Four-gene expression model predictive of lymph node metastases in oral squamous cell carcinoma

Background. Previous knowledge of cervical lymph node compromise may be crucial to choose the best treatment strategy in oral squamous cell carcinoma (OSCC). Here we propose a set four genes, whose mRNA expression in the primary tumor predicts nodal status in OSCC, excluding tongue. Material and methods. We identified differentially expressed genes in OSCC with and without compromised lymph nodes using Differential Display RT-PCR. Known genes were chosen to be validated by means of Northern blotting or real time RT-PCR (qRT-PCR). Thereafter we constructed a Nodal Index (NI) using discriminant analysis in a learning set of 35 patients, which was further validated in a second independent group of 20 patients. Results. Of the 63 differentially expressed known genes identified comparing three lymph node positive (pN+) and three negative (pN0) primary tumors, 23 were analyzed by Northern analysis or RT-PCR in 49 primary tumors. Six genes confirmed as differentially expressed were used to construct a NI, as the best set predictive of lymph nodal status, with the final result including four genes. The NI was able to correctly classify 32 of 35 patients comprising the learning group (88.6%; p = 0.009). Casein kinase 1alpha1 and scavenger receptor class B, member 2 were found to be up regulated in pN + group in contrast to small proline-rich protein 2B and Ras-GTPase activating protein SH3 domain-binding protein 2 which were upregulated in the pN0 group. We validated further our NI in an independent set of 20 primary tumors, 11 of them pN0 and nine pN+ with an accuracy of 80.0% (p = 0.012). Conclusions. The NI was an independent predictor of compromised lymph nodes, taking into the consideration tumor size and histological grade. The genes identified here that integrate our "Nodal Index" model are predictive of lymph node metastasis in OSCC.

Three-feature model to reproduce the topology of citation networks and the effects from authors' visibility on their h-index

Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.

The role of clouds in improving the regression model for hourly values of diffuse solar radiation

The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

Predicting Growth of Panicum maximum: An Adaptation of the CROPGRO-Perennial Forage Model

Warm-season grasses are economically important for cattle production in tropical regions and tools to aid in management and research on these forages would be highly beneficial both in research and the industry. This research was conducted to adapt the CROPGRO-Perennial Forage model to simulate growth of the tropical species guineagrass (Panicum maximum Jacq. cv. 'Tanzania') and to describe model adaptation for this species. To develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation, and partitioning during a 17-mo experiment with Tanzania guineagrass in Piracicaba, SP, Brazil. Compared with starting parameters for palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. 'Xaraes'], dormancy effects of the perennial forage model had to be minimized, partitioning to storage tissue or root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield was 6576 kg ha(-1), averaged across 11 regrowth cycles of 35 (summer) or 63 d (winter), with a RMSE of 494 kg ha(-1) (Willmott's index of agreement d = 0.985, simulated/observed ratio = 1.014). The model also gave good predictions against an independent data set, with similar RMSE, ratio, and d. The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of guineagrass and can be used to simulate growth.

Previous Exercise Training Has a Beneficial Effect on Renal and Cardiovascular Function in a Model of Diabetes

Exercise training (ET) is an important intervention for chronic diseases such as diabetes mellitus (DM). However, it is not known whether previous exercise training intervention alters the physiological and medical complications of these diseases. We investigated the effects of previous ET on the progression of renal disease and cardiovascular autonomic control in rats with streptozotocin (STZ)-induced DM. Male Wistar rats were divided into five groups. All groups were followed for 15 weeks. Trained control and trained diabetic rats underwent 10 weeks of exercise training, whereas previously trained diabetic rats underwent 14 weeks of exercise training. Renal function, proteinuria, renal sympathetic nerve activity (RSNA) and the echocardiographic parameters autonomic modulation and baroreflex sensitivity (BRS) were evaluated. In the previously trained group, the urinary albumin/creatinine ratio was reduced compared with the sedentary diabetic and trained diabetic groups (p < 0.05). Additionally, RSNA was normalized in the trained diabetic and previously trained diabetic animals (p < 0.05). The ejection fraction was increased in the previously trained diabetic animals compared with the diabetic and trained diabetic groups (p < 0.05), and the myocardial performance index was improved in the previously trained diabetic group compared with the diabetic and trained diabetic groups (p < 0.05). In addition, the previously trained rats had improved heart rate variability and BRS in the tachycardic response and bradycardic response in relation to the diabetic group (p < 0.05). This study demonstrates that previous ET improves the functional damage that affects DM. Additionally, our findings suggest that the development of renal and cardiac dysfunction can be minimized by 4 weeks of ET before the induction of DM by STZ.

Infrared (810 nm) Low-Level Laser Therapy in Experimental Model of Strain-Induced Skeletal Muscle Injury in Rats: Effects on Functional Outcomes

Muscle strains are among the most prevalent causes for athletes absence from sport activities. Low-level laser therapy (LLLT) has recently emerged as a potential contender to nonsteroidal anti-inflammatory drugs in muscle strain treatment. In this work we investigated effects of LLLT and diclofenac on functional outcomes in the acute stage after muscle strain injury in rats. Muscle strain was induced by overloading the tibialis anterior muscle of rats during anesthesia. The injured groups received either no treatment, or a single treatment with diclofenac 30 min prior to injury, or LLLT (810 nm, 100 mW) with doses of 1, 3, 6 or 9 J, at 1 h after injury. Functional outcome measures included a walking index and assessment of electrically induced muscle performance. All treatments (except 9 J LLLT) significantly improved the walking index 12 h postinjury compared with the untreated group. The 3 J group also showed a significantly better walking index than the drug group. All treatments significantly improved muscle performance at 6 and 12 h. LLLT dose of 3 J was as effective as the pharmacological agent in improving functional outcomes in the early phase after a muscle strain injury in rats.

Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations

The leaf area index (LAI) is a key characteristic of forest ecosystems. Estimations of LAI from satellite images generally rely on spectral vegetation indices (SVIs) or radiative transfer model (RTM) inversions. We have developed a new and precise method suitable for practical application, consisting of building a species-specific SVI that is best-suited to both sensor and vegetation characteristics. Such an SVI requires calibration on a large number of representative vegetation conditions. We developed a two-step approach: (1) estimation of LAI on a subset of satellite data through RTM inversion; and (2) the calibration of a vegetation index on these estimated LAI. We applied this methodology to Eucalyptus plantations which have highly variable LAI in time and space. Previous results showed that an RTM inversion of Moderate Resolution Imaging Spectroradiometer (MODIS) near-infrared and red reflectance allowed good retrieval performance (R-2 = 0.80, RMSE = 0.41), but was computationally difficult. Here, the RTM results were used to calibrate a dedicated vegetation index (called "EucVI") which gave similar LAI retrieval results but in a simpler way. The R-2 of the regression between measured and EucVI-simulated LAI values on a validation dataset was 0.68, and the RMSE was 0.49. The additional use of stand age and day of year in the SVI equation slightly increased the performance of the index (R-2 = 0.77 and RMSE = 0.41). This simple index opens the way to an easily applicable retrieval of Eucalyptus LAI from MODIS data, which could be used in an operational way.

STOCHASTIC MODEL FOR SIMULATING MAIZE YIELD

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment.

MODEL PARTITIONS AND COMPACT TEST CASE SUITES

We present a generalized test case generation method, called the G method. Although inspired by the W method, the G method, in contrast, allows for test case suite generation even in the absence of characterization sets for the specification models. Instead, the G method relies on knowledge about the index of certain equivalences induced at the implementation models. We show that the W method can be derived from the G method as a particular case. Moreover, we discuss some naturally occurring infinite classes of FSM models over which the G method generates test suites that are exponentially more compact than those produced by the W method.

Oral health and access to dental care services in relation to the Health Necessities Index. Sao Paulo, Brazil, 2008

The Health Department of Sao Paulo, Brazil, has developed a Health Necessities Index (HNI) to identify priority areas for providing health assistance. In 2008, a survey of the status of oral health was conducted. The objective of this ecological study was to analyze the status of oral health in relation to the HNI. The variables, stratified by the age of 5, 12 and 15 years old were: percentage of individuals with difficulty of access to dental care services; DMFT and DMFS; prevalence of the need for tooth extraction and treatment of dental caries. Data were analyzed for the 25 Health Technical Supervision Units (HTS). The Statistical Covariance Test was used as well as the Pearson correlation coefficient and linear regression model. A positive correlation was observed between high scores of the HNI and difficulty of access to services. In the HTS with high scores of HNI a higher incidence of dental caries was observed, a greater need for tooth extractions and low caries-free incidence. In order to improve health conditions of the population it is mandatory to prioritize actions in areas of social deprivation.

Birth weight, current body mass index, and insulin sensitivity and secretion in young adults in two Latin American populations

Background and aims: Although studies have shown association of birth weight (BW) and adult body mass index (BMI) with insulin sensitivity in adults, there is limited evidence that BW is associated with insulin secretion. We assessed the associations between BW and current BMI with insulin sensitivity and secretion in young Latin American adults. Methods and results: Two birth cohorts, one from Ribeirao Preto, Brazil, based on 1984 participants aged 23-25 years, and another from Limache, Chile, based on 965 participants aged 22-28 years were studied. Weight and height at birth, and current fasting plasma glucose and insulin levels were measured. Insulin sensitivity (HOMA%S) and secretion (HOMA%beta) were estimated using the Homeostatic Model Assessment (HOMA2). Multiple linear regression analyses were carried out to test the associations between BW and adult BMI z-scores on log HOMA%S and log HOMA%beta. BW z-score was associated with HOMA%S in the two populations and HOMA%beta in Ribeirao Preto when adult BMI z-score was included in the model. BW z-score was associated with decreasing insulin secretion even without adjusting for adult BMI, but only in Ribeirao Preto. BMI z-score was associated with low HOMA%S and high HOMA%beta. No interactions between BW and BMI z-scores on insulin sensitivity were shown. Conclusions: This study supports the finding that BW may affect insulin sensitivity and secretion in young adults. The effect size of BW on insulin status is small in comparison to current BMI. (C) 2010 Elsevier B.V. All rights reserved.

Effects of volume resuscitation on splanchnic perfusion in canine model of severe sepsis induced by live Escherichia coli infusion

Abstract Introduction We conducted the present study to investigate whether early large-volume crystalloid infusion can restore gut mucosal blood flow and mesenteric oxygen metabolism in severe sepsis. Methods Anesthetized and mechanically ventilated male mongrel dogs were challenged with intravenous injection of live Escherichia coli (6 × 109 colony-forming units/ml per kg over 15 min). After 90 min they were randomly assigned to one of two groups – control (no fluids; n = 13) or lactated Ringer's solution (32 ml/kg per hour; n = 14) – and followed for 60 min. Cardiac index, mesenteric blood flow, mean arterial pressure, systemic and mesenteric oxygen-derived variables, blood lactate and gastric carbon dioxide tension (PCO2; by gas tonometry) were assessed throughout the study. Results E. coli infusion significantly decreased arterial pressure, cardiac index, mesenteric blood flow, and systemic and mesenteric oxygen delivery, and increased arterial and portal lactate, intramucosal PCO2, PCO2 gap (the difference between gastric mucosal and arterial PCO2), and systemic and mesenteric oxygen extraction ratio in both groups. The Ringer's solution group had significantly higher cardiac index and systemic oxygen delivery, and lower oxygen extraction ratio and PCO2 gap at 165 min as compared with control animals. However, infusion of lactated Ringer's solution was unable to restore the PCO2 gap. There were no significant differences between groups in mesenteric oxygen delivery, oxygen extraction ratio, or portal lactate at the end of study. Conclusion Significant disturbances occur in the systemic and mesenteric beds during bacteremic severe sepsis. Although large-volume infusion of lactated Ringer's solution restored systemic hemodynamic parameters, it was unable to correct gut mucosal PCO2 gap.

Modified crop model estimation of depleted and potential soybean yield

Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.

Changes in renal glucose transporters in an animal model of metabolic syndrome

Considering the similarity between structural, hemodynamic, and functional changes of obesity-related renal disease and diabetic nephropathy, we hypothesized that renal glucose transporter changes occur in obesity as in diabetes. The aim of the work was to evaluate GLUT1 and GLUT2 in kidneys of an animal model of metabolic syndrome. Neonate spontaneously hypertensive rats (SHR), n=15/group, were treated with monosodium glutamate (5 mg/g) (MetS) for 9 days and compared with saline-treated Wistar-Kyoto (C) and SHR (H) rats. Lee index, systolic arterial pressure (SAP), glycemia, insulin resistance, triglycerides, and HDL cholesterol were evaluated at 3 and 6 months. Medullar GLUT1 and cortical GLUT2 were analyzed by Western blot. MetS vs. C and H rats had the highest Lee index (p<0.001) and insulin resistance (3-months C: 4.3±0.7, H: 3.9±0.9, MetS: 2.7±0.6; 6-months C: 4.2±0.6, H: 3.8±0.5, MetS: 2.4±0.6% • min−1, p<0.001), similar glycemia, and the lowest HDL-cholesterol at 6-months (p<0.001). In the MetS and H rats, SAP was higher vs. C at 3-months (p<0.001) and 6-months (C: 151±15, H: 190±11, MetS: 185±13 mm Hg, p<0.001) of age. GLUT1 was ̴ 13× lower (p<0.001) at 3-months, reestablishing its content at 6-months in MetS group, while GLUT2 was 2× higher (p<0.001) in this group at 6-months of age. Renal GLUT1 and GLUT2 are modulated in kidney of rats with metabolic syndrome, where obesity, insulin resistance and hypertension coexist, despite normoglycemia. Like in diabetes, cortical GLUT2 overexpression may contribute to the development of kidney disease