A NEW POSTURAL MOTOR RESPONSE TO SPINAL CORD STIMULATION: POST-STIMULATION REBOUND EXTENSION.

Spinal cord stimulation (SCS) has emerged as a therapeutic tool for improving motor function following spinal cord injury. While many studies focus on restoring locomotion, little attention is paid to enabling standing which is a prerequisite of walking. In this study, we fully characterize a new type of response to SCS, a long extension activated post-stimulation (LEAP). LEAP is primarily directed to ankle extensors and hence has great clinical potential to assist postural movements. To characterize this new response, we used the decerebrate cat model to avoid the suppressive effects of anesthesia, and combined EMG and force measurement in the hindlimb with intracellular recordings in the lumbar spinal cord. Stimulation was delivered as five-second trains via bipolar electrodes placed on the cord surface, and multiple combinations of stimulation locations (L4 to S2), amplitudes (50-600 uA), and frequencies (10-40 Hz) were tested. While the optimum stimulation location and frequency differed slightly among animals, the stimulation amplitude was key for controlling LEAP duration and amplitude. To study the mechanism of LEAP, we performed in vivo intracellular recordings of motoneurons. In 70% of motoneurons, LEAP increased at hyperpolarized membrane potentials indicating a synaptic origin. Furthermore, spinal interneurons exhibited changes in firing during LEAP, confirming the circuit origin of this behavior. Finally, to identify the type of afferents involved in generating LEAP, we used shorter stimulation pulses (more selective for proprioceptive afferents), as well as peripheral stimulation of the sural nerve (cutaneous afferents). The data indicates that LEAP primarily relies on proprioceptive afferents and has major differences from pain or withdrawal reflexes mediated by cutaneous afferents. Our study has thus identified and characterized a novel postural motor response to SCS which has the potential to expand the applications of SCS for patients with motor disorders.

A Mitochondrial Basis for Heart Failure Progression.

In health, the human heart is able to match ATP supply and demand perfectly. It requires 6 kg of ATP per day to satisfy demands of external work (mechanical force generation) and internal work (ion movements and basal metabolism). The heart is able to link supply with demand via direct responses to ADP and AMP concentrations but calcium concentrations within myocytes play a key role, signalling both inotropy, chronotropy and matched increases in ATP production. Calcium/calmodulin-dependent protein kinase (CaMKII) is a key adapter to increased workload, facilitating a greater and more rapid calcium concentration change. In the failing heart, this is dysfunctional and ATP supply is impaired. This review aims to examine the mechanisms and pathologies that link increased energy demand to this disrupted situation. We examine the roles of calcium loading, oxidative stress, mitochondrial structural abnormalities and damage-associated molecular patterns.

Creating augmented reality-based experiences for aviation weather training: Challenges, opportunities, and design implications for 3D authoring.

This paper examines opportunities and challenges of integrating augmented reality (AR) into education and investigates requirements to enable instructors to author AR educational experiences. Although AR technology is recognised for its potential in educational enhancement, it poses challenges for instructors creating AR-based experiences due to their limited digital skills and the complexity of 3D authoring tools. Semi-structured interviews with 17 aviation instructors identified current pedagogical approaches, gaps, and potential applications of AR in aviation weather education. Additionally, results highlighted the benefits of AR and obstacles to its integration into education, followed by outlining design priorities and user needs for educational AR authoring. For AR authoring toolkit development, this study recommended incorporating interactive AR lesson modules, early development of user requirements, and prebuilt AR modules. Findings will guide the development of a 3D authoring toolkit for non-technologist instructors, enabling wider AR use in aviation weather education and other educational fields.

Research interviews with aviation instructors were conducted to derive design implications of AR authoring toolkits for non-technologist instructors. Key findings highlighted gaps in aviation weather education, potential AR applications, and barriers to AR in education. Design recommendations emphasised incorporating interactive AR lesson modules, initial user requirements, and prebuilt AR modules.

Design of Efficient Artificial Enzymes Using Crystallographically Enhanced Conformational Sampling.

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing the catalytic efficiency of de novo enzymes by several orders of magnitude without relying on directed evolution and high-throughput screening. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models, with catalytic contacts present as designed and transition-state root-mean-square deviations of ≤0.65 Å. Our work shows how ensemble-based design can generate efficient artificial enzymes by exploiting the true conformational ensemble to design improved active sites.

Design of efficient artificial enzymes using crystallographically-enhanced conformational sampling.

The ability to create efficient artificial enzymes for any chemical reaction is of great interest. Here, we describe a computational design method for increasing catalytic efficiency of de novo enzymes to a level comparable to their natural counterparts without relying on directed evolution. Using structural ensembles generated from dynamics-based refinement against X-ray diffraction data collected from crystals of Kemp eliminases HG3 (kcat/KM 125 M-1 s-1) and KE70 (kcat/KM 57 M-1 s-1), we design from each enzyme ≤10 sequences predicted to catalyze this reaction more efficiently. The most active designs display kcat/KM values improved by 100-250-fold, comparable to mutants obtained after screening thousands of variants in multiple rounds of directed evolution. Crystal structures show excellent agreement with computational models. Our work shows how computational design can generate efficient artificial enzymes by exploiting the true conformational ensemble to more effectively stabilize the transition state.

Impact of digital screen media activity on functional brain organization in late childhood: Evidence from the ABCD study.

The idea that the increased ubiquity of digital devices negatively impacts neurodevelopment is as compelling as it is disturbing. This study investigated this concern by systematically evaluating how different profiles of screen-based engagement related to functional brain organization in late childhood. We studied participants from a large and representative sample of young people participating in the first two years of the ABCD study (ages 9-12 years) to investigate the relations between self-reported use of various digital screen media activity (SMA) and functional brain organization. A series of generalized additive mixed models evaluated how these relationships related to functional outcomes associated with health and cognition. Of principal interest were two hypotheses: First, that functional brain organization (assessed through resting state functional connectivity MRI; rs-fcMRI) is related to digital screen engagement; and second, that children with higher rates of engagement will have functional brain organization profiles related to maladaptive functioning. Results did not support either of these predictions for SMA. Further, exploratory analyses predicting how screen media activity impacted neural trajectories showed no significant impact of SMA on neural maturation over a two-year period.

A Framework for Predicting X-Nuclei Transmitter Gain Using 1H Signal.

Commercial human MR scanners are optimised for proton imaging, containing sophisticated prescan algorithms with setting parameters such as RF transmit gain and power. These are not optimal for X-nuclear application and are challenging to apply to hyperpolarised experiments, where the non-renewable magnetisation signal changes during the experiment. We hypothesised that, despite the complex and inherently nonlinear electrodynamic physics underlying coil loading and spatial variation, simple linear regression would be sufficient to accurately predict X-nuclear transmit gain based on concomitantly acquired data from the proton body coil. We collected data across 156 scan visits at two sites as part of ongoing studies investigating sodium, hyperpolarised carbon, and hyperpolarised xenon. We demonstrate that simple linear regression is able to accurately predict sodium, carbon, or xenon transmit gain as a function of position and proton gain, with variation that is less than the intrasubject variability. In conclusion, sites running multinuclear studies may be able to remove the time-consuming need to separately acquire X-nuclear reference power calibration, inferring it from the proton instead.

A multivariate blood metabolite algorithm stably predicts risk and resilience to major depressive disorder in the general population.

BACKGROUND: Socioeconomic pressures, sex, and physical health status strongly influence the development of major depressive disorder (MDD) and mask other contributing factors in small cohorts. Resilient individuals overcome adversity without the onset of psychological symptoms, but resilience, as for susceptibility, has a complex and multifaceted molecular basis. The scale and depth of the UK Biobank affords an opportunity to identify resilience biomarkers in rigorously matched, at-risk individuals. Here, we evaluated whether blood metabolites could prospectively classify and indicate a biological basis for susceptibility or resilience to MDD. METHODS: Using the UK Biobank, we employed random forests, a supervised, interpretable machine learning statistical method to determine the relative importance of sociodemographic, psychosocial, anthropometric, and physiological factors that govern the risk of prospective MDD onset (total n = 15,710). We then used propensity scores to rigorously match individuals with a history of MDD (n = 491) against a resilient subset of individuals without an MDD diagnosis (retrospectively or during follow-up; n = 491) using an array of key social, demographic, and disease-associated drivers of depression risk. 381 blood metabolites and clinical chemistry variables and 4 urine metabolites were integrated to generate a multivariate random forest-based algorithm using 10-fold cross-validation to predict prospective MDD risk and resilience. OUTCOMES: In unmatched individuals, a first case of MDD, with a median time-to-diagnosis of 72 years, can be predicted using random forest classification probabilities with an area under the receiver operator characteristic curve (ROC AUC) of 0.89. Prospective resilience/susceptibility to MDD was then predicted with a ROC AUC of 0.72 (x˜ = 3.2 years follow-up) and 0.68 (x˜ = 7.2 years follow-up). Increased pyruvate was identified as a key biomarker of resilience to MDD and was validated retrospectively in the TwinsUK cohort. INTERPRETATION: Blood metabolites prospectively associate with substantially reduced MDD risk. Therapeutic targeting of these metabolites may provide a framework for MDD risk stratification and reduction. FUNDING: New York Academy of Sciences' Interstellar Programme Award; Novo Fonden; Lincoln Kingsgate award; Clarendon Fund; Newton-Abraham studentship (University of Oxford). The funders had no role in the development of the present study.

Compartment-based reconstruction of 3D acquisition-weighted 31 P cardiac magnetic resonance spectroscopic imaging at 7 T: A reproducibility study.

Even at 7 T, cardiac 31 P magnetic resonance spectroscopic imaging (MRSI) is fundamentally limited by low signal-to-noise ratio (SNR), leading to long scan times and poor temporal and spatial resolutions. Compartment-based reconstruction algorithms such as magnetic resonance spectroscopy with linear algebraic modeling (SLAM) and spectral localization by imaging (SLIM) may improve SNR or reduce scan time without changes to acquisition. Here, we compare the repeatability and SNR performance of these compartment-based methods, applied to three different acquisition schemes at 7 T. Twelve healthy volunteers were scanned twice. Each scan session consisted of a 6.5-min 3D acquisition-weighted (AW) cardiac 31 P phase encode-based MRSI acquisition and two 6.5-min truncated k-space acquisitions with increased averaging (4 × 4 × 4 central k-space phase encodes and fractional SLAM [fSLAM] optimized k-space phase encodes). Spectra were reconstructed using (i) AW Fourier reconstruction; (ii) AW SLAM; (iii) AW SLIM; (iv) 4 × 4 × 4 SLAM; (v) 4 × 4 × 4 SLIM; and (vi) fSLAM acquisition-reconstruction combinations. The phosphocreatine-to-adenosine triphosphate (PCr/ATP) ratio, the PCr SNR, and spatial response functions were computed, in addition to coefficients of reproducibility and variability. Using the compartment-based reconstruction algorithms with the AW 31 P acquisition resulted in a significant increase in SNR compared with previously published Fourier-based MRSI reconstruction methods while maintaining the measured PCr/ATP ratio and improving interscan reproducibility. The alternative acquisition strategies with truncated k-space performed no better than the common AW approach. Compartment-based spectroscopy approaches provide an attractive reconstruction method for cardiac 31 P spectroscopy at 7 T, improving reproducibility and SNR without the need for a dedicated k-space sampling strategy.

Assessment of Cardiac Energy Metabolism, Function, and Physiology in Patients With Heart Failure Taking Empagliflozin: The Randomized, Controlled EMPA-VISION Trial.

BACKGROUND: Sodium-glucose co-transporter 2 inhibitors (SGLT2i) have emerged as a paramount treatment for patients with heart failure (HF), irrespective of underlying reduced or preserved ejection fraction. However, a definite cardiac mechanism of action remains elusive. Derangements in myocardial energy metabolism are detectable in all HF phenotypes, and it was proposed that SGLT2i may improve energy production. The authors aimed to investigate whether treatment with empagliflozin leads to changes in myocardial energetics, serum metabolomics, and cardiorespiratory fitness. METHODS: EMPA-VISION (Assessment of Cardiac Energy Metabolism, Function and Physiology in Patients With Heart Failure Taking Empagliflozin) is a prospective, randomized, double-blind, placebo-controlled, mechanistic trial that enrolled 72 symptomatic patients with chronic HF with reduced ejection fraction (HFrEF; n=36; left ventricular ejection fraction ≤40%; New York Heart Association class ≥II; NT-proBNP [N-terminal pro-B-type natriuretic peptide] ≥125 pg/mL) and HF with preserved ejection fraction (HFpEF; n=36; left ventricular ejection fraction ≥50%; New York Heart Association class ≥II; NT-proBNP ≥125 pg/mL). Patients were stratified into respective cohorts (HFrEF versus HFpEF) and randomly assigned to empagliflozin (10 mg; n=35: 17 HFrEF and 18 HFpEF) or placebo (n=37: 19 HFrEF and 18 HFpEF) once daily for 12 weeks. The primary end point was a change in the cardiac phosphocreatine:ATP ratio (PCr/ATP) from baseline to week 12, determined by phosphorus magnetic resonance spectroscopy at rest and during peak dobutamine stress (65% of age-maximum heart rate). Mass spectrometry on a targeted set of 19 metabolites was performed at baseline and after treatment. Other exploratory end points were investigated. RESULTS: Empagliflozin treatment did not change cardiac energetics (ie, PCr/ATP) at rest in HFrEF (adjusted mean treatment difference [empagliflozin - placebo], -0.25 [95% CI, -0.58 to 0.09]; P=0.14) or HFpEF (adjusted mean treatment difference, -0.16 [95% CI, -0.60 to 0.29]; P=0.47]. Likewise, there were no changes in PCr/ATP during dobutamine stress in HFrEF (adjusted mean treatment difference, -0.13 [95% CI, -0.35 to 0.09]; P=0.23) or HFpEF (adjusted mean treatment difference, -0.22 [95% CI, -0.66 to 0.23]; P=0.32). No changes in serum metabolomics or levels of circulating ketone bodies were observed. CONCLUSIONS: In patients with either HFrEF or HFpEF, treatment with 10 mg of empagliflozin once daily for 12 weeks did not improve cardiac energetics or change circulating serum metabolites associated with energy metabolism when compared with placebo. Based on our results, it is unlikely that enhancing cardiac energy metabolism mediates the beneficial effects of SGLT2i in HF. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03332212.

Machine intelligence for radiation science: summary of the Radiation Research Society 67th annual meeting symposium.

The era of high-throughput techniques created big data in the medical field and research disciplines. Machine intelligence (MI) approaches can overcome critical limitations on how those large-scale data sets are processed, analyzed, and interpreted. The 67th Annual Meeting of the Radiation Research Society featured a symposium on MI approaches to highlight recent advancements in the radiation sciences and their clinical applications. This article summarizes three of those presentations regarding recent developments for metadata processing and ontological formalization, data mining for radiation outcomes in pediatric oncology, and imaging in lung cancer.

Developing a metabolic clearance rate framework as a translational analysis approach for hyperpolarized 13C magnetic resonance imaging.

Hyperpolarized carbon-13 magnetic resonance imaging is a promising technique for in vivo metabolic interrogation of alterations between health and disease. This study introduces a formalism for quantifying the metabolic information in hyperpolarized imaging. This study investigated a novel perfusion formalism and metabolic clearance rate (MCR) model in pre-clinical stroke and in the healthy human brain. Simulations showed that the proposed model was robust to perturbations in T1, transmit B1, and kPL. A significant difference in ipsilateral vs contralateral pyruvate derived cerebral blood flow (CBF) was detected in rats (140 ± 2 vs 89 ± 6 mL/100 g/min, p < 0.01, respectively) and pigs (139 ± 12 vs 95 ± 5 mL/100 g/min, p = 0.04, respectively), along with an increase in fractional metabolism (26 ± 5 vs 4 ± 2%, p < 0.01, respectively) in the rodent brain. In addition, a significant increase in ipsilateral vs contralateral MCR (0.034 ± 0.007 vs 0.017 ± 0.02/s, p = 0.03, respectively) and a decrease in mean transit time (31 ± 8 vs 60 ± 2 s, p = 0.04, respectively) was observed in the porcine brain. In conclusion, MCR mapping is a simple and robust approach to the post-processing of hyperpolarized magnetic resonance imaging.

Reversible pH-responsive MRI contrast with paramagnetic polymer micelles.

Paramagnetically-doped polymer micelles, containing an ionizable poly(acrylic acid) (PAA) block, support high-contrast MR imaging at clinically relevant field strengths in a manner that is strongly pH responsive. A reversible switch in polymer strand charge specifically has a direct impact on local rigidity, and rotational correlation time characteristics, of the integrated Gd-chelate, driving a ∼50% amplitude switch in positive contrast.

Functional and Metabolic Imaging in Heart Failure with Preserved Ejection Fraction: Promises, Challenges, and Clinical Utility.

Heart failure with preserved ejection fraction (HFpEF) is recognised as an increasingly prevalent, morbid and burdensome condition with a poor outlook. Recent advances in both the understanding of HFpEF and the technological ability to image cardiac function and metabolism in humans have simultaneously shone a light on the molecular basis of this complex condition of diastolic dysfunction, and the inflammatory and metabolic changes that are associated with it, typically in the context of a complex patient. This review both makes the case for an integrated assessment of the condition, and highlights that metabolic alteration may be a measurable outcome for novel targeted forms of medical therapy. It furthermore highlights how recent technological advancements and advanced medical imaging techniques have enabled the characterisation of the metabolism and function of HFpEF within patients, at rest and during exercise.

Compartment-based reconstruction of acquisition-weighted 31P cardiac MRSI reduces sensitivity to cardiac motion and scan planning.

Motivation: 31P magnetic resonance spectroscopic imaging (31P MRSI) is a powerful technique for investigating the metabolic effects of treatments for heart failure in vivo, allowing a better understanding of their mechanism of action in patient cohorts. Unfortunately, cardiac 31P MRSI is fundamentally limited by low SNR, which leads to compromises in acquisition, such as no cardiac or respiratory gating or low spatial resolution, in order to achieve reasonable scan times. Spectroscopy with linear algebra modeling (SLAM) reconstruction may be able to address these challenges and therefore improve repeatability by incorporating a segmented localizer into the reconstruction. Methods: Six healthy volunteers were scanned twice in a test-retest procedure to allow quantification of repeatability. Each scan consisted of anatomical localizers and two acquisition-weighted (AW) 31P MRSI acquisitions, which were acquired with and without cardiac gating. Five patients with heart failure with a preserved ejection fraction were then scanned with the same 31P MRSI sequence without cardiac gating. All 31P MRSI datasets were reconstructed with both conventional Fourier transform (FT)-based reconstruction and SLAM reconstruction, which were compared statistically. The effect of shifting the 31P MRSI acquisition field of view was also investigated. Results: In the healthy volunteer cohort, the spectral fit of the SLAM reconstructions had significantly improved Cramer-Rao lower bounds (CRLBs) compared to the FT-based reconstruction of non-cardiac gated data, as well as improved coefficients of variability and repeatability. The SLAM reconstruction found a significant difference in the PCr/ATP ratio between the healthy volunteer and patient cohorts, which the FT-based reconstruction did not find. Furthermore, the SLAM reconstruction was less influenced by the placement of the field of view (FOV) of the 31P MRSI acquisition in post hoc analysis. Discussion: The experimental benefits of the SLAM reconstruction for AW data were demonstrated by the improvements in fit confidence and repeatability seen in the healthy volunteer cohort and post hoc FOV analysis. The benefit of SLAM reconstruction of AW data for clinical studies was then illustrated by the patient cohort, which suggested improved sensitivity to clinically significant changes in the PCr/ATP ratio.

Direct observation of the molecular mechanism underlying protein polymerization.

Protein assembly is a main route to generating complexity in living systems. Revealing the relevant molecular details is challenging because of the intrinsic heterogeneity of species ranging from few to hundreds of molecules. Here, we use mass photometry to quantify and monitor the full range of actin oligomers during polymerization with single-molecule sensitivity. We find that traditional nucleation-based models cannot account for the observed distributions of actin oligomers. Instead, the key step of filament formation is a slow transition between distinct states of an actin filament mediated by cation exchange or ATP hydrolysis. The resulting model reproduces important aspects of actin polymerization, such as the critical concentration for filament formation and bulk growth behavior. Our results revise the mechanism of actin nucleation, shed light on the role and function of actin-associated proteins, and introduce a general and quantitative means to studying protein assembly at the molecular level.

The effects of endogenously- and exogenously-induced hyperketonemia on exercise performance and adaptation.

Elevating blood ketones may enhance exercise capacity and modulate adaptations to exercise training; however, these effects may depend on whether hyperketonemia is induced endogenously through dietary carbohydrate restriction, or exogenously through ketone supplementation. To determine this, we compared the effects of endogenously- and exogenously-induced hyperketonemia on exercise capacity and adaptation. Trained endurance athletes undertook 6 days of laboratory based cycling ("race") whilst following either: a carbohydrate-rich control diet (n = 7; CHO); a carbohydrate-rich diet + ketone drink four-times daily (n = 7; Ex Ket); or a ketogenic diet (n = 7; End Ket). Exercise capacity was measured daily, and adaptations in exercise metabolism, exercise physiology and postprandial insulin sensitivity (via an oral glucose tolerance test) were measured before and after dietary interventions. Urinary ß-hydroxybutyrate increased by ⁓150-fold and ⁓650-fold versus CHO with Ex Ket and End Ket, respectively. Exercise capacity was increased versus pre-intervention by ~5% on race day 1 with CHO (p < 0.05), by 6%-8% on days 1, 4, and 6 (all p < 0.05) with Ex Ket and decreased by 48%-57% on all race days (all p > 0.05) with End Ket. There was an ⁓3-fold increase in fat oxidation from pre- to post-intervention (p < 0.05) with End Ket and increased perceived exercise exertion (p < 0.05). No changes in exercise substrate metabolism occurred with Ex Ket, but participants had blunted postprandial insulin sensitivity (p < 0.05). Dietary carbohydrate restriction and ketone supplementation both induce hyperketonemia; however, these are distinct physiological conditions with contrasting effects on exercise capacity and adaptation to exercise training.

Assessing the effect of anesthetic gas mixtures on hyperpolarized 13 C pyruvate metabolism in the rat brain.

PURPOSE: To determine the effect of altering anesthetic oxygen protocols on measurements of cerebral perfusion and metabolism in the rodent brain. METHODS: Seven rats were anesthetized and underwent serial MRI scans with hyperpolarized [1-13 C]pyruvate and perfusion weighted imaging. The anesthetic carrier gas protocol used varied from 100:0% to 90:10% to 60:40% O2 :N2 O. Spectra were quantified with AMARES and perfusion imaging was processed using model-free deconvolution. A 1-way ANOVA was used to compare results across groups, with pairwise t tests performed with correction for multiple comparisons. Spearman's correlation analysis was performed between O2 % and MR measurements. RESULTS: There was a significant increase in bicarbonate:total 13 C carbon and bicarbonate:13 C pyruvate when moving between 100:0 to 90:10 and 100:0 to 60:40 O2 :N2 O % (0.02 ± 0.01 vs. 0.019 ± 0.005 and 0.02 ± 0.01 vs. 0.05 ± 0.02, respectively) and (0.04 ± 0.01 vs. 0.03 ± 0.01 and 0.04 ± 0.01 vs. 0.08 ± 0.02, respectively). There was a significant difference in 13 C pyruvate time to peak when moving between 100:0 to 90:10 and 100:0 to 60:40 O2 :N2 O % (13 ± 2 vs. 10 ± 1 and 13 ± 2 vs. 7.5 ± 0.5 s, respectively) as well as significant differences in cerebral blood flow (CBF) between gas protocols. Significant correlations between bicarbonate:13 C pyruvate and gas protocol (ρ = -0.47), mean transit time and gas protocol (ρ = 0.41) and 13 C pyruvate time-to-peak and cerebral blood flow (ρ = -0.54) were also observed. CONCLUSIONS: These results demonstrate that the detection and quantification of cerebral metabolism and perfusion is dependent on the oxygen protocol used in the anesthetized rodent brain.

Acute intermittent hypoxia drives hepatic de novo lipogenesis in humans and rodents.

Background and aims: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver condition. It is tightly associated with an adverse metabolic phenotype (including obesity and type 2 diabetes) as well as with obstructive sleep apnoea (OSA) of which intermittent hypoxia is a critical component. Hepatic de novo lipogenesis (DNL) is a significant contributor to hepatic lipid content and the pathogenesis of NAFLD and has been proposed as a key pathway to target in the development of pharmacotherapies to treat NAFLD. Our aim is to use experimental models to investigate the impact of hypoxia on hepatic lipid metabolism independent of obesity and metabolic disease. Methods: Human and rodent studies incorporating stable isotopes and hyperinsulinaemic euglycaemic clamp studies were performed to assess the regulation of DNL and broader metabolic phenotype by intermittent hypoxia. Cell-based studies, including pharmacological and genetic manipulation of hypoxia-inducible factors (HIF), were used to examine the underlying mechanisms. Results: Hepatic DNL increased in response to acute intermittent hypoxia in humans, without alteration in glucose production or disposal. These observations were endorsed in a prolonged model of intermittent hypoxia in rodents using stable isotopic assessment of lipid metabolism. Changes in DNL were paralleled by increases in hepatic gene expression of acetyl CoA carboxylase 1 and fatty acid synthase. In human hepatoma cell lines, hypoxia increased both DNL and fatty acid uptake through HIF-1α and -2α dependent mechanisms. Conclusions: These studies provide robust evidence linking intermittent hypoxia and the regulation of DNL in both acute and sustained in vivo models of intermittent hypoxia, providing an important mechanistic link between hypoxia and NAFLD.

Concentration-dependent effects of dichloroacetate in type 2 diabetic hearts assessed by hyperpolarized [1-13 C]-pyruvate magnetic resonance imaging.

Personalized medicine or individualized therapy promises a paradigm shift in healthcare. This is particularly true in complex and multifactorial diseases such as diabetes and the multitude of related pathophysiological complications. Diabetic cardiomyopathy represents an emerging condition that could be effectively treated if better diagnostic and, in particular, better therapeutic monitoring tools were available. In this study, we investigate the ability to differentiate low and high doses of metabolically targeted therapy in an obese type 2 diabetic rat model. Low-dose dichloroacetate (DCA) treatment was associated with increased lactate production, while no or little change was seen in bicarbonate production. High-dose DCA treatment was associated with a significant metabolic switch towards increased bicarbonate production. These findings support further studies using hyperpolarized [1-13 C]-pyruvate magnetic resonance imaging to differentiate treatment effects and thus allow for personalized titration of therapeutics.