Wait-times Benchmarks for risk-based prioritization in Transcatheter Aortic Valve Implantation: a simulation study.

BACKGROUND: Demand for transcatheter aortic valve implantation (TAVI) has increased in the last decade, resulting in prolonged wait-times and undesirable health outcomes in many health systems. Risk-based prioritization and wait-times benchmarks can improve equitable access to patients. METHODS: We used simulation models to follow-up a synthetic population of 50,000 individuals from referral to completion of TAVI. Based on their risk of adverse events, patients could be classified as "low-", "medium-" and "high-risk", and shorter wait-times were assigned for the higher risk groups. We assessed the impacts of the size and wait-times for each risk group on waitlist mortality, hospitalization and urgent TAVIs. All scenarios had the same resource constraints, allowing us to explore the trade-offs between faster access for prioritized patients and deferred access for non-prioritized groups. RESULTS: Increasing the proportion of patients categorized as high-risk, and providing more rapid access to the higher-risk groups achieved the greatest reductions in mortality, hospitalizations and urgent TAVIs (relative reductions of up to 29%, 23% and 38%, respectively). However, this occurs at the expense of excessive wait-times in the non-prioritized low-risk group (up to 25 weeks). We propose wait-times of up to 3 weeks for high-risk patients and 7 weeks for medium-risk patients. CONCLUSIONS: Prioritizing higher-risk patients with faster access leads to better health outcomes, however this also results in unacceptably long wait-times for the non-prioritized groups in settings with limited capacity. Decision-makers must be aware of these implications when developing and implementing waitlist prioritization strategies.

Reassessing the alternative ecosystem states proposition in the African savanna-forest domain.

Ecologists are being challenged to predict how ecosystems will respond to climate changes. According to the Multi-Colored World (MCW) hypothesis, climate impacts may not manifest because consumers such as fire and herbivory can override the influence of climate on ecosystem state. One MCW interpretation is that climate determinism fails because alternative ecosystem states (AES) are possible at some locations in climate space. We evaluated theoretical and empirical evidence for the proposition that forest and savanna are AES in Africa. We found that maps which infer where AES zones are located were contradictory. Moreover, data from longitudinal and experimental studies provide inconclusive evidence for AES. That is, although the forest-savanna AES proposition is theoretically sound, the existing evidence is not yet convincing. We conclude by making the case that the AES proposition has such fundamental consequences for designing management actions to mitigate and adapt to climate change in the savanna-forest domain that it needs a more robust evidence base before it is used to prescribe management actions.

Increasing frequency and intensity of the most extreme wildfires on Earth.

Climate change is exacerbating wildfire conditions, but evidence is lacking for global trends in extreme fire activity itself. Here we identify energetically extreme wildfire events by calculating daily clusters of summed fire radiative power using 21 years of satellite data, revealing that the frequency of extreme events (≥99.99th percentile) increased by 2.2-fold from 2003 to 2023, with the last 7 years including the 6 most extreme. Although the total area burned on Earth may be declining, our study highlights that fire behaviour is worsening in several regions-particularly the boreal and temperate conifer biomes-with substantial implications for carbon storage and human exposure to wildfire disasters.

Post-January 6th deplatforming reduced the reach of misinformation on Twitter.

The social media platforms of the twenty-first century have an enormous role in regulating speech in the USA and worldwide1. However, there has been little research on platform-wide interventions on speech2,3. Here we evaluate the effect of the decision by Twitter to suddenly deplatform 70,000 misinformation traffickers in response to the violence at the US Capitol on 6 January 2021 (a series of events commonly known as and referred to here as 'January 6th'). Using a panel of more than 500,000 active Twitter users4,5 and natural experimental designs6,7, we evaluate the effects of this intervention on the circulation of misinformation on Twitter. We show that the intervention reduced circulation of misinformation by the deplatformed users as well as by those who followed the deplatformed users, though we cannot identify the magnitude of the causal estimates owing to the co-occurrence of the deplatforming intervention with the events surrounding January 6th. We also find that many of the misinformation traffickers who were not deplatformed left Twitter following the intervention. The results inform the historical record surrounding the insurrection, a momentous event in US history, and indicate the capacity of social media platforms to control the circulation of misinformation, and more generally to regulate public discourse.

Implications of Five Different Risk Models In Primary Prevention Guidelines.

BACKGROUND: A lack of consensus exists across guidelines as to which risk model should be used for the primary prevention of cardiovascular disease (CVD). Our objective was to determine potential improvements in the number needed to treat (NNT) and number of events prevented (NEP) using different risk models in patients eligible for risk stratification. METHODS: A retrospective observational cohort was assembled from primary care patients in Ontario, Canada between January 1st, 2010, to December 31st, 2014 and followed for up to 5 years. Risk estimation was undertaken in patients 40-75 years of age, without CVD, diabetes, or chronic kidney disease using the Framingham Risk Score (FRS), Pooled Cohort Equations (PCEs), a recalibrated FRS (R-FRS), Systematic Coronary Risk Evaluation 2 (SCORE2), and the low-risk region recalibrated SCORE2 (LR-SCORE2). RESULTS: The cohort consisted of 47,399 patients (59% women, mean age 54). The NNT with statins was lowest for SCORE2 at 40, followed by LR-SCORE2 at 41, R-FRS at 43, PCEs at 55, and FRS at 65. Models that selected for individuals with a lower NNT recommended statins to fewer, but higher risk patients. For instance, SCORE2 recommended statins to 7.9% of patients (5-year CVD incidence 5.92%). The FRS, however, recommended statins to 34.6% of patients (5-year CVD incidence 4.01%). Accordingly, the NEP was highest for the FRS at 406 and lowest for SCORE2 at 156. CONCLUSIONS: Newer models such as SCORE2 may improve statin allocation to higher risk groups with a lower NNT but prevent fewer events at the population level.

Transcatheter Aortic Valve Implantation Wait-Time Management: Derivation and Validation of the Canadian TAVI Triage Tool (CAN3T).

BACKGROUND: Transcatheter aortic valve implantation (TAVI) has seen indication expansion and thus exponential growth in demand over the past decade. In many jurisdictions, the growing demand has outpaced capacity, increasing wait times and preprocedural adverse events. In this study, we derived prediction models that estimate the risk of adverse events on the waitlist and developed a triage tool to identify patients who should be prioritized for TAVI. METHODS AND RESULTS: We included adult patients in Ontario, Canada referred for TAVI and followed up until one of the following events first occurred: death, TAVI procedure, removal from waitlist, or end of the observation period. We used subdistribution hazards models to find significant predictors for each of the following outcomes: (1) all-cause death while on the waitlist; (2) all-cause hospitalization while on the waitlist; (3) receipt of urgent TAVI; and (4) a composite outcome. The median predicted risk at 12 weeks was chosen as a threshold for a maximum acceptable risk while on the waitlist and incorporated in the triage tool to recommend individualized wait times. Of 13 128 patients, 586 died while on the waitlist, and 4343 had at least 1 hospitalization. A total of 6854 TAVIs were completed, of which 1135 were urgent procedures. We were able to create parsimonious models for each outcome that included clinically relevant predictors. CONCLUSIONS: The Canadian TAVI Triage Tool (CAN3T) is a triage tool to assist clinicians in the prioritization of patients who should have timely access to TAVI. We anticipate that the CAN3T will be a valuable tool as it may improve equity in access to care, reduce preventable adverse events, and improve system efficiency.

Understanding the perspectives and needs of multiple stakeholders: Identifying key elements of a digital health intervention to protect against environmental hazards.

AirRater is a free environmental health smartphone app developed and available in Australia that collects individual health data and disseminates environmental hazard information to populations. Following previous evaluations with app users, the aim of this study was to better understand how clinicians, government agency and non-government advocacy group representatives perceive an app designed to reduce the impacts of environmental hazards on individual and public health. Nine government agency and non-government advocacy group representatives, along with 11 clinicians based in Australia participated in a semi-structured interview or focus group to explore perspectives on AirRater. Interview and focus group data were transcribed and analysed using the qualitative data analysis software NVivo. Results indicate that for clinicians, apps like AirRater can add value as an educational, patient self-management and diagnostic tool. For government and peak bodies, apps can add value by addressing environmental health literacy and monitoring and forecasting gaps, as well as supporting advocacy efforts and public health surveillance. We conclude that environmental health smartphone apps can support a range of stakeholders to achieve shared goals and priorities related to individual and public health outcomes. Further research is needed to better understand how apps could be embedded into clinical practice and policy settings.

Pyrogeography in flux: Reorganization of Australian fire regimes in a hotter world.

Changes to the spatiotemporal patterns of wildfire are having profound implications for ecosystems and society globally, but we have limited understanding of the extent to which fire regimes will reorganize in a warming world. While predicting regime shifts remains challenging because of complex climate-vegetation-fire feedbacks, understanding the climate niches of fire regimes provides a simple way to identify locations most at risk of regime change. Using globally available satellite datasets, we constructed 14 metrics describing the spatiotemporal dimensions of fire and then delineated Australia's pyroregions-the geographic area encapsulating a broad fire regime. Cluster analysis revealed 18 pyroregions, notably including the (1) high-intensity, infrequent fires of the temperate forests, (2) high-frequency, smaller fires of the tropical savanna, and (3) low-intensity, diurnal, human-engineered fires of the agricultural zones. To inform the risk of regime shifts, we identified locations where the climate under three CMIP6 scenarios is projected to shift (i) beyond each pyroregion's historical climate niche, and (ii) into climate space that is novel to the Australian continent. Under middle-of-the-road climate projections (SSP2-4.5), an average of 65% of the extent of the pyroregions occurred beyond their historical climate niches by 2081-2100. Further, 52% of pyroregion extents, on average, were projected to occur in climate space without present-day analogues on the Australian continent, implying high risk of shifting to states that also lack present-day counterparts. Pyroregions in tropical and hot-arid climates were most at risk of shifting into both locally and continentally novel climate space because (i) their niches are narrower than southern temperate pyroregions, and (ii) their already-hot climates lead to earlier departure from present-day climate space. Such a shift implies widespread risk of regime shifts and the emergence of no-analogue fire regimes. Our approach can be applied to other regions to assess vulnerability to rapid fire regime change.

Climate Change, Landscape Fires, and Human Health: A Global Perspective.

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

An electroencephalography-based sleep index and supervised machine learning as a suitable tool for automated sleep classification in children.

STUDY OBJECTIVES: Although sleep is frequently disrupted in the pediatric intensive care unit, it is currently not possible to perform real-time sleep monitoring at the bedside. In this study, spectral band powers of electroencephalography data are used to derive a simple index for sleep classification. METHODS: Retrospective study at Erasmus MC Sophia Children's Hospital, using hospital-based polysomnography recordings obtained in non-critically ill children between 2017 and 2021. Six age categories were defined: 6-12 months, 1-3 years, 3-5 years, 5-9 years, 9-13 years, and 13-18 years. Candidate index measures were derived by calculating spectral band powers in different frequent frequency bands of smoothed electroencephalography. With the best performing index, sleep classification models were developed for two, three, and four states via decision tree and five-fold nested cross-validation. Model performance was assessed across age categories and electroencephalography channels. RESULTS: In total 90 patients with polysomnography were included, with a mean (standard deviation) recording length of 10.3 (1.1) hours. The best performance was obtained with the gamma to delta spectral power ratio of the F4-A1 and F3-A1 channels with smoothing. Balanced accuracy was 0.88, 0.74, and 0.57 for two-, three-, and four-state classification. Across age categories, balanced accuracy ranged between 0.83 and 0.92 and 0.72 and 0.77 for two- and three-state classification, respectively. CONCLUSIONS: We propose an interpretable and generalizable sleep index derived from single-channel electroencephalography for automated sleep monitoring at the bedside in non-critically ill children ages 6 months to 18 years, with good performance for two- and three-state classification. CITATION: van Twist E, Hiemstra FW, Cramer ABG, et al. An electroencephalography-based sleep index and supervised machine learning as a suitable tool for automated sleep classification in children. J Clin Sleep Med. 2024;20(3):389-397.

Validation of the European SCORE2 models in a Canadian primary care cohort.

AIMS: Systematic Coronary Risk Evaluation Model 2 (SCORE2) was recently developed to predict atherosclerotic cardiovascular disease (ASCVD) in Europe. Whether these models could be used outside of Europe is not known. The objective of this study was to test the validity of SCORE2 in a large Canadian cohort. METHODS AND RESULTS: A primary care cohort of persons with routinely collected electronic medical record data from 1 January 2010 to 31 December 2014, in Ontario, Canada, was used for validation. The SCORE2 models for younger persons (YP) were applied to 57 409 individuals aged 40-69 while the models for older persons (OPs) were applied to 9885 individuals 70-89 years of age. Five-year ASCVD predictions from both the uncalibrated and low-risk region recalibrated SCORE2 models were evaluated. The C-statistic for SCORE2-YP was 0.74 in women and 0.69 in men. The uncalibrated SCORE2-YP overestimated risk by 17% in women and underestimated by 2% in men. In contrast, the low-risk region recalibrated model demonstrated worse calibration, overestimating risk by 100% in women and 36% in men. The C-statistic for SCORE2-OP was 0.64 and 0.62 in older women and men, respectively. The uncalibrated SCORE2-OP overestimated risk by more than 100% in both sexes. The low-risk region recalibrated model demonstrated improved calibration but still overestimated risk by 60% in women and 13% in men. CONCLUSION: The performance of SCORE2 to predict ASCVD risk in Canada varied by age group and depended on whether regional calibration was applied. This underscores the necessity for validation assessment of SCORE2 prior to implementation in new jurisdictions.

In this study, new tools [Systematic Coronary Risk Evaluation Model 2 (SCORE2)] that were developed across Europe to predict heart attack and stroke risk in healthy individuals were tested independently for the first time in a Canadian setting. Key findings are as follows:The accuracy of predictions from SCORE2 in Canadians depends on the age group considered and whether uncalibrated or recalibrated equations are being used.Independent assessment of tools such as SCORE2 remains useful prior to widespread implementation in new jurisdictions.

Development and Validation of the CANHEART Population-Based Laboratory Prediction Models for Atherosclerotic Cardiovascular Disease.

BACKGROUND: Prediction of atherosclerotic cardiovascular disease (ASCVD) in primary prevention assessments exclusively with laboratory results may facilitate automated risk reporting and improve uptake of preventive therapies. OBJECTIVE: To develop and validate sex-specific prediction models for ASCVD using age and routine laboratory tests and compare their performance with that of the pooled cohort equations (PCEs). DESIGN: Derivation and validation of the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) Lab Models. SETTING: Population-based cohort study in Ontario, Canada. PARTICIPANTS: A derivation and internal validation cohort of adults aged 40 to 75 years without cardiovascular disease from April 2009 to December 2015; an external validation cohort of primary care patients from January 2010 to December 2014. MEASUREMENTS: Age and laboratory predictors measured in the outpatient setting included serum total cholesterol, high-density lipoprotein cholesterol, triglycerides, hemoglobin, mean corpuscular volume, platelets, leukocytes, estimated glomerular filtration rate, and glucose. The ASCVD outcomes were defined as myocardial infarction, stroke, and death from ischemic heart or cerebrovascular disease within 5 years. RESULTS: Sex-specific models were developed and internally validated in 2 160 497 women and 1 833 147 men. They were well calibrated, with relative differences less than 1% between mean predicted and observed risk for both sexes. The c-statistic was 0.77 in women and 0.71 in men. External validation in 31 697 primary care patients showed a relative difference less than 14% and an absolute difference less than 0.3 percentage points in mean predicted and observed risks for both sexes. The c-statistics for the laboratory models were 0.72 for both sexes and were not statistically significantly different from those for the PCEs in women (change in c-statistic, -0.01 [95% CI, -0.03 to 0.01]) or men (change in c-statistic, -0.01 [CI, -0.04 to 0.02]). LIMITATION: Medication use was not available at the population level. CONCLUSION: The CANHEART Lab Models predict ASCVD with similar accuracy to more complex models, such as the PCEs. PRIMARY FUNDING SOURCE: Canadian Institutes of Health Research.

Cost-Effectiveness Analysis of CT-Based Finite Element Modeling for Osteoporosis Screening in Secondary Fracture Prevention: An Early Health Technology Assessment in the Netherlands.

Objective. To conduct cost-utility analyses for Computed Tomography To Strength (CT2S), a novel osteoporosis screening service, compared with dual-energy X-ray absorptiometry (DXA), treat all without screening, and no screening methods for Dutch postmenopausal women referred to fracture liaison service (FLS). CT2S uses CT scans to generate femur models and simulate sideways fall scenarios for bone strength assessment. Methods. Early health technology assessment (HTA) was adopted to evaluate CT2S as a novel osteoporosis screening tool for secondary fracture prevention. We constructed a 2-dimensional simulation model considering 4 strategies (no screening, treat all without screening, DXA, CT2S) together with screening intervals (5 y, 2 y), treatments (oral alendronate, zoledronic acid), and discount rate scenarios among Dutch women in 3 age groups (60s, 70s, and 80s). Strategy comparisons were based on incremental cost-effectiveness ratios (ICERs), considering an ICER below €20,000 per QALY gained as cost-effective in the Netherlands. Results. Under the base-case scenario, CT2S versus DXA had estimated ICERs of €41,200 and €14,083 per QALY gained for the 60s and 70s age groups, respectively. For the 80s age group, CT2S was more effective and less costly than DXA. Changing treatment from weekly oral alendronate to annual zoledronic acid substantially decreased CT2S versus DXA ICERs across all age groups. Setting the screening interval to 2 y increased CT2S versus DXA ICERs to €100,333, €55,571, and €15,750 per QALY gained for the 60s, 70s, and 80s age groups, respectively. In all simulated populations and scenarios, CT2S was cost-effective (in some cases dominant) compared with the treat all strategy and cost-saving (more effective and less costly) compared with no screening. Conclusion. CT2S was estimated to be potentially cost-effective in the 70s and 80s age groups considering the willingness-to-pay threshold of the Netherlands. This early HTA suggests CT2S as a potential novel osteoporosis screening tool for secondary fracture prevention. Highlights: For postmenopausal Dutch women who have been referred to the FLS, direct access to CT2S may be cost-effective compared with DXA for age groups 70s and 80s, when considering the ICER threshold of the Netherlands. This study positions CT2S as a potential novel osteoporosis-screening tool for secondary fracture prevention in the clinical setting.A shorter screening interval of 2 y increases the effectiveness of both screening strategies, but the ICER of CT2S compared with DXA also increased substantially, which made CT2S no longer cost-effective for the 70s age group; however, it remains cost-effective for individuals in their 80s.Annual zoledronic acid treatment with better adherence may contribute to a lower cost-effectiveness ratio when comparing CT2S to DXA screening and the treat all strategies for all age groups.

Taming the flame, from local to global extreme wildfires.

Australia rethinks strategies after 2019 to 2020 bushfires.

Linking folding dynamics and function of SAM/SAH riboswitches at the single molecule level.

Riboswitches are regulatory elements found in bacterial mRNAs that control downstream gene expression through ligand-induced conformational changes. Here, we used single-molecule FRET to map the conformational landscape of the translational SAM/SAH riboswitch and probe how co-transcriptional ligand-induced conformational changes affect its translation regulation function. Riboswitch folding is highly heterogeneous, suggesting a rugged conformational landscape that allows for sampling of the ligand-bound conformation even in the absence of ligand. The addition of ligand shifts the landscape, favoring the ligand-bound conformation. Mutation studies identified a key structural element, the pseudoknot helix, that is crucial for determining ligand-free conformations and their ligand responsiveness. We also investigated ribosomal binding site accessibility under two scenarios: pre-folding and co-transcriptional folding. The regulatory function of the SAM/SAH riboswitch involves kinetically favoring ligand binding, but co-transcriptional folding reduces this preference with a less compact initial conformation that exposes the Shine-Dalgarno sequence and takes min to redistribute to more compact conformations of the pre-folded riboswitch. Such slow equilibration decreases the effective ligand affinity. Overall, our study provides a deeper understanding of the complex folding process and how the riboswitch adapts its folding pattern in response to ligand, modulates ribosome accessibility and the role of co-transcriptional folding in these processes.

Structure and ion-dependent folding of k-junctions.

k-Junctions are elaborated forms of kink turns with an additional helix on the nonbulged strand, thus forming a three-way helical junction. Two were originally identified in the structures of Arabidopsis and Escherichia coli thiamine pyrophosphate (TPP) riboswitches, and another called DUF-3268 was tentatively identified from sequence information. In this work we show that the Arabidopsis and E. coli riboswitch k-junctions fold in response to the addition of magnesium or sodium ions, and that atomic mutations that should disrupt key hydrogen bonding interactions greatly impair folding. Using X-ray crystallography, we have determined the structure of the DUF-3268 RNA and thus confirmed that it is a k-junction. It also folds upon the addition of metal ions, though requiring a 40-fold lower concentration of either divalent or monovalent ions. The key difference between the DUF-3268 and riboswitch k-junctions is the lack of nucleotides inserted between G1b and A2b in the former. We show that this insertion is primarily responsible for the difference in folding properties. Finally, we show that the DUF-3268 can functionally substitute for the k-junction in the E. coli TPP riboswitch such that the chimera can bind the TPP ligand, although less avidly.

Mechanical treatments and prescribed burning can reintroduce low-severity fire in southern Australian temperate sclerophyll forests.

The establishment of sustainable, low-intensity fire regimes is a pressing global challenge given escalating risk of wildfire driven by climate change. Globally, colonialism and industrialisation have disrupted traditional fire management, such as Indigenous patch burning and silvo-pastoral practices, leading to substantial build-up of fuel and increased fire risk. The disruption of fire regimes in southeastern Tasmania has led to dense even-aged regrowth in wet forests that are prone to crown fires, and dense Allocasuarina-dominated understoreys in dry forests that burn at high intensities. Here, we investigated the effectiveness of several fire management interventions at reducing fire risk. These interventions involved prescribed burning or mechanical understorey removal techniques. We focused on wet and dry Eucalyptus-dominated sclerophyll forests on the slopes of kunanyi/Mt. Wellington in Hobart, Tasmania, Australia. We modelled potential fire behaviour in these treated wet and dry forests using fire behaviour equations based on measurements of fuel load, vegetation structure, understorey microclimate and regional meteorological data. We found that (a) fuel treatments were effective in wet and dry forests in reducing fuel load, though each targeted different layers, (b) both mechanical treatments and prescribed burning resulted in slightly drier, and hence more fire prone understorey microclimate, and (c) all treatments reduced predicted subsequent fire severity by roughly 2-4 fold. Our results highlight the importance of reducing fuel loads, even though fuel treatments make forest microclimates drier, and hence fuel more flammable. Our finding of the effectiveness of mechanical treatments in lowering fire risk enables managers to reduce fuels without the risk of uncontrolled fires and smoke pollution that is associated with prescribed burning. Understanding the economic and ecological costs and benefits of mechanic treatment compared to prescribed burning requires further research.

Buckling Metamaterials for Extreme Vibration Damping.

Damping mechanical resonances is a formidable challenge in an increasing number of applications. Many passive damping methods rely on using low stiffness, complex mechanical structures or electrical systems, which render them unfeasible in many of these applications. Herein, a new method for passive vibration damping, by allowing buckling of the primary load path in mechanical metamaterials and lattice structures, is introduced, which sets an upper limit for vibration transmission: the transmitted acceleration saturates at a maximum value in both tension and compression, no matter what the input acceleration is. This nonlinear mechanism leads to an extreme damping coefficient tanδ ≈ 0.23 in a metal metamaterial-orders of magnitude larger than the linear damping coefficient of traditional lightweight structural materials. This principle is demonstrated experimentally and numerically in free-standing rubber and metal mechanical metamaterials over a range of accelerations. It is also shown that damping nonlinearities even allow buckling-based vibration damping to work in tension, and that bidirectional buckling can further improve its performance. Buckling metamaterials pave the way toward extreme vibration damping without mass or stiffness penalty, and, as such, could be applicable in a multitude of high-tech applications, including aerospace, vehicles, and sensitive instruments.

Biochemical and mechanistic analysis of the cleavage of branched DNA by human ANKLE1.

ANKLE1 is a nuclease that provides a final opportunity to process unresolved junctions in DNA that would otherwise create chromosomal linkages blocking cell division. It is a GIY-YIG nuclease. We have expressed an active domain of human ANKLE1 containing the GIY-YIG nuclease domain in bacteria, that is monomeric in solution and when bound to a DNA Y-junction, and unilaterally cleaves a cruciform junction. Using an AlphaFold model of the enzyme we identify the key active residues, and show that mutation of each leads to impairment of activity. There are two components in the catalytic mechanism. Cleavage rate is pH dependent, corresponding to a pKa of 6.9, suggesting an involvement of the conserved histidine in proton transfer. The reaction rate depends on the nature of the divalent cation, likely bound by glutamate and asparagine side chains, and is log-linear with the metal ion pKa. We propose that the reaction is subject to general acid-base catalysis, using a combination of tyrosine and histidine acting as general base and water directly coordinated to the metal ion as general acid. The reaction is temperature dependent; activation energy Ea = 37 kcal mol-1, suggesting that cleavage is coupled to opening of DNA in the transition state.