Active cycle of breathing technique for cystic fibrosis.

Cochrane Database Syst Rev. 2016 Jul 5;7:CD007862

Authors: Mckoy NA, Wilson LM, Saldanha IJ, Odelola OA, Robinson KA

Abstract
BACKGROUND: People with cystic fibrosis experience chronic airway infections as a result of mucus build up within the lungs. Repeated infections often cause lung damage and disease. Airway clearance therapies aim to improve mucus clearance, increase sputum production, and improve airway function. The active cycle of breathing technique (also known as ACBT) is an airway clearance method that uses a cycle of techniques to loosen airway secretions including breathing control, thoracic expansion exercises, and the forced expiration technique. This is an update of a previously published review.
OBJECTIVES: To compare the clinical effectiveness of the active cycle of breathing technique with other airway clearance therapies in cystic fibrosis.
SEARCH METHODS: We searched the Cochrane Cystic Fibrosis Trials Register, compiled from electronic database searches and handsearching of journals and conference abstract books. We also searched the reference lists of relevant articles and reviews.Date of last search: 25 April 2016.
SELECTION CRITERIA: Randomised or quasi-randomised controlled clinical studies, including cross-over studies, comparing the active cycle of breathing technique with other airway clearance therapies in cystic fibrosis.
DATA COLLECTION AND ANALYSIS: Two review authors independently screened each article, abstracted data and assessed the risk of bias of each study.
MAIN RESULTS: Our search identified 62 studies, of which 19 (440 participants) met the inclusion criteria. Five randomised controlled studies (192 participants) were included in the meta-analysis; three were of cross-over design. The 14 remaining studies were cross-over studies with inadequate reports for complete assessment. The study size ranged from seven to 65 participants. The age of the participants ranged from six to 63 years (mean age 22.33 years). In 13 studies, follow up lasted a single day. However, there were two long-term randomised controlled studies with follow up of one to three years. Most of the studies did not report on key quality items, and therefore, have an unclear risk of bias in terms of random sequence generation, allocation concealment, and outcome assessor blinding. Due to the nature of the intervention, none of the studies blinded participants or the personnel applying the interventions. However, most of the studies reported on all planned outcomes, had adequate follow up, assessed compliance, and used an intention-to-treat analysis.Included studies compared the active cycle of breathing technique with autogenic drainage, airway oscillating devices, high frequency chest compression devices, conventional chest physiotherapy, and positive expiratory pressure. Preference of technique varied: more participants preferred autogenic drainage over the active cycle of breathing technique; more preferred the active cycle of breathing technique over airway oscillating devices; and more were comfortable with the active cycle of breathing technique versus high frequency chest compression. No significant difference was seen in quality of life, sputum weight, exercise tolerance, lung function, or oxygen saturation between the active cycle of breathing technique and autogenic drainage or between the active cycle of breathing technique and airway oscillating devices. There was no significant difference in lung function and the number of pulmonary exacerbations between the active cycle of breathing technique alone or in conjunction with conventional chest physiotherapy. All other outcomes were either not measured or had insufficient data for analysis.
AUTHORS' CONCLUSIONS: There is insufficient evidence to support or reject the use of the active cycle of breathing technique over any other airway clearance therapy. Five studies, with data from eight different comparators, found that the active cycle of breathing technique was comparable with other therapies in outcomes such as participant preference, quality of life, exercise tolerance, lung function, sputum weight, oxygen saturation, and number of pulmonary exacerbations. Longer-term studies are needed to more adequately assess the effects of the active cycle of breathing technique on outcomes important for people with cystic fibrosis such as quality of life and preference.

PMID: 27378490 [PubMed - as supplied by publisher]

Eradication of methicillin resistant Staphylococcus aureus detected for the first time in cystic fibrosis: A single center observational study.

Pediatr Pulmonol. 2016 Jul 5;

Authors: Kappler M, Nagel F, Feilcke M, Kröner C, Pawlita I, Naehrig S, Ripper J, Hengst M, von Both U, Forstner M, Hector A, Griese M

Abstract
OBJECTIVE: To retrospectively identify CF patients with methicillin resistant Staphylococcus aureus (MRSA) and to assess the long-term success of an eradication scheme introduced in 2002 for all newly colonized patients.
PATIENTS: All microbiological results from all 505 CF patients followed between 2002 and 2012 were analyzed focusing on the detection of MRSA.
METHODS: Retrospective patient record analysis of MRSA positive CF patients regarding eradication and clinical outcome.
RESULTS: We identified 57 patients with MRSA, mean age 15.3 years (range: 0.6-36.9, incidence 0.9%/year). Of these, nine patients were lost to follow-up; seven chronically colonized patients were excluded from the intervention. Eradication was suggested to all patients, 37/41 gave their consent to the following two-step approach: (i) dual iv antibiotic treatment over 3 weeks, accompanied by hygienic directives and topical therapy for 5 days followed by a 6-week period with dual oral antibiotic therapy and inhalation with vancomycin. (ii) Each new MRSA detection was treated with 6 weeks inhalation of vancomycin and topical therapy for 5 days. Long-term eradication was rated by the microbiological status in the third year after first detection. MRSA was eradicated in 31 of 37 patients (84%) whose clinical course was stable (mean FEV1 one year before MRSA 80.4%, 3 years after MRSA 81.0%).
CONCLUSIONS: MRSA colonization mandates complex and expensive hygienic measures which are not well accepted by patients. Therefore, MRSA eradication is desirable. Intensive therapy regimens may be successful in patients with CF and might help to maintain a stable clinical course. Pediatr Pulmonol. © 2016 Wiley Periodicals, Inc.

PMID: 27378061 [PubMed - as supplied by publisher]

Colonization of CF patients' upper airways with S. aureus contributes more decisively to upper airway inflammation than P. aeruginosa.

Med Microbiol Immunol. 2016 Jul 4;

Authors: Janhsen WK, Arnold C, Hentschel J, Lehmann T, Pfister W, Baier M, Böer K, Hünniger K, Kurzai O, Hipler UC, Mainz JG

Abstract
In cystic fibrosis (CF) patients' airways, inflammatory processes decisively contribute to remodeling and pulmonary destruction. The aims of this study were to compare upper airway (UAW) inflammation in the context of Staphylococcus aureus and Pseudomonas aeruginosa colonization in a longitudinal setting, and to examine further factors influencing UAW inflammation. Therefore, we analyzed soluble inflammatory mediators in noninvasively obtained nasal lavage (NL) of CF patients together with microbiology, medication, and relevant clinical parameters. NL, applying 10 mL of isotonic saline per nostril, was serially performed in 74 CF patients (326 samples). Concentrations of the inflammatory mediators' interleukin (IL)-1β, IL-6, IL-8, matrix metalloproteinase (MMP)-9, and its anti-protease TIMP-1 were quantified by bead-based multiplexed assay, neutrophil elastase (NE) via ELISA. Culture-based microbiology of the upper and lower airways (LAW), as well as serological and clinical findings, were compiled. Our results indicate that UAW colonization with S. aureus significantly impacts the concentration of all measured inflammatory mediators in NL fluid except TIMP-1, whereas these effects were not significant for P. aeruginosa. Patients with S. aureus colonization of both the UAW and LAW showed significantly increased concentrations of IL-1β, IL-6, IL-8, MMP-9, and slightly elevated concentrations of NE in NL fluid compared to non-colonized patients. This work elaborates a survey on S. aureus' virulence factors that may contribute to this underestimated pathology. Serial assessment of epithelial lining fluid by NL reveals that colonization of the UAW with S. aureus contributes more to CF airway inflammatory processes than hitherto expected.

PMID: 27377929 [PubMed - as supplied by publisher]

Classification of CFTR mutation classes.

Lancet Respir Med. 2016 Jul 1;

Authors: Stanke F, Tümmler B

PMID: 27377412 [PubMed - as supplied by publisher]

Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

PLoS Genet. 2016 Jul;12(7):e1006132

Authors: Mannakee BK, Gutenkunst RN

Abstract
The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

PMID: 27380265 [PubMed - as supplied by publisher]

Humoral Dysregulation Associated with Increased Systemic Inflammation among Injection Heroin Users.

PLoS One. 2016;11(7):e0158641

Authors: Piepenbrink MS, Samuel M, Zheng B, Carter B, Fucile C, Bunce C, Kiebala M, Khan AA, Thakar J, Maggirwar SB, Morse D, Rosenberg AF, Haughey NJ, Valenti W, Keefer MC, Kobie JJ

Abstract
BACKGROUND: Injection drug use is a growing major public health concern. Injection drug users (IDUs) have a higher incidence of co-morbidities including HIV, Hepatitis, and other infections. An effective humoral response is critical for optimal homeostasis and protection from infection; however, the impact of injection heroin use on humoral immunity is poorly understood. We hypothesized that IDUs have altered B cell and antibody profiles.
METHODS AND FINDINGS: A comprehensive systems biology-based cross-sectional assessment of 130 peripheral blood B cell flow cytometry- and plasma- based features was performed on HIV-/Hepatitis C-, active heroin IDUs who participated in a syringe exchange program (n = 19) and healthy control subjects (n = 19). The IDU group had substantial polydrug use, with 89% reporting cocaine injection within the preceding month. IDUs exhibited a significant, 2-fold increase in total B cells compared to healthy subjects, which was associated with increased activated B cell subsets. Although plasma total IgG titers were similar between groups, IDUs had significantly higher IgG3 and IgG4, suggestive of chronic B cell activation. Total IgM was also increased in IDUs, as well as HIV Envelope-specific IgM, suggestive of increased HIV exposure. IDUs exhibited numerous features suggestive of systemic inflammation, including significantly increased plasma sCD40L, TNF-α, TGF-α, IL-8, and ceramide metabolites. Machine learning multivariate analysis distilled a set of 10 features that classified samples based on group with absolute accuracy.
CONCLUSIONS: These results demonstrate broad alterations in the steady-state humoral profile of IDUs that are associated with increased systemic inflammation. Such dysregulation may impact the ability of IDUs to generate optimal responses to vaccination and infection, or lead to increased risk for inflammation-related co-morbidities, and should be considered when developing immune-based interventions for this growing population.

PMID: 27379802 [PubMed - as supplied by publisher]

Editorial: Protein Interaction Networks in Health and Disease.

Front Genet. 2016;7:111

Authors: Petrakis S, Andrade-Navarro MA

PMID: 27379161 [PubMed - as supplied by publisher]

Silicon: Potential to Promote Direct and Indirect Effects on Plant Defense Against Arthropod Pests in Agriculture.

Front Plant Sci. 2016;7:744

Authors: Reynolds OL, Padula MP, Zeng R, Gurr GM

Abstract
Silicon has generally not been considered essential for plant growth, although it is well recognized that many plants, particularly Poaceae, have substantial plant tissue concentrations of this element. Recently, however, the International Plant Nutrition Institute [IPNI] (2015), Georgia, USA has listed it as a "beneficial substance". This reflects that numerous studies have now established that silicon may alleviate both biotic and abiotic stress. This paper explores the existing knowledge and recent advances in elucidating the role of silicon in plant defense against biotic stress, particularly against arthropod pests in agriculture and attraction of beneficial insects. Silicon confers resistance to herbivores via two described mechanisms: physical and biochemical/molecular. Until recently, studies have mainly centered on two trophic levels; the herbivore and plant. However, several studies now describe tri-trophic effects involving silicon that operate by attracting predators or parasitoids to plants under herbivore attack. Indeed, it has been demonstrated that silicon-treated, arthropod-attacked plants display increased attractiveness to natural enemies, an effect that was reflected in elevated biological control in the field. The reported relationships between soluble silicon and the jasmonic acid (JA) defense pathway, and JA and herbivore-induced plant volatiles (HIPVs) suggest that soluble silicon may enhance the production of HIPVs. Further, it is feasible that silicon uptake may affect protein expression (or modify proteins structurally) so that they can produce additional, or modify, the HIPV profile of plants. Ultimately, understanding silicon under plant ecological, physiological, biochemical, and molecular contexts will assist in fully elucidating the mechanisms behind silicon and plant response to biotic stress at both the bi- and tri-trophic levels.

PMID: 27379104 [PubMed - as supplied by publisher]

AMIGO2, a toolbox for dynamic modeling, optimization and control in systems biology.

Bioinformatics. 2016 Jul 4;

Authors: Balsa-Canto E, Henriques D, Gabor A, Banga JR

Abstract
MOTIVATION: Many problems of interest in dynamic modeling and control of biological systems can be posed as non-linear optimization problems subject to algebraic and dynamic constraints. In the context of modeling, this is the case of e.g. parameter estimation, optimal experimental design and dynamic flux balance analysis. In the context of control, model-based metabolic engineering or drug dose optimization problems can be formulated as (multi-objective) optimal control problems. Finding a solution to those problems is a very challenging task which requires advanced numerical methods.
RESULTS: This work presents the AMIGO2 toolbox: the first multiplatform software tool that automatizes the solution of all those problems, offering a suite of state-of-the-art (multi-objective) global optimizers and advanced simulation approaches.
AVAILABILITY: The toolbox and its documentation are available at: sites.google.com/site/amigo2toolbox CONTACT: ebalsa@iim.csic.es.

PMID: 27378288 [PubMed - as supplied by publisher]

Comparative genomic analysis of novel Acinetobacter symbionts: A combined systems biology and genomics approach.

Sci Rep. 2016;6:29043

Authors: Gupta V, Haider S, Sood U, Gilbert JA, Ramjee M, Forbes K, Singh Y, Lopes BS, Lal R

Abstract
The increasing trend of antibiotic resistance in Acinetobacter drastically limits the range of therapeutic agents required to treat multidrug resistant (MDR) infections. This study focused on analysis of novel Acinetobacter strains using a genomics and systems biology approach. Here we used a network theory method for pathogenic and non-pathogenic Acinetobacter spp. to identify the key regulatory proteins (hubs) in each strain. We identified nine key regulatory proteins, guaA, guaB, rpsB, rpsI, rpsL, rpsE, rpsC, rplM and trmD, which have functional roles as hubs in a hierarchical scale-free fractal protein-protein interaction network. Two key hubs (guaA and guaB) were important for insect-associated strains, and comparative analysis identified guaA as more important than guaB due to its role in effective module regulation. rpsI played a significant role in all the novel strains, while rplM was unique to sheep-associated strains. rpsM, rpsB and rpsI were involved in the regulation of overall network topology across all Acinetobacter strains analyzed in this study. Future analysis will investigate whether these hubs are useful as drug targets for treating Acinetobacter infections.

PMID: 27378055 [PubMed - as supplied by publisher]

CO2-evoked release of PGE2 modulates sighs and inspiration as demonstrated in brainstem organotypic culture.

Elife. 2016 Jul 5;5

Authors: Forsberg D, Horn Z, Tserga E, Smedler E, Silberberg G, Shvarev Y, Kaila K, Uhlén P, Herlenius E

Abstract
Inflammation-induced release of prostaglandin E2 (PGE2) changes breathing patterns and the response to CO2 levels. This may have fatal consequences in newborn babies and result in sudden infant death. To elucidate the underlying mechanisms, we present a novel breathing brainstem organotypic culture that generates rhythmic neural network and motor activity for 3 weeks. We show that increased CO2 elicits a gap junction-dependent release of PGE2. This alters neural network activity in the preBötzinger rhythm-generating complex and in the chemosensitive brainstem respiratory regions, thereby increasing sigh frequency and the depth of inspiration. We used mice lacking eicosanoid prostanoid 3 receptors (EP3R), breathing brainstem organotypic slices and optogenetic inhibition of EP3R(+/+)cells to demonstrate that the EP3R is important for the ventilatory response to hypercapnia. Our study identifies a novel pathway linking the inflammatory and respiratory systems, with implications for inspiration and sighs throughout life, and the ability to autoresuscitate when breathing fails.

PMID: 27377173 [PubMed - as supplied by publisher]

Piecewise linear approximations to model the dynamics of adaptation to osmotic stress by food-borne pathogens.

Int J Food Microbiol. 2016 Jun 22;

Authors: Métris A, George SM, Ropers D

Abstract
Addition of salt to food is one of the most ancient and most common methods of food preservation. However, little is known of how bacterial cells adapt to such conditions. We propose to use piecewise linear approximations to model the regulatory adaptation of Escherichiacoli to osmotic stress. We apply the method to eight selected genes representing the functions known to be at play during osmotic adaptation. The network is centred on the general stress response factor, sigma S, and also includes a module representing the catabolic repressor CRP-cAMP. Glutamate, potassium and supercoiling are combined to represent the intracellular regulatory signal during osmotic stress induced by salt. The output is a module where growth is represented by the concentration of stable RNAs and the transcription of the osmotic gene osmY. The time course of gene expression of transport of osmoprotectant represented by the symporter proP and of the osmY is successfully reproduced by the network. The behaviour of the rpoS mutant predicted by the model is in agreement with experimental data. We discuss the application of the model to food-borne pathogens such as Salmonella; although the genes considered have orthologs, it seems that supercoiling is not regulated in the same way. The model is limited to a few selected genes, but the regulatory interactions are numerous and span different time scales. In addition, they seem to be condition specific: the links that are important during the transition from exponential to stationary phase are not all needed during osmotic stress. This model is one of the first steps towards modelling adaptation to stress in food safety and has scope to be extended to other genes and pathways, other stresses relevant to the food industry, and food-borne pathogens. The method offers a good compromise between systems of ordinary differential equations, which would be unmanageable because of the size of the system and for which insufficient data are available, and the more abstract Boolean methods.

PMID: 27377009 [PubMed - as supplied by publisher]

"Initial investigation into computer scoring of candidate essays for personnel selection": Correction to Campion et al. (2016).

J Appl Psychol. 2016 Jul;101(7):975

Authors:

Abstract
Reports an error in "Initial Investigation Into Computer Scoring of Candidate Essays for Personnel Selection" by Michael C. Campion, Michael A. Campion, Emily D. Campion and Matthew H. Reider (Journal of Applied Psychology, Advanced Online Publication, Apr 14, 2016, np). In the article the affiliations for Emily D. Campion and Matthew H. Reider were originally incorrect. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-18130-001.) Emerging advancements including the exponentially growing availability of computer-collected data and increasingly sophisticated statistical software have led to a "Big Data Movement" wherein organizations have begun attempting to use large-scale data analysis to improve their effectiveness. Yet, little is known regarding how organizations can leverage these advancements to develop more effective personnel selection procedures, especially when the data are unstructured (text-based). Drawing on literature on natural language processing, we critically examine the possibility of leveraging advances in text mining and predictive modeling computer software programs as a surrogate for human raters in a selection context. We explain how to "train" a computer program to emulate a human rater when scoring accomplishment records. We then examine the reliability of the computer's scores, provide preliminary evidence of their construct validity, demonstrate that this practice does not produce scores that disadvantage minority groups, illustrate the positive financial impact of adopting this practice in an organization (N ∼ 46,000 candidates), and discuss implementation issues. Finally, we discuss the potential implications of using computer scoring to address the adverse impact-validity dilemma. We suggest that it may provide a cost-effective means of using predictors that have comparable validity but have previously been too expensive for large-scale screening. (PsycINFO Database Record

PMID: 27379396 [PubMed - as supplied by publisher]

Transfer Learning for Class Imbalance Problems with Inadequate Data.

Knowl Inf Syst. 2016 Jul;48(1):201-228

Authors: Al-Stouhi S, Reddy CK

Abstract
A fundamental problem in data mining is to effectively build robust classifiers in the presence of skewed data distributions. Class imbalance classifiers are trained specifically for skewed distribution datasets. Existing methods assume an ample supply of training examples as a fundamental prerequisite for constructing an effective classifier. However, when sufficient data is not readily available, the development of a representative classification algorithm becomes even more difficult due to the unequal distribution between classes. We provide a unified framework that will potentially take advantage of auxiliary data using a transfer learning mechanism and simultaneously build a robust classifier to tackle this imbalance issue in the presence of few training samples in a particular target domain of interest. Transfer learning methods use auxiliary data to augment learning when training examples are not sufficient and in this paper we will develop a method that is optimized to simultaneously augment the training data and induce balance into skewed datasets. We propose a novel boosting based instance-transfer classifier with a label-dependent update mechanism that simultaneously compensates for class imbalance and incorporates samples from an auxiliary domain to improve classification. We provide theoretical and empirical validation of our method and apply to healthcare and text classification applications.

PMID: 27378821 [PubMed - as supplied by publisher]

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("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

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"Cystic Fibrosis"

These pubmed results were generated on 2016/07/05

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.

J Cheminform. 2016;8:35

Authors: Vilar S, Hripcsak G

Abstract
BACKGROUND: Drug-target identification is crucial to discover novel applications for existing drugs and provide more insights about mechanisms of biological actions, such as adverse drug effects (ADEs). Computational methods along with the integration of current big data sources provide a useful framework for drug-target and drug-adverse effect discovery.
RESULTS: In this article, we propose a method based on the integration of 3D chemical similarity, target and adverse effect data to generate a drug-target-adverse effect predictor along with a simple leveraging system to improve identification of drug-targets and drug-adverse effects. In the first step, we generated a system for multiple drug-target identification based on the application of 3D drug similarity into a large target dataset extracted from the ChEMBL. Next, we developed a target-adverse effect predictor combining targets from ChEMBL with phenotypic information provided by SIDER data source. Both modules were linked to generate a final predictor that establishes hypothesis about new drug-target-adverse effect candidates. Additionally, we showed that leveraging drug-target candidates with phenotypic data is very useful to improve the identification of drug-targets. The integration of phenotypic data into drug-target candidates yielded up to twofold precision improvement. In the opposite direction, leveraging drug-phenotype candidates with target data also yielded a significant enhancement in the performance.
CONCLUSIONS: The modeling described in the current study is simple and efficient and has applications at large scale in drug repurposing and drug safety through the identification of mechanism of action of biological effects.

PMID: 27375776 [PubMed]

Using systems biology to evaluate targets and mechanism of action of drugs for diabetes comorbidities.

Diabetologia. 2016 Jul 4;

Authors: Mayer B

Abstract
Medications approved for diabetes-associated renal and cardiovascular morbidities and candidate drugs currently in development are subject to substantial variability in drug response. Heterogeneity on a molecular phenotype level is not apparent at clinical presentation, which means that inter-individual differences in drug effect at the molecular level are masked. These findings identify the need for optimising patient phenotyping via use of molecular biomarkers for a personalised therapy approach. Molecular diversity may, on the one hand, result from the effect of genetic polymorphisms on drug transport, metabolism and effective target modulation. Equally relevant, differences may be due to molecular pathologies. The presence of distinct molecular phenotypes is suggested by classifiers aimed at modelling progressive disease. Such functions for prognosis incorporate a complex set of clinical variables or a multitude of molecular markers reflecting a diverse set of molecular disease mechanisms. This information on disease pathology and the mechanism of action of the drug needs to be systematically integrated with data on molecular biomarkers to develop an experimental tool for personalising medicine. The large amount of molecular data available for characterising diabetes-associated morbidities allows for elucidation of molecular process model representations of disease pathologies. Selecting biomarker candidates on such grounds and, in turn identifying their association with progressive disease allows for the identification of molecular processes associated with disease progression. The molecular effect of a drug can also be modelled at a molecular process level, and the integration of disease pathology and drug effect molecular models reveals candidate biomarkers for assessing drug response. Such tools serve as enrichment strategies aimed at adding precision to drug development and use.

PMID: 27376542 [PubMed - as supplied by publisher]

Affinity and dose of TCR engagement yield proportional enhancer and gene activity in CD4+ T cells.

Elife. 2016;5

Authors: Allison KA, Sajti E, Collier JG, Gosselin D, Troutman TD, Stone EL, Hedrick SM, Glass CK

Abstract
Affinity and dose of T cell receptor (TCR) interaction with antigens govern the magnitude of CD4+ T cell responses, but questions remain regarding the quantitative translation of TCR engagement into downstream signals. We find that while the response of mouse CD4+ T cells to antigenic stimulation is bimodal, activated cells exhibit analog responses proportional to signal strength. Gene expression output reflects TCR signal strength, providing a signature of T cell activation. Expression changes rely on a pre-established enhancer landscape and quantitative acetylation at AP-1 binding sites. Finally, we show that graded expression of activation genes depends on ERK pathway activation, suggesting that an ERK-AP-1 axis plays an important role in translating TCR signal strength into proportional activation of enhancers and genes essential for T cell function.

PMID: 27376549 [PubMed - as supplied by publisher]

Using systems biology to evaluate targets and mechanism of action of drugs for diabetes comorbidities.

Diabetologia. 2016 Jul 4;

Authors: Mayer B

Abstract
Medications approved for diabetes-associated renal and cardiovascular morbidities and candidate drugs currently in development are subject to substantial variability in drug response. Heterogeneity on a molecular phenotype level is not apparent at clinical presentation, which means that inter-individual differences in drug effect at the molecular level are masked. These findings identify the need for optimising patient phenotyping via use of molecular biomarkers for a personalised therapy approach. Molecular diversity may, on the one hand, result from the effect of genetic polymorphisms on drug transport, metabolism and effective target modulation. Equally relevant, differences may be due to molecular pathologies. The presence of distinct molecular phenotypes is suggested by classifiers aimed at modelling progressive disease. Such functions for prognosis incorporate a complex set of clinical variables or a multitude of molecular markers reflecting a diverse set of molecular disease mechanisms. This information on disease pathology and the mechanism of action of the drug needs to be systematically integrated with data on molecular biomarkers to develop an experimental tool for personalising medicine. The large amount of molecular data available for characterising diabetes-associated morbidities allows for elucidation of molecular process model representations of disease pathologies. Selecting biomarker candidates on such grounds and, in turn identifying their association with progressive disease allows for the identification of molecular processes associated with disease progression. The molecular effect of a drug can also be modelled at a molecular process level, and the integration of disease pathology and drug effect molecular models reveals candidate biomarkers for assessing drug response. Such tools serve as enrichment strategies aimed at adding precision to drug development and use.

PMID: 27376542 [PubMed - as supplied by publisher]