The application of a long period grating array for respiratory function monitoring

In this paper, multiplexed sensor network capable of monitoring the shape changes of the torso for respiratory function monitoring is developed. As a demonstration, LPGs written into refractive index insensitive, progressive three layered fibre are embedded into supporting material is then placed on a resuscitation training manikin simulating respiration. A derivative spectroscopy interrogation technique is implemented and the bend sensitivity of the LPGs is used to reconstruct the shape of the manikin's torso. © 2003 IEEE.

Application of long-period-grating sensors to respiratory plethysmography

A series of in-line curvature sensors on a garment are used to monitor the thoracic and abdominal movements of a human during respiration. These results are used to obtain volumetric tidal changes of the human torso in agreement with a spirometer used simultaneously at the mouth. The curvature sensors are based on long-period gratings (LPGs) written in a progressive three-layered fiber to render the LPGs insensitive to the refractive index external to the fiber. A curvature sensor consists of the fiber long-period grating laid on a carbon fiber ribbon, which is then encapsulated in a low-temperature curing silicone rubber. The sensors have a spectral sensitivity to curvature, dλ/dR from ∼7-nm m to ∼9-nm m. The interrogation technique is borrowed from derivative spectroscopy and monitors the changes in the transmission spectral profile of the LPG's attenuation band due to curvature. The multiplexing of the sensors is achieved by spectrally matching a series of distributed feedback (DFB) lasers to the LPGs. The versatility of this sensing garment is confirmed by it being used on six other human subjects covering a wide range of body mass indices. Just six fully functional sensors are required to obtain a volumetric error of around 6%. © 2007 Society of Photo-Optical Instrumentation Engineers.

Motion correction algorithm of lung tumors for respiratory gated PET images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

What We Mean When We Talk About Adherence In Respiratory Medicine

Funding acknowledgements The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. AD, EvG and MdB have received funding from the European Community’s 7th Framework (FP7/2007-2013) under grant agreement n°282593.

What We Mean When We Talk About Adherence In Respiratory Medicine

Funding acknowledgements The Respiratory Effectiveness Group (REG; www.effectivenessevaluation.org) supported the Expert Adherence Panel Meeting at which many of the concepts presented in this paper were first discussed. REG also supported the manuscript submission costs. AD, EvG and MdB have received funding from the European Community’s 7th Framework (FP7/2007-2013) under grant agreement n°282593.

“Trying, But Failing” : The Role of Inhaler Technique and Mode of Delivery in Respiratory Medication Adherence

Peer reviewed

Scaling up strategies of the chronic respiratory disease programme of the European Innovation Partnership on Active and Healthy Ageing (Action Plan B3: Area 5)

Peer reviewed

Host gene expression classifiers diagnose acute respiratory illness etiology.

Acute respiratory infections caused by bacterial or viral pathogens are among the most common reasons for seeking medical care. Despite improvements in pathogen-based diagnostics, most patients receive inappropriate antibiotics. Host response biomarkers offer an alternative diagnostic approach to direct antimicrobial use. This observational cohort study determined whether host gene expression patterns discriminate noninfectious from infectious illness and bacterial from viral causes of acute respiratory infection in the acute care setting. Peripheral whole blood gene expression from 273 subjects with community-onset acute respiratory infection (ARI) or noninfectious illness, as well as 44 healthy controls, was measured using microarrays. Sparse logistic regression was used to develop classifiers for bacterial ARI (71 probes), viral ARI (33 probes), or a noninfectious cause of illness (26 probes). Overall accuracy was 87% (238 of 273 concordant with clinical adjudication), which was more accurate than procalcitonin (78%, P < 0.03) and three published classifiers of bacterial versus viral infection (78 to 83%). The classifiers developed here externally validated in five publicly available data sets (AUC, 0.90 to 0.99). A sixth publicly available data set included 25 patients with co-identification of bacterial and viral pathogens. Applying the ARI classifiers defined four distinct groups: a host response to bacterial ARI, viral ARI, coinfection, and neither a bacterial nor a viral response. These findings create an opportunity to develop and use host gene expression classifiers as diagnostic platforms to combat inappropriate antibiotic use and emerging antibiotic resistance.

Clinical potential of oligonucleotide-based therapeutics in the respiratory system

The discovery of an ever-expanding plethora of coding and non-coding RNAs with nodal and causal roles in the regulation of lung physiology and disease is reinvigorating interest in the clinical utility of the oligonucleotide therapeutic class. This is strongly supported through recent advances in nucleic acids chemistry, synthetic oligonucleotide delivery and viral gene therapy that have succeeded in bringing to market at least three nucleic acid-based drugs. As a consequence, multiple new candidates such as RNA interference modulators, antisense, and splice switching compounds are now progressing through clinical evaluation. Here, manipulation of RNA for the treatment of lung disease is explored, with emphasis on robust pharmacological evidence aligned to the five pillars of drug development: exposure to the appropriate tissue, binding to the desired molecular target, evidence of the expected mode of action, activity in the relevant patient population and commercially viable value proposition.

EGFR interacts with the fusion protein of respiratory syncytial virus strain 2-20 and mediates infection and mucin expression.

Respiratory syncytial virus (RSV) is the major cause of viral lower respiratory tract illness in children. In contrast to the RSV prototypic strain A2, clinical isolate RSV 2-20 induces airway mucin expression in mice, a clinically relevant phenotype dependent on the fusion (F) protein of the RSV strain. Epidermal growth factor receptor (EGFR) plays a role in airway mucin expression in other systems; therefore we hypothesized that the RSV 2-20 F protein stimulates EGFR signaling. Infection of cells with chimeric strains RSV A2-2-20F and A2-2-20GF or over-expression of 2-20 F protein resulted in greater phosphorylation of EGFR than infection with RSV A2 or over-expression of A2 F, respectively. Chemical inhibition of EGFR signaling or knockdown of EGFR resulted in diminished infectivity of RSV A2-2-20F but not RSV A2. Over-expression of EGFR enhanced the fusion activity of 2-20 F protein in trans. EGFR co-immunoprecipitated most efficiently with RSV F proteins derived from “mucogenic” strains. RSV 2-20 F and EGFR co-localized in H292 cells, and A2-2-20GF-induced MUC5AC expression was ablated by EGFR inhibitors in these cells. Treatment of BALB/c mice with the EGFR inhibitor erlotinib significantly reduced the amount of RSV A2-2-20F-induced airway mucin expression. Our results demonstrate that RSV F interacts with EGFR in a strain-specific manner, EGFR is a co-factor for infection, and EGFR plays a role in RSV-induced mucin expression, suggesting EGFR is a potential target for RSV disease.

Raman Analysis of Dilute Aqueous Samples by Localized Evaporation of Submicroliter Droplets on the Tips of Superhydrophobic Copper Wires

Raman analysis of dilute aqueous solutions is normally prevented by their low signal levels. A very general method to increase the concentration to detectable levels is to evaporate droplets of the sample to dryness, creating solid deposits which are then Raman probed. Here, superhydrophobic (SHP) wires with hydrophilic tips have been used as supports for drying droplets, which have the advantage that the residue is automatically deposited at the tip. The SHP wires were readily prepared in minutes using electroless galvanic deposition of Ag onto copper wires followed by modification with a polyfluorothiol (3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-heptadecafluoro-1-decanethiol, HDFT). Cutting the coated wires with a scalpel revealed hydrophilic tips which could support droplets whose maximum size was determined by the wire diameter. Typically, 230 μm wires were used to support 0.6 μL droplets. Evaporation of dilute melamine droplets gave solid deposits which could be observed by scanning electron microscopy (SEM) and Raman spectroscopy. The limit of detection for melamine using a two stage evaporation procedure was 1 × 10^-6 mol dm^-3. The physical appearance of dried droplets of sucrose and glucose showed that the samples retained significant amounts of water, even under high vacuum. Nonetheless, the Raman detection limits of sucrose and glucose were 5 × 10^-4 and 2.5 × 10^-3 mol dm^-3, respectively, which is similar to the sensitivity reported for surface-enhanced Raman spectroscopy (SERS) detection of glucose. It was also possible to quantify the two sugars in mixtures at concentrations which were similar to those found in human blood through multivariate analysis.