Deep neural networks detect regional wall motion abnormalities and preclinical cardiovascular disease from 12-lead ECGs.

Background: Identifying regional wall motion abnormalities (RWMAs) is critical for diagnosing and risk stratifying patients with cardiovascular disease, particularly ischemic heart disease. We hypothesized that a deep neural network could accurately identify patients with regional wall motion abnormalities from a readily available standard 12-lead electrocardiogram (ECG). Methods: This observational, retrospective study included patients who were treated at Beth Israel Deaconess Medical Center and had an ECG and echocardiogram performed within 14 days of each other between 2008 and 2019. We trained a convolutional neural network to detect the presence of RWMAs, qualitative global right ventricular (RV) hypokinesis, and varying degrees of left ventricular dysfunction (left ventricular ejection fraction [LVEF] ≤50%, LVEF ≤40%, and LVEF ≤35%) identified by echocardiography, using ECG data alone. Patients were randomly split into development (80%) and test sets (20%). Model performance was assessed using area under the receiver operating characteristic curve (AUC). Cox proportional hazard models adjusted for age and sex were performed to estimate the risk of future acute coronary events. Results: The development set consisted of 19,837 patients (mean age 66.7±16.4; 46.7% female) and the test set comprised of 4,953 patients (mean age 67.5±15.8 years; 46.5% female). On the test dataset, the model accurately identified the presence of RWMA, RV hypokinesis, LVEF ≤50%, LVEF ≤40%, and LVEF ≤35% with AUCs of 0.87 (95% CI 0.858-0.882), 0.888 (95% CI 0.878-0.899), 0.923 (95% CI 0.914-0.933), 0.93 (95% CI 0.921-0.939), and 0.876 (95% CI 0.858-0.896), respectively. Among patients with normal biventricular function at the time of the index ECG, those classified as having RMWA by the model were 3 times the risk (age- and sex-adjusted hazard ratio, 2.8; 95% CI 1.9-3.9) for future acute coronary events compared to those classified as negative. Conclusions: We demonstrate that a deep neural network can help identify regional wall motion abnormalities and reduced LV function from a 12-lead ECG and could potentially be used as a screening tool for triaging patients who need either initial or repeat echocardiographic imaging.

Maternal stress and breastfeeding outcomes in the NICU couplet care experience: a prospective cohort study.

OBJECTIVE: Couplet care is an innovative approach to provide postpartum care in the neonatal intensive care unit (NICU) with little known about its impact on infant feeding outcomes and maternal stress. STUDY DESIGN: We compared breastfeeding outcomes and maternal NICU-related stress among mother-infant dyads based on exposure to couplet care in a prospective cohort study. RESULT: Among 19 couplet-care exposed (CCE) dyads and 19 traditional postpartum care dyads, CCE mothers had lower self-reported stress related to parent-infant relationship as compared to traditional care (P < 0.001). CCE infants received relatively more feeds at the breast (P < 0.001), more breastmilk feeds (P = 0.002), and fewer feeds by staff (P < 0.001). Adjusted for gestational age, marital status, and infant length of stay, couplet care was associated with being in a higher tertile of percent breastmilk feeds (aOR 7.29, 95% CI 1.45-36.65). CONCLUSION: NICU couplet care was associated with improved parental stress and breastfeeding outcomes during hospitalization.

Clinical validation of an artificial intelligence algorithm offering cross-platform detection of atrial fibrillation using smart device electrocardiograms.

BACKGROUND: Several smart devices are able to detect atrial fibrillation automatically by recording a single-lead electrocardiogram, and have created a work overload at the hospital level as a result of the need for over-reads by physicians. AIM: To compare the atrial fibrillation detection performances of the manufacturers' algorithms of five smart devices and a novel deep neural network-based algorithm. METHODS: We compared the rate of inconclusive tracings and the diagnostic accuracy for the detection of atrial fibrillation between the manufacturers' algorithms and the deep neural network-based algorithm on five smart devices, using a physician-interpreted 12-lead electrocardiogram as the reference standard. RESULTS: Of the 117 patients (27% female, median age 65 years, atrial fibrillation present at time of recording in 30%) included in the final analysis (resulting in 585 analyzed single-lead electrocardiogram tracings), the deep neural network-based algorithm exhibited a higher conclusive rate relative to the manufacturer algorithm for all five models: 98% vs. 84% for Apple; 99% vs. 81% for Fitbit; 96% vs. 77% for AliveCor; 99% vs. 85% for Samsung; and 97% vs. 74% for Withings (P<0.01, for each model). When applying our deep neural network-based algorithm, sensitivity and specificity to correctly identify atrial fibrillation were not significantly different for all assessed smart devices. CONCLUSION: In this clinical validation, the deep neural network-based algorithm significantly reduced the number of tracings labeled inconclusive, while demonstrating similarly high diagnostic accuracy for the detection of atrial fibrillation, thereby providing a possible solution to the data surge created by these smart devices.

Evaluation of the transverse venous sinus with transcranial color-coded duplex.

BACKGROUND AND PURPOSE: Ultrasound-derived diagnosis of transverse venous sinus stenosis (TVSS) may have a promise given recent exploration of its role in pathophysiology of intracranial hypertension and availability of interventions like venous stenting. We investigated transverse venous sinus (TVS) insonation using transcranial color-coded duplex (TCCD) to establish normative values, inform on inherent physiological variability, and other measures to allow future studies on testing the construct validity of TCCD venous in diagnosing TVSS. METHODS: An institutional review board-approved prospective observational study evaluated 20 healthy volunteers to define TCCD-based measures for the TVS. Comparatively, the basal vein of Rosenthal, deep middle cerebral veins, and internal jugular veins were insonated. We report on physiological variability including the intrasubject, intersubject, and side-to-side variability; gradient of TVS velocities on each side from medial to lateral insonation; and the relationship between TVS and other insonated venous structures. RESULTS: Fifteen out of 20 subjects had the TVS insonated bilaterally, and five had unilaterally (four right, one left). TVS velocities had comparable intrasubject variability to other intracranial veins insonated and lower velocity-based variability than the pulsatility index. There was significant side-side variability in TVS-derived measures without discernible patterns. Insonating TVS from medial to lateral revealed a gradient with a bimodal peak in ultrasound-derived velocities. We did not find discernible relationships between TVS and other veins for TCCD-derived measures. CONCLUSIONS: These results can inform future studies validating the normative values in a larger sample and help explore the role of TCCD venous in the diagnosis of venous sinus stenosis.

Evaluation of an Ambulatory ECG Analysis Platform Using Deep Neural Networks in Routine Clinical Practice.

Background Holter analysis requires significant clinical resources to achieve a high-quality diagnosis. This study sought to assess whether an artificial intelligence (AI)-based Holter analysis platform using deep neural networks is noninferior to a conventional one used in clinical routine in detecting a major rhythm abnormality. Methods and Results A total of 1000 Holter (24-hour) recordings were collected from 3 tertiary hospitals. Recordings were independently analyzed by cardiologists for the AI-based platform and by electrophysiologists as part of clinical practice for the conventional platform. For each Holter, diagnostic performance was evaluated and compared through the analysis of the presence or absence of 5 predefined cardiac abnormalities: pauses, ventricular tachycardia, atrial fibrillation/flutter/tachycardia, high-grade atrioventricular block, and high burden of premature ventricular complex (>10%). Analysis duration was monitored. The deep neural network-based platform was noninferior to the conventional one in its ability to detect a major rhythm abnormality. There were no statistically significant differences between AI-based and classical platforms regarding the sensitivity and specificity to detect the predefined abnormalities except for atrial fibrillation and ventricular tachycardia (atrial fibrillation, 0.98 versus 0.91 and 0.98 versus 1.00; pause, 0.95 versus 1.00 and 1.00 versus 1. 00; premature ventricular contractions, 0.96 versus 0.87 and 1.00 versus 1.00; ventricular tachycardia, 0.97 versus 0.68 and 0.99 versus 1.00; atrioventricular block, 0.93 versus 0.57 and 0.99 versus 1.00). The AI-based analysis was >25% faster than the conventional one (4.4 versus 6.0 minutes; P<0.001). Conclusions These preliminary findings suggest that an AI-based strategy for the analysis of Holter recordings is faster and at least as accurate as a conventional analysis by electrophysiologists.

Short-term prediction of atrial fibrillation from ambulatory monitoring ECG using a deep neural network.

Aims: Atrial fibrillation (AF) is associated with significant morbidity but remains underdiagnosed. A 24 h ambulatory electrocardiogram (ECG) is largely used as a tool to document AF but yield remains limited. We hypothesize that a deep learning model can identify patients at risk of AF in the 2 weeks following a 24 h ambulatory ECG with no documented AF. Methods and results: We identified a training set of Holter recordings of 7-15 days duration, in which no AF could be found in the first 24 h. We trained a neural network to predict the presence or absence of AF in the 15 following days, using only the first 24 h of the recording. We evaluated the neural network on a testing set and an external data set not used during algorithm development. In the testing data set, out of 9993 Holters with no AF on the first day, we found 361 (4%) recordings with AF within the 15 subsequent days of monitoring [5808, 218 (4%), respectively in the external data set]. The neural network could discriminate future AF with an area under the receiver operating curve, a sensitivity, and specificity of 79.4%, 76%, and 69%, respectively (75.8%, 78%, and 58% in the external data set), and outperformed ECG features previously shown to be predictive of AF. Conclusion: We show here the very first study of short-term AF prediction using 24 h Holter monitoring. This could help identify patients who would benefit the most from longer recordings and proactively initiate treatment and AF mitigation strategies in high-risk patients.

AI Filter Improves Positive Predictive Value of Atrial Fibrillation Detection by an Implantable Loop Recorder.

OBJECTIVES: The purpose of this study was to determine whether incorporation of a 2-part artificial intelligence (AI) filter can improve the positive predictive value (PPV) of implantable loop recorder (ILR)-detected atrial fibrillation (AF) episodes. BACKGROUND: ILRs can detect AF. Devices transmit data daily. It is critical that the PPV of ILR-detected AF events be high. METHODS: In total, 1,500 AF episodes were evaluated from patients with cryptogenic stroke or known AF who underwent ILR implantation (Reveal LINQ, Medtronic, Minneapolis, Minnesota). Each episode was annotated as either a true or false AF episode to determine the PPV. A 2-part AI-based filter (Cardiologs, Paris, France) was then employed using a deep neural network (DNN) for AF detection. The impact of this DNN filter on the PPV was then assessed. RESULTS: The cohort included 425 patients (mean age 69 ± 10 years; 62% men) with an ILR. After excluding 17 (1.1%) uninterpretable electrocardiograms, 800 (53.9%) of the remaining 1,483 episodes were manually adjudicated to represent an actual atrial arrhythmia. The PPV of ILR-detected AF episodes was 53.9% (95% confidence interval (CI): 51.4% to 56.5%), which increased to 74.5% (95% CI: 71.8% to 77.0%; p < 0.001) following use of the DNN filter. The increase was greatest for AF episodes ≤30 min. The most common reason for a false-positive AF event was premature atrial contractions. There was a negligible failure to identify true AF episodes. CONCLUSIONS: Despite currently available ILR programming options, designed to maximize PPV in a given population, false-positive AF episodes remain common. An AI-based solution may significantly reduce the time and effort needed to adjudicate these false-positive events.

Reliability of parylene-based multi-electrode arrays chronically implanted in adult rat brains, and evidence of electrical stimulation on contact impedance.

OBJECTIVE: The goal of this study was to evaluate the long-term behavior of the surface electrode through electrochemical characterization and follow-up of implanted parylene/platinum microelectrodes. APPROACH: To this aim, we designed and manufactured specific planar electrodes for cortical implantation for a rat model. This work was included in the INTENSE® project, one of the goals of which was to prove the feasibility of selective neural recording or stimulation with cuff electrodes around the vagus nerve. MAIN RESULTS: After a 12-week implantation in a rat model, we can report that these microelectrodes have withstood in vivo use. Regarding the biocompatibility of the electrodes (materials and manufacturing process), no adverse effect was reported. Indeed, after the three-month implantation, we characterized limited tissue reaction beneath the electrodes and showed an increase and a stabilization of their impedance. Interestingly, the follow-up of the electrochemical impedance combined with electrical stimulation highlighted a drop in the impedance up to 60% at 1 kHz after ten minutes of electrical stimulation at 110 Hz. SIGNIFICANCE: This study gives evidence of the biocompatibility of the parylene platinum contact array designed for the project and confirms the effect of stimulation on the contact impedance.

Chronic abdominal vagus stimulation increased brain metabolic connectivity, reduced striatal dopamine transporter and increased mid-brain serotonin transporter in obese miniature pigs.

BACKGROUND/OBJECTIVE: Changes in brain metabolism has been investigated thoroughly during unilateral cervical chronic vagal stimulation in epileptic or depressive patients. Bilateral stimulation of the abdominal vagus (aVNS) has received less attention despite the reduction in body weight and an altered feeding behavior in obese animals that could be clinically relevant in obese individuals. Our study aims to examine the changes in brain glucose metabolism (CMRglu) induced by aVNS in obese adult miniature pigs. Dopamine (DAT) and serotonin transporters (SERT) were also quantified to further understand the molecular origins of the alterations in brain metabolism. SUBJECTS/METHODS: Pairs of stimulating electrodes were implanted during laparoscopy on both abdominal vagal trunks in 20 obese adult's miniature pigs. Half of the animals were permanently stimulated while the remaining were sham stimulated. Two months after the onset of stimulation, dynamic 18FDG PET and 123I-ioflupane SPECT were performed. Food intake, resting energy expenditure and fat deposition were also assessed longitudinally. RESULTS: Food intake was halved and resting energy expenditure was increased by 60% in aVNS group compared to sham. The gain in body weight was also 38% less in aVNS group compared to sham. Brain metabolic connectivity increased between numerous structures including striatum, mid-brain, amygdala and hippocampus. On the contrary, increased CMRglu were restricted to the thalamus, the periaqueducal grey and the amygdala. DAT binding potential was decreased by about one third in the striatum while SERT was about doubled in the midbrain. CONCLUSIONS: Our findings demonstrated that aVNS reduced weight gain as a consequence of diminished daily food intake and increased resting energy expenditure. These changes were associated with enhanced connectivity between several brain areas. A lower striatal DAT together with a doubled mid-brain SERT were likely causative for these changes.

Two KTR Mannosyltransferases Are Responsible for the Biosynthesis of Cell Wall Mannans and Control Polarized Growth in Aspergillus fumigatus.

Fungal cell wall mannans are complex carbohydrate polysaccharides with different structures in yeasts and molds. In contrast to yeasts, their biosynthetic pathway has been poorly investigated in filamentous fungi. In Aspergillus fumigatus, the major mannan structure is a galactomannan that is cross-linked to the ß-1,3-glucan-chitin cell wall core. This polymer is composed of a linear mannan with a repeating unit composed of four α1,6-linked and α1,2-linked mannoses with side chains of galactofuran. Despite its use as a biomarker to diagnose invasive aspergillosis, its biosynthesis and biological function were unknown. Here, we have investigated the function of three members of the Ktr (also named Kre2/Mnt1) family (Ktr1, Ktr4, and Ktr7) in A. fumigatus and show that two of them are required for the biosynthesis of galactomannan. In particular, we describe a newly discovered form of α-1,2-mannosyltransferase activity encoded by the KTR4 gene. Biochemical analyses showed that deletion of the KTR4 gene or the KTR7 gene leads to the absence of cell wall galactomannan. In comparison to parental strains, the Δktr4 and Δktr7 mutants showed a severe growth phenotype with defects in polarized growth and in conidiation, marked alteration of the conidial viability, and reduced virulence in a mouse model of invasive aspergillosis. In yeast, the KTR proteins are involved in protein 0- and N-glycosylation. This study provided another confirmation that orthologous genes can code for proteins that have very different biological functions in yeasts and filamentous fungi. Moreover, in A. fumigatus, cell wall mannans are as important structurally as ß-glucans and chitin.IMPORTANCE The fungal cell wall is a complex and dynamic entity essential for the development of fungi. It allows fungal pathogens to survive environmental challenge posed by nutrient stress and host defenses, and it also is central to polarized growth. The cell wall is mainly composed of polysaccharides organized in a three-dimensional network. Aspergillus fumigatus produces a cell wall galactomannan whose biosynthetic pathway and biological functions remain poorly defined. Here, we described two new mannosyltransferases essential to the synthesis of the cell wall galactomannan. Their absence leads to a growth defect with misregulation of polarization and altered conidiation, with conidia which are bigger and more permeable than the conidia of the parental strain. This study showed that in spite of its low concentration in the cell wall, this polysaccharide is absolutely required for cell wall stability, for apical growth, and for the full virulence of A. fumigatus.

Herpes simplex virus-binding IgG traps HSV in human cervicovaginal mucus across the menstrual cycle and diverse vaginal microbial composition.

IgG possesses an important yet little recognized effector function in mucus. IgG bound to viral surface can immobilize otherwise readily diffusive viruses to the mucin matrix, excluding them from contacting target cells and facilitating their elimination by natural mucus clearance mechanisms. Cervicovaginal mucus (CVM) is populated by a microbial community, and its viscoelastic and barrier properties can vary substantially not only across the menstrual cycle, but also in women with distinct microbiota. How these variations impact the "muco-trapping" effector function of IgGs remains poorly understood. Here we obtained multiple fresh, undiluted CVM specimens (n = 82 unique specimens) from six women over time, and employed high-resolution multiple particle tracking to quantify the mobility of fluorescent Herpes Simplex Viruses (HSV-1) in CVM treated with different HSV-1-binding IgG. The IgG trapping potency was then correlated to the menstrual cycle, and the vaginal microbial composition was determined by 16 s rRNA. In the specimens studied, both polyclonal and monoclonal HSV-1-binding IgG appeared to consistently and effectively trap HSV-1 in CVM obtained at different times of the menstrual cycle and containing a diverse spectrum of commensals, including G. vaginalis-dominant microbiota. Our findings underscore the potential broad utility of this "muco-trapping" effector function of IgG to reinforce the vaginal mucosal defense, and motivates further investigation of passive immunization of the vagina as a strategy to protect against vaginally transmitted infections.

Model based optimal multipolar stimulation without a priori knowledge of nerve structure: application to vagus nerve stimulation.

OBJECTIVE: Multipolar cuff electrode can selectively stimulate areas of peripheral nerves and therefore enable to control independent functions. However, the branching and fascicularization are known for a limited set of nerves and the specific organization remains subject-dependent. This paper presents general modeling and optimization methods in the context of multipolar stimulation using a cuff electrode without a priori knowledge of the nerve structure. Vagus nerve stimulation experiments based on the optimization results were then investigated. APPROACH: The model consisted of two independent components: a lead field matrix representing the transfer function from the applied current to the extracellular voltage present on the nodes of Ranvier along each axon, and a linear activation model. The optimization process consisted in finding the best current repartition (ratios) to reach activation of a targeted area depending on three criteria: selectivity, efficiency and robustness. MAIN RESULTS: The results showed that state-of-the-art configurations (tripolar transverse, tripolar longitudinal) were part of the optimized solutions but new ones could emerge depending on the trade-off between the three criteria and the targeted area. Besides, the choice of appropriate current ratios was more important than the choice of the stimulation amplitude for a stimulation without a priori knowledge of the nerve structure. We successfully assessed the solutions in vivo to selectively induce a decrease in cardiac rhythm through vagus nerve stimulation while limiting side effects. Compared to the standard whole ring configuration, a selective solution found by simulation provided on average 2.6 less adverse effects. SIGNIFICANCE: The preliminary results showed the rightness of the simulation, using a generic nerve geometry. It suggested that this approach will have broader applications that would benefit from multicontact cuff electrodes to elicit selective responses. In the context of the vagus nerve stimulation for heart failure therapy, we show that the simulation results were confirmed and improved the therapy while decreasing the side effects.

Glycosylphosphatidylinositol Anchors from Galactomannan and GPI-Anchored Protein Are Synthesized by Distinct Pathways in Aspergillus fumigatus.

Glycosylphosphatidylinositols (GPIs) are lipid anchors allowing the exposure of proteins at the outer layer of the plasma membrane. In fungi, a number of GPI-anchored proteins (GPI-APs) are involved in the remodeling of the cell wall polymers. GPIs follow a specific biosynthetic pathway in the endoplasmic reticulum. After the transfer of the protein onto the GPI-anchor, a lipid remodeling occurs to substitute the diacylglycerol moiety by a ceramide. In addition to GPI-APs, A. fumigatus produces a GPI-anchored polysaccharide, the galactomannan (GM), that remains unique in the fungal kingdom. To investigate the role of the GPI pathway in the biosynthesis of the GM and cell wall organization, the deletion of PER1-coding for a phospholipase required for the first step of the GPI lipid remodeling-was undertaken. Biochemical characterization of the GPI-anchor isolated from GPI-APs showed that the PER1 deficient mutant produced a lipid anchor with a diacylglycerol. The absence of a ceramide on GPI-anchors in the Δper1 mutant led to a mislocation of GPI-APs and to an alteration of the composition of the cell wall alkali-insoluble fraction. On the other hand, the GM isolated from the Δper1 mutant membranes possesses a ceramide moiety as the parental strain, showing that GPI anchor of the GM follow a distinct unknown biosynthetic pathway.

Closed-Loop Vagus Nerve Stimulation Based on State Transition Models.

OBJECTIVE: Vagus nerve stimulation (VNS) is a potential therapeutic approach in a number of clinical applications. Although VNS is commonly delivered in an open-loop approach, it is now recognized that closed-loop stimulation may be necessary to optimize the therapy. In this paper, we propose an original generic closed-loop control system that can be readily integrated into an implantable device and allows for the adaptive modulation of multiple VNS parameters. METHODS: The proposed control method consists of a state transition model (STM), in which each state represents a set of VNS parameters, and a state transition algorithm that optimally selects the best STM state, minimizing the error between an observed physiological variable and a given target value. The proposed method has been integrated into a real-time adaptive VNS prototype system and has been applied here to the regulation of the instantaneous heart rate, working synchronously with cardiac cycles. A quantitative performance evaluation is performed on seven sheep by computing classical control performance indicators. A comparison with a proportional-integral (PI) controller is also performed. RESULTS: The STM controller presents a median mean square error, overshoot, and settling time, respectively, equal to 622.21 ms , 72.8%, and 7.5 beats. CONCLUSION: The proposed control method yields satisfactory accuracy and time response, while presenting a number of benefits over classical PI controllers. It represents a feasible approach for multiparametric VNS control on implantable devices. SIGNIFICANCE: Closed-loop multiparametric stimulation may improve response and minimize side effects on current pathologies treated by VNS.

A novel controller based on state-transition models for closed-loop vagus nerve stimulation: Application to heart rate regulation.

Vagus nerve stimulation (VNS) is an established adjunctive therapy for pharmacologically refractory epilepsy and depression and is currently in active clinical research for other applications. In current clinical studies, VNS is delivered in an open-loop approach, where VNS parameters are defined during a manual titration phase. However, the physiological response to a given VNS configuration shows significant inter and intra-patient variability and may significantly evolve through time. VNS closed-loop approaches, allowing for the optimization of the therapy in an adaptive manner, may be necessary to improve efficacy while reducing side effects. This paper proposes a generic, closed-loop control VNS system that is able to optimize a number of VNS parameters in an adaptive fashion, in order to keep a control variable within a specified range. Although the proposed control method is completely generic, an example application using the cardiac beat to beat interval (RR) as control variable will be developed in this paper. The proposed controller is based on a state transition model (STM) that can be configured using a partially or a fully-connected architecture, different model orders and different state-transition algorithms. The controller is applied to the adaptive regulation of heart rate and evaluated on 6 sheep, for 13 different targets, using partially-connected STM with 10 states. Also, partially and fully-connected STM defined by 30 states were applied to 7 other sheep for the same 10 targets. Results illustrate the interest of the proposed fully-connected STM and the feasibility of integrating this control system into an implantable neuromodulator.

Effects of chronic abdominal vagal stimulation of small-diameter neurons on brain metabolism and food intake.

BACKGROUND: Abdominal bilateral vagal stimulation reduces food intake in animals. However, the classical square wave, mA range current generator is poorly effective to evoke action potentials on A∂ and C neurons that represent the majority of vagal neurons at the abdominal level. OBJECTIVE/HYPOTHESIS: METHODS: The current thresholds for pulsons (S2 & S3) and millisecond pulses (S1) required to trigger action potentials were calculated in 5 anaesthetized pigs using single fibre recording. Similar stimulation protocols were compared chronically to sham stimulation in 24 pigs. After two weeks of chronic stimulation, food intake and brain metabolism were investigated. The electrical characteristics and histology of the vagus nerve were also studied. RESULTS: S3 stimulation required a lower amount of charges to trigger an action potential. Chronically applied S2 & S3 activated the dorsal vagal complex and increased the metabolism of its afferent cortical structures. They also reduced energy intake together with a reduced ingestion of high fat and high sugar diets. All these effects were not observed for the S1 group. The vagal histology for the S1, S2 and S3 groups was not different from that of the sham. CONCLUSIONS: These findings demonstrate that pulsons applied bilaterally on the abdominal vagus reduced food intake as a consequence of the activation of the brainstem and higher-order brain areas.

Obesity-Associated Alterations in Glucose Metabolism Are Reversed by Chronic Bilateral Stimulation of the Abdominal Vagus Nerve.

Acute vagal stimulation modifies glucose and insulin metabolism, but the effect of chronic bilateral vagal stimulation is not known. Our aim was to quantify the changes in whole-body and organ-specific insulin sensitivities 12 weeks after permanent, bilateral, vagal stimulation performed at the abdominal level in adult mini-pigs. In 15 adult mini-pigs, stimulating electrodes were placed around the dorsal and ventral vagi using laparoscopy and connected to a dual-channel stimulator placed subcutaneously. Animals were divided into three groups based on stimulation and body weight (i.e., lean nonstimulated, obese nonstimulated, and obese stimulated). Twelve weeks after surgery, glucose uptake and insulin sensitivity were measured using positron emission tomography during an isoglycemic clamp. Mean whole-body insulin sensitivity was lower by 34% (P < 0.01) and the hepatic glucose uptake rate was lower by 33% (P < 0.01) in obese-nonstimulated mini-pigs but was no different in obese-stimulated compared with lean mini-pigs. An improvement in skeletal glucose uptake rate was also observed in obese-stimulated compared with obese-nonstimulated groups (P < 0.01). Vagal stimulation was associated with increased glucose metabolism in the cingulate and prefrontal brain areas. We conclude that chronic vagal stimulation improves insulin sensitivity substantially in diet-induced obesity by both peripheral and central mechanisms.

Sensitivity Analysis of Vagus Nerve Stimulation Parameters on Acute Cardiac Autonomic Responses: Chronotropic, Inotropic and Dromotropic Effects.

Although the therapeutic effects of Vagus Nerve Stimulation (VNS) have been recognized in pre-clinical and pilot clinical studies, the effect of different stimulation configurations on the cardiovascular response is still an open question, especially in the case of VNS delivered synchronously with cardiac activity. In this paper, we propose a formal mathematical methodology to analyze the acute cardiac response to different VNS configurations, jointly considering the chronotropic, dromotropic and inotropic cardiac effects. A latin hypercube sampling method was chosen to design a uniform experimental plan, composed of 75 different VNS configurations, with different values for the main parameters (current amplitude, number of delivered pulses, pulse width, interpulse period and the delay between the detected cardiac event and VNS onset). These VNS configurations were applied to 6 healthy, anesthetized sheep, while acquiring the associated cardiovascular response. Unobserved VNS configurations were estimated using a Gaussian process regression (GPR) model. In order to quantitatively analyze the effect of each parameter and their combinations on the cardiac response, the Sobol sensitivity method was applied to the obtained GPR model and inter-individual sensitivity markers were estimated using a bootstrap approach. Results highlight the dominant effect of pulse current, pulse width and number of pulses, which explain respectively 49.4%, 19.7% and 6.0% of the mean global cardiovascular variability provoked by VNS. More interestingly, results also quantify the effect of the interactions between VNS parameters. In particular, the interactions between current and pulse width provoke higher cardiac effects than the changes on the number of pulses alone (between 6 and 25% of the variability). Although the sensitivity of individual VNS parameters seems similar for chronotropic, dromotropic and inotropic responses, the interacting effects of VNS parameters provoke significantly different cardiac responses, showing the feasibility of a parameter-based functional selectivity. These results are of primary importance for the optimal, subject-specific definition of VNS parameters for a given therapy and may lead to new closed-loop methods allowing for the optimal adaptation of VNS therapy through time.

Biosynthesis of cell wall mannan in the conidium and the mycelium of Aspergillus fumigatus.

The galactomannan is a major cell wall molecule of Aspergillus fumigatus. This molecule is composed of a linear mannan with a repeating unit composed of four α1,6 and α1,2 linked mannose with side chains of galactofuran. To obtain a better understanding of the mannan biosynthesis in A. fumigatus, it was decided to undertake the successive deletion of the 11 genes which are putative orthologs of the mannosyltransferases responsible for establishing α1,6 and α1,2 mannose linkages in yeast. These deletions did not lead to a reduction of the mannan content of the cell wall of the mycelium of A. fumigatus. In contrast, the mannan content of the conidial cell wall was reduced and this reduction was associated with a partial disorganization of the cell wall leading to defects in conidial survival both in vitro and in vivo.