6,301 research outputs found
A guide to designing photocontrol in proteins: methods, strategies and applications
Light is essential for various biochemical processes in all domains of life. In its presence certain proteins inside a cell are excited, which either stimulates or inhibits subsequent cellular processes. The artificial photocontrol of specifically proteins is of growing interest for the investigation of scientific questions on the organismal, cellular and molecular level as well as for the development of medicinal drugs or biocatalytic tools. For the targeted design of photocontrol in proteins, three major methods have been developed over the last decades, which employ either chemical engineering of small-molecule photosensitive effectors (photopharmacology), incorporation of photoactive non-canonical amino acids by genetic code expansion (photoxenoprotein engineering), or fusion with photoreactive biological modules (hybrid protein optogenetics). This review compares the different methods as well as their strategies and current applications for the light-regulation of proteins and provides background information useful for the implementation of each technique
Internationalisation dynamics in contemporary South American life sciences: the case of zebrafish
We tend to assume that science is inherently international. Geographical boundaries
are not a matter of concern in science, and when they do – e.g. due to the rise of
nationalist or populist movements – they are thought to constitute a threat to the
essence of the scientific enterprise; namely, the global mobility of ideas, knowledge
and researchers. Quite recently, we also started to consider that research could
become ‘more international’ under the assumption that in doing so it becomes better,
i.e. more collaborative, innovative, dynamic, and of greater quality. Such a positive
conceptualisation of internationalisation, however, rests on interpretations coming
almost exclusively from the Global North that systematically ignore power dynamics
in scientific practice and that regard scientific internationalisation as an unproblematic
transformative process and as a desired outcome.
In Science and Technology Studies (STS), social research on model
organisms is perhaps the clearest example of the influence of the dominant vision of
internationalisation. This body of literature tends to describe model organism science
and their research communities as uniform and harmonious international ecosystems
governed by a strong collaborative ethos of sharing specimens, knowledge and
resources. But beyond these unproblematic descriptions, how does
internationalisation actually transform research on life? To what extent do the power
dynamics of internationalisation intervene in contemporary practices of knowledge
production and diffusion in this field of research?
This thesis revisits the dynamics and practices of scientific internationalisation
in contemporary science from the perspective of South American life sciences. It takes
the zebrafish (Danio rerio), a small tropic freshwater fish, originally from the Ganges
region in India and quite popular in pet shops, as a case study of how complex
dynamics of internationalisation intervene in science. While zebrafish research has
experienced a remarkable growth in recent years at the global scale, in South America
its growth has been unprecedented, allowing average laboratories, which often
operate with small budgets and with less well-developed science infrastructures, to
conduct world-class research.
My approach is based on a consideration of internationalisation as a
conceptual model of change. I consider internationalisation to be a process essentially
marked by tensions in the spatial, cognitive and evaluative dimensions of scientific
practice. These tensions, I claim, are not just a key feature of internationalisation, but
also aspects of a conceptual opposition that is geared towards explaining how change
comes about in science. By studying the dynamics of internationalisation, I seek to
understand various transformations of zebrafish research: from its construction as a
research artefact to its diffusion across geographical boundaries. My focus on South
America, on the other hand, helps me to understand the complexity of such dynamics
beyond the lenses of the dominant discourse of internationalisation that prevails in
the STS literature on model organisms. I use mixed-methods (i.e. semi-structured
interviews, document analysis, bibliometrics and social network analysis) to observe
and interpret transformations of internationalisation at different scales and levels.
My analysis suggests first, that internationalisation played an important role in
the construction of the zebrafish as a model organism and that, in the infrastructures
and practices of resource exchange that sustain the scientific value of the organism
internationally, dynamics of asymmetry and empowerment problematise the
collaborative ethos of this community. Second, I found that collaborative networks –
measured through co-authorships – also played an important role in the diffusion of
zebrafish as a model organism in South America. However, I did not find a clear
indication of international dependency in the diffusion of zebrafish, explained by a
geographical concentration of scientific expertise in the zebrafish collaboration
network. Rather than exposing peripheral researchers to novel ideas, networks of
international collaboration seem to be more related to access to privileged material
infrastructures resulting from the social organisation of scientific labour worldwide.
Lastly, by examining practices of biological data curation and researchers’
international mobility trajectories, I describe how dynamics of internationalisation
shape the notion of research excellence in model organism science. In this case, I
found mobility trajectories to play a key role in boosting researchers’ contributions to
the community’s database, especially among researchers from peripheral
communities like South America. Overall, while these findings show the value of
considering internationalisation as a conceptual model of change in science, more
research is needed on the intervention of complex dynamics of internationalisation in
other cases and fields of research
The effects of ocean acidification on microbial nutrient cycling and productivity in coastal marine sediments
Ocean Acidification (OA), commonly referred to as the “other CO₂ problem,” illustrates the current rise in atmospheric carbon dioxide (CO₂) levels, precipitated in large by human-related activity (e.g., fossil fuel combustion and mass deforestation). The dissolution of atmospheric CO₂ into the surface of the ocean over time has reduced oceanic pH levels by 0.1 units since the start of the pre-industrial era and has resulted in wholesale shifts in seawater carbonate chemistry on a planetary scale. The chemical processes of ocean acidification are increasingly well documented, demonstrating clear rates of increase for global CO₂ emissions predicted by the IPCC (Intergovernmental Panel on Climate Change) under the business-as-usual CO₂ emissions scenario. The ecological impact of ocean acidification alters seawater chemical speciation and disrupts vital biogeochemical cycling processes for various chemicals and compounds. Whereby the unidentified potential fallout of this is the cascading effects on the microbial communities within the benthic sediments. These microorganisms drive the marine ecosystem through a network of vast biogeochemical cycling processes aiding in the moderation of ecosystem-wide primary productivity and fundamentally regulating the global climate. The benthic sediments are determinably one of the largest and most diverse ecosystems on the planet. Marine sediments are also conceivably one of the most productive in terms of microbial activity and nutrient flux between the water-sediment interface (i.e., boundary layer). The absorption and sequestering of CO₂ from the atmosphere have demonstrated significant impacts on various marine taxa and their associated ecological processes. This is commonly observed in the reduction in calcium carbonate saturation states in most shell-forming organisms (i.e., plankton, benthic mollusks, echinoderms, and Scleractinia corals). However, the response of benthic sediment microbial communities to a reduction in global ocean pH remains considerably less well characterized. As these microorganisms operate as the lifeblood of the marine ecosystem, understanding their response and physiological plasticity to increased levels of CO₂ is of critical importance when it comes to investigating regional and global implications for the effects of ocean acidification
Bayesian optimization with known experimental and design constraints for chemistry applications
Optimization strategies driven by machine learning, such as Bayesian
optimization, are being explored across experimental sciences as an efficient
alternative to traditional design of experiment. When combined with automated
laboratory hardware and high-performance computing, these strategies enable
next-generation platforms for autonomous experimentation. However, the
practical application of these approaches is hampered by a lack of flexible
software and algorithms tailored to the unique requirements of chemical
research. One such aspect is the pervasive presence of constraints in the
experimental conditions when optimizing chemical processes or protocols, and in
the chemical space that is accessible when designing functional molecules or
materials. Although many of these constraints are known a priori, they can be
interdependent, non-linear, and result in non-compact optimization domains. In
this work, we extend our experiment planning algorithms Phoenics and Gryffin
such that they can handle arbitrary known constraints via an intuitive and
flexible interface. We benchmark these extended algorithms on continuous and
discrete test functions with a diverse set of constraints, demonstrating their
flexibility and robustness. In addition, we illustrate their practical utility
in two simulated chemical research scenarios: the optimization of the synthesis
of o-xylenyl Buckminsterfullerene adducts under constrained flow conditions,
and the design of redox active molecules for flow batteries under synthetic
accessibility constraints. The tools developed constitute a simple, yet
versatile strategy to enable model-based optimization with known experimental
constraints, contributing to its applicability as a core component of
autonomous platforms for scientific discovery.Comment: 15 pages, 5 figures (SI with 13 pages, 8 figures
Systems Biology in ELIXIR: modelling in the spotlight
In this white paper, we describe the founding of a new ELIXIR Community - the Systems Biology Community - and its proposed future contributions to both ELIXIR and the broader community of systems biologists in Europe and worldwide. The Community believes that the infrastructure aspects of systems biology - databases, (modelling) tools and standards development, as well as training and access to cloud infrastructure - are not only appropriate components of the ELIXIR infrastructure, but will prove key components of ELIXIR\u27s future support of advanced biological applications and personalised medicine. By way of a series of meetings, the Community identified seven key areas for its future activities, reflecting both future needs and previous and current activities within ELIXIR Platforms and Communities. These are: overcoming barriers to the wider uptake of systems biology; linking new and existing data to systems biology models; interoperability of systems biology resources; further development and embedding of systems medicine; provisioning of modelling as a service; building and coordinating capacity building and training resources; and supporting industrial embedding of systems biology. A set of objectives for the Community has been identified under four main headline areas: Standardisation and Interoperability, Technology, Capacity Building and Training, and Industrial Embedding. These are grouped into short-term (3-year), mid-term (6-year) and long-term (10-year) objectives
Investigating modularity and transparency within bioinspired connectionist architectures using genetic and epigenetic models
Machine learning algorithms allow computers to deal with incomplete data in tasks such as speech recognition and object detection. Some machine learning algorithms take inspiration from biological systems due to useful properties such as robustness, allowing algorithms to be flexible and domain agnostic. This comes at a cost, resulting in difficulty when one attempts to understand the reasoning behind decisions. This is problematic when such models are applied in realworld situations where accountability, legality, and maintenance are of concern. Artificial gene regulatory networks (AGRNs) are a type of connectionist architecture inspired by gene regulatory mechanisms. AGRNs are of interest within this thesis due to their ability to solve tasks in chaotic dynamical systems despite their relatively small size.The overarching aim of this work was to investigate the properties of connectionist architectures to improve the transparency of their execution. Initially, the evolutionary process and internal structure of AGRNs were investigated. Following this, the creation of an external control layer used to improve the transparency of execution of an external connectionist architecture was attempted.When investigating the evolutionary process of AGRNs, pathways were found that when followed, produced more performant networks in a shorter time frame. Evidence that AGRNs are capable of performing well despite internal interference was found when investigating their modularity, where it was also discovered that they do not develop strict modularity consistently. A control layer inspired by epigenetics that selectively deactivates nodes in trained artificial neural networks (ANNs) was developed; the analysis of its behaviour provided an insight into the internal workings of the ANN
Collected Papers (on various scientific topics), Volume XIII
This thirteenth volume of Collected Papers is an eclectic tome of 88 papers in various fields of sciences, such as astronomy, biology, calculus, economics, education and administration, game theory, geometry, graph theory, information fusion, decision making, instantaneous physics, quantum physics, neutrosophic logic and set, non-Euclidean geometry, number theory, paradoxes, philosophy of science, scientific research methods, statistics, and others, structured in 17 chapters (Neutrosophic Theory and Applications; Neutrosophic Algebra; Fuzzy Soft Sets; Neutrosophic Sets; Hypersoft Sets; Neutrosophic Semigroups; Neutrosophic Graphs; Superhypergraphs; Plithogeny; Information Fusion; Statistics; Decision Making; Extenics; Instantaneous Physics; Paradoxism; Mathematica; Miscellanea), comprising 965 pages, published between 2005-2022 in different scientific journals, by the author alone or in collaboration with the following 110 co-authors (alphabetically ordered) from 26 countries: Abduallah Gamal, Sania Afzal, Firoz Ahmad, Muhammad Akram, Sheriful Alam, Ali Hamza, Ali H. M. Al-Obaidi, Madeleine Al-Tahan, Assia Bakali, Atiqe Ur Rahman, Sukanto Bhattacharya, Bilal Hadjadji, Robert N. Boyd, Willem K.M. Brauers, Umit Cali, Youcef Chibani, Victor Christianto, Chunxin Bo, Shyamal Dalapati, Mario Dalcín, Arup Kumar Das, Elham Davneshvar, Bijan Davvaz, Irfan Deli, Muhammet Deveci, Mamouni Dhar, R. Dhavaseelan, Balasubramanian Elavarasan, Sara Farooq, Haipeng Wang, Ugur Halden, Le Hoang Son, Hongnian Yu, Qays Hatem Imran, Mayas Ismail, Saeid Jafari, Jun Ye, Ilanthenral Kandasamy, W.B. Vasantha Kandasamy, Darjan Karabašević, Abdullah Kargın, Vasilios N. Katsikis, Nour Eldeen M. Khalifa, Madad Khan, M. Khoshnevisan, Tapan Kumar Roy, Pinaki Majumdar, Sreepurna Malakar, Masoud Ghods, Minghao Hu, Mingming Chen, Mohamed Abdel-Basset, Mohamed Talea, Mohammad Hamidi, Mohamed Loey, Mihnea Alexandru Moisescu, Muhammad Ihsan, Muhammad Saeed, Muhammad Shabir, Mumtaz Ali, Muzzamal Sitara, Nassim Abbas, Munazza Naz, Giorgio Nordo, Mani Parimala, Ion Pătrașcu, Gabrijela Popović, K. Porselvi, Surapati Pramanik, D. Preethi, Qiang Guo, Riad K. Al-Hamido, Zahra Rostami, Said Broumi, Saima Anis, Muzafer Saračević, Ganeshsree Selvachandran, Selvaraj Ganesan, Shammya Shananda Saha, Marayanagaraj Shanmugapriya, Songtao Shao, Sori Tjandrah Simbolon, Florentin Smarandache, Predrag S. Stanimirović, Dragiša Stanujkić, Raman Sundareswaran, Mehmet Șahin, Ovidiu-Ilie Șandru, Abdulkadir Șengür, Mohamed Talea, Ferhat Taș, Selçuk Topal, Alptekin Ulutaș, Ramalingam Udhayakumar, Yunita Umniyati, J. Vimala, Luige Vlădăreanu, Ştefan Vlăduţescu, Yaman Akbulut, Yanhui Guo, Yong Deng, You He, Young Bae Jun, Wangtao Yuan, Rong Xia, Xiaohong Zhang, Edmundas Kazimieras Zavadskas, Zayen Azzouz Omar, Xiaohong Zhang, Zhirou Ma.
4D structure of biochar and its impact on soil water characteristics
Intensification of agricultural practices is necessary to support a growing global
population. Water movement and storage in soils are very crucial for successful
intensification of agriculture. They are important for nutrient delivery to plant and
overall crop productivity. Climate change and population growth have been predicted
to limit water supply especially in arid regions. Therefore, there is an urgent need to
proffer solutions that would help maintain or even increase soil moisture retention. The
use of biochar for improving soil hydraulic properties is a current and growing area of
research. Biochar is a stable form of charcoal gotten from heating natural organic
materials in a high temperature and low oxygen process known as pyrolysis.
Biochar
physical and chemical properties vary due to the pyrolysis process conditions, the type
of feedstock, and the ratios of lignin, cellulose, and hemicellulose in the biomass.
These change the structure of the biochar and will invariably affect to what extent it
can improve soil water retention. To understand how biochar affects soil water
properties we must understand the specific characteristics of biochar that influence
these changes. Understanding the mechanisms is important for easy prediction of
when and by how much biochar will improve soil water properties. The aim of this
thesis is to provide new and extensive insight into 4D structural changes of biochar
produced from different feedstock and pyrolysis conditions and how these affects soil
moisture characteristics of different soil textures.
The first aspect of the thesis was to carry out a meta-analysis of the available literature
to quantify the effect of biochar on soil hydraulic properties. To enable matching of
biochar to soil constraints and application needs, a thorough understanding of the
impact of biochar properties on relevant soil parameters is necessary. This meta-
analysis of the available literature for the first time quantitatively assessed the effect
of not just biochar application, but different biochar properties on the full sets of key
soil hydraulic parameters. The review shows that the key factors influencing biochar
performance were particle size, specific surface area and porosity indicating that both
soil-biochar inter-particle and biochar intra-particle pores are important factors.
Next,
the role of biochar particle size and hydrophobicity in controlling soil water movement
and retention was assessed. Softwood pellet biochar in five particle size ranges was
used for the experiment. These particle sizes were tested on two soil types at four
different application rates in the laboratory. The results clearly show that both biochar
intraporosity (pores inside biochar particles) and interporosity (pore spaces between
biochar and soil particles) are important factors affecting amended soil hydraulic
properties. Biochar interpores affect mainly hydraulic conductivity; both interpores and
intrapores control soil water retention properties. Our results suggest that for a more
effective increase in soil water retention of coarse soils, the use of hydrophilic biochar
with high intraporosity is recommended. The third aspect of the thesis was to assess
the 4D structural changes and pore network model of standard biomass feedstock
during pyrolysis. Biochar properties are highly variable and are dependent on the
biomass feedstock and production conditions. Despite these variabilities, there has
been no study that uses a single sample to study the development of microstructural
properties of biomass and biochar through the full range of pyrolysis temperatures. In
this study, synchrotron x-ray micro-tomography (SµCT) was used to visualize the
internal structure and characterise pore structure of biochar from several feedstock
during pyrolysis (50 - 800 °C). The results show a wide range of variation in the pore
structural characteristics of the biochar depending on feedstock and pyrolysis
temperature, with observed porosity in the range of 7.41 – 60.56 %. The results from
this study are not only important for the use of biochar as soil amendments but also a
range of other applications relying on biochar pore characteristics, such as biochar as
habitat for microbes, water, and wastewater treatments, as an absorbent for the
removal of acid gases, or an additive in construction or engineering materials. In
addition, the in-depth insights into changes in biomass structure during heating are
valuable for research and applications related to fire safety. Finally, the data set from
the SµCT was used to produce statistical models enabling the prediction of the effect
of biochar on soil water holding capacity from biochar microstructural properties.
The results of this thesis, therefore, clearly establish the mechanisms with which
biochar improves soil hydraulic properties. It also demonstrates that by appropriately
matching microstructural properties of biochar to those of the target soil, it is possible
to achieve considerable improvement in soil properties using relatively low application
rates of biochar. The relationship between biochar structural properties and its effect
on soil moisture characteristics of specific soil texture, is an attractive pathway towards
development of precisely tailored biochars aimed to enhance water use efficiency and
provide low-dose, high-efficiency benefits
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