Detection of all four dengue serotypes in Aedes aegypti female mosquitoes collected in a rural area in Colombia

The Aedes aegypti vector for dengue virus (DENV) has been reported in urban and periurban areas. The information about DENV circulation in mosquitoes in Colombian rural areas is limited, so we aimed to evaluate the presence of DENV in Ae. aegypti females caught in rural locations of two Colombian municipalities, Anapoima and La Mesa. Mosquitoes from 497 rural households in 44 different rural settlements were collected. Pools of about 20 Ae. aegypti females were processed for DENV serotype detection. DENV in mosquitoes was detected in 74% of the analysed settlements with a pool positivity rate of 62%. The estimated individual mosquito infection rate was 4.12% and the minimum infection rate was 33.3/1,000 mosquitoes. All four serotypes were detected; the most frequent being DENV-2 (50%) and DENV-1 (35%). Two-three serotypes were detected simultaneously in separate pools. This is the first report on the co-occurrence of natural DENV infection of mosquitoes in Colombian rural areas. The findings are important for understanding dengue transmission and planning control strategies. A potential latent virus reservoir in rural areas could spill over to urban areas during population movements. Detecting DENV in wild-caught adult mosquitoes should be included in the development of dengue epidemic forecasting models.

Automatic landmarks detection in breast reconstruction aesthetic assessment.

This paper addresses a fully automatic landmarks detection method for breast reconstruction aesthetic assessment. The set of landmarks detected are the supraesternal notch (SSN), armpits, nipples, and inframammary fold (IMF). These landmarks are commonly used in order to perform anthropometric measurements for aesthetic assessment. The methodological approach is based on both illumination and morphological analysis. The proposed method has been tested with 21 images. A good overall performance is observed, although several improvements must be achieved in order to refine the detection of nipples and SSNs.

Detection of the movement of the humerus during daily activity.

A new ambulatory technique for qualitative and quantitative movement analysis of the humerus is presented. 3D gyroscopes attached on the humerus were used to recognize the movement of the arm and to classify it as flexion, abduction and internal/external rotations. The method was first validated in a laboratory setting and then tested on 31 healthy volunteer subjects while carrying the ambulatory system during 8 h of their daily life. For each recording, the periods of sitting, standing and walking during daily activity were detected using an inertial sensor attached on the chest. During each period of daily activity the type of arm movement (flexion, abduction, internal/external rotation) its velocity and frequency (number of movement/hour) were estimated. The results showed that during the whole daily activity and for each activity (i.e. walking, sitting and walking) the frequency of internal/external rotation was significantly higher while the frequency of abduction was the lowest (P < 0.009). In spite of higher number of flexion, abduction and internal/external rotation in the dominant arm, we have not observed in our population a significant difference with the non-dominant arm, implying that in healthy subjects the arm dominance does not lie considerably on the number of movements. As expected, the frequency of the movement increased from sitting to standing and from standing to walking, while we provide a quantitative value of this change during daily activity. This study provides preliminary evidence that this system is a useful tool for objectively assessing upper-limb activity during daily activity. The results obtained with the healthy population could be used as control data to evaluate arm movement of patients with shoulder diseases during daily activity.

Coronary magnetic resonance angiography for the detection of coronary stenoses.

BACKGROUND: An accurate, noninvasive technique for the diagnosis of coronary disease would be an important advance. We investigated the accuracy of coronary magnetic resonance angiography among patients with suspected coronary disease in a prospective, multicenter study. METHODS: Coronary magnetic resonance angiography was performed during free breathing in 109 patients before elective x-ray coronary angiography, and the results of the two diagnostic procedures were compared. RESULTS: A total of 636 of 759 proximal and middle segments of coronary arteries (84 percent) were interpretable on magnetic resonance angiography. In these segments, 78 (83 percent) of 94 clinically significant lesions (those with a > or = 50 percent reduction in diameter on x-ray angiography) were also detected by magnetic resonance angiography. Overall, coronary magnetic resonance angiography had an accuracy of 72 percent (95 percent confidence interval, 63 to 81 percent) in diagnosing coronary artery disease. The sensitivity, specificity, and accuracy for patients with disease of the left main coronary artery or three-vessel disease were 100 percent (95 percent confidence interval, 97 to 100 percent), 85 percent (95 percent confidence interval, 78 to 92 percent), and 87 percent (95 percent confidence interval, 81 to 93 percent), respectively. The negative predictive values for any coronary artery disease and for left main artery or three-vessel disease were 81 percent (95 percent confidence interval, 73 to 89 percent) and 100 percent (95 percent confidence interval, 97 to 100 percent), respectively. CONCLUSIONS: Among patients referred for their first x-ray coronary angiogram, three-dimensional coronary magnetic resonance angiography allows for the accurate detection of coronary artery disease of the proximal and middle segments. This noninvasive approach reliably identifies (or rules out) left main coronary artery or three-vessel disease.

Detection of possible variant forms of hemoglobin in HbA1c measurements by chromatography liquid ion exchange high resolution (HPLC)

Background: The glycosylated hemoglobin (HbA1c) is used to help monitor the degree of a diabetic’s hyperglycemia. Security and accuracy of the methods used in its detection are affected by variants forms of Hb or elevations in levels of Fetal Hb (HbF). These interference are the result of a change in the haemoglobin total net charge of the variant due of a substitution of one amino acid in the remaining amino terminal of the beta chain. International Standardization for HbA1c values (NGSP) not include interference assessment as part of the certification program. Therefore, the effect of each variant or the lifting of the HbF on HbA1c result should be examined in each sample depending on the detected variant and the method used for the detection of the same. The objectives were: to describe the possible variants of Hb and their interference in HbA1c measurement by our method, after the implementation of a computer program for their detection. To identify some variants detected by chromatography liquid ion exchange high resolution (HPLC) with DNA molecular sequencing.

Evaluation of the speed-oligo direct Mycobacterium tuberculosis assay for molecular detection of mycobacteria in clinical respiratory specimens.

We present the first evaluation of a novel molecular assay, the Speed-oligo Direct Mycobacterium tuberculosis (SO-DMT) assay, which is based on PCR combined with a dipstick for the detection of mycobacteria and the specific identification of M. tuberculosis complex (MTC) in respiratory specimens. A blind evaluation was carried out in two stages: first, under experimental conditions on convenience samples comprising 20 negative specimens, 44 smear- and culture-positive respiratory specimens, and 11 sputa inoculated with various mycobacterium-related organisms; and second, in the routine workflow of 566 fresh respiratory specimens (4.9% acid-fast bacillus [AFB] smear positives, 7.6% MTC positives, and 1.8% nontuberculous mycobacteria [NTM] culture positives) from two Mycobacterium laboratories. SO-DMT assay showed no reactivity in any of the mycobacterium-free specimens or in those with mycobacterium-related organisms. Compared to culture, the sensitivity in the selected smear-positive specimens was 0.91 (0.92 for MTC and 0.90 for NTM), and there was no molecular detection of NTM in a tuberculosis case or vice versa. With respect to culture and clinical data, the sensitivity, specificity, and positive and negative predictive values for the SO-DMT system in routine specimens were 0.76 (0.93 in smear positives [1.0 for MTC and 0.5 for NTM] and 0.56 in smear negatives [0.68 for MTC and 0.16 for NTM]), 0.99, 0.85 (1.00 in smear positives and 0.68 in smear negatives), and 0.97, respectively. Molecular misidentification of NTM cases occurred when testing 2 gastric aspirates from two children with clinically but not microbiologically confirmed lung tuberculosis. The SO-DMT assay appears to be a fast and easy alternative for detecting mycobacteria and differentiating MTC from NTM in smear-positive respiratory specimens.

New Granada Medium for detection and identification of group B streptococci.

A methotrexate-containing medium for the detection of beta-hemolytic group B streptococci from clinical specimens on the basis of detection of pigment is described. The medium contained peptone, starch, serum, MgSO4, glucose, pyruvate, methotrexate (as pigment enhancer), phosphate-morpholine-propanesulfonic acid buffer, and selective agents. The recovery of beta-hemolytic group B streptococci was comparable to that obtained with selective broth.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.