Plasma Nitric Oxide Consumption Is Elevated and Associated With Adverse Outcomes in Critically Ill Patients.

OBJECTIVES: Impaired nitric oxide (NO) bioavailability may contribute to microvascular dysfunction in sepsis. Excessive plasma NO consumption has been attributed to scavenging by circulating cell-free hemoglobin. This may be a mechanism for NO deficiency in sepsis and critical illness. We hypothesized that plasma NO consumption is high in critically ill patients, particularly those with sepsis, acute respiratory distress syndrome (ARDS), shock, and in hospital nonsurvivors. We further hypothesized that plasma NO consumption is correlated with plasma cell-free hemoglobin concentration. DESIGN: Retrospective cohort study. SETTING: Adult ICUs of an academic medical center. PATIENTS AND SUBJECTS: Three hundred sixty-two critically ill patients and 46 healthy control subjects. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Plasma NO consumption was measured using reductive chemiluminescence and cell-free hemoglobin was measured with a colorimetric assay. Mean (95% CI) plasma NO consumption (µM) was higher in critically ill patients versus healthy control subjects (3.9 [3.7-4.1] vs 2.1 [1.8-2.5]), septic versus nonseptic patients (4.1 [3.8-4.3] vs 3.6 [3.3-3.8]), ARDS versus non-ARDS patients (4.4 [4.0-4.9] vs 3.7 [3.6-3.9]), shock vs nonshock patients (4.4 [4.0-4.8] vs 3.6 [3.4-3.8]), and hospital nonsurvivors versus survivors (5.3 [4.4-6.4] vs 3.7 [3.6-3.9]). These relationships remained significant in multivariable analyses. Plasma cell-free hemoglobin was weakly correlated with plasma NO consumption. CONCLUSIONS: Plasma NO consumption is elevated in critically ill patients and independently associated with sepsis, ARDS, shock, and hospital death. These data suggest that excessive intravascular NO scavenging characterizes sepsis and adverse outcomes of critical illness.

Antibiotic-Specific Risk for Community-Acquired Clostridioides difficile Infection in the United States from 2008 to 2020.

Antibiotic exposure is a crucial risk factor for community-acquired Clostridioides difficile infection (CA-CDI). However, the relative risks associated with specific antibiotics may vary over time, and the absolute risks have not been clearly established. This is a retrospective cohort study. Adults were included if they received an outpatient antibiotic prescription within the IBM MarketScan databases between 2008 and 2020. The primary exposure was an outpatient antibiotic prescription, and the receipt of doxycycline was used as the reference comparison. The primary outcome was CA-CDI, defined as the presence of an International Classification of Diseases (ICD) diagnosis code for CDI within 90 days of receiving an outpatient antibiotic prescription, and subsequent treatment for CDI. There were 36,626,794 unique patients who received outpatient antibiotics, including 11,607 (0.03%) who developed CA-CDI. Relative to doxycycline, the antibiotics conferring the highest risks for CA-CDI were clindamycin (adjusted odds ratio [aOR], 8.81; 95% confidence interval [CI], 7.76 to 10.00), cefdinir (aOR, 5.86; 95% CI, 5.03 to 6.83), cefuroxime (aOR, 4.57; 95% CI, 3.87 to 5.39), and fluoroquinolones (aOR, 4.05; 95% CI, 3.58 to 4.59). Among older patients with CA-CDI risk factors, nitrofurantoin was also associated with CA-CDI (aOR, 3.05; 95% CI, 1.92 to 4.84), with a smaller number needed to harm, compared to the fluoroquinolones. While clindamycin, cefuroxime, and fluoroquinolone use declined from 2008 to 2020, nitrofurantoin use increased by 40%. Clindamycin was associated with the greatest CA-CDI risk, overall. Among older patients with an elevated baseline risk for CA-CDI, multiple antibiotics, including nitrofurantoin, had strong associations with CA-CDI. These results may guide antibiotic selection and future stewardship efforts.

Towards Multiplexed and Multimodal Biosensor Platforms in Real-Time Monitoring of Metabolic Disorders.

Metabolic syndrome (MS) is a cluster of conditions that increases the probability of heart disease, stroke, and diabetes, and is very common worldwide. While the exact cause of MS has yet to be understood, there is evidence indicating the relationship between MS and the dysregulation of the immune system. The resultant biomarkers that are expressed in the process are gaining relevance in the early detection of related MS. However, sensing only a single analyte has its limitations because one analyte can be involved with various conditions. Thus, for MS, which generally results from the co-existence of multiple complications, a multi-analyte sensing platform is necessary for precise diagnosis. In this review, we summarize various types of biomarkers related to MS and the non-invasively accessible biofluids that are available for sensing. Then two types of widely used sensing platform, the electrochemical and optical, are discussed in terms of multimodal biosensing, figure-of-merit (FOM), sensitivity, and specificity for early diagnosis of MS. This provides a thorough insight into the current status of the available platforms and how the electrochemical and optical modalities can complement each other for a more reliable sensing platform for MS.

BioVR: a platform for virtual reality assisted biological data integration and visualization.

BACKGROUND: Functional characterization of single nucleotide variants (SNVs) involves two steps, the first step is to convert DNA to protein and the second step is to visualize protein sequences with their structures. As massively parallel sequencing has emerged as a leading technology in genomics, resulting in a significant increase in data volume, direct visualization of SNVs together with associated protein sequences/structures in a new user interface (UI) would be a more effective way to assess their potential effects on protein function. RESULTS: We have developed BioVR, an easy-to-use interactive, virtual reality (VR)-assisted platform for integrated visual analysis of DNA/RNA/protein sequences and protein structures using Unity3D and the C# programming language. It utilizes the cutting-edge Oculus Rift, and Leap Motion hand detection, resulting in intuitive navigation and exploration of various types of biological data. Using Gria2 and its associated gene product as an example, we present this proof-of-concept software to integrate protein and nucleic acid data. For any amino acid or nucleotide of interest in the Gria2 sequence, it can be quickly linked to its corresponding location on Gria2 protein structure and visualized within VR. CONCLUSIONS: Using innovative 3D techniques, we provide a VR-based platform for visualization of DNA/RNA sequences and protein structures in aggregate, which can be extended to view omics data.

Krebs cycle metabolites and preferential succinate oxidation following neonatal hypoxic-ischemic brain injury in mice.

BackgroundReverse electron transport (RET) driven by the oxidation of succinate has been proposed as the mechanism of accelerated production of reactive oxygen species (ROS) in post-ischemic mitochondria. However, it remains unclear whether upon reperfusion, mitochondria preferentially oxidase succinate.MethodsNeonatal mice were subjected to Rice-Vannucci model of hypoxic-ischemic brain injury (HI) followed by assessment of Krebs cycle metabolites, mitochondrial substrate preference, and H2O2 generation rate in the ischemic brain.ResultsWhile brain mitochondria from control mice exhibited a rotenone-sensitive complex-I-dependent respiration, HI-brain mitochondria, at the initiation of reperfusion, demonstrated complex-II-dependent respiration, as rotenone minimally affected, but inhibition of complex-II ceased respiration. This was associated with a 30-fold increase of cerebral succinate concentration and significantly elevated H2O2 emission rate in HI-mice compared to controls. At 60 min of reperfusion, cerebral succinate content and the mitochondrial response to rotenone did not differ from that in controls.ConclusionThese data are the first ex vivo evidence, that at the initiation of reperfusion, brain mitochondria transiently shift their metabolism from complex-I-dependent oxidation of NADH toward complex II-linked oxidation of succinate. Our study provides a critical piece of support for existence of the RET-dependent mechanism of elevated ROS production in reperfusion.

Potential mechanisms linking SIRT activity and hypoxic 2-hydroxyglutarate generation: no role for direct enzyme (de)acetylation.

2-Hydroxyglutarate (2-HG) is a hypoxic metabolite with potentially important epigenetic signaling roles. The mechanisms underlying 2-HG generation are poorly understood, but evidence suggests a potential regulatory role for the sirtuin family of lysine deacetylases. Thus, we hypothesized that the acetylation status of the major 2-HG-generating enzymes [lactate dehydrogenase (LDH), isocitrate dehydrogenase (IDH) and malate dehydrogenase (MDH)] may govern their 2-HG-generating activity. In vitro acetylation of these enzymes, with confirmation by western blotting, mass spectrometry, reversibility by recombinant sirtuins and an assay for global lysine occupancy, yielded no effect on 2-HG-generating activity. In addition, while elevated 2-HG in hypoxia is associated with the activation of lysine deacetylases, we found that mice lacking mitochondrial SIRT3 exhibited hyperacetylation and elevated 2-HG. These data suggest that there is no direct link between enzyme acetylation and 2-HG production. Furthermore, our observed effects of in vitro acetylation on the canonical activities of IDH, MDH and LDH appeared to contrast with previous findings wherein acetyl-mimetic lysine mutations resulted in the inhibition of these enzymes. Overall, these data suggest that a causal relationship should not be assumed between acetylation of metabolic enzymes and their activities, canonical or otherwise.

Characterization of the trigeminovascular actions of several adenosine A2A receptor antagonists in an in vivo rat model of migraine.

BACKGROUND: Migraine is considered a neurovascular disorder, but its pathophysiological mechanisms are not yet fully understood. Adenosine has been shown to increase in plasma during migraine attacks and to induce vasodilation in several blood vessels; however, it remains unknown whether adenosine can interact with the trigeminovascular system. Moreover, caffeine, a non-selective adenosine receptor antagonist, is included in many over the counter anti-headache/migraine treatments. METHODS: This study used the rat closed cranial window method to investigate in vivo the effects of the adenosine A2A receptor antagonists with varying selectivity over A1 receptors; JNJ-39928122, JNJ-40529749, JNJ-41942914, JNJ-40064440 or JNJ-41501798 (0.3-10 mg/kg) on the vasodilation of the middle meningeal artery produced by either CGS21680 (an adenosine A2A receptor agonist) or endogenous CGRP (released by periarterial electrical stimulation). RESULTS: Regarding the dural meningeal vasodilation produced neurogenically or pharmacologically, all JNJ antagonists: (i) did not affect neurogenic vasodilation but (ii) blocked the vasodilation produced by CGS21680, with a blocking potency directly related to their additional affinity for the adenosine A1 receptor. CONCLUSIONS: These results suggest that vascular adenosine A2A (and, to a certain extent, also A1) receptors mediate the CGS21680-induced meningeal vasodilation. These receptors do not appear to modulate prejunctionally the sensory release of CGRP. Prevention of meningeal arterial dilation might be predictive for anti-migraine drugs, and since none of these JNJ antagonists modified per se blood pressure, selective A2A receptor antagonism may offer a novel approach to antimigraine therapy which remains to be investigated in clinical trials.

The cardioprotective compound cloxyquin uncouples mitochondria and induces autophagy.

Mitochondrial quality control mechanisms have been implicated in protection against cardiac ischemia-reperfusion (IR) injury. Previously, cloxyquin (5-chloroquinolin-8-ol) was identified via phenotypic screening as a cardioprotective compound. Herein, cloxyquin was identified as a mitochondrial uncoupler in both isolated heart mitochondria and adult cardiomyocytes. Additionally, cardiomyocytes isolated from transgenic mice expressing green fluorescent protein-tagged microtubule-associated protein light chain 3 showed increased autophagosome formation with cloxyquin treatment. The autophagy inhibitor chloroquine abolished cloxyquin-induced cardioprotection in both cellular and perfused heart (Langendorff) models of IR injury. Finally, in an in vivo murine left anterior descending coronary artery occlusion model of IR injury, cloxyquin significantly reduced infarct size from 31.4 ± 3.4% to 16.1 ± 2.2%. In conclusion, the cardioprotective compound cloxyquin simultaneously uncoupled mitochondria and induced autophagy. Importantly, autophagy appears to be required for cloxyquin-induced cardioprotection.

Metabolomic profiling of the heart during acute ischemic preconditioning reveals a role for SIRT1 in rapid cardioprotective metabolic adaptation.

Ischemic preconditioning (IPC) protects tissues such as the heart from prolonged ischemia-reperfusion (IR) injury. We previously showed that the lysine deacetylase SIRT1 is required for acute IPC, and has numerous metabolic targets. While it is known that metabolism is altered during IPC, the underlying metabolic regulatory mechanisms are unknown, including the relative importance of SIRT1. Thus, we sought to test the hypothesis that some of the metabolic adaptations that occur in IPC may require SIRT1 as a regulatory mediator. Using both ex-vivo-perfused and in-vivo mouse hearts, LC-MS/MS based metabolomics and (13)C-labeled substrate tracing, we found that acute IPC altered several metabolic pathways including: (i) stimulation of glycolysis, (ii) increased synthesis of glycogen and several amino acids, (iii) increased reduced glutathione levels, (iv) elevation in the oncometabolite 2-hydroxyglutarate, and (v) inhibition of fatty-acid dependent respiration. The majority (83%) of metabolic alterations induced by IPC were ablated when SIRT1 was acutely inhibited with splitomicin, and a principal component analysis revealed that metabolic changes in response to IPC were fundamentally different in nature when SIRT1 was inhibited. Furthermore, the protective benefit of IPC was abrogated by eliminating glucose from perfusion media while sustaining normal cardiac function by burning fat, thus indicating that glucose dependency is required for acute IPC. Together, these data suggest that SIRT1 signaling is required for rapid cardioprotective metabolic adaptation in acute IPC.

Clinical correlates in an experimental model of repetitive mild brain injury.

OBJECTIVE: Although there is growing awareness of the long-term cognitive effects of repetitive mild traumatic brain injury (rmTBI; eg, sports concussions), whether repeated concussions cause long-term cognitive deficits remains controversial. Moreover, whether cognitive deficits depend on increased amyloid ß deposition and tau phosphorylation or are worsened by the apolipoprotein E4 allele remains unknown. Here, we use an experimental model of rmTBI to address these clinical controversies. METHODS: A weight drop rmTBI model was used that results in cognitive deficits without loss of consciousness, seizures, or gross or microscopic evidence of brain damage. Cognitive function was assessed using a Morris water maze (MWM) paradigm. Immunostaining and enzyme-linked immunosorbent assay (ELISA) were used to assess amyloid ß deposition and tau hyperphosphorylation. Brain volume and white matter integrity were assessed by magnetic resonance imaging (MRI). RESULTS: Mice subjected to rmTBI daily or weekly but not biweekly or monthly had persistent cognitive deficits as long as 1 year after injuries. Long-term cognitive deficits were associated with increased astrocytosis but not tau phosphorylation or amyloid ß (by ELISA); plaques or tangles (by immunohistochemistry); or brain volume loss or changes in white matter integrity (by MRI). APOE4 was not associated with worse MWM performance after rmTBI. INTERPRETATION: Within the vulnerable time period between injuries, rmTBI produces long-term cognitive deficits independent of increased amyloid ß or tau phosphorylation. In this model, cognitive outcome is not influenced by APOE4 status. The data have implications for the long-term mental health of athletes who suffer multiple concussions.

Derivation and internal validation of the multivariate toxigenic C. difficile diarrhea model and risk score for emergency room and hospitalized patients with diarrhea.

Background: Many factors have been associated with the risk of toxigenic C. difficile diarrhea (TCdD). This study derived and internally validated a multivariate model for estimating the risk of TCdD in patients with diarrhea using readily available clinical factors. Methods: A random sample of 3,050 symptomatic emergency department or hospitalized patients undergoing testing for toxigenic C. difficile at a single teaching hospital between 2014 and 2018 was created. Unformed stool samples positive for both glutamate dehydrogenase antigen by enzyme immunoassay and tcdB gene by polymerase chain reaction were classified as TCdD positive. The TCdD Model was created using logistic regression and was modified to the TCdD Risk Score to facilitate its use. Results: 8.1% of patients were TCdD positive. TCdD risk increased with abdominal pain (adjusted odds ratio 1.3; 95% CI, 1.0-1.8), previous C. difficile diarrhea (2.5, 1.1-6.1), and prior antibiotic exposure, especially when sampled in the emergency department (4.2, 2.5-7.0) versus the hospital (1.7, 1.3-2.3). TCdD risk also increased when testing occurred earlier during the hospitalization encounter, when age and white cell count increased concurrently, and with decreased eosinophil count. In internal validation, the TCdD Model had moderate discrimination (optimism-corrected C-statistic 0.65, 0.62-0.68) and good calibration (optimism-corrected Integrated Calibration Index [ICI] 0.017, 0.001-0.022). Performance decreased slightly for the TCdD Risk Score (C-statistic 0.63, 0.62-0.63; ICI 0.038, 0.004-0.038). Conclusions: TCdD risk can be predicted using readily available clinical risk factors with modest accuracy.

Machine learning models identify predictive features of patient mortality across dementia types.

BACKGROUND: Dementia care is challenging due to the divergent trajectories in disease progression and outcomes. Predictive models are needed to flag patients at risk of near-term mortality and identify factors contributing to mortality risk across different dementia types. METHODS: Here, we developed machine-learning models predicting dementia patient mortality at four different survival thresholds using a dataset of 45,275 unique participants and 163,782 visit records from the U.S. National Alzheimer's Coordinating Center (NACC). We built multi-factorial XGBoost models using a small set of mortality predictors and conducted stratified analyses with dementiatype-specific models. RESULTS: Our models achieved an area under the receiver operating characteristic curve (AUC-ROC) of over 0.82 utilizing nine parsimonious features for all 1-, 3-, 5-, and 10-year thresholds. The trained models mainly consisted of dementia-related predictors such as specific neuropsychological tests and were minimally affected by other age-related causes of death, e.g., stroke and cardiovascular conditions. Notably, stratified analyses revealed shared and distinct predictors of mortality across eight dementia types. Unsupervised clustering of mortality predictors grouped vascular dementia with depression and Lewy body dementia with frontotemporal lobar dementia. CONCLUSIONS: This study demonstrates the feasibility of flagging dementia patients at risk of mortality for personalized clinical management. Parsimonious machine-learning models can be used to predict dementia patient mortality with a limited set of clinical features, and dementiatype-specific models can be applied to heterogeneous dementia patient populations.

Dementia has emerged as a major cause of death in societies with increasingly aging populations. However, predicting the exact timing of death in dementia cases is challenging, due to variations in the gradual process where cognitive decline interferes with the body's normal functions. In our study, we build machine-learning models to predict whether a patient diagnosed with dementia will survive or die within 1, 3, 5, or 10 years. We found that the prediction models can work well across patients from different parts of the US and across patients with different types of dementia. The key predictive factor was the information that is already used to diagnose and stage dementia, such as the results of memory tests. Interestingly, broader risk factors related to other causes of death, such as heart conditions, were less significant for predicting death in dementia patients. The ability of these models to identify dementia patients at a heightened risk of mortality could aid clinical practices, potentially allowing for earlier interventions and tailored treatment strategies to improve patient outcomes.

Beneficial effect of amyloid beta after controlled cortical impact.

BACKGROUND: Worse functional outcomes after controlled cortical impact (CCI) in Bace1(-/-) mice have previously been demonstrated. This study investigated whether reconstitution of amyloid-beta (Aß) after CCI in Bace1(-/-) animals would reverse the detrimental effect of Bace1 deletion. METHODS: Bace1(-/-) and wild type Bace1(+/+) (C57Bl/6) mice were subjected to CCI (n = 14-23/group) or sham injury (n = 6/group). After injury, mice underwent intracerebroventricular injections of Aß40 (n = 23 Bace1(-/-) and 17 Bace1(+/+) per group) or vehicle (n = 14 Bace1(-/-) and 22 Bace1(+/+) per group). Functional outcomes were assessed with wire grip (motor) and Morris water maze (spatial memory). Soluble Aß levels were assessed at 24 hours and 21 days after CCI. Lesion volume was assessed 21 days after injury. RESULTS: At 24 hours after injury, Aß-treated Bace1(-/-) mice had Aß40 levels similar to vehicle-treated Bace1(+/+) mice, but by 21 days after injury there were no differences between Aß-treated versus vehicle-treated Bace1(-/-) mice. Reconstitution with Aß40 improved motor but not spatial memory or histopathological outcome in injured Bace1(-/-) mice. In contrast, treatment with Aß40 worsened motor performance in Bace1(+/+) mice. CONCLUSIONS: The data suggest Aß40 may have some beneficial effects after CCI in young adult mice and that therapies targeting BACE should be approached cautiously.

Predictive Models and Features of Patient Mortality across Dementia Types.

Dementia care is challenging due to the divergent trajectories in disease progression and outcomes. Predictive models are needed to identify patients at risk of near-term mortality. Here, we developed machine learning models predicting survival using a dataset of 45,275 unique participants and 163,782 visit records from the U.S. National Alzheimer's Coordinating Center (NACC). Our models achieved an AUC-ROC of over 0.82 utilizing nine parsimonious features for all one-, three-, five-, and ten-year thresholds. The trained models mainly consisted of dementia-related predictors such as specific neuropsychological tests and were minimally affected by other age-related causes of death, e.g., stroke and cardiovascular conditions. Notably, stratified analyses revealed shared and distinct predictors of mortality across eight dementia types. Unsupervised clustering of mortality predictors grouped vascular dementia with depression and Lewy body dementia with frontotemporal lobar dementia. This study demonstrates the feasibility of flagging dementia patients at risk of mortality for personalized clinical management.

Consecutive treatments of methamphetamine promote the development of cardiac pathological symptoms in zebrafish.

Chronic methamphetamine use, a widespread drug epidemic, has been associated with cardiac morphological and electrical remodeling, leading to the development of numerous cardiovascular diseases. While methamphetamine has been documented to induce arrhythmia, most results originate from clinical trials from users who experienced different durations of methamphetamine abuse, providing no documentation on the use of methamphetamine in standardized settings. Additionally, the underlying molecular mechanism on how methamphetamine affects the cardiovascular system remains elusive. A relationship was sought between cardiotoxicity and arrhythmia with associated methamphetamine abuse in zebrafish to identify and to understand the adverse cardiac symptoms associated with methamphetamine. Zebrafish were first treated with methamphetamine 3 times a week over a 2-week duration. Immediately after treatment, zebrafish underwent electrocardiogram (ECG) measurement using an in-house developed acquisition system for electrophysiological analysis. Subsequent analyses of cAMP expression and Ca2+ regulation in zebrafish cardiomyocytes were conducted. cAMP is vital to development of myocardial fibrosis and arrhythmia, prominent symptoms in the development of cardiovascular diseases. Ca2+ dysregulation is also a factor in inducing arrhythmias. During the first week of treatment, zebrafish that were administered with methamphetamine displayed a decrease in heart rate, which persisted throughout the second week and remained significantly lower than the heart rate of untreated fish. Results also indicate an increased heart rate variability during the early stage of treatment followed by a decrease in the late stage for methamphetamine-treated fish over the duration of the experiment, suggesting a biphasic response to methamphetamine exposure. Methamphetamine-treated fish also exhibited reduced QTc intervals throughout the experiment. Results from the cAMP and Ca2+ assays demonstrate that cAMP was upregulated and Ca2+ was dysregulated in response to methamphetamine treatment. Collagenic assays indicated significant fibrotic response to methamphetamine treatment. These results provide potential insight into the role of methamphetamine in the development of fibrosis and arrhythmia due to downstream effectors of cAMP.

Microelectrode array membranes to simultaneously assess cardiac and neurological signals of xenopus laevis under chemical exposures and environmental changes.

Simultaneous monitoring of electrocardiogram (ECG) and electroencephalogram (EEG) in studied animal models requires innovative engineering techniques that can capture minute physiological changes. However, this is often administered with a bulky and/or invasive system that may cause discomfort to animals and signal distortions. Here, we develop an integrated bioelectronic sensing system to provide simultaneous recordings of ECG and EEG in real-time for Xenopus laevis. The microelectrode array (MEA) membrane and the distinct anatomy of Xenopus offer noninvasive multi-modal electrophysiological monitoring with favorable spatial resolution. The system was validated under different environmental conditions, including drug exposure and temperature changes. Under the exposure of Pentylenetetrazol (PTZ), an epilepsy-inducing drug, clear ECG and EEG alterations, including frequent ictal and interictal EEG events, 30 dB average EEG amplitude elevations, abnormal ECG morphology, and heart rate changes, were observed. Furthermore, the ECG and EEG were monitored and analyzed under different temperatures. A decrease in relative power of delta band was observed when cold environment was brought about, in contrast to an increase in relative power of other higher frequency bands while the ECG remained stable. Overall, the real-time electrophysiology monitoring system using the Xenopus model holds potential for many applications in drug screening and remote environmental monitoring.

A novel wireless ECG system for prolonged monitoring of multiple zebrafish for heart disease and drug screening studies.

Zebrafish and their mutant lines have been extensively used in cardiovascular studies. In the current study, the novel system, Zebra II, is presented for prolonged electrocardiogram (ECG) acquisition and analysis for multiple zebrafish within controllable working environments. The Zebra II is composed of a perfusion system, apparatuses, sensors, and an in-house electronic system. First, the Zebra II is validated in comparison with a benchmark system, namely iWORX, through various experiments. The validation displayed comparable results in terms of data quality and ECG changes in response to drug treatment. The effects of anesthetic drugs and temperature variation on zebrafish ECG were subsequently investigated in experiments that need real-time data assessment. The Zebra II's capability of continuous anesthetic administration enabled prolonged ECG acquisition up to 1 h compared to that of 5 min in existing systems. The novel, cloud-based, automated analysis with data obtained from four fish further provided a useful solution for combinatorial experiments and helped save significant time and effort. The system showed robust ECG acquisition and analytics for various applications including arrhythmia in sodium induced sinus arrest, temperature-induced heart rate variation, and drug-induced arrhythmia in Tg(SCN5A-D1275N) mutant and wildtype fish. The multiple channel acquisition also enabled the implementation of randomized controlled trials on zebrafish models. The developed ECG system holds promise and solves current drawbacks in order to greatly accelerate drug screening applications and other cardiovascular studies using zebrafish.

Rhythm-Monitoring Strategy and Arrhythmia Recurrence in Atrial Fibrillation Ablation Trials: A Systematic Review.

Background: : The rhythm-monitoring strategy after catheter ablation (CA) for atrial fibrillation (AF) impacts the detection of atrial arrhythmia recurrence and is not well characterized. We performed a systematic review and meta-regression analysis to determine whether the duration and mode of rhythm monitoring after CA affects detection of atrial arrhythmia recurrence. Methods: Databases were systematically searched for randomized controlled trials of adult patients undergoing first CA for AF from 2007 to 2021. Duration and strategy of rhythm monitoring were extracted. Meta-regression was used to identify any association between duration of monitoring and detection of atrial arrhythmia recurrence. The primary measure of outcome was single-procedure recurrence of atrial arrhythmia. Results: The search strategy yielded 57 trial arms from 56 randomized controlled trials comprising 5322 patients: 36 arms of patients with paroxysmal AF (PAF), and 21 arms of patients with persistent AF (PeAF) or both PAF/PeAF. Intermittent monitoring was associated with detection of significantly less atrial arrhythmia recurrence than continuous monitoring in PAF arms (31.2% vs 46.9%, P = 0.001), but not in PeAF/PAF-PeAF combined arms (43.3% vs 63.6%, P = 0.12). No significant relationship was seen between the duration of intermittent rhythm monitoring and atrial arrhythmia recurrence detection in either the PAF (P = 0.93) or PeAF/PAF-PeAF combined arms (P = 0.20). Conclusions: Continuous rhythm monitoring detected higher atrial arrhythmia recurrence rates, compared to intermittent rhythm monitoring, in patients with PAF. The duration of intermittent monitoring did not show a statistically significant relationship to the yield of arrhythmia detection, in near identical cohorts of trial subjects undergoing similar interventions, with clinical and research implications.

Contexte: La stratégie qui consiste à surveiller le rythme cardiaque après une ablation par cathéter dans le traitement de la fibrillation auriculaire (FA) a un effet sur la détection de récidive de l'arythmie auriculaire, mais elle n'est pas bien définie. Nous avons mené une revue systématique et une méta-régression pour déterminer si le mode employé pour surveiller le rythme après une ablation par cathéter et la durée de cette surveillance ont un effet sur la détection de récidive de l'arythmie auriculaire. Méthodologie: Des bases de données ont été systématiquement épluchées à la recherche d'essais contrôlés randomisés menés auprès d'adultes subissant leur première ablation par cathéter pour une FA entre 2007 et 2021. La durée et la stratégie utilisées dans la surveillance du rythme ont été recensées. La méta-régression a été utilisée pour déceler tout lien entre la durée de la surveillance et la détection d'une récidive de l'arythmie auriculaire. Le paramètre d'évaluation principal était la récidive de l'arythmie auriculaire avec une seule intervention. Résultats: La stratégie de recherche a fait ressortir 57 groupes de 56 essais contrôlés randomisés comprenant 5 322 patients : 36 groupes de patients présentant une FA paroxystique et 21 groupes de patients présentant une FA persistante ou ces deux types de FA (paroxystique et persistante). La surveillance intermittente a été associée à une moins grande détection de cas d'arythmie auriculaire récidivante, comparativement à la surveillance constante (31,2 % vs 46,9 %, p = 0,001), ce qui n'a pas été le cas dans les groupes où les types de FA (persistante ou paroxystique et persistante) étaient combinés (43,3 % vs 63,6 %, p = 0,12). Aucun lien notable n'a été observé entre la durée de la surveillance intermittente du rythme et la détection de l'arythmie auriculaire récidivante dans le groupe FA paroxystique (p = 0,93) ou dans le groupe des types de FA combinés (p = 0,20). Conclusions: Le taux de détection de l'arythmie auriculaire récidivante était plus élevé avec la surveillance constante qu'avec la surveillance intermittente chez les patients atteints de FA paroxystique. La durée de la surveillance intermittente n'a pas eu de lien statistiquement significatif avec le rendement de détection de l'arythmie, dans des cohortes presque identiques de participants aux essais subissant des interventions similaires, comportant des implications cliniques ou expérimentales.

The polypyrimidine tract binding protein regulates desaturase alternative splicing and PUFA composition.

The Δ6 desaturase, encoded by FADS2, plays a crucial role in omega-3 and omega-6 fatty acid synthesis. These fatty acids are essential components of the central nervous system, and they act as precursors for eicosanoid signaling molecules and as direct modulators of gene expression. The polypyrimidine tract binding protein (PTB or hnRNP I) is a splicing factor that regulates alternative pre-mRNA splicing. Here, PTB is shown to bind an exonic splicing silencer element and repress alternative splicing of FADS2 into FADS2 AT1. PTB and FADS2AT1 were inversely correlated in neonatal baboon tissues, implicating PTB as a major regulator of tissue-specific FADS2 splicing. In HepG2 cells, PTB knockdown modulated alternative splicing of FADS2, as well as FADS3, a putative desaturase of unknown function. Omega-3 fatty acids decreased by nearly one half relative to omega-6 fatty acids in PTB knockdown cells compared with controls, with a particularly strong decrease in eicosapentaenoic acid (EPA) concentration and its ratio to arachidonic acid (ARA). This is a rare demonstration of a mechanism specifically altering the cellular omega-3 to omega-6 fatty acid ratio without any change in diet/media. These findings reveal a novel role for PTB, regulating availability of membrane components and eicosanoid precursors for cell signaling.

Prediction of individual COVID-19 diagnosis using baseline demographics and lab data.

The global surge in COVID-19 cases underscores the need for fast, scalable, and reliable testing. Current COVID-19 diagnostic tests are limited by turnaround time, limited availability, or occasional false findings. Here, we developed a machine learning-based framework for predicting individual COVID-19 positive diagnosis relying only on readily-available baseline data, including patient demographics, comorbidities, and common lab values. Leveraging a cohort of 31,739 adults within an academic health system, we trained and tested multiple types of machine learning models, achieving an area under the curve of 0.75. Feature importance analyses highlighted serum calcium levels, temperature, age, lymphocyte count, smoking, hemoglobin levels, aspartate aminotransferase levels, and oxygen saturation as key predictors. Additionally, we developed a single decision tree model that provided an operable method for stratifying sub-populations. Overall, this study provides a proof-of-concept that COVID-19 diagnosis prediction models can be developed using only baseline data. The resulting prediction can complement existing tests to enhance screening and pandemic containment workflows.