magnetic resonance spectroscopy is used to detect and quantify contaminants originating from the glovebox atmosphere and common laboratory consumables used during device fabrication. Importantly, this in-depth understanding of the sources of contamination allows the establishment of clean fabrication protocols, and the fabrication of organic field effect transistors (OFETs) with improved performance and stability. This study highlights the role of unintentional contaminants in organic electronic devices, and demonstrates that certain stringent processing conditions need to be met to avoid scientific misinterpretation, ensure device reproducibility, and facilitate performance stability. The experimental procedures and conditions used herein are typical of those used by many groups in the field of solution-processed organic semiconductors. Therefore, the insights gained into the effects of contamination are likely to be broadly applicable to studies, not just of OFETs, but also of other devices based on these materials.

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Mutagens often prefer specific nucleotides or oligonucleotide motifs that can be revealed by studying the hypermutation spectra in single-stranded (ss) DNA. We utilized a yeast model to explore mutagenesis by glycidamide, a simple epoxide formed endogenously in humans from the environmental toxicant acrylamide. Glycidamide caused ssDNA hypermutation in yeast predominantly in cytosines and adenines. The most frequent mutations in adenines occurred in the nAt→nGt trinucleotide motif. Base substitutions A→G in this motif relied on Rev1 translesion polymerase activity. Inactivating Rev1 did not alter the nAt trinucleotide preference, suggesting it may be an intrinsic specificity of the chemical reaction between glycidamide and adenine in the ssDNA. We found this mutational motif enriched in published sequencing data from glycidamide-treated mouse cells and ubiquitous in human cancers. In cancers, this motif was positively correlated with the single base substitution (SBS) smoking-associated SBS4 signature, with the clock-like signatures SBS1, SBS5, and was strongly correlated with smoking history and with age of tumor donors. Clock-like feature of the motif was also revealed in cells of human skin and brain. Given its pervasiveness, we propose that this mutational motif reflects mutagenic lesions to adenines in ssDNA from a potentially broad range of endogenous and exogenous agents.

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Combinatorial post-translational modifications (PTMs), such as those forming the so-called "histone code", have been linked to cell differentiation, embryonic development, cellular reprogramming, aging, cancers, neurodegenerative disorders, etc. Nevertheless, a reliable mass spectral analysis of the combinatorial isomers represents a considerable challenge. The difficulty stems from the incompleteness of information that could be generated by the standard MS to differentiate cofragmented isomeric sequences in their naturally occurring mixtures based on the fragment mass-to-charge ratio and relative abundance information only. Here we show that fragment-fragment correlations revealed by two-dimensional partial covariance mass spectrometry (2D-PC-MS) allow one to solve the combinatorial PTM puzzles that cannot be tackled by the standard MS as a matter of principle. We introduce 2D-PC-MS marker ion correlation approach and demonstrate experimentally that it can provide the missing information enabling identification of cofragmentated combinatorially modified isomers. Our in silico study shows that the marker ion correlations can be used to unambiguously identify 5 times more cofragmented combinatorially acetylated tryptic peptides and 3 times more combinatorially modified Glu-C peptides of human histones than is possible using standard MS methods.

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Mutational signatures discerned in cancer genomes, in aging tissues and in cells exposed to toxic agents, reflect complex processes underlying transformation of cells from normal to dysfunctional. Due to its ubiquitous and chronic nature, redox stress contributions to cellular makeover remain equivocal. The deciphering of a new mutational signature of an environmentally-relevant oxidizing agent, potassium bromate, in yeast single strand DNA uncovered a surprising heterogeneity in the mutational signatures of oxidizing agents. NMR-based analysis of molecular outcomes of redox stress revealed profound dissimilarities in metabolic landscapes following exposure to hydrogen peroxide versus potassium bromate. The predominance of G to T substitutions in the mutational spectra distinguished potassium bromate from hydrogen peroxide and paraquat and mirrored the observed metabolic changes. We attributed these changes to the generation of uncommon oxidizing species in a reaction with thiol-containing antioxidants; a nearly total depletion of intracellular glutathione and a paradoxical augmentation of potassium bromate mutagenicity and toxicity by antioxidants. Our study provides the framework for understanding multidimensional processes triggered by agents collectively known as oxidants. Detection of increased mutational loads associated with potassium bromate-related mutational motifs in human tumors may be clinically relevant as a biomarker of this distinct type of redox stress.

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We extend covariance velocity map ion imaging to four particles, establishing cumulant mapping and allowing for measurements that provide insights usually associated with coincidence detection, but at much higher count rates. Without correction, a fourfold covariance analysis is contaminated by the pairwise correlations of uncorrelated events, but we have addressed this with the calculation of a full cumulant, which subtracts pairwise correlations. We demonstrate the approach on the four-body breakup of formaldehyde following strong field multiple ionization in few-cycle laser pulses. We compare Coulomb explosion imaging for two different pulse durations (30 and 6 fs), highlighting the dynamics that can take place on ultrafast timescales. These results have important implications for Coulomb explosion imaging as a tool for studying ultrafast structural changes in molecules, a capability that is especially desirable for high-count-rate x-ray free-electron laser experiments.

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Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of 'multi-fold' or 'multi-dimensional' covariance mapping. Explicit formulae have been derived for the expected values of up to the 6th cumulant and the variance has been calculated for up to the 4th cumulant. A method of extending these formulae to higher cumulants has been described. The formulae take into account reduced fragment detection efficiency and a background from uncorrelated events. Number of samples needed for suppressing the statistical noise to a required level can be estimated using Matlab code included in Supplemental Material. The theory can be used to assess the experimental feasibility of studying molecular fragmentations induced by femtosecond or X-ray free-electron lasers. It is also relevant for extending the conventional mass spectrometry of biomolecules to multiple dimensions.

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The field of organic electronics has profited from the discovery of new conjugated semiconducting polymers that have molecular backbones which exhibit resilience to conformational fluctuations, accompanied by charge carrier mobilities that routinely cross the 1 cm2/Vs benchmark. One such polymer is indacenodithiophene-co-benzothiadiazole. Previously understood to be lacking in microstructural order, we show here direct evidence of nanosized domains of high order in its thin films. We also demonstrate that its device-based high-performance electrical and thermoelectric properties are not intrinsic but undergo rapid stabilization following a burst of ambient air exposure. The polymer's nanomechanical properties equilibrate on longer timescales owing to an orthogonal mechanism; the gradual sweating-out of residual low molecular weight solvent molecules from its surface. We snapshot the quasistatic temporal evolution of the electrical, thermoelectric and nanomechanical properties of this prototypical organic semiconductor and investigate the subtleties which play on competing timescales. Our study documents the untold and often overlooked story of a polymer device's dynamic evolution toward stability.

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Doped organic semiconductors are critical to emerging device applications, including thermoelectrics, bioelectronics, and neuromorphic computing devices. It is commonly assumed that low conductivities in these materials result primarily from charge trapping by the Coulomb potentials of the dopant counterions. Here, we present a combined experimental and theoretical study rebutting this belief. Using a newly developed doping technique based on ion exchange, we prepare highly doped films with several counterions of varying size and shape and characterize their carrier density, electrical conductivity, and paracrystalline disorder. In this uniquely large data set composed of several classes of high-mobility conjugated polymers, each doped with at least five different ions, we find electrical conductivity to be strongly correlated with paracrystalline disorder but poorly correlated with ionic size, suggesting that Coulomb traps do not limit transport. A general model for interacting electrons in highly doped polymers is proposed and carefully parametrized against atomistic calculations, enabling the calculation of electrical conductivity within the framework of transient localization theory. Theoretical calculations are in excellent agreement with experimental data, providing insights into the disorder-limited nature of charge transport and suggesting new strategies to further improve conductivities.

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We present a protein database search engine for the automatic identification of peptide and protein sequences using the recently introduced method of two-dimensional partial covariance mass spectrometry (2D-PC-MS). Because the 2D-PC-MS measurement reveals correlations between fragments stemming from the same or consecutive decomposition processes, the first-of-its-kind 2D-PC-MS search engine is based entirely on the direct matching of the pairs of theoretical and the experimentally detected correlating fragments, rather than of individual fragment signals or their series. We demonstrate that the high structural specificity afforded by 2D-PC-MS fragment correlations enables our search engine to reliably identify the correct peptide sequence, even from a spectrum with a large proportion of contaminant signals. While for peptides, the 2D-PC-MS correlation-matching procedure is based on complementary and internal ion correlations, the identification of intact proteins is entirely based on the ability of 2D-PC-MS to spatially separate and resolve the experimental correlations between complementary fragment ions.

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Lung cancer in never smokers (LCINS) is a common cause of cancer mortality but its genomic landscape is poorly characterized. Here high-coverage whole-genome sequencing of 232 LCINS showed 3 subtypes defined by copy number aberrations. The dominant subtype (piano), which is rare in lung cancer in smokers, features somatic UBA1 mutations, germline AR variants and stem cell-like properties, including low mutational burden, high intratumor heterogeneity, long telomeres, frequent KRAS mutations and slow growth, as suggested by the occurrence of cancer drivers' progenitor cells many years before tumor diagnosis. The other subtypes are characterized by specific amplifications and EGFR mutations (mezzo-forte) and whole-genome doubling (forte). No strong tobacco smoking signatures were detected, even in cases with exposure to secondhand tobacco smoke. Genes within the receptor tyrosine kinase-Ras pathway had distinct impacts on survival; five genomic alterations independently doubled mortality. These findings create avenues for personalized treatment in LCINS.

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Two-dimensional partial covariance mass spectrometry (2D-PC-MS) exploits the inherent fluctuations of fragment ion abundances across a series of tandem mass spectra, to identify correlated pairs of fragment ions produced along the same fragmentation pathway of the same parent (e.g., peptide) ion. Here, we apply 2D-PC-MS to the analysis of intact protein ions in a standard linear ion trap mass analyzer, using the fact that the fragment-fragment correlation signals are much more specific to the biomolecular sequence than one-dimensional (1D) tandem mass spectrometry (MS/MS) signals at the same mass accuracy and resolution. We show that from the distribution of signals on a 2D-PC-MS map it is possible to extract the charge state of both parent and fragment ions without resolving the isotopic envelope. Furthermore, the 2D map of fragment-fragment correlations naturally separates the products of the primary decomposition pathways of the molecular ions from those of the secondary ones. We access this spectral information using an adapted version of the Hough transform. We demonstrate the successful identification of highly charged, intact protein molecules bypassing the need for high mass resolution. Using this technique, we also perform the in silico deconvolution of the overlapping fragment ion signals from two co-isolated and co-fragmented intact proteins, demonstrating a viable new method for the concurrent mass spectrometric identification of a mixture of intact protein ions from the same fragment ion spectrum.

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