Generalized log-gamma regression models with cure fraction

In this paper, the generalized log-gamma regression model is modified to allow the possibility that long-term survivors may be present in the data. This modification leads to a generalized log-gamma regression model with a cure rate, encompassing, as special cases, the log-exponential, log-Weibull and log-normal regression models with a cure rate typically used to model such data. The models attempt to simultaneously estimate the effects of explanatory variables on the timing acceleration/deceleration of a given event and the surviving fraction, that is, the proportion of the population for which the event never occurs. The normal curvatures of local influence are derived under some usual perturbation schemes and two martingale-type residuals are proposed to assess departures from the generalized log-gamma error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed.

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model.

A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

A model of cellular dosimetry for macroscopic tumors in radiopharmaceutical therapy.

PURPOSE: In the radiopharmaceutical therapy approach to the fight against cancer, in particular when it comes to translating laboratory results to the clinical setting, modeling has served as an invaluable tool for guidance and for understanding the processes operating at the cellular level and how these relate to macroscopic observables. Tumor control probability (TCP) is the dosimetric end point quantity of choice which relates to experimental and clinical data: it requires knowledge of individual cellular absorbed doses since it depends on the assessment of the treatment's ability to kill each and every cell. Macroscopic tumors, seen in both clinical and experimental studies, contain too many cells to be modeled individually in Monte Carlo simulation; yet, in particular for low ratios of decays to cells, a cell-based model that does not smooth away statistical considerations associated with low activity is a necessity. The authors present here an adaptation of the simple sphere-based model from which cellular level dosimetry for macroscopic tumors and their end point quantities, such as TCP, may be extrapolated more reliably. METHODS: Ten homogenous spheres representing tumors of different sizes were constructed in GEANT4. The radionuclide 131I was randomly allowed to decay for each model size and for seven different ratios of number of decays to number of cells, N(r): 1000, 500, 200, 100, 50, 20, and 10 decays per cell. The deposited energy was collected in radial bins and divided by the bin mass to obtain the average bin absorbed dose. To simulate a cellular model, the number of cells present in each bin was calculated and an absorbed dose attributed to each cell equal to the bin average absorbed dose with a randomly determined adjustment based on a Gaussian probability distribution with a width equal to the statistical uncertainty consistent with the ratio of decays to cells, i.e., equal to Nr-1/2. From dose volume histograms the surviving fraction of cells, equivalent uniform dose (EUD), and TCP for the different scenarios were calculated. Comparably sized spherical models containing individual spherical cells (15 microm diameter) in hexagonal lattices were constructed, and Monte Carlo simulations were executed for all the same previous scenarios. The dosimetric quantities were calculated and compared to the adjusted simple sphere model results. The model was then applied to the Bortezomib-induced enzyme-targeted radiotherapy (BETR) strategy of targeting Epstein-Barr virus (EBV)-expressing cancers. RESULTS: The TCP values were comparable to within 2% between the adjusted simple sphere and full cellular models. Additionally, models were generated for a nonuniform distribution of activity, and results were compared between the adjusted spherical and cellular models with similar comparability. The TCP values from the experimental macroscopic tumor results were consistent with the experimental observations for BETR-treated 1 g EBV-expressing lymphoma tumors in mice. CONCLUSIONS: The adjusted spherical model presented here provides more accurate TCP values than simple spheres, on par with full cellular Monte Carlo simulations while maintaining the simplicity of the simple sphere model. This model provides a basis for complementing and understanding laboratory and clinical results pertaining to radiopharmaceutical therapy.

On the unification of long-term survival models

In this paper we extend the long-term survival model proposed by Chen et al. [Chen, M.-H., Ibrahim, J.G., Sinha, D., 1999. A new Bayesian model for survival data with a surviving fraction. journal of the American Statistical Association 94, 909-919] via the generating function of a real sequence introduced by Feller [Feller, W., 1968. An Introduction to Probability Theory and its Applications, third ed., vol. 1, Wiley, New York]. A direct consequence of this new formulation is the unification of the long-term survival models proposed by Berkson and Gage [Berkson, J., Gage, R.P., 1952. Survival cure for cancer patients following treatment. journal of the American Statistical Association 47, 501-515] and Chen et al. (see citation above). Also, we show that the long-term survival function formulated in this paper satisfies the proportional hazards property if, and only if, the number of competing causes related to the occurrence of an event of interest follows a Poisson distribution. Furthermore, a more flexible model than the one proposed by Yin and Ibrahim [Yin, G., Ibrahim, J.G., 2005. Cure rate models: A unified approach. The Canadian journal of Statistics 33, 559-570] is introduced and, motivated by Feller`s results, a very useful competing index is defined. (c) 2008 Elsevier B.V. All rights reserved.

Modelo de tempo de falha acelerado com fração de cura : uma abordagem unificada

In this work we study the accelerated failure-time generalized Gamma regression models with a unified approach. The models attempt to estimate simultaneously the effects of covariates on the acceleration/deceleration of the timing of a given event and the surviving fraction. The method is implemented in the free statistical software R. Finally the model is applied to a real dataset referring to the time until the return of the disease in patients diagnosed with breast cancer

Is glutathione an important neuroprotective effector molecule against amyloid beta toxicity?

Cellular thiols are critical moieties in signal transduction, regulation of gene expression, and ultimately are determinants of specific protein activity. Whilst protein bound thiols are the critical effector molecules, low molecular weight thiols, such as glutathione, play a central role in cytoprotection through (1) direct consumption of oxidants, (2) regeneration of protein thiols and (3) export of glutathione containing mixed disulphides. The brain is particularly vulnerable to oxidative stress, as it consumes 20% of oxygen load, contains high concentrations of polyunsaturated fatty acids and iron in certain regions, and expresses low concentrations of enzymic antioxidants. There is substantial evidence for a role for oxidative stress in neurodegenerative disease, where excitotoxic, redox cycling and mitochondrial dysfunction have been postulated to contribute to the enhanced oxidative load. Others have suggested that loss of important trophic factors may underlie neurodegeneration. However, the two are not mutually exclusive; using cell based model systems, low molecular weight antioxidants have been shown to play an important neuroprotective role in vitro, where neurotrophic factors have been suggested to modulate glutathione levels. Glutathione levels are regulated by substrate availability, synthetic enzyme and metabolic enzyme activity, and by the presence of other antioxidants, which according to the redox potential, consume or regenerate GSH from its oxidised partner. Therefore we have investigated the hypothesis that amyloid beta neurotoxicity is mediated by reactive oxygen species, where trophic factor cytoprotection against oxidative stress is achieved through regulation of glutathione levels. Using PC12 cells as a model system, amyloid beta 25-35 caused a shift in DCF fluorescence after four hours in culture. This fluorescence shift was attenuated by both desferioxamine and NGF. After four hours, cellular glutathione levels were depleted by as much as 75%, however, 24 hours following oxidant exposure, glutathione concentration was restored to twice the concentration seen in controls. NGF prevented both the loss of viability seen after 24 hours amyloid beta treatment and also protected glutathione levels. NGF decreased the total cellular glutathione concentration but did not affect expression of GCS. In conclusion, loss of glutathione precedes cell death in PC12 cells. However, at sublethal doses the surviving fraction respond to oxidative stress by increasing glutathione levels, where this is achieved, at least in part, at the gene level through upregulation of GCS. Whilst NGF does protect against oxidative toxicity, this is not achieved through upregulation of GCS or glutathione.

Clinical outcomes of patients with low-flow, low-gradient, severe aortic stenosis and either preserved or reduced ejection fraction undergoing transcatheter aortic valve implantation

AIMS Our aim was to evaluate the invasive haemodynamic indices of high-risk symptomatic patients presenting with 'paradoxical' low-flow, low-gradient, severe aortic stenosis (AS) (PLF-LG) and low-flow, low-gradient severe AS (LEF-LG) and to compare clinical outcomes following transcatheter aortic valve implantation (TAVI) among these challenging AS subgroups. METHODS AND RESULTS Of 534 symptomatic patients undergoing TAVI, 385 had a full pre-procedural right and left heart catheterization. A total of 208 patients had high-gradient severe AS [HGAS; mean gradient (MG) ≥40 mmHg], 85 had PLF-LG [MG ≤ 40 mmHg, indexed aortic valve area [iAVA] ≤0.6 cm(2) m(-2), stroke volume index ≤35 mL/m(2), ejection fraction (EF) ≥50%], and 61 had LEF-LG (MG ≤ 40 mmHg, iAVA ≤0.6 cm(2) m(-2), EF ≤40%). Compared with HGAS, PLF-LG and LEF-LG had higher systemic vascular resistances (HGAS: 1912 ± 654 vs. PLF-LG 2006 ± 586 vs. LEF-LG 2216 ± 765 dyne s m(-5), P = 0.007) but lower valvulo-arterial impedances (HGAS: 7.8 ± 2.7 vs. PLF-LG 6.9 ± 1.9 vs. LEF-LG 7.7 ± 2.5 mmHg mL(-1) m(-2), P = 0.027). At 30 days, no differences in cardiac death (6.5 vs. 4.9 vs. 6.6%, P = 0.90) or death (8.4 vs. 6.1 vs. 6.6%, P = 0.88) were observed among HGAS, PLF-LG, and LEF-LG groups, respectively. At 1 year, New York Heart Association functional improvement occurred in most surviving patients (HGAS: 69.2% vs. PLF-LG 71.7% vs. LEF-LG 89.3%, P = 0.09) and no significant differences in overall mortality were observed (17.6 vs. 20.5 vs. 24.5%, P = 0.67). Compared with HGAS, LEF-LG had a higher 1 year cardiac mortality (adjusted hazard ratio 2.45, 95% confidence interval 1.04-5.75, P = 0.04). CONCLUSION TAVI in PLF-LG or LEF-LG patients is associated with overall mortality rates comparable with HGAS patients and all groups profit symptomatically to a similar extent.

Gastroprotective Effects (in Rodents) Of A Flavonoid Rich Fraction Obtained From Syngonanthus Macrolepsis.

Syngonanthus macrolepis, popularly known in Brazil as 'sempre-vivas', is a plant from the family Eriocaulaceae, it is found in the states of Minas Gerais and Bahia. The species contains a variety of constituents, including flavonoids with gastroprotective effect. In this work, a flavonoid-rich fraction (Sm-FRF) obtained from scapes of S. macrolepis was investigated for preventing gastric ulceration in mice and rats. The activity was evaluated in models of induced gastric ulcer (absolute ethanol, stress, non-steroidal anti-inflammatory drugs and pylorus ligation). The cytoprotective mechanisms of the Sm-FRF in relation to sulfhydryl (SH) groups, nitric oxide (NO) and antioxidant enzymes were also evaluated. The Sm-FRF (100 mg/kg, p.o.) significantly reduced gastric injury in all models, and did not alter gastric juice parameters after pylorus ligation. The results indicate significant gastroprotective activity for the Sm-FRF, which probably involves the participation of both SH groups and the antioxidant system. Both are integral parts of the gastrointestinal mucosa's cytoprotective mechanisms against aggressive factors.

Productive performance and milk protein fraction composition of dairy cows supplemented with sodium monensin

The objective of this work was to evaluate the levels of sodium monensin on lactating cows and their effects on productive performance and milk protein fraction composition. It was used 12 Holstein cows, distributed in four balanced 3 × 3 Latin squares, and fed three diets: one control without monensin, and two diets with monensin at the levels of 24 or 48 mg/kg DM added to the concentrate. Milk production was daily measured throughout the entire experimental period. The samples used for analysis of milk composition were collected on two alternated days from the two daily milking. Non-protein nitrogen, total nitrogen and non-casein nitrogen contents were directly evaluated in the milk, and casein, whey protein and true protein contents were indirectly determined. The use of monensin in the rations reduced dry matter and nutrient intake, especially when diet with 48 mg/kg of dry matter was given. The ration with 24 mg/kg of DM increased milk production, with or without correction, and also fat and lactose yield, and it improved productive efficiency. The levels of monensin in the ratios did not influence contents of milk crude protein, non-protein nitrogen, non-casein nitrogen, true protein, casein, casein/true protein ratio, whey protein, and of all those fractions expressed as percentage of crude protein. The utilization of monensin in the ratio at the dose of 24 mg/kg of DM influences positively the productive performance of lactating cows, and it does not influence the composition of milk protein fractions.

Productive performance and composition of milk protein fraction in dairy cows supplemented with fat sources

The objective of this study was to evaluate the use of fat sources in rations for lactating cows on the productive performance and composition of milk protein fraction. Twelve Holstein cows were used, grouped in three balanced 4 × 4 Latin squares, fed with the following rations: control; refined soybean oil; whole raw soybean; and calcium salts of unsaturated fatty acid (Megalac-E). Dry matter and nutrient intake, and daily milk production were evaluated. The samples used to analyze milk composition were collected in two alternate days and were obtained from two daily milking. Milk composition and total nitrogen, non-protein nitrogen and non-casein nitrogen ratios were analyzed. The casein, serum protein and true protein ratios were obtained by difference. Dry matter and nutrient intakes were lower when cows received the diet containing calcium salts of fatty acids, in relation to the control diet. Among the diets with fat sources, the one with whole raw soybean and calcium salts decreased milk production. There was no effect of fat sources added to the diet on crude protein, non-protein nitrogen, non-casein nitrogen, true protein, casein, casein/milk true protein ratio and serum protein. Similarly, the experimental diets did not influence the protein fractions when expressed in percentage of milk crude protein. The utilization of fat sources in diets changes milk production and composition of lactating cows, but does not influence the composition of milk protein fractions.

Bioassay guided purification of the antimicrobial fraction of a Brazilian propolis from Bahia state

Background: Brazilian propolis type 6 (Atlantic forest, Bahia) is distinct from the other types of propolis especially due to absence of flavonoids and presence of other non-polar, long chain compounds, but presenting good in vitro and in vivo antimicrobial activity. Several authors have suggested that fatty acids found in this propolis might be responsible for its antimicrobial activity; however, so far no evidence concerning this finding has been reported in the literature. The goals of this study were to evaluate the antibacterial activity of the main pure fatty acids in the ethanolic extract and fractions and elucidate the chemical nature of the bioactive compounds isolated from Brazilian propolis type 6. Methods: Brazilian propolis type 6 ethanolic extract (EEP), hexane fraction (H-Fr), major fatty acids, and isolated sub-fractions were analyzed using high performance liquid chromatography (HPLC), high resolution gas chromatography with flame ionization detection (HRGC-FID), and gas chromatography-mass spectrometry (GC-MS). Three sub-fractions of H-Fr were obtained through preparative HPLC. Antimicrobial activity of EEP, H-Fr, sub-fractions, and fatty acids were tested against Staphyloccus aureus ATCC 25923 and Streptococcus mutans Ingbritt 1600 using minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC). Results: EEP and H-Fr inhibited the growth of the microorganisms tested; nevertheless, no antimicrobial activity was found for the major fatty acids. The three sub-fractions (1, 2, and 3) were isolated from H-Fr by preparative HPLC and only sub-fraction 1 showed antimicrobial activity. Conclusion: a) The major fatty acids tested were not responsible for the antimicrobial activity of propolis type 6; b) Sub-fraction 1, belonging to the benzophenone class, was responsible for the antimicrobial activity observed in the present study. The identification of the bioactive compound will improve the development of more efficient uses of this natural product.

Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

A novel use for sugarcane bagasse hemicellulosic fraction: Xylitol enzymatic production

The excess of sugarcane bagasse (SCB) from the sugar-alcohol industry is considered a by-product with great potential for many bioproducts production. This work had as objective to verify the performance of sugarcane bagasse hemicellulosic hydrolysate (SCBHH) as source of sugars for enzymatic or in vitro xylitol production. For this purpose, xylitol enzymatic production was evaluated using different concentrations of treated SCBHH in the commercial reaction media. The weak acid hydrolysis of SCB provided a hydrolysate with 18 g L(-1) and 6 g L(-1) of xylose and glucose, respectively. Considering the reactions, changes at xylose xylitol conversion efficiency and volumetric productivity in xylitol were not observed for the control experiment and using 20 and 40% v.v (1) of SCBHH in the reaction media. The conversion efficiency achieved 100% in all the experiments tested. The results showed that treated SCBHH is suitable as xylose and glucose source for the enzymatic xylitol production and that this process has potential as an alternative for traditional xylitol production ways. (C) 2011 Published by Elsevier Ltd.

Phase fraction distribution measurement of oil-water flow using a capacitance wire-mesh sensor

In this paper, a novel wire-mesh sensor based on permittivity (capacitance) measurements is applied to generate images of the phase fraction distribution and investigate the flow of viscous oil and water in a horizontal pipe. Phase fraction values were calculated from the raw data delivered by the wire-mesh sensor using different mixture permittivity models. Furthermore, these data were validated against quick-closing valve measurements. Investigated flow patterns were dispersion of oil in water (Do/w) and dispersion of oil in water and water in oil (Do/w&w/o). The Maxwell-Garnett mixing model is better suited for Dw/o and the logarithmic model for Do/w&w/o flow pattern. Images of the time-averaged cross-sectional oil fraction distribution along with axial slice images were used to visualize and disclose some details of the flow.