Multicenter validation of PIM3 and PIM2 in Brazilian pediatric intensive care units.

Objective: To validate the PIM3 score in Brazilian PICUs and compare its performance with the PIM2. Methods: Observational, retrospective, multicenter study, including patients younger than 16 years old admitted consecutively from October 2013 to September 2019. We assessed the Standardized Mortality Ratio (SMR), the discrimination capability (using the area under the receiver operating characteristic curve - AUROC), and the calibration. To assess the calibration, we used the calibration belt, which is a curve that represents the correlation of predicted and observed values and their 95% Confidence Interval (CI) through all the risk ranges. We also analyzed the performance of both scores in three periods: 2013-2015, 2015-2017, and 2017-2019. Results: 41,541 patients from 22 PICUs were included. Most patients aged less than 24 months (58.4%) and were admitted for medical conditions (88.6%) (respiratory conditions = 53.8%). Invasive mechanical ventilation was used in 5.8%. The median PICU length of stay was three days (IQR, 2-5), and the observed mortality was 1.8% (763 deaths). The predicted mortality by PIM3 was 1.8% (SMR 1.00; 95% CI 0.94-1.08) and by PIM2 was 2.1% (SMR 0.90; 95% CI 0.83-0.96). Both scores had good discrimination (PIM3 AUROC = 0.88 and PIM2 AUROC = 0.89). In calibration analysis, both scores overestimated mortality in the 0%-3% risk range, PIM3 tended to underestimate mortality in medium-risk patients (9%-46% risk range), and PIM2 also overestimated mortality in high-risk patients (70%-100% mortality risk). Conclusions: Both scores had a good discrimination ability but poor calibration in different ranges, which deteriorated over time in the population studied.

Reproducibility of Heart Rate Variability Indices at Post-maximal Exercise.

To analyze whether heart rate variability is reproducible after maximal exercise, 11 men (22.1±3.2 years) performed four incremental exercise tests followed by passive or active recovery. There was high reliability (intraclass coefficient correlation: 0.72-0.96) and fair-to-excellent agreement (coefficient of variation: 7.81-22.09%) in passive recovery, as well as moderate-to-high reliability (intraclass coefficient correlation: 0.50-0.87) and good agreement (coefficient of variation: 11.08-20.89%) in active recovery for LnRMSSD index. There was moderate-to-high reliability (intraclass coefficient correlation: 0.51-0.81) and good agreement (coefficient of variation: 10.41-18.87%) in most of the analyzed time points, in both recovery types for LnSDNN. In both types of recovery, the time domain heart rate variability 5-10 min indices (passive: intraclass coefficient correlation : 0.87-0.88; coefficient of variation: 7.67-13.44%; active: intraclass coefficient correlation 0.59-0.80; coefficient of variation: 14.62-16.26%) presented higher intraclass coefficient correlation and lower coefficient of variation than the spectral heart rate variability indices (passive: intraclass coefficient correlation: 0.71-0.87; coefficient of variation: 12.33-34.21%; active: intraclass coefficient correlation: 0.46-0.77; coefficient of variation: 24.41-105.12%). The LnRMSSD and LnSDNN indices analyzed in 30 s segments and the heart rate variability 5-10 min indices after maximal exercise in untrained healthy men showed satisfactory reproducibility, regardless of the type of recovery, with the time-domain indices showing higher reproducibility than the frequency-domain indices.

Yeast isolation and identification in water used in a Brazilian hemodialysis unit by classic microbiological techniques and Raman spectroscopy.

The use of poorly treated water in hemodialysis centers may lead to fungal contamination, which poses a serious threat to immunologically debilitated hemodialysis patients. This study aimed to isolate and identify yeast species in the water of a Brazilian hemodialysis center by using classic microbiological techniques and Raman spectroscopy. For 12 months, a total of 288 water samples were collected from different points of the hemodialysis treatment distribution center. One hundred and forty-six yeast species were isolated and identified in the samples that tested positive for the presence of yeasts such as Candida parapsilosis (100 isolates, or 68.50%), C. guilliermondii (17 isolates, or 11.65%), Rhodotorula mucilaginosa (23 isolates, or 15.75%), R. glutinis (three isolates, or 2.05%), and Trichosporon inkin (three isolates, or 2.05%). Yeast susceptibility to the antifungal fluconazole was also assayed. Only two C. guilliermondii isolates were resistant to fluconazole: the minimal inhibitory concentrations were higher than 64 µg/mL. The different yeast species present in the water of a Brazilian hemodialysis center call for more effective water disinfection procedures in this unit. Raman spectroscopy is an excellent tool to identify yeast species and is potentially applicable in routine water monitoring in hemodialysis units.

Fast determination of thyroid stimulating hormone in human blood serum without chemical preprocessing by using infrared spectroscopy and least squares support vector machines.

The least squares support vector machines (LS-SVM) was used to model infrared spectral data for TSH hormone secreted by thyroid, which regulates the basal metabolic rate. This model was used for direct estimation of the content of TSH in blood serum samples, and the results were comparable with those obtained with the conventional analytical method based on chemoluminescence methodology. Excellent agreement was observed between the conventional method and the newly developed calibration model based in analysis of spectral data with LS-SVM. The latter has clear advantages, because it is fast and requires no reagent once the measurements were done directly in the serum by using a simple mid-infrared spectrometer in the ATR mode. An important advantage observed in this calibration method based on LS-SVM is the remarkable capacity to avoid overfitting in the model-building step, that is, the developed method is highly robust.

Effect of consanguinity on Argentinean Angus beef DNA traceability.

Since the 1990s several authors have envisaged the use of DNA to certify meat origin. Two major parameters must be assessed before a DNA based traceability protocol can be implemented in the food chain: (i) the information content of a DNA marker set in a specific livestock breed or group of breeds; (ii) the minimum number of DNA markers needed to obtain a statistically acceptable match probability. The objective of the present work was to establish the effect of different levels of inbreeding in the matching efficiency, and the minimum number of microsatellite markers needed, in a DNA based meat traceability program, starting from an 11-microsatellite marker panel. Samples were obtained from beef production farms in South America, where animals are typically bred under pasture-based extensive conditions. Three groups of animals with different consanguinity rates were sampled. Exclusion power (Q) was higher than 0.999998 and match probability lower than 3.01E-08, for the whole set of markers within each group. Both values were affected by consanguinity. To reach a two mismatch criteria exclusion power (Q(2)) of 99.99, six markers were needed in unrelated animals whereas seven markers were needed in related animals. To reach Q(2)=99.9999, 8 and 10 microsatellite markers, respectively, were needed. In general, one or two more microsatellite markers were needed to identify consanguineous animals. This study proved the DNA marker set used to be suitable for the identification of the meat from all slaughtered animals in Argentina, per week, month, and year.

Microstructures formation in a seemingly ideal homogeneous mixture of ethanol and methanol: An experimental evidence and two-dimensional correlation spectroscopy approach.

An anomalous solution behavior at the molecular scale was observed for macroscopically homogeneous mixtures of methanol and ethanol. Two-dimensional Raman correlation spectroscopy was used to elucidate the possible existence of microstructures formed in the mixture. The result suggests that separate methanol and ethanol clusters are formed without heterohydrogen bonding between different alcohol species. Supramolecular structures seem to be formed by the interaction of such clusters with each other through cohesion and dispersion forces, but not through direct hydrogen bonding connections.

Elimination of iron interference in the molecular spectrophotometric determination of aluminum in soil extracts using artificial neural networks.

An artificial neural network (ANN) calibration model was developed to determine aluminum in the presence of iron in soil extracts, using xylenol orange as chromogenic reagent. The spectral data of synthetic mixtures of Al(3+) and Fe(3+) as well as of the soil extracts, were recorded in the range between 410 and 580 nm. Method validation was carried out using 18 soil extracts. The results gave good linear correlations between the ANN model and the ICP OES measurements for both species.

Non-destructive method for determination of hydroxyl value of soybean polyol by LS-SVM using HATR/FT-IR.

This paper presents the use of least-squares support vector machine (LS-SVM) for quantitative determination of hydroxyl value (OHV) of hydroxylated soybean oils by horizontal attenuated total reflection Fourier transform infrared (HATR/FT-IR) spectroscopy. A least-squares support vector machine (LS-SVM) calibration model for the prediction of hydroxyl value (OHV) was developed using the range 1805.1-649.9 cm(-1). Validation of the method was carried out by comparing the OHV of a series of hydroxylated soybean oil predicted by the LS-SVM model to the values obtained by the AOCS standard method. A correlation coefficient equal to 0.989 and RMSEP = 4.96 mg of KOH/g was obtained. This study demonstrates a better prediction ability of the LS-SVM technique to determine OHV in hydroxylated soybean oil samples by HATR/FT-IR spectra.

Quantification of Lactobacillus in fermented milk by multivariate image analysis with least-squares support-vector machines.

This paper reports an approach for quantification of Lactobacillus in fermented milk, grown in a selective medium (MRS agar), by use of digital colour images of Petri plates easily obtained by use of a flatbed scanner. A one-dimensional data vector was formed to characterize each digital image on the basis of the frequency-distribution curves of the red (R), green (G), and blue (B) colour values, and quantities derived from them, for example lightness (L), relative red (RR), relative green (RG), and relative blue (RB). The frequency distributions of hue, saturation, and intensity (HSI) were also calculated and included in the data vector used to describe each image. Multivariate non-linear modelling using the least-squares support vector machine (LS-SVM) and a linear model based on PLS regression were developed to relate the microbiological count and the frequency vector. Feasibly models were developed using the LS-SVM and errors were below than 10% for Lactobacillus quantification, indicating the proposed approach can be used for automatic counting of colonies.

Least-squares support vector machines and near infrared spectroscopy for quantification of common adulterants in powdered milk.

This paper proposes the use of the least-squares support vector machine (LS-SVM) as an alternative multivariate calibration method for the simultaneous quantification of some common adulterants (starch, whey or sucrose) found in powdered milk samples, using near-infrared spectroscopy with direct measurements by diffuse reflectance. Due to the spectral differences of the three adulterants a nonlinear behavior is present when all groups of adulterants are in the same data set, making the use of linear methods such as partial least squares regression (PLSR) difficult. Excellent models were built using LS-SVM, with low prediction errors and superior performance in relation to PLSR. These results show it possible to built robust models to quantify some common adulterants in powdered milk using near-infrared spectroscopy and LS-SVM as a nonlinear multivariate calibration procedure.

Rapid differentiation among bacteria that cause gastroenteritis by use of low-resolution Raman spectroscopy and PLS discriminant analysis.

Use of classical microbiological methods to differentiate bacteria that cause gastroenteritis is cumbersome but usually very efficient. The high cost of reagents and the time required for such identifications, approximately four days, could have serious consequences, however, mainly when the patients are children, the elderly, or adults with low resistance. The search for new methods enabling rapid and reagentless differentiation of these microorganisms is, therefore, extremely relevant. In this work the main microorganisms responsible for gastroenteritis, Escherichia coli, Salmonella choleraesuis, and Shigella flexneri, were studied. For each microorganism sixty different dispersions were prepared in physiological solution. The Raman spectra of these dispersions were recorded using a diode laser operating in the near infrared region. Partial least-squares (PLS) discriminant analysis was used to differentiate among the bacteria by use of their respective Raman spectra. This approach enabled correct classification of 100% of the bacteria evaluated and unknown samples from the clinical environment, in less time ( approximately 10 h), by use of a low-cost, portable Raman spectrometer, which can be easily used in intensive care units and clinical environments.

Improvement of trypanocidal metabolites production by Aspergillus fumigatus using neural networks.

An optimization procedure using artificial neural networks was developed to determine the optimal combination of parameters, such as medium culture, initial pH, temperature and time of fermentation for maximal trypanocidal metabolites production by Aspergillus fumigatus. A data set of 81 experiments was carried out and an artificial neural network was trained to identify the optimal conditions for this process. Good correlation was obtained between the experimental and predicted values of lysis of the trypomastigote forms of Trypanosoma cruzi (r2 = 0.9990). The simulations of fermentation performance were undertaken on combinations of input variables and the highest level of activity against T. cruzi was obtained from the chloroform extract of the modified Jackson medium culture, initial pH of 6.0, incubated at 40 degrees C for 144 h. It displayed lysis of 95% of the trypomastigote forms of T. cruzi and the red blood cells remained normal.

Construçäo de um micrótomo de congelamento a partir da adaptaçäo de um micrótomo de parafina / Building of a frozen microtome by the adaptation of a paraffin microtome

A microtome for frozen sections was developed using the facilities and equipment avaiable in our country. The requirements for making it were: 1) fast frozen of the tissue; 2) easy hystological procedure; 3) no necessity of long period for preparation of the tissue for histological procedure, and 4) low cost for making. This study shows results obtained by using the microtome for frozen sections of brain of rats