The Clinical Pharmacogenetics Implementation Consortium (CPIC) publishes genotype-based drug guidelines to help clinicians understand how available genetic test results could be used to optimize drug ...therapy. CPIC has focused initially on well-known examples of pharmacogenomic associations that have been implemented in selected clinical settings, publishing nine to date. Each CPIC guideline adheres to a standardized format and includes a standard system for grading levels of evidence linking genotypes to phenotypes and assigning a level of strength to each prescribing recommendation. CPIC guidelines contain the necessary information to help clinicians translate patient-specific diplotypes for each gene into clinical phenotypes or drug dosing groups. This paper reviews the development process of the CPIC guidelines and compares this process to the Institute of Medicine's Standards for Developing Trustworthy Clinical Practice Guidelines.
Centrioles are critical for the formation of centrosomes, cilia and flagella in eukaryotes. They are thought to assemble around a nine-fold symmetric cartwheel structure established by SAS-6 ...proteins. Here, we have engineered Chlamydomonas reinhardtii SAS-6-based oligomers with symmetries ranging from five- to ten-fold. Expression of a SAS-6 mutant that forms six-fold symmetric cartwheel structures in vitro resulted in cartwheels and centrioles with eight- or nine-fold symmetries in vivo. In combination with Bld10 mutants that weaken cartwheel-microtubule interactions, this SAS-6 mutant produced six- to eight-fold symmetric cartwheels. Concurrently, the microtubule wall maintained eight- and nine-fold symmetries. Expressing SAS-6 with analogous mutations in human cells resulted in nine-fold symmetric centrioles that exhibited impaired length and organization. Together, our data suggest that the self-assembly properties of SAS-6 instruct cartwheel symmetry, and lead us to propose a model in which the cartwheel and the microtubule wall assemble in an interdependent manner to establish the native architecture of centrioles.
Summary
Plant rhizosphere soil houses complex microbial communities in which microorganisms are often involved in intraspecies as well as interspecies and inter‐kingdom signalling networks. Some ...members of these networks can improve plant health thanks to an important diversity of bioactive secondary metabolites. In this competitive environment, the ability to form biofilms may provide major advantages to microorganisms. With the aim of highlighting the impact of bacterial lifestyle on secondary metabolites production, we performed a metabolomic analysis on four fluorescent Pseudomonas strains cultivated in planktonic and biofilm colony conditions. The untargeted metabolomic analysis led to the detection of hundreds of secondary metabolites in culture extracts. Comparison between biofilm and planktonic conditions showed that bacterial lifestyle is a key factor influencing Pseudomonas metabolome. More than 50% of the detected metabolites were differentially produced according to planktonic or biofilm lifestyles, with the four Pseudomonas strains overproducing several secondary metabolites in biofilm conditions. In parallel, metabolomic analysis associated with genomic prediction and a molecular networking approach enabled us to evaluate the impact of bacterial lifestyle on chemically identified secondary metabolites, more precisely involved in microbial interactions and plant‐growth promotion. Notably, this work highlights the major effect of biofilm lifestyle on acyl‐homoserine lactone and phenazine production in P. chlororaphis strains.
Pseudomonas strains overproduce a higher diversity of secondary metabolites in biofilm colony than in planktonic lifestyle. In particular, the biosynthesis of key compounds implicated in bacterial biotic interactions like AHLs or phenazines are strongly enhanced in biofilms. Biofilms are thus key ways to enhance the biocontrol and biostimulant activities of bioinoculant for agriculture purposes.
Fibrous aggregates of Tau protein are characteristic features of Alzheimer disease. We applied high resolution atomic force and EM microscopy to study fibrils assembled from different human Tau ...isoforms and domains. All fibrils reveal structural polymorphism; the “thin twisted” and “thin smooth” fibrils resemble flat ribbons (cross-section ∼10 × 15 nm) with diverse twist periodicities. “Thick fibrils” show periodicities of ∼65–70 nm and thicknesses of ∼9–18 nm such as routinely reported for “paired helical filaments” but structurally resemble heavily twisted ribbons. Therefore, thin and thick fibrils assembled from different human Tau isoforms challenge current structural models of paired helical filaments. Furthermore, all Tau fibrils reveal axial subperiodicities of ∼17–19 nm and, upon exposure to mechanical stress or hydrophobic surfaces, disassemble into uniform fragments that remain connected by thin thread-like structures (∼2 nm). This hydrophobically induced disassembly is inhibited at enhanced electrolyte concentrations, indicating that the fragments resemble structural building blocks and the fibril integrity depends largely on hydrophobic and electrostatic interactions. Because full-length Tau and repeat domain constructs assemble into fibrils of similar thickness, the “fuzzy coat” of Tau protein termini surrounding the fibril axis is nearly invisible for atomic force microscopy and EM, presumably because of its high flexibility.
•A shift to a new socio-metabolic regime requires transformation of in-use stocks.•Decoupling extends the option space for mitigating greenhouse gas emissions.•Decoupling throughput from service may ...be sufficient to reach the 2°C target.•Deliberate design of in-use stocks determines success of mitigation strategies.
Human well-being includes the use of physical services from buildings, infrastructure, and consumer products. These in-use stocks link the services enjoyed by humans to energy and material consumption. Climate change mitigation requires us to transform current in-use stocks to decouple energy and material throughput from service provision. Assessing the potential environmental benefits of emissions mitigation and other sustainable development strategies requires a solid understanding of in-use stocks and their dynamics.
We identified the different roles of in-use stocks in the social metabolism and showed to what extent they are included in current impact assessment models. We extended state-of-the-art dynamic stock models by including direct and indirect energy demand and greenhouse gas emissions. We applied the new modeling framework to three case studies in the major sectors transportation, buildings, and industry. We assessed the emissions reduction potential of the decoupling strategies energy efficiency, material efficiency, and moderate lifestyle changes.
For the global steel industry and for residential buildings the emissions reduction potential of the above-mentioned strategies was so large that the benchmarks corresponding to the 2°C climate target could be reached. Decoupling alone might be sufficient to reach the 2°C benchmarks in some sectors. Considering decoupling next to supply side measures such as new energy technologies may make it easier to consider other objectives than emissions reduction. Decoupling may therefore revitalize the debate about sustainable development because it allows us to loosen the focus on climate change mitigation and put more weight on the economic, social, cultural, and other environmental aspects of sustainability.
This study aims to compare the effectiveness of EEG frequency band activity including interhemispheric asymmetry and prefrontal theta cordance in predicting response to escitalopram therapy at ...8-weeks post-treatment, in a multi-site initiative.
Resting state 64-channel EEG data were recorded from 44 patients with a diagnosis of major depressive disorder (MDD) as part of a larger, multisite discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). Clinical response was measured at 8-weeks post-treatment as change from baseline Montgomery-Asberg Depression Rating Scale (MADRS) score of 50% or more. EEG measures were analyzed at (1) pre-treatment baseline (2) 2 weeks post-treatment and (3) as an ‘‘early change” variable defined as change in EEG from baseline to 2 weeks post-treatment.
At baseline, treatment responders showed elevated absolute alpha power in the left hemisphere while non-responders showed the opposite. Responders further exhibited a cortical asymmetry in the parietal region. Groups also differed in pre-treatment relative delta power with responders showing greater power in the right hemisphere over the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to the right and the opposite was noted for non-responders. A reverse pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reductions in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance.
Hemispheric asymmetries in the alpha and delta bands at baseline and at 2 weeks post-treatment have moderately strong predictive utility in predicting response to antidepressant treatment.
•Escitalopram responders show elevated baseline alpha power in the left hemisphere.•Responders exhibit baseline cortical asymmetry in the parietal region.•Treatment responders show greater baseline delta power in the right hemisphere.•Responders and non-responders display opposite patterns of power post-treatment.•Responders exhibit early reduction in alpha power and early increment in theta power.
Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could ...personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD.
CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response.
From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.
ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.
Practice of meditation or exercise may enhance health to protect against acute infectious illness.
To assess preventive effects of meditation and exercise on acute respiratory infection (ARI) ...illness.
Randomized controlled prevention trial with three parallel groups.
Madison, Wisconsin, USA.
Community-recruited adults who did not regularly exercise or meditate.
1) 8-week behavioral training in mindfulness-based stress reduction (MBSR); 2) matched 8-week training in moderate intensity sustained exercise (EX); or 3) observational waitlist control. Training classes occurred in September and October, with weekly ARI surveillance through May. Incidence, duration, and area-under-curve ARI global severity were measured using daily reports on the WURSS-24 during ARI illness. Viruses were identified multiplex PCR. Absenteeism, health care utilization, and psychosocial health self-report assessments were also employed.
Of 413 participants randomized, 390 completed the trial. In the MBSR group, 74 experienced 112 ARI episodes with 1045 days of ARI illness. Among exercisers, 84 had 120 episodes totaling 1010 illness days. Eighty-two of the controls had 134 episodes with 1210 days of ARI illness. Mean global severity was 315 for MBSR (95% confidence interval 244, 386), 256 (193, 318) for EX, and 336 (268, 403) for controls. A prespecified multivariate zero-inflated regression model suggested reduced incidence for MBSR (p = 0.036) and lower global severity for EX (p = 0.042), compared to control, not quite attaining the p<0.025 prespecified cut-off for null hypothesis rejection. There were 73 ARI-related missed-work days and 22 ARI-related health care visits in the MBSR group, 82 days and 21 visits for exercisers, and 105 days and 24 visits among controls. Viruses were identified in 63 ARI episodes in the MBSR group, compared to 64 for EX and 72 for control. Statistically significant (p<0.05) improvements in general mental health, self-efficacy, mindful attention, sleep quality, perceived stress, and depressive symptoms were observed in the MBSR and/or EX groups, compared to control.
Training in mindfulness meditation or exercise may help protect against ARI illness.
This trial was likely underpowered.
Clinicaltrials.gov NCT01654289.
Abstract
Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual’s own environment. Long periods of data ...collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.
Plants do not grow as axenic organisms in nature, but host a diverse community of microorganisms, termed the plant microbiota. There is an increasing awareness that the plant microbiota plays a role ...in plant growth and can provide protection from invading pathogens. Apart from intense research on crop plants,
Arabidopsis
is emerging as a valuable model system to investigate the drivers shaping stable bacterial communities on leaves and roots and as a tool to decipher the intricate relationship among the host and its colonizing microorganisms. Gnotobiotic experimental systems help establish causal relationships between plant and microbiota genotypes and phenotypes and test hypotheses on biotic and abiotic perturbations in a systematic way. We highlight major recent findings in plant microbiota research using comparative community profiling and omics analyses, and discuss these approaches in light of community establishment and beneficial traits like nutrient acquisition and plant health.
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