EFFECTS OF A POTENT PEROXYNITRITE DECOMPOSITION CATALYST IN MURINE MODELS OF ENDOTOXEMIA AND SEPSIS

Excessive free-radical production due to various bacterial components released during bacterial infection has been linked to cell death and tissue injury. Peroxynitrite is a highly reactive oxidant produced by the combination of nitric oxide (NO) and superoxide anion, which has been implicated in cell death and tissue injury in various forms of critical illness. Pharmacological decomposition of peroxynitrite may represent a potential therapeutic approach in diseases associated with the overproduction of NO and superoxide. In the present study, we tested the effect of a potent peroxynitrite decomposition catalyst in murine models of endotoxemia and sepsis. Mice were injected i.p. with LPS 40 mg/kg with or without FP15 [Fe(III) tetrakis-2-(N-triethylene glycol monomethyl ether) pyridyl porphyrin] (0.1, 0.3, 1, 3, or 10 mg/kg per hour). Mice were killed 12 h later, followed by the harvesting of samples from the lung, liver, and gut for malondialdehyde and myeloperoxidase measurements. In other subsets of animals, blood samples were obtained by cardiac puncture at 1.5, 4, and 8 h after LPS administration for cytokine (TNF-alpha, IL-1 beta, and IL-10), nitrite/nitrate, alanine aminotransferase, and blood urea nitrogen measurements. Endotoxemic animals showed an increase in survival from 25% to 80% at the FP15 doses of 0.3 and 1 mg/kg per hour. The same dose of FP15 had no effect on plasma levels of nitrite/nitrate. There was a reduction in liver and lung malondialdehyde in the endotoxemic animals pretreated with FP15, as well as in hepatic myeloperoxidase and biochemical markers of liver and kidney damage (alanine aminotransferase and blood urea nitrogen). In a bacterial model of sepsis induced by cecal ligation and puncture, FP15 treatment (0.3 mg/kg per day) significantly protected against mortality. The current data support the view that peroxynitrite is a critical factor mediating liver, gut, and lung injury in endotoxemia and septic shock: its pharmacological neutralization may be of therapeutic benefit.

Maned wolf survival rate in central Brazil

Although many carnivores are of conservation concern, most are poorly studied. The maned wolf Chrysocyon brachyurus Illiger, 1811 is the largest South American canid with a broad distribution; however, the largest portion of its range is in the Brazilian Cerrado savannah, where due to intensive agricultural expansion, it is threatened by habitat loss. Maned wolf population trends are virtually unknown. We analyzed radio telemetry data from a 13-year study in Emas National Park, central Brazil, with Burnham`s live recapture/dead recovery models in the program MARK to obtain the first analytically sound estimate of the apparent maned wolf survival rate. We constructed 16 candidate models including variation in survival rate and resighting probability associated with an individual`s sex or age and year of study. Apparent adult survival rate throughout the study ranged from 0.28 (se=0.08) to 0.97 (se=0.06). There was no evidence for sex specificity but strong support for time variation. Model weights supported an age effect and the subadult survival rate was 0.63 (se=0.15). Results indicate similar life patterns for male and female maned wolves and similar mortality risks for adults and subadults in the study area. The observed temporal fluctuations of adult survival rate are important for population dynamics as they decrease average population growth rates. Population dynamics are central for conservation planning and our results are an important step towards a better understanding of the maned wolf`s ecology.

Central NO-cGMP pathway in thermoregulation and survival rate during polymicrobial sepsis

Sepsis induces production of inflammatory mediators such as nitric oxide (NO) and causes physiological alterations, including changes in body temperature (T(b)). We evaluated the involvement of the central NO cGMP pathway in thermoregulation during sepsis induced by cecal ligation and puncture (CLP), and analyzed its effect on survival rate. Male Wistar rats with a T(b) probe inserted in their abdomen were intracerebroventricularly injected with 1 mu L N(G)-nitro-L-arginine methyl ester (L-NAME, 250 mu g), a nonselective NO synthase (NOS) inhibitor; or aminoguanidine (250 mu g), an inducible NOS inhibitor; or 1H-[1,2,4]oxadiazolo[4,3,-a]quinoxalin-1-one (ODQ, 0.25 mu g), a guanylate cyclase inhibitor. Thirty minutes after injection, sepsis was induced by cecal ligation and puncture (CLP), or the rats were sham operated. The animals were divided into 2 groups for determination of T(b) for 24 h and assessment of survival during 3 days. The drop in T(b) seen in the CLP group was attenuated by pretreatment with the NOS inhibitors (p < 0.05) and blocked with ODQ. CLP rats pretreated with either of the inhibitors showed higher survival rates than vehicle injected groups (p < 0.05), and were even higher in the ODQ pretreated group. Our results showed that the effect of NOS inhibition on the hypothermic response to CLP is consistent with the role of nitrergic pathways in thermoregulation.

Development and survival of the diamondback moth (Lepidoptera : Plutellidae) at constant and alternating temperatures

Survival and development time from egg to adult emergence of the diamondback moth, Plutella xylostella (L.), were determined at 19 constant and 14 alternating temperature regimes from 4 to 40degreesC. Plutella xylostella developed successfully front egg to adult emergence at constant temperatures from 8 to 32degreesC. At temperatures from 4 to 6degreesC or from 34 to 40degreesC, partial or complete development of individual stages or instars was possible, with third and fourth instars having the widest temperature limits. The insect developed successfully from egg to adult emergence under alternating regimes including temperatures as low as 4degreesC or as high as 38degreesC. The degree-day model, the logistic equation, and the Wang model were used to describe the relationships between temperature and development rate at both constant and alternating temperatures. The degree-day model described the relationships well from 10 to 30degreesC. The logistic equation and the Wang model fit the data well at temperatures 32degreesC. Under alternating regimes, all three models gave good simulations of development in the mid-temperature range, but only the logistic equation gave close simulations in the low temperature range, and none gave close or consistent simulations in the high temperature range. The distribution of development time was described satisfactorily by a Weibull function. These rate and time distribution functions provide tools for simulating population development of P. xylostella over a wide range of temperature conditions.

The impact of positive peritoneal washings and serosal and adnexal involvement on survival in patients with stage IIIA uterine cancer

Objective. The aim of this study was to determine the prognostic significance of serosal involvement (SER), adnexal involvement (ADN), and positive peritoneal washings (PPW) in patients with Stage IIIA uterine cancer. We also sought to determine patterns of recurrence in patients with this disease. Methods. The records of 136 patients with Stage IIIA uterine cancer treated at the Queensland Centre for Gynecological Cancer between March 1983 and August 2001 were reviewed. One hundred thirty-six patients underwent surgery and 58 (42.6%) had full surgical staging. Seventy-five patients (55.2%) had external beam radiotherapy and/or brachytherapy postoperatively. Overall survival was the primary statistical endpoint. Statistical analysis included univariate and multivariate Cox models. Results. Forty-six patients (33.8%) had adnexal involvement, 23 (16.9%) had serosal involvement, and 40 (29.4%) had positive peritoneal washings. Median follow-up was 55.1 months (95% confidence interval, 36.9 to 73.4 months) after which time 71 patients (52.2%) remained alive. For patients with endometrioid adenocarcinoma, ADN and SER were associated with impaired survival on multivariate analysis (odds ratio 2.8 and 3.2, respectively). In the subgroup of patients with high-risk tumors (including papillary serous carcinomas, clear cell carcinomas, and uterine sarcomas), neither ADN, nor SER, nor PPW influenced survival. Conclusion. Patients with Stage IIIA uterine cancer constitute a heterogeneous group. For patients with endometrioid adenocarcinoma, both ADN and SER, but not PPW, were associated with impaired prognosis. For patients with high-risk histological types, prognosis is poor for all three factors. (C) 2002 Elsevier Science (USA).

Prospective independent validation of APACHE III models in an Australian tertiary adult intensive care unit

Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.

Dietary influences on survival after ovarian cancer

We evaluated the effects of various food groups and micronutrients in the diet on survival among women who originally participated in a population-based case-control study of ovarian cancer conducted across 3 Australian states between 1990 and 1993. This analysis included 609 women with invasive epithelial ovarian cancer, primarily because there was negligible mortality in women with borderline tumors. The women's usual diet was assessed using a validated food frequency questionnaire. Deaths in the cohort were identified using state-based cancer registries and the Australian National Death Index (NDI). Crude 5-year survival probabilities were estimated using the Kaplan-Meier technique, and adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained from Cox regression models. After adjusting for important confounding factors, a survival advantage was observed for those who reported higher intake of vegetables in general (HR = 0.75, 95% CI = 0.57-0.99, p-value trend 0.01 for the highest third, compared to the lowest third), and cruciferous vegetables in particular (HR = 0.75, 95% CI = 0.57-0.98, p-value trend 0.03), and among women in the upper third of intake of vitamin E (HR = 0.76, 95% CI = 0.58-1.01, p-value trend 0.04). Inverse associations were also seen with protein (p-value trend 0.09), red meat (p-value trend 0.06) and white meat (p-value trend 0.07), and modest positive trends (maximum 30% excess) with lactose (p-value trend 0.04), calcium and dairy products. Although much remains to be learned about the influence of nutritional factors after a diagnosis of ovarian cancer, our study suggests the possibility that a diet high in vegetable intake may help improve survival. (C) 2003 Wiley-Liss, Inc.

Survival Analysis Employed in Predicting Corporate Failure: A Forecasting Model Proposal

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores – Sistemas Digitais e Percepcionais pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

Coronary Revascularization Induces a Shift From Cardiac Toward Noncardiac Mortality Without Improving Survival in Vascular Surgery Patient

OBJECTIVE: Although evidence has shown that ischemic heart disease (IHD) in vascular surgery patients has a negative impact on the prognosis after surgery, it is unclear whether directed treatment of IHD may influence cause-specific and overall mortality. The objective of this study was to determine the prognostic implication of coronary revascularization (CR) on overall and cause-specific mortality in vascular surgery patients. METHODS: Patients undergoing surgery for abdominal aortic aneurysm, carotid artery stenosis, or peripheral artery disease in a university hospital in The Netherlands between January 2003 and December 2011 were retrospectively included. Survival estimates were obtained by Kaplan-Meier and Cox regression analysis. RESULTS: A total of 1104 patients were included. Adjusted survival analyses showed that IHD significantly increased the risk of overall mortality (hazard ratio [HR], 1.50; 95% confidence interval, 1.21-1.87) and cardiovascular death (HR, 1.93; 95% confidence interval, 1.35-2.76). Compared with those without CR, patients previously undergoing CR had similar overall mortality (HR, 1.38 vs 1.62; P = .274) and cardiovascular mortality (HR, 1.83 vs 2.02; P = .656). Nonrevascularized IHD patients were more likely to die of IHD (6.9% vs 35.7%), whereas revascularized IHD patients more frequently died of cardiovascular causes unrelated to IHD (39.1% vs 64.3%; P = .018). CONCLUSIONS: This study confirms the significance of IHD for postoperative survival of vascular surgery patients. CR was associated with lower IHD-related death rates. However, it failed to provide an overall survival benefit because of an increased rate of cardiovascular mortality unrelated to IHD. Intensification of secondary prevention regimens may be required to prevent this shift toward non-IHD-related death and thereby improve life expectancy.

Diabetes Mellitus as a Risk Factor in Glaucoma's Physiopathology and Surgical Survival Time: A Literature Review

Glaucoma is a multifactorial condition under serious influence of many risk factors. The role of diabetes mellitus (DM) in glaucoma etiology or progression remains inconclusive. Although, the diabetic patients have different healing mechanism comparing to the general population and it has a possible-negative role on surgical outcomes. This review article attempts to analyze the association of both diseases, glaucoma and DM, before and after the surgery. The epidemiological studies, based mainly in population prevalence analyzes, have shown opposite outcomes in time and even in the most recent articles also the association remains inconclusive. On the contrary, the experimental models based on animal induced chronic hyperglycemia have shown an important association of both diseases, explained by common neurodegenerative mechanisms. Diabetic patients have a different wound healing process in the eye viz-a-viz other organs. The healing process is more and it results in lower surgical survival time, higher intraocular pressure (IOP) levels and, therefore, these patients usually need more medication to lower the IOP. Both randomized and nonrandomized retrospective and experimental molecular studies have shown the association between DM and glaucoma. Further studies are needed to get better explanations about outcomes on more recent surgical procedures and with the exponential use of antifibrotics. How to cite this article: Costa L, Cunha JP, Amado D, Pinto LA, Ferreira J. Diabetes Mellitus as a Risk Factor in Glaucoma's Physiopathology and Surgical Survival Time: A Literature Review.

Joint modelling of longitudinal and survival data on breast cancer

Tese de Doutoramento em Ciências (Especialidade em Matemática)

The ghost of past species occurrence: improving species distribution models for presence-only data

1. Model-based approaches have been used increasingly in conservation biology over recent years. Species presence data used for predictive species distribution modelling are abundant in natural history collections, whereas reliable absence data are sparse, most notably for vagrant species such as butterflies and snakes. As predictive methods such as generalized linear models (GLM) require absence data, various strategies have been proposed to select pseudo-absence data. However, only a few studies exist that compare different approaches to generating these pseudo-absence data. 2. Natural history collection data are usually available for long periods of time (decades or even centuries), thus allowing historical considerations. However, this historical dimension has rarely been assessed in studies of species distribution, although there is great potential for understanding current patterns, i.e. the past is the key to the present. 3. We used GLM to model the distributions of three 'target' butterfly species, Melitaea didyma, Coenonympha tullia and Maculinea teleius, in Switzerland. We developed and compared four strategies for defining pools of pseudo-absence data and applied them to natural history collection data from the last 10, 30 and 100 years. Pools included: (i) sites without target species records; (ii) sites where butterfly species other than the target species were present; (iii) sites without butterfly species but with habitat characteristics similar to those required by the target species; and (iv) a combination of the second and third strategies. Models were evaluated and compared by the total deviance explained, the maximized Kappa and the area under the curve (AUC). 4. Among the four strategies, model performance was best for strategy 3. Contrary to expectations, strategy 2 resulted in even lower model performance compared with models with pseudo-absence data simulated totally at random (strategy 1). 5. Independent of the strategy model, performance was enhanced when sites with historical species presence data were not considered as pseudo-absence data. Therefore, the combination of strategy 3 with species records from the last 100 years achieved the highest model performance. 6. Synthesis and applications. The protection of suitable habitat for species survival or reintroduction in rapidly changing landscapes is a high priority among conservationists. Model-based approaches offer planning authorities the possibility of delimiting priority areas for species detection or habitat protection. The performance of these models can be enhanced by fitting them with pseudo-absence data relying on large archives of natural history collection species presence data rather than using randomly sampled pseudo-absence data.

Growth and Survival Determinants of Chinese Private Firms: Fieldwork evidence and econometric estimates

This paper reports on one of the first empirical attempts to investigate small firm growth and survival, and their determinants, in the Peoples’ Republic of China. The work is based on field work evidence gathered from a sample of 83 Chinese private firms (mainly SMEs) collected initially by face-to-face interviews, and subsequently by follow-up telephone interviews a year later. We extend the models of Gibrat (1931) and Jovanovic (1982), which traditionally focus on size and age alone (e.g. Brock and Evans, 1986), to a ‘comprehensive’ growth model with two types of additional explanatory variables: firm-specific (e.g. business planning); and environmental (e.g. choice of location). We estimate two econometric models: a ‘basic’ age-size-growth model; and a ‘comprehensive’ growth model, using Heckman’s two-step regression procedure. Estimation is by log-linear regression on cross-section data, with corrections for sample selection bias and heteroskedasticity. Our results refute a pure Gibrat model (but support a more general variant) and support the learning model, as regards the consequences of size and age for growth; and our extension to a comprehensive model highlights the importance of location choice and customer orientation for the growth of Chinese private firms. In the latter model, growth is explained by variables like planning, R&D orientation, market competition, elasticity of demand etc. as well as by control variables. Our work on small firm growth achieves two things. First, it upholds the validity of ‘basic’ size-age-growth models, and successfully applies them to the Chinese economy. Second, it extends the compass of such models to a ‘comprehensive’ growth model incorporating firm-specific and environmental variables.