Biologists Research Articles

Simulation of neutron dark-field data for grating-based interferometers

Hierarchical structures and heterogeneous materials are found in many natural and engineered systems including additive manufacturing, alternative energy, biology and polymer science. Though the structure–function relationship is important for developing more advanced materials, structural characterization over broad length scales often requires multiple complementary measurements. Neutron far-field interferometry aims to enable multi-scale characterization by combining the best of neutron imaging with small-angle neutron scattering (SANS) via dark-field imaging. The microstructure, nominally from 1 nm to 10 µm, is averaged over each volume element ∼(50 µm)3 in the sample, resulting in a `tomographic SANS' measurement. Unlike in small-angle scattering, there are few analytical models to fit dark-field imaging data to extract properties of the microstructure. Fortunately, the dark field and SANS are related through a single Hankel transform. In this work, we discuss the development of a Python-based library, correlogram-tools, that makes use of existing small-angle scattering models and a numerical implementation of the Hankel transform to simulate dark-field interferometry data. We demonstrate how this software can be used to inform researchers of viable sample sets for interferometry experiments, analyze interferometry data, and simulate raw and reconstructed interferometry images for the training of more advanced segmentation models and analysis protocols.

Scientific literacy in biology and attitudes towards science in the Chilean education system

ABSTRACT Background The development of scientific literacy in young people is seen as important in several countries. In recent decades, Chile’s educational reforms aimed at performance have led to a market-oriented funding and management system, worsening social inequality and segregation. Purpose The study looked at biology literacy and science attitudes in Chilean secondary school students, considering two aims: 1) to analyse the level of scientific literacy in biology and attitudes toward science posed by secondary school students, making comparisons by gender, age, socio-economic status (SES), and type of school; and 2) to evaluate the relationship between scientific literacy in biology and attitudes towards science. Sample 612 secondary school students in a central southern region of Chile, took part in the study. Design & Methods A quantitative method was used to analyse the students’ responses on two validated and adapted instruments; A test to measure biological knowledge (TOSLS) and Likert Scale Science-related (LSSr) to measure attitude towards science. These instruments were administered to secondary students, and descriptive and inferential analyses were conducted. Results The adapted TOSLS showed significant differences in SES, school type and slight variations by gender and age, although, no illiteracy level in biology was found among the Chilean students. The adapted LSSr showed significant differences concerning attitudes toward science were found in school type, and variations by SES and age, and gender. Also, the correlation analysis shows a weak positive relationship between scientific literacy in biology and attitudes towards science, although of moderate magnitude. Conclusion This study found that scientific literacy in biology does not necessarily impact attitudes towards science. However, SES and type of school can affect understanding and views of science and its role in society, which aligns with previous findings on social inequality in Chilean education.

PhD Student Funding Patterns: Placing Biomedical, Biological, and Biosystems Engineering in the Context of Engineering Sub-disciplines, Biological Sciences, and Other STEM Disciplines

AbstractWhether doctoral students are funded primarily by fellowships, research assistantships, or teaching assistantships impacts their degree completion, time to degree, learning outcomes, and short- and long-term career outcomes. Variations in funding patterns have been studied at the broad field level but not comparing engineering sub-disciplines. We addressed two research questions: How do PhD student funding mechanisms vary across engineering sub-disciplines? And how does variation in funding mechanisms across engineering sub-disciplines map onto the larger STEM disciplinary landscape? We analyzed 103,373 engineering and computing responses to the U.S. Survey of Earned Doctorates collected between 2007 and 2016. We conducted analysis of variance with Bonferroni post hoc comparisons to examine variation in funding across sub-disciplines. Then, we conducted a k-means cluster analysis on percentage variables for fellowship, research, and teaching assistantship funding mechanism with STEM sub-discipline as the unit of analysis. A statistically significantly greater percentage of biomedical/biological engineering doctoral students were funded via a fellowship, compared to every other engineering sub-discipline. Consequently, biomedical/biological engineering had significantly lower proportions of students supported via research and teaching assistantships than nearly all other engineering sub-disciplines. We identified five clusters. The majority of engineering sub-disciplines grouped together into a cluster with high research assistantships and low teaching assistantships. Biomedical/biological engineering clustered in the high fellowships grouping with most other biological sciences but no other engineering sub-disciplines. Biomedical/biological engineering behaves much more like biological and life sciences in utilizing fellowships to fund graduate students, far more than other engineering sub-disciplines. Our study provides further evidence of the prevalence of fellowships in life sciences and how it stretches into biomedical/biological engineering. The majority of engineering sub-disciplines relied more on research assistantships to fund graduate study. The lack of uniformity provides an opportunity to diversify student experiences during their graduate programs but also necessitates an awareness to the advantages and disadvantages that different funding portfolios can bestow on students.

Selective Hydrolysis of Ovalbumin by Zr-Based Lacunary Polyoxotungstate in Surfactant Solutions.

This study aims to design an artificial metalloprotease based on a Zr-containing polyoxometalate Na8[Zr(W5O18)2] [Zr(W5)2] for the hydrolysis of ovalbumin (OVA) in the presence of different surfactants, which can be used in many areas of the biological and medical sciences, particularly for targeted proteolytic drug design. For this reason, parameters, including the free energy of binding, the chemical nature of amino acid residues, secondary structures, and electrostatic potentials, of Zr(W5)2-OVA and Zr(W5)2-OVA-surfactant were analyzed by molecular docking simulations. The investigations showed that the presence of surfactants decreases the binding affinity of Zr(W5)2 for OVA amino acids, and hydrogen bonds and van der Waals interactions are formed between Zr(W5)2 and OVA amino acids. Additionally, GROMACS further illustrated the significance of SDS and CTAB surfactants in influencing the conformational changes of the OVA that lead to selective protein hydrolysis. In agreement with molecular dynamics simulation results, the experimental analysis showed more protein hydrolysis for the Zr(W5)2-OVA-surfactant systems. For instance, circular dichroism spectroscopy indicated that Zr(W5)2-OVA-CTAB and Zr(W5)2-OVA-TX-100 were more hydrolytically efficient due to the increased level of β-structures rather than α-chains, which showed that surfactants can facilitate the accessibility of Zr(W5)2 to the cleavage sites by inducing partial unfolding of the OVA structure.

To the anniversary of Evgeny Ivanovich Chumasov

On March 19, 2024, Evgeniy Ivanovich Chumasov, a well-known neuromorphologist, Doctor of Biological Sciences, and Professor, celebrated his 85th birthday. Here we describe the stages of E.I. Chumasov’s scientific way in the field of normal and pathological neurohistology. Evgeniy Ivanovich is a highly qualified professional in cell biology, cytology, zoology, and histology. Throughout his life, he studied the histogenesis and regeneration of tissues of the central and peripheral nervous systems. He is a great specialist in the cultivation of the nervous tissue; his works on the development of embryonic anlages of the central nervous system and PNS in vitro and after transplantation are still highly relevant and being cited. He authored multiple books and textbooks, several patents, and inventions.

Self-medication with antibiotics and its associated factors among university students: a cross-sectional study

Background Self-medication is the use of medications to address self-perceived disorders or symptoms, typically without a prescription or medical oversight. Throughout the COVID-19 pandemic, there has been a notable increase in self-medication practices, particularly with antibiotics. This study is incited by the rising prevalence of antibiotic resistance and the increased antibiotic consumption observed during the COVID-19 crisis in Pakistan. Methods This study was conducted at the University of Balochistan from April to November 2022, to find out the prevalence of self-medication among students through a comprehensive questionnaire covering frequency, reasons, types of medications used, sources of information, and demographic characteristics. SPSS version 21 was used to analyze the data. Results In this study, a total of 730 participants took part, resulting in a response rate of (708) 97%. The average age of the study participants was 22.78 ± 2.758 years. The study found that most participants were male (69.5%), with the highest representation from third-year students in the biological sciences field (30.5%), primarily residing in hostels (59.3%) and receiving monthly allowances between 10000-15000 (54.2%). Factors such as gender, marital status, field of study in biological and natural sciences, residing in a hostel, absence of family members in the health profession, and specific monthly allowance ranges. Conclusion The study concluded high rates of self-administration of antibiotics among University of Balochistan students, with factors such as gender, marital status, field of study, hostel residency, family healthcare background, and financial constraints playing significant roles. Urgent interventions are necessary to educate students on the dangers of self-medication.

Designing Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning

Designing novel biological sequences with desired properties is a significant challenge in biological science because of the extra large search space. The traditional design process usually involves multiple rounds of costly wet lab evaluations. To reduce the need for expensive wet lab experiments, machine learning methods are used to aid in designing biological sequences. However, the limited availability of biological sequences with known properties hinders the training of machine learning models, significantly restricting their applicability and performance. To fill this gap, we present ERLBioSeq, an Evolutionary Reinforcement Learning algorithm for BIOlogical SEQuence design. ERLBioSeq leverages the capability of reinforcement learning to learn without prior knowledge and the potential of evolutionary algorithms to enhance the exploration of reinforcement learning in the large search space of biological sequences. Additionally, to enhance the efficiency of biological sequence design, we developed a predictor for sequence screening in the biological sequence design process, which incorporates both the local and global sequence information. We evaluated the proposed method on three main types of biological sequence design tasks, including the design of DNA, RNA, and protein. The results demonstrate that the proposed method achieves significant improvement compared to the existing state-of-the-art methods.

Scalable Enumeration of Trap Spaces in Boolean Networks via Answer Set Programming

Boolean Networks (BNs) are widely used as a modeling formalism in several domains, notably systems biology and computer science. A fundamental problem in BN analysis is the enumeration of trap spaces, which are hypercubes in the state space that cannot be escaped once entered. Several methods have been proposed for enumerating trap spaces, however they often suffer from scalability and efficiency issues, particularly for large and complex models. To our knowledge, the most efficient and recent methods for the trap space enumeration all rely on Answer Set Programming (ASP), which has been widely applied to the analysis of BNs. Motivated by these considerations, our work proposes a new method for enumerating trap spaces in BNs using ASP. We evaluate the method on a mix of 250+ real-world and 400+ randomly generated BNs, showing that it enables analysis of models beyond the capabilities of existing tools (namely pyboolnet, mpbn, trappist, and trapmvn).

New insights into ion migration time under nonuniform electric fields: Mechanism and application to designing fast exhaustive electroextraction

Electrokinetic techniques, such as electrophoresis, electroextraction, and electrodialysis, have found a wide range of applications in fields such as chemical engineering, chemistry, biology, and environmental science. A critical parameter in these techniques is the time required for ion migration, which is often driven by a nonuniform three-dimensional electric field. However, the influence of the inhomogeneity of an electric field on ion migration time remains unclear, impeding procedures for its control. Herein, for the first time, we propose a concise, universal equation that clearly describes the features of electrophoresis times in nonuniform electric fields and reveals a linear relationship between ion migration time and the degree of dispersion of the electric field (or ion velocity). This discovery should facilitate the rational design for development of electrokinetic techniques to replace previous trial-and-error approaches. We demonstrate the viability of our method using a test case involving the design of an electroextraction device with high efficiency and matrix tolerance. The device with the optimized electric field geometry enables the exhaustive enrichment of crystal violet from a milliliter-level donor phase into a microliter-level acceptor phase within 540 s and avoids agitation. The direct, rapid electroextraction of trace analytes from complex essential oils and honey samples within 300–480 s is realized using this device, which is further coupled with liquid chromatography-mass spectrometry. The resulting analytical method displays low limits of detection (0.01–0.06 ng·mL−1; 0.08–0.30 μg·kg−1), overcoming the issues of time- and labor-intensive and error-prone sample preparation.

Generalised shot-noise representations of stochastic systems driven by non-Gaussian Lévy processes

Abstract We consider the problem of obtaining effective representations for the solutions of linear, vector-valued stochastic differential equations (SDEs) driven by non-Gaussian pure-jump Lévy processes, and we show how such representations lead to efficient simulation methods. The processes considered constitute a broad class of models that find application across the physical and biological sciences, mathematics, finance, and engineering. Motivated by important relevant problems in statistical inference, we derive new, generalised shot-noise simulation methods whenever a normal variance-mean (NVM) mixture representation exists for the driving Lévy process, including the generalised hyperbolic, normal-gamma, and normal tempered stable cases. Simple, explicit conditions are identified for the convergence of the residual of a truncated shot-noise representation to a Brownian motion in the case of the pure Lévy process, and to a Brownian-driven SDE in the case of the Lévy-driven SDE. These results provide Gaussian approximations to the small jumps of the process under the NVM representation. The resulting representations are of particular importance in state inference and parameter estimation for Lévy-driven SDE models, since the resulting conditionally Gaussian structures can be readily incorporated into latent variable inference methods such as Markov chain Monte Carlo, expectation-maximisation, and sequential Monte Carlo.

A Novel One-Pot Three-Component Approach to Orthoaminocarbonitrile Tetrahydronaphthalenes Using Triethylamine (Et_3N) as a Highly Efficient and Homogeneous Catalyst Under Mild Conditions and Investigating Its Anti-cancer Properties Through Molecular Docking Studies and Calculations

An efficient and environmentally friendly method for the one-pot synthesis of ortho-aminocarbonitrile tetrahydronaphthalenes has been developed in the presence of triethylamine (Et3N) as a homogeneous catalyst. The multicomponent reactions of benzaldehydes, cyclohexanone and malononitrile were carried out under mild conditions to obtain some ortho-aminocarbonitrile tetrahydronaphthalene derivatives. A broad range of structurally diverse benzaldehydes were applied successfully, and corresponding products (4A-L) were obtained in good to excellent yields (87-98%) in very short times (10-25 minutes). The present approach provides several advantages including simple workup, high yields, very mild reaction conditions, short reaction times, little catalyst loading and not requiring specialized equipment. Furthermore, with the help of computational chemistry and drug design methods, the anti-cancer properties of these compounds were studied and investigated. All the synthesized compounds bind to an agonist at the active site of the 3A8P protein, which leads to the inactivation of this protein and produces beneficial effects during cancer treatment. In synthesized compounds, the ligands establish hydrogen bonds with leucine A:728 residues through nitrogen, which has a very special and vital role in biological sciences and pharmaceutical connections. In this study, it was found that these compounds have the potential to become an oral anti-cancer drug.

Point biserial correlation symbiotic organism search nanoengineering based drug delivery for tumor diagnosis

Nanoparticulate systems have the prospect of accounting for a new making of drug delivery systems. Nanotechnology is manifested to traverse the hurdle of both physical and biological sciences by implementing nanostructures indistinct fields of science, particularly in nano-based drug delivery. The low delivery efficiency of nanoparticles is a critical obstacle in the field of tumor diagnosis. Several nano-based drug delivery studies are focused on for tumor diagnosis. But, the nano-based drug delivery efficiency was not increased for tumor diagnosis. This work proposes a method called point biserial correlation symbiotic organism search nanoengineering-based drug delivery (PBC-SOSN). The objective and aim of the PBC-SOSN method is to achieve higher drug delivery efficiency and lesser drug delivery time for tumor diagnosis. The contribution of the PBC-SOSN is to optimized nanonengineering-based drug delivery with higher r drug delivery detection rate and smaller drug delivery error detection rate. Initially, raw data acquired from the nano-tumor dataset, and nano-drugs for glioblastoma dataset, overhead improved preprocessed samples are evolved using nano variational model decomposition-based preprocessing. After that, the preprocessed samples as input are subjected to variance analysis and point biserial correlation-based feature selection model. Finally, the preprocessed samples and features selected are subjected to symbiotic organism search nanoengineering (SOSN) to corroborate the objective. Based on these findings, point biserial correlation-based feature selection and a symbiotic organism search nanoengineering were tested for their modeling performance with a nano-tumor dataset and nano-drugs for glioblastoma dataset, finding the latter the better algorithm. Incorporated into the method is the potential to adjust the drug delivery detection rate and drug delivery error detection rate of the learned method based on selected features determined by nano variational model decomposition for efficient drug delivery.

Kingdom Fungi capabilities as materials for design

Background Living organisms such as algae, bacteria, and fungi are used to construct novel materials that offer possibilities for innovation. The article aims to explore mycelial growth and analyze the necessary conditions for its development and durability showing its visual potential as a material to be included in a design project. We have explored the aesthetic and metabolic opportunities offered by some species of filamentous fungi for the integration of this kingdom in the design and production of new materials. Methods Taking processes commonly implemented in biology and adopting them into design processes, we grow filamentous fungi and isolate them into pieces designed to display and ensure their natural development. The process was made through biological science methodology, preparing a PDA culture medium, optimal for the specific growth of these living organisms. The inoculation and incubation of some species of filamentous fungi, mainly of the species Fusarium Proliferatum, was carried out to generate a mother culture, exposing them to stress variables such as changes in temperature, incidence of sunlight, humidity, amount of oxygen received, among others. to generate differences in their morphology and pigmentation. Subsequently, the colonies obtained were transferred to each of the designed and prepared artifacts through spores transferred with a mycological loop. These artifacts were sealed to encapsulate the fungus and wait for the colonization of the piece. Results Perpetuity is evident after nine years of cultivation; the colonies remain in the container preserving their morphological character and the pigmentation presented from the beginning of incubation with a slight variation in the saturation of the colors. Conclusions Depending on the species of fungi used and the stimuli applied by the designer, a wide variety of textures, shapes, and colors can be propitiated, generating new product languages and artifacts where their aesthetic qualities are maintained over time.

Understanding, being, and doing of bioethics; a state-level cross-sectional study of knowledge, attitude, and practice among healthcare professionals.

The field of bioethics examines the moral and ethical dilemmas that arise in the biological sciences, healthcare, and medical practices. There has been a rise in medical negligence cases, complaints against healthcare workers, and public dissatisfaction with healthcare professionals, according to reports from the Indian Medical Council and other healthcare associations. We intend to assess the level of knowledge, attitude, and practice of bioethics among the registered healthcare professionals (HCPs) of Maharashtra, India. A State-level online survey was conducted among the registered HCPs (n = 2143) casing all five regions of the Maharashtra state using a pre-tested self-administered questionnaire. The responses were expressed as mean, and proportions with their standard deviation and 95% CI respectively. Binary logistic regression and a multivariate logistic model were used to determine factors associated with knowledge, attitude, and practice of bioethics. Of the 2143 registered HCPs in Maharashtra included in this study, most of them (65.2%) had adequate knowledge of bioethics. Adequate knowledge was associated with lower age, profession (nurses and dentists), employment in the private sector, HCPS at Marathwada and Pune, and higher educational attainment. About 3 in 5 HCPs (59.4%) had a favorable attitude towards the ethical practice of bioethics, and was associated with profession, place of work, region of practice, and work experience. The distribution of unethical bioethics practices among 10 items was proportionally high, and only 34.4% reported good/fair practice. The common unethical practices in the state were allowing patients to be examined by interns, and not informing them about professional misconduct to the regulatory bodies. Most HCPs had adequate knowledge of bioethics, which is encouraging and would favor the laying foundation for forming a good bioethics framework. Only 3/5 HCPs demonstrated a favorable attitude, and the observed unethical practice is alarmingly common. A serious consideration to evaluate the compliance level of bioethics practice periodically and measures to educate, sensitize, and train bioethics among HCPs in Maharashtra is warranted.

Molecular and Supramolecular Materials: From Light-Harvesting to Quantum Information Science and Technology.

The past two decades have witnessed immense advances in quantum information technology (QIT), benefited by advances in physics, chemistry, biology, and materials science and engineering. It is intriguing to consider whether these diverse molecular and supramolecular structures and materials, partially inspired by quantum effects as observed in sophisticated biological systems such as light-harvesting complexes in photosynthesis and the magnetic compass of migratory birds, might play a role in future QIT. If so, how? Herein, we review materials and specify the relationship between structures and quantum properties, and we identify the challenges and limitations that have restricted the intersection of QIT and chemical materials. Examples are broken down into two categories: materials for quantum sensing where nonclassical function is observed on the molecular scale and systems where nonclassical phenomena are present due to intermolecular interactions. We discuss challenges for materials chemistry and make comparisons to related systems found in nature. We conclude that if chemical materials become relevant for QIT, they will enable quite new kinds of properties and functions.

Investigation of the dynamical structures of double-chain deoxyribonucleic acid model in biological sciences

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain’s base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system’s potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.

Regulamentele și alte acte normative ale municipalității bucureștene referitoare la piețe și hale (1870–1914)

Since 1864, cities have played an increasingly important role in creating the norms and rules that governed human life, from economic activity to leisure. These rules had a very important role in the modernization process, contributing substantially to changing behaviours and practices, creating professional bodies, and adopting Western models. However, in Romanian historiography, this phenomenon is far from receiving the attention it deserves. Our paper aims to analyse the regulations, ordinances, and decisions issued by the Bucharest City Hall, regarding trade carried out in market halls, markets, in various places on the city streets, or by peddlers. Markets and market halls were, in the City Hall's conception, not just places intended for the trade of food and various other goods. They were supposed to be fundamental tools through which the municipality ensured that the citizens of Bucharest had access to safe food – from a hygienic and sanitary point of view – and that the numerous diseases transmitted through food had as few consequences as possible on the health of the capital's inhabitants. To attain this aim, the mayor, the Municipal Council, and the Hygiene Council elaborated and enacted numerous rules, which, under the combined pressure of the city's development, advances in the medical, chemical, and biological sciences, not least the professionalization of the municipal administration, experienced a rapid evolution during the chronologic span discussed. At the same time, the City Hall invested in the creation of an infrastructure that would allow the application of these measures (market halls and market, abattoir, laboratory for chemical and bacteriological analysis, etc.), and a body of officials that would ensure their compliance.

Optimal 3D angular sampling with applications to cryo-EM problems

The goal of cryo-EM experiments in the biological sciences is to determine the atomic structure of a molecule and deduce insights into its functions and mechanisms. Despite improvements in instrumentation for data collection and new software algorithms, in most cases, individual atoms are not resolved. Model building of proteins, nucleic acids, or molecules in general, is feasible from the experimentally determined density maps at resolutions up to the range of 3–4 Angstroms. For lower-resolution maps or parts of maps, fitting smaller structures obtained by modelling or experimental techniques with higher resolution is a way to resolve the issue. In practice, we have an atomic structure, generate its density map at a given resolution, and translate/rotate the map within a region of interest in the experimental map, computing a measure-of-fit score with the corresponding areas of the experimental map. This procedure is computationally intensive since we work in 6D space. An optimal ordered list of rotations will reduce the angular error and help to find the best-fitting positions faster for a coarse global search or a local refinement. It can be used for adaptive approaches to stop fitting algorithms earlier once the desired accuracy has been achieved. We demonstrate how the performance of some fitting algorithms can be improved by grouping sets of rotations. We present an approach to generate more efficient 3D angular sampling, and provide the computer code to generate lists of optimal orientations for single and grouped rotations and the lists themselves.

Academic publishing requires linguistically inclusive policies.

Scientific knowledge is produced in multiple languages but is predominantly published in English. This practice creates a language barrier to generate and transfer scientific knowledge between communities with diverse linguistic backgrounds, hindering the ability of scholars and communities to address global challenges and achieve diversity and equity in science, technology, engineering and mathematics (STEM). To overcome those barriers, publishers and journals should provide a fair system that supports non-native English speakers and disseminates knowledge across the globe. We surveyed policies of 736 journals in biological sciences to assess their linguistic inclusivity, identify predictors of inclusivity, and propose actions to overcome language barriers in academic publishing. Our assessment revealed a grim landscape where most journals were making minimal efforts to overcome language barriers. The impact factor of journals was negatively associated with adopting a number of inclusive policies whereas ownership by a scientific society tended to have a positive association. Contrary to our expectations, the proportion of both open access articles and editors based in non-English speaking countries did not have a major positive association with the adoption of linguistically inclusive policies. We proposed a set of actions to overcome language barriers in academic publishing, including the renegotiation of power dynamics between publishers and editorial boards.

Unraveling Eumelanin Radical Formation by Nanodiamond Optical Relaxometry in a Living Cell.

Defect centers in a nanodiamond (ND) allow the detection of tiny magnetic fields in their direct surroundings, rendering them as an emerging tool for nanoscale sensing applications. Eumelanin, an abundant pigment, plays an important role in biology and material science. Here, for the first time, we evaluate the comproportionation reaction in eumelanin by detecting and quantifying semiquinone radicals through the nitrogen-vacancy color center. A thin layer of eumelanin is polymerized on the surface of nanodiamonds (NDs), and depending on the environmental conditions, such as the local pH value, near-infrared, and ultraviolet light irradiation, the radicals form and react in situ. By combining experiments and theoretical simulations, we quantify the local number and kinetics of free radicals in the eumelanin layer. Next, the ND sensor enters the cells via endosomal vesicles. We quantify the number of radicals formed within the eumelanin layer in these acidic compartments by applying optical relaxometry measurements. In the future, we believe that the ND quantum sensor could provide valuable insights into the chemistry of eumelanin, which could contribute to the understanding and treatment of eumelanin- and melanin-related diseases.