A synthetic biology approach for the treatment of pollutants with microalgae.

The increase in global population and industrial development has led to a significant release of organic and inorganic pollutants into water streams, threatening human health and ecosystems. Microalgae, encompassing eukaryotic protists and prokaryotic cyanobacteria, have emerged as a sustainable and cost-effective solution for removing these pollutants and mitigating carbon emissions. Various microalgae species, such as C. vulgaris, P. tricornutum, N. oceanica, A. platensis, and C. reinhardtii, have demonstrated their ability to eliminate heavy metals, salinity, plastics, and pesticides. Synthetic biology holds the potential to enhance microalgae-based technologies by broadening the scope of treatment targets and improving pollutant removal rates. This review provides an overview of the recent advances in the synthetic biology of microalgae, focusing on genetic engineering tools to facilitate the removal of inorganic (heavy metals and salinity) and organic (pesticides and plastics) compounds. The development of these tools is crucial for enhancing pollutant removal mechanisms through gene expression manipulation, DNA introduction into cells, and the generation of mutants with altered phenotypes. Additionally, the review discusses the principles of synthetic biology tools, emphasizing the significance of genetic engineering in targeting specific metabolic pathways and creating phenotypic changes. It also explores the use of precise engineering tools, such as CRISPR/Cas9 and TALENs, to adapt genetic engineering to various microalgae species. The review concludes that there is much potential for synthetic biology based approaches for pollutant removal using microalgae, but there is a need for expansion of the tools involved, including the development of universal cloning toolkits for the efficient and rapid assembly of mutants and transgenic expression strains, and the need for adaptation of genetic engineering tools to a wider range of microalgae species.

Integrated care van delivery of evidence-based services for people who inject drugs: A cluster-randomized trial.

BACKGROUND AND AIMS: People who inject drugs (PWID) are at risk for adverse outcomes across multiple dimensions. While evidence-based interventions are available, services are often fragmented and difficult to access. We measured the effectiveness of an integrated care van (ICV) that offered services for PWID. DESIGN, SETTING AND PARTICIPANTS: This was a cluster-randomized trial, which took place in Baltimore, MD, USA. Prior to randomization, we used a research van to recruit PWID cohorts from 12 Baltimore neighborhoods (sites), currently served by the city's mobile needle exchange program. INTERVENTION AND COMPARATOR: We randomized sites to receive weekly visits from the ICV (n = 6) or to usual services (n = 6) for 14 months. The ICV offered case management; buprenorphine/naloxone; screening for HIV, hepatitis C virus and sexually transmitted infections; HIV pre-exposure prophylaxis; and wound care. MEASUREMENTS: The primary outcome was a composite harm mitigation score that captured access to evidence-based services, risk behaviors and adverse health events (range = 0-15, with higher numbers indicating worse status). We evaluated effectiveness by comparing changes in the composite score at 7 months versus baseline in the two study arms. FINDINGS: We enrolled 720 cohort participants across the study sites (60 per site) between June 2018 and August 2019: 38.3% women, 72.6% black and 85.1% urine drug test positive for fentanyl. Over a median of 10.4 months, the ICV provided services to 734 unique clients (who may or may not have been cohort participants) across the six intervention sites, including HIV/hepatitis C virus testing in 577 (78.6%) and buprenorphine/naloxone initiation in 540 (74%). However, only 52 (7.2%) of cohort participants received services on the ICV. The average composite score decreased at 7 months relative to baseline, with no significant difference in the change between ICV and usual services (difference in differences: -0.31; 95% confidence interval: -0.70, 0.08; P = 0.13). CONCLUSIONS: This cluster-randomized trial in Baltimore, MD, USA, found no evidence that weekly neighborhood visits from a mobile health van providing injection-drug-focused services improved access to services and outcomes among people who injected drugs in the neighborhood, relative to usual services. The van successfully served large numbers of clients but unexpectedly low use of the van by cohort participants limited the ability to detect meaningful differences.

Implementation of a Self-Audit Tool Improves Regulatory Compliance for Point-of-Care Respiratory Virus Testing in the Emergency Department.

BACKGROUND: Point-of-care testing in the emergency department decreases wait times and supports evidence-based patient care. However, hurdles to successful implementation include management of interdisciplinary work flows and establishment of an effective quality control program. As COVID-19 testing is now integrated into screening protocols in emergency and urgent care settings, hospital systems must maintain flexible and adaptable respiratory virus testing to adapt to regional trends in transmission. In response to this challenge, our hospital system established a point-of-care respiratory virus laboratory within the emergency department to test for COVID, influenza A/B, and respiratory syncytial virus (RSV). However, maintaining regulatory compliance and standardized protocols within such a dynamic environment became challenging. METHODS: We launched a quality improvement initiative to support improved performance and efficiency in the point-of-care laboratory with a focus on regulatory benchmarks. Following a period of observation and discussion with key stakeholders in the emergency department and pathology, an audit tool was developed and to be deployed in collaboration with ED nursing. Utilizing the new tool, ED nursing would perform audits in parallel to audits performed by point-of-care staff. RESULTS: Prior to the intervention, the average audit score was approximately 55%; 6 months following the intervention, audit scores have remained stable at approximately 80%, representing a significant improvement in regulatory compliance. CONCLUSIONS: Creation of a regulatory tool enabled real-time cross-departmental monitoring of regulatory compliance. These findings underscore the importance of developing transparent interdisciplinary work flows and effective communication to improve patient care.

Whole-brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism.

Deuterium metabolic imaging (DMI) is an emerging magnetic resonance technique, for non-invasive mapping of human brain glucose metabolism following oral or intravenous administration of deuterium-labeled glucose. Regional differences in glucose metabolism can be observed in various brain pathologies, such as Alzheimer's disease, cancer, epilepsy or schizophrenia, but the achievable spatial resolution of conventional phase-encoded DMI methods is limited due to prolonged acquisition times rendering submilliliter isotropic spatial resolution for dynamic whole brain DMI not feasible. The purpose of this study was to implement non-Cartesian spatial-spectral sampling schemes for whole-brain 2H FID-MR Spectroscopic Imaging to assess time-resolved metabolic maps with sufficient spatial resolution to reliably detect metabolic differences between healthy gray and white matter regions. Results were compared with lower-resolution DMI maps, conventionally acquired within the same session. Six healthy volunteers (4 m/2 f) were scanned for ~90 min after administration of 0.8 g/kg oral [6,6']-2H glucose. Time-resolved whole brain 2H FID-DMI maps of glucose (Glc) and glutamate + glutamine (Glx) were acquired with 0.75 and 2 mL isotropic spatial resolution using density-weighted concentric ring trajectory (CRT) and conventional phase encoding (PE) readout, respectively, at 7 T. To minimize the effect of decreased signal-to-noise ratios associated with smaller voxels, low-rank denoising of the spatiotemporal data was performed during reconstruction. Sixty-three minutes after oral tracer uptake three-dimensional (3D) CRT-DMI maps featured 19% higher (p = .006) deuterium-labeled Glc concentrations in GM (1.98 ± 0.43 mM) compared with WM (1.66 ± 0.36 mM) dominated regions, across all volunteers. Similarly, 48% higher (p = .01) 2H-Glx concentrations were observed in GM (2.21 ± 0.44 mM) compared with WM (1.49 ± 0.20 mM). Low-resolution PE-DMI maps acquired 70 min after tracer uptake featured smaller regional differences between GM- and WM-dominated areas for 2H-Glc concentrations with 2.00 ± 0.35 mM and 1.71 ± 0.31 mM, respectively (+16%; p = .045), while no regional differences were observed for 2H-Glx concentrations. In this study, we successfully implemented 3D FID-MRSI with fast CRT encoding for dynamic whole-brain DMI at 7 T with 2.5-fold increased spatial resolution compared with conventional whole-brain phase encoded (PE) DMI to visualize regional metabolic differences. The faster metabolic activity represented by 48% higher Glx concentrations was observed in GM- compared with WM-dominated regions, which could not be reproduced using whole-brain DMI with the low spatial resolution protocol. Improved assessment of regional pathologic alterations using a fully non-invasive imaging method is of high clinical relevance and could push DMI one step toward clinical applications.

3D ultra-short echo time 31P-MRSI with rosette k-space pattern: Feasibility and comparison with conventional weighted CSI.

Phosphorus-31 magnetic resonance spectroscopic imaging (31P-MRSI) provides valuable non-invasive in vivo information on tissue metabolism but is burdened by poor sensitivity and prolonged scan duration. Ultra-short echo time (UTE) acquisitions minimize signal loss when probing signals with relatively short spin-spin relaxation time (T2), while also preventing first-order dephasing. Here, a three-dimensional (3D) UTE sequence with a rosette k-space trajectory is applied to 31P-MRSI at 3T. Conventional chemical shift imaging (CSI) employs highly regular Cartesian k-space sampling, susceptible to substantial artifacts when accelerated via undersampling. In contrast, this novel sequence's "petal-like" pattern offers incoherent sampling more suitable for compressed sensing (CS). These results showcase the competitive performance of UTE rosette 31P-MRSI against conventional weighted CSI with simulation, phantom, and in vivo leg muscle comparisons.

Elucidating Local Structure and Positional Effect of Dopants in Colloidal Transition Metal Dichalcogenide Nanosheets for Catalytic Hydrogenolysis.

Tailoring nanoscale catalysts to targeted applications is a vital component in reducing the carbon footprint of industrial processes; however, understanding and controlling the nanostructure influence on catalysts is challenging. Molybdenum disulfide (MoS2), a transition metal dichalcogenide (TMD) material, is a popular example of a nonplatinum-group-metal catalyst with tunable nanoscale properties. Doping with transition metal atoms, such as cobalt, is one method of enhancing its catalytic properties. However, the location and influence of dopant atoms on catalyst behavior are poorly understood. To investigate this knowledge gap, we studied the influence of Co dopants in MoS2 nanosheets on catalytic hydrodesulfurization (HDS) through a well-controlled, ligand-directed, tunable colloidal doping approach. X-ray absorption spectroscopy and density functional theory calculations revealed the nonmonotonous relationship between dopant concentration, location, and activity in HDS. Catalyst activity peaked at 21% Co:Mo as Co saturates the edge sites and begins basal plane doping. While Co prefers to dope the edges over basal sites, basal Co atoms are demonstrably more catalytically active than edge Co. These findings provide insight into the hydrogenolysis behavior of doped TMDs and can be extended to other TMD materials.

Effect of feeding frequency on the anaerobic digestion of berry fruit waste.

On-site anaerobic digesters for small agricultural farms typically have feeding schedules that fluctuate according to farm operations. Shocks in feeding, particularly for putrescible waste can disrupt the stable operation of a digester. The effect of intermittent feeding on the anaerobic digestion of rejected raspberries was investigated in four 3L reactors operated in semicontinuous mode for 350 days at 38 °C with a hydraulic retention time of 25 days and an organic loading rate (OLR) of 1gVS/L/d. During the acclimatisation period (147 days) the organic loading was 5 feeds per week. The feeding regime of two reactors was then changed while maintaining the same OLR and HRT to one weekly feed event in one reactor and 3 equal feeds per week in another. The feeding regime did not significantly affect specific methane yield (369 ± 47 L/kgVS on average) despite very different weekly patterns in methane production. Volatile fatty acids (VFA) comprised >83 % of the organics in the effluent, while the rest included non-inhibitory concentrations of phenolic compounds (515-556 mg gallic acid/L). The microbial composition and relative abundance of predominant groups in all reactors were the archaeal genera Methanobacterium and Methanolinea and the bacterial phyla Bacteridota and Firmicutes. Increasing the OLR to 2gVS/L/d on day 238 resulted in failure of all reactors, attributed to the insufficient alkalinity to counterbalance the VFA produced, and the pH decrease below 6. Overall results suggests that optimal digestion of raspberry waste is maintained despite variations in feeding frequency, but acidification can occur with OLR changes.

Universal dynamic fitting of magnetic resonance spectroscopy.

PURPOSE: Dynamic (2D) MRS is a collection of techniques where acquisitions of spectra are repeated under varying experimental or physiological conditions. Dynamic MRS comprises a rich set of contrasts, including diffusion-weighted, relaxation-weighted, functional, edited, or hyperpolarized spectroscopy, leading to quantitative insights into multiple physiological or microstructural processes. Conventional approaches to dynamic MRS analysis ignore the shared information between spectra, and instead proceed by independently fitting noisy individual spectra before modeling temporal changes in the parameters. Here, we propose a universal dynamic MRS toolbox which allows simultaneous fitting of dynamic spectra of arbitrary type. METHODS: A simple user-interface allows information to be shared and precisely modeled across spectra to make inferences on both spectral and dynamic processes. We demonstrate and thoroughly evaluate our approach in three types of dynamic MRS techniques. Simulations of functional and edited MRS are used to demonstrate the advantages of dynamic fitting. RESULTS: Analysis of synthetic functional 1H-MRS data shows a marked decrease in parameter uncertainty as predicted by prior work. Analysis with our tool replicates the results of two previously published studies using the original in vivo functional and diffusion-weighted data. Finally, joint spectral fitting with diffusion orientation models is demonstrated in synthetic data. CONCLUSION: A toolbox for generalized and universal fitting of dynamic, interrelated MR spectra has been released and validated. The toolbox is shared as a fully open-source software with comprehensive documentation, example data, and tutorials.

Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling.

Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.

Toward point-of-care diagnostics: Running enzymatic assays on a photonic waveguide-based sensor chip with a portable, benchtop measurement system.

We demonstrate a portable, compact system to perform absorption-based enzymatic assays at a visible wavelength of 639 nm on a photonic waveguide-based sensor chip, suitable for lab-on-a-chip applications. The photonic design and fabrication of the sensor are described, and a detailed overview of the portable measurement system is presented. In this publication, we use an integrated photonic waveguide-based absorbance sensor to run a full enzymatic assay. An assay to detect creatinine in plasma is simultaneously performed on both the photonic sensor on the portable setup and on a commercial microplate reader for a clinically relevant creatinine concentration range. We observed a high correlation between the measured waveguide propagation loss and the optical density measurement from the plate reader and measured a limit-of-detection of 4.5 µM creatinine in the sensor well, covering the relevant clinical range for creatinine detection.

Analytical Validation of Aptamer-Based Serum Vancomycin Monitoring Relative to Automated Immunoassays.

The practice of monitoring therapeutic drug concentrations in patient biofluids can significantly improve clinical outcomes while simultaneously minimizing adverse side effects. A model example of this practice is vancomycin dosing in intensive care units. If dosed correctly, vancomycin can effectively treat methicillin-resistant streptococcus aureus (MRSA) infections. However, it can also induce nephrotoxicity or fail to kill the bacteria if dosed too high or too low, respectively. Although undeniably important to achieve effectiveness, therapeutic drug monitoring remains inconvenient in practice due primarily to the lengthy process of sample collection, transport to a centralized facility, and analysis using costly instrumentation. Adding to this workflow is the possibility of backlogs at centralized clinical laboratories, which is not uncommon and may result in additional delays between biofluid sampling and concentration measurement, which can negatively affect clinical outcomes. Here, we explore the possibility of using point-of-care electrochemical aptamer-based (E-AB) sensors to minimize the time delay between biofluid sampling and drug measurement. Specifically, we conducted a clinical agreement study comparing the measurement outcomes of E-AB sensors to the benchmark automated competitive immunoassays for vancomycin monitoring in serum. Our results demonstrate that E-ABs are selective for free vancomycin─the active form of the drug, over total vancomycin. In contrast, competitive immunoassays measure total vancomycin, including both protein-bound and free drug. Accounting for these differences in a pilot study consisting of 85 clinical samples, we demonstrate that the E-AB vancomycin measurement achieved a 95% positive correlation rate with the benchmark immunoassays. Therefore, we conclude that E-AB sensors could provide clinically useful stratification of patient samples at trough sampling to guide effective vancomycin dose recommendations.

Population-level analysis of natural control of HIV infection in Zambia and South Africa: HPTN 071 (PopART).

INTRODUCTION: HIV controllers have low viral loads (VL) without antiretroviral treatment (ART). We evaluated viraemic control in a community-randomized trial conducted in Zambia and South Africa that evaluated the impact of a combination prevention intervention on HIV incidence (HPTN 071 [PopART]; 2013-2018). METHODS: VL and antiretroviral (ARV) drug testing were performed using plasma samples collected 2 years after enrolment for 4072 participants who were HIV positive at the start of the study intervention. ARV drug use was assessed using a qualitative laboratory assay that detects 22 ARV drugs in five drug classes. Participants were classified as non-controllers if they had a VL ≥2000 copies/ml with no ARV drugs detected at this visit. Additional VL and ARV drug testing was performed at a second annual study visit to confirm controller status. Participants were classified as controllers if they had VLs <2000 with no ARV drugs detected at both visits. Non-controllers who had ARV drugs detected at either visit were excluded from the analysis to minimize potential confounders associated with ARV drug access and uptake. RESULTS: The final cohort included 126 viraemic controllers and 766 non-controllers who had no ARV drugs detected. The prevalence of controllers among the 4072 persons assessed was 3.1% (95% confidence interval [CI]: 2.6%, 3.6%). This should be considered a minimum estimate, since high rates of ARV drug use in the parent study limited the ability to identify controllers. Among the 892 participants in the final cohort, controller status was associated with biological sex (female > male, p = 0.027). There was no significant association between controller status and age, study country or herpes simplex virus type 2 (HSV-2) status at study enrolment. CONCLUSIONS: To our knowledge, this report presents the first large-scale, population-level study evaluating the prevalence of viraemic control and associated factors in Africa. A key advantage of this study was that a biomedical assessment was used to assess ARV drug use (vs. self-reported data). This study identified a large cohort of HIV controllers and non-controllers not taking ARV drugs, providing a unique repository of longitudinal samples for additional research. This cohort may be useful for further studies investigating the mechanisms of virologic control.

Comprehensive profiling of pre-infection antibodies identifies HIV targets associated with viremic control and viral load.

Background: High HIV viral load (VL) is associated with increased transmission risk and faster disease progression. HIV controllers achieve viral suppression without antiretroviral (ARV) treatment. We evaluated viremic control in a community-randomized trial with >48,000 participants. Methods: A massively multiplexed antibody profiling system, VirScan, was used to quantify pre- and post-infection antibody reactivity to HIV peptides in 664 samples from 429 participants (13 controllers, 135 viremic non-controllers, 64 other non-controllers, 217 uninfected persons). Controllers had VLs <2,000 copies/mL with no ARV drugs detected at the first HIV-positive visit and one year later. Viremic non-controllers had VLs 2,000 copies/mL with no ARV drugs detected at the first HIV-positive visit. Other non-controllers had either ARV drugs detected at the first HIV-positive visit (n=47) or VLs <2,000 copies/mL with no ARV drugs detected at only one HIV-positive visit (n=17). Results: We identified pre-infection HIV antibody reactivities that correlated with post-infection VL. Pre-infection reactivity to an epitope in the HR2 domain of gp41 was associated with controller status and lower VL. Pre-infection reactivity to an epitope in the C2 domain of gp120 was associated with non-controller status and higher VL. Different patterns of antibody reactivity were observed over time for these two epitopes. Conclusion: These studies suggest that pre-infection HIV antibodies are associated with controller status and modulation of HIV VL. These findings may inform research on antibody-based interventions for HIV treatment.

Continuous Automated Analysis Workflow for MRS Studies.

Magnetic resonance spectroscopy (MRS) can non-invasively measure levels of endogenous metabolites in living tissue and is of great interest to neuroscience and clinical research. To this day, MRS data analysis workflows differ substantially between groups, frequently requiring many manual steps to be performed on individual datasets, e.g., data renaming/sorting, manual execution of analysis scripts, and manual assessment of success/failure. Manual analysis practices are a substantial barrier to wider uptake of MRS. They also increase the likelihood of human error and prevent deployment of MRS at large scale. Here, we demonstrate an end-to-end workflow for fully automated data uptake, processing, and quality review.The proposed continuous automated MRS analysis workflow integrates several recent innovations in MRS data and file storage conventions. They are efficiently deployed by a directory monitoring service that automatically triggers the following steps upon arrival of a new raw MRS dataset in a project folder: (1) conversion from proprietary manufacturer file formats into the universal format NIfTI-MRS; (2) consistent file system organization according to the data accumulation logic standard BIDS-MRS; (3) executing a command-line executable of our open-source end-to-end analysis software Osprey; (4) e-mail delivery of a quality control summary report for all analysis steps.The automated architecture successfully completed for a demonstration dataset. The only manual step required was to copy a raw data folder into a monitored directory.Continuous automated analysis of MRS data can reduce the burden of manual data analysis and quality control, particularly for non-expert users and multi-center or large-scale studies and offers considerable economic advantages.

GABA and Glutamate in hMT+ Link to Individual Differences in Residual Visual Function After Occipital Stroke.

BACKGROUND: Damage to the primary visual cortex following an occipital stroke causes loss of conscious vision in the contralateral hemifield. Yet, some patients retain the ability to detect moving visual stimuli within their blind field. The present study asked whether such individual differences in blind field perception following loss of primary visual cortex could be explained by the concentration of neurotransmitters γ-aminobutyric acid (GABA) and glutamate or activity of the visual motion processing, human middle temporal complex (hMT+). METHODS: We used magnetic resonance imaging in 19 patients with chronic occipital stroke to measure the concentration of neurotransmitters GABA and glutamate (proton magnetic resonance spectroscopy) and functional activity in hMT+ (functional magnetic resonance imaging). We also tested each participant on a 2-interval forced choice detection task using high-contrast, moving Gabor patches. We then measured and assessed the strength of relationships between participants' residual vision in their blind field and in vivo neurotransmitter concentrations, as well as visually evoked functional magnetic resonance imaging activity in their hMT+. Levels of GABA and glutamate were also measured in a sensorimotor region, which served as a control. RESULTS: Magnetic resonance spectroscopy-derived GABA and glutamate concentrations in hMT+ (but not sensorimotor cortex) strongly predicted blind-field visual detection abilities. Performance was inversely related to levels of both inhibitory and excitatory neurotransmitters in hMT+ but, surprisingly, did not correlate with visually evoked blood oxygenation level-dependent signal change in this motion-sensitive region. CONCLUSIONS: Levels of GABA and glutamate in hMT+ appear to provide superior information about motion detection capabilities inside perimetrically defined blind fields compared to blood oxygenation level-dependent signal changes-in essence, serving as biomarkers for the quality of residual visual processing in the blind-field. Whether they also reflect a potential for successful rehabilitation of visual function remains to be determined.

A Saliva-Based Serological and Behavioral Analysis of SARS-CoV-2 Antibody Prevalence in Howard County, Maryland.

The objective of the study was to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in the Howard County, Maryland, general population and demographic subpopulations attributable to natural infection or coronavirus disease 2019 (COVID-19) vaccination and to identify self-reported social behaviors that may affect the likelihood of recent or past SARS-CoV-2 infection. A cross-sectional, saliva-based serological study of 2,880 residents of Howard County, Maryland, was carried out from July through September 2021. Natural SARS-CoV-2 infection prevalence was estimated by inferring infections among individuals according to anti-nucleocapsid immunoglobin G levels and calculating averages weighted by sample proportions of various demographics. Antibody levels between BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) recipients were compared. Antibody decay rate was calculated by fitting exponential decay curves to cross-sectional indirect immunoassay data. Regression analysis was carried out to identify demographic factors, social behaviors, and attitudes that may be linked to an increased likelihood of natural infection. The estimated overall prevalence of natural infection in Howard County, Maryland, was 11.9% (95% confidence interval, 9.2% to 15.1%), compared with 7% reported COVID-19 cases. Antibody prevalence indicating natural infection was highest among Hispanic and non-Hispanic Black participants and lowest among non-Hispanic White and non-Hispanic Asian participants. Participants from census tracts with lower average household income also had higher natural infection rates. After accounting for multiple comparisons and correlations between participants, none of the behavior or attitude factors had significant effects on natural infection. At the same time, recipients of the mRNA-1273 vaccine had higher antibody levels than those of BNT162b2 vaccine recipients. Older study participants had overall lower antibody levels compared with younger study participants. The true prevalence of SARS-CoV-2 infection is higher than the number of reported COVID-19 cases in Howard County, Maryland. A disproportionate impact of infection-induced SARS-CoV-2 positivity was observed across different ethnic/racial subpopulations and incomes, and differences in antibody levels across different demographics were identified. Taken together, this information may inform public health policy to protect vulnerable populations. IMPORTANCE We employed a highly innovative noninvasive multiplex oral fluid SARS-CoV-2 IgG assay to ascertain our seroprevalence estimates. This laboratory-developed test has been applied in NCI's SeroNet consortium, possesses high sensitivity and specificity according to FDA Emergency Use Authorization guidelines, correlates strongly with SARS-CoV-2 neutralizing antibody responses, and is Clinical Laboratory Improvement Amendments-approved by the Johns Hopkins Hospital Department of Pathology. It represents a broadly scalable public health tool to improve understanding of recent and past SARS-CoV-2 exposure and infection without drawing any blood. To our knowledge, this is the first application of a high-performance salivary SARS-CoV-2 IgG assay to estimate population-level seroprevalence, including identifying COVID-19 disparities. We also are the first to report differences in SARS-CoV-2 IgG responses by COVID-19 vaccine manufacturers (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]). Our findings demonstrate remarkable consistency with those of blood-based SARS-CoV-2 IgG assays in terms of differences in the magnitude of SARS-CoV-2 IgG responses between COVID-19 vaccines.

Retained Metabolic Flexibility of the Failing Human Heart.

BACKGROUND: The failing heart is traditionally described as metabolically inflexible and oxygen starved, causing energetic deficit and contractile dysfunction. Current metabolic modulator therapies aim to increase glucose oxidation to increase oxygen efficiency of adenosine triphosphate production, with mixed results. METHODS: To investigate metabolic flexibility and oxygen delivery in the failing heart, 20 patients with nonischemic heart failure with reduced ejection fraction (left ventricular ejection fraction 34.9±9.1) underwent separate infusions of insulin+glucose infusion (I+G) or Intralipid infusion. We used cardiovascular magnetic resonance to assess cardiac function and measured energetics using phosphorus-31 magnetic resonance spectroscopy. To investigate the effects of these infusions on cardiac substrate use, function, and myocardial oxygen uptake (MVo2), invasive arteriovenous sampling and pressure-volume loops were performed (n=9). RESULTS: At rest, we found that the heart had considerable metabolic flexibility. During I+G, cardiac glucose uptake and oxidation were predominant (70±14% total energy substrate for adenosine triphosphate production versus 17±16% for Intralipid; P=0.002); however, no change in cardiac function was seen relative to basal conditions. In contrast, during Intralipid infusion, cardiac long-chain fatty acid (LCFA) delivery, uptake, LCFA acylcarnitine production, and fatty acid oxidation were all increased (LCFA 73±17% of total substrate versus 19±26% total during I+G; P=0.009). Myocardial energetics were better with Intralipid compared with I+G (phosphocreatine/adenosine triphosphate 1.86±0.25 versus 2.01±0.33; P=0.02), and systolic and diastolic function were improved (LVEF 34.9±9.1 baseline, 33.7±8.2 I+G, 39.9±9.3 Intralipid; P<0.001). During increased cardiac workload, LCFA uptake and oxidation were again increased during both infusions. There was no evidence of systolic dysfunction or lactate efflux at 65% maximal heart rate, suggesting that a metabolic switch to fat did not cause clinically meaningful ischemic metabolism. CONCLUSIONS: Our findings show that even in nonischemic heart failure with reduced ejection fraction with severely impaired systolic function, significant cardiac metabolic flexibility is retained, including the ability to alter substrate use to match both arterial supply and changes in workload. Increasing LCFA uptake and oxidation is associated with improved myocardial energetics and contractility. Together, these findings challenge aspects of the rationale underlying existing metabolic therapies for heart failure and suggest that strategies promoting fatty acid oxidation may form the basis for future therapies.