Differential In Vitro Pharmacological Profiles of Structurally Diverse Nociceptin Receptor Agonists in Activating G Protein and Beta-Arrestin Signaling at the Human Nociceptin Opioid Receptor.

Agonists at the nociceptin opioid peptide receptor (NOP) are under investigation as therapeutics for nonaddicting analgesia, opioid use disorder, Parkinson's disease, and other indications. NOP full and partial agonists have both been of interest, particularly since NOP partial agonists show a reduced propensity for behavioral disruption than NOP full agonists. Here, we investigated the in vitro pharmacological properties of chemically diverse NOP receptor agonists in assays measuring functional activation of the NOP receptor such as guanosine 5'-O-[gamma-thio]triphosphate (GTPγS) binding, cAMP inhibition, G protein-coupled inwardly rectifying potassium (GIRK) channel activation, phosphorylation, ß-arrestin recruitment and receptor internalization. When normalized to the efficacy of the natural agonist nociceptin/orphanin FQ (N/OFQ), we found that different functional assays that measure intrinsic activity produce inconsistent levels of agonist efficacy, particularly for ligands that were partial agonists. Agonist efficacy obtained in the GTPγS assay tended to be lower than that in the cAMP and GIRK assays. These structurally diverse NOP agonists also showed differential receptor phosphorylation profiles at the phosphosites we examined and induced varying levels of receptor internalization. Interestingly, although the rank order for ß-arrestin recruitment by these NOP agonists was consistent with their ability to induce receptor internalization, their phosphorylation signatures at the time point we investigated were not indicative of the levels of ß-arrestin recruitment or internalization induced by these agonists. It is possible that other phosphorylation sites, yet to be identified, drive the recruitment of NOP receptor ensembles and subsequent receptor trafficking by some nonpeptide NOP agonists. These findings potentially help understand NOP agonist pharmacology in the context of ligand-activated receptor trafficking. SIGNIFICANCE STATEMENT: Chemically diverse agonist ligands at the nociceptin opioid receptor G protein-coupled receptor showed differential efficacy for activating downstream events after receptor binding, in a suite of functional assays measuring guanosine 5'-O-[gamma-thio]triphosphate binding, cAMP inhibition, G protein-coupled inwardly rectifying protein channel activation, ß-arrestin recruitment, receptor internalization and receptor phosphorylation. These analyses provide a context for understanding nociceptin opioid peptide receptor (NOP) agonist pharmacology driven by ligand-induced differential NOP receptor signaling.

A bifunctional nociceptin and mu opioid receptor agonist is analgesic without opioid side effects in nonhuman primates.

Misuse of prescription opioids, opioid addiction, and overdose underscore the urgent need for developing addiction-free effective medications for treating severe pain. Mu opioid peptide (MOP) receptor agonists provide very effective pain relief. However, severe side effects limit their use in the clinical setting. Agonists of the nociceptin/orphanin FQ peptide (NOP) receptor have been shown to modulate the antinociceptive and reinforcing effects of MOP agonists. We report the discovery and development of a bifunctional NOP/MOP receptor agonist, AT-121, which has partial agonist activity at both NOP and MOP receptors. AT-121 suppressed oxycodone's reinforcing effects and exerted morphine-like analgesic effects in nonhuman primates. AT-121 treatment did not induce side effects commonly associated with opioids, such as respiratory depression, abuse potential, opioid-induced hyperalgesia, and physical dependence. Our results in nonhuman primates suggest that bifunctional NOP/MOP agonists with the appropriate balance of NOP and MOP agonist activity may provide a dual therapeutic action for safe and effective pain relief and treating prescription opioid abuse.

Automated Information Extraction on Treatment and Prognosis for Non-Small Cell Lung Cancer Radiotherapy Patients: Clinical Study.

BACKGROUND: In outcome studies of oncology patients undergoing radiation, researchers extract valuable information from medical records generated before, during, and after radiotherapy visits, such as survival data, toxicities, and complications. Clinical studies rely heavily on these data to correlate the treatment regimen with the prognosis to develop evidence-based radiation therapy paradigms. These data are available mainly in forms of narrative texts or table formats with heterogeneous vocabularies. Manual extraction of the related information from these data can be time consuming and labor intensive, which is not ideal for large studies. OBJECTIVE: The objective of this study was to adapt the interactive information extraction platform Information and Data Extraction using Adaptive Learning (IDEAL-X) to extract treatment and prognosis data for patients with locally advanced or inoperable non-small cell lung cancer (NSCLC). METHODS: We transformed patient treatment and prognosis documents into normalized structured forms using the IDEAL-X system for easy data navigation. The adaptive learning and user-customized controlled toxicity vocabularies were applied to extract categorized treatment and prognosis data, so as to generate structured output. RESULTS: In total, we extracted data from 261 treatment and prognosis documents relating to 50 patients, with overall precision and recall more than 93% and 83%, respectively. For toxicity information extractions, which are important to study patient posttreatment side effects and quality of life, the precision and recall achieved 95.7% and 94.5% respectively. CONCLUSIONS: The IDEAL-X system is capable of extracting study data regarding NSCLC chemoradiation patients with significant accuracy and effectiveness, and therefore can be used in large-scale radiotherapy clinical data studies.

Improved Identification of Venous Thromboembolism From Electronic Medical Records Using a Novel Information Extraction Software Platform.

INTRODUCTION: The United States federally mandated reporting of venous thromboembolism (VTE), defined by Agency for Healthcare Research & Quality Patient Safety Indicator 12 (AHRQ PSI-12), is based on administrative data, the accuracy of which has not been consistently demonstrated. We used IDEAL-X, a novel information extraction software system, to identify VTE from electronic medical records and evaluated its accuracy. METHODS: Medical records for 13,248 patients admitted to an orthopedic specialty hospital from 2009 to 2014 were reviewed. Patient encounters were defined as a hospital admission where both surgery (of the spine, hip, or knee) and a radiology diagnostic study that could detect VTE was performed. Radiology reports were both manually reviewed by a physician and analyzed by IDEAL-X. RESULTS: Among 2083 radiology reports, IDEAL-X correctly identified 176/181 VTE events, achieving a sensitivity of 97.2% [95% confidence interval (CI), 93.7%-99.1%] and specificity of 99.3% (95% CI, 98.9%-99.7%) when compared with manual review. Among 422 surgical encounters with diagnostic radiographic studies for VTE, IDEAL-X correctly identified 41 of 42 VTE events, achieving a sensitivity of 97.6% (95% CI, 87.4%-99.6%) and specificity of 99.8% (95% CI, 98.7%-100.0%). The performance surpassed that of AHRQ PSI-12, which had a sensitivity of 92.9% (95% CI, 80.5%-98.4%) and specificity of 92.9% (95% CI, 89.8%-95.3%), though only the difference in specificity was statistically significant (P<0.01). CONCLUSION: IDEAL-X, a novel information extraction software system, identified VTE from radiology reports with high accuracy, with specificity surpassing AHRQ PSI-12. IDEAL-X could potentially improve detection and surveillance of many medical conditions from free text of electronic medical records.

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies.

BACKGROUND: Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. OBJECTIVE: Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. METHODS: A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. RESULTS: Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports-each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. CONCLUSIONS: IDEAL-X adopts a unique online machine learning-based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable.

Support patient search on pathology reports with interactive online learning based data extraction.

BACKGROUND: Structural reporting enables semantic understanding and prompt retrieval of clinical findings about patients. While synoptic pathology reporting provides templates for data entries, information in pathology reports remains primarily in narrative free text form. Extracting data of interest from narrative pathology reports could significantly improve the representation of the information and enable complex structured queries. However, manual extraction is tedious and error-prone, and automated tools are often constructed with a fixed training dataset and not easily adaptable. Our goal is to extract data from pathology reports to support advanced patient search with a highly adaptable semi-automated data extraction system, which can adjust and self-improve by learning from a user's interaction with minimal human effort. METHODS: We have developed an online machine learning based information extraction system called IDEAL-X. With its graphical user interface, the system's data extraction engine automatically annotates values for users to review upon loading each report text. The system analyzes users' corrections regarding these annotations with online machine learning, and incrementally enhances and refines the learning model as reports are processed. The system also takes advantage of customized controlled vocabularies, which can be adaptively refined during the online learning process to further assist the data extraction. As the accuracy of automatic annotation improves overtime, the effort of human annotation is gradually reduced. After all reports are processed, a built-in query engine can be applied to conveniently define queries based on extracted structured data. RESULTS: We have evaluated the system with a dataset of anatomic pathology reports from 50 patients. Extracted data elements include demographical data, diagnosis, genetic marker, and procedure. The system achieves F-1 scores of around 95% for the majority of tests. CONCLUSIONS: Extracting data from pathology reports could enable more accurate knowledge to support biomedical research and clinical diagnosis. IDEAL-X provides a bridge that takes advantage of online machine learning based data extraction and the knowledge from human's feedback. By combining iterative online learning and adaptive controlled vocabularies, IDEAL-X can deliver highly adaptive and accurate data extraction to support patient search.

ASLForm: an adaptive self learning medical form generating system.

To facilitate the process of extracting information from narrative medical reports and transforming extracted data into standardized structured forms, we present an interactive, incrementally learning based information extraction system - ASLForm. ASLForm provides users a convenient interface that can be used as a simple data extraction and data entry system. It is unique, however, in its ability to transparently analyze and quickly learn, from users' interactions with a small number of reports, the desired values for the data fields. Additional user feedback (through acceptance decision or edits on the generated values) can incrementally refine the decision model in real-time, which further reduces users' interaction effort thereafter. The system eventually achieves high accuracy on data extraction with minimal effort from users. ASLForm requires no special configuration or training sets, and is not constrained to specific domains, thus it is easy to use and highly portable. Our experiments demonstrate the effectiveness of the system.

A novel mechanism is involved in cationic lipid-mediated functional siRNA delivery.

A key challenge for therapeutic application of RNA interference is to efficiently deliver synthetic small interfering RNAs (siRNAs) into target cells that will lead to the knockdown of the target transcript (functional siRNA delivery). To facilitate rational development of nonviral carriers, we have investigated by imaging, pharmacological and genetic approaches the mechanisms by which a cationic lipid carrier mediates siRNA delivery into mammalian cells. We show that approximately 95% of siRNA lipoplexes enter the cells through endocytosis and persist in endolysosomes for a prolonged period of time. However, inhibition of clathrin-, caveolin-, or lipid-raft-mediated endocytosis or macropinocytosis fails to inhibit the knockdown of the target transcript. In contrast, depletion of cholesterol from the plasma membrane has little effect on the cellular uptake of siRNA lipoplexes, but it abolishes the target transcript knockdown. Furthermore, functional siRNA delivery occurs within a few hours and is gradually inhibited by lowering temperatures. These results demonstrate that although endocytosis is responsible for the majority of cellular uptake of siRNA lipoplexes, a minor pathway, probably mediated by fusion between siRNA lipoplexes and the plasma membrane, is responsible for the functional siRNA delivery. Our findings suggest possible directions for improving functional siRNA delivery by cationic lipids.

Cytosolic delivery mediated via electrostatic surface binding of protein, virus, or siRNA cargos to pH-responsive core-shell gel particles.

We recently described a strategy for intracellular delivery of macromolecules, utilizing pH-responsive "core-shell" structured gel particles. These cross-linked hydrogel particles disrupt endosomes with low toxicity by virtue of physical sequestration of an endosome-disrupting "proton sponge" core inside a nontoxic hydrophilic shell. Here we tested the efficacy of this system for cytosolic delivery of a broad range of macromolecular cargos, and demonstrate the delivery of proteins, whole viral particles, or siRNA oligonucleotides into the cytosol of dendritic cells and epithelial cells via core-shell particles. We assessed the functional impact of particle delivery for vaccine applications and found that cytosolic delivery of protein antigens in dendritic cells via the core-shell particles promotes priming of CD8(+) T-cells at 100-fold lower doses than soluble protein. Functional gene knockdown following delivery of siRNA using the particles was demonstrated in epithelial cells. Based on these findings, these materials may be of interest for a broad range of biomedical applications.

Fine-grained record integration and linkage tool.

BACKGROUND: As part of the surveillance program to monitor the occurrence of birth defects in the metropolitan Atlanta area, we developed a record linkage software tool that provides latitude in the choice of linkage parameters, allows for efficient and accurate linkages, and enables objective assessments of the quality of the linked data. METHODS: We developed and implemented a Java-based fine-grained probabilistic record integration and linkage tool (FRIL) that incorporates a rich collection of record distance metrics, search methods, and analysis tools. Along its workflow, FRIL provides a rich set of user-tunable parameters augmented with graphic visualization tools to assist users in understanding the effects of parameter choices. We used this software tool to link data from vital records (n = 1.25 million) with birth defects surveillance records (n = 12,700) from the metropolitan Atlanta Congenital Defects Program (MACDP) for the birth years 1967-2006. RESULTS: Compared with the data linkage performed by conventional algorithms, the data linkage of birth certificates with birth defect records in MACDP using FRIL was more efficient. The linkage based on FRIL was also accurate, showing 99% precision and 95% recall. Based on positive user feedback, new features continue to be developed, and the tool is being adopted in several other data linkage projects in MACDP. CONCLUSIONS: A software tool that allows significant user interaction and control, such as FRIL, can provide accurate data linkages for birth defect surveillance programs and allows an objective assessment of the quality of linked data.

FRIL: A tool for comparative record linkage.

A fine-grained record integration and linkage tool (FRIL) is presented. The tool extends traditional record linkage tools with a richer set of parameters. Users may systematically and iteratively explore the optimal combination of parameter values to enhance linking performance and accuracy. Results of linking a birth defects monitoring program and birth certificate data using FRIL show 99% precision and 95% recall rates when compared to results obtained through handcrafted algorithms, and the process took significantly less time to complete. Experience and experimental result suggest that FRIL has the potential to increase the accuracy of data linkage across all studies involving record linkage. In particular, FRIL will enable researchers to assess objectively the quality of linked data.

Non-viral siRNA delivery to the lung.

SiRNAs exert their biological effect by guiding the degradation of their cognate mRNA sequence, thereby shutting down the corresponding protein production (gene silencing by RNA interference or RNAi). Due to this property, siRNAs are emerging as promising therapeutic agents for the treatment of inherited and acquired diseases, as well as research tools for the elucidation of gene function in both health and disease. Because of their lethality and prevalence, lung diseases have attracted particular attention as targets of siRNA-mediated cures. In addition, lung is accessible to therapeutic agents via multiple routes, e.g., through the nose and the mouth, thus obviating the need for targeting and making it an appealing target for RNAi-based therapeutic strategies. The clinical success of siRNA-mediated interventions critically depends upon the safety and efficacy of the delivery methods and agents. Delivery of siRNAs relevant to lung diseases has been attempted through multiple routes and using various carriers in animal models. This review focuses on the recent progress in non-viral delivery of siRNAs for the treatment of lung diseases, particularly infectious diseases. The rapid progress will put siRNA-based therapeutics on fast track to the clinic.

Identification of novel superior polycationic vectors for gene delivery by high-throughput synthesis and screening of a combinatorial library.

PURPOSE: Low efficiency and toxicity are two major drawbacks of current non-viral gene delivery vectors. Since DNA delivery to mammalian cells is a multi-step process, generating and searching combinatorial libraries of vectors employing high-throughput synthesis and screening methods is an attractive strategy for the development of new improved vectors because it increases the chance of identifying the most overall optimized vectors. MATERIALS AND METHODS: Based on the rationale that increasing the effective molecular weight of small PEIs, which are poor vectors compared to the higher molecular weight homologues but less toxic, raises their transfection efficiency due to better DNA binding, we synthesized a library of 144 biodegradable derivatives from two small PEIs and 24 bi- and oligo-acrylate esters. A 423-Da linear PEI and its 1:1 (w/w) mixture with a 1.8-kDa branched PEI were cross-linked with the acrylates at three molar ratios in DMSO. The resulting polymers were screened for their efficiency in delivering a beta-galactosidase expressing plasmid to COS-7 monkey kidney cells. Selected most potent polymers from the initial screen were tested for toxicity in A549 human lung cancer cells, and in vivo in a systemic gene delivery model in mice employing a firefly luciferase expressing plasmid. RESULTS: Several polycations that exhibited high potency and low toxicity in vitro were identified from the library. The most potent derivative of the linear 423-Da PEI was that cross-linked with tricycle-[5.2.1.0]-decane-dimethanol diacrylate (diacrylate 14), which exhibited an over 3,600-fold enhancement in efficiency over the parent. The most potent mixed PEI was that cross-linked with ethylene glycol diacrylate (diacrylate 4) which was over 850-fold more efficient than the physically mixed parent PEIs. The relative efficiencies of these polymers were even up to over twice as high as that of the linear 22-kDa PEI, considered the "gold standard" for in vitro and systemic gene delivery. The potent cross-linked polycations identified were also less toxic than the 22-kDa PEI. The optimal vector in vivo was the mixed PEI cross-linked with propylene glycol glycerolate diacrylate (diacrylate 7); it mediated the highest gene expression in the lungs, followed by the spleen, with the expression in the former being 53-fold higher compared to the latter. In contrast, the parent PEIs mediated no gene expression at all under similar conditions, and injection of the polyplexes of the 22-kDa PEI at its optimal N/P of 10 prepared under identical conditions killed half of the mice injected. CONCLUSIONS: High-throughput synthesis and transfection assay of a cross-linked library of biodegradable PEIs was proven effective in identifying highly transfecting vectors. The identified vectors exhibited dramatically superior efficiency compared to their parents both in vitro and in an in vivo systemic gene delivery model. The majority of these vectors mediated preferential gene delivery to the lung, and their in vivo toxicity paralleled that in vitro.

Cervical laminectomy: technique.

Spinal canal decompression via cervical laminectomy with or without foraminotomy is a mainstay of treatment of cervical spondylotic myelopathy and myeloradiculopathy. The goal of this surgery is to expand the cervical canal dorsally by removing the spinous processes, laminae, ligamentum flavum, and bony hypertrophy that are contributing to the canal stenosis. In selecting this particular approach to decompression, the surgeon must take into account the spinal geometry and the primary pathology of the patient: an "effective" cervical kyphosis is a contraindication to a dorsal approach, and spinal canal compromise secondary to ventral compression is best addressed through a ventral or a combined ventral and dorsal approach. This technique is technically facile and versatile in application. Complications with this procedure are relatively rare, with postoperative spinal instability being the primary concern. With proper patient selection and attention to surgical technique, laminectomy is a safe and effective approach to the management of cervical myelopathy in selected patients.

Polycation-mediated delivery of siRNAs for prophylaxis and treatment of influenza virus infection.

Influenza A virus causes one of the most prevalent infections in humans. In a typical year, 10-20% of the population of the US is infected by influenza virus, resulting in up to 40,000 deaths and 200,000 hospitalisations. Vaccination is the most effective preventative measure that can protect 70-90% of healthy adults aged < 65; however, the protection rate is much lower in those most susceptible to infection, namely infants, the elderly and individuals with weakened immune systems. Although four drugs have been approved by the FDA for use as prophylaxis and/or treatment of influenza, concerns about their side effects and the emergence of drug-resistant viruses persist. RNA interference (RNAi), an emerging method of post transcriptional gene silencing, appears ideal for the prevention and treatment of influenza. RNAi in mammals can be mediated by short interfering RNAs (siRNAs) of approximately 21-27 nucleotides in length. The authors have previously shown that siRNAs specific for conserved regions of the influenza virus genome are potent inhibitors of influenza virus replication in both cell lines and chicken embryos. This review discusses the recent progress in the in vivo inhibition of influenza virus by the delivery of siRNAs mediated by non-viral vectors, and the prospects of this strategy for prophylaxis and treatment of influenza infection in humans.

Full deacylation of polyethylenimine dramatically boosts its gene delivery efficiency and specificity to mouse lung.

High-molecular-mass polyethylenimines (PEIs) are widely used vectors for nucleic acid delivery. We found that removal of the residual N-acyl moieties from commercial linear 25-kDa PEI enhanced its plasmid DNA delivery efficiency 21 times in vitro, as well as 10,000 times in mice with a concomitant 1,500-fold enhancement in lung specificity. Several additional linear PEIs were synthesized by acid-catalyzed hydrolysis of poly(2-ethyl-2-oxazoline), yielding the pure polycations. PEI87 and PEI217 exhibited the highest efficiency in vitro: 115-fold and 6-fold above those of the commercial and deacylated PEI25s, respectively; moreover, PEI87 delivered DNA to mouse lung as efficiently as the pure PEI25 but at a lower concentration and with a 200-fold lung specificity. These improvements stem from an increase in the number of protonatable nitrogens, which presumably results in a tighter condensation of plasmid DNA and a better endosomal escape of the PEI/DNA complexes. As a validation of the potential of such linear, fully deacylated PEIs in gene therapy for lung diseases, systemic delivery in mice of the complexes of a short interfering RNA (siRNA) against a model gene, firefly luciferase, and PEI25 or PEI87 afforded a 77% and 93% suppression of the gene expression in the lungs, respectively. Furthermore, a polyplex of a siRNA against the influenza viral nucleocapsid protein gene and PEI87 resulted in a 94% drop of virus titers in the lungs of influenza-infected animals.

Cross-linked small polyethylenimines: while still nontoxic, deliver DNA efficiently to mammalian cells in vitro and in vivo.

PURPOSE: Polyethylenimine (PEI) is among the most efficient nonviral gene delivery vectors. Its efficiency and cytotoxicity depend on molecular weight, with the 25-kDa PEI being most efficient but cytotoxic. Smaller PEIs are noncytotoxic but less efficient. Enhancement in gene delivery efficiency with minimal cytotoxicity by cross-linking of small PEIs via potentially biodegradable linkages was explored herein. The hypothesis was that cross-linking would raise the polycation's effective molecular weight and hence the transfection efficiency, while biodegradable linkages would undergo the intracellular breakdown after DNA delivery and hence not lead to cytotoxicity. Toward this goal, we carried out cross-linking of branched 2-kDa PEI and its 1:1 (w/w) mixture with a linear 423-Da PEI via ester- and/or amide-bearing linkages; the in vitro and in vivo gene delivery efficiency, as well as toxicity to mammalian cells, of the resultant cross-linked polycations were investigated. METHODS: The efficiency of the cross-linked PEIs in delivering in vitro a plasmid containing beta-galactosidase gene and their cytotoxicity were investigated in monkey kidney cells (COS-7). Dynamic light scattering was used to compare the relative DNA condensation efficiency of the unmodified and cross-linked PEIs. In vivo gene delivery efficiency was evaluated by intratracheal delivery in mice of the complexes of a luciferase-encoding plasmid and the PEIs and estimating the luciferase expression in the lungs. RESULTS: Cross-linking boosted the gene delivery efficiency of the small PEIs by 40- to 550-fold in vitro; the efficiency of the most potent conjugates even exceeded by an order of magnitude that of the branched 25-kDa PEI. Effective condensation of DNA was evident from the fact that the mean diameter of the complexes of the cross-linked PEIs was some 300 nm with a narrow size distribution, while the complexes of the unmodified small PEIs exhibited a mean size of >700 nm with a very broad size distribution. At concentrations where the 25-kDa PEI resulted in >95% cell death, the conjugates afforded nearly full cell viability. The cross-linked PEIs were 17 to 80 times more efficient than the unmodified ones in vivo; furthermore, their efficiencies were up to twice that of the 25-kDa PEI. CONCLUSIONS: Cross-linking of small PEIs with judiciously designed amide- and ester-bearing linkers boosts their gene delivery efficiency both in vitro and in vivo without increasing the cytotoxicity. The high efficiency is dependent on the nature of the linkages and the PEIs used.

Poly(ethylene glycol) (PEG) enhances dynamic surface activity of a bovine lipid extract surfactant (BLES).

Shortage or malfunction of pulmonary surfactant in alveolar space leads to a critical condition termed respiratory distress syndrome (RDS). Surfactant replacement therapy, the major method to treat RDS, is an expensive treatment. In this paper, the effect of poly(ethylene glycol) (PEG) to improve dynamic surface activity of a bovine lipid extract surfactant (BLES) was studied by axisymmetric drop shape analysis (ADSA) and a captive bubble method. The activity of BLES+PEG mixtures was compared to that of a natural surfactant containing surfactant proteins A and D. When PEG was added into BLES mixtures, the surface tension hysteresis of BLES films was minimized when the films were compressed by more than 50%. PEG also helps to quickly restore surfactant films after film collapse. Thus, as far as surface tension effects go, the findings suggest that PEG might be used as a substitute for surfactant-associated protein SP-A in therapeutic surfactant products, and might also be used to reduce the amount of BLES required in clinical applications.

Poly(ethylene glycol) enhances the surface activity of a pulmonary surfactant.

The primary role of lung surfactant is to reduce surface tension at the air-liquid interface of alveoli during respiration. Axisymmetric drop shape analysis (ADSA) was used to study the effect of poly(ethylene glycol) (PEG) on the rate of surface film formation of a bovine lipid extract surfactant (BLES), a therapeutic lung surfactant preparation. PEG of molecular weights 3,350; 8,000; 10,000; 35,000; and 300,000 in combination with a BLES mixture of 0.5 mg/mL was studied. The adsorption rate of BLES alone at 0.5 mg/mL was much slower than that of a natural lung surfactant at the same concentration; more than 200 s are required to reach the equilibrium surface tension of 25 mJ/m(2). PEG, while not surface active itself, enhances the adsorption of BLES to an extent depending on its concentration and molecular weight. These findings suggest that depletion attraction induced by higher molecular weight PEG (in the range of 8,000 to 35,000) may be responsible for increasing the adsorption rate of BLES at low concentration. The results provide a basis for using PEG as an additive to BLES to reduce its required concentration in clinical treatment, thus reducing the cost for surfactant replacement therapy.

Constrained sessile drop as a new configuration to measure low surface tension in lung surfactant systems.

Existing methodology for surface tension measurements based on drop shapes suffers from the shortcoming that it is not capable to function at very low surface tension if the liquid dispersion is opaque, such as therapeutic lung surfactants at clinically relevant concentrations. The novel configuration proposed here removes the two big restrictions, i.e., the film leakage problem that is encountered with such methods as the pulsating bubble surfactometer as well as the pendant drop arrangement, and the problem of the opaqueness of the liquid, as in the original captive bubble arrangement. A sharp knife edge is the key design feature in the constrained sessile drop that avoids film leakage at low surface tension. The use of the constrained sessile drop configuration in conjunction with axisymmetric drop shape analysis to measure surface tension allows complete automation of the setup. Dynamic studies with lung surfactant can be performed readily by changing the volume of a sessile drop, and thus the surface area, by means of a motor-driven syringe. To illustrate the validity of using this configuration, experiments were performed using an exogenous lung surfactant preparation, bovine lipid extract surfactant (BLES) at 5.0 mg/ml. A comparison of results obtained for BLES at low concentration between the constrained sessile drop and captive bubble arrangement shows excellent agreement between the two approaches. When the surface area of the BLES film (0.5 mg/ml) was compressed by about the same amount in both systems, the minimum surface tensions attained were identical within the 95% confidence limits.