Human Leukocyte Antigen F Presents Peptides and Regulates Immunity through Interactions with NK Cell Receptors.

Evidence is mounting that the major histocompatibility complex (MHC) molecule HLA-F (human leukocyte antigen F) regulates the immune system in pregnancy, infection, and autoimmunity by signaling through NK cell receptors (NKRs). We present structural, biochemical, and evolutionary analyses demonstrating that HLA-F presents peptides of unconventional length dictated by a newly arisen mutation (R62W) that has produced an open-ended groove accommodating particularly long peptides. Compared to empty HLA-F open conformers (OCs), HLA-F tetramers bound with human-derived peptides differentially stained leukocytes, suggesting peptide-dependent engagement. Our in vitro studies confirm that NKRs differentiate between peptide-bound and peptide-free HLA-F. The complex structure of peptide-loaded ß2m-HLA-F bound to the inhibitory LIR1 revealed similarities to high-affinity recognition of the viral MHC-I mimic UL18 and a docking strategy that relies on contacts with HLA-F as well as ß2m, thus precluding binding to HLA-F OCs. These findings provide a biochemical framework to understand how HLA-F could regulate immunity via interactions with NKRs.

Video-based AI for beat-to-beat assessment of cardiac function.

Accurate assessment of cardiac function is crucial for the diagnosis of cardiovascular disease1, screening for cardiotoxicity2 and decisions regarding the clinical management of patients with a critical illness3. However, human assessment of cardiac function focuses on a limited sampling of cardiac cycles and has considerable inter-observer variability despite years of training4,5. Here, to overcome this challenge, we present a video-based deep learning algorithm-EchoNet-Dynamic-that surpasses the performance of human experts in the critical tasks of segmenting the left ventricle, estimating ejection fraction and assessing cardiomyopathy. Trained on echocardiogram videos, our model accurately segments the left ventricle with a Dice similarity coefficient of 0.92, predicts ejection fraction with a mean absolute error of 4.1% and reliably classifies heart failure with reduced ejection fraction (area under the curve of 0.97). In an external dataset from another healthcare system, EchoNet-Dynamic predicts the ejection fraction with a mean absolute error of 6.0% and classifies heart failure with reduced ejection fraction with an area under the curve of 0.96. Prospective evaluation with repeated human measurements confirms that the model has variance that is comparable to or less than that of human experts. By leveraging information across multiple cardiac cycles, our model can rapidly identify subtle changes in ejection fraction, is more reproducible than human evaluation and lays the foundation for precise diagnosis of cardiovascular disease in real time. As a resource to promote further innovation, we also make publicly available a large dataset of 10,030 annotated echocardiogram videos.

Assembly of a pangenome for global cattle reveals missing sequences and novel structural variations, providing new insights into their diversity and evolutionary history.

A cattle pangenome representation was created based on the genome sequences of 898 cattle representing 57 breeds. The pangenome identified 83 Mb of sequence not found in the cattle reference genome, representing 3.1% novel sequence compared with the 2.71-Gb reference. A catalog of structural variants developed from this cattle population identified 3.3 million deletions, 0.12 million inversions, and 0.18 million duplications. Estimates of breed ancestry and hybridization between cattle breeds using insertion/deletions as markers were similar to those produced by single nucleotide polymorphism-based analysis. Hundreds of deletions were observed to have stratification based on subspecies and breed. For example, an insertion of a Bov-tA1 repeat element was identified in the first intron of the APPL2 gene and correlated with cattle breed geographic distribution. This insertion falls within a segment overlapping predicted enhancer and promoter regions of the gene, and could affect important traits such as immune response, olfactory functions, cell proliferation, and glucose metabolism in muscle. The results indicate that pangenomes are a valuable resource for studying diversity and evolutionary history, and help to delineate how domestication, trait-based breeding, and adaptive introgression have shaped the cattle genome.

Reactive Carbon Capture Enables CO2 Electrolysis with Liquid Feedstocks.

ConspectusThe electrochemical reduction of carbon dioxide (CO2RR) is a promising strategy for mitigating global CO2 emissions while simultaneously yielding valuable chemicals and fuels, such as CO, HCOO-, and C2H4. This approach becomes especially appealing when integrated with surplus renewable electricity, as the ensuing production of fuels could facilitate the closure of the carbon cycle. Despite these advantages, the realization of industrial-scale electrolyzers fed with CO2 will be challenged by the substantial energy inputs required to isolate, pressurize, and purify CO2 prior to electrolysis.To address these challenges, we devised an electrolyzer capable of directly converting reactive carbon solutions (e.g., a bicarbonate-rich eluent that exits a carbon capture unit) into higher value products. This "reactive carbon electrolyzer" operates by reacting (bi)carbonate with acid generated within the electrolyzer to produce CO2 in situ, thereby facilitating CO2RR at the cathode. This approach eliminates the need for expensive CO2 recovery and compression steps, as the electrolyzer can then then coupled directly to the CO2 capture unit.This Account outlines our endeavors in developing this type of electrolyzer, focusing on the design and implementation of materials for electrocatalytic (bi)carbonate conversion. We highlight the necessity for a permeable cathode that allows the efficient transport of (bi)carbonate ions while maintaining a sufficiently high catalytic surface area. We address the importance of the supporting electrolyte, detailing how (bi)carbonate concentration, counter cations, and ionic impurities impact selectivity for products formed in the electrolyzer. We also catalog state-of-the-art performance metrics for reactive carbon electrolyzers (i.e., Faradaic efficiency, full cell voltage, CO2 utilization efficiency) and outline strategies to bridge the gap between these values and those required for commercial operation Collectively, these findings contribute to the ongoing efforts to realize industrial-scale electrochemical reactors for CO2 conversion, bringing us closer to a sustainable and closed-loop carbon cycle.

Revisiting the cold case of cold fusion.

The 1989 claim of 'cold fusion' was publicly heralded as the future of clean energy generation. However, subsequent failures to reproduce the effect heightened scepticism of this claim in the academic community, and effectively led to the disqualification of the subject from further study. Motivated by the possibility that such judgement might have been premature, we embarked on a multi-institution programme to re-evaluate cold fusion to a high standard of scientific rigour. Here we describe our efforts, which have yet to yield any evidence of such an effect. Nonetheless, a by-product of our investigations has been to provide new insights into highly hydrided metals and low-energy nuclear reactions, and we contend that there remains much interesting science to be done in this underexplored parameter space.

External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT.

OBJECTIVES: There is a need for CT pulmonary angiography (CTPA) lung segmentation models. Clinical translation requires radiological evaluation of model outputs, understanding of limitations, and identification of failure points. This multicentre study aims to develop an accurate CTPA lung segmentation model, with evaluation of outputs in two diverse patient cohorts with pulmonary hypertension (PH) and interstitial lung disease (ILD). METHODS: This retrospective study develops an nnU-Net-based segmentation model using data from two specialist centres (UK and USA). Model was trained (n = 37), tested (n = 12), and clinically evaluated (n = 176) on a diverse 'real-world' cohort of 225 PH patients with volumetric CTPAs. Dice score coefficient (DSC) and normalised surface distance (NSD) were used for testing. Clinical evaluation of outputs was performed by two radiologists who assessed clinical significance of errors. External validation was performed on heterogenous contrast and non-contrast scans from 28 ILD patients. RESULTS: A total of 225 PH and 28 ILD patients with diverse demographic and clinical characteristics were evaluated. Mean accuracy, DSC, and NSD scores were 0.998 (95% CI 0.9976, 0.9989), 0.990 (0.9840, 0.9962), and 0.983 (0.9686, 0.9972) respectively. There were no segmentation failures. On radiological review, 82% and 71% of internal and external cases respectively had no errors. Eighteen percent and 25% respectively had clinically insignificant errors. Peripheral atelectasis and consolidation were common causes for suboptimal segmentation. One external case (0.5%) with patulous oesophagus had a clinically significant error. CONCLUSION: State-of-the-art CTPA lung segmentation model provides accurate outputs with minimal clinical errors on evaluation across two diverse cohorts with PH and ILD. CLINICAL RELEVANCE: Clinical translation of artificial intelligence models requires radiological review and understanding of model limitations. This study develops an externally validated state-of-the-art model with robust radiological review. Intended clinical use is in techniques such as lung volume or parenchymal disease quantification. KEY POINTS: • Accurate, externally validated CT pulmonary angiography (CTPA) lung segmentation model tested in two large heterogeneous clinical cohorts (pulmonary hypertension and interstitial lung disease). • No segmentation failures and robust review of model outputs by radiologists found 1 (0.5%) clinically significant segmentation error. • Intended clinical use of this model is a necessary step in techniques such as lung volume, parenchymal disease quantification, or pulmonary vessel analysis.

Large-Sample Genome-Wide Association Study of Resistance to Retained Placenta in U.S. Holstein Cows.

A genome-wide association study of resistance to retained placenta (RETP) using 632,212 Holstein cows and 74,747 SNPs identified 200 additive effects with p-values < 10-8 on thirteen chromosomes but no dominance effect was statistically significant. The regions of 87.61-88.74 Mb of Chr09 about 1.13 Mb in size had the most significant effect in LOC112448080 and other highly significant effects in CCDC170 and ESR1, and in or near RMND1 and AKAP12. Four non-ESR1 genes in this region were reported to be involved in ESR1 fusions in humans. Chr23 had the largest number of significant effects that peaked in SLC17A1, which was involved in urate metabolism and transport that could contribute to kidney disease. The PKHD1 gene contained seven significant effects and was downstream of another six significant effects. The ACOT13 gene also had a highly significant effect. Both PKHD1 and ACOT13 were associated with kidney disease. Another highly significant effect was upstream of BOLA-DQA2. The KITLG gene of Chr05 that acts in utero in germ cell and neural cell development, and hematopoiesis was upstream of a highly significant effect, contained a significant effect, and was between another two significant effects. The results of this study provided a new understanding of genetic factors underlying RETP in U.S. Holstein cows.

A Million-Cow Validation of a Chromosome 14 Region Interacting with All Chromosomes for Fat Percentage in U.S. Holstein Cows.

A genome-wide association study (GWAS) of fat percentage (FPC) using 1,231,898 first lactation cows and 75,198 SNPs confirmed a previous result that a Chr14 region about 9.38 Mb in size (0.14-9.52 Mb) had significant inter-chromosome additive × additive (A×A) effects with all chromosomes and revealed many new such effects. This study divides this 9.38 Mb region into two sub-regions, Chr14a at 0.14-0.88 Mb (0.74 Mb in size) with 78% and Chr14b at 2.21-9.52 Mb (7.31 Mb in size) with 22% of the 2761 significant A×A effects. These two sub-regions were separated by a 1.3 Mb gap at 0.9-2.2 Mb without significant inter-chromosome A×A effects. The PPP1R16A-FOXH1-CYHR1-TONSL (PFCT) region of Chr14a (29 Kb in size) with four SNPs had the largest number of inter-chromosome A×A effects (1141 pairs) with all chromosomes, including the most significant inter-chromosome A×A effects. The SLC4A4-GC-NPFFR2 (SGN) region of Chr06, known to have highly significant additive effects for some production, fertility and health traits, specifically interacted with the PFCT region and a Chr14a region with CPSF1, ADCK5, SLC52A2, DGAT1, SMPD5 and PARP10 (CASDSP) known to have highly significant additive effects for milk production traits. The most significant effects were between an SNP in SGN and four SNPs in PFCT. The CASDSP region mostly interacted with the SGN region. In the Chr14b region, the 2.28-2.42 Mb region (138.46 Kb in size) lacking coding genes had the largest cluster of A×A effects, interacting with seventeen chromosomes. The results from this study provide high-confidence evidence towards the understanding of the genetic mechanism of FPC in Holstein cows.

Participatory investigation of goat farmers' breeding practices, trait preference, and selection criteria in Burkina Faso.

The community-based breeding program (CBBP) is an innovative approach recommended for genetic improvement and sustainable use of animal genetic resources in extensive farming systems. Successful implementation of this approach requires an understanding of the characteristics of production systems, breeding objectives, and farmers' trait preference. This study aimed to identify the selection criteria of goat farmers in rural areas of Burkina Faso and their potential implications in establishing CBBP. Following focus group discussions, a well-structured questionnaire was designed and administered to 372 randomly selected goat farmers in two different agro-ecological zones. A list of traits obtained during focus group discussions was provided to farmers individually, and they were asked to rank the ones they preferentially use to select breeding animals. Statistical tests were conducted to compare data between the two agro-ecological zones. The results showed that the average goat flock per household was higher (P < 0.05) in the Sudanian (15.68 ± 13.76), compared to the Sudano-Sahelian area (12.93 ± 13.3). Adult females were the dominant age-sex group in both areas. Reasons for culling, keeping breeding bucks, and castration practice were significantly different (P < 0.05) among agro-ecological zones. The most important common criterion for selection in the two zones was body size, coat color, and growth rate for the bucks and does, while fertility (0.06) parameters including twining ability (0.18), kidding frequency (0.11), and mothering ability (0.15) were furthermore considered for breeding does selection. These findings provide valuable insights for developing CBBPs tailored to goat production in the study areas.

Oxygen-Resistant CO2 Reduction Enabled by Electrolysis of Liquid Feedstocks.

Electrolytic CO2 reduction fails in the presence of O2. This failure occurs because the reduction of O2 is thermodynamically favored over the reduction of CO2. Consequently, O2 must be removed from the CO2 feed prior to entering an electrolyzer, which is expensive. Here, we show that the use of liquid bicarbonate feedstocks (e.g., aqueous 3.0 M KHCO3), rather than gaseous CO2 feedstocks, enables efficient and selective CO2 reduction without additional procedures for removing O2. This effect is made possible because liquid bicarbonate solutions, which serve as a liquid CO2 carrier, deliver high concentrations of captured CO2 to the cathode, while the low solubility of O2 in aqueous media maintains a low O2 concentration at the same cathode surface. Consequently, electrolyzers fed with liquid bicarbonate feedstocks create an environment at the cathode that favors the reduction of CO2 over O2. We validate this claim by electrochemically converting CO2 into CO with reaction selectivities of 65% at 100 mA cm-2 using a 3.0 M KHCO3 solution bubbled with 100% CO2 or 100% O2. Similar experiments performed with a gaseous CO2 feedstock showed that merely 0.5% of O2 in the feedstock reduced CO selectivity by >90% after 1 h of electrolysis. Our findings demonstrate that a liquid bicarbonate feedstock enables efficient CO2 reduction without the need for expensive O2 removal steps.

Endergonic Hydrogenation at Ambient Conditions Using an Electrochemical Membrane Reactor.

Here, we determine how the hydrogen loading (x) of an electrochemical palladium membrane reactor (ePMR) varies with electrochemical conditions (e.g., applied current density, electrolyte concentration). We detail how x influences the thermodynamic driving force of an ePMR. These studies are accomplished by measuring the fugacity (P) of hydrogen desorbing from the palladium-hydrogen membrane and subsequently relating P to pressure-composition isotherms to determine x. We find that x increases with both applied current density and electrolyte concentration, but plateaus at a loading of x ≅ 0.92 in 1.0 M H2SO4 at -200 mA·cm-2. The validity of the fugacity measurements is supported experimentally and computationally by: (a) electrochemical hydrogen permeation studies; and (b) a palladium-hydrogen porous flow finite element analysis (FEA) model. Both (a) and (b) agree with the fugacity measurements on the following x-dependent properties of the palladium-hydrogen system during electrolysis: (i) the onset for spontaneous hydrogen desorption; (ii) the point of steady-state hydrogen loading; and (iii) the function describing hydrogen desorption between (i) and (ii). We proceed to detail how x defines the free energy of palladium-hydrogen alloy formation (ΔG(x)PdH), which is a descriptor for the thermodynamic driving force of hydrogenation at the PdHx surface of an ePMR. A maximum value ΔGPdH of 11 kJ·mol-1 is observed, suggesting that an ePMR is capable of driving endergonic hydrogenation reactions. We empirically demonstrate this capability by reducing carbon dioxide to formate (ΔGCO2/HCO2H = 3.4 kJ·mol-1) at ambient conditions and neutral pH.

Catalyst Aggregation Matters for Immobilized Molecular CO2RR Electrocatalysts.

Here, we detail how the catalytic behavior of immobilized molecular electrocatalysts for the CO2 reduction reaction (CO2RR) can be impacted by catalyst aggregation. Operando Raman spectroscopy was used to study the CO2RR mediated by a layer of cobalt phthalocyanine (CoPc) immobilized on the cathode of an electrochemical flow reactor. We demonstrate that during electrolysis, the oxidation state of CoPc in the catalyst layer is dependent upon the degree of catalyst aggregation. Our data indicate that immobilized molecular catalysts must be dispersed on conductive supports to mitigate the formation of aggregates and produce meaningful performance data. We leveraged insights from this mechanistic study to engineer an improved CO-forming immobilized molecular catalyst─cobalt octaethoxyphthalocyanine (EtO8-CoPc)─that exhibited high selectivity (FECO ≥ 95%), high partial current density (JCO ≥ 300 mA/cm2), and high durability (ΔFECO < 0.1%/h at 150 mA/cm2) in a flow cell. This work demonstrates how to accurately identify CO2RR active species of molecular catalysts using operando Raman spectroscopy and how to use this information to implement improved molecular electrocatalysts into flow cells. This work also shows that the active site of CoPc during CO2RR catalysis in a flow cell is the metal center.

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle.

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

Estimating test-day milk yields by modeling proportional daily yields: Going beyond linearity.

In the United States, lactation milk yields are not measured directly but are calculated from the test-day milk yields. Still, test-day milk yields are estimated from partial yields obtained from single milkings. Various methods have been proposed to estimate test-day milk yields, primarily to deal with unequal milking intervals dating back to the 1970s and 1980s. The Wiggans model is a de facto method for estimating test-day milk yields in the United States, which was initially proposed for cows milked 3 times daily, assuming a linear relationship between a proportional test-day milk yield and milking interval. However, the linearity assumption did not hold precisely in Holstein cows milked twice daily because of prolonged and uneven milking intervals. The present study reviewed and evaluated the nonlinear models that extended the Wiggans model for estimating daily or test-day milk yields. These nonlinear models, except step functions, demonstrated smaller errors and greater accuracies for estimated test-day milk yields compared with the conventional methods. The nonlinear models offered additional benefits. For example, the locally weighted regression model (e.g., locally estimated scatterplot smoothing) could utilize data information in scalable neighborhoods and weigh observations according to their distance in milking interval time. General additive models provide a flexible, unified framework to model nonlinear predictor variables additively. Another drawback of the conventional methods is a loss of accuracy caused by discretizing milking interval time into large bins while deriving multiplicative correction factors for estimating test-day milk yields. To overcome this problem, we proposed a general approach that allows milk yield correction factors to be derived for every possible milking interval time, resulting in more accurately estimated test-day milk yields. This approach can be applied to any model, including nonparametric models.

Invited review: Reliability computation from the animal model era to the single-step genomic model era.

The calculation of exact reliabilities involving the inversion of mixed model equations poses a heavy computational challenge when the system of equations is large. This has prompted the development of different approximation methods. We give an overview of the various methods and computational approaches in calculating reliability from the era before the animal model to the era of single-step genomic models. The different methods are discussed in terms of modeling, development, and applicability in large dairy cattle populations. The paper also describes the problems faced in reliability computation. Many details dispersed throughout the literature are presented in this paper. It is clear that a universal solution applicable to every model and input data may not be possible, but we point out several efficient and accurate algorithms developed recently for a variety of very large genomic evaluations.

Improved Fine-Tuning of In-Domain Transformer Model for Inferring COVID-19 Presence in Multi-Institutional Radiology Reports.

Building a document-level classifier for COVID-19 on radiology reports could help assist providers in their daily clinical routine, as well as create large numbers of labels for computer vision models. We have developed such a classifier by fine-tuning a BERT-like model initialized from RadBERT, its continuous pre-training on radiology reports that can be used on all radiology-related tasks. RadBERT outperforms all biomedical pre-trainings on this COVID-19 task (P<0.01) and helps our fine-tuned model achieve an 88.9 macro-averaged F1-score, when evaluated on both X-ray and CT reports. To build this model, we rely on a multi-institutional dataset re-sampled and enriched with concurrent lung diseases, helping the model to resist to distribution shifts. In addition, we explore a variety of fine-tuning and hyperparameter optimization techniques that accelerate fine-tuning convergence, stabilize performance, and improve accuracy, especially when data or computational resources are limited. Finally, we provide a set of visualization tools and explainability methods to better understand the performance of the model, and support its practical use in the clinical setting. Our approach offers a ready-to-use COVID-19 classifier and can be applied similarly to other radiology report classification tasks.

Towards the detection of copy number variation from single sperm sequencing in cattle.

BACKGROUND: Copy number variation (CNV) has been routinely studied using bulk-cell sequencing. However, CNV is not well studied on the single-cell level except for humans and a few model organisms. RESULTS: We sequenced 143 single sperms of two Holstein bulls, from which we predicted CNV events using 14 single sperms with deep sequencing. We then compared the CNV results derived from single sperms with the bulk-cell sequencing of one bull's family trio of diploid genomes. As a known CNV hotspot, segmental duplications were also predicted using the bovine ARS-UCD1.2 genome. Although the trio CNVs validated only some single sperm CNVs, they still showed a distal chromosomal distribution pattern and significant associations with segmental duplications and satellite repeats. CONCLUSION: Our preliminary results pointed out future research directions and highlighted the importance of uniform whole genome amplification, deep sequence coverage, and dedicated software pipelines for CNV detection using single cell sequencing data.

Genome-wide recombination map construction from single sperm sequencing in cattle.

BACKGROUND: Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, except for human and a few model organisms, it is not well studied in livestock, including cattle. RESULTS: To investigate their distributions in the cattle sperm genome, we sequenced 143 single sperms from two Holstein bulls. We mapped meiotic recombination events at high resolution based on phased heterozygous single nucleotide polymorphism (SNP). In the absence of evolutionary selection pressure in fertilization and survival, recombination events in sperm are enriched near distal chromosomal ends, revealing that such a pattern is intrinsic to the molecular mechanism of meiosis. Furthermore, we further validated these findings in single sperms with results derived from sequencing its family trio of diploid genomes and our previous studies of recombination in cattle. CONCLUSIONS: To our knowledge, this is the first large-scale single sperm whole-genome sequencing effort in livestock, which provided useful information for future studies of recombination, genome instability, and male infertility.

Direct H2O2 Synthesis, without H2 Gas.

We report here the direct hydrogenation of O2 gas to form hydrogen peroxide (H2O2) using a membrane reactor without H2 gas. Hydrogen is sourced from water, and the reactor is driven by electricity. Hydrogenation chemistry is achieved using a hydrogen-permeable Pd foil that separates an electrolysis chamber that generates reactive H atoms, from a hydrogenation chamber where H atoms react with O2 to form H2O2. Our results show that the concentration of H2O2 can be increased ∼8 times (from 56.5 to 443 mg/L) by optimizing the ratio of methanol-to-water in the chemical chamber, and through catalyst design. We demonstrate that the concentration of H2O2 is acutely sensitive to the H2O2 decomposition rate. This decomposition rate can be minimized by using AuPd alloy catalysts instead of pure Pd. This study presents a new pathway to directly synthesize H2O2 using water electrolysis without ever using H2 gas.

Quantification of the Effect of an External Magnetic Field on Water Oxidation with Cobalt Oxide Anodes.

Here, we quantify the effect of an external magnetic field (ß) on the oxygen evolution reaction (OER) for a cobalt oxide|fluorine-doped tin oxide coated glass (CoOx|FTO) anode. A bespoke apparatus enables us to precisely determine the relationship between magnetic flux density (ß) and OER activity at the surface of a CoOx|FTO anode. The apparatus includes a strong NdFeB magnet (ßmax = 450 ± 1 mT) capable of producing a magnetic field of 371 ± 1 mT at the surface of the anode. The distance between the magnet and the anode surface is controlled by a linear actuator, enabling submillimeter distance positioning of the magnet relative to the anode surface. We couple this apparatus with a finite element analysis magnetic model that was validated by Hall probe measurements to determine the value of ß at the anode surface. At the largest tested magnetic field strength of ß = 371 ± 1 mT, a 4.7% increase in current at 1.5 V vs the normal hydrogen electrode (NHE) and a change in the Tafel slope of 14.5 mV/dec were observed. We demonstrate through a series of OER measurements at sequential values of ß that the enhancement consists of two distinct regions. The possible use of this effect to improve the energy efficiency of commercial water electrolyzers is discussed, and major challenges pertaining to the accurate measurement of the phenomenon are demonstrated.