Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula.

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.

NAVA enhances tidal volume and diaphragmatic electro-myographic activity matching: a Range90 analysis of supply and demand.

Neurally adjusted ventilatory assist (NAVA) is a ventilation assist mode that delivers pressure in proportionality to electrical activity of the diaphragm (Eadi). Compared to pressure support ventilation (PS), it improves patient-ventilator synchrony and should allow a better expression of patient's intrinsic respiratory variability. We hypothesize that NAVA provides better matching in ventilator tidal volume (Vt) to patients inspiratory demand. 22 patients with acute respiratory failure, ventilated with PS were included in the study. A comparative study was carried out between PS and NAVA, with NAVA gain ensuring the same peak airway pressure as PS. Robust coefficients of variation (CVR) for Eadi and Vt were compared for each mode. The integral of Eadi (ʃEadi) was used to represent patient's inspiratory demand. To evaluate tidal volume and patient's demand matching, Range90 = 5-95 % range of the Vt/ʃEadi ratio was calculated, to normalize and compare differences in demand within and between patients and modes. In this study, peak Eadi and ʃEadi are correlated with median correlation of coefficients, R > 0.95. Median ʃEadi, Vt, neural inspiratory time (Ti_ ( Neural )), inspiratory time (Ti) and peak inspiratory pressure (PIP) were similar in PS and NAVA. However, it was found that individual patients have higher or smaller ʃEadi, Vt, Ti_ ( Neural ), Ti and PIP. CVR analysis showed greater Vt variability for NAVA (p < 0.005). Range90 was lower for NAVA than PS for 21 of 22 patients. NAVA provided better matching of Vt to ʃEadi for 21 of 22 patients, and provided greater variability Vt. These results were achieved regardless of differences in ventilatory demand (Eadi) between patients and modes.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

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.

Neurally adjusted ventilatory assist can improve arterial oxygenation

INTRODUCTION. Neurally Adjusted Ventilatory Assist (NAVA) [1] is a new spontaneousassisted ventilatory mode which uses the diaphragmatic electrical activity (Eadi) to pilot the ventilator. Eadi is used to initiate the ventilator's pressurization and cycling off. Delivered inspiratory assistance is proportional to Eadi. NAVA can improve patient-ventilator synchrony [2] compared to pressure support (PS), but little is known about its effect on minute ventilation and oxygenation. OBJECTIVES. To compare the effects of NAVA and PS on minute ventilation and oxygenation and to analyze potential determinant factors for oxygenation. METHODS. Comparison between two 20-min periods under NAVA and PS. NAVA gain (proportionality factor between Eadi and delivered pressure) set as to obtain the same peak pressure as in PS. FIO2 and positive end-expiratory pressure (PEEP) were the same in NAVA and PS. Blood gas analyses were performed at the end of both recording periods. Statistical analysis: groups were compared with paired t tests or non parametric Wilcoxon signed-rank tests. p\0.05 was considered significant. RESULTS. [Mean ± SD]: 22 patients (age 66 ± 12 year, 7 M/15F, BMI 23.4 ± 3.1 kg/m2), 8 patients with COPD. Initial settings: PS 13 ± 3 cmH2O, PEEP 7 ± 2 cmH2O, NAVA gain 2.2 ± 1.8. Minute ventilation and PaCO2 were the same with both modes (p = 0.296 and 0.848, respectively). Tidal volume was lower with NAVA (427 ± 102 vs. 477 ± 102 ml, p\0.001). In contrast respiratory rate was higher with NAVA (25.6 ± 9.5 vs. 22.3 ± 8.9 cycles/min). Arterial oxygenation was improved with NAVA (PaO2 85.1 ± 28.9 vs. 75.8 ± 11.9 mmHg, p = 0.017, PaO2/FIO2 210 ± 53 vs. 195 ± 58 mmHg, p = 0.019). Neural inspiratory time (Tin) was comparable between NAVA and PS (p = 0.566). Among potential determinant factors for oxygenation, mean airway pressure (Pmean) was lower with NAVA (10.6 ± 2.6 vs. 11.1 ± 2.4 cmH2O, p = 0.006), as was the pressure time product (PTP) (6.8 ± 3.0 vs. 9.2 ± 3.5 cmH2O 9 s, p = 0.004). There were less asynchrony events with NAVA (2.3 ± 2.0 vs. 4.4 ± 3.8, p = 0.009).Tidal volume variability was higher with NAVA (variation coefficient: 30 ± 19.5 vs. 13.5 ± 8.6, p\0.001). Inspiratory time in excess (Tiex) was lower with NAVA (56 ± 23 vs. 202 ± 200 ms, p = 0.001). CONCLUSION. Despite lower Pmean and PTP in NAVA, arterial oxygenation was improved compared to PS. As asynchronies may be associated with an increased work of breathing and a higher oxygen consumption, their decrease in number with NAVA could be an explanation for oxygenation improvement. Another explanation could be the increase in VT variability. Further studies should now be performed to confirm the potential of NAVA in improving arterial oxygenation and explore the underlying mechanisms.

Ecological assembly rules in plant communities--approaches, patterns and prospects.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

Mind the Gap. Do Proportional Electoral Systems Foster a More Equal Representation of Women and Men, Poor and Rich ?

Female gender and low income are two markers for groups that have been historically disadvantaged within most societies. The study explores two research questions related to their political representation: 1) Are parties ideologically biased towards the ideological preferences of male and rich citizens? 2) Does the proportionality of the electoral system moderate the degree of underrepresentation of women and poor citizens in the party system? A multilevel analysis of survey data from 24 parliamentary democracies indicates that there is some bias against those with low income and, at a much smaller rate, women. This has systemic consequences for the quality of representation, as the preferences of the complementary groups differ. The proportionality of the electoral system influences the degree of underrepresentation: specifically, larger district magnitudes help closing the considerable gap between rich and poor.