Effect of Mixer Type on Particle Coating by Magnesium Stearate for Friction and Adhesion Modification

Glidants and lubricants are often used to modify interparticle friction and adhesion in order to improve powder characteristics, such as flowability and compactability. Magnesium stearate (MgSt) powder is widely used as a lubricant. Shear straining causes MgSt particles to break, delaminate, and adhere to the surfaces of the host particles. In this work, a comparison is made of the effect of three mixer types on the lubricating role of MgSt particles. The flow behaviour of α-lactose monohydrate, coated with MgSt at different mass percentages of 0.2, 0.5, 1, and 5 is characterised. The mixing and coating process is carried out by dry blending using Turbula, ProCepT, and Mechanofusion. Measures have been taken to operate under equivalent mixing conditions, as reported in the literature. The flow resistance of the coated samples is measured using the FT4 rheometer. The results indicate that the flow characteristics of the processed powders are remarkably similar in the cases of samples treated by Turbula and Mechanofusion, despite extreme conditions of shear strain rate. The least flow resistance of samples is observed in the case of samples treated by the ProCepT mixer. High-velocity collisions of particles round off the sharp corners and edges, making them less resistant to flow. The optimal percentage of magnesium stearate is found to be approximately 1% by weight for all mixer types, as the addition of higher amounts of lubricant does not further improve the flowability of the material

Characterisation of gas-atomised metal powders used in binder jet 3D printing

A comprehensive characterisation study has been undertaken to examine the flowability and spreadability of two distinct types of gas-atomised metal powders used in Binder Jet 3D printing technology. The experimental characterisation encompasses an analysis of the physical properties of individual particles as well as the flow behaviour of bulk powder. The data gathered from individual particle analysis are subsequently employed in numerical simulations of roller spreading by Discrete Element Method (DEM) to gain valuable insights into the intricate interplay between powder attributes and its spreading characteristics. The findings reveal that employing bulk characterisation tests, such as shear cell tests and compressibility indices, results in contradictory outcomes. Moreover, the spreadability data derived from the DEM simulations do not exhibit a strong correlation with the results obtained from the characterisation of the bulk powder. These results underscore that the flowability of the powder may not necessarily serve as an accurate measure of its spreadability when applied in thin layers for additive manufacturing. This study further establishes a crucial connection between the intrinsic properties of individual particles and the collective behaviour of particles within the bulk material

Quenching and reactivation of electroluminescence by charge trapping and detrapping in Si-implanted silicon nitride thin film

In this brief, quenching of electroluminescence (EL) from Si-implanted silicon nitride (SNR) thin film under a forward bias has been observed. The quenching phenomenon is shown to be due to charge trapping in the defect states involved in the radiative recombination. The composite EL bands have different quenching rates, causing a change in the EL spectrum shape by the EL quenching. Release of the trapped charges by a low-temperature annealing at 120 °C or an application of a reverse gate bias can partially recover the quenched EL both in the intensity and spectrum shape. The quenching phenomenon poses a serious challenge to the application of Si-implanted SNR thin films in light-emitting devices. © 2009 IEEE.published_or_final_versio

Evolution of electroluminescence from multiple Si-implanted silicon nitride films with thermal annealing

Influence of thermal annealing on electroluminescence (EL) from multiple-Si-implanted silicon nitride films has been investigated. A reduced injection current and an enhanced EL intensity have been obtained simultaneously by increasing the annealing temperature, which results in a higher EL quantum efficiency. In addition, four emission bands are identified, and their peak energies, intensities, and full widths at half maxima are found to change with annealing temperature. A model is proposed to illustrate the carrier transport, the mechanisms of the four emission bands, and the evolution of the EL bands with annealing as well. The two major bands and the minor ultraviolet band are explained in terms of the recombination of the injected electrons in either the silicon dangling-bond (≡ Si 0) states or the nitride conduction band with the injected holes in either the band tail states above the nitride valence band or the valence band itself, while the minor near infrared band is attributed to the Si nanocrystals formed in the thin film. © 2009 American Institute of Physics.published_or_final_versio

A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets

Objective: Gastric cancer is a major gastrointestinal malignancy for which targeted therapies are emerging as treatment options. This study sought to identify the most prevalent molecular targets in gastric cancer and to elucidate systematic patterns of exclusivity and co-occurrence among these targets, through comprehensive genomic analysis of a large panel of gastric cancers. Design: Using high-resolution single nucleotide polymorphism arrays, copy number alterations were profiled in a panel of 233 gastric cancers (193 primary tumours, 40 cell lines) and 98 primary matched gastric non-malignant samples. For selected alterations, their impact on gene expression and clinical outcome were evaluated. Results: 22 recurrent focal alterations (13 amplifications and nine deletions) were identified. These included both known targets (FGFR2, ERBB2) and also novel genes in gastric cancer (KLF5, GATA6). Receptor tyrosine kinase (RTK)/RAS alterations were found to be frequent in gastric cancer. This study also demonstrates, for the first time, that these alterations occur in a mutually exclusive fashion, with KRAS gene amplifications highlighting a clinically relevant but previously underappreciated gastric cancer subgroup. FGFR2-amplified gastric cancers were also shown to be sensitive to dovitinib, an orally bioavailable FGFR/VEGFR targeting agent, potentially representing a subtype-specific therapy for FGFR2-amplified gastric cancers. Conclusion: The study demonstrates the existence of five distinct gastric cancer patient subgroups, defined by the signature genomic alterations FGFR2 (9% of tumours), KRAS (9%), EGFR (8%), ERBB2 (7%) and MET (4%). Collectively, these subgroups suggest that at least 37% of gastric cancer patients may be potentially treatable by RTK/RAS directed therapies

Low-dose pembrolizumab in the treatment of advanced non-small cell lung cancer

A dose of 200 mg 3-weekly of pembrolizumab was approved by the Food and Drug Administration (FDA) as treatment for advanced non-small cell lung cancer (NSCLC) without oncogenic drivers. This is despite evidence showing no difference in efficacy with 2 mg/kg. Our study aimed to assess the efficacy of a lower fixed dose of 100 mg, which is closer to 2 mg/kg weight-based dose in an average-sized Asian patient. All patients receiving pembrolizumab for advanced NSCLC from January 2016 to March 2020 in National University Hospital, Singapore, were included in this retrospective observational study. The effect of pembrolizumab 100 mg (Pem100) vs 200 mg (Pem200) upon survival outcomes, toxicity and cost were examined. One hundred fourteen patients received pembrolizumab. Sixty-five (57%) and 49 (43%) received Pem100 and Pem200, respectively. There was no difference in progression-free survival (PFS) and overall survival (OS) between Pem100 vs Pem200 as a single agent (PFS: 6.8 vs 4.2 months, hazard ratio [HR] 0.72, 95% confidence interval [CI] 0.36-1.46, P = .36; 9 month OS: 58% vs 63%, HR 1.08, 95% CI 0.48-2.41, P = .86) and when combined with chemotherapy (9-month PFS: 60% vs 50%, HR0.84, 95% CI 0.34-2.08, P = .71; 9-month OS: 85% vs 58%, HR 0.27, 95% CI 0.062-1.20, P = .09). No significant difference in response rate or ≥G3 immune-related toxicities between Pem100 and Pem200 was observed. A cost minimisation analysis evaluating the degree of cost savings related to drug costs estimated a within study cost saving of SGD4,290,912 and cost saving per patient of SGD39,942 in the Pem100 group. A 100 mg of pembrolizumab appears to be effective with reduction in cost. A randomised trial should be done to investigate a lower dose of pembrolizumab

Extracellular Matrix Aggregates from Differentiating Embryoid Bodies as a Scaffold to Support ESC Proliferation and Differentiation

Embryonic stem cells (ESCs) have emerged as potential cell sources for tissue engineering and regeneration owing to its virtually unlimited replicative capacity and the potential to differentiate into a variety of cell types. Current differentiation strategies primarily involve various growth factor/inducer/repressor concoctions with less emphasis on the substrate. Developing biomaterials to promote stem cell proliferation and differentiation could aid in the realization of this goal. Extracellular matrix (ECM) components are important physiological regulators, and can provide cues to direct ESC expansion and differentiation. ECM undergoes constant remodeling with surrounding cells to accommodate specific developmental event. In this study, using ESC derived aggregates called embryoid bodies (EB) as a model, we characterized the biological nature of ECM in EB after exposure to different treatments: spontaneously differentiated and retinoic acid treated (denoted as SPT and RA, respectively). Next, we extracted this treatment-specific ECM by detergent decellularization methods (Triton X-100, DOC and SDS are compared). The resulting EB ECM scaffolds were seeded with undifferentiated ESCs using a novel cell seeding strategy, and the behavior of ESCs was studied. Our results showed that the optimized protocol efficiently removes cells while retaining crucial ECM and biochemical components. Decellularized ECM from SPT EB gave rise to a more favorable microenvironment for promoting ESC attachment, proliferation, and early differentiation, compared to native EB and decellularized ECM from RA EB. These findings suggest that various treatment conditions allow the formulation of unique ESC-ECM derived scaffolds to enhance ESC bioactivities, including proliferation and differentiation for tissue regeneration applications. © 2013 Goh et al

Trees on networks: resolving statistical patterns of phylogenetic similarities among interacting proteins

<p>Abstract</p> <p>Background</p> <p>Phylogenies capture the evolutionary ancestry linking extant species. Correlations and similarities among a set of species are mediated by and need to be understood in terms of the phylogenic tree. In a similar way it has been argued that biological networks also induce correlations among sets of interacting genes or their protein products.</p> <p>Results</p> <p>We develop suitable statistical resampling schemes that can incorporate these two potential sources of correlation into a single inferential framework. To illustrate our approach we apply it to protein interaction data in yeast and investigate whether the phylogenetic trees of interacting proteins in a panel of yeast species are more similar than would be expected by chance.</p> <p>Conclusions</p> <p>While we find only negligible evidence for such increased levels of similarities, our statistical approach allows us to resolve the previously reported contradictory results on the levels of co-evolution induced by protein-protein interactions. We conclude with a discussion as to how we may employ the statistical framework developed here in further functional and evolutionary analyses of biological networks and systems.</p

Impact of routine PCV7 (Prevenar) vaccination of infants on the clinical and economic burden of pneumococcal disease in Malaysia

<p>Abstract</p> <p>Background</p> <p>Pneumococcal disease is the leading cause of vaccine-preventable death in children younger than 5 years of age worldwide. The World Health Organization recommends pneumococcal conjugate vaccine as a priority for inclusion into national childhood immunization programmes. Pneumococcal vaccine has yet to be included as part of the national vaccination programme in Malaysia although it has been available in the country since 2005. This study sought to estimate the disease burden of pneumococcal disease in Malaysia and to assess the cost effectiveness of routine infant vaccination with PCV7.</p> <p>Methods</p> <p>A decision model was adapted taking into consideration prevalence, disease burden, treatment costs and outcomes for pneumococcal disease severe enough to result in a hospital admission. Disease burden were estimated from the medical records of 6 hospitals. Where local data was unavailable, model inputs were obtained from international and regional studies and from focus group discussions. The model incorporated the effects of herd protection on the unvaccinated adult population.</p> <p>Results</p> <p>At current vaccine prices, PCV7 vaccination of 90% of a hypothetical 550,000 birth cohort would incur costs of RM 439.6 million (US$128 million). Over a 10 year time horizon, vaccination would reduce episodes of pneumococcal hospitalisation by 9,585 cases to 73,845 hospitalisations with cost savings of RM 37.5 million (US$10.9 million) to the health system with 11,422.5 life years saved at a cost effectiveness ratio of RM 35,196 (US$10,261) per life year gained.</p> <p>Conclusions</p> <p>PCV7 vaccination of infants is expected to be cost-effective for Malaysia with an incremental cost per life year gained of RM 35,196 (US$10,261). This is well below the WHO's threshold for cost effectiveness of public health interventions in Malaysia of RM 71,761 (US$20,922).</p

Predicting cancer involvement of genes from heterogeneous data

<p>Abstract</p> <p>Background</p> <p>Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data.</p> <p>Results</p> <p>We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature.</p> <p>Conclusion</p> <p>Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks. </p