Comprehensive disease control (CDC): what does achieving CDC mean for patients with rheumatoid arthritis?

BACKGROUND: This study assessed the impact of simultaneous achievement of clinical, functional and structural efficacy, herein referred to as comprehensive disease control (CDC), on short-term and long-term work-related outcomes, health-related quality of life (HRQoL), pain and fatigue. METHODS: Data were pooled from three randomised trials of adalimumab plus methotrexate for treatment of early-stage or late-stage rheumatoid arthritis (RA). CDC was defined as 28-joint Disease Activity Score using C reactive protein <2.6, Health Assessment Questionnaire <0.5 and change from baseline in modified Total Sharp Score ≤0.5. Changes in scores at weeks 26 and 52 for work-related outcomes, Short Form 36 (SF-36) physical (PCS) and mental component scores (MCS), a Visual Analogue Scale measuring pain (VAS-Pain) and Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) were compared between patient groups defined by achievement of CDC at week 26 using linear regression with adjustment for baseline scores. RESULTS: Patients with RA who achieved CDC at week 26 (n=200) had significantly greater improvements in VAS-Pain (46.9 vs 26.9; p<0.0001), FACIT-F (13.3 vs 7.5; p<0.0001), SF-36 PCS (19.7 vs 8.9; p<0.0001) and SF-36 MCS (8.1 vs 5.0; p=0.0004) than those who did not (n=1267). Results were consistent at week 52 and among methotrexate-naive patients with early RA, methotrexate-experienced patients with late-stage RA and patients with inadequate response to methotrexate. CONCLUSIONS: Patients with RA who achieved CDC at week 26 had improved short-term and long-term HRQoL, pain, fatigue and work-related outcomes compared with patients who do not. These results demonstrate that the joint achievement of all CDC components provides meaningful benefits to patients. TRIAL REGISTRATION NUMBERS: DE019: NCT00195702, PREMIER: NCT00195702, OPTIMA: NCT00195702

Plasma Membrane Factor XIIIA Transglutaminase Activity Regulates Osteoblast Matrix Secretion and Deposition by Affecting Microtubule Dynamics

Transglutaminase activity, arising potentially from transglutaminase 2 (TG2) and Factor XIIIA (FXIIIA), has been linked to osteoblast differentiation where it is required for type I collagen and fibronectin matrix deposition. In this study we have used an irreversible TG-inhibitor to ‘block –and-track’ enzyme(s) targeted during osteoblast differentiation. We show that the irreversible TG-inhibitor is highly potent in inhibiting osteoblast differentiation and mineralization and reduces secretion of both fibronectin and type I collagen and their release from the cell surface. Tracking of the dansyl probe by Western blotting and immunofluorescence microscopy demonstrated that the inhibitor targets plasma membrane-associated FXIIIA. TG2 appears not to contribute to crosslinking activity on the osteoblast surface. Inhibition of FXIIIA with NC9 resulted in defective secretory vesicle delivery to the plasma membrane which was attributable to a disorganized microtubule network and decreased microtubule association with the plasma membrane. NC9 inhibition of FXIIIA resulted in destabilization of microtubules as assessed by cellular Glu-tubulin levels. Furthermore, NC9 blocked modification of Glu-tubulin into 150 kDa high-molecular weight Glu-tubulin form which was specifically localized to the plasma membrane. FXIIIA enzyme and its crosslinking activity were colocalized with plasma membrane-associated tubulin, and thus, it appears that FXIIIA crosslinking activity is directed towards stabilizing the interaction of microtubules with the plasma membrane. Our work provides the first mechanistic cues as to how transglutaminase activity could affect protein secretion and matrix deposition in osteoblasts and suggests a novel function for plasma membrane FXIIIA in microtubule dynamics

Artificial Intelligence Based Control Power Optimization on Tailless Aircraft

Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process

Shortening harvest interval, reaping benefits? A study on harvest practices in oil palm smallholder farming systems in Indonesia

CONTEXT: Smallholders are responsible for a large share of global palm oil production. Yet, in Indonesia, the main palm oil producing country, smallholders’ yields remain low. Better management practices, including short harvest interval (HI, the number of days between two harvest rounds), could help to raise smallholder yields. However, at present, HI is long in smallholder fields and the drivers underlying this phenomenon are poorly understood. OBJECTIVE: We explored agronomic, socio-economic, and institutional factors that underlie harvesting practices in independent oil palm smallholder farming systems in Indonesia to assess scope for sustainable intensification through shorter HI and reduced harvest losses. METHODS: Combining methods from agronomy and anthropology, we followed harvest interval of 950 farmers in six representative locations across Indonesia via farmer diaries over a period of two years to establish a correlation with yield. To quantify this relationship, we conducted post-harvest field measurements, and to explain which underlying factors impact HI we did qualitative interviews and surveys. RESULTS AND CONCLUSIONS: The HI of smallholders in our study ranged from 10 to 39 days (average: 17-d). Half of the farmers followed long HI (\u3e16-d). Key factors impacting HI include annual fresh fruit bunch (FFB) yield, total palm area per farmer, trusted labor availability, plantation accessibility, and FFB price. Farmers responded to low yield by prolonging HI to increase labor productivity and optimize labor and transportation costs. SIGNIFICANCE: This study contributes to a better understanding of the relation between HI and yield in smallholder farming systems, by uncovering how socio-economic and institutional factors sometimes override agronomic considerations. Long HI can potentially lead to harvest loss from loose fruits and missed bunches, and reduce oil quality from overripe bunches. However, to obtain the benefits of shorter HI requires collective action and incentives along the supply chain to streamline the harvest and sale process

COP27 Climate Change Conference: urgent action needed for Africa and the world

No abstract

Photocatalytic behavior of Ba(Sb/Ta)2O6 perovskite for reduction of organic pollutants: Experimental and DFT correlation

We have synthesized closely packed hexagonal 2D plates and clustered nanoparticle morphologies of Ba(Sb/Ta)2O6 (BSTO) perovskite via the polymerizable complex method for photocatalytic dye degradation activities. The BSTO crystallized in a hexagonal structure. The presence of Ba2+, Sb5+, Ta5+, and O2− chemical states identified from XPS confirmed the formation of mixed Ba(Sb/Ta)2O6 phase accompanied with a minor amount of TaOx. Furthermore, BSTO showed excellent photocatalytic activity for the degradation of various organic dyes. The kinetic studies revealed 65.9%, 77.3%, 89.8%, and 84.2%, of Crystal Violet (CV), Methylene Blue (MB), Rhodamine blue (RhB), and Methylene Orange (MO), respectively, after irradiation of 180 min without using a cocatalyst. The formation of and OH−surface radicals, which are believed to facilitate the degradation of the dyes, are unveiled through first-principles Density Functional Theory (DFT) calculations and scavenging studies. Our results suggest that BSTO holds promise as an excellent photocatalyst with better degradation efficiency for various organic dyes

A Robust Digital Image Watermarking Using Dwt -Pca

A comprehensive approach for watermarking is introduced in this system, and a hybrid digital watermarking scheme based on Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA) is used. There are some watermarking techniques like DCT, DWT, and DWT-SVD, but there is disadvantage in the watermarking to withstand attacks. Hence the new digital image watermarking algorithm is proposed which provide robust watermarking with minimal amount of distortion in case of attacks. DWT offers scalability and PCA helps in reducing correlation among the wavelet coefficients obtained from wavelet decomposition of each block thereby dispersing the watermark bits into the uncorrelated coefficient. Peak signal ratio is used to measure invisibility whereas similarity between two images by normalized correlation coefficient test the transparency and robustness against various attacks like cropping, noise, rotation, filtering etc. The proposedsystem should provide recoverable watermark without any reasonable amount of distortion even in case of attacks

Analysisof Biomedical Image Using Wavelet Transform

Image fusion can be defined as the process by which several images or some of their features are combined together to form a fused image. Its aim is to combine maximum information from multiple images of the same scene such that the obtained new image is more suitable for human visual and machine perception or further image processing and analysis tasks. The fusion of images acquired from dissimilar modalities or instrument has been successfully used for remote sensing images. The biomedical image fusion plays an important role in analysis towards clinical application which can support more accurate information for physician to diagnose different diseases