Field Of Science Research Articles

Biochemical Society 2025 award winners

Each year, the Biochemical Society presents a series of prestigious awards that recognize excellence and achievement in both specific and general fields of science. Candidates are nominated by their peers and the winners are agreed by a judging panel of respected scientists from across a range of different scientific backgrounds.

Light Intensity of Phosphorescent-Netting Pots and Determining Their Visibility to Snow Crab (Chionoecetes opilio) Using Visual Modeling Techniques

This study explores the visibility of phosphorescent-netting pots to snow crab (Chionoecetes opilio) using visual modeling techniques. Light emitted from such pots increases catch per unit effort, yet little is understood about the factors driving these higher catch rates. In this study, we measure pot light emission and snow crab visual acuity. Combining these data with estimates obtained in the literature for other biotic and abiotic factors, we model snow crab vision in relation to the pots. Utilizing these factors and environmental conditions, we derive a contrast ratio between the pot light and the ambient light. Findings reveal that the visibility of pot lights at 200-m depth depends primarily on solar angle (time of day) and time elapsed post-deployment. Additional factors influencing the vision of the pots include water column quality and benthic boundary layer turbidity. This study is the first to model the visual ecology of snow crab and the first to estimate snow crab visual acuity. These insights into snow crab visual ecology can potentially enhance fishing techniques, promote catch efficiency and sustainability, and help provide a path forward for visual ecology research in the fisheries science field.

Leadership Development Interventions to Reduce Imposter Phenomenon in the STEM Fields in Minorities

Background: There is a significant lack of diversity in the Science, Technology, Engineering, and Mathematics (STEM) fields. Evidence shows that lack of representation can feed into feelings of imposter phenomenon which in turn influences leadership qualities. Objectives: An argument is made that by providing leadership development training to minorities in science, technology, engineering, and mathematics fields, confidence will be boosted, feelings of imposter phenomenon will be reduced, and thus these students will be retained. Approach: Theories explored to explain this challenge include the imposter phenomenon, servant leadership, and transformational leadership. Results: The goal of this article is to demonstrate the need for research into leadership development of minorities in the science, technology, engineering, and mathematics fields. Conclusions: A program proposal is also introduced as a suggested plan of action based on the findings.

The right to information under the conditions of armed aggression of the Russia

The article is devoted to the understanding and scientific and theoretical analysis of the peculiarities of the implementation and protection of the right to information in the conditions of the armed aggression of the Russian Federation against Ukraine. It was determined that private law, despite all its focus on the maximum provision of personal freedom, including freedom in the exercise of rights, the admissibility of limiting a person in the exercise of these rights solely on the grounds and in the manner determined by law, recognizes not only the admissibility of such restrictions, but also necessary, if the interests of national security, territorial integrity or public order require it in order to prevent riots or crimes, to protect public health, to protect the reputation or rights of other people, to prevent the disclosure of information obtained in confidence, or to maintain authority and impartiality justice. It was determined that a person has the right to confidentiality of information about himself, which is meaningfully a component of the right to respect for his private life and the right to information in the context of his free receipt, use, distribution, storage and protection of information necessary for the realization of his rights, freedoms and legitimate interests. Content-wise, the latter can be information in the field of science, nature, politics, culture and art, sports, finance, leisure, business and economy, etc. It was concluded that the prohibition of censorship under Art. 15 of the Constitution of Ukraine forces to carefully resolve the issue of balance between censorship and restriction of the right to information in the conditions of martial law, which forces the Law to determine the grounds, procedure and procedure for restricting a person’s right to information. It was concluded that the list of information with limited access, determined by the Order of the Commander-in-Chief of the Armed Forces of Ukraine No. 73 of 03.03.2022, regarding the prohibition of the dissemination of information, the disclosure of which could lead to the enemy becoming aware of the actions of the Armed Forces of Ukraine and other components of the defense forces, negatively affect the course of performing tasks as assigned during the legal regime of martial law must be depersonalized, because the specified order is aimed at streamlining relations between representatives of the Ministry of Defense of Ukraine and journalists.

Applicability of ChatGPT 3.5 in the development of new analytical procedures

Artificial intelligence (AI) is gradually expanding into various fields of science and research, and chemistry is no exception. Although the use of AI in analytical chemistry is today in its infancy, significant progress and an increasing number of publications can be observed here, too. The emergence of user-friendly AI models, such as ChatGPT 3.5, which can understand human-oriented texts and engage in natural conversations without requiring programming skills, offers undeniable benefits. In this work experiences with the use of ChatGPT in the development of a new analytical procedure are presented. The development of a new method for the extraction and determination of bioactive compounds in plant samples was chosen as a model. The goal was to use AI in as many steps as possible in the development of a new procedure and to verify whether AI can fully plan an experiment, choose the optimal conditions, explain the results and evaluate the environmental friendliness of the developed procedure. What AI can do, how it can be useful for the analyst by relieving him of boring and routine tasks, to what extent it can be trusted and what the analyst must pay attention to were examined. We also explored whether AI, on the basis of experimental results, can write a high-quality scientific paper and therefore stand in for analysts. The role and importance of the analytical chemist and his knowledge, experience and creativity for obtaining the best results is emphasized. We hope that our observations, findings and considerations will interest analytical chemists and help them in their research.

The design of a scientific data management system based on DOMAS at CSNS-II (preliminary stage)

At the second stage of China Spallation Neutron Source (CSNS-II), it is predicted that 2 PB raw experimental data will be produced annually from twenty instruments. Scientific computing puts forward higher requirements for data sharing, utilization, retrieval, analysis efficiency, and security. However, the existing data management system (DMS) based on ICAT has several limitations including poor scalability of metadata database, imperfect data-management lifecycle and inflexible API. To ensure the accuracy, usability, scalability and efficiency of CSNS-II experimental data, a new scientific data management system is therefore designed based on the DOMAS framework developed by the Computing Center of IHEP. The data acquisition, transmission, storage and service systems are re-designed and tailored specifically for CSNS-II. Upon its completion, the new DMS will overcome the existing challenges and offer functions such as online display, search functionality and rapid download capabilities for metadata, raw data and analyzed data; flexible and user-friendly authorization; and data lifecycle management. Ultimately, the implementation of the new Data Management System (DMS) is expected to enhance the efficiency of experimental data analysis, propelling CSNS-II to achieve international advanced standards. Furthermore, it aims to reinforce self-reliance and technological strength in the field of science and technology at a high level in China. The development and deployment of the new DMS begin at the end of 2023.

Using Optimization Techniques in Grammatical Evolution

The Grammatical Evolution technique has been successfully applied to a wide range of problems in various scientific fields. However, in many cases, techniques that make use of Grammatical Evolution become trapped in local minima of the objective problem and fail to reach the optimal solution. One simple method to tackle such situations is the usage of hybrid techniques, where local minimization algorithms are used in conjunction with the main algorithm. However, Grammatical Evolution is an integer optimization problem and, as a consequence, techniques should be formulated that are applicable to it as well. In the current work, a modified version of the Simulated Annealing algorithm is used as a local optimization procedure in Grammatical Evolution. This approach was tested on the Constructed Neural Networks and a remarkable improvement of the experimental results was shown, both in classification data and in data fitting cases.

Exploring proteins at soft interfaces and in thin liquid films – From classical methods to advanced applications of reflectometry

The history of the topic of proteins at soft interfaces dates back to the 19th century, and until the present day, it has continuously attracted great scientific interest. A multitude of experimental methods and theoretical approaches have been developed to serve the research progress in this large domain of colloid and interface science, including the area of soft colloids such as foams and emulsions. From classical methods like surface tension adsorption isotherms, surface pressure-area measurements for spread layers, and surface rheology probing the dynamics of adsorption, nowadays, advanced surface-sensitive techniques based on spectroscopy, microscopy, and the reflection of light, X-rays and neutrons at liquid/fluid interfaces offers important complementary sources of information. Apart from the fundamental characteristics of protein adsorption layers, i.e., surface tension and surface excess, the nanoscale structure of such layers and the interfacial protein conformations and morphologies are of pivotal importance for extending the depth of understanding on the topic. In this review article, we provide an extensive overview of the application of three methods, namely, ellipsometry, X-ray reflectometry and neutron reflectometry, for adsorption and structural studies on proteins at water/air and water/oil interfaces. The main attention is placed on the development of experimental approaches and on a discussion of the relevant achievements in terms of notable experimental results. We have attempted to cover the whole history of protein studies with these techniques, and thus, we believe the review should serve as a valuable reference to fuel ideas for a wide spectrum of researchers in different scientific fields where proteins at soft interface may be of relevance.

Revisiting Male Allies in Mathematics and Physics Throughout History: Role Models for Men in STEM Education

In the academic world, there are also gender inequalities, which are especially visible in certain masculinized STEM areas, such as physics and mathematics. An essential factor in correcting these inequalities is the involvement of men, who should act as “allies” in the university setting. Likewise, as the literature shows us, we must offer models with gender-incongruent roles to break down stereotypes and promote non-traditional behaviors. However, to date, these actions have been especially directed toward women, who generally do not hold power and therefore have less possibility of promoting change. For the first time, this work compiles, in a single document, important male physicists and mathematicians who acted as allies of women throughout history. These examples can be presented to provide male references in the teaching of physics and mathematics at university (and high school). With this initiative, we intend to contribute to incorporating the gender perspective in university teaching, since, in practice, university professors are unaware of references of alternative masculinities in the academic world. We hope that this article will be the seed to recover hidden male allies in these and other scientific fields. This can help break down stereotypes, and contrary to previous actions, this work is especially directed toward men.

The policy is dead, long live the policy—Revealing science, technology, and innovation policy priorities and government transitions via network analysis

Abstract Each government has priorities for science, technology, and innovation policies (STIP). How can we identify the changing or reinforced STIP research priorities induced by government transitions? This study aims to unveil the STIP changing structure in the public funding research call contents in Colombia from 2007 to 2022, applying a co-word and network analysis approach to 389 funding research calls. We showed each government’s changing distribution of the betweenness centrality of 334 fields from Health, Life, Physical, and Social Sciences. We found that STIP priorities are getting denser and more diverse in terms of research fields. Despite this complexity, just 14 fields of Life, Physical, and Social Sciences, such as drug discovery, general business, management & accounting, and nature and landscape conservation, maintained their higher strategic relevance despite the government in office. This study maps the short and long-term focus of STIP regardless of the changing political tide inherent in democratic countries.

“Recovery is Complicated”: A Qualitative Exploration of Canadian University Students’ Diverse Recovery Experiences

ABSTRACT While the field of recovery science has burgeoned over the past two decades, little research has considered the experiences of university students in recovery from addiction, particularly in Canada. Addressing this gap, using a recovery capital framework, 16 qualitative interviews were conducted to explore students’ meanings, experiences, and barriers/facilitators to recovery from problematic substance use and/or behaviors. Reflexive thematic analysis revealed three main themes: 1. multiple recovery pathways and identities; 2. stigma and disclosure; and 3. proximity to campus community and resources. Recommendations to create more recovery-friendly campuses are provided.

Comparison between Statistical Approaches and Data Mining Algorithms for Outlier Detection

Outliers are observation values that are very different from most observations. The presence of outliers in data can have a negative impact on research but can contain important information for other research. So, identifying outliers before conducting data analysis is a crucial thing to do. Outlier detection methods/techniques were first pioneered by researchers in statistics. However, due to rapid technological advances which have an impact on the ease of collecting extensive data, the development of outlier detection techniques is now handled mainly by researchers in the field of computer science (data mining) using computing facilities. This research aims to examine the results of simulation studies by comparing methods for identifying several outliers using statistical approaches and data mining algorithm approaches in various predetermined data scenarios. Based on the scenario carried out, the outlier detection method using a statistical approach is generally better than the outlier detection method using a data mining-based approach. Suggestions for further research are to improve the data mining method by focusing more on statistical analysis apart from focusing on data processing computing time so that the expected results of outlier detection are faster and more precise.

A ‘heavy hammer to crack a small nut'? The creation of the European Molecular Biology Conference (EMBC), 1963–1970

ABSTRACT This article reconstructs the complex diplomatic negotiations that led to the peculiar organization of molecular biology at the European level, by focusing in particular on the establishment of the European Molecular Biology Conference (EMBC), the intergovernmental structure founded in 1969–70 to support the scientific program of the European Molecular Biology Organization (EMBO). By combining the analysis of the informal decision-making kept in the Nobel Prize laureate John C. Kendrew’s personal papers (Oxford) with the in-depth exploration of the institutional documentation available in the EMBO and CERN archives (Heidelberg and Geneva) and the Swiss Federal Archives (Bern), the article sheds light on the importance of the EMBC not only for the construction of molecular biology as a scientific, social, and political field in the European context, but also for the broader process of definition of the European research policy. Far from being just a mere replica of CERN, the EMBO/EMBC inaugurated in fact an alternative and flexible ‘bottom-up’ model of science policy in the European context, based on competition, networking, and scientific excellence, which paved the way to the establishment of the European Research Council (ERC) in the early 2000s.

Development of an IoT based 3D printed Mobile Robot Platform for training of Mechatronics Engineering Students

The advent of the Internet of Things (IoT) has opened up new opportunities in education, particularly in the field of mobile robotics. Mobile robotics is a fast-growing field, and with the increasing demand for skilled robotics engineers, it is essential to provide students with hands-on experience in designing and developing robots. In this regard, an IoT-based 3D printed mobile robot platform has been developed for students training. STEM (Science, Technology, Engineering, and Mathematics) education has been gaining attention as a means to improve science and engineering education. STEM education aims to foster critical thinking, problem-solving skills, creativity, and innovation among students. It involves an educational policy that aims to develop the next generation of skilled professionals by integrating the fields of Science, Technology, Engineering and Mathematics. The goal of this approach is to provide students in mechatronics, who are assigned to the robotics lab during their studies, an up to date knowledge and experience in research and development activities. Thus, this paper aims to provide education that focuses on the acquisition and application of engineering knowledge, including control engineering, mechanical engineering, electrical and electronic engineering, information engineering, among others, with the main focus on mobile robot research.

Reimagining Colorectal Cancer Screening: Innovations and Challenges with Dr. Aasma Shaukat.

Colorectal cancer (CRC) currently ranks as the third most common cancer and the second leading cause of cancer-related deaths worldwide, posing a significant global health burden to the population. Recent studies have reported the emergence of a new clinical picture of the disease, with a notable increase in CRC rates in younger populations of <50 years of age. The American Cancer Society (ACS) now recommends CRC screening starting at age 45 for average-risk individuals. Dr. Aasma Shaukat's Keynote Conference highlights the critical need for updated screening strategies, with an emphasis on addressing the suboptimal adherence rates and the effective management of the growing burden of CRC. Lowering the adenoma detection screening age can facilitate early identification of adenomas in younger asymptomatic patients, altering the epidemiologic landscape. However, its implications may not be as profound unless a drastic shift in the age distribution of CRC is observed. Currently, various screening options are available in practice, including stool-based tests like multitarget stool DNA (mtDNA) tests, fecal immunochemical testing (FIT), and imaging-based tests. In addition to existing screening methods, blood-based tests are now emerging as promising tools for early CRC detection. These tests leverage innovative techniques along with AI and machine learning algorithms, aiding in tumor detection at a significantly earlier stage, which was not possible before. Medicare mandates specific criteria for national coverage of blood-based tests, including sensitivity ≥ 74%, specificity ≥ 90%, FDA approval, and inclusion in professional society guidelines. Ongoing clinical trials, such as Freenome, Guardant, and CancerSEEK, offer hope for further advancements in blood-based CRC screening. The development of multicancer early detection tests like GRAIL demonstrates a tremendous potential for detecting various solid tumors and hematologic malignancies. Despite these breakthroughs, the question of accessibility and affordability still stands. The ever-evolving landscape of CRC screening reflects the strength of the scientific field in light of an altered disease epidemiology. Lowering screening age along with the integration of blood-based tests with existing screening methods holds great potential in reducing the CRC-related burden. At the same time, it is increasingly important to address the challenges of adaptation of the healthcare system to this change in the epidemiologic paradigm.

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

Aerosol Mass Spectrometry

Mass spectrometry is widely used in various scientific fields. In atmospheric chemistry, there has been a long call for a detailed on-line analysis of the chemical composition of aerosol particles (i.e., particles in the solid or liquid state) in the atmosphere resulting in the development of the so-called aerosol mass spectrometers in the past 20 years. These instruments allow the measurement of the chemical composition of particles with sizes of ca. 50–800 nm, typically at minute resolution. Their development and possible applications are discussed in this review.

Enhancing Flood Risk Management: A Comprehensive Review on Flood Early Warning Systems with Emphasis on Numerical Modeling

During recent decades there has been an increase in extreme flood events and their intensity in most regions, mainly driven by climate change. Furthermore, these critical events are expected to intensify in the future. Therefore, the improvement of preparedness, mitigation, and adaptation counterparts is mandatory. Many scientific fields are involved in this task, but from a meteorological and hydrological perspective, one of the main tools that can contribute to mitigating the impact of floods is the development of Early Warning Systems. In this sense, this paper presents a scientific literature review of some of the most representative Flood Early Warning Systems worldwide, many of which are currently fully operational, with a special focus on the numerical modeling component when it is developed and integrated into the system. Thus, from basic to technically complex, and from basin or regional to continental or global scales of application, these systems have been reviewed. In this sense, a brief description of their main features, operational procedures, and implemented numerical models is also depicted. Additionally, a series of indications regarding the key aspects of the newly developed FEWSs, based on recent trends and advancements in FEWSs development found in the literature, are also summarized. Thus, this work aims to provide a literature review useful to scientists and engineers involved in flood analysis to improve and develop supporting tools to assist in the implementation of mitigation measures to reduce flood damage for people, goods, and ecosystems and to improve the community resilience.

A Systematic Review of Synthesis MgO Nanoparticles and Their Applications

Recently, nanoscale biotechnology has emerged as an essential field of contemporary science and a new era in the study of materials. It draws the attention of many scientists from all over the world due to its versatility in various fields. Many physical, chemical, and biological processes are used to create biomaterials. Among the materials of interest is magnesium oxide (MgO), which can be widely used in medical and biotechnological applications due to its non-toxicity and environmental friendliness. This review article discusses various methods for the synthesis of magnesium oxide nanoparticles (MgONPs), with particular emphasis on recent developments and applications of these nanomaterials.

Silicon extraction from x-ray amorphous soil constituents: a method comparison of alkaline extracting agents

The growing interest in amorphous silica (ASi) within the fields of soil science and ecology underscores the necessity for a reliable protocol to estimate ASi contents in soil. Alkaline wet chemical extraction methods are commonly employed for silicon (Si) extraction from operationally defined (x-ray) amorphous Si phases or short-range ordered mineral phases in soils and marine sediments. In our study we conducted a comparative analysis of four alkaline extraction methods (1% sodium carbonate, 0.5 M sodium carbonate, 0.2 M sodium hydroxide, and 0.1 M Tiron), assessing their extraction selectivity as well as effectiveness using soils artificially enriched with varying, defined amounts of ASi. While extraction effectiveness was evaluated by determining the recovery rate of initially added ASi, extraction selectivity was determined by measuring aluminum (Al) and iron (Fe) concentrations as indicators of the dissolution of non-target mineral phases. Microwave plasma atom emission spectrometry was used to analyze Al, Fe, and Si concentrations in the extracts. Our results indicate that extraction with 0.2 M sodium hydroxide yields the best outcomes in terms of both extraction effectiveness and selectivity. This more recent extraction technique is conducted at the most alkaline pH (13.3) of all four methods tested, but at ambient temperature (21°C) decreasing the dissolution of non-target mineral phases. Though, no wet-chemical extraction used on heterogeneous samples like soil is precisely selective, and thus able to quantify the target analyte only. Hence, data obtained by such procedures still need to be interpreted with caution considering all their limitations.