Functionally distinct roles for TET-oxidized 5-methylcytosine bases in somatic reprogramming to pluripotency.

Active DNA demethylation via ten-eleven translocation (TET) family enzymes is essential for epigenetic reprogramming in cell state transitions. TET enzymes catalyze up to three successive oxidations of 5-methylcytosine (5mC), generating 5-hydroxymethylcytosine (5hmC), 5-formylcytosine (5fC), or 5-carboxycytosine (5caC). Although these bases are known to contribute to distinct demethylation pathways, the lack of tools to uncouple these sequential oxidative events has constrained our mechanistic understanding of the role of TETs in chromatin reprogramming. Here, we describe the first application of biochemically engineered TET mutants that unlink 5mC oxidation steps, examining their effects on somatic cell reprogramming. We show that only TET enzymes proficient for oxidation to 5fC/5caC can rescue the reprogramming potential of Tet2-deficient mouse embryonic fibroblasts. This effect correlated with rapid DNA demethylation at reprogramming enhancers and increased chromatin accessibility later in reprogramming. These experiments demonstrate that DNA demethylation through 5fC/5caC has roles distinct from 5hmC in somatic reprogramming to pluripotency.

Streptolysin S is required for Streptococcus pyogenes nasopharyngeal and skin infection in HLA-transgenic mice.

Streptococcus pyogenes is a human-specific pathogen that commonly colonizes the upper respiratory tract and skin, causing a wide variety of diseases ranging from pharyngitis to necrotizing fasciitis and toxic shock syndrome. S. pyogenes has a repertoire of secreted virulence factors that promote infection and evasion of the host immune system including the cytolysins streptolysin O (SLO) and streptolysin S (SLS). S. pyogenes does not naturally infect the upper respiratory tract of mice although mice transgenic for MHC class II human leukocyte antigens (HLA) become highly susceptible. Here we used HLA-transgenic mice to assess the role of both SLO and SLS during both nasopharyngeal and skin infection. Using S. pyogenes MGAS8232 as a model strain, we found that an SLS-deficient strain exhibited a 100-fold reduction in bacterial recovery from the nasopharynx and a 10-fold reduction in bacterial burden in the skin, whereas an SLO-deficient strain did not exhibit any infection defects in these models. Furthermore, depletion of neutrophils significantly restored the bacterial burden of the SLS-deficient bacteria in skin, but not in the nasopharynx. In mice nasally infected with the wildtype S. pyogenes, there was a marked change in localization of the tight junction protein ZO-1 at the site of infection, demonstrating damage to the nasal epithelia that was absent in mice infected with the SLS-deficient strain. Overall, we conclude that SLS is required for the establishment of nasopharyngeal infection and skin infection in HLA-transgenic mice by S. pyogenes MGAS8232 and provide evidence that SLS contributes to nasopharyngeal infection through the localized destruction of nasal epithelia.

Responses to Pattern-Violating Visual Stimuli Evolve Differently Over Days in Somata and Distal Apical Dendrites.

Scientists have long conjectured that the neocortex learns patterns in sensory data to generate top-down predictions of upcoming stimuli. In line with this conjecture, different responses to pattern-matching vs pattern-violating visual stimuli have been observed in both spiking and somatic calcium imaging data. However, it remains unknown whether these pattern-violation signals are different between the distal apical dendrites, which are heavily targeted by top-down signals, and the somata, where bottom-up information is primarily integrated. Furthermore, it is unknown how responses to pattern-violating stimuli evolve over time as an animal gains more experience with them. Here, we address these unanswered questions by analyzing responses of individual somata and dendritic branches of layer 2/3 and layer 5 pyramidal neurons tracked over multiple days in primary visual cortex of awake, behaving female and male mice. We use sequences of Gabor patches with patterns in their orientations to create pattern-matching and pattern-violating stimuli, and two-photon calcium imaging to record neuronal responses. Many neurons in both layers show large differences between their responses to pattern-matching and pattern-violating stimuli. Interestingly, these responses evolve in opposite directions in the somata and distal apical dendrites, with somata becoming less sensitive to pattern-violating stimuli and distal apical dendrites more sensitive. These differences between the somata and distal apical dendrites may be important for hierarchical computation of sensory predictions and learning, since these two compartments tend to receive bottom-up and top-down information, respectively.

Adult neurogenesis acts as a neural regularizer.

New neurons are continuously generated in the subgranular zone of the dentate gyrus throughout adulthood. These new neurons gradually integrate into hippocampal circuits, forming new naive synapses. Viewed from this perspective, these new neurons may represent a significant source of "wiring" noise in hippocampal networks. In machine learning, such noise injection is commonly used as a regularization technique. Regularization techniques help prevent overfitting training data and allow models to generalize learning to new, unseen data. Using a computational modeling approach, here we ask whether a neurogenesis-like process similarly acts as a regularizer, facilitating generalization in a category learning task. In a convolutional neural network (CNN) trained on the CIFAR-10 object recognition dataset, we modeled neurogenesis as a replacement/turnover mechanism, where weights for a randomly chosen small subset of hidden layer neurons were reinitialized to new values as the model learned to categorize 10 different classes of objects. We found that neurogenesis enhanced generalization on unseen test data compared to networks with no neurogenesis. Moreover, neurogenic networks either outperformed or performed similarly to networks with conventional noise injection (i.e., dropout, weight decay, and neural noise). These results suggest that neurogenesis can enhance generalization in hippocampal learning through noise injection, expanding on the roles that neurogenesis may have in cognition.

Comparing in planta accumulation with microbial routes to set targets for a cost-competitive bioeconomy.

Plants and microbes share common metabolic pathways for producing a range of bioproducts that are potentially foundational to the future bioeconomy. However, in planta accumulation and microbial production of bioproducts have never been systematically compared on an economic basis to identify optimal routes of production. A detailed technoeconomic analysis of four exemplar compounds (4-hydroxybenzoic acid [4-HBA], catechol, muconic acid, and 2-pyrone-4,6-dicarboxylic acid [PDC]) is conducted with the highest reported yields and accumulation rates to identify economically advantaged platforms and breakeven targets for plants and microbes. The results indicate that in planta mass accumulation ranging from 0.1 to 0.3 dry weight % (dwt%) can achieve costs comparable to microbial routes operating at 40 to 55% of maximum theoretical yields. These yields and accumulation rates are sufficient to be cost competitive if the products are sold at market prices consistent with specialty chemicals ($20 to $50/kg). Prices consistent with commodity chemicals will require an order-of-magnitude-greater accumulation rate for plants and/or yields nearing theoretical maxima for microbial production platforms. This comparative analysis revealed that the demonstrated accumulation rates of 4-HBA (3.2 dwt%) and PDC (3.0 dwt%) in engineered plants vastly outperform microbial routes, even if microbial platforms were to reach theoretical maximum yields. Their recovery and sale as part of a lignocellulosic biorefinery could enable biofuel prices to be competitive with petroleum. Muconic acid and catechol, in contrast, are currently more attractive when produced microbially using a sugar feedstock. Ultimately, both platforms can play an important role in replacing fossil-derived products.

Glioblastoma Margin as a Diffusion Barrier Revealed by Photoactivation of Plasmonic Nanovesicles.

Glioblastoma (GBM) is the most complex and lethal primary brain cancer. Adequate drug diffusion and penetration are essential for treating GBM, but how the spatial heterogeneity in GBM impacts drug diffusion and transport is poorly understood. Herein, we report a new method, photoactivation of plasmonic nanovesicles (PANO), to measure molecular diffusion in the extracellular space of GBM. By examining three genetically engineered GBM mouse models that recapitulate key clinical features including the angiogenic core and diffuse infiltration, we found that the tumor margin has the lowest diffusion coefficient (highest tortuosity) compared with the tumor core and surrounding brain tissue. Analysis of the cellular composition shows that tortuosity in the GBM is strongly correlated with neuronal loss and astrocyte activation. Our all-optical measurement reveals the heterogeneous GBM microenvironment and highlights the tumor margin as a diffusion barrier for drug transport in the brain, with implications for therapeutic delivery.

Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.

INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence-enabled tool to guide lactulose use through a smartphone application. METHODS: Subjects with hepatic encephalopathy on lactulose captured bowel movement pictures during lead-in and intervention phases. During the intervention phase, daily feedback on lactulose titration was delivered through the application. Goals were determined according to number of bowel movement and Bristol Stool Scale reports. RESULTS: Subjects completed the study with more than 80% satisfaction. In the lead-in phase, less compliant subjects achieved Bristol Stool Scale goal on 62/111 (56%) of days compared with 107/136 (79%) in the intervention phase ( P = 0.041), while the most compliant subjects showed no difference. Severe/recurrent hepatic encephalopathy group achieved Bristol Stool Scale goal on 80/104 (77%) days in the lead-in phase and 90/110 (82%) days in the intervention phase ( P = NS), compared with 89/143 (62%) days and 86/127 (68%) days in the stable group. DISCUSSION: Dieta application is a promising tool for objective Bowel Movement/Bristol Stool Scale tracking for hepatic encephalopathy and may potentially be used to assist with lactulose titration.

The Streptococcus pyogenes hyaluronic acid capsule promotes experimental nasal and skin infection by preventing neutrophil-mediated clearance.

Streptococcus pyogenes is a globally prominent human-specific pathogen responsible for an enormous burden of human illnesses, including >600 million pharyngeal and >100 million skin infections each year. Despite intensive efforts that focus on invasive indications, much remains unknown about this bacterium in its natural state during colonization of the nasopharynx and skin. Using acute experimental infection models in HLA-transgenic mice, we evaluated how the hyaluronic acid (HA) capsule contributes to S. pyogenes MGAS8232 infection within these limited biological niches. Herein, we demonstrate that HA capsule expression promotes bacterial burden in murine nasal turbinates and skin lesions by resisting neutrophil-mediated killing. HA capsule production is encoded by the hasABC operon and compared to wildtype S. pyogenes infections, mice infected with a ΔhasA mutant exhibited over a 1000-fold CFU reduction at 48-hours post-nasal challenge, and a 10,000-fold CFU reduction from skin lesions 72-hours post-skin challenge. HA capsule expression contributed substantially to skin lesion size development following subdermal inoculations. In the absence of capsule expression, S. pyogenes revealed drastically impeded growth in whole human blood and increased susceptibility to killing by isolated neutrophils ex vivo, highlighting its important role in resisting phagocytosis. Furthermore, we establish that neutrophil depletion in mice recovered the reduced burden by the ΔhasA mutant in both the nasopharynx and skin. Together, this work confirms that the HA capsule is a key virulence determinant during acute infections by S. pyogenes and demonstrates that its predominant function is to protect S. pyogenes against neutrophil-mediated killing.

Systematic engineering for production of anti-aging sunscreen compound in Pseudomonas putida.

Sunscreen has been used for thousands of years to protect skin from ultraviolet radiation. However, the use of modern commercial sunscreen containing oxybenzone, ZnO, and TiO2 has raised concerns due to their negative effects on human health and the environment. In this study, we aim to establish an efficient microbial platform for production of shinorine, a UV light absorbing compound with anti-aging properties. First, we methodically selected an appropriate host for shinorine production by analyzing central carbon flux distribution data from prior studies alongside predictions from genome-scale metabolic models (GEMs). We enhanced shinorine productivity through CRISPRi-mediated downregulation and utilized shotgun proteomics to pinpoint potential competing pathways. Simultaneously, we improved the shinorine biosynthetic pathway by refining its design, optimizing promoter usage, and altering the strength of ribosome binding sites. Finally, we conducted amino acid feeding experiments under various conditions to identify the key limiting factors in shinorine production. The study combines meta-analysis of 13C-metabolic flux analysis, GEMs, synthetic biology, CRISPRi-mediated gene downregulation, and omics analysis to improve shinorine production, demonstrating the potential of Pseudomonas putida KT2440 as platform for shinorine production.

Genome-scale and pathway engineering for the sustainable aviation fuel precursor isoprenol production in Pseudomonas putida.

Sustainable aviation fuel (SAF) will significantly impact global warming in the aviation sector, and important SAF targets are emerging. Isoprenol is a precursor for a promising SAF compound DMCO (1,4-dimethylcyclooctane) and has been produced in several engineered microorganisms. Recently, Pseudomonas putida has gained interest as a future host for isoprenol bioproduction as it can utilize carbon sources from inexpensive plant biomass. Here, we engineer metabolically versatile host P. putida for isoprenol production. We employ two computational modeling approaches (Bilevel optimization and Constrained Minimal Cut Sets) to predict gene knockout targets and optimize the "IPP-bypass" pathway in P. putida to maximize isoprenol production. Altogether, the highest isoprenol production titer from P. putida was achieved at 3.5 g/L under fed-batch conditions. This combination of computational modeling and strain engineering on P. putida for an advanced biofuels production has vital significance in enabling a bioproduction process that can use renewable carbon streams.

Normative Magnetic Resonance Imaging Data Increase the Sensitivity to Brain Volume Abnormalities in the Classification of Fetal Alcohol Spectrum Disorder.

OBJECTIVE: To evaluate the use of a large magnetic resonance imaging (MRI) normative dataset to quantify structural brain anomalies that may improve diagnostic sensitivity for atypical brain volume in youth with fetal alcohol spectrum disorder (FASD). STUDY DESIGN: Participants included 48 children with prenatal alcohol exposure (PAE) and 43 controls, ages 8-17 years, from the longitudinal Collaborative Initiative on FASD s. Recently published lifespan brain charts were used to quantify participants' (per)centile for brain volumes (cortical and subcortical gray matter and cortical white matter), providing an index of (dis)similarity to typically developing individuals of the same age and sex. RESULTS: Participants with PAE demonstrated lower mean centile scores compared with controls. Participants with PAE and scores ≤ 10th centile on at least 1 brain volume metric demonstrated significantly lower performance on measures of intellectual function and aspects of executive functioning compared with participants with PAE and "typical" volumes (>10th centile). Brain volume centiles explained a greater amount of variance in IQ and improved sensitivity to brain volume anomalies in FASD compared with the most commonly used diagnostic criterion of occipitofrontal circumference (OFC) ≤ 10th. CONCLUSION: Age- and sex-adjusted brain volumes based on a large normative dataset may be useful predictors of functional outcomes and may identify a greater number of individuals with FASD than the currently used criterion of OFC.

Adoption of an Enhanced Recovery After Surgery Protocol Increases Cost of Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy and Does not Improve Outcomes.

BACKGROUND: Enhanced recovery after surgery (ERAS) protocols have been shown to reduce length of stay (LOS) and complications. The impact of ERAS protocols on the cost of cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) has not been studied. PATIENTS AND METHODS: We performed a retrospective cohort analysis of patients undergoing CRS-HIPEC from 2016-2022 at a single quaternary center. Propensity score matching was used to create pre-and post-ERAS cohorts. Cost, overall and serious complications, and intensive care unit (ICU) length of stay (LOS) between the two cohorts were compared using the Mann-Whitney U-test for continuous variables and χ2 test for categorical variables. RESULTS: Our final matched cohort consisted of 100 patients, with 50 patients in both the pre- and post-ERAS groups. After adjusting for patient complexity and inflation, the median total cost [$75,932 ($67,166-102,645) versus $92,992 ($80,720-116,710), p = 0.02] and operating room cost [$26,817 ($23,378-33,121) versus $34,434 ($28,085-$41,379), p < 0.001] were significantly higher in the post-ERAS cohort. Overall morbidity (n = 22, 44% versus n = 17, 34%, p = 0.40) and ICU length of stay [2 days (IQR 1-3) versus 2 days (IQR 1-4), p = 0.70] were similar between the two cohorts. A total cost increase of $22,393 [SE $13,047, 95% CI (-$3178 to $47,965), p = 0.086] was estimated after implementation of ERAS, with operating room cost significantly contributing to this increase [$8419, SE $1628, 95% CI ($5228-11,609), p < 0.001]. CONCLUSIONS: CRS-HIPEC ERAS protocols were associated with higher total costs due to increased operating room costs at a single institution. There was no significant difference in ICU LOS and complications after the implementation of the ERAS protocol.

Making Sense of Psychedelics in the CNS.

For centuries, ancient lineages have consumed psychedelic compounds from natural sources. In the modern era, scientists have since harnessed the power of computational tools, cellular assays, and behavioral metrics to study how these compounds instigate changes on molecular, cellular, circuit-wide, and system levels. Here, we provide a brief history of psychedelics and their use in science, medicine, and culture. We then outline current techniques for studying psychedelics from a pharmacological perspective. Finally, we address known gaps in the field and potential avenues of further research to broaden our collective understanding of physiological changes induced by psychedelics, the limits of their therapeutic capabilities, and how researchers can improve and inform treatments that are rapidly becoming accessible worldwide.

Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector.

We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{µ4}|^{2} in the mass ranges 10≤m_{HNL}≤150 MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245 MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35

First Search for Dark-Trident Processes Using the MicroBooNE Detector.

We present a first search for dark-trident scattering in a neutrino beam using a dataset corresponding to 7.2×10^{20} protons on target taken with the MicroBooNE detector at Fermilab. Proton interactions in the neutrino target at the main injector produce π^{0} and η mesons, which could decay into dark-matter (DM) particles mediated via a dark photon A^{'}. A convolutional neural network is trained to identify interactions of the DM particles in the liquid-argon time projection chamber (LArTPC) exploiting its imagelike reconstruction capability. In the absence of a DM signal, we provide limits at the 90% confidence level on the squared kinematic mixing parameter ϵ^{2} as a function of the dark-photon mass in the range 10≤M_{A^{'}}≤400 MeV. The limits cover previously unconstrained parameter space for the production of fermion or scalar DM particles χ for two benchmark models with mass ratios M_{χ}/M_{A^{'}}=0.6 and 2 and for dark fine-structure constants 0.1≤α_{D}≤1.

First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE.

We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41} cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.

Extreme ultraviolet time-resolved photoelectron spectroscopy of adenine, adenosine and adenosine monophosphate in a liquid flat jet.

Time-resolved photoelectron spectroscopy using an extreme-ultraviolet (XUV) probe pulse was used to investigate the UV photoinduced dynamics of adenine (Ade), adenosine (Ado), and adenosine-5-monophosphate (AMP) in a liquid water jet. In contrast to previous studies using UV probe pulses, the XUV pulse at 21.7 eV can photoionize all excited states of a molecule, allowing for full relaxation pathways to be addressed after excitation at 4.66 eV. This work was carried out using a gas-dynamic flat liquid jet, resulting in considerably enhanced signal compared to a cylindrical jet. All three species decay on multiple time scales that are assigned based on their decay associated spectra; the fastest decay of ∼100 fs is assigned to ππ* decay to the ground state, while a smaller component with a lifetime of ∼500 fs is attributed to the nπ* state. An additional slower channel in Ade is assigned to the 7H Ade conformer, as seen previously. This work demonstrates the capability of XUV-TRPES to disentangle non-adiabatic dynamics in an aqueous solution in a state-specific manner and represents the first identification of the nπ* state in the relaxation dynamics of adenine and its derivatives.

The F-box protein gene exo-1 is a target for reverse engineering enzyme hypersecretion in filamentous fungi.

Carbohydrate active enzymes (CAZymes) are vital for the lignocellulose-based biorefinery. The development of hypersecreting fungal protein production hosts is therefore a major aim for both academia and industry. However, despite advances in our understanding of their regulation, the number of promising candidate genes for targeted strain engineering remains limited. Here, we resequenced the genome of the classical hypersecreting Neurospora crassa mutant exo-1 and identified the causative point of mutation to reside in the F-box protein-encoding gene, NCU09899. The corresponding deletion strain displayed amylase and invertase activities exceeding those of the carbon catabolite derepressed strain Δcre-1, while glucose repression was still mostly functional in Δexo-1 Surprisingly, RNA sequencing revealed that while plant cell wall degradation genes are broadly misexpressed in Δexo-1, only a small fraction of CAZyme genes and sugar transporters are up-regulated, indicating that EXO-1 affects specific regulatory factors. Aiming to elucidate the underlying mechanism of enzyme hypersecretion, we found the high secretion of amylases and invertase in Δexo-1 to be completely dependent on the transcriptional regulator COL-26. Furthermore, misregulation of COL-26, CRE-1, and cellular carbon and nitrogen metabolism was confirmed by proteomics. Finally, we successfully transferred the hypersecretion trait of the exo-1 disruption by reverse engineering into the industrially deployed fungus Myceliophthora thermophila using CRISPR-Cas9. Our identification of an important F-box protein demonstrates the strength of classical mutants combined with next-generation sequencing to uncover unanticipated candidates for engineering. These data contribute to a more complete understanding of CAZyme regulation and will facilitate targeted engineering of hypersecretion in further organisms of interest.

Development and validation of the Work Capital Scale.

Vocational psychologists have called for greater attention to different forms of capital, any resource or asset that confers profit and power, to better understand the vocational development process, particularly for those who lack resources and power. However, previous research has had several conceptual and measurement limitations, such as the use of less inclusive frameworks; a focus on more privileged populations; and the overuse of categorical, dummy coded, and objective measures. To address these limitations, the present study aimed to (a) develop an inclusive, subjective, continuous, and multidimensional work capital scale and (b) validate the new scale with representative samples of working adults and job seekers across two studies. We developed a 16-item four-factor Work Capital Scale that consists of Economic Work Capital, Human Work Capital, Social Work Capital, and Cultural Work Capital. Scores from the Work Capital Scale were invariant across household income, social class, gender, race, and employment status. We found that the correlational model fit best to the data and provided evidence for convergent and divergent validity by relating the subscales to subjective social class, objective socioeconomic indicators, and existing measures of capital. The present study advances theory and research in work capital and provides a tool for practitioners to use. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes and reservoirs.

This forecasting approach may be useful for water managers and associated public health managers to predict near-term future high-risk cyanobacterial harmful algal blooms (cyanoHAB) occurrence. Freshwater cyanoHABs may grow to excessive concentrations and cause human, animal, and environmental health concerns in lakes and reservoirs. Knowledge of the timing and location of cyanoHAB events is important for water quality management of recreational and drinking water systems. No quantitative tool exists to forecast cyanoHABs across broad geographic scales and at regular intervals. Publicly available satellite monitoring has proven effective in detecting cyanobacteria biomass near-real time within the United States. Weekly cyanobacteria abundance was quantified from the Ocean and Land Colour Instrument (OLCI) onboard the Sentinel-3 satellite as the response variable. An Integrated Nested Laplace Approximation (INLA) hierarchical Bayesian spatiotemporal model was applied to forecast World Health Organization (WHO) recreation Alert Level 1 exceedance >12 µg L-1 chlorophyll-a with cyanobacteria dominance for 2192 satellite resolved lakes in the United States across nine climate zones. The INLA model was compared against support vector classifier and random forest machine learning models; and Dense Neural Network, Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Gneural Network (GNU) neural network models. Predictors were limited to data sources relevant to cyanobacterial growth, readily available on a weekly basis, and at the national scale for operational forecasting. Relevant predictors included water surface temperature, precipitation, and lake geomorphology. Overall, the INLA model outperformed the machine learning and neural network models with prediction accuracy of 90% with 88% sensitivity, 91% specificity, and 49% precision as demonstrated by training the model with data from 2017 through 2020 and independently assessing predictions with data from the 2021 calendar year. The probability of true positive responses was greater than false positive responses and the probability of true negative responses was less than false negative responses. This indicated the model correctly assigned lower probabilities of events when they didn't exceed the WHO Alert Level 1 threshold and assigned higher probabilities when events did exceed the threshold. The INLA model was robust to missing data and unbalanced sampling between waterbodies.