Successes and challenges of artificial intelligence in cardiology

In the past decades there has been a substantial evolution in data management and data processing techniques. New data architectures made analysis of big data feasible, healthcare is orienting towards personalized medicine with digital health initiatives, and artificial intelligence (AI) is becoming of increasing importance. Despite being a trendy research topic, only very few applications reach the stage where they are implemented in clinical practice. This review provides an overview of current methodologies and identifies clinical and organizational challenges for AI in healthcare

Characterization of Tryptophanase from Vibrio cholerae O1

AbstractTryptophanase (Trpase) encoded by the tnaA gene catalyzes the conversion of tryptophan to indole, which is an extracellular signaling molecule detected in various bacteria including Vibrio cholerae. Indole has been demonstrated to regulate biofilm formation, drug resistance, plasmid maintenance and spore formation of bacteria. In the present study, the tnaA gene from V. cholerae O1 (VcTrpase) was cloned and expressed in E. coli BL21(DE3) tn5:tnaA (a Trpase-deficient competent). VcTrpase was purified by Ni2+-NTA chromatography. The obtained VcTrpase had a molecular mass of approximately 49 kDa, a specific activity of 3 U/mg protein, and absorption peaks at 330 and 435nm. Using a site-directed mutagenesis technique, replacement of Arg419 by Val resulted in a VcTrpase completely devoid of activity. Thus, this site can be a target for drug design for controlling V. cholerae

Phosphorylation decelerates conformational dynamics in bacterial translation elongation factors

Bacterial protein synthesis is intricately connected to metabolic rate. One of the ways in which bacteria respond to environmental stress is through posttranslational modifications of translation factors. Translation elongation factor Tu (EF-Tu) is methylated and phosphorylated in response to nutrient starvation upon entering stationary phase, and its phosphorylation is a crucial step in the pathway toward sporulation. We analyze how phosphorylation leads to inactivation of Escherichia coli EF-Tu. We provide structural and biophysical evidence that phosphorylation of EF-Tu at T382 acts as an efficient switch that turns off protein synthesis by decoupling nucleotide binding from the EF-Tu conformational cycle. Direct modifications of the EF-Tu switch I region or modifications in other regions stabilizing the β-hairpin state of switch I result in an effective allosteric trap that restricts the normal dynamics of EF-Tu and enables the evasion of the control exerted by nucleotides on G proteins. These results highlight stabilization of a phosphorylation-induced conformational trap as an essential mechanism for phosphoregulation of bacterial translation and metabolism. We propose that this mechanism may lead to the multisite phosphorylation state observed during dormancy and stationary phase

Precision and accuracy of single-molecule FRET measurements - a multi-laboratory benchmark study

Single-molecule Förster resonance energy transfer (smFRET) is increasingly being used to determine distances, structures, and dynamics of biomolecules in vitro and in vivo. However, generalized protocols and FRET standards to ensure the reproducibility and accuracy of measurements of FRET efficiencies are currently lacking. Here we report the results of a comparative blind study in which 20 labs determined the FRET efficiencies (E) of several dye-labeled DNA duplexes. Using a unified, straightforward method, we obtained FRET efficiencies with s.d. between ±0.02 and ±0.05. We suggest experimental and computational procedures for converting FRET efficiencies into accurate distances, and discuss potential uncertainties in the experiment and the modeling. Our quantitative assessment of the reproducibility of intensity-based smFRET measurements and a unified correction procedure represents an important step toward the validation of distance networks, with the ultimate aim of achieving reliable structural models of biomolecular systems by smFRET-based hybrid methods

Scholarly publishing depends on peer reviewers

The peer-review crisis is posing a risk to the scholarly peer-reviewed journal system. Journals have to ask many potential peer reviewers to obtain a minimum acceptable number of peers accepting reviewing a manuscript. Several solutions have been suggested to overcome this shortage. From reimbursing for the job, to eliminating pre-publication reviews, one cannot predict which is more dangerous for the future of scholarly publishing. And, why not acknowledging their contribution to the final version of the article published? PubMed created two categories of contributors: authors [AU] and collaborators [IR]. Why not a third category for the peer-reviewer?Scopu

Clinical Updates in Cardiac Pacing—The Future Is Bright

The history of cardiac pacing has been defined by many innovation milestones starting in the early 1960s [...

Cortical Mechanisms of Central Fatigue and Sense of Effort.

The purpose of this study was to investigate cortical mechanisms upstream to the corticospinal motor neuron that may be associated with central fatigue and sense of effort during and after a fatigue task. We used two different isometric finger abduction protocols to examine the effects of muscle activation and fatigue the right first dorsal interosseous (FDI) of 12 participants. One protocol was intended to assess the effects of muscle activation with minimal fatigue (control) and the other was intended to elicit central fatigue (fatigue). We hypothesized that high frequency repetitive transcranial magnetic stimulation (rTMS) of the supplementary motor area (SMA) would hasten recovery from central fatigue and offset a fatigue-induced increase in sense of effort by facilitating the primary motor cortex (M1). Constant force-sensation contractions were used to assess sense of effort associated with muscle contraction. Paired-pulse TMS was used to assess intracortical inhibition (ICI) and facilitation (ICF) in the active M1 and interhemispheric inhibitory (IHI) was assessed to determine if compensation occurs via the resting M1. These measures were made during and after the muscle contraction protocols. Corticospinal excitability progressively declined with fatigue in the active hemisphere. ICF increased at task failure and ICI was also reduced at task failure with no changes in IHI found. Although fatigue is associated with progressive reductions in corticospinal excitability, compensatory changes in inhibition and facilitation may act within, but not between hemispheres of the M1. rTMS of the SMA following fatigue enhanced recovery of maximal voluntary force and higher levels of ICF were associated with lower sense of effort following stimulation. rTMS of the SMA may have reduced the amount of upstream drive required to maintain motor output, thus contributing to a lower sense of effort and increased rate of recovery of maximal force

A machine learning approach to detection and quantificiation of QRS fragmentation

OBJECTIVE: Fragmented QRS (fQRS) is an accessible biomarker and indication of myocardial scarring that can be detected from the electrocardiogram (ECG). Nowadays, fQRS scoring is done on a visual basis, which is time consuming and leads to subjective results. This study proposes an automated method to detect and quantify fQRS in a continuous way using features extracted from variational mode decomposition (VMD) and phase-rectified signal averaging (PRSA). METHODS: In the proposed framework, QRS complexes in the ECG signals were first segmented using VMD. Then, ten VMD- and PRSA-based features were computed and fed into well-known classifiers such as support vector machine (SVM), K-nearest neighbors (KNN), Naive Bayesian (NB), and TreeBagger (TB) in order to compare their performance. The proposed method was evaluated with 12-lead ECG data of 616 patients from the University Hospitals Leuven. The presence of fQRS in each ECG lead was scored by five raters. Both detection and quantification of fQRS could be achieved in this way. RESULTS: The experimental results indicated that the proposed method achieved AUC values of 0.95, 0.94, 0.90, and 0.89 using SVM, KNN, NB, and TB classifiers, respectively, for detecting QRS fragmentation. Assessment of quantification performance was done by comparing the fQRS score with the total score, obtained by summing the scores from the individual raters. Results showed that the fQRS score clearly correlated with this estimate of fQRS certainty. CONCLUSION: The proposed method obtained good results in both fQRS detection and quantification, and is a novel way of assessing the certainty of QRS fragmentation in the ECG signal.status: publishe