GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry.

Profiling bacterial populations in mixed communities is a common task in microbiology. Sequencing of 16S small subunit ribosomal-RNA (16S rRNA) gene amplicons is a widely accepted and functional approach but relies on amplification primers and cannot quantify isotope incorporation. Tandem mass spectrometry proteotyping is an effective alternative for taxonomically profiling microorganisms. We suggest that targeted proteotyping approaches can complement traditional population analyses. Therefore, we describe an approach to assess bacterial community compositions at the family level using the taxonomic marker protein GroEL, which is ubiquitously found in bacteria, except a few obligate intracellular species. We refer to our method as GroEL-proteotyping. GroEL-proteotyping is based on high-resolution tandem mass spectrometry of GroEL peptides and identification of GroEL-derived taxa via a Galaxy workflow and a subsequent Python-based analysis script. Its advantage is that it can be performed with a curated and extendable sample-independent database and that GroEL can be pre-separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) to reduce sample complexity, improving GroEL identification while simultaneously decreasing the instrument time. GroEL-proteotyping was validated by employing it on a comprehensive raw dataset obtained through a metaproteome approach from synthetic microbial communities as well as real human gut samples. Our data show that GroEL-proteotyping enables fast and straightforward profiling of highly abundant taxa in bacterial communities at reasonable taxonomic resolution.

Yoga for Preventive Health: A Holistic Approach.

Yoga has been prevalent for over 5000 years; it originated in India and has become an essential lifestyle ingredient for achieving optimal health. The goal of this article in lifestyle modification is to increase awareness about the benefits of yoga and how its practice can reduce the overall risk of chronic diseases. Yoga has been proven to be therapeutic for enhancing immunity and support management of chronic diseases such as cardiovascular, respiratory, endocrine disorders, obesity, cancer, and metabolic syndrome. Yoga techniques called asanas, such as pranayama for breathing regulation and dhyana for meditation, boost innate immune response, interrupt inflammation, and thereby prevent the manifestation of chronic diseases. Yoga also provides symptomatic relief for chronic arthritis by increasing joint flexibility and microcirculation. Yoga and meditation regulate neurotransmitters, neuropeptides, hormones, and cytokines that mediate interactions between the central nervous system and the immune system. These techniques reduce the psychological and physiological effects of chronic stress. Serotonin, oxytocin, and melatonin released directly due to practicing yoga have been shown to better manage anxiety and fear, especially during the pandemic. We believe the current trends of chronic disease management will become more effective with the implementation of lifestyle changes using yoga.

Right middle lobe syndrome after upper lobectomy: Role of the bronchial angle.

BACKGROUND: Right middle lobe syndrome is part of a spectrum of relatively rare but serious conditions that may occur following right upper lobectomy. We aimed to assess whether the preoperative middle lobe bronchial angle on CT predicted patients at risk of developing middle lobe syndrome. METHOD: All patients who had a complete upper lobectomy over 4 years were retrospectively reviewed for clinical and imaging findings of middle lobe syndrome. Patients with previous lung surgery, preoperative chemo- or radiation therapy, or more extensive surgical resection were excluded. Patient demographics and symptoms, the surgical, pathologic and bronchoscopy reports, and pre- and post-operative chest imaging, to include 3D CT reconstructions and measurements of the middle lobe angles in a subset of patients, were retrospectively reviewed. RESULT: One hundred and twenty-eight patients met inclusion criteria. Ten (8%) had middle lobe syndrome based on symptoms and imaging features. Eight had severe middle lobe consolidation. Two had postoperative onset of wheezing, with middle lobe bronchial abnormality on CT. The pre- and postoperative middle lobe bronchial angles of 14 patients without middle lobe syndrome were compared to 10 patients with middle lobe syndrome. The middle lobe bronchus was completely obliterated postoperatively and could not be determined in 1 patient. There was no significant difference between the pre- and postoperative angles in patients with or without middle lobe syndrome. CONCLUSION: Middle lobe syndrome occurred in 8% of patients with right upper lobectomy. The preoperative middle lobe bronchial angle did not predict patients at risk for developing middle lobe syndrome.

cMRI-BED: A novel informatics framework for cardiac MRI biomarker extraction and discovery applied to pediatric cardiomyopathy classification.

BACKGROUND: Pediatric cardiomyopathies are a rare, yet heterogeneous group of pathologies of the myocardium that are routinely examined clinically using Cardiovascular Magnetic Resonance Imaging (cMRI). This gold standard powerful non-invasive tool yields high resolution temporal images that characterize myocardial tissue. The complexities associated with the annotation of images and extraction of markers, necessitate the development of efficient workflows to acquire, manage and transform this data into actionable knowledge for patient care to reduce mortality and morbidity. METHODS: We develop and test a novel informatics framework called cMRI-BED for biomarker extraction and discovery from such complex pediatric cMRI data that includes the use of a suite of tools for image processing, marker extraction and predictive modeling. We applied our workflow to obtain and analyze a dataset of 83 de-identified cases and controls containing cMRI-derived biomarkers for classifying positive versus negative findings of cardiomyopathy in children. Bayesian rule learning (BRL) methods were applied to derive understandable models in the form of propositional rules with posterior probabilities pertaining to their validity. Popular machine learning methods in the WEKA data mining toolkit were applied using default parameters to assess cross-validation performance of this dataset using accuracy and percentage area under ROC curve (AUC) measures. RESULTS: The best 10-fold cross validation predictive performance obtained on this cMRI-derived biomarker dataset was 80.72% accuracy and 79.6% AUC by a BRL decision tree model, which is promising from this type of rare data. Moreover, we were able to verify that mycocardial delayed enhancement (MDE) status, which is known to be an important qualitative factor in the classification of cardiomyopathies, is picked up by our rule models as an important variable for prediction. CONCLUSIONS: Preliminary results show the feasibility of our framework for processing such data while also yielding actionable predictive classification rules that can augment knowledge conveyed in cardiac radiology outcome reports. Interactions between MDE status and other cMRI parameters that are depicted in our rules warrant further investigation and validation. Predictive rules learned from cMRI data to classify positive and negative findings of cardiomyopathy can enhance scientific understanding of the underlying interactions among imaging-derived parameters.

Single coronary artery anomaly: classification and evaluation using multidetector computed tomography and magnetic resonance angiography.

The aim of this study was to use multidetector computed tomography (MDCT) and magnetic resonance (MRA) angiography to illustrate the classification and clinical characteristics of single coronary artery anomaly (SCAA). Retrospective evaluation of 22 adult and pediatric patients with SCAA by way of a medical archiving system was performed between June 2001 and August 2012. Imaging modalities used for coronary artery evaluation included MRA and MDCT angiography. Of the 22 patients, the majority (n = 8; 36%) showed an interarterial course, the subtype having the worst prognosis. The retroaortic course (n = 3; 14%) and course anterior to the pulmonary trunk (n = 3; 14%) were the next most frequent patterns. Additional types (n = 8; 36%) included the following: L-I, R-III, septal, and combined. Four patients (18%) showed atherosclerotic involvement. SCAA anomaly was diagnosed as an incidental finding in the majority of patients evaluated initially for cardiovascular diseases (n = 19; 86%). Two patients (9%) required surgical interventions solely for their anomaly. Nine patients (41%) were found to have coexisting congenital heart disease. Although conventional catheter angiography is responsible for the current classification of SCAA, advanced imaging modalities are useful in the evaluation of morphological and clinical characteristics of single coronary arteries.

Right- and left-ventricular strain evaluation in repaired pediatric Tetralogy of Fallot patients using magnetic resonance tagging.

Residual pulmonary insufficiency in post-repair Tetralogy of Fallot (rToF) patients often mediates biventricular dysfunction which is associated with long-term adverse clinical outcomes. The objective of this study was to demonstrate the presence of impaired left ventricle (LV) circumferential strain (CS) in pediatric rToF patients as compared to controls using cardiac magnetic resonance imaging (CMRI). Additionally, bivariate analysis between right ventricle (RV) and LV functional measures in rToF patients was performed to further characterize the interventricular interactions thought to mediate LV dysfunction secondary to RV volume overload. The medical records of 12 rToF patients (mean age 13.3 years) and 9 controls (mean age 10.9 years) were analyzed. LV global CS was significantly decreased in rToF patients versus controls (p = 0.04). This impairment was differentially distributed within the LV, with only the LV anterior and anterior lateral walls significantly decreased versus controls (p = 0.04, p = 0.03). Bivariate analysis revealed a significant correlation between RV mean CS and LV EF (r = 0.71, p = 0.01), RV infundibulum CS and LV EF (r = 0.70, p = 0.01), RV infundibulum CS and LV anterolateral wall CS (r = 0.59, p = 0.04), and RV infundibulum CS and pulmonary regurgitation fraction (r = -0.63, p = 0.03). These findings support existing research implicating interventricular interactions in the development of LV dysfunction. Furthermore, the segment specific CS impairment in the LV suggests a possible spatial component to these interactions. The success of this study in identifying regional myocardial strain impairment indicates CMRI based techniques may be useful in localizing otherwise undetectable myocardial dysfunction.

Noncompaction cardiomyopathy in children with congenital heart disease: evaluation using cardiovascular magnetic resonance imaging.

Noncompaction of the left ventricle, a genetic cardiomyopathy with a reported incidence of 0.05% to 0.24%, can lead to sudden cardiac death, particularly among children, if left undetected. Because the diagnosis of isolated noncompaction cardiomyopathy (NCM) can be overlooked, its association with other congenital heart diseases (CHDs) makes the diagnosis of NCM even more difficult. This study aimed to assess the impact of NCM on the cardiovascular physiology of children with coexisting CHDs evaluated by cardiovascular magnetic resonance imaging. A case-control study was performed with 12 children (6 patients with combined NCM and CHD and 6 control subjects with isolated CHD). The mean left ventricular end-diastolic and end-systolic volume indices were significantly higher in the CHD patients presenting with NCM than in the CHD patients with no NCM (P = 0.028). However, no differences were observed for right ventricular end-diastolic and end-systolic volume indices, biventricular ejection fractions, stroke volumes and indices, left ventricular wall thickness, left ventricular fractional shortening, cardiac output, or cardiac index. This study suggests that NCM in children with CHDs increases left ventricular volumes, and larger studies are required to demonstrate other changes (e.g., ejection fraction, stroke volume) that were close to being significant.

Left ventricular non-compaction on MRI in a patient with 22q11.2 distal deletion.

We report on a 22-year-old male carrying a presumptive clinical diagnosis of Dubowitz-like phenotype who has been followed-up by cardiology for bicuspid aortic valve with ascending aorta and aortic root dilatation. Cardiac magnetic resonance imaging (CMRI) confirmed these findings, along with an incidental finding of left ventricular non-compaction (LVNC). Genetic workup revealed the diagnosis of 22q11.2 distal deletion encompassing the BCR gene. This is the first time LVNC has been reported in a patient with 22q11.2 distal deletion.

Dynamic multidimensional imaging of the human left atrial appendage.

AIMS: The human left atrial appendage (LAA) is a region of increasing interest as a target for intervention. We sought to improve insight into the anatomy of this region using computed tomography (CT). METHODS AND RESULTS: Multidimensional cardiac reconstruction (whole heart and isolated left atrium) from CT images was performed in each of three groups: (i) patients without atrial fibrillation (AF, n =10); (ii) patients with intermittent (paroxysmal) AF (n = 25); (iii) patients with continuous (persistent) AF (n = 10). Indices included LAA morphology, anatomical relationships, dimensions, angulation, and motility. There was substantial interindividual variation in each index. LAA morphologic differences were associated with variations in anatomical relationships. LAA dimensions in AF patients exceeded those in patients without AF, but angulation and motility were similar. The LAA could be subdivided into proximal and distal portions, each of which had distinct morphology and anatomical relationships. Dimensions in men tended to exceed those in women. CONCLUSION: Regardless of AF history, there is broad variation in LAA morphology, anatomical relationships, dimensions, angulation, and motility. These observations may have importance for the development of technologies for therapy delivery in this region.

A novel two-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern recognition for rapid automated ejection fraction.

OBJECTIVES: We sought to test the hypothesis that a novel 2-dimensional echocardiographic image analysis system using artificial intelligence-learned pattern recognition can rapidly and reproducibly calculate ejection fraction (EF). BACKGROUND: Echocardiographic EF by manual tracing is time consuming, and visual assessment is inherently subjective. METHODS: We studied 218 patients (72 female), including 165 with abnormal left ventricular (LV) function. Auto EF incorporated a database trained on >10,000 human EF tracings to automatically locate and track the LV endocardium from routine grayscale digital cineloops and calculate EF in 15 s. Auto EF results were independently compared with manually traced biplane Simpson's rule, visual EF, and magnetic resonance imaging (MRI) in a subset. RESULTS: Auto EF was possible in 200 (92%) of consecutive patients, of which 77% were completely automated and 23% required manual editing. Auto EF correlated well with manual EF (r = 0.98; 6% limits of agreement) and required less time per patient (48 +/- 26 s vs. 102 +/- 21 s; p < 0.01). Auto EF correlated well with visual EF by expert readers (r = 0.96; p < 0.001), but interobserver variability was greater (3.4 +/- 2.9% vs. 9.8 +/- 5.7%, respectively; p < 0.001). Visual EF was less accurate by novice readers (r = 0.82; 19% limits of agreement) and improved with trainee-operated Auto EF (r = 0.96; 7% limits of agreement). Auto EF also correlated with MRI EF (n = 21) (r = 0.95; 12% limits of agreement), but underestimated absolute volumes (r = 0.95; bias of -36 +/- 27 ml overall). CONCLUSIONS: Auto EF can automatically calculate EF similarly to results by manual biplane Simpson's rule and MRI, with less variability than visual EF, and has clinical potential.