Carbon nanotube (CNT) reinforced (0.05–0.5% by wt) polycaprolactone (PCL)‐based composites were prepared by compression molding. Addition of 0.2% CNT caused a 131% improvement of tensile strength (TS) of PCL films. The tensile modulus (TM) and elongation at break (Eb) of PCL were also significantly improved with the addition of CNT. The water vapor permeability of PCL was 1.51 g·mm/m2·day but 0.2% CNT containing PCL films showed 1.08 g·mm/m2·day. Similarly, the oxygen transmission rate (OTR) of PCL films was found to decrease with the addition of CNT. But, carbon dioxide transmission rate (CO2TR) of PCL film was improved due to incorporation of CNT. Effect of gamma radiation on PCL films and CNT reinforced PCL‐based composites were also studied. The TS of the irradiated (10 kGy) PCL films gained to 75% higher than control sample. The TS of the 0.2% CNT reinforced composite film was reached to 41 MPa at 15 kGy dose. The barrier properties of non‐irradiated and irradiated (10 kGy) PCL films and composites (0.2% CNT reinforced) were also measured. Both PCL films and composites showed lower values of WVP upon irradiation and indicated better water vapor barrier. The OTR and CO2TR of the irradiated (10 kGy) PCL films and composites were decreased compared to their counterparts. Surface and interface morphologies of the composites were studied by scanning electron microscopy. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013

Objective To develop a new evidence‐based, pharmacologic treatment guideline for rheumatoid arthritis (RA). Methods We conducted systematic reviews to synthesize the evidence for the benefits and harms of various treatment options. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to rate the quality of evidence. We employed a group consensus process to grade the strength of recommendations (either strong or conditional). A strong recommendation indicates that clinicians are certain that the benefits of an intervention far outweigh the harms (or vice versa). A conditional recommendation denotes uncertainty over the balance of benefits and harms and/or more significant variability in patient values and preferences. Results The guideline covers the use of traditional disease‐modifying antirheumatic drugs (DMARDs), biologic agents, tofacitinib, and glucocorticoids in early (<6 months) and established (≥6 months) RA. In addition, it provides recommendations on using a treat‐to‐target approach, tapering and discontinuing medications, and the use of biologic agents and DMARDs in patients with hepatitis, congestive heart failure, malignancy, and serious infections. The guideline addresses the use of vaccines in patients starting/receiving DMARDs or biologic agents, screening for tuberculosis in patients starting/receiving biologic agents or tofacitinib, and laboratory monitoring for traditional DMARDs. The guideline includes 74 recommendations: 23% are strong and 77% are conditional. Conclusion This RA guideline should serve as a tool for clinicians and patients (our two target audiences) for pharmacologic treatment decisions in commonly encountered clinical situations. These recommendations are not prescriptive, and the treatment decisions should be made by physicians and patients through a shared decision‐making process taking into account patients’ values, preferences, and comorbidities. These recommendations should not be used to limit or deny access to therapies.

Objective To develop a new evidence‐based, pharmacologic treatment guideline for rheumatoid arthritis (RA). Methods We conducted systematic reviews to synthesize the evidence for the benefits and harms of various treatment options. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to rate the quality of evidence. We employed a group consensus process to grade the strength of recommendations (either strong or conditional). A strong recommendation indicates that clinicians are certain that the benefits of an intervention far outweigh the harms (or vice versa). A conditional recommendation denotes uncertainty over the balance of benefits and harms and/or more significant variability in patient values and preferences. Results The guideline covers the use of traditional disease‐modifying antirheumatic drugs (DMARDs), biologic agents, tofacitinib, and glucocorticoids in early (<6 months) and established (≥6 months) RA. In addition, it provides recommendations on using a treat‐to‐target approach, tapering and discontinuing medications, and the use of biologic agents and DMARDs in patients with hepatitis, congestive heart failure, malignancy, and serious infections. The guideline addresses the use of vaccines in patients starting/receiving DMARDs or biologic agents, screening for tuberculosis in patients starting/receiving biologic agents or tofacitinib, and laboratory monitoring for traditional DMARDs. The guideline includes 74 recommendations: 23% are strong and 77% are conditional. Conclusion This RA guideline should serve as a tool for clinicians and patients (our two target audiences) for pharmacologic treatment decisions in commonly encountered clinical situations. These recommendations are not prescriptive, and the treatment decisions should be made by physicians and patients through a shared decision‐making process taking into account patients’ values, preferences, and comorbidities. These recommendations should not be used to limit or deny access to therapies.

No abstract

BackgroundThe adaptive immune response in rheumatoid arthritis (RA) is influenced by an interaction between host genetics and environment, particularly the host microbiome. Association of the gut microbiota with various diseases has been reported, though the specific components of the microbiota that affect the host response leading to disease remain unknown. However, there is limited information on the role of gut microbiota in RA. In this study we aimed to define a microbial and metabolite profile that could predict disease status. In addition, we aimed to generate a humanized model of arthritis to confirm the RA-associated microbe.MethodsTo identify an RA biomarker profile, the 16S ribosomal DNA of fecal samples from RA patients, first-degree relatives (to rule out environment/background as confounding factors), and random healthy non-RA controls were sequenced. Analysis of metabolites and their association with specific taxa was performed to investigate a potential mechanistic link. The role of an RA-associated microbe was confirmed using a human epithelial cell line and a humanized mouse model of arthritis.ResultsPatients with RA exhibited decreased gut microbial diversity compared with controls, which correlated with disease duration and autoantibody levels. A taxon-level analysis suggested an expansion of rare taxa, Actinobacteria, with a decrease in abundant taxa in patients with RA compared with controls. Prediction models based on the random forests algorithm suggested that three genera, Collinsella, Eggerthella, and Faecalibacterium, segregated with RA. The abundance of Collinsella correlated strongly with high levels of alpha-aminoadipic acid and asparagine as well as production of the proinflammatory cytokine IL-17A. A role for Collinsella in altering gut permeability and disease severity was confirmed in experimental arthritis.ConclusionsThese observations suggest dysbiosis in RA patients resulting from the abundance of certain rare bacterial lineages. A correlation between the intestinal microbiota and metabolic signatures could determine a predictive profile for disease causation and progression.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-016-0299-7) contains supplementary material, which is available to authorized users.