Béatrice Lessard-Hamel, Marcel Babin, Simon Thibault
Sea ice harbours a rich community of well-adapted microorganisms that inhabit liquid micro-spaces where extreme conditions prevail. Currently at risk under climate change, the sea-ice microbiome holds mysteries about evolution of life on Earth and possibly elsewhere, which require methodological innovation to be unravelled. Gaining microscopic insight into the internal structure and biology of sea ice has traditionally been limited to destructive and extrusive ice core sampling methods. Here we present an in situ microscopic imaging system to observe undisturbed living microorganisms directly within sea the ice matrix. The complex and heterogeneous nature of sea ice, including its water crystal lattice, brine channels, air bubbles, and various impurities, presents engineering challenges for the development of this imaging system. Despite the fragile nature of the sea-ice matrix, we could successfully deploy, test and use the new in situ microscope during a recent expedition on the icepack in Arctic. We collected numerous images of live and intact single-celled and colony-forming diatoms, and documented for the first time at such a high resolution some microphysical features of sea ice. The hardware and software design of the endoscope is presented along with acquisition results of the microstructure and diatom images. These findings collectively demonstrate the potential for this new in situ microscopic imaging system to transform the way we study sea ice and to allow a deeper understanding of its complex microstructure and living microorganisms.
Glycerol dialkyl glycerol tetraethers (GDGTs) derived from microorganisms are important tools for the study of paleoclimate changes. Incubation experiments are helpful to clarify the mechanisms for the responses of GDGTs to environmental parameters, and to test the reliability of related climatic proxies. However, previous GDGT incubation experiments were mainly conducted on a single strain or suffered from the influence of a background signal, hampering systematically understanding the precise response of this biomarker to environmental factors in a soil environment. In this paper, artificial soils without GDGTs were incubated under the same temperature but different soil water content (SWC) conditions. The results showed that: (1) The abundances of GDGTs were positively correlated with SWC, but phosphate buffer could inhibit the production of GDGTs; (2) The branched and isoprenoid tetraether index (BIT), a soil moisture proxy developed in natural soils, was not significantly correlated with SWC; (3) 6-methyl brGDGTs were more abundant than 5-methyl brGDGTs, resulting in extremely high values of MBT'5ME and low MBT'. The results suggest that the BIT soil moisture proxy may indirectly (rather than directly) respond to SWC changes and confirm that high relative abundance of 6-methyl brGDGTs can affect the applicability of the MBT'5ME paleothermometer in soils. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202405240120.
Sajib Acharjee Dip, Adrika Zafor, Bikash Kumar Paul
et al.
Large language models (LLMs) and emerging agentic frameworks are beginning to transform single-cell biology by enabling natural-language reasoning, generative annotation, and multimodal data integration. However, progress remains fragmented across data modalities, architectures, and evaluation standards. LLM4Cell presents the first unified survey of 58 foundation and agentic models developed for single-cell research, spanning RNA, ATAC, multi-omic, and spatial modalities. We categorize these methods into five families-foundation, text-bridge, spatial, multimodal, epigenomic, and agentic-and map them to eight key analytical tasks including annotation, trajectory and perturbation modeling, and drug-response prediction. Drawing on over 40 public datasets, we analyze benchmark suitability, data diversity, and ethical or scalability constraints, and evaluate models across 10 domain dimensions covering biological grounding, multi-omics alignment, fairness, privacy, and explainability. By linking datasets, models, and evaluation domains, LLM4Cell provides the first integrated view of language-driven single-cell intelligence and outlines open challenges in interpretability, standardization, and trustworthy model development.
Vision-language-action (VLA) models have shown promise as generalist robotic policies by jointly leveraging visual, linguistic, and proprioceptive modalities to generate action trajectories. While recent benchmarks have advanced VLA research in domestic tasks, professional science-oriented domains remain underexplored. We introduce AutoBio, a simulation framework and benchmark designed to evaluate robotic automation in biology laboratory environments--an application domain that combines structured protocols with demanding precision and multimodal interaction. AutoBio extends existing simulation capabilities through a pipeline for digitizing real-world laboratory instruments, specialized physics plugins for mechanisms ubiquitous in laboratory workflows, and a rendering stack that support dynamic instrument interfaces and transparent materials through physically based rendering. Our benchmark comprises biologically grounded tasks spanning three difficulty levels, enabling standardized evaluation of language-guided robotic manipulation in experimental protocols. We provide infrastructure for demonstration generation and seamless integration with VLA models. Baseline evaluations with two SOTA VLA models reveal significant gaps in precision manipulation, visual reasoning, and instruction following in scientific workflows. By releasing AutoBio, we aim to catalyze research on generalist robotic systems for complex, high-precision, and multimodal professional environments. The simulator and benchmark are publicly available to facilitate reproducible research.
By unifying three foundational principles of modern biology, we develop a mathematical framework to analyze the growing tree of life. Contrary to the static case, where the analogy between phylogenetic trees and the tree that grows in soil is drawn, our framework shows that the living tree of life is analogous to a Cantor dust where each branch is a distinct fractal curve. The system as a whole is therefore multifractal in the sense that it consists of many unique fractals. The three foundational principles for the mathematical framework are that phylogeny is nested, phylogeny is dualistic (i.e., transitive between singularities and populations), and phylogeny is stochastic. Integrating these three principles, we model the dynamic (i.e., living) tree of life as a random iterated function system that generates unique convexly related sequences of branching random variables (visualized in Animation 1). The multifractal nature of this dynamic tree of life implies that, for any two living entities, the time interval from their last common ancestor to the present moment is a distinct fractal curve for each. Thus, the length of a time interval along each distinct branch is unique, so that time is also multifractal and not an ultrametric on the tree of life.
Insight into the non-random distribution patterns of species in different regions is a foundational aim of research in community ecology and biogeography. The nestedness pattern, which investigates changes in species composition and abundance, has been widely used in numerous studies. However, studies on the nestedness of benthic diatoms are extremely rare, and consequently little has been mentioned of their assemblage mechanisms. To fill this gap, based on 168 benthic diatom species from 147 sampling sites in the Thousand Island Lake (TIL) catchment, we calculated their nestedness and niche width with the aim of i) analyzing the nestedness of benthic diatoms communities with different attachment abilities in TIL; ii) calculating niche width differences between nested and idiosyncratic species with different attachment abilities; iii) investigating the differences in alpha and beta diversity between nested and idiosyncratic sites; iv) examining whether environmental variables influencing the nestedness of benthic diatom communities are dependent on attachment ability. The results demonstrated a significant nestedness pattern in the benthic diatom metacommunity, and the sampling sites of low attachment species not only exhibited a nestedness pattern, but also with a lower nestedness value compared to the sampling sites of all species. Nested and idiosyncratic species differed in niche width, whereas differences between nested and idiosyncratic species of low attachment species were smaller. Additionally, significant differences in alpha and beta diversity were observed between nested and idiosyncratic sites. Furthermore, it was revealed that the nestedness of benthic diatom metacommunity in our study area were mostly influenced by local environmental variables. Our study contributes to the understanding of the significant nestedness observed in benthic diatom metacommunity in TIL, highlighting its relevance to biodiversity conservation efforts.
Zooplankton is the important component of aquatic ecosystems. These organisms are important biological indicator of water quality of aquatic ecosystem due to their response to the environmental changes. In this study, we investigated distribution of zooplankton biomass in the Shatt Al-Basra Canal and Shatt Al-Arab River. Zooplankton samples were collected from two stations in the Shatt Al-Basra Canal, before (S1) and after (S2) the dam, and two stations in the Shatt Al-Arab River, Al-Siba (S3) and Al-Faw (S4). The biomass of zooplankton in the Shatt Al-Basra Canal varied between 23.102 - 520.875 mg/m3 in terms of wet weight and 3.787 - 102.132 mg/m3 in terms of dry weight at two stations (before the dam and after the dam) during the period of January and May, respectively. The displacement volume and standing crops also showed variations of the biomass of zooplankton. In the Shatt Al-Basra Canal, the range was from 0.06 ml/m3 and 3.9 mgC/m3 during January at S1 to 1.083 ml/m3 and 70.395 mgC/m3 during May at S2. While in the Shatt Al-Arab River, the biomass of zooplankton in terms of wet weight ranged from 10.671 - 655.78 mg/m3 during December at S3 (Al-Siba) and may at S4 (Al-Faw) respectively. In terms of dry weight, the biomass ranged from 1.423 to 168.149 mg/m3 in S3 during the December and in S4 during May respectively. In terms of displacement volume and standing crops, they ranged from 0.03 ml/m3 to 1.95 mgC/m3 during December at S3 to 1.819 ml/m3 and 118.235 mgC/m3 during February at S4.
Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a serious disease that affects wheat worldwide. There is a great need to develop cultivars with combinations of all-stage resistance (ASR) and adult-plant resistance (APR) genes for sustainable control of the disease. QYrsv.swust-1BL in the Italian durum wheat (Triticum turgidum ssp. durum) cultivar Svevo is effective against Pst races in China and Israel, and the gene has been previously mapped to the long arm of chromosome 1B. The gene is flanked by SNP (single nucleotide polymorphism) markers IWB5732 and IWB4839 (0.75 cM). In the present study, we used high-density 660K SNP array genotyping and the phenotypes of 137 recombinant inbred lines (RILs) to fine map the QYrsv.swust-1BL locus within a 1.066 Mb region in durum wheat Svevo (RefSeq Rel. 1.0) on chromosome arm 1BL. The identified 1.066 Mb region overlaps with a previously described map of Yr29/QYr.ucw-1BL, a stripe rust APR gene. Twenty-five candidate genes for QYrsv.swut-1BL were identified through comparing polymorphic genes within the 1.066 Mb region in the resistant cultivar. SNP markers were selected and converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers. Five KASP markers based on SNP were validated in a F2 and F2:3 breeding population, providing further compelling evidence for the significant effects of QYrsv.swut-1BL. These markers should be useful in marker-assisted selection for incorporating Yr29/QYrsv.swust-1BL into new durum and common wheat cultivars for resistance to stripe rust.
Neurodegenerative disorders (ND) are a group of conditions that affect the neurons in the brain and spinal cord, leading to their degeneration and eventually causing the loss of function in the affected areas. These disorders can be caused by a range of factors, including genetics, environmental factors, and lifestyle choices. Major pathological signs of these diseases are protein misfolding, proteosomal dysfunction, aggregation, inadequate degradation, oxidative stress, free radical formation, mitochondrial dysfunctions, impaired bioenergetics, DNA damage, fragmentation of Golgi apparatus neurons, disruption of axonal transport, dysfunction of neurotrophins (NTFs), neuroinflammatory or neuroimmune processes, and neurohumoral symptoms. According to recent studies, defects or imbalances in gut microbiota can directly lead to neurological disorders through the gut-brain axis. Probiotics in ND are recommended to prevent cognitive dysfunction, which is a major symptom of these diseases. Many in vivo and clinical trials have revealed that probiotics (<i>Lactobacillus acidophilus</i>, <i>Bifidobacterium bifidum</i>, and <i>Lactobacillus casei</i>, etc.) are effective candidates against the progression of ND. It has been proven that the inflammatory process and oxidative stress can be modulated by modifying the gut microbiota with the help of probiotics. As a result, this study provides an overview of the available data, bacterial variety, gut-brain axis defects, and probiotics’ mode of action in averting ND. A literature search on particular sites, including PubMed, Nature, and Springer Link, has identified articles that might be pertinent to this subject. The search contains the following few groups of terms: (1) Neurodegenerative disorders and Probiotics OR (2) Probiotics and Neurodegenerative disorders. The outcomes of this study aid in elucidating the relationship between the effects of probiotics on different neurodegenerative disorders. This systematic review will assist in discovering new treatments in the future, as probiotics are generally safe and cause mild side effects in some cases in the human body.
Buecherl Lukas, Mitchell Thomas, Scott-Brown James
et al.
Synthetic biology builds upon genetics, molecular biology, and metabolic engineering by applying engineering principles to the design of biological systems. When designing a synthetic system, synthetic biologists need to exchange information about multiple types of molecules, the intended behavior of the system, and actual experimental measurements. The Synthetic Biology Open Language (SBOL) has been developed as a standard to support the specification and exchange of biological design information in synthetic biology, following an open community process involving both bench scientists and scientific modelers and software developers, across academia, industry, and other institutions. This document describes SBOL 3.1.0, which improves on version 3.0.0 by including a number of corrections and clarifications as well as several other updates and enhancements. First, this version includes a complete set of validation rules for checking whether documents are valid SBOL 3. Second, the best practices section has been moved to an online repository that allows for more rapid and interactive of sharing these conventions. Third, it includes updates based upon six community approved enhancement proposals. Two enhancement proposals are related to the representation of an object’s namespace. In particular, the Namespace class has been removed and replaced with a namespace property on each class. Another enhancement is the generalization of the CombinatorialDeriviation class to allow direct use of Features and Measures. Next, the Participation class now allow Interactions to be participants to describe higher-order interactions. Another change is the use of Sequence Ontology terms for Feature orientation. Finally, this version of SBOL has generalized from using Unique Reference Identifiers (URIs) to Internationalized Resource Identifiers (IRIs) to support international character sets.
Henry V. Jakubowski, Henry Agnew, Bartholomew E. Jardine
et al.
Biology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent properties such as memory, consciousness, and recognition of self and non-self. To understand how these interconnected reactions lead to cellular life characterized by activation, inhibition, regulation, homeostasis, and adaptation, computational analyses and simulations are essential, a fact recognized by the biological communities. At the same time, students struggle to understand and apply binding and kinetic analyses for the simplest reactions such as the irreversible first-order conversion of a single reactant to a product. This likely results from cognitive difficulties in combining structural, chemical, mathematical, and textual descriptions of binding and catalytic reactions. To help students better understand dynamic reactions and their analyses, we have introduced two kinds of interactive graphs and simulations into the online educational resource, Fundamentals of Biochemistry, a multivolume biochemistry textbook that is part of the LibreText collection. One type is available for simple binding and kinetic reactions. The other displays progress curves (concentrations vs time) for both simple reactions and more complex metabolic and signal transduction pathways, including those available through databases using systems biology markup language (SBML) files. Users can move sliders to change dissociation and kinetic constants as well as initial concentrations and see instantaneous changes in the graphs. They can also export data into a spreadsheet for further processing, such as producing derivative Lineweaver-Burk and traditional Michaelis-Menten graphs of initial velocity (v0) vs substrate concentration.
Soil microorganisms play an indispensable role in the forest ecosystem. It is necessary to study the soil microorganisms in <i>Pinus sylvestris</i> var. <i>mongolica</i>, which is one of the afforestation species widely planted in the northern sandy region of China. We collected soil samples of <i>P. sylvestris</i> at large spatial scales and analyzed bacterial and fungal community composition differences using high-throughput sequencing techniques. The results showed that: (1) the richness index of different sandy lands was significantly different. The α-diversity of bacteria was the highest in Mu Us Sandy Land, and the α-diversity of fungi was the highest in Horqin Sandy Land. (2) The dominant phyla of bacteria were Actinobacteria, Proteobacteria, Chloroflexi and Acidobacteria, while the dominant phyla of fungi were Ascomycota and Basidiomycota. The relative abundance of dominant phyla was different. (3) Temperature and precipitation were the main driving factors of bacterial and fungal community change at large spatial scale. In addition, bacteria were also affected by total nitrogen, soil organic carbon and pH content; fungal community was affected by pH. The microorganisms showed obvious differences in geographical distribution, which could provide ideas for promoting sustainable management of <i>P. sylvestris</i> stand.
Salivary content has been reported as a potential biomarker for oxidative stress assessments especially in context of exercise-induced oxidative stress. This systematic review following PRISMA guidelines aimed to evaluate the effects of physical exercise and changes promoted in oxidative stress identified in saliva. Methods: Studies published up to May 2022 were searched in online databases (PubMed, Scopus, Web of Science, The Cochrane Library, LILACS, OpenGrey, and Google Scholar). Risk of bias evaluation were performed using the Quality Assessment Tool for Before-After (Pre-Post) Studies with No Control Group. Results: A total of 473 references were identified and 22 considered eligible. In this case 14 studies reported increase of antioxidant parameters in saliva while eight studies demonstrated increased lipid peroxidation after exercise. Regarding nitrite levels, two studies showed higher levels after exercise. The quality of evidence was very low due to high heterogeneity, inconsistency and indirectness among studies according Grading of Recommendations, Assessment, Development and Evaluation analysis. Conclusion: Increase of oxidative stress and antioxidant activity in saliva appears to be present after exercise, especially at moderate intensity. However, the wide variety of methods leads to divergent data. For precision in salivary assessments, new research with larger sample sizes and better participant matching are recommended.
Composite slab systems have become increasingly popular over the last few decades because of the advantages of merging the two building materials, profiled steel sheets and concrete. The profiled composite slab’s performance depends on the composite interaction at the longitudinal direction of the concrete–steel interface. Geopolymer concrete has emerged over the last few years as a potential sustainable construction material, with 80% less carbon dioxide emissions than cementitious concrete. Recently, self-compacted geopolymer concrete (SCGC) has been developed, synthesised from a fly ash/slag ratio equal to 60/40, micro fly ash (5%), anhydrous sodium metasilicate solid powder as the alkali-activator and a water/solid content ratio equal to 0.45. The production of SCGC eliminates the need for an elevated temperature during curing and high corrosive alkali-activator solutions, as in traditional geopolymer concrete. The bond characteristics of the profiled composite slab system incorporated with the SCGC mix have not yet been thoroughly investigated. The cost-effectiveness of small-scale tests has popularised its usage by many researchers as an alternative technique to large-scale testing for assessing composite slab load shear capacity. In this paper, small-scale push tests were conducted to investigate the load slip behaviour of the SCGC composite slab compared to the normal concrete (NC) composite slab, with targeted compressive strengths of 40 and 60 MPa. The results indicate that SCGC has better chemical adhesion with profiled steel sheets than NC. Additionally, the profiled composite slab incorporated with SCGC possesses higher ultimate strength and toughness than the normal concrete composite slab.
Alexis Laurent, Corinne Scaletta, Philippe Abdel-Sayed
et al.
Cultured fibroblast progenitor cells (FPC) have been studied in Swiss translational regenerative medicine for over two decades, wherein clinical experience was gathered for safely managing burns and refractory cutaneous ulcers. Inherent FPC advantages include high robustness, optimal adaptability to industrial manufacture, and potential for effective repair stimulation of wounded tissues. Major technical bottlenecks in cell therapy development comprise sustainability, stability, and logistics of biological material sources. Herein, we report stringently optimized and up-scaled processing (i.e., cell biobanking and stabilization by lyophilization) of dermal FPCs, with the objective of addressing potential cell source sustainability and stability issues with regard to active substance manufacturing in cutaneous regenerative medicine. Firstly, multi-tiered FPC banking was optimized in terms of overall quality and efficiency by benchmarking key reagents (e.g., medium supplement source, dissociation reagent), consumables (e.g., culture vessels), and technical specifications. Therein, fetal bovine serum batch identity and culture vessel surface were confirmed, among other parameters, to largely impact harvest cell yields. Secondly, FPC stabilization by lyophilization was undertaken and shown to maintain critical functions for devitalized cells in vitro, potentially enabling high logistical gains. Overall, this study provides the technical basis for the elaboration of next-generation off-the-shelf topical regenerative medicine therapeutic products for wound healing and post-burn care.
A compact low-energy and high-intensity X-ray source for radiation biology applications is presented. A laser-induced plasma moves inside a 30 kV diode and produces a beam of 10$^{14}$ electrons at the anode location. An aluminum foil converts a part of the energy of these electrons into X-ray photons which are characterized using filtered imaging plates. The dose that would be deposited by these X-ray photons in C. elegans larvae is calculated from Geant4 simulations. It can be set to a value ranging between 10 $μ$Gy and 10 mGy per laser shot by simply changing the aluminum foil thickness and the diode voltage. Therefore, this versatile and compact X-ray source opens a new path to explore the radiation effects induced by dose rates varying over several orders of magnitude.
Wang-Zhou Dai, Liam Hallett, Stephen H. Muggleton
et al.
The application of Artificial Intelligence (AI) to synthetic biology will provide the foundation for the creation of a high throughput automated platform for genetic design, in which a learning machine is used to iteratively optimise the system through a design-build-test-learn (DBTL) cycle. However, mainstream machine learning techniques represented by deep learning lacks the capability to represent relational knowledge and requires prodigious amounts of annotated training data. These drawbacks strongly restrict AI's role in synthetic biology in which experimentation is inherently resource and time intensive. In this work, we propose an automated biodesign engineering framework empowered by Abductive Meta-Interpretive Learning ($Meta_{Abd}$), a novel machine learning approach that combines symbolic and sub-symbolic machine learning, to further enhance the DBTL cycle by enabling the learning machine to 1) exploit domain knowledge and learn human-interpretable models that are expressed by formal languages such as first-order logic; 2) simultaneously optimise the structure and parameters of the models to make accurate numerical predictions; 3) reduce the cost of experiments and effort on data annotation by actively generating hypotheses and examples. To verify the effectiveness of $Meta_{Abd}$, we have modelled a synthetic dataset for the production of proteins from a three gene operon in a microbial host, which represents a common synthetic biology problem.
We consider nonlinear mutation selection models, known as replicator-mutator equations in evolutionary biology. They involve a nonlocal mutation kernel and a confining fitness potential. We prove that the long time behaviour of the Cauchy problem is determined by the principal eigenelement of the underlying linear operator. The novelties compared to the literature on these models are about the case of symmetric mutations: we propose a new milder sufficient condition for the existence of a principal eigenfunction, and we provide what is to our knowledge the first quantification of the spectral gap. We also recover existing results in the non-symmetric case, through a new approach.
The site frequency spectrum (SFS) is a popular summary statistic of genomic data. While the SFS of a constant-sized population undergoing neutral mutations has been extensively studied in population genetics, the rapidly growing amount of cancer genomic data has attracted interest in the spectrum of an exponentially growing population. Recent theoretical results have generally dealt with special or limiting cases, such as considering only cells with an infinite line of descent, assuming deterministic tumor growth, or taking large-time or large-population limits. In this work, we derive exact expressions for the expected SFS of a cell population that evolves according to a stochastic branching process, first for cells with an infinite line of descent and then for the total population, evaluated either at a fixed time (fixed-time spectrum) or at the stochastic time at which the population reaches a certain size (fixed-size spectrum). We find that while the rate of mutation scales the SFS of the total population linearly, the rates of cell birth and cell death change the shape of the spectrum at the small-frequency end, inducing a transition between a $1/j^2$ power-law spectrum and a $1/j$ spectrum as cell viability decreases. We show that this insight can in principle be used to estimate the ratio between the rate of cell death and cell birth, as well as the mutation rate, using the site frequency spectrum alone. Although the discussion is framed in terms of tumor dynamics, our results apply to any exponentially growing population of individuals undergoing neutral mutations.