Method for retinal gene repair in neonatal mouse.

Gene correction at the site of the mutation in the chromosome is the absolute way to really cure a genetic disease. The oligonucleotide (ODN)-mediated gene repair technology uses an ODN perfectly complementary to the genomic sequence except for a mismatch at the base that is mutated. The endogenous repair machinery of the targeted cell then mediates substitution of the desired base in the gene, resulting in a completely normal sequence. Theoretically, it avoids potential gene silencing or random integration associated with common viral gene augmentation approaches and allows an intact regulation of expression of the therapeutic protein. The eye is a particularly attractive target for gene repair because of its unique features (small organ, easily accessible, low diffusion into systemic circulation). Moreover therapeutic effects on visual impairment could be obtained with modest levels of repair. This chapter describes in details the optimized method to target active ODNs to the nuclei of photoreceptors in neonatal mouse using (1) an electric current application at the eye surface (saline transpalpebral iontophoresis), (2) combined with an intravitreous injection of ODNs, as well as the experimental methods for (3) the dissection of adult neural retinas, (4) their immuno-labelling, and (5) flat-mounting for direct observation of photoreceptor survival, a relevant criteria of treatment outcomes for retinal degeneration.

The wound watch: an objective staging system for wounds in the diabetic (db/db) mouse model.

As in cancer biology, in wound healing there is a need for objective staging systems to decide for the best treatment and predictors of outcome. We developed in the diabetic (db/db) wound healing model, a staging system, the "wound watch," based on the quantification of angiogenesis and cell proliferation in open wounds. In chronic wounds, there is often a lack of cellular proliferation and angiogenesis that leads to impaired healing. The wound watch addresses this by quantifying the proliferative phase of wound healing in two dimensions (cellular division and angiogenesis). The results are plotted in a two-dimensional graph to monitor the course of healing and compare the response to different treatments.

Altitudinal variation in haemosporidian parasite distribution in great tit populations.

BACKGROUND: One of the major issues concerning disease ecology and conservation is knowledge of the factors that influence the distribution of parasites and consequently disease outbreaks. This study aimed to investigate avian haemosporidian composition and the distribution of these parasites in three altitudinally separated great tit (Parus major) populations in western Switzerland over a three-year period. The objectives were to determine the lineage diversity of parasites occuring across the study populations and to investigate whether altitudinal gradients govern the distribution of haemosporidian parasites by lineage. METHODS: In this study molecular approaches (PCR and sequencing) were used to detect avian blood parasites (Plasmodium sp., Haemoproteus sp. and Leucocytozoon sp.) in populations of adult great tits caught on their nests during three consecutive breeding seasons. RESULTS: High levels of parasite prevalence (88-96%) were found across all of the study populations with no significant altitude effect. Altitude did, however, govern the distribution of parasites belonging to different genera, with Plasmodium parasites being more prevalent at lower altitudes, Leucocytozoon parasites more at high altitude and Haemoproteus parasite prevalence increasing with altitude. A total of 27 haemosporidian parasite lineages were recorded across all study sites, with diversity showing a positive correlation to altitude. Parasites belonging to lineage SGS1 (P. relictum) and PARUS4 and PARUS19 (Leucocytozoon sp.) dominated lower altitudes. SW2 (P. polare) was the second most prevalent lineage of parasite detected overall and these parasites were responsible for 68% of infections at intermediate altitude, but were only documented at this one study site. CONCLUSIONS: Avian haemosporidian parasites are not homogeneously distributed across host populations, but differ by altitude. This difference is most probably brought about by environmental factors influencing vector prevalence and distribution. The high occurrence of co-infection by different genera of parasites might have pronounced effects on host fitness and should consequently be investigated more rigorously.

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology.

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

Diagnostic performance of Fluorine-18-Fluorodeoxyglucose positron emission tomography in the assessment of pleural abnormalities in cancer patients: A systematic review and a meta-analysis.

OBJECTIVE: To systematically review and meta-analyze published data about the diagnostic performance of Fluorine-18-Fluorodeoxyglucose ((18)F-FDG) positron emission tomography (PET) and PET/computed tomography (PET/CT) in the assessment of pleural abnormalities in cancer patients. METHODS: A comprehensive literature search of studies published through June 2013 regarding the role of (18)F-FDG-PET and PET/CT in evaluating pleural abnormalities in cancer patients was performed. All retrieved studies were reviewed and qualitatively analyzed. Pooled sensitivity, specificity, positive and negative likelihood ratio (LR+ and LR-) and diagnostic odd ratio (DOR) of (18)F-FDG-PET or PET/CT on a per patient-based analysis were calculated. The area under the summary ROC curve (AUC) was calculated to measure the accuracy of these methods in the assessment of pleural abnormalities. Sub-analyses considering (18)F-FDG-PET/CT and patients with lung cancer only were carried out. RESULTS: Eight studies comprising 360 cancer patients (323 with lung cancer) were included. The meta-analysis of these selected studies provided the following results: sensitivity 86% [95% confidence interval (95%CI): 80-91%], specificity 80% [95%CI: 73-85%], LR+ 3.7 [95%CI: 2.8-4.9], LR- 0.18 [95%CI: 0.09-0.34], DOR 27 [95%CI: 13-56]. The AUC was 0.907. No significant improvement considering PET/CT studies only and patients with lung cancer was found. CONCLUSIONS: (18)F-FDG-PET and PET/CT demonstrated to be useful diagnostic imaging methods in the assessment of pleural abnormalities in cancer patients, nevertheless possible sources of false-negative and false-positive results should be kept in mind. The literature focusing on the use of (18)F-FDG-PET and PET/CT in this setting remains still limited and prospective studies are needed.

High rate of completion of preventive therapy for latent tuberculosis infection among asylum seekers in a Swiss Canton.

BACKGROUND: Preventive treatment may avoid future cases of tuberculosis among asylum seekers. The effectiveness of preventive treatment depends in large part on treatment completion. METHODS: In a prospective cohort study, asylum seekers of two of the Swiss Canton Vaud migration centres were screened with the Interferon Gamma Release Assay (IGRA). Those with a positive IGRA were referred for medical examination. Individuals with active or past tuberculosis were excluded. Preventive treatment was offered to all participants with positive IGRA but without active tuberculosis. The adherence was assessed during monthly follow-up. RESULTS: From a population of 393 adult migrants, 98 (24.9%) had a positive IGRA. Eleven did not attend the initial medical assessment. Of the 87 examined, eight presented with pulmonary disease (five of them received a full course of antituberculous therapy), two had a history of prior tuberculosis treatment and two had contraindications to treatment. Preventive treatment was offered to 75 individuals (4 months rifampicin in 74 and 9 months isoniazid in one), of whom 60 (80%) completed the treatment. CONCLUSIONS: The vulnerability and the volatility of this population make screening and observance of treatment difficult. It seems possible to obtain a high rate of completion using a short course of treatment in a closely monitored population living in stable housing conditions.

Measurement Errors Should Always Be Incorporated in Phylogenetic Comparative Analysis

The evolution of continuous traits is the central component of comparative analyses in phylogenetics, and the comparison of alternative models of trait evolution has greatly improved our understanding of the mechanisms driving phenotypic differentiation. Several factors influence the comparison of models, and we explore the effects of random errors in trait measurement on the accuracy of model selection. We simulate trait data under a Brownian motion model (BM) and introduce different magnitudes of random measurement error. We then evaluate the resulting statistical support for this model against two alternative models: Ornstein-Uhlenbeck (OU) and accelerating/decelerating rates (ACDC). Our analyses show that even small measurement errors (10%) consistently bias model selection towards erroneous rejection of BM in favour of more parameter-rich models (most frequently the OU model). Fortunately, methods that explicitly incorporate measurement errors in phylogenetic analyses considerably improve the accuracy of model selection. Our results call for caution in interpreting the results of model selection in comparative analyses, especially when complex models garner only modest additional support. Importantly, as measurement errors occur in most trait data sets, we suggest that estimation of measurement errors should always be performed during comparative analysis to reduce chances of misidentification of evolutionary processes.

Nanoinventory : a representative survey of nanoparticle usage in Suisse industry

Background Addressing the risks of nanoparticles requires knowledge about their hazards, which is generated progressively, but also about occupational exposure and liberation into the environment. However, currently such information is not systematically collected, therefore the risk assessment of this exposure or liberation lacks quantitative data. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate on the totality of the Swiss workforce. The goal of this study was to evaluate in a representative way the current prevalence and level of nanoparticle usage in Swiss industry, the health, safety and environment measures, and the number of potentially exposed workers. Results A representative, stratified mail survey was conducted among 1,626 clients of the Swiss National Accident Insurance Fund (SUVA). SUVA insures about 80,000 manufacturing firms, which represent 84% of all Swiss manufacturing companies. 947 companies answered the survey (58.3% response rate). Extrapolation to all Swiss manufacturing companies results in 1,309 workers (95%-confidence interval, 1,073 to 1,545) across the Swiss manufacturing sector being potentially exposed to nanoparticles in 586 companies (95%-CI: 145 to 1'027). This corresponds to 0.08% (95%-CI: 0.06% to 0.09%) of all Swiss manufacturing sector workers and to 0.6% (95%-CI: 0.2% to 1.1%) of companies. The industrial chemistry sector showed the highest percentage of companies using nanoparticles (21.2% of those surveyed) and a high percentage of potentially exposed workers (0.5% of workers in these companies), but many other important sectors also reported nanoparticles. Personal protection equipment was the predominant protection strategy. Only a minority applied specific environmental protection measures. Conclusions This is the first representative nationwide study on the prevalence of nanoparticle usage across a manufacturing sector. The information about the number of companies can be used for quantitative risk assessment. Furthermore it can help policy makers designing strategies to support companies in the responsible development of safer nanomaterial use. Noting the low prevalence of nanoparticle usage, there would still seem to be time to introduce necessary protection methods in a proactive and cost effective way in Swiss industry. But if the predicted "nano-revolution" becomes true, now is the time to take action.

Multicenter phase II trial of gefitinib first-line therapy followed by chemotherapy in advanced non-small-cell lung cancer (NSCLC): SAKK protocol 19/03.

BACKGROUND: Gefitinib is active in patients with pretreated non-small-cell lung cancer (NSCLC). We evaluated the activity and toxicity of gefitinib first-line treatment in advanced NSCLC followed by chemotherapy at disease progression. PATIENTS AND METHODS: In all, 63 patients with chemotherapy-naive stage IIIB/IV NSCLC received gefitinib 250 mg/day. At disease progression, gefitinib was replaced by cisplatin 80 mg/m(2) on day 1 and gemcitabine 1250 mg/m(2) on days 1, 8 for up to six 3-week cycles. Primary end point was the disease stabilization rate (DSR) after 12 weeks of gefitinib. RESULTS: After 12 weeks of gefitinib, the DSR was 24% and the response rate (RR) was 8%. Median time to progression (TtP) was 2.5 months and median overall survival (OS) 11.5 months. Never smokers (n = 9) had a DSR of 56% and a median OS of 20.2 months; patients with epidermal growth factor receptor (EGFR) mutation (n = 4) had a DSR of 75% and the median OS was not reached after the follow-up of 21.6 months. In all, 41 patients received chemotherapy with an overall RR of 34%, DSR of 71% and median TtP of 6.7 months. CONCLUSIONS: First-line gefitinib monotherapy led to a DSR of 24% at 12 weeks in an unselected patients population. Never smokers and patients with EGFR mutations tend to have a better outcome; hence, further trials in selected patients are warranted.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Cardiorenal end points in a trial of aliskiren for type 2 diabetes.

BACKGROUND: This study was undertaken to determine whether use of the direct renin inhibitor aliskiren would reduce cardiovascular and renal events in patients with type 2 diabetes and chronic kidney disease, cardiovascular disease, or both. METHODS: In a double-blind fashion, we randomly assigned 8561 patients to aliskiren (300 mg daily) or placebo as an adjunct to an angiotensin-converting-enzyme inhibitor or an angiotensin-receptor blocker. The primary end point was a composite of the time to cardiovascular death or a first occurrence of cardiac arrest with resuscitation; nonfatal myocardial infarction; nonfatal stroke; unplanned hospitalization for heart failure; end-stage renal disease, death attributable to kidney failure, or the need for renal-replacement therapy with no dialysis or transplantation available or initiated; or doubling of the baseline serum creatinine level. RESULTS: The trial was stopped prematurely after the second interim efficacy analysis. After a median follow-up of 32.9 months, the primary end point had occurred in 783 patients (18.3%) assigned to aliskiren as compared with 732 (17.1%) assigned to placebo (hazard ratio, 1.08; 95% confidence interval [CI], 0.98 to 1.20; P=0.12). Effects on secondary renal end points were similar. Systolic and diastolic blood pressures were lower with aliskiren (between-group differences, 1.3 and 0.6 mm Hg, respectively) and the mean reduction in the urinary albumin-to-creatinine ratio was greater (between-group difference, 14 percentage points; 95% CI, 11 to 17). The proportion of patients with hyperkalemia (serum potassium level, ≥6 mmol per liter) was significantly higher in the aliskiren group than in the placebo group (11.2% vs. 7.2%), as was the proportion with reported hypotension (12.1% vs. 8.3%) (P<0.001 for both comparisons). CONCLUSIONS: The addition of aliskiren to standard therapy with renin-angiotensin system blockade in patients with type 2 diabetes who are at high risk for cardiovascular and renal events is not supported by these data and may even be harmful. (Funded by Novartis; ALTITUDE ClinicalTrials.gov number, NCT00549757.).

Urinary D-lactate excretion in infants receiving Lactobacillus johnsonii with formula.

BACKGROUND/AIMS: Supplementation with certain probiotics can improve gut microbial flora and immune function but should not have adverse effects. This study aimed to assess the risk of D-lactate accumulation and subsequent metabolic acidosis in infants fed on formula containing Lactobacillus johnsonii (La1). METHODS: In the framework of a double-blind, randomized controlled trial enrolling 71 infants aged 4-5 months, morning urine samples were collected before and 4 weeks after being fed formulas with or without La1 (1 x 10(8)/g powder) or being breastfed. Urinary D- and L-lactate concentrations were assayed by enzymatic, fluorimetric methods and excretion was normalized per mol creatinine. RESULTS: At baseline, no significant differences in urinary D-/L-lactate excretion among the formula-fed and breastfed groups were found. After 4 weeks, D-lactate excretion did not differ between the two formula groups, but was higher in both formula groups than in breastfed infants. In all infants receiving La1, urinary D-lactate concentrations remained within the concentration ranges of age-matched healthy infants which had been determined in an earlier study using the same analytical method. Urinary L-lactate also did not vary over time or among groups. CONCLUSIONS: Supplementation of La1 to formula did not affect urinary lactate excretion and there is no evidence of an increased risk of lactic acidosis.

Zoledronic Acid in Reducing Clinical Fracture and Mortality after Hip Fracture.

BACKGROUND: Mortality is increased after a hip fracture, and strategies that improve outcomes are needed. METHODS: In this randomized, double-blind, placebo-controlled trial, 1065 patients were assigned to receive yearly intravenous zoledronic acid (at a dose of 5 mg), and 1062 patients were assigned to receive placebo. The infusions were first administered within 90 days after surgical repair of a hip fracture. All patients received supplemental vitamin D and calcium. The median follow-up was 1.9 years. The primary end point was a new clinical fracture. RESULTS: The rates of any new clinical fracture were 8.6% in the zoledronic acid group and 13.9% in the placebo group, a 35% risk reduction (P = 0.001); the respective rates of a new clinical vertebral fracture were 1.7% and 3.8% (P = 0.02), and the respective rates of new nonvertebral fractures were 7.6% and 10.7% (P = 0.03). In the safety analysis, 101 of 1054 patients in the zoledronic acid group (9.6%) and 141 of 1057 patients in the placebo group (13.3%) died, a reduction of 28% in deaths from any cause in the zoledronic-acid group (P = 0.01). The most frequent adverse events in patients receiving zoledronic acid were pyrexia, myalgia, and bone and musculoskeletal pain. No cases of osteonecrosis of the jaw were reported, and no adverse effects on the healing of fractures were noted. The rates of renal and cardiovascular adverse events, including atrial fibrillation and stroke, were similar in the two groups. CONCLUSIONS: An annual infusion of zoledronic acid within 90 days after repair of a low-trauma hip fracture was associated with a reduction in the rate of new clinical fractures and improved survival. (ClinicalTrials.gov number, NCT00046254.).

Frequency and determinants of using pharmacological enhancement in the clinical practice of in-hospital stroke rehabilitation.

Background: Pharmacological enhancement in stroke rehabilitation (PESR) is promising. Data about its use in clinical practice are missing. Methods: In a prospective, explorative study of four rehabilitation centers, we systematically observed the frequency and determinants of using PESR in consecutive patients. PESR was defined as using agents potentially enhancing post-stroke recovery exclusively to aid rehabilitation without an established indication. Results: 257 (55.4%) of 464 patients had agents potentially enhancing recovery. Selective serotonin reuptake inhibitors (SSRI) (n = 125, 26.9%), levodopa (n = 114, 24.6%), serotonin-noradrenaline reuptake inhibitors (SNRI) (n = 52, 11.2%), and acetylcholinesterase inhibitors (n = 48, 10.3%) were used most often. SSRI in 102/125 patients and SNRI in 46/52 patients were mostly used for accompanying depressive symptoms. 159 (34.3%) patients had PESR (without an otherwise established indication). In PESR patients, levodopa (n = 102, 64.1%) was used most commonly. PESR was primarily used for aphasia (36.5%) and paresis (25.2%). PESR patients did not differ from non-PESR patients in age, gender and stroke type. However, the utilization rates of PESR differed significantly across centers (2, 4, 38 and 55%). Conclusion: SSRI and SNRI were predominately used for accompanying depression, while levodopa was nearly exclusively used to aid stroke rehabilitation in the absence of an otherwise established indication. The differences in utilization rates for PESR between centers suggest therapeutic uncertainty and indicate the need for additional studies.

Genome-wide search reveals a novel GacA-regulated small RNA in Pseudomonas species.

BACKGROUND: Small RNAs (sRNAs) are widespread among bacteria and have diverse regulatory roles. Most of these sRNAs have been discovered by a combination of computational and experimental methods. In Pseudomonas aeruginosa, a ubiquitous Gram-negative bacterium and opportunistic human pathogen, the GacS/GacA two-component system positively controls the transcription of two sRNAs (RsmY, RsmZ), which are crucial for the expression of genes involved in virulence. In the biocontrol bacterium Pseudomonas fluorescens CHA0, three GacA-controlled sRNAs (RsmX, RsmY, RsmZ) regulate the response to oxidative stress and the expression of extracellular products including biocontrol factors. RsmX, RsmY and RsmZ contain multiple unpaired GGA motifs and control the expression of target mRNAs at the translational level, by sequestration of translational repressor proteins of the RsmA family. RESULTS: A combined computational and experimental approach enabled us to identify 14 intergenic regions encoding sRNAs in P. aeruginosa. Eight of these regions encode newly identified sRNAs. The intergenic region 1698 was found to specify a novel GacA-controlled sRNA termed RgsA. GacA regulation appeared to be indirect. In P. fluorescens CHA0, an RgsA homolog was also expressed under positive GacA control. This 120-nt sRNA contained a single GGA motif and, unlike RsmX, RsmY and RsmZ, was unable to derepress translation of the hcnA gene (involved in the biosynthesis of the biocontrol factor hydrogen cyanide), but contributed to the bacterium's resistance to hydrogen peroxide. In both P. aeruginosa and P. fluorescens the stress sigma factor RpoS was essential for RgsA expression. CONCLUSION: The discovery of an additional sRNA expressed under GacA control in two Pseudomonas species highlights the complexity of this global regulatory system and suggests that the mode of action of GacA control may be more elaborate than previously suspected. Our results also confirm that several GGA motifs are required in an sRNA for sequestration of the RsmA protein.