抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

https://dc.engconfintl.org/cgi/viewcontent.cgi?article=1032&context=superalloys_ii

A critical review of high entropy alloys and related concepts

I read this book the same weekend that the Packers took on the Rams, and the experience of the latter event, obviously, colored my judgment. Although I abhor anything that smacks of being a handbook (like, \"How to Earn a Merit Badge in Neurosurgery\") because too many volumes in biomedical science already evince a boyscout-like approach, I must confess that parts of this volume are fast, scholarly, and significant, with certain reservations. I like parts of this well-illustrated book because Dr. Sj6strand, without so stating, develops certain subjects on technique in relation to the acquisition of judgment and sophistication. And this is important! So, given that the author (like all of us) is somewhat deficient in some areas, and biased in others, the book is still valuable if the uninitiated reader swallows it in a general fashion, realizing full well that what will be required from the reader is a modulation to fit his vision, propreception, adaptation and response, and the kind of problem he is undertaking. A major deficiency of this book is revealed by comparison of its use of physics and of chemistry to provide understanding and background for the application of high resolution electron microscopy to problems in biology. Since the volume is keyed to high resolution electron microscopy, which is a sophisticated form of structural analysis, but really morphology in a modern guise, the physical and mechanical background of The instrument and its ancillary tools are simply and well presented. The potential use of chemical or cytochemical information as it relates to biological fine structure , however, is quite deficient. I wonder when even sophisticated morphol-ogists will consider fixation a reaction and not a technique; only then will the fundamentals become self-evident and predictable and this sine qua flon will become less mystical. Staining reactions (the most inadequate chapter) ought to be something more than a technique to selectively enhance contrast of morphological elements; it ought to give the structural addresses of some of the chemical residents of cell components. Is it pertinent that auto-radiography gets singled out for more complete coverage than other significant aspects of cytochemistry by a high resolution microscopist, when it has a built-in minimal error of 1,000 A in standard practice? I don't mean to blind-side (in strict football terminology) Dr. Sj6strand's efforts for what is \"routinely used in our laboratory\"; what is done is usually well done. It's just that …

Methods in Enzymology.

Configurational disorder can be compositionally engineered into mixed oxide by populating a single sublattice with many distinct cations. The formulations promote novel and entropy-stabilized forms of crystalline matter where metal cations are incorporated in new ways. Here, through rigorous experiments, a simple thermodynamic model, and a five-component oxide formulation, we demonstrate beyond reasonable doubt that entropy predominates the thermodynamic landscape, and drives a reversible solid-state transformation between a multiphase and single-phase state. In the latter, cation distributions are proven to be random and homogeneous. The findings validate the hypothesis that deliberate configurational disorder provides an orthogonal strategy to imagine and discover new phases of crystalline matter and untapped opportunities for property engineering.

/pdf/entropy-stabilized-oxides-5ohwbnqv93.pdf

Entropy-stabilized oxides

One of the most exciting tools that have entered the material science toolbox in recent years is machine learning. This collection of statistical methods has already proved to be capable of considerably speeding up both fundamental and applied research. At present, we are witnessing an explosion of works that develop and apply machine learning to solid-state systems. We provide a comprehensive overview and analysis of the most recent research in this topic. As a starting point, we introduce machine learning principles, algorithms, descriptors, and databases in materials science. We continue with the description of different machine learning approaches for the discovery of stable materials and the prediction of their crystal structure. Then we discuss research in numerous quantitative structure–property relationships and various approaches for the replacement of first-principle methods by machine learning. We review how active learning and surrogate-based optimization can be applied to improve the rational design process and related examples of applications. Two major questions are always the interpretability of and the physical understanding gained from machine learning models. We consider therefore the different facets of interpretability and their importance in materials science. Finally, we propose solutions and future research paths for various challenges in computational materials science.

/pdf/recent-advances-and-applications-of-machine-learning-in-55gs85xsws.pdf

Recent advances and applications of machine learning in solid-state materials science

Rational materials design based on prior knowledge is attractive because it promises to avoid time-consuming synthesis and testing of numerous materials candidates. However with the increase of complexity of materials, the scientific ability for the rational materials design becomes progressively limited. As a result of this complexity, combinatorial and high-throughput (CHT) experimentation in materials science has been recognized as a new scientific approach to generate new knowledge. This review demonstrates the broad applicability of CHT experimentation technologies in discovery and optimization of new materials. We discuss general principles of CHT materials screening, followed by the detailed discussion of high-throughput materials characterization approaches, advances in data analysis/mining, and new materials developments facilitated by CHT experimentation. We critically analyze results of materials development in the areas most impacted by the CHT approaches, such as catalysis, electronic and fun...

Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art

This work describes the first report of the use of an aminosilicone solvent mix for the capture of CO(2). To maintain a liquid state, a hydroxyether co-solvent was employed which allowed enhanced physisorption of CO(2) in the solvent mixture. Regeneration of the capture solvent system was demonstrated over 6 cycles and absorption isotherms indicate a 25-50 % increase in dynamic CO(2) capacity over 30 % MEA. In addition, proof of concept for continuous CO(2) absorption was verified. Additionally, modeling to predict heats of reaction of aminosilicone solvents with CO(2) was in good agreement with experimental results.

Aminosilicone Solvents for CO2 Capture

Methods and sensors for selective fluid sensing are provided. A gas dosimeter includes a housing configured with an opening to admit an analyte. The gas dosimeter also includes a multivariate sensor disposed in the housing. The sensor is configured to determine a concentration of the analyte over time. In addition, the multivariate sensor includes an irreversible sensing material. Electrical properties of the irreversible sensing material are configured to change irreversibly upon exposure to the analyte.

Sensors for gas dosimetry

Combinatorial and High‐Throughput Screening of Materials Libraries: Review of State of the Art

The novel concept of using a molecule possessing both physi-sorbing and chemi-sorbing properties for post-combustion CO2 capture was explored and mixtures of aminosilicones and hydroxyterminated polyethers had the best performance characteristics of materials examined. The optimal solvent composition was a 60/40 blend of GAP-1/TEG and a continuous bench-top absorption/desorption unit was constructed and operated. Plant and process models were developed for this new system based on an existing coal-fired power plant and data from the laboratory experiments were used to calculate an overall COE for a coal-fired power plant fitted with this capture technology. A reduction in energy penalty, from 30% to 18%, versus an optimized 30% MEA capture system was calculated with a concomitant COE decrease from 73% to 41% for the new aminosilicone solvent system.

/pdf/novel-high-capacity-oligomers-for-low-cost-co2-capture-3xklepk6t5.pdf

Hubert Lam

Papers

Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art

Aminosilicone Solvents for CO2 Capture

Sensors for gas dosimetry

Combinatorial and High‐Throughput Screening of Materials Libraries: Review of State of the Art

Novel High Capacity Oligomers for Low Cost CO2 Capture