The use of plant in vitro (bio)technologies offers an attractive alternative for the production of plant-based active ingredients. Plant cells are small factories able to synthesize an exceptional variety of commercially important phytochemicals used as flavors, dyes, pharmaceuticals, nutraceuticals, cosmeceuticals, etc. Conventional plant propagation techniques are subjected to variety of pests, environmental challenges and poor management practices that adversely affect the quality and yield of these valuable phytochemicals. Plant in vitro culture platform offers considerable advantages and advancements over conventional phytochemical production techniques. However, during culture development, the yield of metabolites is generally low due to poor understanding of various factors that affect the biosynthetic pathway. Therefore, various strategies have been developed and reported to enhance biosynthesis of these phytochemicals in plant cell cultures. The recent emergence of omics technologies, molecular biology, metabolic engineering and synthetic biology has revolutionized diverse fields in life sciences. These modern aspects of life sciences have considerably influencing plant in vitro technology and phytochemical production. An application of these technologies is expanding horizons for an understanding of metabolic pathways involved in the biosynthesis of valuable biologically active ingredients and their cost-efficient production.
On behalf of the journal Biomolecules (https://www.mdpi.com/journal/biomolecules), we introduce the discussion group “Intrinsically Disordered Proteins and the Janus Challenge”.
To gain insight into the role of proteins in the origin of life on Earth, two leading experts in the field of intrinsically disordered proteins (IDPs) and the current Editors-in-Chief of the journal Biomolecules, Dr. Prakash Kulkarni and Dr. Vladimir N. Uversky, presented the Janus Challenge. This challenge consists in identifying an IDP, naturally occurring or synthetic, that has catalytic activity. Meeting this challenge may not only shed new light and even provide an alternative to the RNA world hypothesis, but may also serve as an impetus for technological advances with important biomedical applications.
A more comprehensive description of the Janus Challenge was published as an Editorial in the journal Biomolecules: https://www.mdpi.com/2218-273X/8/4/179
In order to support the Janus Challenge and improve the communication within the IDP community, we have opened this discussion group. Herewith, we aim to set in motion a debate in which every scientist can share their interesting ideas and points of views regarding the science behind the Janus Challenge.
Following a request for Special Issue topics for the novel AI Journal (https://www.mdpi.com/journal/ai), three ideas emerged and are herein offered to the community for discussion.
The first of those is deemed to capture AI applications to Structural Engineering.
Possible contributions span AI assisted conceptual design of structures until monitoring along structural life. Those include, but are not limited to, AI applications on design methods, safety checking, resistance prediction, data-driven design, design optimization, form finding, developing Structural Health Monitoring towards predictive maintenance in structural systems and assessment of structures and project reviewing.
Focus has been set on Artificial Intelligence applications to classical engineering fields, some of those regarded as latecomers in AI mass applications, but all with an immense potential for development and widespread uses.
This request aims to foster discussion on this topic, as well as finding valuable researchers and practitioners willing to contribute to the possible Special Issue.
Thank you for your interest.
The second of those is deemed to capture AI applications to Civil Engineering and the Construction Industry.
Possible contributions include, but are not limited to, AI applications on manufacture control, real-time work assessment and re-scheduling, optimization, economic aspects of construction, using Building Information Models for data analysis, buildings energy and environment management and predictive maintenance in buildings.
The third of those is deemed to capture AI applications to the Oil and Gas Industry. Going through a Digital Transformation impetus, O&G industry use of AI goes far beyond the classical oil barrel price forecasting.
Exciting new applications of Data Analytics, Machine Learning, Predictive Maintenance or Blockchain are fuelling changes, not only in digital oilfields but also in industry’s whole business models.
This request aims to foster discussion on this topic, as well as finding valuable researchers and practitioners willing to contribute (including with price forecasting works) to the possible Special Issue.