Development and Validation of A Stability-Indicating Mekc Method for Determination of Flucloxacillin Sodium in Capsules

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Intra-abdominal pressure as a predictor of acute kidney injury in postoperative abdominal surgery

Objectives: The purpose of this study was to determine if intra-abdominal pressure (IAP) could predict acute renal injury (AKI) in the postoperative period of abdominal surgeries, and which would be its cutoff value. Patients and methods: A prospective observational study was conducted in the period from January 2010 to March 2011 in the Intensive Care Units (ICUs) of the University Hospital of Botucatu Medical School, UNESP. Consecutive patients undergoing abdominal surgery were included in the study. Initial evaluation, at admission in ICU, was performed in order to obtain demographic, clinical surgical and therapeutic data. Evaluation of IAP was obtained by the intravesical method, four times per day, and renal function was evaluated during the patient's stay in the ICU until discharge, death or occurrence of AKI. Results: A total of 60 patients were evaluated, 16 patients developed intra-abdominal hypertension (IAH), 45 developed an abnormal IAP (>7 mmHg) and 26 developed AKI. The first IAP at the time of admission to the ICU was able to predict the occurrence of AKI (area under the receiver-operating characteristic curve was 0.669; p=0.029) with the best cutoff point (by Youden index method) >= 7.68 mmHg, sensitivity of 87%, specificity of 46% at this point. The serial assessment of this parameter did not added prognostic value to initial evaluation. Conclusion: IAH was frequent in patients undergoing abdominal surgeries during ICU stay, and it predicted the occurrence of AKI. Serial assessments of IAP did not provided better discriminatory power than initial evaluation.

Resting heart rate as a predictor of metabolic dysfunctions in obese children and adolescents

Background: Recent studies have identified that a higher resting heart rate (RHR) is associated with elevated blood pressure, independent of body fatness, age and ethnicity. However, it is still unclear whether RHR can also be applied as a screening for other risk factors, such as hyperglycemia and dyslipidemia. Thus, the purpose of the presented study was to analyze the association between RHR, lipid profile and fasting glucose in obese children and adolescents. Methods: The sample was composed of 180 obese children and adolescents, aged between 7-16 years. Whole-body and segmental body composition were estimated by Dual-energy X-ray absorptiometry. Resting heart rate (RHR) was measured by heart rate monitors. The fasting blood samples were analyzed for serum triglycerides, total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and glucose, using the colorimetric method. Results: Fasting glucose, TC, triglycerides, HDL-C, LDL-C and RHR were similar in both genders. The group of obese subjects with a higher RHR presented, at a lower age, higher triglycerides and TC. There was a significant relationship between RHR, triglycerides and TC. In the multivariate model, triglycerides and TC maintained a significant relationship with RHR independent of age, gender, general and trunk adiposity. The ROC curve indicated that RHR has a high potential for screening elevated total cholesterol and triglycerides as well as dyslipidemia. Conclusion: Elevated RHR has the potential to identify subjects at an increased risk of atherosclerosis development.

INVESTIGATION OF INTRAOCULAR PRESSURE AS A PREDICTOR OF TRAUMATIC EYE INJURIES

Eye injuries are a large societal problem in both the military and civilian sectors. Eye injury rates are increasing in recent military conflicts, and there are over 1.9 million eye injuries in the United States civilian sector annually. In order to develop a better understanding of eye injury risk, several previous studies have developed eye injury criteria based on projectile characteristics. While these injury criteria have been used to estimate eye injury potential of impact scenarios, they require that the mass, size and velocity of the projectile are known. It is desirable to develop a method to assess the severity of an eye impact in environments where it would be difficult or impossible to determine these projectile characteristics. The current study presents a measurement technique for monitoring intraocular pressure of the eye under impactloading. Through experimental tests with a custom pressure chamber, a subminiature pressure transducer was validated to be thermally stable and suitable for testing in an impact environment.Once validated, the transducer was utilized intraocularly, inserted through the optic nerve, to measure the pressure of the eye during blunt-projectile impacts. A total of 150 impact tests were performed using projectiles ranging from 3.2 mm to 17.5 mm in diameter. Investigation of the relationship between projectile energy and intraocular pressure lead to the identification of at least two distinct trends. Intraocular pressure and normalized energy measurements indicated a different response for penetrating-type globe rupture injuries with smaller diameter (d < 1 cm)projectiles, and blunt-type globe rupture injuries with larger diameter (d > 1 cm) projectiles. Furthermore, regression analysis indicates that relationships exist between intraocular pressureand projectile energy that may allow quantification of eye injury risk based on pressure data, and also that intraocular pressure measurements of impact may lead to a better understanding of thetransition between penetrating and blunt globe rupture injury mechanisms.

Membrane microdialysis: Evaluation of a new method to assess splanchnic tissue metabolism

OBJECTIVE: Measuring peritoneal lactate concentrations could be useful for detecting splanchnic hypoperfusion. The aims of this study were to evaluate the properties of a new membrane-based microdialyzer in vitro and to assess the ability of the dialyzer to detect a clinically relevant decrease in splanchnic blood flow in vivo. DESIGN: A membrane-based microdialyzer was first validated in vitro. The same device was tested afterward in a randomized, controlled animal experiment. SETTING: University experimental research laboratory. SUBJECTS: Twenty-four Landrace pigs of both genders. INTERVENTIONS: In vitro: Membrane microdialyzers were kept in warmed sodium lactate baths with lactate concentrations between 2 and 8 mmol/L for 10-120 mins, and microdialysis lactate concentrations were measured repeatedly (210 measurements). In vivo: An extracorporeal shunt with blood reservoir and roller pump was inserted between the proximal and distal abdominal aorta, and a microdialyzer was inserted intraperitoneally. In 12 animals, total splanchnic blood flow (measured by transit time ultrasound) was reduced by a median 43% (range, 13% to 72%) by activating the shunt; 12 animals served as controls. MEASUREMENTS AND MAIN RESULTS: In vitro: The fractional lactate recovery was 0.59 (0.32-0.83) after 60 mins and 0.82 (0.71-0.87) after 90 mins, with no further increase thereafter. At 60 and 90 mins, the fractional recovery was independent of the lactate concentration. In vivo: Abdominal blood flow reduction resulted in an increase in peritoneal microdialysis lactate concentration from 1.7 (0.3-3.8) mmol/L to 2.8 (1.3-6.2) mmol/L (p = .006). At the same time, mesenteric venous-arterial lactate gradient increased from 0.1 (-0.2-0.8) mmol/L to 0.3 (-0.3 -1.8) mmol/L (p = .032), and mesenteric venous-arterial Pco2 gradients increased from 12 (8-19) torr to 21 (11-54) torr (p = .005). CONCLUSIONS: Peritoneal membrane microdialysis provides a method for the assessment of splanchnic ischemia, with potential for clinical application.

Glomerular filtration rate, urine production, and fractional clearance of electrolytes in acute kidney injury in dogs and their association with survival.

BACKGROUND Acute kidney injury (AKI) is common in dogs. Few studies have assessed sequential changes in indices of kidney function in dogs with naturally occurring AKI. OBJECTIVE To document sequential changes of conventional indices of renal function, to better define the course of AKI, and to identify a candidate marker for recovery. ANIMALS Ten dogs with AKI. METHODS Dogs were prospectively enrolled and divided into surviving and nonsurviving dogs. Urine production was measured with a closed system for 7 days. One and 24-hour urinary clearances were performed daily to estimate solute excretion and glomerular filtration rate (GFR). Solute excretion was calculated as an excretion ratio (ER) and fractional clearance (FC) based on both the 1- and 24-hour urine collections. RESULTS Four dogs survived and 6 died. At presentation, GFR was not significantly different between the outcome groups, but significantly (P = .03) increased over time in the surviving, but not in the nonsurviving dogs. Fractional clearance of Na decreased significantly over time (20.2-9.4%, P < .0001) in the surviving, but not in the nonsurviving dogs. The ER and FC of solutes were highly correlated (r, 0.70-0.95). CONCLUSION AND CLINICAL IMPACT Excretion ratio might be used in the clinical setting as a surrogate marker to follow trends in solute excretion. Increased GFR, urine production, and decreased FC of Na were markers of renal recovery. The FC of Na is a simple, noninvasive, and cost-effective method that can be used to evaluate recovery of renal function.

Retrocrural space involvement on computed tomography as a predictor of mortality and disease severity in acute pancreatitis

BACKGROUND Because computed tomography (CT) has advantages for visualizing the manifestation of necrosis and local complications, a series of scoring systems based on CT manifestations have been developed for assessing the clinical outcomes of acute pancreatitis (AP), including the CT severity index (CTSI), modified CTSI, etc. Despite the internationally accepted CTSI having been successfully used to predict the overall mortality and disease severity of AP, recent literature has revealed the limitations of the CTSI. Using the Delphi method, we establish a new scoring system based on retrocrural space involvement (RCSI), and compared its effectiveness at evaluating the mortality and severity of AP with that of the CTSI. METHODS We reviewed CT images of 257 patients with AP taken within 3-5 days of admission in 2012. The RCSI scoring system, which includes assessment of infectious conditions involving the retrocrural space and the adjacent pleural cavity, was established using the Delphi method. Two radiologists independently assessed the RCSI and CTSI scores. The predictive points of the RCSI and CTSI scoring systems in evaluating the mortality and severity of AP were estimated using receiver operating characteristic (ROC) curves. PRINCIPAL FINDINGS The RCSI score can accurately predict the mortality and disease severity. The area under the ROC curve for the RCSI versus CTSI score was 0.962±0.011 versus 0.900±0.021 for predicting the mortality, and 0.888±0.025 versus 0.904±0.020 for predicting the severity of AP. Applying ROC analysis to our data showed that a RCSI score of 4 was the best cutoff value, above which mortality could be identified. CONCLUSION The Delphi method was innovatively adopted to establish a scoring system to predict the clinical outcome of AP. The RCSI scoring system can predict the mortality of AP better than the CTSI system, and the severity of AP equally as well.

Early Improvement As a Predictor of Later Response to Antipsychotics in Schizophrenia: A Diagnostic Test Review

OBJECTIVE How long clinicians should wait before considering an antipsychotic ineffective and changing treatment in schizophrenia is an unresolved clinical question. Guidelines differ substantially in this regard. The authors conducted a diagnostic test meta-analysis using mostly individual patient data to assess whether lack of improvement at week 2 predicts later nonresponse. METHOD The search included EMBASE, MEDLINE, BIOSIS, PsycINFO, Cochrane Library, CINAHL, and reference lists of relevant articles, supplemented by requests to authors of all relevant studies. The main outcome was prediction of nonresponse, defined as <50% reduction in total score on either the Positive and Negative Syndrome Scale (PANSS) or Brief Psychiatric Rating Scale (BPRS) (corresponding to at least much improved) from baseline to endpoint (4-12 weeks), by <20% PANSS or BPRS improvement (corresponding to less than minimally improved) at week 2. Secondary outcomes were absent cross-sectional symptomatic remission and <20% PANSS or BPRS reduction at endpoint. Potential moderator variables were examined by meta-regression. RESULTS In 34 studies (N=9,460) a <20% PANSS or BPRS reduction at week 2 predicted nonresponse at endpoint with a specificity of 86% and a positive predictive value (PPV) of 90%. Using data for observed cases (specificity=86%, PPV=85%) or lack of remission (specificity=77%, PPV=88%) yielded similar results. Conversely, using the definition of <20% reduction at endpoint yielded worse results (specificity=70%, PPV=55%). The test specificity was significantly moderated by a trial duration of <6 weeks, higher baseline illness severity, and shorter illness duration. CONCLUSIONS Patients not even minimally improved by week 2 of antipsychotic treatment are unlikely to respond later and may benefit from a treatment change.

Predictor paramétrico de glucosa subcutánea

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa (por ejemplo la obtenida a partir de los alimentos ingeridos) llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Hoy en día la tecnología actual permite abordar el desarrollo del llamado “páncreas endocrino artificial”, que consta de un sensor continuo de glucosa subcutánea, una bomba de infusión subcutánea de insulina y un algoritmo de control en lazo cerrado que calcule la dosis de insulina requerida por el paciente en cada momento, según la medida de glucosa obtenida por el sensor y según unos objetivos. El mayor problema que presentan los sistemas de control en lazo cerrado son los retardos, el sensor de glucosa subcutánea mide la glucosa del líquido intersticial, que representa la que hubo en la sangre un tiempo atrás, por tanto, un cambio en los niveles de glucosa en la sangre, debidos por ejemplo, a una ingesta, tardaría un tiempo en ser detectado por el sensor. Además, una dosis de insulina suministrada al paciente, tarda un tiempo aproximado de 20-30 minutos para la llegar a la sangre. Para evitar trabajar en la medida que sea posible con estos retardos, se intenta predecir cuál será el nivel de glucosa en un futuro próximo, para ello se utilizara un predictor de glucosa subcutánea, con la información disponible de glucosa e insulina. El objetivo del proyecto es diseñar una metodología para estimar el valor futuro de los niveles de glucosa obtenida a partir de un sensor subcutáneo, basada en la identificación recursiva del sistema glucorregulatorio a través de modelos lineales y determinando un horizonte de predicción óptimo de trabajo y analizando la influencia de la insulina en los resultados de la predicción. Se ha implementado un predictor paramétrico basado en un modelo autorregresivo ARX que predice con mejor precisión y con menor RMSE que un predictor ZOH a un horizonte de predicción de treinta minutos. Utilizar información relativa a la insulina no tiene efecto en la predicción. El preprocesado, postprocesado y el tratamiento de la estabilidad tienen un efecto muy beneficioso en la predicción. Diabetes mellitusis a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. Nowadays, the actual technology allows raising the development of the “artificial endocrine pancreas”. It involves a continuous glucose sensor, an insulin bump, and a full closed loop algorithm that calculate the insulin units required by patient at any time, according to the glucose measure obtained by the sensor and any target. The main problem of the full closed loop systems is the delays, the glucose sensor measures the glucose in the interstitial fluid that represents the glucose was in the blood some time ago. Because of this, a change in the glucose in blood would take some time to be detected by the sensor. In addition, insulin units administered by a patient take about 20-30 minutes to reach the blood stream. In order to avoid this effect, it will try to predict the glucose level in the near future. To do that, a subcutaneous glucose predictor is used to predict the future glucose with the information about insulin and glucose. The goal of the proyect is to design a method in order to estimate the future valor of glucose obtained by a subcutaneous sensor. It is based on the recursive identification of the regulatory system through the linear models, determining optimal prediction horizon and analyzing the influence of insuline on the prediction results. A parametric predictor based in ARX autoregressive model predicts with better precision and with lesser RMSE than ZOH predictor in a thirty minutes prediction horizon. Using the relative insulin information has no effect in the prediction. The preprocessing, the postprocessing and the stability treatment have many advantages in the prediction.

Simulator of the JET real-time disruption predictor

A disruption predictor based on support vector machines (SVM) has been developed to be used in JET. The training process uses thousands of discharges and, therefore, high performance computing has been necessary to obtain the models. To this respect, several models have been generated with data from different JET campaigns. In addition, various kernels (mainly linear and RBF) and parameters have been tested. The main objective of this work has been the implementation of the predictor model under real-time constraints. A “C-code” software application has been developed to simulate the real-time behavior of the predictor. The application reads the signals from the JET database and simulates the real-time data processing, in particular, the specific data hold method to be developed when reading data from the JET ATM real time network. The simulator is fully configurable by means of text files to select models, signal thresholds, sampling rates, etc. Results with data between campaigns C23and C28 will be shown.

Results of the JET real-time disruption predictor in the ITER-like wall campaigns

The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 realtime signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 1 ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426 ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%.

Characterizing chaos in a type of fractional duffing's equation

We characterize the chaos in a fractional Duffing’s equation computing the Lyapunov exponents and the dimension of the strange attractor in the effective phase space of the system. We develop a specific analytical method to estimate all Lyapunov exponents and check the results with the fiduciary orbit technique and a time series estimation method.

TATPred:a Bayesian method for the identification of twin arginine translocation pathway signal sequences

The twin arginine translocation (TAT) system ferries folded proteins across the bacterial membrane. Proteins are directed into this system by the TAT signal peptide present at the amino terminus of the precursor protein, which contains the twin arginine residues that give the system its name. There are currently only two computational methods for the prediction of TAT translocated proteins from sequence. Both methods have limitations that make the creation of a new algorithm for TAT-translocated protein prediction desirable. We have developed TATPred, a new sequence-model method, based on a Nave-Bayesian network, for the prediction of TAT signal peptides. In this approach, a comprehensive range of models was tested to identify the most reliable and robust predictor. The best model comprised 12 residues: three residues prior to the twin arginines and the seven residues that follow them. We found a prediction sensitivity of 0.979 and a specificity of 0.942.

A predictor of membrane class:discriminating α-helical and β-barrel membrane proteins from non-membranous proteins

Accurate protein structure prediction remains an active objective of research in bioinformatics. Membrane proteins comprise approximately 20% of most genomes. They are, however, poorly tractable targets of experimental structure determination. Their analysis using bioinformatics thus makes an important contribution to their on-going study. Using a method based on Bayesian Networks, which provides a flexible and powerful framework for statistical inference, we have addressed the alignment-free discrimination of membrane from non-membrane proteins. The method successfully identifies prokaryotic and eukaryotic α-helical membrane proteins at 94.4% accuracy, β-barrel proteins at 72.4% accuracy, and distinguishes assorted non-membranous proteins with 85.9% accuracy. The method here is an important potential advance in the computational analysis of membrane protein structure. It represents a useful tool for the characterisation of membrane proteins with a wide variety of potential applications.

Numerical Approximation of a Fractional-In-Space Diffusion Equation, I

2000 Mathematics Subject Classification: 26A33 (primary), 35S15 (secondary)