The characteristics of depressive symptoms in medical students during medical education and training: a cross-sectional study

Background: Medical education and training can contribute to the development of depressive symptoms that might lead to possible academic and professional consequences. We aimed to investigate the characteristics of depressive symptoms among 481 medical students (79.8% of the total who matriculated). Methods: The Beck Depression Inventory (BDI) and cluster analyses were used in order to better describe the characteristics of depressive symptoms. Medical education and training in Brazil is divided into basic (1(st) and 2(nd) years), intermediate (3(rd) and 4(th) years), and internship (5(th) and 6(th) years) periods. The study organized each item from the BDI into the following three clusters: affective, cognitive, and somatic. Statistical analyses were performed using analysis of variance (ANOVA) with post-hoc Tukey corrected for multiple comparisons. Results: There were 184 (38.2%) students with depressive symptoms (BDI > 9). The internship period resulted in the highest BDI scores in comparison to both the basic (p < .001) and intermediate (p < .001) periods. Affective, cognitive, and somatic clusters were significantly higher in the internship period. An exploratory analysis of possible risk factors showed that females (p = .020) not having a parent who practiced medicine (p = .016), and the internship period (p = .001) were factors for the development of depressive symptoms. Conclusion: There is a high prevalence towards depressive symptoms among medical students, particularly females, in the internship level, mainly involving the somatic and affective clusters, and not having a parent who practiced medicine. The active assessment of these students in evaluating their depressive symptoms is important in order to prevent the development of co-morbidities and suicide risk.

Genetic Background of Patients from a University Medical Center in Manhattan: Implications for Personalized Medicine

Background: The rapid progress currently being made in genomic science has created interest in potential clinical applications; however, formal translational research has been limited thus far. Studies of population genetics have demonstrated substantial variation in allele frequencies and haplotype structure at loci of medical relevance and the genetic background of patient cohorts may often be complex. Methods and Findings: To describe the heterogeneity in an unselected clinical sample we used the Affymetrix 6.0 gene array chip to genotype self-identified European Americans (N = 326), African Americans (N = 324) and Hispanics (N = 327) from the medical practice of Mount Sinai Medical Center in Manhattan, NY. Additional data from US minority groups and Brazil were used for external comparison. Substantial variation in ancestral origin was observed for both African Americans and Hispanics; data from the latter group overlapped with both Mexican Americans and Brazilians in the external data sets. A pooled analysis of the African Americans and Hispanics from NY demonstrated a broad continuum of ancestral origin making classification by race/ethnicity uninformative. Selected loci harboring variants associated with medical traits and drug response confirmed substantial within-and between-group heterogeneity. Conclusion: As a consequence of these complementary levels of heterogeneity group labels offered no guidance at the individual level. These findings demonstrate the complexity involved in clinical translation of the results from genome-wide association studies and suggest that in the genomic era conventional racial/ethnic labels are of little value.

Comparison of multispectral wide-field optical imaging modalities to maximize image contrast for objective discrimination of oral neoplasia

Multispectral widefield optical imaging has the potential to improve early detection of oral cancer. The appropriate selection of illumination and collection conditions is required to maximize diagnostic ability. The goals of this study were to (i) evaluate image contrast between oral cancer/precancer and non-neoplastic mucosa for a variety of imaging modalities and illumination/collection conditions, and (ii) use classification algorithms to evaluate and compare the diagnostic utility of these modalities to discriminate cancers and precancers from normal tissue. Narrowband reflectance, autofluorescence, and polarized reflectance images were obtained from 61 patients and 11 normal volunteers. Image contrast was compared to identify modalities and conditions yielding greatest contrast. Image features were extracted and used to train and evaluate classification algorithms to discriminate tissue as non-neoplastic, dysplastic, or cancer; results were compared to histologic diagnosis. Autofluorescence imaging at 405-nm excitation provided the greatest image contrast, and the ratio of red-to-green fluorescence intensity computed from these images provided the best classification of dysplasia/cancer versus non-neoplastic tissue. A sensitivity of 100% and a specificity of 85% were achieved in the validation set. Multispectral widefield images can accurately distinguish neoplastic and non-neoplastic tissue; however, the ability to separate precancerous lesions from cancers with this technique was limited. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3516593]

Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content

Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.

Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

MEMORY TRAINING FOR OLDER ADULTS WITH LOW EDUCATION: MENTAL IMAGES VERSUS CATEGORIZATION

This study aimed to describe the benefits of memory training for older adults with low education. Twenty-nine healthy older adults with zero to two years of formal education participated. Sixteen participants received training based on categorization (categorization group = CATG) and 13 received training based on mental images (imagery group = IMG). One group served as control for the other because they trained with different strategies. Training was offered in eight sessions of 90 minutes. The participants were evaluated pre- and posttraining. IMG improved performance in episodic memory tests and had reduced depressive symptoms. CATG increased the use of categorization but did not increase performance in episodic memory tests. Results suggest that the strategy based on the creation of mental images was more effective for older adults with low formal education.

Images of a `good nurse` presented by teaching staff

Nursing is at the same time a vocation, a profession and a job. By nature, nursing is a moral endeavor, and being a `good nurse` is an issue and an aspiration for professionals. The aim of our qualitative research project carried out with 18 nurse teachers at a university nursing school in Brazil was to identify the ethical image of nursing. In semistructured interviews the participants were asked to choose one of several pictures, to justify their choice and explain what they meant by an ethical nurse. Five different perspectives were revealed: good nurses fulfill their duties correctly; they are proactive patient advocates; they are prepared and available to welcome others as persons; they are talented, competent, and carry out professional duties excellently; and they combine authority with power sharing in patient care. The results point to a transition phase from a historical introjection of religious values of obedience and service to a new sense of a secular, proactive, scientific and professional identity.

Evaluation of therapeutic ultrasound equipments performance

The therapeutic ultrasound (US) is one of the resources mostly used by physiotherapists; however the use of uncalibrated equipments results in inefficient or even harmful therapies to the patient. In this direction, the objective of this study was to evaluate the performance and the procedures of utilization and maintenance of US in use in clinics and Physical-therapy offices. A questionnaire with questions related to the procedures applied in service during the use of therapeutic ultrasound was applied to physiotherapists. The performance of 31 equipments of 6 different brands and 13 different models was evaluated according to the IEC 61689 norm. The parameters measured were: acoustic power; effective radiating area (AER); non-uniformity ratio of the beam (RBN); maximum effective intensity; acoustic frequency of operation, modulation factor and wave form on pulsate mode. As for the questionnaires, it was evident that the professionals are not concerned about the calibration of the equipment. The results demonstrated that only 32.3% of the equipments were in accordance with the norms for the variables power and effective radiation area. The frequency analysis indicated that 20% of the 3 MHz transducers and 12.5% of the 1 MHz contemplated the norms. In the pulsate mode, 12.7% presented relation rest/duration inside allowed limits. A great variation of the ultrasonic field was observed on the obtained images, which presented beams not centered, sometimes with bifurcation of its apex. The results allow concluding that, although used in therapeutic sessions with the population, none of the equipments presents all the analyzed variables inside technical norms. (C) 2010 Elsevier B. V. All rights reserved.

Recycling Krylov subspaces for efficient large-scale electrical impedance tomography

Electrical impedance tomography (EIT) captures images of internal features of a body. Electrodes are attached to the boundary of the body, low intensity alternating currents are applied, and the resulting electric potentials are measured. Then, based on the measurements, an estimation algorithm obtains the three-dimensional internal admittivity distribution that corresponds to the image. One of the main goals of medical EIT is to achieve high resolution and an accurate result at low computational cost. However, when the finite element method (FEM) is employed and the corresponding mesh is refined to increase resolution and accuracy, the computational cost increases substantially, especially in the estimation of absolute admittivity distributions. Therefore, we consider in this work a fast iterative solver for the forward problem, which was previously reported in the context of structural optimization. We propose several improvements to this solver to increase its performance in the EIT context. The solver is based on the recycling of approximate invariant subspaces, and it is applied to reduce the EIT computation time for a constant and high resolution finite element mesh. In addition, we consider a powerful preconditioner and provide a detailed pseudocode for the improved iterative solver. The numerical results show the effectiveness of our approach: the proposed algorithm is faster than the preconditioned conjugate gradient (CG) algorithm. The results also show that even on a standard PC without parallelization, a high mesh resolution (more than 150,000 degrees of freedom) can be used for image estimation at a relatively low computational cost. (C) 2010 Elsevier B.V. All rights reserved.

Strategic alignment and performance: Brazilian companies in the medical diagnostics sector

A gap has been identified in the literature on the diagnosis and monitoring of the degree of strategic alignment. The main objective of this article is to diagnose and analyze the strategic alignment profile using the alignment diagnostic profile (ADP) tool, which enables organizations to show visually their degree of strategic alignment. The methodological approach adopted is multiple-case studies, which were conducted at five organizations in the medical diagnostics sector. The results indicate that the ADP enables organizations to understand the steps required to improve their level of alignment and to identify and locate gaps and conflicts.

Ciratefi: An RST-invariant template matching with extension to color images

Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

Recognition of noisy images by PLL networks

We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.

In Vitro and In Vivo Evaluation of Lyophilized Bioprosthetic Valve

Freeze-drying of biological tissues allows for dry storage and gamma ray sterilization, which may improve their use as a medical prosthesis. The objective of this study was to evaluate the rehydration characteristics and hydrodynamic performance of prosthetic valves before and after lyophilization. Two size 23 bovine pericardium aortic valve prostheses from different manufacturers were evaluated in a Shelhigh (Union, NJ, USA) pulse duplicator (80 ppm, 5 L/min) before and after lyophilization. Flow and transvalvular pressure gradient were registered in vitro and in vivo, and images of opening and closing of the prosthesis were obtained in the pulse duplicator in a digital camera. Rehydration was evaluated by comparison of dry valve weight with valve weight after 15 min, and 1, 24, 48, and 72 h in saline solution, inside the pulse duplicator. In vivo performance was assessed by surgical implantation in Santa Ines young male sheep in the pulmonary position after 30 min rehydration with 0.9% saline. Transvalvular pressure gradient and flow measurements were obtained immediately after implantation and 3 months after surgery when valves were explanted. Captured images showed a change in the profile opening and closing of valve prosthesis after lyophilization. The gradient measured (in vitro) in two valves was 17.08 +/- 0.57 and 18.76 +/- 0.70 mm Hg before lyophilization, and 34.24 +/- 0.59 and 30.40 +/- 0.97 mm Hg after lyophilization. Rehydration of both lyophilized valves was approximately 82%. Drying changed the profile of the opening and closing of valve prostheses, and increased on average by 83% the gradient in vitro tests. The result of the in vivo tests suggests maintaining pressure levels of the animal with the lyophilized prostheses within acceptable levels.

Animated solid model of the lung constructed from unsynchronized MR sequential images

This work discusses a 4D lung reconstruction method from unsynchronized MR sequential images. The lung, differently from the heart, does not have its own muscles, turning impossible to see its real movements. The visualization of the lung in motion is an actual topic of research in medicine. CT (Computerized Tomography) can obtain spatio-temporal images of the heart by synchronizing with electrocardiographic waves. The FOV of the heart is small when compared to the lung`s FOV. The lung`s movement is not periodic and is susceptible to variations in the degree of respiration. Compared to CT, MR (Magnetic Resonance) imaging involves longer acquisition times and it is not possible to obtain instantaneous 3D images of the lung. For each slice, only one temporal sequence of 2D images can be obtained. However, methods using MR are preferable because they do not involve radiation. In this paper, based on unsynchronized MR images of the lung an animated B-Repsolid model of the lung is created. The 3D animation represents the lung`s motion associated to one selected sequence of MR images. The proposed method can be divided in two parts. First, the lung`s silhouettes moving in time are extracted by detecting the presence of a respiratory pattern on 2D spatio-temporal MR images. This approach enables us to determine the lung`s silhouette for every frame, even on frames with obscure edges. The sequence of extracted lung`s silhouettes are unsynchronized sagittal and coronal silhouettes. Using our algorithm it is possible to reconstruct a 3D lung starting from a silhouette of any type (coronal or sagittal) selected from any instant in time. A wire-frame model of the lung is created by composing coronal and sagittal planar silhouettes representing cross-sections. The silhouette composition is severely underconstrained. Many wire-frame models can be created from the observed sequences of silhouettes in time. Finally, a B-Rep solid model is created using a meshing algorithm. Using the B-Rep solid model the volume in time for the right and left lungs were calculated. It was possible to recognize several characteristics of the 3D real right and left lungs in the shaded model. (C) 2007 Elsevier Ltd. All rights reserved.

Sterilization of Medical Devices by Ethylene Oxide, Determination of the Dissipation of Residues, and Use of Green Fluorescent Protein as an Indicator of Process Control

Ethylene oxide (EO) is used to sterilize Oxygenator and Tubing applied to heart surgery. Residual levels of EO and its derivatives, ethylene chlorohydrin (ECH) and ethylene glycol (EG), may be hazardous to the patients. Therefore, it must be removed by the aeration process. This study aimed to estimate the minimum aeration time for these devices to attain safe limits for use (avoiding excessive aeration time) and to evaluate the Green Fluorescent Protein (GFP) as a biosensor capable of best indicating the distribution and penetration of EO gas throughout the sterilization chamber. Sterilization cycles of 2, 4, and 8 h were monitored by Bacillus atrophaeus ATCC 9372 as a biological indicator (131) and by the GFP. Residual levels of EO, ECH, and EG were determined by gas chromatography (GC), and the residual dissipation was studied. Safe limits were reached right after the sterilization process for Oxygenator and after 204 h of aeration for Tubing. In the 2 h cycle, the GFP concentration decreased from 4.8 (+/- 3.2)% to 7.5 (+/- 2.5)%. For the 4 h cycle, the GFP concentration decreased from 17.4 (+/- 3.0)% to 21.5 (+/- 6.8)%, and in the 8 h cycle, it decreased from 22.5 (+/- 3.2)% to 23.9 (+/- 3.9)%. This finding showed the potentiality for GFP applications as an EO biosensor. (C) 2009 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater 9113: 626-630, 2009