Sustaining sleep spindles through enhanced SK2-channel activity consolidates sleep and elevates arousal threshold.

Sleep spindles are synchronized 11-15 Hz electroencephalographic (EEG) oscillations predominant during nonrapid-eye-movement sleep (NREMS). Rhythmic bursting in the reticular thalamic nucleus (nRt), arising from interplay between Ca(v)3.3-type Ca(2+) channels and Ca(2+)-dependent small-conductance-type 2 (SK2) K(+) channels, underlies spindle generation. Correlative evidence indicates that spindles contribute to memory consolidation and protection against environmental noise in human NREMS. Here, we describe a molecular mechanism through which spindle power is selectively extended and we probed the actions of intensified spindling in the naturally sleeping mouse. Using electrophysiological recordings in acute brain slices from SK2 channel-overexpressing (SK2-OE) mice, we found that nRt bursting was potentiated and thalamic circuit oscillations were prolonged. Moreover, nRt cells showed greater resilience to transit from burst to tonic discharge in response to gradual depolarization, mimicking transitions out of NREMS. Compared with wild-type littermates, chronic EEG recordings of SK2-OE mice contained less fragmented NREMS, while the NREMS EEG power spectrum was conserved. Furthermore, EEG spindle activity was prolonged at NREMS exit. Finally, when exposed to white noise, SK2-OE mice needed stronger stimuli to arouse. Increased nRt bursting thus strengthens spindles and improves sleep quality through mechanisms independent of EEG slow waves (<4 Hz), suggesting SK2 signaling as a new potential therapeutic target for sleep disorders and for neuropsychiatric diseases accompanied by weakened sleep spindles.

Mitochondrial tRNA(Leu(UUR)) mutation m.3302A > G presenting as childhood-onset severe myopathy: threshold determination through segregation study.

Mitochondrial tRNA(Leu(UUR)) mutation m.3302A > G is associated with respiratory chain complex I deficiency and has been described as a rare cause of mostly adult-onset slowly progressive myopathy. Five families with 11 patients have been described so far; 5 of them died young due to cardiorespiratory failure. Here, we report on a segregation study in a family with an index patient who already presented at the age of 18 months with proximal muscular hypotonia, abnormal fatigability, and lactic acidosis. This early-onset myopathy was rapidly progressive. At 8 years, the patient is wheel-chair bound, requires nocturnal assisted ventilation, and suffers from recurrent respiratory infections. Severe complex I deficiency and nearly homoplasmy for m.3302A > G were found in muscle. We collected blood, hair, buccal swabs and muscle biopsies from asymptomatic adults in this pedigree and determined heteroplasmy levels in these tissues as well as OXPHOS activities in muscle. All participating asymptomatic adults had normal OXPHOS activities. In contrast to earlier reports, we found surprisingly little variation of heteroplasmy levels in different tissues of the same individual. Up to 45% mutation load in muscle and up to 38% mutation load in other tissues were found in non-affected adults. The phenotypic spectrum of tRNA(Leu(UUR)) m.3302A > G mutation seems to be wider than previously described. A threshold of more than 45% heteroplasmy in muscle seems to be necessary to alter complex I activity leading to clinical manifestation. The presented data may be helpful for prognostic considerations and counseling in affected families.

Neurally adjusted ventilatory assist (NAVA) improves patient-ventilator interaction during non-invasive ventilation delivered by face mask.

PURPOSE: To determine if, compared to pressure support (PS), neurally adjusted ventilatory assist (NAVA) reduces patient-ventilator asynchrony in intensive care patients undergoing noninvasive ventilation with an oronasal face mask. METHODS: In this prospective interventional study we compared patient-ventilator synchrony between PS (with ventilator settings determined by the clinician) and NAVA (with the level set so as to obtain the same maximal airway pressure as in PS). Two 20-min recordings of airway pressure, flow and electrical activity of the diaphragm during PS and NAVA were acquired in a randomized order. Trigger delay (T(d)), the patient's neural inspiratory time (T(in)), ventilator pressurization duration (T(iv)), inspiratory time in excess (T(iex)), number of asynchrony events per minute and asynchrony index (AI) were determined. RESULTS: The study included 13 patients, six with COPD, and two with mixed pulmonary disease. T(d) was reduced with NAVA: median 35 ms (IQR 31-53 ms) versus 181 ms (122-208 ms); p = 0.0002. NAVA reduced both premature and delayed cyclings in the majority of patients, but not the median T(iex) value. The total number of asynchrony events tended to be reduced with NAVA: 1.0 events/min (0.5-3.1 events/min) versus 4.4 events/min (0.9-12.1 events/min); p = 0.08. AI was lower with NAVA: 4.9 % (2.5-10.5 %) versus 15.8 % (5.5-49.6 %); p = 0.03. During NAVA, there were no ineffective efforts, or late or premature cyclings. PaO(2) and PaCO(2) were not different between ventilatory modes. CONCLUSION: Compared to PS, NAVA improved patient ventilator synchrony during noninvasive ventilation by reducing T(d) and AI. Moreover, with NAVA, ineffective efforts, and late and premature cyclings were absent.

Nava enhances ventilatory variability and diaphragmatic activity/tidal volume coupling

INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) is a new ventilatory mode in which ventilator settings are adjusted based on the electrical activity detected in the diaphragm (Eadi). This mode offers significant advantages in mechanical ventilation over standard pressure support (PS) modes, since ventilator input is determined directly from patient ventilatory demand. Therefore, it is expected that tidal volume (Vt) under NAVA would show better correlation with Eadi compared with PS, and exhibit greater variability due to the variability in the Eadi input to the ventilator. OBJECTIVES. To compare tidal volume variability in PS and NAVA ventilation modes, and its correlation with patient ventilatory demand (as characterized by maximum Eadi). METHODS. Acomparative study of patient-ventilator interaction was performed for 22 patients during standard PS with clinician determined ventilator settings; and NAVA, with NAVA gain set to ensure the same peak airway pressure as the total pressure obtained in PS. A 20 min continuous recording was performed in each ventilator mode. Respiratory rate, Vt, and Eadi were recorded. Tidal volume variance and Pearson correlation coefficient between Vt and Eadi were calculated for each patient. A periodogram was plotted for each ventilator mode and each patient, showing spectral power as a function of frequency to assess variability. RESULTS. Median, lower quartile and upper quartile values for Vt variance and Vt/Eadi correlation are shown in Table 1. The NAVA cohort exhibits substantially greater correlation and variance than the PS cohort. Power spectrums for Vt and Eadi are shown in Fig. 1 (PS and NAVA) for a typical patient. The enlarged section highlights how changes in Eadi are highly synchronized with NAVA ventilation, but less so for PS. CONCLUSIONS. There is greater variability in tidal volume and correlation between tidal volume and diaphragmatic electrical activity with NAVA compared to PS. These results are consistent with the improved patient-ventilator synchrony reported in the literature.

Addition of inspiratory resistance increases the amplitude of the slow component of O2 uptake kinetics.

The contribution of respiratory muscle work to the development of the O(2) consumption (Vo(2)) slow component is a point of controversy because it has been shown that the increased ventilation in hypoxia is not associated with a concomitant increase in Vo(2) slow component. The first purpose of this study was thus to test the hypothesis of a direct relationship between respiratory muscle work and Vo(2) slow component by manipulating inspiratory resistance. Because the conditions for a Vo(2) slow component specific to respiratory muscle can be reached during intense exercise, the second purpose was to determine whether respiratory muscles behave like limb muscles during heavy exercise. Ten trained subjects performed two 8-min constant-load heavy cycling exercises with and without a threshold valve in random order. Vo(2) was measured breath by breath by using a fast gas exchange analyzer, and the Vo(2) response was modeled after removal of the cardiodynamic phase by using two monoexponential functions. As anticipated, when total work was slightly increased with loaded inspiratory resistance, slight increases in base Vo(2), the primary phase amplitude, and peak Vo(2) were noted (14.2%, P < 0.01; 3.5%, P > 0.05; and 8.3%, P < 0.01, respectively). The bootstrap method revealed small coefficients of variation for the model parameter, including the slow-component amplitude and delay (15 and 19%, respectively), indicating an accurate determination for this critical parameter. The amplitude of the Vo(2) slow component displayed a 27% increase from 8.1 +/- 3.6 to 10.3 +/- 3.4 ml. min(-1). kg(-1) (P < 0.01) with the addition of inspiratory resistance. Taken together, this increase and the lack of any differences in minute volume and ventilatory parameters between the two experimental conditions suggest the occurrence of a Vo(2) slow component specific to the respiratory muscles in loaded condition.

Trazodone increases arousal threshold in obstructive sleep apnoea.

A low arousal threshold is believed to predispose to breathing instability during sleep. The present authors hypothesised that trazodone, a nonmyorelaxant sleep-promoting agent, would increase the effort-related arousal threshold in obstructive sleep apnoea (OSA) patients. In total, nine OSA patients, mean+/-sd age 49+/-9 yrs, apnoea/hypopnoea index 52+/-32 events.h(-1), were studied on 2 nights, one with trazodone at 100 mg and one with a placebo, in a double blind randomised fashion. While receiving continuous positive airway pressure (CPAP), repeated arousals were induced: 1) by increasing inspired CO(2) and 2) by stepwise decreases in CPAP level. Respiratory effort was measured with an oesophageal balloon. End-tidal CO(2 )tension (P(ET,CO(2))) was monitored with a nasal catheter. During trazodone nights, compared with placebo nights, the arousals occurred at a higher P(ET,CO(2)) level (mean+/-sd 7.30+/-0.57 versus 6.62+/-0.64 kPa (54.9+/-4.3 versus 49.8+/-4.8 mmHg), respectively). When arousals were triggered by increasing inspired CO(2) level, the maximal oesophageal pressure swing was greater (19.4+/-4.0 versus 13.1+/-4.9 cm H(2)O) and the oesophageal pressure nadir before the arousals was lower (-5.1+/-4.7 versus -0.38+/-4.2 cm H(2)O) with trazodone. When arousals were induced by stepwise CPAP drops, the maximal oesophageal pressure swings before the arousals did not differ. Trazodone at 100 mg increased the effort-related arousal threshold in response to hypercapnia in obstructive sleep apnoea patients and allowed them to tolerate higher CO(2) levels.

Can neurally adjusted ventilatory assist (NAVA) improve patient-ventilator interaction? A preliminary study

INTRODUCTION. NAVA is a new spontaneous-assisted ventilatory mode based on thedetection of diaphragmatic electrical activity (Eadi) and its feedback to adjust ventilatorsettings. NAVA uses the Eadi, an expression of the respiratory center's activity, to initiatepressurization, set the level of pressure support and cycle the ventilator into exhalation.Therefore, NAVA should theoretically allow near-perfect synchronization between the patientand the ventilator. However there are few data documenting these effects in intensive carepatients.OBJECTIVES. To determine whether NAVA can improve patient-ventilator synchronycompared to standard pressure support (PS) in intubated intensive care patients.METHODS. Comparative study of patient-ventilator interaction during PS with cliniciandetermined ventilator settings and NAVA with NAVA gain (proportionality factor betweenEadi and the amount of delivered inspiratory pressure) set as to obtain the same peak airwaypressure as the total pressure obtained in PS. A 20 min continuous recording with eachventilatory mode was performed allowing determination of trigger delay (Td), patient neuralinspiratory time (Tin), duration of pressurization by the ventilator (Tiv), excess durationof pressurization (Ti excess = Tiv - Tin/Tin 9 100) and number of asynchrony events byminute: non-triggering breaths, auto-triggering, double triggering, premature and delayedcycling.Results are given in mean ± SD. p is considered significant if\0.05.RESULTS. Preliminary results (mean ± SD): five patients (age 75 ± 12 years, 1 M/4F,BMI 25.7 ± 4.1 kg m-2), two pts with COPD, 1 with restrictive disease, initial settings: PS14.6 ± 1.7 cm H2O, PEEP 6.4 ± 1.5 cm H2O, NAVA gain 2.8 ± 1.3PS NAVA % reduction NAVAversus PSTd (ms) 210.4 ± 63.0 51.8 ± 12.1* 74.5 ± 5.0Ti excess (%) 12.9 ± 19.6 2.2 ± 0.6 70.8 ± 37.8n asynchrony/minute 7.6 ± 6.4 4.1 ± 3.7* 47.5 ± 17.0Respiratory rate (min-1) 16.8 ± 2.6 20.4 ± 4.7 NA* p\0.05CONCLUSION. Compared to standard PS, NAVA improves patient ventilator interaction byreducing Td and the overall incidence of asynchrony events. There is also a strong trend inreducing delayed cycling. This ongoing trial should provide evidence that NAVA can indeedimprove patient-ventilator synchrony in intubated patients undergoing PS.REFERENCE(S). 1. Sinderby C, Navalesi P et al (1995) Neural control of mechanicalventilation in respiratory failure. Nat Med 5(12):1433-1436.2. Colombo D, Cammarota G et al (2008) Physiologic response to varying levels of pressuresupport and neurally adjusted ventilator assist in patients with acute respiratory failure.Intensive Care Med 34(11):2010-2018.

Physiological differences between cycling and running

This review compares the differences in systemic responses (VO2max, anaerobic threshold, heart rate and economy) and in underlying mechanisms of adaptation (ventilatory and hemodynamic and neuromuscular responses) between cycling and running. VO2max is specific to the exercise modality. Overall, there is more physiological training transfer from running to cycling than vice-versa. Several other physiological differences between cycling and running are discussed: HR is different between the two activities both for maximal and sub-maximal intensities. The delta efficiency is higher in running. Ventilation is more impaired in cycling than running due to mechanical constraints. Central fatigue and decrease in maximal strength are more important after prolonged exercise in running than in cycling.

Neurally Adjusted Ventilatory Assist (NAVA) improves the matching of diaphragmatic electrical activity and tidal volume in comparison to pressure support (PS) under non invasive ventilation

INTRODUCTION. Patient-ventilator asynchrony is a frequent issue in non invasivemechanical ventilation (NIV) and leaks at the patient-mask interface play a major role in itspathogenesis. NIV algorithms alleviate the deleterious impact of leaks and improve patient-ventilator interaction. Neurally adusted ventilatory assist (NAVA), a neurally triggered modethat avoids interferences between leaks and the usual pneumatic trigger, could further improvepatient-ventilator interaction in NIV patients.OBJECTIVES. To evaluate the feasibility ofNAVAin patients receiving a prophylactic postextubationNIV and to compare the respective impact ofPSVandNAVAwith and withoutNIValgorithm on patient-ventilator interaction.METHODS. Prospective study conducted in 16 beds adult critical care unit (ICU) in a tertiaryuniversity hospital. Over a 2 months period, were included 17 adult medical ICU patientsextubated for less than 2 h and in whom a prophylactic post-extubation NIV was indicated.Patients were randomly mechanically ventilated for 10 min with: PSV without NIV algorithm(PSV-NIV-), PSV with NIV algorithm (PSV-NIV+),NAVAwithout NIV algorithm (NAVANIV-)and NAVA with NIV algorithm (NAVA-NIV+). Breathing pattern descriptors, diaphragmelectrical activity, leaks volume, inspiratory trigger delay (Tdinsp), inspiratory time inexcess (Tiexcess) and the five main asynchronies were quantified. Asynchrony index (AI) andasynchrony index influenced by leaks (AIleaks) were computed.RESULTS. Peak inspiratory pressure and diaphragm electrical activity were similar in thefour conditions. With both PSV and NAVA, NIV algorithm significantly reduced the level ofleak (p\0.01). Tdinsp was not affected by NIV algorithm but was shorter in NAVA than inPSV (p\0.01). Tiexcess was shorter in NAVA and PSV-NIV+ than in PSV-NIV- (p\0.05).The prevalence of double triggering was significantly lower in PSV-NIV+ than in NAVANIV+.As compared to PSV,NAVAsignificantly reduced the prevalence of premature cyclingand late cycling while NIV algorithm did not influenced premature cycling. AI was not affectedby NIV algorithm but was significantly lower in NAVA than in PSV (p\0.05). AIleaks wasquasi null with NAVA and significantly lower than in PSV (p\0.05).CONCLUSIONS. NAVA is feasible in patients receiving a post-extubation prophylacticNIV. NAVA and NIV improve patient-ventilator synchrony in different manners. NAVANIV+offers the best patient-ventilator interaction. Clinical studies are required to assess thepotential clinical benefit of NAVA in patients receiving NIV.

Blood glucose and prognosis in children with presumed severe malaria: is there a threshold for 'hypoglycaemia'?

OBJECTIVES: Hypoglycaemia (glucose <2.2 mmol/l) is a defining feature of severe malaria, but the significance of other levels of blood glucose has not previously been studied in children with severe malaria. METHODS: A prospective study of 437 consecutive children with presumed severe malaria was conducted in Mali. We defined hypoglycaemia as <2.2 mmol/l, low glycaemia as 2.2-4.4 mmol/l and hyperglycaemia as >8.3 mmol/l. Associations between glycaemia and case fatality were analysed for 418 children using logistic regression models and a receiver operator curve (ROC). RESULTS: There was a significant difference between blood glucose levels in children who died (median 4.6 mmol/l) and survivors (median 7.6 mmol/l, P < 0.001). Case fatality declined from 61.5% of the hypoglycaemic children to 46.2% of those with low glycaemia, 13.4% of those with normal glycaemia and 7.6% of those with hyperglycaemia (P < 0.001). Logistic regression showed an adjusted odds ratio (AOR) of 0.75 (0.64-0.88) for case fatality per 1 mmol/l increase in baseline blood glucose. Compared to a normal blood glucose, hypoglycaemia and low glycaemia both significantly increased the odds of death (AOR 11.87, 2.10-67.00; and 5.21, 1.86-14.63, respectively), whereas hyperglycaemia reduced the odds of death (AOR 0.34, 0.13-0.91). The ROC [area under the curve at 0.753 (95% CI 0.684-0.820)] indicated that glycaemia had a moderate predictive value for death and identified an optimal threshold at glycaemia <6.1 mmol/l, (sensitivity 64.5% and specificity 75.1%). CONCLUSIONS: If there is a threshold of blood glucose which defines a worse prognosis, it is at a higher level than the current definition of 2.2 mmol/l.

Evidence for a TCR affinity threshold delimiting maximal CD8 T cell function.

Protective adaptive immune responses rely on TCR-mediated recognition of Ag-derived peptides presented by self-MHC molecules. However, self-Ag (tumor)-specific TCRs are often of too low affinity to achieve best functionality. To precisely assess the relationship between TCR-peptide-MHC binding parameters and T cell function, we tested a panel of sequence-optimized HLA-A(*)0201/NY-ESO-1(157-165)-specific TCR variants with affinities lying within physiological boundaries to preserve antigenic specificity and avoid cross-reactivity, as well as two outliers (i.e., a very high- and a low-affinity TCR). Primary human CD8 T cells transduced with these TCRs demonstrated robust correlations between binding measurements of TCR affinity and avidity and the biological response of the T cells, such as TCR cell-surface clustering, intracellular signaling, proliferation, and target cell lysis. Strikingly, above a defined TCR-peptide-MHC affinity threshold (K(D) < approximately 5 muM), T cell function could not be further enhanced, revealing a plateau of maximal T cell function, compatible with the notion that multiple TCRs with slightly different affinities participate equally (codominantly) in immune responses. We propose that rational design of improved self-specific TCRs may not need to be optimized beyond a given affinity threshold to achieve both optimal T cell function and avoidance of the unpredictable risk of cross-reactivity.