Detection of muscle wasting in patients with chronic heart failure using C-terminal agrin fragment: results from the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF).

AIMS Skeletal muscle wasting affects 20% of patients with chronic heart failure and has serious implications for their activities of daily living. Assessment of muscle wasting is technically challenging. C-terminal agrin-fragment (CAF), a breakdown product of the synaptically located protein agrin, has shown early promise as biomarker of muscle wasting. We sought to investigate the diagnostic properties of CAF in muscle wasting among patients with heart failure. METHODS AND RESULTS We assessed serum CAF levels in 196 patients who participated in the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF). Muscle wasting was identified using dual-energy X-ray absorptiometry (DEXA) in 38 patients (19.4%). Patients with muscle wasting demonstrated higher CAF values than those without (125.1 ± 59.5 pmol/L vs. 103.8 ± 42.9 pmol/L, P = 0.01). Using receiver operating characteristics (ROC), we calculated the optimal CAF value to identify patients with muscle wasting as >87.5 pmol/L, which had a sensitivity of 78.9% and a specificity of 43.7%. The area under the ROC curve was 0.63 (95% confidence interval 0.56-0.70). Using simple regression, we found that serum CAF was associated with handgrip (R = - 0.17, P = 0.03) and quadriceps strength (R = - 0.31, P < 0.0001), peak oxygen consumption (R = - 0.5, P < 0.0001), 6-min walk distance (R = - 0.32, P < 0.0001), and gait speed (R = - 0.2, P = 0.001), as well as with parameters of kidney and liver function, iron metabolism and storage. CONCLUSION CAF shows good sensitivity for the detection of skeletal muscle wasting in patients with heart failure. Its assessment may be useful to identify patients who should undergo additional testing, such as detailed body composition analysis. As no other biomarker is currently available, further investigation is warranted.

Impact of Different Illumination Conditions on Visual Caries Detection with ICDAS

The aim of this study was to test the influence of different degrees of additional illumination on visual caries detection using the International Caries Detection and Assessment System (ICDAS). Two calibrated examiners assessed 139 occlusal surfaces of extracted permanent molars using a standard operation lamp with or without an additional headlamp providing three default brightness intensities. Histology served as the gold standard. Pooled data showed no differences in sensitivities. Specificities were not influenced by additional light. The area under the curve for the Marthaler classification D3 threshold was significantly lower when an additional strong headlamp was used (0.59 compared to 0.69-0.72 when reduced illumination intensities were used). One of the two examiners also had a significantly lower sensitivity for the D1 threshold when an additional headlamp was used. The use of additional white light led to a reduced detection of dentine lesions.

Performance of undergraduate dental students on ICDAS clinical caries detection after different learning strategies

AIM This study aimed to evaluate the effect of a digital learning tool on undergraduate dental students' performance in detecting dental caries using ICDAS. METHODS An experimental digital learning tool (DLT) was created using digital photographs of sound and carious teeth. Thirty-nine students were divided into three groups (n = 13) and each assessed 12 randomly allocated patients before and after learning strategies: G1, ICDAS e-learning program; G2, ICDAS e-learning program plus DLT; G3, no learning strategy. Students (n = 32) reassessed patients 2 weeks after training. RESULTS Comparing before and after the learning strategies, any difference in the values of specificity and area under the ROC curve for all groups was found. Sensitivity was statistically significantly higher for G1 and G2. Comparing the groups, G2 showed a significant increase in sensitivity at the D2 and D3 thresholds. Spearman's correlations with the gold standard before and after the learning strategy were 0.60 and 0.61 for G1, 0.57 and 0.63 for G2, and 0.54 and 0.54 for G3, respectively. The Wilcoxon test showed a statistically significant difference between the values obtained before and after learning strategies for G1 and G2. CONCLUSIONS Use of the DLT after the ICDAS e-learning program tended to increase the sensitivity of ICDAS used by undergraduate dental students. The DLT appeared to improve dental students' ability to use ICDAS.

Detection of significant coronary artery disease by noninvasive anatomical and functional imaging.

BACKGROUND The choice of imaging techniques in patients with suspected coronary artery disease (CAD) varies between countries, regions, and hospitals. This prospective, multicenter, comparative effectiveness study was designed to assess the relative accuracy of commonly used imaging techniques for identifying patients with significant CAD. METHODS AND RESULTS A total of 475 patients with stable chest pain and intermediate likelihood of CAD underwent coronary computed tomographic angiography and stress myocardial perfusion imaging by single photon emission computed tomography or positron emission tomography, and ventricular wall motion imaging by stress echocardiography or cardiac magnetic resonance. If ≥1 test was abnormal, patients underwent invasive coronary angiography. Significant CAD was defined by invasive coronary angiography as >50% stenosis of the left main stem, >70% stenosis in a major coronary vessel, or 30% to 70% stenosis with fractional flow reserve ≤0.8. Significant CAD was present in 29% of patients. In a patient-based analysis, coronary computed tomographic angiography had the highest diagnostic accuracy, the area under the receiver operating characteristics curve being 0.91 (95% confidence interval, 0.88-0.94), sensitivity being 91%, and specificity being 92%. Myocardial perfusion imaging had good diagnostic accuracy (area under the curve, 0.74; confidence interval, 0.69-0.78), sensitivity 74%, and specificity 73%. Wall motion imaging had similar accuracy (area under the curve, 0.70; confidence interval, 0.65-0.75) but lower sensitivity (49%, P<0.001) and higher specificity (92%, P<0.001). The diagnostic accuracy of myocardial perfusion imaging and wall motion imaging were lower than that of coronary computed tomographic angiography (P<0.001). CONCLUSIONS In a multicenter European population of patients with stable chest pain and low prevalence of CAD, coronary computed tomographic angiography is more accurate than noninvasive functional testing for detecting significant CAD defined invasively. CLINICAL TRIAL REGISTRATION URL http://www.clinicaltrials.gov. Unique identifier: NCT00979199.

On-line breath analysis of volatile organic compounds as a method for colorectal cancer detection

Background: Analysis of exhaled volatile organic compounds (VOCs) in breath is an emerging approach for cancer diagnosis, but little is known about its potential use as a biomarker for colorectal cancer (CRC). We investigated whether a combination of VOCs could distinct CRC patients from healthy volunteers. Methods: In a pilot study, we prospectively analyzed breath exhalations of 38 CRC patient and 43 healthy controls all scheduled for colonoscopy, older than 50 in the average-risk category. The samples were ionized and analyzed using a Secondary ElectroSpray Ionization (SESI) coupled with a Time-of-Flight Mass Spectrometer (SESI-MS). After a minimum of 2 hours fasting, volunteers deeply exhaled into the system. Each test requires three soft exhalations and takes less than ten minutes. No breath condensate or collection are required and VOCs masses are detected in real time, also allowing for a spirometric profile to be analyzed along with the VOCs. A new sampling system precludes ambient air from entering the system, so background contamination is reduced by an overall factor of ten. Potential confounding variables from the patient or the environment that could interfere with results were analyzed. Results: 255 VOCs, with masses ranging from 30 to 431 Dalton have been identified in the exhaled breath. Using a classification technique based on the ROC curve for each VOC, a set of 9 biomarkers discriminating the presence of CRC from healthy volunteers was obtained, showing an average recognition rate of 81.94%, a sensitivity of 87.04% and specificity of 76.85%. Conclusions: A combination of cualitative and cuantitative analysis of VOCs in the exhaled breath could be a powerful diagnostic tool for average-risk CRC population. These results should be taken with precaution, as many endogenous or exogenous contaminants could interfere as confounding variables. On-line analysis with SESI-MS is less time-consuming and doesn’t need sample preparation. We are recruiting in a new pilot study including breath cleaning procedures and spirometric analysis incorporated into the postprocessing algorithms, to better control for confounding variables.

On-site tests for the detection of potential induced degradation in modules

This paper presents different test alternatives which can be used on-site in a PV installation to detect potential induced degradation (PID) in modules. The testing procedures proposed are: thermal imaging; electroluminescence imaging; open circuit voltage measurements; operating voltage measurements; IV curve measurements; and dark IV curve measurements. Advantages and disadvantages of each test are reported.

Optimization of Dengue immunoassay by label-free interferometric optical detection method

In this communication we report a direct immunoassay for detecting dengue virus by means of a label-free interferometric optical detection method. We also demonstrate how we can optimize this sensing response by adding a blocking step able to significantly enhance the optical sensing response. The blocking reagent used for this optimization is a dry milk diluted in phosphate buffered saline. The recognition curve of dengue virus over the proposed surface sensor demonstrates the capacity of this method to be applied in Point of Care technology.

Population-based detection of systolic and diastolic dysfunction with amino-terminal pro-B-type natriuretic peptide

Background There is limited information regarding the clinical utility of amino-terminal pro-B-type natriuretic pepticle (NT-proBNP) for the detection of left ventricular (LV) dysfunction in the community. We evaluated predictors of circulating NT-proBNP levels and determined the utility of NT-proBNP to detect systolic and diastolic LV dysfunction in older adults. Methods. A population-based sample of 1229 older adults (mean age 69.4 years, 50.1% women) underwent echocardiographic assessment of cardiac structure and function and measurement of circulating NT-proBNP levels. Results Predictors of NT-proBNP included age, female sex, body mass index, and cardiorenal parameters (diastolic dysfunction [DID] severity; LV mass and left atrial volume; right ventricular overload; decreasing ejection fraction [EF] and creatinine clearance). The performance of NT-proBNP to detect any degree of LV dysfunction, including mild DID, was poor (area under the curve 0.56-0.66). In contrast, the performance of NT-proBNP for the detection of EF 0.90 regardless of age and sex; history of hypertension, diabetes, coronary artery disease; or body mass category. The ability of NT-proBNP to detect EF

Rapid detection of a chromosomally mediated penicillin resistance-associated ponA mutation in Neisseria gonorrhoeae using a real-time PCR assay

The recent emergence of a decreased susceptibility of Neisseria gonorrhoeae strains to penicillin in New Caledonia has lead clinicians to operate a change in the treatment strategy. In addition, this important health issue has emphasized the need for a rapid means of detecting penicillin resistance in N. gonorrhoeae in order to select an effective treatment and limit the spread of resistant strains. In recent years, the use of fluorescence resonance energy transfer on the LightCycler has proven to be a valuable tool for the screening of mutations occurring in the genome of various microorganisms. In this study, we developed a real-time PCR assay coupled with a fluorometric hybridization probes system to detect a penicillin resistance-associated mutation on the N. gonorrhoeae ponA gene. Following an extensive evaluation involving 136 isolates, melting curve analysis correctly evidenced a 5 degrees C T-m shift in all N. gonorrhoeae strains possessing this mutation, as determined by conventional sequencing analysis. Moreover, the mutation profiles obtained with the real-time PCR showed good correlation with the pattern of penicillin susceptibility generated with classical antibiograms. Overall, our molecular assay allowed an accurate and reproducible determination of the susceptibility to penicillin corresponding to a mutation present in all chromosomally mediated resistant strains of N. gonorrhoeae.

Lesion detection performance: comparative analysis of low-dose CT data of the chest on two hybrid imaging systems

Incidental findings on low-dose CT images obtained during hybrid imaging are an increasing phenomenon as CT technology advances. Understanding the diagnostic value of incidental findings along with the technical limitations is important when reporting image results and recommending follow-up, which may result in an additional radiation dose from further diagnostic imaging and an increase in patient anxiety. This study assessed lesions incidentally detected on CT images acquired for attenuation correction on two SPECT/CT systems. Methods: An anthropomorphic chest phantom containing simulated lesions of varying size and density was imaged on an Infinia Hawkeye 4 and a Symbia T6 using the low-dose CT settings applied for attenuation correction acquisitions in myocardial perfusion imaging. Twenty-two interpreters assessed 46 images from each SPECT/CT system (15 normal images and 31 abnormal images; 41 lesions). Data were evaluated using a jackknife alternative free-response receiver-operating-characteristic analysis (JAFROC). Results: JAFROC analysis showed a significant difference (P < 0.0001) in lesion detection, with the figures of merit being 0.599 (95% confidence interval, 0.568, 0.631) and 0.810 (95% confidence interval, 0.781, 0.839) for the Infinia Hawkeye 4 and Symbia T6, respectively. Lesion detection on the Infinia Hawkeye 4 was generally limited to larger, higher-density lesions. The Symbia T6 allowed improved detection rates for midsized lesions and some lower-density lesions. However, interpreters struggled to detect small (5 mm) lesions on both image sets, irrespective of density. Conclusion: Lesion detection is more reliable on low-dose CT images from the Symbia T6 than from the Infinia Hawkeye 4. This phantom-based study gives an indication of potential lesion detection in the clinical context as shown by two commonly used SPECT/CT systems, which may assist the clinician in determining whether further diagnostic imaging is justified.

Wind turbine indirect ice detection and operational analysis

Wind energy is one of the most promising and fast growing sector of energy production. Wind is ecologically friendly and relatively cheap energy resource available for development in practically all corners of the world (where only the wind blows). Today wind power gained broad development in the Scandinavian countries. Three important challenges concerning sustainable development, i.e. energy security, climate change and energy access make a compelling case for large-scale utilization of wind energy. In Finland, according to the climate and energy strategy, accepted in 2008, the total consumption of electricity generated by means of wind farms by 2020, should reach 6 - 7% of total consumption in the country [1]. The main challenges associated with wind energy production are harsh operational conditions that often accompany the turbine operation in the climatic conditions of the north and poor accessibility for maintenance and service. One of the major problems that require a solution is the icing of turbine structures. Icing reduces the performance of wind turbines, which in the conditions of a long cold period, can significantly affect the reliability of power supply. In order to predict and control power performance, the process of ice accretion has to be carefully tracked. There are two ways to detect icing – directly or indirectly. The first way applies to the special ice detection instruments. The second one is using indirect characteristics of turbine performance. One of such indirect methods for ice detection and power loss estimation has been proposed and used in this paper. The results were compared to the results directly gained from the ice sensors. The data used was measured in Muukko wind farm, southeast Finland during a project 'Wind power in cold climate and complex terrain'. The project was carried out in 9/2013 - 8/2015 with the partners Lappeenranta university of technology, Alstom renovables España S.L., TuuliMuukko, and TuuliSaimaa.

Identifying and enhancing risk thresholds in the detection of elder financial abuse: A signal detection analysis of professionals' decision making

Background: Financial abuse of elders is an under acknowledged problem and professionals' judgements contribute to both the prevalence of abuse and the ability to prevent and intervene. In the absence of a definitive "gold standard" for the judgement, it is desirable to try and bring novice professionals' judgemental risk thresholds to the level of competent professionals as quickly and effectively as possible. This study aimed to test if a training intervention was able to bring novices' risk thresholds for financial abuse in line with expert opinion. Methods: A signal detection analysis, within a randomised controlled trial of an educational intervention, was undertaken to examine the effect on the ability of novices to efficiently detect financial abuse. Novices (n = 154) and experts (n = 33) judged "certainty of risk" across 43 scenarios; whether a scenario constituted a case of financial abuse or not was a function of expert opinion. Novices (n = 154) were randomised to receive either an on-line educational intervention to improve financial abuse detection (n = 78) or a control group (no on-line educational intervention, n = 76). Both groups examined 28 scenarios of abuse (11 "signal" scenarios of risk and 17 "noise" scenarios of no risk). After the intervention group had received the on-line training, both groups then examined 15 further scenarios (5 "signal" and 10 "noise" scenarios). Results: Experts were more certain than the novices, pre (Mean 70.61 vs. 58.04) and post intervention (Mean 70.84 vs. 63.04); and more consistent. The intervention group (mean 64.64) were more certain of abuse post-intervention than the control group (mean 61.41, p = 0.02). Signal detection analysis of sensitivity (Á) and bias (C) revealed that this was due to the intervention shifting the novices' tendency towards saying "at risk" (C post intervention -.34) and away from their pre intervention levels of bias (C-.12). Receiver operating curves revealed more efficient judgments in the intervention group. Conclusion: An educational intervention can improve judgements of financial abuse amongst novice professionals.

Detection and Grading of Prostate Cancer in Temporal Enhanced Ultrasound using Convolutional Neural Networks

Prostate cancer is the most common non-dermatological cancer amongst men in the developed world. The current definitive diagnosis is core needle biopsy guided by transrectal ultrasound. However, this method suffers from low sensitivity and specificity in detecting cancer. Recently, a new ultrasound based tissue typing approach has been proposed, known as temporal enhanced ultrasound (TeUS). In this approach, a set of temporal ultrasound frames is collected from a stationary tissue location without any intentional mechanical excitation. The main aim of this thesis is to implement a deep learning-based solution for prostate cancer detection and grading using TeUS data. In the proposed solution, convolutional neural networks are trained to extract high-level features from time domain TeUS data in temporally and spatially adjacent frames in nine in vivo prostatectomy cases. This approach avoids information loss due to feature extraction and also improves cancer detection rate. The output likelihoods of two TeUS arrangements are then combined to form our novel decision support system. This deep learning-based approach results in the area under the receiver operating characteristic curve (AUC) of 0.80 and 0.73 for prostate cancer detection and grading, respectively, in leave-one-patient-out cross-validation. Recently, multi-parametric magnetic resonance imaging (mp-MRI) has been utilized to improve detection rate of aggressive prostate cancer. In this thesis, for the first time, we present the fusion of mp-MRI and TeUS for characterization of prostate cancer to compensates the deficiencies of each image modalities and improve cancer detection rate. The results obtained using TeUS are fused with those attained using consolidated mp-MRI maps from multiple MR modalities and cancer delineations on those by multiple clinicians. The proposed fusion approach yields the AUC of 0.86 in prostate cancer detection. The outcomes of this thesis emphasize the viable potential of TeUS as a tissue typing method. Employing this ultrasound-based intervention, which is non-invasive and inexpensive, can be a valuable and practical addition to enhance the current prostate cancer detection.

An investigation into the utility of the Mini Addenbrooke's Cognitive Examination (M-ACE) for the early detection of dementia and mild cognitive impairment in people aged 75 and over

Background/Aims: The Mini Addenbrooke’s Cognitive Examination (M-ACE) is the abbreviated version of the widely-used Addenbrooke’s Cognitive Examination (ACE-III), a cognitive screening tool that is used internationally in the assessment of mild cognitive impairment (MCI) and dementia. The objectives of this study were to investigate the diagnostic accuracy of the M-ACE with individuals aged 75 and over to distinguish between those who do and do not have a dementia or MCI, and also to establish whether the cut-off scores recommended by Hsieh et al. (2014) [9] in the original validation study for the M-ACE are optimal for this age group. Methods: The M-ACE was administered to 58 participants (24 with a diagnosis of dementia, 17 with a diagnosis of MCI and 17 healthy controls). The extent to which scores distinguished between groups (dementia, MCI or no diagnosis) was explored using receiver operating characteristic curve analysis. Results: The optimal cut-off for detecting dementia was ≤ 21/30 (score ≤ 21/30 indicating dementia with a sensitivity of 0.95, a specificity of 1 and a positive predictive value of 1) compared to the original higher published cut-off of ≤ 25/30 (sensitivity of 0.95, specificity of 0.70 and a positive predictive value of 0.82 in this sample). Conclusions: The M-ACE has excellent diagnostic accuracy for the detection of dementia in a UK clinical sample. It may be necessary to consider lower cut-offs than those given in the original validation study.