Identification of enteropathogens from buffalo calves with and without diarrhoea in the Ribeira Valley, State of São Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Identification and characterization of different accessions of itchgrass (Rottboellia cochinchinensis)

Studies were conducted to identify and characterize different accessions of itchgrass. Seeds were collected in the counties of Aramina, Campinas, Dumont, Igarapava, Jaboticabal, and Ribeirao Preto, all in the state of São Paulo, Brazil. Accessions were characterized based on dimensions of their stomata, stomatal index (SI), and length and width of their seed (caryopses and husk). Chromosome number and length also were determined, and accessions were further differentiated using molecular markers (polymerase chain reaction [PCR]). Itchgrass from Ribeirao Preto had much longer and narrower seeds than those from the other locations, and their husks were longer as well. Accessions had similar SIs, both on the abaxial and adaxial leaf surfaces. Stomata from Campinas and Igarapava accessions were longer and wider, whereas those from Dumont and Ribeirao Preto were similar and smaller than all others. The accession from Ribeirao Preto is diploid (2n = 20); the rest are polyploid, with the total length of chromosomes smaller than all others. These differences were confirmed by molecular differentiation (PCR).

The diagnostic value of Gram stain for initial identification of the etiologic agent of peritonitis in CAPD patients

Objective: To evaluate the effectiveness of the Gram stain in the initial diagnosis of the etiologic agent of peritonitis in continuous ambulatory peritoneal dialysis (CAPD). Design: Retrospective study analyzing the sensitivity (S), specificity (SS), positive predictive value (+PV), and negative predictive value (-PV) of the Gram stain relating to the results of cultures in 149 episodes of peritonitis in CAPD. The data were analyzed in two studies. In the first, only the cases with detection of a single agent by Gram stain were taken (Study 1). In the second, only the cases with two agents in Gram stain were evaluated (Study 2). Setting: Dialysis Unit and Laboratory of Microbiology of a tertiary medical center. Patients: Sixty-three patients on regular CAPD who presented one or more episodes of peritonitis from May 1992 to May 1995. Results: The positivity of Gram stain was 93.2% and the sensitivity was 95.7%. The values of S, SS, +PV, and -PV were respectively: 94.9%, 53.5%, 68.3%, and 90.9% for gram-positive cocci and 83.3%, 98.8%, 95.2%, and 95.6% for gram-negative bacilli. The association of gram-positive cocci plus gram-negative bacilli were predictive of growth of both in 6.8%, growth of gram-positive cocci in 13.7%, and growth of gram-negative bacilli in 72.5%. Conclusions: The Gram stain is a method of great value in the initial diagnosis of the etiologic agent of peritonitis in CAPD, especially for gram-negative bacilli.

Oropharyngeal dysphagia identification using wavelets and optimum path forest

The swallowing disturbers are defined as oropharyngeal dysphagia when present specifies signals and symptoms that are characterized for alterations in any phases of swallowing. Early diagnosis is crucial for the prognosis of patients with dysphagia and the potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. This study proposes a new framework for oropharyngeal dysphagia identification, having two main contributions: a new set of features extract from swallowing signal by discrete wavelet transform and the dysphagia classification by a novel pattern classifier called OPF. We also employed the well known SVM algorithm in the dysphagia identification task, for comparison purposes. We performed the experiments in two sub-signals: the first was the moment of the maximal peak (MP) of the signal and the second is the swallowing apnea period (SAP). The OPF final accuracy obtained were 85.2% and 80.2% for the analyzed signals MP and SAP, respectively, outperforming the SVM results. ©2008 IEEE.

Multiplex PCR use for Staphylococcus aureus identification and oxacillin and mupirocin resistance evaluation

Oxacillin-resistant Staphylococcus aureus represents a serious problem in hospitals worldwide, increasing infected patients' mortality and morbidity and raising treatment costs and internment time. In this study, the results of using the Multiplex PCR technique to amplify fragments of the genes femA (specific-species), mecA (oxacillin resistance) and ileS-2 (mupirocin resistance) were compared with those of tests conventionally used to identify S. aureus isolates and ascertain their resistance to drugs. Fifty S. aureus strains were isolated from patients receiving treatment at UNOESTE University Hospital in Presidente Prudente, SP, Brazil. The 686 bp fragment corresponding to the gene femA was amplified and detected in all the isolates. On the other hand, the 310 bp fragment corresponding to the mecA gene was amplified in 29 (58%) of the isolates. All of the isolates showed sensitivity to mupirocin in the agar diffusion test, which was corroborated by the lack of any amplicon of the 456 bp fragment corresponding to the ileS-2 gene, in the PCR bands. The conventional tests to identify S. aureus and detect resistance to oxacillin and mupirocin showed 100% agreement with the PCR Multiplex results. The use of techniques for rapid and accurate identification of bacteria and assessment of their resistance may be valuable in the control of infection by resistant strains, allowing the rapid isolation and treatment of an infected patient. However, the results demonstrate that traditional phenotypic tests are also reliable, though they take more time.

Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis

This paper presents the study of computational methods applied to histological texture analysis in order to identify plant species, a very difficult task due to the great similarity among some species and presence of irregularities in a given species. Experiments were performed considering 300 ×300 texture windows extracted from adaxial surface epidermis from eight species. Different texture methods were evaluated using Linear Discriminant Analysis (LDA). Results showed that methods based on complexity analysis perform a better texture discrimination, so conducting to a more accurate identification of plant species. © 2009 Springer Berlin Heidelberg.

Evaluation of a digital methodology for human identification using palatal rugoscopy

Palatal rugoscopy, or palatoscopy, is the process by which human identification can be obtained by inspecting the transverse palatal rugae inside the mouth. Aim: This study evaluated a digital method for human identification using palatoscopy, by comparing photographs of the palate against the images of cast models of the maxilla photographed with and without highlighting of the palatal rugae. Methods: Condensation silicone impressions were made from the upper arches of 30 adult subjects of both genders and their palates were then photographed. The first impression was made with heavy silicone, the second impression with light silicone, and then the models were cast in improved type IV dental stone. The casts were photographed, the palatal rugae of each one were highlighted with a pencil, and then the models were photographed again. Using a free image-editing software, the digital photographs were overlapped over the images of the palatal rugae of the models with and without highlighting of the palatal rugae, in order to identify the pairs. Results: The result of overlapping the digital photographs with the images of the models without highlighted palatal rugae resulted in 90% positive identification. For the overlapping of the digital photographs with the images of models with highlighted palatal rugae, there was 100% positive identification. Conclusions: The digital method evaluated in this study was proven effective for human identification.

What is the importance of selecting features for non-technical losses identification?

Although non-technical losses automatic identification has been massively studied, the problem of selecting the most representative features in order to boost the identification accuracy has not attracted much attention in this context. In this paper, we focus on this problem applying a novel feature selection algorithm based on Particle Swarm Optimization and Optimum-Path Forest. The results demonstrated that this method can improve the classification accuracy of possible frauds up to 49% in some datasets composed by industrial and commercial profiles. © 2011 IEEE.

Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets

The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind of classifier can be important for many applications. In this paper we report a fast method to combine OPF-based classifiers trained with disjoint training subsets. Given a fixed number of subsets, the algorithm chooses random samples, without replacement, from the original training set. Each subset accuracy is improved by a learning procedure. The final decision is given by majority vote. Experiments with simulated and real data sets showed that the proposed combining method is more efficient and effective than naive approach provided some conditions. It was also showed that OPF training step runs faster for a series of small subsets than for the whole training set. The combining scheme was also designed to support parallel or distributed processing, speeding up the procedure even more. © 2011 Springer-Verlag.

Improving Parkinson's disease identification through evolutionary-based feature selection

Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.

Fast identification of individuals based on iris characteristics for biometric systems

Nowadays, systems based on biométrie techniques have a wide acceptance in many different areas, due to their levels of safety and accuracy. A biometrie technique that is gaining prominence is the identification of individuals through iris recognition. However, to be proficiently used these systems must process their recognition task as fast as possible. The goal of this work has been the development of an iris recognition method to produce results rapidly, yet without losing the recognition accuracy. The experimental results show that the method is quite promising. © 2012 Taylor & Francis Group.

Determinação de GMP e CMP* no leite por métodos espectrofotométrico (ANSM) e cromatográfico (HPLC) - parâmetros metodológicos (*glicomacropeptídeo e caseinomacropeptídeo)

Glycomacropeptide is a glycosilated fraction of bovine kappa-casein that remains soluble when milk is clotted by rennin. Determinations of milk sialic acid content are useful because its concentration reflects the amount of free GMP of milk. In normal milk these amounts are very low, 12 to 16 times lower than in sweet whey. Therefore, its determination may be applied to verify possible frauds with whey addictions, since it works as a fingerprint. With the description of a new spectrophotometric method for determination of free GMP (ANSM) occurred a simplification of procedures, being faster than others (HPLC method), without loss of accuracy. However, due to variations of glycosilation in kappa-casein between animals, during the lactation period, due to mastitis and yet due to proteolysis on milk, it was necessary to know these variations to interpret correctly the analytical results. It was analyzed 1,703 samples of producer's raw milk and 1,189 samples of processed milk (HTST and UHT). The results showed that normal milk from herd (producer's milk) have only small amounts of free GMP, with A470nm = 0.232±0.088 or 3.89±1.25 mg of sialic acid/L. The upper limit of this distribution was A = 0.496; thus every bigger value may represent a problem, being outside of normal distribution.

What affective neuroscience means for science of consciousness

The field of affective neuroscience has emerged from the efforts of Jaak Panksepp in the 1990s and reinforced by the work of, among others, Joseph LeDoux in the 2000s. It is based on the ideas that affective processes are supported by brain structures that appeared earlier in the phylogenetic scale (as the periaqueductal gray area), they run in parallel with cognitive processes, and can influence behaviour independently of cognitive judgements. This kind of approach contrasts with the hegemonic concept of conscious processing in cognitive neurosciences, which is based on the identification of brain circuits responsible for the processing of (cognitive) representations. Within cognitive neurosciences, the frontal lobes are assigned the role of coordinators in maintaining affective states and their emotional expressions under cognitive control. An intermediary view is the Damasio-Bechara Somatic Marker model, which puts cognition under partial somatic-affective control. We present here our efforts to make a synthesis of these views, by proposing the existence of two interacting brain circuits; the first one in charge of cognitive processes and the second mediating feelings about cognitive contents. The coupling of the two circuits promotes an endogenous feedback that supports conscious processes. Within this framework, we present the defence that detailed study of both affective and cognitive processes, their interactions, as well of their respective brain networks, is necessary for a science of consciousness.© MSM 2013.