Revealing the hierarchical structure of microbial communities.

Measuring the dynamics of microbial communities results in high-dimensional measurements of taxa abundances over time and space, which is difficult to analyze due to complex changes in taxonomic compositions. This paper presents a new method to investigate and visualize the intrinsic hierarchical community structure implied by the measurements. The basic idea is to identify significant intersection sets, which can be seen as sub-communities making up the measured communities. Using the subset relationship, the intersection sets together with the measurements form a hierarchical structure visualized as a Hasse diagram. Chemical organization theory (COT) is used to relate the hierarchy of the sets of taxa to potential taxa interactions and to their potential dynamical persistence. The approach is demonstrated on a data set of community data obtained from bacterial 16S rRNA gene sequencing for samples collected monthly from four groundwater wells over a nearly 3-year period (n = 114) along a hillslope area. The significance of the hierarchies derived from the data is evaluated by showing that they significantly deviate from a random model. Furthermore, it is demonstrated how the hierarchy is related to temporal and spatial factors; and how the idea of a core microbiome can be extended to a set of interrelated core microbiomes. Together the results suggest that the approach can support developing models of taxa interactions in the future.

Computing all persistent subspaces of a reaction-diffusion system.

An algorithm is presented for computing a reaction-diffusion partial differential equation (PDE) system for all possible subspaces that can hold a persistent solution of the equation. For this, all possible sub-networks of the underlying reaction network that are distributed organizations (DOs) are identified. Recently it has been shown that a persistent subspace must be a DO. The algorithm computes the hierarchy of DOs starting from the largest by a linear programming approach using integer cuts. The underlying constraints use elementary reaction closures as minimal building blocks to guarantee local closedness and global self-maintenance, required for a DO. Additionally, the algorithm delivers for each subspace an affiliated set of organizational reactions and minimal compartmentalization that is necessary for this subspace to persist. It is proved that all sets of organizational reactions of a reaction network, as already DOs, form a lattice. This lattice contains all potentially persistent sets of reactions of all constrained solutions of reaction-diffusion PDEs. This provides a hierarchical structure of all persistent subspaces with regard to the species and also to the reactions of the reaction-diffusion PDE system. Here, the algorithm is described and the corresponding Python source code is provided. Furthermore, an analysis of its run time is performed and all models from the BioModels database as well as further examples are examined. Apart from the practical implications of the algorithm the results also give insights into the complexity of solving reaction-diffusion PDEs.

HOT CRT-The Effective Combination of Conventional Cardiac Resynchronization and His Bundle Pacing.

Background and Objectives: Cardiac Resynchronization Therapy (CRT) has, besides its benefits, various limitations. For instance, atrial fibrillation (AF) has a huge impact on the therapy efficacy. It usually reduces the overall BiV pacing percentage and leads, inevitably, to lack of fusion beats. In many patients with heart failure that could benefit from resynchronization, the QRS morphology is often IVCD and atypical, or non-LBBB, which further diminishes the CRT response. In those cases, we established His pacing combined with LV pacing as a feasible option to reduce the impact of AF on the CRT response and regain partially physiological ventricular activation to improve the electromechanical sequence. Materials and Methods: We implanted two patients with AF, HF, EF < 35%, NYHA II-III and QRS > 150 ms with CRT-D systems modified to HOT-CRT and observed their clinical, ECG and echocardiographic improvements over a follow-up period of three months. Results: In both patients we observed improvements of the initial parameters. We were able to shorten the QRS duration to approx. 120 ms, improve NYHA functional class, increase the EF by approximately 12% and distinctly reduce mitral regurgitation. Conclusion: Since the conventional CRT reaches its limits within this specific patient group, we need to consider alternative pacing sites and the effective combination of them. Our results and respectively other studies that are also mentioned in the current guidelines, support the feasibility of HOT-CRT in the above mentioned patient group.

The P wave dispersion-one pixel, one millisecond.

The electrophysiological activity of the heart is recorded and presented in form of electrocardiogram (ECG). In 1998 the concept of P wave dispersion as the risk factor for atrial fibrillation (AF) recurrence was introduced. It was calculated as the difference between the longest and the shortest P wave. The aim of our study is to prove that the P wave dispersion is an artifact of low accuracy in P wave measurement. The study included 186 patients (78M 108F) aged 59.7 ± 12.9 years, undergoing various electrophysiological procedures. The P wave was measured twice: first, at the paper speed of 50 mm/s, enhancement 8× (standard - imprecise) and the second time at 200 mm/s, 64-256× (precise). The imprecise measurement method resulted in different duration of all P wave parameters in comparison with precise measurement. The difference between Δ P max and Δ P min indicated a higher value for the latter parameter. It was indicated that the imprecise P wave dispersion value correlated most significantly with the maximal P wave duration, which was measured in a similar way. In contrast with the imprecise measurement method, the minimal and maximal durations of the P waves, being measured accurately, were almost identical. Using precise methodology, the P wave dispersion reaches negligible values and tends to zero. The measurements of the P wave have to be precise to assure the highest scientific and medical sincerity. The highest clinical value is related to the P wave duration.

P wave duration in paroxysmal and persistent atrial fibrillation.

BACKGROUND: Functional and structural changes in the atrial muscle constitute a substrate for atrial fibrillation (AF). The pathological changes in the left atrium decrease the conduction velocity and result in prolongation of the P wave duration. OBJECTIVES: To assess the duration of the P wave in patients with AF in different clinical presentations of arrhythmia. MATERIAL AND METHODS: The study group consisted of 119 patients diagnosed with AF: 57 women and 62 men, aged 65.3 ±9.4 years. There were 65 patients with paroxysmal AF and 54 with persistent AF. In this group, electrical cardioversion was performed. The P wave duration was measured using an electrophysiological system in all leads at a paper speed of 200 mm/s. RESULTS: The patients did not differ in terms of age, gender or comorbidities. The patients with persistent AF had longer P wave duration (159.9 ±22.3 ms compared to 144.6 ±17.2 ms; p < 0.001) and higher glucose concentration (119.4 ±33.4 mg/dL compared to 108.0 ±24.6 mg/dL; p = 0.015). These results were not influenced by the anti-arrhythmic treatment. CONCLUSIONS: Persistent AF shows a longer P wave duration than the paroxysmal AF, independent of age, gender and anti-arrhythmic medication. The prolongation of the P wave related to persistent arrhythmia should force physicians to restore the sinus rhythm earlier in order to more successfully maintain it in the long term.

Structure and Hierarchy of SARS-CoV-2 Infection Dynamics Models Revealed by Reaction Network Analysis.

This work provides a mathematical technique for analyzing and comparing infection dynamics models with respect to their potential long-term behavior, resulting in a hierarchy integrating all models. We apply our technique to coupled ordinary and partial differential equation models of SARS-CoV-2 infection dynamics operating on different scales, that is, within a single organism and between several hosts. The structure of a model is assessed by the theory of chemical organizations, not requiring quantitative kinetic information. We present the Hasse diagrams of organizations for the twelve virus models analyzed within this study. For comparing models, each organization is characterized by the types of species it contains. For this, each species is mapped to one out of four types, representing uninfected, infected, immune system, and bacterial species, respectively. Subsequently, we can integrate these results with those of our former work on Influenza-A virus resulting in a single joint hierarchy of 24 models. It appears that the SARS-CoV-2 models are simpler with respect to their long term behavior and thus display a simpler hierarchy with little dependencies compared to the Influenza-A models. Our results can support further development towards more complex SARS-CoV-2 models targeting the higher levels of the hierarchy.

Structure and Hierarchy of Influenza Virus Models Revealed by Reaction Network Analysis.

Influenza A virus is recognized today as one of the most challenging viruses that threatens both human and animal health worldwide. Understanding the control mechanisms of influenza infection and dynamics is crucial and could result in effective future treatment strategies. Many kinetic models based on differential equations have been developed in recent decades to capture viral dynamics within a host. These models differ in their complexity in terms of number of species elements and number of reactions. Here, we present a new approach to understanding the overall structure of twelve influenza A virus infection models and their relationship to each other. To this end, we apply chemical organization theory to obtain a hierarchical decomposition of the models into chemical organizations. The decomposition is based on the model structure (reaction rules) but is independent of kinetic details such as rate constants. We found different types of model structures ranging from two to eight organizations. Furthermore, the model's organizations imply a partial order among models entailing a hierarchy of model, revealing a high model diversity with respect to their long-term behavior. Our methods and results can be helpful in model development and model integration, also beyond the influenza area.

Copeptin for risk stratification in non-traumatic headache in the emergency setting: a prospective multicenter observational cohort study.

BACKGROUND: In the emergency setting, non-traumatic headache is a benign symptom in 80% of cases, but serious underlying conditions need to be ruled out. Copeptin improves risk stratification in several acute diseases. Herein, we investigated the value of copeptin to discriminate between serious secondary headache and benign headache forms in the emergency setting. METHODS: Patients presenting with acute non-traumatic headache were prospectively enrolled into an observational cohort study. Copeptin was measured upon presentation to the emergency department. Primary endpoint was serious secondary headache defined by a neurologic cause requiring immediate treatment of the underlying disease. Secondary endpoint was the combination of mortality and hospitalization within 3 months. Two board-certified neurologist blinded to copeptin levels verified the endpoints after a structured 3-month-telephone interview. RESULTS: Of the 391 patients included, 75 (19%) had a serious secondary headache. Copeptin was associated with serious secondary headache (OR 2.03, 95%CI 1.52-2.70, p < 0.0001). Area under the curve (AUC) for copeptin to identify the primary endpoint was 0.70 (0.63-0.76). After adjusting for age > 50, focal-neurological abnormalities, and thunderclap onset of symptoms, copeptin remained an independent predictive factor for serious secondary headache (OR 1.74, 95%CI 1.26-2.39, p = 0.001). Moreover, copeptin improved the AUC of the multivariate logistic clinical model (p-LR-test < 0.001). Even though copeptin values were higher in patients reaching the secondary endpoint, this association was not significant in multivariate logistic regression. CONCLUSIONS: Copeptin was independently associated with serious secondary headache as compared to benign headaches forms. Copeptin may be a promising novel blood biomarker that should be further validated to rule out serious secondary headache in the emergency department. TRIAL REGISTRATION: Study Registration on 08/02/2010 as NCT01174901 at clinicaltrials.gov.

Effects of small particle numbers on long-term behaviour in discrete biochemical systems.

MOTIVATION: The functioning of many biological processes depends on the appearance of only a small number of a single molecular species. Additionally, the observation of molecular crowding leads to the insight that even a high number of copies of species do not guarantee their interaction. How single particles contribute to stabilizing biological systems is not well understood yet. Hence, we aim at determining the influence of single molecules on the long-term behaviour of biological systems, i.e. whether they can reach a steady state. RESULTS: We provide theoretical considerations and a tool to analyse Systems Biology Markup Language models for the possibility to stabilize because of the described effects. The theory is an extension of chemical organization theory, which we called discrete chemical organization theory. Furthermore we scanned the BioModels Database for the occurrence of discrete chemical organizations. To exemplify our method, we describe an application to the Template model of the mitotic spindle assembly checkpoint mechanism. AVAILABILITY AND IMPLEMENTATION: http://www.biosys.uni-jena.de/Services.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genetic alterations in the tyrosine kinase transcriptome of human cancer cell lines.

Protein tyrosine kinases (PTKs) play a critical role in the manifestation of cancer cell properties, and respective signaling mechanisms have been studied extensively on immortalized tumor cells. To characterize and analyze commonly used cancer cell lines with regard to variations in the primary structure of all expressed PTKs, we conducted a cDNA-based sequence analysis of the entire tyrosine kinase transcriptome of 254 established tumor cell lines. The profiles of cell line intrinsic PTK transcript alterations and the evaluation of 155 identified polymorphisms and 234 somatic mutations are made available in a database designated "Tykiva" (tyrosine kinome variant). Tissue distribution analysis and/or the localization within defined protein domains indicate functional relevance of several genetic alterations. The cysteine replacement of the highly conserved Y367 residue in fibroblast growth factor receptor 4 or the Q26X nonsense mutation in the tumor-suppressor kinase CSK are examples, and may contribute to cell line-specific signaling characteristics and tumor progression. Moreover, known variants, such as epidermal growth factor receptor G719S, that were shown to mediate anticancer drug sensitivity could be detected in other than the previously reported tumor types. Our data therefore provide extensive system information for the design and interpretation of cell line-based cancer research, and may stimulate further investigations into broader clinical applications of current cancer therapeutics.

PTP-PEST phosphatase variations in human cancer.

Signal transduction via tyrosine phosphorylation, normally fine-tuned by the concerted action of both protein tyrosine kinases and protein tyrosine phosphatases (PTPs), is a key mechanism in tumorigenesis. PTP-PEST, a ubiquitously expressed cytoplasmic tyrosine phosphatase, is thought to play an important role in cell adhesion and motility, and may be involved in metastasis. A search for sequence variations within the gene PTPN12 (alias PTP-PEST) was performed in breast cancer cell lines, leading to the identification of three amino acid substitutions at positions 322, 573, and 709. These alterations were also found in squamous cell carcinoma cell lines and could be verified in primary human breast and kidney tumor samples. Analysis of peripheral blood samples confirmed the germline origin of these alterations. Furthermore, functional characterization of the Ile322 and Ala573 PTP-PEST mutants revealed an enhancement of in vitro phosphatase activity, whereas the Lys709 variant showed reduced catalytic activity. These data demonstrate the existence of PTP-PEST variants that might be meaningful for human cancer and underscore the need for further characterizing PTP-PEST and its signaling pathways in context of this disease.