Analysis of heterogeneous growth changes in longitudinal height of children.

BACKGROUND: There have been methodologies developed for a wide range of longitudinal data types; nevertheless, the conventional growth study is restricted if individuals in the sample have heterogeneous growth trajectories across time. Using growth mixture modeling approaches, we aimed to investigate group-level heterogeneities in the growth trajectories of children aged 1 to 15 years. METHOD: This longitudinal study examined group-level growth heterogeneities in a sample of 3401 males and 3200 females. Data were analyzed using growth mixture modeling approaches. RESULTS: We examined different trajectories of growth change in children across four low- and middle-income countries using a data-driven growth mixture modeling technique. The study identified two-group trajectories: the most male samples group (n = 4260, 69.7%) and the most female samples group (n = 2341, 81.6%). The findings show that the two groups had different growth trajectories. Gender and country differences were shown to be related to growth factors; however, the association varied depending on the trajectory group. In both latent groups, females tended to have lower growth factors (initial height and rate of growth) than their male counterparts. Compared with children from Ethiopia, children from Peru and Vietnam tended to exhibit faster growth in height over time: In contrast, children from India showed a lower rate of change in both latent groups than that of children from Ethiopia. CONCLUSIONS: The height of children in four low- and middle-income countries showed heterogeneous changes over time with two different groups of growth trajectories.

Influence of management practices on water-related grain yield determinants.

Adequate management of N supply, plant density, row spacing, and soil cover has proved useful for increasing grain yields and/or grain yield stability of rainfed crops over the years. We review the impact of these management practices on grain yield water-related determinants: seasonal crop evapotranspiration (ET) and water use efficiency for grain production per unit of evapotranspired water during the growing season (WUEG,ET,s). We highlight a large number of conflicting results for the impact of management on ET and expose the complexity of the ET response to environmental factors. We analyse the influence of management practices on WUEG,ET,s in terms of the three main processes controlling it: (i) the proportion of transpiration in ET (T/ET), (ii) transpiration efficiency for shoot biomass production (TEB), and (iii) the harvest index. We directly relate the impact of management practices on T/ET to their effect on crop light interception and provide evidence that management practices significantly influence TEB. To optimize WUEG,ET,s, management practices should favor soil water availability during critical periods for seed set, thereby improving the harvest index. The need to improve the performance of existing crop growth models for the prediction of water-related grain yield determinants under different management practices is also discussed.

Global stability of a continuous bioreactor model under persistent variation of the dilution rate.

In this work, the global stability of a continuous bioreactor model is studied, with the concentrations of biomass and substrate as state variables, a general non-monotonic function of substrate concentration for the specific growth rate, and constant inlet substrate concentration. Also, the dilution rate is time varying but bounded, thus leading to state convergence to a compact set instead of an equilibrium point. Based on the Lyapunov function theory with dead-zone modification, the convergence of the substrate and biomass concentrations is studied. The main contributions with respect to closely related studies are: i) The convergence regions of the substrate and biomass concentrations are determined as function of the variation region of the dilution rate (D) and the global convergence to these compact sets is proved, considering monotonic and non-monotonic growth functions separately; ii) several improvements are proposed in the stability analysis, including the definition of a new dead zone Lyapunov function and the properties of its gradient. These improvements allow proving convergence of substrate and biomass concentrations to their compact sets, while tackling the interwoven and nonlinear nature of the dynamics of biomass and substrate concentrations, the non-monotonic nature of the specific growth rate, and the time-varying nature of the dilution rate. The proposed modifications are a basis for further global stability analysis of bioreactor models exhibiting convergence to a compact set instead of an equilibrium point. Finally, the theoretical results are illustrated through numerical simulation, showing the convergence of the states under varying dilution rate.

Growth estimates of young-of-the-year broadnose sevengill shark, Notorynchus cepedianus, a top predator with poorly calcified vertebrae.

The broadnose sevengill shark, Notorynchus cepedianus (Péron, 1807), is a large marine top predator in temperate coastal ecosystems. Some aspects of its life history have been determined, but its growth pattern is yet to be fully understood. The authors used a multi-modelling approach and a sensitivity test to estimate growth parameters from young-of-year (YOY) length data collected off San Antonio Cape (SAC), Argentina, a critical habitat in the Southwest Atlantic Coastal Zone (SACZ). The best selected model, a sex-combined logistic growth model, estimated an asymptotic length (L∞ ) of 92.58 cm TL (95% C.I.: 86.48-105.89 cm), a growth coefficient (K) of 0.006818 days -1 (95% C.I.: 0.004948-0.008777) and a size at birth (L0 ) of 40.73 cm. The predicted annual growth (i.e., L1 - L0 ) was 43.2 cm TL. Males had smaller L0 , higher K and achieved larger sizes after 1 year. The YOY in SAC attained a larger L1 and grew faster than their Australian and South African wild counterparts. The consistent year-round presence of YOY in the SAC highlights the importance of this area as a pupping ground and potential nursery for N. cepedianus; this has direct implications for the allocation of research and management effort for the conservation of this species in the Southwest Atlantic.

Age and growth of skipjack tuna (Katsuwonus pelamis) in the western equatorial Atlantic based on dorsal spines analysis / Idade e crescimento do bonito-listrado (Katsuwonus pelamis) no Atlântico Oeste Equatorial com base na análise dos espinhos dorsais

The skipjack tuna (Katsuwonus pelamis) is a migratory pelagic fish occurring in all tropical and subtropical oceans of the world. Due to its economic importance and the unbridled increase in fishing efforts, stocks may collapse if this resource is not managed properly. The present study aimed to estimate growth parameters from different growth models based on annual rings from the dorsal spines of skipjack tuna caught in the western equatorial Atlantic. The first dorsal spine of each individual was extracted to produce cross-sections with 0.6 to 0.8 mm in thickness. We used a multi-model approach to select the best growth model based on the Akaike information criterion (AIC). Two hundred seventy individuals were analyzed, with an average length of 49.58 ± 7.72 cm. The von Bertalanffy growth model had the best fit to the data, but the Gompertz and Logistic models also had essential support. Average asymptotic length (LL) was estimated to be 114.05 and 102.63 cm for observed and back-calculated data, respectively. The dorsal spines are indeed efficient tools for estimating growth parameters and multi-model inference is a novel approach for adjusting discrepancies that likely result from a single-model approach.

O bonito-listrado (Katsuwonus pelamis) é um peixe pelágico migratório que ocorre em todos os oceanos tropicais e subtropicais do mundo. Devido à sua importância econômica e ao aumento desen-freado do esforço de pesca, os estoques podem entrar em colapso se este recurso não for manejado adequadamente. O presente estudo teve como objetivo estimar parâmetros de crescimento para di-ferentes modelos baseados nos anéis etários formados nos espinhos dorsais do bonito-listrado cap-turado no Atlântico Oeste Equatorial. O primeiro espinho dorsal de cada indivíduo foi extraído para produzir cortes transversais com 0,6 a 0,8 mm de espessura. Utilizamos uma abordagem de múltiplos modelos para selecionar o melhor modelo de crescimento com base no critério de informação de Akaike (AIC). Foram analisados 277 indivíduos, com comprimento médio de 49,58 ± 7,72 cm. O modelo de crescimento de von Bertalanffy teve o melhor ajuste aos dados, mas os modelos de Gompertz e Logístico também tiveram um suporte essencial. O comprimento assintótico médio (LL) foi estimado em 114,05 e 102,63 cm para dados observados e retrocalculados, respectivamente. Os espinhos dorsais são de fato ferramentas eficientes para estimativa dos parâmetros de crescimento e a inferência de multi-modelos é uma nova abordagem para ajustar as discrepâncias que provavelmente resultam de uma abordagem com base em um único modelo.

Enceladus as a Potential Niche for Methanogens and Estimation of Its Biomass.

Enceladus is a potential target for future astrobiological missions. NASA's Cassini spacecraft demonstrated that the Saturnian moon harbors a salty ocean beneath its icy crust and the existence and analysis of the plume suggest water-rock reactions, consistent with the possible presence of hydrothermal vents. Particularly, the plume analysis revealed the presence of molecular hydrogen, which may be used as an energy source by microorganisms ( e.g., methanogens). This could support the possibility that populations of methanogens could establish in such environments if they exist on Enceladus. We took a macroscale approximation using ecological niche modeling to evaluate whether conditions suitable for methanogenic archaea on Earth are expected in Enceladus. In addition, we employed a new approach for computing the biomass using the Monod growth model. The response curves for the environmental variables performed well statistically, indicating that simple correlative models may be used to approximate large-scale distributions of these genera on Earth. We found that the potential hydrothermal conditions on Enceladus fit within the macroscale conditions identified as suitable for methanogens on Earth, and estimated a concentration of 1010-1011 cells/cm3.

Piecewise Modeling the Accumulated Daily Growth of COVID-19 Deaths: The Case of the State of São Paulo, Brazil.

The pandemic scenery caused by the new coronavirus, called SARS-CoV-2, increased interest in statistical models capable of projecting the evolution of the number of cases (and associated deaths) due to COVID-19 in countries, states and/or cities. This interest is mainly due to the fact that the projections may help the government agencies in making decisions in relation to procedures of prevention of the disease. Since the growth of the number of cases (and deaths) of COVID-19, in general, has presented a heterogeneous evolution over time, it is important that the modeling procedure is capable of identifying periods with different growth rates and proposing an adequate model for each period. Here, we present a modeling procedure based on the fit of a piecewise growth model for the cumulative number of deaths. We opt to focus on the modeling of the cumulative number of deaths because, other than for the number of cases, these values do not depend on the number of diagnostic tests performed. In the proposed approach, the model is updated in the course of the pandemic, and whenever a "new" period of the pandemic is identified, it creates a new sub-dataset composed of the cumulative number of deaths registered from the change point and a new growth model is chosen for that period. Three growth models were fitted for each period: exponential, logistic and Gompertz models. The best model for the cumulative number of deaths recorded is the one with the smallest mean square error and the smallest Akaike information criterion (AIC) and Bayesian information criterion (BIC) values. This approach is illustrated in a case study, in which we model the number of deaths due to COVID-19 recorded in the State of São Paulo, Brazil. The results have shown that the fit of a piecewise model is very effective for explaining the different periods of the pandemic evolution.

Simulated data from a genotype-to-phenotype crop growth model for pepper.

The data in this article includes 300 simulated two-way data tables with 200 genotypes in the rows and 12 environments in the columns each. The yield data was obtained from a genotype-to-phenotype crop growth model that was adapted for pepper. The genotypes were characterized by 237 markers covering all the 12 chromosomes, and the environments were obtained as a combination of: (i) two levels of radiation based on historical data; (ii) three levels of daily average temperatures, 15, 20 and 25 °C; and (iii) two countries, Spain and The Netherlands. 100 two-way data tables were obtained for each of the three levels of heritability in the environments, 0.3, 0.5 and 0.8. The data is available as supplementary material of this paper.

Modelling fatality curves of COVID-19 and the effectiveness of intervention strategies.

The main objective of the present article is twofold: first, to model the fatality curves of the COVID-19 disease, as represented by the cumulative number of deaths as a function of time; and second, to use the corresponding mathematical model to study the effectiveness of possible intervention strategies. We applied the Richards growth model (RGM) to the COVID-19 fatality curves from several countries, where we used the data from the Johns Hopkins University database up to May 8, 2020. Countries selected for analysis with the RGM were China, France, Germany, Iran, Italy, South Korea, and Spain. The RGM was shown to describe very well the fatality curves of China, which is in a late stage of the COVID-19 outbreak, as well as of the other above countries, which supposedly are in the middle or towards the end of the outbreak at the time of this writing. We also analysed the case of Brazil, which is in an initial sub-exponential growth regime, and so we used the generalised growth model which is more appropriate for such cases. An analytic formula for the efficiency of intervention strategies within the context of the RGM is derived. Our findings show that there is only a narrow window of opportunity, after the onset of the epidemic, during which effective countermeasures can be taken. We applied our intervention model to the COVID-19 fatality curve of Italy of the outbreak to illustrate the effect of several possible interventions.

Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th-March 30th, 2020.

The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.9 (95%CI: 0.9,1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

Early transmission dynamics of COVID-19 in a southern hemisphere setting: Lima-Peru: February 29th-March 30th, 2020.

The COVID-19 pandemic that emerged in Wuhan China has generated substantial morbidity and mortality impact around the world during the last four months. The daily trend in reported cases has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil followed by Peru as of April 15th, 2020. Although Peru implemented a range of social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to accumulate in this country. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru. We estimated the reproduction number, R, during the early transmission phase in Lima from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place. Prior to the implementation of the social distancing measures in Lima, the local incidence curve by the date of symptoms onset displays near exponential growth dynamics with the mean scaling of growth parameter, p, estimated at 0.96 (95% CI: 0.87, 1.0) and the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped slow down the spread of the novel coronavirus, with the nearly exponential growth trend shifting to an approximately linear growth trend soon after the broad scale social distancing interventions were put in place by the government. While the interventions appear to have slowed the transmission rate in Lima, the number of new COVID-19 cases continue to accumulate, highlighting the need to strengthen social distancing and active case finding efforts to mitigate disease transmission in the region.

Analysis of a generalized Fujikawa's growth model.

We analyze a generalized form of the Fujikawas growth model which involves an adaptation function that enhances the representation of the lag phase. This model is autonomous, and combines a power law term, a saturation term and an adaptation function that suppresses the growth rate during initial period corresponding to the lag phase. The properties of the adaptation function are determined, and the proposed model is examined separately for the regular measure and the logarithmic measure, including: Convergence and boundedness properties; population at the inflection point; conditions for the existence of the inflection point and lag phase; effect of model parameters on the existence of the inflection point and lag phase; population size of the inflection point under limiting values of the model parameters; and parameter values that lead to inflection point located at the mean value of the curve. Different combinations of model parameters lead to different possibilities for the existence of the inflection point and the lag phase. It was noticed that the power law term has a strong effect on the representation of the exponential growth phase, whereas the adaptation function has a strong effect on the representation of the lag phase. The lag phase duration depends on the exponent parameter of the adaptation function, and its dependence with respect to the power law parameter is low. Also, an approach is proposed for the analytical determination of the lag time, based on the application of the classical approach to a simplified model. Ascertained lag time values were obtained, what confirms the assumptions. At last, the model is applied to experimental data.

Production of annual ryegrass with different doses of nitrogen fertilization in topdressing / Produção de azevém sob doses de adubação nitrogenada em cobertura

The objective of this study was to assess the growth of annual ryegrass (Lolium multiflorum) cv. BRS Ponteio with different doses of nitrogen applied in the pasture, thereby adjusting their growth to the exponential growth model. A randomized block design was used with five nitrogen application rates (0, 150, 250, 350, and 450 kg N ha-1) and four replicates, applied in installments. Each plot measured 9 m2. On April 15, 2014, 25 kg ha-1 of viable pure seeds of annual ryegrass were sown at a depth of 0.02 m, in 18 rows spaced at 0.17 m in each plot. Growth in the control treatment (zero nitrogen) pasture lasted 167 days with only three cuts, whereas in pastures treated with 350 and 450 kg N ha-1, growth was extended for an additional 45 days with a 333% increase in the number of cuts. The pastures were used for the same duration (188 days) in the treatments with 150 and 250 kg N ha-1, however, increased nitrogen resulted in two additional cuts and a shorter time interval between cuts. The time interval between each cut and the degree-days interacted dynamically causing distinct growth. Growth of the annual ryegrass BRS Ponteio without nitrogen application is poor and cannot be represented even by a first order linear model. The application of nitrogen topdressing, in the form of urea, decreases the time interval between cuts, increases the dry matter production per hectare, stimulates this production, and follows the exponential growth model.(AU)

Objetivou-se estudar a produção da cultura de azevém anual (Lolium multiflorum) BRS Ponteio com diferentes doses de nitrogênio aplicadas em cobertura ajustando-as ao modelo de crescimento exponencial. Foi utilizado delineamento completamente casualizado com quatro repetições por tratamentos com parcelas de 9m2 de área útil, nas quais foram distribuídos os tratamentos: 0, 150, 250, 350 e 450 quilogramas de nitrogênio por hectare aplicados de forma parcelada. No dia 15 de abril de 2014 realizou-se a semeadura do azevém na densidade de 25 kg de sementes puras viáveis ha-1 na profundidade de 0,02 m, com 18 linhas em cada parcela espaçadas 0,17 m. No tratamento testemunha (zero de nitrogênio) o pasto durou 167 dias com apenas três cortes, enquanto nas doses de 350 e 450 kg de nitrogênio por hectare a espécie estendeu-se por mais 45 dias com número de cortes 333% maior. Nos tratamentos 150 e 250 quilogramas de nitrogênio por hectare verificou-se que o tempo de utilização da pastagem foi o mesmo, 188 dias, mas houve diferença de dois cortes, ou seja, as diferentes doses de nitrogênio impactam sobre os intervalos entre cortes. O intervalo de dias entre cada corte e os graus-dia interagem de forma dinâmica ocasionando crescimento distintos. O cultivo de azevém anual BRS Ponteio sem aplicação de nitrogênio é limitado e não apresenta ajuste nem mesmo a modelo linear de primeira ordem. A aplicação de nitrogênio em cobertura na forma de ureia diminui o intervalo entre cortes e aumenta a produção de matéria seca por hectare. A aplicação de nitrogênio em cobertura na forma de ureia estimula a produção de matéria seca, seguindo o modelo de crescimento exponencial.(AU)

Production of annual ryegrass with different doses of nitrogen fertilization in topdressing / Produção de azevém sob doses de adubação nitrogenada em cobertura

The objective of this study was to assess the growth of annual ryegrass (Lolium multiflorum) cv. BRS Ponteio with different doses of nitrogen applied in the pasture, thereby adjusting their growth to the exponential growth model. A randomized block design was used with five nitrogen application rates (0, 150, 250, 350, and 450 kg N ha-1) and four replicates, applied in installments. Each plot measured 9 m2. On April 15, 2014, 25 kg ha-1 of viable pure seeds of annual ryegrass were sown at a depth of 0.02 m, in 18 rows spaced at 0.17 m in each plot. Growth in the control treatment (zero nitrogen) pasture lasted 167 days with only three cuts, whereas in pastures treated with 350 and 450 kg N ha-1, growth was extended for an additional 45 days with a 333% increase in the number of cuts. The pastures were used for the same duration (188 days) in the treatments with 150 and 250 kg N ha-1, however, increased nitrogen resulted in two additional cuts and a shorter time interval between cuts. The time interval between each cut and the degree-days interacted dynamically causing distinct growth. Growth of the annual ryegrass BRS Ponteio without nitrogen application is poor and cannot be represented even by a first order linear model. The application of nitrogen topdressing, in the form of urea, decreases the time interval between cuts, increases the dry matter production per hectare, stimulates this production, and follows the exponential growth model.

Objetivou-se estudar a produção da cultura de azevém anual (Lolium multiflorum) BRS Ponteio com diferentes doses de nitrogênio aplicadas em cobertura ajustando-as ao modelo de crescimento exponencial. Foi utilizado delineamento completamente casualizado com quatro repetições por tratamentos com parcelas de 9m2 de área útil, nas quais foram distribuídos os tratamentos: 0, 150, 250, 350 e 450 quilogramas de nitrogênio por hectare aplicados de forma parcelada. No dia 15 de abril de 2014 realizou-se a semeadura do azevém na densidade de 25 kg de sementes puras viáveis ha-1 na profundidade de 0,02 m, com 18 linhas em cada parcela espaçadas 0,17 m. No tratamento testemunha (zero de nitrogênio) o pasto durou 167 dias com apenas três cortes, enquanto nas doses de 350 e 450 kg de nitrogênio por hectare a espécie estendeu-se por mais 45 dias com número de cortes 333% maior. Nos tratamentos 150 e 250 quilogramas de nitrogênio por hectare verificou-se que o tempo de utilização da pastagem foi o mesmo, 188 dias, mas houve diferença de dois cortes, ou seja, as diferentes doses de nitrogênio impactam sobre os intervalos entre cortes. O intervalo de dias entre cada corte e os graus-dia interagem de forma dinâmica ocasionando crescimento distintos. O cultivo de azevém anual BRS Ponteio sem aplicação de nitrogênio é limitado e não apresenta ajuste nem mesmo a modelo linear de primeira ordem. A aplicação de nitrogênio em cobertura na forma de ureia diminui o intervalo entre cortes e aumenta a produção de matéria seca por hectare. A aplicação de nitrogênio em cobertura na forma de ureia estimula a produção de matéria seca, seguindo o modelo de crescimento exponencial.

Topography and neighborhood crowding can interact to shape species growth and distribution in a diverse Amazonian forest.

Abiotic constraints and biotic interactions act simultaneously to shape communities. However, these community assembly mechanisms are often studied independently, which can limit understanding of how they interact to affect species dynamics and distributions. We develop a hierarchical Bayesian neighborhood modeling approach to quantify the simultaneous effects of topography and crowding by neighbors on the growth of 124,704 individual stems ≥1 cm DBH for 1,047 tropical tree species in a 25-ha mapped rainforest plot in Amazonian Ecuador. We build multi-level regression models to evaluate how four key functional traits (specific leaf area, maximum tree size, wood specific gravity and seed mass) mediate tree growth response to topography and neighborhood crowding. Tree growth is faster in valleys than on ridges and is reduced by neighborhood crowding. Topography and crowding interact to influence tree growth in ~10% of the species. Specific leaf area, maximum tree size and seed mass are associated with growth responses to topography, but not with responses to neighborhood crowding or with the interaction between topography and crowding. In sum, our study reveals that topography and neighborhood crowding each influence tree growth in tropical forests, but act largely independently in shaping species distributions. While traits were associated with species response to topography, their role in species response to neighborhood crowding was less clear, which suggests that trait effects on neighborhood dynamics may depend on the direction (negative/positive) and degree of symmetry of biotic interactions. Our study emphasizes the importance of simultaneously assessing the individual and interactive role of multiple mechanisms in shaping species dynamics in high diversity tropical systems.

Estimation of tumour volume at therapy initiation by back-extrapolating the post-therapy regression curve of tumour volume

Background: Tumour volume at therapy initiation, Vi, is rarely available in cancer patients, and the last pre-treatment tumour volume available is from previous diagnostic imaging (Vd). Therapeutic efficacy is thus evaluated by comparing tumour volume after treatment with Vd, instead of Vi, which results in underestimation of treatment efficacy. Vi, together with Vd, can also be used for estimation of the natural growth rate of tumour valuable for, e.g., screening programs, prognostication and individualised treatment planning such as chemotherapy scheduling. The aim of this work was to study the feasibility of estimating Vi by back-extrapolating the post-therapy regression of tumour volume, based on data from animal model. Methods: Nude mice bearing human neuroendocrine GOT1 tumour cell line were treated with 177Lu-DOTA-TATE. Tumour volumes were measured regularly after therapy and Vi was estimated by back-extrapolation of (a) linear and (b) exponential regression lines of the two earliest post-therapy tumour volumes and (c) the long-term exponential regression of tumour volume. The estimated Vi values (Vest) were compared with the measured volume of tumour at therapy initiation. Results: The linear regression of the two earliest post-therapy tumour volumes gave the best estimate for Vi (Vest = 0.91 Vi, p < 0.00001), compared with the exponential regression models either on short-term (Vest = 2.30 Vi, p < 0.01), or long-term (Vest = 0.93 Vi, non-significant) follow up of tumour volume after therapy. Conclusion: Back-extrapolation of the early linear regression of tumour volume after therapy gave the best estimate for tumour volume at time of therapy initiation. This estimate can be used as baseline for treatment efficacy evaluation or for estimation of the natural growth rate of tumour (together with the measured tumour volume at pre-treatment diagnostic imaging)

Logistic growth models of China pinks, cultivated on seven substrates, as a function of degree days / Modelo logístico de crescimento de cravina de jardim cultivada em sete substratos em função da soma térmica

ABSTRACT: The objective of this study was to characterize the height (H) and leaf number (LN) of China pinks, grown in seven substrates, as a function of degree days, using the logistic growth model. H and LN were measured from 56 plants per substrate, for 392 plants in total. Plants that were grown on substrates formed of 50% soil with 50% rice husk ash (50% S + 50% RH) and 80% rice husk ash with 20% worm castings (80% RH + 20% W) had the longest vegetative growth period (74d), corresponding to 1317.9ºCd. The logistic growth model, adjusted for H, showed differences in the estimation of maximum expected height (α) between the substrates, with values between 10.47cm for 50% S + 50% RH and 35.75cm for Mecplant(r). When α was estimated as LN, variation was also observed between the different substrates, from approximately 30 leaves on plants growing on 50% S + 50% RH to 34 leaves on the plants growing on the substrate formed of 80% RH + 20% W. Growth of China pinks can be characterized using H or LN in the logistic growth model as a function of degree days, being the provided plants adequately fertilized. The best substrates in terms of maximum height and leaf number were 80% soil + 20% worm castings and Mecplant(r). However, users must recalibrate the model with the estimated parameters before applying it to different growing conditions.

RESUMO: O objetivo do estudo foi caracterizar a altura (H) e o número de folhas (NF), pelo modelo logístico, de cravina de jardim cultivada em sete substratos em função da soma térmica. Foram avaliadas a H e o NF de 56 plantas por substrato, totalizando 392 plantas ajustadas. As plantas dos substratos compostos de: 50% de solo e 50% de cinzas de casca de arroz (50% S + 50% CA); e 80% cinzas de casca de arroz e 20% húmus de minhoca (80% CA + 20% H) tiveram o maior ciclo, de 74 dias, e o completaram com soma térmica de 1317,9ºC dia. O modelo logístico ajustado para H apresentou diferenças para a estimativa da altura máxima esperada (α) entre os substratos, com valores de 10,47cm para 50% S + 50% CA e, 35,75cm, para o substrato Mecplant(r). Para o NF, observou-se que α teve menor variação entre os substratos, desde aproximadamente 30 folhas, nas plantas do substrato 50% S + 50% CA até 34 folhas, nas plantas do substrato 80% CA + 20% H. O crescimento de cravina de jardim, a partir das variáveis estudadas, pode ser caracterizado pelo modelo logístico, em função da soma térmica acumulada, quando as plantas estão sem restrições nutricionais. Considerando a altura máxima e o número máximo de folhas, os melhores substratos foram o composto de 80% de solo + 20% húmus de minhoca e o Mecplant(r). Entretanto, os usuários devem testar as calibrações do modelo, com os parâmetros sugeridos, antes de aplicar o modelo para outras condições climáticas.

Quality of life of residents living in a city hosting mega-sport events: a longitudinal study.

BACKGROUND: It remains unknown whether and when the hosting of mega-sport events increases quality of life of host city residents. The aim of this study is to assess the changes in quality of life of host city residents over the course of hosting a mega-sport event until three months after the event, depending on residents' perception of the atmosphere during the event. METHODS: The study was conducted in Rio de Janeiro, one of the host cities of the 2014 FIFA World Cup in soccer. Participants were recruited from a Brazilian market research agency's panel and surveyed online. The WHOQOL-BREF was used to measure quality of life of residents of Rio de Janeiro (n = 281) in three waves in the context of the 2014 FIFA World Cup. Perceived atmosphere at the event was measured via an established scale. Piecewise latent growth models were used to analyze individual changes in the four domains of quality of life per se and depending on perceived atmosphere. RESULTS: There was no change in quality of life with respect to physical, social, psychological, and environmental health for all participants during the course of the event. However, residents who perceived a positive atmosphere rated the social and environmental domains of quality of life more positively right after the end (vs. at the beginning) of the World Cup. This increase sustained until three months after the event. Physical health (particularly at high levels of perceived atmosphere) and psychological health decreased from right after the event until three months after. CONCLUSIONS: There was no positive effect of the hosting of the mega-sport event on the four quality of life domains of the panel members (who were residents of a city hosting a mega-sport event) per se. The individual changes in quality of life vary by perception of atmosphere and by domain of quality of life.

Functional trait differences influence neighbourhood interactions in a hyperdiverse Amazonian forest.

As distinct community assembly processes can produce similar community patterns, assessing the ecological mechanisms promoting coexistence in hyperdiverse rainforests remains a considerable challenge. We use spatially explicit neighbourhood models of tree growth to quantify how functional trait and phylogenetic similarities predict variation in growth and crowding effects for the 315 most abundant tree species in a 25-ha lowland rainforest plot in Ecuador. We find that functional trait differences reflect variation in (1) species maximum potential growth, (2) the intensity of interspecific interactions for some species, and (3) species sensitivity to neighbours. We find that neighbours influenced tree growth in 28% of the 315 focal tree species. Neighbourhood effects are not detected in the remaining 72%, which may reflect the low statistical power to model rare taxa and/or species insensitivity to neighbours. Our results highlight the spectrum of ways in which functional trait differences can shape community dynamics in highly diverse rainforests.

Logistic growth models of China pinks, cultivated on seven substrates, as a function of degree days / Modelo logístico de crescimento de cravina de jardim cultivada em sete substratos em função da soma térmica

The objective of this study was to characterize the height (H) and leaf number (LN) of China pinks, grown in seven substrates, as a function of degree days, using the logistic growth model. H and LN were measured from 56 plants per substrate, for 392 plants in total. Plants that were grown on substrates formed of 50% soil with 50% rice husk ash (50% S + 50% RH) and 80% rice husk ash with 20% worm castings (80% RH + 20% W) had the longest vegetative growth period (74d), corresponding to 1317.9ºCd. The logistic growth model, adjusted for H, showed differences in the estimation of maximum expected height () between the substrates, with values between 10.47cm for 50% S + 50% RH and 35.75cm for Mecplant(r). When was estimated as LN, variation was also observed between the different substrates, from approximately 30 leaves on plants growing on 50% S + 50% RH to 34 leaves on the plants growing on the substrate formed of 80% RH + 20% W. Growth of China pinks can be characterized using H or LN in the logistic growth model as a function of degree days, being the provided plants adequately fertilized. The best substrates in terms of maximum height and leaf number were 80% soil + 20% worm castings and Mecplant(r). However, users must recalibrate the model with the estimated parameters before applying it to different growing conditions.(AU)

O objetivo do estudo foi caracterizar a altura (H) e o número de folhas (NF), pelo modelo logístico, de cravina de jardim cultivada em sete substratos em função da soma térmica. Foram avaliadas a H e o NF de 56 plantas por substrato, totalizando 392 plantas ajustadas. As plantas dos substratos compostos de: 50% de solo e 50% de cinzas de casca de arroz (50% S + 50% CA); e 80% cinzas de casca de arroz e 20% húmus de minhoca (80% CA + 20% H) tiveram o maior ciclo, de 74 dias, e o completaram com soma térmica de 1317,9ºC dia. O modelo logístico ajustado para H apresentou diferenças para a estimativa da altura máxima esperada (α) entre os substratos, com valores de 10,47cm para 50% S + 50% CA e, 35,75cm, para o substrato Mecplant(r). Para o NF, observou-se que teve menor variação entre os substratos, desde aproximadamente 30 folhas, nas plantas do substrato 50% S + 50% CA até 34 folhas, nas plantas do substrato 80% CA + 20% H. O crescimento de cravina de jardim, a partir das variáveis estudadas, pode ser caracterizado pelo modelo logístico, em função da soma térmica acumulada, quando as plantas estão sem restrições nutricionais. Considerando a altura máxima e o número máximo de folhas, os melhores substratos foram o composto de 80% de solo + 20% húmus de minhoca e o Mecplant(r). Entretanto, os usuários devem testar as calibrações do modelo, com os parâmetros sugeridos, antes de aplicar o modelo para outras condições climáticas.(AU)