20 research outputs found
Enhancing treatment success in inflammatory bowel disease: Optimising the use of anti-TNF agents and utilising their biosimilars in clinical practice.
Abstract Anti-tumour necrosis factor (TNF) agents such as infliximab and adalimumab have greatly altered the treatment landscape in inflammatory bowel disease (IBD). However, there are remaining unmet needs and opportunities to optimise their use. Recent data suggest that proactive therapeutic drug monitoring may lead to more efficient usage of these agents, with potential for higher rates of corticosteroid-free clinical remission than with reactive monitoring. Expanded application of faecal calprotectin measurements may also be valuable, given the ease of use of the assay and its proven effectiveness as a diagnostic tool and predictor of relapse risk. From a practical viewpoint, improved multidisciplinary working may be essential to optimise patient care, with IBD nurse specialists playing an increasingly central role within this model. Finally, the availability of biosimilars of the anti-TNF agents allow drug costs to be reduced without compromising safety or efficacy – thereby providing opportunities to improve accessibility. Alongside extensive data on originator to biosimilar infliximab switch, new studies are beginning to demonstrate the safety of biosimilar to biosimilar switch, as well as adalimumab biosimilar transitions. The risk of a nocebo effect when switching to a biosimilar can be reduced through improved patient education and preparation
anti tnf biosimilars in crohn s disease a patient centric interdisciplinary approach
ABSTRACTIntroduction: The purpose of this review is to highlight the role of biosimilars in early treatment in IBD and introduce ways to facilitate a patient-centric switching process through multi..
Erratum to: Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer
Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer
Copeptin with high-sensitivity troponin at presentation is not inferior to serial troponin measurements for ruling out acute myocardial infarction
Objective We aimed to compare the multi-marker strategy (copeptin and high-sensitivity cardiac troponin I [hs-cTnI]) with serial hs-cTnI measurements to rule out acute myocardial infarction (AMI) in patients with chest pain. Methods This prospective observational study was performed in a single emergency department. To test the non-inferiority margin of 4% in terms of negative predictive value (NPV) between the multi-marker strategy (0 hour) and serial hs-cTnI measurements (0 and 2 hours), 262 participants were required. Samples for copeptin and hs-cTnI assays were collected at presentation (0 hour) and after 2 hours. The measured biomarkers were considered abnormal when hs-cTnI was >26.2 ng/L and when copeptin was >10 pmol/L. Results AMI was diagnosed in 28 patients (10.7%). The NPV of the multi-marker strategy was 100% (160/160; 95% confidence interval [CI], 97.7% to 100%), which was not inferior to that of serial hs-cTnI measurements (201/201; 100%; 95% CI, 98.2% to 100%). The sensitivity, specificity, and positive predictive value of the multi-marker strategy were 100% (95% CI, 87.7% to 100%), 68.1% (95% CI, 61.7% to 74.0%), and 27.2% (95% CI, 18.9% to 36.8%), respectively. The sensitivity, specificity, and positive predictive value of serial hs-cTnI measurements were 100% (95% CI, 87.7% to 100%), 85.5% (95% CI, 80.4% to 89.8%), and 45.2% (95% CI, 32.5% to 58.3%), respectively. Conclusion The multi-marker strategy (copeptin and hs-cTnI measurement) was not inferior to serial hs-cTnI measurements in terms of NPV for AMI diagnosis, with a sensitivity and NPV of 100%. Copeptin may help in the early rule-out of AMI in patients with chest pain
Erratum to: Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer
Novel quantitative electroencephalogram feature image adapted for deep learning: Verification through classification of Alzheimer's disease dementia
Quantitative electroencephalography (QEEG) analysis is commonly adopted for the investigation of various neurological disorders, revealing electroencephalogram (EEG) features associated with specific dysfunctions. Conventionally, topographies are widely utilized for spatial representation of EEG characteristics at specific frequencies or frequency bands. However, multiple topographies at various frequency bands are required for a complete description of brain activity. In consequence, use of topographies for the training of deep learning algorithms is often challenging. The present study describes the development and application of a novel QEEG feature image that integrates all required spatial and spectral information within a single image, overcoming conventional obstacles. EEG powers recorded at 19 channels defined by the international 10-20 system were pre-processed using the EEG auto-analysis system iSyncBrain (R), removing the artifact components selected through independent component analysis (ICA) and rejecting bad epochs. Hereafter, spectral powers computed through fast Fourier transform (FFT) were standardized into Z-scores through iMediSync, Inc.'s age- and sex-specific normative database. The standardized spectral powers for each channel were subsequently rearranged and concatenated into a rectangular feature matrix, in accordance with their spatial location on the scalp surface. Application of various feature engineering techniques on the established feature matrix yielded multiple types of feature images. Such feature images were utilized in the deep learning classification of Alzheimer's disease dementia (ADD) and non-Alzheimer's disease dementia (NADD) data, in order to validate the use of our novel feature images. The resulting classification accuracy was 97.4%. The Classification criteria were further inferred through an explainable artificial intelligence (XAI) algorithm, which complied with the conventionally known EEG characteristics of AD. Such outstanding classification performance bolsters the potential of our novel QEEG feature images in broadening QEEG utility.Y
Aspect-Ratio Effect of Nanorod Compatibilizers in Conducting Polymer Blends
Nanoparticles
(NPs) at the interface between two different polymer
blends or fluid mixtures can function as compatibilizers, thereby
dramatically improving the interfacial properties of the blends or
the fluid mixtures. Their compatibilizing ability is strongly dependent
on their size, shape, and aspect ratios (ARs), which determines their
adsorption energy to the interface as well as their entropic penalty
when they are being strongly segregated at the interface. Herein,
we investigated the effect of the ARs of nanorod surfactants on the
conducting polymer blend of poly(triphenylamine) (PTPA) templated
by polystyrene (PS) colloids. The lengths of the polymer-coated CuPt
nanorods (CuPt NRs) were 5, 15, and 32 nm with a fixed width of 5
nm, thus producing three different AR values of 1, 3, and 6, respectively.
For quantitative analysis, the morphological and electrical behaviors
of the polymer blends were investigated in terms of the volume fraction
and AR of the NRs. The dramatic change in the morphological and electrical
properties of the blend film was observed for all three NR surfactants
at the NR volume fraction of approximately 1 vol %. Therefore, NR
surfactants with larger ARs had better compatibilizing power for a
given number of NRs in the blends. Also, they exhibited a stronger
tendency to be aligned parallel to the PS/PTPA interface. Also, we
demonstrated the successful use of the NR surfactants in the fabrication
of conducting polymer blend film that requires only minimal concentrations
of conducting polymers. To the best of our knowledge, this is the
first report of an experiment on the AR effect of NR compatibilizers
in polymer blends
Size-controlled polymer-coated nanoparticles as efficient compatibilizers for polymer blends
Polymer-coated gold nanoparticles (Au NPs)
with controlled size and surface chemistry were successfully
synthesized and applied to tailor the structures and properties
of polytriphenylamine (PTPA) and polystyrene (PS)
blends. Two different polymer-coated Au NPs with sizes of
5.9 nm (Au NP-1) and 20.7 nm (Au NP-2) were designed to
be thermally stable above 200 �C and neutral to both PS and
PTPA phases. Hence, both Au NPs localize at the PS/PTPA
interface and function as compatibilizers in the PS/PTPA
blend. To show the compatibilizing effect of the particles, the
morphological behaviors of PS/PTPA blends containing
different particle volume fractions (ϕp) of Au NPs were observed using cross-sectional TEM, and for quantitative analysis,
the size distribution of PTPA droplets in the PS matrix was obtained for each sample. The number-average droplet diameter
(Dn) of the PTPA domain in the blend was dramatically reduced from 1.4 μmto 500 nm at a small ϕp of 1.0 vol % Au NP-1. The
same trend of decreasing Dn was also observed with the addition of larger Au NP-2, but a higher ϕp was required to obtain the
same amount of reduction in the PTPA droplet size. The ϕp required to fully cover the PS/PTPA interface as a packed
monolayer of Au NPs was calculated as 0.98 vol % for Au NP-1 and 3.38 vol % for Au NP-2, thus giving excellent agreement
with critical ϕp values for the saturation of the PTPA droplet diameter Dn. To demonstrate the effectiveness of Au NPs as
compatibilizers, polystyrene-b-poly(triphenylamine) (PS-b-PTPA) block copolymers were also synthesized and used as
compatibilizers in the PS/PTPA blend. The decrease in Dn with the addition of PS-b-PTPA was always smaller than that with
addition of Au NP-1 at the same ϕp, indicating that Au NPs are more effective compatibilizers. This different behavior can be
attributed to the presence of PS-b-PTPA compatibilizers as micelles or free chains in the homopolymer matrix. In contrast,
most Au NPs were strongly adsorbed to the PS/PTPA interface