GEDAE-LaB: A Free Software to Calculate the Energy System Contributions during Exercise

Purpose

The aim of the current study is to describe the functionality of free software developed for energy system contributions and energy expenditure calculation during exercise, namely GEDAE-LaB.

Methods

Eleven participants performed the following tests: 1) a maximal cycling incremental test to measure the ventilatory threshold and maximal oxygen uptake (V˙O₂max); 2) a cycling workload constant test at moderate domain (90% ventilatory threshold); 3) a cycling workload constant test at severe domain (110% V˙O₂max). Oxygen uptake and plasma lactate were measured during the tests. The contributions of the aerobic (A_MET), anaerobic lactic (LA_MET), and anaerobic alactic (AL_MET) systems were calculated based on the oxygen uptake during exercise, the oxygen energy equivalents provided by lactate accumulation, and the fast component of excess post-exercise oxygen consumption, respectively. In order to assess the intra-investigator variation, four different investigators performed the analyses independently using GEDAE-LaB. A direct comparison with commercial software was also provided.

Results

All subjects completed 10 min of exercise at moderate domain, while the time to exhaustion at severe domain was 144 ± 65 s. The A_MET, LA_MET, and AL_MET contributions during moderate domain were about 93, 2, and 5%, respectively. The A_MET, LA_MET, and AL_MET contributions during severe domain were about 66, 21, and 13%, respectively. No statistical differences were found between the energy system contributions and energy expenditure obtained by GEDAE-LaB and commercial software for both moderate and severe domains (P > 0.05). The ICC revealed that these estimates were highly reliable among the four investigators for both moderate and severe domains (all ICC ≥ 0.94).

Conclusion

These findings suggest that GEDAE-LaB is a free software easily comprehended by users minimally familiarized with adopted procedures for calculations of energetic profile using oxygen uptake and lactate accumulation during exercise. By providing availability of the software and its source code we hope to facilitate future related research.     

A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm

Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organisms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the bacteria, with great impact on their evolution and behavior. Nevertheless, these adaptations are usually associated with pathogenicity, antibiotic resistance, degradation and metabolism. Identification of such regions is of medical and industrial interest. For this reason, different approaches for genomic islands prediction have been proposed. However, none of them are capable of predicting precisely the complete repertory of GIs in a genome. The difficulties arise due to the changes in performance of different algorithms in the face of the variety of nucleotide distribution in different species. In this paper, we present a novel method to predict GIs that is built upon mean shift clustering algorithm. It does not require any information regarding the number of clusters, and the bandwidth parameter is automatically calculated based on a heuristic approach. The method was implemented in a new user-friendly tool named MSGIP—Mean Shift Genomic Island Predictor. Genomes of bacteria with GIs discussed in other papers were used to evaluate the proposed method. The application of this tool revealed the same GIs predicted by other methods and also different novel unpredicted islands. A detailed investigation of the different features related to typical GI elements inserted in these new regions confirmed its effectiveness. Stand-alone and user-friendly versions for this new methodology are available at http://msgip.integrativebioinformatics.me.     

Glucose Metabolism Disorder Is Associated with Pulmonary Tuberculosis in Individuals with Respiratory Symptoms from Brazil

BackgroundDiabetes mellitus (DM) has been associated with increased risk for pulmonary tuberculosis (PTB) in endemic settings but it is unknown whether PTB risk is also increased by pre-DM. Here, we prospectively examined the association between glucose metabolism disorder (GMD) and PTB in patients with respiratory symptoms at a tuberculosis primary care reference center in Brazil.MethodsOral glucose tolerance test was performed and levels of fasting plasma glucose and glycohemoglobin (HbA1c) were measured in a cohort of 892 individuals presenting with respiratory symptoms of more than two weeks duration. Patients were also tested for PTB with sputum cultures. Prevalence of pre-DM and DM (based on HbA1c) was estimated and tested for association with incident PTB. Other TB risk factors including smoking history were analyzed.ResultsThe majority of the study population (63.1%) exhibited GMD based on HbA1c ≥5.7%. Patients with GMD had higher prevalence of PTB compared to normoglycemic patients. Individuals with DM exhibited increased frequency of TB-related symptoms and detection of acid-fast bacilli in sputum smears. Among patients with previous DM diagnosis, sustained hyperglycemia (HbA1c ≥7.0%) was associated with increased TB prevalence. Smoking history alone was not significantly associated with TB in our study population but the combination of smoking and HbA1c ≥7.0% was associated with 6 times higher odds for PTB.ConclusionsSustained hyperglycemia and pre-DM are independently associated with active PTB. This evidence raises the question whether improving glycemic control in diabetic TB patients would reduce the risk of TB transmission and simultaneously reduce the clinical burden of disease. A better understanding of mechanisms underlying these associations, especially those suggesting that pre-DM may be a factor driving susceptibility to TB is warranted.     

The Buzz of Drinking on the Wing in Echolocating Bats

Bats broadcast rapid sequences of echolocation calls, named ‘drinking buzzes’, when they approach water to drink on the wing. So far this phenomenon has received little attention. We recorded echolocation sequences of drinking bats for 12 species, for 11 of which we also recorded feeding buzzes. Based on the different sensorial tasks faced by feeding and drinking bats, we hypothesize that the drinking buzz structure will differ from that of feeding buzzes since unlike the latter drinking buzzes are not designed to detect and track mobile prey. We demonstrated that drinking buzzes are structurally different from feeding buzzes. We show that the buzz‐II phase common in feeding buzzes is absent in drinking buzzes; that is, call frequency is not lowered to broaden sonar beam since the task of drinking does not imply tracking fast‐moving targets. This finding indirectly confirms the role of buzz II in feeding buzzes. Pulse rate in drinking buzzes is also lower than in feeding buzzes, as predicted since the high pulse rate typical of feeding buzzes is important to update rapidly the relative location of moving targets. The most likely function of drinking buzzes is to guide a safe drinking manoeuvre, similar to ‘landing buzzes’ broadcast when bats land on the ground.     

Virtual screening,docking, and dynamics of potential new inhibitors of dihydrofolate reductase from Yersinia pestis

In the present work, we propose to design drugs that target the enzyme dihydrofolate redutase (DHFR) as a means of a novel drug therapy against plague. Potential inhibitors of DHFR from Yersinia pestis (YpDHFR) were selected by virtual screening and subjected to docking, molecular dynamics (MD) simulations, and Poisson–Boltzmann surface area method, in order to evaluate their interactions in the active sites of YpDHFR and human DHFR (HssDHFR). The results suggested selectivity for three compounds that were further used to propose the structures of six new potential selective inhibitors for YpDHFR.     

Structure‐based classification of FAD binding sites: A comparative study of structural alignment tools

A total of six different structural alignment tools (TM‐Align, TriangleMatch, CLICK, ProBis, SiteEngine and GA‐SI) were assessed for their ability to perform two particular tasks: (i) discriminating FAD (flavin adenine dinucleotide) from non‐FAD binding sites, and (ii) performing an all‐to‐all comparison on a set of 883 FAD binding sites for the purpose of classifying them. For the first task, the consistency of each alignment method was evaluated, showing that every method is able to distinguish FAD and non‐FAD binding sites with a high Matthews correlation coefficient. Additionally, GA‐SI was found to provide alignments different from those of the other approaches. The results obtained for the second task revealed more significant differences among alignment methods, as reflected in the poor correlation of their results and highlighted clearly by the independent evaluation of the structural superimpositions generated by each method. The classification itself was performed using the combined results of all methods, using the best result found for each comparison of binding sites. A number of different clustering methods (Single‐linkage, UPGMA, Complete‐linkage, SPICKER and k‐Means clustering) were also used. The groups of similar binding sites (proteins) or clusters generated by the best performing method were further analyzed in terms of local sequence identity, local structural similarity and conservation of analogous contacts with the FAD ligands. Each of the clusters was characterized by a unique set of structural features or patterns, demonstrating that the groups generated truly reflect the structural diversity of FAD binding sites. Proteins 2016; 84:1728–1747. © 2016 Wiley Periodicals, Inc.     

Sequential and compartmentalized action of Rabs,SNAREs, and MAL in the apical delivery of fusiform vesicles in urothelial umbrella cells

Uroplakins (UPs) are major differentiation products of urothelial umbrella cells and play important roles in forming the permeability barrier and in the expansion/stabilization of the apical membrane. Further, UPIa serves as a uropathogenic Escherichia coli receptor. Although it is understood that UPs are delivered to the apical membrane via fusiform vesicles (FVs), the mechanisms that regulate this exocytic pathway remain poorly understood. Immunomicroscopy of normal and mutant mouse urothelia show that the UP-delivering FVs contained Rab8/11 and Rab27b/Slac2-a, which mediate apical transport along actin filaments. Subsequently a Rab27b/Slp2-a complex mediated FV–membrane anchorage before SNARE-mediated and MAL-facilitated apical fusion. We also show that keratin 20 (K20), which forms a chicken-wire network ∼200 nm below the apical membrane and has hole sizes allowing FV passage, defines a subapical compartment containing FVs primed and strategically located for fusion. Finally, we show that Rab8/11 and Rab27b function in the same pathway, Rab27b knockout leads to uroplakin and Slp2-a destabilization, and Rab27b works upstream from MAL. These data support a unifying model in which UP cargoes are targeted for apical insertion via sequential interactions with Rabs and their effectors, SNAREs and MAL, and in which K20 plays a key role in regulating vesicular trafficking.