Characterization of waste. State of the art document. Chromium VI specification in solid matrices

2003 ◽  
1997 ◽  
Vol 31 (10) ◽  
pp. 2898-2902 ◽  
Author(s):  
M. A. Olazabal ◽  
N. P. Nikolaidis ◽  
S. A. Suib ◽  
J. M. Madariaga
Keyword(s):  

2021 ◽  
Vol 14 (6) ◽  
pp. 498
Author(s):  
Evolène Deslignière ◽  
Anthony Ehkirch ◽  
Bastiaan L. Duivelshof ◽  
Hanna Toftevall ◽  
Jonathan Sjögren ◽  
...  

Antibody-drug conjugates (ADCs) are biotherapeutics consisting of a tumor-targeting monoclonal antibody (mAb) linked covalently to a cytotoxic drug. Early generation ADCs were predominantly obtained through non-selective conjugation methods based on lysine and cysteine residues, resulting in heterogeneous populations with varying drug-to-antibody ratios (DAR). Site-specific conjugation is one of the current challenges in ADC development, allowing for controlled conjugation and production of homogeneous ADCs. We report here the characterization of a site-specific DAR2 ADC generated with the GlyCLICK three-step process, which involves glycan-based enzymatic remodeling and click chemistry, using state-of-the-art native mass spectrometry (nMS) methods. The conjugation process was monitored with size exclusion chromatography coupled to nMS (SEC-nMS), which offered a straightforward identification and quantification of all reaction products, providing a direct snapshot of the ADC homogeneity. Benefits of SEC-nMS were further demonstrated for forced degradation studies, for which fragments generated upon thermal stress were clearly identified, with no deconjugation of the drug linker observed for the T-GlyGLICK-DM1 ADC. Lastly, innovative ion mobility-based collision-induced unfolding (CIU) approaches were used to assess the gas-phase behavior of compounds along the conjugation process, highlighting an increased resistance of the mAb against gas-phase unfolding upon drug conjugation. Altogether, these state-of-the-art nMS methods represent innovative approaches to investigate drug loading and distribution of last generation ADCs, their evolution during the bioconjugation process and their impact on gas-phase stabilities. We envision nMS and CIU methods to improve the conformational characterization of next generation-empowered mAb-derived products such as engineered nanobodies, bispecific ADCs or immunocytokines.


2018 ◽  
Author(s):  
Arghavan Bahadorinejad ◽  
Ivan Ivanov ◽  
Johanna W Lampe ◽  
Meredith AJ Hullar ◽  
Robert S Chapkin ◽  
...  

AbstractWe propose a Bayesian method for the classification of 16S rRNA metagenomic profiles of bacterial abundance, by introducing a Poisson-Dirichlet-Multinomial hierarchical model for the sequencing data, constructing a prior distribution from sample data, calculating the posterior distribution in closed form; and deriving an Optimal Bayesian Classifier (OBC). The proposed algorithm is compared to state-of-the-art classification methods for 16S rRNA metagenomic data, including Random Forests and the phylogeny-based Metaphyl algorithm, for varying sample size, classification difficulty, and dimensionality (number of OTUs), using both synthetic and real metagenomic data sets. The results demonstrate that the proposed OBC method, with either noninformative or constructed priors, is competitive or superior to the other methods. In particular, in the case where the ratio of sample size to dimensionality is small, it was observed that the proposed method can vastly outperform the others.Author summaryRecent studies have highlighted the interplay between host genetics, gut microbes, and colorectal tumor initiation/progression. The characterization of microbial communities using metagenomic profiling has therefore received renewed interest. In this paper, we propose a method for classification, i.e., prediction of different outcomes, based on 16S rRNA metagenomic data. The proposed method employs a Bayesian approach, which is suitable for data sets with small ration of number of available instances to the dimensionality. Results using both synthetic and real metagenomic data show that the proposed method can outperform other state-of-the-art metagenomic classification algorithms.


2011 ◽  
Vol 51 (1) ◽  
pp. 76-81 ◽  
Author(s):  
Mohammad Ilias ◽  
Iftekhar Md. Rafiqullah ◽  
Bejoy Chandra Debnath ◽  
Khanjada Shahnewaj Bin Mannan ◽  
Md. Mozammel Hoq

Author(s):  
Pablo Minguez ◽  
Joaquin Dopazo

Here the authors review the state of the art in the use of protein-protein interactions (ppis) within the context of the interpretation of genomic experiments. They report the available resources and methodologies used to create a curated compilation of ppis introducing a novel approach to filter interactions. Special attention is paid in the complexity of the topology of the networks formed by proteins (nodes) and pairwise interactions (edges). These networks can be studied using graph theory and a brief introduction to the characterization of biological networks and definitions of the more used network parameters is also given. Also a report on the available resources to perform different modes of functional profiling using ppi data is provided along with a discussion on the approaches that have typically been applied into this context. They also introduce a novel methodology for the evaluation of networks and some examples of its application.


Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1167 ◽  
Author(s):  
Mohammad H. Bhuiyan ◽  
Nicolaine Agofack ◽  
Kamila M. Gawel ◽  
Pierre R. Cerasi

In carbon storage activities, and in shale oil and gas extraction (SOGE) with carbon dioxide (CO2) as stimulation fluid, CO2 comes into contact with shale rock and its pore fluid. As a reactive fluid, the injected CO2 displays a large potential to modify the shale’s chemical, physical, and mechanical properties, which need to be well studied and documented. The state of the art on shale–CO2 interactions published in several review articles does not exhaust all aspects of these interactions, such as changes in the mechanical, petrophysical, or petrochemical properties of shales. This review paper presents a characterization of shale rocks and reviews their possible interaction mechanisms with different phases of CO2. The effects of these interactions on petrophysical, chemical and mechanical properties are highlighted. In addition, a novel experimental approach is presented, developed and used by our team to investigate mechanical properties by exposing shale to different saturation fluids under controlled temperatures and pressures, without modifying the test exposure conditions prior to mechanical and acoustic measurements. This paper also underlines the major knowledge gaps that need to be filled in order to improve the safety and efficiency of SOGE and CO2 storage.


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