Comprehensive evidence implies a higher social cost of CO2.

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Genomic landscape of non-small cell lung cancer in smokers and never-smokers.

We report the results of whole-genome and transcriptome sequencing of tumor and adjacent normal tissue samples from 17 patients with non-small cell lung carcinoma (NSCLC). We identified 3,726 point mutations and more than 90 indels in the coding sequence, with an average mutation frequency more than 10-fold higher in smokers than in never-smokers. Novel alterations in genes involved in chromatin modification and DNA repair pathways were identified, along with DACH1, CFTR, RELN, ABCB5, and HGF. Deep digital sequencing revealed diverse clonality patterns in both never-smokers and smokers. All validated EFGR and KRAS mutations were present in the founder clones, suggesting possible roles in cancer initiation. Analysis revealed 14 fusions, including ROS1 and ALK, as well as novel metabolic enzymes. Cell-cycle and JAK-STAT pathways are significantly altered in lung cancer, along with perturbations in 54 genes that are potentially targetable with currently available drugs.

The origin and evolution of mutations in acute myeloid leukemia.

Most mutations in cancer genomes are thought to be acquired after the initiating event, which may cause genomic instability and drive clonal evolution. However, for acute myeloid leukemia (AML), normal karyotypes are common, and genomic instability is unusual. To better understand clonal evolution in AML, we sequenced the genomes of M3-AML samples with a known initiating event (PML-RARA) versus the genomes of normal karyotype M1-AML samples and the exomes of hematopoietic stem/progenitor cells (HSPCs) from healthy people. Collectively, the data suggest that most of the mutations found in AML genomes are actually random events that occurred in HSPCs before they acquired the initiating mutation; the mutational history of that cell is "captured" as the clone expands. In many cases, only one or two additional, cooperating mutations are needed to generate the malignant founding clone. Cells from the founding clone can acquire additional cooperating mutations, yielding subclones that can contribute to disease progression and/or relapse.

AI-guided histopathology predicts brain metastasis in lung cancer patients.

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Site IQ in mitochondrial complex I generates S1QEL-sensitive superoxide/hydrogen peroxide in both the reverse and forward reactions.

Superoxide/hydrogen peroxide production by site IQ in complex I of the electron transport chain is conventionally assayed during reverse electron transport (RET) from ubiquinol to NAD. However, S1QELs (specific suppressors of superoxide/hydrogen peroxide production by site IQ) have potent effects in cells and in vivo during presumed forward electron transport (FET). Therefore, we tested whether site IQ generates S1QEL-sensitive superoxide/hydrogen peroxide during FET (site IQf), or alternatively, whether RET and associated S1QEL-sensitive superoxide/hydrogen peroxide production (site IQr) occurs in cells under normal conditions. We introduce an assay to determine if electron flow through complex I is thermodynamically forward or reverse: on blocking electron flow through complex I, the endogenous matrix NAD pool will become more reduced if flow before the challenge was forward, but more oxidised if flow was reverse. Using this assay we show in the model system of isolated rat skeletal muscle mitochondria that superoxide/hydrogen peroxide production by site IQ can be equally great whether RET or FET is running. We show that sites IQr and IQf are equally sensitive to S1QELs, and to rotenone and piericidin A, inhibitors that block the Q-site of complex I. We exclude the possibility that some sub-fraction of the mitochondrial population running site IQr during FET is responsible for S1QEL-sensitive superoxide/hydrogen peroxide production by site IQ. Finally, we show that superoxide/hydrogen peroxide production by site IQ in cells occurs during FET, and is S1QEL-sensitive.

A comparison of three automated root-knot nematode egg counting approaches using machine learning, image analysis, and a hybrid model.

Meloidogyne spp. (root-knot nematodes, RKN) are a major threat to a wide range of agricultural crops worldwide. Breeding crops for RKN resistance is an effective management strategy, yet assaying large numbers of breeding lines requires laborious bioassays that are time-consuming and require experienced researchers. In these bioassays, quantifying nematode eggs through manual counting is considered the current standard for quantifying establishing resistance in plant genotypes. Counting RKN eggs is highly laborious, and even experienced researchers are subject to fatigue or misclassification, leading to potential errors in phenotyping. Here, we present three automated egg counting models that rely on machine learning and image analysis to quantify RKN eggs extracted from tobacco and sweetpotato plants. The first method relied on convolutional neural networks trained using annotated images to identify eggs (M. enterolobii R2 = 0.899, M. incognita R2 = 0.927, M. javanica R2 = 0.886), while a second contour-based approach used image analysis to identify eggs from their morphological characteristics and did not rely on neural networks (M. enterolobii R2 = 0.977, M. incognita R2 = 0.990, M. javanica R2 = 0.924). A third hybrid model combined these approaches and was able to detect and count eggs nearly as well as human raters (M. enterolobii R2 = 0.985, M. incognita R2 = 0.992, M. javanica R2 = 0.983). These automated counting protocols have the potential to provide significant time and resource savings annually for breeders and nematologists, and may be broadly applicable to other nematode species.

The big four of plant taxonomy - a comparison of global checklists of vascular plant names.

Taxonomic checklists used to verify published plant names and identify synonyms are a cornerstone of biological research. Four global authoritative checklists for vascular plants exist: Leipzig Catalogue of Vascular Plants, World Checklist of Vascular Plants, World Flora Online (successor of The Plant List, TPL), and WorldPlants. We compared these four checklists in terms of size and differences across taxa. We matched taxon names of these checklists and TPL against each other, identified differences across checklists, and evaluated the consistency of accepted names linked to individual taxon names. We assessed geographic and phylogenetic patterns of variance. All checklists differed strongly compared with TPL and provided identical information on c. 60% of plant names. Geographically, differences in checklists increased from low to high latitudes. Phylogenetically, we detected strong variability across families. A comparison of name-matching performance on taxon names submitted to the functional trait database TRY, and a check of completeness of accepted names evaluated against an independent, expert-curated checklist of the family Meliaceae, showed a similar performance across checklists. This study raises awareness on the differences in data and approach across these checklists potentially impacting analyses. We propose ideas on the way forward exploring synergies and harmonizing the four global checklists.

Comment on the Definition and Labeling of pK50.

We propose a more rigorous definition for the recently introduced concept of pK50. The value of pK50 should be associated not with a "functional group", as originally postulated, but instead with an atom. The proposed clarification is meant to improve the interpretation and labeling of pK50.

Comparison of in vitro growth characteristics of Cryptosporidium hominis (IdA15G1) and Cryptosporidium parvum (Iowa-IIaA17G2R1 and IIaA18G3R1).

Cryptosporidium is a major cause of diarrhoeal disease and mortality in young children in resource-poor countries, for which no vaccines or adequate therapeutic options are available. Infection in humans is primarily caused by two species: C. hominis and C. parvum. Despite C. hominis being the dominant species infecting humans in most countries, very little is known about its growth characteristics and life cycle in vitro, given that the majority of our knowledge of the in vitro development of Cryptosporidium has been based on C. parvum. In the present study, the growth and development of two C. parvum isolates (subtypes Iowa-IIaA17G2R1 and IIaA18G3R1) and one C. hominis isolate (subtype IdA15G1) in HCT-8 cells were examined and compared at 24 h and 48 h using morphological data acquired with scanning electron microscopy. Our data indicated no significant differences in the proportion of meronts or merozoites between species or subtypes at either time-point. Sexual development was observed at the 48-h time-point across both species through observations of both microgamonts and macrogamonts, with a higher frequency of macrogamont observations in C. hominis (IdA15G1) cultures at 48-h post-infection compared to both C. parvum subtypes. This corresponded to differences in the proportion of trophozoites observed at the same time point. No differences in proportion of microgamonts were observed between the three subtypes, which were rarely observed across all cultures. In summary, our data indicate that asexual development of C. hominis is similar to that of C. parvum, while sexual development is accelerated in C. hominis. This study provides new insights into differences in the in vitro growth characteristics of C. hominis when compared to C. parvum, which will facilitate our understanding of the sexual development of both species.

A conserved role of the insulin-like signaling pathway in diet-dependent uric acid pathologies in Drosophila melanogaster.

Elevated uric acid (UA) is a key risk factor for many disorders, including metabolic syndrome, gout and kidney stones. Despite frequent occurrence of these disorders, the genetic pathways influencing UA metabolism and the association with disease remain poorly understood. In humans, elevated UA levels resulted from the loss of the of the urate oxidase (Uro) gene around 15 million years ago. Therefore, we established a Drosophila melanogaster model with reduced expression of the orthologous Uro gene to study the pathogenesis arising from elevated UA. Reduced Uro expression in Drosophila resulted in elevated UA levels, accumulation of concretions in the excretory system, and shortening of lifespan when reared on diets containing high levels of yeast extract. Furthermore, high levels of dietary purines, but not protein or sugar, were sufficient to produce the same effects of shortened lifespan and concretion formation in the Drosophila model. The insulin-like signaling (ILS) pathway has been shown to respond to changes in nutrient status in several species. We observed that genetic suppression of ILS genes reduced both UA levels and concretion load in flies fed high levels of yeast extract. Further support for the role of the ILS pathway in modulating UA metabolism stems from a human candidate gene study identifying SNPs in the ILS genes AKT2 and FOXO3 being associated with serum UA levels or gout. Additionally, inhibition of the NADPH oxidase (NOX) gene rescued the reduced lifespan and concretion phenotypes in Uro knockdown flies. Thus, components of the ILS pathway and the downstream protein NOX represent potential therapeutic targets for treating UA associated pathologies, including gout and kidney stones, as well as extending human healthspan.

Controlled power: how biology manages succinate-driven energy release.

Oxidation of succinate by mitochondria can generate a higher protonmotive force (pmf) than can oxidation of NADH-linked substrates. Fundamentally, this is because of differences in redox potentials and gearing. Biology adds kinetic constraints that tune the oxidation of NADH and succinate to ensure that the resulting mitochondrial pmf is suitable for meeting cellular needs without triggering pathology. Tuning within an optimal range is used, for example, to shift ATP consumption between different consumers. Conditions that overcome these constraints and allow succinate oxidation to drive pmf too high can cause pathological generation of reactive oxygen species. We discuss the thermodynamic properties that allow succinate oxidation to drive pmf higher than NADH oxidation, and discuss the evidence for kinetic tuning of ATP production and for pathologies resulting from substantial succinate oxidation in vivo.

Pattern-free generation and quantum mechanical scoring of ring-chain tautomers.

In contrast to the computational generation of conventional tautomers, the analogous operation that would produce ring-chain tautomers is rarely available in cheminformatics codes. This is partly due to the perceived unimportance of ring-chain tautomerism and partly because specialized algorithms are required to realize the non-local proton transfers that occur during ring-chain rearrangement. Nevertheless, for some types of organic compounds, including sugars, warfarin analogs, fluorescein dyes and some drug-like compounds, ring-chain tautomerism cannot be ignored. In this work, a novel ring-chain tautomer generation algorithm is presented. It differs from previously proposed solutions in that it does not rely on hard-coded patterns of proton migrations and bond rearrangements, and should therefore be more general and maintainable. We deploy this algorithm as part of a workflow which provides an automated solution for tautomer generation and scoring. The workflow identifies protonatable and deprotonatable sites in the molecule using a previously described approach based on rapid micro-pKa prediction. These data are used to distribute the active protons among the protonatable sites exhaustively, at which point alternate resonance structures are considered to obtain pairs of atoms with opposite formal charge. These pairs are connected with a single bond and a 3D undistorted geometry is generated. The scoring of the generated tautomers is performed with a subsequent density functional theory calculation employing an implicit solvent model. We demonstrate the performance of our workflow on several types of organic molecules known to exist in ring-chain tautomeric equilibria in solution. In particular, we show that some ring-chain tautomers not found using previously published algorithms are successfully located by ours.

Longitudinal CSF proteomics identifies NPTX2 as a prognostic biomarker of Alzheimer's disease.

INTRODUCTION: Biomarkers that reflect pathologic processes affecting neuronal function during preclinical and early stages of Alzheimer's disease (AD) are needed to aid drug development. METHODS: A targeted, stable isotope, quantitative mass spectrometry-based investigation of longitudinal changes in concentrations of previously identified candidate biomarkers was performed in cerebrospinal fluid (CSF) of Alzheimer's Disease Neuroimaging Initiative participants who were classified as cognitively normal (CN; n = 76) or with mild cognitive impairment (MCI; n = 111) at baseline. RESULTS: Of the candidate biomarkers, the CSF concentration of neuronal pentraxin 2 (NPTX2), a protein involved in synaptic function, exhibited rates of change that were significantly different between three comparison groups (i.e., CN vs. MCI participants; AD pathology positive vs. negative defined by phosphorylated tau181/amyloid beta1-42 ratio; and clinical progressors vs. non-progressors). The rate of change of NPTX2 also significantly correlated with declining cognition. DISCUSSION: CSF NPTX2 concentration is a strong prognostic biomarker candidate of accelerated cognitive decline with potential use as a therapeutic target.

Single-cell transcriptomic profiling provides insights into retinal endothelial barrier properties.

Purpose: To better characterize retinal endothelial barrier properties through analysis of individual transcriptomes of primary bovine retinal microvascular endothelial cells (RMECs). Methods: Individual RMECs were captured on the Fluidigm C1 system, cDNA libraries were prepared using a Nextera XT kit, and sequencing was performed on a NextSeq system (Illumina). Data analysis was performed using R packages Scater, SC3, and Seurat, and the browser application Automated Single-cell Analysis Pipeline (ASAP). Alternative splicing events in single cells were quantified with Outrigger. Cytoscape was used for network analyses. Results: Application of a single-cell RNA sequencing (scRNA-seq) analysis workflow showed that RMECs form a relatively homogeneous population in culture, with the main differences related to proliferation status. Expression of markers from along the arteriovenous tree suggested that most cells originated from capillaries. Average gene expression levels across all cells were used to develop an in silico model of the inner blood-retina barrier incorporating junctional proteins not previously reported within the retinal vasculature. Correlation of barrier gene expression among individual cells revealed a subgroup of genes highly correlated with PECAM-1 at the center of the correlation network. Numerous alternative splicing events involving exons within microvascular barrier genes were observed, and in many cases, individual cells expressed one isoform exclusively. Conclusions: We optimized a workflow for single-cell transcriptomics in primary RMECs. The results provide fundamental insights into the genes involved in formation of the retinal-microvascular barrier.

HLA-A*32:01 is strongly associated with vancomycin-induced drug reaction with eosinophilia and systemic symptoms.

BACKGROUND: Vancomycin is a prevalent cause of the severe hypersensitivity syndrome drug reaction with eosinophilia and systemic symptoms (DRESS), which leads to significant morbidity and mortality and commonly occurs in the setting of combination antibiotic therapy, affecting future treatment choices. Variations in HLA class I in particular have been associated with serious T cell-mediated adverse drug reactions, which has led to preventive screening strategies for some drugs. OBJECTIVE: We sought to determine whether variation in the HLA region is associated with vancomycin-induced DRESS. METHODS: Probable vancomycin-induced DRESS cases were matched 1:2 with tolerant control subjects based on sex, race, and age by using BioVU, Vanderbilt's deidentified electronic health record database. Associations between DRESS and carriage of HLA class I and II alleles were assessed by means of conditional logistic regression. An extended sample set from BioVU was used to conduct a time-to-event analysis of those exposed to vancomycin with and without the identified HLA risk allele. RESULTS: Twenty-three subjects met the inclusion criteria for vancomycin-associated DRESS. Nineteen (82.6%) of 23 cases carried HLA-A*32:01 compared with 0 (0%) of 46 of the matched vancomycin-tolerant control subjects (P = 1 × 10-8) and 6.3% of the BioVU population (n = 54,249, P = 2 × 10-16). Time-to-event analysis of DRESS development during vancomycin treatment among the HLA-A*32:01-positive group indicated that 19.2% had DRESS and did so within 4 weeks. CONCLUSIONS: HLA-A*32:01 is strongly associated with vancomycin-induced DRESS in a population of predominantly European ancestry. HLA-A*32:01 testing could improve antibiotic safety, help implicate vancomycin as the causal drug, and preserve future treatment options with coadministered antibiotics.

Regioselective Hydrogenation of a 60-Carbon Nanographene Molecule toward a Circumbiphenyl Core.

Regioselective peripheral hydrogenation of a nanographene molecule with 60 contiguous sp2 carbons provides unprecedented access to peralkylated circumbiphenyl (1). Conversion to the circumbiphenyl core structure was unambiguously validated by MALDI-TOF mass spectrometry, NMR, FT-IR, and Raman spectroscopy. UV-vis absorption spectra and DFT calculations demonstrated the significant change of the optoelectronic properties upon peripheral hydrogenation. Stimulated emission from 1, observed via ultrafast transient absorption measurements, indicates potential as an optical gain material.

Drug-induced alloreactivity: A new paradigm for allorecognition.

Abacavir administration is associated with drug-induced hypersensitivity reactions in HIV+ individuals expressing the HLA-B*57:01 allele. However, the immunological effects of abacavir administration in an HLA-B57 mismatched transplantation setting have not been studied. We hypothesized that abacavir exposure could induce de novo HLA-B57-specific allorecognition. HIV-specific CD8 T cell clones were generated from HIV+ individuals, using single cell sorting based on HIV peptide/HLA tetramer staining. The T cell clones were assayed for alloreactivity against a panel of single HLA-expressing cell lines, in the presence or absence of abacavir. Cytokine assay, CD137 upregulation, and cytotoxicity were used as readout. Abacavir exposure can induce de novo HLA-B57 allorecognition by HIV-specific T cells. A HIV Gag RK9/HLA-A3-specific T cell did exhibit interferon-γ production, CD137 upregulation, and cytolytic effector function against allogeneic HLA-B57, but only in the presence of abacavir. Allorecognition was specific to the virus specificity, HLA restriction, and T cell receptor TRBV use of the T cell. We provide proof-of-principle evidence that administration of a drug could induce specific allorecognition of mismatched HLA molecules in the transplant setting. We suggest that HIV-seropositive recipients of an HLA-B57 mismatched graft should not receive abacavir until further studies are completed.

Gene expression analysis to detect disseminated tumor cells in the bone marrow of triple-negative breast cancer patients predicts metastatic relapse.

PURPOSE: Disseminated tumor cells (DTCs) in the BM of breast cancer patients predict early disease relapse, but the molecular heterogeneity of these cells is less well characterized. Expression of a 46-gene panel was used to detect DTCs and classify patient BM samples to determine whether a composite set of biomarkers could better predict metastatic relapse. METHODS: Using a high-throughput qRT-PCR assay platform, BM specimens collected from 70 breast cancer patients prior to neoadjuvant therapy were analyzed for the expression of 46 gene transcripts. Gene expression was scored positive (detectable) relative to a reference pool of 16 healthy female control BM specimens. To validate findings from a subset of 28 triple-negative breast cancer (TNBC) patients in the initial 70 patient cohort, an independent set of pre-therapeutic BM specimens from 16 TNBC patients was analyzed. RESULTS: Expression of each of the 46 gene transcripts was highly variable between patients. Individual gene expression was detected in 0-84% of BM specimens analyzed and all but two patient BM specimens expressed at least one transcript. Among a subset of 28 patients with TNBC, positivity of one or more of eight transcripts correlated with time to distant relapse (p = 0.03). In an independent set of 16 triple-negative patient BM samples, detection of five of these same eight gene transcripts also correlated with time to distant relapse (p = 0.03) with a positive predictive value of 89%. CONCLUSIONS: We identified a set of gene transcripts whose detection in the BM of TNBC patients, prior to any treatment intervention, predicts time to first distant relapse, thus identifying a TNBC patient population which requires additional treatment intervention. Because these genes are presumably expressed in populations of DTCs and many encode proteins that are known therapeutic targets (e.g., ERBB2), these results also suggest a potential approach for targeted DTC therapy to mitigate distant metastases in TNBC.

Use of S1QELs and S3QELs to link mitochondrial sites of superoxide and hydrogen peroxide generation to physiological and pathological outcomes.

Changes in mitochondrial superoxide and hydrogen peroxide production may contribute to various pathologies, and even aging, given that over time and in certain conditions, they damage macromolecules and disrupt normal redox signalling. Mitochondria-targeted antioxidants such as mitoQ, mitoVitE, and mitoTEMPO have opened up the study of the importance of altered mitochondrial matrix superoxide/hydrogen peroxide in disease. However, the use of such tools has caveats and they are unable to distinguish precise sites of production within the reactions of substrate oxidation and the electron transport chain. S1QELs are specific small-molecule Suppressors of site IQElectron Leak and S3QELs are specific small-molecule Suppressors of site IIIQoElectron Leak; they prevent superoxide/hydrogen production at specific sites without affecting electron transport or oxidative phosphorylation. We discuss the benefits of using S1QELs and S3QELs as opposed to mitochondria-targeted antioxidants, mitochondrial poisons, and genetic manipulation. We summarise pathologies in which site IQ in mitochondrial complex I and site IIIQo in mitochondrial complex III have been implicated using S1QELs and S3QELs.

Generation of Tautomers Using Micro-p Ka's.

Solutions of organic molecules containing one or more heterocycles with conjugated bonds may exist as a mixture of tautomers, but typically only a few of them are significantly populated even though the potential number grows combinatorially with the number of protonation and deprotonation sites. Generating the most stable tautomers from a given input structure is an important and challenging task, and numerous algorithms to tackle it have been proposed in the literature. This work describes a novel approach for tautomer prediction that involves the combined use of molecular mechanics, semiempirical quantum chemistry, and density functional theory. The key idea in our method is to identify the protonation and deprotonation sites using estimated micro-p Ka's for every atom in the molecule as well as in its nearest protonated and deprotonated forms. To generate tautomers in a systematic way with minimal bias, we then consider the full set of tautomers that arise from the combinatorial distribution of all such mobile protons among all protonatable sites, with efficient postprocessing to screen away high-energy species. To estimate the micro-p Ka's, we present a new method designed for the current task, but we emphasize that any alternative method can be used in conjunction with our basic algorithm. Our approach is therefore grounded in the computational prediction of physical properties in aqueous solution, in contrast to other approaches that may rely on the use of hard-coded rules of proton distribution, previously observed tautomerization patterns from a known chemical space, or human input. We present examples of the application of our algorithm to organic and drug-like molecules, with a focus on novel structures where traditional methods are expected to perform worse.