scholarly journals Virtual Cocrystal Screening Methods as Tools to Understand the Formation of Pharmaceutical Cocrystals—A Case Study of Linezolid, a Wide-Range Antibacterial Drug

2021 ◽  
Vol 21 (4) ◽  
pp. 2301-2314
Author(s):  
Mehrnaz Khalaji ◽  
Marek J. Potrzebowski ◽  
Marta K. Dudek
Keyword(s):  
Screening Methods ◽  
Antibacterial Drug ◽  
Pharmaceutical Cocrystals ◽  
Wide Range ◽  
Cocrystal Screening

scholarly journals Evolution of Antibacterial Drug Screening Methods: Current Prospects for Mycobacteria

2021 ◽  
Vol 9 (12) ◽  
pp. 2562
Author(s):  
Clara M. Bento ◽  
Maria Salomé Gomes ◽  
Tânia Silva
Keyword(s):  
Rapid Development ◽  
Drug Susceptibility Testing ◽  
New Drugs ◽  
Host Cells ◽  
Screening Methods ◽  
Antibacterial Drug ◽  
Efficient Treatment ◽  
Wide Range

The increasing resistance of infectious agents to available drugs urges the continuous and rapid development of new and more efficient treatment options. This process, in turn, requires accurate and high-throughput techniques for antimicrobials’ testing. Conventional methods of drug susceptibility testing (DST) are reliable and standardized by competent entities and have been thoroughly applied to a wide range of microorganisms. However, they require much manual work and time, especially in the case of slow-growing organisms, such as mycobacteria. Aiming at a better prediction of the clinical efficacy of new drugs, in vitro infection models have evolved to closely mimic the environment that microorganisms experience inside the host. Automated methods allow in vitro DST on a big scale, and they can integrate models that recreate the interactions that the bacteria establish with host cells in vivo. Nonetheless, they are expensive and require a high level of expertise, which makes them still not applicable to routine laboratory work. In this review, we discuss conventional DST methods and how they should be used as a first screen to select active compounds. We also highlight their limitations and how they can be overcome by more complex and sophisticated in vitro models that reflect the dynamics present in the host during infection. Special attention is given to mycobacteria, which are simultaneously difficult to treat and especially challenging to study in the context of DST.

Evaluation on Cocrystal Screening Methods and Synthesis of Multicomponent Crystals: A Case Study

2021 ◽  
Author(s):  
Di Wu ◽  
Bei Zhang ◽  
Qichao Yao ◽  
Baohong Hou ◽  
Lina Zhou ◽  
...  
Keyword(s):  
Screening Methods ◽  
Cocrystal Screening

Site specific agricultural soil management with the use of new technologies

2013 ◽  
Vol 16 (1) ◽  
pp. 59-67
Keyword(s):  
New Technologies ◽  
Digital Interface ◽  
Appropriate Treatment ◽  
Wide Range ◽  
Soil Variation ◽  
Soil Information ◽  
Remote Sensing Techniques ◽  
Agricultural Areas

<p>The Soil Science Institute of Thessaloniki produces new digitized Soil Maps that provide a useful electronic database for the spatial representation of the soil variation within a region, based on in situ soil sampling, laboratory analyses, GIS techniques and plant nutrition mathematical models, coupled with the local land cadastre. The novelty of these studies is that local agronomists have immediate access to a wide range of soil information by clicking on a field parcel shown in this digital interface and, therefore, can suggest an appropriate treatment (e.g. liming, manure incorporation, desalination, application of proper type and quantity of fertilizer) depending on the field conditions and cultivated crops. A specific case study is presented in the current work with regards to the construction of the digitized Soil Map of the regional unit of Kastoria. The potential of this map can easily be realized by the fact that the mapping of the physicochemical properties of the soils in this region provided delineation zones for differential fertilization management. An experiment was also conducted using remote sensing techniques for the enhancement of the fertilization advisory software database, which is a component of the digitized map, and the optimization of nitrogen management in agricultural areas.</p>

Oxford Studies in Ancient Philosophy, Volume 55

2018 ◽  
Keyword(s):  
Middle Ages ◽  
Ancient Philosophy ◽  
Recent Book ◽  
Loss Of Control ◽  
Ancient Greek ◽  
Original Essays ◽  
Constant Change ◽  
Wide Range ◽  
Metaphysical Principle

Oxford Studies in Ancient Philosophy provides, twice each year, a collection of the best current work in the field of ancient philosophy. Each volume features original essays that contribute to an understanding of a wide range of themes and problems in all periods of ancient Greek and Roman philosophy, from the beginnings to the threshold of the Middle Ages. From its first volume in 1983, OSAP has been a highly influential venue for work in the field, and has often featured essays of substantial length as well as critical essays on books of distinctive importance. Volume LV contains: a methodological examination on how the evidence for Presocratic thought is shaped through its reception by later thinkers, using discussions of a world soul as a case study; an article on Plato’s conception of flux and the way in which sensible particulars maintain a kind of continuity while undergoing constant change; a discussion of J. L. Austin’s unpublished lecture notes on Aristotle’s Nicomachean Ethics and his treatment of loss of control (akrasia); an article on the Stoics’ theory of time and in particular Chrysippus’ conception of the present and of events; and two articles on Plotinus, one that identifies a distinct argument to show that there is a single, ultimate metaphysical principle; and a review essay discussing E. K. Emilsson’s recent book, Plotinus.

scholarly journals Assessing the Relation between Mud Components and Rheology for Loss Circulation Prevention Using Polymeric Gels: A Machine Learning Approach

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1377
Author(s):  
Musaab I. Magzoub ◽  
Raj Kiran ◽  
Saeed Salehi ◽  
Ibnelwaleed A. Hussein ◽  
Mustafa S. Nasser
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Nearest Neighbor ◽  
Drilling Fluid ◽  
Gradient Boosting ◽  
K Nearest Neighbor ◽  
Wide Range ◽  
Machine Learning Approach ◽  
Drilling Operations

The traditional way to mitigate loss circulation in drilling operations is to use preventative and curative materials. However, it is difficult to quantify the amount of materials from every possible combination to produce customized rheological properties. In this study, machine learning (ML) is used to develop a framework to identify material composition for loss circulation applications based on the desired rheological characteristics. The relation between the rheological properties and the mud components for polyacrylamide/polyethyleneimine (PAM/PEI)-based mud is assessed experimentally. Four different ML algorithms were implemented to model the rheological data for various mud components at different concentrations and testing conditions. These four algorithms include (a) k-Nearest Neighbor, (b) Random Forest, (c) Gradient Boosting, and (d) AdaBoosting. The Gradient Boosting model showed the highest accuracy (91 and 74% for plastic and apparent viscosity, respectively), which can be further used for hydraulic calculations. Overall, the experimental study presented in this paper, together with the proposed ML-based framework, adds valuable information to the design of PAM/PEI-based mud. The ML models allowed a wide range of rheology assessments for various drilling fluid formulations with a mean accuracy of up to 91%. The case study has shown that with the appropriate combination of materials, reasonable rheological properties could be achieved to prevent loss circulation by managing the equivalent circulating density (ECD).

scholarly journals Using citizen science data to monitor the Sustainable Development Goals: a bottom-up analysis

2021 ◽  
Author(s):  
Laura Ballerini ◽  
Sylvia I. Bergh
Keyword(s):  
Sustainable Development ◽  
Citizen Science ◽  
Sustainable Development Goals ◽  
Comparative Case Study ◽  
Science Data ◽  
The Sustainable Development ◽  
Case Study Analysis ◽  
Wide Range ◽  
Development Goals

AbstractOfficial data are not sufficient for monitoring the United Nations Sustainable Development Goals (SDGs): they do not reach remote locations or marginalized populations and can be manipulated by governments. Citizen science data (CSD), defined as data that citizens voluntarily gather by employing a wide range of technologies and methodologies, could help to tackle these problems and ultimately improve SDG monitoring. However, the link between CSD and the SDGs is still understudied. This article aims to develop an empirical understanding of the CSD-SDG link by focusing on the perspective of projects which employ CSD. Specifically, the article presents primary and secondary qualitative data collected on 30 of these projects and an explorative comparative case study analysis. It finds that projects which use CSD recognize that the SDGs can provide a valuable framework and legitimacy, as well as attract funding, visibility, and partnerships. But, at the same time, the article reveals that these projects also encounter several barriers with respect to the SDGs: a widespread lack of knowledge of the goals, combined with frustration and political resistance towards the UN, may deter these projects from contributing their data to the SDG monitoring apparatus.

Sign in / Sign up

Export Citation Format

Share Document