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.

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.

Personalized and automated remote monitoring of atrial fibrillation.

AIMS: Remote monitoring of cardiac implantable electronic devices is a growing standard; yet, remote follow-up and management of alerts represents a time-consuming task for physicians or trained staff. This study evaluates an automatic mechanism based on artificial intelligence tools to filter atrial fibrillation (AF) alerts based on their medical significance. METHODS AND RESULTS: We evaluated this method on alerts for AF episodes that occurred in 60 pacemaker recipients. AKENATON prototype workflow includes two steps: natural language-processing algorithms abstract the patient health record to a digital version, then a knowledge-based algorithm based on an applied formal ontology allows to calculate the CHA2DS2-VASc score and evaluate the anticoagulation status of the patient. Each alert is then automatically classified by importance from low to critical, by mimicking medical reasoning. Final classification was compared with human expert analysis by two physicians. A total of 1783 alerts about AF episode >5 min in 60 patients were processed. A 1749 of 1783 alerts (98%) were adequately classified and there were no underestimation of alert importance in the remaining 34 misclassified alerts. CONCLUSION: This work demonstrates the ability of a pilot system to classify alerts and improves personalized remote monitoring of patients. In particular, our method allows integration of patient medical history with device alert notifications, which is useful both from medical and resource-management perspectives. The system was able to automatically classify the importance of 1783 AF alerts in 60 patients, which resulted in an 84% reduction in notification workload, while preserving patient safety.

Deletion of the α-(1,3)-glucan synthase genes induces a restructuring of the conidial cell wall responsible for the avirulence of Aspergillus fumigatus.

α-(1,3)-Glucan is a major component of the cell wall of Aspergillus fumigatus, an opportunistic human fungal pathogen. There are three genes (AGS1, AGS2 and AGS3) controlling the biosynthesis of α-(1,3)-glucan in this fungal species. Deletion of all the three AGS genes resulted in a triple mutant that was devoid of α-(1,3)-glucan in its cell wall; however, its growth and germination was identical to that of the parental strain in vitro. In the experimental murine aspergillosis model, this mutant was less pathogenic than the parental strain. The AGS deletion resulted in an extensive structural modification of the conidial cell wall, especially conidial surface where the rodlet layer was covered by an amorphous glycoprotein matrix. This surface modification was responsible for viability reduction of conidia in vivo, which explains decrease in the virulence of triple agsΔ mutant.

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.

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.

Artificial intelligence-based electrocardiogram analysis improves atrial arrhythmia detection from a smartwatch electrocardiogram.

Aims: Smartwatch electrocardiograms (SW ECGs) have been identified as a non-invasive solution to assess abnormal heart rhythm, especially atrial arrhythmias (AAs) that are related to stroke risk. However, the performance of these tools is limited and could be improved with the use of deep neural network (DNN) algorithms, particularly for specific populations encountered in clinical cardiology practice. Methods and results: A total of 400 patients from the electrophysiology department of one tertiary care hospital were included in two similar clinical trials (respectively, 200 patients per study). Simultaneous ECGs were recorded with the watch and a 12-lead recording system during consultation or before and after an electrophysiology procedure if any. The SW ECGs were processed by using the DNN and with the Apple watch ECG software (Apple app). Corresponding 12-lead ECGs (12L ECGs) were adjudicated by an expert electrophysiologist. The performance of the DNN was assessed vs. the expert interpretation of the 12L ECG, and inconclusive rates were reported. Overall, the DNN and the Apple app presented, respectively, a sensitivity of 91% [95% confidence interval (CI) 85-95%] and 61% (95% CI 44-75%) with a specificity of 95% (95% CI 91-97%) and 97% (95% CI 93-99%) when compared with the physician 12L ECG interpretation. The DNN was able to provide a diagnosis on 99% of ECGs, while the Apple app was able to classify only 78% of strips (22% of inconclusive diagnosis). Conclusion: In this study, by including patients from a cardiology department, a DNN-based algorithm applied to an SW ECG provided an accurate diagnosis for AA detection on virtually all tracings, outperforming the SW algorithm.

Prehospital Partial Resuscitative Endovascular Balloon Occlusion of the Aorta for Exsanguinating Subdiaphragmatic Hemorrhage.

Importance: Hemorrhage is the most common cause of preventable death after injury. Most deaths occur early, in the prehospital phase of care. Objective: To establish whether prehospital zone 1 (supraceliac) partial resuscitative endovascular balloon occlusion of the aorta (Z1 P-REBOA) can be achieved in the resuscitation of adult trauma patients at risk of cardiac arrest and death due to exsanguination. Design, Setting, and Participants: This was a prospective observational cohort study (Idea, Development, Exploration, Assessment and Long-term follow-up [IDEAL] 2A design) with recruitment from June 2020 to March 2022 and follow-up until discharge from hospital, death, or 90 days evaluating a physician-led and physician-delivered, urban prehospital trauma service in the Greater London area. Trauma patients aged 16 years and older with suspected exsanguinating subdiaphragmatic hemorrhage, recent or imminent hypovolemic traumatic cardiac arrest (TCA) were included. Those with unsurvivable injuries or who were pregnant were excluded. Of 2960 individuals attended by the service during the study period, 16 were included in the study. Exposures: ZI REBOA or P-REBOA. Main Outcomes and Measures: The main outcome was the proportion of patients in whom Z1 REBOA and Z1 P-REBOA were achieved. Clinical end points included systolic blood pressure (SBP) response to Z1 REBOA, mortality rate (1 hour, 3 hours, 24 hours, or 30 days postinjury), and survival to hospital discharge. Results: Femoral arterial access for Z1 REBOA was attempted in 16 patients (median [range] age, 30 [17-76] years; 14 [81%] male; median [IQR] Injury Severity Score, 50 [39-57]). In 2 patients with successful arterial access, REBOA was not attempted due to improvement in clinical condition. In the other 14 patients (8 [57%] of whom were in traumatic cardiac arrest [TCA]), 11 successfully underwent cannulation and had aortic balloons inflated in Z1. The 3 individuals in whom cannulation was unsuccessful were in TCA (failure rate = 3/14 [21%]). Median (IQR) pre-REBOA SBP in the 11 individuals for whom cannulation was successful (5 [46%] in TCA) was 47 (33-52) mm Hg. Z1 REBOA plus P-REBOA was associated with a significant improvement in BP (median [IQR] SBP at emergency department arrival, 101 [77-107] mm Hg; 0 of 10 patients were in TCA at arrival). The median group-level improvement in SBP from the pre-REBOA value was 52 (95% CI, 42-77) mm Hg (P < .004). P-REBOA was feasible in 8 individuals (8/11 [73%]) and occurred spontaneously in 4 of these. The 1- and 3-hour postinjury mortality rate was 9% (1/11), 24-hour mortality was 27% (3/11), and 30-day mortality was 82% (9/11). Survival to hospital discharge was 18% (2/11). Both survivors underwent early Z1 P-REBOA. Conclusions and Relevance: In this study, prehospital Z1 P-REBOA is feasible and may enable early survival, but with a significant incidence of late death. Trial Registration: ClinicalTrials.gov Identifier: NCT04145271.

Associations between faith, distress and mental adjustment--a Danish survivorship study.

OBJECTIVE: Several studies have suggested that religion and spirituality are important for overcoming psychological distress and adjusting mentally to cancer, but these studies did not differentiate between spiritual well-being and specific aspects of faith. We examined the extent to which spiritual well-being, the faith dimension of spiritual well-being and aspects of performed faith are associated with distress and mental adjustment among cancer patients. METHODS: In a cross-sectional design, 1043 survivors of various cancers filled in a questionnaire on spiritual well-being (FACIT-Sp-12), specific aspects of faith ('belief in a god', 'belief in a god with whom I can talk' and 'experiences of god or a higher power'), religious community and church attendance (DUREL), distress (POMS-SF), adjustment to cancer (Mini-MAC) and sociodemographic factors. Linear regression models were used to analyze the associations between exposure (spiritual well-being and specific faith aspects) and outcome (distress and adjustment to cancer) with adjustment for age, gender, cancer diagnosis and physical and social well-being. RESULTS: Higher spiritual well-being was associated with less total distress (ß = -0.79, CI -0.92; -0.66) and increased adjustment to cancer (fighting spirit, anxious preoccupation, helplessness-hopelessness). Specific aspects of faith were associated with high confusion-bewilderment and tension-anxiety, but also lower score on vigor-activity, and with higher anxious-preoccupation, both higher and lower cognitive avoidance, but also more fighting spirit. CONCLUSIONS: As hypothesized, spiritual well-being were associated with less distress and better mental adjustment. However, specific aspects of faith were both positively and negatively associated with distress and mental adjustment. The results illustrate the complexity of associations between spiritual well-being and specific aspects of faith with psychological function among cancer survivors.

α1,3 glucans are dispensable in Aspergillus fumigatus.

A triple α1,3 glucan synthase mutant of Aspergillus fumigatus obtained by successive deletions of the three α1,3 glucan synthase genes (AGS1, AGS2, and AGS3) has a cell wall devoid of α1,3 glucans. The lack of α1,3 glucans affects neither conidial germination nor mycelial vegetative growth and is compensated by an increase in ß1,3 glucan and/or chitin content.

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.

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.

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.

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.

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.

The link between ion specific bubble coalescence and Hofmeister effects is the partitioning of ions within the interface.

Specific ion effects are ubiquitous in soft matter systems and are most readily observed at high salt concentrations where long-range electrostatic forces are screened. In biological systems, ion-specificity is universal and is necessary to introduce the complexity required to carry out the processes of life. Many specific ion effects fall within the Hofmeister paradigm, whereby the strengths of action of the anions and cations follow a well-defined order, independent of the counterion. In contrast, specific ion effects evident in bubble coalescence inhibition depend on the combination of ions, and this phenomenon can be codified using simple ion-combining rules not evident in the Hofmeister systems. Here we show that these disparate specific ion effects have the same origin: They result from the variation in ion affinity for the solution interface. Equilibrium affinities explain Hofmeister effects, whereas we argue that the cation/anion combination controls bubble coalescence inhibition because of dynamic interfacial processes occurring at the more deformable gas-water interface.

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.

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.

Transcriptomic analysis of the exit from dormancy of Aspergillus fumigatus conidia.

BACKGROUND: Establishment of aspergillosis is depending upon the exit from dormancy and germination of the conidia of Aspergillus fumigatus in the lung. To gain an understanding of the molecular mechanisms underlying the early steps of conidial germination, we undertook a transcriptomic analysis using macroarrays constructed with PCR fragments from > 3,000 genes (around one third of the annotated A. fumigatus genome). RESULTS: Major results of this analysis are the following: (i) conidia stored pre-packaged mRNAs transcripts (27% of genes have transcripts in the resting conidia; (ii) incubation at 37 degrees C in a nutritive medium induced up- and down-regulation of genes: 19% of the total number of genes deposited on the array were up-regulated whereas 22% of the genes with pre-packaged mRNA in the resting conidia were down-regulated; (iii) most modifications were seen during the first 30 min of germination whereas very little modification of gene expression occurred during the following hour; (iv) one-year old conidia and one-week old conidia behaved similarly at transcriptional level. CONCLUSION: Transcriptomic data indicate that the exit from dormancy is associated with a shift from a fermentative metabolism to a respiratory metabolism as well as a trend toward immediate protein synthesis.

Sampling and modeling for the quantification of adventitious genetically modified presence in maize.

The coexistence of genetically modified (GM) and non-GM crops is an important economic and political issue in the European Union. We examined the GM content in non-GM maize crops in Spain in 2005. Both the standing crop and the harvest were tested, and the %GM DNA was quantified by real-time polymerase chain reaction. We compared the level of GM as a function of distance from known GM source fields in a 1.2 km2 landscape. The distribution of GM was compared to predictions from previous studies, and good agreement was found. Control and monitoring of adventitious GM presence in non-GM crops can only be achieved by fit-for-purpose sampling and testing schemes. We used a GM dispersal function to simulate non-GM crops in the studied zone and tested the accuracy of five different sampling schemes. Random sampling was found to be the most accurate and least susceptible to bias by GM spatial structure or gradients. Simulations showed that to achieve greater than 95% confidence in a GM labeling decision of a harvest (when treated as a single marketed lot), 34 samples would be needed when the harvest was outside 50% of the GM threshold value. The number of samples required increased rapidly as the harvest approached the GM threshold, implying that accurate labeling when the harvest is within +/-17% of the threshold may not be possible with high confidence.