How does the body-scale model affect back-calculated growth: the example of arctic charr Salvelinus alpinus (L.) of Lake Geneva (Switzerland)

When back-calculating fish length from scale measurements, the choice of the body-scale relationship is a fundamental step. Using data from the arctic charrSalvelinus alpinus (L.) of Lake Geneva (Switzerland) we show the need for a curvilinear model, on both statistical and biological grounds. From several 2-parameters models, the log-linear relationship appears to provide the best fit. A 3-parameters, Bertalanffy model did not improve the fit. We show moreover that using the proportional model would lead to important misinterpretations of the data.

Source wavelet estimation for waveform inversion of crosshole georadar data

AbstractFor a wide range of environmental, hydrological, and engineering applications there is a fast growing need for high-resolution imaging. In this context, waveform tomographic imaging of crosshole georadar data is a powerful method able to provide images of pertinent electrical properties in near-surface environments with unprecedented spatial resolution. In contrast, conventional ray-based tomographic methods, which consider only a very limited part of the recorded signal (first-arrival traveltimes and maximum first-cycle amplitudes), suffer from inherent limitations in resolution and may prove to be inadequate in complex environments. For a typical crosshole georadar survey the potential improvement in resolution when using waveform-based approaches instead of ray-based approaches is in the range of one order-of- magnitude. Moreover, the spatial resolution of waveform-based inversions is comparable to that of common logging methods. While in exploration seismology waveform tomographic imaging has become well established over the past two decades, it is comparably still underdeveloped in the georadar domain despite corresponding needs. Recently, different groups have presented finite-difference time-domain waveform inversion schemes for crosshole georadar data, which are adaptations and extensions of Tarantola's seminal nonlinear generalized least-squares approach developed for the seismic case. First applications of these new crosshole georadar waveform inversion schemes on synthetic and field data have shown promising results. However, there is little known about the limits and performance of such schemes in complex environments. To this end, the general motivation of my thesis is the evaluation of the robustness and limitations of waveform inversion algorithms for crosshole georadar data in order to apply such schemes to a wide range of real world problems.One crucial issue to making applicable and effective any waveform scheme to real-world crosshole georadar problems is the accurate estimation of the source wavelet, which is unknown in reality. Waveform inversion schemes for crosshole georadar data require forward simulations of the wavefield in order to iteratively solve the inverse problem. Therefore, accurate knowledge of the source wavelet is critically important for successful application of such schemes. Relatively small differences in the estimated source wavelet shape can lead to large differences in the resulting tomograms. In the first part of my thesis, I explore the viability and robustness of a relatively simple iterative deconvolution technique that incorporates the estimation of the source wavelet into the waveform inversion procedure rather than adding additional model parameters into the inversion problem. Extensive tests indicate that this source wavelet estimation technique is simple yet effective, and is able to provide remarkably accurate and robust estimates of the source wavelet in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity as well as significant ambient noise in the recorded data. Furthermore, our tests also indicate that the approach is insensitive to the phase characteristics of the starting wavelet, which is not the case when directly incorporating the wavelet estimation into the inverse problem.Another critical issue with crosshole georadar waveform inversion schemes which clearly needs to be investigated is the consequence of the common assumption of frequency- independent electromagnetic constitutive parameters. This is crucial since in reality, these parameters are known to be frequency-dependent and complex and thus recorded georadar data may show significant dispersive behaviour. In particular, in the presence of water, there is a wide body of evidence showing that the dielectric permittivity can be significantly frequency dependent over the GPR frequency range, due to a variety of relaxation processes. The second part of my thesis is therefore dedicated to the evaluation of the reconstruction limits of a non-dispersive crosshole georadar waveform inversion scheme in the presence of varying degrees of dielectric dispersion. I show that the inversion algorithm, combined with the iterative deconvolution-based source wavelet estimation procedure that is partially able to account for the frequency-dependent effects through an "effective" wavelet, performs remarkably well in weakly to moderately dispersive environments and has the ability to provide adequate tomographic reconstructions.

Stratification by smoking status reveals an association of CHRNA5-A3-B4 genotype with body mass index in never smokers.

We previously used a single nucleotide polymorphism (SNP) in the CHRNA5-A3-B4 gene cluster associated with heaviness of smoking within smokers to confirm the causal effect of smoking in reducing body mass index (BMI) in a Mendelian randomisation analysis. While seeking to extend these findings in a larger sample we found that this SNP is associated with 0.74% lower body mass index (BMI) per minor allele in current smokers (95% CI -0.97 to -0.51, P = 2.00 × 10(-10)), but also unexpectedly found that it was associated with 0.35% higher BMI in never smokers (95% CI +0.18 to +0.52, P = 6.38 × 10(-5)). An interaction test confirmed that these estimates differed from each other (P = 4.95 × 10(-13)). This difference in effects suggests the variant influences BMI both via pathways unrelated to smoking, and via the weight-reducing effects of smoking. It would therefore be essentially undetectable in an unstratified genome-wide association study of BMI, given the opposite association with BMI in never and current smokers. This demonstrates that novel associations may be obscured by hidden population sub-structure. Stratification on well-characterized environmental factors known to impact on health outcomes may therefore reveal novel genetic associations.

Marijuana use, diet, body mass index, and cardiovascular risk factors (from the CARDIA study).

Marijuana use has been associated with increased appetite, high caloric diet, acute increase in blood pressure, and decreases in high-density lipoprotein cholesterol and triglycerides. Marijuana is the most commonly used illicit drug in the United States, but its long-term effects on body mass index (BMI) and cardiovascular risk factors are unknown. Using 15 years of longitudinal data from 3,617 black and white young adults participating in the Coronary Artery Risk Development in Young Adults (CARDIA) study, we assessed whether marijuana use was associated with caloric intake, BMI, and cardiovascular risk factors. Of the 3,617 participants, 1,365 (38%) reported ever using marijuana. Marijuana use was associated with male gender, tobacco smoking, and other illicit drug use. More extensive marijuana use was associated with a higher caloric intake (2,746 kcal/day in never users to 3,365 kcal/day in those who used marijuana for > or = 1,800 days over 15 years) and alcohol intake (3.6 to 10.8 drinks/week), systolic blood pressure (112.7 to 116.5 mm Hg), and triglyceride levels (84 to 100 mg/dl or 0.95 to 1.13 mmol/L, all p values for trend < 0.001), but not with higher BMI and lipid and glucose levels. In multivariate analysis, the associations between marijuana use and systolic blood pressure and triglycerides disappeared, having been mainly confounded by greater alcohol use in marijuana users. In conclusion, although marijuana use was not independently associated with cardiovascular risk factors, it was associated with other unhealthy behaviors, such as high caloric diet, tobacco smoking, and other illicit drug use, which all have long-term detrimental effects on health.

Body surface area and body weight predict total liver volume in Western adults.

Computed tomography (CT) is used increasingly to measure liver volume in patients undergoing evaluation for transplantation or resection. This study is designed to determine a formula predicting total liver volume (TLV) based on body surface area (BSA) or body weight in Western adults. TLV was measured in 292 patients from four Western centers. Liver volumes were calculated from helical computed tomographic scans obtained for conditions unrelated to the hepatobiliary system. BSA was calculated based on height and weight. Each center used a different established method of three-dimensional volume reconstruction. Using regression analysis, measurements were compared, and formulas correlating BSA or body weight to TLV were established. A linear regression formula to estimate TLV based on BSA was obtained: TLV = -794.41 + 1,267.28 x BSA (square meters; r(2) = 0.46; P &lt;.0001). A formula based on patient weight also was derived: TLV = 191.80 + 18.51 x weight (kilograms; r(2) = 0.49; P &lt;.0001). The newly derived TLV formula based on BSA was compared with previously reported formulas. The application of a formula obtained from healthy Japanese individuals underestimated TLV. Two formulas derived from autopsy data for Western populations were similar to the newly derived BSA formula, with a slight overestimation of TLV. In conclusion, hepatic three-dimensional volume reconstruction based on helical CT predicts TLV based on BSA or body weight. The new formulas derived from this correlation should contribute to the estimation of TLV before liver transplantation or major hepatic resection.

Whole-body protein turnover and resting energy expenditure in obese, prepubertal children.

BACKGROUND: Obesity is becoming more frequent in children; understanding the extent to which this condition affects not only carbohydrate and lipid metabolism but also protein metabolism is of paramount importance. OBJECTIVE: We evaluated the kinetics of protein metabolism in obese, prepubertal children in the static phase of obesity. DESIGN: In this cross-sectional study, 9 obese children (x +/- SE: 44+/-4 kg, 30.9+/-1.5% body fat) were compared with 8 lean (28+/-2 kg ,16.8+/-1.2% body fat), age-matched (8.5+/-0.2 y) control children. Whole-body nitrogen flux, protein synthesis, and protein breakdown were calculated postprandially over 9 h from 15N abundance in urinary ammonia by using a single oral dose of [15N]glycine; resting energy expenditure (REE) was assessed by indirect calorimetry (canopy) and body composition by multiple skinfold-thickness measurements. RESULTS: Absolute rates of protein synthesis and breakdown were significantly greater in obese children than in control children (x +/- SE: 208+/-24 compared with 137+/-14 g/d, P < 0.05, and 149+/-20 compared with 89+/-13 g/d, P < 0.05, respectively). When these variables were adjusted for fat-free mass by analysis of covariance, however, the differences between groups disappeared. There was a significant relation between protein synthesis and fat-free mass (r = 0.83, P < 0.001) as well as between protein synthesis and REE (r = 0.79, P < 0.005). CONCLUSIONS: Obesity in prepubertal children is associated with an absolute increase in whole-body protein turnover that is consistent with an absolute increase in fat-free mass, both of which contribute to explaining the greater absolute REE in obese children than in control children.

The relation of body mass index and abdominal adiposity with dyslipidemia in 27 general populations of the WHO MONICA Project.

The association between adiposity measures and dyslipidemia has seldom been assessed in a multipopulational setting. 27 populations from Europe, Australia, New Zealand and Canada (WHO MONICA project) using health surveys conducted between 1990 and 1997 in adults aged 35-64 years (n = 40,480). Dyslipidemia was defined as the total/HDL cholesterol ratio >6 (men) and >5 (women). Overall prevalence of dyslipidemia was 25% in men and 23% in women. Logistic regression showed that dyslipidemia was strongly associated with body mass index (BMI) in men and with waist circumference (WC) in women, after adjusting for region, age and smoking. Among normal-weight men and women (BMI<25 kg/m(2)), an increase in the odds for being dyslipidemic was observed between lowest and highest WC quartiles (OR = 3.6, p < 0.001). Among obese men (BMI ≥ 30), the corresponding increase was smaller (OR = 1.2, p = 0.036). A similar weakening was observed among women. Classification tree analysis was performed to assign subjects into classes of risk for dyslipidemia. BMI thresholds (25.4 and 29.2 kg/m(2)) in men and WC thresholds (81.7 and 92.6 cm) in women came out at first stages. High WC (>84.8 cm) in normal-weight men, menopause in women and regular smoking further defined subgroups at increased risk. standard categories of BMI and WC, or their combinations, do not lead to optimal risk stratification for dyslipidemia in middle-age adults. Sex-specific adaptations are necessary, in particular by taking into account abdominal obesity in normal-weight men, post-menopausal age in women and regular smoking in both sexes.

Expérimentation et clinique électroencéphalographiques entre physiologie, neurologie et psychiatrie (Suisse, 1935-1965)

The electroencephalogram (EEG), invented by the German psychiatrist Hans Berger in 1924, reached the neurophysiological laboratories and several clinical contexts in the mid-30s. In Switzerland, some skeptical physiologists and enthusiastic psychiatrists paved the way for its integration, but it was only after the Second World War that an emerging field of epileptology became part of a process of technological and epistemological innovation which raised great expectations and produced a large body of research at the crossroads of physiology, neurology and psychiatry. An informal network was created, characterized by clinical, scientific and local institutional cultures. The EEG also made it possible to detect some clinical entities, not however without transforming them, as in the case of epilepsy. Some attempts to probe psychiatric diseases and subjects with the EEG are described as negotiated relationships between clinical observations, subjective manifestations or symptoms and inscriptions of a spontaneous or elicited electrical brain activity. These attempts shape a clinical and experimental cerebral subject, which is analyzed in this article from the point of view of its technical aspects and the concrete procedures on which it depends.

Correction: Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women.

This corrects the article on p. e73445 in vol. 8.]. This corrects the article "Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Non-Obese Women" , e73445. There was an error in the title of the article. The correct version of the title in the article is: Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women The correct citation is: Martin F-PJ, Montoliu I, Collino S, Scherer M, Guy P, et al. (2013) Topographical Body Fat Distribution Links to Amino Acid and Lipid Metabolism in Healthy Obese Women. PLoS ONE 8(9): e73445. doi:10.1371/journal.pone.0073445

Gentamicin Improves the Activities of Daptomycin and Vancomycin against Enterococcus faecalis In Vitro and in an Experimental Foreign-Body Infection Model.

For enterococcal implant-associated infections, the optimal treatment regimen has not been defined. We investigated the activity of daptomycin, vancomycin, and gentamicin (and their combinations) against Enterococcus faecalis in vitro and in a foreign-body infection model. Antimicrobial activity was investigated by time-kill and growth-related heat production studies (microcalorimetry) as well as with a guinea pig model using subcutaneously implanted cages. Infection was established by percutaneous injection of E. faecalis in the cage. Antibiotic treatment for 4 days was started 3 h after infection. Cages were removed 5 days after end of treatment to determine the cure rate. The MIC, the minimal bactericidal concentration (MBC) in the logarithmic phase, and the MBC in the stationary phase were 1.25, 5, and >20 μg/ml for daptomycin, 1, >64, and >64 μg/ml for vancomycin, and 16, 32, and 4 μg/ml for gentamicin, respectively. In vitro, gentamicin at subinhibitory concentrations improved the activity against E. faecalis when combined with daptomycin or vancomycin in the logarithmic and stationary phases. In the animal model, daptomycin cured 25%, vancomycin 17%, and gentamicin 50% of infected cages. In combination with gentamicin, the cure rate for daptomycin increased to 55% and that of vancomycin increased to 33%. In conclusion, daptomycin was more active than vancomycin against adherent E. faecalis, and its activity was further improved by the addition of gentamicin. Despite a short duration of infection (3 h), the cure rates did not exceed 55%, highlighting the difficulty of eradicating E. faecalis from implants already in the early stage of implant-associated infection.

Large-scale evolutionary trends of Acrochordiceratidae Arthaber, 1911 (Ammonoidea, Middle Triassic) and Cope's rule

Directed evolution of life through millions of years, such as increasing adult body size, is one of the most intriguing patterns displayed by fossil lineages. Processes and causes of such evolutionary trends are still poorly understood. Ammonoids (externally shelled marine cephalopods) are well known to have experienced repetitive morphological evolutionary trends of their adult size, shell geometry and ornamentation. This study analyses the evolutionary trends of the family Acrochordiceratidae Arthaber, 1911 from the Early to Middle Triassic (251228 Ma). Exceptionally large and bed-rock-controlled collections of this ammonoid family were obtained from strata of Anisian age (Middle Triassic) in north-west Nevada and north-east British Columbia. They enable quantitative and statistical analyses of its morphological evolutionary trends. This study demonstrates that the monophyletic clade Acrochordiceratidae underwent the classical evolute to involute evolutionary trend (i.e. increasing coiling of the shell), an increase in its shell adult size (conch diameter) and an increase in the indentation of its shell suture shape. These evolutionary trends are statistically robust and seem more or less gradual. Furthermore, they are nonrandom with the sustained shift in the mean, the minimum and the maximum of studied shell characters. These results can be classically interpreted as being constrained by the persistence and common selection pressure on this mostly anagenetic lineage characterized by relatively moderate evolutionary rates. Increasing involution of ammonites is traditionally interpreted by increasing adaptation mostly in terms of improved hydrodynamics. However, this trend in ammonoid geometry can also be explained as a case of Copes rule (increasing adult body size) instead of functional explanation of coiling, because both shell diameter and shell involution are two possible paths for ammonoids to accommodate size increase.

The association between body mass index and patients' experiences with inpatient care.

OBJECTIVE: To explore the association between patients' body mass index (BMI) and their experiences with inpatient care. DESIGN: Cross-sectional. Mail survey. SETTING: University Hospital of Geneva. PARTICIPANTS: Questionnaires were mailed to 2385 eligible adult patients, 6 weeks after discharge (response rate = 69%). MAIN OUTCOME MEASURES: Patients' experiences with care were measured using the Picker inpatient survey questionnaire. BMI was calculated using self-reported height and weight. Main dependent variables were the global Picker patient experience (PPE-15) score and nine dimension-specific problem scores, scored from 0 (no reported problems) to 1 (all items coded as problems). We used linear regressions, adjusting for age, gender, education, subjective health, smoking and hospitalization, to assess the association between patients' BMI and their experiences with inpatient care. RESULTS: Of the patients, 4.8% were underweight, 50.8% had normal weight, 30.3% were overweight and 14.1% were obese. Adjusted analysis shows that compared with normal weight, obesity was significantly associated with fewer problematic items in the surgery-related information domain, and being underweight or overweight was associated with more problematic items in the involvement of family/friends domain. The global PPE-15 score was significantly higher (more problems) for underweight patients. CONCLUSIONS: Underweight patients, but not obese patients, reported more problems during hospitalization.

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance.

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.