Search

AIM Prediction models may be useful in accurately identifying children who will benefit from growth hormone (GH) treatment. We aimed to validate the Gothenburg prediction model for this purpose. METHODS The study included prepubertal children with GH deficiency who started treatment with GH during 2004-2016 at Queen Silvia Children's Hospital, Gothenburg, based on a first-year growth prediction of ≥0.7 SDS in height according to the Gothenburg prediction model on a GH dose of 33 μg/kg/day. Observed heights retrieved from medical charts were compared with predicted heights. RESULTS The study included 121 patients (64% boys) with at least one year of data after the start of GH treatment. The median (range) GH dose was 30 (10-43) µg/kg/day for the first year and age at start of treatment was 5.32 (3-11.8) years. The model correctly excluded poor responders resulting in 119/121 (98%) patients having a height gain of at least ≥0.5 SDS in a year. However, the model underestimated relatively low predictions and overestimated relatively high predictions, with a residual standard deviation of 0.31 SDS. CONCLUSION By using a validated prediction model for GH in a clinical context, unnecessarily treating short children with an expected poor height outcome can be avoided.

PURPOSE To provide the first scrutiny of adult height prediction protocols based on automated Greulich-Pyle and Tanner-Whitehouse (TW) skeletal ages applied to elite youth soccer players from the Middle East. METHODS We examined the application of modified Bayley-Pinneau (BoneXpert®), TW-II, and TW-III protocols using mixed-longitudinal data available for 103 subjects (chronological age range, 19.4 to 27.9 yr) previously enrolled as academy student-athletes (annual screening range, one to six visits). Random-effects generalized additive models quantified the presence of systematic mean differences between actual versus predicted adult height. Effects were deemed practically equivalent based on the location of the confidence interval (95% CI) against a realistic difference value of Δ = ± 1 cm. Each model pooled residual standard deviation described the actual precision of height predictions and was used to calculate a 95% prediction interval. RESULTS The BoneXpert® method overpredicted adult height systematically at chronological ages in the range of approximately 13.5 to 14.5 yr (95% CI range, -1.9 to -1 cm) and Greulich-Pyle skeletal ages between 13.5 and 15 yr (95% CI range, -3.1 to -1 cm). Effects based on TW-II were practically equivalent across the chronological and skeletal age measurement ranges, with this protocol yielding adult height predictions with a precision (standard deviation) of approximately ±2.6 cm. The mean TW-III effects indicated systematic adult height overpredictions until the attainment of 14.5 and 15 yr of chronological age (95% CI range, -3.8 to -1.1 cm) and TW-III skeletal age (95% CI range: -5.2 to -2.3 cm), respectively. CONCLUSIONS Tanner-Whitehouse-II adult height prediction method provided more consistent estimates and can be considered the method of choice for talent development purposes in youth soccer players from the Middle East.

Data from 655 treatments of 116 studies were used in a meta-analysis to determine the daily digestible energy (DE), metabolizable energy (ME) and net energy (NE) intake of Chinese growing-finishing pigs, and to predict feed efficiency responses to change in dietary DE, ME and NE. Three alternative functions (i.e., polynomial, Bridges and asymptotic function) were employed for fitting daily DE, ME or NE intakes to mean body weight. The results showed that the three models from the current study provided reasonable fit (all R2 > 0.83) for the energy intake data. However, under the same energy system, the polynomial function had the smallest Akaike's information criteria (AIC) and residual standard deviation (RSD), followed by Bridges and asymptotic functions. The three model-generated energy intakes of growing pigs were significantly less than that of the Chinese Feeding Standard of Swine, but similar to that of the National Research Council (2012), while the values of finishing pigs were greater than both standards. Compared with those that predict feed efficiency based on DE or ME, the equation with NE as a predictor had the minimized AIC and RSD. It was also found that feed efficiency increased with increasing dietary energy density (DED), but this response varied with pig body weight, and the lighter pigs were more sensitive to DED than heavier pigs.

Aim. This work aimed to validate an assay procedure for desloratadine tablets by direct spectrophotometric method. Materials and methods. A pilot-scale batch of the pharmaceutical preparationAlerdez, film-coated tablets containing 5 mg of desloratadine, manufactured by PJSC SIC “Borshchahivskiy CPP”, Ukraine, was used as an object of the study. A UV-Vis spectrophotometer Lambda 25 (Perkin Elmer), analytical balance Mettler Toledo XP 205DR, and class A volumetric apparatus were used in the study. Validation of the procedure was performed following the metrological approach of the State Pharmacopoeia of Ukraine (SPhU), whose requirements for the target uncertainty and bias, which rest on the risk assessment of making incorrect decisions on compliance (a confidence level of 95 %), were translated into criteria for all validation characteristics recommended by ICH. All calculations were made in normalised coordinates. The linearity, accuracy and precision (repeatability) were studied in a single experiment using nine different concentrations that uniformly covered the range of ±30 % from the nominal concentration of desloratadine. For validation of the procedure, an SPhU reference standard of desloratadine was used. Results. The experiment design and validation characteristics being tested were in full compliance with ICH Q2(R1) recommendations. All performance characteristics conformed to the criteria recommended by the SPhU. Requirements for the target uncertainty (1.6 %) and bias for any systematic source of variation (≤0.51 %, negligible in relation to 1.6 %) were established. The analytical procedure was specific – the absorbance from the placebo solution was insignificant (A %=0.36). The procedure met the requirements for linearity, accuracy, and precision at the repeatability level. The residual standard deviations0was 0.34 (≤ 0.84); correlation indexRcwas 0.9998 (≥0.9991); interceptаwas 0.045 (less than its confidence interval ∆a=1.14). The confidence interval for recovery∆Z, which was used as a precision estimate, was 0.55 % (less than the target uncertainty). The mean recovery, which was used as an accuracy estimate, statistically insignificantly deviated from 100% (|Zmean‑100| = 0.022 %). The confidence interval for the intermediate precision∆intrawas 0.33 % (less than the target uncertainty). The developed analytical procedure was found to be robust. Conclusions. A spectrophotometric procedure suitable for the assay of desloratadine in film-coated tabletsAlerdezwith content limits of ±5 % was validated by the SPhU approach.

Objective Increased visit-to-visit blood pressure variability (vvBPV) has negative effects on multiple organ systems. Prior research has suggested that dihydropyridine calcium channel blockers (CCB) may reduce vvBPV, which we attempted to verify in a high-quality dataset with robust statistical methodology. Methods We performed a post hoc analysis of the SPRINT trial and included participants who were on a dihydropyridine CCB either 0 or 100% of follow-up study visits. The primary outcome was vvBPV, defined as residual standard deviation (rSD) of SBP from month 6 until study completion. We estimated the average treatment effect of the treated (ATET) after augmented inverse-probability-weighting (AIPW) matching. Results Of the 9361 participants enrolled in SPRINT, we included 5020, of whom 1959 were on a dihydropyridine CCB and 3061 were not; mean age was 67.4 ± 9.2 years, 34.5% were men, 65.9% were white, 49.4% were randomized to intensive blood pressure control, and the rSD was 10.1 ± 4.0 mmHg. Amlodipine represented greater than 95% of dihydropyridine CCB use. After AIPW matching of demographics and other antihypertensive medications, the ATET estimation for participants on a dihydropyridine CCB was an rSD that was 2.05 mmHg lower (95% CI -3.19 to -0.91). We did not find that other antihypertensive medications classes decreased vvBPV, and several increased it. Conclusion In the SPRINT trial, consistent use of a dihydropyridine CCB was associated with a 2 mmHg reduction in vvBPV. The implication of this hypothesis-generating finding in a high-quality dataset is that future trials to reduce vvBPV could consider using dihydropyridine CCBs.

Bioequivalence testing is an essential step during the development of generic drugs. Regulatory agencies have drafted recommendations and guidelines to frame this step but without finding any consensus. Different methodologies are applied depending on the geographical region. For instance, in the EU, EMA recommends using average bioequivalence test (ABE), while in the USA, FDA recommends using population bioequivalence (PBE) test. Both methods present some limitations (e.g., when batch variability is non-negligible) making it difficult to conclude to equivalence without subsequently increasing the sample size. This article proposes an alternative method to evaluate bioequivalence: between-batch bioequivalence (BBE). It is based on the comparison between the mean difference (Reference − Test) and the Reference between-batch variability. After presenting the theoretical concepts, BBE relevance is evaluated through simulation and real case (nasal spray) studies. Simulation results showed high performance of the method based on false positive and false negative rate estimations (type I and type II errors respectively). Especially, BBE has shown significantly greater true positive rates than ABE and PBE when the Reference residual standard deviation is higher than 15%, depending on the between-batch variability and the number of batches. Finally, real case applications revealed that BBE is more efficient than ABE and PBE to demonstrate equivalence, in some well-known situations where the between-batch variability is not negligible. These results suggest that BBE could be considered as an alternative to the state-of-the-art methods allowing costless development. Graphical abstract Electronic supplementary material The online version of this article (10.1208/s12248-020-00486-5) contains supplementary material, which is available to authorized users.

Hydrogen sulfide (H2S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H2S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H2S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H2S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H2S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H2S·h−1. Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

Sofosbuvir is one of the new direct-acting antiviral drugs against hepatitis C virus (HCV) infection. This drug has recently been launched into the market, and generic versions of the medication are expected to be produced by local drug producers in some countries. Therefore, new methods are required to control sofosbuvir in pharmaceuticals. In the present study, a new method based on reversed phase (RP)-ultra-high performance liquid chromatography (UHPLC) coupled to diode array detection (DAD) and mass spectrometry (MS) was developed to facilitate the qualitative and quantitative analysis of sofosbuvir in film coated tablets. A wavelength of 260 nm was selected to perform a cost-effective quantification and the method showed adequate linearity, with an R2 value of 0.9998, and acceptable values of accuracy (75%–102%) and precision (residual standard deviation, Graphical abstract fx1

Cacao (Theobroma cacao L.) is an important fruit in the Brazilian economy, which is mainly cultivated in the southern State of Bahia. The optimal stage for harvesting is a major factor for fruit quality and the knowledge on its growth curves can help, especially in identifying the ideal maturation stage for harvesting. Nonlinear regression models have been widely used for description of growth curves. However, several studies in this subject do not consider the residual analysis, the existence of a possible dependence between longitudinal observations, or the sample variance heterogeneity, compromising the modeling quality. The objective of this work was to compare the fit of nonlinear regression models, considering residual analysis and assumption violations, in the description of the cacao (clone Sial-105) fruit growth. The data evaluated were extracted from Brito and Silva (1983), who conducted the experiment in the Cacao Research Center, Ilheus, State of Bahia. The variables fruit length, diameter and volume as a function of fruit age were studied. The use of weighting and incorporation of residual dependencies was efficient, since the modeling became more consistent, improving the model fit. Considering the first-order autoregressive structure, when needed, leads to significant reduction in the residual standard deviation, making the estimates more reliable. The Logistic model was the most efficient for the description of the cacao fruit growth. O cacau é um importante produto para a economia brasileira, sendo cultivado principalmente no sul da Bahia. O ponto ótimo de colheita é um dos principais fatores de perda na qualidade do fruto e o conhecimento de suas curvas de crescimento pode auxiliar principalmente na identificação deste ponto. Os modelos de regressão não linear tem sido amplamente utilizados na descrição de curvas de crescimento. No entanto, em várias pesquisas nesse sentido não é realizada a análise de resíduos, não consideram a existência de uma possível dependência entre as observações longitudinais e nem a heterogeneidade de variâncias amostrais, comprometendo a qualidade da modelagem. Assim, este trabalho objetivou comparar o ajuste de modelos de regressão não lineares, considerando os possíveis desvios de pressuposição sobre os resíduos, na descrição do crescimento dos frutos de cacaueiro do clone Sial-105. Os dados analisados foram extraídos de Brito e Silva (1983) e correspondem a um experimento realizado no Centro de Pesquisa de Cacau, em Ilhéus-BA. As variáveis estudadas foram o comprimento, diâmetro e volume do fruto tomados em função da sua idade. O uso da ponderação e incorporação da dependência residual foi eficiente pois tornou a modelagem mais coerente melhorando a qualidade do ajuste. Considerar a estrutura auto-regressiva de primeira ordem, quando necessária, leva a redução significativa do desvio padrão residual, tornando as estimativas mais confiáveis. O modelo Logístico foi o mais eficiente na descrição do crescimento do fruto do cacau.

International audience; The objective was to compare eight methods for estimation of dairy goat body composition, by calibrating against chemical composition (water, lipid, protein, mineral and energy) measured post-mortem. The methods tested on 20 Alpine goats were body condition score (BCS), 3-dimension imaging (3D) automatic assessment of BCS or whole body scan, ultrasound, computer tomography (CT), adipose cell diameter, deuterium oxide dilution space (D 2 OS) and bioelectrical impedance spectroscopy (BIS). Regressions were tested between predictive variates derived from the methods and empty body (EB) composition. The best equations for estimation of EB lipid mass included BW combined with i) perirenal adipose tissue mass and cell diameter (R 2 = 0.95, residual standard deviation, rSD = 0.57 kg), ii) volume of fatty tissues measured by CT (R 2 = 0.92, rSD = 0.76 kg), iii) D 2 OS (R 2 = 0.91, rSD = 0.85 kg), and iv) resistance at infinite frequency from BIS (R 2 = 0.87, rSD = 1.09 kg). The D 2 OS combined with BW provided the best equation for EB protein mass (R 2 = 0.97, rSD = 0.17 kg), whereas BW alone provided a fair estimate (R 2 = 0.92, rSD = 0.25 kg). Sternal BCS combined with BW provided good estimation of EB lipid and protein mass (R 2 = 0.80 and 0.95, rSD = 1.27 and 0.22 kg, respectively). Compared to manual BCS, BCS by 3D slightly decreased the precision of the predictive equation for EB lipid (R 2 = 0.74, rSD = 1.46 kg), and did not improve the estimation of EB protein compared with BW alone. Ultrasound measurements and whole body 3D imaging methods were not satisfactory estimators of body composition (R 2 ≤ 0.40). Further developments in body composition techniques may contribute for high-throughput phenotyping of robustness.

The growth of plants and animals can be described through a growth curve. This curve is given by the equation of a nonlinear model, such as the Logistic model and the Gompertz model. The objective of this study was to adjust the Chanter model, as well as Logistic and Gompertz, using a set of cocoa (clone Sial-105) fruit whose length and diameter measurements were evaluated from 30 to 180 days after pollination, every 15 days. The Chanter model is a hybrid between the Logistic model and Gompertz model whose parameters can be interpreted similarly. A comparison of the quality of fit between the models was made using the following statistical measures: the Akaike’s information criterion (AIC), the Akaike’s weights criterion, Bayesian information criterion (BIC), residual standard deviation (RSD),the adjusted coefficient of determination (R²aj) and the measures of non-linearity Box’s bias and curvature of Bates and Watts. It was verified that the Chanter model is the most suitable one among the studied models for modeling the cocoa data. RESUMO: O crescimento de plantas e animais pode ser descrito por meio de uma curva. Essa curva é dada pela equação de um modelo não linear, como o modelo Logístico e o modelo Gompertz. O objetivo deste trabalho foi ajustar o modelo Chanter, assim como o Logístico e Gompertz, utilizando um conjunto de dados do fruto do cacaueiro do clone SIAL - 105, cujas medidas de comprimento e diâmetro foram avaliadas de 30 até 180 dias após a polinização, a cada 15 dias. O modelo Chanter é um híbrido entre o modelo Logístico e o modelo Gompertz cujos parâmetros podem ser interpretados similarmente. A avaliação da qualidade do ajuste entre os modelos foi feita utilizando as seguintes medidas estatísticas: o critério de informação de Akaike (AIC), o critério Peso de Akaike, o critério de informação de Bayes (BIC), o desvio padrão residual (DPR), o coeficiente de determinação ajustado (R²aj) e as medidas de não linearidade, vício de Box e curvatura de Bates e Watts. Verificou-se que o modelo Chanter dentre os modelos estudados neste trabalho é o mais adequado para o ajuste aos dados do fruto do cacaueiro.

The compensation of thermal errors plays a critical role in developing the machine tools of intelligent computer numerically controlled (CNC). According to the international standards, the testing, modeling, and compensation of thermal error of CNC machine tools are carried out only in a so-called idling state where the spindle is free running without any workload. However, in practical applications, machine tools are often applied in the actual cutting state with more influence factors, such as cutting parameters, cooling liquid, and cutting force. Subsequently, the thermal characteristics at idling state and actual cutting state are compared and analyzed in this paper. It was found that the thermal error compensation model under idling state is not precise enough to be applied in actual cutting state. Also, further research finds that different combinations of cutting parameters, such as spindle speed and feed rate, also have influences on the accuracy of prediction and robustness of thermal error model under actual cutting state. Therefore, the cutting parameters of spindle speed, feed rate, depth of cut, and ambient temperature are studied with the usage of the Taguchi method. Through calculating signal-to-noise ratio (SN) of each combination through residual standard deviation of thermal error model, the combination of optimal cutting parameters can be obtained. The resultant analysis shows that the thermal error model under the combination of optimal cutting parameters demonstrates higher accuracy of prediction and better robustness.

Carbon dioxide capture and storage is expected to reduce large amount of CO2 emissions from pointwise large sources, such as coal power plants, by 2030 in Japan. For offshore CO2 storage, it is necessary to monitor concentrations associated with CO2 in seawater to ensure safe storage. To do so, it is also necessary to know the baseline concentrations in the target seas. However, such concentrations have large regional and seasonal variations, mainly because of biological activity. In this study, we compared various indicators of CO2 dissolved in seawater, using the seawater off Tomakomai, Japan, observed between 2013 and 2018. Among the indicators, we found very strong correlations between [nDIC + kDO] and T and between [DIC − 0.5TA + kDO] and T. These indicators are thought to be effective for investigating the possibility of unexpected leakage of CO2 stored in sub-seabed geological formations. However, data always contain a degree of scattering, even when their correlation is very high. In the case of the seawater off Tomakomai, the data that exceeded a criteria based on the residual standard deviation of some indicators were not necessarily the same as those of the other indicators. Therefore, it is suggested that two or more, different types of indicators should be used, such as pCO2-[DO saturation] and [nDIC + kDO]-T or [DIC − 0.5TA + kDO]-T.

INTRODUCTION Vascular access dysfunction is a major cause of morbidity in patients with end-stage renal disease (ESRD) on hemodialysis (HD). Thus, identifying risk factors for vascular access failure is important. Patients on HD are routinely exposed to high blood pressure variability (BPV) during HD. However, the impact of intradialytic BPV on vascular access outcomes is unknown. Therefore, we investigated the association of intradialytic BPV with vascular access outcomes in patients on HD. METHODS One hundred and thirty patients with ESRD who created vascular access for HD were evaluated. We examined 12 dialysis sessions per patient and recorded BP five times for each session. BPV was assessed using residual standard deviation derived from the linear regression model. The patients were divided into two groups according to a level below or above the median value of intradialytic BPV and compared. The primary outcome was primary unassisted vascular access patency. FINDINGS The median time to loss of primary unassisted patency was significantly longer in low intradialytic BPV group than in high intradialytic BPV group (52 months vs. 21 months, P < 0.001) during the mean follow-up of 3.7 years. After adjustment for other variables, high intradialytic BPV was significantly associated with loss of primary unassisted vascular access patency (hazard ratio, 2.605; 95% confidence interval, 1.462-4.643; P = 0.001). DISCUSSION Our study revealed a significant correlation between intradialytic BPV and vascular access patency. Further studies are needed to identify methods for lowering BPV.

Background Electrocardiographic (ECG) safety evaluation is a required element of drug development. Performance characteristics of ECG measurement methodologies have rarely been studied prospectively. Methods We conducted a randomized, placebo-controlled, crossover study in 24 subjects to evaluate effects of moxifloxacin on the Fridericia rate-corrected QT (QTcF) interval. Five ECG replicates were obtained at 30 time points. Change from baseline QTcF (ΔQTcF) was fit by mixed-model analysis of variance to evaluate residual standard deviation. Precision was defined as intrasubject QTcF variance. Two core lab approaches were compared: QTinno, fully automated, 5 replicates and HeartSignals, computer-assisted manual, 3 replicates. Core lab values were then compared to an automated commercial algorithm (VERITAS). Results Twenty-three subjects provided 3450 ECGs potentially available for analysis. QTinno QTcF values were based upon 3419 ECGs, HeartSignals data on 2028 ECGs. Variance was similar between the QTinno and HeartSignals approaches (41.5 and 44 ms2). After excluding VERITAS QTcF measurements that deviated by >40 ms on visual review, variance in a set of 1907 common ECGs was lowest for HeartSignal, followed by QTinno and VERITAS (43.8, 52.6, 89.4 ms2) P = 0.02 HeartSignals versus QTinno, P < 0.0001 for both HeartSignals and QTinno versus VERITAS. Conclusions A fully automated core lab approach using 5 replicates and a computer-assisted manual approach using 3 replicates were equally precise. When an identical number of ECGs were compared, the computer-assisted manual method was most precise, while the commercial algorithm was relatively imprecise. Although suitable for clinical assessment the standard commercial algorithm cannot be recommended for regulated safety research.

WOS: 000290875900004, The extent of the usefulness of a lactation model depends on how well it succeeds in imitating the biological lactation process and how well it adjust for environmental and other factors that could influence production. Therefore, the objective of this study was to compare five different lactation curve models (Wood, Cobby and Le Du, Wilmink, Exponential and Parabolic Exponential model), and to find the best model that provided a good description of the lactation curve of Jersey cattle herd. Data used in this study were the first to seventh lactation official milk yield records from monthly recording of 3 630 lactations between 1984 and 2008 in the farm. The results showed that Wood model which has minimum residual standard deviation (3.562), maximum adjusted R(2) value (91.6%) and maximum persistency value (93.3%) performed the best fit to the data and allowed a suitable description of the lactation curve. It was concluded that the Wood model provided accurate estimates of milk yield for all lactation numbers because this model was found to be more superior to the other models. Consequently, the usage of Wood model would provide some useful information on genetic improvement of the Jersey breed under pasture-based dry seasonal production systems., Tubitak [TOVAG-107 O 338], This study was supported by TOVAG-107 O 338 Project of Tubitak. The authors wish to thank the staff of Karakoy State Farm for technical assistance and the Dr. N Ocak for his critical editing of the manuscript.

This experiment was conducted to evaluate the chemical composition and apparent ileal digestibility (AID) and standardized ileal digestibility (SID) of amino acids (AA) in cottonseed meals (CSM) and to develop prediction equations for estimating AA digestibility for growing pigs based on the chemical composition and AA content of CSM. 10 CSM were collected from 10 provinces in China. 11 barrows (initial body weight: 34.4 ± 1.9 kg), fitted with an ileal T-cannula, were allotted to 6 × 11 Youden square with 6 periods and 11 diets. The diets included one N-free diet and 10 CSM test diets containing 40% CSM as the sole source of AA. The nitrogen-free diet was used to measure the basal endogenous losses of CP and AA. The AID and SID for crude protein (CP), Lys, Met, Trp, and Thr among the 10 CSM differed (p

The stability of γ-hydroxybutyrate (GHB) was determined in 50 blood samples from impaired drivers after storage at 4 °: C for up to 12 months. GHB was determined in whole blood by gas chromatography-flame ionization detector (GC-FID) after conversion into γ-butyrolactone (GBL) and results were compared with LC-MS-MS. Both analytical methods showed a linear response (R(2) > 0.99) to GHB concentrations from 2 to 250 mg/kg. The mean decrease in concentration after storage was 4.8 mg/kg, with extreme changes of +13 mg/kg or -29 mg/kg. Results by the GC-FID-GBL method (y-variate) and the LC-MS-MS method (x-variate) were highly correlated (R(2) = 0.974). The regression equation was y = 0.85x + 2.2 and residual standard deviation (SD) was 7.8 mg/kg. The y-intercept (2.2 mg/kg) was not significantly different from zero (P > 0.05), although the slope of the regression line (0.85) differed from unity (P < 0.001), indicating a proportional bias of 15%. The LC-MS-MS method tended to give higher results than the GC-FID-GBL method. The mean difference (bias) was 12 mg/kg (P < 0.001). The SD of individual differences was 11.3 mg/kg and 95% limits of agreement were -11 to +33 mg/kg. The results of this study show that concentrations of GHB in whole blood are stable during storage at 4 °: C for up to 6 months.

A study was conducted to determine the performance of a low cost plantar measuring device. The aim of the device was to establish an in-shoe measurement system with high resolution and to take relatively accurate measurements. The calibration method for the smart material was established with the use of a Kistler force plate. The coefficient of determination r2 of the force against resistance calibration curve was 0.974. The residual standard deviation amounted to 13.91 N. The r2 value of the repetitive loading experiments amounted to 0.981. The residual standard deviation was 70.35 N for forces larger than 700 N. From the data obtained, the insole is deemed to be sufficiently accurate for quantitative analysis.

EnglishThe goal of this study was to elucidate the growth and development of the Asian pear fruit, on the grounds of length, diameter and fresh weight determined over time, using the non-linear Gompertz and Logistic models. The specifications of the models were assessed utilizing the R statistical software, via the least squares method and iterative Gauss-Newton process (DRAPER & SMITH, 2014). The residual standard deviation, adjusted coefficient of determination and the Akaike information criterion were used to compare the models. The residual correlations, observed in the data for length and diameter, were modeled using the second-order regression process to render the residuals independent. The logistic model was highly suitable in demonstrating the data, revealing the Asian pear fruit growth to be sigmoid in shape, showing remarkable development for three variables. It showed an average of up to 125 days for length and diameter and 140 days for fresh fruit weight, with values of 72mm length, 80mm diameter and 224g heavy fat. Key words: Biometric measurements; Asian pear; model Gompertz; logistic model portuguesEste trabalho teve por objetivo descrever o crescimento e desenvolvimento de frutos de pereira asiatica, com base no comprimento, diâmetro e peso fresco obtidos ao longo do tempo, pelos modelos nao lineares Gompertz e Logistico. Os parâmetros dos modelos foram estimados utilizando rotinas no software R, pelo metodo de minimos quadrados e processo iterativo de Gauss-Newton (DRAPER & SMITH, 2014). Os modelos foram comparados utilizando o desvio padrao residual, coeficiente de determinacao ajustado e o criterio de informacao de Akaike. A correlacao residual presente nos dados de comprimento e diâmetro foi modelada por processo auto-regressivo de segunda ordem, tornando os residuos independentes. O modelo Logistico mostrou-se mais adequado para descrever os dados, comprovando o carater sigmoidal do crescimento da pera asiatica com desenvolvimento acentuado das tres variaveis, com ate 125 dias para o comprimento e diâmetro e 140 dias para o peso fresco dos frutos, estabilizando-se, em media, com 72mm de comprimento, 80mm de diâmetro e 224g de peso fresco. Palavras-chave: medidas biometricas; pera asiatica; modelo Gompertz; modelo Logistico

Whether elevated beat-to-beat blood pressure variability (BPV) has an influence on vascular elasticity is confounded and poorly understood. This study hypothesized that the increased BPV could have an adverse effect on the vascular elasticity, as estimated by total arterial compliance (TAC), independent of blood pressure (BP) values. Beat-to-beat BP and TAC were measured in 81 hypertensive patients (experimental population) and in 80 normal adults (control population). Beat-to-beat BPV was assessed by standard deviation (SD), average real variability (ARV), residual standard deviation (RSD) and variation independent of mean (VIM). In experimental population, systolic BPV (SBPV) showed a significant correlation with TAC (SD, r = −0.326, p

Two experiments were conducted to determine the digestible energy (DE) and metabolizable energy (ME) contents of corn gluten feed (CGF) for finishing pigs and to develop equations predicting the DE and ME content from the chemical composition of the CGF samples, as well as validate the accuracy of the prediction equations. In Exp. 1, ten CGF samples from seven provinces of China were collected and fed to 66 finishing barrows (Duroc×Landrace×Yorkshire) with an initial body weight (BW) of 51.9±5.5 kg. The pigs were assigned to 11 diets comprising one basal diet and 10 CGF test diets with six pigs fed each diet. The basal diet contained corn (76%), dehulled soybean meal (21%) and premix (3%). The ten test diets were formulated by substituting 25% of the corn and dehulled soybean meal with CGF and contained corn (57%), dehulled soybean meal (15.75%), CGF (24.25%) and premix (3%). In Exp. 2, two additional CGF sources were collected as validation samples to test the accuracy of the prediction equations. In this experiment, 18 barrows (Duroc×Landrace×Yorkshire) with an initial BW of 61.1±4.0 kg were randomly allotted to be fed either the basal diet or two CGF containing diets which had a similar composition as used in Exp. 1. The DE and ME of CGF ranged from 10.37 to 12.85 MJ/kg of dry matter (DM) and 9.53 to 12.49 MJ/kg of DM, respectively. Through stepwise regression analysis, several prediction equations of DE and ME were generated. The best fit equations were: DE, MJ/kg of DM = 18.30-0.13 neutral detergent fiber-0.22 ether extract, with R(2) = 0.95, residual standard deviation (RSD) = 0.21 and p

Heap bioleaching is an established technology for recovering copper from low-grade sulphide ores. Recently, genetics-based approaches have been employed to characterize mineral-processing bacteria. In these approaches, data analysis is a key issue. Consequently, it is of fundamental importance to provide adequate mathematical models and statistical tools to draw reliable conclusions. The present work relates to current studies of the consortium of organisms inhabiting the bioleaching heap of the Escondida mine in Northern Chile. These studies aim to describe and understand the relationship between the dynamics of the community and the performance of the industrial process. Here, we consider a series of quantitative real-time polymerase chain reaction (PCR) experiments performed to quantify six different microorganisms at various stages of the bioleaching cycle. Establishing the reliability of the data obtained by real-time PCR requires the estimation of the error variance at several different levels. The results obtained show that the sampling component of the error variance is the dominant source of variability for most microorganisms. An estimate for the proportional reduction in residual standard deviation from the use of extraction and real-time PCR triplicates was found to range from 3% to 27% for the different organisms. This result suggests that triplicate assays would produce only a modest reduction in error variance compared to more frequent sampling from the heap.

Knowledge of growth in body dimension and mass is important to understanding fundamental elements of wildlife biology and ecology. We evaluated five classical growth models (Gompertz, Logistic, Monomolecular, Richards, and von Bertalanffy) in describing body length and mass growth curves as a function of age to determine which best fit wild Puma concolor coryi (Florida Panther). When used for inferences on body length and mass growth curves of both genders, the von Bertalanffy function proved to be the best-fitting theoretical equation to our data set because it used the fewest parameters derived directly from metabolic laws, had lowest residual standard deviation of data points about fitted model, with lower Akaike Information Criterion value, and largest Akaike weight. The von Bertalanffy model estimated that male asymptotic body length was 9.4% longer and mass was 33.2% heavier than for females. Both genders grew in body mass for a longer duration than length. Male-biased sexual size dimorphis...