scholarly journals Microscale to manufacturing scale‐up of cell‐free cytokine production—a new approach for shortening protein production development timelines

2011 ◽  
Vol 108 (7) ◽  
pp. 1570-1578 ◽  
Author(s):  
James F. Zawada ◽  
Gang Yin ◽  
Alexander R. Steiner ◽  
Junhao Yang ◽  
Alpana Naresh ◽  
...  
Keyword(s):  
Protein Production ◽  
Cytokine Production ◽  
Scale Up ◽  
New Approach ◽  
Production Development

Solid Lipid Nanoparticles: A Promising Drug Delivery Technology

2009 ◽  
Vol 2 (2) ◽  
pp. 509-516
Author(s):  
S. Pragati ◽  
S. Kuldeep ◽  
S. Ashok ◽  
M. Satheesh
Keyword(s):  
Drug Delivery ◽  
Solid Lipid Nanoparticles ◽  
Large Scale ◽  
Colloidal Particles ◽  
Scale Up ◽  
Lipid Nanoparticles ◽  
Scale Production ◽  
Research Activity ◽  
New Approach ◽  
Solid Lipid

One of the situations in the treatment of disease is the delivery of efficacious medication of appropriate concentration to the site of action in a controlled and continual manner. Nanoparticle represents an important particulate carrier system, developed accordingly. Nanoparticles are solid colloidal particles ranging in size from 1 to 1000 nm and composed of macromolecular material. Nanoparticles could be polymeric or lipidic (SLNs). Industry estimates suggest that approximately 40% of lipophilic drug candidates fail due to solubility and formulation stability issues, prompting significant research activity in advanced lipophile delivery technologies. Solid lipid nanoparticle technology represents a promising new approach to lipophile drug delivery. Solid lipid nanoparticles (SLNs) are important advancement in this area. The bioacceptable and biodegradable nature of SLNs makes them less toxic as compared to polymeric nanoparticles. Supplemented with small size which prolongs the circulation time in blood, feasible scale up for large scale production and absence of burst effect makes them interesting candidates for study. In this present review this new approach is discussed in terms of their preparation, advantages, characterization and special features.

Lesson Study to Scale Up Research-Based Knowledge: A Randomized, Controlled Trial of Fractions Learning

2017 ◽  
Vol 48 (3) ◽  
pp. 261-299 ◽  
Author(s):  
Catherine Lewis ◽  
Rebecca Perry
Keyword(s):  
Randomized Controlled Trial ◽  
Elementary Teachers ◽  
Teacher Leadership ◽  
Lesson Study ◽  
Controlled Trial ◽  
Scale Up ◽  
Linear Representation ◽  
The United States ◽  
New Approach ◽  
Randomized Controlled

An understanding of fractions eludes many U.S. students, and research-based knowledge about fractions, such as the utility of linear representation, has not broadly influenced instruction. This randomized trial of lesson study supported by mathematical resources assigned 39 educator teams across the United States to locally managed lesson study supported by a fractions lesson study resource kit or to 1 of 2 control conditions. Educators (87% of whom were elementary teachers) self-managed learning over a 3-month period. HLM analyses indicated significantly greater improvement of educators' and students' fractions knowledge for teams randomly assigned to lesson study with resource kits. Results suggest that integrating researchbased resources into lesson study offers a new approach to the problem of “scale-up” by combining the strengths of teacher leadership and research-based knowledge.

Cloning, expression and purification of human PDGF-BB gene in Escherichia coli: New approach in PDGF-BB protein production

Gene Reports ◽  
2020 ◽  
Vol 19 ◽  
pp. 100653
Author(s):  
Younes Ghasemi ◽  
Mohammad Bagher Ghoshoon ◽  
Mohammad Taheri ◽  
Manica Negahdaripour ◽  
Fatemeh Nouri
Keyword(s):  
Escherichia Coli ◽  
Protein Production ◽  
Expression And Purification ◽  
New Approach

scholarly journals Immunomodulatory Role of the Antimicrobial LL-37 Peptide in Autoimmune Diseases and Viral Infections

Vaccines ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 517 ◽  
Author(s):  
Bapi Pahar ◽  
Stefania Madonna ◽  
Arpita Das ◽  
Cristina Albanesi ◽  
Giampiero Girolomoni
Keyword(s):  
Lupus Erythematosus ◽  
Cytokine Production ◽  
Viral Infections ◽  
Normal Skin ◽  
Epidermal Keratinocytes ◽  
New Approach ◽  
Virus Dissemination ◽  
Monocytes And Macrophages ◽  
Progression Of Disease

Antimicrobial peptides (AMPs) are produced by neutrophils, monocytes, and macrophages, as well as epithelial cells, and are an essential component of innate immunity system against infection, including several viral infections. AMPs, in particular the cathelicidin LL-37, also exert numerous immunomodulatory activities by inducing cytokine production and attracting and regulating the activity of immune cells. AMPs are scarcely expressed in normal skin, but their expression increases when skin is injured by external factors, such as trauma, inflammation, or infection. LL-37 complexed to self-DNA acts as autoantigen in psoriasis and lupus erythematosus (LE), where it also induces production of interferon by plasmocytoid dendritic cells and thus initiates a cascade of autocrine and paracrine processes, leading to a disease state. In these disorders, epidermal keratinocytes express high amounts of AMPs, which can lead to uncontrolled inflammation. Similarly, LL-37 had several favorable and unfavorable roles in virus replication and disease pathogenesis. Targeting the antiviral and immunomodulatory functions of LL-37 opens a new approach to limit virus dissemination and the progression of disease.

scholarly journals Online Multikernel Learning Based on a Triple-Norm Regularizer for Semantic Image Classification

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Shuangping Huang ◽  
Lianwen Jin ◽  
Yunyu Li
Keyword(s):  
Scale Up ◽  
Model Complexity ◽  
New Approach ◽  
Online Mode ◽  
Kernel Weights ◽  
Hinge Loss ◽  
Fast Convergence Rate ◽  
Benchmark Datasets ◽  
Primal Dual ◽  
Kernel Combination

Currently image classifiers based on multikernel learning (MKL) mostly use batch approach, which is slow and difficult to scale up for large datasets. In the meantime, standard MKL model neglects the correlations among examples associated with a specific kernel, which makes it infeasible to adjust the kernel combination coefficients. To address these issues, a new and efficient multikernel multiclass algorithm called TripleReg-MKL is proposed in this work. Taking the principle of strong convex optimization into consideration, we propose a new triple-norm regularizer (TripleReg) to constrain the empirical loss objective function, which exploits the correlations among examples to tune the kernel weights. It highlights the application of multivariate hinge loss and a conservative updating strategy to filter noisy samples, thereby reducing the model complexity. This novel MKL formulation is then solved in an online mode using a primal-dual framework. A theoretical analysis of the complexity and convergence of TripleReg-MKL is presented. It shows that the new algorithm has a complexity ofOCMTand achieves a fast convergence rate ofOlogT/T. Extensive experiments on four benchmark datasets demonstrate the effectiveness and robustness of this new approach.

Global trends in antimicrobial resistance in animals in low- and middle-income countries

Science ◽  
2019 ◽  
Vol 365 (6459) ◽  
pp. eaaw1944 ◽  
Author(s):  
Thomas P. Van Boeckel ◽  
João Pires ◽  
Reshma Silvester ◽  
Cheng Zhao ◽  
Julia Song ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Large Scale ◽  
Protein Production ◽  
Animal Health ◽  
Scale Up ◽  
Global Scale ◽  
Animal Protein ◽  
Middle Income ◽  
Global Trends ◽  
Middle Income Countries

The global scale-up in demand for animal protein is the most notable dietary trend of our time. Antimicrobial consumption in animals is threefold that of humans and has enabled large-scale animal protein production. The consequences for the development of antimicrobial resistance in animals have received comparatively less attention than in humans. We analyzed 901 point prevalence surveys of pathogens in developing countries to map resistance in animals. China and India represented the largest hotspots of resistance, with new hotspots emerging in Brazil and Kenya. From 2000 to 2018, the proportion of antimicrobials showing resistance above 50% increased from 0.15 to 0.41 in chickens and from 0.13 to 0.34 in pigs. Escalating resistance in animals is anticipated to have important consequences for animal health and, eventually, for human health.

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