Hasil untuk "Biology (General)"

Junting Zhou, Jin Chen, Linfeng Hao et al.

The rapid evolution of large language models (LLMs) has expanded their capabilities from basic dialogue to advanced scientific reasoning. However, existing benchmarks in biology often fail to assess a critical skill required of researchers: the ability to integrate experimental results with contextual knowledge to derive meaningful conclusions. To address this gap, we introduce BABE(Biology Arena BEnchmark), a comprehensive benchmark designed to evaluate the experimental reasoning capabilities of biological AI systems. BABE is uniquely constructed from peer-reviewed research papers and real-world biological studies, ensuring that tasks reflect the complexity and interdisciplinary nature of actual scientific inquiry. BABE challenges models to perform causal reasoning and cross-scale inference. Our benchmark provides a robust framework for assessing how well AI systems can reason like practicing scientists, offering a more authentic measure of their potential to contribute to biological research.

Peidong Guo, Yueheng Liu, Luyin Tan et al.

Nowadays, many of the top-selling video games include options to purchase loot boxes as paid virtual items. As research progressed, loot boxes have been found to have similar characteristics to gambling, and there has been an ongoing debate as to whether loot boxes can be defined as gambling. In order to better study loot boxes, psychometrically meaningful scales are necessary. The Risky Loot Box Index (RLI) was developed by Brooks and Clark, which is the most commonly used tool to assess the use of loot boxes. This study aimed to translate the original RLI into Chinese and evaluate its psychometric properties. Two samples were recruited through online gaming forums (n = 143) and offline internet cafes (n = 236). An exploratory factor analysis of the online sample yielded a one-dimensional nine-item model, with the factor focused on risky behaviors associated with loot boxes. The confirmatory factor analysis carried out on the offline sample corroborated the results obtained from the exploratory factor analysis, and the Chinese version of the RLI displays satisfactory psychometric properties. Furthermore, the Problem Gambling Severity Index (r = 0.57, P < 0.001) and the Internet Gaming Disorder Scale-Short Form (r = 0.67, P < 0.001) were found to be significantly associated with the RLI. We also found that players with high RLI scores may have higher levels of anxiety and depression, and they were more willing to spend money on loot boxes, with some spending nearly all their earnings. Interestingly, no significant correlations between age, gender, education, or income level, and the RLI were found.

Simon P. Preston, Richard D. Wilkinson, Richard H. Clayton et al.

Reliable predictions from systems biology models require knowing whether parameters can be estimated from available data, and with what certainty. Identifiability analysis reveals whether parameters are learnable in principle (structural identifiability) and in practice (practical identifiability). We introduce the core ideas using linear models, highlighting how experimental design and output sensitivity shape identifiability. In nonlinear models, identifiability can vary with parameter values, motivating global and simulation-based approaches. We summarise computational methods for assessing identifiability noting that weakly identifiable parameters can undermine predictions beyond the calibration dataset. Strategies to improve identifiability include measuring different outputs, refining model structure, and adding prior knowledge. Far from a technical afterthought, identifiability determines the limits of inference and prediction. Recognising and addressing identifiability is essential for building models that are not only well-fitted to data, but also capable of delivering predictions with robust, quantifiable uncertainty.

Anna Ulldemolins, Maria Narciso, Maria Narciso et al.

Introduction: Aging induces functional and structural changes in the lung, characterized by a decline in elasticity and diminished pulmonary remodeling and regenerative capacity. Emerging evidence suggests that most biomechanical alterations in the lung result from changes in the composition of the lung extracellular matrix (ECM), potentially modulating the behavior of pulmonary cells and increasing the susceptibility to chronic lung diseases. Therefore, it is crucial to investigate the mechanical properties of the aged lung. This study aims to assess the mechanical alterations in the lung ECM due to aging at both residual (RV) and functional (FV) lung volumes and to evaluate their effects on the survival and proliferation of mesenchymal stromal cells (MSCs).Methods: The lungs from young (4-6-month-old) and aged (20-24-month-old) mice were inflated with optimal cutting temperature compound to reach FV or non-inflated (RV). ECM proteins laminin, collagen I and fibronectin were quantified by immunofluorescence and the mechanical properties of the decellularized lung sections were assessed using atomic force microscopy. To investigate whether changes in ECM composition by aging and/or mechanical properties at RV and FV volumes affects MSCs, their viability and proliferation were evaluated after 72 h.Results: Laminin presence was significantly reduced in aged mice compared to young mice, while fibronectin and collagen I were significantly increased in aged mice. In RV conditions, the acellular lungs from aged mice were significantly softer than from young mice. By contrast, in FV conditions, the aged lung ECM becomes stiffer than that of in young mice, revealing that strain hardening significantly depends on aging. Results after MSCs recellularization showed similar viability and proliferation rate in all conditions.Discussion: This data strongly suggests that biomechanical measurements, especially in aging models, should be carried out in physiomimetic conditions rather than following the conventional non-inflated lung (RV) approach. The use of decellularized lung scaffolds from aged and/or other lung disease murine/human models at physiomimetic conditions will help to better understand the potential role of mechanotransduction on the susceptibility and progression of chronic lung diseases, lung regeneration and cancer.

Marco Nicola Mastrone, Lucas Hildebrand, Constantin Paschold et al.

The circular layout and the kinematics of planetary gearboxes result in characteristic oil flow phenomena. The goal of this paper is to apply a new remeshing strategy, based on the finite volume method, on the numerical analysis of a planetary gearbox and its evaluation of results as well as its validation. The numerical results are compared with experimental data acquired on the underlying test rig with high-speed camera recordings. By use of a transparent housing cover, the optical access in the front region of the gearbox is enabled. Different speeds of the planet carrier and immersion depths are considered. A proper domain partitioning and a specifically suited mesh-handling strategy provide a highly efficient numerical model. The open-source software OpenFOAM^® is used.

Sarah O’Flaherty, Natalia Cobian, Rodolphe Barrangou

Despite rising interest in understanding intestinal bacterial survival in situ, relatively little attention has been devoted to deciphering the interaction between bacteria and functional food ingredients. Here, we examined the interplay between diverse beneficial <i>Lactobacillaceae</i> species and a pomegranate (POM) extract and determined the impact of this functional ingredient on bacterial growth, cell survival, transcription and target metabolite genesis. Three commercially available probiotic strains (<i>Lactobacillus acidophilus</i> NCFM, <i>Lacticaseibacillus rhamnosus</i> GG and <i>Lactiplantibacillus plantarum</i> Lp-115) were used in growth assays and flow cytometry analysis, indicating differential responses to the presence of POM extract across the three strains. The inclusion of POM extract in the growth medium had the greatest impact on <i>L. acidophilus</i> cell counts. LIVE/DEAD staining determined significantly fewer dead cells when <i>L. acidophilus</i> was grown with POM extract compared to the control with no POM (1.23% versus 7.23%). Whole-transcriptome analysis following exposure to POM extract showed markedly different global transcriptome responses, with 15.88% of the <i>L. acidophilus</i> transcriptome, 19.32% of the <i>L. rhamnosus</i> transcriptome and only 2.37% of the <i>L. plantarum</i> transcriptome differentially expressed. We also noted strain-dependent metabolite concentrations in the medium with POM extract compared to the control medium for punicalagin, ellagic acid and gallic acid. Overall, the results show that POM extract triggers species-specific responses by probiotic strains and substantiates the rising interest in using POM as a prebiotic compound.

Thaís Almeida de Menezes, Flávia Figueira Aburjaile, Gabriel Quintanilha-Peixoto et al.

<i>Ophiocordyceps australis</i> (Ascomycota, Hypocreales, Ophiocordycipitaceae) is a classic entomopathogenic fungus that parasitizes ants (Hymenoptera, Ponerinae, Ponerini). Nonetheless, according to our results, this fungal species also exhibits a complete set of genes coding for plant cell wall degrading Carbohydrate-Active enZymes (CAZymes), enabling a full endophytic stage and, consequently, its dual ability to both parasitize insects and live inside plant tissue. The main objective of our study was the sequencing and full characterization of the genome of the fungal strain of <i>O. australis</i> (CCMB661) and its predicted secretome. The assembled genome had a total length of 30.31 Mb, N50 of 92.624 bp, GC content of 46.36%, and 8,043 protein-coding genes, 175 of which encoded CAZymes. In addition, the primary genes encoding proteins and critical enzymes during the infection process and those responsible for the host–pathogen interaction have been identified, including proteases (Pr1, Pr4), aminopeptidases, chitinases (Cht2), adhesins, lectins, lipases, and behavioral manipulators, such as enterotoxins, Protein Tyrosine Phosphatases (PTPs), and Glycoside Hydrolases (GHs). Our findings indicate that the presence of genes coding for Mad2 and GHs in <i>O. australis</i> may facilitate the infection process in plants, suggesting interkingdom colonization. Furthermore, our study elucidated the pathogenicity mechanisms for this <i>Ophiocordyceps</i> species, which still is scarcely studied.

Christopher S. Thom, C. Dickson, D. Gell et al.

G. Meyers, H. Thiel

Naila Chahinez Boukhebache, Nabila Amirouche, Rachid Amirouche

This paper provides new cytotaxonomic data on the genus Narcissus Linnaeus, 1753, in Algeria. Populations of seven taxa, N. tazetta Linnaeus, 1753, N. pachybolbus Durieu, 1847, N. papyraceus Ker Gawler, 1806, N. elegans (Haworth) Spach, 1846, N. serotinus sensu lato Linnaeus, 1753, including N. obsoletus (Haworth) Steudel, 1841, and N. cantabricus De Candolle, 1815, were karyologically investigated through chromosome counting and karyotype parameters. N. tazetta and N. elegans have the same number of chromosomes 2n = 2x = 20 with different karyotype formulas. Karyological and morphological characteristics, confirm the specific status of N. pachybolbus and N. papyraceus, both are diploids with 2n = 22 but differing in asymmetry indices. The morphotypes corresponding to N. serotinus sensu lato show two ploidy levels 2n = 4x = 20 and 2n = 6x = 30 characterized by a yellow corona. Some hexaploid cytotypes have more asymmetric karyotype with predominance of subtelocentric chromosomes. They are distinguished by orange corona and may correspond to N. obsoletus. Other cytotype 2n = 28 of N. serotinus was observed in the North Western biogeographic sectors. N. cantabricus was found to be diploid with 2n = 2x = 14, which is a new diploid report in the southernmost geographic range of this polyploid complex.

A. Gargantilla Becerra, M. Gutiérrez, R. Lahoz-Beltra

Bacteria have been a source of inspiration for the design of evolutionary algorithms. At the beginning of the 20th century synthetic biology was born, a discipline whose goal is the design of biological systems that do not exist in nature, for example, programmable synthetic bacteria. In this paper, we introduce as a novelty the designing of evolutionary algorithms where all the steps are conducted by synthetic bacteria. To this end, we designed a genetic algorithm, which we have named BAGA, illustrating its utility solving simple instances of optimization problems such as function optimization, 0/1 knapsack problem, Hamiltonian path problem. The results obtained open the possibility of conceiving evolutionary algorithms inspired by principles, mechanisms and genetic circuits from synthetic biology. In summary, we can conclude that synthetic biology is a source of inspiration either for the design of evolutionary algorithms or for some of their steps, as shown by the results obtained in our simulation experiments.

Jennifer Brunke, Isa-Rita M. Russo, Pablo Orozco-terWengel et al.

Abstract Background Constraints in migratory capabilities, such as the disruption of gene flow and genetic connectivity caused by habitat fragmentation, are known to affect genetic diversity and the long-term persistence of populations. Although negative population trends due to ongoing forest loss are widespread, the consequence of habitat fragmentation on genetic diversity, gene flow and genetic structure has rarely been investigated in Bornean small mammals. To fill this gap in knowledge, we used nuclear and mitochondrial DNA markers to assess genetic diversity, gene flow and the genetic structure in the Bornean tree shrew, Tupaia longipes, that inhabits forest fragments of the Lower Kinabatangan Wildlife Sanctuary, Sabah. Furthermore, we used these markers to assess dispersal regimes in male and female T. longipes. Results In addition to the Kinabatangan River, a known barrier for dispersal in tree shrews, the heterogeneous landscape along the riverbanks affected the genetic structure in this species. Specifically, while in larger connected forest fragments along the northern riverbank genetic connectivity was relatively undisturbed, patterns of genetic differentiation and the distribution of mitochondrial haplotypes in a local scale indicated reduced migration on the strongly fragmented southern riverside. Especially, oil palm plantations seem to negatively affect dispersal in T. longipes. Clear sex-biased dispersal was not detected based on relatedness, assignment tests, and haplotype diversity. Conclusion This study revealed the importance of landscape connectivity to maintain migration and gene flow between fragmented populations, and to ensure the long-term persistence of species in anthropogenically disturbed landscapes.

Allan L. Alinea, Takahiro Kubota

Primordial cosmological perturbations are the seeds that were cultivated by inflation and the succeeding dynamical processes, eventually leading to the current Universe. In this work, we investigate the behavior of the gauge-invariant scalar and tensor perturbations under the general extended disformal transformation, namely, $g_{μν} \rightarrow A(X,Y,Z)g_{μν} + Φ_μΦ_ν$, where $X \equiv -\tfrac{1}{2}φ^{;μ}φ_{;μ}, Y \equiv φ^{;μ}X_{;μ}, Z \equiv X^{;μ}X_{;μ} $ and $Φ_μ\equiv Cφ_{;μ} + DX_{;μ}$, with $C$ and $D$ being a general functional of $(φ,X,Y,Z)$. We find that the tensor perturbation is invariant under this transformation. On the other hand, the scalar curvature perturbation receives a correction due the conformal term only; it is independent of the disformal term at least up to linear order. Within the framework of the full Horndeski theory, the correction terms turn out to depend linearly on the gauge-invariant comoving density perturbation and the first time-derivative thereof. In the superhorizon limit, all these correction terms vanish, leaving only the original scalar curvature perturbation. In other words, it is invariant under the general extended disformal transformation in the superhorizon limit, in the context of full Horndeski theory. Our work encompasses a chain of research studies on the transformation or invariance of the primordial cosmological perturbations, generalizing their results under our general extended disformal transformation.

Seongyong Park, Shujaat Khan, Abdul Wahab

Understanding E3 ligase and target substrate interactions are important for cell biology and therapeutic development. However, experimental identification of E3 target relationships is not an easy task due to the labor-intensive nature of the experiments. In this article, a sequence-based E3-target prediction model is proposed for the first time. The proposed framework utilizes composition of k-spaced amino acid pairs (CKSAAP) to learn the relationship between E3 ligases and their target protein. A class separable latent space encoding scheme is also devised that provides a compressed representation of feature space. A thorough ablation study is performed to identify an optimal gap size for CKSAAP and the number of latent variables that can represent the E3-target relationship successfully. The proposed scheme is evaluated on an independent dataset for a variety of standard quantitative measures. In particular, it achieves an average accuracy of $70.63\%$ on an independent dataset. The source code and datasets used in the study are available at the author's GitHub page (https://github.com/psychemistz/E3targetPred).

Kevin Achberger, Christopher Probst, Jasmin Haderspeck et al.

The devastating effects and incurable nature of hereditary and sporadic retinal diseases such as Stargardt disease, age-related macular degeneration or retinitis pigmentosa urgently require the development of new therapeutic strategies. Additionally, a high prevalence of retinal toxicities is becoming more and more an issue of novel targeted therapeutic agents. Ophthalmologic drug development, to date, largely relies on animal models, which often do not provide results that are translatable to human patients. Hence, the establishment of sophisticated human tissue-based in vitro models is of upmost importance. The discovery of self-forming retinal organoids (ROs) derived from human embryonic stem cells (hESCs) or human induced pluripotent stem cells (hiPSCs) is a promising approach to model the complex stratified retinal tissue. Yet, ROs lack vascularization and cannot recapitulate the important physiological interactions of matured photoreceptors and the retinal pigment epithelium (RPE). In this study, we present the retina-on-a-chip (RoC), a novel microphysiological model of the human retina integrating more than seven different essential retinal cell types derived from hiPSCs. It provides vasculature-like perfusion and enables, for the first time, the recapitulation of the interaction of mature photoreceptor segments with RPE in vitro. We show that this interaction enhances the formation of outer segment-like structures and the establishment of in vivo-like physiological processes such as outer segment phagocytosis and calcium dynamics. In addition, we demonstrate the applicability of the RoC for drug testing, by reproducing the retinopathic side-effects of the anti-malaria drug chloroquine and the antibiotic gentamicin. The developed hiPSC-based RoC has the potential to promote drug development and provide new insights into the underlying pathology of retinal diseases.

Daniel Blixt, Manuel Hohmann, Martin Krššák et al.

It is known that one can formulate an action in teleparallel gravity which is equivalent to general relativity, up to a boundary term. In this geometry we have vanishing curvature, and non-vanishing torsion. The action is constructed by three different contractions of torsion with specific coefficients. By allowing these coefficients to be arbitrary we get the theory which is called `new general relativity'. In this note, the Lagrangian for new general relativity is written down in ADM-variables. In order to write down the Hamiltonian we need to invert the velocities to canonical variables. However, the inversion depends on the specific combination of constraints satisfied by the theory (which depends on the coefficients in the Lagrangian). It is found that one can combine these constraints in 9 different ways to obtain non-trivial theories, each with a different inversion formula.

S. Hopkin, H. Read

Raphaël Boursereau, Michel Abou-Samra, Sophie Lecompte et al.

Abstract Background The hormone adiponectin (ApN) exerts powerful anti-inflammatory effects on skeletal muscle and can reverse devastating myopathies, like Duchenne muscular dystrophy (DMD), where inflammation exacerbates disease progression. The NLRP3 inflammasome plays a key role in the inflammation process, and its aberrant activation leads to several inflammatory or immune diseases. Here we investigated the expression of the NLRP inflammasome in skeletal muscle and its contribution to DMD. Results We find that NLRP3 is expressed in skeletal muscle and show that ApN downregulates NLRP3 via its anti-inflammatory mediator, miR-711. This repression occurs both in vitro in C2C12 myotubes and in vivo after either local (via muscle electrotransfer) or systemic (by using transgenic mice) ApN supplementation. To explore the role of the NLRP3 inflammasome in a murine model of DMD, we crossed mdx mice with Nlrp3-knockout mice. In mdx mice, all components of the inflammasome were upregulated in muscle, and the complex was overactivated. By contrast, in mdx mice lacking Nlrp3, there was a reduction in caspase-1 activation, inflammation and oxidative stress in dystrophic muscle, and these mice showed higher global muscle force/endurance than regular mdx mice as well as decreased muscle damage. To investigate the relevance of NLPR3 regulation in a human disease context, we characterized NLRP3 expression in primary cultures of myotubes from DMD subjects and found a threefold increase compared to control subjects. This overexpression was attenuated by ApN or miR-711 mimic treatments. Conclusions The NLRP3 inflammasome plays a key pathogenic role in DMD and muscle inflammation, thereby opening new therapeutic perspectives for these and other related disorders.

Richard Y. Li, Rosa Di Felice, Remo Rohs et al.

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems.

Anatoly Sorokin, Oksana Sorokina, J. Douglas Armstrong

RKappa is a framework for the development, simulation and analysis of rule-base models within the mature statistically empowered R environment. It is designed for model editing, parameter identification, simulation, sensitivity analysis and visualisation. The framework is optimised for high-performance computing platforms and facilitates analysis of large-scale systems biology models where knowledge of exact mechanisms is limited and parameter values are uncertain. The RKappa software is an open source (GLP3 license) package for R, which is freely available online ( https://github.com/lptolik/R4Kappa ).